Hindsight API
Memory System for AI Agents — Temporal + Semantic + Entity Memory Architecture using PostgreSQL with pgvector.
Hindsight gives AI agents persistent memory that works like human memory: it stores facts, tracks entities and relationships, handles temporal reasoning ("what happened last spring?"), and forms opinions based on configurable disposition traits.
Installation
pip install hindsight-api
Quick Start
Run the Server
# Set your LLM provider
export HINDSIGHT_API_LLM_PROVIDER=openai
export HINDSIGHT_API_LLM_API_KEY=sk-xxxxxxxxxxxx
# Start the server (uses embedded PostgreSQL by default)
hindsight-api
The server starts at http://localhost:8888 with:
- REST API for memory operations
- MCP server at
/mcpfor tool-use integration
Use the Python API
from hindsight_api.engine.memory_engine import MemoryEngine
from hindsight_api.models import RequestContext
# Create and initialize the memory engine
memory = MemoryEngine()
await memory.initialize()
ctx = RequestContext()
# Create a memory bank for your agent
# (optional: banks are also auto-created on first retain)
await memory.ensure_bank_profile("my-assistant", request_context=ctx)
await memory.set_bank_mission(
"my-assistant",
"A helpful coding assistant",
request_context=ctx,
)
# Store a memory
await memory.retain_async(
bank_id="my-assistant",
content="The user prefers Python for data science projects",
request_context=ctx,
)
# Recall memories
results = await memory.recall_async(
bank_id="my-assistant",
query="What programming language does the user prefer?",
request_context=ctx,
)
# Reflect with reasoning
answer = await memory.reflect_async(
bank_id="my-assistant",
query="Should I recommend Python or R for this ML project?",
request_context=ctx,
)
CLI Options
hindsight-api --help
# Common options
hindsight-api --port 9000 # Custom port (default: 8888)
hindsight-api --host 127.0.0.1 # Bind to localhost only
hindsight-api --workers 4 # Multiple worker processes
hindsight-api --log-level debug # Verbose logging
Configuration
Configure via environment variables:
| Variable | Description | Default |
|---|---|---|
HINDSIGHT_API_DATABASE_URL |
PostgreSQL connection string | pg0 (embedded) |
HINDSIGHT_API_LLM_PROVIDER |
LLM provider, including openai, anthropic, gemini, groq, ollama, lmstudio, and github-copilot |
openai |
HINDSIGHT_API_LLM_API_KEY |
API key for providers that require one; unused by github-copilot |
- |
HINDSIGHT_API_LLM_MODEL |
Model name | gpt-4o-mini |
HINDSIGHT_API_HOST |
Server bind address | 0.0.0.0 |
HINDSIGHT_API_PORT |
Server port | 8888 |
Example with External PostgreSQL
export HINDSIGHT_API_DATABASE_URL=postgresql://user:pass@localhost:5432/hindsight
export HINDSIGHT_API_LLM_PROVIDER=groq
export HINDSIGHT_API_LLM_API_KEY=gsk_xxxxxxxxxxxx
hindsight-api
Docker
docker run -it --name hindsight --restart unless-stopped -p 8888:8888 \
-e HINDSIGHT_API_LLM_API_KEY=$OPENAI_API_KEY \
-v $HOME/.hindsight-docker:/home/hindsight/.pg0 \
ghcr.io/vectorize-io/hindsight:latest
MCP Server
For local MCP integration without running the full API server:
hindsight-local-mcp
This runs a stdio-based MCP server that can be used directly with MCP-compatible clients.
Key Features
- Multi-Strategy Retrieval (TEMPR) — Semantic, keyword, graph, and temporal search combined with RRF fusion
- Entity Graph — Automatic entity extraction and relationship tracking
- Temporal Reasoning — Native support for time-based queries
- Disposition Traits — Configurable skepticism, literalism, and empathy influence opinion formation
- Three Memory Types — World facts, experience facts (the bank's own actions), and observations
Documentation
Full documentation: https://hindsight.vectorize.io
License
- Apache 2.0
1 maintainer
Metadata
1 maintainer
Release files for hindsight-api 1.0.0
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