DEV Community: Souvik Biswas

Memories: Personal Media Viewer for TV with local visual intelligence

Souvik Biswas — Sun, 04 Oct 2026 09:44:10 +0000

This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend

What I Built

Memories is a photo and video viewer for our Android TV. I built it for especially my mom who loves to browse through old photos and videos on TV 🙂

Just last week my mom asked if there's an app that can analyze a picture and tell me where it was taken. I thought that would be a fun weekend project to try out Gemma for visual intelligence. Now, this app has that capability plus a lot more!

You plug the photo SSD into the TV and the app opens by itself. Everything works from the couch with the regular remote. You can browse folders and run slideshows. It even plays the 4K Dolby Vision videos from our trips. Every photo also shows the date and the place it was taken. One of the other reasons why I started working on this app was the sheer lack of a good photo viewer for Android TV. The built-in one is slow and clunky. I wanted something that was fast, simple, and fun to use.

This weekend I added the part I'm most excited about. On any photo you can press Down on the remote and just ask about it. Things like "What is this place called?" or "What's that tower on the left called?". You can type the question or hold the mic button and say it.

If you zoom into part of the photo first then the question is about that part. The answer comes from Gemma running on a Mac in the same house. It shows up in a couple of seconds and the TV reads it out loud.

Demo

Code

sbis04 / memories_gemma

Media viewer for Android TV

Memories

A photo and video viewer for Android TV that lets you ask questions about your photos. The answers come from Gemma running on a computer in your home, so your photos never leave the house.

Features

Made for the remote. Plug in your photo drive and the app opens by itself. Browse folders as a grid or list and pin the ones you use most.
Slideshows with fade, Ken Burns or slide transitions. They resume where you left off.
4K, HDR and Dolby Vision video through the TV's own decoder.
Date and place on every photo, read from its GPS data.
Ask Gemma. Press Down on a photo and ask about it by typing or with the remote's mic. Zoom in first to ask about one part. The answer streams in and the TV reads it aloud.

Memories.Gemma.Demo.mov


Photos and videos laid out to fill the screen	Pin, rename

…

View on GitHub

How I Built It

The app is written in Flutter and runs on a Sony Bravia with Android TV 14. There's no touch screen and no mouse. Every screen had to work with just the D-pad.

For the AI part I'm using Gemma 4 (the E2B size) through Ollama. It runs on my MacBook and the TV talks to it over the home Wi-Fi:

TV app  ── photo + question over LAN ──▶  Mac: Ollama → gemma4              ▲                                                             │
└──────── answer, streamed word by word ◀───────────────┘
   then read aloud by the TV's built-in text-to-speech

Here's roughly what happens when you ask something:

The app sends Gemma the photo shrunk to about 1024px. If you're zoomed in it also sends a sharper crop of what's on screen. Gemma is told to focus on that crop. That's what makes "what's that building?" work on a wide skyline shot.
The first question also carries what the app already knows about the photo. That's the date and the place name from the photo's GPS and the album folder. So for our Shanghai photo Gemma came back with "This photo was taken in Shanghai, China, on September 14, 2026… landmarks like the Oriental Pearl Tower" instead of guessing.
Follow-up questions keep the earlier ones as context. So "and the one next to it?" works.
The answer streams in over Ollama's /api/chat as Gemma writes it. Once it's done the TV reads it out with Android's built-in voice.

Speed took the most work. My first version took anywhere from 10 to 30 seconds per answer. On a TV that feels like the app has frozen. When I looked at where the time went I found Gemma 4 spending around 500 tokens "thinking" before answering even "what is this?". I turned thinking off (think: false) and switched to the smaller E2B model. For photo questions I honestly couldn't tell the difference in the answers:

Setup (M3 Max, model already loaded)	Full answer	First words on screen
`gemma4` (E4B), thinking on	10 to 29 s	nothing until the whole answer is done
`gemma4` (E4B), thinking off	about 5 s	under 1 s (streamed)
`gemma4:e2b`, thinking off	about 2.5 to 3 s	under 1 s

I also ask Ollama to keep the model in memory for 30 minutes. That way only the first question of the evening has to wait for it to load.

If you want to try it then the Mac side is just this:

brew install ollama
ollama pull gemma4:e2b
OLLAMA_HOST=0.0.0.0 ollama serve   # so the TV can reach it over Wi-Fi

Then put the Mac's IP address in Memories under Settings > Gemma server.

Why Does Open Innovation Matter?

The first version of this feature actually used a cloud API. Every question sent the photo off to a hosted model. You also needed an API key to use it. Switching to Gemma changed a few things that matter a lot for an app like this.

The big one is privacy. These are our family photos. They have kids and faces in them along with our house and every place we've lived. Now when you ask about a photo it only travels from the TV to the Mac in the next room. Nothing gets uploaded and I don't have to read anyone's data policy.

It's also free to run. Nobody has to type an API key with a TV remote. There's no bill or rate limit to think about either.My parents will never need to know what a token is 😂

It won't change on me. The cloud model I started with sat behind a "latest" alias. That's nice right up until it starts answering differently one day. The Gemma weights are sitting on my disk. If it works today it should keep working.

Running it locally also meant I could dig into it. I found the thinking problem myself and measured every change I made. Picking the smaller model and adding streaming came out of that. Trying another model is just a setting in the app. I use gemma4:e2b for speed. gemma4 gives slightly nicer wording and gemma4:26b is there if you have a beefier machine.

The catch is that a computer at home has to be switched on. We mostly use the TV in the evening and the Mac is right there anyway. I'm happy with that if it means our photos stay at home.

My Agent Session

I did the Gemma work in one afternoon with Claude Code. I swapped the cloud API for Ollama and set up Gemma on the Mac. Then I chased down the slow answers and tested everything on the actual TV. I even had it write the little script I used to record the demo.

Memories: Personal Media Viewer for TV with Gemma for visual intelligence

You

can we add gemma to this project to make it eligible for this hackathon: https://dev.to/challenges/hacktoberfest-weekend-2026-10-01

[Image #1] [Image #2] [Image #3] [Image #4] [Image #5]
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Agent

▸ Bash git log --oneline | head -20 && ls && cat pubspec.yaml && find lib -name '*.d...

Input

$ git log --oneline | head -20 && ls && cat pubspec.yaml && find lib -name '*.dart' | xargs wc -l | sort -n | tail -40 && ls *.md 2>/dev/null; cat CLAUDE.md 2>/dev/null | head -100

Output

4bfe9c4 Read Gemini's answers aloud with the TV's built-in text-to-speech
82e7ea5 Ask Gemini about photos; zoom in paused slideshows; fix double Back
bed29a4 Open Memories when the photo SSD is plugged in
baedb5f Show time after the date on loading placeholders
8e4b916 Fix 4K/Dolby Vision video stutter: free decoders early, native caption
daffbc8 Smoother video playback; save slideshow resume point on every slide
53bb028 Folder actions menu (pin/rename/delete) and date-sorted folders
5698fc3 Persist folder summaries so counts and covers show instantly
94d6792 Read drives directly on Android; list view, pins, priority loading
31d727c set to latest stable flutter
ed0c773 Instant folder browsing on Android + folder drawer, zoom and Back fixes
2835821 Viewer: aspect-fit native video, media-location grant, subtler caption
15c7f0e Viewer/slideshow: date + reverse-geocoded location caption
39c48af Slideshow: 95%-quality images + hold current slide until next is decoded
bbde43a Viewer: focusable video controls + wakelock while playing
c2b6c77 Native ExoPlayer video (HDR/DV), faster thumbnails, focus & nav fixes
8567f5c Viewer: add 200% zoom step
7bd5a4d Viewer: stepped zoom + D-pad pan
758394d Polish: faster thumbnails, slideshow pre-warm/resume, grid fill, fixes
9dbae65 Auto-refresh as Android indexes the USB drive
README.md
analysis_options.yaml
android
assets
build
lib
macos
pubspec.lock
pubspec.yaml
test
tv_gallery.iml
name: tv_gallery
description: "A new Flutter project."
# The 
…[7393 more chars]

▸ Bash cat lib/services/gemini_service.dart README.md && grep -n -i "gemini\|apikey\...

Input

$ cat lib/services/gemini_service.dart README.md && grep -n -i "gemini\|apikey\|api_key" -r lib --include=*.dart | grep -v "^lib/services/gemini_service.dart" && git show --stat HEAD~1 | head -30

Output

Exit code 1
import 'dart:convert';
import 'dart:io';
import 'dart:math' as math;
import 'dart:ui' as ui;

import 'package:flutter/painting.dart';

import 'package:path/path.dart' as p;

import '../models/media_entry.dart';
import '../widgets/media_caption.dart';
import 'location_service.dart';
import 'settings_controller.dart';
import 'thumbnail_service.dart';

/// A conversation with Gemini about one photo (or a video's poster frame).
///
/// Uses the Gemini API directly over HTTPS with the user's API key from
/// Settings. The image is sent downscaled (~1024px) along with what the app
/// already knows — date, place, folder — so questions like "where was this?"
/// get grounded answers. Follow-ups keep the history, so "and that building
/// on the left?" works.
class GeminiChat {
  GeminiChat(this.entry, {Rect? focus})
      : focus = focus == null || focus == const Rect.fromLTRB(0, 0, 1, 1)
            ? null
            : focus;

  final MediaEntry entry;

  /// The zoomed-in region (normalized 0–1), or null for the whole photo.
  final Rect? focus;

  bool get zoomed => focus != null;

  /// Newest Flash model (Google keeps this alias pointing at it).
  static const model = 'gemini-flash-latest';

  final List<Map<String, Object>> _history = [];
  String? _imageData;
  String? _cropData;
  Future<void>? _prepared;

  /// Prepares the image(s) to send — called as soon as the Ask screen opens,
  /// so they're ready by the time a question has been typed or spoken.
  Future
…[8049 more chars]

▸ Bash grep -rn -i "gemini" lib | grep -v "^lib/services/gemini_service.dart"; grep ...

Input

$ grep -rn -i "gemini" lib | grep -v "^lib/services/gemini_service.dart"; grep -n "minSdk\|targetSdk" android/app/build.gradle* ; cat android/app/src/main/AndroidManifest.xml | head -40

Output

lib/screens/settings_screen.dart:179:                      _SectionHeader('Gemini'),
lib/screens/settings_screen.dart:181:                        title: 'Gemini API key',
lib/screens/settings_screen.dart:182:                        subtitle: s.geminiApiKey == null
lib/screens/settings_screen.dart:185:                            : 'Set (…${_tail(s.geminiApiKey!)}) — stored only '
lib/screens/settings_screen.dart:189:                          label: s.geminiApiKey == null ? 'Add' : 'Change',
lib/screens/settings_screen.dart:190:                          onPressed: () => _editGeminiKey(context),
lib/screens/settings_screen.dart:195:                        subtitle: 'Speak Gemini’s answers with the TV voice',
lib/screens/settings_screen.dart:228:  Future<void> _editGeminiKey(BuildContext context) async {
lib/screens/settings_screen.dart:232:      title: 'Gemini API key',
lib/screens/settings_screen.dart:233:      initial: settings.geminiApiKey ?? '',
lib/screens/settings_screen.dart:237:    if (key != null) await settings.setGeminiApiKey(key);
lib/screens/settings_screen.dart:468:  static const _sample = 'Hi! This is how Gemini’s answers will sound.';
lib/screens/slideshow_screen.dart:314:  /// Pauses (if needed) and asks Gemini about the current slide — the
lib/screens/slideshow_screen.dart:328:  /// arrows pan while zoomed. Up goes to the top-bar chips, Down asks Gemini.
lib/screens/viewer_screen.dart:240:        // Down asks Gemini (zoomed: pan down first, ask at the bottom ed
…[5245 more chars]

▸ Bash which ollama llama-server lms 2>/dev/null; ollama list 2>/dev/null; sysctl -n...

Input

$ which ollama llama-server lms 2>/dev/null; ollama list 2>/dev/null; sysctl -n hw.memsize machdep.cpu.brand_string; flutter --version 2>/dev/null | head -1

Output

ollama not found
llama-server not found
lms not found
38654705664
Apple M3 Max
Flutter 3.47.6 • channel stable • https://github.com/flutter/flutter.git

▸ AskUserQuestion {"questions": [{"question": "Right now \"Ask Gemini\" sends each photo to Goo...

Input

{
  "questions": [
    {
      "question": "Right now \"Ask Gemini\" sends each photo to Google's Gemini API. Where should Gemma run instead? (This decides how strong the \"why open matters\" part of your post is.)",
      "header": "Gemma host",
      "multiSelect": false,
      "options": [
        {
          "label": "Home server via Ollama (Recommended)",
          "description": "Gemma runs on your Mac (or any machine on the home Wi-Fi) through Ollama. The TV sends photos over the LAN, so family photos never leave the house, it's free, and you can swap models. Needs the Mac on while you use the feature. The app also gets a 'Gemma server address' setting.",
          "preview": "TV (Memories app)\n   │  photo + question, LAN only\n   ▼\nMac: ollama serve  →  gemma3 (vision)\n   │\n   ▼\nanswer → read aloud on TV\n\nNo cloud, no API key."
        },
        {
          "label": "On the TV itself",
          "description": "Gemma 3n runs on-device via flutter_gemma/LiteRT. Fully offline, but the Bravia's MediaTek chip and RAM may make it very slow or crash. Needs a ~3GB model download onto the TV. Highest risk to finish this weekend.",
          "preview": "TV (Memories app)\n   └─ flutter_gemma → Gemma 3n E2B (on-device)\n\n~3GB model on the TV, slow on TV SoC,\nmay not fit in memory."
        },
        {
          "label": "Gemma via Gemini API",
          "description": "Same API key, just change the model to a hosted Gemma. About 20 lines of code, but photos still go to Google, so it's a weak fit for 'open AI at its core'.",
          "preview": "TV → generativelanguage.googleapis.com\n     model: gemma-3-27b-it\n\nSame key, photos still go to the cloud."
        },
        {
          "label": "Ollama + keep Gemini option",
          "description": "Same as the first option, but Settings has a Gemma (local) / Gemini (cloud) toggle. Gemma is the default and Gemini stays as a fallback when the Mac is off."
        }
      ]
    }
  ]
}

Output

Your questions have been answered: "Right now "Ask Gemini" sends each photo to Google's Gemini API. Where should Gemma run instead? (This decides how strong the "why open matters" part of your post is.)"="Home server via Ollama (Recommended)" selected preview:
TV (Memories app)
   │  photo + question, LAN only
   ▼
Mac: ollama serve  →  gemma3 (vision)
   │
   ▼
answer → read aloud on TV

No cloud, no API key.. You can now continue with these answers in mind.

▸ ToolSearch {"query": "select:WebSearch", "max_results": 1}

Input

{
  "query": "select:WebSearch",
  "max_results": 1
}

Output

[image]

▸ WebSearch {"query": "ollama gemma latest vision model tag 2026", "mode": "standard"}

Input

{
  "query": "ollama gemma latest vision model tag 2026",
  "mode": "standard"
}

Output

Web search results for query: "ollama gemma latest vision model tag 2026"

Links: [{"title":"Best Ollama Models (2026): 25+ Ranked by VRAM, Context, and SWE-Bench (August 2026)","url":"https://www.morphllm.com/best-ollama-models"},{"title":"How to Run Gemma 4 with Ollama: Step-by-Step Setup Guide (2026)","url":"https://codersera.com/blog/how-to-run-gemma-4-with-ollama-setup-guide/amp/"},{"title":"top open source models ollama","url":"https://www.promptquorum.com/local-llms/top-open-source-models-ollama"},{"title":"which ollama models support vision","url":"https://www.promptquorum.com/es/prompt-bites/which-ollama-models-support-vision"},{"title":"www.serverman.co.uk","url":"https://www.serverman.co.uk/?p=4092"},{"title":"which ollama models support vision","url":"https://www.promptquorum.com/pt/prompt-bites/which-ollama-models-support-vision"},{"title":"top open source models ollama","url":"https://www.promptquorum.com/es/local-llms/top-open-source-models-ollama"},{"title":"Ir al contenido principal","url":"https://www.javadex.es/blog/ollama-modelos-ranking-completo-mejores-modelos-local-2026"},{"title":"which ollama models support vision","url":"https://www.promptquorum.com/prompt-bites/which-ollama-models-support-vision"}]

Based on the search results, here's what I found regarding Ollama Gemma vision models in 2026:

## Gemma 4 Vision Model

Google DeepMind released Gemma 4 on April 2, 2026, and it comes in four sizes — E2B, E4B, E12B, and E27B — all natively multimodal, m
…[585 more chars]

▸ Bash sed -n 30,130p lib/services/settings_controller.dart && sed -n 170,185p lib/s...

Input

$ sed -n 30,130p lib/services/settings_controller.dart && sed -n 170,185p lib/services/settings_controller.dart && sed -n 150,260p lib/screens/settings_screen.dart && sed -n 440,480p lib/screens/settings_screen.dart

Output

static const _kSlideShuffle = 'slideshowShuffle';
  static const _kSource = 'sourcePath';
  static const _kSourceLabel = 'sourceLabel';
  static const _kLastFolder = 'lastFolderPath';
  static const _kSlideLastFolder = 'slideshowLastFolder';
  static const _kSlideLastItem = 'slideshowLastItem';
  static const _kFolderCounts = 'folderMediaCounts';
  static const _kListView = 'listView';
  static const _kPinned = 'pinnedFolders';
  static const _kGeminiKey = 'geminiApiKey';
  static const _kReadAloud = 'readAnswersAloud';
  static const _kAnswerVoice = 'answerVoice'; // "name|locale"

  // ---- State (defaults) ----
  ThemeMode _themeMode = ThemeMode.dark;
  int _gridZoom = 2; // 0..maxZoom (2 = default, one step below "Medium")
  // Media defaults to chronological order, oldest first.
  SortBy _sortBy = SortBy.date;
  bool _sortDesc = false;
  bool _showTitles = false;
  bool _showCaption = true;
  bool _autoplayVideos = true;
  bool _muteVideo = false;
  int _slideshowSeconds = 6;
  SlideshowTransition _slideshowTransition = SlideshowTransition.kenBurns;
  bool _slideshowLoop = true;
  bool _slideshowShuffle = false;
  String? _sourcePath;
  String? _sourceLabel;
  String? _lastFolderPath;
  String? _slideshowLastFolder;
  String? _slideshowLastItem;
  Map<String, int> _folderCounts = {};
  bool _listView = false;
  List<String> _pinned = [];
  String? _geminiApiKey;
  bool _readAloud = true;
  String? _answerVoice;

  // ---- Getters ----
  ThemeMode get themeMode => _themeM
…[8459 more chars]

▸ Bash cat lib/widgets/ask_panel.dart; sed -n 20,40p lib/services/answer_voice.dart;...

Input

$ cat lib/widgets/ask_panel.dart; sed -n 20,40p lib/services/answer_voice.dart; cat macos/Runner/*.entitlements; ls android/app/src/main/res/xml 2>/dev/null; grep -n "Cleartext\|networkSecurity" -r android/app/src

Output

import 'dart:async';
import 'dart:io';
import 'dart:ui' as ui;

import 'package:flutter/material.dart';
import 'package:flutter/services.dart';
import 'package:flutter_animate/flutter_animate.dart';
import 'package:lucide_icons_flutter/lucide_icons.dart';

import '../core/app_theme.dart';
import '../core/transitions.dart';
import '../models/media_entry.dart';
import '../screens/settings_screen.dart';
import '../services/answer_voice.dart';
import '../services/gemini_service.dart';
import '../services/settings_controller.dart';
import '../services/thumbnail_service.dart';
import 'focusable.dart';

/// Opens "Ask Gemini" full screen over the blurred photo: a centred question
/// field (focused, so the TV keyboard — with its voice button — comes straight
/// up), a preview of exactly what Gemini is shown (the zoomed-in part, if
/// zoomed), quick suggestions and the conversation. Back closes it.
/// [focus] is the zoomed-in region (normalized).
Future<void> showAskPanel(
  BuildContext context,
  MediaEntry entry, {
  Rect? focus,
}) {
  return showGeneralDialog<void>(
    context: context,
    barrierDismissible: false,
    barrierLabel: 'Ask Gemini',
    barrierColor: Colors.transparent,
    transitionDuration: AppTheme.focusAnim * 2,
    pageBuilder: (context, _, _) => _AskPanel(entry, focus: focus),
    transitionBuilder: (context, animation, _, child) =>
        FadeTransition(opacity: animation, child: child),
  );
}

class _AskPanel extends StatefulWidget {
  const _AskPa
…[20454 more chars]

▸ Bash grep -rn "allowSlash" lib | head; grep -n "Future<String?> showTextInputDialo...

Input

$ grep -rn "allowSlash" lib | head; grep -n "Future<String?> showTextInputDialog" -A40 -r lib | head -60; sed -n 1,30p lib/screens/settings_screen.dart

Output

lib/screens/settings_screen.dart:235:      allowSlash: true,
lib/widgets/folder_actions.dart:77:  bool allowSlash = false,
lib/widgets/folder_actions.dart:86:      allowSlash: allowSlash,
lib/widgets/folder_actions.dart:285:    required this.allowSlash,
lib/widgets/folder_actions.dart:292:  final bool allowSlash;
lib/widgets/folder_actions.dart:331:            if (!widget.allowSlash) FilteringTextInputFormatter.deny(RegExp('[/]')),
lib/widgets/folder_actions.dart:71:Future<String?> showTextInputDialog(
lib/widgets/folder_actions.dart-72-  BuildContext context, {
lib/widgets/folder_actions.dart-73-  required String title,
lib/widgets/folder_actions.dart-74-  String initial = '',
lib/widgets/folder_actions.dart-75-  String? hint,
lib/widgets/folder_actions.dart-76-  String confirmLabel = 'Save',
lib/widgets/folder_actions.dart-77-  bool allowSlash = false,
lib/widgets/folder_actions.dart-78-}) {
lib/widgets/folder_actions.dart-79-  return _showPanel<String>(
lib/widgets/folder_actions.dart-80-    context,
lib/widgets/folder_actions.dart-81-    builder: (context) => _TextForm(
lib/widgets/folder_actions.dart-82-      title: title,
lib/widgets/folder_actions.dart-83-      initial: initial,
lib/widgets/folder_actions.dart-84-      hint: hint,
lib/widgets/folder_actions.dart-85-      confirmLabel: confirmLabel,
lib/widgets/folder_actions.dart-86-      allowSlash: allowSlash,
lib/widgets/folder_actions.dart-87-    ),
lib/widgets/folder_actions.dart-88-  );
lib/widgets/folder_actions
…[2401 more chars]

▸ Bash git mv lib/services/gemini_service.dart lib/services/gemma_service.dart

Input

$ git mv lib/services/gemini_service.dart lib/services/gemma_service.dart

Output

(Bash completed with no output)

Going with Gemma on a home Mac through Ollama, as you picked. I'm now swapping the app's Gemini code over to call it.

You

actually first commti the inital app before making these new cahnges, create a commit called "Add Memories TV app"

Agent

▸ Bash git mv lib/services/gemma_service.dart lib/services/gemini_service.dart && gi...

Input

$ git mv lib/services/gemma_service.dart lib/services/gemini_service.dart && git status --short && git remote -v && git rev-list --count HEAD

Output

Exit code 128
fatal: not under version control, source=lib/services/gemma_service.dart, destination=lib/services/gemini_service.dart

▸ Bash git status; ls lib/services/ | grep gem; git remote -v; git log --oneline | h...

Input

$ git status; ls lib/services/ | grep gem; git remote -v; git log --oneline | head -3

Output

On branch main

No commits yet

Untracked files:
  (use "git add <file>..." to include in what will be committed)
    .fvmrc
    .gitignore
    .metadata
    .vscode/
    README.md
    analysis_options.yaml
    android/
    assets/
    lib/
    macos/
    pubspec.lock
    pubspec.yaml
    test/

nothing added to commit but untracked files present (use "git add" to track)
gemma_service.dart
fatal: your current branch 'main' does not have any commits yet

The git history has been reset (no commits yet). First I'll undo my file rename so the commit has the original app, then check that nothing secret or generated gets staged.

▸ Bash mv lib/services/gemma_service.dart lib/services/gemini_service.dart && cat .g...

Input

$ mv lib/services/gemma_service.dart lib/services/gemini_service.dart && cat .gitignore | head -50 && git add -A && git status --short | wc -l && git status --short | grep -v "^A  \(lib\|android\|macos\|assets\|test\)/" ; grep -rnE "AIza[0-9A-Za-z_-]{20,}" $(git diff --cached --name-only) 2>/dev/null | head

Output

# Miscellaneous
*.class
*.log
*.pyc
*.swp
.DS_Store
.atom/
.build/
.buildlog/
.history
.svn/
.swiftpm/
migrate_working_dir/

# IntelliJ related
*.iml
*.ipr
*.iws
.idea/

# The .vscode folder contains launch configuration and tasks you configure in
# VS Code which you may wish to be included in version control, so this line
# is commented out by default.
#.vscode/

# Flutter/Dart/Pub related
**/doc/api/
**/ios/Flutter/.last_build_id
.dart_tool/
.flutter-plugins-dependencies
.pub-cache/
.pub/
/build/
/coverage/

# Symbolication related
app.*.symbols

# Obfuscation related
app.*.map.json

# Android Studio will place build artifacts here
/android/app/debug
/android/app/profile
/android/app/release

# FVM Version Cache
.fvm/
# Golden test failure diffs
test/failures/
     134
A  .fvmrc
A  .gitignore
A  .metadata
A  .vscode/settings.json
A  README.md
A  analysis_options.yaml
A  pubspec.lock
A  pubspec.yaml

▸ Bash git diff --cached --name-only | grep -iE "local.properties|key.properties|\.j...

Input

$ git diff --cached --name-only | grep -iE "local.properties|key.properties|\.jks|\.keystore|google-services|\.env" ; git commit -q -m "Add Memories TV app

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>" && git log --stat --oneline | tail -1

Output

134 files changed, 15268 insertions(+)

▸ Bash git mv lib/services/gemini_service.dart lib/services/gemma_service.dart

Input

$ git mv lib/services/gemini_service.dart lib/services/gemma_service.dart

Output

(Bash completed with no output)

▸ Bash cat > <scratch>/head.dart <<'EOF' /// A conversation with Gemma about one pho...

Input

$ cat > <scratch>/head.dart <<'EOF'
/// A conversation with Gemma about one photo (or a video's poster frame).
///
/// Gemma, Google's open-weight model, runs on a computer at home through
/// Ollama (Settings → Gemma server); the TV talks to it over the local
/// network, so photos never leave the house and there's no API key or bill.
/// The image is sent downscaled (~1024px) along with what the app already
/// knows — date, place, folder — so questions like "where was this?" get
/// grounded answers. Follow-ups keep the history, so "and that building on
/// the left?" works.
class GemmaChat {
  GemmaChat(this.entry, {Rect? focus})
      : focus = focus == null || focus == const Rect.fromLTRB(0, 0, 1, 1)
            ? null
            : focus;

  final MediaEntry entry;

  /// The zoomed-in region (normalized 0–1), or null for the whole photo.
  final Rect? focus;

  bool get zoomed => focus != null;

  final List<Map<String, Object>> _history = [];
  String? _imageData;
  String? _cropData;
  Future<void>? _prepared;

  /// Prepares the image(s) to send — called as soon as the Ask screen opens,
  /// so they're ready by the time a question has been typed or spoken.
  Future<void> prepare() => _prepared ??= () async {
        final crop = focus;
        final results = await Future.wait([
          _image(),
          crop == null ? Future<String?>.value() : _crop(crop),
        ]);
        _cropData = results[1];
      }();

  static bool get hasServer => SettingsController.instance.gemmaServer != null;

  /// Asks [question] about the photo; returns the answer text. Throws a
  /// [GemmaException] with a user-facing message on failure.
  Future<String> ask(String question) async {
    final settings = SettingsController.instance;
    final server = settings.gemmaServer;
    if (server == null) {
      throw const GemmaException('Add your Gemma server in Settings.');
    }
    final model = settings.gemmaModel;

    final Map<String, Object> turn;
    if (_history.isEmpty) {
      await prepare();
      final crop = _cropData;
      turn = {
        'role': 'user',
        'content': [
          await _context(),
          if (crop != null)
            'The viewer has zoomed in: the second image is the part of the '
                'photo on screen. Focus on it; the first image is the whole '
                'photo for context.',
          question,
        ].join('\n\n'),
        'images': [await _image(), ?crop],
      };
    } else {
      turn = {'role': 'user', 'content': question};
    }

    final body = jsonEncode({
      'model': model,
      'messages': [
        {
          'role': 'system',
          'content': 'You help someone look through their own photos and '
              'videos on a TV. Answer about the attached picture in plain '
              'text (no markdown), concisely: usually 2–5 sentences, readable '
              'from a couch. Use the date, place and folder given as context '
              'when relevant. If you ar
…[2753 more chars]

Output

(Bash completed with no output)

Now the settings: replacing the API key with a server address and a model name.

▸ Bash python3 - <<'EOF' p='lib/services/settings_controller.dart' s=open(p).read() ...

Input

$ python3 - <<'EOF'
p='lib/services/settings_controller.dart'
s=open(p).read()
def r(a,b):
    global s
    assert a in s, a
    s=s.replace(a,b)
r("  static const _kGeminiKey = 'geminiApiKey';\n",
  "  static const _kGemmaServer = 'gemmaServer';\n  static const _kGemmaModel = 'gemmaModel';\n")
r("  String? _geminiApiKey;\n", "  String? _gemmaServer;\n  String _gemmaModel = defaultGemmaModel;\n")
a=s.index("  /// Gemini API key (from aistudio.google.com)")
b=s.index("  /// Read Gemini's answers aloud")
s=s[:a]+'''  /// The Ollama server running Gemma on the home network, as a base URL
  /// (e.g. http://192.168.1.20:11434), or null if not set up yet.
  String? get gemmaServer => _gemmaServer;

  /// Accepts a bare host or IP ("192.168.1.20", "mac.local") and fills in
  /// Ollama's scheme and port.
  Future<void> setGemmaServer(String? address) async {
    var a = address?.trim() ?? '';
    while (a.endsWith('/')) {
      a = a.substring(0, a.length - 1);
    }
    if (a.isNotEmpty) {
      if (!a.contains('://')) a = 'http://$a';
      final uri = Uri.tryParse(a);
      if (uri != null && uri.host.isNotEmpty && !uri.hasPort) {
        a = uri.replace(port: 11434).toString();
      }
    }
    _gemmaServer = a.isEmpty ? null : a;
    if (_gemmaServer == null) {
      await _prefs.remove(_kGemmaServer);
    } else {
      await _prefs.setString(_kGemmaServer, _gemmaServer!);
    }
    notifyListeners();
  }

  /// Gemma 4's default (E4B) build: multimodal and quick on a laptop.
  static const defaultGemmaModel = 'gemma4';

  /// Ollama model tag to ask (e.g. gemma4, gemma4:26b).
  String get gemmaModel => _gemmaModel;

  Future<void> setGemmaModel(String? model) async {
    final m = model?.trim() ?? '';
    _gemmaModel = m.isEmpty ? defaultGemmaModel : m;
    await _prefs.setString(_kGemmaModel, _gemmaModel);
    notifyListeners();
  }

'''+s[b:]
r("  /// Read Gemini's answers aloud","  /// Read Gemma's answers aloud")
r("    _geminiApiKey = _prefs.getString(_kGeminiKey);\n",
  "    _gemmaServer = _prefs.getString(_kGemmaServer);\n    _gemmaModel = _prefs.getString(_kGemmaModel) ?? defaultGemmaModel;\n")
open(p,'w').write(s)

p='lib/screens/settings_screen.dart'
s=open(p).read()
a=s.index("                      _SectionHeader('Gemini'),")
b=s.index("                      _SettingTile(\n                        title: 'Read answers aloud',")
s=s[:a]+'''                      _SectionHeader('Gemma'),
                      _SettingTile(
                        title: 'Gemma server',
                        subtitle: s.gemmaServer == null
                            ? 'A computer at home running Ollama — photos '
                                'stay on your network'
                            : s.gemmaServer!,
                        trailing: IconFocusButton(
                          icon: LucideIcons.server,
                          label: s.gemmaServer == null ? 'Add' : 'Change',
                          onPressed: () => _editGemmaServer(context)
…[2567 more chars]

Output

android/app/src/main/AndroidManifest.xml:11:    <!-- Network access for "Ask Gemini" (Flutter's template only grants it
android/app/src/main/AndroidManifest.xml:15:         visibility) to read Gemini's answers aloud. -->

▸ Bash python3 - <<'EOF' p='android/app/src/main/AndroidManifest.xml' s=open(p).read...

Input

$ python3 - <<'EOF'
p='android/app/src/main/AndroidManifest.xml'
s=open(p).read()
s=s.replace('''    <!-- Network access for "Ask Gemini" (Flutter's template only grants it
         in debug/profile builds, so release builds couldn't connect). -->''','''    <!-- Network access for "Ask Gemma" (Flutter's template only grants it
         in debug/profile builds, so release builds couldn't connect). -->''')
s=s.replace("visibility) to read Gemini's answers aloud.","visibility) to read Gemma's answers aloud.")
old='''        android:banner="@drawable/tv_banner">'''
assert old in s
s=s.replace(old,'''        android:banner="@drawable/tv_banner"
        android:usesCleartextTraffic="true">''')
s=s.replace('''    <application
        android:label="Memories"''','''    <!-- usesCleartextTraffic: Gemma runs on a computer on the home network
         via Ollama, which speaks plain HTTP. -->
    <application
        android:label="Memories"''')
open(p,'w').write(s)
EOF
flutter analyze 2>&1 | tail -15

Output

Upgrading analysis_options.yaml to exclude build and platform directories.
Analyzing tv_gallery_gemma...                                   
No issues found! (ran in 8.4s)

▸ Bash git status --short && git diff analysis_options.yaml

Input

$ git status --short && git diff analysis_options.yaml

Output

M analysis_options.yaml
 M android/app/src/main/AndroidManifest.xml
 M lib/screens/settings_screen.dart
 M lib/screens/slideshow_screen.dart
 M lib/screens/viewer_screen.dart
 M lib/services/answer_voice.dart
RM lib/services/gemini_service.dart -> lib/services/gemma_service.dart
 M lib/services/settings_controller.dart
 M lib/widgets/ask_panel.dart
 M lib/widgets/zoomable_image.dart
diff --git a/analysis_options.yaml b/analysis_options.yaml
index 0d29021..13c3ff6 100644
--- a/analysis_options.yaml
+++ b/analysis_options.yaml
@@ -7,6 +7,11 @@
 
 # The following line activates a set of recommended lints for Flutter apps,
 # packages, and plugins designed to encourage good coding practices.
+analyzer:
+  exclude:
+    - build/**
+    - android/**
+    - macos/**
 include: package:flutter_lints/flutter.yaml
 
 linter:

▸ Bash git checkout analysis_options.yaml && git diff --stat && which brew

Input

$ git checkout analysis_options.yaml && git diff --stat && which brew

Output

Updated 1 path from the index
 android/app/src/main/AndroidManifest.xml |   9 +-
 lib/screens/settings_screen.dart         |  58 ++++++----
 lib/screens/slideshow_screen.dart        |   4 +-
 lib/screens/viewer_screen.dart           |   6 +-
 lib/services/answer_voice.dart           |   2 +-
 lib/services/gemma_service.dart          | 185 +++++++++++++------------------
 lib/services/settings_controller.dart    |  54 ++++++---
 lib/widgets/ask_panel.dart               |  40 +++----
 lib/widgets/zoomable_image.dart          |   2 +-
 9 files changed, 192 insertions(+), 168 deletions(-)
/opt/homebrew/bin/brew

"Ask Gemini" is now "Ask Gemma". Gemma runs on a computer at home through Ollama, and the TV sends it the photo over the home Wi-Fi. flutter analyze passes, but I haven't sent it a real question yet because Ollama isn't installed on your Mac. These changes aren't committed; the commit before them is "Add Memories TV app".

What changed
- lib/services/gemma_service.dart (renamed from gemini_service.dart): it now calls Ollama's /api/chat instead of Google's API. It still sends the downscaled photo, the zoomed-in crop, and the date, place and folder, and follow-up questions still work.
- It asks Ollama to keep the model loaded for 30 minutes, so later questions don't wait for it to reload.
- The first question can take up to 3 minutes while the model loads.
- Error messages say what to fix: Mac off or Ollama not on the network, model not downloaded (with the exact ollama pull command), or the model being too slow.
- Settings: the Gemini API key is replaced by "Gemma server" and "Model".
- For the server you can type just an IP or name like [REDACTED] and it fills in http://…:11434.
- The model defaults to gemma4, Gemma 4's smaller default size (~9.6 GB).
- Text on screen: every "Gemini" is now "Gemma". The "no server set" screen explains the setup in one sentence.
- AndroidManifest.xml: I turned on plain-HTTP traffic. Android blocks it by default, and Ollama doesn't use HTTPS on a home network, so without this the TV couldn't connect.

Setting up the Mac
sh brew install ollama ollama pull gemma4 # or gemma4:26b — fits in your 36 GB and answers better OLLAMA_HOST=[REDACTED] ollama serve # listen on the LAN, not just localhost
Then put the Mac's IP into the TV's Settings.

For your post: the photos stay in the house, there's no API key or bill, and you can switch models by changing one setting. That covers both "keep data off a server they don't control" and "cost nothing to run". The one catch is that the Mac has to be on while you use it.

Do you want me to install Ollama and download gemma4 (about 10 GB) so I can test a real question end to end before we commit?

Sources:
- How to Run Gemma 4 with Ollama (codersera)
- Best Ollama Models 2026 (morphllm)

You

can you do that mac setup

Agent

▸ Bash brew install ollama 2>&1 | tail -5; which ollama; ollama --version

Input

$ brew install ollama 2>&1 | tail -5; which ollama; ollama --version

Output

==> ollama
To start ollama now and restart at login:
  brew services start ollama
Or, if you don't want/need a background service you can just run:
  OLLAMA_FLASH_ATTENTION="1" OLLAMA_KV_CACHE_TYPE="q8_0" /opt/homebrew/opt/ollama/bin/ollama serve
/opt/homebrew/bin/ollama
Warning: could not connect to a running Ollama instance
Warning: client version is 0.35.1

▸ Bash brew services start ollama 2>&1 | tail -2; P=~/Library/LaunchAgents/homebrew....

Input

$ brew services start ollama 2>&1 | tail -2; P=~/Library/LaunchAgents/homebrew.mxcl.ollama.plist; sleep 2; /usr/libexec/PlistBuddy -c "Print :EnvironmentVariables" $P

Output

Exit code 1
==> Successfully started `ollama` (label: sh.brew.ollama)
Print: Entry, ":EnvironmentVariables", Does Not Exist
File Doesn't Exist, Will Create: ~/Library/LaunchAgents/homebrew.mxcl.ollama.plist

▸ Bash ls ~/Library/LaunchAgents/ | grep -i ollama; P=~/Library/LaunchAgents/sh.brew...

Input

$ ls ~/Library/LaunchAgents/ | grep -i ollama; P=~/Library/LaunchAgents/sh.brew.ollama.plist; cat $P

Output

sh.brew.ollama.plist
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
    <key>EnvironmentVariables</key>
    <dict>
        <key>OLLAMA_FLASH_ATTENTION</key>
        <string>1</string>
        <key>OLLAMA_KV_CACHE_TYPE</key>
        <string>q8_0</string>
    </dict>
    <key>KeepAlive</key>
    <true/>
    <key>Label</key>
    <string>sh.brew.ollama</string>
    <key>LimitLoadToSessionType</key>
    <array>
        <string>Aqua</string>
        <string>Background</string>
        <string>LoginWindow</string>
        <string>StandardIO</string>
        <string>System</string>
    </array>
    <key>ProgramArguments</key>
    <array>
        <string>/opt/homebrew/opt/ollama/bin/ollama</string>
        <string>serve</string>
    </array>
    <key>RunAtLoad</key>
    <true/>
    <key>StandardErrorPath</key>
    <string>/opt/homebrew/var/log/ollama.log</string>
    <key>StandardOutPath</key>
    <string>/opt/homebrew/var/log/ollama.log</string>
    <key>WorkingDirectory</key>
    <string>/opt/homebrew/var</string>
</dict>
</plist>

Ollama is running as a background service. Next I'm making it listen on the home network so the TV can reach it (by default it only accepts connections from the Mac itself):

▸ Bash P=~/Library/LaunchAgents/sh.brew.ollama.plist; /usr/libexec/PlistBuddy -c "Ad...

Input

$ P=~/Library/LaunchAgents/sh.brew.ollama.plist; /usr/libexec/PlistBuddy -c "Add :EnvironmentVariables:OLLAMA_HOST string 0.0.0.0" $P && launchctl bootout gui/$(id -u)/sh.brew.ollama; sleep 1; launchctl bootstrap gui/$(id -u) $P; sleep 3; lsof -nP -iTCP:11434 -sTCP:LISTEN; curl -s localhost:11434/api/version

Output

COMMAND   PID         USER   FD   TYPE            DEVICE SIZE/OFF NODE NAME
ollama  35387 souvikbiswas    3u  IPv6 0xa12519e1d1b6e03      0t0  TCP *:11434 (LISTEN)
{"version":"0.35.1"}

Ollama is now listening on all interfaces. Downloading gemma4 (~10 GB) next:

▸ Bash ollama pull gemma4 2>&1 | tail -3; ollama list

Input

$ ollama pull gemma4 2>&1 | tail -3; ollama list

Output

verifying sha256 digest [K
writing manifest [K
success [K[?25h[?2026l
NAME             ID              SIZE      MODIFIED               
gemma4:latest    dc35e8d9c606    6.6 GB    Less than a second ago

Model downloaded. Now I'll send it the same request the TV sends, with a photo, through the Mac's network address instead of localhost:

▸ Bash IP=$(ipconfig getifaddr en0 || ipconfig getifaddr en1); echo "IP=$IP"; S=<scr...

Input

$ IP=$(ipconfig getifaddr en0 || ipconfig getifaddr en1); echo "IP=$IP"; S=<scratch>; IMG=$(ls /System/Library/Desktop\ Pictures/*.heic 2>/dev/null | head -1); echo "$IMG"; sips -s format jpeg -Z 1024 "$IMG" --out $S/t.jpg >/dev/null; python3 - "$IP" "$S/t.jpg" <<'EOF'
import json,base64,sys,urllib.request,time
ip,img=sys.argv[1:]
b=base64.b64encode(open(img,'rb').read()).decode()
sysmsg='You help someone look through their own photos and videos on a TV. Answer about the attached picture in plain text (no markdown), concisely: usually 2–5 sentences, readable from a couch. Use the date, place and folder given as context when relevant. If you are unsure, say so briefly.'
msgs=[{'role':'system','content':sysmsg},{'role':'user','content':'Taken: 12 Mar 2024. Album/folder: Wallpapers. File: t.jpg.\n\nWhat is this?','images':[b]}]
def call(m,model='gemma4'):
    t=time.time()
    r=urllib.request.urlopen(urllib.request.Request(f'http://{ip}:11434/api/chat',json.dumps({'model':model,'messages':m,'stream':False,'keep_alive':'30m'}).encode(),{'Content-Type':'application/json'}))
    j=json.load(r); print(f'[{time.time()-t:.1f}s]',j['message']['content']); return j['message']['content']
a=call(msgs)
msgs+= [{'role':'assistant','content':a},{'role':'user','content':'What colours stand out?'}]
call(msgs)
try: call(msgs[:2],'gemma4:nope')
except urllib.error.HTTPError as e: print(e.code, e.read().decode())
EOF

Output

IP=192.168.68.56
/System/Library/Desktop Pictures/Mac Blue.heic
[149.4s] This is an abstract, modern digital wallpaper featuring a repeating pattern of rounded shapes. The image uses a beautiful color gradient, primarily composed of cool tones like deep blue, indigo, and lavender, which blend softly into warm peach and light pink. These smooth, stacked vertical columns and circles create a visually calming and aesthetic texture. This image, filed under Wallpapers, was captured on 12 Mar 2024.
[9.5s] The most striking colors are the deep, saturated indigo and navy blues that define the taller column shapes. These rich, cool tones stand out powerfully against the softer, lighter hues. Specifically, the gentle warm peaches and lavenders create a strong contrast with the dark blues. This beautiful blend of intense blues and delicate pastels gives the wallpaper its visually appealing, glowing quality.
404 {"error":"model 'gemma4:nope' not found"}

The test went through before your reply arrived. Since you've accepted the dialog, I'll run it again to check the first-answer time:

▸ Bash S=<scratch>; python3 - 192.168.68.56 $S/t.jpg <<'EOF' import json,base64,sys,...

Input

$ S=<scratch>; python3 - 192.168.68.56 $S/t.jpg <<'EOF'
import json,base64,sys,urllib.request,time
ip,img=sys.argv[1:]
b=base64.b64encode(open(img,'rb').read()).decode()
t=time.time()
r=urllib.request.urlopen(urllib.request.Request(f'http://{ip}:11434/api/chat',json.dumps({'model':'gemma4','messages':[{'role':'user','content':'Describe this photo in two sentences.','images':[b]}],'stream':False,'keep_alive':'30m'}).encode(),{'Content-Type':'application/json'}))
j=json.load(r); print(f'[{time.time()-t:.1f}s]',j['message']['content'])
EOF
ollama ps; /usr/libexec/ApplicationFirewall/socketfilterfw --getglobalstate; /usr/libexec/ApplicationFirewall/socketfilterfw --getappblocked /opt/homebrew/Cellar/ollama/*/bin/ollama 2>/dev/null

Output

[10.6s] This is an abstract, seamless pattern composed of various rounded geometric shapes, such as circles and elongated rectangles. The design utilizes soft, luminous gradients of blues, purples, and peachy pastels, giving the image a dreamy and ethereal quality.
NAME             ID              SIZE      PROCESSOR    CONTEXT    UNTIL               
gemma4:latest    dc35e8d9c606    404 MB    100% GPU     32768      29 minutes from now    
Firewall is enabled. (State = 1)
Incoming connection to /opt/homebrew/Cellar/ollama/0.35.1_1/bin/ollama is permitted.

Your Mac is set up, and Gemma answers questions about a photo over the home network.

What I did
- Installed Ollama 0.35.1 with Homebrew. It runs as a background service that starts when you log in.
- Set OLLAMA_HOST=[REDACTED] in the service's launch file (~/Library/LaunchAgents/sh.brew.ollama.plist), so it accepts connections from other devices on the Wi-Fi.
- Downloaded gemma4 (6.6 GB) and checked that it runs on the M3 Max's GPU.
- The dialog you accepted was the macOS firewall. It now shows incoming connections to Ollama as permitted.

Test results (I sent the app's exact request to http://[REDACTED]:11434 with a 1024px JPEG):
- First question: took 149 s. That was the model loading for the first time, and probably the firewall dialog waiting on you too.
- Same question again, model already loaded: 10.6 s.
- Follow-up question: 9.5 s, and the answer used the earlier conversation.
- Answers: accurate, plain text, 2–5 sentences as the app asks for, and they used the folder and date I passed in.
- Model name that doesn't exist: returns 404 with model '…' not found, which the app turns into the "run ollama pull …" message.

These requests came from the Mac to its own network address. The TV itself hasn't connected yet.

On the TV: go to Settings → Gemma server and enter [REDACTED]. The app fills in the port.

Two things to watch
- The Mac's IP can change. If the router hands out a new address, the TV can't find Gemma. Set a fixed (reserved) address for the Mac in your router, or use its .local name.
- brew services restart ollama undoes the network setting. It rewrites the launch file without OLLAMA_HOST, so after it Ollama only listens to the Mac itself. Plain reboots are fine. If you run that command, tell me and I'll put the setting back.

The Gemma code changes are still not committed. Should I commit them now, or first build the app onto the TV and test it there?

You

Can we use faster model to make it reply under 5 seconds or even less

Agent

I'll first measure where the 10 s goes (reading the image, thinking, or writing the answer), then compare models and settings.

▸ Bash ollama pull gemma4:e2b 2>&1 | tail -1; S=<scratch>; sips -Z 512 $S/t.jpg --ou...

Input

$ ollama pull gemma4:e2b 2>&1 | tail -1; S=<scratch>; sips -Z 512 $S/t.jpg --out $S/t512.jpg >/dev/null; python3 - $S <<'EOF'
import json,base64,sys,urllib.request,time
S=sys.argv[1]
sysmsg='You help someone look through their own photos and videos on a TV. Answer about the attached picture in plain text (no markdown), concisely: usually 2–5 sentences, readable from a couch. Use the date, place and folder given as context when relevant. If you are unsure, say so briefly.'
def call(model,img,think=None,label=''):
    b=base64.b64encode(open(f'{S}/{img}','rb').read()).decode()
    body={'model':model,'messages':[{'role':'system','content':sysmsg},{'role':'user','content':'Taken: 12 Mar 2024. Album/folder: Wallpapers.\n\nWhat is this?','images':[b]}],'stream':False,'keep_alive':'30m'}
    if think is not None: body['think']=think
    t=time.time()
    try:
        j=json.load(urllib.request.urlopen(urllib.request.Request('http://localhost:11434/api/chat',json.dumps(body).encode(),{'Content-Type':'application/json'})))
    except urllib.error.HTTPError as e: print(label,e.code,e.read().decode()); return
    ns=1e9
    print(f"{label:28} total {time.time()-t:5.1f}s | load {j.get('load_duration',0)/ns:4.1f} prompt {j.get('prompt_eval_count')}tok {j.get('prompt_eval_duration',0)/ns:4.1f}s | gen {j.get('eval_count')}tok {j.get('eval_duration',0)/ns:4.1f}s | thinking {len(j['message'].get('thinking') or '')}ch")
for m in ['gemma4','gemma4:e2b']:
    call(m,'t.jpg',label=f'{m} warmup')
    call(m,'t.jpg',label=f'{m} 1024 default')
    call(m,'t.jpg',think=False,label=f'{m} 1024 think=false')
    call(m,'t512.jpg',think=False,label=f'{m} 512 think=false')
EOF

Output

success [K[?25h[?2026l
gemma4 warmup                total  27.7s | load  0.0 prompt 545tok  2.2s | gen 521tok 25.4s | thinking 1654ch
gemma4 1024 default          total  29.2s | load  0.0 prompt 545tok  0.1s | gen 563tok 29.0s | thinking 1797ch
gemma4 1024 think=false      total   5.2s | load  0.0 prompt 543tok  2.4s | gen 46tok  2.8s | thinking 0ch
gemma4 512 think=false       total   4.9s | load  0.0 prompt 223tok  1.0s | gen 61tok  3.9s | thinking 0ch
gemma4:e2b warmup            total  15.3s | load  5.1 prompt 545tok  1.5s | gen 369tok  8.7s | thinking 1151ch
gemma4:e2b 1024 default      total   9.9s | load  0.0 prompt 545tok  0.0s | gen 400tok  9.8s | thinking 1401ch
gemma4:e2b 1024 think=false  total   3.2s | load  0.0 prompt 543tok  1.6s | gen 56tok  1.5s | thinking 0ch
gemma4:e2b 512 think=false   total   2.7s | load  0.0 prompt 223tok  0.5s | gen 71tok  2.1s | thinking 0ch

▸ Bash S=<scratch>; F=$(find ~/Pictures ~/Downloads ~/Desktop -maxdepth 3 -iname '*....

Input

$ S=<scratch>; F=$(find ~/Pictures ~/Downloads ~/Desktop -maxdepth 3 -iname '*.jp*g' -size +300k 2>/dev/null | head -1); echo "$F"; sips -s format jpeg -Z 1024 "$F" --out $S/real.jpg >/dev/null && python3 - $S <<'EOF'
import json,base64,sys,urllib.request,time
S=sys.argv[1]
sysmsg='You help someone look through their own photos and videos on a TV. Answer about the attached picture in plain text (no markdown), concisely: usually 2–5 sentences, readable from a couch. Use the date, place and folder given as context when relevant. If you are unsure, say so briefly.'
b=base64.b64encode(open(f'{S}/real.jpg','rb').read()).decode()
for m in ['gemma4','gemma4:e2b']:
  for q in ['What is this?','Where was this taken?']:
    t=time.time()
    j=json.load(urllib.request.urlopen(urllib.request.Request('http://localhost:11434/api/chat',json.dumps({'model':m,'think':False,'messages':[{'role':'system','content':sysmsg},{'role':'user','content':q,'images':[b]}],'stream':False,'keep_alive':'30m'}).encode(),{'Content-Type':'application/json'})))
    print(f'--- {m} | {q} [{time.time()-t:.1f}s]\n{j["message"]["content"]}')
EOF

Output

~/Pictures/story_4.jpg
--- gemma4 | What is this? [10.9s]
This is a beautiful shot of a large ocean wave crashing. The water has a vibrant turquoise color where the wave is breaking against the deep dark blue of the open sea. It looks like a dynamic scene from the beach.
--- gemma4 | Where was this taken? [4.7s]
This appears to be a striking aerial or high-angle shot of a wave rolling into the ocean. The image shows bright white foam contrasting sharply with the deep turquoise and dark blue of the water. Without specific metadata, I cannot tell you where this photo was taken.
--- gemma4:e2b | What is this? [6.5s]
This appears to be a video or photo of ocean waves crashing onto a shore. The water is a deep turquoise color, contrasting with the white foam of the breaking waves. It looks like a dynamic scene capturing the energy of the ocean.
--- gemma4:e2b | Where was this taken? [2.5s]
This image appears to be a long exposure of ocean waves crashing onto a shore. It shows white, foamy waves meeting dark blue water. Without specific date, place, or folder information, it is impossible to say exactly where this was taken.

▸ Bash grep -n "Future<String> ask\|final body = jsonEncode\|'stream': false\|final ...

Input

$ grep -n "Future<String> ask\|final body = jsonEncode\|'stream': false\|final (status, json)\|/// One /api/chat call\|/// The photo (or video poster)" lib/services/gemma_service.dart

Output

59:  Future<String> ask(String question) async {
87:    final body = jsonEncode({
101:      'stream': false,
107:    final (status, json) = await _post(server, body);
127:  /// One /api/chat call: (HTTP status, decoded JSON body).
154:  /// The photo (or video poster) as a ~1024px JPEG, base64-encoded.

▸ Bash sed -n 55,60p lib/services/gemma_service.dart; sed -n 96,153p lib/services/ge...

Input

$ sed -n 55,60p lib/services/gemma_service.dart; sed -n 96,153p lib/services/gemma_service.dart

Output

static bool get hasServer => SettingsController.instance.gemmaServer != null;

  /// Asks [question] about the photo; returns the answer text. Throws a
  /// [GemmaException] with a user-facing message on failure.
  Future<String> ask(String question) async {
    final settings = SettingsController.instance;
              'when relevant. If you are unsure, say so briefly.',
        },
        ..._history,
        turn,
      ],
      'stream': false,
      // Keep the model loaded between questions while browsing (loading it
      // takes several seconds; Ollama's default unloads after 5 minutes).
      'keep_alive': '30m',
    });

    final (status, json) = await _post(server, body);
    final error = json['error'] as String?;
    if (status == 200 && error == null) {
      final answer =
          ((json['message'] as Map?)?['content'] as String? ?? '').trim();
      if (answer.isEmpty) {
        throw const GemmaException('Gemma didn’t return an answer.');
      }
      _history
        ..add(turn)
        ..add({'role': 'assistant', 'content': answer});
      return answer;
    }
    throw GemmaException(switch (status) {
      404 => 'The model “$model” isn’t on the Gemma server yet — run '
          '“ollama pull $model” there, or pick another model in Settings.',
      _ => 'Gemma error $status${error == null ? '' : ': $error'}',
    });
  }

  /// One /api/chat call: (HTTP status, decoded JSON body).
  Future<(int, Map<String, dynamic>)> _post(String server, String 
…[1096 more chars]

▸ Bash python3 - <<'EOF' p='lib/services/gemma_service.dart' s=open(p).read() def r(...

Input

$ python3 - <<'EOF'
p='lib/services/gemma_service.dart'
s=open(p).read()
def r(a,b):
    global s
    assert a in s, a
    s=s.replace(a,b)
r('''  /// Asks [question] about the photo; returns the answer text. Throws a
  /// [GemmaException] with a user-facing message on failure.
  Future<String> ask(String question) async {''','''  /// Asks [question] about the photo; returns the answer text. The answer
  /// streams in: [onPartial] gets the text so far as each piece arrives, so
  /// it can be shown while Gemma is still writing. Throws a [GemmaException]
  /// with a user-facing message on failure.
  Future<String> ask(
    String question, {
    void Function(String partial)? onPartial,
  }) async {''')
a=s.index("      'stream': false,")
b=s.index("  /// The photo (or video poster) as a ~1024px JPEG")
s=s[:a]+'''      'stream': true,
      // Answer straight away: with thinking on, Gemma 4 reasons for ~500
      // tokens first (10–30 s), and describing a photo doesn't need it.
      'think': false,
      // Keep the model loaded between questions while browsing (loading it
      // takes several seconds; Ollama's default unloads after 5 minutes).
      'keep_alive': '30m',
    });

    final answer = (await _chat(server, model, body, onPartial)).trim();
    if (answer.isEmpty) {
      throw const GemmaException('Gemma didn’t return an answer.');
    }
    _history
      ..add(turn)
      ..add({'role': 'assistant', 'content': answer});
    return answer;
  }

  /// One streaming /api/chat call; returns the whole answer. Ollama sends a
  /// JSON object per line, each with the next piece of the message.
  Future<String> _chat(
    String server,
    String model,
    String body,
    void Function(String partial)? onPartial,
  ) async {
    final client = HttpClient()..connectionTimeout = const Duration(seconds: 8);
    const unreachable = GemmaException(
        'Couldn’t reach the Gemma server — is the computer on, with Ollama '
        'running and listening on the network (OLLAMA_HOST=0.0.0.0)?');
    try {
      final req = await client.postUrl(Uri.parse('$server/api/chat'));
      req.headers.contentType = ContentType.json;
      req.add(utf8.encode(body));
      // Generous: the first question may wait for the model to load.
      final res = await req.close().timeout(const Duration(seconds: 180));
      final lines = res
          .transform(utf8.decoder)
          .transform(const LineSplitter())
          .where((l) => l.trim().isNotEmpty)
          .timeout(const Duration(seconds: 60));
      final answer = StringBuffer();
      await for (final line in lines) {
        final json = jsonDecode(line) as Map<String, dynamic>;
        final error = json['error'] as String?;
        if (res.statusCode != 200 || error != null) {
          throw GemmaException(switch (res.statusCode) {
            404 => 'The model “$model” isn’t on the Gemma server yet — run '
                '“ollama pull $model” there, or pick another model in '
        
…[1798 more chars]

Output

2:import 'dart:convert';
145:          .transform(const LineSplitter())
lib/screens/settings_screen.dart:251:      hint: 'Ollama tag, e.g. gemma4 or gemma4:26b',

▸ Bash python3 - <<'EOF' p='lib/widgets/ask_panel.dart' s=open(p).read() old=''' ...

Input

$ python3 - <<'EOF'
p='lib/widgets/ask_panel.dart'
s=open(p).read()
old='''    } on GemmaException catch (e) {
      turn.error = e.message;
    } catch (e) {
      turn.error = 'Something went wrong: $e';
    }'''
assert old in s
s=s.replace(old,'''    } on GemmaException catch (e) {
      turn
        ..answer = null // drop a half-streamed answer
        ..error = e.message;
    } catch (e) {
      turn
        ..answer = null
        ..error = 'Something went wrong: $e';
    }''')
open(p,'w').write(s)
p='lib/screens/settings_screen.dart'
s=open(p).read()
s=s.replace("hint: 'Ollama tag, e.g. gemma4 or gemma4:26b',","hint: 'Ollama tag — gemma4:e2b (fastest) or gemma4',")
open(p,'w').write(s)
EOF
flutter analyze 2>&1 | tail -3; git checkout analysis_options.yaml 2>/dev/null; git status --short

Output

Upgrading analysis_options.yaml to exclude build and platform directories.
Analyzing tv_gallery_gemma...                                   
No issues found! (ran in 7.9s)
 M android/app/src/main/AndroidManifest.xml
 M lib/screens/settings_screen.dart
 M lib/screens/slideshow_screen.dart
 M lib/screens/viewer_screen.dart
 M lib/services/answer_voice.dart
RM lib/services/gemini_service.dart -> lib/services/gemma_service.dart
 M lib/services/settings_controller.dart
 M lib/widgets/ask_panel.dart
 M lib/widgets/zoomable_image.dart

Code updated and analyzer clean. Now I'm timing the streaming request against the real Gemma server: when the first words arrive and when the answer finishes.

▸ Bash S=<scratch>; cat > $S/stream_test.dart <<'EOF' import 'dart:convert'; import ...

Input

$ S=<scratch>; cat > $S/stream_test.dart <<'EOF'
import 'dart:convert';
import 'dart:io';
Future<void> main(List<String> a) async {
  final img = base64Encode(File(a[1]).readAsBytesSync());
  for (final model in [a[2], a[2]]) {
    final sw = Stopwatch()..start();
    final client = HttpClient();
    final req = await client.postUrl(Uri.parse('${a[0]}/api/chat'));
    req.headers.contentType = ContentType.json;
    req.add(utf8.encode(jsonEncode({
      'model': model, 'stream': true, 'think': false, 'keep_alive': '30m',
      'messages': [{'role': 'user', 'content': 'What is this?', 'images': [img]}],
    })));
    final res = await req.close();
    final answer = StringBuffer();
    int? first;
    await for (final line in res.transform(utf8.decoder).transform(const LineSplitter()).where((l) => l.trim().isNotEmpty)) {
      final j = jsonDecode(line) as Map<String, dynamic>;
      if (j['error'] != null) { print('${res.statusCode} ${j['error']}'); break; }
      final piece = (j['message'] as Map?)?['content'] as String?;
      if (piece != null && piece.isNotEmpty) { first ??= sw.elapsedMilliseconds; answer.write(piece); }
      if (j['done'] == true) break;
    }
    client.close();
    print('$model first words ${first}ms, done ${sw.elapsedMilliseconds}ms: ${answer.toString().trim()}');
  }
}
EOF
dart run $S/stream_test.dart http://192.168.68.56:11434 $S/real.jpg gemma4:e2b; dart run $S/stream_test.dart http://192.168.68.56:11434 $S/real.jpg gemma4; dart run $S/stream_test.dart http://192.168.68.56:11434 $S/real.jpg nope 2>&1 | head -1

Output

gemma4:e2b first words 847ms, done 6094ms: This is a photograph of a **seascape** or **ocean wave breaking on a shore**.

Here's a breakdown of what the image shows:

* **Waves:** The foreground is dominated by white, foamy waves crashing onto the shore.
* **Water Color:** The water in the deeper areas appears very dark (almost black), suggesting deep water or a dark sky/lighting condition. However, where the water is shallower or illuminated by light, it displays beautiful shades of **turquoise and deep blue/teal**.
* **Motion/Texture:** The photograph captures the dynamic motion of the water—the energy of the breaking waves and the flow of the ocean.
* **Contrast:** There is a very high contrast between the bright white of the surf and the dark, deep tones of the water.

In short, it's a dramatic and beautiful shot of the **ocean waves**.
gemma4:e2b first words 89ms, done 4384ms: This is a **photograph of ocean waves crashing onto a shore**.

Here's a breakdown of what the image shows:

* **Waves:** There is a dynamic interaction between the ocean water and the land. You can see white, foamy waves breaking and rolling in, contrasted against the deep blue/teal color of the water.
* **Water Color:** The water exhibits beautiful shades of turquoise, teal, and deep navy/black in the deeper sections, suggesting clear, deep ocean water.
* **Action:** The photograph captures the energy of the surf, showing the white water spray and the continuous movement of the waves.

**In summa
…[1613 more chars]

Answers are now about 2–3 s from asking to the full answer on screen with the default gemma4:e2b, and the first words show up in under a second. All of this was measured on the Mac against its own network address. I haven't run it on the TV yet.

What I changed
- Thinking off: this was the main cause. Gemma 4 was silently reasoning for about 500 words before every answer, which took 10–29 s. Turning it off (think: false) costs almost nothing in quality for describing a photo.
- Default model is now gemma4:e2b: I downloaded it next to gemma4, which stays one setting away under Settings → Model if you prefer slightly better wording.
- Answers stream in: the words appear on screen as Gemma writes them, instead of all at once at the end. If something fails halfway through, the partial answer is replaced by the error message. Reading aloud still starts once the full answer is in.

Measured (photo already prepared, model loaded)

	Full answer	First words
`gemma4:e2b`	~2.5–3 s	~0.1–0.9 s
`gemma4`	~5 s	~0.1–0.9 s*
Before (thinking on)	10–29 s	same as full answer

*The first gemma4 question after using e2b took about 6 s before any words appeared, because the Mac had to load the model. That only happens when you switch models or after 30 minutes idle.

In the streaming test I left out the app's short-answer instruction, so the answers ran long and slow there (4–13 s). With the instruction, as in the earlier test, they're 2–5 sentences, which gives the times in the table.

flutter analyze passes. Should I commit now, or build onto the TV first so you can try it there?

You

build and install on the TV

Agent

▸ Bash adb devices -l; cat ~/MobileDev/Flutter/tv_gallery_gemma/.fvmrc; ls ~/.claude...

Input

$ adb devices -l; cat ~/MobileDev/Flutter/tv_gallery_gemma/.fvmrc; ls ~/.claude/projects/-Users-souvikbiswas-MobileDev-Flutter-tv-gallery-gemma/memory/ 2>/dev/null

Output

List of devices attached

{
  "flutter": "stable"
}

You

let's do debug for now

Agent

No TV is connected over adb right now. I'll check whether it shows up on the network:

▸ Bash adb mdns check; adb mdns services; grep -rh "adb connect" ~/.zsh_history 2>/d...

Input

$ adb mdns check; adb mdns services; grep -rh "adb connect" ~/.zsh_history 2>/dev/null | tail -3

Output

mdns daemon version [adb discovery 0.0.0]
List of discovered mdns services

▸ Bash arp -a | grep -v incomplete | head -30; for ip in $(arp -a | grep -v incomple...

Input

$ arp -a | grep -v incomplete | head -30; for ip in $(arp -a | grep -v incomplete | sed -E 's/.*\(([0-9.]+)\).*/\1/'); do (nc -z -G 1 $ip 5555 2>/dev/null && echo "adb port open: $ip") & done; wait

Output

? (192.168.68.1) at 48:22:54:c3:8a:e8 on en0 ifscope [ethernet]
? (192.168.68.50) at 7c:9e:bd:6:b0:74 on en0 ifscope [ethernet]
? (192.168.68.51) at 90:70:69:12:a6:a4 on en0 ifscope [ethernet]
? (192.168.68.52) at 10:5a:95:3f:f4:36 on en0 ifscope [ethernet]
? (192.168.68.55) at da:6e:e6:4a:5e:71 on en0 ifscope [ethernet]
? (192.168.68.56) at 60:3e:5f:88:47:44 on en0 ifscope permanent [ethernet]
? (192.168.68.58) at ba:7:f0:f7:3f:c1 on en0 ifscope [ethernet]
? (192.168.68.59) at 38:e1:3d:ba:53:63 on en0 ifscope [ethernet]
? (192.168.68.60) at 32:8a:d5:d:97:ae on en0 ifscope [ethernet]
? (192.168.68.62) at 78:46:5c:60:b0:d3 on en0 ifscope [ethernet]
? (192.168.68.63) at 84:d3:28:da:69:4d on en0 ifscope [ethernet]
? (192.168.68.65) at 68:ef:dc:9a:e6:e2 on en0 ifscope [ethernet]
? (192.168.68.66) at a4:83:e7:e4:e1:89 on en0 ifscope [ethernet]
? (192.168.68.67) at 56:c4:3d:e6:bb:3b on en0 ifscope [ethernet]
? (192.168.71.255) at ff:ff:ff:ff:ff:ff on en0 ifscope [ethernet]
mdns.mcast.net (224.0.0.251) at 1:0:5e:0:0:fb on en0 ifscope permanent [ethernet]
? (239.255.255.250) at 1:0:5e:7f:ff:fa on en0 ifscope permanent [ethernet]

I can't find the TV on the network. None of the devices answers on adb's port (5555), and nothing advertises wireless debugging. I need you to turn on debugging on the Bravia:

Go to Settings → System → About and click Build seven times to unlock developer options (skip this if you've done it before).
Go to Settings → System → Developer options and turn on USB debugging, plus Network debugging / ADB over network if it's there.
Send me the TV's IP address from Settings → Network & Internet → (your Wi-Fi) → IP address.

Once you send the IP, I'll run adb connect <ip>. You'll need to accept an "Allow USB debugging?" prompt on the TV, then I'll start the debug build with flutter run. If you'd rather connect it yourself, type ! adb connect <tv-ip> here and I'll take it from there.

You

chedck now

Agent

▸ Bash adb devices -l; adb mdns services; for ip in $(arp -a | grep -v incomplete | ...

Input

$ adb devices -l; adb mdns services; for ip in $(arp -a | grep -v incomplete | sed -E 's/.*\(([0-9.]+)\).*/\1/'); do (nc -z -G 1 $ip 5555 2>/dev/null && echo "adb port open: $ip") & done; wait

Output

List of devices attached
<tv-adb-serial> device product:BRAVIA_AE2_PA model:BRAVIA_4K_AE2 device:BRAVIA_AE2 transport_id:759

List of discovered mdns services
<tv-adb-serial>   _adb-tls-connect._tcp   192.168.68.62:39273

The TV is connected (BRAVIA 4K AE2 at [REDACTED]). Starting the debug build on it:

▸ Bash S=<scratch> && mkfifo $S/run.fifo 2>/dev/null; (tail -f $S/run.fifo | flutter...

Input

$ S=<scratch> && mkfifo $S/run.fifo 2>/dev/null; (tail -f $S/run.fifo | flutter run --debug -d "<tv-adb-serial>" > $S/run.log 2>&1) &
echo started

Output

Command running in background with ID: bdfva43ve. Output is being written to: <tmp> You will be notified when it completes. To check interim output, use Read on that file path.

▸ ToolSearch {"query": "select:Monitor", "max_results": 1}

Input

{
  "query": "select:Monitor",
  "max_results": 1
}

Output

[image]

▸ Bash S=<scratch>; until grep -qE "Flutter run key commands|Error|FAILURE|Exception...

Input

$ S=<scratch>; until grep -qE "Flutter run key commands|Error|FAILURE|Exception|No supported devices|not found" $S/run.log; do sleep 2; done; tail -25 $S/run.log

Output

I/flutter ( 7444):     These options are going to go away in an upcoming Flutter release. Remove
I/flutter ( 7444):     the explicit opt-out. If you need to opt-out, please report a bug describing
I/flutter ( 7444):     the issue.
I/flutter ( 7444): 
I/flutter ( 7444):     https://github.com/flutter/flutter/issues/new?template=02_bug.yml
I/flutter ( 7444): 
D/FlutterRenderer( 7444): Width is zero. 0,0
Syncing files to device BRAVIA 4K AE2 (wireless)...             
I/Choreographer( 7444): Skipped 283 frames!  The application may be doing too much work on its main thread.
Syncing files to device BRAVIA 4K AE2 (wireless)...                168ms

Flutter run key commands.
r Hot reload. 🔥🔥🔥
R Hot restart.
h List all available interactive commands.
d Detach (terminate "flutter run" but leave application running).
c Clear the screen
q Quit (terminate the application on the device).

A Dart VM Service on BRAVIA 4K AE2 is available at: http://127.0.0.1:50620/lBlMT0wSeBI=/
The Flutter DevTools debugger and profiler on BRAVIA 4K AE2 is available at: http://127.0.0.1:50620/lBlMT0wSeBI=/devtools/?uri=ws://127.0.0.1:50620/lBlMT0wSeBI=/ws
D/FlutterRenderer( 7444): Width is zero. 0,0
D/FlutterJNI( 7444): Sending viewport metrics to the engine.
I/TextToSpeech( 7444): Setting up the connection to TTS engine...
E/OpenGLRenderer( 7444): Unable to match the desired swap behavior.

▸ Monitor tail -n 0 -f <scratch>/run.log | grep -E --line-buffered "EXCEPTION|Exception...

Input

tail -n 0 -f <scratch>/run.log | grep -E --line-buffered "EXCEPTION|Exception|Error:|══╡|Lost connection|Application finished"

Output

Monitor started (task b1r1vuvr2, expires in 30m unless the source ends first; you get one notice at expiry — re-arm if you still need the watch). You will be notified on each event. Keep working — do not poll or sleep. Events may arrive while you are waiting for the user — an event is not their reply.

The debug build is running on the TV, the BRAVIA 4K AE2, connected over Wi-Fi. I'm watching its log for errors while you try it.

To try it:
1. In Memories, open Settings → Gemma, go to Gemma server → Add, and enter [REDACTED] (the Mac). Leave Model as gemma4:e2b.
2. Open a photo and press Down on the remote to open Ask Gemma, then pick a suggestion or ask something.

The first question can take about 5 s while the Mac loads the model. After that, answers should start appearing within about a second.

Tell me how it goes. I can hot-reload any changes straight onto the TV.

You

'~/Desktop/Screenshots/tv-125724.png'

remove the "-- or use the keyboard mic" text part in hint

Agent

▸ Read ~/Desktop/Screenshots/tv-125724.png

Input

~/Desktop/Screenshots/tv-125724.png

Output

[image]

▸ Bash sed -i '' "s/'Ask anything about this photo — or use the keyboard’s mic'/'Ask...

Input

$ sed -i '' "s/'Ask anything about this photo — or use the keyboard’s mic'/'Ask anything about this photo'/" lib/widgets/ask_panel.dart && grep -n "Ask anything" lib/widgets/ask_panel.dart && echo r > <scratch>/run.fifo; sleep 4; tail -3 <scratch>/run.log

Output

353:              ? 'Ask anything about this photo'

Performing hot reload...                                        
Reloaded 1 of 2219 libraries in 3,294ms (compile: 80 ms, reload: 1318 ms, reassemble: 1648 ms).

The hint now just says "Ask anything about this photo". I hot-reloaded it onto the TV, so it shows next time Ask Gemma opens.

You

seems like even with the keyboard closed, I can't hit down to selct any of the options from there

Agent

Down is being swallowed by the text field: it handles Down itself, as "move the cursor to the end". Once there's a conversation, Down already moves into the answers. Before any question, it should go to the suggestion pills instead:

▸ Bash python3 - <<'EOF' p='lib/widgets/ask_panel.dart' s=open(p).read() old=''' ...

Input

$ python3 - <<'EOF'
p='lib/widgets/ask_panel.dart'
s=open(p).read()
old='''        // Down (keyboard hidden) moves into the answers to scroll them.
        if (event.logicalKey == LogicalKeyboardKey.arrowDown &&
            _field.hasFocus &&
            _turns.isNotEmpty) {
          if (event is KeyDownEvent) _answers.requestFocus();
          return KeyEventResult.handled;
        }'''
assert old in s
s=s.replace(old,'''        // Down (keyboard hidden) moves into the answers to scroll them, or
        // to the suggestions before anything's been asked. (The field would
        // otherwise keep Down to move its cursor.)
        if (event.logicalKey == LogicalKeyboardKey.arrowDown &&
            _field.hasFocus) {
          if (event is KeyDownEvent) {
            if (_turns.isNotEmpty) {
              _answers.requestFocus();
            } else {
              _field.focusInDirection(TraversalDirection.down);
            }
          }
          return KeyEventResult.handled;
        }''')
open(p,'w').write(s)
EOF
echo r > <scratch>/run.fifo; sleep 4; tail -1 <scratch>/run.log

Output

Reloaded 1 of 2219 libraries in 2,909ms (compile: 19 ms, reload: 1150 ms, reassemble: 1587 ms).

I fixed it and hot-reloaded it onto the TV. With the keyboard closed and nothing asked yet, Down from the question field now jumps to the suggestion pills, and Up should take you back to the field. After you've asked something, Down still moves into the answers to scroll them. Close and reopen Ask Gemma to try it.

You

closing the keyboard with back shoudl actually unfocus the text field as well I think

Agent

First I'll check how the TV reports the keyboard closing. I can drive the TV over adb and take screenshots:

▸ Bash cat android/app/src/main/kotlin/*/*/*/MainActivity.kt 2>/dev/null | head -60 ...

Input

$ cat android/app/src/main/kotlin/*/*/*/MainActivity.kt 2>/dev/null | head -60 || find android/app/src/main -name "*.kt" | head; adb shell dumpsys input_method | grep -E "mInputShown|mImeWindowVis|mCurMethodId|mShowRequested" | head

Output

package com.souvikbiswas.tvgallery

import io.flutter.embedding.android.FlutterActivity
import io.flutter.embedding.engine.FlutterEngine

class MainActivity : FlutterActivity() {
    override fun configureFlutterEngine(flutterEngine: FlutterEngine) {
        super.configureFlutterEngine(flutterEngine)
        flutterEngine.platformViewsController.registry.registerViewFactory(
            "tv_gallery/video",
            VideoPlayerViewFactory(flutterEngine.dartExecutor.binaryMessenger),
        )
        MediaIndexChannel(applicationContext, flutterEngine.dartExecutor.binaryMessenger)
    }
}
  mCurMethodId=com.google.android.inputmethod.latin/com.android.inputmethod.latin.LatinIME
  mInputShown=true

▸ Bash grep -n "class _AskPanelState\|void initState() {\| void dispose() {" lib/wi...

Input

$ grep -n "class _AskPanelState\|void initState() {\|  void dispose() {" lib/widgets/ask_panel.dart | head -4

Output

58:class _AskPanelState extends State<_AskPanel> {
71:  void initState() {
97:  void dispose() {
504:  void initState() {

▸ Bash python3 - <<'EOF' p='lib/widgets/ask_panel.dart' s=open(p).read() s=s.replace...

Input

$ python3 - <<'EOF'
p='lib/widgets/ask_panel.dart'
s=open(p).read()
s=s.replace('''class _AskPanelState extends State<_AskPanel> {''','''class _AskPanelState extends State<_AskPanel> with WidgetsBindingObserver {
  @override
  void didChangeMetrics() {
    final v = View.of(context);
    debugPrint('DBGIME insets=${v.viewInsets.bottom} padding=${v.viewPadding.bottom} size=${v.physicalSize}');
  }
''',1)
s=s.replace('''  void initState() {
    super.initState();
    _loadBackdrop();''','''  void initState() {
    super.initState();
    WidgetsBinding.instance.addObserver(this);
    _loadBackdrop();''',1)
open(p,'w').write(s)
EOF
S=<scratch>; echo R > $S/run.fifo; sleep 6; tail -2 $S/run.log; adb exec-out screencap -p > $S/s1.png

Output

Performing hot restart...

▸ Bash S=<scratch>; sleep 3; tail -2 $S/run.log; adb exec-out screencap -p > $S/s1.p...

Input

$ S=<scratch>; sleep 3; tail -2 $S/run.log; adb exec-out screencap -p > $S/s1.png; sips -Z 960 $S/s1.png >/dev/null

Output

D/FlutterJNI( 7444): Sending viewport metrics to the engine.
I/iswas.tvgallery( 7444): Background concurrent copying GC freed 59728(1758KB) AllocSpace objects, 0(0B) LOS objects, 49% free, 3417KB/6834KB, paused 127us,42us total 131.333ms

▸ Read <scratch>/s1.png

Input

<scratch>/s1.png

Output

[image]

▸ Bash S=<scratch>; sleep 4; adb exec-out screencap -p > $S/s1.png; sips -Z 960 $S/s...

Input

$ S=<scratch>; sleep 4; adb exec-out screencap -p > $S/s1.png; sips -Z 960 $S/s1.png >/dev/null

Output

(Bash completed with no output)

▸ Read <scratch>/s1.png

Input

<scratch>/s1.png

Output

[image]

▸ Bash S=<scratch>; adb shell input keyevent DPAD_DOWN; sleep 3; adb shell dumpsys i...

Input

$ S=<scratch>; adb shell input keyevent DPAD_DOWN; sleep 3; adb shell dumpsys input_method | grep mInputShown; grep DBGIME $S/run.log | tail -3; echo ---back; adb shell input keyevent BACK; sleep 2; adb shell dumpsys input_method | grep mInputShown; grep DBGIME $S/run.log | tail -3; adb exec-out screencap -p > $S/s2.png; sips -Z 960 $S/s2.png >/dev/null

Output

mInputShown=false
I/flutter ( 7444): DBGIME insets=0.0 padding=0.0 size=Size(1920.0, 1080.0)
I/flutter ( 7444): DBGIME insets=0.0 padding=0.0 size=Size(1920.0, 1080.0)
I/flutter ( 7444): DBGIME insets=0.0 padding=0.0 size=Size(1920.0, 1080.0)
---back
  mInputShown=false
I/flutter ( 7444): DBGIME insets=0.0 padding=0.0 size=Size(1920.0, 1080.0)
I/flutter ( 7444): DBGIME insets=0.0 padding=0.0 size=Size(1920.0, 1080.0)
I/flutter ( 7444): DBGIME insets=0.0 padding=0.0 size=Size(1920.0, 1080.0)

▸ Read <scratch>/s2.png

Input

<scratch>/s2.png

Output

[image]

I'm checking how the TV signals the keyboard closing. A debug probe I added caused an error (I didn't unregister it when the panel closes), so I'm looking at that first:

▸ Bash S=<scratch>; grep -n -A12 "EXCEPTION CAUGHT" $S/run.log | tail -14

Input

$ S=<scratch>; grep -n -A12 "EXCEPTION CAUGHT" $S/run.log | tail -14

Output

432:══╡ EXCEPTION CAUGHT BY WIDGETS LIBRARY ╞═══════════════════════════════════════════════════════════
433-The following assertion was thrown while dispatching notifications for
434-WidgetsBindingObserver.didChangeMetrics:
435-This widget has been unmounted, so the State no longer has a context (and should be considered
436-defunct).
437-Consider canceling any active work during "dispose" or using the "mounted" getter to determine if
438-the State is still active.
439-
440-When the exception was thrown, this was the stack:
441-#0      State.context.<anonymous closure> (package:flutter/src/widgets/framework.dart:952:9)
442-#1      State.context (package:flutter/src/widgets/framework.dart:958:6)
443-#2      _AskPanelState.didChangeMetrics (package:tv_gallery/widgets/ask_panel.dart:61:23)
444-#3      WidgetsBinding.handleMetricsChanged (package:flutter/src/widgets/binding.dart:926:18)

▸ Bash adb shell input keyevent DPAD_CENTER; sleep 3; adb shell dumpsys input_method...

Input

$ adb shell input keyevent DPAD_CENTER; sleep 3; adb shell dumpsys input_method | grep mInputShown; adb shell dumpsys window | grep -iE "InsetsSource.*ime|type=ime|mImeInsetsSourceProvider|isImeShowing|ImeInsetsSourceProvider" | head -8

Output

mInputShown=true
    mIsImeShowing=false
        InsetsSource id=3 type=ime frame=[0,1080][1920,1080] visibleFrame=[0,1080][1920,1080] visible=true flags= insetsRoundedCornerFrame=false
        InsetsSourceControl: {3 mType=ime mSurfacePosition=Point(0, 0) mInsetsHint=Insets{left=0, top=0, right=0, bottom=0}}
      ImeInsetsSourceProvider
        mSource=InsetsSource id=3 type=ime frame=[0,1080][1920,1080] visibleFrame=[0,1080][1920,1080] visible=true flags= insetsRoundedCornerFrame=false
        mControl=InsetsSourceControl mId=3 mType=ime mLeash=Surface(name=Surface(name=73cc467 InputMethod)/@0xb81a8b2 - animation-leash of insets_animation)/@0xda3be45 mInitiallyVisible=false mSurfacePosition=Point(0, 0) mInsetsHint=Insets{left=0, top=0, right=0, bottom=0} mSkipAnimationOnce=false

▸ Bash adb shell getprop ro.build.version.sdk; cd ~/MobileDev/Flutter/tv_gallery_gem...

Input

$ adb shell getprop ro.build.version.sdk; cd ~/MobileDev/Flutter/tv_gallery_gemma && ls android/app/src/main/kotlin/com/souvikbiswas/tvgallery/; grep -n "dependencies" -A8 android/app/build.gradle.kts; grep -n "minSdk" -r android/app/build.gradle.kts; sed -n 1,40p android/app/src/main/kotlin/com/souvikbiswas/tvgallery/MediaIndexChannel.kt

Output

34
MainActivity.kt
MediaIndexChannel.kt
VideoPlayerView.kt
VideoPlayerViewFactory.kt
43:dependencies {
44-    // ExoPlayer (Media3) for native video rendered to a SurfaceView — gives true
45-    // HDR10/HLG/Dolby Vision passthrough and smooth high-frame-rate playback,
46-    // which the Flutter-texture path can't do.
47-    implementation("androidx.media3:media3-exoplayer:1.4.1")
48-}
49-
50-flutter {
51-    source = "../.."
android/app/build.gradle.kts:22:        minSdk = flutter.minSdkVersion
package com.souvikbiswas.tvgallery

import android.content.Context
import android.database.Cursor
import android.graphics.Bitmap
import android.graphics.BitmapFactory
import android.media.ExifInterface
import android.media.ThumbnailUtils
import android.os.Build
import android.os.CancellationSignal
import android.os.Environment
import android.os.Handler
import android.os.Looper
import android.os.storage.StorageManager
import android.provider.MediaStore
import android.provider.MediaStore.Files.FileColumns
import android.util.Size
import io.flutter.plugin.common.BinaryMessenger
import io.flutter.plugin.common.MethodCall
import io.flutter.plugin.common.MethodChannel
import java.io.File
import java.io.FileOutputStream
import java.util.concurrent.ConcurrentHashMap
import java.util.concurrent.atomic.AtomicBoolean
import java.util.concurrent.Executors

/**
 * Lightweight MediaStore queries for the folder browser.
 *
 * photo_manager's asset listing materialises a full entity per file — inclu
…[693 more chars]

Okay, I'll leave it. Removing my debug probe:

▸ Bash python3 - <<'EOF' p='lib/widgets/ask_panel.dart' s=open(p).read() probe='''cl...

Input

$ python3 - <<'EOF'
p='lib/widgets/ask_panel.dart'
s=open(p).read()
probe='''class _AskPanelState extends State<_AskPanel> with WidgetsBindingObserver {
  @override
  void didChangeMetrics() {
    final v = View.of(context);
    debugPrint('DBGIME insets=${v.viewInsets.bottom} padding=${v.viewPadding.bottom} size=${v.physicalSize}');
  }
'''
assert probe in s
s=s.replace(probe,'class _AskPanelState extends State<_AskPanel> {\n')
s=s.replace('''    WidgetsBinding.instance.addObserver(this);
    _loadBackdrop();''','''    _loadBackdrop();''')
open(p,'w').write(s)
EOF
grep -c "DBGIME\|addObserver" lib/widgets/ask_panel.dart; S=<scratch>; echo r > $S/run.fifo; sleep 4; tail -1 $S/run.log; git diff --stat

Output

0
Reloaded 8 of 2219 libraries in 3,098ms (compile: 46 ms, reload: 1362 ms, reassemble: 1610 ms).
 analysis_options.yaml                    |   5 +
 android/app/src/main/AndroidManifest.xml |   9 +-
 lib/screens/settings_screen.dart         |  58 +++++---
 lib/screens/slideshow_screen.dart        |   4 +-
 lib/screens/viewer_screen.dart           |   6 +-
 lib/services/answer_voice.dart           |   2 +-
 lib/services/gemma_service.dart          | 227 ++++++++++++++++---------------
 lib/services/settings_controller.dart    |  55 ++++++--
 lib/widgets/ask_panel.dart               |  74 ++++++----
 lib/widgets/zoomable_image.dart          |   2 +-
 10 files changed, 260 insertions(+), 182 deletions(-)

▸ Bash git checkout analysis_options.yaml && git status --short | wc -l

Input

$ git checkout analysis_options.yaml && git status --short | wc -l

Output

Updated 1 path from the index
       9

I'm leaving the Back/keyboard behaviour as it is. I removed the temporary debug code (it was what caused the error in the log) and hot-reloaded the TV. I also reverted the analysis_options.yaml change that flutter run added on its own.

If you change your mind later, here's what I found: the TV keyboard never tells the app it's open (the space it covers always reads 0). Android does still mark it as visible, so the app could ask Android directly through a small piece of Android code.

Nothing is committed yet. The changes are the switch to Gemma, the speed changes, the shorter hint, and Down reaching the suggestion pills. The debug app is still running on the TV. Say when you want me to commit.

The old panels are still registered for my removed debug hook in the running app, so they keep throwing. A hot restart clears them:

▸ Bash S=<scratch>; echo R > $S/run.fifo; sleep 8; grep -n "Restarted application" $...

Input

$ S=<scratch>; echo R > $S/run.fifo; sleep 8; grep -n "Restarted application" $S/run.log | tail -1; L=$(grep -n "Restarted application" $S/run.log | tail -1 | cut -d: -f1); tail -n +$L $S/run.log | grep -c didChangeMetrics

Output

710:Restarted application in 7,528ms.
0

Those alerts are from before the restart arriving late. To confirm:

▸ Bash S=<scratch>; L=$(grep -n "Restarted application" $S/run.log | tail -1 | cut -...

Input

$ S=<scratch>; L=$(grep -n "Restarted application" $S/run.log | tail -1 | cut -d: -f1); wc -l < $S/run.log; tail -n +$L $S/run.log | grep -c "didChangeMetrics\|EXCEPTION"

Output

711
0

The errors have stopped. They came from my temporary debug code still being hooked into panels that were already open, and a hot restart cleared them. The log has been clean since the restart, and the TV app reopened where you were.

The rest is unchanged: nothing is committed yet, and the debug app is still running on the TV.

You

'~/Desktop/Screenshots/tv-130502.png'for the top bar buttons can you add a 50% opacity dash background color to make sure the texts are always reasdable

Agent

▸ Read ~/Desktop/Screenshots/tv-130502.png

Input

~/Desktop/Screenshots/tv-130502.png

Output

[image]

I'm taking "dash" to mean a dark background. Finding the top-bar chip widget:

▸ Bash grep -n "'Ask'\|'Slideshow'" lib/screens/*.dart | head; grep -n "class _TopCh...

Input

$ grep -n "'Ask'\|'Slideshow'" lib/screens/*.dart | head; grep -n "class _TopChip\|class _Chip\|class _ActionChip\|class .*Chip" -r lib | head

Output

lib/screens/settings_screen.dart:135:                      _SectionHeader('Slideshow'),
lib/screens/slideshow_screen.dart:590:                label: 'Ask',
lib/screens/viewer_screen.dart:404:                      label: 'Ask',
lib/screens/viewer_screen.dart:413:                      label: 'Slideshow',
lib/screens/settings_screen.dart:334:class _ChoiceChips<T> extends StatelessWidget {
lib/screens/slideshow_screen.dart:614:class _GlassChip extends StatefulWidget {
lib/screens/slideshow_screen.dart:630:class _GlassChipState extends State<_GlassChip> {

▸ Bash sed -n 395,425p lib/screens/viewer_screen.dart; sed -n 580,700p lib/screens/s...

Input

$ sed -n 395,425p lib/screens/viewer_screen.dart; sed -n 580,700p lib/screens/slideshow_screen.dart

Output

fontSize: 13,
                              shadows: [Shadow(blurRadius: 8, color: Colors.black54)],
                            ),
                          ),
                        ],
                      ),
                    ),
                    _TopPill(
                      icon: LucideIcons.sparkles,
                      label: 'Ask',
                      focusNode: _askFocus,
                      onActivate: _ask,
                      onDown: () => _imageFocus.requestFocus(),
                      onRight: () => _slideshowFocus.requestFocus(),
                    ),
                    const SizedBox(width: 10),
                    _TopPill(
                      icon: LucideIcons.play,
                      label: 'Slideshow',
                      focusNode: _slideshowFocus,
                      onActivate: _startSlideshow,
                      onDown: () => _imageFocus.requestFocus(),
                      onLeft: () => _askFocus.requestFocus(),
                    ),
                  ],
                ),
              ),
            ),
            // Bare chevron hints (fill on hover; D-pad uses Left/Right directly).
            Positioned(
              left: 18,
                icon: _paused
                    ? LucideIcons.play
                    : LucideIcons.pause,
                label: _paused ? 'Play' : 'Pause',
                onTap: _togglePause,
                focusNode: _playFocus,
              ),
              const SizedBox(width: 
…[3146 more chars]

▸ Bash grep -n "class _PillButton" -A60 lib/screens/viewer_screen.dart | grep -n "co...

Input

$ grep -n "class _PillButton" -A60 lib/screens/viewer_screen.dart | grep -n "color\|decoration\|border"

Output

(Bash completed with no output)

▸ Bash L=$(grep -n "class _TopPill " lib/screens/viewer_screen.dart | cut -d: -f1); ...

Input

$ L=$(grep -n "class _TopPill " lib/screens/viewer_screen.dart | cut -d: -f1); sed -n "$L,$((L+110))p" lib/screens/viewer_screen.dart | grep -n "color:\|alpha"

Output

69:                  color: active ? Colors.white : Colors.transparent,
72:                      color: Colors.white.withValues(alpha: active ? 1 : 0.4)),
77:                    Icon(widget.icon, size: 16, color: fg),
81:                            color: fg,

▸ Bash python3 - <<'EOF' import re p='lib/screens/viewer_screen.dart' s=open(p).read...

Input

$ python3 - <<'EOF'
import re
p='lib/screens/viewer_screen.dart'
s=open(p).read()
old="color: active ? Colors.white : Colors.transparent,"
assert s.count(old)==1
s=s.replace(old,"""// Dark when idle so the label reads over bright photos.
                  color: active
                      ? Colors.white
                      : Colors.black.withValues(alpha: 0.5),""")
open(p,'w').write(s)
p='lib/screens/slideshow_screen.dart'
s=open(p).read()
old="color: _hover ? Colors.white : Colors.white.withValues(alpha: 0.14),"
assert s.count(old)==1
s=s.replace(old,"""// Dark when idle so the label reads over bright photos.
            color: _hover ? Colors.white : Colors.black.withValues(alpha: 0.5),""")
open(p,'w').write(s)
EOF
S=<scratch>; echo r > $S/run.fifo; sleep 4; tail -1 $S/run.log; adb exec-out screencap -p > $S/s3.png; sips -Z 960 $S/s3.png >/dev/null

Output

Reloaded 2 of 2219 libraries in 3,044ms (compile: 53 ms, reload: 1416 ms, reassemble: 1511 ms).
[This command modified 2 files you've previously read: lib/screens/slideshow_screen.dart, lib/screens/viewer_screen.dart. Call Read before editing.]

▸ Read <scratch>/s3.png

Input

<scratch>/s3.png

Output

[image]

The controls have auto-hidden. Pressing Up to bring them back:

▸ Bash S=<scratch>; adb shell input keyevent DPAD_UP; sleep 1; adb exec-out screenca...

Input

$ S=<scratch>; adb shell input keyevent DPAD_UP; sleep 1; adb exec-out screencap -p > $S/s3.png; sips -c 200 960 --cropOffset 0 960 $S/s3.png --out $S/s3c.png >/dev/null

Output

(Bash completed with no output)

▸ Read <scratch>/s3c.png

Input

<scratch>/s3c.png

Output

[image]

I gave the top-bar buttons a 50% black background when they're not selected. The selected button stays solid white. I assumed "dash" was a typo for "dark". It's hot-reloaded on the TV. In the screenshot I took, "Ask" now reads clearly over the bright sky, where before it nearly disappeared.

I changed the same thing on the slideshow's top bar (the Play/Pause and Ask buttons) so the two screens match. Those were faint white at 14% before.

You

is ther a way I can record the screen of the TV? from this mac

I already have an alis to capture screenshot using tvshot

Agent

▸ Bash grep -n "tvshot" ~/.zshrc ~/.zprofile ~/.aliases 2>/dev/null; which scrcpy

Input

$ grep -n "tvshot" ~/.zshrc ~/.zprofile ~/.aliases 2>/dev/null; which scrcpy

Output

Exit code 1
~/.zshrc:167:unalias tvshot 2>/dev/null
~/.zshrc:168:tvshot() {
scrcpy not found

▸ Bash sed -n 160,185p ~/.zshrc

Input

$ sed -n 160,185p ~/.zshrc

Output

# bun
export BUN_INSTALL="<scratch>/bun"
export PATH="$BUN_INSTALL/bin:$PATH"

# Screenshot the Sony TV over wireless adb. Finds the TV by model, connecting
# via wireless-debugging discovery if needed, so port changes don't matter.
unalias tvshot 2>/dev/null
tvshot() {
  local s=$(adb devices -l | awk '/BRAVIA/ {print $1; exit}')
  if [ -z "$s" ]; then
    local addr=$(adb mdns services | awk '/_adb-tls-connect/ {print $3; exit}')
    [ -n "$addr" ] && adb connect "$addr" >/dev/null && s=$addr
  fi
  if [ -z "$s" ]; then
    echo "TV not reachable — turn on Settings › System › Developer options › Wireless debugging on the TV."
    return 1
  fi
  local f=~/Desktop/Screenshots/tv-$(date +%H%M%S).png
  adb -s "$s" exec-out screencap -p > "$f" && echo "Saved $f"
}

# Added by DevRelay installer
export PATH="$HOME/.devrelay/bin:$PATH"

Yes. Android TV has a built-in screen recorder (adb shell screenrecord), so you don't need to install anything. I'll add a tvrec command next to your tvshot, in the same style:

▸ Edit {"replace_all": false, "file_path": "~/.zshrc", "old_string": " adb -s \"$s\...

Input

{
  "replace_all": false,
  "file_path": "~/.zshrc",
  "old_string": "  adb -s \"$s\" exec-out screencap -p > \"$f\" && echo \"Saved $f\"\n}\n",
  "new_string": "  adb -s \"$s\" exec-out screencap -p > \"$f\" && echo \"Saved $f\"\n}\n\n# Record the Sony TV's screen: `tvrec`, press Enter to stop (Android caps a\n# recording at 3 minutes). Saves an .mp4 next to the screenshots.\nunalias tvrec 2>/dev/null\ntvrec() {\n  local s=$(adb devices -l | awk '/BRAVIA/ {print $1; exit}')\n  if [ -z \"$s\" ]; then\n    local addr=$(adb mdns services | awk '/_adb-tls-connect/ {print $3; exit}')\n    [ -n \"$addr\" ] && adb connect \"$addr\" >/dev/null && s=$addr\n  fi\n  if [ -z \"$s\" ]; then\n    echo \"TV not reachable — turn on Settings › System › Developer options › Wireless debugging on the TV.\"\n    return 1\n  fi\n  local remote=/sdcard/tvrec.mp4\n  local f=~/Desktop/Screenshots/tv-$(date +%H%M%S).mp4\n  adb -s \"$s\" shell \"screenrecord --bit-rate 20000000 $remote\" &\n  local pid=$!\n  echo \"Recording… press Enter to stop.\"\n  read -r\n  # SIGINT lets screenrecord finish the file properly.\n  adb -s \"$s\" shell pkill -INT screenrecord\n  wait $pid 2>/dev/null\n  sleep 1\n  adb -s \"$s\" pull $remote \"$f\" >/dev/null && adb -s \"$s\" shell rm $remote &&\n    echo \"Saved $f\"\n}\n"
}

Output

The file ~/.zshrc has been updated successfully.

▸ Bash S=<scratch>; ( sleep 6; echo ) | zsh -ic 'tvrec' 2>&1 | tail -3; f=$(ls -t ~/...

Input

$ S=<scratch>; ( sleep 6; echo ) | zsh -ic 'tvrec' 2>&1 | tail -3; f=$(ls -t ~/Desktop/Screenshots/tv-*.mp4 | head -1); ls -la "$f"; ffprobe -v error -show_entries format=duration:stream=width,height,codec_name -of compact "$f" 2>/dev/null || mdls -name kMDItemDurationSeconds -name kMDItemPixelWidth "$f"

Output

Recording… press Enter to stop.
/sdcard/tvrec.mp4: 1 file pulled, 0 skipped. 8.3 MB/s (127411 bytes in 0.015s)
Saved ~/Desktop/Screenshots/tv-130718.mp4
-rw-r--r--@ 1 souvikbiswas  staff  127411 Oct  4 13:07 ~/Desktop/Screenshots/tv-130718.mp4
kMDItemDurationSeconds = (null)
kMDItemPixelWidth      = (null)

A test recording saved. I'm checking that the file is a complete, playable video:

▸ Bash f=$(ls -t ~/Desktop/Screenshots/tv-*.mp4 | head -1); S=<scratch>; cat > $S/d....

Input

$ f=$(ls -t ~/Desktop/Screenshots/tv-*.mp4 | head -1); S=<scratch>; cat > $S/d.swift <<EOF
import AVFoundation
let a = AVURLAsset(url: URL(fileURLWithPath: "$f"))
let sem = DispatchSemaphore(value: 0)
Task { let d = try await a.load(.duration); let t = try await a.loadTracks(withMediaType: .video); let sz = try await t.first!.load(.naturalSize); print("duration \(d.seconds)s size \(sz)"); sem.signal() }
sem.wait()
EOF
swift $S/d.swift 2>&1 | tail -2

Output

[#NoUseUnstructuredThrowingTask]: <https://docs.swift.org/compiler/documentation/diagnostics/no-use-throwing-unstructured-task>
duration 0.0s size (1920.0, 1080.0)

The file is 1080p but only 0 s long. The TV screen didn't change during the test, and Android's recorder only saves frames when something on screen moves. I'll test again while moving through photos:

▸ Bash S=<scratch>; rm -f ~/Desktop/Screenshots/tv-130718.mp4; ( sleep 2; adb shell ...

Input

$ S=<scratch>; rm -f ~/Desktop/Screenshots/tv-130718.mp4; ( sleep 2; adb shell input keyevent DPAD_DOWN; sleep 2; adb shell input keyevent DPAD_RIGHT; sleep 2; adb shell input keyevent DPAD_LEFT; sleep 2; echo ) | zsh -ic 'tvrec' 2>&1 | tail -1; f=$(ls -t ~/Desktop/Screenshots/tv-*.mp4 | head -1); sed -i '' "s|URL(fileURLWithPath: \".*\")|URL(fileURLWithPath: \"$f\")|" $S/d.swift; swift $S/d.swift 2>&1 | tail -1

Output

Saved ~/Desktop/Screenshots/tv-130753.mp4
duration 6.8034888888888885s size (1920.0, 1080.0)

Yes. I added a tvrec command to your ~/.zshrc, right below tvshot, and it works.

tvrec        # starts recording; press Enter to stop

It finds the TV the same way tvshot does and saves ~/Desktop/Screenshots/tv-HHMMSS.mp4 at 1080p. It uses the recorder built into Android TV, so nothing extra is installed. Open a new terminal, or run source ~/.zshrc, to get it.

Tested: I recorded while pressing the remote buttons over adb and got a 6.8 s, 1920×1080 video. The test clip is at ~/Desktop/Screenshots/tv-130753.mp4 if you want to look at it or delete it.
Limits: a single recording stops at 3 minutes, and there's no sound. A screen that doesn't change records as almost nothing; my first test on a still photo came out 0 s long.
If you need sound or longer clips (for example the voice reading answers aloud in your demo): brew install scrcpy, then scrcpy --record demo.mp4. It mirrors the TV in a window on the Mac and records audio too, on Android 11 and later. I haven't installed it. Tell me if you want it.

You

can it record voice that I speak during the input and the output voice too?

Agent

The TV's own sound (Gemma's answers read aloud) can be recorded. Your voice is harder, because it goes into the remote's mic and only the TV's voice search hears it.

	`tvrec` (now)	scrcpy	Mac microphone
Video	✅	✅	—
TV sound / spoken answers	❌	✅ likely	✅ if the Mac is in the room
Your voice	❌	⚠️ probably not	✅

TV sound: scrcpy can grab everything the TV plays, which would include the spoken answers. I haven't tested it with this TV's text-to-speech yet. That's the first thing to check.
Your voice through scrcpy: it can record from the TV's microphone (--audio-source=mic). But while you hold the mic button, Google's voice typing is using that mic, and Android usually gives other recorders silence then. It's also unclear whether a Bluetooth remote's mic counts as the TV's mic at all. I expect this not to work.
Most reliable for a demo: scrcpy records the TV's picture and sound while the Mac's microphone records the room. I'd make a tvrec that runs both and merges them into one .mp4 with ffmpeg. Your voice comes from the Mac mic, and the answers come straight from the TV so they're clean.

The one thing in your voice that always ends up on the TV screen is the text: voice typing writes your question into the box.

Want me to install scrcpy and ffmpeg (brew install scrcpy ffmpeg), check that the answers are recorded, and make tvrec record both? You'd need to say a test question into the remote while I record.

You

yes, set it up

Agent

▸ Bash brew install scrcpy ffmpeg 2>&1 | tail -3; scrcpy --version | head -1; ffmpeg...

Input

$ brew install scrcpy ffmpeg 2>&1 | tail -3; scrcpy --version | head -1; ffmpeg -version | head -1; ffmpeg -f avfoundation -list_devices true -i "" 2>&1 | grep -A10 "audio devices"

Output

You can install adb from Homebrew Cask:
  brew install --cask android-platform-tools
scrcpy 4.1 <https://github.com/Genymobile/scrcpy>
ffmpeg version 9.0.2 Copyright (c) 2000-2026 the FFmpeg developers
[AVFoundation indev @ 0x7b21018140] AVFoundation audio devices:
[AVFoundation indev @ 0x7b21018140] [0] ZoomAudioDevice
[AVFoundation indev @ 0x7b21018140] [1] MacBook Pro Microphone
[in#0 @ 0x7b21018000] Error opening input: Input/output error
Error opening input file .
Error opening input files: Input/output error

▸ Bash S=<scratch>; SER=$(adb devices -l | awk '/BRAVIA/ {print $1; exit}'); adb exe...

Input

$ S=<scratch>; SER=$(adb devices -l | awk '/BRAVIA/ {print $1; exit}'); adb exec-out screencap -p > $S/a.png; sips -Z 640 $S/a.png >/dev/null; echo $SER

Output

<tv-adb-serial>

▸ Read <scratch>/a.png

Input

<scratch>/a.png

Output

[image]

▸ Bash S=<scratch>; adb shell input keyevent DPAD_UP; sleep 0.5; adb shell input key...

Input

$ S=<scratch>; adb shell input keyevent DPAD_UP; sleep 0.5; adb shell input keyevent DPAD_CENTER; sleep 2; adb shell input keyevent BACK; sleep 1; adb exec-out screencap -p > $S/a.png; sips -Z 640 $S/a.png >/dev/null

Output

(Bash completed with no output)

▸ Read <scratch>/a.png

Input

<scratch>/a.png

Output

[image]

▸ Bash S=<scratch>; adb shell input keyevent DPAD_LEFT; sleep 0.5; adb shell input k...

Input

$ S=<scratch>; adb shell input keyevent DPAD_LEFT; sleep 0.5; adb shell input keyevent DPAD_CENTER; sleep 2.5; adb shell input keyevent BACK; sleep 1; adb exec-out screencap -p > $S/a.png; sips -Z 640 $S/a.png >/dev/null

Output

(Bash completed with no output)

▸ Read <scratch>/a.png

Input

<scratch>/a.png

Output

[image]

▸ Bash S=<scratch>; adb shell input keyevent DPAD_DOWN; sleep 3; adb exec-out screen...

Input

$ S=<scratch>; adb shell input keyevent DPAD_DOWN; sleep 3; adb exec-out screencap -p > $S/a.png; sips -Z 640 $S/a.png >/dev/null; adb shell dumpsys input_method | grep mInputShown

Output

mInputShown=true

▸ Read <scratch>/a.png

Input

<scratch>/a.png

Output

[image]

Ask Gemma is open on the TV. Next I start a scrcpy recording, have the TV ask "What is this?", and check whether the spoken answer was captured:

▸ Bash S=<scratch>; SER=$(adb devices -l | awk '/BRAVIA/ {print $1; exit}'); rm -f $...

Input

$ S=<scratch>; SER=$(adb devices -l | awk '/BRAVIA/ {print $1; exit}'); rm -f $S/t1.mkv; scrcpy -s "$SER" --no-window --no-control --audio-source=playback --audio-dup --record=$S/t1.mkv --time-limit=22 > $S/scrcpy.log 2>&1 &
sleep 3; adb shell input keyevent BACK; sleep 1; adb shell input keyevent DPAD_DOWN; sleep 0.7; adb shell input keyevent DPAD_CENTER; wait; tail -5 $S/scrcpy.log; ffmpeg -i $S/t1.mkv -af volumedetect -vn -f null - 2>&1 | grep -E "Stream|mean_volume|max_volume"; ffmpeg -i $S/t1.mkv -af silencedetect=n=-45dB:d=1 -vn -f null - 2>&1 | grep silence_ | head

Output

INFO: ADB device found:
INFO:     --> (tcpip)  <tv-adb-serial>            device  BRAVIA_4K_AE2
INFO: Recording started to matroska file: <scratch>/t1.mkv
INFO: Time limit reached
INFO: Recording complete to matroska file: <scratch>/t1.mkv
  Stream #0:0: Video: h264 (High), yuv420p(tv, bt709, progressive), 1920x1080, 1k tbr, 1k tbn
  Stream #0:1: Audio: opus, 48000 Hz, stereo, fltp, start 0.089000
Stream mapping:
  Stream #0:1 -> #0:0 (opus (native) -> pcm_s16le (native))
  Stream #0:0: Audio: pcm_s16le, 48000 Hz, stereo, s16, 1536 kb/s
[Parsed_volumedetect_0 @ 0x75c7024a80] mean_volume: -22.3 dB
[Parsed_volumedetect_0 @ 0x75c7024a80] max_volume: -4.0 dB
[Parsed_silencedetect_0 @ 0x7c61024a80] silence_start: 0.0595
[Parsed_silencedetect_0 @ 0x7c61024a80] silence_end: 8.995917 | silence_duration: 8.936417

Sound was captured: silence for the first 9 s, then about 13 s of audio. I'll check a frame to confirm it's the answer being read:

▸ Bash S=<scratch>; ffmpeg -y -v error -ss 12 -i $S/t1.mkv -frames:v 1 -vf scale=640...

Input

$ S=<scratch>; ffmpeg -y -v error -ss 12 -i $S/t1.mkv -frames:v 1 -vf scale=640:-1 $S/f.png

Output

(Bash completed with no output)

▸ Read <scratch>/f.png

Input

<scratch>/f.png

Output

File does not exist. Note: your current working directory is ~/MobileDev/Flutter/tv_gallery_gemma.

▸ Bash S=<scratch>; ffmpeg -y -v error -i $S/t1.mkv -vf "select=gte(t\,12),scale=640...

Input

$ S=<scratch>; ffmpeg -y -v error -i $S/t1.mkv -vf "select=gte(t\,12),scale=640:-1" -frames:v 1 $S/f.png; ls $S/f.png; ffprobe -v error -show_entries format=duration -of csv=p=0 $S/t1.mkv

Output

ls: <scratch>/f.png: No such file or directory
21.748000

▸ Read <scratch>/f.png

Input

<scratch>/f.png

Output

File does not exist. Note: your current working directory is ~/MobileDev/Flutter/tv_gallery_gemma.

▸ Bash S=<scratch>; ffprobe -v error -select_streams v -show_entries packet=pts_time...

Input

$ S=<scratch>; ffprobe -v error -select_streams v -show_entries packet=pts_time -of csv=p=0 $S/t1.mkv | tail -3; ffmpeg -y -v error -sseof -1 -i $S/t1.mkv -update 1 -vf scale=640:-1 $S/f.png; ls $S/f.png

Output

Exit code 1
8.674000
8.774000
8.874000
ls: <scratch>/f.png: No such file or directory

▸ Read <scratch>/f.png

Input

<scratch>/f.png

Output

File does not exist. Note: your current working directory is ~/MobileDev/Flutter/tv_gallery_gemma.

▸ Bash S=<scratch>; ffmpeg -y -v error -i $S/t1.mkv -an -update 1 -vf scale=640:-1 $...

Input

$ S=<scratch>; ffmpeg -y -v error -i $S/t1.mkv -an -update 1 -vf scale=640:-1 $S/f.png && ls $S/f.png

Output

<scratch>/f.png

▸ Read <scratch>/f.png

Input

<scratch>/f.png

Output

[image]

▸ Bash python3 - <<'EOF' import os,re p=os.path.expanduser('~/.zshrc') s=open(p).rea...

Input

$ python3 - <<'EOF'
import os,re
p=os.path.expanduser('~/.zshrc')
s=open(p).read()
a=s.index("# Record the Sony TV's screen")
b=s.index("}\n",s.index("tvrec() {"))+2
new='''# Record the Sony TV for a demo: `tvrec`, press Enter to stop. Captures the
# TV's picture and sound (e.g. answers read aloud) with scrcpy, plus your
# voice through the Mac's microphone, mixed into one .mp4 next to the
# screenshots. `tvrec --no-mic` skips the microphone.
unalias tvrec 2>/dev/null
tvrec() {
  local s=$(adb devices -l | awk '/BRAVIA/ {print $1; exit}')
  if [ -z "$s" ]; then
    local addr=$(adb mdns services | awk '/_adb-tls-connect/ {print $3; exit}')
    [ -n "$addr" ] && adb connect "$addr" >/dev/null && s=$addr
  fi
  if [ -z "$s" ]; then
    echo "TV not reachable — turn on Settings › System › Developer options › Wireless debugging on the TV."
    return 1
  fi
  local mic=1; [ "$1" = "--no-mic" ] && mic=0
  local tmp=$(mktemp -d)
  local f=~/Desktop/Screenshots/tv-$(date +%H%M%S).mp4
  # --audio-dup keeps the sound playing on the TV while it's recorded.
  scrcpy -s "$s" --no-window --no-control --audio-source=playback --audio-dup \\
    --record="$tmp/tv.mkv" >"$tmp/scrcpy.log" 2>&1 &
  local tv=$!
  local m
  if [ $mic = 1 ]; then
    ffmpeg -nostdin -loglevel error -f avfoundation -i ":MacBook Pro Microphone" \\
      -c:a aac -b:a 160k "$tmp/mic.m4a" &
    m=$!
  fi
  echo "Recording… press Enter to stop."
  read -r
  # SIGINT lets both finish their files properly.
  kill -INT $tv ${m:-} 2>/dev/null
  wait $tv ${m:-} 2>/dev/null
  if [ ! -s "$tmp/tv.mkv" ]; then
    echo "Recording failed:"; cat "$tmp/scrcpy.log"; return 1
  fi
  echo "Saving…"
  # scrcpy only sends frames when the screen changes; hold the last frame so
  # the video runs as long as the sound.
  local v="tpad=stop=-1:stop_mode=clone,fps=30,format=yuv420p"
  if [ $mic = 1 ] && [ -s "$tmp/mic.m4a" ]; then
    ffmpeg -loglevel error -i "$tmp/tv.mkv" -i "$tmp/mic.m4a" -filter_complex \\
      "[0:v]$v[v];[0:a][1:a]amix=inputs=2:duration=longest:normalize=0[a]" \\
      -map "[v]" -map "[a]" -shortest -c:v libx264 -crf 18 -preset veryfast \\
      -c:a aac -b:a 192k -movflags +faststart "$f"
  else
    ffmpeg -loglevel error -i "$tmp/tv.mkv" -vf "$v" -shortest -c:v libx264 \\
      -crf 18 -preset veryfast -c:a aac -b:a 192k -movflags +faststart "$f"
  fi && rm -rf "$tmp" && echo "Saved $f"
}
'''
s=s[:a]+new+s[b:]
open(p,'w').write(s)
EOF
zsh -n ~/.zshrc && echo syntax ok; grep -n "^tvrec\|^tvshot" ~/.zshrc

Output

syntax ok
168:tvshot() {
187:tvrec() {

Syntax checks out. Before handing it over, I'll test the merge step on the TV recording I already have, plus a stand-in mic track:

▸ Bash S=<scratch>; cd $S; ffmpeg -y -loglevel error -f lavfi -i "sine=f=440:d=20" -...

Input

$ S=<scratch>; cd $S; ffmpeg -y -loglevel error -f lavfi -i "sine=f=440:d=20" -c:a aac mic.m4a; v="tpad=stop=-1:stop_mode=clone,fps=30,format=yuv420p"; ffmpeg -y -loglevel error -i t1.mkv -i mic.m4a -filter_complex "[0:v]$v[v];[0:a][1:a]amix=inputs=2:duration=longest:normalize=0[a]" -map "[v]" -map "[a]" -shortest -c:v libx264 -crf 18 -preset veryfast -c:a aac -b:a 192k -movflags +faststart out.mp4 && ffprobe -v error -show_entries stream=codec_type,duration -of compact out.mp4; ffmpeg -y -loglevel error -i t1.mkv -vf "$v" -shortest -c:v libx264 -crf 18 -preset veryfast -c:a aac -movflags +faststart out2.mp4 && ffprobe -v error -show_entries stream=codec_type,duration -of compact out2.mp4

Output

Exit code 1
(eval):1: bad math expression: ':' without '?'

That caught a real bug: zsh reads $v[v] as an array lookup. I'm fixing it in tvrec and rerunning:

▸ Bash sed -i '' 's/"\[0:v\]\$v\[v\];/"[0:v]${v}[v];/' ~/.zshrc && grep -n '\[0:v\]'...

Input

$ sed -i '' 's/"\[0:v\]\$v\[v\];/"[0:v]${v}[v];/' ~/.zshrc && grep -n '\[0:v\]' ~/.zshrc; S=<scratch>; cd $S; v="tpad=stop=-1:stop_mode=clone,fps=30,format=yuv420p"; ffmpeg -y -loglevel error -i t1.mkv -i mic.m4a -filter_complex "[0:v]${v}[v];[0:a][1:a]amix=inputs=2:duration=longest:normalize=0[a]" -map "[v]" -map "[a]" -shortest -c:v libx264 -crf 18 -preset veryfast -c:a aac -b:a 192k -movflags +faststart out.mp4 && ffprobe -v error -show_entries stream=codec_type,duration -of compact out.mp4; ffmpeg -y -loglevel error -i t1.mkv -vf "$v" -shortest -c:v libx264 -crf 18 -preset veryfast -c:a aac -movflags +faststart out2.mp4 && ffprobe -v error -show_entries stream=codec_type,duration -of compact out2.mp4

Output

224:      "[0:v]${v}[v];[0:a][1:a]amix=inputs=2:duration=longest:normalize=0[a]" \
stream|codec_type=video|duration=21.766667
stream|codec_type=audio|duration=21.693333
stream|codec_type=video|duration=22.900000
stream|codec_type=audio|duration=21.693333
Shell cwd was reset to ~/MobileDev/Flutter/tv_gallery_gemma

tvrec is set up. Open a new terminal (or run source ~/.zshrc) to pick it up.

tvrec            # TV picture + TV sound + your voice via the Mac mic → press Enter to stop
tvrec --no-mic   # TV picture and sound only

It saves ~/Desktop/Screenshots/tv-HHMMSS.mp4. While it records, the TV keeps playing sound normally, and there's no 3-minute limit any more.

What I tested:
- TV sound: recording a real question on the TV captured Gemma's spoken answer about the Shanghai photo, clearly, starting at 9 s.
- Merge step: I ran it on that recording plus a fake mic track and got a 21.7 s mp4 with the picture and sound lined up. This test caught a zsh quoting bug in the merge command, which I fixed.
- Not tested: a full run with your real voice through the Mac mic, since you're testing that yourself.

On your first run:
- Mic permission: macOS will ask whether your terminal app can use the microphone. Allow it, or your voice will be silent.
- Echo: the Mac mic also hears the TV's speakers, so the spoken answers may echo slightly over the clean copy. If that bothers you, I can turn the mic down while answers are playing, or switch to an external mic. Your mic list shows only the MacBook's built-in mic and a Zoom virtual device right now.

▸ Bash S=<scratch>; grep -n -B6 -A8 "dead thread" $S/run.log | tail -20

Input

$ S=<scratch>; grep -n -B6 -A8 "dead thread" $S/run.log | tail -20

Output

1587-D/MediaCodec( 7444): flushMediametrics
1588-D/MediaCodec( 7444): notifyMediaStatistics hash (0)
1589-D/MediaCodec( 7444): flushMediametrics
1590-W/MediaCodec( 7444): no metrics handle found
1591-I/hw-BpHwBinder( 7444): onLastStrongRef automatically unlinking death recipients
1592-I/ExoPlayerImpl( 7444): Release 5c4814 [AndroidXMedia3/1.4.1] [BRAVIA_AE2, BRAVIA 4K AE2, Sony, 34] [media3.common, media3.exoplayer, media3.decoder, media3.datasource, media3.extractor]
1593:W/MessageQueue( 7444): Handler (android.os.Handler) {3ef5f55} sending message to a Handler on a dead thread
1594:W/MessageQueue( 7444): java.lang.IllegalStateException: Handler (android.os.Handler) {3ef5f55} sending message to a Handler on a dead thread
1595-W/MessageQueue( 7444):     at android.os.MessageQueue.enqueueMessage(MessageQueue.java:560)
1596-W/MessageQueue( 7444):     at android.os.Handler.enqueueMessage(Handler.java:786)
1597-W/MessageQueue( 7444):     at android.os.Handler.sendMessageAtTime(Handler.java:735)
1598-W/MessageQueue( 7444):     at android.os.Handler.sendMessageDelayed(Handler.java:705)
1599-W/MessageQueue( 7444):     at android.os.Handler.sendMessage(Handler.java:643)
1600-W/MessageQueue( 7444):     at android.os.Message.sendToTarget(Message.java:468)
1601-W/MessageQueue( 7444):     at androidx.media3.common.util.SystemHandlerWrapper$SystemMessage.sendToTarget(SystemHandlerWrapper.java:160)
1602-W/MessageQueue( 7444):     at androidx.media3.exoplayer.ExoPlayerImplInternal.stop(ExoPlayerImplInternal.java:3
…[3 more chars]

The new log alert is harmless. It's an Android warning from the video player as it shuts down: after a video was released, its stop() call reached a background thread that had already ended. The app didn't crash, and it isn't related to the Gemma changes. The video player code hasn't changed.

You

got this:

<pasted_content id="396a">
~ » tvrec me@mac
[2] 86157
[4] 86158
Recording… press Enter to stop.

[2] 86157 done scrcpy -s "$s" --no-window --no-control --audio-source=playback --audio-dup
[4] + 86158 exit 255 ffmpeg -nostdin -loglevel error -f avfoundation -i ":MacBook Pro Microphone"
Recording failed:
/opt/homebrew/Cellar/scrcpy/4.1_1/share/scrcpy/scrcpy-server: 1 file pushed, 0 skipped. 81.4 MB/s (733706 bytes in 0.009s)
[server] INFO: Device: [Sony] Sony BRAVIA 4K AE2 (Android 14)
scrcpy 4.1 https://github.com/Genymobile/scrcpy
INFO: ADB device found:
INFO: --> (tcpip) <tv-adb-serial> device BRAVIA_4K_AE2
</pasted_content id="396a">

Agent

Two separate failures here: the microphone recorder exited straight away (code 255), and scrcpy stopped before it ever began writing the video. I'll reproduce each on its own:

▸ Bash S=<scratch>; cd $S; timeout 4 ffmpeg -y -nostdin -f avfoundation -i ":MacBook...

Input

$ S=<scratch>; cd $S; timeout 4 ffmpeg -y -nostdin -f avfoundation -i ":MacBook Pro Microphone" -t 2 m.m4a 2>&1 | tail -4; echo "exit $?"; timeout 4 ffmpeg -y -nostdin -f avfoundation -i ":1" -t 2 m.m4a 2>&1 | tail -3

Output

encoder         : Lavc63.1.102 aac
size=       0KiB time=00:00:00.44 bitrate=   0.8kbits/s speed=0.895x elapsed=0:00:00.50    
size=       0KiB time=00:00:00.96 bitrate=   0.4kbits/s speed=0.954x elapsed=0:00:01.00    
size=       0KiB time=00:00:01.46 bitrate=   0.2kbits/s speed=0.967x elapsed=0:00:01.51    
[out#0/ipod @ 0x7c6511c840] video:0KiB audio:16KiB subtitle:0KiB other streams:0KiB global headers:0KiB muxing overhead: 9.286878%
size=      17KiB time=00:00:02.00 bitrate=  69.8kbits/s speed=0.987x elapsed=0:00:02.02    
[aac @ 0x7c648b8a80] Qavg: 128.304
exit 0
size=       0KiB time=00:00:00.44 bitrate=   0.8kbits/s speed=0.89x elapsed=0:00:00.50    
size=       0KiB time=00:00:00.96 bitrate=   0.4kbits/s speed=0.952x elapsed=0:00:01.00    
size=       0KiB time=00:00:01.46 bitrate=   0.2kbits/s speed=0.969x elapsed=0:00:01.50    
size=       0KiB time=00:00:01.94 bitrate=   0.2kbits/s speed=0.964x elapsed=0:00:02.01    
[out#0/ipod @ 0x77690ac840] video:0KiB audio:15KiB subtitle:0KiB other streams:0KiB global headers:0KiB muxing overhead: 9.242797%
size=      17KiB time=00:00:02.00 bitrate=  69.3kbits/s speed=0.987x elapsed=0:00:02.02    
[aac @ 0x7768944a80] Qavg: 107.855
Shell cwd was reset to ~/MobileDev/Flutter/tv_gallery_gemma

▸ Bash ls -lat $(zsh -ic 'echo $TMPDIR' 2>/dev/null)/ | grep "tmp\." | head -3; d=$(...

Input

$ ls -lat $(zsh -ic 'echo $TMPDIR' 2>/dev/null)/ | grep "tmp\." | head -3; d=$(ls -dt $(zsh -ic 'echo $TMPDIR' 2>/dev/null)/tmp.* | head -1); ls -la $d; cat $d/scrcpy.log

Output

drwx------@   4 souvikbiswas  staff      128 Oct  4 13:19 tmp.Rn3ryW7fvX
total 816
drwx------@   4 souvikbiswas  staff     128 Oct  4 13:19 .
drwx------@ 377 souvikbiswas  staff   12064 Oct  4 13:20 ..
-rw-r--r--@   1 souvikbiswas  staff  352810 Oct  4 13:20 mic.m4a
-rw-r--r--@   1 souvikbiswas  staff     376 Oct  4 13:20 scrcpy.log
/opt/homebrew/Cellar/scrcpy/4.1_1/share/scrcpy/scrcpy-server: 1 file pushed, 0 skipped. 81.4 MB/s (733706 bytes in 0.009s)
[server] INFO: Device: [Sony] Sony BRAVIA 4K AE2 (Android 14)
scrcpy 4.1 <https://github.com/Genymobile/scrcpy>
INFO: ADB device found:
INFO:     --> (tcpip)  <tv-adb-serial>            device  BRAVIA_4K_AE2

The mic part worked: your run saved about 18 s of mic audio. The problem is scrcpy. It connected to the TV and then never started recording. Reproducing that in an interactive shell like yours:

▸ Bash ( sleep 10; echo ) | zsh -ic 'tvrec --no-mic' 2>&1 | tail -8

Input

$ ( sleep 10; echo ) | zsh -ic 'tvrec --no-mic' 2>&1 | tail -8

Output

Command did not complete within its 90s timeout and was moved to the background (ID: bt2a7o097). Output is being written to: <tmp> You will be notified when it completes. To check interim output, use Read on that file path.

▸ Bash pgrep -fl "scrcpy|ffmpeg" ; d=$(ls -dt $(zsh -ic 'echo $TMPDIR' 2>/dev/null)/...

Input

$ pgrep -fl "scrcpy|ffmpeg" ; d=$(ls -dt $(zsh -ic 'echo $TMPDIR' 2>/dev/null)/tmp.* | head -1); ls -la $d; cat $d/scrcpy.log; cat <tmp>

Output

87352 scrcpy -s <tv-adb-serial> --no-window --no-control --audio-source=playback --audio-dup --record=<tmp>
87357 adb -s <tv-adb-serial> shell CLASSPATH=/data/local/tmp/scrcpy-server.jar app_process / com.genymobile.scrcpy.Server 4.1 scid=5234291b log_level=info audio_source=playback audio_dup=true control=false
total 8712
drwx------@   4 souvikbiswas  staff      128 Oct  4 13:21 .
drwx------@ 378 souvikbiswas  staff    12096 Oct  4 13:21 ..
-rw-r--r--@   1 souvikbiswas  staff      185 Oct  4 13:21 scrcpy.log
-rw-r--r--@   1 souvikbiswas  staff  4194304 Oct  4 13:21 tv.mkv
/opt/homebrew/Cellar/scrcpy/4.1_1/share/scrcpy/scrcpy-server: 1 file pushed, 0 skipped. 93.6 MB/s (733706 bytes in 0.007s)
[server] INFO: Device: [Sony] Sony BRAVIA 4K AE2 (Android 14)

▸ Bash kill -TERM 87352; sleep 3; pgrep -fl scrcpy; cat <tmp> | tail -5; d=$(ls -dt ...

Input

$ kill -TERM 87352; sleep 3; pgrep -fl scrcpy; cat <tmp> | tail -5; d=$(ls -dt $(zsh -ic 'echo $TMPDIR' 2>/dev/null)/tmp.* | head -1); cat $d/scrcpy.log 2>/dev/null | tail -3; ls ~/Desktop/Screenshots/*.mp4 | tail -2

Output

scrcpy 4.1 <https://github.com/Genymobile/scrcpy>
INFO: ADB device found:
INFO:     --> (tcpip)  <tv-adb-serial>            device  BRAVIA_4K_AE2
~/Desktop/Screenshots/tv-131849.mp4
~/Desktop/Screenshots/tv-132112.mp4

▸ Bash python3 - <<'EOF' import os p=os.path.expanduser('~/.zshrc') s=open(p).read()...

Input

$ python3 - <<'EOF'
import os
p=os.path.expanduser('~/.zshrc')
s=open(p).read()
def r(a,b):
    global s
    assert a in s, a
    s=s.replace(a,b)
r('''# Record the Sony TV for a demo: `tvrec`, press Enter to stop. Captures the
# TV's picture and sound (e.g. answers read aloud) with scrcpy, plus your
# voice through the Mac's microphone, mixed into one .mp4 next to the
# screenshots. `tvrec --no-mic` skips the microphone.''','''# Record the Sony TV for a demo: `tvrec`, press Enter to stop. Captures the
# TV's picture and sound (e.g. answers read aloud) with scrcpy, plus your
# voice through the Mac's microphone, mixed into one .mp4 next to the
# screenshots. The TV's speakers go quiet while recording so the mic doesn't
# pick them up as an echo; the sound is still recorded directly.
# `tvrec --no-mic` skips the microphone and keeps the TV's sound on.''')
r('''  # --audio-dup keeps the sound playing on the TV while it's recorded.
  scrcpy -s "$s" --no-window --no-control --audio-source=playback --audio-dup \\
    --record="$tmp/tv.mkv" >"$tmp/scrcpy.log" 2>&1 &
  local tv=$!''','''  # Capturing the TV's sound silences its speakers; --audio-dup keeps them
  # playing (only wanted without the mic, which would hear them).
  local dup=(); [ $mic = 0 ] && dup=(--audio-dup)
  scrcpy -s "$s" --no-window --no-control --audio-source=playback $dup \\
    --record="$tmp/tv.mkv" >"$tmp/scrcpy.log" 2>&1 &
  local tv=$!
  # Wait until scrcpy is actually writing before saying we're recording.
  local i=0
  while [ ! -s "$tmp/tv.mkv" ] && kill -0 $tv 2>/dev/null && [ $i -lt 100 ]; do
    sleep 0.1; i=$((i+1))
  done
  if [ ! -s "$tmp/tv.mkv" ]; then
    kill -TERM $tv 2>/dev/null
    echo "Couldn't start recording the TV:"; cat "$tmp/scrcpy.log"; return 1
  fi''')
r('''  echo "Recording… press Enter to stop."
  read -r
  # SIGINT lets both finish their files properly.
  kill -INT $tv ${m:-} 2>/dev/null''','''  echo "Recording… press Enter to stop."
  read -r
  # SIGTERM lets both finish their files properly (scrcpy can ignore SIGINT
  # when run as a background job).
  kill -TERM $tv ${m:-} 2>/dev/null''')
r('''  if [ ! -s "$tmp/tv.mkv" ]; then
    echo "Recording failed:"; cat "$tmp/scrcpy.log"; return 1
  fi
  echo "Saving…"''','''  echo "Saving…"''')
open(p,'w').write(s)
EOF
zsh -n ~/.zshrc && echo ok

Output

ok

Testing the full path (TV plus mic) the same way your shell runs it:

▸ Bash ( sleep 8; echo ) | zsh -ic 'tvrec' 2>&1 | grep -v "^\[" | tail -4; f=$(ls -t...

Input

$ ( sleep 8; echo ) | zsh -ic 'tvrec' 2>&1 | grep -v "^\[" | tail -4; f=$(ls -t ~/Desktop/Screenshots/tv-*.mp4 | head -1); ffprobe -v error -show_entries stream=codec_type,duration -of compact "$f"

Output

Couldn't start recording the TV:
/opt/homebrew/Cellar/scrcpy/4.1_1/share/scrcpy/scrcpy-server: 1 file pushed, 0 skipped. 92.2 MB/s (733706 bytes in 0.008s)
stream|codec_type=video|duration=108.933333
stream|codec_type=audio|duration=108.953000

That reproduces your failure. I suspect scrcpy only creates the file once the TV screen changes, and the screen was still both times. To check, I'll start a recording, wait, then press a key:

▸ Bash S=<scratch>; SER=$(adb devices -l | awk '/BRAVIA/ {print $1; exit}'); rm -f $...

Input

$ S=<scratch>; SER=$(adb devices -l | awk '/BRAVIA/ {print $1; exit}'); rm -f $S/t2.mkv; scrcpy -s "$SER" --no-window --no-control --audio-source=playback --record=$S/t2.mkv > $S/s2.log 2>&1 & P=$!; for t in 2 4 6; do sleep 2; echo "t=$t size=$(stat -f %z $S/t2.mkv 2>/dev/null || echo none)"; done; adb shell input keyevent DPAD_UP; for t in 7 8 10; do sleep 1; echo "after key t=$t size=$(stat -f %z $S/t2.mkv 2>/dev/null || echo none)"; done; kill -TERM $P; wait $P; ffprobe -v error -show_entries stream=codec_type -of csv=p=0 $S/t2.mkv | tr '\n' ' '

Output

t=2 size=0
t=4 size=0
t=6 size=0
after key t=7 size=262144
after key t=8 size=262144
after key t=10 size=262144
video audio

▸ Bash python3 - <<'EOF' import os p=os.path.expanduser('~/.zshrc') s=open(p).read()...

Input

$ python3 - <<'EOF'
import os
p=os.path.expanduser('~/.zshrc')
s=open(p).read()
old='''  # Wait until scrcpy is actually writing before saying we're recording.
  local i=0
  while [ ! -s "$tmp/tv.mkv" ] && kill -0 $tv 2>/dev/null && [ $i -lt 100 ]; do
    sleep 0.1; i=$((i+1))
  done'''
assert old in s
s=s.replace(old,'''  # scrcpy only starts writing once something on the TV screen changes; start
  # the mic then too, so the two line up.
  echo "Press any button on the TV remote to start…"
  local i=0
  while [ ! -s "$tmp/tv.mkv" ] && kill -0 $tv 2>/dev/null && [ $i -lt 600 ]; do
    sleep 0.1; i=$((i+1))
  done''')
open(p,'w').write(s)
EOF
zsh -n ~/.zshrc && echo ok; S=<scratch>; ( sleep 4; adb shell input keyevent DPAD_UP; sleep 6; echo ) | zsh -ic 'tvrec' 2>&1 | grep -v "^\[" | tail -4; f=$(ls -t ~/Desktop/Screenshots/tv-*.mp4 | head -1); echo $f; ffprobe -v error -show_entries stream=codec_type,duration -of compact "$f"

Output

ok
Press any button on the TV remote to start…
Recording… press Enter to stop.
Saving…
Saved ~/Desktop/Screenshots/tv-132426.mp4
~/Desktop/Screenshots/tv-132426.mp4
stream|codec_type=video|duration=7.633333
stream|codec_type=audio|duration=7.665000

▸ Bash rm -f ~/Desktop/Screenshots/tv-132112.mp4 ~/Desktop/Screenshots/tv-132426.mp4...

Input

$ rm -f ~/Desktop/Screenshots/tv-132112.mp4 ~/Desktop/Screenshots/tv-132426.mp4; rm -rf $(zsh -ic 'echo $TMPDIR' 2>/dev/null)/tmp.Rn3ryW7fvX $(zsh -ic 'echo $TMPDIR' 2>/dev/null)/tmp.9ovndpgV5O; ls ~/Desktop/Screenshots/*.mp4

Output

~/Desktop/Screenshots/Voice Mode AI Agent.mp4
~/Desktop/Screenshots/tv-130753.mp4
~/Desktop/Screenshots/tv-131849.mp4

tvrec works now. Open a new terminal (or run source ~/.zshrc), then:

~ » tvrec
Press any button on the TV remote to start…
Recording… press Enter to stop.
Saving…
Saved ~/Desktop/Screenshots/tv-HHMMSS.mp4

Why your run failed: scrcpy doesn't start writing until something on the TV screen changes. Your screen was still, so it never started, and when you pressed Enter it quit with nothing saved. tvrec now waits for that first change, and pressing any button on the remote kicks it off. It also starts the mic at that moment, so your voice and the TV stay in sync. Separately, it now stops scrcpy with a signal the background process can't ignore; in my test it had ignored Ctrl-C and run on.

Echo: during tvrec the TV's speakers go quiet, so the Mac mic hears only you. Gemma's spoken answer still goes straight into the video, cleanly. You won't hear the answer in the room while recording, but it's in the file. tvrec --no-mic leaves the TV's speakers on.

Tested: I ran it the way your terminal does, with a simulated button press, and got a 7.6 s mp4 with the picture and the mixed audio lined up. I haven't been able to confirm by ear that the TV actually goes quiet, so check that on your first take.

I deleted my test recordings and the leftover temp files from your failed run. tv-131849.mp4 isn't one of mine as far as I can tell, so I left it. tv-130753.mp4 is my first silent test clip, so delete it if you don't want it.

You

there's a weird bug seems like, in the latest one there's a sound from the tv recorded even before the actual tv sound started, and it's overlapped with the actual tv sound

also no need to do fancy stuff for cancelling tv sound separwately, I have turned off tv sound while recording

Agent

▸ Bash ls -lt ~/Desktop/Screenshots/*.mp4 | head -3; f=$(ls -t ~/Desktop/Screenshots...

Input

$ ls -lt ~/Desktop/Screenshots/*.mp4 | head -3; f=$(ls -t ~/Desktop/Screenshots/tv-*.mp4 | head -1); ffprobe -v error -show_entries stream=codec_type,start_time,duration -of compact "$f"; ls -dt $(zsh -ic 'echo $TMPDIR' 2>/dev/null)/tmp.* | head -2

Output

-rw-r--r--@ 1 souvikbiswas  staff   1900247 Oct  4 13:25 ~/Desktop/Screenshots/tv-132510.mp4
-rw-r--r--@ 1 souvikbiswas  staff    530955 Oct  4 13:18 ~/Desktop/Screenshots/tv-131849.mp4
-rw-r--r--@ 1 souvikbiswas  staff    531157 Oct  4 13:08 ~/Desktop/Screenshots/tv-130753.mp4
stream|codec_type=video|start_time=0.000000|duration=25.266667
stream|codec_type=audio|start_time=0.056667|duration=25.234333
<tmp>

▸ Bash f=~/Desktop/Screenshots/tv-132510.mp4; ffmpeg -v error -i "$f" -af "astats=me...

Input

$ f=~/Desktop/Screenshots/tv-132510.mp4; ffmpeg -v error -i "$f" -af "astats=metadata=1:reset=25,ametadata=print:key=lavfi.astats.Overall.RMS_level" -vn -f null - 2>&1 | awk '/pts_time/ {split($0,a,"pts_time:"); t=a[2]} /RMS_level/ {split($0,b,"="); printf "%5.1fs %6.1f dB\n", t, b[2]}' | awk 'NR%2==1' | head -60

Output

(Bash completed with no output)

▸ Bash f=~/Desktop/Screenshots/tv-132510.mp4; ffmpeg -v error -i "$f" -vn -af "asetn...

Input

$ f=~/Desktop/Screenshots/tv-132510.mp4; ffmpeg -v error -i "$f" -vn -af "asetnsamples=24000,astats=metadata=1:reset=1,ametadata=print:key=lavfi.astats.Overall.RMS_level:file=-" -f null - 2>/dev/null | paste - - | awk '{split($2,a,":"); split($NF,b,"="); printf "%s %s\n", a[2], b[2]}' | head -60

Output

2720 -60.679237
25352 -59.313539
48968 -60.036571
73496 -44.973808
97016 -42.570723
121640 -46.826949
145160 -54.462430
169784 -59.963995
193256 -60.107647
216968 -60.166600
241400 -60.252781
264968 -60.595553
289544 -57.373680
313064 -42.247397
337880 -40.367841
361256 -42.251075
384968 -42.542862
409376 -39.869026
433016 -43.901877
457496 -58.547904
481016 -40.801929
505640 -39.061137
529208 -42.182243
553832 -48.722109
577352 -45.456716
600968 -18.391808
625448 -16.381484
649016 -18.839625
673592 -18.792132
697112 -17.496528
721736 -18.207228
745256 -29.211740
768920 -24.429086
793352 -16.417064
816920 -16.961133
841544 -19.864309
865064 -27.600557
889688 -22.012297
913208 -94.214709
937832 -20.262983
961304 -18.922062
985016 -19.438950
1009448 -25.601466
1032944 -20.620395
1057592 -20.690211
1081160 -21.930093
1105784 -35.974297
1129256 -94.770664
1152872 -inf
1177352 -inf
1200872 -inf

I'll line up when the answer appears on screen with when the loud audio starts:

▸ Bash S=<scratch>; f=~/Desktop/Screenshots/tv-132510.mp4; mkdir -p $S/fr; rm -f $S/...

Input

$ S=<scratch>; f=~/Desktop/Screenshots/tv-132510.mp4; mkdir -p $S/fr; rm -f $S/fr/*; ffmpeg -v error -i "$f" -vf "fps=1,scale=480:-1,tile=5x5" -frames:v 1 $S/fr/tile.png; ls $S/fr

Output

(eval):1: no matches found: <scratch>/fr/*
tile.png

▸ Read <scratch>/fr/tile.png

Input

<scratch>/fr/tile.png

Output

[image]

▸ Bash S=<scratch>; ffprobe -v error -show_entries stream=codec_type,start_time,dura...

Input

$ S=<scratch>; ffprobe -v error -show_entries stream=codec_type,start_time,duration -of compact $S/t2.mkv; ffprobe -v error -select_streams v -show_entries packet=pts_time -of csv=p=0 $S/t2.mkv | head -2; ffprobe -v error -select_streams a -show_entries packet=pts_time -of csv=p=0 $S/t2.mkv | head -2

Output

stream|codec_type=video|start_time=0.000000|duration=N/A
stream|codec_type=audio|start_time=0.091000|duration=N/A
0.000000
0.100000
0.091000
0.092000

▸ Bash S=<scratch>; ffprobe -v error -select_streams a -show_entries packet=pts_time...

Input

$ S=<scratch>; ffprobe -v error -select_streams a -show_entries packet=pts_time -of csv=p=0 $S/t2.mkv | tail -1; ffprobe -v error -select_streams v -show_entries packet=pts_time -of csv=p=0 $S/t2.mkv | tail -1

Output

8.181000
6.523000

▸ Bash python3 - <<'EOF' import os p=os.path.expanduser('~/.zshrc') s=open(p).read()...

Input

$ python3 - <<'EOF'
import os
p=os.path.expanduser('~/.zshrc')
s=open(p).read()
def r(a,b):
    global s
    assert a in s, a
    s=s.replace(a,b)
r('''# screenshots. The TV's speakers go quiet while recording so the mic doesn't
# pick them up as an echo; the sound is still recorded directly.
# `tvrec --no-mic` skips the microphone and keeps the TV's sound on.''','''# screenshots (mute the TV so the mic doesn't hear it as an echo).
# `tvrec --no-mic` skips the microphone.''')
r('''  # Capturing the TV's sound silences its speakers; --audio-dup keeps them
  # playing (only wanted without the mic, which would hear them).
  local dup=(); [ $mic = 0 ] && dup=(--audio-dup)
  scrcpy -s "$s" --no-window --no-control --audio-source=playback $dup \\
    --record="$tmp/tv.mkv" >"$tmp/scrcpy.log" 2>&1 &
  local tv=$!
  # scrcpy only starts writing once something on the TV screen changes; start
  # the mic then too, so the two line up.
  echo "Press any button on the TV remote to start…"
  local i=0
  while [ ! -s "$tmp/tv.mkv" ] && kill -0 $tv 2>/dev/null && [ $i -lt 600 ]; do
    sleep 0.1; i=$((i+1))
  done
  if [ ! -s "$tmp/tv.mkv" ]; then
    kill -TERM $tv 2>/dev/null
    echo "Couldn't start recording the TV:"; cat "$tmp/scrcpy.log"; return 1
  fi
  local m''','''  # --audio-dup keeps the sound playing on the TV while it's recorded.
  scrcpy -s "$s" --no-window --no-control --audio-source=playback --audio-dup \\
    --record="$tmp/tv.mkv" >"$tmp/scrcpy.log" 2>&1 &
  local tv=$!
  # The TV recording's clock starts when the device starts capturing (its
  # first log line); start the mic then so the two line up.
  local i=0
  until grep -q "Device:" "$tmp/scrcpy.log" 2>/dev/null; do
    if ! kill -0 $tv 2>/dev/null || [ $i -ge 100 ]; then
      kill -TERM $tv 2>/dev/null
      echo "Couldn't start recording the TV:"; cat "$tmp/scrcpy.log"; return 1
    fi
    sleep 0.05; i=$((i+1))
  done
  local m''')
r('''  echo "Recording… press Enter to stop."
  read -r''','''  echo "Recording… press Enter to stop."
  read -r
  if [ ! -s "$tmp/tv.mkv" ]; then
    # scrcpy writes nothing until something on the TV screen has changed.
    echo "Nothing changed on the TV screen — press a button on the remote, then Enter."
    read -r
  fi''')
open(p,'w').write(s)
EOF
zsh -n ~/.zshrc && echo ok; sed -n '/^tvrec() {/,/^}/p' ~/.zshrc | head -40

Output

ok
tvrec() {
  local s=$(adb devices -l | awk '/BRAVIA/ {print $1; exit}')
  if [ -z "$s" ]; then
    local addr=$(adb mdns services | awk '/_adb-tls-connect/ {print $3; exit}')
    [ -n "$addr" ] && adb connect "$addr" >/dev/null && s=$addr
  fi
  if [ -z "$s" ]; then
    echo "TV not reachable — turn on Settings › System › Developer options › Wireless debugging on the TV."
    return 1
  fi
  local mic=1; [ "$1" = "--no-mic" ] && mic=0
  local tmp=$(mktemp -d)
  local f=~/Desktop/Screenshots/tv-$(date +%H%M%S).mp4
  # --audio-dup keeps the sound playing on the TV while it's recorded.
  scrcpy -s "$s" --no-window --no-control --audio-source=playback --audio-dup \
    --record="$tmp/tv.mkv" >"$tmp/scrcpy.log" 2>&1 &
  local tv=$!
  # The TV recording's clock starts when the device starts capturing (its
  # first log line); start the mic then so the two line up.
  local i=0
  until grep -q "Device:" "$tmp/scrcpy.log" 2>/dev/null; do
    if ! kill -0 $tv 2>/dev/null || [ $i -ge 100 ]; then
      kill -TERM $tv 2>/dev/null
      echo "Couldn't start recording the TV:"; cat "$tmp/scrcpy.log"; return 1
    fi
    sleep 0.05; i=$((i+1))
  done
  local m
  if [ $mic = 1 ]; then
    ffmpeg -nostdin -loglevel error -f avfoundation -i ":MacBook Pro Microphone" \
      -c:a aac -b:a 160k "$tmp/mic.m4a" &
    m=$!
  fi
  echo "Recording… press Enter to stop."
  read -r
  if [ ! -s "$tmp/tv.mkv" ]; then
    # scrcpy writes nothing until something on the TV screen has changed.
    echo "No
…[92 more chars]

Before handing it back, I'll measure the sync. I'll press a key at a known moment and compare when the screen change shows up in the TV track with when the mic would have started:

▸ Bash S=<scratch>; SER=$(adb devices -l | awk '/BRAVIA/ {print $1; exit}'); rm -f $...

Input

$ S=<scratch>; SER=$(adb devices -l | awk '/BRAVIA/ {print $1; exit}'); rm -f $S/t3.mkv $S/s3.log; scrcpy -s "$SER" --no-window --no-control --audio-source=playback --audio-dup --record=$S/t3.mkv > $S/s3.log 2>&1 & P=$!; until grep -q "Device:" $S/s3.log; do sleep 0.02; done; t0=$(python3 -c 'import time;print(time.time())'); sleep 4; tk=$(python3 -c 'import time;print(time.time())'); adb shell input keyevent DPAD_UP; sleep 3; kill -TERM $P; wait $P; python3 -c "print('key pressed', round($tk-$t0,2), 's after mic would start')"; ffprobe -v error -select_streams v -show_entries packet=pts_time -of csv=p=0 $S/t3.mkv | awk 'NR<=3'

Output

key pressed 4.18 s after mic would start
0.000000
0.100000
0.200000

▸ Bash S=<scratch>; ffmpeg -v error -i $S/t3.mkv -an -vf "select='gt(scene,0.002)',s...

Input

$ S=<scratch>; ffmpeg -v error -i $S/t3.mkv -an -vf "select='gt(scene,0.002)',showinfo" -f null - 2>&1 | grep -o "pts_time:[0-9.]*" | head -5

Output

(Bash completed with no output)

▸ Bash S=<scratch>; ffmpeg -v error -i $S/t3.mkv -an -vf "scale=160:-1,signalstats,m...

Input

$ S=<scratch>; ffmpeg -v error -i $S/t3.mkv -an -vf "scale=160:-1,signalstats,metadata=print:key=lavfi.signalstats.YAVG:file=-" -f null - 2>/dev/null | paste - - | awk '{split($2,a,":"); split($3,b,"="); printf "%s %.2f\n", a[2], b[2]}' | awk 'prev!="" && ($2-prev>0.3 || prev-$2>0.3) {print "change at", $1, prev, "->", $2} {prev=$2}' | head -5; adb exec-out screencap -p > $S/now.png; sips -Z 480 $S/now.png >/dev/null

Output

(Bash completed with no output)

▸ Read <scratch>/now.png

Input

<scratch>/now.png

Output

[image]

My key press only moved the keyboard highlight, which is too small to measure. Trying again with Back, which closes the keyboard, a much bigger change on screen:

▸ Bash S=<scratch>; SER=$(adb devices -l | awk '/BRAVIA/ {print $1; exit}'); rm -f $...

Input

$ S=<scratch>; SER=$(adb devices -l | awk '/BRAVIA/ {print $1; exit}'); rm -f $S/t3.mkv $S/s3.log; scrcpy -s "$SER" --no-window --no-control --audio-source=playback --audio-dup --record=$S/t3.mkv > $S/s3.log 2>&1 & P=$!; until grep -q "Device:" $S/s3.log; do sleep 0.02; done; t0=$(python3 -c 'import time;print(time.time())'); sleep 4; tk=$(python3 -c 'import time;print(time.time())'); adb shell input keyevent BACK; sleep 3; kill -TERM $P; wait $P; python3 -c "print('key sent', round($tk-$t0,2), 's after mic would start')"; ffmpeg -v error -i $S/t3.mkv -an -vf "crop=iw:ih/2:0:ih/2,scale=160:-1,signalstats,metadata=print:key=lavfi.signalstats.YAVG:file=-" -f null - 2>/dev/null | paste - - | awk '{split($2,a,":"); split($3,b,"="); print a[2], b[2]}' | awk 'prev!="" && ($2-prev>1 || prev-$2>1) {print "screen change at", $1} {prev=$2}' | head -3

Output

key sent 4.16 s after mic would start

▸ Bash S=<scratch>; ffmpeg -v error -i $S/t3.mkv -an -vf "crop=iw:ih/2:0:ih/2,scale=...

Input

$ S=<scratch>; ffmpeg -v error -i $S/t3.mkv -an -vf "crop=iw:ih/2:0:ih/2,scale=160:-1,signalstats,metadata=print:key=lavfi.signalstats.YAVG:file=-" -f null - 2>/dev/null | head -6; ffprobe -v error -select_streams v -show_entries packet=pts_time -of csv=p=0 $S/t3.mkv | tr '\n' ' ' | head -c 600

Output

frame:0    pts:0       pts_time:0
lavfi.signalstats.YAVG=40.7443
frame:1    pts:100     pts_time:0.1
lavfi.signalstats.YAVG=40.7443
frame:2    pts:200     pts_time:0.2
lavfi.signalstats.YAVG=40.7549
0.000000 0.100000 0.200000 0.300000 0.400000 0.473000 0.573000 0.673000 0.773000 0.873000 0.968000 1.068000 1.168000 1.268000 1.368000 1.469000 1.569000 1.669000 1.769000 1.869000 1.969000 2.069000 2.169000 2.269000 2.369000 2.469000 2.569000 2.669000 2.769000 2.869000 2.970000 3.070000 3.170000 3.270000 3.370000 3.470000 3.570000 3.670000 3.770000 3.870000 3.969000 4.069000 4.138000 4.153000 4.176000 4.189000 4.211000 4.224000 4.241000 4.256000 4.271000 4.291000 4.306000 4.326000 4.340000 4.358000 4.372000 4.395000 4.405000 4.426000 4.437000 4.473000 4.490000 4.590000 4.690000 4.790000 4.8900

Fixed. Your voice and the TV now stay in sync in the recording.

The bug: scrcpy times its recording from the moment it connects to the TV, but tvrec only started the mic after the first change on screen. Your mic track started later yet was placed at 0:00 in the merge, so everything the mic heard came out several seconds early. In your recording, the mic also picked up the TV's speakers, which gave the early copy that overlapped the real, clean TV sound.

The fix: the mic now starts when scrcpy connects to the TV, so both tracks begin at the same moment.

Measured: I sent Back to the TV 4.16 s after the mic would have started, and the keyboard began closing at 4.14 s in the TV recording. That puts the two tracks within a fraction of a second of each other. This is a timing test; I didn't make a full recording with speech.
Simplified, as you asked: the TV's speakers stay on in every mode now. You mute the TV yourself to avoid echo.
"Press a button" step removed: recording starts right away. If you press Enter and nothing on the TV screen changed the whole time, it asks you to press a remote button first, because otherwise there'd be no video to save.

tv-132510.mp4 still has the offset audio, so you'll need to record that take again (open a new terminal or source ~/.zshrc first).

You

why do we need to understand a key press can't we directly start the recrding

Agent

You're right to question it. My explanation was probably wrong, and the step may not be needed at all. In the last test the TV sent video frames every 0.1 s from the very start, without any key press. So scrcpy was more likely waiting for audio: the capture mode I'm using (playback) sends nothing until some app plays a sound, and a key press makes a click sound. scrcpy has a second mode (output) that records everything the TV outputs, silence included, all the time. I'll test whether it starts writing straight away with no button press:

▸ Bash S=<scratch>; SER=$(adb devices -l | awk '/BRAVIA/ {print $1; exit}'); for src...

Input

$ S=<scratch>; SER=$(adb devices -l | awk '/BRAVIA/ {print $1; exit}'); for src in playback output; do rm -f $S/t4.mkv; scrcpy -s "$SER" --no-window --no-control --audio-source=$src --record=$S/t4.mkv > $S/s4.log 2>&1 & P=$!; sleep 6; echo "$src: size after 6s with no key = $(stat -f %z $S/t4.mkv 2>/dev/null || echo none)"; kill -TERM $P; wait $P; done; ffprobe -v error -show_entries stream=codec_type,start_time -show_entries format=duration -of compact $S/t4.mkv

Output

playback: size after 6s with no key = 0
output: size after 6s with no key = 0
stream|codec_type=video|start_time=0.000000
stream|codec_type=audio|start_time=0.051000
format|duration=4.876000

Neither mode writes anything to disk during the 6 s. But output still saved a complete 4.9 s recording when stopped, without any key press. Now the same check for the current playback mode:

▸ Bash S=<scratch>; SER=$(adb devices -l | awk '/BRAVIA/ {print $1; exit}'); rm -f $...

Input

$ S=<scratch>; SER=$(adb devices -l | awk '/BRAVIA/ {print $1; exit}'); rm -f $S/t5.mkv; scrcpy -s "$SER" --no-window --no-control --audio-source=playback --audio-dup --record=$S/t5.mkv > $S/s5.log 2>&1 & P=$!; sleep 6; kill -TERM $P; wait $P; ls -la $S/t5.mkv 2>&1; cat $S/s5.log | tail -3; ffprobe -v error -show_entries stream=codec_type -show_entries format=duration -of compact $S/t5.mkv

Output

-rw-r--r--@ 1 souvikbiswas  wheel  307484 Oct  4 13:31 <scratch>/t5.mkv
INFO:     --> (tcpip)  <tv-adb-serial>            device  BRAVIA_4K_AE2
INFO: Recording started to matroska file: <scratch>/t5.mkv
INFO: Recording complete to matroska file: <scratch>/t5.mkv
stream|codec_type=video
stream|codec_type=audio
format|duration=4.957000

▸ Bash python3 - <<'EOF' import os p=os.path.expanduser('~/.zshrc') s=open(p).read()...

Input

$ python3 - <<'EOF'
import os
p=os.path.expanduser('~/.zshrc')
s=open(p).read()
old='''  read -r
  if [ ! -s "$tmp/tv.mkv" ]; then
    # scrcpy writes nothing until something on the TV screen has changed.
    echo "Nothing changed on the TV screen — press a button on the remote, then Enter."
    read -r
  fi
'''
assert old in s
s=s.replace(old,'  read -r\n')
old='''  wait $tv ${m:-} 2>/dev/null
  echo "Saving…"'''
assert old in s
s=s.replace(old,'''  wait $tv ${m:-} 2>/dev/null
  if [ ! -s "$tmp/tv.mkv" ]; then
    echo "Recording failed:"; cat "$tmp/scrcpy.log"; return 1
  fi
  echo "Saving…"''')
open(p,'w').write(s)
EOF
zsh -n ~/.zshrc && echo ok; ( sleep 6; echo ) | zsh -ic 'tvrec' 2>&1 | grep -v "^\[" | tail -3; f=$(ls -t ~/Desktop/Screenshots/tv-*.mp4 | head -1); ffprobe -v error -show_entries stream=codec_type,duration -of compact "$f" && rm "$f"

Output

ok
Recording… press Enter to stop.
Saving…
Saved ~/Desktop/Screenshots/tv-133123.mp4
stream|codec_type=video|duration=3.433333
stream|codec_type=audio|duration=3.429333

Recording now starts right away, with no key press. But this clip came out 3.4 s long for a 6 s recording, so something is cutting the end off. Looking at the intermediate files:

▸ Bash sed -i '' 's| fi \&\& rm -rf "$tmp" \&\& echo "Saved $f"| fi \&\& echo "Sav...

Input

$ sed -i '' 's|  fi \&\& rm -rf "$tmp" \&\& echo "Saved $f"|  fi \&\& echo "Saved $f (tmp $tmp)"|' ~/.zshrc; grep -n 'Saved \$f' ~/.zshrc; ( sleep 6; echo ) | zsh -ic 'tvrec' 2>&1 | grep -v "^\[" | tail -1; d=$(ls -dt $(zsh -ic 'echo $TMPDIR' 2>/dev/null)/tmp.* | head -1); for x in $d/tv.mkv $d/mic.m4a; do echo $x; ffprobe -v error -show_entries stream=codec_type,start_time,duration -show_entries format=duration -of compact $x; done

Output

179:  adb -s "$s" exec-out screencap -p > "$f" && echo "Saved $f"
242:  fi && echo "Saved $f (tmp $tmp)"
Saved ~/Desktop/Screenshots/tv-133139.mp4 (tmp <tmp>)
<tmp>
stream|codec_type=video|start_time=0.000000|duration=N/A
stream|codec_type=audio|start_time=0.070000|duration=N/A
format|duration=3.616000
<tmp>
stream|codec_type=audio|start_time=0.000000|duration=3.637333
format|duration=3.637333

▸ Bash sed -i '' 's| fi \&\& echo "Saved $f (tmp $tmp)"| fi \&\& rm -rf "$tmp" \&\...

Input

$ sed -i '' 's|  fi \&\& echo "Saved $f (tmp $tmp)"|  fi \&\& rm -rf "$tmp" \&\& echo "Saved $f"|' ~/.zshrc; grep -n 'rm -rf "\$tmp"' ~/.zshrc; zsh -n ~/.zshrc && echo ok; rm -rf <tmp> <tmp> ~/Desktop/Screenshots/tv-133139.mp4

Output

242:  fi && rm -rf "$tmp" && echo "Saved $f"
ok

No key press is needed. I was wrong about that: scrcpy was recording from the start the whole time. It keeps the data in memory and may only write the file when it stops, so the file looked empty while recording, and I misread that as "nothing is happening". A test with nothing happening on the TV still saved a full 5 s video with sound.

tvrec now just starts:

~ » tvrec
Recording… press Enter to stop.
Saving…
Saved ~/Desktop/Screenshots/tv-HHMMSS.mp4

Removed: the button-press check I'd added. A short check remains that only reports an error if scrcpy saved nothing.
Tested: with no key press. The TV and mic tracks both came out 3.6 s, so they start and stop together. I deleted the test clips.
Startup delay: there's still about 1–2 s before "Recording…" appears while scrcpy connects to the TV. Wait for that line before you start talking.

You

while recoridng somehow my mac seems to play the tv output sound, that seems like a bug csusing weird duplicates

Agent

That's scrcpy: --no-window hides the video window, but scrcpy still plays the TV's sound through the Mac's speakers by default, and the Mac mic was recording that. Adding --no-audio-playback:

▸ Bash sed -i '' 's|scrcpy -s "$s" --no-window --no-control --audio-source=playback ...

Input

$ sed -i '' 's|scrcpy -s "$s" --no-window --no-control --audio-source=playback --audio-dup \\|scrcpy -s "$s" --no-window --no-audio-playback --no-control \\\n    --audio-source=playback --audio-dup \\|' ~/.zshrc; sed -n '/# --audio-dup keeps/,/local tv=/p' ~/.zshrc; zsh -n ~/.zshrc && echo ok; scrcpy --help | grep -A2 -- "--no-audio-playback" | head -3

Output

# --audio-dup keeps the sound playing on the TV while it's recorded.
  scrcpy -s "$s" --no-window --no-audio-playback --no-control \
    --audio-source=playback --audio-dup \
    --record="$tmp/tv.mkv" >"$tmp/scrcpy.log" 2>&1 &
  local tv=$!
ok
        --no-video-playback --no-audio-playback).

    --new-display[=[<width>x<height>][/<dpi>]]

▸ Bash ( sleep 7; echo ) | zsh -ic 'tvrec --no-mic' 2>&1 | grep -v "^\[" | tail -1; ...

Input

$ ( sleep 7; echo ) | zsh -ic 'tvrec --no-mic' 2>&1 | grep -v "^\[" | tail -1; f=$(ls -t ~/Desktop/Screenshots/tv-*.mp4 | head -1); ffprobe -v error -show_entries stream=codec_type,duration -of compact "$f" && rm "$f"

Output

Saved ~/Desktop/Screenshots/tv-133352.mp4
stream|codec_type=video|duration=4.466667
stream|codec_type=audio|duration=4.434333

I fixed it, and that was the cause of the duplicates. scrcpy's --no-window only hides the picture; it was still playing the TV's sound through the Mac's speakers, and the Mac mic recorded that as a second, slightly delayed copy. tvrec now runs scrcpy with --no-audio-playback, so the Mac stays silent and the TV's sound goes only into the file.

A test recording still saved the picture and TV sound fine. I didn't check by ear that the Mac stays quiet, since nothing was playing on the TV. Open a new terminal (or source ~/.zshrc) before your next take.

You

commit all the changes

Agent

▸ Bash git checkout analysis_options.yaml 2>/dev/null; git status --short; git diff ...

Input

$ git checkout analysis_options.yaml 2>/dev/null; git status --short; git diff --stat | tail -1

Output

M android/app/src/main/AndroidManifest.xml
 M lib/screens/settings_screen.dart
 M lib/screens/slideshow_screen.dart
 M lib/screens/viewer_screen.dart
 M lib/services/answer_voice.dart
RM lib/services/gemini_service.dart -> lib/services/gemma_service.dart
 M lib/services/settings_controller.dart
 M lib/widgets/ask_panel.dart
 M lib/widgets/zoomable_image.dart
 9 files changed, 261 insertions(+), 184 deletions(-)

▸ Bash git add -A && git commit -q -F - <<'EOF' Ask Gemma on a home server instead o...

Input

$ git add -A && git commit -q -F - <<'EOF'
Ask Gemma on a home server instead of Gemini in the cloud

Photos are now answered by Gemma 4, Google's open-weight model, running
on a computer at home through Ollama. The TV talks to it over the local
network, so photos never leave the house and there's no API key or bill.

- Settings: Gemma server address (a bare IP fills in Ollama's port) and
  model, defaulting to gemma4:e2b; replaces the Gemini API key.
- Thinking off and answers streamed in as they're written: ~2-3s for a
  full answer instead of 10-30s.
- Allow cleartext HTTP, since Ollama on the LAN doesn't use TLS.
- Ask panel: Down from the field reaches the suggestions; shorter hint.
- Top-bar buttons get a dark backdrop so labels read over bright photos.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01XoMk31HXnGGpCKcAS4CKpF
EOF
git log --oneline | head -3; git status --short | wc -l

Output

5176aa9 Ask Gemma on a home server instead of Gemini in the cloud
a3e3eaa Add Memories TV app
       0

I committed everything as 5176aa9 "Ask Gemma on a home server instead of Gemini in the cloud", on top of "Add Memories TV app". The working tree is clean.

The commit includes:
- Gemma instead of Gemini: Ask now uses Gemma through Ollama on your Mac. Settings has a server address and a model (default gemma4:e2b) in place of the Gemini API key.
- Speed: thinking is off and answers stream in as they're written, so a full answer takes about 2–3 s instead of 10–30 s.
- Plain HTTP allowed: Android otherwise blocks connections to Ollama on the home network.
- Ask panel: Down from the question field reaches the suggestions, and the hint is shorter.
- Top-bar buttons: they get the dark background so the labels read over bright photos.

tvrec isn't in the commit because it lives in your ~/.zshrc, outside the repo.

You

push to this remote repo: https://github.com/sbis04/memories_gemma.git

Agent

▸ Bash git remote -v; gh repo view sbis04/memories_gemma --json visibility,isEmpty,d...

Input

$ git remote -v; gh repo view sbis04/memories_gemma --json visibility,isEmpty,defaultBranchRef 2>&1 | head -5

Output

Unknown JSON field: "visibility"
Available fields:
  assignableUsers
  codeOfConduct
  contactLinks

▸ Bash gh repo view sbis04/memories_gemma --json isPrivate,isEmpty,defaultBranchRef ...

Input

$ gh repo view sbis04/memories_gemma --json isPrivate,isEmpty,defaultBranchRef 2>&1; git ls-remote https://github.com/sbis04/memories_gemma.git 2>&1 | head

Output

{
  "defaultBranchRef": {
    "name": ""
  },
  "isEmpty": true,
  "isPrivate": true
}

The repo is empty and private, so nothing gets overwritten. Pushing:

▸ Bash git remote add origin https://github.com/sbis04/memories_gemma.git && git pus...

Input

$ git remote add origin https://github.com/sbis04/memories_gemma.git && git push -u origin main 2>&1 | tail -3; git ls-remote origin

Output

To https://github.com/sbis04/memories_gemma.git
 * [new branch]      main -> main
branch 'main' set up to track 'origin/main'.
5176aa9952b35cce3e408651edfc075bee4c583c    HEAD
5176aa9952b35cce3e408651edfc075bee4c583c    refs/heads/main

I pushed both commits to main on https://github.com/sbis04/memories_gemma. The repo was empty, so nothing was overwritten, and GitHub now shows 5176aa9 as the latest commit. I added the repo as the origin remote, and local main is set to track origin/main, so git push and git pull will work without extra arguments.

The repo is private. For the hackathon, judges will probably need to open it, so you'll likely want to make it public before you submit (GitHub → Settings → Change visibility).

You

this is the hackathon template can you fill it in a temporary .md file don't commit it

<pasted_content id="396a">
This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend

What I Built

Demo

Code

How I Built It

Why Does Open Innovation Matter?

My Agent Session

Prize Categories

Best Use of Gemma
</pasted_content id="396a">

[Image #8]
[screenshot]

Agent

I'll draft it from what's actually in the app and what we measured. A few things only you know: who it's for, their reaction, and the demo video. Those get clearly marked TODO placeholders rather than invented details.

▸ Write {"file_path": "~/MobileDev/Flutter/tv_gallery_gemma/SUBMISSION.md", "content"...

Input

{"file_path": "~/MobileDev/Flutter/tv_gallery_gemma/SUBMISSION.md", "content": "<!-- Suggested title: \"Memories: our family photos on the TV, with Gemma to answer 'where was this?'\" -->\n<!-- Tags already on the post: devchallenge, weekendchallenge, hf26challenge (+ consider: gemma, flutter) -->\n\n*This is a submission for the [Hacktoberfest Weekend Challenge: Build for a Friend](https://dev.to/challenges/hacktoberfest-weekend-2026-10-01)*\n\n## What I Built\n\n**Memories** is a photo and video gallery for an Android TV, built for <!-- TODO: who, e.g. \"my parents\" \u2014 and one line on why: they love looking back at trips, but the photos live on an SSD and the phone screen is too small to share around the room -->.\n\nPlug the photo SSD into the TV and Memories opens on its own. From the couch, with just the remote, you can browse folders, start a slideshow, or play 4K/Dolby Vision videos. Each photo shows when and where it was taken.\n\nThe part I built this weekend: **press Down on any photo and ask about it.** \"What is this?\", \"Where was this taken?\", \"What's the tower on the left called?\" You can type the question or say it into the remote's mic. Zoom in first and the question is about the part on screen. **Gemma**, running on a computer in the same house, answers in a couple of seconds, and the TV reads the answer aloud.\n\nThe problem it solves: <!-- TODO: in your words \u2014 e.g. half the stories behind our photos are \"what was that place called again?\", and nobody wants to pull out a phone mid-slideshow to look it up -->.\n\n## Demo\n\n<!-- TODO: upload the tvrec recording (YouTube/Loom/etc.) and embed it:\n{% embed https://www.youtube.com/watch?v=... %}\nA good 60\u201390s cut: SSD plugged in \u2192 Memories opens \u2192 slideshow \u2192 pause, zoom on a landmark \u2192 press Down, ask by voice \u2192 answer streams in and is read aloud \u2192 a follow-up question. -->\n\n## Code\n\n{% embed https://github.com/sbis04/memories_gemma %}\n\n<!-- NOTE: the repo is private right now; make it public before publishing. -->\n\nThe Gemma integration lives in [`lib/services/gemma_service.dart`](https://github.com/sbis04/memories_gemma/blob/main/lib/services/gemma_service.dart). The Ask screen is [`lib/widgets/ask_panel.dart`](https://github.com/sbis04/memories_gemma/blob/main/lib/widgets/ask_panel.dart).\n\n## How I Built It\n\nThe app is **Flutter** on a Sony Bravia (Android TV 14). Everything is driven by the D-pad: no touch, no mouse.\n\n**The AI is Gemma 4 (E2B), running locally with Ollama** on a MacBook on the home Wi-Fi:\n\n```\nTV (Memories)  \u2500\u2500 photo + question, over the LAN \u2500\u2500\u25b6  Mac: Ollama \u2192 gemma4:e2b\n      \u25b2                                                        \u2502\n      \u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500 answer, streamed word by word \u25c0\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518\n                then re
…[3979 more chars]

Output

File created successfully at: ~/MobileDev/Flutter/tv_gallery_gemma/SUBMISSION.md (file state is current in your context — no need to Read it back)

▸ Bash echo "SUBMISSION.md" >> .git/info/exclude && git status --short | wc -l

Input

$ echo "SUBMISSION.md" >> .git/info/exclude && git status --short | wc -l

Output

▸ Edit {"replace_all": false, "file_path": "~/MobileDev/Flutter/tv_gallery_gemma/SUB...

Input

{
  "replace_all": false,
  "file_path": "~/MobileDev/Flutter/tv_gallery_gemma/SUBMISSION.md",
  "old_string": "So \"where was this?\" gets \"Shanghai, on the Bund\", not a guess.",
  "new_string": "So asking about a skyline gets *\"This photo was taken in Shanghai, China, on September 14, 2026… landmarks like the Oriental Pearl Tower\"*, not a guess."
}

Output

The file ~/MobileDev/Flutter/tv_gallery_gemma/SUBMISSION.md has been updated successfully. (file state is current in your context — no need to Read it back)

I filled in the template in SUBMISSION.md at the repo root. I also listed it in .git/info/exclude, a local-only ignore list, so git doesn't see it and it can't be committed by accident (git status is clean).

What's filled in, all from the code and the tests we ran:
- The app: what Memories does, and how Ask Gemma works (sending both the photo and the zoomed-in crop, the date/place/folder context, follow-up questions, streaming, reading aloud).
- The speed story: a table of the latency numbers we measured, the architecture diagram, and the three Mac setup commands.
- Why open matters: written around the actual switch from the Gemini API to local Gemma: privacy for family photos, no key or bill, nothing changing under you, and being able to tune it. It also says plainly that the trade-off is a computer at home having to be on.
- Code: the GitHub embed plus links to the two main files.

What only you can fill in (marked  in the file):
1. Who it's for, and the problem in your own words. This is the heart of "Build for a Friend", and writing quality counts most in judging, so it should be real.
2. The demo video. Upload a tvrec recording and embed it. I suggested a 60–90 s flow in the comment.
3. What they said when you handed it over. The challenge gives bonus points for this.
4. Your agent session embed, if you want to include it.

Before publishing: make the GitHub repo public, or the embed won't work for judges.

Want me to save this session to DevRelay so you have the {% agent_session %} embed ready?

Prize Categories

Best Use of Gemma

Ghost Maintainer — An AI Junior Partner for Open Source

Souvik Biswas — Fri, 27 Mar 2026 04:13:12 +0000

This is a submission for the Notion MCP Challenge

What I Built

I maintain a couple of open source projects on my own, and the worst part has never been writing code — it's the stuff around it. Going through new issues, deciding if something's a bug or a feature request, digging into the codebase to figure out what's actually wrong, and then sitting down to fix it. Half the issues end up sitting untouched for weeks because I just don't get to them.

So I built Ghost Maintainer. It turns Notion into an operations center for a GitHub repo, and handles most of the grunt work with AI. Here's what happens when someone opens an issue:

It shows up in a Triage Queue in Notion
Gemini reads the issue and classifies it — bug or feature, priority level, confidence score
Bugs go to the Maintenance Backlog, features go to the Feature Backlog
If auto-fix is on, it reads through the codebase, figures out a fix, and opens a PR

All I have to do is review the PR and merge.

If you've turned off auto-fix (or want to handle features), there's a CLI:

ghost_maintainer fix 3
ghost_maintainer implement 9

Same pipeline — reads the code, writes a fix, opens a PR.

Setting it up is one command from inside your repo:

curl -sL https://raw.githubusercontent.com/sbis04/ghost_maintainer/main/install.sh \
  -o install.sh && \
  bash install.sh && \
  rm install.sh

You plug in your Notion, GitHub, and Gemini tokens, and it handles the rest — creates the databases, sets up GitHub secrets, pushes the workflows.

There's also a Dart MCP server that pairs with Notion MCP (@notionhq/notion-mcp-server). Hook both up to Gemini CLI or Claude, and you can interact with your backlog in plain English — triage stuff, investigate bugs, ship fixes. 5 tools, 2 resources, 2 prompts.

The Notion workspace

Triage Queue — everything starts here, AI sorts it out
Maintenance Backlog — bugs, with AI summaries and PR links
Feature Backlog — feature requests, ready when you are
Archive — done items land here with timestamps
Project Vision Statement — tells the AI what matters to your project

Video Demo

Link to Code on GitHub

sbis04 / ghost_maintainer

AI-powered junior partner for solo open-source maintainers

Ghost Maintainer

Solo maintainers wear too many hats. Ghost Maintainer takes over the repetitive parts — triaging issues, reading code, writing fixes, and opening PRs — so you can focus on the work that actually needs a human.

It uses Notion as an operations center. Bugs get triaged and fixed automatically. Features queue up until you're ready. Everything stays visible in Notion so you never lose track.

Built with Dart, MCP, Google Gemini, and the Notion API.

Getting Started

You'll need Dart (>= 3.7.0) and GitHub CLI installed.

Grab three API keys before you start:

What	Where	Notes
Notion token	notion.so/profile/integrations	See steps below
GitHub PAT	github.com/settings/tokens	Classic token, `repo` + `actions` scopes
Gemini key	aistudio.google.com/apikey	Any project works

You can either follow the steps in the next section, or have a look at the demo video to learn more about the tool and get step-by-step instruction for installing Ghost…

View on GitHub

Three main pieces:

ghost_maintainer_mcp/ — Dart MCP server. 5 tools, 2 resources, 2 prompts.
notion_setup/ — CLI tool + the GitHub Action scripts.
.github/workflows/ — 4 workflows covering ingestion, triage, implementation, and archival.

The CLI installs globally via dart pub global activate straight from the repo — no need to publish to pub.dev.

How I Used Notion MCP

The whole system runs on two MCP servers working together.

Notion MCP (@notionhq/notion-mcp-server) is the foundation. It's what gives the AI access to the Notion workspace — searching databases, reading pages, creating content, appending blocks. Without it, the AI would be blind to what's going on.

Ghost Maintainer MCP sits on top of that. It's a custom Dart server that adds the maintenance-specific stuff — ghost_triage_issue, ghost_investigate_issue, ghost_deploy_fix. The prompts are written to use both servers together. The triage prompt, for instance, tells the AI to search for duplicates through Notion MCP before classifying, and to append its analysis notes to the Notion page afterward.

Ghost Maintainer also exposes a couple of resources that pull from Notion — ghost://vision grabs the Project Vision Statement, and ghost://backlog/summary aggregates stats across all the databases. These save the AI from having to navigate the workspace manually every time.

Everything lives in Notion. The Triage Queue, backlogs, and archive are all databases with properties like Stage, Priority, Labels, AI Summary, and PR URL. The Vision Statement is a regular Notion page — update it and the AI adjusts. If you write "security issues are always P0" in there, that's exactly what happens.

PRs link back to the Notion page. When they get merged, the item auto-archives with a date.

The GitHub Actions pipeline handles the automated side (new issue triggers triage, etc.), but the MCP layer is what makes it interactive. Connect both servers to Gemini CLI and you get conversations like:

You: "What's in the backlog?"
AI: [uses ghost://backlog/summary] "3 bugs, 2 features..."

You: "Any duplicates for the dark mode request?"
AI: [uses Notion MCP search] "Found a similar one from last week."

You: "Triage the login crash"
AI: [uses ghost_triage_issue] "Bug, P1-High."

You: "Fix it"
AI: [uses ghost_investigate_issue + ghost_deploy_fix] "PR #15 created."

The thing I like about this is that Notion ends up being the shared workspace for both me and the AI. I open Notion and see what's going on. The AI checks the same workspace through Notion MCP. Same board, same data, no surprises.

WanderXP — Organize your travel with ease

Souvik Biswas — Mon, 20 Feb 2023 16:09:40 +0000

Overview

It's always a hassle to manage all the necessities while deciding a travel plan. What if you could keep everything organized inside a single app?

WanderXP helps you to keep your travel requirements organized including flight and hotel details, and the notable places that you don't want to miss visiting.

Category Submission:

Integration Innovators

App Link

The app is designed for mobile platforms (small form factor), but as Flutter is used for building so it's a cross-platform app capable of running on Android, iOS, Windows, Linux, and Web.

Web app link: https://wanderxp.flutterflow.app

Please scale the window to mobile form factor while running on web.

Mobile app link (Android): https://appdistribution.firebase.dev/i/a0b42613bd16e37e

Please try this for better experience, as it's optimized for mobile platforms.

You can also follow the steps on the GitHub project page if you want to try out the app on other platforms.

Project Description

The primary features of the app are as follows:

Store multiple trip information (travel start & end dates, flight info, hotel info, places to visit during the trip).
Upload documents in a organized manner (like flight and hotel booking documents).
Secure user management with a robust authentication system.
Discover new suggestions for popular places to travel.

Architecture

Here's an overview of the entire architecture of the cross-platform application along with the backend infrastructure built with Flask and managed on Linode:

The tech stack used for building this project:

FlutterFlow: It's a no-code platform that I have used for designing the app from scratch, connecting with the REST API, and then generating the source code in Flutter.
Flask: Used for building the REST API to manage user authentication, database CRUD operations, and storing files.
Linode: For getting access to the cloud computing infrastructure along with their managed database (SQL) and object storage.

Frontend app

The Flutter application consists of the following screens/pages:

SplashScreen
HomePage
LoginPage
SignUpPage
DiscoverPage
TripViewPage
CreateTripPage
FlightInfoPage
HotelReservationPage
PlacesToVisitPage
TripPage
EditProfile

Backend REST API

The REST API built with Flask mainly consists of the following endpoints:

/register: To create account for a new user.
/login: To log in an already registered user.
/places: Fetching all the top places to discover.
/place: To retrieve a single place with the ID.
/places_to_visit/<trip_id>: Retrieve all the places to visit by the provided trip ID.
/trips/<trip_id>: Retrieve a single trip by its ID.
/trips/<trip_id>/update: Update the details of a trip.
/trips: Retrieve and store trip based on the uid (Unique user identifier) provided.
/store_file: For storing a file to the Object Storage.
/get_file: For retrieving a file from the storage.

Linode

Overview of the Linode Cloud Console:

Managed Database using MySQL v8 for storing user data, trips, places, and more:

Object Storage used for storing user flight and hotel booking files:

Link to Source Code

The entire app is open sourced - try it out and also feel free to contribute to this project 😉 :

sbis04 / wander_xp

Organise your travel with ease

WanderXP

Blog post about this project: https://dev.to/sbis04/wanderxp-organize-your-travel-with-ease-205d

Try out the app (Android): https://appdistribution.firebase.dev/i/a0b42613bd16e37e

Try out the app (Web): https://wanderxp.flutterflow.app

WanderXP helps you to keep your travel requirements organized including flight and hotel details, and the notable places that you don't want to miss visiting.

Architecture

Here's an overview of the entire architecture of the cross-platform application along with the backend infrastructure built with Flask and managed on Linode:

The tech stack used for building this project:

FlutterFlow: It's a no-code platform that I have used for designing the app from scratch, connecting with the REST API, and then generating the source code in Flutter.
Flask: Used for building the REST API to manage user authentication, database CRUD operations, and storing files.
Linode: For getting access to the cloud computing infrastructure along with their managed database (SQL) and object storage.

Screenshots

License

Permission…

View on GitHub

Permissive License

The project is licensed under the MIT License.

Background

To most people the problem with travel management might not seem that hard to solve. But upon searching we found that there's very limited applications available on the market that provides a minimalist UI and also gets the job done.

The second reason behind building a travel management app was that I wanted to learn how to use Linode, and this seemed to me a very good usecase of Managed Database and Object Storage services provided by Linode.

How I built it

I have mainly used three services provided by Linode:

Shared CPU: I used a Ubuntu 22.04 shared compute instance.
Managed Database (with MySQL v8.0.26): For storing user data, location information and the trips planned by each user. I have also designed a robust email-password authentication system
Object storage: For storing the trip documents like flight bookings and hotel reservation files.

This was my first time using Linode for managing the backend of a mobile application. And, the entire integration process was pretty smooth for me (some of the documentation pages helped a lot).

This hackathon helped me to learn how to build a end-to-end product (consisting of a frontend, backend, and cloud server). Thanks to Linode & DEV team for organzing this hackathon! 🙂

One suggestion of improvement: "It would have been a lot faster while working with the Managed Database if there was a SQL viewer/editor inside the Linode Cloud Console (I spent a lot of time authenticating into the database locally and then running the SQL command to view the table data every time while testing the queries from the mobile app)"

Additional Resources/Info

Some resources that helped while working on this project are as follows:

Slibro — a story writing platform

Souvik Biswas — Thu, 12 May 2022 20:19:22 +0000

Overview

Slibro is a story writing platform that supports short and long format stories. Flutter and Appwrite is used to create this amazing cross-platform experience.

Try out the app on Android from here.

The inspiration behind this idea is to simplify the process of story writing, formatting, and publishing to reach a wider audience. Whether you just getting started with your first story or a seasoned writer, Slibro has got you covered!

Submission Category:

Mobile Moguls

Link to Code

The app is completely open sourced, have a look around the code and also feel free to contribute to this project 😉 :

sbis04 / slibro

Platform for story writers and publishing houses

Slibro

Slibro is a story writing platform that supports short and long format stories. Flutter and Appwrite is used to create this amazing cross-platform experience.

Try out the app on Android from here.

Usage

To run this from your system, you should have:

Flutter SDK installed and configured on your system.
Setup Appwrite using Docker.
Host the server locally using ngrok.

Under lib directory, create a secret.dart file, and add the server URL and Appwrite project ID to it. Example:

class Secrets {
  static String hostname = 'https://127b-203-163-244-125.in.ngrok.io/v1';
  static String projectID = '6276341092e81e829ab0';
}

Run using the following command:
```
flutter run
```

App Overview

The app now has full-fledged story editor (rich text - markdown), story reader, and story management system (to manage published/unpublished stories and explore other publisher's stories).

Some glimpses of Slibro's user interface are as follows:

The above four screens cover the authentication…

View on GitHub

How it started

I initially started working on the idea of this app by creating rough UI sketches and notes ...

... also some database structures.

How it's going

Some glimpses of Slibro's user interface are as follows:

The above four screens cover the authentication flow on the app using email/password method. These screens help a user to either create a new account or login using an existing account. Once a user signs up to the app, it navigates to the story creation flow.

These screens help a user to create the first story as a draft in the Slibro app. The user can also publish the story if wanted.

The editor and the reader screens are the most important ones, the editor also has rich text support using Markdown.

The three screens (Home, My Stories, and My Profile) shown above are part of the dashboard of the app, user can navigate to any of these using the Navigation bar accessible from these pages.

Navigation bar has a subtle animation to improve the UX of the app:

Project Description

In this project, three of the major Appwrite APIs are used:

Account API: Used for implementing user authentication and user data management.
Database API: Used for storing app data related to stories and chapters.
Storage API: Used for storing the Rich Text story file in JSON format.

The Flutter plugins used:

The Appwrite console view:

Two databases are used for this project: (1) stories, and (2) chapters.

Stories database documents preview:

Stories database attributes:

Chapters database attributes:

The files storage preview (the chapters are stored as JSON rich text files):

References

Decifer — Generate transcripts from audio using Flutter and Deepgram

Souvik Biswas — Sat, 02 Apr 2022 18:40:59 +0000

Overview

Decifer is a cross-platform mobile app that helps to generate transcripts either from a voice recording or by uploading an audio file.

Try out the app: https://play.google.com/store/apps/details?id=com.souvikbiswas.deepgram_transcribe

Typically, for using Deepgram API you would require to maintain a server but I have made this project totally serverless. To know more continue reading.

Here's a brief demo of the entire app in action:

Submission Category:

Analytics Ambassadors

Link to Code on GitHub

The entire app is open sourced - try it out and also feel free to contribute to this project 😉 :

sbis04 / decifer

Generate your audio transcripts with ease.

Decifer

Blog post about this project: https://dev.to/sbis04/decifer-generate-transcripts-with-ease-5hl3

Try out the app: https://appdistribution.firebase.dev/i/a57e37b2fda28351

A cross-platform mobile app that helps you to generate transcripts either from a voice recording or by uploading an audio file. The project uses a totally serverless architecture.

Architecture

The mobile app is created using Flutter which is integrated with Firebase. Firebase Cloud Functions is used to deploy the backend code required for communicating with the Deepgram API.

App overview

The Flutter application consists of the following pages/screens:

Login Page
Register Page
Dashboard Page
Record Page
Upload Page
Transcription Page

For authenticating the user inside the app -- Login and Register pages are used. Authentication is required to generate unique accounts for users required for storing the generated transcripts to Firestore and facilitate cloud-sync.

The Dashboard Page displays a list of all the transcripts currently present on the user's account. It also has two buttons -…

View on GitHub

Project Description

The primary features of the app are as follows:

Generate transcript from audio recording & audio file using Deepgram API.
Cloud-sync for syncing across multiple devices using the same account.
Transcribe confidence map view.
Export as PDF and share with anyone.

Architecture

I'm using a totally serverless architecture for this project 🤯, let's have a look how it works:

The mobile app is created using Flutter which is integrated with Firebase. I have used Firebase Cloud Functions to deploy the backend code required for communicating with the Deepgram API.

Firebase Cloud Functions lets you run backend code in a severless architecture.

I have deployed the following function to Firebase:



const functions = require("firebase-functions");
const {Deepgram} = require("@deepgram/sdk");

exports.getTranscription = functions.https.onCall(async (data, context) => {
  try {
    const deepgram = new Deepgram(process.env.DEEPGRAM_API_KEY);
    const audioSource = {
      url: data.url,
    };

    const response = await deepgram.transcription.preRecorded(audioSource, {
      punctuate: true,
      utterances: true,
    });

    console.log(response.results.utterances.length);

    const confidenceList = [];
    for (let i =0; i < response.results.utterances.length; i++) {
      confidenceList.push(response.results.utterances[i].confidence);
    }

    const webvttTranscript = response.toWebVTT();

    const finalTranscript = {
      transcript: webvttTranscript,
      confidences: confidenceList,
    };

    const finalTranscriptJSON = JSON.stringify(finalTranscript);
    console.log(finalTranscriptJSON);

    return finalTranscriptJSON;
  } catch (error) {
    console.error(`Unable to transcribe. Error ${error}`);
    throw new functions.https.HttpsError("aborted", "Could not transcribe");
  }
});

The getTranscription function takes an audio URL, generates the transcripts using Deepgram API along with the respective confidences, and returns the data in a particular JSON format (that can be parsed within the app).

App screens

The Flutter application consists of the following pages/screens:

Login Page
Register Page
Dashboard Page
Record Page
Upload Page
Transcription Page

The Dashboard Page displays a list of all the transcripts currently present on the user's account. It also has two buttons - one for navigating to the Record Page and the other for navigating to the Upload Page.

Record Page lets you record your audio using the device microphone and the transcribe it using Deepgram. You always have an option to re-record if you think the last recording wasn't good.

From the Upload Page, you can choose any audio file present on your device and generate the transcript of it.

Transcription Page is where the entire transcript can be viewed. It has an audio-transcript synchronized playback that highlights the text transcript part with respect to the audio that is playing.

You can also see the confidence map of each of the parts of the transcript (it shows how much accurate is that part of transcript generation - darker is higher confidence).

You can also easily print or share the generated transcript in the PDF format.

Deepgram

Overview of my Deepgram dashboard (completed the mission, Get a Transcript via API or SDK):

Usage analytics of the Deepgram API:

Log of one of the API calls for transcribing from audio:

References

Plant Monitor - Using IoT, MongoDB and Flutter

Souvik Biswas — Wed, 12 Jan 2022 17:58:56 +0000

Overview

Plant Monitor is an IoT-based project for monitoring plant health with ease. The projects consists of three parts:

IoT: Sensors (for monitoring plant data)
Database: MongoDB (Atlas, Realm and Chart)
Cross platform mobile app: Flutter (for getting realtime plant data)

Submission Category:

Action Star

Link to Code

The code for both the app and the IoT part is present in the following GitHub repo:

sbis04 / plant-monitor

Plant monitoring system using IoT, MongoDB, and Flutter

Plant Monitor

IoT based plant monitoring system which is connected to MongoDB. This is a Flutter app to display the realtime data from the sensors attached to the plant on a mobile device.

License

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

View on GitHub

Project Description

A detailed description of all the three parts of this project is present below.

IoT: Sensors

ESP32 module is used for collecting data, processing and uploading to the MongoDB database. It is a low powered microcontroller integrated with WiFi and Bluetooth.

DHT11 sensor is used for measuring raw temperate and humidity data from the surroundings of the plant.

LDR is used for calculating the light intensity that the plant is receiving.

Soil Moisture sensor module is used to measure the moisture or the water level of the soil. The sensor includes a potentiometer to set the desired moisture threshold.

Database: MongoDB

MongoDB Atlas provides cloud database service using AWS, Azure, and Google Cloud. It also has various automation tools for performing various backend functionalities and comes with visualization tools. The services that are used in this project are described below.

Atlas is used as the main cloud database for storing the sensor readings along with timestamps.

Realm Function is defined to easily store the sensor data from the ESP32 module. A HTTP Endpoint is created to access the MongoDB database from the ESP32.

The following function is used for storing the sensor data:

exports = function(payload){
    var atlas = context.services.get("mongodb-atlas");
    var coll = atlas.db("plantdata").collection("readings");
    try {
      if (payload.body) 
      {
        body = EJSON.parse(payload.body.text());
      }
      coll.insertOne(body);
      console.log(body);
    } catch (e) {
      console.log("Error inserting doc: " + e);
      return e.message();
    }
};

Charts are used to visualize the sensor readings directly inside the MongoDB web app.

For this project I have created four charts:

Plant Light (%): Amount of light intensity plant is receiving
Plant Humidity (%): Humidity around the plant
Plant Moisture (%): Amount of water present in the soil
Plant Temperature (°C): Current temperature around the plant

Mobile app: Flutter

To use the Realm data inside the Flutter application I have created a modified version of the flutter_mongodb_realm plugin to support Dart null safety and run it on the latest version of the Flutter SDK.

References

Flutter: Custom Painter | PART-1

Souvik Biswas — Thu, 23 Apr 2020 10:30:07 +0000

You might have seen a lot of apps having highly customized designs and amazing animations. It is really time-consuming and painful to achieve that level of customization on a native Android and iOS apps.

Flutter has got your back. With the help of CustomPainter combined with the legendary Hot Reload feature of Flutter you can iterate upon your creations efficiently and fast.

In this series, I will start with the basics of painting using CustomPainter (drawing basic shapes) in the first few parts, and then I will go into the complex designs.

NOTE: The series will involve some basic concepts of mathematics (mainly Trigonometry and Coordinate Geometry).

So, let's get started.

Initial App Structure

The basic structure of the app will just consist of a Scaffold having an AppBar, and a CustomPaint widget in the body.

class MyPainter extends StatelessWidget {
  @override
  Widget build(BuildContext context) {
    return Scaffold(
      appBar: AppBar(
        title: Text('Custom Painter'),
      ),
      body: CustomPaint(
        painter: ShapePainter(),
        child: Container(),
      ),
    );
  }
}

CustomPaint Widget Properties

Some of the most important properties of the CustomPaint widget are:

painter: The painter that paints before the child.
foregroundPainter: The painter that paints after the child.
child: The canvas will by default take the size of the child, if it is defined.
size: If the child is not defined, then the size of the canvas should be specified.

For getting started with the basic shapes, you will just need two of these properties:

painter
child

In the previous code snippet, I have defined a Container as the child. As you might know, Container by default takes up the entire size of the screen when there is no child specified within it.

Intro to CustomPainter

Now, you have to define the ShapePainter widget which should extend the CustomPainter class.

paint: This method is called whenever the object needs to be repainted.
shouldRepaint: This method is called when a new instance of the class is provided.

class ShapePainter extends CustomPainter {
  @override
  void paint(Canvas canvas, Size size) {
    // TODO: implement paint
  }

  @override
  bool shouldRepaint(CustomPainter oldDelegate) {
    // TODO: implement shouldRepaint
    return null;
  }
}

Deep dive into paint method

The paint method has two parameters:

canvas
size

If we have a child specified inside the CustomPaint widget, then the canvas will have the same size as that. In our case, the canvas area will take the size of the entire Container.

The Canvas Area uses a coordinate system in order to located positions and they can be connected in various fashion in order to generate different custom shapes.

By default, the origin (0, 0) is located at the top-left corner of the canvas, and with respect to it all the drawings are done as the painter starts from the origin.

Conclusion

I believe you have enjoyed this first part of the series which should have given you a good insight into the small concepts of CustomPainter and the Canvas.

From the next article onwards, we will start painting on this canvas. And trust me you will love Flutter for this.

I also write articles on Medium and Codemagic Blog. You can follow me on Twitter and find some of my projects on GitHub. Also, don’t forget to check out my website.

Thank you for reading!