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Official Python Client for Condensate Memory System

Project description

Condensate Python SDK

Official Python client for Condensate — the open-source Agent Memory System.

PyPI License

Installation

pip install condensate

Requires Python 3.9+.

Quick Start

from condensate import CondensateClient

client = CondensateClient(
    base_url="http://localhost:8000",
    api_key="sk-your-api-key"
)

# Store a memory
client.store_memory(
    content="The team decided to use PostgreSQL for the primary store.",
    type="episodic",
    metadata={"source": "meeting", "project": "infra-v2"}
)

# Retrieve relevant memories
result = client.retrieve("What database did we choose?")
print(result["answer"])
print(result["sources"])   # list of episodic item IDs
print(result["strategy"])  # "recall" | "research" | "meta"

Configuration

Environment Variables

Set these before initialising the client, or pass them directly:

Variable Description Default
CONDENSATE_URL Base URL of your Condensate server http://localhost:8000
CONDENSATE_API_KEY API key (create one in the admin dashboard)
import os
from condensate import CondensateClient

client = CondensateClient(
    base_url=os.environ["CONDENSATE_URL"],
    api_key=os.environ["CONDENSATE_API_KEY"]
)

Connecting to a Remote Server

client = CondensateClient(
    base_url="https://memory.yourcompany.com",
    api_key="sk-prod-xxxx"
)

API Reference

store_memory(content, type, metadata)

Stores a raw episodic item and runs the full condensation pipeline (NER → entity extraction → assertion creation).

client.store_memory(
    content="Alice approved the Q3 roadmap.",
    type="episodic",          # episodic | note | event
    metadata={
        "source": "slack",
        "channel": "#product"
    }
)

retrieve(query)

Routes the query through the Memory Router (vector search + optional graph traversal) and returns a synthesised answer.

result = client.retrieve("What did Alice approve?")
# {
#   "answer": "Alice approved the Q3 roadmap.",
#   "sources": ["<uuid>", ...],
#   "strategy": "recall"
# }

add_item(item) (low-level)

Directly posts an EpisodicItemCreate payload to the v1 API.

from condensate import EpisodicItem
import uuid

client.add_item(EpisodicItem(
    project_id=str(uuid.uuid4()),
    source="api",
    text="User prefers dark mode."
))

CLI

The package ships a condensate CLI:

# Store a memory from stdin
echo "Deploy to prod on Friday" | condensate store --type episodic

# Retrieve
condensate retrieve "When are we deploying?"

Set CONDENSATE_URL and CONDENSATE_API_KEY in your shell before using the CLI.

Self-Hosting

See the main README for Docker Compose setup. The server must be running before the SDK can connect.

Development

cd sdks/python
python -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"
pytest

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