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Nicolò Boschi
11e624325b
* refactor(config): make HindsightConfig the only parser of HINDSIGHT_API_* env vars Thirty-odd call sites across the engine read HINDSIGHT_API_* out of os.environ themselves rather than off the resolved config. Two parsers for one variable is how the engine and the config drift apart: LLMProvider.from_env() had grown its own copies of the provider defaulting, the Gemini tier gating and the cache-affinity default, each carrying a comment asking the next reader not to let them disagree. Those comments are now unnecessary. Every fixed, server-level HINDSIGHT_API_* value is parsed in config.py and read as a field. Seventeen variables that worked but had no field got one, including the seven xai-oauth knobs; the five that carry secrets are registered in _CREDENTIAL_FIELDS so they stay off the API surface. Three fields become `str | None` — host, otel_service_name, xai_oauth_base_url. Each had a caller that needed to tell "the operator set this" from "this is the default" and was reading the environment a second time to find out. The default is now applied at the single point of use. requires_api_key moves to a new leaf module, engine/provider_auth.py. config.py needs it while building HindsightConfig and llm_wrapper needs the built config at import time to size its semaphores; that cycle is the reason the LLM factory had its own env parser to begin with. Both existing import paths still work. Two consequences worth knowing: * LLMProvider.from_env() now builds the full config, so an unrelated invalid setting surfaces there instead of being bypassed. The test that asserted the opposite asserts the new contract instead. * resolve_daemon_host_port() takes configured_host from its caller rather than reading HINDSIGHT_API_HOST itself. Value vocabularies are preserved exactly where they differed from _parse_boolean_env — ACCESS_LOG still accepts yes/on, XAI_OAUTH_DEBUG_HEADERS still never raises — so no working deployment turns into a start-up error. A new test walks the package AST and fails on any HINDSIGHT_API_* read outside config.py, with a short exemption list (standalone Alembic, pre-config bootstraps, the open-ended per-extension config namespaces) and a second test that fails when an exemption goes stale. tests/conftest.py resets the config cache per test: now that values are read off a cached config, a test's monkeypatch.setenv would otherwise land against whichever config the first test in that xdist worker happened to build. * fix(config): restore the DEFAULT_HOST import and keep .env authoritative Two defects from the previous commit, both caught by CI's server start rather than the suite. DEFAULT_HOST was dropped from main.py's imports during a rebase while `config.host or DEFAULT_HOST` stayed, so every entry point died with a NameError. No test caught it: each one hands _parse_cli_args a config whose host is already a string, so the fallback branch never evaluated. The new TestParseCliArgsHostDefault covers the unset-host path, and --help no longer advertises "default: None". The second is worse. HindsightConfig is cached process-wide on first build, and an entry point imports its whole module graph before main() reaches load_dotenv_for_entrypoint(). Modules reading the config at import scope (llm_wrapper sizes its semaphores there) therefore froze a config built before the .env was applied, and it stayed frozen — a discovered .env silently ignored, surfacing as "LLM API key is required" on a server that had always started. load_dotenv_for_entrypoint() now clears the cache after loading, and daemon.py's log path and poller.py's backpressure value resolve per call instead of at import.
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 |
LLM provider, including openai, anthropic, gemini, groq, ollama, lmstudio, and github-copilot |
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 -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