cognitive-memory 0.5.1

Biologically-inspired agent memory with decay, consolidation, and tiered storage

cognitive-memory

Biologically-inspired agent memory with decay, consolidation, and tiered storage.

Python SDK. v0.4.0 brings hybrid retrieval (BM25 + vector), power-law decay, graph expansion, LLM rerank, deferred conflict resolution, multi-tenancy, a pluggable LLMProvider, and a JSONL file adapter. Behavioural parity with the TypeScript SDK.

Install

pip install cognitive-memory

For the OpenAI extractor and embedder:

pip install "cognitive-memory[openai]"
export OPENAI_API_KEY=sk-...

Requires Python 3.10+.

Quick Start

from cognitive_memory import SyncCognitiveMemory

mem = SyncCognitiveMemory(embedder="hash")  # zero-dep, deterministic

mem.add("User is allergic to shellfish", category="core", importance=0.95)

response = mem.search("what allergies does the user have?")
for r in response.results:
    print(r.memory.content, f"(score: {r.combined_score:.2f})")

For async code, use CognitiveMemory directly (same API, await mem.add(...) / await mem.search(...)).

Production setup

from cognitive_memory import CognitiveMemory, JsonlFileAdapter

mem = CognitiveMemory(
    embedder="openai",                                  # OpenAIEmbeddings, reads OPENAI_API_KEY
    adapter=JsonlFileAdapter("/var/lib/myapp/mem.jsonl"),  # durable, single-process
    user_id="alice",                                    # multi-tenant scoping
)

await mem.extract_and_store(conversation_text, session_id="sess-1")
results = await mem.search("UI preferences", deep_recall=True, rerank=True)

extract_and_store(...) runs the LLM extractor; add(...) skips it for pre-extracted facts.

Custom LLM provider

The extractor and conflict-resolver talk to an LLMProvider interface — swap OpenAI for Anthropic, a local model, or a gateway:

from cognitive_memory import CognitiveMemory, LLMProvider

class MyProvider(LLMProvider):
    def complete(self, prompt: str, **kwargs) -> str:
        ...  # your model

mem = CognitiveMemory(llm=MyProvider())

Multi-tenancy

user_id namespaces every read and write. Two instances sharing an adapter are fully isolated.

alice = CognitiveMemory(adapter=shared, user_id="alice")
bob   = CognitiveMemory(adapter=shared, user_id="bob")

await alice.add("alice's secret")
# bob.search() never returns alice's memories

Adapters

• InMemoryAdapter — default, ephemeral
• JsonlFileAdapter — append-only event log, replay on startup
• Custom — implement MemoryAdapter from cognitive_memory.adapters
• Postgres (pgvector) — planned for 0.4.1

Migration

See MIGRATION.md for the 0.3.0 → 0.4.0 changes (all additive — existing code keeps working).

Docs

Full documentation, guides, concepts, and API reference: planetaryescape.github.io/cognitive-memory.

License

MIT