fleet-memory/hindsight-integrations/autogen
2026-04-01 17:51:46 +02:00
..
hindsight_autogen feat: add AutoGen integration for Hindsight (#719) 2026-04-01 17:48:11 +02:00
tests feat: add AutoGen integration for Hindsight (#719) 2026-04-01 17:48:11 +02:00
pyproject.toml release(autogen): v0.1.1 2026-04-01 17:51:46 +02:00
README.md feat: add AutoGen integration for Hindsight (#719) 2026-04-01 17:48:11 +02:00
uv.lock feat: add AutoGen integration for Hindsight (#719) 2026-04-01 17:48:11 +02:00

hindsight-autogen

AutoGen integration for Hindsight — persistent long-term memory for AI agents.

Provides FunctionTool instances that give AutoGen agents the ability to store, search, and synthesize memories across conversations.

Prerequisites

Installation

pip install hindsight-autogen autogen-agentchat "autogen-ext[openai]"

hindsight-autogen pulls in autogen-core and hindsight-client. You also need autogen-agentchat for AssistantAgent and autogen-ext[openai] for the OpenAI model client.

Quick Start

import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from hindsight_client import Hindsight
from hindsight_autogen import create_hindsight_tools

async def main():
    client = Hindsight(base_url="http://localhost:8888")
    await client.acreate_bank(bank_id="user-123")

    model_client = OpenAIChatCompletionClient(model="gpt-4o")
    tools = create_hindsight_tools(client=client, bank_id="user-123")

    agent = AssistantAgent(
        name="assistant",
        model_client=model_client,
        tools=tools,
    )

    # Store a memory
    result = await agent.run(task="Remember that I prefer dark mode")
    print(result.messages[-1].content)

    # Hindsight processes retained content asynchronously (fact extraction,
    # entity resolution, embeddings). A brief pause ensures memories are
    # searchable before the next recall. In production, this delay is only
    # needed when retain and recall happen back-to-back in the same script.
    await asyncio.sleep(3)

    # Recall it later
    result = await agent.run(task="What are my UI preferences?")
    print(result.messages[-1].content)

    # Clean up
    await client.aclose()
    await model_client.close()

asyncio.run(main())

The agent gets three tools:

  • hindsight_retain — Store information to long-term memory
  • hindsight_recall — Search long-term memory for relevant facts
  • hindsight_reflect — Synthesize a reasoned answer from memories

Selecting Tools

Include only the tools you need:

tools = create_hindsight_tools(
    client=client,
    bank_id="user-123",
    include_retain=True,
    include_recall=True,
    include_reflect=False,  # Omit reflect
)

Global Configuration

Instead of passing a client to every call, configure once:

from hindsight_autogen import configure, create_hindsight_tools

configure(
    hindsight_api_url="http://localhost:8888",
    api_key="your-api-key",       # Or set HINDSIGHT_API_KEY env var
    budget="mid",                  # Recall budget: low/mid/high
    max_tokens=4096,               # Max tokens for recall results
    tags=["env:prod"],             # Tags for stored memories
    recall_tags=["scope:global"],  # Tags to filter recall
    recall_tags_match="any",       # Tag match mode
)

# Now create tools without passing client
tools = create_hindsight_tools(bank_id="user-123")

Memory Scoping with Tags

Use tags to partition memories by topic, session, or user:

# Store memories tagged by source
tools = create_hindsight_tools(
    client=client,
    bank_id="user-123",
    tags=["source:chat", "session:abc"],
    recall_tags=["source:chat"],
    recall_tags_match="any",
)

Configuration Reference

Parameter Default Description
bank_id required Hindsight memory bank ID
client None Pre-configured Hindsight client
hindsight_api_url None API URL (used if no client provided)
api_key None API key (used if no client provided)
budget "mid" Recall/reflect budget level (low/mid/high)
max_tokens 4096 Maximum tokens for recall results
tags None Tags applied when storing memories
recall_tags None Tags to filter when searching
recall_tags_match "any" Tag matching mode (any/all/any_strict/all_strict)
retain_metadata None Default metadata dict for retain operations
retain_document_id None Default document_id for retain (groups/upserts memories)
recall_types None Fact types to filter (world, experience, opinion, observation)
recall_include_entities False Include entity information in recall results
reflect_context None Additional context for reflect operations
reflect_max_tokens None Max tokens for reflect results (defaults to max_tokens)
reflect_response_schema None JSON schema to constrain reflect output format
reflect_tags None Tags to filter memories used in reflect (defaults to recall_tags)
reflect_tags_match None Tag matching for reflect (defaults to recall_tags_match)
include_retain True Include the retain (store) tool
include_recall True Include the recall (search) tool
include_reflect True Include the reflect (synthesize) tool

Requirements

  • Python >= 3.10
  • autogen-core >= 0.4.0
  • hindsight-client >= 0.4.0

Documentation