rememhq 0.1.5

Reasoning memory layer for AI agents — Python SDK

remem Python SDK

This is the Python SDK for remem, providing a typed interface over the REST API.

Installation

pip install rememhq

Quick Start

from rememhq import Memory

memory = Memory(base_url="http://localhost:7474")

# Store a memory
await memory.store("User prefers Python", tags=["language"])

# Recall memories
results = await memory.recall("what language does the user prefer?")
for result in results:
    print(f"Content: {result.content}")
    print(f"Reasoning: {result.reasoning}")

Development

Prerequisites

• Python 3.11+
• pip or uv

Setup

cd sdk/python

# Install in development mode with dev dependencies
pip install -e ".[dev]"

Testing

# Run all tests
pytest tests/ -v

# Run with coverage
pytest tests/ --cov=rememhq

# Run specific test
pytest tests/test_memory.py -v

Code Quality

# Format code
black rememhq/ tests/

# Lint
ruff check rememhq/ tests/

# Type checking
mypy rememhq/

Building

# Build distribution
python -m build

# Install locally from build
pip install dist/rememhq-*.whl

Running the API Server

Before using the SDK, start the remem API server from the repository root:

cargo run -p rememhq-api -- --project default

The API will be available at http://localhost:7474 by default.

API Reference

Memory

store(content: str, tags: Optional[List[str]] = None, importance: Optional[float] = None) -> StoreResponse

Store a memory with optional tags and importance score.

response = await memory.store(
    "Production database is PostgreSQL 15",
    tags=["infra", "database"],
    importance=0.95
)

recall(query: str, limit: int = 8) -> List[RecallResult]

Retrieve memories most relevant to the query, with reasoning traces.

results = await memory.recall("what database are we using?", limit=8)
for result in results:
    print(f"Content: {result.content}")
    print(f"Score: {result.score}")
    print(f"Reasoning: {result.reasoning}")

search(query: str, limit: int = 10) -> List[SearchResult]

Full-text search over all memories.

results = await memory.search("deployment", limit=10)

update(memory_id: str, content: str) -> UpdateResponse

Update an existing memory's content.

forget(memory_id: str) -> ForgetResponse

Delete a memory.

consolidate(session_id: str) -> ConsolidateResponse

Consolidate session logs into durable facts.

Configuration

Configure the SDK via constructor parameters or environment variables:

from rememhq import Memory

memory = Memory(
    base_url="http://localhost:7474",
    project="my-agent",
    reasoning_model="claude-sonnet-4-6",
    timeout=30.0
)

Environment variables:

• REMEM_API_URL — API server URL (default: http://localhost:7474)
• REMEM_PROJECT — Project name (default: default)
• REMEM_REASONING_MODEL — Reasoning model (default: claude-sonnet-4-6)
• REMEM_TIMEOUT — Request timeout in seconds (default: 30)

Examples

Check the examples/ directory for complete working scripts.

Contributing

See CONTRIBUTING.md for guidelines on contributing to the Python SDK.

License

Apache License 2.0 — See LICENSE for details.