ce45d301ce
* Load operation validator extension in main entry point Enable the operation validator extension to be loaded from environment configuration and passed to MemoryEngine, allowing pre/post operation hooks for usage metering, rate limiting, and audit logging. * Fix reflect background task authentication and add internal flag - Pass API key to background opinion storage task for proper auth - Add internal flag to RequestContext for tracking internal operations - Background opinion storage now authenticates correctly with tenant * Add api_key_id to RequestContext for usage tracking - Add api_key_id field to RequestContext to track which API key was used - Enables per-API-key usage analytics in the metering system * Fix HTTP error handling for authentication and validation errors - Add status_code parameter to ValidationResult and OperationValidationError - Convert OperationValidationError to HTTPException with proper status codes - Fix authentication errors to return 401 instead of raising internal errors - Re-raise HTTPException in exception handlers to prevent swallowing errors * Fix AuthenticationError handling in memory engine - Raise AuthenticationError from memory_engine._authenticate_tenant instead of HTTPException so unit tests pass - Add AuthenticationError handling in HTTP layer to convert to 401 responses - Fixes failing TestMemoryEngineTenantAuth tests * Add global exception handler for AuthenticationError Returns proper 401 status code for all authentication failures across all endpoints, not just the ones with explicit handlers. * Simplify exception handling: use global AuthenticationError handler - Remove redundant individual exception handlers - Add 'except AuthenticationError: raise' before generic Exception handlers to let global handler process auth errors uniformly * Refactor background tasks to use tenant_id instead of api_key This makes the core more generic - it passes tenant_id (which is extension-agnostic) rather than api_key (which is cloud-specific). - Add tenant_id field to RequestContext - Pass tenant_id instead of api_key to background tasks - Extensions can check internal=True with tenant_id to bypass normal auth * Fix exception propagation: include HTTPException in re-raise After cleanup of redundant exception handlers, 404 errors were returning 500 because HTTPException was caught by the generic except Exception handler. Fixed by combining AuthenticationError and HTTPException in the re-raise pattern. |
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| .. | ||
| hindsight_api | ||
| tests | ||
| pyproject.toml | ||
| README.md | ||
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 import MemoryEngine
# Create and initialize the memory engine
memory = MemoryEngine()
await memory.initialize()
# Create a memory bank for your agent
bank = await memory.create_memory_bank(
name="my-assistant",
background="A helpful coding assistant"
)
# Store a memory
await memory.retain(
memory_bank_id=bank.id,
content="The user prefers Python for data science projects"
)
# Recall memories
results = await memory.recall(
memory_bank_id=bank.id,
query="What programming language does the user prefer?"
)
# Reflect with reasoning
response = await memory.reflect(
memory_bank_id=bank.id,
query="Should I recommend Python or R for this ML project?"
)
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 |
openai, anthropic, gemini, groq, ollama, lmstudio |
openai |
HINDSIGHT_API_LLM_API_KEY |
API key for LLM provider | - |
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 --rm -it -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, bank actions, and formed opinions with confidence scores
Documentation
Full documentation: https://hindsight.vectorize.io
License
Apache 2.0