Level 7 of nine in Project Arc Rector - an agentic RAG stack built from free, self-hostable parts, one swappable level at a time. Level 6 was ingestion. This one is memory, whose trap is that three things all get called that: the chunks retrieved for this question, thrown away when it is answered; the session history, which lives until the visitor leaves; and durable facts, which outlive every session.
The dependency-free adapter is where the argument lives, and it is the part to read before the vendors:
_STOP = r"(?=[.!?,;]|\s+(?:and|but|so|because|then|while|which|what|who)\b|$)"
re.compile(r"\bi\s+(?:live|work|am based)\s+in\s+([\w\s'\-]{2,60}?)" + _STOP, re.I),
# add(): seven first-person patterns, exact-text dedupe, append. No reconciliation.
Repo: https://github.com/dev48v/arc-rector - 174 tests, no network, no model, no container. The page runs the extraction, the add/update/delete/noop decision, the scoping leak and the compaction in a dependency-free engine in your browser: https://dev48.infy.uk/arcrector/level7-memory.html
Run the canonical case against the real LocalMemory, six turns, printing what each stored:
"I live in Pune." -> ['I live in Pune']
"I moved to Goa." -> [] # no pattern matches
"Forget that I live in Goa." -> ['I live in Goa'] # the request IS the fact
store: ['My name is Devanshu', 'I live in Pune', 'I work with Java', 'I live in Goa']
search("where do I live") -> [('I live in Goa', 1.0018), ('I live in Pune', 1.0018)]
The sentence announcing the move stores nothing; the sentence asking to forget it is the only thing that ever writes Goa. Both locations then come back tied, Goa first purely because recency is the tie-break. Negation behaves the same way: "I don't use Windows" is appended beside "I use Windows", so a fact and its own negation are recalled together. That is the argument for the layer existing, and why use: mem0 is the default - Mem0 spends an LLM call choosing between ADD, UPDATE, DELETE and NOOP, and on these six turns the reconciling decision leaves 2 facts where the append-only store holds 5.
The defaults, as they ship: use: mem0, path: .arc_rector/memory, fallback_to_local: true. Mem0 is reconfigured onto local Ollama (llama3.2:3b, nomic-embed-text at 768 dims) and a local Qdrant collection so it needs no vendor key, with MEM0_TELEMETRY set before the import because the module reads it at load time. A hang is not an exception, so add runs under a 45-second wall clock on its own daemon thread per call - the first version used a single-worker pool, which head-of-line blocks: a timed-out call keeps running and later calls wait for it plus their own timeout. recall asks for top_k=3 and returns [] on any exception, because a Qdrant timeout is not the user's problem.
Where compaction's cost actually was
Squeeze ten turns into a 220-token budget and 51% of the text survives: 4 kept whole, 2 summarised by extraction, 4 dropped. Recall@3 over seven fact probes falls 1.00 to 0.43.
| budget | tokens kept | kept / summarised / dropped | recall@3 |
|---|---|---|---|
| 120 | 31% | 2 / 1 / 7 | 0.29 |
| 220 (default) | 51% | 4 / 2 / 4 | 0.43 |
| 320 | 78% | 5 / 4 / 1 | 1.00 |
I assumed the losses were the dropped turns. Two of the four are; the other two are turns still in the context. The Goa turn and the InXpress turn both survived as extractive summaries, and the summariser kept the preference sentence and threw the location away. A dashboard reporting turns retained would say 6 of 10 survived; recall says 3 of 7 facts did. Compression above 78% here is free and below it the curve falls off a cliff, so a system reporting its ratio without its recall drop is telling you half the story.
Next is Level 8, safety and guardrails. Nine levels, all free to self-host: https://dev48.infy.uk/arcrector.php
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