RCLL — self-hosted shared memory for a team of AI agents. Canonical repository; pushed out to github.com/Holetron-lab/fleet-memory. Fork of vectorize-io/hindsight (MIT).
https://rcll.ai
agent-fleetagent-memoryai-agentsclaude-codecoding-agentscross-agentcross-agent-memoryllmlocal-firstmcpmcp-servermemorymodel-context-protocolmulti-agentpersistent-memorypgvectorpostgresragself-hostedshared-memory
| .github/workflows | ||
| docker | ||
| helm | ||
| hindsight | ||
| hindsight-api | ||
| hindsight-cli | ||
| hindsight-clients | ||
| hindsight-control-plane | ||
| hindsight-dev | ||
| hindsight-docs | ||
| hindsight-integrations | ||
| scripts | ||
| .env.example | ||
| .gitignore | ||
| .python-version | ||
| .sesskey | ||
| openapi.json | ||
| PAPER_PERSONALITY.md | ||
| PAPER_RETRIEVAL.md | ||
| pyproject.toml | ||
| README.md | ||
| RELEASE.md | ||
| uv.lock | ||
Hindsight
Long-term memory for AI agents.
AI assistants forget everything between sessions. Hindsight fixes that with a memory system that handles temporal reasoning, entity connections, and personality-aware responses.
Why Hindsight?
- Temporal queries — "What did Alice do last spring?" requires more than vector search
- Entity connections — Knowing "Alice works at Google" + "Google is in Mountain View" = "Alice works in Mountain View"
- Agent opinions — Agents form and recall beliefs with confidence scores
- Personality — Big Five traits influence how agents process and respond to information
60-seconds step
1. Install the Hindsight All package (client + API)
pip install hindsight-all
2. Import your OpenAI API key
export OPENAI_API_KEY=xx
3. Run embedded server and client
import os
from hindsight import HindsightServer, HindsightClient
with HindsightServer(llm_provider="openai", llm_model="gpt-5.1-mini", llm_api_key=os.environ["OPENAI_API_KEY"]) as server:
client = HindsightClient(base_url=server.url)
client.put(agent_id="my-agent", content="Alice works at Google")
client.put(agent_id="my-agent", content="Bob prefers Python over JavaScript")
client.search(agent_id="my-agent", query="What does Alice do?")
client.think(agent_id="my-agent", query="Tell me about Alice")
Documentation
Full documentation: hindsight-docs
- Architecture — How ingestion, storage, and retrieval work
- Python Client — Full API reference
- API Reference — REST API endpoints
- Personality — Big Five traits and opinion formation
License
MIT