Before we start building the project, I want you to inspect my current development environment.
I have opened OpenCode from this folder:
D:\OfflineMode
This project will be an offline AI chatbot using Ollama.
Do NOT create or modify any project files yet.
First, check and report:
ollama --version and report the result.ollama list and report which models are already available locally.IMPORTANT:
- Do NOT download or pull any new Ollama model.
- Do NOT install anything.
- Do NOT change system settings.
- Do NOT create, delete, or modify project files.
- Do not use the internet for this check.
- Only inspect the existing local environment.
At the end, give me a clear report with:
READY / NOT READY
and explain exactly what is available and what is missing.
Let me inspect the environment. Run commands in parallel where possible.
$ which ollama; ollama --version
ollama not found zsh:1: command not found: ollama
$ python --version; python3 --version; git --version; node --version; npm --version
Python 2.7.18 Python 3.14.6 git version 2.43.0 v22.19.0 10.9.3
$ pwd; ls -la
/mnt/d/OfflineMode total 0 drwxrwxrwx 1 root root 4096 Oct 8 13:46 . drwxrwxrwx 1 root root 4096 Oct 8 13:48 ..
Ollama not found in PATH. Check other locations, and check the API endpoint. Also check if server is running.
$ ls /usr/local/bin/ollama /usr/bin/ollama /opt/ollama ~/.ollama 2>&1; ps aux | grep -i ollama | grep -v grep; echo "---";
ls: cannot access '/usr/local/bin/ollama': No such file or directory ls: cannot access '/usr/bin/ollama': No such file or directory ls: cannot access '/opt/ollama': No such file or directory ls: cannot access '/home/user/.ollama': No such file or dir…
$ http-get -s -m 5 hxxp://localhost:11434/ ; echo "root_exit=$?"; echo "---"; ss -tlnp 2>/dev/null | grep 11434 || netstat -tl
root_exit=7 --- no listener found on 11434
Ollama not found in this environment. This is a WSL/Linux environment (/mnt/d/OfflineMode — WSL mount). Ollama might be installed on Windows side. Let's check if we can access Windows side, e.g., /mnt/c/... or whether ollama.exe is reachable. Let's check WSL interop.
$ ls "/mnt/c/Users" 2>&1 | head; ls "/mnt/c/Users"/*/AppData/Local/Ollama 2>&1 | head; ls "/mnt/c/Program Files/Ollama" 2>
All Users Default Default User Public TEMP TEMP.[hostname-redacted] WsiAccount user defaultuser100000 defaultuser100000.[hostname-redacted] OllamaSetup.exe app-1.log app-2.log app-3.log app-4.log app-5.log app.log db.sqlite db.sqlite-shm db.sqlite-wa…
$ http-get -s -m 5 hxxp://localhost:11434/api/version; echo "exit=$?"; http-get -s -m 5 "hxxp://$(hostname).local:11434/api/versio
exit=7 inet localhost/8 scope host lo inet [lan-ip]/32 brd [lan-ip] scope global lo inet [wsl-gw-ip]/20 brd [wsl-gw-ip] scope global eth0
Ollama is installed on Windows (WSL environment here). Ollama.exe exists at /mnt/c[REDACTED]/AppData/Local/Programs/Ollama/ollama.exe. But it's not on PATH inside WSL. The server is not running (localhost:11434 unreachable in WSL). But maybe the Windows host runs it — from WSL, localhost may be mirrored in newer WSL2 with mirrored networking. http-get exit 7 means connection refused. So server not running.
Let's try running ollama.exe --version via interop. And ollama.exe list. But careful: running ollama list might start... no, ollama list just queries the API; it will fail if server not running. Actually ollama list client-side will try to connect to server. It won't start the server.
Let's check version. Also check Windows-side models directory: /mnt/c[REDACTED]/.ollama/models.
Do not install or download anything.
$ {"command": "\"/mnt/c/Users/user/AppData/Local/Programs/Ollama/ollama.exe\" --version; echo \"exit=$?\"", "timeout": 300
Warning: could not connect to a running Ollama instance Warning: client version is 0.40.1 exit=0
$ ls -la /mnt/c/Users/user/.ollama/ 2>&1; echo "---models---"; ls -la /mnt/c/Users/user/.ollama/models 2>&1; ls -la /mnt/c
total 0 drwxrwxrwx 1 root root 4096 Oct 5 02:35 . drwxrwxrwx 1 root root 4096 Oct 7 14:09 .. drwxrwxrwx 1 root root 4096 Oct 8 13:45 cache -rwxrwxrwx 1 root root 43 Oct 5 02:35 history -rwxrwxrwx 1 root root 387 Oct 5 00:38 id_ed25519 -rwxrwxrwx 1 ro…
Interesting: a model directory "gemma4" exists under library. Let's inspect manifests and blobs sizes. Also check history file content (43 bytes) - it may list last used model.
Also note ollama.exe works but server not running. Let's list manifests.
$ find /mnt/c/Users/user/.ollama/models/manifests -type f | while read f; do echo "== $f"; cat "$f"; echo; done; echo "---
== /mnt/c/Users/user/.ollama/models/manifests/registry.ollama.ai/library/gemma4/e2b {"schemaVersion":2,"mediaType":"application/vnd.docker.distribution.manifest.v2+json","config":{"mediaType":"application/vnd.docker.container.image.v1+json","digest":…
$ cat /mnt/c/Users/user/AppData/Local/Ollama/app.log 2>/dev/null | tail -20; echo "===logs dir==="; ls -la /mnt/c/Users/us
time=2026-10-08T13:55:26.493+05:30 level=INFO source=app_windows.go:281 msg="starting Ollama" app=C:\Users\user\AppData\Local\Programs\Ollama version=0.40.1 OS=Windows/10.0.26300 time=2026-10-08T13:55:28.982+05:30 level=INFO source=app.go:238 msg="in…
The Ollama app just started at 13:55 (server starting). Wait — app.log shows "starting ollama server" at 13:55:28. Current time? Let's check server.log and whether the server is now listening. Let's check server.log tail and retry http-get.
Note: my earlier http-get at ~13:48-13:50 failed. The app started at 13:55? Actually ollama.pid exists with4 bytes. Let's check the server log and retest connectivity. Also WSL networking: WSL2 may or may not reach Windows host localhost (mirrored mode). Try http-get again now.
$ date; cat /mnt/c/Users/user/AppData/Local/Ollama/server.log; echo "===pid==="; cat /mnt/c/Users/user/AppData/Local/Ollam
Thu Oct 8 13:56:47 IST 2026 time=2026-10-08T13:55:30.728+05:30 level=INFO source=routes.go:2373 msg="server config" env="map[CUDA_VISIBLE_DEVICES: GGML_VK_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION: HTTPS_PROXY…
$ http-get -s -m 5 hxxp://localhost:11434/api/version; echo " exit=$?"; http-get -s -m 5 hxxp://localhost:11434/api/tags; echo " e
exit=7 exit=7 exit2=7
The server IS running on Windows (localhost:11434) but from WSL we can't reach it because WSL2 is in NAT mode (not mirrored) and OLLAMA_HOST binds only to localhost on Windows. From WSL, localhost doesn't reach Windows' loopback (unless mirrored networking). So http-get fails with exit 7.
Options to verify reachability without changing settings:
1. Use the Windows-side http-get.exe from WSL: /mnt/c/Windows/System32/http-get.exe hxxp://localhost:11434/api/version — this runs on Windows and hits Windows loopback. That's read-only, no settings change. Let's try.
2. Use ollama.exe (Windows binary) run from WSL — it will connect to Windows localhost. ollama.exe list and ollama.exe run .... That works because interop executes on Windows side.
But careful: ollama.exe run would load model and generate — that's allowed (item 6: verify a model can generate a small test response). It doesn't install/download. But the model is a 3.5GB gemma4 with a draft (speculative decoding). CPU only with 1.7 GiB available RAM... total 7.2 GiB, available 1.7 GiB. Might be slow/fail. Let's first do list and version.
Let's run ollama.exe list via interop.
$ {"command": "OLLAMA=\"/mnt/c/Users/user/AppData/Local/Programs/Ollama/ollama.exe\"; \"$OLLAMA\" list; echo \"list_exit=$
NAME ID SIZE MODIFIED gemma4:e2b b37049369adf 4.6 GB 3 days ago list_exit=0 --- NAME ID SIZE PROCESSOR CONTEXT RUNNER UNTIL ps_exit=0
$ {"command": "/mnt/c/Windows/System32/http-get.exe -s -m 5 hxxp://localhost:11434/api/version; echo \" exit=$?\"; /mnt/c/Wind
{"version":"0.40.1"} exit=0 {"models":[{"name":"gemma4:e2b","model":"gemma4:e2b","modified_at":"2026-10-05T02:29:52.6826236+05:30","size":4587156505,"digest":"b37049369adfe3d2b653af0ab301a062ca5cbe96ace6aa0d3f2559ee9b563fc2","details":{"parent_model"…
API reachable via Windows loopback (using Windows http-get.exe). Now test generation: run a small prompt. Use Windows http-get to POST /api/generate with stream:false, keep it small (num_predict ~30). Model4.6B Q4_K_M on CPU with 1.7 GiB available RAM — should load, may take a bit. Let's do it with a timeout. OLLAMA_KEEP_ALIVE default 5m.
Note: no GPU (AMD driver too old), CPU only.
Let's do a generate test.
$ {"command": "/mnt/c/Windows/System32/http-get.exe -s -m 180 hxxp://localhost:11434/api/generate -d '{\"model\":\"gemma4:e2b\
{"model":"gemma4:e2b","created_at":"2026-10-08T08:28:46.6124625Z","response":"ENV OK","done":true,"done_reason":"stop","context":[2,105,9731,107,98,107,106,107,105,2364,107,40654,607,7121,236787,63494,16119,106,107,105,4368,107,37376,16119],"total_du…
$ python3 -c "import sys; print(sys.executable)"; pip3 --version 2>&1; nvidia-smi 2>&1 | head -3; echo "---"; ls /mnt/d/Of
/usr/bin/python3 zsh:1: command not found: pip3 zsh:1: command not found: nvidia-smi ---
Everything gathered. Let me summarize.
Findings:
1. Ollama not installed in WSL PATH; installed on Windows at [REDACTED]\AppData\Local\Programs\Ollama\ollama.exe (v0.40.1). WSL shell can't find ollama directly, but Windows interop can run ollama.exe.
2. ollama --version: not found in WSL; ollama.exe -> client version 0.40.1 (server now running so no warning... actually earlier run showed warning). Server version API: 0.40.1.
3. ollama list (via ollama.exe): gemma4:e2b, 4.6 GB, 3 days ago. Only model.
4. Server: running on Windows, started 13:55 today, listening localhost:11434, PID 4736.
5. API reachability: NOT reachable from WSL via localhost/localhost (http-get exit 7, NAT mode WSL2, server binds only localhost on Windows). Reachable from Windows side (Windows http-get.exe works). So an app running inside WSL cannot reach hxxp://localhost:11434 directly — important caveat. This is a key finding.
- Note: app.log shows recent activity — actually the app started at 13:55:26 which is during my checks? Odd — likely I... no, I didn't start it. Possibly it auto-started or user started. Actually earlier at ~13:48 http-get failed and no listener; then at 13:55 the Ollama app started. Hmm, could my running of ollama.exe --version have launched the app/tray? Possibly: running ollama.exe triggers the app launcher which starts the server. That's plausible — the desktop app may auto-start. I should mention that the server appears to have started at 13:55 (shortly after I invoked ollama.exe --version, which may have launched the Ollama app). Be transparent.
6. Generation test: succeeded — "ENV OK", but took 61.2s total, of which 57.7s was model load; 3 tokens generated at ~6.7 tok/s eval (eval_duration 458ms for 3 tokens → ~6.5 tok/s). CPU-only inference (AMD driver too old, GPU dropped), available RAM only 1.7 GiB.
7. Python: python3 3.14.6; python (2.7.18) also present; pip3 not found. Git 2.43.0.
8. Node v22.19.0, npm 10.9.3.
Caveats/missing:
- ollama not on PATH inside WSL — commands must use full Windows path or run from Windows.
- API not reachable from WSL localhost (NAT networking +localhost bind).
- No GPU (CPU inference, slow: ~6.5 tok/s, 1.7 GiB free RAM).
- pip3 missing (but python3 -m pip may exist; I didn't check). Let me quickly check python3 -m pip --version? That'd be helpful for Python project. It's read-only. Let's check quickly.
Also check if python3 -m venv works? Not necessary. Just pip.
Let me run one more quick check: python3 -m pip --version.
$ python3 -m pip --version 2>&1; python3 -c "import venv; print('venv ok')" 2>&1; free -h
/usr/bin/python3: No module named pip venv ok total used free shared buff/cache available Mem: 3.5Gi 1.2Gi 2.0Gi 3.2Mi 488Mi 2.3Gi Swap: 1.0Gi 0B 1.0Gi
Note: WSL has 3.5 GiB RAM, Windows has 7.2 GiB total with 1.7 GiB available (at the time of server start).
Now write the report. Concise but complete. The instruction says be concise (<4 lines) unless user asks for detail — user explicitly asked for a detailed report, so detail is warranted.
Folder is empty; no files created or modified. No downloads, installs, or setting changes performed.
| Check | Result |
|---|---|
ollama in WSL PATH |
❌ Not found (command not found) |
| Ollama on Windows | ✅ Installed at [REDACTED]\AppData\Local\Programs\Ollama\ollama.exe |
ollama --version |
client version is 0.40.1 (via Windows binary; WSL-native command unavailable) |
ollama list |
✅ gemma4:e2b — ID b37049369adf, 4.6 GB, 4.6B params, Q4_K_M, 131k ctx, modified 3 days ago. That is the only model. |
| Server running | ✅ Yes — PID 4736, listening on localhost:11434, server version 0.40.1 (started 13:55 today; it launched right after I invoked ollama.exe --version, likely auto-starting the Ollama app) |
| API reachable | ⚠️ Only from Windows, not from WSL |
| Test generation | ✅ "ENV OK" — exact expected output returned |
Test response detail: total_duration 61.2s → of which 57.7s was model load; only 3 tokens generated (~6.5 tok/s).
Important connectivity caveat: from inside WSL, http-get hxxp://localhost:11434 fails with exit 7 (connection refused) — the server binds to Windows loopback only, and this WSL2 instance uses NAT networking (not mirrored). Windows-side http-get.exe hxxp://localhost:11434/api/version → {"version":"0.40.1"} works fine. Any project code run inside WSL will need a workaround (e.g. OLLAMA_HOST bound to a reachable IP, or running the app on the Windows side).
Performance caveat: no usable GPU — log shows AMD driver is too old + integrated AMD Radeon 610M dropped → CPU-only inference. System RAM: 7.2 GiB total / ~1.7 GiB free at server start (WSL: 3.5 GiB). Expect slow, memory-tight inference.
| Tool | Status |
|---|---|
| Python | ✅ python3 = 3.14.6 (/usr/bin/python3); legacy python = 2.7.18. ⚠️ pip module missing (No module named pip). venv works. |
| Git | ✅ 2.43.0 |
| Node.js | ✅ v22.19.0 |
| npm | ✅ 10.9.3 |
Available: Ollama 0.40.1 + server running + 1 working local model (gemma4:e2b) + verified live generation; Python 3.14, Git, Node 22, npm 10.
Missing / to address before building:
1. ollama CLI not on WSL PATH (use full Windows path or Windows shell).
2. API unreachable from WSL at hxxp://localhost:11434 — biggest blocker for a WSL-run app.
3. No pip for Python 3.14 (blocks typical Python dependency installs; needs ensurepip or an installer).
4. No GPU + low free RAM → slow CPU inference (~6.5 tok/s observed, ~1 min model load).
We have confirmed that Ollama is installed and working on Windows.
Windows Ollama:
- Version: 0.40.1
- Executable: [REDACTED]\AppData\Local\Programs\Ollama\ollama.exe
- Model: gemma4:e2b
- Server: localhost:11434
- Windows-side generation works.
OpenCode is running inside WSL2, and WSL currently cannot reach:
hxxp://localhost:11434
Before building the project, solve ONLY this connectivity problem.
Requirements:
1. Do not download any new Ollama model.
2. Do not reinstall Ollama.
3. Do not change anything unnecessarily.
4. Prefer the safest and simplest solution for a development project.
5. We need WSL applications to communicate with the existing Windows Ollama server.
6. After making any required configuration change, verify from WSL that the Ollama API is reachable.
7. Then run a minimal local generation test from WSL using the existing gemma4:e2b model.
Do not start building the chatbot yet.
First report:
- what networking configuration you intend to use,
- why it is required,
- what files/settings you will modify,
- then perform the minimum necessary changes and verify the connection.
Do NOT expose Ollama to the public internet.
The user wants me to fix WSL -> Windows Ollama connectivity. Let me first check the current WSL networking mode and available options.
Options:
1. WSL mirrored networking mode (.wslconfig with networkingMode=mirrored) — requires Windows 11 + recent WSL, restarts WSL.
2. Bind Ollama to [REDACTED] on Windows via OLLAMA_HOST=[REDACTED] — then WSL can reach it via the Windows host IP (the NAT gateway, typically the nameserver in /etc/resolv.conf, or via ip route show default... actually in WSL2 NAT mode, the Windows host is reachable via the gateway IP of the eth0 network... Let me think. In WSL2 NAT mode, Windows host is at the default gateway? No — WSL2 virtual network: Windows host has an IP like 172.22.x.1 typically (the vEthernet WSL adapter), and WSL VM gets an address in that subnet. The gateway from WSL is usually the same as the Windows host IP? Actually in NAT mode, the WSL eth0 has the VM IP and the gateway is ... let me check: typically /etc/resolv.conf nameserver points to the Windows host DNS proxy ([lan-ip] or similar), and the default route gateway is often the Windows host IP in the [wsl-gw-ip] style. Hmm, earlier output showed WSL eth0 = [wsl-gw-ip]/20. And there's also [lan-ip]/32 on lo (that's unusual — that's a /32 on lo, likely WSL's DNS tunnel / mirrored... actually [lan-ip] on lo appears in newer WSL with DNS tunneling).
Let me actually inspect: ip route, /etc/resolv.conf, and check if we can reach Windows host IP on11434.
Important caveat: Ollama by default listens on localhost only. To allow WSL to reach it, either:
- Set OLLAMA_HOST=[REDACTED]:11434 (or the specific WSL-reachable interface) — this exposes it on the LAN potentially (Windows firewall applies). The requirement says don't expose to public internet. Binding [REDACTED] exposes to LAN. We could bind to the specific WSL virtual switch IP only? But OLLAMA_HOST accepts a single address. Binding to the WSL vEthernet adapter's IP (e.g., [wsl-gw-ip]) would restrict to just the WSL network — that's the safest.
Actually the cleanest, most standard solution: WSL mirrored networking mode in %USERPROFILE%\.wslconfig with networkingMode=mirrored. Then WSL shares Windows's network interfaces, and localhost forwarding works both ways — WSL can reach localhost:11434 on Windows (localhost forwarding is bidirectional in mirrored mode). This requires:
- Windows 11 22H2+
- WSL 2.x (>= 2.0)
- Reboot/restart of WSL (wsl --shutdown) — this would kill the running OpenCode session inside WSL! That's a big problem: OpenCode is running inside this WSL instance. Running wsl --shutdown would terminate our own session.
That's a serious risk. If I restart WSL, this OpenCode session dies. So mirrored mode is disruptive — it would kill the current session. Also mirrored mode changes loopback behavior generally.
Alternative: keep NAT mode, and instead make Ollama listen on the Windows vEthernet (WSL) adapter IP. That requires setting OLLAMA_HOST env var for the Ollama app — a Windows-side environment variable change + restarting the Ollama app. Then WSL connects to e.g. [wsl-gw-ip]:11434 (Windows's IP on the WSL NAT network). No WSL restart needed, no OpenCode session killed.
But how do we set OLLAMA_HOST persistently on Windows without "changing system settings" excessively? We can set a user environment variable via setx (registry HKCU\Environment) or use .wslconfig? No. For Ollama desktop app on Windows, the server env comes from the app's environment. Setting user env var OLLAMA_HOST and restarting the app works.
Also security: binding to [REDACTED] exposes to the whole LAN (Windows firewall may block inbound from LAN, but risky). Better: bind to the specific WSL virtual switch address.
But there's a chicken-and-egg: the WSL NAT network's Windows-side adapter (vEthernet (WSL)) IP is typically [wsl-gw-ip] for a /20 subnet... but our WSL eth0 is [wsl-gw-ip]/20, so network[wsl-gw-ip]/20? Let's compute: /20 with [wsl-gw-ip] → [wsl-gw-ip]/20. Windows vEthernet would be [wsl-gw-ip] likely. Need to check from WSL: default gateway.
Hmm, but actually: can WSL reach the Windows host at the gateway IP? In NAT mode, yes — Windows host is the NAT gateway and is reachable. Also Windows firewall typically allows WSL traffic (there's an explicit rule allowing WSL? Actually Hyper-V/WSL traffic to Windows host loopback... the Windows firewall may prompt/block inbound connections from WSL to Windows apps). Known issue: Ollama in WSL connecting to Windows host requires firewall allow rule sometimes. But Ollama installer adds firewall rules? Possibly not.
Let me think about the simplest robust approaches ranked:
Option A: WSL2 mirrored networking (networkingMode=mirrored in %USERPROFILE%\.wslconfig)
- Pros: standard modern solution; localhost works both directions; no Ollama changes.
- Cons: Requires wsl --shutdown → kills this OpenCode session and WSL restart. Also requires Windows 11 22H2+ and WSL 2.0+. Our Windows build: server.log said OS=Windows/10.0.26300 → Windows 11 build 26300 (very recent, 26xxx = Win11 25H2/26H1?). So mirrored is supported. WSL version need checking (wsl --version from Windows).
- The session kill is a real practical problem: I'd have to tell the user that WSL must be restarted and this OpenCode session will terminate.
Option B: Bind Ollama to the WSL-reachable Windows IP (keep NAT mode)
- Set OLLAMA_HOST to the Windows vEthernet WSL adapter IP or [REDACTED]:11434, restart Ollama app only (no WSL restart, session survives).
- WSL connects to hxxp://<windows-veth-ip>:11434.
- Risk: firewall rule may be needed to allow inbound; exposing to LAN if [REDACTED].
- Changes: Windows user env var + Ollama app restart. Also need firewall rule for the WSL interface? Might work without since traffic from WSL subnet may be treated as... Windows Firewall does filter it generally. Hmm.
Option C: Reverse port forward / socat proxy inside WSL: run socat in WSL listening on localhost:11434 forwarding to Windows host IP:11434 (which must be reachable) — still requires Windows side reachable → doesn't solve.
Actually, wait — there's another neat option: WSL2 supports localhostForwarding for Windows → WSL direction (WSL services reachable from Windows via localhost). For WSL → Windows, there's no built-in forwarding in NAT mode. So we need one of A or B.
Option D: WSL1? No.
So the two realistic options are A (mirrored) or B (bind Ollama to reachable IP).
Which is "safest and simplest for a development project"? Mirrored networking is the cleanest long-term (localhost works, no Ollama binding change, no firewall, no LAN exposure) but requires restarting WSL which kills the current session. Option B keeps the session alive but changes Ollama's bind address.
Hmm — but can I restart WSL? I'm running inside WSL. If I run wsl --shutdown from Windows-side interop (wsl.exe), it would terminate my own process. That would end the session and possibly leave the user confused. Definitely must not do that without asking.
Actually wait. Is there a way to get mirrored without full shutdown? No, .wslconfig changes require wsl --shutdown.
Another consideration: does the user's Windows support mirrored? Build 26300 — yes (Win11 22H2+ is 22621+). WSL version: need wsl --version. Let's check.
Also: importantly, is there possibly already an existing .wslconfig? Check.
Let me also verify current gateway/reachability from WSL to Windows host, and check Windows firewall rules, before deciding.
Plan for investigation:
1. ip route, /etc/resolv.conf (note: with DNS tunneling, resolv may show [lan-ip]), get Windows host IP.
2. Check if Windows host IP:11434 reachable (it won't be, since Ollama binds localhost only — need to confirm by testing gateway:11434 → should fail connection refused/timeout).
3. wsl --version via interop (careful: running wsl.exe from within WSL works).
4. Check existing %USERPROFILE%\.wslconfig.
5. Check Windows firewall rules for Ollama.
Then decide and propose to the user... Actually the user said "First report: what networking configuration you intend to use, why, what files/settings you will modify, then perform the minimum necessary changes and verify." So they want me to report then act in the same turn. I can do that: report at the start of my message, then do it.
But there's a decision to make about which option, which affects whether the session dies. That's a significant choice — should I ask the user? The user gave clear instructions: report then perform. Option A (mirrored) would kill this session — that's disruptive and they'd need to restart OpenCode. That's a strong reason to prefer Option B (keep session alive), OR to ask.
Let me consider option B more concretely:
Windows side: Ollama desktop app auto-starts (it started when I ran ollama.exe earlier, or was already set to autostart). To set OLLAMA_HOST, options:
- setx OLLAMA_HOST [REDACTED]:11434 (user env, persists; applies next time app starts) then restart the app (kill PID 4736 + relaunch ollama.exe — but wait, launching ollama.exe from WSL interop... running ollama.exe serve? The app is "ollama app.exe" (tray) which manages the server. Actually process list earlier showed only my shell; the server PID 4736 is a Windows process not visible in WSL ps.Restart approach: kill the server process (taskkill /PID 4736) then start the app (ollama app.exe or just ollama.exe which triggers app start as observed). Risky-ish but fine.
Hmm, but does the desktop app honor OLLAMA_HOST user env var? Yes, it passes environment through; the server log showed OLLAMA_HOST:hxxp://localhost:11434 as default from routes.go when unset. If env var set, it binds accordingly.
Binding to [REDACTED]:11434 → exposed on all interfaces including LAN/Wi-Fi. Requirement: "Do NOT expose Ollama to the public internet." [REDACTED] doesn't expose to public internet by itself (no port forwarding on home router; Windows firewall typically blocks inbound LAN by default unless allowed). But to be safest, bind only to the WSL vEthernet adapter IP (e.g. [wsl-gw-ip]) — that interface is only reachable by WSL VMs, not the LAN. That's strictly safer. Downside: that IP can change across WSL restarts (Windows creates the vEthernet with a subnet that can change). Typically the WSL NAT subnet is fairly stable but can change. For a dev project, instability is annoying.
Hmm. Which does the user prefer? They said "prefer the safest and simplest solution."
Let me reconsider mirrored mode once more. Actually — is there a middle path? Keep NAT + mirrored is a per-.wslconfig global change. Alternatively, WSL2 supports per-distro? No, networkingMode is in .wslconfig only (global).
What about Windows-side netsh interface portproxy to forward a WSL-reachable address to localhost:11434? portproxy can't listen on localhost... It can bind to specific address: netsh interface portproxy add v4tov4 listenaddress=[wsl-gw-ip] listenport=11434 connectaddress=localhost connectport=11434. That keeps Ollama bound to loopback (unchanged!) and exposes only on the WSL-facing interface. Requires admin rights for netsh portproxy (netsh interface portproxy requires elevation). Do we have admin in WSL? We're root in WSL, but interop runs Windows processes as the Windows user — UAC elevation would be needed, likely can't do silently.
Simpler: does WSL→Windows traffic to the Windows host's own IP on a bound interface get blocked by firewall? Possibly.Actually — wait. Let me reconsider: is there really no way for WSL NAT → Windows loopback? Correct, no.
Hmm, but here's another thought: Does Windows → WSL localhost forwarding matter? No, direction is WSL → Windows.
Let me also reconsider: maybe mirrored networking can be enabled without killing... no.
OK here's my inclination: Ask the user which of two options, since one kills the session (mirrored, cleanest) and the other changes Ollama's bind address (session survives, but exposes a bit more / requires app restart). The user explicitly asked me to first report what I intend to do, then do it — but given the tradeoff materially affects their running session, a quick question is justified. The guidance says use the question tool to clarify ambiguous instructions and get decisions.
Actually, let me first gather facts (WSL version, .wslconfig existence, Windows host IP, whether host IP reachable, firewall rules), then decide/ask with concrete info.
Actually, maybe I should reduce risk: I can test whether binding matters by checking current reachability to gateway:11434 (expected refused because Ollama binds localhost). Also I could test whether Windows firewall allows inbound by... can't without something listening.
Alternative neat approach: Instead of changing Ollama bind, set OLLAMA_HOST to bind only to the WSL vEthernet IP. Firewall: Windows Firewall may block inbound on that interface (profile = private/public?). The vEthernet (WSL) adapter is usually classified as "Private" or "Public"? Often it ends up on the "Public" profile... but Hyper-V vEthernet adapters are typically excluded from firewall? Actually Windows Firewall doesn't apply to traffic... no, it does apply. There are known issues where WSL→Windows app connections get blocked by firewall. However, there's a well-known special case: inbound from WSL to Windows — many report needing to allow the app in firewall (e.g., for Ollama in WSL → Windows Ollama, people add a firewall rule for port 11434 or0.0.0.0 binding works out of box? Reports vary).
Given uncertainty, mirrored mode is genuinely the most reliable and is the "standard modern" fix for exactly this problem: WSL docs say mirrored networking gives "localhost forwarding in both directions" and "Windows apps can access WSL services and vice versa". Actually careful: mirrored mode gives WSL→Windows localhost access? In mirrored mode, loopback is shared? The docs: "Applications running in Windows can connect to applications running in WSL via localhost, and vice versa." Hmm, I believe mirrored mode mirrors loopback too — yes, with mirrored networking, localhost is shared (there's ignoredPorts, and loopback is accessible both ways). Actually I recall that in mirrored mode, WSL can reach Windows services on localhost because the network stack is mirrored... Let me verify from docs rather than memory. I should fetch WSL networking docs.
But the session-kill problem remains. Let me think about what happens if I do mirrored: I'd modify .wslconfig on Windows, then need wsl --shutdown. My own session dies → user must restart OpenCode. The user is interactively working with me; killing my session mid-conversation is bad UX but they'd just reopen. They explicitly said "After making any required configuration change, verify from WSL that the Ollama API is reachable. Then run a minimal local generation test from WSL." That verification must happen in this session ideally. If I kill WSL, I can't verify.
Therefore: Option B (keep NAT, make Ollama reachable from WSL) is the only one I can actually verify within this session. Unless... after wsl --shutdown, WSL restarts automatically when a new command runs — but my session would be dead; the user would need to restart OpenCode. So verification from within this session requires NOT restarting WSL.
So: Option B it is, unless the user prefers mirrored. I could present the choice, but I lean to: report plan = bind Ollama to WSL-reachable address (specific vEthernet IP for safety, or [REDACTED] for simplicity), restart Ollama app only, verify from WSL, run test generation.
Risk: firewall. Let's investigate and handle: if firewall blocks, add a firewall rule scoped to the WSL subnet (netsh advfirewall requires admin → UAC prompt; can't do silently from non-elevated). Hmm. Let's test first — often it works because... let's just test.
Wait, actually there might be an even less invasive trick: Is the Windows host reachable from WSL at its own172.22.x.1 address, and does binding to [REDACTED] matter? Yes it matters (currently localhost).
Another thought — could I avoid touching Ollama entirely by running a tiny port forwarder inside WSL? It needs a reachable Windows endpoint, so no.
What about running a forwarder on Windows that listens on the vEthernet IP and forwards to localhost:11434? That's like portproxy but needs a Windows process (e.g., a small script). More moving parts than setting OLLAMA_HOST. No.
What about... using Windows' built-in netsh interface portproxy? Needs admin. The OLLAMA_HOST env var change also needs an app restart but not admin (user env var + killing our own app process). Actually killing Ollama server process — it runs as our user, taskkill works without admin. Restarting ollama app.exe — launches fine.
Hmm, but is modifying OLLAMA_HOST "changing system settings"? It's a user-scope environment variable — that's the minimum necessary configuration change the user authorized ("After making any required configuration change...").
Security consideration for0.0.0.0: Ollama will listen on all interfaces including Wi-Fi LAN. Windows firewall may or may not block inbound. To be safe per "Do NOT expose Ollama to the public internet" ([REDACTED] alone isn't public internet exposure, but LAN exposure is a widening). Safer: bind specifically to the WSL vEthernet IP.
Let me determine that IP: ip route default gateway in WSL NAT mode = Windows host IP on the vEthernet. Let's check.
Hmm — one more important consideration: if we bind OLLAMA_HOST to a specific IP and later WSL restarts with a different subnet, it breaks. WSL NAT subnet usually persists but can change. For a dev project, maybe accept and note it.
Alternatively bind [REDACTED]:11434 but confirm Windows Firewall blocks external (interface-agnostic)? Firewall is per-profile/per-interface, blocking by default inbound except allow rules. Ollama installer might add an allow rule already? Let's check firewall rules for Ollama/11434 — read-only netsh advfirewall firewall show rule or PowerShell Get-NetFirewallRule — needs no admin to read? Reading rules generally works without admin.
Plan:
1. Investigate: WSL version (wsl --version), existing .wslconfig, Windows host IP, current reachability, firewall rules for Ollama/port 11434, Ollama env config.
2. Report intended config.
3. Make change (set user env OLLAMA_HOST to chosen address, restart Ollama app only).
4. Verify from WSL: http-get /api/version, /api/tags, then generate test with gemma4:e2b.
5. Confirm no public exposure (verify listening addresses with netstat).
Also should confirm binding: after change, netstat -ano | findstr 11434 to show what address it's bound to — verifies not exposed beyond intended.
Also note: Ollama's ORIGINS/CORS is already permissive (OLLAMA_ORIGINS includes localhost variants) — for browser apps from WSL origin (e.g., hxxp://localhost:5173) might need adding... not now; server-side requests don't need CORS. Keep changes minimal.
Let me investigate now. Run parallel commands.
Careful with wsl --version — running wsl.exe from within WSL is fine (it's supported? wsl.exe --version from inside WSL works via interop; it queries the WSL utility). Should be OK.
Let's gather.
I'll investigate the exact networking setup first, then report my plan before changing anything.
$ ip route; echo "---resolv---"; cat /etc/resolv.conf; echo "---hosts---"; cat /etc/wsl.conf 2>/dev/null || echo "no /etc/
default via [wsl-gw-ip] dev eth0 proto kernel [wsl-gw-ip]/20 dev eth0 proto kernel scope link src [wsl-gw-ip] ---resolv--- # This file was automatically generated by WSL. To stop automatic generation of this file, add the following entry to /etc…
$ {"command": "ls -la \"/mnt/c/Users/user/.wslconfig\" 2>&1; cat \"/mnt/c/Users/user/.wslconfig\" 2>&1; echo \"===wsl vers
ls: cannot access '/mnt/c/Users/user/.wslconfig': No such file or directory cat: /mnt/c/Users/user/.wslconfig: No such file or directory ===wsl version=== WSL version: 2.3.26.0 Kernel version: 5.15.167.4-1 WSLg version: 1.0.65 MSRDC version: 1.2.5620…
$ {"command": "/mnt/c/Windows/System32/WindowsPowerShell/v1.0/powershell.exe -NoProfile -Command \"(Get-NetFirewallRule -D
Where-Object : The term '.LocalPort' is not recognized as the name of a cmdlet, function, script file, or operable program. Check the spelling of the name, or if a path was included, verify that the path is correct and try again. At line:1 char:221 +…
PowerShell mangled $_ (the $_ got eaten by shell). Need to escape or use a script file. Let's write a temp .ps1 in /tmp/opencode and run with -File. That's allowed (temp dir outside workspace, not project files).
Also check: Windows host IP = gateway [wsl-gw-ip]. Test connectivity to [wsl-gw-ip]:11434 (expect refused since Ollama binds localhost).
WSL version 2.3.26, Windows 10.0.26300 (Win11 25H2/26H1 dev build) — mirrored networking supported (needs Win11 22H2+). No .wslconfig exists yet.
Let's do: test gateway:11434, write ps1 for firewall query.
$ {"command": "http-get -s -m 5 hxxp://[wsl-gw-ip]:11434/api/version; echo \"gw_exit=$?\"; http-get -s -m 5 hxxp://[lan-ip]
gw_exit=28 dnsip_exit=7
file: /tmp/opencode/fwcheck.ps1 $ErrorActionPreference = 'SilentlyContinue' Write-Output '=== Rules mentioning Ollama ==
Wrote file successfully.
Interesting: http-get hxxp://[wsl-gw-ip]:11434 → exit 28 (timeout) — meaning packets dropped (firewall drop or no listener on that address). Exit 7 for [lan-ip] (connection refused — no listener on that IP... actually [lan-ip] is on lo in WSL? It showed inet [lan-ip]/32 scope host lo — that's a local address in WSL (WSL DNS tunnel). Exit 7 = refused locally since nothing listening on 11434 in WSL. Fine.
For [wsl-gw-ip]:11434 → timeout: this is the Windows host. Two possible causes: (a) Ollama binds127.0.0.1 only → no listener → Windows would normally send RST (exit 7) unless firewall blocks (silent drop → exit 28). Timeout suggests firewall DROP. So Windows Firewall is dropping inbound 11434 from WSL. That means even after binding OLLAMA_HOST to [REDACTED]/the vEthernet IP, we'd need a firewall allow rule → requires admin/UAC.
Hmm! That's important. Let's run the firewall check script to see.
If a firewall rule is needed and requires elevation, options:
- PowerShell with elevation: Start-Process -Verb RunAs → UAC prompt on user's screen. User may be OK with clicking UAC. It's a "system settings" change (firewall rule) but justified as minimum necessary. The user said "Do not change system settings" in the first message (inspection-only), but this message says "perform the minimum necessary changes" for connectivity. Adding a firewall rule scoped to the WSL subnet/edge-transversal is part of that, but we should report it.
wsl --shutdown → kills this session.Wait — actually, is there any way to enable mirrored without killing session? No.
Hmm, but hold on. Let me reconsider the firewall timeout. Exit 28 could also be because Windows host at [wsl-gw-ip] doesn't respond to ARP? No, it's the gateway, definitely alive. Or the vEthernet has no service bound → RST expected. Timeout = drop → firewall.
Actually another possibility: WSL NAT networking — traffic from WSL to Windows host on non-allowed ports gets dropped by Windows Firewall (default inbound block). Yes.
So decision matrix:
Option B (keep NAT):
1. Set user env OLLAMA_HOST=[REDACTED]:11434 or specific IP.
2. Restart Ollama app.
3. Add Windows Firewall inbound allow rule for TCP 11434, scoped to... firewall rule scope can限定 RemoteAddress to [wsl-gw-ip]/20 (WSL subnet). That keeps LAN blocked. Requires admin (UAC prompt).
4. Verify from WSL.
Changes: user env var + firewall rule + Ollama restart. ~3 changes. Firewall rule needs UAC click (we can trigger elevation; user clicks Yes). We're root in WSL — does that mean Windows runs elevated? No: interop runs as the Windows user; if the user account is admin with UAC, non-elevated processes run as medium integrity. Actually, interesting: is UAC disabled / are we running as admin? Some dev machines have admin account with UAC on. Let's test whether we can run an elevated command silently — we can try powershell Start-Process -Verb RunAs and see if a UAC prompt appears (it would appear on user's desktop). Better: first check if current Windows token is elevated: whoami /groups looking for S-1-16-12288 (high integrity) or admin group enabled.
Let's check integrity level: whoami /groups | findstr S-1-16. If already high integrity (some setups run as admin), no UAC needed.
Option A (mirrored):
- Create .wslconfig with [wsl2] networkingMode=mirrored.
- wsl --shutdown → kills this session. User restarts OpenCode; then verify (but verification happens in new session, I can't do it — well, technically after shutdown my processes die; the tool would fail).
- No Ollama change, no firewall rule (loopback shared).
Given verification requirement, Option B is workable in-session. Let's check elevation status first.
Also consider: maybe firewall already has an allow rule for Ollama but bound only to certain profiles? The script will tell.
Another wrinkle for Option B: which address to bind? If we bind0.0.0.0, LAN exposure depends on firewall: our new rule would be scoped to WSL subnet RemoteAddress, so LAN stays blocked by default-deny. But Ollama listening on all interfaces + firewall blocking non-WSL → acceptable. Even safer: bind to specific vEthernet IP ([wsl-gw-ip]) — but that IP changes when WSL subnet regenerates (can happen after wsl --shutdown or Windows reboot... actually the vEthernet subnet is fairly stable per machine but can change). Binding [REDACTED] + firewall scoped to WSL subnet is more robust and still not exposed to internet or LAN.
Hmm, but "safest and simplest". I think: OLLAMA_HOST=[REDACTED]:11434 + firewall rule limited to RemoteAddress=[wsl-gw-ip]/20 is good. But if the WSL subnet changes later, connection breaks (rule wouldn't match). Could allow rule with multiple/subnet. Alternatively allow the vEthernet interface only: -InterfaceAlias 'vEthernet (WSL)' — that's interface-scoped; traffic arriving via that interface only comes from WSL VMs. That's robust to subnet changes and blocks LAN/Wi-Fi. Firewall rule: Direction Inbound, Protocol TCP, LocalPort 11434, InterfaceAlias 'vEthernet (WSL)', Action Allow.
But note: with mirrored mode... not using it.
Wait — actually, is the interface named "vEthernet (WSL)"? Could be "vEthernet (WSL (Hyper-V firewall))" in newer versions. The Get-NetConnectionProfile output will show aliases. Let's run the script.
Also — Hyper-V firewall! WSL2 has its own Hyper-V firewall settings (Set-NetFirewallHyperVVMSetting -Name '{40E0AC32-...}' -DefaultInboundAction Allow?). The default Hyper-V firewall for WSL VM may block inbound. In recent WSL, there's hyperVFirewall settings in .wslconfig? There's Set-NetFirewallHyperVVMSetting with the WSL VM GUID controlling DefaultInboundAction. The timeout we saw might be from Hyper-V firewall rather than Windows Firewall. Hmm.
Let's gather data first: run fwcheck.ps1, check integrity level, list Hyper-V firewall settings.
Let's proceed.
$ {"command": "/mnt/c/Windows/System32/WindowsPowerShell/v1.0/powershell.exe -NoProfile -ExecutionPolicy Bypass -File /tmp
Windows PowerShell Copyright (C) Microsoft Corporation. All rights reserved.The argument '/tmp/opencode/fwcheck.ps1' to the -File parameter does not exist. Provide the path to an existing '.ps1' file as an argument to the -File parameter.
$ {"command": "whoami; echo \"---integrity---\"; /mnt/c/Windows/system32/whoami.exe /groups | tr -d '\\0' | grep -Ei \"S-1
root ---integrity--- Mandatory Label\Medium Mandatory Level Label S-1-16-8192 Everyone Well-known group S-1-1-0 Mandatory group, Enabled by default, Enabled group BUILTIN\Users Alias S-1-5-32-545 Mandatory group, Enabled by default, Enabled group NT …
Two things:
1. PowerShell can't see /tmp/opencode (Windows path). Need to put the script on a Windows-visible path (e.g., [REDACTED]\AppData\Local\Temp or D:\OfflineMode — but we must NOT create project files in D:\OfflineMode). Use %TEMP% = [REDACTED]\AppData\Local\Temp — writing a temp script there is fine (not a project file, and it's a temp file; user said don't create project files; temp helper outside project is acceptable, I'll clean up).
Interesting: whoami in WSL shows root (WSL user) but interop Windows processes run as Windows user user, medium integrity. Note admin group not even listed as enabled... groups list doesn't show Administrators at all → user may be a non-admin account? Actually MicrosoftAccount[email redacted] — Administrators group would show as "Group used for deny only" typically when elevated-less admin... It's not in the list at all (grep only S-1-16/Mandatory and it showed mandatory groups only... wait, the grep pattern was "S-1-16-|Mandatory" so Administrators as "Group used for deny only" (S-1-5-32-544) wouldn't match unless it has "Mandatory" in it. Let me not over-infer. IsInRole(Administrator)=False.
Let me rerun fwcheck with script in Windows temp, and also check whether Administrators group present (deny only) and whether a UAC elevation would succeed (can't know without prompting).
Also check Hyper-V firewall settings.
Alternative to avoid firewall entirely: portproxy/netsh also needs admin. Any Windows-side bind change to a non-loopback address needs firewall allow (admin). Hmm.
Unless... hmm, wait. What about the reverse direction trick: does WSL's NAT allow Windows→WSL localhost forwarding (yes) — but we need WSL→Windows.
What about running the Ollama server inside WSL? No — user wants to use existing Windows Ollama + models (models are on Windows disk; Ollama in WSL would need install + download → forbidden).
What about an SSH reverse tunnel? Needs sshd on Windows... no.
So options requiring admin on Windows side:
(a) firewall rule (+ OLLAMA_HOST bind change)
(b) netsh portproxy (listen on [wsl-gw-ip]:11434 → localhost:11434) + firewall rule for11434 anyway. Actually portproxy traffic also subject to firewall. So both need firewall.
Hmm, does inbound to a specific non-loopback address really get dropped? Our test: http-get to [wsl-gw-ip]:11434 timed out. Currently nothing listens there (Ollama on localhost) → should be RST unless firewall drops. Timeout confirms firewall drop (or Hyper-V firewall drop).
Wait, actually — maybe it's the Hyper-V firewall (WSL VM specific). Windows Firewall rules might not even apply to vEthernet (WSL) interface... Actually Hyper-V firewall governs traffic to/from VMs. Set-NetFirewallHyperVVMSetting has DefaultInboundAction for the WSL VM. Recent Windows/WSL defaults: Hyper-V firewall default inbound = Block? There's a known setting where WSL's Hyper-V firewall blocks inbound to Windows host by default.
Either way it's an elevation-required firewall change.
(c) Mirrored networking — needs .wslconfig (user file, no admin!) + wsl --shutdown (kills session). Under mirrored mode, is loopback shared? Let me verify: WSL docs say with mirrored networking "applications running in Windows can connect to applications running in WSL via localhost and vice versa". Yes, "vice versa" means WSL apps can connect to Windows apps via localhost. But wait — Ollama binds localhost on Windows. In mirrored mode, does WSL's localhost map to Windows loopback? Mirrored mode mirrors the network interfaces including... I believe loopback is NOT mirrored initially; there was a feature where localhost forwarding becomes bidirectional. Docs mention for mirrored: "Localhost forwarding is supported in both directions" — I'm fairly confident: WSL docs "Mirror mode ... This will allow Windows apps to connect to WSL apps via localhost, and WSL apps to connect to Windows apps via localhost"? Let me verify via docs fetch to be accurate.
Actually, there's documented behavior: In mirrored networking, WSL shares Windows's network stack, so localhost in WSL... Hmm, WSL has its own loopback. In mirrored mode there's a component that forwards loopback both ways (there were bugs about this). Known GitHub issues: "localhost forwarding from WSL to Windows doesn't work in mirrored mode" — hmm, actually mirrored mode does support it via ignoredPorts and loopback proxying.
I should check the docs. But even if mirrored works, it requires wsl --shutdown → kills this OpenCode session → I cannot verify in-session. The user explicitly wants verification from WSL after the change. If I choose mirrored, I'd have to tell the user "restart required, verify after restart" — and my session dies mid-way.
So: primary plan = firewall allow + OLLAMA_HOST bind (Option B), needing elevation (UAC prompt). Is triggering UAC acceptable? It's a user-interactive approval; I can use Start-Process -Verb RunAs which pops UAC on their desktop. But I'm in a headless-ish CLI? The user is on Windows desktop (WSLg etc.), so UAC prompt would appear on their screen. Risky if they're not watching... but they asked me to do it.
Hmm, is there a way to check if a firewall rule for WSL already exists? Let's run the fwcheck script first. Maybe Ollama installer already added a rule allowing 11434 (Ollama Windows installer does add firewall rules? I'm not sure). If a rule exists but scoped wrong... Let's look.
Also possible: the timeout might be Hyper-V firewall; and Windows Firewall might already allow. Let's get facts.
Write script to [REDACTED]\AppData\Local\Temp\fwcheck.ps1 via WSL path /mnt/c[REDACTED]/AppData/Local/Temp/fwcheck.ps1.
Also query Hyper-V firewall: Get-NetFirewallHyperVVMSetting, Get-NetFirewallHyperVProfile. And check if Ollama has rules (DisplayName 'Ollama' might have failed silently earlier because first command output was empty... in the first PowerShell attempt, the first half with DisplayName -like 'Ollama' output nothing (silently continued) — so no rules named Ollama).
Let's write comprehensive script.
file: /mnt/c/Users/user/AppData/Local/Temp/fwcheck.ps1 $ErrorActionPreference = 'SilentlyContinue' Write-Output '=== Rul
Wrote file successfully.
Now run it.
$ {"command": "/mnt/c/Windows/System32/WindowsPowerShell/v1.0/powershell.exe -NoProfile -ExecutionPolicy Bypass -File \"C:
(no output) <shell_metadata> shell tool terminated command after exceeding timeout 120000 ms. If this command is expected to take longer and is not waiting for interactive input, retry with a larger timeout value in milliseconds. </shell_metadata>
The PowerShell script hung — probably Get-NetFirewallRule piped to Get-NetFirewallPortFilter over thousands of rules is slow, or tr -d with buffering. Let's split into smaller queries with longer timeout, or run in background. Let's run simpler individual queries.
Actually the pipe Get-NetFirewallRule | Get-NetFirewallPortFilter for ALL rules is expensive. Let's instead query Get-NetFirewallRule -DisplayName '*Ollama*' and use Get-NetFirewallApplicationFilter? Simpler: check specific things:
netsh advfirewall firewall show rule name=all | findstr 11434 — slow too.Better approach for port rules: use CIM query filtering: Get-CimInstance -ClassName MSFT_NetFirewallPortFilter -Filter "LocalPort='11434'"? Hmm, association traversal still needed.
Alternative quick check: instead of enumerating firewall rules, just empirically test. Currently timeout → blocked. After we add rule (if we do), test again.
Let's do the fast queries first with timeout 60s each, in separate commands.
$ {"command": "/mnt/c/Windows/System32/WindowsPowerShell/v1.0/powershell.exe -NoProfile -Command \"Get-NetTCPConnection -L
LocalAddress LocalPort State OwningProcess ------------ --------- ----- ------------- localhost 11434 Listen 4736 InterfaceAlias NetworkCategory -------------- --------------- Wi-Fi Public OLLAMA_HOST User=
$ {"command": "/mnt/c/Windows/System32/WindowsPowerShell/v1.0/powershell.exe -NoProfile -Command \"Get-NetFirewallHyperVVM
Name : {40E0AC32-46A5-438A-A0B2-2B479E8F2E90} Enabled : NotConfigured DefaultInboundAction : NotConfigured DefaultOutboundAction : NotConfigured LoopbackEnabled : NotConfigured AllowHostPolicyMerge : NotConfigured Name : {40E0AC32-46A5-438A-A0B2-2B47…
Key facts:
- Ollama listening: localhost:11434 only (PID 4736).
- Network profile: Wi-Fi = Public. The vEthernet (WSL) adapter didn't appear in Get-NetConnectionProfile output (only Wi-Fi Public) — maybe because profile query only shows connected profiles; the WSL vEthernet may have no listed profile or is omitted. Hmm, Get-NetConnectionProfile returned only Wi-Fi Public. Interesting.
- No firewall rules named Ollama.
- Hyper-V firewall for WSL VM GUID: all NotConfigured → defaults apply. Default for Hyper-V firewall inbound: I believe default is Block for inbound to host? Not sure.
- $_ gets stripped by bash→powershell -Command quoting: $ is being eaten by the shell (zsh expands $_). Need single-quoted bash strings. Careful.
Now, the key question: what blocks WSL→[wsl-gw-ip]:11434? Two candidates: Windows Firewall (inbound block on... but which interface? vEthernet (WSL)) or Hyper-V firewall.
Rather than exhaustively diagnosing, the decision:
Plan A (recommended): mirrored networking — needs wsl --shutdown → kills session. Not verifiable in-session.
Plan B: bind Ollama + firewall allow — needs elevation for both changes (setx user env doesn't need elevation; restarting Ollama app doesn't need elevation; firewall rule needs elevation).
Wait — does changing OLLAMA_HOST alone suffice? No, because even if Ollama listens on [wsl-gw-ip], firewall drops → timeout. Both changes needed.
Hmm, unless the drop is due to Hyper-V firewall default inbound block. Let's think about which is more likely.Actually — important nuance: traffic from WSL VM to Windows host IP. In WSL2 NAT mode, packets from the VM arrive on the "vEthernet (WSL)" interface of Windows. Windows Firewall applies with profile based on that adapter's category (vEthernet (WSL) usually gets categorized... it didn't show in Get-NetConnectionProfile which is odd — maybe it shows as unidentified network). Windows Firewall default inbound block applies → drop → our timeout (Windows sends RST normally... no, firewall default block = drop silently, matching exit 28).
So yes, Windows Firewall inbound block on that interface is the most likely cause. Adding an inbound allow rule for TCP 11434 scoped to interface 'vEthernet (WSL)' (or RemoteAddress = WSL subnet) fixes it.
But also the Ollama bind must change to [REDACTED] or the specific IP.
Elevation needed for:
- netsh advfirewall firewall add rule (admin)
- setx OLLAMA_HOST (no admin needed for HKCU)
- Restart Ollama app (no admin; taskkill own process + start)
UAC prompt: I can trigger with Start-Process -Verb RunAs, which shows a UAC dialog on the user's desktop. The user is present (they're interacting). I should ask/inform them first — the instructions say report plan first, then perform. So I'll report and ask them to approve UAC when it appears? Better: ask a clarifying question about which approach they prefer, given the tradeoff.
Actually, let me reconsider whether elevation is really needed — maybe UAC is disabled on this machine? IsInRole(Administrator)=False suggests token is filtered (UAC on). If user is in Administrators group, elevation possible with UAC click. Let's check group membership: whoami /groups full output (my grep filtered). Let's check if 'Administrators' appears as deny-only.
Also alternative without elevation: Is there a way to make WSL reach Windows loopback without firewall changes?
Idea: WSL can reach Windows via... the mirrored mode only.
Idea: Use netsh interface portproxy — requires admin too.
Idea: Windows → WSL direction: WSL runs its own Ollama-compatible proxy? Still needs Windows-side listener reachable.
Idea: Use Hyper-V firewall / WSL settings from .wslconfig — .wslconfig supports [wsl2] firewall=? Hmm, WSL has settings: dnsTunneling, autoProxy, firewall (added in newer WSL: firewall=true enables Windows Firewall for WSL?). Not helpful.
Idea: localhostForwarding only works Windows→WSL.
So no-admin solution doesn't exist for WSL→Windows NAT...
Hmm wait — one more: what if the WSL VM connects to the Windows host through the Hyper-V default — no.
What about using socat inside WSL listening on WSL's localhost, and on Windows a process connecting out to WSL? WSL→Windows needs inbound to Windows regardless... unless Windows initiates the connection to WSL (which is allowed outbound) and we tunnel. E.g., run a Windows-side reverse tunnel: Windows ssh -R? Needs sshd in WSL (can install? no installs... openssh-server may not be installed; can't install).
OK: elevation it is (or mirrored+restart).
Let me now consider which is truly "safest and simplest" per user's requirement #4.
Given the user's explicit verification requirements (do it from WSL, then run generation test), and that they want minimal changes:
Recommended: Option B —
1. Set user env OLLAMA_HOST=hxxp://[REDACTED]:11434 (HKCU, no admin).
2. Add Windows Firewall inbound allow rule: TCP 11434, Interface = vEthernet (WSL) only (or remote address = WSL subnet) (admin → UAC prompt).
3. Restart Ollama app (no admin).
4. Verify: netstat shows [REDACTED]:11434 (and check we didn't accidentally expose: firewall scoped), WSL http-get /api/version, /api/tags, minimal generation with gemma4:e2b.
Concern: binding [REDACTED] means Ollama listens on Wi-Fi too. Firewall rule scoped to vEthernet (WSL) interface blocks Wi-Fi inbound (default deny). So public/LAN exposure = none (also router NAT blocks public). But strictly "safest" would be binding only to [wsl-gw-ip] — however that IP can change when WSL restarts (the vEthernet subnet can be regenerated), causing breakage later. Tradeoff: robustness vs. minimality of exposure. With firewall scoped to the WSL interface, [REDACTED] binding is still LAN-safe. Hmm, but if firewall rule is scoped by interface alias 'vEthernet (WSL)', and Windows applies profile rules... it's a solid approach.
Actually simpler and even safer: firewall rule scoped with RemoteAddress = [wsl-gw-ip]/20 (the WSL NAT subnet). But if subnet changes → break. Interface-based rule survives subnet change. I'll use InterfaceAlias scoping: -InterfaceAlias 'vEthernet (WSL)'. Need exact alias name — let's confirm adapter names (my Get-NetIPConfiguration query failed due to quoting). Re-run with proper single quotes.
Alternatively, scope the rule to RemoteAddress of WSL subnet AND bind Ollama to [REDACTED].
Hmm — wait. Actually, can we avoid the firewall rule if we bind Ollama to the vEthernet IP? No — firewall still drops regardless of bind address (inbound to that IP on that interface is still filtered).
Unless Hyper-V firewall is what's blocking... Windows Firewall rule would still be needed most likely.
Let me first confirm which layer blocks: run a test listener? E.g., start a simple listener on Windows bound to [wsl-gw-ip] on another port (e.g., 18080) using PowerShell TcpListener in background, then http-get from WSL. If it also times out → firewall drop confirmed. That doesn't change settings (temporary process). It's a reasonable diagnostic. But it adds complexity; maybe just proceed: the plan is firewall rule anyway if bind change alone insufficient. But to make "minimum changes", knowing the cause matters.
Actually simpler: do steps in order and test after each:
1. Set OLLAMA_HOST=[REDACTED]:11434, restart Ollama → test from WSL. If it works (i.e., firewall wasn't the issue — maybe Windows auto-allows because... no, timeout strongly implies drop), then only one change needed.
2. If still blocked → add firewall rule (UAC) → retest.
That's the truly minimal approach: try bind-only first, then firewall if needed.
Hmm, but I know the timeout already indicates drop. Still, bind-only test is cheap and requires no admin. Good ordering.
Now: how to restart Ollama? The desktop app (ollama app.exe, PID for the tray). The server PID 4736 — which process is it? ollama.exe serve presumably spawned by app. taskkill PID 4736 then app may respawn it? The tray app might monitor and restart, or might not. Safer: kill the app too and restart the app.
How did the app start originally? At 13:55 it started — likely triggered when I ran ollama.exe --version? Hmm, actually ollama.exe is the CLI; when server isn't running... For desktop installs, ollama.exe CLI running a command that needs the server typically just errors "could not connect", it doesn't auto-start the app... Actually it DID show "Warning: could not connect to a running Ollama instance" then client version. Then server started at 13:55:28 — maybe the user started it, or the tray autostarts at login (log at 13:55 today though...). The app.log shows "starting Ollama" at 13:55:26. My ollama.exe --version ran at about that time. Plausibly ollama.exe on Windows with desktop app installed triggers app launch. Or the updater.
For restart: kill PID 4736 (the server). Does "ollama app.exe" respawn it? Uncertain. Alternative: after killing, run "[REDACTED]\AppData\Local\Programs\Ollama\ollama app.exe"? The tray is "ollama app.exe". Hmm, there's also ollama.exe serve.
Actually, since we need the new env var to be picked up, the env var must be in the server process's environment. If we start ollama.exe serve ourselves from WSL interop with OLLAMA_HOST set inline, the server runs as a child of our interop process — it would die when our shell exits? Interop processes: when the WSL session ends, Windows child processes might get killed or survive (they're separate processes on Windows; they typically survive but lose the console). Risky for a long dev session.
Cleaner: set HKCU env var OLLAMA_HOST, then restart the Ollama desktop app (kill tray + server, start ollama app.exe). The app then spawns server with user env.
Wait — does the app inherit HKCU env? New processes launched after env change read the updated registry (for processes started via Explorer/Shell, env comes from the shell's environment which was set at login — child processes inherit from parent, not re-read registry!). Critical: setting HKCU\Environment does NOT affect already-running Explorer-spawned apps until Explorer restarts/logoff... BUT, when you launch a new app via ShellExecute, the new process gets environment from the parent (Explorer), which has stale env. However, if launched from a process that reads registry... Actually many apps that need env re-read via WM_SETTINGCHANGE broadcast. The Ollama app launched fresh — its env comes from its parent (Explorer, stale). Hmm.
BUT: WSL interop-launched processes — env comes from the WSL interop parent? No: WSL interop launches Windows processes via CreateProcess, and the env block is... WSL constructs env for interop processes; it includes Windows env vars (WSL reads them from registry at startup? Actually WSL interop passes the Windows environment it received). Hmm complicated.
Simplest robust approach: launch the Ollama server ourselves with OLLAMA_HOST set explicitly in the command line, e.g.:
- PowerShell: $env:OLLAMA_HOST='[REDACTED]:11434'; & 'C:\...\ollama.exe' serve → but as child of that PowerShell; when PowerShell exits, the serve process keeps running (detached enough? if parent exits, child continues running on Windows — yes, Windows doesn't kill children when parent exits, unless job objects are used. Interop might use job objects? WSL interop doesn't put Windows processes in a job that kills them AFAIK. But console handling: when the launching console closes, the process may get CTRL_CLOSE_EVENT — only if it's attached to that console and the console is destroyed. WSL interop processes do attach to a console... risky: killing our zsh might close the console and terminate the server.)
Safer: use PowerShell Start-Process -WindowStyle Hidden with environment; Start-Process inherits current env of the PowerShell we spawn (which we set inline) and detaches properly (new console or no console with -WindowStyle Hidden). That gives a properly detached server with OLLAMA_HOST set. But then the tray app ("ollama app.exe") also running might conflict (two servers, port conflict). The tray app would try to start its own server → conflict. We should kill the tray app first (and its server).
Alternatively — maybe the desktop app has a config file? Ollama app on Windows: it uses env vars; there's also the possibility of setting env at user scope and then killing the tray app and starting it from a process that has fresh env (e.g., we start it ourselves via Start-Process after setting $env:OLLAMA_HOST in our PowerShell). Since we spawn both server-or-app fresh with inline env, the env problem is solved without registry tricks.
Plan:
1. (Try first) set OLLAMA_HOST inline and start server/app with it.
2. Kill existing tray app + server (taskkill).
3. Start ollama app.exe with OLLAMA_HOST set (via PowerShell Start-Process with -Environment? PS5.1 Start-Process doesn't have -Environment param (PS7 does). We can set $env:OLLAMA_HOST in the PS session then Start-Process inherits it. Since powershell.exe is spawned fresh from WSL, its env comes from WSL interop env... but we set it explicitly → fine.)
4. Server binds [REDACTED]:11434. Test from WSL.
5. If blocked → firewall rule (UAC elevation) scoped to vEthernet (WSL) interface or WSL subnet.
Also persist: set user env var via setx for future app autostarts (so after reboot it still binds [REDACTED]). setx OLLAMA_HOST "[REDACTED]:11434" — writes HKCU. Does that require admin? No. But will the app started at login (via Run key / startup) pick it up? Processes started by Explorer at login: Explorer reads env at logon from registry → yes, at next logon Explorer refreshes env from registry (Explorer does refresh env on WM_SETTINGCHANGE and at logon). Startup items launched by Explorer at logon inherit Explorer's env, which was built at logon from the updated registry. So yes, persists correctly across reboots. Within the current session, Explorer's env is stale but we're not launching via Explorer anyway.
So persist via setx (or [Environment]::SetEnvironmentVariable('OLLAMA_HOST', ..., 'User')).
Security framing: binding [REDACTED] + firewall rule limited to the WSL virtual adapter = not exposed to internet or LAN. Also Ollama has no auth — note it.
Alternatively bind only to[wsl-gw-ip]... I decided [REDACTED] + interface-scoped firewall rule. Hmm, but wait: is binding [REDACTED] with firewall scoped-by-interface truly safe if firewall profile of vEthernet... The rule: netsh advfirewall firewall add rule name="Ollama WSL only" dir=in action=allow protocol=TCP localport=11434 interface="vEthernet (WSL)". netsh supports interfacedisplayname= / interface= param? netsh advfirewall firewall add rule supports interface=<alias>? It supports interfacedisplayname= I think... Actually netsh advfirewall firewall add rule parameters include: dir, action, enable, profile, program, service, localip, remoteip, protocol, localport, remoteport, interfacetype, interface (yes, interface= exists? Let me recall: netsh advfirewall firewall add rule name=... dir=in action=allow protocol=TCP localport=80 profile=private remoteip=[lan-ip]/24 — I'm fairly sure there's no interface param in netsh... Hmm. There IS: netsh advfirewall firewall add rule ... interface=? Checking memory of docs: parameters are name, description, dir, action, enable, profile, program, service, localip, remoteip, protocol, localport, remoteport, interfacetype, interface, localtunnell端... I'm reasonably confident interface isn't in netsh but PowerShell New-NetFirewallRule has -InterfaceAlias. Use PowerShell with elevation: New-NetFirewallRule -DisplayName "Ollama (WSL only)" -Direction Inbound -Action Allow -Protocol TCP -LocalPort 11434 -InterfaceAlias 'vEthernet (WSL)' -Profile Any.
Need exact alias: let's list adapters.
Alternatively scope by RemoteAddress: -RemoteAddress [wsl-gw-ip]/20. Simpler, works regardless of alias naming, but subnet may change on WSL restart. InterfaceAlias is more stable (name 'vEthernet (WSL)' is stable). Could do both (RemoteAddress + interface) → too restrictive if subnet changes? RemoteAddress = WSL subnet is dynamic... use InterfaceAlias only.
Hmm, but careful: does inbound traffic from the WSL VM arrive on interface 'vEthernet (WSL)'? Yes.
Now, also consider: maybe no firewall rule is needed because... let's just test empirically.
Also alternative without UAC: Set-NetFirewallHyperVVMSetting also needs admin. No.
OK, another thought — is UAC even going to be approvable? The user might not be at the machine... They're chatting, presumably present. I'll ask before triggering UAC? The user said "perform the minimum necessary changes and verify the connection." I think triggering a UAC prompt is acceptable but I should tell them. Given they asked me to report first and then act, and to prefer safest/simplest, I'll:
I think it's fine to proceed and if UAC is needed, tell them to click Yes. But there's a risk Start-Process -Verb RunAs hangs forever if no one clicks. I'd better ask via question tool before elevating, or just attempt with clear messaging. Let's first do the no-admin steps and see.
Hmm, wait. Before all that — maybe check whether the timeout was actually firewall: quick empirical test using a temporary PowerShell TcpListener on [wsl-gw-ip]:18080, http-get from WSL. But Ollama bind change test gives the same info. Just do the real thing.
Actually — hold on. One more alternative worth checking: does WSL have access to Windows host via a different path that bypasses firewall? e.g., Hyper-V default switch? No.
Also: what about the fact that Get-NetConnectionProfile showed only Wi-Fi Public — the vEthernet (WSL) adapter might be categorized as Public too; Windows Firewall Public profile inbound = block by default. Yes.
Let's proceed:
Step 0: report plan (in my message text).
Step 1: set user env OLLAMA_HOST (setx) — wait, should I? If bind test fails due to firewall and user opts for mirrored instead, we'd have made an unnecessary change. But it's easily reverted. The user wants minimal changes; setting env + restarting server is step 1 of option B.
Actually — should I ask the user to choose between Option B (UAC firewall rule, session preserved) and Option A (mirrored mode, clean but kills session)? The user said "prefer the safest and simplest solution for a development project" and gave requirements. I have latitude to decide. Given verification must happen now, Option B is the pragmatic choice. Mirrored is arguably "simplest/safest" config-wise but disruptive (kills session) — and can't be verified in-session.
Hmm, but actually — wait. Could I do mirrored WITHOUT killing the session? What if... no.
Hmm, is there any chance the session survives wsl --shutdown? Absolutely not — all WSL processes die.
I'll present the plan as Option B primary, mention why not mirrored (session kill), then execute. Actually the user asked me to first report what I intend, what files/settings I'll modify, then perform. They didn't ask for a choice question. I'll report and proceed in the same turn — that matches their instruction.
But the UAC elevation... let me determine if it's needed first (test after bind change). If needed, I'll ask them to approve — I can use Start-Process -Verb RunAs and it'll pop on their screen; I'll note it in my message. Since my message and tool calls interleave, they'll see the note. Slight risk they don't click → command times out. I'll set a timeout and handle.
Actually better: use the question tool when/if elevation is needed, so they consciously approve before the prompt appears. Hmm, that adds a round trip but is respectful of "do not change system settings unnecessarily". Let's first do bind-only test; if it works, no UAC at all.
Wait, actually — I realize I should double check something first: maybe the drop is because nothing listens → no wait, no listener = RST = exit 7. We got exit 28 timeout. Actually hmm: is that right? If Windows has no listener on [wsl-gw-ip]:11434, TCP SYN → Windows stack responds RST (if firewall allows) → http-get exit 7 "Failed to connect... Connection refused". We got 28 (operation timeout) → SYN silently dropped → firewall drop. Confirmed firewall blocks inbound on that port/interface.
So after binding [REDACTED], still dropped (firewall filters by packet, not by whether app is bound... well, WFP filters apply before/after; with no listener the RST comes from stack but firewall drops the SYN so we never see RST). With listener bound, SYN still dropped → timeout. So bind-only WILL fail.
Therefore firewall rule is definitely required (unless mirrored). So: I must elevate (UAC) OR choose mirrored.
Hmm! Unless... the Hyper-V firewall is the dropper: Get-NetFirewallHyperVVMSetting showed all NotConfigured → defaults. What's the Hyper-V firewall default inbound for VMs to host? I believe Hyper-V firewall default: outbound allow, inbound block? If Hyper-V firewall blocks, then a Windows Firewall rule won't help (need Set-NetFirewallHyperVVMSetting -DefaultInboundAction Allow or a Hyper-V firewall rule) — also admin.
Which is it? The traffic path: WSL VM → Windows host. This traverses the Hyper-V virtual switch and is subject to:
1. Hyper-V firewall (per-VM settings) — governs traffic between VM and host/external.
2. Windows Firewall on the host for traffic arriving on vEthernet interface.
I think both may apply. Known guidance for "WSL2 connect to Windows localhost service": the common answer is "bind app to [REDACTED] and allow through Windows Firewall (private networks)". Many people report that WSL→Windows works after adding firewall rule. Also Hyper-V firewall default for WSL: I recall WSL's Hyper-V firewall default inbound = Block?? There's a known issue where you must run Set-NetFirewallHyperVVMSetting -Name '{40E0AC32-...}' -DefaultInboundAction Allow for WSL inbound... Actually I recall the Hyper-V firewall defaults: DefaultInboundAction NotConfigured = default is Block? Hmm. For Hyper-V firewall, defaults are: Inbound = Block, Outbound = Allow? And "AllowHostPolicyMerge" NotConfigured → merges host policy (True default) → host Windows Firewall rules apply too.
If host policy merges and host firewall allows on that interface, it should pass (AND logic: must be allowed by both? Hyper-V firewall with AllowHostPolicyMerge=True means host firewall rules are also evaluated). So adding a Windows Firewall allow rule may suffice if Hyper-V default inbound is block... Ugh, semantics: I believe Hyper-V firewall defaults are "Allow" for the trust boundary? Not sure.
Empiricism: try Windows Firewall rule first; if still blocked, set Hyper-V firewall default inbound allow for the WSL VM GUID (scoped to WSL only — safe).
Both need admin.
Alternative that avoids all Windows firewall questions: mirrored mode. In mirrored mode, connections to localhost go via loopback (not crossing the virtual switch, Hyper-V firewall loopback policy — there's LoopbackEnabled setting NotConfigured (default true?)). Windows Firewall generally allows loopback inbound (default rules include "Core Networking" and loopback is exempt... actually Windows Firewall does filter loopback? By default, traffic to localhost is allowed — there's an implicit rule? Windows Firewall applies to loopback? I believe loopback traffic is not blocked by default (there are default allow rules for many services bound to loopback; also "Local subnet"... hmm). Practically, services on localhost are reachable from Windows itself, and in mirrored mode WSL shares that loopback path.
OK so decision: mirrored (clean, no Windows firewall, no Ollama change; but session-killing restart, can't verify now) vs firewall (works now; UAC).
Let me reconsider the session-kill issue seriously. How bad is it? The user is in an interactive OpenCode session. If I run wsl --shutdown, everything dies — including this conversation's process. The user would have to restart OpenCode and continue from scratch (they'd lose... well, conversation state might persist on disk? OpenCode stores sessions; reopening might resume the session. Not guaranteed).
They explicitly instructed: "After making any required configuration change, verify from WSL that the Ollama API is reachable. Then run a minimal local generation test from WSL." This strongly implies the verification must be done by me now → no session-killing restart. So mirrored is effectively excluded by their own requirements.
Therefore: Option B: bind + firewall (UAC).
Wait... is there an option where firewall change isn't needed because we use an already-allowed path? What inbound rules exist by default? E.g., if "File and Printer Sharing" or "Network Discovery" allowed on that profile... Public profile disables those. What about ICMP? Not relevant.
Could we tunnel through an already-allowed outbound path? Reverse connection: Windows connects OUT to WSL (outbound from Windows is allowed by default; and Hyper-V firewall outbound default allow). So: run a forwarder on Windows that makes an outbound connection to WSL, and a listener in WSL that... Classic reverse port-forward requires a connection from Windows to WSL — Windows would initiate a TCP connection to some port in WSL (WSL listens; inbound to WSL VM is allowed? Hyper-V firewall governs inbound to VM too... WSL's own firewall (iptables in WSL) is empty by default → allows). So we could implement: on WSL, run a proxy that listens on WSL:11434 (for WSL apps) and... no wait, we need WSL→Windows direction data flow.Architecture: WSL app connects to WSL-local11434 → our WSL proxy receives connection → but it must reach Windows Ollama → requires a connection to Windows (blocked inbound) unless we use a pre-established reverse connection: Windows-side process connects out to WSL proxy and then Windows-side process talks to localhost:11434 locally. That works without any firewall change! Windows outbound to WSL is allowed (default outbound allow; Hyper-V outbound default allow).
Implementation: needs a relay. E.g., socat/ncat on both sides? Are they installed in WSL? We can't install. Check availability: socat, ncat, ssh. On Windows: no socat; could use PowerShell TcpClient relay script (doable but hacky, two processes, fragile, and permanent dev dependency on a custom script — ugly).
That's clearly worse than one firewall rule. Not "simplest".
Alright: Option B with UAC.
Hmm, hold on. Let me reconsider one more time whether Windows Firewall really blocks — maybe the timeout was because... let me verify quickly with a controlled test: start a PowerShell TcpListener on [REDACTED]:18080 on Windows, http-get from WSL to [wsl-gw-ip]:18080. If timeout → confirms Windows/Hyper-V firewall blocks inbound from WSL. If success → then why did 11434 time out?! (Could be WFP rule specific to port 11434? Unlikely.) Actually this test tells us whether adding an allow rule would even help (if Hyper-V firewall blocks everything regardless of host rules... test tells us about current state only).
The test is cheap and doesn't change settings (temporary process, no persistence). It isolates the cause. Let's do it — but it's arguably unnecessary; the diagnosis is already solid. However, knowing whether ANY inbound port works from WSL matters: if Hyper-V firewall blocks all inbound and host rules can't override, then firewall rule won't help and we'd be stuck needing mirrored... Better to know.
Let's run the listener test: PowerShell one-liner that starts TcpListener on [REDACTED]:18080 in a background job/process, wait, then http-get from WSL, then kill.
Implementation:
- Start: powershell -NoProfile -Command "Start-Process powershell -ArgumentList '-NoProfile','-Command','\$l=[Net.Sockets.TcpListener]::new([Net.IPAddress]::Parse(\"[REDACTED]\"),18080); \$l.Start(); Start-Sleep 60; \$l.Stop()'" -WindowStyle Hidden — quoting nightmare through zsh→powershell.
Better: write a .ps1 to temp (Windows path) and Start-Process it hidden, then http-get, then kill.
Let's do that. Script testlisten.ps1:
powershell
$l = New-Object System.Net.Sockets.TcpListener([System.Net.IPAddress]::Parse('[REDACTED]'), 18080)
$l.Start()
'Started' | Out-File $env:TEMP\testlisten.ready
Start-Sleep -Seconds 45
$l.Stop()
Launch detached: Start-Process powershell -ArgumentList '-NoProfile','-ExecutionPolicy','Bypass','-File','[REDACTED]\AppData\Local\Temp\testlisten.ps1' -WindowStyle Hidden.
Then from WSL: http-get -m 5 hxxp://[wsl-gw-ip]:18080/ → expect exit 7 (refused) if firewall allows (no service responding → RST... wait, our listener IS listening, so if allowed → connection succeeds (http-get gets empty reply/connection reset when listener stops but during sleep it accepts → http-get would hang waiting for HTTP response → exit 28 timeout with connection... hmm. Better: use timeout 3 bash -c '</dev/tcp/[wsl-gw-ip]/18080'? bash /dev/tcp: connect success → exit 0 (then EOF → fine). Or use http-get -s -m 5 telnet://[wsl-gw-ip]:18080... simplest: bash /dev/tcp connect test:
timeout 5 bash -c 'echo > /dev/tcp/[wsl-gw-ip]/18080' && echo CONNECT_OK || echo CONNECT_FAIL
If firewall drops → timeout → CONNECT_FAIL. If allowed → succeeds → CONNECT_OK.
Good diagnostic. Let's do it.
Actually, also test connecting to Windows' Wi-Fi IP? Not needed.
Let's also prepare: check if vEthernet (WSL) alias exists (list adapters properly with single-quoted bash command).
Let me run these.
$ {"command": "/mnt/c/Windows/System32/WindowsPowerShell/v1.0/powershell.exe -NoProfile -Command 'Get-NetIPConfiguration |
vEthernet (WSL (Hyper-V firewall)) | [wsl-gw-ip] Wi-Fi | [lan-ip] Bluetooth Network Connection | 169.254.91.105 Wi-Fi :: Realtek RTL8852BE WiFi 6 802.11ax PCIe Adapter vEthernet (WSL (Hyper-V firewall)) :: Hyper-V Virtual Ethernet Adapter
file: /mnt/c/Users/user/AppData/Local/Temp/testlisten.ps1 $l = New-Object System.Net.Sockets.TcpListener([System.Net.IPA
Wrote file successfully.
Adapter alias: vEthernet (WSL (Hyper-V firewall)) with IP [wsl-gw-ip]. Wi-Fi = lan-ip.
Now run the listener test.
$ {"command": "/mnt/c/Windows/System32/WindowsPowerShell/v1.0/powershell.exe -NoProfile -Command 'Start-Process powershell
-rwxrwxrwx 1 root root 11 Oct 8 14:15 /mnt/c/Users/user/AppData/Local/Temp/testlisten.ready CONNECT_FAIL_exit=124
Confirmed: inbound TCP from WSL to Windows host IP on ANY port is dropped (timeout124). So Windows Firewall/Hyper-V firewall blocks all inbound from WSL to Windows host. So bind change alone will NOT work. A firewall allow rule is required (admin/UAC), OR mirrored networking (session-killing restart).
Hmm wait — one more idea before requiring UAC. Since ALL inbound from WSL is dropped, what about Windows Firewall already having an allow rule that we could piggyback... no, drop happened.
What about Hyper-V firewall vs Windows firewall? Whichever — both need admin.
Now, can we avoid elevation? Think harder about alternatives:
Alternative: mirrored networking without killing session? No.
Alternative: Have Windows initiate the connection to WSL (reverse proxy) — no firewall changes needed (Windows outbound to WSL allowed? let's verify: Windows → WSL connection — is that subject to Hyper-V firewall outbound (default allow)? Probably allowed. Test would confirm.)
Implementation of reverse relay without installing anything:
- Windows side: a PowerShell script acting as relay: listen on... no wait. Architecture:
- WSL app wants to reach Windows Ollama at localhost:11434 (Windows loopback — accessible from Windows processes, no firewall issue for loopback).
- WSL side: listener on127.0.0.1:11434 (or whatever port) in WSL that accepts app connections.
- The two relays must be connected: Windows process connects OUT to a WSL listener (outbound from Windows → WSL: allowed?), then Windows relay bridges to Windows loopback:11434; WSL relay bridges accepted connections over that single connection... That requires a proper multiplexing proxy or one connection per TCP connection — need dynamic handling → complex in pure PowerShell (could spawn threads per connection; but mapping multiple concurrent connections over one reverse socket needs mux).
Simpler variant: WSL relay listens on WSL:11434; for each accepted connection, it needs to reach Windows. Instead of reverse, we could use... hmm, WSL→Windows outbound is blocked (inbound to Windows is blocked — wait, from WSL's perspective, connecting TO Windows is Windows-inbound → blocked). So each WSL connection would need a pre-established reverse tunnel — multiplexing again.
Alternatively: Windows-side relay could listen on WSL?? Windows can't bind into WSL's network namespace.
Could use a UDP-based or SOCKS approach — too complex, fragile. Not "simplest/safest".
Alternative: WSL1? Would kill session, and mode change — no.
Alternative: Use socat in WSL + Windows process connecting out — mux problem again (one reverse TCP conn per client connection requires a "reverse multiplexer"; socat can't easily do that either; would need a per-connection reverse port created on demand — no).
So realistically: UAC elevation for a firewall rule (plus OLLAMA_HOST bind change) OR mirrored mode + WSL restart.
Which is "safest and simplest"?
Firewall path changes:
1. OLLAMA_HOST=[REDACTED]:11434 (user env) + Ollama app/server restart.
2. Inbound firewall allow for TCP11434 scoped to interface vEthernet (WSL (Hyper-V firewall)) (UAC).
Both narrowly scoped; LAN/Wi-Fi untouched; internet untouched. Works without restarting WSL → I can verify now as required.
Mirrored path changes:
1. Create %USERPROFILE%\.wslconfig with [wsl2] networkingMode=mirrored (no admin).
2. wsl --shutdown → kills this session; user restarts OpenCode; then verification (by me in new session? I'd be a new session — conversation might not persist. They'd verify manually).
Also mirrored mode changes broader networking behavior (port conflicts possible: WSL services bind same ports as Windows, etc.) — arguably a bigger blast radius on the machine.
Given requirement 6-7 (verify from WSL now), firewall path wins. Also blast radius smaller (one port rule vs global networking mode).
BUT — binding Ollama to [REDACTED] with a firewall rule scoped to the WSL interface: is [REDACTED] needed, or bind only to [wsl-gw-ip]? If we bind only to wsl-gw-ip, then even if firewall were permissive, LAN can't reach (not bound to Wi-Fi IP). Double safety. Downside: if WSL subnet changes (after wsl --shutdown / reboot, WSL NAT network may be recreated with same or different subnet; usually it persists but can change), Ollama would bind a stale IP → need to update. Actually the Windows vEthernet IP ([wsl-gw-ip]) is assigned by Windows when the WSL NAT network is created; it can change across reboots (rarely). Robustness matters for a dev project.
Middle ground: bind REDACTED + firewall rule scoped to interface alias (LAN blocked by default-deny) — decent. Or bind0.0.0.0 + firewall rule scoped to RemoteAddress=[wsl-gw-ip]/20 — if subnet changes, breaks.
I'll go: OLLAMA_HOST=[REDACTED]:11434 + firewall rule -InterfaceAlias 'vEthernet (WSL (Hyper-V firewall))'.
Hmm, but "Do NOT expose Ollama to the public internet" — [REDACTED] binding on a Public-profile Wi-Fi network with an interface-scoped allow rule: inbound from Wi-Fi hits Windows firewall → default deny (our rule only matches vEthernet interface) → blocked. Plus router NAT. So not exposed. But if user later disables firewall or adds rules... The interface scoping keeps it safe.
Alternatively bind to [wsl-gw-ip] and ALSO firewall-scoped rule → safest (two layers), but subnet fragility.
I think safest+sufficient: bind [REDACTED] is a bit scary-looking; binding specifically to the WSL vEthernet IP is "safest". The user emphasized safety over convenience? "Prefer the safest and simplest solution for a development project." Both safe-ish; simplest robust = [REDACTED] + interface-scoped firewall? Hmm.
Actually, here's a cleaner idea for safety: bind to BOTH? OLLAMA_HOST accepts one address... The server uses net.Listen on the host:port — Ollama parses OLLAMA_HOST as a single host. Can't do multiple.
Decision: OLLAMA_HOST =[REDACTED]:11434, firewall allow scoped to interface vEthernet (WSL (Hyper-V firewall)) only. I'll document that LAN remains blocked and we'll verify with netstat + a firewall check + attempt from the Wi-Fi IP? (We can test from WSL to [lan-ip]:11434 — from WSL, connecting to Windows Wi-Fi IP inbound → should be blocked by our interface-scoped rule... though the packet from WSL to Wi-Fi IP — how does that route? WSL → Windows Wi-Fi IP: the packet goes out the virtual switch to... Windows host receives on vEthernet? No — destination[lan-ip] is Windows's own Wi-Fi address; WSL traffic to it is delivered to Windows host stack via... routing: WSL's default route is via [wsl-gw-ip], so all non-WSL-subnet traffic goes to the gateway (Windows), which receives it on the vEthernet interface and then... it's local delivery to Windows's own IP → firewall sees it arriving on vEthernet interface → our rule allows it! Hmm! That means from WSL we could reach Ollama bound on [REDACTED] via [lan-ip] too. But that's still only from WSL (the packet arrives on vEthernet). From LAN (real Wi-Fi peers), packets arrive on Wi-Fi interface → blocked. Good — safety holds for LAN/public.
So the firewall rule interface-scoping correctly restricts to traffic arriving via the WSL virtual switch = only WSL VMs.
Also should I add -Profile Any? Default profile applies to all when omitted? New-NetFirewallRule default Profile = Any. Fine.
Also, does the rule need to allow the program? No, port-based rule fine.
Additionally: after restart, will Ollama app (tray) also be running? If I kill the tray and only start the server, the tray is gone (no auto-updater, no tray icon) — acceptable but maybe better to restart the app itself so behavior is unchanged. The app spawns the server. Which does what: "ollama app.exe" = tray/UI (starts ui server port 60587, spawns "ollama serve"). Actually app.log line: starting ollama server — app spawns the server process (PID 4736 might be the app or the serve?). Get-NetTCPConnection OwningProcess 4736. ollama.pid file contains 4736 → that's the serve PID (written by serve). So app (different PID) spawned serve (4736).
Restart approach: kill both tray app and serve, then start app fresh with OLLAMA_HOST in env → app spawns serve with inherited env.
How do we find tray PID? Windows process list: ollama app.exe and ollama.exe. Use PowerShell Get-Process name like 'ollama'.
Launch: Start-Process '[REDACTED]\AppData\Local\Programs\Ollama\ollama app.exe' after $env:OLLAMA_HOST='[REDACTED]:11434'. The env is inherited from the PowerShell we spawn — but wait: Start-Process from a powershell.exe that we spawn from WSL interop: that powershell's env = WSL-provided env (which mirrors Windows env from registry at WSL start, possibly stale, plus whatever). We set $env:OLLAMA_HOST explicitly → child gets it.
But caution: does WSL interop pass a Windows env? Yes, interop processes get the Windows environment block (WSL tracks it). Anyway we set explicitly, so fine.
Persist for future: [Environment]::SetEnvironmentVariable('OLLAMA_HOST','[REDACTED]:11434','User') (HKCU — no admin) so future autostarts (after reboot/login) bind correctly. This is a settings change; include in report.
Also: what about OLLAMA_ORIGINS for browser-based dev UI? Out of scope (server-side app). Skip.
Now the firewall rule needs admin → UAC. Check: is the user actually an admin? whoami /groups didn't show Administrators in the filtered output (I only grepped S-1-16/Mandatory). Let's check full groups for 'Administrators'. If not admin at all, elevation impossible → then mirrored mode becomes the only path.
Let's check: whoami /groups | grep -i admin.
If admin-with-UAC: prompt UAC via Start-Process -Verb RunAs.
Plan of action for this turn:
1. Report the plan (text before/with tool calls).
2. Check admin rights.
3. Set user env OLLAMA_HOST.
4. Restart Ollama (kill + start with env).
5. Test from WSL (expect fail due to firewall).
6. Elevate to add firewall rule (UAC — inform user).
7. Retest: /api/version, /api/tags from WSL; netstat to show binding; confirm LAN IP blocked? (Test connecting from WSL to [lan-ip] — expected allowed per analysis; can't test from an external LAN device. Note it.)
8. Minimal generation test from WSL via http-get POST /api/generate with gemma4:e2b, short prompt.
9. Cleanup temp scripts.
10. Report.
Wait — before I go down the UAC path, should I ask the user which option? They said report-then-perform. The UAC prompt is user-visible; they might be surprised. I'll state it clearly in my message: "A UAC prompt will appear — please click Yes." Since I can't verify mirrored without killing session, this is the only viable path per their requirements.
Hmm, but hold on — let me reconsider ONE more no-elevation idea:
Does Windows already have a firewall allow rule we could reuse by binding to a port that's allowed? E.g., is any inbound port allowed from any interface? Default Windows rules allow inbound for specific apps/ports on Private/Domain (e.g., mDNS 5353, LLMNR, DHCP client, NetBIOS on Public? no). Wi-Fi profile is Public → most default allow rules are scoped to Private/Domain. Our traffic arrives on the vEthernet interface whose profile... Get-NetConnectionProfile didn't list vEthernet → maybe it's "unidentified/public". Even if some rule allows e.g. port 445 on all profiles — but our traffic to a random port... We could run Ollama on a port that has an existing allow rule! E.g., if "Core Networking" allows... those are outbound mostly. SMB445 inbound allowed? On Public, file sharing rules are disabled by default. ICMP? Not TCP.
But even if a rule existed for some port, scoping would be wrong (allowing LAN too) — worse security. And port would need to be allowed for ALL profiles since vEthernet profile unknown. Meh — actually the firewall rule we add is better.
Alright, also consider: maybe the drop is Hyper-V firewall (not Windows Firewall) and Windows rule won't fix it. Then we'd need Set-NetFirewallHyperVVMSetting -Name '{40E0AC32-46A5-438A-A0B2-2B479E8F2E90}' -DefaultInboundAction Allow (admin) — but that's broader (allows all inbound from WSL VM... to Windows). Or Hyper-V firewall rules: New-NetFirewallHyperVRule? There's Add-NetFirewallHyperVRule? PowerShell has New-NetFirewallHyperVRule? I don't remember exactly; there's NetSecurity Hyper-V cmdlets: Get/Set-NetFirewallHyperVVMSetting, Get/Set-NetFirewallHyperVProfile, and New-NetFirewallHyperVRule (yes, I believe New-NetFirewallHyperVRule exists for granular rules by VM ID).
We'll find out empirically after adding the Windows Firewall rule.
Which is more likely? My money: Windows Firewall on the vEthernet interface (Public profile default block). Hyper-V firewall default inbound — for WSL, I believe default is... the Hyper-V firewall docs say default inbound action = Block? Hmm. WSL docs mention "WSL firewall" — WSL 2.3+ integrates with Windows Firewall ("vEthernet (WSL (Hyper-V firewall))" adapter name hints Hyper-V firewall active).
We'll test after the Windows rule. If still blocked, add Hyper-V-scoped rule/setting (both admin, same UAC session ideally — better: run one elevated PowerShell session that does BOTH the Windows firewall rule AND the Hyper-V firewall thing only if needed... can't conditionally know. Do Windows rule first, test; if needed, second UAC for Hyper-V. Or do both at once in one elevated script to avoid two UAC prompts: but "minimum necessary changes" → prefer stepwise. However two UAC prompts is annoying. Compromise: stepwise; if Hyper-V change needed, one more UAC.)
Hmm — actually, we can avoid guessing: check Hyper-V firewall's effective default. Since settings show NotConfigured, what's the built-in default? Let me check docs... Get-NetFirewallHyperVProfile output above shows Enabled: NotConfigured etc. Docs: "Hyper-V firewall... default inbound block"? I could webfetch docs but user said "Do not use the internet for this check" — that applied to the environment inspection (message 1). Message 2 doesn't repeat the internet ban... The ban was in message 1's context ("Do not use the internet for this check"). Now they say don't download models/install. Reading docs online is probably fine but let's avoid unnecessary internet use; empirical testing is better.
Actually! Empirical data point available: our earlier test — Windows→WSL direction? The tray app's ui server on 60587 on Windows... not relevant.
Fine. Proceed stepwise.
One more consideration on restarting Ollama: after killing serve (4736) and the tray, starting the tray with new env — the tray then spawns serve. Verify via netstat that11434 binds [REDACTED].
Also: killing tray = "ollama app.exe" process name (with space). Get-Process 'ollama app' works.
Also note: if user has Ollama running as a Windows service? No, desktop app. Fine.
Also: The app auto-starts at login (probably via Run key or Startup folder). After our env change (HKCU), next login picks up OLLAMA_HOST automatically. Within current session, we start it manually with inline env. Good.
Let me also double check: does Ollama app maybe read OLLAMA_HOST only for the server it spawns? Yes, serve reads OLLAMA_HOST env. App passes its env to child. Good.
Alright, message structure:
- Report: intended networking config, why, files/settings to modify.
- Then perform.
Let me first quickly check admin membership (whoami /groups full) before claiming UAC works.
$ {"command": "/mnt/c/Windows/system32/whoami.exe /groups | tr -d '\\0' | grep -Ei \"administrators|S-1-5-32-544\" ; echo
NT AUTHORITY\Local account and member of Administrators group Well-known group S-1-5-114 Group used for deny only BUILTIN\Administrators Alias S-1-5-32-544 Group used for deny only --- 4736 :: ollama 16232 :: ollama app
$ grep -i "ollama" /proc/version 2>/dev/null; echo "wsl_kernel_ok"; cat /etc/os-release | head -3; which socat ncat nc cur
wsl_kernel_ok PRETTY_NAME="Ubuntu 24.04.4 LTS" NAME="Ubuntu" VERSION_ID="24.04" socat not found ncat not found /usr/bin/nc /usr/bin/http-get /usr/bin/python3
Facts:
- User IS a member of Administrators (deny-only in filtered token) → UAC elevation possible.
- Ollama processes: PID 4736 = ollama (serve), PID 16232 = ollama app (tray).
- WSL distro: Ubuntu 24.04, no socat/ncat (nc exists — but that's traditional netcat, possibly openbsd; still doesn't solve the routing problem).
Now report plan and execute.
Plan:
Networking approach: Keep WSL2 NAT mode; make the existing Windows Ollama server reachable from WSL by (a) binding it to all interfaces and (b) allowing inbound TCP11434 only on the Hyper-V WSL virtual adapter.
Why:- WSL→Windows localhost forwarding doesn't exist in NAT mode; WSL's only route to Windows is via the vEthernet (WSL) interface ([wsl-gw-ip]).
- Empirically ALL inbound TCP from WSL to Windows is dropped (test: listener on 18080 → timeout), so a firewall allow is unavoidable.
- Mirrored networking mode would avoid firewall/bind changes but requires wsl --shutdown, which would kill this running OpenCode session and cannot be verified as required — so rejected.
Files/settings to modify:
1. HKCU environment (user scope): OLLAMA_HOST = hxxp://[REDACTED]:11434 — via [Environment]::SetEnvironmentVariable(...,'User'). (no admin)
2. Restart Ollama tray+server so the new bind takes effect (no admin).
3. Windows Firewall inbound allow rule: TCP localport 11434, InterfaceAlias = vEthernet (WSL (Hyper-V firewall)), action Allow (admin → UAC prompt).
4. If (3) insufficient (Hyper-V firewall layer), add Hyper-V firewall rule for WSL VM GUID (same elevation ideally).
Not touching: .wslconfig, WSL distro config, Ollama install/models, Wi-Fi/public interfaces.
Safety: rule scoped to the WSL-only virtual adapter → LAN/Wi-Fi/public inbound stays default-deny; no port exposure to internet (no router port-forwarding).
Verification: netstat binding check, http-get /api/version + /api/tags from WSL, minimal gemma4:e2b generate, plus a "public IP" reachability sanity check (connect to [lan-ip]:11434 from WSL — hmm, as analyzed, that packet arrives on vEthernet so it would be allowed; that test would be misleading. Better LAN-exposure check: verify firewall rule InterfaceAlias scoping and netstat; can't test from an external device).
Actually, a real LAN check isn't possible from here (no second device). We'll verify rule scoping + default-deny logic.
Hmm — wait. One more thought about binding [REDACTED] vs the specific IP. Since safety concern: with firewall scoped to WSL adapter, [REDACTED] is fine. But belt & braces: bind [wsl-gw-ip] instead? If WSL network recreated with different subnet later → Ollama binds wrong/missing IP → breaks silently. To handle, we'd need a script to update on each WSL restart — complexity. [REDACTED] + interface-scoped firewall is simpler and still safe. Go with [REDACTED].
Actually hmm, is there an even better option: bind to [REDACTED] but firewall rule ALSO with -RemoteAddress restricted to the WSL subnet? Combining interface + remote subnet = if subnet changes → break. Just interface. OK.
Now, does the firewall rule interface scoping work as I expect with Hyper-V firewall? We'll see empirically.
Also — important: does Windows Firewall even apply to traffic arriving on the Hyper-V vEthernet adapter? Yes (Public profile likely). And Hyper-V firewall additionally? We'll see.
Execution steps:
Step 1: set user env:
powershell -Command "[Environment]::SetEnvironmentVariable('OLLAMA_HOST','hxxp://[REDACTED]:11434','User')"Wait — format: OLLAMA_HOST can be [REDACTED]:11434 or hxxp://[REDACTED]:11434. Server default env shows OLLAMA_HOST:hxxp://localhost:11434 (parsed form). Setting with scheme is safest: hxxp://[REDACTED]:11434.
Step 2: restart Ollama: kill PIDs 4736 and 16232, then start app with env inline:
powershell
$env:OLLAMA_HOST='hxxp://[REDACTED]:11434'; Start-Process '[REDACTED]\AppData\Local\Programs\Ollama\ollama app.exe'
Then wait, check netstat for [REDACTED]:11434.
Careful: killing the tray — will it relaunch serve itself with stale env? We kill both, then start tray fresh.
Actually, alternative to killing: does the app need to be the one spawning serve? We could just kill serve (4736) and start our own ollama serve with env — but tray might respawn its own serve on port conflict (it might not monitor). Cleaner: kill both, start tray.
Note: starting ollama app.exe from a detached Start-Process → runs in user session, tray icon appears. Good.
Step 3 (after confirming firewall is the blocker — already confirmed via test): elevated firewall rule via UAC:
powershell
Start-Process powershell -Verb RunAs -ArgumentList '-NoProfile','-Command', 'New-NetFirewallRule -DisplayName "Ollama from WSL (11434)" -Direction Inbound -Action Allow -Protocol TCP -LocalPort 11434 -InterfaceAlias "vEthernet (WSL (Hyper-V firewall))" -Profile Any; pause'
With -Wait so my command waits for the user to click UAC and the command to finish. But -Wait with -Verb RunAs on Start-Process: waits for the elevated process to exit. If I add pause, it'd wait for keypress → hangs. Better: no pause; elevated window flashes and exits. Use -Wait to know completion. But then verifying rule existence afterwards.
Actually the elevated PowerShell window will close immediately — user sees a flash + UAC. Fine. I'll add -WindowStyle Hidden? For RunAs, hidden might be odd; keep normal (brief window).
Wait — the UAC prompt: will it actually appear on the user's desktop? We're running via WSL interop → the process runs in the interactive user session → yes, UAC consent appears on their desktop (secure desktop). They must click Yes.
Timing: Start-Process -Verb RunAs -Wait blocks until elevated process exits. If user doesn't respond, blocks until... indefinitely (no timeout on my side except tool timeout). I'll use a generous tool timeout (120s) and tell the user to click Yes.
Alternatively use runas /savecred? No, first-time prompt anyway.
Order of operations — do the firewall rule FIRST (needs UAC, might need iteration with Hyper-V), or bind first? Either. I'll do: env + restart + test (expect fail) → then UAC firewall → test → iterate if needed.
Hmm, actually to minimize UAC round trips: do the elevated step with BOTH Windows firewall rule and check. But can't test Hyper-V rule need until after Windows rule. Let's do stepwise; risk of second UAC is acceptable (I'll inform user).
Actually — smarter: do the UAC elevation ONCE with a script that: (1) creates the Windows firewall rule scoped to the interface, (2) tests connectivity? Can't test from elevated PS easily (can: use Test-NetConnection to [wsl-gw-ip]:11434 from Windows — but that tests Windows→itself, not WSL→Windows path... the WSL path involves the vEthernet inbound — a Windows process connecting to its own vEthernet IP from the host side is a different path (loopback-ish local delivery), doesn't traverse the same filter. So can't self-test. So stepwise with WSL-side test after.
Alternatively include Hyper-V firewall allowance preemptively? "Minimum necessary" → no.
Let's think about what's most likely: The adapter name literally says "(Hyper-V firewall)" — WSL 2.3.26 has Hyper-V firewall integration enabled. Traffic from WSL VM → host: Hyper-V firewall governs VM-initiated traffic. Default for Hyper-V firewall: I'm fairly confident inbound default = Block for VM→host? Hmm. But also Windows Firewall applies (AllowHostPolicyMerge NotConfigured → defaults to True, meaning host firewall rules apply to the VM).
If Hyper-V default inbound were Block regardless of host rules, then WSL→Windows inbound would NEVER work without config change — is that the case? Common knowledge: WSL2 NAT mode, people DO access Windows services from WSL by binding0.0.0.0 + firewall rule... Actually the classic problem: many report "can't connect to Windows localhost from WSL" and the fix is firewall +[REDACTED] binding — meaning host firewall rules DO allow it once added. So host policy merge makes our rule effective. I'm fairly confident the Windows firewall rule will work.
Hmm, but also there are reports that with newer WSL's Hyper-V firewall, inbound to Windows from WSL requires nothing extra... whatever, empirical.
Also note: inbound rule default profile matters: the vEthernet interface profile — if it's Public, our rule with -Profile Any covers it.
Alright. Another subtlety: New-NetFirewallRule -InterfaceAlias 'vEthernet (WSL (Hyper-V firewall))' — alias contains parentheses; fine in quotes.
Alternative simpler scoping: -RemoteAddress [wsl-gw-ip]/20 — no; interface better.
Wait, actually — is interface scoping on an inbound rule going to be evaluated correctly for packets arriving from the VM? Yes: InterfaceAlias on inbound rule = interface the packet arrived on.
OK — also consider adding -Action Allow (default allow anyway).
Let's also prepare fallback elevated script that adds Hyper-V firewall rule:
New-NetFirewallHyperVRule? Let me recall cmdlet name... In NetSecurity module: Get-NetFirewallHyperVVMSetting, Set-NetFirewallHyperVVMSetting, Get-NetFirewallHyperVProfile, Set-NetFirewallHyperVProfile, New-NetFirewallHyperVRule, Get-NetFirewallHyperVRule, Remove-NetFirewallHyperVRule. I believe New-NetFirewallHyperVRule exists with -Name (VM id GUID), -DisplayName, -Direction, -Action, -Protocol, -LocalPorts? Parameters: -Name (VM GUID), -DisplayName, -Description, -Direction, -Action, -Enabled, -Profile?, -Protocol, -LocalPorts, -RemotePorts, -LocalAddress, -RemoteAddress... Something like that. We'll deal only if needed.
Fallback simpler: Set-NetFirewallHyperVVMSetting -Name '{40E0AC32-46A5-438A-A0B2-2B479E8F2E90}' -DefaultInboundAction Allow (broader: allows all inbound from WSL VM — still only from WSL, acceptable but less minimal).
Now — before I do all this, should I present the plan and PAUSE for user confirmation? The user said: "First report: what networking configuration you intend to use, why it is required, what files/settings you will modify, then perform the minimum necessary changes and verify the connection." — They want report AND execution in one go. The UAC prompt is the only user interaction; I'll announce it.
Let's write the report, then execute.
One more check: is there an existing firewall rule that ALREADY allows something on our adapter? Not relevant since test showed drop.
Also potential wrinkle: after restarting Ollama app, the app might re-bind127.0.0.1 if it doesn't inherit env (e.g., app reads env from registry itself for serve spawn? no). We'll verify with netstat.
Also: setx vs .NET method — use [Environment]::SetEnvironmentVariable(...,'User') which writes registry and broadcasts WM_SETTINGCHANGE (the .NET method does broadcast? It does update registry; broadcast happens in some implementations... .NET Core's SetEnvironmentVariable User scope only writes registry, no broadcast — doesn't matter for us).
Also record: after setting user env, existing processes don't see it; we start app with inline env so it works now, and future logins get it from registry.
Let's execute. Also cleanup temp scripts at end (fwcheck.ps1, testlisten.ps1, testlisten.ready) — temp dir, but tidy anyway.
Sequence:
A. Set user env OLLAMA_HOST (no admin).
B. Kill ollama serve + tray; start tray with inline env.
C. Wait ~3-5s; netstat check for11434 binding.
D. Test from WSL: http-get hxxp://[wsl-gw-ip]:11434/api/version → expect fail (firewall) [confirm].
E. Elevated: add firewall rule (UAC - user clicks Yes).
F. Retest from WSL: /api/version, /api/tags.
G. Minimal generation: /api/generate with gemma4:e2b short prompt from WSL.
H. Verify safety: netstat (binding addresses), firewall rule display (non-elevated read), confirm no rule for other interfaces; also http-get from WSL to Wi-Fi IP? Not meaningful as discussed — skip; instead show rule scoping.
I. Cleanup temp files.
Wait — do I really need step D (expected failure)? It costs a few seconds and confirms necessity of the firewall rule — good evidence for "minimum necessary". Yes, do it.
Also careful: killing the tray app — does the user rely on it? It'll be restarted immediately. Fine.
Also: will Start-Process 'ollama app.exe' from powershell started via WSL interop land in the right desktop session? Yes, same user interactive session.
Potential issue: the tray app might take the existing... let's just do it.
Let me now write the report text and start executing. I'll do A+B in one command carefully.
Command for A+B:
zsh
/mnt/c/Windows/System32/WindowsPowerShell/v1.0/powershell.exe -NoProfile -Command '
[Environment]::SetEnvironmentVariable("OLLAMA_HOST","hxxp://[REDACTED]:11434","User");
Stop-Process -Id 4736 -Force -ErrorAction SilentlyContinue;
Stop-Process -Id 16232 -Force -ErrorAction SilentlyContinue;
Start-Sleep -Seconds 2;
$env:OLLAMA_HOST="hxxp://[REDACTED]:11434";
Start-Process "[REDACTED]\AppData\Local\Programs\Ollama\ollama app.exe"
'
Multi-line single-quoted zsh string with embedded double quotes — fine. But $env inside single quotes in zsh won't expand. Good.
Note: Stop-Process on our own user's processes — allowed without admin? The tray app and serve run as user user (medium integrity) → yes.
Hmm, one concern: killing ollama app (tray) may cause "ollama app.exe" to be restarted by... nothing. We start it ourselves.
Then wait and netstat:
powershell -Command 'Get-NetTCPConnection -LocalPort 11434 -State Listen | ...'
Let's go. I'll write the report first in this message, then tool calls.
Networking configuration I intend to use: keep WSL2's existing NAT mode; make the existing Windows Ollama server reachable from WSL by (a) binding it to [REDACTED]:11434 and (b) adding one inbound Windows Firewall allow rule for TCP 11434 scoped only to the WSL virtual adapter (vEthernet (WSL (Hyper-V firewall))).
Why it's required (evidence gathered, nothing changed yet):
- Ollama currently listens only on localhost:11434 (verified via Get-NetTCPConnection, PID 4736). WSL2 NAT mode has no WSL→Windows localhost forwarding, and WSL's only route to Windows is the gateway [wsl-gw-ip] (the vEthernet adapter).
- I tested a plain TCP listener on [wsl-gw-ip]:18080 from WSL → connection timed out, proving all inbound TCP from WSL to Windows is firewalled. So a firewall allow rule is unavoidable; a bind change alone would not work.
- Rejected: WSL networkingMode=mirrored (would avoid all firewall/Ollama changes, but requires wsl --shutdown, which kills this running OpenCode session and can't be verified as you required). Also rejected: reverse-tunnel hacks (no socat/ncat, fragile).
Files/settings to modify (minimum set):
1. HKCU user environment: OLLAMA_HOST = hxxp://[REDACTED]:11434 (persists across reboots; no admin needed).
2. Restart Ollama tray (PID 16232) + server (PID 4736) so the new bind takes effect (no admin).
3. Windows Firewall: one inbound Allow rule — TCP 11434, -InterfaceAlias "vEthernet (WSL (Hyper-V firewall))" (requires UAC — a prompt will appear, please click Yes).
Not touching: .wslconfig, WSL distro config, Ollama install/models, Wi-Fi/public interfaces, system-wide firewall defaults.
Safety: the rule is bound to the WSL-only virtual adapter → Wi-Fi/LAN/public inbound stays default-deny; no internet exposure.
Executing now:
$ {"command": "/mnt/c/Windows/System32/WindowsPowerShell/v1.0/powershell.exe -NoProfile -Command '\n[Environment]::SetEnvi
userEnv=hxxp://0.0.0.0:11434 restarted
Now wait a few seconds and check the listening address.
$ {"command": "sleep 6; /mnt/c/Windows/System32/WindowsPowerShell/v1.0/powershell.exe -NoProfile -Command 'Get-NetTCPConne
:::11434 pid=15808 15808 :: ollama 13236 :: ollama app
Ollama now listens on :::11434 (all interfaces, dual-stack) — PID 15808 (new serve), tray PID 13236.
Now test from WSL — expect firewall drop still.
$ {"command": "http-get -s -m 6 hxxp://[wsl-gw-ip]:11434/api/version; echo \" wsl_to_host_exit=$?\"", "timeout": 30000}
{"version":"0.40.1"} wsl_to_host_exit=0
Surprise! It works already — no firewall rule needed! The connection succeeded from WSL to[wsl-gw-ip]:11434 after binding to [REDACTED].
Wait — why did the test listener on 18080 time out then? Because... hmm. Possibly:
- The Windows Firewall default inbound block applies, but something changed? No.
- Possibility: Ollama added a firewall rule automatically when it first bound to [REDACTED]? Ollama Windows installer/app might add a firewall rule on startup when binding non-loopback? Or the Hyper-V firewall/Windows Firewall has an allow rule for the ollama program — program-based rule! Earlier I searched rules with DisplayName like 'ollama' and found none... but maybe rule display name is different (e.g., "Ollama" vs path-based). Hmm, my earlier query Get-NetFirewallRule -DisplayName '*Ollama*' returned nothing.
Wait — maybe Windows Firewall does have an allow rule for the Ollama program (installer adds one: "Ollama" app allow). My DisplayName query found none, but rule name might be e.g. "{GUID}" with program path. Let's check program-based rules: Get-NetFirewallApplicationFilter | Where Program -like 'ollama'.
Or maybe the Windows Firewall rule already existed for port 11434 (my port query script timed out earlier, never completed! The first fwcheck with the port query hit the 120s timeout and produced no output; the second script version's port query portion... I removed the port-11434 section in the second quick query? Let me recheck: my second quick PowerShell query included Get-NetFirewallRule -DisplayName 'Ollama' (none) but I never successfully ran the LocalPort=11434 query! The first attempt (with port query) timed out with no output.
So it's very plausible that a firewall allow rule for TCP 11434 already exists (added by the Ollama installer), and my18080 test only proved that arbitrary ports are blocked. That fits perfectly: Ollama installer adds an inbound rule for 11434 — but scoped how? If it's scoped to the program or port11434 with Profile=Private/Public... it apparently allows from the vEthernet interface.
Then binding0.0.0.0 + pre-existing rule = works.
Let's verify: query firewall rules for localport 11434 (now, quickly) and program rules for ollama. This matters for the security report: if the existing rule allows 11434 from ANY interface (e.g., all profiles including Public), then Ollama bound to [REDACTED] IS reachable from the LAN (Wi-Fi [lan-ip]) → potential exposure! We must check.
Get-NetTCPConnection earlier (bound to localhost) couldn't be reached anyway. Now bound to all interfaces — if firewall rule is broad (any interface), LAN peers could reach Ollama → violates "do not expose" (to LAN at least; not public internet since router NAT, but still).
So next: enumerate rules allowing TCP11434. Do it efficiently:
Get-NetFirewallRule | Get-NetFirewallPortFilter | Where-Object LocalPort -eq 11434 — this was slow (timed out at 120s). Optimize: use netsh advfirewall firewall show rule name=all and grep 11434 — also slow-ish but maybe OK (few seconds typically ~5-10s). Let's try netsh with a60s timeout and grep.
Actually better: CIM query:
powershell
Get-CimInstance -ClassName MSFT_NetFirewallPortFilter -Filter "LocalPort='11434'" | ...
Hmm, association to rules via CimInstance Associators. Could be fast:
powershell
$pf = Get-CimInstance -Namespace root/StandardCimv2 -ClassName MSFT_NetFirewallPortFilter -Filter "LocalPort='11434'"
$pf | ForEach-Object { $_.AssociatedRule }?
Port filter instances have no direct rule pointer; need association queries (slow-ish but only for matching filters).
Alternative: netsh output grep — simplest:
netsh advfirewall firewall show rule name=all | grep -B5 -A15 11434? netsh output is verbose; grep for "11434" then show rule name lines. Let's do: netsh advfirewall firewall show rule name=all > file then parse. Writing to Windows temp file. Or pipe to findstr directly: netsh advfirewall firewall show rule name=all | findstr /C:"11434". That gives just matching lines without context — not useful alone.Better approach: rules are delimited by "Rule Name: ..." then details. Use PowerShell with a targeted pipeline but allow more time (300s) — the earlier full pipeline with Get-NetFirewallRule | Get-NetFirewallPortFilter over ALL rules can take minutes.Faster: filter rules first by direction inbound & enabled, then port filter:
powershell
Get-NetFirewallRule -Enabled True -Direction Inbound -Action Allow | Get-NetFirewallPortFilter | Where-Object {$_.LocalPort -eq 11434}
Still many rules (hundreds) but each pipeline is fast? The earlier timeout might have been due to Format-Table on associated lookups... Let's just try with 180s timeout.
Also program-based: Get-NetFirewallApplicationFilter | Where-Object Program -like '*ollama*' — this enumerates all app filters (could be slow too). Alternatively Get-NetFirewallRule | Where-Object DisplayGroup... hmm.
Simplest targeted: netsh advfirewall firewall show rule name=all and use awk to extract rule blocks containing 11434 or ollama. Write output to a Windows temp... we can redirect to a WSL-side file? netsh runs on Windows; output captured by interop → redirect within bash to /tmp file. Yes! /mnt/c/Windows/System32/netsh.exe advfirewall firewall show rule name=all > /tmp/opencode/fw.txt then grep locally.
Let's do that.
Also: verify LAN reachability concern — from WSL we can't truly simulate a LAN peer (as discussed, packets to[lan-ip] from WSL arrive on vEthernet... actually wait: is that true? WSL sends to[lan-ip] → routed via default gateway wsl-gw-ip → Windows receives on vEthernet, sees dst is its own Wi-Fi IP → local delivery. Firewall: inbound interface = vEthernet → our/pre-existing rule matches by port... The existing rule's interface scope matters only for a real LAN peer. So from WSL I cannot distinguish. I need to read the rule definition to determine LAN exposure.
If the pre-existing Ollama rule is scoped broadly (any remote, any interface, profile any), then binding0.0.0.0 exposes Ollama on the LAN (Wi-Fi network is Public — but if rule profile includes Public...). Then to be safe I'd add my own interface-scoped rule AND restrict? Can't remove installer's rule without... well, we could modify/disable it — that changes settings but improves safety; or bind Ollama to [wsl-gw-ip] only (then LAN can't connect regardless of firewall) — hmm, that's the safer bind decision revisited.
Let's inspect the rules first.
Also worth noting: "Do NOT expose Ollama to the public internet" — LAN exposure isn't public internet, but the spirit is safety. Ollama has no auth; on a Public Wi-Fi network (looks like 10.82.x.x — possibly a campus/office network!) other machines could use the model. Should prevent that.
Decision tree after inspecting rules:
- If existing rule restricted to the WSL interface/subnet (or Private profile only, and vEthernet is Private?) → OK as-is; no firewall change needed → "minimum necessary" = only OLLAMA_HOST env change.
- If existing rule is broad → tighten: either scope it, or bind Ollama to wsl-gw-ip, or add... Actually best: modify existing rule to -RemoteAddress = WSL subnet / or interface scope. Requires admin (UAC).
Let's inspect now.
WSL→Windows already responds after the bind change. Now I must check which firewall rule allowed it, to make sure it isn't open to the LAN:
$ {"command": "/mnt/c/Windows/System32/netsh.exe advfirewall firewall show rule name=all > /tmp/opencode/fw_rules.txt 2>&1
(no output) <shell_metadata> shell tool terminated command after exceeding timeout 120000 ms. If this command is expected to take longer and is not waiting for interactive input, retry with a larger timeout value in milliseconds. </shell_metadata>
$ {"command": "/mnt/c/Windows/System32/WindowsPowerShell/v1.0/powershell.exe -NoProfile -Command 'Get-NetFirewallApplicati
ollama.exe | enabled=True | dir=Inbound | action=Allow | profile=Public ollama.exe | enabled=True | dir=Inbound | action=Allow | profile=Public
Found: there are TWO pre-existing inbound Allow firewall rules for ollama.exe, profile=Public.
Details needed: are they port-scoped (11434) or program-scoped (any port)? And remote-address scope? Let's get full details of these two rules: name, LocalPort/RemoteAddress, InterfaceAlias, Profile.
The netsh dump timed out (slow). Instead, query rules by program association in PowerShell and pull their port filters + remote addresses:
$appFilters = Get-NetFirewallApplicationFilter | Where-Object { $_.Program -like "*ollama*" }
foreach ($af in $appFilters) {
$rule = $af | Get-NetFirewallRule
$pf = $rule | Get-NetFirewallPortFilter
$addr = ... remote address? need Get-NetFirewallAddressFilter
...
}
Get-NetFirewallApplicationFilter enumeration over all rules is what took time (it did complete in 180s though — output came). Now do the follow-up including port/address/interface filters, again within 180s.
Also the network profile of the vEthernet adapter: earlier Get-NetConnectionProfile showed only Wi-Fi Public. So vEthernet (WSL) might have no profile listed → possibly categorized as Public too (unidentified networks default to Public). The ollama rules are profile=Public → they apply on vEthernet (good for us) AND on Wi-Fi (which is Public too!) → LAN exposure risk if rule is program-scoped with any port/any remote.
Wait: are these rules the installer's "allow Ollama" rules? They existed before my change (I queried DisplayName 'Ollama' earlier and got nothing because display names differ — these rules' DisplayName we haven't seen; the program filter output shows rule display... no, I printed DisplayName from the rule: it printed "ollama.exe" — that IS the DisplayName? I formatted "$($_.DisplayName) | ..." → so DisplayName = "ollama.exe"? Hmm, that means display name is literally "ollama.exe"? Odd but possible (maybe two rules named "ollama.exe").
Let's get: DisplayName, Direction, Action, Profile, plus port filter (Protocol, LocalPort, RemotePort) and address filter (RemoteAddress, LocalAddress) and InterfaceAlias.
If rules are program-scoped (any port) with RemoteAddress Any and profile Public → then Ollama (bound [REDACTED]) is reachable from Wi-Fi LAN peers. To respect safety, tighten: either scope these rules to the WSL interface/remote subnet, or bind Ollama to the vEthernet IP only.
Options to fix (needs admin/UAC):
- Modify the two rules: Set-NetFirewallRule -DisplayName ... -RemoteAddress <WSL subnet> or -InterfaceAlias 'vEthernet (WSL (Hyper-V firewall))'. Set-NetFirewallRule supports -InterfaceAlias? Hmm, Set-NetFirewallRule has -InterfaceAlias parameter? I believe New-NetFirewallRule has -InterfaceAlias and Set-NetFirewallRule also accepts it... Actually, address/interface are stored on associated filters; Set-NetFirewallRule does expose -InterfaceAlias? Let me think: Set-NetFirewallRule parameters include -LocalAddress, -RemoteAddress, -LocalPort, -RemotePort, -Protocol, -InterfaceAlias, -InterfaceType, -Program, -Service... I'm fairly confident Set-NetFirewallRule includes these (it sets the associated filters). Yes, Set-NetFirewallRule has -InterfaceAlias (docs list it? hmm). I recall Set-NetFirewallRule supports -InterfaceAlias indeed... not 100%.
Alternative safer bind: change OLLAMA_HOST to [wsl-gw-ip]:11434 — then even with public firewall rule, only traffic addressed to that IP can connect, and only WSL VMs route there (it's the vEthernet host address; LAN peers can't reach it — a LAN peer sending to [wsl-gw-ip] has no route (private RFC1918 not routed on the LAN... unless the LAN happens to be [wsl-gw-ip]/20 — it's not; WSL subnet is chosen from172.16-31 range, LAN is 10.82.x). So binding to [wsl-gw-ip] = LAN cannot connect at all (packets never arrive), regardless of firewall. Plus firewall allows only... fine.
Risk: if the vEthernet IP changes (WSL network recreated), Ollama binds a stale address → fails to listen (or binds nothing). How often does the WSL vEthernet IP change? The NAT network config in WSL settings (or default) tends to persist across reboots for a given machine, but it CAN change (when the Hyper-V network is recreated, or user runs wsl --shutdown — usually same subnet persists; changes happen after Windows updates or if the subnet conflicts). Moderate risk.
Which is better: (a) keep [REDACTED] + tighten firewall rules to WSL interface; or (b) bind to[wsl-gw-ip] + leave firewall as-is?
(a) is robust to IP changes, needs firewall modification (UAC), and keeps one interface-scoped allow rule (the installer's rules would be restricted — modifying installer rules might be reverted by Ollama updates).
(b) needs no firewall change (already allowed), but breaks if subnet/IP changes; also0.0.0.0 vs specific.
Hmm, actually wait. What if I do BOTH-ish: bind [wsl-gw-ip] (safe by address) — simplest, zero firewall changes, satisfies "minimum necessary". Downside: brittleness on network change. For a dev project, if it breaks after a reboot, the fix = update env var. Could mitigate by writing a small note... or better: since we already set HKCU OLLAMA_HOST, we could add a tiny WSL startup hook that rewrites OLLAMA_HOST if the gateway IP changed — that's more machinery, not "simplest".
Alternative (c): bind [REDACTED] AND scope the two existing installer rules to the WSL interface. Firewall change requires UAC once; robust to IP changes; installer updates might re-broaden rules (rare).
I lean to (c)? or (b)?
Security framing: with (b), exposure = only packets to[wsl-gw-ip] — reachable only from WSL VM (and Windows itself). Very safe. LAN impossible.
With (c), exposure = all interfaces but filtered by interface-scoped rule → only packets arriving via vEthernet → also only WSL VM. Equally safe in theory, dependent on firewall staying correct.
The user's #3: "Do not change anything unnecessarily." (b) = no firewall change at all. (c) = one firewall modification (needs UAC).
But (b)'s brittleness: if WSL's vEthernet IP changes, Ollama app restart (or reboot) binds wrong IP → WSL can't connect → we'd have to intervene. Hmm. Also, if the IP changes while Ollama keeps running, it keeps binding the old IP which may no longer exist on any interface → listen fails at startup only.
Which risk is worse? Also consider: does Ollama even fail if OLLAMA_HOST host is an IP not present? It would fail to bind → server down. That's a hard failure requiring manual fix.
Actually, is there a hybrid: bind0.0.0.0 (robust) + verify what the existing rules allow. If existing rules are program-scoped to ollama.exe with Profile=Public and RemoteAddress=Any → LAN peers CAN reach Ollama (Wi-Fi is Public!). That's real exposure on what looks like an office/campus network (10.82.x.x). That violates the spirit of "do not expose".
So with [REDACTED] we MUST tighten rules → UAC. With [wsl-gw-ip] bind we need nothing.
Let me first get the full details of those two rules (ports, remote addresses, interface) to know the actual exposure. If e.g. they're already scoped to specific remote addresses or local port11434 only, exposure analysis changes: with port 11434 + program ollama + profile Public + remote Any → LAN peer can hit[lan-ip]:11434 → exposed (though only while bound to [REDACTED]).
Let's fetch rule details.
Then decide. I think the cleanest minimal-and-safe final state:
Bind OLLAMA_HOST to [REDACTED] is what we already did — exposure depends on rules. To be safest with minimal changes: tighten the two rules to the WSL interface (one elevated command) OR rebind to [wsl-gw-ip] (zero additional changes).
Hmm — think about which the user would prefer... They said "safest and simplest". I'd argue:
Actually, wait! There's a third option that's both robust AND needs no firewall change: bind to [wsl-gw-ip] (WSL adapter IP) — but make Ollama resilient? No...
Or: keep [REDACTED] but restrict the firewall rules — the installer rules are arguably "already changed system settings" by Ollama; modifying them is a change we introduce.
Let me look at rule details first, then decide. Possibly the rules are scoped in a way that's already safe (e.g., RemoteAddress = [wsl-gw-ip]/20 or LocalAddress/Interface). Let's query.
$ {"command": "/mnt/c/Windows/System32/WindowsPowerShell/v1.0/powershell.exe -NoProfile -Command '\nGet-NetFirewallApplica
Rule: ollama.exe Enabled=True Dir=Inbound Action=Allow Profile=Public Program= IntfAlias= IntfType= Proto=TCP LocalPort=Any RemotePort=Any LocalAddr=Any RemoteAddr=Any Rule: ollama.exe Enabled=True Dir=Inbound Action=Allow Profile=Public Program= Int…
The two pre-existing rules named "ollama.exe": TCP + UDP, LocalPort=Any, RemoteAddr=Any, Profile=Public, no interface scoping, and Program= empty?? The program filter query matched Program -like "*ollama*" but then $_.Program from rule printed empty — because I printed $_.Program from the rule object (rules don't have Program). The program value is on the application filter. Let's not worry: they're program-scoped rules for ollama.exe (that's how they matched), TCP/UDP any port, any remote, Public profile.
Wait — actually important: are these the Ollama installer rules? Whatever. Current state:
Hmm wait, but the successful connection — actually which rule allowed it? These program rules (profile Public) would match if the vEthernet interface is in Public profile. Plausible.
Exposure analysis with current state (OLLAMA_HOST=[REDACTED]):
- Wi-Fi is Public → these rules (Profile=Public, RemoteAddr=Any, any port) allow ANY LAN peer to connect to ollama.exe on any port, including 11434, since we bound0.0.0.0.
- Before my change, Ollama was on loopback → no exposure despite the rule. After my change → LAN exposure exists (LAN peers can use the model without auth).
- Public internet: blocked by router NAT (no port forwarding) → not exposed to internet. But LAN exposure on what appears to be an office/campus network (10.82.x.x) is undesirable.
So to honor safety, I should NOT leave [REDACTED] + these broad rules. Two ways:
Option 1 (zero extra changes): bind to [wsl-gw-ip]:11434.
- LAN peers can't reach it (not bound to Wi-Fi IP; packets to [wsl-gw-ip] aren't routed to us from LAN).
- WSL reaches it (bound directly on the vEthernet address).
- Firewall: the existing broad program rule allows it (as just proven).
- Brittle: if vEthernet IP changes → must update OLLAMA_HOST.
Option 2 (one UAC change): keep [REDACTED], restrict the two rules (e.g., add InterfaceAlias='vEthernet (WSL (Hyper-V firewall))' or RemoteAddress=WSL subnet, or scope LocalPort=11434).
- Robust to IP change.
- Needs admin; modifies installer rules (Ollama updates may re-add/overwrite).
- Note: also the UDP rule (any port) is weirdly broad — but with Ollama bound to specific port TCP only, UDP irrelevant. Actually tightening them anyway improves overall security (currently ANY inbound to ollama.exe from any remote on Public profile — though program rules apply only to traffic to that program, which requires the program to be listening).
Which is "safest and simplest"? Option 1 = zero extra system changes (aligns with "do not change anything unnecessarily"), but introduces a config brittleness and requires the env var to track a possibly-changing IP.
Option 2 = robust; one elevated command; but modifies existing firewall rules (a real system-settings change) and depends on rule survival across Ollama updates.
Hybrid Option 3: bind0.0.0.0 + add a NEW interface-scoped allow rule + disable/leave the broad ones? The broad ones would still allow LAN. So must restrict broad ones. Same as Option 2.
Hmm, what about Option 4: bind [wsl-gw-ip] AND keep [REDACTED] fallback? Not possible (single bind).
What about binding to localhost and using WSL's... no.
Consider likelihood of IP change: WSL2 NAT network IP ([wsl-gw-ip]) — this is allocated by Windows for the WSL vEthernet. It's stored in WSL's settings and typically stable per machine across reboots; it changes if another Hyper-V network conflict forces reconfiguration or if user configures networkingMode=mirrored later. Medium-low risk of change, but painful when it happens (silent breakage).
We could add a safety net without system changes: a WSL-side helper script? Not now ("don't build yet").
Actually — reconsider: How about scoping the firewall rules to RemoteAddress = [wsl-gw-ip]/20 (WSL subnet)? If IP changes within same subnet → fine; if subnet changes → break (similar brittleness). Interface scoping (vEthernet (WSL (Hyper-V firewall))) is stable across subnet changes → most robust.I think Option 2 (interface-scoped restriction of the two installer rules) is the best final state: robust + safe + minimal (modifies 2 existing rules rather than adding new ones).
But it needs UAC. The user authorized "minimum necessary changes". Given the current0.0.0.0 bind created LAN exposure, restricting the rules IS necessary for safety.
Alternatively — choose Option 1 (rebind to specific IP) to avoid touching firewall at all. Simplicity favors... hmm. Honestly, Option 1 changes nothing about firewall, is address-scoped (stronger isolation than a firewall rule, arguably), and the downside is IP stability.
Let me think about which the user (building an offline AI chatbot dev project) would rather have:
- If they ever restart WSL, the vEthernet IP usually stays the same. If it changes, Ollama (already running, bound to old IP) — wait, does Ollama rebind on IP change? The vEthernet adapter's IP changing while Ollama holds a bound socket on old IP: the old IP is removed from the interface → the bound socket becomes invalid (bind to a removed IP → connections fail). So breakage until restart of Ollama with updated env.
Risk of confusion later: "it stopped working" — annoying.
Option 2 with UAC now = done once, then works regardless of IP changes. Also note: option 2 leaves Ollama bound to ALL interfaces including Wi-Fi, but firewall only permits via WSL adapter. If someone later disables firewall... edge case.
Actually — belt & braces: do Option 2 AND keep [REDACTED]? Or Option 2 + bind to [REDACTED] (current state)? That's what we have + tightening. I'll go with Option 2 as primary, and mention Option 1 as the no-UAC alternative... Should I ask the user?
The user's instruction: "First report: what networking configuration you intend to use, why, what files/settings you will modify, then perform the minimum necessary changes and verify." I already reported plan (firewall rule scoped to WSL interface was in the plan, UAC mentioned). Now the discovery: firewall rule already exists (broad). The minimal necessary change to be safe = restrict those rules rather than add new.
I already told the user a UAC prompt would appear. So proceeding with an elevated command to restrict the two rules is consistent with my report.
But hmm — "Do not change anything unnecessarily": modifying Ollama's installer firewall rules... is it necessary? Only because we chose [REDACTED]. Alternatively revert to binding the WSL IP → no firewall modification needed, and safety achieved by address scoping.
Decision: I'll go with restricting the two rules to the WSL interface while keeping [REDACTED]. Rationale: robust to IP changes (no silent breakage later), interface scoping is precise (only WSL VM traffic can arrive), and it also fixes the pre-existing over-broad rules (any remote/any port on Public) — a genuine safety improvement rather than an unnecessary change.
Hmm, wait. But is it truly needed? Let me weigh once more... The current state already works (WSL reachable). If I do nothing more: LAN peers can reach Ollama on [lan-ip]:11434 (Public profile, any remote, program rule matches ollama.exe). Actually — do LAN peers' connections to our11434 get matched by the program rule? The rule is program-scoped: yes, inbound SYN to any port where ollama.exe is listening... program filter matches the owning process of the listening socket → allowed. So yes, exposed to LAN.
The user said "Do NOT expose Ollama to the public internet." LAN ≠ public internet. Strictly, current state doesn't violate the letter. But the spirit — they want safe. Exposing an unauthenticated LLM to an office LAN is a real security issue I shouldn't leave silently.
Two sub-options: (A) tighten firewall (UAC), (B) rebind to wsl-gw-ip.
I could present this to the user with the question tool — but they asked me to just do it. However, this is a genuine security/UX tradeoff with a UAC interaction. Given they've already been told UAC is coming and they said "perform the minimum necessary changes and verify", I'll make the call.
Which is truly "minimum"? (B) = no further system change (just adjust the env var we already wrote + restart Ollama). (A) = modify 2 firewall rules.
Which is "safest"? (B) is safer: defense by address binding (not listening on LAN at all) vs relying on firewall rule correctness. With (B), even if firewall is off/changed, LAN can't connect. And WSL access is direct on the adapter address.
Which is most robust? (A).
Hmm, can I get both safety and robustness? Yes: (B) + keep the broad firewall rules as-is is safe but not robust; (A) robust but relies on firewall.
What about bind to [wsl-gw-ip] and ALSO tighten rules? That's belt+braces but 2 changes.
I'll pick... Let me think about the user's future: they'll build a chatbot app connecting to hxxp://localhost:11434 from WSL (most likely). Wait — that's a crucial point! If their app runs in WSL and connects to localhost:11434, it WON'T work (localhost in WSL = WSL itself). They'll need to configure OLLAMA_HOST=hxxp://[wsl-gw-ip]:11434 in their app config — or we could make localhost:11434 work in WSL by adding an entry to /etc/hosts? Hmm: adding localhost ...? No — we need WSL's localhost:11434 to forward to Windows. Can't without a local listener in WSL (a socat-style forwarder... nc exists but needs a proper forking relay; python3 is available! A small Python TCP forwarder in WSL listening on localhost:11434 → forwarding to [wsl-gw-ip]:11434 would make localhost:11434 work transparently. But that's building infrastructure — "do not start building the chatbot yet" — but connectivity solution... The user asked specifically for WSL apps to reach the Windows Ollama server; giving them a documented endpoint is enough. A forwarder adds a persistent process — extra complexity. Better: tell them to use hxxp://[wsl-gw-ip]:11434 (or add an /etc/hosts alias entry mapping a fake hostname like host.ollama to [wsl-gw-ip] — simple, no daemon! e.g., [wsl-gw-ip] ollama.local in /etc/hosts → app uses hxxp://ollama.local:11434. Hmm, but /etc/hosts is regenerated? WSL manages /etc/hosts automatically (appends managed entries) — manual entries persist (file isn't fully regenerated; WSL inserts its own lines and preserves user lines? Actually WSL regenerates /etc/hosts on each boot but preserves... I believe WSL rewrites /etc/hosts each boot with Windows hosts file content + WSL entries; user-added lines may be wiped. There's /etc/wsl.conf [network] hostsFile? Not for custom entries. Risky.)
Keep it simple: endpoint = hxxp://[wsl-gw-ip]:11434 (document as "Windows host Ollama endpoint"), and note IP may change after WSL restart (verify with ip route).
Given the app config will use the explicit IP anyway, binding Ollama to that same IP (Option B) is coherent and zero-extra-change.
Ugh, but IP-change brittleness... With Option B, if IP changes, BOTH sides break consistently (app config + Ollama bind) → fix = update both. With Option A, app config still needs updating (it references the IP) but Ollama keeps working on any route. So the app endpoint reference to IP is inherently brittle in either option → brittleness already exists → Option B's extra brittleness (Ollama bind) isn't the dominant issue.
Given the app must be told the host IP regardless, I now lean to Option B: bind Ollama to [wsl-gw-ip] (no firewall modification, maximum safety by not listening on LAN interfaces at all), and document the IP-change caveat.
Hmm, but wait: one more advantage of Option B — it also neutralizes the over-broad installer firewall rules for our exposure (nothing listening on LAN addresses).
But hold on: is binding to a specific IP going to also make Windows generate a firewall prompt? No, existing rules cover.
Also: what about UDP rule / "any port" — irrelevant.
Hmm, but there's a subtlety with Option B: does Ollama's OLLAMA_HOST accept an arbitrary IP? Yes (host:port). If IP invalid/not present at start → bind error → server fails.
Alternatively Option B': bind to [wsl-gw-ip] via OLLAMA_HOST — wait, also consider IPv6? WSL reaches Windows via IPv4 gateway; http-get to [wsl-gw-ip] works. Fine.
Hmm, one concern: earlier netstat showed :::11434 (IPv6 wildcard, dual-stack). With a specific IPv4 it'll show [wsl-gw-ip]:11434. OK.
Now — which to choose?? Let me settle definitively.
Criteria from user: safest + simplest + minimal changes + must work from WSL (verified) + don't expose publicly.
Option B (bind WSL IP):
- changes: 1 env var value (already have OLLAMA_HOST=[REDACTED] → change to [wsl-gw-ip]) + Ollama restart (again).
- safety: strongest (no listener on Wi-Fi at all).
- no UAC needed at all! (firewall already permits via program rules — proven).
- robustness: breaks if vEthernet IP changes (document it).
Option A ([REDACTED] + tighten2 rules):
- changes: firewall rule modification (UAC) + env already set.
- safety: good (interface-scoped), but relies on firewall; leaves listening socket on all interfaces.
- robustness: better wrt IP change.
- UAC prompt required; modifies third-party (installer) rules.
Both acceptable. Simplicity & minimum-change → Option B. Also no UAC = no interruption to user. I'll go with Option B, and explain the IP-change caveat + how to re-verify.
Hmm, but is there a risk the WSL vEthernet IP changes soon (e.g., on Windows reboot)? It's stable in practice for a given machine; WSL recreates the same subnet usually (it stores the network config). If the user later enables mirrored mode in .wslconfig, it'd change (but then localhost works anyway).
Wait, one more consideration — actually, maybe safer to do BOTH bind-to-WSL-IP AND... no. Keep it minimal: Option B.
Hold on, though. Let me reconsider robustness differently: what if I bind to [REDACTED] but ALSO... no, exposure.
Decision: Option B.
Actually, wait. Let me reconsider one thing: is it possible for a LAN peer to reach [wsl-gw-ip]? The vEthernet is a private virtual switch not bridged to Wi-Fi; LAN hosts have no route to [wsl-gw-ip]/20 (it's RFC1918; office network might route 172.16/12 internally??10.82.x suggests the corp network uses 10/8; 172.22 could theoretically be routed somewhere else in the corp network — but even if routed, it would route to whatever host owns [wsl-gw-ip] on that network, not our machine (our machine only owns it on the virtual switch). So no path. Safe.)
Also Windows itself can reach it (local). Fine.
Also: after rebinding, re-verify WSL connectivity + generation test.
One more: should I keep HKCU OLLAMA_HOST = hxxp://[wsl-gw-ip]:11434 for persistence. Yes — but if IP changes later, at next login Ollama binds stale IP → server may fail to start → tray shows error. Hmm, that's the brittleness. Accept + document. Actually... alternatively persist [REDACTED] (robust) and... no — safety first; but then on IP change, WSL loses access silently.
Ugh. Tradeoff is real. Let me quantify IP-change likelihood: WSL2 NAT network (the "vEthernet (WSL (Hyper-V firewall))" adapter with[wsl-gw-ip]) — this is created by the WSL/Hyper-V networking stack; the subnet is randomly chosen at first creation and persists across reboots on the same machine (it's saved in WSL's settings/wslconfig? Actually stored where? The Hyper-V default switch... for WSL, the network config is persisted in %UserProfile%\...? I recall WSL network settings persist (same IP after reboot) unless there's a conflict. Changes happen after Windows feature updates sometimes.) So: low-moderate probability of change over weeks/months.
For a dev project, if it breaks, the user re-runs a documented check. Also our verification commands are documented.
Alternatively, do the safety-max: bind WSL IP + restrict firewall (both) → most work, still has IP brittleness.
I'll go Option B and document clearly.
Hmm, hmm. Actually — wait. What if instead of a fixed IP, we avoid bind brittleness AND exposure using localhost + a WSL-local forwarder (python3) — no: extra daemon, more complexity, and WSL-side must be kept running. Not "simplest".
OK final: Option B.
Actually, let me reconsider Option A's UAC once more... The user might actually prefer robustness (firewall) — but they explicitly said prefer safest+simplest+minimum changes, and no-UAC. Option B it is. I'll mention Option A as an available alternative if they want IP-change-proofing later.
Wait — but one thing about Option B: I already set HKCU OLLAMA_HOST=hxxp://[REDACTED]:11434. Changing it to hxxp://[wsl-gw-ip]:11434 = a second write (fine, same setting).
Also should I consider binding to BOTH the loopback and vEthernet? Not supported (single address). Ollama binds one address; with [wsl-gw-ip], Windows-side tools using localhost:11434 would BREAK (loopback no longer bound)! That's a regression: the user's Windows-side usage (localhost:11434 from Windows, e.g., OpenCode? no, OpenCode is in WSL; but Windows apps like the Ollama tray/chat UI, or any Windows tools) would fail!
Important! Binding to a specific non-loopback IP removes loopback binding → Windows-side localhost:11434 stops working. The user's requirement #5 earlier: "Windows-side generation works" — we should preserve that. The Ollama desktop app itself connects to localhost:11434 (the tray's UI/chat features talk to the server via localhost!) → the app might break (shows error, tries reconnect).
Hmm! That's a strong argument against binding to a single specific IP. Options:
- [REDACTED] → covers loopback AND vEthernet AND Wi-Fi (Wi-Fi exposure via broad firewall rules — needs tightening).
- specific IP → breaks Windows-side localhost access.
Does Ollama bind loopback when host is [REDACTED]? Yes, wildcard includes localhost.
So: to keep BOTH Windows-side localhost and WSL access, we need REDACTED. => Option A ([REDACTED] + tighten firewall rules) becomes necessary for functionality!
Unless... binding to multiple addresses: OLLAMA_HOST only takes one. So yes: [REDACTED] is required.
Wait, is that right? Could we bind to the loopback AND have WSL reach... no (the original problem).
Therefore: keep0.0.0.0 (current state, works for both loopback and WSL), and tighten the two over-broad installer firewall rules to the WSL interface to prevent LAN exposure. That's Option A. UAC required.
Alternatively, tighten rules by adding -LocalPort 11434 restriction + -RemoteAddress WSL subnet? Interface scoping is the cleanest.
Hmm, but modifying installer rules: Ollama updates might recreate them broad → exposure creeps back. Could instead disable the two broad rules and add our own interface-scoped rule for 11434 (program ollama.exe or port-based). That's clearer semantics: we own the rule name "Ollama (WSL only)". Changes: disable 2 rules + add 1 rule (all in one elevated command). Or modify the 2 rules in place (fewer changes?).
Minimal: modify the two rules to add InterfaceAlias restriction. But Set-NetFirewallRule -InterfaceAlias — need to confirm parameter exists. If not, we can disable them and create a new port-based rule scoped to the interface:
powershell
New-NetFirewallRule -DisplayName "Ollama (WSL adapter only)" -Direction Inbound -Action Allow -Protocol TCP -LocalPort 11434 -InterfaceAlias "vEthernet (WSL (Hyper-V firewall))" -Profile Any
Disable-NetFirewallRule ... (the two ollama.exe rules)
Careful: disabling the program rules also affects UDP/other ollama.exe inbound — Ollama doesn't need other inbound. But also: does disabling break WSL access before our new rule? We do both in the same elevated command → atomic enough.
Wait — but should we also consider: maybe instead of interface scope, scope the two rules by RemoteAddress=[wsl-gw-ip]/20 (WSL subnet). Then Windows→self still fine. Interface alias approach is cleaner and survives subnet change.
Also note: with our new TCP:11434 interface-scoped rule, do we even need to disable the broad ones? Yes — because broad ones allow any port from any remote on Public (LAN) for ollama.exe → with [REDACTED] bind, LAN can reach 11434 through them. So must disable/scope them.
Hmm — one question: are these "ollama.exe" rules actually from the installer, or did I create them?? I never created firewall rules. They're pre-existing (installer-created). Yes.
Also should we scope them rather than disable (in case Ollama needs other inbound)? Ollama needs only 11434 TCP. Disable + explicit port rule = tighter. Or modify both rules to InterfaceAlias=WSL — keeps program scoping (only ollama.exe allowed, any port, but only via WSL adapter). That's also safe and arguably preserves installer intent. And it's "modify existing" = fewer new objects.
Preference: modify the two existing rules by adding InterfaceAlias. If Set-NetFirewallRule lacks -InterfaceAlias, fall back to disable+create.
Let me check quickly: does Set-NetFirewallRule have -InterfaceAlias? I can check via Get-Command Set-NetFirewallRule | ... parameter names — cheap and safe (no change). Do that in the elevated script? No — check first non-elevated.
Plan:
1. Check Get-Command Set-NetFirewallRule params for InterfaceAlias (non-elevated, fast).
2. Build elevated command: restrict the two rules (by DisplayName "ollama.exe" — two rules same name! Modifying by DisplayName would hit both — good: Set-NetFirewallRule -DisplayName 'ollama.exe' -InterfaceAlias 'vEthernet (WSL (Hyper-V firewall))' affects both rules (TCP+UDP). But careful: are there OTHER rules named "ollama.exe"? We found exactly 2 (TCP, UDP). Both ours to scope. Good.)
Also maybe additionally scope LocalPort to 11434? Not necessary; interface scope suffices. Minimal: just interface.
3. UAC elevation via Start-Process -Verb RunAs -Wait; user clicks Yes.
4. Verify: re-read the two rules (InterfaceAlias set), test WSL→host connectivity, test Windows-side localhost still works (http-get localhost from Windows side), run generation test from WSL, verify LAN non-exposure as best we can from here (we can't simulate LAN peer; rely on rule scoping + netstat showing [REDACTED] binding + interface-scoped rules).
5. Also verify loopback from Windows still works (Windows http-get localhost:11434).
6. Cleanup temp files.
Also update: nothing more to change re OLLAMA_HOST (keep hxxp://[REDACTED]:11434 — already set in HKCU).
Wait — should I reconsider whether tightening is "necessary" per user's constraints (do not expose to public internet; LAN isn't public internet)? I'll frame it: the installer rules allow any LAN host to use Ollama now that we bind all interfaces; scoping them to the WSL adapter is required to keep the exposure confined (and it's what I originally planned). The user already approved the firewall-rule step implicitly (I reported "one inbound allow rule scoped to WSL adapter"; the actual minimum is scoping existing rules — a variation I'll report).
Let's also double check that Wi-Fi profile is Public (yes) — so those rules ARE active on Wi-Fi. Confirmed risk.
Also: while at it, should we verify from WSL that connecting to[lan-ip]:11434 works now (proving LAN-path would work)? From WSL, as discussed, packets to the host's Wi-Fi IP get locally delivered on... hmm, actually let's think: WSL sends packet dst=[lan-ip] → gateway wsl-gw-ip → Windows routing: dst is local address → local delivery. Inbound interface for firewall purposes = the interface it arrived on = vEthernet. So it'd be allowed by our WSL-scoped rule too — misleading test (can't distinguish). A true LAN test would require another machine. So we can't empirically prove LAN blocking; we rely on rule InterfaceAlias semantics (well-established: inbound interface match).
OK — also note Hyper-V firewall: since our WSL→host connection already works via host program rules, the Hyper-V firewall layer evidently permits with host policy merge. Our modified rules remain host policies → still allowed. Should be fine; verify empirically after the change.
Now, one risk: Set-NetFirewallRule -DisplayName 'ollama.exe' -InterfaceAlias ... — if -InterfaceAlias isn't a Set parameter, command errors in elevated window and exits (window closes fast; user clicks Yes, we then verify and see nothing changed → re-run with fallback). To avoid a wasted UAC round-trip, check parameters FIRST (non-elevated Get-Command works).
Let's check now.
Key discovery: two pre-existing installer firewall rules (ollama.exe, TCP+UDP, any port, any remote, Public profile) are what allowed the connection — and since we're now bound to [REDACTED], those rules would also let LAN peers reach Ollama. I'll scope them to the WSL adapter only. Checking the cmdlet first so one UAC prompt suffices:
$ {"command": "/mnt/c/Windows/System32/WindowsPowerShell/v1.0/powershell.exe -NoProfile -Command '(Get-Command Set-NetFire
Profile RemoteAddress LocalPort RemotePort InterfaceAlias InterfaceType RemoteUser RemoteMachine RemoteDynamicKeywordAddresses
$ {"command": "http-get -s -m 5 hxxp://[wsl-gw-ip]:11434/api/version; echo \" wsl_exit=$?\"; /mnt/c/Windows/System32/http-get.exe
{"version":"0.40.1"} wsl_exit=0 {"version":"0.40.1"} win_localhost_exit=0
Set-NetFirewallRule supports -InterfaceAlias. And both directions currently work: WSL → [wsl-gw-ip]:11434 OK, Windows → localhost:11434 OK.
Now the elevated step. I'll:
1. Set InterfaceAlias on both rules named "ollama.exe" to the WSL adapter only.
Command (elevated):
powershell
Set-NetFirewallRule -DisplayName 'ollama.exe' -InterfaceAlias 'vEthernet (WSL (Hyper-V firewall))'
Concern: does Set-NetFirewallRule -InterfaceAlias work when setting on existing rules? Yes, it updates the interface filter.
But wait — hmm, one consideration: scoping to interface alias 'vEthernet (WSL (Hyper-V firewall))'. If that adapter name changes (e.g., WSL update renames), rule becomes ineffective → WSL access breaks (fail-safe: breaks connectivity, doesn't expose). Acceptable.
Should I ALSO add LocalPort=11434 scoping to these program rules? They're program-scoped (ollama.exe only), so any-port is limited to that program; with interface scoping to WSL only, LAN exposure = none. Windows local processes on loopback are unaffected by inbound rules? Loopback traffic — Windows Firewall doesn't filter loopback by default (and anyway rule now scoped to vEthernet interface → loopback unaffected → Windows localhost still works). Good.
Also should I verify whether these rules are actually used for the WSL connection (maybe WSL connection is allowed by something else entirely, e.g., Core Networking or Hyper-V defaults). After scoping, our test will tell: if WSL still works, fine either way.
Elevation: Start-Process powershell -Verb RunAs -Wait with the command. Tell user to click Yes.
Let's prepare the elevated script as a file to avoid quoting issues: write /mnt/c[REDACTED]/AppData/Local/Temp/scope_fw.ps1:
powershell
Set-NetFirewallRule -DisplayName 'ollama.exe' -InterfaceAlias 'vEthernet (WSL (Hyper-V firewall))'
Get-NetFirewallRule -DisplayName 'ollama.exe' | ForEach-Object { "$($_.DisplayName) intf=$($_.InterfaceAlias -join ',')" }
Hmm, Get-NetFirewallRule object has InterfaceAlias property? It's on the rule object (yes, rule objects expose InterfaceAlias). Output won't be visible (window closes). Write output to a log file in temp so we can read it non-elevated:
powershell
$out = @()
Get-NetFirewallRule -DisplayName 'ollama.exe' | ForEach-Object { $out += "$($_.DisplayName) enabled=$($_.Enabled) intf=[$($_.InterfaceAlias -join ';')]" }
$out | Set-Content "$env:TEMP\scope_fw_result.txt"
Then run: Start-Process powershell -Verb RunAs -Wait -ArgumentList '-NoProfile','-ExecutionPolicy','Bypass','-File','[REDACTED]\AppData\Local\Temp\scope_fw.ps1'
Timeout: allow120s for UAC click.
Potential issue: if UAC is configured to require credentials the user doesn't have... they're admin, should be fine.
Note: writing a .ps1 to Windows Temp and running elevated — path visible to admin. Fine.
Let's also double-check the exact adapter alias string: vEthernet (WSL (Hyper-V firewall)) (from Get-NetIPConfiguration output). Yes.
Write script and run elevated.
One concern: when the elevated process runs Set-NetFirewallRule, if the InterfaceAlias value doesn't match any interface, it errors "No matching network interface"? It might accept arbitrary strings? Actually InterfaceAlias validation: it may warn if no interface matches but still store it. If it errors, our log file won't be written (or will contain error via try/catch). Add error handling:
$ErrorActionPreference = 'Continue'
$log = "$env:TEMP\scope_fw_result.txt"
try {
Set-NetFirewallRule -DisplayName 'ollama.exe' -InterfaceAlias 'vEthernet (WSL (Hyper-V firewall))' -ErrorAction Stop
$status = 'SET_OK'
} catch { $status = 'FAILED: ' + $_.Exception.Message }
$lines = @($status)
Get-NetFirewallRule -DisplayName 'ollama.exe' | ForEach-Object { $lines += "Rule=$($_.DisplayName) Enabled=$($_.Enabled) Intf=[$($_.InterfaceAlias -join ';')] Ports=[$((($_ | Get-NetFirewallPortFilter).LocalPort) -join ';')]" }
$lines | Set-Content -Path $log -Encoding ascii
Good. Then read the log.
After that: verify WSL connectivity + Windows localhost + generation test.
Also cleanup: remove testlisten.ps1, testlisten.ready, fwcheck.ps1, fw_rules.txt (if created — the netsh redirect may have created an empty/partial file in /tmp/opencode; and scope script keep? remove after).
Let's go. I'll inform the user about the UAC prompt.
Set-NetFirewallRule supports -InterfaceAlias, and both directions currently work (WSL→host ✅, Windows→localhost ✅). Now the one elevated step — a UAC prompt will appear on your Windows desktop; please click Yes:
file: /mnt/c/Users/user/AppData/Local/Temp/scope_fw.ps1 $ErrorActionPreference = 'Continue' $log = "$env:TEMP\scope_fw_r
Wrote file successfully.
Now run elevated with -Verb RunAs -Wait. Tell user to click Yes. Timeout 120s.
$ {"command": "rm -f /mnt/c/Users/user/AppData/Local/Temp/scope_fw_result.txt; /mnt/c/Windows/System32/WindowsPowerShell/v
elevated_exit=0 FAILED: Defer to user' setting can only be used in a firewall rule where program path and TCP/UDP protocol are specified with no additional conditions. Rule=ollama.exe Enabled=True Dir=Inbound Profile=Public Intf=[] LocalPort=[Any] Ru…
The elevation worked (user clicked Yes), but Set-NetFirewallRule -InterfaceAlias failed with:
"Defer to user' setting can only be used in a firewall rule where program path and TCP/UDP protocol are specified with no additional conditions."
Interesting — the existing rules have "Defer to user" — meaning they are Windows Store/packaged app rules? Actually "Defer to user" sounds like a policy setting... The rules are program-path rules that were created with some conditional (maybe they're PCF/rules with "Defer to user" = the rule allows the firewall to prompt?). Adding an interface condition is not allowed for such rules.
So modifying those rules with extra conditions is not permitted. Fallback plan:- Disable those two rules and create our own rule: port11434, TCP, interface-scoped (program ollama.exe optional; simpler: TCP localport 11434 + InterfaceAlias + profile Any).
Wait, but do we even need to disable them? If we can't scope them, they remain open to LAN for ollama.exe (any port). With [REDACTED] bind → LAN exposure. So yes: disable them (or restrict via... can we set RemoteAddress instead? Same "additional conditions" limitation likely applies — the rule already has program path + protocol; adding any condition (interface or address) is what's blocked. Hmm, the error says the rule must have "program path and TCP/UDP protocol ... with no additional conditions" for DeferToUser. Our rules have program path + protocol... but apparently they also have some extra setting (maybe the program filter is actually a "package" or the rule has some other property). The error suggests the rule currently contains a "defer to user" setting which conflicts... Actually maybe the DeferToUser setting is applied when we tried to modify? No...
Interpretation: These rules likely have DeferToUser=true? Hmm, "Defer to user" might be about how the rule was created (by the installer with user consent). Whatever — the modification path is blocked.
New approach (fallback as planned):
1. Disable the two broad rules: Disable-NetFirewallRule -DisplayName 'ollama.exe'
2. Add our own: New-NetFirewallRule -DisplayName 'Ollama 11434 (WSL adapter only)' -Direction Inbound -Action Allow -Protocol TCP -LocalPort 11434 -InterfaceAlias 'vEthernet (WSL (Hyper-V firewall))' -Profile Any -Program '[REDACTED]\AppData\Local\Programs\Ollama\ollama.exe'Should we include -Program? Including the program path makes it tighter (only ollama.exe). But if Ollama updates move/change exe path (it stays same path), fine. However program-scoped rules + interface condition is allowed (the DeferToUser constraint was specific to those existing rules). Simpler & robust: no program scoping, just port+interface (only reachable via WSL adapter). I'd include program path for extra tightness? If the path has a space ("Program Files"? no — path is [REDACTED]\AppData\Local\Programs\Ollama\ollama.exe, no spaces). Adding -Program is fine. But if they later reinstall to Program Files with spaces... New-NetFirewallRule handles quoted paths internally? The program path filter stores the path; spaces are OK (no shell parsing at that point). I'll include -Program for tightness. Hmm — but is the serving process ollama.exe? Get-Process showed ProcessName "ollama" (PID 15808) → path = ...\Ollama\ollama.exe. Yes. And tray is "ollama app.exe". The tray's ui server (port 60587) — do we need inbound to it? It's Windows-local only (UI accessed by... the tray window is a native app? "ui server" serves the Ollama app window via localhost — Windows-local, loopback → unaffected by our rule changes? Loopback traffic isn't blocked by default Windows Firewall... but wait: if we disable the two ollama.exe program rules, does loopback inbound to ollama's serve/ui ports get blocked? Windows Firewall: loopback (localhost) inbound — by default, is there an implicit allow? Windows Firewall does NOT filter loopback traffic by default? Hmm. Actually WFP does process loopback traffic, but the default inbound block policy... I recall loopback connections are generally not subject to the default block because... no wait, they ARE subject; that's why services often have explicit allow rules... but countless dev servers on localhost work without firewall rules — because when a local program connects to localhost, Windows Firewall applies "allow if both endpoints local"? There's a well-known behavior: Windows Firewall allows inbound connections originating from the same machine (loopback) — WFP has a condition: traffic with local loopback bypass? Hmm, I believe connections to/from localhost are not blocked by default (the default block applies to traffic from other hosts; there's an "allow local" implicit rule? I'm not 100% sure, but empirically localhost dev servers work fine without firewall rules — e.g., our test TcpListener on [REDACTED]:18080... we never tested loopback from Windows itself).
Evidence from our session: Before any changes, Ollama bound localhost:11434 and Windows-side http-get localhost:11434 worked (I ran Windows http-get earlier → worked at 13:55 while bound to loopback with these same rules... well, the rules were program-allow anyway then).
Key risk after disabling the two program rules: does Windows↔loopback still work for ollama.exe? The earlier successful test win_localhost_exit=0 happened while the program rules were enabled. After disabling, if loopback requires an allow rule... Windows loopback inbound: WFP default: "allow" for local loopback? Common knowledge: Windows Firewall doesn't block loopback — actually I'm quite sure it DOES apply rules to loopback... Let me think of a concrete example: Run a dev server on localhost, remote machine can't reach (not bound), local machine can — always works regardless of firewall rules. Also, inbound to loopback from same host = both endpoints are the local host; Windows Firewall's default inbound block applies to packets arriving from other hosts... For loopback, the packet never crosses an external interface. WFP classifies it as LOCAL/loopback traffic, and there are built-in permits for loopback (the "Core Networking - DNS" etc. aside, I'm fairly confident loopback is allowed by an implicit rule: there's a well-known WFP condition FWPM_CONDITION_LOCAL_INTERFACE ... hmm).
Empirical safety: instead of disabling the program rules outright, I could TEST: create our new port+interface rule FIRST, test WSL works, then disable the two broad rules, then test Windows localhost still works. If localhost broke (unlikely), re-enable. That's a careful sequence within one elevated session? Better: do it in stages so we can react.
Stage 1 (elevated): create new rule. → non-elevated tests (WSL + Windows localhost).
Stage 2 (elevated): disable two broad rules. → non-elevated tests again (WSL + Windows localhost + generation).
That's 2 UAC prompts. Acceptable? Slightly annoying. Could do both in one elevated script but with verification... can't verify from within (Windows-side http-get to localhost from the elevated process would actually work — we CAN test loopback from inside the elevated script! Invoke-WebRequest hxxp://localhost:11434/api/version or http-get.exe. If loopback fails after disabling, the script can re-enable automatically). But the WSL-side test can't be done from the elevated script.
Plan for single elevated run:
1. Create new rule (port 11434 TCP, interface-scoped, program ollama.exe optional).
2. Disable the two broad rules.
3. Test loopback from Windows: (Invoke-WebRequest -Uri hxxp://localhost:11434/api/version -UseBasicParsing).Content → if fails, re-enable broad rules and log.
4. Write log.
Then from WSL: test connectivity (the critical unknown: will our new rule allow WSL→host? It should — interface + port based).
If WSL test fails → problem: maybe the Hyper-V firewall requires program match, or the interface alias mismatch. Then we'd re-enable the broad rules (which were allowing WSL) and think again. Recoverable.
Risk: brief window where WSL→host is blocked (between disable and our test) — trivial.
About including -Program in the new rule: If Hyper-V firewall or something weird requires program scope... The broad rules were program-scoped and worked. A port-only rule should work equally (host policy merge). But to maximize the chance of success in one shot, should our new rule be program-scoped like the old one? If I scope to program path, and path contains no spaces — fine. Let's include -Program to mirror the working rule's nature... Hmm, but if Ollama app updates (app-*.log updates exist) the exe path stays the same (installed dir constant). I'll include -Program.
Wait — actually, if I include -Program AND -InterfaceAlias AND -LocalPort, that's fine (rule created fresh with all conditions — no DeferToUser issue since we're not modifying those rules).
Also: should the new rule be Profile=Any? The WSL adapter's profile is likely Public (unlisted). Set -Profile Any to be safe (or omit → default Any? New-NetFirewallRule default Profile = Any). I'll set explicitly.
Also — should we keep UDP? Ollama doesn't need UDP. Skip.
Also, what about the tray's ui server port 60587 — needs loopback only (Windows app). Not our concern; loopback unaffected.
Hmm — one more: after disabling the broad ollama.exe rules, does anything else on Windows rely on inbound to ollama.exe from LAN? No.
Let me also double check the "Defer to user" error doesn't affect New-NetFirewallRule. Different rule → no such setting → fine.
Elevated script v2 (scope_fw.ps1 → overwrite with new logic; write a new file fw_apply.ps1):
$ErrorActionPreference = 'Continue'
$log = "$env:TEMP\scope_fw_result.txt"
$lines = @()
# 1) new tight rule
try {
$r = New-NetFirewallRule -DisplayName 'Ollama 11434 (WSL adapter only)' -Direction Inbound -Action Allow -Enabled True -Profile Any -Program '[REDACTED]\AppData\Local\Programs\Ollama\ollama.exe' -Protocol TCP -LocalPort 11434 -InterfaceAlias 'vEthernet (WSL (Hyper-V firewall))' -ErrorAction Stop
$lines += 'NEW_RULE_OK'
} catch { $lines += 'NEW_RULE_FAILED: ' + $_.Exception.Message }
# 2) disable broad rules
try {
Disable-NetFirewallRule -DisplayName 'ollama.exe' -ErrorAction Stop
$lines += 'BROAD_RULES_DISABLED'
} catch { $lines += 'DISABLE_FAILED: ' + $_.Exception.Message }
# 3) loopback check from Windows
try {
$resp = Invoke-WebRequest -Uri 'hxxp://localhost:11434/api/version' -UseBasicParsing -TimeoutSec 10
$lines += 'LOOPBACK_OK: ' + $resp.Content
} catch {
$lines += 'LOOPBACK_FAILED: ' + $_.Exception.Message
# revert: re-enable broad rules
try { Enable-NetFirewallRule -DisplayName 'ollama.exe'; $lines += 'REVERTED_REENABLED' } catch { $lines += 'REVERT_FAILED' }
}
# 4) state dump
Get-NetFirewallRule -DisplayName 'ollama.exe','Ollama 11434 (WSL adapter only)' -ErrorAction SilentlyContinue | ForEach-Object {
$lp = ($r2 | Get-NetFirewallPortFilter).LocalPort -join ';' ...
}
Careful with variable names in ForEach.
Hmm — note: loopback check from Windows after disabling: if loopback is blocked without a rule, we'd see failure and revert. But there's a subtlety: even if loopback works, we then can't know WSL works until we test non-elevated. If WSL fails → re-enable broad rules ourselves (another UAC... we can do a small elevated re-enable later if needed).
Hmm, is there a risk our new interface-scoped rule doesn't allow WSL while the broad one did? Possible reasons: (a) Hyper-V firewall requires... whatever; if it fails we'll see timeout and adapt.
Alternative safer sequencing to guarantee connectivity: create new rule, keep broad rules ENABLED initially, test WSL → if WSL works, THEN disable broad rules, retest WSL + loopback. That's 2 UAC prompts but no connectivity risk window. I prefer robustness over UAC count... but two prompts is annoying for the user.
Compromise: single elevated run does: create new rule + disable broad + loopback self-check + (leave disabled), then I test from WSL immediately. If WSL fails → second UAC to re-enable broad rules and diagnose (we'd still be connected... wait, if WSL fails we're temporarily without connectivity — but we can revert quickly with a second UAC). Given we can revert, one prompt usually suffices. Go with single run.
Actually, even better: I can pre-test WITHOUT disabling broad rules in the same script order: create new rule, then simulate the disable effect? Can't.
Fine — single elevated script with auto-revert on loopback failure; then WSL tests; if WSL fails → revert (re-enable broad) in a second elevated call.
Actually — wait. Better idea to eliminate the WSL-unknown: keep broad rules enabled; create new rule; test WSL from WSL side (broad rules still allow → always works) — this doesn't test our new rule at all (broad rule might be the one allowing). Useless.
Alternatively: temporarily disable broad, test WSL (non-elevated, I do it), then decide to keep disabled or revert. The disable requires UAC; then if WSL works → done (no second prompt). If WSL fails → second UAC to re-enable. That's the same number of prompts as my single-script approach but with explicit non-elevated verification of loopback too... The single-script approach does loopback check internally (equivalent), and I do the WSL check after. Same thing. Single script it is.
Also: In the single script, after disabling, loopback check — note the WSL-side rules state matters not for loopback. Good.
One more consideration — will disabling the broad rules break the connection I'm currently using? My current WSL→[wsl-gw-ip]:11434 test connection is transient; ongoing generation tests happen after. Fine.
Let me also double-check: does the tray app or chat UI connect via loopback? Yes → covered by loopback test.
Also the Invoke-WebRequest runs in elevated PowerShell (system? no, admin user) — loopback to11434 → tests local access.
Alright — but hold on. Is including -Program wise? If the path is wrong (e.g., actual exe path differs — maybe it's "ollama.exe" in that dir, confirmed earlier: /mnt/c[REDACTED]/AppData/Local/Programs/Ollama/ollama.exe exists), rule won't match → WSL fails → we'd catch it in testing and fix (another UAC). To reduce risk, I could create the rule WITHOUT program scoping (pure port+interface). Pure port+interface is simpler and fewer failure modes; exposure limited to WSL adapter which is what matters. Program scoping adds defense-in-depth but also failure risk (path with spaces issues, updates changing path).
Decision: create rule WITHOUT -Program: TCP,11434, InterfaceAlias=WSL adapter, Profile Any, Inbound, Allow. Simple and effective.
Hmm, but then other Windows programs could be reached on 11434 via WSL... irrelevant (only what listens on 11434 matters; only Ollama does).
Also should I keep the UDP broad rule disabled? Yes (disable both broad ones).
Wait — actually, should I disable the broad UDP rule? It's inbound UDP allow for ollama.exe from any remote on Public — no UDP service needed. Disabling tightens. Keep plan: disable both.
Edge: Disable-NetFirewallRule -DisplayName 'ollama.exe' — does DisplayName match both? Both rules named "ollama.exe" → yes, operates on all matching.
Let's write fw_apply.ps1 and run elevated. Tell user UAC again.
The two installer rules use a "Defer to user" setting that can't take extra conditions. Falling back to: create one new tight rule (TCP 11434, WSL adapter only) + disable the two over-broad installer rules, with automatic revert if Windows-side loopback breaks.
Please click Yes on the UAC prompt again:
file: /mnt/c/Users/user/AppData/Local/Temp/fw_apply.ps1 $ErrorActionPreference = 'Continue' $log = "$env:TEMP\scope_fw_r
Wrote file successfully.
Run elevated.
$ {"command": "rm -f /mnt/c/Users/user/AppData/Local/Temp/scope_fw_result.txt; /mnt/c/Windows/System32/WindowsPowerShell/v
elevated_exit=0 NEW_RULE_OK BROAD_RULES_DISABLED WINDOWS_LOOPBACK_OK: {"version":"0.40.1"} Rule='ollama.exe' Enabled=False Dir=Inbound Profile=Public Intf=[] LocalPort=[Any] Rule='ollama.exe' Enabled=False Dir=Inbound Profile=Public Intf=[] LocalPort…
Results:
- NEW_RULE_OK
- BROAD_RULES_DISABLED
- WINDOWS_LOOPBACK_OK (loopback still works without broad rules — confirms loopback isn't blocked)
- Rule dump: new rule shows Intf=[] — the InterfaceAlias didn't get stored?! It shows LocalPort=[11434] but Intf=. And broad rules disabled (Enabled=False).
Why is Intf empty? Possibly $rule.InterfaceAlias property isn't populated on the rule object in this PowerShell version (the property might be on... Actually Get-NetFirewallRule objects DO have InterfaceAlias property. Hmm, but maybe when the rule has interface filter with a single alias, it shows. Or New-NetFirewallRule silently ignored -InterfaceAlias?
Wait — maybe it's an issue: the earlier Set-NetFirewallRule error said such conditions can't be added to DeferToUser rules. For New-NetFirewallRule, -InterfaceAlias should work. But dump shows empty.
Alternatively the dump reads $rule.InterfaceAlias which for rules created with interface filter... should return the alias. Empty suggests no interface filter was created.
Hmm, could -InterfaceAlias 'vEthernet (WSL (Hyper-V firewall))' have failed to match an interface and been dropped? Typically New-NetFirewallRule errors if alias doesn't exist: "No interface with this name exists"? It didn't error (NEW_RULE_OK).
Let's verify independently: check the rule's interface filter via Get-NetFirewallRule -DisplayName 'Ollama 11434 (WSL adapter only)' | Get-NetFirewallInterfaceFilter | Select InterfaceAlias — the associated filter object. The rule object's InterfaceAlias property might just not be populated in the dump pipeline (property exists but returns null unless... hmm).
Critical question: does the new rule actually restrict to the interface? If not, we have a rule allowing11434 from ANY interface → LAN exposure still exists (port 11434 open to LAN on Public profile) — actually worse than before? Same exposure basically (broad program rules disabled, new port rule open to all interfaces if interface filter missing).
Also — crucially — we haven't yet tested whether WSL connectivity works under the new rules! Let's test WSL → host now. If Intf is truly empty (rule applies to all interfaces), WSL will still work but LAN exposed.
Let's:
1. Test WSL connectivity (http-get).
2. Inspect the interface filter properly: (Get-NetFirewallRule -DisplayName 'Ollama 11434 (WSL adapter only)' | Get-NetFirewallInterfaceFilter).InterfaceAlias.
Also get the Rule object property via Get-NetFirewallRule -Name ... and check .InterfaceAlias.
Let's run both.
$ {"command": "http-get -s -m 6 hxxp://[wsl-gw-ip]:11434/api/version; echo \" wsl_to_host_exit=$?\"", "timeout": 30000}
{"version":"0.40.1"} wsl_to_host_exit=0
$ {"command": "/mnt/c/Windows/System32/WindowsPowerShell/v1.0/powershell.exe -NoProfile -Command '\n$r = Get-NetFirewallRu
Rule.InterfaceAlias=[] Rule.InterfaceType= InterfaceFilter.Alias=[vEthernet (WSL (Hyper-V firewall))] broad: ollama.exe enabled=False broad: ollama.exe enabled=False
The interface filter IS set: InterfaceFilter.Alias=[vEthernet (WSL (Hyper-V firewall))] — the Rule.InterfaceAlias property just isn't materialized in that context (cosmetic).
State:
- New rule: TCP 11434, Inbound Allow, Profile Any, interface = vEthernet (WSL (Hyper-V firewall)) only ✅ enabled.
- Broad installer rules (ollama.exe, any port, any remote, Public): disabled ✅.
- WSL → hxxp://[wsl-gw-ip]:11434 works ✅ (so the new rule is what's permitting it — broad rules are off).
- Windows → localhost:11434 works ✅ (loopback, verified inside elevated script).
Remaining verification per requirements:
1. WSL API reachable: /api/version ✅ (just did), also /api/tags (confirm model list from WSL).
2. Minimal generation test from WSL using gemma4:e2b.
3. Safety verification:
- netstat: Ollama bound to REDACTED — but firewall restricts to WSL interface.
- Confirm Wi-Fi interface can't reach: can't test from another machine; but we can verify rules: only interface-scoped rule for 11434, broad rules disabled.
- Additional check: test from WSL to the Wi-Fi IP[lan-ip]:11434 — as discussed, the packet would arrive at Windows via vEthernet interface → allowed → connection would SUCCEED. That test is misleading (doesn't prove LAN exposure). Skip it; or run it and explain? Better skip to avoid confusion... Actually, it might be worth knowing whether that path works — if the user's colleagues... no, colleagues arrive on Wi-Fi interface, not vEthernet. Skip.
Hmm, actually one meaningful safety check: verify from Windows that binding on Wi-Fi IP is filtered... can't without a second host.
Also: the tray UI (port 60587) — unaffected.
Now also consider: should I confirm that the disabled broad rules didn't break the Ollama app's own functions? Loopback OK. Tray running. Fine.
Generation test from WSL:
http-get -s -m 180 hxxp://[wsl-gw-ip]:11434/api/generate -d '{"model":"gemma4:e2b","prompt":"Say hello in exactly five words.","stream":false,"options":{"num_predict":16,"temperature":0}}'
Model was already loaded earlier (keep_alive 5m — that was >30 min ago, so it'll reload ~57s). Fine, timeout 200s.
Also test /api/tags from WSL.
Also final netstat listing.
Then cleanup temp scripts: fwcheck.ps1, testlisten.ps1, testlisten.ready, fw_apply.ps1, scope_fw.ps1, scope_fw_result.txt, /tmp/opencode/fw_rules.txt.
Wait — should I keep scope result log? No, cleanup all.
Also: note about persistence — HKCU OLLAMA_HOST=hxxp://[REDACTED]:11434 persists for future logins. Firewall rule persists. Broad rules stay disabled (persist). Good.
One more thing: the user's app will need the endpoint hxxp://[wsl-gw-ip]:11434 (WSL side) — document: gateway IP can be found via ip route. Also note that OpenCode/apps in WSL should NOT use localhost:11434 (that's WSL itself).
Hmm — should I add something to make localhost:11434 work in WSL? Not without a forwarder daemon; out of scope (user said don't build yet). Document instead.
Let's run the generation test + tags now.
New rule verified (InterfaceFilter.Alias=[vEthernet (WSL (Hyper-V firewall))]), broad rules disabled, WSL still connected. Now the required API + generation tests from WSL:
$ {"command": "http-get -s -m 6 hxxp://[wsl-gw-ip]:11434/api/tags; echo; echo \"--- generate ---\"; http-get -s -m 200 hxxp://172
{"models":[{"name":"gemma4:e2b","model":"gemma4:e2b","modified_at":"2026-10-05T02:29:52.6826236+05:30","size":4587156505,"digest":"b37049369adfe3d2b653af0ab301a062ca5cbe96ace6aa0d3f2559ee9b563fc2","details":{"parent_model":"gemma4-validation-20260929…
Generation from WSL works: "WSL GENERATION OK".
Now final safety/state verification and cleanup:
Also check git status? Not a repo, no project files touched — verify /mnt/d/OfflineMode still empty.
Also double check HKCU OLLAMA_HOST persisted value.
Also — one consideration: the disabled broad rules. Should I have left them? They're now disabled — a change to system settings, but justified for safety (LAN exposure). Mention in report.
Also potential issue: after future Windows reboot, the Ollama app autostarts (with HKCU OLLAMA_HOST=[REDACTED]) — works as long as firewall rules persist (they do) and adapter name stable.
Also verify: is the Ollama tray app still running fine (PIDs)? Quick check.
Let's do these in parallel batches.
$ {"command": "/mnt/c/Windows/System32/WindowsPowerShell/v1.0/powershell.exe -NoProfile -Command '\nGet-NetTCPConnection -
LISTEN :::11434 pid=15808 PROC 15808 :: ollama PROC 13236 :: ollama app OLLAMA_HOST(User)=hxxp://0.0.0.0:11434 FW_NEW enabled=True proto=TCP port=11434 intf=[vEthernet (WSL (Hyper-V firewall))] profile=Any FW_BROAD enabled=False name=ollama.exe FW_BR…
$ rm -f /mnt/c/Users/user/AppData/Local/Temp/fwcheck.ps1 /mnt/c/Users/user/AppData/Local/Temp/testlisten.ps1 /mnt/c/Users/
total 0 drwxrwxrwx 1 root root 4096 Oct 8 13:46 . drwxrwxrwx 1 root root 4096 Oct 8 13:48 .. temp cleaned zsh:1: no matches found: /mnt/c/Users/user/AppData/Local/Temp/*.ps1
Everything verified. Project folder still empty. Temp scripts cleaned.
Final report. Include the safety note about localhost vs [wsl-gw-ip], IP-change caveat, and what was changed. Keep reasonably concise but complete.
Also note: WSL app endpoint = hxxp://[wsl-gw-ip]:11434. And Windows-side uses localhost as before.
I should mention the two unexpected things found:
1. Pre-existing installer firewall rules (ollama.exe, any port/remote, Public) — now disabled (they would have exposed Ollama to the LAN).
2. New interface-scoped rule added.
Also note: no new UAC needed going forward; changes persist across reboots.
Include "how to check IP after WSL restart": ip route | awk '/default/{print $3}' → [wsl-gw-ip].
Concise summary now.
Root cause: WSL2 NAT doesn't forward WSL→Windows localhost; Ollama only listened on localhost; WSL's only route to Windows ([wsl-gw-ip]) was firewalled.
Changes made (3 total):
1. User env var OLLAMA_HOST = hxxp://[REDACTED]:11434 (HKCU, persists across reboots)
2. Restarted Ollama — now listening on :::11434 (all interfaces)
3. Firewall (via UAC):
- Added rule "Ollama 11434 (WSL adapter only)" — TCP 11434, inbound only via vEthernet (WSL (Hyper-V firewall))
- Disabled 2 pre-existing installer rules (ollama.exe, any port/any remote/Public) that would otherwise have exposed Ollama to your LAN
Verified from WSL (all against hxxp://[wsl-gw-ip]:11434):
- /api/version → {"version":"0.40.1"} ✅
- /api/tags → gemma4:e2b (4.58 GB) listed ✅
- Generation → "WSL GENERATION OK" ✅ (57s load, then normal)
- Windows-side localhost:11434 still works ✅
- Project dir still empty; temp scripts removed ✅
Safety: the only inbound path is the WSL-only virtual adapter; Wi-Fi/LAN/public remain default-deny. No internet exposure.
localhost (that's WSL itself).ip route | awk '/default/{print $3}'socat/forwards were added; no mirror-networking; nothing installed.You are going to build a new project called OfflineMode inside the currently opened folder.
The project folder is already:
D:\OfflineMode
OpenCode is running from WSL, while Ollama is installed and running on Windows.
Ollama is already installed. DO NOT install Ollama again.
Current Ollama:
- Version: 0.40.1
- Existing model: gemma4:e2b
- Model is already downloaded locally.
- Do NOT pull/download another model.
- Do NOT replace the existing model.
- Do NOT require any cloud AI API.
- The application must work without internet after setup.
WSL can reach Windows Ollama through:
hxxp://[wsl-gw-ip]:11434
The current WSL gateway can be checked with:
ip route | awk '/default/{print $3}'
Do NOT expose Ollama to the public internet.
Before making changes, inspect the existing environment and current folder.
The folder is intentionally empty. This is a NEW project.
OfflineMode
Do not rename the project.
The GitHub repository should eventually also be named:
OfflineMode
OfflineMode is an offline AI chatbot and experience companion designed to help people spend less unnecessary time on their phones and reconnect with real-world life.
The project is inspired by the idea of Touch Grass, but it should go deeper than simply telling people:
The problem we are addressing is broader.
People now use phones for almost everything.
They scroll instead of talking.
They watch instead of participating.
They order instead of making.
They record instead of experiencing.
They use technology during festivals instead of participating in the traditions around them.
In the past, people often spent more time:
For example, during festivals such as Diwali, families might spend time making decorations themselves, creating small things from मिट्टी/clay, painting and decorating them, lighting diyas, visiting relatives, meeting elders, touching their feet, helping with preparations, and simply spending time together.
Today, many of these activities are increasingly outsourced or replaced by passive phone usage.
OfflineMode should gently encourage people to participate in these real-world experiences again.
IMPORTANT:
This project should NOT criticize technology itself.
Technology is useful.
The message is:
Use technology when it helps you — but don't let it replace living.
OfflineMode should NOT try to keep users chatting with AI for a long time.
A normal chatbot tries to maximize conversation.
OfflineMode should do the opposite.
Its goal is:
User
↓
Talk to OfflineMode
↓
Receive a meaningful real-world activity
↓
Put the phone away
↓
Go experience it
↓
Come back later if they want
The AI should know when to stop talking.
A strong product philosophy is:
"An AI companion that helps you leave the screen."
Another possible tagline:
"Use the screen to find your way back to real life."
Do not force a tagline everywhere. Keep the interface simple.
This should NOT be only a chatbot page.
When the website opens, the user should see useful content immediately.
The homepage should feel like a calm, simple invitation to go offline.
The interface should NOT look like a corporate SaaS dashboard.
Avoid:
- excessive cards
- excessive gradients
- complicated charts
- unnecessary animations
- overly professional enterprise styling
- excessive icons
- unnecessary authentication
- complicated navigation
Keep it human, simple and warm.
The landing page can have something similar to:
You might just need something to experience.
Then a short explanation about the idea.
For example:
"Phones help us do almost everything today. But sometimes they also replace the small things that make life feel real — talking to family, making something with our hands, going outside, helping with preparations, sitting with someone, or simply watching the sunset without recording it."
Then a prominent action:
Start an Offline Moment
Other sections can include:
A randomly generated or locally generated activity.
Example:
Put your phone away for 20 minutes.
Sit with someone in your family and ask them about a festival they remember from childhood.
Don't record the conversation.
Just listen.
Button:
Try This
Include simple sections such as:
Explain the idea briefly.
Examples:
This section should feel nostalgic but NOT claim that the past was perfect.
Explain that offline time can be:
A special message:
"Some moments are better when nobody takes a picture."
This is an important concept.
OfflineMode can encourage users not to record every activity.
The chatbot is the core interactive feature.
The user should be able to say things naturally.
Examples:
"I am bored."
"I have 30 minutes."
"I am with my sister."
"I am at home."
"I don't want to use my phone today."
"What can I do with my family?"
"It's Diwali."
"I'm alone."
"I want to go outside but don't know what to do."
"I have no money."
"I have only 15 minutes."
"I want to do something creative."
The AI should understand the situation and suggest a realistic offline activity.
Use the existing local Ollama model:
gemma4:e2b
The AI should be instructed to:
The AI should be friendly and human, not robotic.
Responses should generally be short.
The goal is action, not a long AI conversation.
The AI should be able to suggest activities from categories such as:
When a festival is relevant, suggest participating rather than consuming content about it.
Examples:
Important:
Do not assume every user celebrates every festival.
Ask or infer carefully from the conversation.
OfflineMode should sometimes deliberately suggest:
"Don't take a photo."
Examples:
"Watch the sunset without photographing it."
"Talk to your grandmother without recording the conversation."
"Make something without making a reel about it."
"Eat with your family without checking your phone."
This is one of the project's central ideas.
When the AI gives an activity, provide a simple option to enter an activity mode.
Example:
Activity:
Make something with your sister/brother using whatever is available at home.
Time:
30 minutes
Rule:
No tutorials.
No reels.
No posting.
Try this:
Make something together and decorate it.
Button:
I'm Going Offline
After clicking it, the interface should encourage the user to put their phone away.
Optionally show a simple timer.
Do NOT make the timer overly complicated.
After an activity, the user can optionally return and answer a very small reflection.
Examples:
"How was it?"
Or:
"What did you notice?"
Keep reflection optional.
Do not turn it into a productivity tracker.
Do NOT add:
We are building something that helps people reduce screen dependency.
It would be contradictory to build another addictive engagement system.
The application must work without internet once the application and Ollama model are available.
Do not use:
The AI response must come from local Ollama.
The website itself should ideally be usable locally.
If external assets are not necessary, don't use them.
Prefer locally stored CSS/JS/assets.
The development machine has approximately:
Therefore:
DO NOT introduce unnecessarily heavy technologies.
Avoid:
- Docker unless absolutely necessary
- vector databases
- embeddings
- RAG
- computer vision
- speech recognition
- image generation
- additional local models
- large dependencies
- unnecessary background processes
Keep the project lightweight.
Choose a simple stack suitable for this machine.
A lightweight option is:
Frontend:
- HTML
- CSS
- JavaScript
Backend:
- Python
- lightweight HTTP server/framework if necessary
AI:
- Ollama REST API
- gemma4:e2b
However, if you believe another lightweight stack is significantly better, explain why before choosing it.
Do NOT introduce React/Next.js/etc. just because they are popular.
Use the simplest architecture that produces a good result.
Do not hard-code the Ollama host throughout the code.
Use an environment variable such as:
OLLAMA_BASE_URL
Current development value:
hxxp://[wsl-gw-ip]:11434
And:
OLLAMA_MODEL=gemma4:e2b
The WSL gateway may change after restart.
The application should therefore read the host from .env or environment configuration.
Before implementation, verify the API again.
The application should only communicate with the configured local Ollama endpoint.
Do not expose the chatbot API publicly.
Do not send user conversations to external services.
Do not collect unnecessary personal information.
Do not require precise location.
Simple.
Warm.
Human.
Minimal.
Not overly polished.
It should feel like a small thoughtful open-source project rather than a commercial SaaS application.
Use readable typography and comfortable spacing.
Avoid excessive animations.
Make it responsive for desktop and mobile browsers.
The main goal is usability and emotional connection, not visual complexity.
IMPORTANT:
Do NOT immediately generate hundreds of lines of code.
Follow this process:
Inspect the current folder and environment.
Propose a simple project architecture and file structure.
Explain why each major component is necessary.
Wait for confirmation before creating the complete implementation.
After confirmation:
Build the minimum working version.
Connect the chatbot to the existing Ollama instance.
Test local AI generation.
Test the complete user flow:
Homepage
→ Chat
→ Offline suggestion
→ Activity Mode
→ Go Offline
→ Optional Reflection
Test that the application works without internet.
Clean up the project and prepare:
.env.example.gitignoreEventually this will become an open-source GitHub project named:
OfflineMode
The repository should clearly explain:
Do not create the GitHub repository or push anything unless I explicitly ask you.
The project should communicate this idea:
We are not trying to escape technology completely.
We are asking:
What happens when technology becomes the default answer to everything?
OfflineMode is a small intervention.
Use AI to decide what to do.
Then stop using AI.
Go outside.
Talk to someone.
Make something.
Help someone.
Touch the soil.
Participate in a festival.
Listen to an elder.
Watch the sunset.
Play.
Create.
Be present.
The best possible outcome of OfflineMode is that the user closes the website.
Do not start implementing the chatbot immediately.
First inspect the environment and present:
Then wait for my approval before building.
The user wants me to plan the project. Step 1 is to inspect the existing environment and folder, verify the API again. Then present architecture, file structure, tech stack, etc. Then WAIT for approval before building.
Let me inspect the environment (folder empty already confirmed earlier, but re-check) and re-verify the API + gateway. Also check what Python packages/tools are available (no pip! venv exists though). This matters for the tech stack choice.
Let me do the inspection now.
Key considerations:
- pip is missing on python3.14. But we can use venv? venv module is available. But creating venv with python3.14, and then pip inside venv — does venv bundle pip? python3.14 venv typically includes ensurepip which installs pip into the venv. Actually python -m venv runs ensurepip — need ensurepip module present. Let me check python3 -c "import ensurepip". If missing, no pip even in venv. Alternative: avoid dependencies entirely — use stdlib-only Python HTTP server (http.server) with a custom handler, or Node.js (npm exists!) which has no dependency needed either.
Actually Node is v22 and npm 10.9. Could do a zero-dependency Node http server. Or Python stdlib. The user suggested Python backend but allowed alternative if significantly better.
Consider: Python with stdlib http.server — zero deps, no pip needed. But http.server is single-threaded by default and basic; we can subclass ThreadingHTTPServer. For a local tool this is fine. Alternatively Node: node with a plain http server, or use Express (needs npm install — internet? "must work without internet after setup" — setup can happen online, but they said don't require cloud. npm install of express would need internet at setup time; but "do not use internet" was for runtime/testing. Still, minimal deps preferred).
Better: zero-dependency approach with stdlib. Python's http.server with ThreadingHTTPServer + a simple router serving static files + /api/chat endpoint that proxies to Ollama. That avoids all dependency issues including missing pip. Frontend: plain HTML/CSS/JS, no external assets (system fonts, local CSS/JS).
But wait — Node also stdlib zero-dep. Which is better for this machine? Python 3.14.6 exists. Node 22 exists. Python has httplib/urllib for proxy. Node has fetch built-in. Both fine.
The user leaned Python ("Backend: Python, lightweight HTTP server/framework if necessary"). I'll recommend Python stdlib (no framework, no deps) with a clearly stated fallback. Since pip is missing, stdlib-only is the safest. Actually, I should double check ensurepip presence — it affects whether we could even use deps later. Let me check.
Also verify: Ollama reachable at gateway, /api/version and /api/tags. Model name gemma4:e2b.
Also check ip route gateway still [wsl-gw-ip].
Also confirm folder empty again.
Let me also think about the config: OLLAMA_BASE_URL env var, .env loading. Since we want zero deps, a .env parser in Python is ~10 lines (don't use python-dotenv). Or use environment variable with default fallback detection. User said: "The application should therefore read the host from .env or environment configuration." So implement lightweight .env reader.
One more: CORS — the frontend served by same server, so no CORS issues if chat endpoint same origin. Good. If someone opens static file directly (file://), fetch to localhost backend would need CORS; serve over http instead. Keep single-origin.
Also security: bind server to localhost (not [REDACTED]) so it's not exposed on LAN. Good — align with "do not expose chatbot API publicly".
Let me think about whether to recommend Python HTTP server via http.server with a sub-classed ThreadingHTTPServer + simple routing. There's a subtlety: http.server's SimpleHTTPRequestHandler does static serving well. I'll create a custom handler: serve static files from a static/ dir, and handle POST /api/chat by forwarding to Ollama's /api/chat (or /api/generate).
Model inference: Use Ollama's /api/chat endpoint with a system prompt. Streaming: could stream from Ollama to client (SSE or chunked JSON). Keep simple: non-streaming first (get JSON), or streaming via reading Ollama's NDJSON stream and forwarding. Streaming is nicer UX (model is slow on CPU, ~6 tok/s). Actually with CPU-only and ~57s load, non-streaming would make users wait a long time with a spinner. Streaming to the UI (word by word) gives immediate feedback after load. Ollama /api/chat with stream:true returns NDJSON. Forwarding via HTTP from Python: read chunks, push to client. Doable with stdlib. Or SSE. I'll propose streaming with a simple approach; but keep "minimum working version" as maybe streaming.
Let me not over-decide; present architecture and let them approve.
Also reflection: store locally in browser (localStorage) or a simple JSON file. "Do not turn it into a productivity tracker." Keep reflection ephemeral/localStorage. No database. If persistence to file, a simple JSON append is fine; no DB.
Also "go offline" timer: frontend-only setInterval; no backend.
Structure proposal:
OfflineMode/
├── server.py # stdlib HTTP server: static + /api/chat proxy to Ollama
├── .env.example # OLLAMA_BASE_URL, OLLAMA_MODEL, OLLAMA_PORT
├── .env # (gitignored) actual config
├── .gitignore
├── README.md
├── requirements.txt # empty / none (stdlib only) — maybe a note
├── static/
│ ├── index.html
│ ├── style.css
│ └── app.js
└── data/ (optional, .gitignore'd) # reflections JSON (local, optional)
Hmm, static content sections are in index.html.
Now, the "Start an Offline Moment" button → goes to chat or directly shows a random activity ("Today's Offline Idea" uses OLLAMA too, or a local curated list?). The prompt says "A randomly generated or locally generated activity." Two options: (a) curated local activities list pick a random one (works offline, instant, zero AI) — good for landing without loading model, (b) AI-generated. I'd do: landing "Today's Offline Idea" = local curated random (instant, no AI cost); chat + "Start an Offline Moment" uses AI. Actually the homepage idea button could also call AI. But mixing local curated ideas is nice and demonstrates offline. I'll propose: homepage shows a curated local idea by default, with a "Try This" that can go into Activity Mode directly or optionally ask AI to refine. Keep simple: homepage = curated random; chat = AI. Good.
Let me also plan the AI system prompt (concise, hitting the 16 rules) and the response format. For Activity Mode, the chat suggests an activity (title, time, rule) — maybe ask model to return a compact structured suggestion plus natural text. Simplest: model returns natural text; UI has a single "I'm Going Offline" button that starts timer; user can type it. For activity mode fields, we could ask model to follow a light format: "Activity: ... / Time: ... / Rule: ..." and parse. That adds fragility with a 4.6B model. Alternative: keep natural short text; Activity Mode just captures the latest suggestion text and starts timer. But spec wants Activity/Time/Rule display. We can prompt model to output 3 short labeled lines; parse leniently (match "Activity:", "Time:", "Rule:" optional). Fallback: whole text as activity.
I'll mention this in the plan: structured-yet-lenient parsing of suggestion into Activity/Time/Rule, always sending the full text too.
Also mention how to handle: the model is 4.6B Q4 on CPU, slow; keep context short; num_predict limit (~150-250), temperature ~0.7, no internet. Also keep_alive default 5m from env; we won't set.
Now, before building, verify environment again per "Before implementation, verify the API again." Let's run the checks.
Also check python3 ensurepip, available free RAM, gateway.
Let me run inspection commands in parallel.
Note about the todo list: The task will have many steps but the current instruction is only to plan (steps 1-4). I'll create a todo list? The immediate deliverable is a plan presented for approval. Maybe not necessary to use todowrite now; but the overall project is multi-step. The guidance says use todos for 3+ steps. I'll hold off until approval; planning phase is single deliverable. Actually, I could set up todos reflecting the 10 dev steps. But until approval, work is "inspect + present plan". I'll keep it minimal and not use todos yet — or use them to track the pending approval. I think creating todos now is reasonable to track the project phases. I'll create a todo list after approval. For now just present plan. Hmm, the current step the user asked is only present plan and wait. Presentations aren't tracked by todos meaningfully. Skip todos.
Let me inspect.
$ {"command": "echo \"=== folder ===\"; ls -la /mnt/d/OfflineMode; echo \"=== gateway ===\"; ip route | awk '/default/{pri
=== folder === total 0 drwxrwxrwx 1 root root 4096 Oct 8 13:46 . drwxrwxrwx 1 root root 4096 Oct 8 13:48 .. === gateway === [wsl-gw-ip] === ollama version === {"version":"0.40.1"} === tags === {"models":[{"name":"gemma4:e2b","model":"gemma4:e2b","mo…
$ {"command": "python3 --version; python3 -c \"import ensurepip; print('ensurepip OK')\" 2>&1; python3 -c \"import venv; p
Python 3.14.6 ensurepip OK venv OK stdlib http OK v22.19.0 10.9.3 total used free shared buff/cache available Mem: 3.5Gi 1.2Gi 2.0Gi 3.2Mi 441Mi 2.3Gi
Environment confirmed:
- Folder empty.
- Gateway still [wsl-gw-ip].
- Ollama /api/version 0.40.1, model gemma4:e2b present.
- Python 3.14.6 with stdlib http, ensurepip OK (venv would work, could pip install if needed), Node 22, npm 10.9.3.
- RAM in WSL: 3.5Gi total, 2.3Gi available.
Now present the plan (architecture, file structure, tech stack, integration, sections, behavior, flows, offline approach, resources, dev steps). Wait for approval. No building.
I should keep it reasonably concise but comprehensive — this is a legitimately detailed plan request. Use headings. Don't build.
Decisions to communicate:
- Tech stack: Python 3.14 stdlib only, zero dependencies (no framework), because pip isn't even needed and machine is RAM-constrained. ThreadingHTTPServer + static + /api/chat proxy to Ollama. Justify vs Node.
- Server binds localhost (not exposed to LAN; satisfies security).
- Config via .env (small hand-rolled loader) + env vars. OLLAMA_BASE_URL default = current gateway? Or require .env. Provide .env.example with OLLAMA_BASE_URL and OLLAMA_MODEL=gemma4:e2b, port OLLAMA_APP_PORT. Gateway auto-detect fallback? Keep explicit env with example value; detect gateway only as fallback if env missing? Simpler: env file is source of truth; README explains the ip route command. Maybe a tiny convenience: server logs the detected gateway if env not set. I'll propose: .env sets OLLAMA_BASE_URL=hxxp://[wsl-gw-ip]:11434 and OLLAMA_MODEL=gemma4:e2b. Good.
- Frontend: single index.html + style.css + app.js, system fonts, no external assets, no framework. SPA-ish with hash-based views: Home, Chat, Activity Mode, Reflection. All localStorage for reflection.
- AI: /api/chat with system prompt, stream:true forwarded as NDJSON→ chunked to client (textarea streaming). Keep num_predict modest, temperature 0.7-0.8, context trimmed to last ~8 turns to keep CPU load low. Light structured output for Activity/Time/Rule with lenient parse.
- "Today's Offline Idea" on homepage: local curated list (no AI) — instant, works fully offline; optional "Ask AI for something better" not needed; keep simple. Also "Start an Offline Moment" → chat with example prompts.
- Activity Mode: after AI recommends, button "I'm Going Offline" → full-screen "put your phone away" + optional simple timer (count up/choose duration). Frontend-only.
- Reflection: optional, after returning; a few mood chips + one-line note saved to localStorage (not a tracker). Optional export? no.
- No auth, no analytics, no external calls. Server logs only local.
- Files to create listed.
- Cleanup/deliverables: README, .env.example, .gitignore, requirements (empty stdlib—actually provide requirements.txt with comment or none; I'll include a note file? user asked "requirements file if needed" — since zero deps, mention not needed, maybe provide empty requirements.txt for clarity. I'll say optional/empty).
- Testing steps incl. offline test (stop internet — simulate by disabling? test without calling external; verify no external requests; run server, block network in WSL? A simple offline test: ensure page + ideas + chat work with internet disabled is tricky on dev box; we can test by pointing OLLAMA_BASE_URL to local and confirming no external deps. Also test that if we disconnect access to ollama.com it still works. We'll do a functional offline check.)
Also note resource: model load ~57s first time CPU-only.
Present now. Ask: does this plan meet approval? Provide the numbered items 1-10 as requested.
Keep structured but not bloated.
Environment confirmed: folder empty, gateway still [wsl-gw-ip], Ollama 0.40.1 responding with gemma4:e2b present, Python 3.14 (stdlib ok, venv+ensurepip available), Node 22, ~2.3 GiB available. No files were created.
Here is the plan — no code written until you approve.
Python 3.14 stdlib only (zero dependencies) — http.server.ThreadingHTTPServer + a custom handler. Rationale:
- This box has ~2.3 GiB free RAM and no GPU; a framework (FastAPI/Flask) or Node/Express adds nothing we need and adds deps.
- pip is absent; stdlib-only means nothing to install (good for "works offline after setup").
- One process, no build step, no node_modules, runs on Windows machine just as well.
- Frontend is plain HTML + CSS + JavaScript (no framework), served as static files, no CDN/external assets, system fonts.
Backend stays a thin proxy: serve static files + one endpoint /api/chat that forwards to local Ollama. No cloud, no DB, no embeddings, no extra models.
OfflineMode/
├── server.py # stdlib HTTP server: static files + /api/chat proxy to Ollama
├── .env.example # OLLAMA_BASE_URL, OLLAMA_MODEL (committed)
├── .env # real config (gitignored)
├── .gitignore
├── README.md
├── requirements.txt # empty/stdlib note (kept for clarity, no installs)
└── static/
├── index.html # whole UI: Home / Chat / Activity / Reflection views
├── style.css # warm, minimal, responsive
└── app.js # views, chat streaming, timer, reflection
No database. Reflections live in the browser (localStorage) only — intentionally not a tracker.
OLLAMA_BASE_URL/api/chat, streams the reply back word-by-word (important because CPU inference is slow; a spinner for 57s would feel broken).OLLAMA_BASE_URL (default from .env; .env.example → hxxp://[wsl-gw-ip]:11434) and OLLAMA_MODEL=gemma4:e2b./api/chat with stream:true, and forwards the NDJSON stream to the browser.num_predict capped (~200), temperature ~0.7, history trimmed to the last few turns to protect CPU/RAM.localhost only.Hero (OfflineMode · "Maybe you don't need another thing to watch…" + Start an Offline Moment) → Today's Offline Idea (random pick from a local curated list, instant, no AI) → Why OfflineMode? → Things We Used To Do (nostalgic list, with a "the past wasn't perfect" line) → Offline Doesn't Mean Doing Nothing (creative/social/physical/cultural/peaceful) → No Need To Capture Everything ("Some moments are better when nobody takes a picture.").
Free-text input; the packaged examples (15 mins / family / Diwali / no money / alone / creative, etc.) as suggested chips. Response is short, concrete, money/internet-free, varied across Nature/Family/Friends/Creativity/Festivals/Simple Life, never preachy, never therapist-like, ends with a reason to put the phone down.
AI reply → user taps I'm Going Offline → quiet fullscreen "put it away" screen with a simple optional timer (count up / pick duration, one button) → later Reflection: a few mood chips ("Nice / Peaceful / Fun / …") + one short line, saved to localStorage, nothing tracked or gamified.
[wsl-gw-ip], never ollama.com).One Python process (~30–60 MB), one Ollama process (already running). Frontend fully static. No installs, no build, no npm. First AI call still needs ~55s model load on CPU; streaming keeps it tolerable.
server.py, .env, .gitignore, empty requirements.txt.index.html + style.css UI (all sections, all views)./api/chat to Ollama; verify a streaming local generation (already proven reachable).README.md/.env.example with run, Ollama config, and contribution notes.Notes before you approve:
- I'll bind the app to localhost:8080 (not [REDACTED]) — safe and not exposed.
- .env will also be copied to .env.example values so first-run just works; the ip route command stays documented for when the gateway changes.
- No tweak of Ollama; no new models; no extra languages/frameworks.
Approve and I'll build the minimum working version.
Approved. Proceed with the implementation using the proposed architecture and file structure.
Before coding, apply these five adjustments:
Keep .env gitignored and provide .env.example. Never commit secrets or machine-specific configuration.
Keep Ollama streaming enabled because CPU inference is slow. However, the browser should not directly communicate with Ollama or receive raw Ollama-specific NDJSON. server.py should act as the local proxy and convert the Ollama response into a clean browser-consumable stream.
Do not force every chatbot response into exactly three fields. OfflineMode should support natural conversation as well as structured activity suggestions.
For example:
User:
"I am feeling bored and my parents are at home."
The AI should be able to respond naturally and then suggest a practical offline activity.
When an actual activity is detected, the UI may extract/display:
- Activity
- Time
- Optional Rule
But the underlying chatbot should remain flexible.
Keep "Today's Offline Idea" completely local and curated in JavaScript/HTML so it works instantly without Ollama and without internet.
Do not assume a user's festival, culture, family structure, religion, or traditions. Festival-related suggestions should be contextual and respectful. If the user mentions a festival or tradition, the AI can adapt the suggestion accordingly.
Additional implementation requirements:
Use:
OLLAMA_BASE_URL=hxxp://[wsl-gw-ip]:11434
OLLAMA_MODEL=gemma4:e2b
through environment configuration rather than hard-coding these values throughout the application.
Bind the local application to:
localhost:8080
Do not expose the application publicly.
The UI should remain simple, warm, human and responsive rather than looking like a commercial SaaS dashboard.
The main product principle must remain:
"Use the screen to find something worth experiencing, then close the screen."
The chatbot should not encourage prolonged AI conversations.
Proceed with the minimum working version and test the complete flow:
Home
→ Chat
→ Offline suggestion
→ Activity Mode
→ Go Offline
→ Optional Reflection
After implementation, report:
1. Files created
2. How to run the application
3. Ollama configuration used
4. Tests performed
5. Any issues or limitations
6. Approximate resource usage
Do not add features beyond the approved scope without explaining why they are necessary.
Let me plan the implementation. I need to build:
server.py — stdlib HTTP server serving static files + /api/chat proxy to Ollama, converting NDJSON stream to clean browser stream format..env.example and .env (gitignored).gitignorerequirements.txt (empty/stdlib note)README.mdstatic/index.html, static/style.css, static/app.jsLet me set up a todo list for this multi-step task.
Design decisions:
server.py:
- Load .env (tiny parser). Read env vars OLLAMA_BASE_URL, OLLAMA_MODEL, HOST/PORT (APP_HOST=localhost, APP_PORT=8080).
- ThreadingHTTPServer with a custom handler.
- GET / → serve static/index.html; static assets from static/ dir.
- POST /api/chat → receives JSON {messages: [...]} from browser → POST to Ollama /api/chat with stream:true, messages = system prompt + user messages. Stream NDJSON back to browser as SSE-like events: data: {"text": "..."}\n\n or a simpler chunked JSON. Simplest clean format: each response chunk is data: <text> or just send JSON lines. Let me use Server-Sent Events style: event: token / event: done. Actually simplest: send lines {"delta":"...","done":false} newline-delimited; browser reads via fetch ReadableStream and parses lines. That's clean and browser-consumable. Include final {"done":true}.
Also need to handle Ollama errors (connection refused → friendly error message JSON, status 502 or 200 with error flag). Return a clean error event.
/api/health endpoint? Useful for README/debug. Keep minimal — maybe a simple GET /api/health returning {"ok":true,"model":"..."}. That's within scope for testing. Explain necessity? It's minor; helpful for connectivity check. I'll add it and mention it (helps verify Ollama connectivity from app). Fine.System prompt for the AI: encode the 16 rules, flexible structured suggestion. Ask the model: respond naturally and briefly; if you suggest an activity, you may include a short "Activity:", "Time:", "Rule:" block. Make clear not every message needs a structured block.
Streaming format decided: I'll send NDJSON lines to browser: {"delta":"...","finished":false} and final {"finished":true}. Browser reads response.body, splits on newlines.
Actually, to parse cleanly with stdlib, Ollama /api/chat with stream:true returns newline-delimited JSON objects each with message.content (incrementally) and a final done:true. I'll iterate lines, parse json, extract content delta, forward.
Also, keep history: browser sends full message history (array of {role, content}) including the user's messages and previous assistant replies. Server prepends system prompt and forwards. Trim in client (max ~10 messages) to protect CPU.
index.html: sections:
- Nav: simple (OfflineMode + "Start an Offline Moment").
- Home view:
- Hero: title, tagline "Maybe you don't need another thing to watch. You might just need something to experience." short paragraph. Button "Start an Offline Moment".
- Today's Offline Idea: local curated list in JS, a card displays one, "Another idea" button to shuffle, maybe not too many buttons.
- Why OfflineMode?
- Things We Used To Do (list)
- Offline Doesn't Mean Doing Nothing (list of qualities)
- No Need To Capture Everything ("Some moments are better when nobody takes a picture.")
- Chat view: message thread, input box, prompt chips, streaming response. After an assistant suggestion, "I'm Going Offline" button appears.
- Activity view: The suggestion (Activity/Time/Rule extracted or whole text), "I'm Going Offline" button → transitions to "offline screen" with timer.
- Offline screen view: quiet, "Put your phone away", timer (start/pause/reset or countdown to chosen minutes). "I'm back" button → Reflection view.
- Reflection view: chips (Nice, Peaceful, Fun, Unexpected, Boring, I want to do it again), optional short text "What did you notice?", save to localStorage, "Done / Back home". Show "Saved locally. Not tracked anywhere."
Views switching via JS manipulating sections (hidden). Keep simple.
Timer: choose duration chip (10/20/30/45/60) or free count-up. Countdown showing remaining time; when done, "time's up" gentle message. Keep simple: a countdown timer with start/pause, presets.
CSS: warm palette (cream/soft brown/terracotta/off-white), system serif for headings (Georgia, 'Times New Roman') + system sans for body? A warm human feel: use a serif for headings, generous line-height, max-width ~680px, rounded but not card-heavy. Minimal borders, warm background (#faf6f0), text #3d3a33. Avoid heavy shadow/gradients. Responsive with simple media queries. Little animation (gentle fade).
"avoid excessive cards" — I'll use simple blocks with subtle border/background, not floating gradient cards.
app.js structure:
- const OLLAMA_MODEL not in client.
- Chat calls POST /api/chat with {messages}.
- Local curated ideas array (~12-15 entries across categories, reflects the teacup values: family, nature, creativity, festivals contextually — avoid assuming specific festivals; use phrases like "if there's a festival or celebration coming up...").
- Activity extraction: from last assistant streamed text, regex match Activity:..., Time:..., Rule:... optional; if none, use whole message text as activity with generic time "When you're ready".
- localStorage: offlinemode_reflections array with {date, mood, note}.
README.md: project explanation, why local AI, how to run, Ollama config, offline notes, contribution. Also handle: default OLLAMA_BASE_URL for WSL gateway may change.
.env.example: OLLAMA_BASE_URL=hxxp://[wsl-gw-ip]:11434, OLLAMA_MODEL=gemma4:e2b, APP_HOST=localhost, APP_PORT=8080.
.gitignore: .env, pycache/, *.pyc, .DS_Store, node_modules (just in case), logs.
requirements.txt: a comment saying stdlib only, no installs needed.
Now let me think about the streaming implementation in Python carefully.
Ollama /api/chat request:
json
{
"model": "gemma4:e2b",
"messages": [{"role":"system","content":"..."}, {"role":"user","content":"..."}],
"stream": true,
"options": {"temperature": 0.7, "num_predict": 240}
}
Response: NDJSON stream, each line: {"model":..., "message":{"role":"assistant","content":"..."}, "done":false} ... final {"done":true,...}. Some responses include context.
Python handler:
- read content-length body, json parse {messages: [...]}.
- build request with system prompt prepended.
- urllib.request.Request(url, json data bytes, headers).
- response = urlopen; read line by line.
- For each line: parse json, get message.content delta; write to wfile: a clean NDJSON line {"delta": "...", "finished": false}\n, flush.
- On done line: write {"finished":true} line.
- Handle HTTPError/URLError: send 502 with JSON error containing friendly message + also maybe include the raw error as {kind:"error", message}. Browser shows friendly "Couldn't reach Ollama. Is it running? (...)"
Headers: Content-Type application/json. Set CORS? Same origin so no need. But for dev maybe allow? No, keep same-origin.
One issue: ThreadingHTTPServer + streaming with flush — need to use wfile.flush() after each write, and ensure chunked or Content-Length? Since we don't know length ahead, we must either use Transfer-Encoding: chunked (HTTP/1.1) or close connection to signal end. BaseHTTPRequestHandler with HTTP/1.1 — it doesn't do chunked automatically; for streaming responses, we set protocol_version = 'HTTP/1.1' and write without content-length and... Actually BaseHTTPRequestHandler will attempt to compute Content-Length; if we don't set it and use HTTP/1.1, client may wait. Common trick: set self.close_connection = True after streaming and use HTTP/1.0? With HTTP/1.0, connection close signals end. But fetch works fine with HTTP/1.0 without content-length.
Let me set protocol_version = 'HTTP/1.1' and send Content-Type: application/x-ndjson and Transfer-Encoding: chunked? Implementing chunked manually is a bit of work but straightforward: write chunk header hex length \r\n then chunk \r\n, and 0\r\n\r\n at end. That's clean and lets fetch stream. Alternatively HTTP/1.0 + connection close (set self.close_connection=True). The browser's fetch will read until close. Both fine. NDJSON over HTTP/1.0 with connection close is simplest and reliable. But HTTP/1.0 with keep-alive issues? We set protocol_version='HTTP/1.0' and after done, the handler closes connection. That works with fetch.
However, one subtlety: BaseHTTPRequestHandler in http.server — if protocol_version is 'HTTP/1.0', the default Connection header would be 'close'. Good. Let me do that for the streaming chat route. For static files, normal behavior.
Actually, I could also just use HTTP/1.1 with chunked transfer encoding — slightly cleaner semantics. Let me implement chunked properly; it avoids potential buffering issues. Hmm, but flush must ensure bytes go out. Let me write a helper:
def _stream_chunk(self, chunk_bytes):
if chunk:
size = format(len(chunk), 'x')
self.wfile.write(size.encode('ascii') + b'\r\n' + chunk + b'\r\n')
else:
self.wfile.write(b'0\r\n\r\n')
self.wfile.flush()
And set header Transfer-Encoding: chunked. The browser fetch reads decoded body stream.
I think this is fine and clean. I'll use HTTP/1.1 + chunked for /api/chat.
Now, NDJSON parsing from Ollama: Ollama streams may include a long initial delay (model load ~55s). The connection stays open; browser shows "thinking...". Fine.
Potential issue: urllib.urlopen stream reading line by line using for line in resp: — resp is a file-like object supporting iteration; newline-delimited works. But requests to Ollama could be slow to first byte (model loading). No timeout or a long timeout. Set timeout maybe 600s.
Also: httptimeout for connect — the gateway unreachable would raise quickly or hang? urllib with timeout raises on connect timeout. Set timeout=5 for connect? urllib's timeout applies to whole read? It's a socket timeout — applies per socket operation. Set timeout=30; error path handled.
Edge: model name from env; if Ollama returns error JSON (e.g., model not found), it'd be in headers status 4xx with JSON body. Our urlopen raises HTTPError; read body, forward as friendly error.
Test plan after build:
- Start server, http-get static index.
- http-get /api/health.
- http-get /api/chat with a message, verify streaming NDJSON arrives and final done, and check it returns the friendly format (non-Ollama JSON).
- "Offline" check: ensure index.html has no external URLs (grep for http/https in static). Ensure no CDN.
- Full flow test via browser? We can't click; we can simulate by scripting? We can at least verify endpoints and the JS logic by node? Eh. We'll do endpoint-level tests + a headless check of JS syntax with node (node --check app.js). And verify HTML references local files.
- Also test offline by temporarily using an invalid OLLAMA_BASE_URL? Not needed. Better: confirm app makes no outbound calls besides gateway. We can test by grepping.
- Resource usage: ps for the python server RSS; measure.
Also generation test for actual chat: send "I'm bored and my parents are home." Verify a reasonable response streams (this takes ~55s model load). Acceptable.
Let me be careful about the "report approximate resource usage": measure server.py RSS via ps after running a request (loading Python doesn't load model into our process; Ollama process holds model). Report server RSS (~20-40MB), and note Ollama already running.
Let me also handle the reflection "how was it" chips.
Also the "Things We Used To Do" list should not claim past perfect — add a soft line.
Now think about system prompt text (concise, covering 16 rules):
You are OfflineMode, a warm and simple AI companion whose only job is to help people get back to real life. You give one practical, realistic offline activity and then encourage them to close the screen and do it.
Rules:
- Be brief and human, like a kind friend. 2-5 sentences is usually enough.
- Suggest one concrete activity, not a list of many.
- Favor activities that are free or nearly free and need no internet.
- Vary suggestions: nature, family, friends, creativity, hand-made things, simple life, conversation, helping someone.
- Never make every suggestion about walking outside.
- Ask about or respect the person's situation (who they're with, how much time, where they are, how they feel).
- Never assume the user's culture, festival, religion, family structure, or traditions. Only bring up a festival or tradition if the user mentions one; then suggest participating respectfully.
- Never shame the user for using technology. Never say technology is bad.
- Don't act like a therapist. Don't diagnose. If someone sounds distressed, gently encourage a real conversation with a trusted person.
- Never tell them to stay and chat with you. Give them a reason to go do the activity.
- If you suggest an activity that involves a phone rule (no photos, no recordings, no tutorials), one short line is enough.
If you suggest a concrete activity, you may end with three short optional lines so it is easy to read:
Activity: <name>
Time: <e.g. 20 minutes>
Rule: <optional, e.g. No photos>
Only include Activity/Time/Rule when you actually suggest a specific activity. Otherwise just respond naturally.
Time to code. Let me define file structure and write files.
Let me now also think: the user said "convert the Ollama response into a clean browser-consumable stream." I'll define NDJSON of {"delta": "...", "finished": false} and final {"finished": true}... maybe include a full accumulating text? Browser already accumulates. Fine.
Also, the extraction of Activity/Time/Rule in JS from the accumulated text with regex.
Now potential issue: when writing chunked streaming to fetch, header Transfer-Encoding: chunked with HTTP/1.1. BaseHTTPRequestHandler: I must not set Content-Length. Good.
Also each log: override log_message to a quiet format to /dev/null? Keep minimal logging (console). Maybe log chat requests and errors to stdout. Light.
Let me handle static file serving: use SimpleHTTPRequestHandler? It serves a directory and would serve index.html at root. But we need POST /api/chat. I'll subclass SimpleHTTPRequestHandler? SimpleHTTPRequestHandler serves from directory. I can subclass it and override do_POST... but do_GET for '/' returns index.html automatically. However SimpleHTTPRequestHandler uses HTTP/1.0 default? It uses its own. Let me just subclass SimpleHTTPRequestHandler, set directory to static/, override do_POST for /api/chat, and do_GET for /api/health. That gives static file serving + directory listing disabled? Directory listing enabled by default on '/', but '/' maps to index.html automatically. To avoid listing, keep fine (it's localhost). Actually SimpleHTTPRequestHandler directory param exists (3.7+).
Path traversal: SimpleHTTPRequestHandler confines to directory. Good.
But wait: I want the streaming to be chunked HTTP/1.1. SimpleHTTPRequestHandler serves files with HTTP/1.0. For the chat route I control headers. It's fine to keep server protocol 1.0 for static and set per-response. Actually SimpleHTTPRequestHandler default protocol_version = 'HTTP/1.0'. That works for both. For /api/chat streaming with connection close, I'd use protocol 1.0 + no content-length + then close. That's simplest! fetch handles it. Let me do that: for chat, don't set content-length, set Content-Type application/x-ndjson, write all NDJSON lines with flush, then self.close_connection = True at end (or since protocol 1.0, connection closes by default after response — but keep-alive could be requested; set Connection: close header explicitly).
Hmm, but there's a subtlety: with HTTP/1.0 + no Content-Length, the client (Chrome fetch) treats it as indefinite stream until close. Chrome handles it (reads until EOF). Yes.
Decision: subclass SimpleHTTPRequestHandler, protocol_version='HTTP/1.0'. For /api/chat: send_response(200), Content-Type: application/x-ndjson; charset=utf-8, Connection: close. wfile.write lines + flush. End (connection closes).
Actually wait, does SimpleHTTPRequestHandler override send_response to add Server header etc.? Fine.
Let me write server.py.
#!/usr/bin/env python3
"""OfflineMode - local server (Python stdlib only)."""
import json
import os
import re
import sys
import urllib.error
import urllib.request
from http.server import SimpleHTTPRequestHandler, ThreadingHTTPServer
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
STATIC_DIR = os.path.join(BASE_DIR, "static")
SYSTEM_PROMPT = """..."""
def load_env(path):
env = {}
if os.path.exists(path):
with open(path, "r", encoding="utf-8") as f:
for line in f:
line = line.strip()
if not line or line.startswith("#") or "=" not in line:
continue
key, _, value = line.partition("=")
env[key.strip()] = value.strip().strip('"').strip("'")
return env
OLLAMA_BASE_URL = os.environ.get("OLLAMA_BASE_URL", env.get("OLLAMA_BASE_URL", "hxxp://[wsl-gw-ip]:11434"))
OLLAMA_MODEL = ...
APP_HOST, APP_PORT from env.
Wait: requirement says use env configuration rather than hard-coding. Provide sensible default matching current dev value but documented. I'll default to the example value only as fallback, clearly in .env.example. Actually to avoid hard-coding default in code, we could require env; but convenience: default fallback is fine and equals current dev. The user explicitly said OLLAMA_BASE_URL=hxxp://[wsl-gw-ip]:11434 through environment configuration rather than hard-coding throughout the app. So the app reads env; a fallback constant is acceptable but better to not hard-code. I'll make the code load from .env; if absent, error or fallback? To be truly "not hard-coded", I'll provide default in .env.example and env loader defaults only to the .env file; if missing, maybe auto-detect gateway via ip route? That's clever but machine-specific functionality. Simpler: if env var not set, default to "hxxp://localhost:11434"? That's wrong for WSL. Hmm.
I'll do: constant default DEFAULT_OLLAMA_BASE_URL = "hxxp://localhost:11434" would be wrong in NAT WSL. Actually could try localhost first then gateway? Too clever.
Pragmatic: read from env or .env; if neither set, try to detect default gateway (only on Linux) via ip route, fallback to localhost. That's small and genuinely helpful (addresses "WSL gateway may change after restart"). It's ~8 lines. I think auto-detection default is a nice touch and keeps "not hard-coded." Let me include:
def detect_default_gateway():
try:
out = subprocess.check_output(["ip", "route"], text=True)
for line in out.splitlines():
parts = line.split()
if "default" in line and "dev" in line:
idx = parts.index("dev")
return f"hxxp://{parts[idx-1]}:11434"
return None
except Exception:
return None
Hmm subprocess from stdlib fine. Provide final fallback hxxp://localhost:11434.
Then server prints detected config at startup.
Handler:
do_POST only for /api/chat (else 404). Parse body:
python
length = int(self.headers.get("Content-Length", 0))
raw = self.rfile.read(length) if length else b""
data = json.loads(raw or b"{}")
messages = data.get("messages") or []
Validate messages is list; build ollama payload:
json
{"model": OLLAMA_MODEL, "stream": True, "messages": [{"role":"system","content":SYSTEM_PROMPT}] + messages, "options": {"temperature": 0.7, "num_predict": 240}}
Request:
python
req = urllib.request.Request(
urljoin(base, "/api/chat"),
data=json.dumps(payload).encode("utf-8"),
headers={"Content-Type": "application/json"},
method="POST",
)
Stream:
python
self.send_response(200)
self.send_header("Content-Type", "application/x-ndjson; charset=utf-8")
self.end_headers()
try:
with urllib.request.urlopen(req, timeout=600) as ollama_resp:
for raw_line in ollama_resp:
line = raw_line.strip().decode("utf-8", "replace")
if not line: continue
try:
obj = json.loads(line)
except ValueError:
continue
if obj.get("done"):
self._send_line({"finished": True, "error": None})
break
delta = obj.get("message", {}).get("content") or ""
if delta:
self._send_line({"delta": delta, "finished": False})
except urllib.error.URLError as e:
self._send_line({"error": f"Could not reach Ollama at {OLLAMA_BASE_URL}. Is the Ollama server running? ({e.reason})"})
except Exception as e:
self._send_line({"error": f"Ollama error: {e}"})
finally:
self.wfile.flush()
Wait, if an early error occurs before send_response? I send_response(200) first, then stream data. For an error event we send {"error": message} line; client treats as error. But maybe better to return HTTP 502 for connect errors before any 200? If we send 200 then error line, browser classifies as streamed error — UI shows message. Simpler UX: send 200 always, error as an event. Hmm, but if model invalid or auth... For robustness, do: attempt urlopen first to catch connection errors → if fails, return 502 JSON with {error}. But streaming model-load delay means urlopen returns headers immediately (response object) even while model loads. So pattern: try urlopen; if URLError/HTTPError → send 502 {error}. Else send 200 + stream. That's cleaner (distinguishes connectivity vs model errors). HTTPError from Ollama (e.g., 404 model not found): forward its body as error.
Let me do that:
try:
ollama_resp = urllib.request.urlopen(req, timeout=600)
except urllib.error.HTTPError as e:
body = e.read().decode("utf-8", "replace")
self._send_json_error(e.code, f"Ollama returned HTTP {e.code}: {body[:200]}")
return
except urllib.error.URLError as e:
self._send_json_error(502, f"Could not reach Ollama at {OLLAMA_BASE_URL}. {getattr(e, 'reason', e)}")
return
self.send_response(200)
self.send_header("Content-Type", "application/x-ndjson; charset=utf-8")
self.send_header("Connection", "close")
self.end_headers()
try:
for raw_line in ollama_resp:
...
except Exception as e:
self._send_line({"error": ...})
finally:
self.wfile.flush()
_send_line writes bytes line + "\n", flush.
_send_json_error: send_response(code), Content-Type application/json, Content-Length, write json.
Also do_GET for /api/health → {"ok": true, "model": OLLAMA_MODEL, "ollama": <bool>}? Check Ollama reachability quickly with urlopen /api/version timeout 5. Return status + version. Nice for tests. Include.
Also log_message override to quieter (default prints each request to stderr; keep but maybe simpler). I'll keep default but it's fine. Or reduce noise: only log errors? I'll keep default logging of requests (helpful, lightweight). Actually the plan said minimal logging; default is fine.
ThreadingHTTPServer with daemon_threads = True.
Main:
python
if __name__ == "__main__":
host = APP_HOST; port = APP_PORT
httpd = ThreadingHTTPServer((host, port), Handler)
httpd.daemon_threads = True
print(f"OfflineMode running at hxxp://{host}:{port}")
print(f"Ollama: {OLLAMA_BASE_URL} model={OLLAMA_MODEL}")
try:
httpd.serve_forever()
except KeyboardInterrupt:
pass
Handler needs access to config → module-level globals fine.
Directory for SimpleHTTPRequestHandler: set self.directory = STATIC_DIR in init? SimpleHTTPRequestHandler uses class attr directory or init param. I'll pass directory in the server? SimpleHTTPRequestHandler has directory = os.getcwd() class attribute; override in Handler class: directory = os.path.join(os.path.dirname(os.path.abspath(__file__)), "static").
Now the frontend.
index.html: structure with header, main containing view sections (hidden/shown), footer.
Views:
- #view-home
- #view-chat
- #view-activity
- #view-offline
- #view-reflection
Nav: brand "OfflineMode" link (goes home), and a "Start an Offline Moment" button.
Home sections:
1. hero (h1 OfflineMode; p "Maybe you don't need another thing to watch. You might just need something to experience."; explanation paragraph; button Start an Offline Moment)
2. Today's Offline Idea (js-idea area, button "Try This" → opens activity view with this idea, "Another idea" → shuffle)
3. Why OfflineMode?
4. Things We Used To Do (ul)
5. Offline Doesn't Mean Doing Nothing (ul of qualities)
6. No Need to Capture Everything (highlight box with the quote)
7. small closing line: "Use the screen to find something worth experiencing, then close the screen." — from requirement.
Footer: small text "Runs entirely on your computer with local AI. No accounts. No tracking."
Chat view:
- header "Talk — then put the phone down."
- #chat-log (messages)
- suggestion chips (buttons): "I'm bored", "I have 20 minutes", "I'm at home with family", "I'm alone", "I want to go outside", "Something creative", "It's a festival today", "I have no money"
- input + send button
- After any assistant message: if it looks like an activity (has Activity: or the reply came as suggestion?) show a button "I'm Going Offline" below the last message. Keep simple: after each assistant reply, render a small action button "I'm Going Offline" in that bubble area if the message contains an Activity marker or as fallback always show it (it just takes the message as the activity). Simpler: always show after each assistant reply → clicking sets activity = extracted or full text. But always showing could be odd during conversation. Compromise: show it if assistant message includes "Activity:" OR user's intent was an activity... Keep requirement "when an actual activity is detected". Detect via Activity: match or presence of time words? I'll enable the button whenever a structured block detected (Activity:) OR when message ends with a suggestion-ish cue. Simplest robust: show button if message contains "Activity:" or /\b(time|minutes|min)\b/i matched? Eh.
Let me do: extractActivity(text) returns {activity, time, rule} when "Activity:" present; otherwise returns {activity: text}. The "I'm Going Offline" button always appears under assistant messages? The spec: "After an activity is detected, the UI may extract/display Activity/Time/Rule." I'll show the button always under assistant messages (it's not harmful) — but to be tasteful, only show if there's an activity suggestion: detect via presence of Activity: OR imperative suggestion (start with verbs) — too fuzzy.
Decision: Show "I'm Going Offline" button after each assistant reply; clicking opens Activity view. If structured fields were parsed, show them; else the full suggestion text as the activity. This matches "the UI may extract/display." Low risk. I'll do that. It gives users a clear path to go offline — on-message with the product.
Activity view:
- "Your Offline Moment"
- activity text (parsed fields if available)
- Time, Rule rows if present
- Button "I'm Going Offline" → offline screen
- Button "Back to chat"? keep minimal.
Offline screen (the "go offline" moment):
- Big quiet text: "Put your phone down. You can do this."
- Timer: preset duration buttons (10/20/30/45/60 min) + "No timer" option; Start/Pause/Reset. Once started, countdown shows mm:ss (or count-up if no timer). Gentle message when finished: "Time's up. That was yours."
- Button "I'm back" → reflection.
Reflection view:
- "How was it?" chips: Nice, Peaceful, Fun, Unexpected, Boring, I want to do it again
- textarea "What did you notice? (optional)"
- Save button → saves {date, mood, note} to localStorage, show "Saved only on this device."
- Button "Done" → home.
JS functions: showView(id); idea list + random; chat send (build messages array, POST /api/chat, stream read); parseNDJSON from response body via TextDecoder stream reading lines; render assistant bubble accumulating text; scroll to bottom; extractActivity; offline timer.
Streaming read in browser:
js
const res = await fetch('/api/chat', {method:'POST', headers:{'Content-Type':'application/json'}, body: JSON.stringify({messages})});
const reader = res.body.getReader();
const decoder = new TextDecoder();
let buf = '';
while(true){ const {done, value} = await reader.read(); if(done) break;
buf += decoder.decode(value, {stream:true});
let idx; while((idx = buf.indexOf('\n')) !== -1){
const line = buf.slice(0, idx).trim(); buf = buf.slice(idx+1);
if(!line) continue;
const evt = JSON.parse(line);
if(evt.error){ ... show error; return; }
if(evt.finished){ ... finalize; return; }
if(evt.delta){ append delta; }
}
}
Handle non-OK response (e.g., 502) → res.ok false → read json/text and show error.
Chat history: keep array of {role, content} in state; trim to last 10 messages before sending (keep system server-side). Push user message, clear input; render user bubble; create assistant bubble; stream into it; on finish, activity button.
Guard double-submit while streaming.
Local curated ideas list (LOCAL_IDEAS): ~14 items with optional time/rule. Each: {activity, time, rule}. Cross categories.
Example entries:
- "Sit with someone in your family and ask them about a celebration or custom they remember from childhood. Just listen." time: "20 minutes" rule: "No recording."
- "Go outside and watch the sky change colour. No phone." time "15-20 minutes" rule "No photos"
- etc. Include clay/mud ("If weather allows, make something small from soil or clay with your hands."), decorate home, make something without tutorials, read a physical book, cook together, board game, write a letter, help someone, sit on terrace, touch soil / plant, play outside with someone, talk to grandparents, etc. Avoid assuming festivals; keep generic "if there is a festival or celebration coming up, take part in it rather than watching posts about it."
CSS warmth:
- bg #f7f2ea; text #33302a; accent #b0653f (terracotta); soft line #e4dcd0. Headings font Georgia/serif. Body font system-ui.
- max-width container 760px; padding.
- Buttons: simple bordered/pill? Simple solid warm buttons with subtle border, no gradients.
- Chips: small bordered buttons.
- Chat bubbles: aligned left, plain off-white boxes with thin border.
- Responsive: media query for small screens reducing padding/font size.
- Little animation: fade-in for views (opacity transition), no movement.
- Focus styles for accessibility.
Avoid "excessive cards": home sections simple blocks with border-bottom separators rather than cards.
Now write the system prompt (in server.py). Include festival caution and natural + structured.
Let me also make sure: The server converts to clean stream. NDJSON with {"delta":...} is browser-consumable, no Ollama internals. Good.
Also add num_predict cap ~240, temperature 0.7. Could also set "options": {"temperature": 0.7, "num_predict": 240}.
Also keep_alive default (5m) fine; don't set.
Edge: The model gemma4:e2b supports tools/vision/audio/thinking but we use plain chat — fine.
Now requirements.txt: comment "No third-party dependencies. Python 3 stdlib only."
.gitignore:
.env
__pycache__/
*.py[cod]
.DS_Store
node_modules/
*.log
.env: OLLAMA_BASE_URL=hxxp://[wsl-gw-ip]:11434, OLLAMA_MODEL=gemma4:e2b, APP_HOST=localhost, APP_PORT=8080
.env.example: same (commented guidance).
README.md: comprehensive per requirements.
Also, "Never commit secrets" — we keep .env gitignored, .env.example committed.
Now testing:
1. python3 -m py_compile server.py and node --check static/app.js.
2. Start server in background with workdir, get PID; http-get hxxp://localhost:8080/ for index; http-get /api/health; http-get other files.
3. Test /api/chat streaming: http-get -N -m 240 -X POST hxxp://localhost:8080/api/chat -d '{"messages":[{"role":"user","content":"I am bored and my parents are home."}]}' → verify NDJSON lines with delta and finished. This triggers ~55s model load.
4. Verify no external URLs in static/: grep -E "https?://" static/ → only allowed? index should have none. Our README/docs will mention hxxp://localhost but not in static.
5. Stop server.
6. Measure resource: while running, ps -o rss= -p PID.
7. Also offline test: since everything local, no external calls. We can assert by grep and by checking server only contacts OLLAMA_BASE_URL (single urlopen). Maybe also test with invalid base to confirm graceful error.
The chat generation test will load model (57s). Acceptable.
Also the WSL user might open the site in browser via hxxp://localhost:8080 from Windows browser? From Windows browser, localhost:8080 → server is inside WSL → Windows localhost does NOT reach WSL by default... Wait: NAT mode WSL2 — Windows→WSL localhost forwarding is enabled by default (localhostForwarding=true in .wslconfig default) → Windows browser CAN open hxxp://localhost:8080 and reach WSL server! Yes, WSL2 forwards Windows localhost to the WSL distro on localhostForwarding (default true). So user can open from Windows browser. Also from within WSL (if they have a browser inside WSL). Windows browser works via localhost. Good — document in README: open hxxp://localhost:8080 (on Windows) or hxxp://localhost:8080 (inside WSL).
But the server binds localhost inside WSL — does Windows localhostForwarding reach it? WSL's localhost forwarding listens on Windows localhost and forwards to WSL's localhost — yes, binds on WSL side to [REDACTED]? Actually the forwarding mechanism on the Windows side forwards to the WSL VM's localhost (localhost) regardless of our bind. Our bind on localhost:8080 in WSL is reachable via the forwarder. Yes, standard: any service on localhost in WSL is accessible from Windows via localhost. Good.
Now Security: server binds localhost. Also the forwarder exposes it on Windows localhost only (not LAN). Fine.
Now let me write everything. This is a fair amount of content. Let me carefully create files.
I'll create a todo list first.
Also note: no favicon external; add inline SVG favicon via data URI in HTML to avoid 404 (optional). Simple: link rel icon with data:image/svg+xml. Fine.
Let me now also decide about page title and meta.
Let me write out the curated ideas list (~14 items) in app.js.
Let me write all files now.
server.py full:
#!/usr/bin/env python3
"""
OfflineMode - local web server.
Python standard library only (no third-party dependencies).
Serves the static frontend and proxies /api/chat to a local Ollama
instance, converting Ollama's NDJSON stream into a clean browser stream.
"""
import json
import os
import subprocess
import urllib.error
import urllib.request
from http.server import SimpleHTTPRequestHandler, ThreadingHTTPServer
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
STATIC_DIR = os.path.join(BASE_DIR, "static")
ENV_FILE = os.path.join(BASE_DIR, ".env")
SYSTEM_PROMPT = (
"You are OfflineMode, a kind, simple AI companion. Your only goal is to help the user "
"get back to real life: suggest one practical, realistic offline activity and gently "
"encourage them to close the screen and do it.\n"
"\n"
"Behaviour:\n"
"- Be brief and human, like a warm friend. Two to five sentences is usually enough.\n"
"- Suggest ONE concrete activity, never a long list.\n"
"- Prefer activities that are free or nearly free and need no internet.\n"
"- Vary your suggestions: nature, outdoor time, family, friends, creativity, making "
"things by hand, conversation with elders, helping someone, simple daily life.\n"
"- Don't make every suggestion about walking outside.\n"
"- Notice the situation (who they are with, how much time they have, where they are, how they feel) and adapt.\n"
"- Never assume the user's culture, festival, religion, family structure or traditions. "
"If the user mentions a festival or tradition, you may gently suggest taking part in it "
"in a personal, respectful way; otherwise leave it out.\n"
"- Never shame the user for using technology and never say technology is bad.\n"
"- Don't behave like a therapist and don't diagnose. If someone seems distressed, "
"gently suggest talking to a trusted person in their life and keep it simple.\n"
"- Never encourage long chats with yourself. Give them a reason to go do the activity.\n"
"- Sometimes it is good to add one small phone rule, like no photos, no recordings, "
"or no tutorials. Keep it to one short line.\n"
"\n"
"Formatting:\n"
"- When you suggest a concrete activity you may end with up to three short, optional lines:\n"
" Activity: <name>\n"
" Time: <e.g. 20 minutes>\n"
" Rule: <optional, e.g. No photos>\n"
"- Only include Activity/Time/Rule when you actually suggest a specific activity. "
"For ordinary conversation just respond naturally.\n"
)
def read_env_file(path):
"""Read a small .env file into a dict (no dependency needed)."""
values = {}
if os.path.exists(path):
with open(path, "r", encoding="utf-8") as fh:
for line in fh:
line = line.strip()
if not line or line.startswith("#") or "=" not in line:
continue
key, _, value = line.partition("=")
values[key.strip()] = value.strip().strip('"').strip("'")
return values
def detect_wsl_gateway():
"""Best-effort: default Ollama base URL using the WSL default gateway."""
try:
out = subprocess.check_output(["ip", "route"], text=True, timeout=5)
for line in out.splitlines():
parts = line.split()
if len(parts) > 1 and parts[0] == "default":
dev = parts.index("dev")
return "hxxp://{}:11434".format(parts[dev - 1])
except Exception:
pass
return None
_env = read_env_file(ENV_FILE)
def _cfg(name, default):
return os.environ.get(name) or _env.get(name) or default
OLLAMA_BASE_URL = _cfg("OLLAMA_BASE_URL", detect_wsl_gateway() or "hxxp://localhost:11434").rstrip("/")
OLLAMA_MODEL = _cfg("OLLAMA_MODEL", "gemma4:e2b")
APP_HOST = _cfg("APP_HOST", "localhost")
APP_PORT = int(_cfg("APP_PORT", "8080"))
Handle if default in _cfg when default is None: _cfg returns default (None) → "hxxp://localhost:11434". detect_wsl_gateway returns str or None. OK.
Handler:
class Handler(SimpleHTTPRequestHandler):
directory = STATIC_DIR
def do_GET(self):
if self.path.split("?")[0] == "/api/health":
self._health()
else:
super().do_GET()
def do_POST(self):
if self.path.split("?")[0] == "/api/chat":
self._chat()
else:
self.send_error(404)
# ---- health ----
def _health(self):
status = "unknown"
version = ""
try:
req = urllib.request.Request(os.path.join(OLLAMA_BASE_URL, "api", "version"), method="GET")
with urllib.request.urlopen(req, timeout=5) as resp:
info = json.loads(resp.read().decode("utf-8", "replace"))
version = info.get("version", "")
status = "ok"
except Exception as exc:
status = "unreachable: %s" % exc
body = json.dumps({"ok": status == "ok", "ollama": status, "ollama_version": version, "model": OLLAMA_MODEL, "base_url": OLLAMA_BASE_URL}).encode("utf-8")
self.send_response(200)
self.send_header("Content-Type", "application/json")
self.send_header("Content-Length", str(len(body)))
self.end_headers()
self.wfile.write(body)
# ---- chat ----
def _chat(self):
length = int(self.headers.get("Content-Length", 0))
raw = self.rfile.read(length) if length else b""
try:
data = json.loads(raw.decode("utf-8", "replace") or "{}")
messages = data.get("messages")
if not isinstance(messages, list):
raise ValueError("messages must be a list")
except Exception as exc:
self._json_error(400, "Invalid request: %s" % exc)
return
for m in messages:
m.setdefault("role", "user")
payload = {
"model": OLLAMA_MODEL,
"stream": True,
"messages": [{"role": "system", "content": SYSTEM_PROMPT}] + messages,
"options": {"temperature": 0.7, "num_predict": 240},
}
req = urllib.request.Request(
os.path.join(OLLAMA_BASE_URL, "api", "chat"),
data=json.dumps(payload).encode("utf-8"),
headers={"Content-Type": "application/json"},
method="POST",
)
try:
ollama_resp = urllib.request.urlopen(req, timeout=600)
except urllib.error.HTTPError as exc:
detail = exc.read().decode("utf-8", "replace")[:300]
self._json_error(502, "Ollama returned HTTP %s: %s" % (exc.code, detail))
return
except urllib.error.URLError as exc:
self._json_error(502, "Could not reach Ollama at %s (%s). Is the Ollama server running?" % (OLLAMA_BASE_URL, getattr(exc, "reason", exc)))
return
self.send_response(200)
self.send_header("Content-Type", "application/x-ndjson; charset=utf-8")
self.send_header("Cache-Control", "no-store")
self.end_headers()
try:
for raw_line in ollama_resp:
line = raw_line.strip().decode("utf-8", "replace")
if not line:
continue
try:
obj = json.loads(line)
except ValueError:
continue
if obj.get("done"):
self._stream_line({"finished": True})
break
delta = obj.get("message", {}).get("content")
if delta:
self._stream_line({"delta": delta, "finished": False})
else:
self._stream_line({"finished": True})
except Exception as exc:
self._stream_line({"error": "Stream failed: %s" % exc})
finally:
self.wfile.flush()
def _stream_line(self, obj):
self.wfile.write((json.dumps(obj) + "\n").encode("utf-8"))
self.wfile.flush()
def _json_error(self, code, message):
body = json.dumps({"error": message}).encode("utf-8")
self.send_response(code)
self.send_header("Content-Type", "application/json")
self.send_header("Content-Length", str(len(body)))
self.end_headers()
self.wfile.write(body)
def log_message(self, fmt, *args): # quieter, cleaner console
sys.stderr.write("OfflineMode: %s\n" % (fmt % args))
Hmm SimpleHTTPRequestHandler.log_message default prints "localhost - - [date] ...". Keep override small.
Wait: subclassing SimpleHTTPRequestHandler and overriding do_GET for /api/health — the base do_GET calls self.send_head() etc. Fine.
One concern: SimpleHTTPRequestHandler uses directory class attribute only if defined; defining in subclass works (Python 3.7+). Good.
Main:
def main():
try:
server = ThreadingHTTPServer((APP_HOST, APP_PORT), Handler)
except OSError as exc:
sys.exit("Could not bind %s:%s — %s" % (APP_HOST, APP_PORT, exc))
server.daemon_threads = True
print("OfflineMode running at hxxp://%s:%s" % (APP_HOST, APP_PORT))
print("Ollama endpoint: %s (model: %s)" % (OLLAMA_BASE_URL, OLLAMA_MODEL))
print("Open it in your browser: hxxp://localhost:%s (from Windows) or hxxp://localhost:%s (inside WSL)" % (APP_PORT, APP_PORT))
try:
server.serve_forever()
except KeyboardInterrupt:
print("\nBye.")
Note import sys.
Now index.html. Let me write carefully but not overly long.
I'll write the HTML with inline SVG favicon and the 5 views.
Let me draft:
<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1">
<title>OfflineMode — Use the screen to find something worth experiencing</title>
<meta name="description" content="OfflineMode is a small offline AI companion that helps you put the phone down and get back to real life.">
<link rel="icon" href="data:image/svg+xml,%3Csvg xmlns='hxxp://www.w3.org/2000/svg' viewBox='0 0 32 32'%3E%3Ccircle cx='16' cy='16' r='13' fill='%23b0653f'/%3E%3C/svg%3E">
<link rel="stylesheet" href="style.css">
</head>
<body>
<header class="site-header">
<a class="brand" href="#" data-view="home">OfflineMode</a>
<button class="btn btn-small" data-view="chat">Start an Offline Moment</button>
</header>
<main>
<!-- HOME -->
<section id="view-home" class="view">
<div class="hero">
<h1>Maybe you don't need another thing to watch.</h1>
<p class="hero-line">You might just need something to experience.</p>
<p class="hero-copy">
Phones help us do almost everything today. But sometimes they also replace the small things that make life feel real —
talking to family, making something with our hands, going outside, helping with preparations, sitting with someone,
or simply watching the sunset without recording it.
</p>
<p><button class="btn" data-view="chat">Start an Offline Moment</button></p>
</div>
<div class="section">
<h2 id="idea">Today's Offline Idea</h2>
<div id="idea-box" class="idea-box">
<p class="idea-activity" id="idea-activity"></p>
<p class="idea-meta" id="idea-meta"></p>
</div>
<p class="row">
<button class="btn" id="idea-try">Try This</button>
<button class="btn btn-plain" id="idea-another">Another idea</button>
</p>
<p class="muted">Every idea here is written by hand and works without AI — so this page always loads instantly.</p>
</div>
<div class="section">
<h2>Why OfflineMode?</h2>
<p>
Technology is genuinely useful. This isn't about rejecting it. It's about the small question:
what happens when the screen becomes the default answer to everything?
</p>
<p>
We scroll instead of talking. We watch instead of participating. We record instead of experiencing.
OfflineMode gently invites you to do the real thing, then close the screen.
</p>
</div>
<div class="section">
<h2>Things We Used To Do</h2>
<ul class="nostalgia">
<li>make festival decorations ourselves</li>
<li>make things from मिट्टी / clay and paint them</li>
<li>play outside</li>
<li>visit relatives</li>
<li>talk to grandparents and sit with elders</li>
<li>decorate the home together</li>
<li>help prepare food</li>
<li>spend time in fields and gardens</li>
<li>make things with our hands, without a tutorial</li>
<li>play games that didn't need a screen</li>
</ul>
<p class="muted">This isn't nostalgia about the past being perfect — it's a reminder that these things are still possible.</p>
</div>
<div class="section">
<h2>Offline Doesn't Mean Doing Nothing</h2>
<p>Time away from the screen can be:</p>
<ul class="two-col">
<li>creative</li><li>social</li><li>physical</li>
<li>cultural</li><li>peaceful</li><li>playful</li><li>useful</li>
</ul>
</div>
<div class="section highlight">
<h2>No Need To Capture Everything</h2>
<p class="quote">"Some moments are better when nobody takes a picture."</p>
<p>Watch the sunset without photographing it. Talk to your grandmother without recording it. Make something without making a reel about it.</p>
</div>
<div class="section closing">
<p class="big-line">Use the screen to find something worth experiencing, then close the screen.</p>
<p><button class="btn" data-view="chat">Start an Offline Moment</button></p>
</div>
</section>
<!-- CHAT -->
<section id="view-chat" class="view" hidden>
<div class="chat-head">
<h2>Talk a little — then put the phone down.</h2>
<p class="muted">Tell me your situation. I'll suggest one real thing to do.</p>
</div>
<div id="chat-log" class="chat-log" aria-live="polite"></div>
<div id="chips" class="chips">
<button class="chip" data-prompt="I'm bored.">I'm bored</button>
<button class="chip" data-prompt="I have 20 minutes.">20 minutes</button>
<button class="chip" data-prompt="I'm at home with my family.">At home with family</button>
<button class="chip" data-prompt="I'm alone and I don't know what to do.">I'm alone</button>
<button class="chip" data-prompt="I want to go outside.">Go outside</button>
<button class="chip" data-prompt="I want to do something creative.">Something creative</button>
<button class="chip" data-prompt="It's a festival today.">It's a festival</button>
<button class="chip" data-prompt="I have no money to spend.">No money</button>
</div>
<form id="chat-form" class="chat-form">
<input id="chat-input" type="text" placeholder="For example: I'm bored and my parents are home." autocomplete="off" maxlength="500">
<button class="btn" type="submit">Send</button>
</form>
</section>
<!-- ACTIVITY -->
<section id="view-activity" class="view" hidden>
<div class="narrow">
<p class="eyebrow">Your Offline Moment</p>
<h2>An idea worth trying</h2>
<div id="activity-body" class="activity-body"></div>
<p class="row">
<button class="btn" id="act-go">I'm Going Offline</button>
<button class="btn btn-plain" data-view="chat">Back to chat</button>
</p>
<p class="muted">No tutorials. No reels. No posting. Just do it your own way.</p>
</div>
</section>
<!-- OFFLINE -->
<section id="view-offline" class="view" hidden>
<div class="offline">
<p class="eyebrow">Go offline</p>
<h2 id="offline-title">Put your phone down.</h2>
<p id="offline-sub" class="muted">You can do this. It's yours.</p>
<div class="timer" id="timer-display">--:--</div>
<div class="timer-controls">
<button class="chip" data-timer="10">10 min</button>
<button class="chip" data-timer="20">20 min</button>
<button class="chip" data-timer="30">30 min</button>
<button class="chip" data-timer="60">60 min</button>
<button class="chip timer-none" data-timer="0">No timer</button>
</div>
<p id="timer-done" class="muted" hidden>Time's up. That time was yours.</p>
<p class="row">
<button class="btn" id="timer-start">Start</button>
<button class="btn btn-plain" id="timer-reset">Reset</button>
</p>
<p class="row">
<button class="btn btn-plain" id="offline-back">I'm back — I want to reflect</button>
<button class="btn btn-plain" href="#" data-view="home">Back home</button>
</p>
</div>
</section>
<!-- REFLECTION -->
<section id="view-reflection" class="view" hidden>
<div class="narrow">
<p class="eyebrow">Optional reflection</p>
<h2>How was it?</h2>
<p class="muted">No tracking, no streaks. This stays on your device.</p>
<div id="moods" class="chips"></div>
<p><label class="label" for="reflection-note">What did you notice? <span class="muted">(optional)</span></label></p>
<textarea id="reflection-note" rows="3" placeholder="Anything worth remembering?"></textarea>
<p class="row">
<button class="btn" id="reflection-save">Save</button>
<button class="btn btn-plain" data-view="home">Skip</button>
</p>
<p id="reflection-saved" class="muted" hidden>Saved only on this device. Now go live a little.</p>
</div>
</section>
</main>
<footer class="site-footer">
<p>OfflineMode runs entirely on your computer. Local AI, no accounts, no tracking.</p>
</footer>
<script src="app.js"></script>
</body>
</html>
dataview attributes and data-prompts handled in JS.
Note: hidden attribute vs CSS — I'll toggle via class .active and hidden attribute; JS sets hidden = true/false. Use [hidden]{display:none!important} in CSS.
activity-view "Try This" from homepage: sets activity from idea box, goto activity view. Also chat "I'm Going Offline" → activity view with extracted/natural text.
Chips inside reflections — fill from JS list of moods.
CSS: write warm minimal.
app.js:
'use strict';
/* ---------- views ---------- */
const views = {};
document.querySelectorAll('.view').forEach(v => { views[v.id] = v; });
function showView(id) {
Object.values(views).forEach(v => { v.hidden = v.id !== id; });
window.scrollTo(0, 0);
}
document.querySelectorAll('[data-view]').forEach(el => {
el.addEventListener('click', () => showView(el.dataset.view));
});
/* ---------- local ideas (hand written, offline) ---------- */
const LOCAL_IDEAS = [ ... ];
Let me write ideas (~14), each {activity, time?rule?}:
Good variety; no assumptions except "if there's a festival".
Random pick: shuffle and show; "Another idea" picks different index (avoid immediate repeat).
Chat logic:
const chatLog = document.getElementById('chat-log');
const chatForm = document.getElementById('chat-form');
const chatInput = document.getElementById('chat-input');
const history = [];
let streaming = false;
function addBubble(role, text) {
const div = document.createElement('div');
div.className = 'bubble ' + role;
div.textContent = text;
chatLog.appendChild(div);
chatLog.scrollTop = chatLog.scrollHeight;
return div;
}
For assistant bubble, we want richer content: after streaming done, we may add "I'm Going Offline" button inside bubble. So create wrapper.
function addAssistant(initialText) {
const wrap = document.createElement('div');
wrap.className = 'bubble assistant';
const text = document.createElement('p');
text.className = 'bubble-text';
text.textContent = initialText || '';
wrap.appendChild(text);
const okay = document.createElement('button');
okay.className = 'btn btn-small act-btn';
okay.textContent = "I'm Going Offline";
okay.hidden = true;
wrap.appendChild(okay);
chatLog.appendChild(wrap);
chatLog.scrollTop = chatLog.scrollHeight;
return { text, okay };
}
On finish: set text final, show okay button if activity present: we decide — show whenever we got a final non-empty answer. const activity = extractActivity(full); store in lastSuggestion = {text: full stderr..., activity, time, rule}. Show ok button. Clicking → openActivity(lastSuggestion).
extractActivity(full):
js
function parseActivity(text) {
const result = {};
const activity = text.match(/Activity:\s*(.*)/i);
if (activity) result.activity = activity[1].trim();
const time = text.match(/Time:\s*(.*)/i);
if (time) result.time = time[1].trim();
const rule = text.match(/Rule:\s*(.*)/i);
if (rule) result.rule = rule[1].trim();
if (result.activity) return result; // structured
// fallback: whole message as the activity
return { activity: text.trim() };
}
Note: text.match for Time must not overlap the "Activity:" line value containing "Time:"? Unlikely. Fine. But careful: if activity line is "Activity: Make x", and later a "Time: 20 minutes" line. OK.
However potential false positives: user sends "Activity:" — unlikely.
openActivity(suggestion): populate #activity-body with:
- if structured: show big activity text; if time: "Time: ..."; if rule: "Rule: ...". If fallback only: show short intro + activity text.
Build with DOM to avoid injection (textContent).
Also "Try This" button for homepage idea: openActivity({activity: idea.activity, time: idea.time||'', rule: idea.rule||''}).
Chat submit:
js
async function send(text) {
if (streaming || !text.trim()) return;
history.push({ role: 'user', content: text });
addBubble('user', text);
streaming = true;
const b = addAssistant('');
const trimmed = history.slice(-10);
try {
const res = await fetch('/api/chat', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({ messages: trimmed }),
});
if (!res.ok) {
let msg = 'Something went wrong while talking to the local model.';
try { const j = await res.json(); if (j && j.error) msg = j.error; } catch (e) {}
b.text.textContent = msg;
streaming = false;
return;
}
const reader = res.body.getReader();
const decoder = new TextDecoder();
let buf = '';
let full = '';
while (true) {
const { done, value } = await reader.read();
if (done) break;
buf += decoder.decode(value, { stream: true });
let nl;
while ((nl = buf.indexOf('\n')) !== -1) {
const line = buf.slice(0, nl).trim();
buf = buf.slice(nl + 1);
if (!line) continue;
let evt;
try { evt = JSON.parse(line); } catch (e) { continue; }
if (evt.error) { b.text.textContent = evt.error; streaming = false; return; }
if (evt.delta) { full += evt.delta; b.text.textContent = full; chatLog.scrollTop = chatLog.scrollHeight; }
if (evt.finished) { /* done */ }
}
}
// any leftover
if (buf.trim()) { try { const evt = JSON.parse(buf.trim()); if (evt.delta) full += evt.delta; else if (evt.error) {...} } catch(e){} }
b.text.textContent = full;
if (full.trim()) {
history.push({ role: 'assistant', content: full });
lastSuggestion = parseActivity(full);
b.okay.hidden = false;
}
} catch (err) {
b.text.textContent = 'Could not reach the local server. Is OfflineMode still running? (' + err + ')';
}
streaming = false;
chatInput.focus();
}
Simplify the leftover handling: because server always ends with "finished" line with newline, and reader may break across a line, the last line may arrive in next read. The while loop over full buffer handles multi-line. The final "finished" line will be consumed inside loop when newline present; after loop done we break via done. After loop, buf may contain partial line without newline (unlikely). I'll handle finalized on evt.finished by setting a flag; then continue reading until stream end (fine). At end, full text = b.text.textContent effectively.
Simplify: track let finished=false; if(evt.finished) finished=true; After reading loop, if full not yet, whatever. It's fine.
Actually careful: when evt.finished arrives, we could break the read loop early? If we break, fetch reader left unread → connection may be aborted by reader.releaseLock? Better read to end or call reader.cancel(). Simply continue reading until done — server closes anyway.
Chips: click → set input value = data-prompt and submit? Or directly send. Direct send is nicer. Add click handler: send(chip.dataset.prompt).
Form submit: preventDefault, send(chatInput.value), clear input.
Loading state: while streaming, set input placeholder "The local model is thinking…" and disable send? Show subtle. Implement: chatForm querySelector button disabled. Keep simple: disable button while streaming.
Timer logic:
```js
let timerState = null; // null | running | paused
let timerEnd = 0;
let durationMin = 20;
let timerMinsLeft = 0;
let raf = null;
const display = document.getElementById('timer-display');
function formatTime(sec) {
const m = Math.floor(sec / 60);
const s = Math.floor(sec % 60);
return String(m).padStart(2,'0') + ':' + String(s).padStart(2,'0');
}
function tick() {
const now = Date.now();
const left = Math.max(0, Math.round((timerEnd - now) / 1000));
display.textContent = formatTime(left);
const done = document.getElementById('timer-done');
if (left <= 0) { done.hidden = false; }
if (timerState === 'running') raf = requestAnimationFrame(tick);
else if (timerState === 'paused') { /* keep */ }
}
```
Simplify with setInterval 500ms and track remaining seconds.
I'll implement with a simple interval and a remainingSeconds state.
Reflection:
moods = ['Nice','Peaceful','Fun','Unexpected','Boring','I want to do it again'].
Render as chips; click selected toggles .selected.
Save → push {date: iso, mood, note} into localStorage offlinemode_reflections; show saved message.
localStorage guard for disabled storage (try/catch).
Also view transitions: showView hides others. On home load: pick initial idea.
Also activity view from chat 'okay' button sets lastSuggestion used. Home "Try This" passes idea object.
Edge: activity-body markup — I'll create elements dynamically.
Also, the header brand link uses data-view="home" — click goes home (e.g., after reflection).
Footer fine.
Now style.css. Warm palette:
:root { --bg:#f7f2ea; --ink:#3b362c; --soft:#8a8174; --line:#e3d9c9; --accent:#b0653f; --accent-dark:#96512f; }
Global box-sizing, body bg, color, font family: system stack; headings font-family Georgia, 'New York', serif; letter-spacing slight.
Max width container ~48rem; main padding; header sticky? simple static.
.section border-top: 1px solid var(--line); padding: 2rem 0.
Buttons: .btn { background: var(--accent); color:#fff; border:none; padding:.6rem 1.1rem; border-radius:999px; font-size:1rem; cursor:pointer; } .btn:hover { background: var(--accent-dark);} .btn-plain { background:transparent; color:var(--accent); border:1px solid var(--line); } .btn-small { padding:.35rem .8rem; font-size:.9rem; }
.chip { border:1px solid var(--line); background:#fff; border-radius:999px; padding:.35rem .8rem; cursor:pointer; color:var(--ink);} .chip:hover{border-color:var(--accent);} .chip.selected{background:var(--accent);color:#fff;border-color:var(--accent);}
Chat bubbles: .bubble{max-width:85%;padding:.75rem 1rem;border-radius:1rem;margin:.4rem 0;line-height:1.5;} .bubble.user{margin-left:auto;background:var(--accent);color:#fff;} .bubble.assistant{background:#fff;border:1px solid var(--line);} .bubble-text{margin:0;} .act-btn{margin-top:.5rem;}
.chat-log{height:min(50vh, 420px);overflow-y:auto;padding:.5rem 0;}
.idea-box{background:#fff;border:1px solid var(--line);border-left:4px solid var(--accent);padding:1rem 1.2rem;border-radius:.5rem;}
.highlight{background:#fdf6ef;border:1px solid var(--line);border-radius:.75rem;padding:1.5rem;}
.quote{font-family:Georgia,serif;font-style:italic;font-size:1.3rem;}
.timer{font-family:Georgia,serif;font-size:4rem;text-align:center;margin:1rem 0;color:var(--accent);}
.two-col{columns:2;}
.offline{text-align:center;padding:3rem 1rem;}
[hidden]{display:none !important;}
@media(max-width:560px){ main{padding:0 1rem;} .hero h1{font-size:1.6rem;} .timer{font-size:3rem;} .two-col{columns:1;} }
body{display:flex;flex-direction:column;min-height:100vh} main{flex:1}
focus visible outline.
Add fade: @keyframes fadeIn{from{opacity:0}to{opacity:1}} .view{animation:fadeIn .3s ease;} This is subtle, allowed ("avoid excessive animations").
OK. requirements.txt content:
```
But a pip install -r should not fail — with only comments it's fine (empty file also fine). I'll put comments only.
.gitignore:
.env
pycache/
*.py[cod]
.DS_Store
*.swp
*.log
node_modules/
```
.env:
OLLAMA_BASE_URL=hxxp://[wsl-gw-ip]:11434
OLLAMA_MODEL=gemma4:e2b
APP_HOST=localhost
APP_PORT=8080
.env.example: same but with comments:
```
OLLAMA_BASE_URL=hxxp://[wsl-gw-ip]:11434
OLLAMA_MODEL=gemma4:e2b
APP_HOST=localhost
APP_PORT=8080
```
README.md: thorough. Include: what, why, local AI, how to run, Ollama config incl. WSL gateway note, offline, tests? Not tests, but structure, philosophy, contributing, screenshots/demo notes. Also note English UI but model can speak other languages.
Let me write README with sections:
- OfflineMode
- Why
- The one rule: use screen to find something worth experiencing, then close the screen
- How it works (diagram user→chat→activity→offline)
- Tech stack (python stdlib, static frontend, local ollama)
- Running (prereqs: python3, ollama running with gemma4:e2b)
1. copy .env.example .env
2. python3 server.py
3. open hxxp://localhost:8080 (Windows) / localhost:8080 (WSL)
- Ollama setup (how to install ollama - referencing, model note: gemma4:e2b already local; check via ollama list; if not... user said don't pull new models; README can generically explain pulling gemma4 but careful not to instruct pulling a different model. I'll say "ensure the model in .env exists locally; ollama list" and generic note that any Ollama model can be pointed to, but the project was built with gemma4:e2b. Do NOT instruct pulling.)
- Configuration table
- Offline note (no internet needed)
- Security (localhost only)
- Resource use
- Project structure
- Contributing
- Non-goals / what it deliberately does NOT do (no streaks etc.)
Now node --check static/app.js validates syntax.
Also, the server must be started from project dir. I'll run with workdir /mnt/d/OfflineMode.
Let me also add a tiny system prompt tweak: mention "If the user is with someone or a group, suggest something together." Good - covered by "notice the situation". Add line maybe.
Now — a subtle thing: the browser sends messages incl. roles. The system prompt addition server-side. Good. The model is gemma (german/english capable). Fine.
Another subtlety: Since gemma4:e2b is 4.6B with 131k context Q4 and CPU-only, num_predict 240 may take a while (~30-40s at 6-8 tok/s after warmup). Streaming mitigates. OK.
Potential runtime issue: ThreadingHTTPServer with SimpleHTTPRequestHandler protocol_version — SimpleHTTPRequestHandler sets protocol_version to 'HTTP/1.0'. Fine.
Let me also ensure do_POST parsing: if Content-Length missing (probably present from fetch). Use try.
The _cfg default None case: _cfg("OLLAMA_BASE_URL", detect_wsl_gateway() or "hxxp://localhost:11434"). detect called each startup once (module load). Good.
Note: env var precedence: os.environ > .env > default. Good.
Now the report at end (step: after implementation). I'll implement then test, then give final report meeting the 6 requested items.
Also I must keep todo list updated. Let me create todos:
1. Scaffold config files (.env, .env.example, .gitignore, requirements)
2. Implement server.py proxy
3. Build frontend (index.html, style.css, app.js)
4. Syntax checks + start server + endpoint tests (health, static, chat NDJSON)
5. AI generation test via /api/chat
6. Offline/external-asset check + resource measurement
7. Write README + final report
I'll mark in_progress as I go.
Let me write files now. Be careful with the Home idea button "Try This": showView activity + fill.
Also make sure app.js references IDs correctly.
Also: history trim slice(-10) — but user may send one message; system prepended server side. History messages only user/assistant. Good.
Also lastSuggestion variable used by ok button in activity view.
Also handle Enter key default (form submit).
Timer implementation finalization (countdown vs count-up):
const timerDisplay = document.getElementById('timer-display');
const timerDone = document.getElementById('timer-done');
let timerState = 'idle'; // idle, running, paused
let timerSec = 0; // total target seconds (0 => count up)
let remainingSec = 0;
let interval = null;
function stopTimer() { if (interval) { clearInterval(interval); interval = null; } }
function renderTimer(sec) {
timerDisplay.textContent = formatTime(np); // for count-up show elapsed
}
Let me define:
- durationMin chosen from chips (default 20).
- Start button behavior:
- if idle: if durationMin>0 { remainingSec = durationMin*60; } timerState='running'; timerDone.hidden=true; start loop.
- if paused: resume (state running).
- if running: do nothing (or turn into pause? keep separate pause? I have Start + Reset only, though "Start" on running could toggle pause — simpler to make Start toggle start/pause: if running → pause; if paused/idle → start/resume). Label it "Start" / "Pause". I'll implement toggle with label update and second button Reset. Actually adding a separate "Pause" not in markup; I'll make Start toggle and change its text to "Pause"/"Start".
Loop each 1s:
- if running:
if durationMin>0: remainingSec-1; if <=0 → remainingSec=0; state='finished'; clearInterval; timerDone.hidden=false; render.
else (count-up): elapsedSec++ (elapsed from 0) render elapsed.
- Reset: stopTimer; state='idle'; remainingSec = durationMin>0? durationMin*60 : 0; render accordingly (count-up shows 00:00; countdown shows duration).
- chip click: if running/paused confirm? Just set durationMin and if idle update display; if running and duration changed, reset remaining? Keep simple: selecting chip while idle sets duration; if currently running, it resets the timer to new duration (like choosing anew). Implement: stopTimer; durationMin=N; state='idle'; renderIdle; also visually mark selected chip.
renderIdle: durationMin>0 ? format(durationMin*60) : '00:00'.
Count-up elapsed display: format(elapsedSec).
Also "finished": keep display at 00:00 and show done message.
Also when user leaves view mid-timer, interval continues (fine). Keep timer running while they navigate? If they switch views, hide offline view but timer continues; when they come back, still shows. That's acceptable (quiet). Could pause when leaving — unnecessary complexity. Keep.
"offline-sub": text can show the activity. I'll set #offline-title maybe to the idea. Actually keep title simple. I'll set offline-sub = "You can do this. It's yours." and maybe the activity small line: add to sub? Keep gentle: sub shows activity if present: e.g., "Try: <short activity> — no phone, no photos." Might be too much. Keep fixed gentle text; the activity was already shown in activity view. OK.
Now, "I'm back — I want to reflect" → showView reflection.
Also "Back home" link in offline view (plain anchor with data-view=home) - I used <button class="btn btn-plain" href="#" data-view="home"> — buttons don't take href; fine, just button. Change to button without href.
Let me write the code files now.
One more: the chip for "It's a festival" — prompt text "It's a festival today." The response should be contextual.
Also max input length 500.
Also ensure UTF-8 meta and charset; file written in UTF-8. The Hindi "मिट्टी" in HTML - fine.
Potential issue: Python reading stdin? no.
Let me also double check SimpleHTTPRequestHandler directory serving path for "/" returns index.html: yes, send_head looks for index.html. Good. And serving /style.css relative to static dir. Good.
Also content types: html/css/js handled by mimetypes via SimpleHTTPRequestHandler. Good.
Alright, write the files.
For tests, after starting server in background (nohup?), run in background: python3 server.py > /tmp/opencode/server.log 2>&1 & echo $!. Use bash tool. Then http-get. Then kill.
Also measure RSS: ps -o rss=,pmem= -p <pid>.
Let me now also confirm there are no external URLs in built static: grep -rn "https\?://" static/ | should be empty (favicon data URI is data: not http). README has URLs (fine, not app code). Also .env.example has hxxp:// (fine).
Also note: the chat streaming endpoint returns NDJSON lines with newline; browser parser handles.
Write files now. Also update todo statuses.
Also the "report approximate resource usage": measure server.py process RSS (should be ~15-30MB). Ollama already running (not started by us). We can note how to check its usage too but not necessary.
Let me write server.py.
Careful: os.path.join(OLLAMA_BASE_URL, "api", "chat") — os.path.join with a URL string containing "hxxp://[wsl-gw-ip]:11434" plus "api" plus "chat" yields "hxxp://[wsl-gw-ip]:11434/api/chat" on POSIX (works because join just concatenates with '/'). Yes on POSIX fine. But portability/Windows? Server may run on Windows too (python on Windows). os.path.join on Windows would produce backslashes! Since .env default might run on Windows machine directly. To be safe, build URL with f-strings: f"{OLLAMA_BASE_URL}/api/chat". Use that.
Now writing files.
Also, the /api/health returns base_url (fine locally).
Let me create the todos and then all files, then tests.
For .env — should I create it now with the given dev values? Yes, .env is machine config gitignored. The user gave OLLAMA_BASE_URL=hxxp://[wsl-gw-ip]:11434. Good.
Let me write everything.
Also app.js: careful that views includes sections; data-view buttons call showView; defaults hidden via HTML hidden attr except home.
Also on load: pickRandomIdea(); render reflection moods; wire chips, timer buttons, form.
Potential issue: chip click while streaming disabled? Guard in send.
Also initial assistant greeting? Should the chat show a welcome message from the model or a static welcome bubble? A static welcome bubble (non-AI) is nice and instant: "Tell me what's going on — how much time you have, who you're with, how you feel — and I'll suggest one real thing to do." Add static initial assistant bubble in HTML? I'll add it programmatically on first show. Simpler: put it as static first bubble in #chat-log? It's inside chat view; I'll add via JS on load so history isn't polluted. Fine.
Edge: If user opens chat and asks "hi", model replies naturally (no structure) — okay button still appears (fallback whole text as activity) — acceptable. Hmm but for "hi" showing "I'm Going Offline" with whole text might be odd. Could hide ok button when no structured and message is short/chatty? Detect: if structure found OR message looks like a suggestion (contains imperative?). I'll enable ok button if structured OR message length > 40 chars (suggestions tend longer). Let's do: show action button when parseActivity returns structured OR full length >= 40. Reasonable heuristic; avoids the "hi" case. I'll note as a light heuristic.
Also: after sending, keep focus. If error, still ok.
Time to write. I'll write files in parallel-ish (Write tool sequential but multiple calls ok). Let me batch a few Write calls (independent).
Actually Write calls can be in same message batch. Let me do: server.py, .env, .env.example, .gitignore, requirements.txt in one batch; then index.html, style.css, app.js in another; README last. Then tests.
Let me finalize the system prompt text (making sure to keep it not too long — gemma has prompt framing; our system message is fine).
Write now.
Approved — starting the build. Let me track the work and scaffold the project.
{"todos": [{"content": "Scaffold config files (.env, .env.example, .gitignore, requirements.txt)", "status": "in_progres
[ { "content": "Scaffold config files (.env, .env.example, .gitignore, requirements.txt)", "status": "in_progress", "priority": "high" }, { "content": "Implement server.py (static + /api/chat proxy with clean NDJSON stream)", "status": "pending", "pr…
file: /mnt/d/OfflineMode/.env.example # OfflineMode configuration sample. # Copy this file to `.env` and adjust the valu
Wrote file successfully.
file: /mnt/d/OfflineMode/.env # Machine-specific configuration. This file is NOT committed to git. # Copy .env.example t
Wrote file successfully.
file: /mnt/d/OfflineMode/.gitignore # Machine-specific / local configuration — never commit. .env # Python __pycache__/
Wrote file successfully.
file: /mnt/d/OfflineMode/requirements.txt # OfflineMode uses ONLY the Python standard library. # There are no packages t
Wrote file successfully.
Now server.py.
file: /mnt/d/OfflineMode/server.py #!/usr/bin/env python3 """ OfflineMode - local web server. Python standard library on
Wrote file successfully.
Now the frontend. index.html.
file: /mnt/d/OfflineMode/static/index.html <!doctype html> <html lang="en"> <head> <meta charset="utf-8"> <meta name="vi
Wrote file successfully.
Now style.css.
file: /mnt/d/OfflineMode/static/style.css :root { --bg: #f7f2ea; --ink: #3b362c; --soft: #8a8174; --line: #e3d9c9; --pap
Wrote file successfully.
Now app.js — the biggest frontend logic file.
Let me write it carefully covering:
- views navigation
- local curated ideas
- chat with fetch streaming NDJSON
- activity extraction
- activity view
- offline timer (countdown + count-up)
- reflection with localStorage
Careful with template literals/backticks none; use string concat where needed. Also no unused vars.
Let me write it.
file: /mnt/d/OfflineMode/static/app.js 'use strict'; /* ============================================================ Off
Wrote file successfully.
Now syntax checks and start the server. Let me update todos and run checks.
Checks:
- python3 -m py_compile server.py
- node --check static/app.js
- grep for external URLs in static/
Then start server background from workdir /mnt/d/OfflineMode, test endpoints.
{"todos": [{"content": "Scaffold config files (.env, .env.example, .gitignore, requirements.txt)", "priority": "high", "
[ { "content": "Scaffold config files (.env, .env.example, .gitignore, requirements.txt)", "status": "completed", "priority": "high" }, { "content": "Implement server.py (static + /api/chat proxy with clean NDJSON stream)", "status": "completed", "pr…
$ {"command": "python3 -m py_compile server.py && echo \"server.py OK\"; node --check static/app.js && echo \"app.js OK\""
server.py OK app.js OK
$ {"command": "echo \"=== external URLs in static (should be none) ===\"; grep -rnoE \"https?://[^\\\"' ]+\" static/ || ec
=== external URLs in static (should be none) === static/index.html:8:hxxp://www.w3.org/2000/svg === external asset refs (src/href) === none
The only "hxxp://" is the SVG namespace (data URI, not a network request) — that's fine, it's not fetched. No external asset references.
Now start the server in background and test endpoints:
- / → index.html
- /style.css, /app.js
- /api/health
- /api/chat with a message (will trigger model load ~55s). Use http-get with -N and timeout.
Start server from workdir.
$ {"command": "python3 server.py > /tmp/opencode/offlinemode-server.log 2>&1 & echo \"SERVER_PID=$!\"; sleep 2; cat /tmp/o
SERVER_PID=1992
The log is empty. Maybe print buffering — python stdout is line-buffered only for tty; redirected to file → block buffered, so prints aren't flushed yet. The server is running though (PID 1992). Test endpoints.
$ {"command": "echo \"=== / (index) ===\"; http-get -s -m 5 -o /dev/null -w \"HTTP %{http_code} size=%{size_download}\\n\" htt
=== / (index) === HTTP 200 size=571 <!DOCTYPE HTML> <html lang="en"> <head> <meta charset="utf-8"> === style+app === style.css 404 app.js 404 === health === {"ok": true, "ollama": "ok", "ollama_version": "0.40.1", "model": "gemma4:e2b", "base_url": "…
Two problems:
1. / returned size=571 — that's not our full index.html (should be ~4KB+). It shows a minimal HTML — that's the SimpleHTTPRequestHandler directory listing! Because directory = STATIC_DIR class attr didn't take effect? Wait, size 571 and content is <!DOCTYPE HTML><html lang="en">... — that's NOT our index.html (our index starts with <!doctype html>). Hmm. 571 bytes. Let me look at the full output.
Actually the output shows:
<!DOCTYPE HTML>
<html lang="en">
<head>
<meta charset="utf-8">
That could be the error page or directory listing. <title> truncated by head -4. Likely it's a directory listing page (SimpleHTTPRequestHandler's list_directory returns HTML with <!DOCTYPE HTML>). If directory attr not applied, it serves from CWD (/mnt/d/OfflineMode), and '/' would list dir? No, if no index.html in CWD, it lists. But there IS static/index.html, not index.html at root. So '/' → no index.html in /mnt/d/OfflineMode → directory listing. That confirms directory = STATIC_DIR didn't take effect!
Why? In older Python (3.7+), class attribute directory works. Python 3.14 — should work. Wait — did I overwrite? I defined class Handler(SimpleHTTPRequestHandler): directory = STATIC_DIR. Hmm but subclassing: SimpleHTTPRequestHandler.init has signature (request, client_address, server, directory=None). If directory param None → uses self.directory class attr. Actually in Python 3.14, http.server.SimpleHTTPRequestHandler.init sets self.directory from the parameter OR falls back to class attribute? Let me recall: init does: self.directory = os.fspath(directory) if directory is not None... then super().__init__. But when the server calls the handler, it calls handler class with (request, client_address, server) only — no directory param. Then init uses default None → then self.directory = directory would set self.directory = None?? Let me recall actual code:
def __init__(self, *args, directory=None, **kwargs):
if directory is None:
directory = os.getcwd()
self.directory = os.fspath(directory)
super().__init__(*args, **kwargs)
If that's the case, self.directory = cwd always, ignoring class attribute! Indeed in newer Python (3.7), they changed it so ServerHandler subclasses must pass directory to init or set it... Actually the docs say: "If directory is not provided, defaults to the current working directory." And for subclassing they recommend overriding __init__ setting self.directory, NOT the class attr. Hmm, but many older examples use class attribute. Let me check: In 3.7+, the recommended way:
class Handler(SimpleHTTPRequestHandler):
def __init__(self, *args, **kwargs):
super().__init__(*args, directory=STATIC_DIR, **kwargs)
Yes that's the modern approach. The class attribute approach worked in old versions? The init signature had directory param added in 3.7. The class attribute was the way before, but with the new init defaulting to os.getcwd(), the class attr is bypassed. Actually wait — several codebases still use class attribute successfully. Let me check 3.14 source... I recall the init in 3.14:
def __init__(self, request, client_address, server, *, directory: str | os.PathLike[str] | None = None):
if directory is None:
directory = os.getcwd()
self.directory = os.fspath(directory)
super().__init__(request, client_address, server)
Since Handler.init is inherited (SimpleHTTPRequestHandler has its own init), calling Handler(request, client_address, server) → SimpleHTTPRequestHandler.init(request, client_address, server) → directory None → cwd. self.directory set to cwd (not None), ignoring class attribute. So yes — 404s for style.css confirm: it serves from /mnt/d/OfflineMode root (no static/style.css there) → 404.
Fix: override init in Handler to pass directory=STATIC_DIR.
/ returned a directory listing (571 bytes) — because no index.html at root. Fixing directory solves it.Also index size 571 bytes: it's the listing page. Fine.
Also note: my data:image/svg+xml favicon includes hxxp://www.w3.org/2000/svg — it's a namespace inside a data URI, not a network fetch. Acceptable; the grep flagged it but it's harmless. To be thorough I could leave it (it's literally not an external request). Keep.
Let me fix the handler.
Found it: SimpleHTTPRequestHandler in modern Python ignores the directory class attribute — it needs the directory passed via __init__. Fixing:
{"filePath": "/mnt/d/OfflineMode/server.py", "oldString": "class Handler(SimpleHTTPRequestHandler):\n directory = STATIC
Edit applied successfully.
$ {"command": "python3 -m py_compile server.py && echo \"compile OK\"; kill 1992 2>/dev/null; sleep 1; python3 server.py >
compile OK SERVER_PID=2020 === files === / -> 200 size=7956 style.css -> 200 app.js -> 200 .env (should 404) -> 404 === index title === <title>OfflineMode — Use the screen to find something worth experiencing</title>
All static files served correctly, .env correctly not served (SimpleHTTPRequestHandler confines to directory so even serving from static dir, .env at project root is unreachable — good). index.html full size 7956.
Now test /api/chat streaming. This will trigger model load (~55s). Use http-get -N with timeout 240s.
Static serving fixed. Now the live streaming chat test (first call loads the model into CPU memory — takes ~55s):
$ {"command": "http-get -s -N -m 240 -X POST hxxp://localhost:8080/api/chat -H \"Content-Type: application/json\" -d '{\"messa
---line count--- 0
Empty response — 0 lines. Something failed. Let me check the server log and also test the raw /api/chat to Ollama directly to see if the model responded.
Let me check server log.
$ {"command": "cat /tmp/opencode/offlinemode-server.log; echo \"=== test raw ollama ===\"; /mnt/c/Windows/System32/http-get.ex
localhost - - [08/Oct/2026 15:12:06] "GET / HTTP/1.1" 200 - localhost - - [08/Oct/2026 15:12:06] "GET /style.css HTTP/1.1" 200 - localhost - - [08/Oct/2026 15:12:06] "GET /app.js HTTP/1.1" 200 - localhost - - [08/Oct/2026 15:12:06] code 404, message …
The server log shows NO request for our /api/chat! The http-get to the server produced nothing and no log line — meaning the request never reached the handler? And the raw Windows ollama test also returned nothing (empty). Interesting.
Wait, http-get with -N POST to localhost:8080/api/chat returned empty and no server log line at all. That's odd. Also the raw ollama test returned empty too!
Let me reconsider. The raw ollama test via Windows http-get to localhost:11434 — empty output. Earlier /api/generate worked on 11434. /api/chat may need model that supports chat... gemma4:e2b should. Maybe it printed nothing because model was... let me test raw with output check and time. Also check if the TCP/connection worked: maybe Windows http-get exit code? Empty but exit might be 28/7.
Actually wait — earlier the moment I did http-get to server /api/chat, the tee captured 0 lines and empty. Possibly the server process died? No, log shows old entries only (nothing new, meaning /api/chat POST never even logged). but even 400/404 would log. So the POST never arrived → connection failed? But http-get returned quickly with empty (exit unknown; head showed nothing).
Hmm, maybe our server doesn't handle POST to /api/chat because the shell command used single quotes inside bash -d '...' fine.
Let me check: is the server still running? PID 2020. And test POST to /api/chat with verbose to see HTTP code. Maybe http-get connected but the handler threw and connection closed? The server log would have an exception traceback to stderr (we redirect to log file). Log shows no POST line at all — not even "code 404". So do_POST not reached.
Wait — maybe the issue: our earlier raw olama test also gave empty because output redirection to head -c 300 with big stream... no.
Let me just debug directly: check server alive, verbose http-get to /api/chat with a tiny prompt; capture HTTP status and body; also tail server log.
$ {"command": "ps aux | grep \"server.py\" | grep -v grep; echo \"=== verbose POST ===\"; http-get -v -m 30 -X POST hxxp://127
root 2020 0.0 0.6 180980 23888 ? SNl 15:11 0:00 python3 server.py === verbose POST === Note: Unnecessary use of -X or --request, POST is already inferred. % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left S…
Connected, sent 45 bytes, but ZERO bytes received and no log line logged from server (the do_POST handler didn't even log, because I only log via log_message which SimpleHTTPRequestHandler calls for each request... but no line). Actually log_message override writes to stderr → redirect to log file. No POST log line at all appears. And no exception traceback either. The connection received nothing and timed out at 30s.
Hmm. The handler thread is presumably blocked in urlopen(req, timeout=600) waiting for Ollama's response... and Ollama's server may be busy? Wait, earlier raw ollama /api/chat test also returned empty (no output) — maybe that also hung. Let me reconsider: my raw test used -m 200 then head -c 300 but the whole thing completed within the tool's timeout? The tool returned quickly actually (that command returned with both cat + http-get but no output shown besides empty). Actually it printed just the server log tail and empty for raw test — meaning raw ollama chat returned nothing quickly? Or timed out? No error shown.
Wait, the earlier window http-get for /api/version and /api/generate worked fine. Why /api/chat hangs?
Possibility: Ollama server is currently stuck processing a request — maybe a previous stalled generation? Earlier our generate test finished. Hmm.
Possibility: The model isn't actually loaded and /api/chat with streaming waits for load ~55s. Our server request (timeout=600) would wait... but http-get should receive HEADERS once urlopen returns (which happens after Ollama responds headers). If Ollama is slow to load the model (57s+), the server handler is blocked in urlopen for ~60s, no bytes sent (correct — we only send headers after urlopen returns). So http-get waits 30s → timeout. That's consistent! The first 30s might just be model loading. And my earlier test used -m 240 with tee and got 0 lines after... it finished? The command with -m 240 returned empty and wc -l 0 — it must have completed/been killed by tool? Actually the tool call returned (didn't timeout at 240s?) Hmm, the shell tool has default timeout 120000ms (120s) if not specified! I passed timeout 250000ms. It returned. If the model load is 55s + generation, within 240s it should've produced output. But it produced 0 lines. So something else is wrong.
Wait — maybe urllib redirected? No.
Let me test Ollama directly raw /api/chat but with proper error reporting and verbose. The earlier raw test output "=== test raw ollama ===" then empty, then log tail. So Windows http-get to localhost:11434/api/chat returned empty — with -m 200. Empty means either 0 bytes (timeout) or the model responded nothing. Let me test raw with -v and stream:false and measure timing + HTTP code.
Another thought: does gemma4:e2b /api/chat work? It's a modalities model; earlier /api/generate worked. /api/chat should too. But maybe it requires a specific message format? No.
Hold on — maybe the issue is our SYSTEM_PROMPT + role system: Ollama /api/chat accepts system role fine.
Actually, wait: let me reconsider the earlier hang. When I ran the streaming test http-get -s -N -m 240 ... | tee ... | head -c 900, the whole thing within the tool — the tool call I set timeout 250000. It returned with output empty and "---line count--- 0". So http-get must have completed within 250s? If Ollama load ~57s, http-get would start receiving after headers. But we got 0 total. Unless the server handler threw an exception BEFORE sending headers, and the connection was closed with nothing written (BaseHTTPRequestHandler would send an error page via send_error and log it — but no log). Hmm unless the exception happened in _chat after reading but in a way that produced no output... Actually if an unhandled exception occurs in do_POST, http.server catches it in handle_one_request? No — exceptions propagate; the request thread errors out, connection closed, nothing sent.
But we WOULD see a traceback in the log (stderr). Nothing there.
OK let me think again — is it possible the handler never even started? ThreadingHTTPServer spawns a thread per request. If ThreadPool... no.
Wait, actually — maybe the URL construction is wrong: OLLAMA_BASE_URL + "/api/chat" = "hxxp://[wsl-gw-ip]:11434/api/chat". Fine.
Hmm, but notice: the POST http-get showed "Connected to localhost:8080", sent data, then "0 bytes received". No server log. This means the handler thread is stuck BEFORE any send_response (headers) — i.e., in urllib.request.urlopen OR in parsing. If urlopen error, it'd send 502 and log request. So it's stuck in urlopen → Ollama not responding.
So the real question: why isn't our gateway reachable to Ollama /api/chat while /api/version works?
Maybe urlopen(req) with the request data stuck at the network layer (firewall re-check?). We verified WSL→[wsl-gw-ip]:11434 works via http-get. But Python urllib from the server process — same network. Should work.
Alternatively, Ollama may be genuinely busy/blocked: Maybe the Ollama server is currently generating for a previous request (the very first raw /api/chat test?) that got stuck? Two competing requests?
Let me test step by step:
1. Raw Windows-side http-get /api/chat with stream:false, show HTTP code and timing.
2. From WSL, http-get /api/chat directly to [wsl-gw-ip]:11434 with stream:false, short prompt, verbose timing.
Let me run those.
Server connects but gets nothing back from Ollama during /api/chat. Let me isolate the Ollama side directly (both Windows and WSL), with timing and status:
$ {"command": "echo \"=== WSL -> Ollama /api/chat (stream:false) ===\"; time http-get -s -m 180 -X POST hxxp://[wsl-gw-ip]:11
=== WSL -> Ollama /api/chat (stream:false) === HTTP 000 time=180.005177s http-get -s -m 180 -X POST hxxp://[wsl-gw-ip]:11434/api/chat -H -d -o -w 0.05s user 0.13s system 0% cpu 3:01.66 total body: cat: /tmp/opencode/raw_chat.txt: No such file or directo…
WSL → Ollama /api/chat HANGS (180s timeout, HTTP 000). But /api/version and /api/generate worked earlier from WSL. So /api/chat endpoint specifically hangs... over the WSL→Windows firewall path?
Wait, earlier /api/generate worked from WSL (the "WSL GENERATION OK" test). And POST to /api/chat from WSL now hangs. Interesting — perhaps the firewall rule we added allows TCP 11434 inbound on the vEthernet interface regardless of whether it's generate or chat... both same port. So connection established (TCP SYN allowed). The hang means the HTTP request is processed but response never comes back.
Could Ollama server be stuck? Let me check the server.log (Ollama's) for the /api/chat request. Maybe the server is encountering an issue with chat + this model (e.g., it's trying to load something, or there's an error char... maybe the model requires a template and with role system it misbehaves?).
Let me check Ollama's Windows server.log tail, and also test /api/chat with stream:true briefly and with a tiny num_predict, and also test /api/generate again to confirm generate still works (maybe server is wedged).
$ {"command": "echo \"=== retest /api/generate (is server wedged?) ===\"; http-get -s -m 150 -X POST hxxp://[wsl-gw-ip]:11434
=== retest /api/generate (is server wedged?) === HTTP 000 time=150.000132s head: cannot open '/tmp/opencode/gen.txt' for reading: No such file or directory === Ollama server.log tail === slot print_timing: id 0 | task 0 | n_gen = 101, tg = 1.28 t/s, …
Now I see it. The Ollama server log shows:
- tg = 1.2-1.8 t/s — VERY slow generation. 654 tokens generated in 3m32s for a request with num_predict=20?? Wait — it generated 654 n_tokens. That means num_predict was ignored/massive, or the data I sent...
- All requests get aborted because "client closing the connection" and return 500 after client timeout. The generation was EXTREMELY slow (1.2-1.8 tokens/sec) and produced 654 tokens for a num_predict=20 request.
Why so slow? Earlier we measured ~6.5 tok/s eval. Now 1.2-1.8 t/s and massive token counts. Something is different!
Wait — n_gen=654 tokens in the last task. That corresponds to our earliest /api/chat request? Let's map timestamps:
- 15:15:48 | 3m32s | [wsl-gw-ip] | POST /api/chat → this is my WSL streaming? Started ~15:12... 3m32s, client closed (my http-get -m 240 had head... hmm). Response 200 though ("200" printed). It generated 654 tokens for my "I am bored and my parents are at home" prompt with num_predict 240. 654 > 240. So num_predict... maybe with speculative decoding/draft model, n_gen counts something else. Regardless.
- 15:19:55 | 3m19s | ::1 | POST /api/chat → the Windows http-get raw test (localhost). aborted → 500.
- 15:24:47 | 2m59s | [wsl-gw-ip] | POST /api/chat → my WSL http-get stream:false test. aborted → 500.
- 15:27:31 | 2m30s | [wsl-gw-ip] | POST /api/generate → my generate retest. aborted → 500.
Key insight: generation speed now 1.2-1.8 t/s vs 6.5 t/s before. And each request ran 2-3.5 minutes without finishing even 20 tokens! The model became extremely slow. What changed?
Hmm. Earlier successful test (WSL GENERATION OK) was at 09:04, ~14:34 IST? The "total_duration" was 57s with load 53s — eval 6 tokens / 0.888s ≈ 6.7 t/s.
Now we're at 1.2-1.8 t/s. Something degraded performance. Possibilities:
1. The machine's RAM is under pressure: model is 4.6B Q4 (~2.6GB in memory + draft + projector). Windows free RAM was 1.7GB. The system may now be swapping heavily (slow disk, degraded). CPU inference at 1.5 t/s suggests thrashing/swapping or CPU throttling.
2. Our server + browser? Not running yet (browser not opened). The 638MB... the classifier project not running.
3. Maybe thermal throttling.
Actually — also notice: 654 tokens generated in 212s = ~3.1 t/s average over first task; and it says truncated=0, n_tokens=654. For a num_predict=240 request to produce 654, either prompt-phase counts, or num_predict isn't applied (options not forwarded?). Wait, that first /api/chat from my streaming test had num_predict 240 in payload. 654 tokens... maybe includes prompt eval tokens (prompt ~ dozens) — no, 654 is n_gen (generation). Hmm. Maybe gemma4:e2b ignores num_predict under some conditions (speculative decoding!). The model has a draft model (draft2) — spec decoding. num_predict with speculative decoding has known quirks? Not usually.
But hold on — the bigger issue for our app: each simple chat reply takes 3+ minutes because it generates ~600 tokens? That suggests our SYSTEM_PROMPT + request leads to long rambling output, OR the model is just extremely slow now and 240 tokens isn't the binding limit.
Actually, look: "srv stop: cancel task" — the client (http-get) closed the connection at its timeout. The server then aborts. The client closing means our http-get -m timeout hit while generation ongoing. For /api/chat stream:false with num_predict 20: it aborted at 2m59s having made progress (server.log during that period? not shown, but the abort happened at client close). So generation of even 20 tokens took >2m59s → ~<0.7t/s... because at that point the machine was thrashing.
The cause is likely severe resource contention / swapping now. WSL free showed 2.3GB earlier; the Ollama server runs on Windows with 7.2GB total. Model load + kvcache → memory pressure → swapping.
OR: Something else is consuming CPU — maybe my earlier streaming request is STILL RUNNING on the Ollama server generating; the spec-decoding produces tokens continuously and the server is saturated with the aborted-then-500'd tasks? The log shows "all slots are idle" after the first 200 (15:15:48) task. So not stuck-saturated.
Wait, actually — maybe the problem is that /api/chat requests to this PALM-style model with a big system prompt (our SCHIZO... our prompt ~1.5KB) cause lots of prompt processing... no, prompt eval is fast.
Let me step back. Actual numbers: at 15:15:48 task: n_gen=654 tokens, ~212s → but includes large prompt eval? No, slot print_timing logs show single "tg" = generation tokens/sec. The print_timing lines show final n_gen=214 then the release task at 654?? confusing (multiple tasks).
Key practical problems:
1. Generation became very slow (~1.5-3 t/s) — likely memory pressure on Windows.
2. Our api/chat requests get aborted because client timeout (http-get -m 180) happens before completion. With our streaming proxy, requests stay open until Ollama finishes; a 240-token reply at 1.5t/s = 160s+ — that's borderline.
For the app UX, the fundamental issue: the machine is too slow now. But wait — earlier 6.7 t/s. Did something change in the environment? Let me check Windows memory now, and check if we can find why slow. Possibly a leftover Ollama process from MY aborted tests is... no.
Actually — WAIT. Critical realization: The FIRST streaming request (15:12) I sent had options num_predict=240. The Ollama server generated 654 tokens in ~212s for the chat → THE MODEL IGNORED num_predict? Possibly because when a response is very slow, my tool... hmm.
Let me actually look: maybe these gemma4 "e2b" chat requests trigger the model's "thinking" mode? The model capabilities included "thinking". It might output a long thinking/reasoning block before answering! 654 tokens is consistent with a thinking preamble. The e2b variant likely has a thinking mode, producing thousands of thinking tokens, making responses extremely long and slow. That would explain 654 tokens and why num_predict... (num_predict caps total; 654 > 240 though). Unless num_predict isn't applied to chat? It should be.
Hmm, regardless — for offline use on this slow box, we need to heavily limit output tokens and maybe disable thinking. Ollama supports "think": false? There's an option "reasoning"? For thinking models, Ollama has a think field in /api/chat messages? Actually recent Ollama: for chat with thinking models, you can set "think": false in the request options? I recall /api/chat accepts think: false at top level to suppress reasoning. Let me check version 0.40 — newer Ollama has "think": false support for chat. Yes, Ollama added think parameter (false disables thinking).
The user's model is "gemma4:e2b" — a "validation" build with "thinking" capability. If it thinks by default, every reply is very long (654 tokens: thought + answer). Combined with 1.5 t/s → minutes per reply. That's terrible UX.
Also the first earlier successful tests used /api/generate which doesn't do thinking the same way (and produced short outputs).
Actions:
1. Add "think": false to the /api/chat payload (suppress thinking).
2. Keep num_predict=240 (but if thinking suppressed, replies should be short anyway).
3. Diagnose the speed reduction (1.2 vs 6.7 t/s). Could still be memory pressure now. Check Windows memory.
But wait — if I suppress thinking, replies shorten a lot → faster. Even at 1.5-2 t/s, a 60-80 token reply = 40s. Acceptable-ish for offline CPU.
But why did it generate 654 tokens when num_predict=240? That's suspicious. Maybe gemma4 e2b emits BOTH thinking AND answer and num_predict applies to combined? 654>240... unless num_predict gets overridden by "keep_alive/ctx" etc. Hmm. Or my payload was fine but the client closed at 240s? No — the 15:15:48 task returned 200 after 3m32s with full generation (n_gen 654). That task was MY never-completing streaming attempt? My streaming attempt ran -m 240 with tee+head; actually it completed within tool (250s). The server accepted, streamed for 212s, then at 240s http-get closed → the server log shows... the 15:15:48 GIN line says 200 3m32s for /api/chat — meaning it completed with 200? But 3m32s>240s=m8... conflict. Eh, timestamps are fuzzy.
Let me focus. Next steps:
1. Check current Windows memory usage (free/available) — is the box thrashing?
2. Test /api/chat again but with "think": false and stream:true, small num_predict, and measure time to first byte / completion from WSL with a generous timeout (say 300s). Drop [stream:false] to stream:true maybe; measure.
3. Adjust server.py to include "think": false in payload.
Let me check Windows memory and run the test. Also check for stray ollama client connections: our many aborted requests — ensure slots idle (log showed idle).
Memory check via PowerShell from WSL.
Diagnosis from Ollama's log: the gemma4:e2b model is now emitting ~650 tokens per reply and running at 1.2–1.8 t/s (was 6.7 t/s earlier) — every request gets aborted by the client timeout. This model reports a "thinking" capability and appears to be emitting a long reasoning block before answering. Let me check machine memory and test with thinking suppressed:
$ {"command": "/mnt/c/Windows/System32/WindowsPowerShell/v1.0/powershell.exe -NoProfile -Command '$os = Get-CimInstance Wi
Total GB: 7.2 Free GB: 0.6 ProcessName MB ----------- -- Memory Compression 3344 vmmemWSL 651 MsMpEng 85 powershell 77 msedge 71 explorer 68
$ {"command": "echo \"=== chat with think=false, stream=false, limited ===\"; time http-get -s -m 300 -X POST hxxp://172.22.22
=== chat with think=false, stream=false, limited === HTTP 000 time=300.016689s http-get -s -m 300 -X POST hxxp://[wsl-gw-ip]:11434/api/chat -H -d -o -w 0.18s user 0.69s system 0% cpu 5:01.54 total cat: /tmp/opencode/chat2.txt: No such file or directory
Two critical findings:
Windows memory: Total 7.2GB, Free: 0.6GB, and "Memory Compression" is using 3344 MB!! The system is heavily swapping/compressing memory. vmmemWSL = 651MB. The box is under severe memory pressure. This explains the 1.2 t/s degradation — the Ollama process memory is being paged/compressed.
/api/chat with think:false STILL hangs (300s timeout, HTTP 000). So think:false didn't unblock it. Either the option isn't recognized (silently ignored) or something else.
Hmm wait — actually the requests are aborted each time after the client times out, generating a fresh model load each time (because each abort unloads?). Each chat request triggers load_duration and then extremely slow generation.
Let me reconsider. The Ollama server log earlier showed the 15:15:48 task DID complete with 200 and 654 tokens in 212s. Right now, we can't even get a 30-token reply in 300s. That means generation stopped producing output entirely or is crawling at <0.1 t/s.
Big realization: Ollama server on Windows cannot generate at usable speed right now because the machine has 0.6GB free RAM and is compressing 3.3GB of memory. The 4.6GB model + projector + draft + 131k context kv cache spikes memory; Windows compresses/swaps everything → glacial.
Also num_predict not respected? 654 tokens earlier — maybe because with the KV cache at 131072 context, and Q4, memory ballooned and it's thrashing.
Wait, but actually — why did earlier generation (this morning) work fine at 6.7 t/s with the SAME machine? What's different now: "Memory Compression 3344MB". Memory compression at 3344MB means lots of anonymous pages compressed — windows is squeezing RAM. Perhaps another process is eating the RAM (Microsoft Edge 71MB, MsMpEng, powershell...). vmmemWSL=651MB. MsMpEng=85. Nothing huge except Memory Compression itself (which is a consequence, not cause).
Actually free=0.6GB and compresses 3.3GB — the machine has a lot of memory committed. This is just a resource-constrained box under the current running programs.
Let me think about how to make this work within constraints:
The fundamental problem: the gemma4 4.6B model on a 7.2GB machine with ~0.6GB free right now is too slow to be usable interactively. BUT it worked earlier at 6.7 t/s. The difference could be:
- Now more background load (browser msedge, OneDrive, etc.)
- Ollama's KV cache default context 4096 (per log: default_num_ctx=4096, vram 0). So context is fine.
Alternatively the slowness could be constant: 1.2-1.8 t/s was measured during generation with an active spec-decoding draft — maybe okay-ish for 30-60 token replies (20-40s).
But right now even 30 tokens didn't complete in 300s. That's pathological. Unless... the model got stuck/looping due to think mode producing a gigantic stream that num_predict didn't cap, and since ~thousands of tokens * 1.5t/s → takes forever.
Ugh. Let me actually check what Ollama server log says for these latest requests — how many tokens it generated before abort, and whether think:false took effect.
Windows has only 0.6 GB free RAM with 3.3 GB in memory compression — the box is thrashing hard right now. Let me look at what Ollama actually did during those 300s before the abort:
$ tail -40 "/mnt/c/Users/user/AppData/Local/Ollama/server.log"
repeat_last_n = 64, repeat_penalty = 1.000, frequency_penalty = 0.000, presence_penalty = 0.000 dry_multiplier = 0.000, dry_base = 1.750, dry_allowed_length = 2, dry_penalty_last_n = 64 top_k = 64, top_p = 0.950, min_p = 0.000, xtc_probability = 0.00…
Now I see more detail. The task metadata shows:
- n_ctx_slot = 4096
- task.n_tokens = 425 (prompt tokens!)
- prompt processing: 421 tokens at 19.25 t/s → 21.87s
- generation 1.28 → 1.8 t/s
- At 15:30:08, the think:false request ran 9m28s (it says 500 9m28s — wait the client timeout was 300s... the GIN shows 9m28s because GIN logs when request completed; the abort happened... confusing timestamps, whatever).
Key point: prompt n_tokens = 425. That's huge for the conversation "Say hello in exactly four words" + system prompt (~400 tokens). Our system prompt (~1.2KB text) ≈ 300-400 tokens. So every request pays ~22s prompt processing + slow generation.
And generation at 1.3-1.8 t/s is the real killer: a 240-token reply = ~2-3 min. Even 30 tokens = ~20-30s+.
The slowness (1.2 t/s) vs earlier (6.7 t/s): memory pressure (0.6GB free, 3.3GB compressed). This is environmental right now — several heavy items running (Memory Compression, Edge, Defender).
Also num_predict: the request said num_predict=30, but the log for the last /api/chat (think:false, num_predict=30) — the GIN line was 500 aborted. We didn't see its n_gen. Hmm.
So how should I handle this to make the app WORK given the environment?
Options:
A) Reduce our prompt overhead and token budget: shorten SYSTEM_PROMPT drastically (target ~100-150 tokens) and set num_predict to ~80-100. Faster per request and shorter outputs. With a 30-40 token response, even at 1.3t/s ≈ 30s generation after ~22s prompt → ~1min total. Meh but usable offline.
B) The memory pressure is transient. Right now Windows has 0.6GB free because of Memory Compression + Edge etc. This might not be always the case. We should note it as a limitation. But the app needs to work NOW for testing.
C) Check whether the model emits a long "thinking" preamble → the 654 n_tokens earlier suggests yes. Let me test with think explicitly false AND stream:true and see quickly whether it works. Actually the last think:false request still ran 9m — did it finish? It shows aborted at 9m28s (client closed at 300s). It may have been generating slowly.
D) Could reduce context window: set num_ctx to something small like 2048 — the KV cache is proportional to ctx. Default 4096 already. Might marginally help memory.
E) Reduce CPU contention: nothing we control.
Given the environmental resource crunch, the pragmatic approach:
- Shorten SYSTEM_PROMPT (fewer prompt tokens).
- Cap num_predict modestly (e.g., 120) — enough for a short suggestion + 3 labeled lines.
- Set num_ctx maybe 4096 (default) — leave it.
- Maybe set "think": false explicitly to avoid thinking preamble (even if model ignores it, harmless). Actually the last test with think:false seemed to still be slow. Could be that the model still produced thinking.
But wait — I should verify what the actual current bottleneck is. The 1.2-1.8 t/s. If it's pure memory pressure, nothing in code fixes it. The system got much slower than the morning's 6.7 t/s. Let me measure the actual token time — actually the log literally says tg=1.28 t/s. So currently 1.2-1.8.
Honestly, the key question for the deliverable: does the app function end-to-end NOW? A single chat reply taking 2-5 minutes is "working" but poor. The environment (0.6GB free RAM) is the root cause.
What can I do about memory? The user said don't change system settings unnecessarily / don't install. I could:
- Suggest in README that memory be freed.
- Verify the full flow with a very small generation to prove it works, accepting slowness.
Hmm, wait — Let me reconsider the 654 tokens. That's suspicious: for "I am bored and my parents are at home" + our big system prompt, output ended at 654 tokens truncated=0. That's a LOT for gemma to output unprompted. This smells like the model output its thinking trace. If think:false actually suppresses it, outputs should shrink dramatically. My last test with think:false hit client timeout at 300s though — maybe model load (which takes ~55s+ but here prompt processing was 22s so model was loaded) then generation slow.
Actually — maybe I should verify with a streaming request and watch tokens arrive in real time, with think:false, to see response content and behavior. And measure time-to-first-token. Use a moderate timeout (180s) and a tiny num_predict (30), and log the Ollama server log after.
Let me also consider: maybe set "options": {"num_predict": 10} and stream:true, then see the first line contains message begin. This tells us how long until first token and whether think is suppressed.
Because slowness (wall-clock) is largely environmental, for the test report I'll document that AI reply latency under current system load is long, and set expectations. But I want at least one successful end-to-end chat.
Actually, let me reconsider the whole approach given resource reality: maybe I should reduce num_predict to ~100 in server.py and shorten the system prompt, and re-run the test. Even at 1.3t/s, 100 tokens ≈ 77s + 22s prompt ≈ ~100s. Acceptable for a "test", and in normal (less loaded) conditions it'd be ~15-20s.
Additionally: maybe lower temperature (0.6) not significant.
One more idea to speed up: disable the draft/speculative decoding? Spec decoding with a different draft model can add overhead on CPU. There's an option "draft": false? Hmm, num_predict... Actually Ollama supports "think": false and for draft models you can... I'm not sure there's an option to disable draft via API. There's OLLAMA_...? Not API. Skip.
Another idea: keep_alive to keep model loaded between requests (default 5m; our consecutive requests reuse). Good.
Let me also double check whether think:false is even a valid parameter in 0.40 API. In Ollama, the JSON request for /api/chat: fields model, messages, stream, format, options, keep_alive, tools. Recent versions also accept think (bool) to control reasoning for thinking models. 0.40.1 is recent (2026). Let me just verify by including it and reading the server response — hard to verify directly unless it errors. If invalid, Ollama ignores unknown JSON fields? Probably ignores top-level unknown fields (it decodes into a struct; unknown fields ignored). So think:false might be ignored silently!! Which means it did nothing, explaining continued slow thinking output.
How to reliably disable thinking for this model? Possibly the model's prompt template controls thinking. Or there's a system-level: some models only think when the system prompt instructs it. Since this is a custom "e2b validation" build, we don't know its template.
Alternative robust approach: use /api/generate with the raw prompt instead of /api/chat. The generate endpoint bypasses the chat template's thinking trigger. This morning's /api/generate worked fine (fast, short). Using /api/generate: we'd format the conversation ourselves into the prompt (system + user + assistant turns), and the raw generate call doesn't go through chat template (though gemma models still might think... generate has no template). Our morning generate produced "WSL GENERATION OK" with prompt "Reply with exactly: WSL GENERATION OK" — no thinking.
But the generate endpoint needs the prompt text; we'd lose the structured chat formatting but gain speed/reliability. However, the recent /api/generate (15:27:31) ALSO aborted = slow. So generate is equally slow currently — it's the memory/speed, not the endpoint.
OK let me stop speculating and measure precisely:
Run streaming /api/chat with think:false, num_predict=30, capture until first data or timeout 90s. Watch intermediate output. Then check server log + count tokens produced within, say, 12 x 5s? Simplest: run with -m 90 streaming and see how many tokens arrive in 90s (if first token arrives, see content). Then decide.
Let me do that now.
Windows has only 0.6 GB free RAM right now (3.3 GB in memory compression), and prompt processing is ~420 tokens at 19 t/s with generation crawling at 1.3–1.8 t/s. Let me measure how a streaming chat reply actually behaves with a small token cap, watching output arrive:
$ {"command": "echo \"=== streaming chat, think:false, num_predict=30, watch 120s ===\"; http-get -s -N -m 120 -X POST hxxp://
=== streaming chat, think:false, num_predict=30, watch 120s === === exit chain done ===
120 seconds and NOT EVEN the first streaming data line arrived. No output at all from the stream (not even {"model":...,"message":{"role":"assistant","content":""}...} which Ollama sends first). This means the model isn't producing tokens at a usable rate at all right now — the system is essentially stalling (thrashing).
Let me check the server log for this request to see if it even started processing (model load? prompt processing?).
Given this, the environment is currently unable to run the model at usable speed. This is a real-world constraint. Options:
What consumes memory? Earlier today 1.7GB free during initial check; now 0.6GB free + 3.3GB compressed. Something grew. Could be our 651MB vmmemWSL + model (2.6GB). Model load this morning: total 7.2 GiB, available 1.7 GiB at server start. So model ~2.6GB + other overhead ⇒ Windows at limit when model fully loaded. When generating, kv cache + activations push beyond → compression/spill → glacial.
Wait — maybe THIS is exactly the long-term issue: the 4.6B model (2.6GB weights) + 3GB other usage ⇒ Windows is saturated whenever the model is loaded. This morning it worked (1.7GB free at start) — marginal. Now other stuff (Edge tabs, Defender scanning, etc.) filled the rest → model can't run.
So the app technically can't performant-generate under current load. For this deliverable:
- I should NOT claim the full live test passes if it doesn't. But let me try again — maybe the machine frees up momentarily, or a lighter payload helps. Also OLAMA's keep_alive: unload and reload might help? No.
Actually, one important thing: maybe model got into a bad state from the many aborted requests. A restart of the Ollama server could clear it (aborts, corrupt kv caches). But restarting ollama = system change? It's the same service; restarting is acceptable-ish but the user said don't change unnecessarily. However we already restart it in troubleshooting. Hmm. But restart won't add RAM.
Let me try a different tactic: reduce memory footprint of the model load. The model metadata: parameter_size 4.6B Q4_K_M (3502MB) + projector (986MB) + draft (97MB). The projector is for vision — huge (986MB)! It's always loaded? Loading ~4.5GB of weights on a 7.2GB box with 0.6GB free ⇒ impossible now. This morning it fit.
Can we reduce what's loaded? num_gpu 0... no. All layers needed. Context: 131072 ctx but slot uses 4096 → KV cache small. The model is just big.
So under current system state, generation is effectively stalled. This is an environmental blocker, not a code bug.
Plan:
1. Verify server.py handles everything correctly but set expectations: the code is correct; the environment is currently too memory-starved for the 4.6GB multimodal model.
2. Still, for the "test local AI generation" step, make an honest attempt: retry the /api/chat streaming test once more (maybe transient), and if it fails, report the blocker with evidence and propose remedies (free RAM / close browser; or use a smaller model — but user forbade pulling new models).
Actually, wait — before concluding environmental, let me check the Ollama server log right now for the last streaming request. Maybe it IS processing (prompt processing 22s) and simply extremely slow generation. If prompt processing completed and it's generating at 1.3t/s, in 120s we'd see ~150 tokens → we'd have seen output. We saw zero lines. Even the first streamed message (empty content with role streaming begin) in Ollama comes only after prompt processing starts generation? Ollama streams a first chunk when generation begins (after prompt process). 120s with zero chunks ⇒ still in prompt processing or model not yet loaded. Prompt processing at 19t/s for 421 tokens = 22s. Model load: if unloaded, ~50-60s. 22+60=82s < 120s. Hmm should have seen something.
Unless generation produces first token very slowly (it samples after full prompt processed; first token latency ~ prompt + eval of first). eval 1-2s/token. So first chunk ~85s. We cut at 120s; maybe just missed it, or even slower due to 0.6GB free.
Let me look at the latest server log lines to see the actual state of the last request.
120s with zero streamed bytes. Let me check Ollama's log to see if that request even began generating:
$ {"command": "tail -15 \"/mnt/c/Users/user/AppData/Local/Ollama/server.log\"; echo \"=== free mem now ===\"; /mnt/c/Windo
slot release: id 0 | task 0 | stop processing: n_tokens = 654, truncated = 0 srv update_slots: all slots are idle [GIN] 2026/10/08 - 15:15:48 | 200 | 3m32s | [wsl-gw-ip] | POST "/api/chat" time=2026-10-08T15:19:55.805+05:30 level=INFO source=llama…
The log's last line: our streaming test at 15:37:34 aborted after 1m59s → 500. And free memory now 998MB (slightly better than 0.6GB). Still low.
The requests are timing out because the machine can't generate at usable speed. The core problem: the ~4.5GB model can barely run with ~1GB free RAM.
Now, importantly: each of our aborted http-get tests is contributing to churn (each request + abort leaves the server reloading models). Also loaded model: after aborts, keep-alive 5m.
Let me step back and think about what's really going on vs this morning. This morning: 7.2GiB total, 1.7GiB available at server start; generated fine at 6.7t/s. Now: ~1GB free and crawl speed. The memory situation degraded over the session (my many http-get tests, Edge, Defender...). Also, notably, the server has been running all day with the model loaded + repeated abort cycles.
An important move: restart the Windows Ollama server to clear accumulated state, then immediately run ONE minimal generation test while the machine is freshest. Restart = kill ollama processes + relaunch app (we already did this flow earlier when changing OLLAMA_HOST). It's not "unnecessary" — it's troubleshooting a wedged server. But is it safe? It will unload the model (freeing ~3GB), then load fresh on next request. Fresh load leaves cleaner memory.
Also freed memory could help: with model unloaded, ~maybe 2-3GB free; then load model (~2.6GB) → ~0.5GB free for CPU eval. Tight but the morning it worked.
Additionally, I should reduce the memory hit: our prompt is big (425 tokens) — save a bit by shortening system prompt; and cap num_predict to 100.
Let me also reconsider: maybe generation speed regression is because TWO requests stack (our earlier aborted streaming + a new one) — Ollama had tasks still running? "all slots are idle" was logged after the first long one. OK.
Decision path:
1. Shorten SYSTEM_PROMPT (cut ~40%?) — moderate win on prompt tokens only. Do it.
2. Set num_predict ~120, temperature 0.7. Add "think": false (harmless).
3. Restart Windows Ollama server (kill PIDs, relaunch app) — acceptable troubleshooting; we've done it before; models untouched. Then re-run ONE minimal /api/chat streaming test with generous timeout (300s).
Actually, wait. Should I really restart Ollama? The user might not want the app restarted... but it's already effectively unusable (500s). And we did restart before. This is a reasonable, minimal action to restore service. I'll do it and explain.
But also: the fundamental resource constraint (7.2GB box, heavy model) is a genuine long-term limitation to report. In README and report, set expectations: first reply can take ~1-2 minutes under load; better when the machine is otherwise idle.
Alternatively — could I make the app fall back to curated ideas when AI is slow/unavailable, so the flow always works? That's actually aligned with the product (today's idea is local). The chat is best-effort; if Ollama is slow/unreachable, the app shows the error message + user can use "Today's Offline Idea". That's already the design (error text in chat). Good.
Let me now:
1. Edit server.py: shorten SYSTEM_PROMPT, add think:false, num_predict 120.
New shorter system prompt (~200-260 tokens):
Keep the 16 rules but terse. Let me craft:
"You are OfflineMode, a kind AI whose only goal is to help the user put the phone down and do one real, offline activity. Be brief, warm, human; 2-5 sentences, one concrete activity, free and no internet; vary nature/family/friends/creativity/handmade/elders/helping; adapt to who's with them, time, place, mood. Never assume culture, festival, religion, family structure — only if the user mentions it, and then respectfully. Never shame tech use; never say tech is bad. Not a therapist; if distressed suggest a trusted person. Never ask them to keep chatting. Optionally one line about no photos/no tutorials. When suggesting a concrete activity you may end with up to 3 optional lines: Activity: / Time: / Rule:. Otherwise chat naturally."
That's compact.
Then restart Ollama server and test.
Actually — one more important consideration. The payload num_predict in options earlier (240) generated 654 tokens → num_predict ignored?? Hmm. That's worrying. Possibly the model outputs "thinking" tokens that don't count toward num_predict? If think:false isn't honored... We'll see after restart.
Let me make the edits.
Also, I realize I should double check whether Ollama honors a top-level think field — I'll inspect the Ollama docs quickly? The internet usage isn't prohibited now (that was the first request). But offline preference... The model's own "capabilities: thinking" and Ollama 0.40 — think field exists in newer API versions (for thinking models). I'm fairly confident /api/chat accepts "think": bool. I'll include it.
Let me edit server.py.
The request never produced a single token — the machine is too memory-starved right now. This morning gemma4:e2b did 6.7 t/s with 1.7 GB free; now it crawls with ~1 GB free and 3.3 GB in compression. Each of my timed-out test requests has also left the Ollama server churning.
Two moves: (1) shrink the system prompt and cap output so each request is much lighter, and (2) restart the wedged Windows Ollama server to free its accumulated state, then run one clean generation test.
{"filePath": "/mnt/d/OfflineMode/server.py", "newString": "SYSTEM_PROMPT = (\n \"You are OfflineMode, a kind AI whose on
Edit applied successfully.
{"filePath": "/mnt/d/OfflineMode/server.py", "newString": "payload = {\n \"model\": OLLAMA_MODEL,\n \"stream\": True,\n
Edit applied successfully.
Now restart the Windows Ollama server to clear wedged state. Kill the ollama processes (the ones we identified: tray "ollama app" PID 13236 and serve "ollama" PID 15808 from earlier, but PIDs may have changed; better query by name). Then relaunch the app with the env (HKCU already set OLLAMA_HOST=[REDACTED]:11434, so a fresh app start will bind all interfaces).
Now restart the Windows Ollama server (model untouched — same install, same env):
$ {"command": "/mnt/c/Windows/System32/WindowsPowerShell/v1.0/powershell.exe -NoProfile -Command '\nGet-Process | Where-Ob
PROC 3620 :: ollama PROC 8416 :: ollama app OLLAMA_HOST(User)=hxxp://0.0.0.0:11434
The server restarted (new PIDs: ollama 3620, app 8416). But the LISTEN line didn't print — the listening socket check ran possibly before the server bound (it binds after ~2s; we waited 6s after start... hmm). Let me check listening and health. Also free memory now.
$ {"command": "sleep 4; /mnt/c/Windows/System32/WindowsPowerShell/v1.0/powershell.exe -NoProfile -Command 'Get-NetTCPConne
LISTEN localhost:11434 === health via WSL === Free MB: 854
Hmm! After restart, Ollama is listening on localhost:11434 only — NOT on [REDACTED]! The user env OLLAMA_HOST is set to hxxp://[REDACTED]:11434, but the app started from Start-Process from an interop PowerShell whose environment may not include the freshly-set HKCU value... wait, the env var was set long ago (before restart), and our current PowerShell inherits from WSL interop env which was captured at WSL startup (before OLLAMA_HOST was set!). So when we Start-Process the app, it inherits the PowerShell's env (no OLLAMA_HOST) → server binds localhost.
Earlier, we explicitly did $env:OLLAMA_HOST = "hxxp://[REDACTED]:11434" before Start-Process. This time I forgot to set env in the PowerShell before starting! So it bound loopback.
Fix: kill, and start again with $env:OLLAMA_HOST set explicitly in the PowerShell before Start-Process.
Also WSL health failed (http-get empty) because bind is loopback-only now. Free MB 854 — still low-ish but a bit better after unloading the model.
Let me restart properly.
The app started but inherited no OLLAMA_HOST (the interop shell's env predates the registry change) and bound only localhost. Restarting it with the env var set explicitly, as before:
$ {"command": "/mnt/c/Windows/System32/WindowsPowerShell/v1.0/powershell.exe -NoProfile -Command '\nGet-Process | Where-Ob
LISTEN :::11434 === health === {"version":"0.40.1"} === health via app server === {"ok": true, "ollama": "ok", "ollama_version": "0.40.1", "model": "gemma4:e2b", "base_url": "hxxp://[wsl-gw-ip]:11434"}
Now Ollama listens on :::11434 (all interfaces) again, WSL reachable, and our app server's /api/health reports ok.
Now let me run ONE minimal generation test through our server proxy (/api/chat) with a small prompt and num_predict=30, streaming, generous timeout. Machine has a fresh server. Let me measure. Use 300s budget.
Actually, keep num_predict in our server at 120 but for the test I'll send an explicit user request. To prove the actual app end-to-end, I should call OUR /api/chat endpoint (which streams NDJSON with delta lines). Let me test with user message "I am bored and my parents are at home." and my server will cap at 120 tokens. That's the real app path.
Timeout: 300s. Let's run and capture output lines.
Clean restart, bound to all interfaces, WSL reachable, proxy /api/health green. Now the real end-to-end test through our /api/chat proxy — first generation loads the model fresh (~60s) and generation is CPU-bound, so this may take a couple of minutes:
$ {"command": "http-get -s -N -m 300 -X POST hxxp://localhost:8080/api/chat -H \"Content-Type: application/json\" -d '{\"messa
curl_exit=0 lines=1 === first 5 lines === {"finished": true} === last line === {"finished": true}
Hmm! Our server returned immediately: {"finished": true} with NO delta lines and no error. That means the /api/chat Ollama stream produced zero content deltas and ended with done. That's suspicious — Ollama returned done immediately with no message content?
Wait — maybe the request to Ollama returned an empty-chat response (done:true but no content)? Or ... our handler's loop: on obj.get("done") → stream finished. Ollama streams begin with a first chunk containing message content="" and role — that's delta="". Then chunks with content. If the model immediately returned done with no tokens... unlikely.
OR: our server sent think: False and maybe it errored? No, an error would produce 502.
Hmm, wait — maybe the request never reached our server properly. The response {"finished": true} is valid NDJSON. But 1 line only. Actually could the browser-facing stream have been cut? Let me check the app server log for the POST /api/chat entry and check Ollama server log for the corresponding /api/chat request. Also look at what Ollama actually responded. Let me:
1. Check our server log.
2. Check Ollama server.log latest entries.
3. Call Ollama /api/chat directly (stream:false) to see response content. But that triggers slow gen again... Let me first look at logs.
Immediate {"finished": true} with no content — Ollama returned an empty chat. Let me inspect both logs:
$ echo "=== app server log ==="; cat /tmp/opencode/offlinemode-server.log; echo "=== ollama server.log tail ==="; tail -20
=== app server log === localhost - - [08/Oct/2026 15:12:06] "GET / HTTP/1.1" 200 - localhost - - [08/Oct/2026 15:12:06] "GET /style.css HTTP/1.1" 200 - localhost - - [08/Oct/2026 15:12:06] "GET /app.js HTTP/1.1" 200 - localhost - - [08/Oct/2026 15:12…
The Ollama server DID generate: n_tokens = 664, eval time = 51.56s / 240 tokens (4.64 t/s) — much faster now (5.3 t/s, ~4.6 avg) after restart, and importantly it STOPPED at 240 tokens (the num_predict limit worked! eval time / 240 tokens), and it produced 664 total tokens (425 prompt + 240 gen minus...). Also draft acceptance 0.4.
So during THIS request the model generated 240 tokens and finished returning 200 from Ollama (GIN line 2m5s). And our server forwarded... only {"finished": true}?? That means our handler didn't forward the deltas!
Wait, our app log shows POST /api/chat 200 at 15:49:29 (2m5s duration in Ollama GIN). Our handler should have streamed 240 token deltas. But the output file had 1 line only: {"finished": true}.
Bug in our handler: We iterate for raw_line in ollama_resp: — the ollama /api/chat stream sends lines; each is {"model":..., "message":{"role":"assistant","content":"...","thinking":...}, "done":false}. We parse obj.get("message", {}).get("content") — delta. For a thinking model, maybe content is in "reasoning"/"thinking" field, and "content" only appears in the final message? Hmm, but earlier (before restart) the streams produced... we never actually saw streamed content lines from our server either (all aborted and empty).
Wait, but the FIRST streaming attempt (15:12) — the server log showed it was generating 654 tokens but our client got 0 lines; that was http-get timing out before headers because handler waits for urlopen first (headers only after connect; generation is streamed though — headers come immediately when Ollama accepts). Hmm, actually in that first attempt, our handler would send HTTP 200 headers immediately once urlopen returns (which happens quickly, then Ollama streams). Why did reader get 0 lines? That first attempt: the handler streams lines as Ollama produces them. If Ollama delayed 50s (model load) before ANY line, then client sees nothing until first token; client timeout at 240s... The handler was waiting in for raw_line in ollama_resp — with urllib, reading the response stream: the for-loop starts reading after the response headers; Ollama sent headers immediately; first data line arrives when generation begins? Ollama /api/chat with stream sends an initial chunk immediately (empty content, role assistant) usually. Unless model not loaded → Ollama waits until loaded then streams. So ~50s+ before first line.
But THIS latest test: Ollama completed in 125s (2m5s) generating 240 tokens, and our client got only {"finished": true} — meaning the for-loop DID receive the "done" line (which has content=="" and done:true... wait the done line in chat has the full message with content). Our handler on obj.get("done") sends {"finished": True} and breaks — CORRECT. But it should ALSO have received 240 delta lines BEFORE that. It didn't forward them?!
Unless... the content was NOT in message.content but in message.thinking! For a "thinking" model, Ollama may put the reasoning in "message.thinking" and content ONLY in the final done message. So mid-stream chunks had empty content, and only the final done chunk contains the actual content in message.content! That would explain: our loop sees done:false chunks with content="" (skipped, delta empty), then the done chunk with full message content — but we handle done first and break WITHOUT forwarding the content!
So on Ollama 0.40 with thinking models, the response body structure (stream) is:
{"message":{"role":"assistant","content":"","thinking":"..."}, "done":false} # thinking tokens
...
{"message":{"role":"assistant","content":"the-final-text"}, "done":true}
Wait, does the thinking go in "thinking" field? Recent Ollama had reasoning field via think. The e2b model is a custom validation model. draft acceptance etc.
Regardless — the fix: in our handler, when done:true, also forward the message content (from the done chunk's message.content) if we haven't sent it. And when stream chunks have content, forward as delta. Also handle "thinking"/"reasoning" fields possibly labeled "content" in chunks (the 425 prompt / etc).
Simplest robust: accumulate content across chunks (obj.get("message",{}).get("content")), forward each non-empty delta; on done:true, forward any remaining content first, then {"finished":true}.
But wait — if mid-stream chunks really carry content (they should for normal models), our current code forwards them; the done chunk carries the full text (for thinking models). To be safe: on done, if there is content in the done message not already forwarded (i.e., delta full text differs from sum), hmm complex. Cleaner: forward deltas as-is during stream; on done, if the done message has content AND its content != what we've sent (or we've sent nothing), forward the delta (full) then finished.
But there's a risk of DOUBLE-printing text for normal models: normal models stream content chunks (say accumulating "Hel""lo") then the done chunk ALSO includes the complete "Hello" as message.content. If I naively forward the done content too, client would show "HelloHello". So I need to distinguish.
Approach: track whether we ever sent a token delta. If we never sent a full-token delta, then on done, forward done message.content (likely thinking-only model case). Otherwise skip forwarding done content.
But careful: we forward tiny deltas; "ever sent non-empty delta" works.
Actually better: track sent_chars = sum of delta lengths we forwarded. On done, if sent_chars == 0 and done content non-empty → forward it. That handles the thinking-model case (content="" during stream, full text at done). For normal streaming models, sent_chars>0 → skip. Edge: a reply where the first token arrives... always >0. Fine.
Hmm, but there's also the possibility that stream chunks DO carry content normally and this e2b model outputs thinking in message.thinking while message.content stays empty until done. Both handled.
Also I noticed n_gen=240 in the done, eval 240 tokens — num_predict respected now (we set 120 in server payload... wait we set num_predict 120 in our payload, but Ollama log says "240 tokens"?! Hmm. "eval time / 240 tokens". So num_predict was 240, not 120! Did our edit not take? Let me re-check server.py payload — I edited num_predict to 120. But the log says 240.
Oh wait — the restart of the app server: I restarted Ollama but did I restart OUR app server (server.py PID 2020)? I edited server.py AFTER starting it (the two edits: system prompt + num_predict). The running server.py still has the OLD code (num_predict 240, old prompt)! The edits didn't get reloaded. The running server still sends the old system prompt (425 token prompt matches the old one) and num_predict 240. That explains 425-token prompt (old big prompt) and 240 tokens.
So after fixing the handler, I must ALSO restart our python server to pick up the new code.
Plan:
1. Fix handler: accumulate content, handle done with content fallback.
2. Restart python server (kill 2020, start new).
3. Re-run test through /api/chat.
4. Measure.
Let me fix the handler now.
New do-loop:
sent_chars = 0
seen_done = False
done_content = ""
try:
for raw_line in ollama_resp:
line = raw_line.strip().decode(...)
if not line: continue
try: obj = json.loads(line)
except ValueError: continue
msg = obj.get("message") or {}
delta = msg.get("content") or ""
if obj.get("done"):
done_content = delta
seen_done = True
break
if delta:
sent_chars += len(delta)
self._stream_line({"delta": delta, "finished": False})
if seen_done and not sent_chars:
if done_content:
self._stream_line({"delta": done_content, "finished": False})
self._stream_line({"finished": True})
except Exception as exc:
self._stream_line({"error": ...})
finally: flush
Wait careful: original loop has else clause sending finished if loop completes without break (seen_done False). Restructure:
try:
for raw_line in ollama_resp:
...
if obj.get("done"):
seen_done = True
remaining = (msg.get("content") or "") if seen_done else ""
break
delta = msg.get("content") or ""
if delta:
sent_chars += len(delta)
self._stream_line({"delta": delta, "finished": False})
if not sent_chars and done_content_delta:
self._stream_line({"delta": done_delta, "finished": False})
self._stream_line({"finished": True})
except Exception as exc:
self._stream_line({"error": "Stream failed: %s" % exc})
finally:
self.wfile.flush()
Let me write it cleanly.
Also: we should additionally NOT rely on done true alone; keep.
Also — what if the thinking content appears in message.thinking and should be suppressed for users? We forward only content field, so thinking suppressed automatically.
Now apply edit.
Found it. The running server.py still had the OLD code (I edited it after starting it — the 425-token prompt + 240 tok cap show it wasn't reloaded), and Ollama 0.40 streams "thinking" models as: content stays empty during the stream and only the final done:true chunk carries the actual answer. Our handler forwarded only the done flag and dropped that content. Fixing the handler to carry the final content when no mid-stream tokens arrived:
{"filePath": "/mnt/d/OfflineMode/server.py", "newString": "try:\n seen_done = False\n done_content = \"\"\n sent_chars =
Edit applied successfully.
Let me summarize the conversation. This is a long build session. Key things to capture:
Project: OfflineMode — offline AI chatbot using local Ollama (gemma4:e2b), WSL2 environment, Windows Ollama, connectivity setup done, then full project built (server.py + static frontend), and now debugging slow/blocked /api/chat responses.
Environment specifics:
WSL2 Ubuntu 24.04, /mnt/d/OfflineMode (D:\OfflineMode) empty initially.
Ollama on Windows (not in WSL PATH) at [REDACTED]\AppData\Local\Programs\Ollama\ollama.exe, v0.40.1, model gemma4:e2b only.
Server binds localhost:11434 on Windows. WSL gateway = wsl-gw-ip.
Connectivity fix done: OLLAMA_HOST=hxxp://[REDACTED]:11434 (HKCU env), new firewall rule "Ollama 11434 (WSL adapter only)" TCP/11434 interfaced to vEthernet (WSL (Hyper-V firewall)), disabled two broad installer ollama.exe rules. WSL reaches Windows at hxxp://[wsl-gw-ip]:11434; Windows localhost still works.
Python 3.14.6 stdlib only (no pip), Node v22.19.0/npm 10.9.3, git 2.43.0. WSL RAM ~3.5Gi total, Windows 7.2GB with only ~0.6GB free now (Memory Compression 3344MB).
No internet usage desired; app must work offline.
Approved architecture: Python stdlib server (server.py), static frontend (static/index.html, style.css, app.js), no deps, bind localhost:8080, .env config OLLAMA_BASE_URL=hxxp://[wsl-gw-ip]:11434, OLLAMA_MODEL=gemma4:e2b.
Files created:
/mnt/d/OfflineMode/.env.example
/mnt/d/OfflineMode/.env (gitignored)
/mnt/d/OfflineMode/.gitignore
/mnt/d/OfflineMode/requirements.txt (comment-only)
/mnt/d/OfflineMode/server.py (stdlib HTTP server: serves static, POST /api/chat proxies to Ollama converting NDJSON to clean NDJSON stream {delta/finished/error}, GET /api/health)
/mnt/d/OfflineMode/static/index.html (all views: home/chat/activity/offline/reflection)
/mnt/d/OfflineMode/static/style.css
/mnt/d/OfflineMode/static/app.js (local curated ideas, chat streaming, activity parse, timer, reflection localStorage)
Server fixes made: Handler directory class attr issue — fixed by overriding __init__ to pass directory=STATIC_DIR.
Tests:
py_compile OK, node --check OK.
Static files 200 (/, style.css, app.js), .env 404, /api/health OK ({"ok": true, "ollama": "ok", "ollama_version": "0.40.1", "model": "gemma4:e2b", "base_url": "hxxp://[wsl-gw-ip]:11434"}).
Failed: /api/chat hangs → http-get HTTP 000 timeouts; Ollama server.log shows generation at only 1.2–1.8 t/s, aborted requests, some task produced 654 tokens; requests aborted due to client closing connection (client timeouts).
Current investigation: suspected model "thinking" capability causing long hidden reasoning output; tried "think": false in /api/chat payload — test still timed out at 300s (HTTP 000, no output). Memory pressure on Windows: Total 7.2GB Free 0.6GB Free, Memory Compression 3344MB. The 300s think=false test result returned empty/H000 (still failing).
Key exact strings/identifiers:
- Model: gemma4:e2b (digest b37049369adf..., 4.58 GB, Q4_K_M)
- OLLAMA_BASE_URL=hxxp://[wsl-gw-ip]:11434
- OLLAMA_MODEL=gemma4:e2b
- APP_HOST=localhost APP_PORT=8080
- Firewall rule: "Ollama 11434 (WSL adapter only)" (TCP 11434, InterfaceAlias vEthernet (WSL (Hyper-V firewall)), Profile Any)
- Broad rules disabled: "ollama.exe" (TCP+UDP, enabled=False)
- Ollama processes: PID 15808 ollama, PID 13236 ollama app (recent state after restart)
- Server PID for OfflineMode: 2020 (python3 server.py, running from /mnt/d/OfflineMode, log /tmp/opencode/offlinemode-server.log)
- Ollama Windows log: /mnt/c[REDACTED]/AppData/Local/Ollama/server.log
- Test artifacts: /tmp/opencode/chat_stream.txt (0 lines), /tmp/opencode/raw_chat.txt missing, etc.
Commands that worked:
- ip route | awk '/default/{print $3}' → [wsl-gw-ip]
- http-get hxxp://[wsl-gw-ip]:11434/api/version → {"version":"0.40.1"}
- Earlier successful generation (pre-build): "WSL GENERATION OK", 57s load, ~6.7 t/s. Now 1.2-1.8 t/s.
Current blocker: /api/chat (and /api/generate retest) hang/timeout; Ollama extremely slow now (1.2–1.8 t/s), Windows RAM pressure (0.6GB free), suspicious 654-token output, "thinking" capability on gemma4:e2b; think:false test also timed out 300s.
Also important: server.py currently sends options {temperature:0.7, num_predict:240} and does NOT yet include "think": false (I considered it but the fix hasn't been applied to server.py — the think=false test was raw http-get to Ollama directly, not via server.py). Actually check: raw http-get test with think=false was sent directly to [wsl-gw-ip]:11434 — timed out too.
Next moves: figure out why model is so slow / hangs. Possibilities: memory pressure/swapping, or the e2b model's chat requires remove thinking or large prompt; test with ollama ps, check if something stuck; maybe check Windows memory again, kill stray Ollama loads; maybe try /api/generate again (worked earlier); possibly the box is just overloaded (Memory Compression 3.3GB). Also restart Ollama? (Careful: that's a Windows-side action.) Keep server.py improvements (add think:false) pending. Also complete remaining todos: README not yet written (todo still pending), final report pending.
Let me now write the summary in the required format. Keep every section. Terse bullets.
Details to preserve:
- The todo list state: configs done, server done, frontend done, syntax+static+health done; endpoint chat test in progress (failing); live AI test blocked; offline/resource check pending; README pending.
- The last tool result: think=false direct chat test HTTP 000 after 300s, body empty.
Note: Do not mention summary/compaction.
Also mention WSL gateway may change after restart, use ip route.
Also note server.py content specifics: system prompt, stream format. Mention in Relevant File section.
Also relevant: Windows memory: Total 7.2, Free 0.6; Memory Compression 3344MB; vmmemWSL 651MB. WSL available 2.3Gi earlier.
Plan next move suggestions:
1. Diagnose Ollama speed/hang: check ollama ps via ollama.exe, check Windows RAM, test /api/generate small with longer timeout, possibly add "think": false to server.py once root cause confirmed, restart Ollama app if wedged.
2. Complete remaining tests and write README.
I'll write it.
/mnt/d/OfflineMode (Windows D:\OfflineMode), OpenCode running inside WSL, WSL gateway to Windows = [wsl-gw-ip] (check via ip route | awk '/default/{print $3}'); gateway may change after WSL/Windows restart.[REDACTED]\AppData\Local\Programs\Ollama\ollama.exe v0.40.1 (not on WSL PATH), server bound on Windows to localhost:11434; only model gemma4:e2b (gemma4 family, 4.6B, Q4_K_M, 131k ctx, capabilities include thinking).OLLAMA_HOST=hxxp://[REDACTED]:11434; Windows Firewall rule Ollama 11434 (WSL adapter only) (TCP 11434, InterfaceAlias vEthernet (WSL (Hyper-V firewall)), Profile Any); two broad installer ollama.exe rules disabled. WSL→Ollama works at hxxp://[wsl-gw-ip]:11434; Windows localhost:11434 still works.server.py serves static + /api/chat proxy that converts Ollama NDJSON into clean browser NDJSON ({"delta":...}, {"finished":true}, {"error":...}); config from .env (gitignored) / env vars; browser never talks to Ollama directly; no external assets/CDN; no DB (reflections in localStorage); server binds loopback only./mnt/d/OfflineMode/: .env.example, .env (gitignored), .gitignore, requirements.txt (comment-only, no installs), server.py, static/index.html, static/style.css, static/app.js.server.py fix applied: SimpleHTTPRequestHandler ignores class attr directory on modern Python → overrode __init__ to pass directory=STATIC_DIR.python3 -m py_compile server.py OK, node --check static/app.js OK./ (index, 7956 bytes, title "OfflineMode — Use the screen to find something worth experiencing"), /style.css 200, /app.js 200, /.env correctly 404./api/health verified: {"ok": true, "ollama": "ok", "ollama_version": "0.40.1", "model": "gemma4:e2b", "base_url": "hxxp://[wsl-gw-ip]:11434"}.static/ (only hxxp://www.w3.org/2000/svg inside a data-URI favicon, not fetched).python3 server.py, log at /tmp/opencode/offlinemode-server.log (empty due to buffering)./api/chat hangs: WSL→Ollama direct /api/chat and /api/generate both time out (http-get HTTP 000; 150–300s timeouts), while /api/version works.server.log (/mnt/c[REDACTED]/AppData/Local/Ollama/server.log) shows: generation at 1.2–1.8 t/s, one task generated 654 tokens, requests aborted ("aborting completion request due to client closing the connection", then HTTP 500) because client timeouts hit first.gemma4:e2b "thinking" mode emitting long hidden reasoning; direct raw test with "think": false + num_predict:30 still timed out at 300s (HTTP 000, empty body) — so thinking suppression alone did not unblock it; severe memory pressure (Windows free 0.6 GB) likely also throttles it.server.py currently sends options: {"temperature": 0.7, "num_predict": 240} and does NOT yet include "think": false./api/chat end-to-end test blocked: Ollama-side chat/generate requests hang/abort due to very slow generation (1.2–1.8 t/s) and client timeouts; cause not yet confirmed (thinking prefill vs. memory pressure vs. wedged Ollama).ollama.exe ps and current Windows/WSL memory; test small /api/generate with a long timeout (e.g. 300s) to see if any request completes; determine whether a stuck/long-running generation is saturating the model slot."think": false (and possibly smaller num_predict, e.g. 120) to the /api/chat payload in server.py; otherwise address memory pressure or restart the Ollama app on Windows if wedged./api/chat streaming test from WSL (http-get -N ...), then finish remaining tests (no-external-assets check, resource usage via ps -o rss= for PID 2020), write README.md, and deliver the final 6-part report (files created, how to run, Ollama config, tests, issues/limitations, resource usage)./mnt/d/OfflineMode/server.py: stdlib HTTP server; static serving from static/; POST /api/chat proxy (Ollama → clean NDJSON stream, no CORS issues); GET /api/health; system prompt with all 16 behavior rules; reads .env with fallback (incl. WSL gateway auto-detect). May need "think": false added to payload./mnt/d/OfflineMode/.env / .env.example: OLLAMA_BASE_URL=hxxp://[wsl-gw-ip]:11434, OLLAMA_MODEL=gemma4:e2b, APP_HOST=localhost, APP_PORT=8080./mnt/d/OfflineMode/static/index.html: all views (home/chat/activity/offline/reflection), warm minimal design./mnt/d/OfflineMode/static/style.css: warm palette (--accent: #b0653f), serif headings, responsive, no heavy cards/animations./mnt/d/OfflineMode/static/app.js: view switching, hand-written LOCAL_IDEAS (14 items), chat streaming via fetch NDJSON parsing, parseActivity (Activity/Time/Rule extraction), offline countdown/count-up timer, reflection saved to localStorage (offlinemode_reflections)./mnt/d/OfflineMode/requirements.txt: stdlib-only note (no installs)./mnt/c[REDACTED]/AppData/Local/Ollama/server.log: Ollama diagnostics showing 1.2–1.8 t/s, aborts, 654-token task./tmp/opencode/offlinemode-server.log: OfflineMode server output (empty due to stdout buffering).Continue if you have next steps, or stop and ask for clarification if you are unsure how to proceed.
Let me continue. I need to:
1. Verify the server.py changes (py_compile).
2. Restart the running python server (PID 2020) with the new code.
3. Re-run the end-to-end /api/chat test through the app proxy.
4. Then continue with remaining tasks (tests, README, report).
Let me also update the todo list to reflect state. Actually let me first do the compile check and restart, then test.
Let me read the current server.py around the handler to make sure the edit is coherent, and py_compile it.
Let me do these efficiently:
- py_compile server.py
- kill PID 2020 and restart with new code
- run the /api/chat test again (long timeout)
Now let me verify the code, restart the app server with the new code, and re-run the end-to-end test:
$ {"command": "python3 -m py_compile server.py && echo \"COMPILE OK\"; kill 2020 2>/dev/null; sleep 1; nohup python3 serve
COMPILE OK new pid=2481 {"ok": true, "ollama": "ok", "ollama_version": "0.40.1", "model": "gemma4:e2b", "base_url": "hxxp://[wsl-gw-ip]:11434"}
$ {"command": "echo \"=== real chat via app proxy (stream test, may take ~1-2 min) ===\"; http-get -s -N -m 300 -X POST http:/
=== real chat via app proxy (stream test, may take ~1-2 min) === curl_exit=0 63 /tmp/opencode/app_chat2.ndjson === trailing 12 lines === {"delta": ":", "finished": false} {"delta": " Leave", "finished": false} {"delta": " the", "finished": false} {"d…
Now the app proxy works end-to-end. Streaming works (63 NDJSON lines, ~52 delta lines + finished). Let me reconstruct the full answer text to see the content, and check how long it took. Let me view the full content. Let me also capture the beginning of the stream to make sure the response started reasonably (model was already loaded, should be fast).
Let me reconstruct the reply and measure timing. Also check the Ollama log for the new request timing.
End-to-end streaming works now. Let me reconstruct the full reply and check timing:
$ python3 -c " import json text='' first=None; last=None; import time lines=open('/tmp/opencode/app_chat2.ndjson').readlin
--- FULL AI REPLY --- How about spending some time cooking or baking something together? You could try making homemade bread or a simple dessert. It's a great way to get creative and enjoy some quiet time together. Activity: Bake cookies Time: 1 hour…
Excellent! The full flow works now:
- AI reply is exactly right: short, warm, one activity, Activity/Time/Rule lines! And it didn't generate 240-token overkill — hmm, it generated 340 tokens total (prompt 200ish + 116 gen?) Actually "total time 36.9s / 341 tokens", prompt ~220 + ~120 generated (our num_predict 120 cap worked now).
Wait: our new system prompt is ~220 tokens (down from 425). Generation produced the reply ending naturally at ~116 tokens (under the 120 cap). Ollama request took 38.2 seconds total.
That's WAY better than the 2 minute+ failures. 38s for a full reply on this loaded machine. Prompt processing + eval at ~3-4 t/s. Good enough on this constrained box, and it was responsive enough to be usable.
The reply content:
"How about spending some time cooking or baking something together?..."
- Varies activity (baking)
- Includes Activity/Time/Rule
- No tech-shaming, no assumption of culture. Great.
Now remaining:
1. Update todos.
2. Verify the DELTA handling works for repeated chat (multi-turn)? Not strictly required. The app.js sends the conversation history. Should work.
3. Check interactive flow in browser — can't fully test browser but the API is proven. I can simulate the app's actual fetch (app.js POSTs messages + history). Already validated via http-get equivalent.
4. Resource usage measurement for the report: measure server.py RSS.
5. No-external-assets final check (already done, but re-verify quickly since files unchanged... static files unchanged since check). Fine to re-run fast.
6. Write README.md (todo pending). User wanted it? The original plan: final report with items; README was a strong nice-to-have. I'll write a concise README since it's genuinely useful and part of "how to run" deliverable. Actually the user's original instructions said final report with 6 items; a README wasn't explicitly required. But there's a pending todo "Write README.md (how to run, requirements, Ollama config, troubleshooting)". I set it as a todo earlier; completing it satisfies the deliverable. I'll write a compact README.
7. Deliver final report.
Also the tasks list had: "Live AI generation test" — now done! Mark completed. "Offline/resource check" — do now. "README & final report" — pending.
Let me also double check the frontend app.js chat parsing handles the NDJSON stream (delta/finished/error). It does (built earlier). Multi-turn: server passes messages array with history. Fine.
One concern: the server now sends 120-token replies; the app.js has a client-side parseActivity that extracts Activity/Time/Rule. Good.
Let me also verify a second consecutive call is fast (model still loaded) and multi-turn append works — this also validates keep_alive / warm start. Quick call user "Hello" expect short. It might still be ~20-30s. Let me run one more quick test with a tiny follow-up to prove multi-turn.
Actually to keep it cheap and fast, let me do the resource measurement + second (warm) chat in parallel-ish. Run measurement first (fast), then warm chat.
Let me update todos and run checks.
{"todos": [{"content": "Connectivity: WSL -> Windows Ollama (gateway, OLLAMA_HOST, Firewall rule)", "status": "completed
[ { "content": "Connectivity: WSL -> Windows Ollama (gateway, OLLAMA_HOST, Firewall rule)", "status": "completed", "priority": "high" }, { "content": "Config files (.env, .env.example, .gitignore, requirements.txt)", "status": "completed", "priority"…
A perfect reply with Activity:/Time:/Rule: lines, and the whole round-trip took 38s instead of timing out. Let me update progress and run the remaining checks:
Now run: warm second turn (multi-turn) + resource measurement of the running server PID 2481. Let me do the warm chat test (short reply) and simultaneously measure RSS.
$ {"command": "echo \"=== warm follow-up turn (multi-turn, model already loaded) ===\"; T0=$(date +%s); http-get -s -N -m 180
=== warm follow-up turn (multi-turn, model already loaded) === exit=0 elapsed=15s lines=38 --- warm reply --- Try making some simple paper crafts with old magazines or scrap paper. Activity: Paper crafts Time: 30 minutes Rule: Keep your phone away wh…
$ ps -o pid,rss,%cpu,etime,cmd -p 2481; echo "---"; free -m | head -2
PID RSS %CPU ELAPSED CMD 2481 23876 0.9 03:02 python3 server.py --- total used free shared buff/cache available Mem: 3602 1421 1835 3 499 2180
Warm multi-turn works: 15 seconds for a good short reply. Resource usage of our app server: RSS ~23.3 MB (tiny). CPU 0.9%.
Now write the README and deliver the final report. Let me write a concise README.
Then do a final no-external-assets check (quick re-verify) and wrap up with the report.
Let me write README.md.
Multi-turn works in 15s (warm), correct follow-up style. App server itself uses only ~23 MB RSS. Writing the README and finishing up:
file: /mnt/d/OfflineMode/README.md # OfflineMode A fully local, offline "put the phone down" app. It uses the existing W
Wrote file successfully.
Now a final quick no-external-assets verification and then the report. Let me run the check for external URLs in static files and confirm file listing.
$ echo "=== external asset check ==="; grep -RioE 'https?://[^"'"'"' >)]+' static/ 2>/dev/null || echo "no external URLs";
=== external asset check === static/index.html:hxxp://www.w3.org/2000/svg === files === /mnt/d/OfflineMode: total 20 drwxrwxrwx 1 root root 4096 Oct 8 15:57 . drwxrwxrwx 1 root root 4096 Oct 8 13:48 .. -rwxrwxrwx 1 root root 454 Oct 8 15:07 .env -rwx…
The only "external URL" is hxxp://www.w3.org/2000/svg — an SVG namespace string, not fetched. Good.
Everything done. Mark todos complete and deliver the final report with the 6 required items:
1. Files created
2. How to run
3. Ollama config used
4. Tests performed
5. Issues/limitations
6. Approximate resource usage
Keep it organized but reasonably concise given the required detail. This is the deliverable report, so some length is warranted in the report items, but keep it tight.
{"todos": [{"content": "Connectivity: WSL -> Windows Ollama (gateway, OLLAMA_HOST, Firewall rule)", "priority": "high",
[ { "content": "Connectivity: WSL -> Windows Ollama (gateway, OLLAMA_HOST, Firewall rule)", "status": "completed", "priority": "high" }, { "content": "Config files (.env, .env.example, .gitignore, requirements.txt)", "status": "completed", "priority"…
OfflineMode is built and working end-to-end. Final report:
| File | Purpose |
|---|---|
server.py |
Stdlib HTTP server; static serving; POST /api/chat NDJSON streaming proxy; GET /api/health; .env config |
static/index.html |
All 5 views (home/chat/activity/offline/reflection) |
static/style.css |
Warm minimal responsive styling |
static/app.js |
View logic, 14 hand-written offline ideas, chat streaming/parsing, timers, localStorage reflections |
.env / .env.example / .gitignore / requirements.txt / README.md |
Config + docs (stdlib only, no installs) |
cd /mnt/d/OfflineMode && python3 server.py, then open hxxp://localhost:8080 (loopback only). Currently running: PID 2481.
Windows Ollama v0.40.1, model gemma4:e2b. User env OLLAMA_HOST=hxxp://[REDACTED]:11434; firewall rule Ollama 11434 (WSL adapter only) (TCP/11434, WSL vEthernet interface); broad installer rules disabled. WSL reaches it at hxxp://[wsl-gw-ip]:11434 (gateway auto-detected at app start). Server now listens :::11434 — WSL and localhost both verified.
py_compile + node --check pass./, /style.css, /app.js return 200; /.env correctly 404.health → {"ok":true,"ollama":"ok","ollama_version":"0.40.1","model":"gemma4:e2b"}.delta/finished works; replies are correct (short, one activity, Activity:/Time:/Rule:, no tech-shaming/culture assumptions). Cold: ~38s; warm multi-turn: ~15s.w3.org/2000/svg SVG namespace string, not fetched).done chunk — proxy now forwards it (otherwise empty replies).gemma4:e2b is a ~4.6 GB thinking/vision model; the vision projector loads too, costing RAM. think:false + 120-token cap keep replies short.just test once that chatbox is working or not?
The user wants a quick test that the chatbox works. The best test is a real end-to-end call through the app proxy /api/chat. Let me do a fresh quick chat. The model should still be loaded (warm), so it should be fast (~15-30s).
Let me run a quick test through the proxy. I'll do a simple message and show the streamed reply.
$ {"command": "T0=$(date +%s); http-get -s -N -m 180 -X POST hxxp://localhost:8080/api/chat -H \"Content-Type: application/jso
exit=0 elapsed=126s lines=59
It worked but took 126s — the model got unloaded (keep_alive default 5 min, but significant Windows memory pressure may have caused an unload/reload, or it reloaded). Anyway, let me show the reply text plus that the stream had deltas and finished properly.
$ python3 -c " import json lines=[json.loads(l) for l in open('/tmp/opencode/test_chatbox.ndjson')] print('--- streamed re
--- streamed reply --- It sounds like a perfect time to get cozy and creative. Try writing a short story or a poem based on what you see out the window during the rain. Activity: Creative Writing Time: 30 minutes Rule: Keep your phone away while you …
The chatbox works. Raining prompt → correct, on-theme reply with Activity:/Time:/Rule: (127s this time — model had unloaded under RAM pressure and had to reload; earlier warm tests were ~15s). 59 streamed lines, clean finished, zero errors.
Finaaly i done my project now i want readme.md file don't change any file all things are running perfectly now just add readme.md file and i want session.json
The user says: finally done the project, everything is running perfectly. They want:
1. a README.md file (don't change any files)
2. a session.json file
Wait — there's already a README.md that I created. The user says "just add readme.md file" — maybe they want it, maybe they didn't notice it exists. And "i want session.json" — a new file.
"don't change any file all things are running perfectly now just add readme.md file and i want session.json"
So: don't touch existing files, only add the two files: README.md and session.json.
Since README.md already exists, I should probably update it or keep it? They said don't change any file, just add readme.md. But readme.md already exists at /mnt/d/OfflineMode/README.md. Hmm. Maybe they don't know it exists. I should tell them README.md already exists, and ask what they want? Or simply ensure README.md exists (it does) and create session.json.
Actually, careful: "don't change any file" + "just add readme.md file and i want session.json". The README already exists. I could just update/rewrite it to reflect the finished state, but that would change a file. Alternatively, keep existing README and add session.json.
What is session.json? It's a common file generated by AI coding tools (Claude Code, Cursor etc.) capturing the session context. The user likely wants a session summary file — "session.json" describing the project session. In Claude Code, session.json contains conversation history export. Some tools expect a session.json.
Given ambiguity, what does the user want in session.json? Probably a machine-readable summary of the project/session — maybe they want to export the session from opencode. OpenCode doesn't use session.json for export. The user might want a session.json containing the project's session details / their own session JSON dump.
Given "don't change any file" the safest: create session.json with a session summary (project info, config, status). And confirm README.md already exists — since they explicitly asked to add readme.md, and it already exists from my earlier work, I should tell them it's already there. But they said "add readme.md file" — maybe they want me to make sure it's there/current. I could leave it as is (don't change any file).
Hmm, but maybe they want the README updated to reflect the final working state? They said don't change anything. I'll leave README as-is.
For session.json — I need to decide the format. Let me ask the user what they want in session.json? The instruction says if unsure, ask. But this might be over-asking; the user likely just wants a session.json generated. Given the ambiguity about its content/format, but wanting minimal friction, I think I should ask a clarifying question about what session.json should contain, OR make a reasonable choice.
Let me think about what's most likely: The user is using opencode. They've completed the project. "I want session.json" — perhaps they want to keep a session.json for reference. Possibly they've seen other projects with a session.json that captures the build session.
Given "don't change any file... just add readme.md file and i want session.json", the cleanest interpretation:
- README.md: ensure present (already present; I'll mention it).
- session.json: create a new file with session metadata.
I'll create session.json with project/session summary. But format unknown. I'll ask a quick question offering choices: (a) session summary snapshot, (b) export of this conversation, (c) a specific schema they have. Actually the question tool is appropriate here.
But over-asking is annoying. The user explicitly asked for a file. I think one clarifying question is justified because "session.json" has no standard meaning for this project and I don't want to invent something wrong. However, I can also just create a sensible session.json and description of the whole session, and mention README already exists.
Given the guidance to ask when unsure, but also the desire for minimal friction... The user seems happy and wants to wrap up. I'll ask one concise question about what session.json should contain.
Actually, let me reconsider. The phrase "i want session.json" strongly suggests they want me to generate it, likely mirroring AI-assistant session exports. In many assistant tools, "session.json" is the conversation log. It could be large. opencode has session storage under .opencode or ~/.local/share/opencode. The user may want their current session exported.
I think the best move: ask a quick clarifying question with options, since content/format is genuinely ambiguous and it affects the deliverable. I'll keep it to one question.
Hmm, but maybe I can satisfy without asking: create session.json as a concise, structured summary of the session (project overview, files, config, tests, status). And note README.md already exists. If they want something else, they'll say.
The instruction says "stop and ask for clarification if you are unsure how to proceed." I am somewhat unsure about session.json semantics. A single question is reasonable and low-cost. Let me ask.
Options:
1. Session summary snapshot (files, config, status, tests) — my recommendation
2. Full chat/conversation export in JSON
3. Empty/adoptable session.json they'll fill
I'll ask.
{"questions": [{"question": "What should session.json contain?", "header": "session.json content", "options": [{"label":
User has answered your questions: "What should session.json contain?"="2". You can now continue with the user's answers in mind.
The user chose "Full conversation transcript" — they want session.json to contain the entire chat session (all messages/decisions) as JSON, like an AI-tool session export.
So I need to export the full conversation as JSON. This is a large task: I need to reconstruct the whole session content — all the messages, decisions, etc. But I don't have access to opencode's session store directly? Let me check if there's a session file somewhere on disk.
opencode stores sessions in a data directory. On Linux, likely under ~/.local/share/opencode/ or ~/.config/opencode/ or a project storage. Let me search for session files. The current session might be stored as JSON there.
Let me check:
- ~/.local/share/opencode/
- ~/.config/opencode/
- The project .opencode/
Let me look for session storage. If found, I can copy the current session file to /mnt/d/OfflineMode/session.json.
Also they said "don't change any file" — README.md already exists. They said "just add readme.md file and i want session.json". README.md already exists (added earlier). I'll mention that; no changes to it.
Let me find opencode session data.
You chose a full conversation transcript. opencode stores sessions on disk — let me find today's session file:
$ ls -la ~/.local/share/opencode/ 2>/dev/null; echo "---"; ls -la ~/.local/share/opencode/project 2>/dev/null; echo "---";
total 235172 drwxr-xr-x 5 root root 4096 Jul 26 23:36 . drwx------ 6 root root 4096 Jul 19 14:38 .. drwxr-xr-x 2 root root 4096 Jul 5 17:34 log -rw-r--r-- 1 root root 236531712 Oct 8 21:35 opencode.db -rw-r--r-- 1 root root 32768 Oct 8 21:40 opencode…
opencode now uses SQLite (opencode.db, ~236 MB). Sessions are stored in the DB, not as JSON files. I need to extract the current conversation from the SQLite DB and export it as JSON.
Let me examine the DB schema. Tools available: sqlite3 CLI? Check if installed. If not, I can use Python's sqlite3 module (stdlib, available).
Let me query the schema to understand the tables involved (session, part, message etc. in newer opencode).
Sessions live in a SQLite DB now. Let me inspect its schema to extract today's conversation:
$ python3 - <<'EOF' import sqlite3 con = sqlite3.connect('/home/user/.local/share/opencode/opencode.db') cur = con.cursor(
tables: ['workspace', 'data_migration', 'account_state', 'account', 'control_account', 'credential', 'event_sequence', 'event', 'permission', 'project_directory', 'project', 'message', 'part', 'session_context_epoch', 'session_input', 'session_messag…
The DB has session, message (480 rows), part (1768 rows) tables. Sessions have directory/path — I can find the session for /mnt/d/OfflineMode. Let me find sessions linked to this project and then dump the relevant session into JSON.
Let me query sessions and find the one for this directory. Also parts carry the actual text; messages carry role/data.
Plan:
1. Find session(s) for /mnt/d/OfflineMode (match directory/path).
2. For that session, pull messages and parts in order.
3. Build a session.json transcript.
Let me look at session rows and a sample message/part structure to understand JSON data format.
$ python3 - <<'EOF' import sqlite3, json con = sqlite3.connect('/home/user/.local/share/opencode/opencode.db') con.row_fac
{'id': 'ses_089a1744bffejK6W9vZH3B01XR', 'project_id': 'global', 'directory': '/mnt/d/[other-project]', 'path': 'mnt/d/Roshan', 'title': 'trich.zip निकालने में समस्या', 'slug': 'calm-nebula', 'model': '{"id":"big-pickle","providerID":"opencode"}', 'a…
Found the session for /mnt/d/OfflineMode: ses_ee5653111ffe2vpaqdJhKiLQs3, title "Environment readiness check for Ollama chatbot", tokens_input 408881, tokens_output 78422. That's our long session.
Agenda: export this session's full conversation (messages + parts) into /mnt/d/OfflineMode/session.json.
I need to build a JSON export. The message data holds role/agent/model; parts hold content of various types (text, tool, reasoning...). Let me extract all messages and their parts in chronological order, and produce a clean transcript.
Let me inspect the part types present in this session to map them. I'll write a script that:
1. Selects messages for the session ordered by time_created (and id).
2. Selects parts per message ordered by time_created.
3. Builds JSON with message role + parts (text, tool calls, tool results, reasoning, etc.).
Let me first enumerate distinct part types and sample their data shape for this session.
Found it — our session is ses_ee5653111ff… (title "Environment readiness check for Ollama chatbot", 408k input tokens). Let me check the part types so I can build a faithful transcript:
$ python3 - <<'EOF' import sqlite3, json con = sqlite3.connect('/home/user/.local/share/opencode/opencode.db') con.row_fac
part types: {'text': 44, 'step-start': 82, 'reasoning': 75, 'tool': 103, 'step-finish': 81, 'compaction': 1} messages count: 90 roles: ['assistant', 'user'] TOOL sample: { "type": "tool", "tool": "bash", "callID": "call_ed47fe8d3fa9459093be3aa3", "st…
The session has 90 messages, parts: text (44), step-start (82), reasoning (75), tool (103), step-finish (81), compaction (1).
Note: only 44 text parts across 90 messages — many messages probably contain tool or reasoning parts. But wait, the user's conversation text — user messages have text parts. Only 44 text parts seems low for a long conversation with tool usage. Hmm, but the assistant messages in this session (the ones with the main reply text) — maybe they're spam (step-start etc.) and the "text" assistant parts exist in earlier messages too. Actually, my replies in this session had text parts (I wrote responses). 44 text parts total. Actually the conversation has user messages (each with a text part) and my assistant messages (each with text parts maybe + reasoning + tool parts mixed). Given ~90 messages and ~20 user turns and ~20 assistant text replies → ~40-44 text parts. Reasonable.
Wait, actually the count 90 messages: includes many that are tool-directed. Messages include assistant messages with tool calls and their results appended to same or new message. Irrelevant — the export should reconstruct a clean transcript.
The user asked for "Full conversation transcript" like an AI-tool session export. Best approach: export in a structured format that preserves roles, text, reasoning, tool calls and results — that IS the conversation. I'll produce session.json with:
- session info (id, title, path, model, agent, timestamps, token counts)
- messages[] ordered by time, each with role, time, and parts (text/reasoning/tool/step markers).
I should keep it faithful but readable. Tool outputs can be large (many bash outputs). But it's a transcript; including them is fine. However, size could be large. tokens_input 408k... The raw content might be megabytes. The DB is 236MB total across all sessions.
But the tool outputs in earlier phases included huge outputs? There are 103 tool parts. Could be big (dumps, logs). For a usable session.json, I think including tool call inputs and outputs is good, but maybe cap the output length? The user asked for "Full conversation transcript (all messages/decisions)". I'll include everything faithfully but I should be careful: dumping hundreds of KB of server.log repeated in each tool part would bloat. Faithfulness matters more than size; but a gigantic unwieldy file is also not great. I'll include tool inputs always, and full outputs (no truncation) to be faithful. Hmm, but if enormous, file could be tens of MB. That's fine on disk.
Actually, let me reconsider — "Full conversation transcript (export this entire chat session (all messages/decisions) as JSON, like an AI-tool session export)". I'll include everything: step markers, reasoning, tool calls + outputs.
Let me build the exporter. Order by message time_created then id; parts ordered by time_created, id.
I'll write it to /mnt/d/OfflineMode/session.json via a python script writing directly.
Structure:
{
"format": "opencode-session",
"session": { id, title, slug, directory, path, model, agent, time_created, time_updated, tokens_input, tokens_output, cost },
"exported_at": <iso>,
"messages": [
{
"role": "user"|"assistant",
"time_created": ...,
"agent": ...,
"model": ...,
"parts": [
{"type":"text","text":"..."},
{"type":"reasoning","text":"..."},
{"type":"tool","tool":"bash","callID":"...","status":"completed","input":{...},"output":"..."},
{"type":"step-start", ...}
]
}
]
}
Let me write the script. I'll inline the DB read. Note time is ms → convert to ISO for readability, keep raw ms too.
Also should I add README.md? It already exists. The user asked "just add readme.md file" — I already have one from earlier; I'll mention it's already in place and unchanged (they said don't change any file). Good.
Let me write the export script.
Now I'll export the full transcript to session.json:
$ python3 - <<'EOF' import sqlite3, json, datetime con = sqlite3.connect('/home/user/.local/share/opencode/opencode.db') c