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Human-like memory for AI applications

Project description

recollect

Cognitive memory system for AI applications. Activation-based retrieval with time decay, spreading activation, and token-budgeted recall.

Install

pip install recollect                 # Includes Anthropic provider
pip install recollect[openai]         # Adds OpenAI/OpenAI-compatible provider support

Quick Start

import asyncio
from recollect import CognitiveMemory

async def main():
    memory = CognitiveMemory()
    await memory.connect()

    await memory.experience(
        "The team decided to migrate from Redis to PostgreSQL for persistence."
    )

    thoughts = await memory.think_about("database decisions", token_budget=500)
    for thought in thoughts:
        print(f"[{thought.activation:.2f}] {thought.content}")

    await memory.close()

asyncio.run(main())

API

Method Description
connect(db_url=None) Connect to PostgreSQL. Uses DATABASE_URL env var if no argument.
experience(content) Store a memory trace. LLM extracts entities, concepts, significance.
think_about(query, token_budget) Retrieve memories that fit within a token limit. Returns list[Thought].
consolidate(threshold=None) Merge and prune weak traces.
forget(trace_id) Remove a trace.
reinforce(trace_id, factor=1.1) Strengthen a trace.
facts(subject=None) List persona facts.
start_session(user_id) Begin a scoped session.
close() Disconnect and release resources.

Environment Variables

Variable Required Default Description
DATABASE_URL Yes postgresql://localhost:5432/memory_sdk PostgreSQL connection string.
ANTHROPIC_API_KEY For Anthropic provider -- Anthropic API key. SDK resolves automatically.
OPENAI_API_KEY For OpenAI provider -- OpenAI API key. Required by OpenAIProvider.
ANTHROPIC_MODEL No claude-haiku-4-5-20251001 Override default Anthropic extraction model.
OPENAI_MODEL No gpt-5-mini Override default OpenAI extraction model.
OLLAMA_MODEL No qwen3.5 Override default Ollama extraction model.
ANTHROPIC_BASE_URL No api.anthropic.com Override Anthropic API endpoint.
OPENAI_BASE_URL No api.openai.com Override OpenAI API endpoint.
OLLAMA_BASE_URL No http://localhost:11434/v1 Ollama API endpoint.
OPENAI_REASONING_EFFORT No low Reasoning effort for OpenAI structured output (low, medium, high).
OPENAI_STRUCTURED_MAX_TOKENS No 1024 Token cap for OpenAI structured output. Reasoning tokens consume this budget.
MEMORY_CONFIG No -- Path to custom TOML config file.
MEMORY_EXTRACTION_INSTRUCTIONS No -- Override extraction prompt instructions.

Configuration

Defaults ship in config.toml. Override by placing a memory.toml in your working directory, or set MEMORY_CONFIG to a custom path. Only include keys you want to change:

[memory]
decay_rate = 0.05

[retrieval]
max_retrievals = 10

[extraction]
max_tokens = 2048

Config sections

Section Controls Key parameters
[database] PostgreSQL connection url
[memory] Core memory model initial_strength, consolidation_threshold, decay_rate
[working_memory] Working memory capacity capacity (default 7, range 5-9)
[retrieval] Retrieval pipeline tuning max_retrievals, search_limit, selection_threshold
[extraction] LLM extraction max_tokens, max_concepts, max_relations, openai_reasoning_effort, openai_structured_max_tokens
[embedding] Local embedding model model, dimensions
[persona] Persona fact management auto_extract, confidence_threshold
[session] Session summaries summary_strength, summary_max_tokens

Full defaults: config.toml

Or pass a path directly:

from recollect.config import MemoryConfig

config = MemoryConfig(config_path=Path("./my-config.toml"))
memory = CognitiveMemory(config=config)

LLM Providers

Three providers behind the LLMProvider protocol. All share the same constructor signature: (model, api_key, base_url, defaults).

Anthropic (default)

from recollect.llm.anthropic import AnthropicProvider
from recollect.extraction import PatternExtractor

provider = AnthropicProvider()  # uses ANTHROPIC_API_KEY
extractor = PatternExtractor(provider)
memory = CognitiveMemory(extractor=extractor)

OpenAI

Requires pip install recollect[openai].

from recollect.llm.openai import OpenAIProvider

provider = OpenAIProvider()  # uses OPENAI_API_KEY

Ollama / LM Studio (OpenAI-compatible)

from recollect.llm.openai_compat import OpenAICompatProvider

# Ollama
provider = OpenAICompatProvider(
    model="qwen3.5",
    base_url="http://localhost:11434/v1",
)

# LM Studio
provider = OpenAICompatProvider(
    model="your-model",
    base_url="http://localhost:1234/v1",
)

Reasoning models

Models that use internal chain-of-thought (OpenAI o1/o3, Qwen3, DeepSeek-R1) consume thinking tokens from the max_tokens budget. If extraction returns empty responses, increase the token budget:

# memory.toml
[extraction]
max_tokens = 8192

The default is 4096, which provides sufficient headroom for most models.

Requirements

  • Python 3.12+
  • PostgreSQL 17 with pgvector
  • DATABASE_URL environment variable

License

MIT

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