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+19
-2
@@ -2,10 +2,10 @@
|
||||
# Copy this file to .env and fill in your values
|
||||
|
||||
# LLM Configuration (Required)
|
||||
# Supported providers: openai, groq, ollama, gemini, anthropic, lmstudio, vertexai
|
||||
# Supported providers: openai, groq, ollama, gemini, anthropic, lmstudio, vertexai, minimax
|
||||
HINDSIGHT_API_LLM_PROVIDER=openai
|
||||
HINDSIGHT_API_LLM_API_KEY=your-api-key-here
|
||||
HINDSIGHT_API_LLM_MODEL=o3-mini
|
||||
HINDSIGHT_API_LLM_MODEL=gpt-4o-mini
|
||||
HINDSIGHT_API_LLM_BASE_URL=https://api.openai.com/v1
|
||||
|
||||
# Example: Anthropic Claude configuration
|
||||
@@ -20,6 +20,11 @@ HINDSIGHT_API_LLM_BASE_URL=https://api.openai.com/v1
|
||||
# HINDSIGHT_API_LLM_VERTEXAI_REGION=us-central1
|
||||
# HINDSIGHT_API_LLM_VERTEXAI_SERVICE_ACCOUNT_KEY=/path/to/service-account-key.json # Optional, uses ADC if not set
|
||||
|
||||
# Example: MiniMax configuration (1M context window)
|
||||
# HINDSIGHT_API_LLM_PROVIDER=minimax
|
||||
# HINDSIGHT_API_LLM_API_KEY=your-minimax-api-key
|
||||
# HINDSIGHT_API_LLM_MODEL=MiniMax-M2.7
|
||||
|
||||
# Example: LM Studio local configuration (Qwen 2.5 32B recommended)
|
||||
# HINDSIGHT_API_LLM_PROVIDER=lmstudio
|
||||
# HINDSIGHT_API_LLM_API_KEY=lmstudio
|
||||
@@ -31,10 +36,22 @@ HINDSIGHT_API_HOST=0.0.0.0
|
||||
HINDSIGHT_API_PORT=8888
|
||||
HINDSIGHT_API_LOG_LEVEL=info
|
||||
|
||||
# Base Path / Reverse Proxy Support (Optional)
|
||||
# Set these when deploying behind a reverse proxy with path-based routing
|
||||
# Example: To deploy at example.com/hindsight/, set both to "/hindsight"
|
||||
# HINDSIGHT_API_BASE_PATH=/hindsight
|
||||
# NEXT_PUBLIC_BASE_PATH=/hindsight
|
||||
|
||||
# Database (Optional - uses embedded pg0 by default)
|
||||
# HINDSIGHT_API_DATABASE_URL=postgresql://user:pass@host:5432/db
|
||||
# HINDSIGHT_API_DATABASE_SCHEMA=public # PostgreSQL schema name (default: public)
|
||||
|
||||
# Vector Extension (Optional - uses pgvector by default)
|
||||
# Options: "pgvector" (default), "vchord", "pgvectorscale" (DiskANN)
|
||||
# HINDSIGHT_API_VECTOR_EXTENSION=pgvector
|
||||
# For Azure PostgreSQL with DiskANN:
|
||||
# HINDSIGHT_API_VECTOR_EXTENSION=pgvectorscale # Auto-detects pg_diskann on Azure
|
||||
|
||||
# Embeddings Configuration (Optional - uses local by default)
|
||||
# Provider: "local" (default) or "tei" (HuggingFace Text Embeddings Inference)
|
||||
# HINDSIGHT_API_EMBEDDINGS_PROVIDER=local
|
||||
|
||||
@@ -0,0 +1,6 @@
|
||||
version: 2
|
||||
updates:
|
||||
- package-ecosystem: "github-actions"
|
||||
directory: "/"
|
||||
schedule:
|
||||
interval: "weekly"
|
||||
@@ -21,17 +21,20 @@ jobs:
|
||||
build:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- uses: actions/setup-node@v4
|
||||
- uses: actions/checkout@v6
|
||||
- uses: actions/setup-node@v6
|
||||
with:
|
||||
node-version: 20
|
||||
cache: npm
|
||||
cache-dependency-path: package-lock.json
|
||||
- uses: astral-sh/setup-uv@v4
|
||||
- uses: astral-sh/setup-uv@v7
|
||||
- run: npm ci --workspace=hindsight-docs
|
||||
- run: uv run generate-llms-full
|
||||
- run: npm run build --workspace=hindsight-docs
|
||||
- uses: actions/upload-pages-artifact@v3
|
||||
env:
|
||||
UMAMI_URL: https://analytics.hindsight.vectorize.io
|
||||
UMAMI_WEBSITE_ID: ${{ secrets.UMAMI_WEBSITE_ID }}
|
||||
- uses: actions/upload-pages-artifact@v4
|
||||
with:
|
||||
path: hindsight-docs/build
|
||||
deploy:
|
||||
|
||||
@@ -0,0 +1,99 @@
|
||||
name: Release Integration
|
||||
|
||||
on:
|
||||
push:
|
||||
tags:
|
||||
- 'integrations/**'
|
||||
|
||||
jobs:
|
||||
publish:
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
id-token: write # for PyPI trusted publishing
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v6
|
||||
|
||||
- name: Extract integration info
|
||||
id: info
|
||||
run: |
|
||||
# refs/tags/integrations/litellm/v0.1.0 → integration=litellm, version=0.1.0
|
||||
TAG="${GITHUB_REF#refs/tags/}"
|
||||
INTEGRATION=$(echo "$TAG" | cut -d'/' -f2)
|
||||
VERSION=$(echo "$TAG" | cut -d'/' -f3 | sed 's/^v//')
|
||||
echo "integration=$INTEGRATION" >> $GITHUB_OUTPUT
|
||||
echo "version=$VERSION" >> $GITHUB_OUTPUT
|
||||
echo "tag=$TAG" >> $GITHUB_OUTPUT
|
||||
echo "Integration: $INTEGRATION, Version: $VERSION"
|
||||
|
||||
- name: Detect integration type
|
||||
id: type
|
||||
run: |
|
||||
if [ -f "hindsight-integrations/${{ steps.info.outputs.integration }}/pyproject.toml" ]; then
|
||||
echo "type=python" >> $GITHUB_OUTPUT
|
||||
else
|
||||
echo "type=typescript" >> $GITHUB_OUTPUT
|
||||
fi
|
||||
|
||||
# ── Python integrations (litellm, pydantic-ai, crewai) ──────────────────
|
||||
|
||||
- name: Install uv
|
||||
if: steps.type.outputs.type == 'python'
|
||||
uses: astral-sh/setup-uv@v7
|
||||
with:
|
||||
enable-cache: true
|
||||
|
||||
- name: Set up Python
|
||||
if: steps.type.outputs.type == 'python'
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version-file: ".python-version"
|
||||
|
||||
- name: Build Python package
|
||||
if: steps.type.outputs.type == 'python'
|
||||
working-directory: ./hindsight-integrations/${{ steps.info.outputs.integration }}
|
||||
run: uv build --out-dir dist
|
||||
|
||||
- name: Publish Python package to PyPI
|
||||
if: steps.type.outputs.type == 'python'
|
||||
uses: pypa/gh-action-pypi-publish@release/v1
|
||||
with:
|
||||
packages-dir: ./hindsight-integrations/${{ steps.info.outputs.integration }}/dist
|
||||
skip-existing: true
|
||||
|
||||
# ── TypeScript integrations (ai-sdk, chat, openclaw) ────────────────────
|
||||
|
||||
- name: Set up Node.js
|
||||
if: steps.type.outputs.type == 'typescript'
|
||||
uses: actions/setup-node@v6
|
||||
with:
|
||||
node-version: '22'
|
||||
registry-url: 'https://registry.npmjs.org'
|
||||
|
||||
- name: Install dependencies
|
||||
if: steps.type.outputs.type == 'typescript'
|
||||
working-directory: ./hindsight-integrations/${{ steps.info.outputs.integration }}
|
||||
run: npm ci
|
||||
|
||||
- name: Build TypeScript package
|
||||
if: steps.type.outputs.type == 'typescript'
|
||||
working-directory: ./hindsight-integrations/${{ steps.info.outputs.integration }}
|
||||
run: npm run build
|
||||
|
||||
- name: Publish TypeScript package to npm
|
||||
if: steps.type.outputs.type == 'typescript'
|
||||
working-directory: ./hindsight-integrations/${{ steps.info.outputs.integration }}
|
||||
run: |
|
||||
set +e
|
||||
OUTPUT=$(npm publish --access public 2>&1)
|
||||
EXIT_CODE=$?
|
||||
echo "$OUTPUT"
|
||||
if [ $EXIT_CODE -ne 0 ]; then
|
||||
if echo "$OUTPUT" | grep -q "cannot publish over"; then
|
||||
echo "Package version already published, skipping..."
|
||||
exit 0
|
||||
fi
|
||||
exit $EXIT_CODE
|
||||
fi
|
||||
env:
|
||||
NODE_AUTH_TOKEN: ${{ secrets.NPM_TOKEN }}
|
||||
+61
-156
@@ -13,15 +13,15 @@ jobs:
|
||||
id-token: write
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- uses: actions/checkout@v6
|
||||
|
||||
- name: Install uv
|
||||
uses: astral-sh/setup-uv@v5
|
||||
uses: astral-sh/setup-uv@v7
|
||||
with:
|
||||
enable-cache: true
|
||||
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v5
|
||||
uses: actions/setup-python@v6
|
||||
with:
|
||||
python-version-file: ".python-version"
|
||||
|
||||
@@ -30,29 +30,39 @@ jobs:
|
||||
working-directory: ./hindsight-clients/python
|
||||
run: uv build --out-dir dist
|
||||
|
||||
- name: Build hindsight-api-slim
|
||||
working-directory: ./hindsight-api-slim
|
||||
run: uv build --out-dir dist
|
||||
|
||||
- name: Build hindsight-api
|
||||
working-directory: ./hindsight-api
|
||||
run: uv build --out-dir dist
|
||||
|
||||
- name: Build hindsight-all
|
||||
working-directory: ./hindsight
|
||||
working-directory: ./hindsight-all
|
||||
run: uv build --out-dir dist
|
||||
|
||||
- name: Build hindsight-litellm
|
||||
working-directory: ./hindsight-integrations/litellm
|
||||
- name: Build hindsight-all-slim
|
||||
working-directory: ./hindsight-all-slim
|
||||
run: uv build --out-dir dist
|
||||
|
||||
- name: Build hindsight-embed
|
||||
working-directory: ./hindsight-embed
|
||||
run: uv build --out-dir dist
|
||||
|
||||
# Publish in order (client and api first, then hindsight-all which depends on them)
|
||||
# Publish in order (client and api-slim first, then api/all wrappers which depend on them)
|
||||
- name: Publish hindsight-client to PyPI
|
||||
uses: pypa/gh-action-pypi-publish@release/v1
|
||||
with:
|
||||
packages-dir: ./hindsight-clients/python/dist
|
||||
skip-existing: true
|
||||
|
||||
- name: Publish hindsight-api-slim to PyPI
|
||||
uses: pypa/gh-action-pypi-publish@release/v1
|
||||
with:
|
||||
packages-dir: ./hindsight-api-slim/dist
|
||||
skip-existing: true
|
||||
|
||||
- name: Publish hindsight-api to PyPI
|
||||
uses: pypa/gh-action-pypi-publish@release/v1
|
||||
with:
|
||||
@@ -62,13 +72,13 @@ jobs:
|
||||
- name: Publish hindsight-all to PyPI
|
||||
uses: pypa/gh-action-pypi-publish@release/v1
|
||||
with:
|
||||
packages-dir: ./hindsight/dist
|
||||
packages-dir: ./hindsight-all/dist
|
||||
skip-existing: true
|
||||
|
||||
- name: Publish hindsight-litellm to PyPI
|
||||
- name: Publish hindsight-all-slim to PyPI
|
||||
uses: pypa/gh-action-pypi-publish@release/v1
|
||||
with:
|
||||
packages-dir: ./hindsight-integrations/litellm/dist
|
||||
packages-dir: ./hindsight-all-slim/dist
|
||||
skip-existing: true
|
||||
|
||||
- name: Publish hindsight-embed to PyPI
|
||||
@@ -79,14 +89,15 @@ jobs:
|
||||
|
||||
# Upload artifacts for GitHub release
|
||||
- name: Upload artifacts
|
||||
uses: actions/upload-artifact@v4
|
||||
uses: actions/upload-artifact@v7
|
||||
with:
|
||||
name: python-packages
|
||||
path: |
|
||||
hindsight-clients/python/dist/*
|
||||
hindsight-api-slim/dist/*
|
||||
hindsight-api/dist/*
|
||||
hindsight/dist/*
|
||||
hindsight-integrations/litellm/dist/*
|
||||
hindsight-all/dist/*
|
||||
hindsight-all-slim/dist/*
|
||||
hindsight-embed/dist/*
|
||||
retention-days: 1
|
||||
|
||||
@@ -95,10 +106,10 @@ jobs:
|
||||
environment: npm
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- uses: actions/checkout@v6
|
||||
|
||||
- name: Set up Node.js
|
||||
uses: actions/setup-node@v4
|
||||
uses: actions/setup-node@v6
|
||||
with:
|
||||
node-version: '20'
|
||||
registry-url: 'https://registry.npmjs.org'
|
||||
@@ -133,119 +144,21 @@ jobs:
|
||||
run: npm pack
|
||||
|
||||
- name: Upload artifacts
|
||||
uses: actions/upload-artifact@v4
|
||||
uses: actions/upload-artifact@v7
|
||||
with:
|
||||
name: typescript-client
|
||||
path: hindsight-clients/typescript/*.tgz
|
||||
retention-days: 1
|
||||
|
||||
release-openclaw-integration:
|
||||
runs-on: ubuntu-latest
|
||||
environment: npm
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Set up Node.js
|
||||
uses: actions/setup-node@v4
|
||||
with:
|
||||
node-version: '22'
|
||||
registry-url: 'https://registry.npmjs.org'
|
||||
|
||||
- name: Install dependencies
|
||||
working-directory: ./hindsight-integrations/openclaw
|
||||
run: npm ci
|
||||
|
||||
- name: Build
|
||||
working-directory: ./hindsight-integrations/openclaw
|
||||
run: npm run build
|
||||
|
||||
- name: Publish to npm
|
||||
working-directory: ./hindsight-integrations/openclaw
|
||||
run: |
|
||||
set +e
|
||||
OUTPUT=$(npm publish --access public 2>&1)
|
||||
EXIT_CODE=$?
|
||||
echo "$OUTPUT"
|
||||
if [ $EXIT_CODE -ne 0 ]; then
|
||||
if echo "$OUTPUT" | grep -q "cannot publish over"; then
|
||||
echo "Package version already published, skipping..."
|
||||
exit 0
|
||||
fi
|
||||
exit $EXIT_CODE
|
||||
fi
|
||||
env:
|
||||
NODE_AUTH_TOKEN: ${{ secrets.NPM_TOKEN }}
|
||||
|
||||
- name: Pack for GitHub release
|
||||
working-directory: ./hindsight-integrations/openclaw
|
||||
run: npm pack
|
||||
|
||||
- name: Upload artifacts
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: openclaw-integration
|
||||
path: hindsight-integrations/openclaw/*.tgz
|
||||
retention-days: 1
|
||||
|
||||
release-ai-sdk-integration:
|
||||
runs-on: ubuntu-latest
|
||||
environment: npm
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Set up Node.js
|
||||
uses: actions/setup-node@v4
|
||||
with:
|
||||
node-version: '22'
|
||||
registry-url: 'https://registry.npmjs.org'
|
||||
|
||||
- name: Install dependencies
|
||||
working-directory: ./hindsight-integrations/ai-sdk
|
||||
run: npm ci
|
||||
|
||||
- name: Build
|
||||
working-directory: ./hindsight-integrations/ai-sdk
|
||||
run: npm run build
|
||||
|
||||
- name: Publish to npm
|
||||
working-directory: ./hindsight-integrations/ai-sdk
|
||||
run: |
|
||||
set +e
|
||||
OUTPUT=$(npm publish --access public 2>&1)
|
||||
EXIT_CODE=$?
|
||||
echo "$OUTPUT"
|
||||
if [ $EXIT_CODE -ne 0 ]; then
|
||||
if echo "$OUTPUT" | grep -q "cannot publish over"; then
|
||||
echo "Package version already published, skipping..."
|
||||
exit 0
|
||||
fi
|
||||
exit $EXIT_CODE
|
||||
fi
|
||||
env:
|
||||
NODE_AUTH_TOKEN: ${{ secrets.NPM_TOKEN }}
|
||||
|
||||
- name: Pack for GitHub release
|
||||
working-directory: ./hindsight-integrations/ai-sdk
|
||||
run: npm pack
|
||||
|
||||
- name: Upload artifacts
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: ai-sdk-integration
|
||||
path: hindsight-integrations/ai-sdk/*.tgz
|
||||
retention-days: 1
|
||||
|
||||
release-control-plane:
|
||||
runs-on: ubuntu-latest
|
||||
environment: npm
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- uses: actions/checkout@v6
|
||||
|
||||
- name: Set up Node.js
|
||||
uses: actions/setup-node@v4
|
||||
uses: actions/setup-node@v6
|
||||
with:
|
||||
node-version: '20'
|
||||
registry-url: 'https://registry.npmjs.org'
|
||||
@@ -268,11 +181,14 @@ jobs:
|
||||
- name: Build
|
||||
run: npm run build --workspace=hindsight-control-plane
|
||||
|
||||
- name: Verify standalone build
|
||||
run: test -f hindsight-control-plane/standalone/server.js || (echo 'standalone/server.js missing - build failed' && exit 1)
|
||||
|
||||
- name: Publish to npm
|
||||
working-directory: ./hindsight-control-plane
|
||||
run: |
|
||||
set +e
|
||||
OUTPUT=$(npm publish --access public 2>&1)
|
||||
OUTPUT=$(npm publish --access public --ignore-scripts 2>&1)
|
||||
EXIT_CODE=$?
|
||||
echo "$OUTPUT"
|
||||
if [ $EXIT_CODE -ne 0 ]; then
|
||||
@@ -290,7 +206,7 @@ jobs:
|
||||
run: npm pack
|
||||
|
||||
- name: Upload artifacts
|
||||
uses: actions/upload-artifact@v4
|
||||
uses: actions/upload-artifact@v7
|
||||
with:
|
||||
name: control-plane
|
||||
path: hindsight-control-plane/*.tgz
|
||||
@@ -313,9 +229,13 @@ jobs:
|
||||
target: aarch64-apple-darwin
|
||||
artifact_name: hindsight
|
||||
asset_name: hindsight-darwin-arm64
|
||||
- os: ubuntu-24.04-arm
|
||||
target: aarch64-unknown-linux-gnu
|
||||
artifact_name: hindsight
|
||||
asset_name: hindsight-linux-arm64
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- uses: actions/checkout@v6
|
||||
|
||||
- name: Install Rust
|
||||
uses: dtolnay/rust-toolchain@stable
|
||||
@@ -333,7 +253,7 @@ jobs:
|
||||
chmod +x artifacts/${{ matrix.asset_name }}
|
||||
|
||||
- name: Upload artifacts
|
||||
uses: actions/upload-artifact@v4
|
||||
uses: actions/upload-artifact@v7
|
||||
with:
|
||||
name: rust-cli-${{ matrix.asset_name }}
|
||||
path: artifacts/${{ matrix.asset_name }}
|
||||
@@ -374,7 +294,7 @@ jobs:
|
||||
PRELOAD_ML_MODELS=false
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- uses: actions/checkout@v6
|
||||
|
||||
- name: Free Disk Space
|
||||
uses: jlumbroso/free-disk-space@main
|
||||
@@ -388,13 +308,13 @@ jobs:
|
||||
swap-storage: true
|
||||
|
||||
- name: Set up QEMU
|
||||
uses: docker/setup-qemu-action@v3
|
||||
uses: docker/setup-qemu-action@v4
|
||||
|
||||
- name: Set up Docker Buildx
|
||||
uses: docker/setup-buildx-action@v3
|
||||
uses: docker/setup-buildx-action@v4
|
||||
|
||||
- name: Log in to GitHub Container Registry
|
||||
uses: docker/login-action@v3
|
||||
uses: docker/login-action@v4
|
||||
with:
|
||||
registry: ghcr.io
|
||||
username: ${{ github.actor }}
|
||||
@@ -406,7 +326,7 @@ jobs:
|
||||
|
||||
- name: Extract metadata for release tags
|
||||
id: meta
|
||||
uses: docker/metadata-action@v5
|
||||
uses: docker/metadata-action@v6
|
||||
with:
|
||||
images: ghcr.io/${{ github.repository_owner }}/${{ matrix.image_name }}
|
||||
flavor: |
|
||||
@@ -422,7 +342,7 @@ jobs:
|
||||
# # Step 1: Build for local testing (single platform, no push)
|
||||
# # This creates an identical image to what will be released, just for one platform
|
||||
# - name: Build image for testing
|
||||
# uses: docker/build-push-action@v6
|
||||
# uses: docker/build-push-action@v7
|
||||
# with:
|
||||
# context: .
|
||||
# file: docker/standalone/Dockerfile
|
||||
@@ -441,7 +361,7 @@ jobs:
|
||||
|
||||
# Build multi-platform and push to release tags
|
||||
- name: Build and push release images
|
||||
uses: docker/build-push-action@v6
|
||||
uses: docker/build-push-action@v7
|
||||
with:
|
||||
context: .
|
||||
file: docker/standalone/Dockerfile
|
||||
@@ -459,7 +379,7 @@ jobs:
|
||||
packages: write
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- uses: actions/checkout@v6
|
||||
|
||||
- name: Install Helm
|
||||
uses: azure/setup-helm@v4
|
||||
@@ -479,7 +399,7 @@ jobs:
|
||||
run: helm push helm-packages/*.tgz oci://ghcr.io/${{ github.repository_owner }}/charts
|
||||
|
||||
- name: Upload artifacts
|
||||
uses: actions/upload-artifact@v4
|
||||
uses: actions/upload-artifact@v7
|
||||
with:
|
||||
name: helm-chart
|
||||
path: helm-packages/*.tgz
|
||||
@@ -487,67 +407,55 @@ jobs:
|
||||
|
||||
create-github-release:
|
||||
runs-on: ubuntu-latest
|
||||
needs: [release-python-packages, release-typescript-client, release-openclaw-integration, release-ai-sdk-integration, release-control-plane, release-rust-cli, release-docker-images, release-helm-chart]
|
||||
needs: [release-python-packages, release-typescript-client, release-control-plane, release-rust-cli, release-docker-images, release-helm-chart]
|
||||
permissions:
|
||||
contents: write
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- uses: actions/checkout@v6
|
||||
|
||||
- name: Extract version from tag
|
||||
id: get_version
|
||||
run: echo "VERSION=${GITHUB_REF#refs/tags/v}" >> $GITHUB_OUTPUT
|
||||
|
||||
- name: Download Python packages
|
||||
uses: actions/download-artifact@v4
|
||||
uses: actions/download-artifact@v8
|
||||
with:
|
||||
name: python-packages
|
||||
path: ./artifacts/python-packages
|
||||
|
||||
- name: Download TypeScript client
|
||||
uses: actions/download-artifact@v4
|
||||
uses: actions/download-artifact@v8
|
||||
with:
|
||||
name: typescript-client
|
||||
path: ./artifacts/typescript-client
|
||||
|
||||
- name: Download OpenClaw Integration
|
||||
uses: actions/download-artifact@v4
|
||||
with:
|
||||
name: openclaw-integration
|
||||
path: ./artifacts/openclaw-integration
|
||||
|
||||
- name: Download AI SDK Integration
|
||||
uses: actions/download-artifact@v4
|
||||
with:
|
||||
name: ai-sdk-integration
|
||||
path: ./artifacts/ai-sdk-integration
|
||||
|
||||
- name: Download Control Plane
|
||||
uses: actions/download-artifact@v4
|
||||
uses: actions/download-artifact@v8
|
||||
with:
|
||||
name: control-plane
|
||||
path: ./artifacts/control-plane
|
||||
|
||||
- name: Download Rust CLI (Linux)
|
||||
uses: actions/download-artifact@v4
|
||||
uses: actions/download-artifact@v8
|
||||
with:
|
||||
name: rust-cli-hindsight-linux-amd64
|
||||
path: ./artifacts/rust-cli-linux
|
||||
|
||||
- name: Download Rust CLI (macOS Intel)
|
||||
uses: actions/download-artifact@v4
|
||||
uses: actions/download-artifact@v8
|
||||
with:
|
||||
name: rust-cli-hindsight-darwin-amd64
|
||||
path: ./artifacts/rust-cli-darwin-amd64
|
||||
|
||||
- name: Download Rust CLI (macOS ARM)
|
||||
uses: actions/download-artifact@v4
|
||||
uses: actions/download-artifact@v8
|
||||
with:
|
||||
name: rust-cli-hindsight-darwin-arm64
|
||||
path: ./artifacts/rust-cli-darwin-arm64
|
||||
|
||||
- name: Download Helm chart
|
||||
uses: actions/download-artifact@v4
|
||||
uses: actions/download-artifact@v8
|
||||
with:
|
||||
name: helm-chart
|
||||
path: ./artifacts/helm-chart
|
||||
@@ -557,16 +465,13 @@ jobs:
|
||||
mkdir -p release-assets
|
||||
# Python packages
|
||||
cp artifacts/python-packages/hindsight-clients/python/dist/* release-assets/ || true
|
||||
cp artifacts/python-packages/hindsight-api-slim/dist/* release-assets/ || true
|
||||
cp artifacts/python-packages/hindsight-api/dist/* release-assets/ || true
|
||||
cp artifacts/python-packages/hindsight/dist/* release-assets/ || true
|
||||
cp artifacts/python-packages/hindsight-integrations/litellm/dist/* release-assets/ || true
|
||||
cp artifacts/python-packages/hindsight-all/dist/* release-assets/ || true
|
||||
cp artifacts/python-packages/hindsight-all-slim/dist/* release-assets/ || true
|
||||
cp artifacts/python-packages/hindsight-embed/dist/* release-assets/ || true
|
||||
# TypeScript client
|
||||
cp artifacts/typescript-client/*.tgz release-assets/ || true
|
||||
# OpenClaw Integration
|
||||
cp artifacts/openclaw-integration/*.tgz release-assets/ || true
|
||||
# AI SDK Integration
|
||||
cp artifacts/ai-sdk-integration/*.tgz release-assets/ || true
|
||||
# Control Plane
|
||||
cp artifacts/control-plane/*.tgz release-assets/ || true
|
||||
# Rust CLI binaries
|
||||
|
||||
+903
-222
File diff suppressed because it is too large
Load Diff
@@ -46,6 +46,7 @@ hindsight-docs/static/llms-full.txt
|
||||
hindsight-dev/benchmarks/locomo/results/
|
||||
hindsight-dev/benchmarks/longmemeval/results/
|
||||
hindsight-dev/benchmarks/consolidation/results/
|
||||
hindsight-dev/benchmarks/perf/results/
|
||||
benchmarks/results/
|
||||
hindsight-cli/target
|
||||
hindsight-clients/rust/target
|
||||
|
||||
@@ -17,20 +17,20 @@ Hindsight is an agent memory system that provides long-term memory for AI agents
|
||||
./scripts/dev/start-api.sh
|
||||
|
||||
# Run all tests (parallelized with pytest-xdist)
|
||||
cd hindsight-api && uv run pytest tests/
|
||||
cd hindsight-api-slim && uv run pytest tests/
|
||||
|
||||
# Run specific test file
|
||||
cd hindsight-api && uv run pytest tests/test_http_api_integration.py -v
|
||||
cd hindsight-api-slim && uv run pytest tests/test_http_api_integration.py -v
|
||||
|
||||
# Run single test function
|
||||
cd hindsight-api && uv run pytest tests/test_retain.py::test_retain_simple -v
|
||||
cd hindsight-api-slim && uv run pytest tests/test_retain.py::test_retain_simple -v
|
||||
|
||||
# Lint and format
|
||||
cd hindsight-api && uv run ruff check .
|
||||
cd hindsight-api && uv run ruff format .
|
||||
cd hindsight-api-slim && uv run ruff check .
|
||||
cd hindsight-api-slim && uv run ruff format .
|
||||
|
||||
# Type checking (uses ty - extremely fast type checker from Astral)
|
||||
cd hindsight-api && uv run ty check hindsight_api/
|
||||
cd hindsight-api-slim && uv run ty check hindsight_api/
|
||||
```
|
||||
|
||||
### Control Plane (Next.js)
|
||||
@@ -57,15 +57,22 @@ cd hindsight-control-plane && npm run dev
|
||||
|
||||
### Benchmarks
|
||||
```bash
|
||||
# Accuracy benchmarks
|
||||
./scripts/benchmarks/run-longmemeval.sh
|
||||
./scripts/benchmarks/run-locomo.sh
|
||||
|
||||
# Performance benchmarks
|
||||
./scripts/benchmarks/run-consolidation.sh
|
||||
./scripts/benchmarks/run-retain-perf.sh --document <path> # Requires API server running
|
||||
|
||||
# Results viewer
|
||||
./scripts/benchmarks/start-visualizer.sh # View results at localhost:8001
|
||||
```
|
||||
|
||||
## Architecture
|
||||
|
||||
### Monorepo Structure
|
||||
- **hindsight-api/**: Core FastAPI server with memory engine (Python, uv)
|
||||
- **hindsight-api-slim/**: Core FastAPI server with memory engine (Python, uv)
|
||||
- **hindsight/**: Embedded Python bundle (hindsight-all package)
|
||||
- **hindsight-control-plane/**: Admin UI (Next.js, npm)
|
||||
- **hindsight-cli/**: CLI tool (Rust, cargo, uses progenitor for API client)
|
||||
@@ -74,9 +81,9 @@ cd hindsight-control-plane && npm run dev
|
||||
- **hindsight-integrations/**: Framework integrations (LiteLLM, OpenAI)
|
||||
- **hindsight-dev/**: Development tools and benchmarks
|
||||
|
||||
### Core Engine (hindsight-api/hindsight_api/engine/)
|
||||
### Core Engine (hindsight-api-slim/hindsight_api/engine/)
|
||||
- `memory_engine.py`: Main orchestrator (~170KB) for retain/recall/reflect operations
|
||||
- `llm_wrapper.py`: LLM abstraction supporting OpenAI, Anthropic, Gemini, Groq, Ollama, LM Studio
|
||||
- `llm_wrapper.py`: LLM abstraction supporting OpenAI, Anthropic, Gemini, Groq, MiniMax, Ollama, LM Studio
|
||||
- `embeddings.py`: Embedding generation (local sentence-transformers or TEI)
|
||||
- `cross_encoder.py`: Reranking (local or TEI)
|
||||
- `entity_resolver.py`: Entity extraction and normalization
|
||||
@@ -94,7 +101,7 @@ cd hindsight-control-plane && npm run dev
|
||||
- `fusion.py`: Reciprocal rank fusion for combining results
|
||||
- `reranking.py`: Cross-encoder reranking
|
||||
|
||||
### API Layer (hindsight-api/hindsight_api/api/)
|
||||
### API Layer (hindsight-api-slim/hindsight_api/api/)
|
||||
- `http.py`: FastAPI HTTP routers (~80KB) for all REST endpoints
|
||||
- `mcp.py`: Model Context Protocol server implementation
|
||||
|
||||
@@ -104,13 +111,13 @@ Main operations:
|
||||
- **Reflect**: Disposition-aware reasoning using memories and mental models.
|
||||
|
||||
### Database
|
||||
PostgreSQL with pgvector. Schema managed via Alembic migrations in `hindsight-api/hindsight_api/alembic/`. Migrations run automatically on API startup.
|
||||
PostgreSQL with pgvector. Schema managed via Alembic migrations in `hindsight-api-slim/hindsight_api/alembic/`. Migrations run automatically on API startup.
|
||||
|
||||
Key tables: `banks`, `memory_units`, `documents`, `entities`, `entity_links`
|
||||
|
||||
### Adding Database Migrations
|
||||
|
||||
1. **Create a new migration file** in `hindsight-api/hindsight_api/alembic/versions/`:
|
||||
1. **Create a new migration file** in `hindsight-api-slim/hindsight_api/alembic/versions/`:
|
||||
- File name format: `<revision_id>_<description>.py` (e.g., `f1a2b3c4d5e6_add_new_index.py`)
|
||||
- Use a unique hex revision ID (12 chars)
|
||||
- Set `down_revision` to the previous migration's revision ID
|
||||
@@ -147,7 +154,7 @@ Key tables: `banks`, `memory_units`, `documents`, `entities`, `entity_links`
|
||||
|
||||
3. **Run migrations locally**:
|
||||
```bash
|
||||
# Set database URL and run migrations
|
||||
# Set database URL and run migrations for the base schema plus all tenants
|
||||
uv run hindsight-admin run-db-migration
|
||||
|
||||
# Run on a specific tenant schema
|
||||
@@ -238,26 +245,61 @@ def process(data: UserData) -> str:
|
||||
|
||||
### Adding New API Configuration Flags
|
||||
|
||||
When adding a new environment variable configuration:
|
||||
Configuration follows a hierarchical system: **Global (env vars) → Tenant (via extension) → Bank (database)**.
|
||||
|
||||
1. **config.py** (`hindsight-api/hindsight_api/config.py`):
|
||||
- Add `ENV_*` constant for the environment variable name
|
||||
Fields must be categorized as either **hierarchical** (can be overridden per-tenant/bank) or **static** (server-level only).
|
||||
|
||||
#### Adding a New Configuration Field
|
||||
|
||||
1. **config.py** (`hindsight-api-slim/hindsight_api/config.py`):
|
||||
- Add `ENV_*` constant for the environment variable name (e.g., `ENV_MY_SETTING = "HINDSIGHT_API_MY_SETTING"`)
|
||||
- Add `DEFAULT_*` constant for the default value
|
||||
- Add field to `HindsightConfig` dataclass
|
||||
- Add field to `HindsightConfig` dataclass with type annotation
|
||||
- **Mark as hierarchical or static** by adding to `_HIERARCHICAL_FIELDS` set (hierarchical) or leaving it out (static)
|
||||
- Add initialization in `from_env()` method
|
||||
|
||||
2. **main.py** (`hindsight-api/hindsight_api/main.py`):
|
||||
```python
|
||||
# Hierarchical field (can be overridden per-bank)
|
||||
_HIERARCHICAL_FIELDS = {
|
||||
...,
|
||||
"my_setting", # Add here for hierarchical
|
||||
}
|
||||
|
||||
# Static field - just don't add to _HIERARCHICAL_FIELDS
|
||||
```
|
||||
|
||||
2. **main.py** (`hindsight-api-slim/hindsight_api/main.py`):
|
||||
- Add field to the manual `HindsightConfig()` constructor call (search for "CLI override")
|
||||
|
||||
3. **Use the config** in code:
|
||||
3. **Use hierarchical config in MemoryEngine**:
|
||||
```python
|
||||
# Config is resolved automatically per bank via ConfigResolver
|
||||
config_dict = await self._config_resolver.get_bank_config(bank_id, context)
|
||||
value = config_dict["my_setting"]
|
||||
```
|
||||
|
||||
4. **Use static config** (non-hierarchical):
|
||||
```python
|
||||
from ...config import get_config
|
||||
config = get_config()
|
||||
value = config.your_new_field
|
||||
value = config.my_static_field
|
||||
```
|
||||
|
||||
4. **Documentation** (`hindsight-docs/docs/developer/configuration.md`):
|
||||
5. **Documentation** (`hindsight-docs/docs/developer/configuration.md`):
|
||||
- Add to appropriate section table with Variable, Description, Default
|
||||
- Mark if it's hierarchical (can be overridden per-bank)
|
||||
|
||||
#### Hierarchical vs Static Guidelines
|
||||
|
||||
**Hierarchical** (per-bank overridable):
|
||||
- LLM settings (provider, model, API key, base URL)
|
||||
- Operation-specific settings (retain mode, chunk size, etc.)
|
||||
- Feature flags that vary by customer/bank
|
||||
|
||||
**Static** (server-level only):
|
||||
- Infrastructure settings (database URL, port, host)
|
||||
- Global limits (max concurrent operations)
|
||||
- System-wide feature flags
|
||||
|
||||
## Environment Setup
|
||||
|
||||
@@ -266,18 +308,19 @@ cp .env.example .env
|
||||
# Edit .env with LLM API key
|
||||
|
||||
# Python deps
|
||||
uv sync --directory hindsight-api/
|
||||
uv sync --directory hindsight-api-slim/
|
||||
|
||||
# Node deps (uses npm workspaces)
|
||||
npm install
|
||||
```
|
||||
|
||||
Required env vars:
|
||||
- `HINDSIGHT_API_LLM_PROVIDER`: openai, anthropic, gemini, groq, ollama, lmstudio
|
||||
- `HINDSIGHT_API_LLM_PROVIDER`: openai, anthropic, gemini, groq, minimax, ollama, lmstudio
|
||||
- `HINDSIGHT_API_LLM_API_KEY`: Your API key
|
||||
- `HINDSIGHT_API_LLM_MODEL`: Model name (e.g., o3-mini, claude-sonnet-4-20250514)
|
||||
- `HINDSIGHT_API_LLM_MODEL`: Model name (e.g., gpt-4o-mini, claude-sonnet-4-20250514)
|
||||
|
||||
Optional (uses local models by default):
|
||||
- `HINDSIGHT_API_EMBEDDINGS_PROVIDER`: local (default) or tei
|
||||
- `HINDSIGHT_API_RERANKER_PROVIDER`: local (default) or tei
|
||||
- `HINDSIGHT_API_DATABASE_URL`: External PostgreSQL (uses embedded pg0 by default)
|
||||
- `HINDSIGHT_API_ENABLE_BANK_CONFIG_API`: Enable per-bank config API (default: true)
|
||||
|
||||
@@ -2,15 +2,16 @@
|
||||
|
||||

|
||||
|
||||
[Documentation](https://hindsight.vectorize.io) • [Paper](https://arxiv.org/abs/2512.12818) • [Cookbook](https://hindsight.vectorize.io/cookbook) • [Hindsight Cloud](https://vectorize.io/hindsight/cloud)
|
||||
[Documentation](https://hindsight.vectorize.io) • [Paper](https://arxiv.org/abs/2512.12818) • [Cookbook](https://hindsight.vectorize.io/cookbook) • [Hindsight Cloud](https://ui.hindsight.vectorize.io/signup)
|
||||
|
||||
[](https://github.com/vectorize-io/hindsight/actions/workflows/release.yml)
|
||||
[](https://join.slack.com/t/hindsight-space/shared_invite/zt-3nhbm4w29-LeSJ5Ixi6j8PdiYOCPlOgg)
|
||||
[](https://opensource.org/licenses/MIT)
|
||||

|
||||

|
||||
<br/>
|
||||
|
||||
|
||||
<a href="https://trendshift.io/repositories/15603" target="_blank"><img src="https://trendshift.io/api/badge/repositories/15603" alt="vectorize-io%2Fhindsight | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
|
||||
</div>
|
||||
|
||||
---
|
||||
@@ -36,7 +37,7 @@ Hindsight is being used in production at Fortune 500 enterprises and by a growin
|
||||
|
||||
## Adding Hindsight to Your AI Agents
|
||||
|
||||
The easiest way use Hindsight with an existing agent is with the LLM Wrapper. You can add memory to your agent with 2 lines of code. That will swap your current LLM client out with the Hindsight wrapper. After that, memories will be stored and retrieved automatically as you make LLM calls.
|
||||
The easiest way to use Hindsight with an existing agent is with the LLM Wrapper. You can add memory to your agent with 2 lines of code. That will swap your current LLM client out with the Hindsight wrapper. After that, memories will be stored and retrieved automatically as you make LLM calls.
|
||||
|
||||
If you need more control over how and when your agent stores and recalls memories, there's also a simple API you can integrate with using the SDKs or directly via HTTP.
|
||||
|
||||
@@ -69,7 +70,7 @@ docker run --rm -it --pull always -p 8888:8888 -p 9999:9999 \
|
||||
>API: http://localhost:8888
|
||||
>UI: http://localhost:9999
|
||||
|
||||
You can modify the LLM provider by setting `HINDSIGHT_API_LLM_PROVIDER`. Valid options are `openai`, `anthropic`, `gemini`, `groq`, `ollama`, and `lmstudio`. The documentation provides more details on [supported models](https://hindsight.vectorize.io/developer/models).
|
||||
You can modify the LLM provider by setting `HINDSIGHT_API_LLM_PROVIDER`. Valid options are `openai`, `anthropic`, `gemini`, `groq`, `ollama`, `lmstudio`, and `minimax`. The documentation provides more details on [supported models](https://hindsight.vectorize.io/developer/models).
|
||||
|
||||
|
||||
|
||||
@@ -181,7 +182,7 @@ Satisfying these requirements in Hindsight is straightforward. When new user inp
|
||||
|
||||

|
||||
|
||||
Most agent memory implementation rely on basic vector search or sometimes use a knowledge graph. Hindsight uses biomimetic data structures to organize agent memories in a way that is more like how human memory works:
|
||||
Most agent memory implementations rely on basic vector search or sometimes use a knowledge graph. Hindsight uses biomimetic data structures to organize agent memories in a way that is more like how human memory works:
|
||||
|
||||
- **World:** Facts about the world ("The stove gets hot")
|
||||
- **Experiences:** Agent's own experiences ("I touched the stove and it really hurt")
|
||||
@@ -307,3 +308,5 @@ MIT — see [LICENSE](./LICENSE)
|
||||
---
|
||||
|
||||
Built by [Vectorize.io](https://vectorize.io)
|
||||
|
||||
<img src="https://umami-pixel.chris-latimer.workers.dev/?id=a8b043e6-6964-454d-80df-69b69d3f0d50&host=github.com&url=/vectorize-io/hindsight" width="1" height="1" alt="" />
|
||||
|
||||
@@ -0,0 +1,139 @@
|
||||
{
|
||||
"version": "5",
|
||||
"specifiers": {
|
||||
"jsr:@std/assert@^1.0.17": "1.0.19",
|
||||
"jsr:@std/assert@^1.0.19": "1.0.19",
|
||||
"jsr:@std/expect@*": "1.0.18",
|
||||
"jsr:@std/internal@^1.0.12": "1.0.12",
|
||||
"jsr:@std/path@^1.1.4": "1.1.4",
|
||||
"jsr:@std/testing@*": "1.0.17"
|
||||
},
|
||||
"jsr": {
|
||||
"@std/[email protected]": {
|
||||
"integrity": "eaada96ee120cb980bc47e040f82814d786fe8162ecc53c91d8df60b8755991e",
|
||||
"dependencies": [
|
||||
"jsr:@std/internal"
|
||||
]
|
||||
},
|
||||
"@std/[email protected]": {
|
||||
"integrity": "8566eab35200466f8609eb7e7aed062ed0db314e9a258d5d201b1b8997ce801a",
|
||||
"dependencies": [
|
||||
"jsr:@std/assert@^1.0.19",
|
||||
"jsr:@std/internal",
|
||||
"jsr:@std/path"
|
||||
]
|
||||
},
|
||||
"@std/[email protected]": {
|
||||
"integrity": "972a634fd5bc34b242024402972cd5143eac68d8dffaca5eaa4dba30ce17b027"
|
||||
},
|
||||
"@std/[email protected]": {
|
||||
"integrity": "1d2d43f39efb1b42f0b1882a25486647cb851481862dc7313390b2bb044314b5",
|
||||
"dependencies": [
|
||||
"jsr:@std/internal"
|
||||
]
|
||||
},
|
||||
"@std/[email protected]": {
|
||||
"integrity": "87bdc2700fa98249d48a17cd72413352d3d3680dcfbdb64947fd0982d6bbf681",
|
||||
"dependencies": [
|
||||
"jsr:@std/assert@^1.0.17",
|
||||
"jsr:@std/internal"
|
||||
]
|
||||
}
|
||||
},
|
||||
"workspace": {
|
||||
"members": {
|
||||
"hindsight-clients/typescript": {
|
||||
"packageJson": {
|
||||
"dependencies": [
|
||||
"npm:@hey-api/[email protected]",
|
||||
"npm:@types/jest@29",
|
||||
"npm:@types/node@20",
|
||||
"npm:jest@29",
|
||||
"npm:ts-jest@29",
|
||||
"npm:tsup@^8.5.1",
|
||||
"npm:typescript@5"
|
||||
]
|
||||
}
|
||||
},
|
||||
"hindsight-control-plane": {
|
||||
"packageJson": {
|
||||
"dependencies": [
|
||||
"npm:@eslint/eslintrc@^3.3.3",
|
||||
"npm:@eslint/js@^9.39.2",
|
||||
"npm:@radix-ui/react-alert-dialog@^1.1.15",
|
||||
"npm:@radix-ui/react-checkbox@^1.3.3",
|
||||
"npm:@radix-ui/react-dialog@^1.1.15",
|
||||
"npm:@radix-ui/react-dropdown-menu@^2.1.16",
|
||||
"npm:@radix-ui/react-label@^2.1.8",
|
||||
"npm:@radix-ui/react-popover@^1.1.15",
|
||||
"npm:@radix-ui/react-radio-group@^1.3.8",
|
||||
"npm:@radix-ui/react-select@^2.2.6",
|
||||
"npm:@radix-ui/react-slider@^1.3.6",
|
||||
"npm:@radix-ui/react-slot@^1.2.4",
|
||||
"npm:@radix-ui/react-switch@^1.2.6",
|
||||
"npm:@radix-ui/react-tabs@^1.1.13",
|
||||
"npm:@radix-ui/react-tooltip@^1.2.8",
|
||||
"npm:@tailwindcss/postcss@^4.1.17",
|
||||
"npm:@tailwindcss/typography@~0.5.19",
|
||||
"npm:@types/cytoscape@^3.21.9",
|
||||
"npm:@types/node@^24.10.0",
|
||||
"npm:@types/react-dom@^19.2.2",
|
||||
"npm:@types/react@^19.2.2",
|
||||
"npm:autoprefixer@^10.4.21",
|
||||
"npm:class-variance-authority@~0.7.1",
|
||||
"npm:clsx@^2.1.1",
|
||||
"npm:cmdk@^1.1.1",
|
||||
"npm:cytoscape-fcose@^2.2.0",
|
||||
"npm:cytoscape@^3.33.1",
|
||||
"npm:eslint-config-next@^16.0.1",
|
||||
"npm:eslint-plugin-react-hooks@^7.0.1",
|
||||
"npm:eslint-plugin-react@^7.37.5",
|
||||
"npm:eslint@^9.39.1",
|
||||
"npm:[email protected]",
|
||||
"npm:next-themes@~0.4.6",
|
||||
"npm:next@^16.1.6",
|
||||
"npm:postcss@^8.5.6",
|
||||
"npm:prettier@^3.7.4",
|
||||
"npm:react-chrono@^2.9.1",
|
||||
"npm:react-dom@^19.2.0",
|
||||
"npm:react-markdown@^10.1.0",
|
||||
"npm:react18-json-view@~0.2.9",
|
||||
"npm:react@^19.2.0",
|
||||
"npm:recharts@^3.5.1",
|
||||
"npm:remark-gfm@^4.0.1",
|
||||
"npm:sonner@^2.0.7",
|
||||
"npm:tailwind-merge@^3.4.0",
|
||||
"npm:tailwindcss-animate@^1.0.7",
|
||||
"npm:tailwindcss@^4.1.17",
|
||||
"npm:[email protected]",
|
||||
"npm:typescript-eslint@^8.50.0",
|
||||
"npm:typescript@^5.9.3"
|
||||
]
|
||||
}
|
||||
},
|
||||
"hindsight-docs": {
|
||||
"packageJson": {
|
||||
"dependencies": [
|
||||
"npm:@docusaurus/[email protected]",
|
||||
"npm:@docusaurus/[email protected]",
|
||||
"npm:@docusaurus/[email protected]",
|
||||
"npm:@docusaurus/theme-common@^3.9.2",
|
||||
"npm:@docusaurus/theme-mermaid@^3.9.2",
|
||||
"npm:@docusaurus/[email protected]",
|
||||
"npm:@docusaurus/[email protected]",
|
||||
"npm:@easyops-cn/docusaurus-search-local@~0.52.2",
|
||||
"npm:@mdx-js/react@3",
|
||||
"npm:clsx@2",
|
||||
"npm:prism-react-renderer@^2.3.0",
|
||||
"npm:raw-loader@^4.0.2",
|
||||
"npm:react-dom@19",
|
||||
"npm:react-icons@^5.6.0",
|
||||
"npm:react@19",
|
||||
"npm:redocusaurus@^2.5.0",
|
||||
"npm:typescript@~5.6.2"
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,96 @@
|
||||
# Nginx Reverse Proxy with Custom Base Path
|
||||
|
||||
Deploy Hindsight API under `/hindsight` (or any custom path) using Nginx reverse proxy.
|
||||
|
||||
## Quick Start (Published Image - API Only)
|
||||
|
||||
```bash
|
||||
docker-compose up
|
||||
```
|
||||
|
||||
- **API:** http://localhost:8080/hindsight/docs
|
||||
- **Control Plane:** http://localhost:9999 (direct access, not proxied)
|
||||
|
||||
## Full Stack with Custom Base Path (Requires Build)
|
||||
|
||||
**Important:** You cannot rebuild from the published image with build args. You must build from source.
|
||||
|
||||
### Build from Source with Custom Base Path
|
||||
|
||||
1. **Clone the repository** (if you haven't):
|
||||
```bash
|
||||
git clone https://github.com/vectorize-io/hindsight.git
|
||||
cd hindsight
|
||||
```
|
||||
|
||||
2. **Build with base path**:
|
||||
```bash
|
||||
docker build \
|
||||
--build-arg NEXT_PUBLIC_BASE_PATH=/hindsight \
|
||||
-f docker/standalone/Dockerfile \
|
||||
-t hindsight:custom \
|
||||
.
|
||||
```
|
||||
|
||||
3. **Update docker-compose.yml** to use your built image:
|
||||
```yaml
|
||||
services:
|
||||
hindsight:
|
||||
image: hindsight:custom # ← Change this
|
||||
environment:
|
||||
HINDSIGHT_API_BASE_PATH: /hindsight
|
||||
NEXT_PUBLIC_BASE_PATH: /hindsight
|
||||
```
|
||||
|
||||
4. **Update nginx.conf** to handle Control Plane routes (see below)
|
||||
|
||||
5. **Run**:
|
||||
```bash
|
||||
docker-compose up
|
||||
```
|
||||
|
||||
### Required nginx.conf for Full Stack
|
||||
|
||||
Replace the current `nginx.conf` with this to proxy both API and Control Plane:
|
||||
|
||||
```nginx
|
||||
events { worker_connections 1024; }
|
||||
|
||||
http {
|
||||
include /etc/nginx/mime.types;
|
||||
default_type application/octet-stream;
|
||||
|
||||
upstream hindsight_api { server hindsight:8888; }
|
||||
upstream hindsight_cp { server hindsight:9999; }
|
||||
|
||||
server {
|
||||
listen 80;
|
||||
|
||||
# API
|
||||
location ~ ^/hindsight/(docs|openapi\.json|health|metrics|v1|mcp) {
|
||||
proxy_pass http://hindsight_api;
|
||||
proxy_set_header Host $http_host;
|
||||
}
|
||||
|
||||
# Control Plane static files
|
||||
location ~ ^/hindsight/_next/ {
|
||||
proxy_pass http://hindsight_cp;
|
||||
proxy_set_header Host $http_host;
|
||||
}
|
||||
|
||||
# Control Plane UI
|
||||
location /hindsight {
|
||||
proxy_pass http://hindsight_cp;
|
||||
proxy_set_header Host $http_host;
|
||||
}
|
||||
|
||||
location = / { return 301 /hindsight; }
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Why Build is Required
|
||||
|
||||
Next.js requires `basePath` at **build time**. The published image was built without a custom base path, so you must rebuild from source with the `NEXT_PUBLIC_BASE_PATH` build arg to deploy the Control Plane under a subpath.
|
||||
|
||||
The API works without rebuild because `HINDSIGHT_API_BASE_PATH` is a runtime environment variable.
|
||||
@@ -0,0 +1,88 @@
|
||||
# Hindsight API deployment with Nginx reverse proxy (API-only)
|
||||
#
|
||||
# This example deploys Hindsight API under the path /hindsight with:
|
||||
# - Hindsight standalone image (API + Control Plane + embedded pg0)
|
||||
# - Nginx reverse proxy (API only)
|
||||
#
|
||||
# Quick Start:
|
||||
# docker-compose -f docker/docker-compose/nginx/docker-compose.yml up
|
||||
#
|
||||
# Access:
|
||||
# API (via nginx): http://localhost:8080/hindsight/docs
|
||||
# Control Plane (direct): http://localhost:9999
|
||||
#
|
||||
# For full stack deployment (API + Control Plane both under /hindsight):
|
||||
# See README.md in this directory for instructions on building with basePath.
|
||||
#
|
||||
# Note: This configuration uses the published image (no build required).
|
||||
# Control Plane is served directly because Next.js basePath requires
|
||||
# build-time configuration. See README.md for the full stack option.
|
||||
|
||||
services:
|
||||
# Hindsight (API + Control Plane + embedded pg0)
|
||||
hindsight:
|
||||
image: ghcr.io/vectorize-io/hindsight:latest
|
||||
ports:
|
||||
- "9999:9999" # Control Plane (direct access, not proxied)
|
||||
environment:
|
||||
# API base path for reverse proxy
|
||||
HINDSIGHT_API_BASE_PATH: /hindsight
|
||||
|
||||
# LLM configuration
|
||||
# Using mock provider for testing (no API key needed)
|
||||
# For production, set OPENAI_API_KEY or ANTHROPIC_API_KEY and use a real provider
|
||||
HINDSIGHT_API_LLM_PROVIDER: ${HINDSIGHT_API_LLM_PROVIDER:-mock}
|
||||
HINDSIGHT_API_LLM_API_KEY: ${OPENAI_API_KEY:-not-needed-for-mock}
|
||||
HINDSIGHT_API_LLM_MODEL: ${HINDSIGHT_API_LLM_MODEL:-mock-model}
|
||||
|
||||
# Production examples (uncomment and set appropriate API key):
|
||||
# HINDSIGHT_API_LLM_PROVIDER: openai
|
||||
# HINDSIGHT_API_LLM_API_KEY: ${OPENAI_API_KEY}
|
||||
# HINDSIGHT_API_LLM_MODEL: gpt-4o-mini
|
||||
|
||||
# HINDSIGHT_API_LLM_PROVIDER: anthropic
|
||||
# HINDSIGHT_API_LLM_API_KEY: ${ANTHROPIC_API_KEY}
|
||||
# HINDSIGHT_API_LLM_MODEL: claude-sonnet-4-20250514
|
||||
|
||||
# Server config
|
||||
HINDSIGHT_API_HOST: 0.0.0.0
|
||||
HINDSIGHT_API_PORT: 8888
|
||||
HINDSIGHT_API_LOG_LEVEL: info
|
||||
|
||||
# Control Plane config
|
||||
HINDSIGHT_CP_DATAPLANE_API_URL: http://localhost:8888
|
||||
volumes:
|
||||
# Persist embedded pg0 database
|
||||
- hindsight_data:/app/data
|
||||
# Note: Ports not exposed - access via Nginx at localhost:8080/hindsight/
|
||||
# To debug directly, uncomment these ports:
|
||||
# ports:
|
||||
# - "8888:8888" # API
|
||||
# - "9999:9999" # Control Plane
|
||||
healthcheck:
|
||||
test: ["CMD", "curl", "-f", "http://localhost:8888/hindsight/health"]
|
||||
interval: 10s
|
||||
timeout: 5s
|
||||
retries: 3
|
||||
start_period: 30s
|
||||
networks:
|
||||
- hindsight
|
||||
|
||||
# Nginx reverse proxy
|
||||
nginx:
|
||||
image: nginx:alpine
|
||||
ports:
|
||||
- "8080:80"
|
||||
volumes:
|
||||
- ./nginx.conf:/etc/nginx/nginx.conf:ro
|
||||
depends_on:
|
||||
hindsight:
|
||||
condition: service_healthy
|
||||
networks:
|
||||
- hindsight
|
||||
|
||||
volumes:
|
||||
hindsight_data:
|
||||
|
||||
networks:
|
||||
hindsight:
|
||||
@@ -0,0 +1,40 @@
|
||||
# Nginx configuration for API-only reverse proxy
|
||||
# Control Plane accessed directly (not through nginx)
|
||||
|
||||
events {
|
||||
worker_connections 1024;
|
||||
}
|
||||
|
||||
http {
|
||||
include /etc/nginx/mime.types;
|
||||
default_type application/octet-stream;
|
||||
|
||||
# Logging
|
||||
access_log /var/log/nginx/access.log;
|
||||
error_log /var/log/nginx/error.log;
|
||||
|
||||
# Upstream - Hindsight API
|
||||
upstream hindsight_api {
|
||||
server hindsight:8888;
|
||||
}
|
||||
|
||||
server {
|
||||
listen 80;
|
||||
server_name _;
|
||||
|
||||
# API endpoints - forward with /hindsight prefix
|
||||
location /hindsight/ {
|
||||
proxy_pass http://hindsight_api;
|
||||
|
||||
proxy_set_header Host $http_host;
|
||||
proxy_set_header X-Real-IP $remote_addr;
|
||||
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
|
||||
proxy_set_header X-Forwarded-Proto $scheme;
|
||||
}
|
||||
|
||||
# Redirect root to API docs
|
||||
location = / {
|
||||
return 301 /hindsight/docs;
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,32 @@
|
||||
# PostgreSQL with pgvector and pg_textsearch extensions
|
||||
# Note: pg_textsearch requires PostgreSQL 17+
|
||||
FROM postgres:17
|
||||
|
||||
# Install build dependencies
|
||||
RUN apt-get update && apt-get install -y \
|
||||
build-essential \
|
||||
git \
|
||||
postgresql-server-dev-17 \
|
||||
libpq-dev \
|
||||
&& rm -rf /var/lib/apt/lists/*
|
||||
|
||||
# Install pgvector
|
||||
RUN cd /tmp && \
|
||||
git clone --branch v0.8.0 https://github.com/pgvector/pgvector.git && \
|
||||
cd pgvector && \
|
||||
make && \
|
||||
make install
|
||||
|
||||
# Install pg_textsearch
|
||||
RUN cd /tmp && \
|
||||
git clone https://github.com/timescale/pg_textsearch.git && \
|
||||
cd pg_textsearch && \
|
||||
make && \
|
||||
make install
|
||||
|
||||
# Clean up source files and build dependencies
|
||||
RUN rm -rf /tmp/pgvector /tmp/pg_textsearch && \
|
||||
apt-get purge -y --auto-remove build-essential git postgresql-server-dev-17
|
||||
|
||||
# Ensure extensions are preloaded
|
||||
RUN echo "shared_preload_libraries = 'pg_textsearch'" >> /usr/share/postgresql/postgresql.conf.sample
|
||||
@@ -0,0 +1,91 @@
|
||||
name: hindsight
|
||||
# Docker Compose file for Hindsight with PostgreSQL and Timescale pg_textsearch
|
||||
# docker compose -f docker/docker-compose/pg_textsearch/docker-compose.yaml down && sleep 2 && docker compose -f docker/docker-compose/pg_textsearch/docker-compose.yaml up -d
|
||||
# Make sure to set the required environment variables before running:
|
||||
# - HINDSIGHT_DB_PASSWORD: Password for the PostgreSQL user
|
||||
# - Configure LLM provider variables as needed (see below in the hindsight service)
|
||||
#
|
||||
# Usage:
|
||||
# docker compose up -d
|
||||
#
|
||||
# Optional environment variables with defaults:
|
||||
# - HINDSIGHT_VERSION: Hindsight application version (default: latest)
|
||||
# - HINDSIGHT_DB_USER: PostgreSQL user (default: hindsight_user)
|
||||
# - HINDSIGHT_DB_NAME: PostgreSQL database name (default: hindsight_db)
|
||||
|
||||
services:
|
||||
db:
|
||||
# Use custom PostgreSQL image with pgvector and pg_textsearch extensions
|
||||
build:
|
||||
context: .
|
||||
dockerfile: Dockerfile
|
||||
container_name: hindsight-db
|
||||
restart: always
|
||||
# Expose PostgreSQL port
|
||||
ports:
|
||||
- "5437:5432"
|
||||
environment:
|
||||
POSTGRES_USER: ${HINDSIGHT_DB_USER:-hindsight_user}
|
||||
POSTGRES_PASSWORD: ${HINDSIGHT_DB_PASSWORD:-hindsight_password}
|
||||
POSTGRES_DB: ${HINDSIGHT_DB_NAME:-hindsight_db}
|
||||
volumes:
|
||||
- pg_data:/var/lib/postgresql/data
|
||||
networks:
|
||||
- hindsight-net
|
||||
|
||||
pg-textsearch-init:
|
||||
build:
|
||||
context: .
|
||||
dockerfile: Dockerfile
|
||||
depends_on:
|
||||
- db
|
||||
environment:
|
||||
- PGPASSWORD=${HINDSIGHT_DB_PASSWORD:-hindsight_password}
|
||||
command: >
|
||||
bash -c "
|
||||
echo 'Waiting for PostgreSQL to be ready...';
|
||||
until pg_isready -h hindsight-db -p 5432 -U hindsight_user; do
|
||||
echo 'PostgreSQL is unavailable - sleeping';
|
||||
sleep 2;
|
||||
done;
|
||||
echo 'PostgreSQL is ready - creating hindsight_db database';
|
||||
psql -h hindsight-db -p 5432 -U hindsight_user -c 'CREATE DATABASE hindsight_db;' 2>/dev/null || echo 'Database already exists';
|
||||
echo 'Creating extensions in hindsight_db database';
|
||||
psql -h hindsight-db -p 5432 -U hindsight_user -d hindsight_db -c 'CREATE EXTENSION IF NOT EXISTS vector CASCADE;';
|
||||
psql -h hindsight-db -p 5432 -U hindsight_user -d hindsight_db -c 'CREATE EXTENSION IF NOT EXISTS pg_textsearch CASCADE;';
|
||||
echo 'Database and extensions created successfully';
|
||||
"
|
||||
restart: "no"
|
||||
networks:
|
||||
- hindsight-net
|
||||
|
||||
hindsight:
|
||||
image: ghcr.io/vectorize-io/hindsight:${HINDSIGHT_VERSION:-latest}
|
||||
container_name: hindsight-app
|
||||
ports:
|
||||
- "8888:8888"
|
||||
- "9999:9999"
|
||||
environment:
|
||||
# LLM Configuration
|
||||
HINDSIGHT_API_LLM_PROVIDER: ${HINDSIGHT_API_LLM_PROVIDER:-openai}
|
||||
HINDSIGHT_API_LLM_API_KEY: ${OPENAI_API_KEY:-your-api-key}
|
||||
|
||||
# Database Configuration
|
||||
HINDSIGHT_API_DATABASE_URL: postgresql://${HINDSIGHT_DB_USER:-hindsight_user}:${HINDSIGHT_DB_PASSWORD:-hindsight_password}@db:5432/${HINDSIGHT_DB_NAME:-hindsight_db}
|
||||
|
||||
# Vector and Text Search Extensions
|
||||
HINDSIGHT_API_VECTOR_EXTENSION: pgvector
|
||||
HINDSIGHT_API_TEXT_SEARCH_EXTENSION: pg_textsearch
|
||||
|
||||
depends_on:
|
||||
- db
|
||||
networks:
|
||||
- hindsight-net
|
||||
|
||||
|
||||
networks:
|
||||
hindsight-net:
|
||||
driver: bridge
|
||||
|
||||
volumes:
|
||||
pg_data:
|
||||
@@ -0,0 +1,83 @@
|
||||
# Docker Compose file for Hindsight with S3 file storage (SeaweedFS)
|
||||
#
|
||||
# SeaweedFS (Apache 2.0) provides an S3-compatible object storage backend
|
||||
# for storing uploaded files instead of PostgreSQL BYTEA storage.
|
||||
#
|
||||
# Make sure to set the required environment variables before running:
|
||||
# - HINDSIGHT_DB_PASSWORD: Password for the PostgreSQL user
|
||||
# - Configure LLM provider variables as needed (see below in the hindsight service)
|
||||
#
|
||||
# Usage:
|
||||
# docker compose up -d
|
||||
#
|
||||
# Optional environment variables with defaults:
|
||||
# - HINDSIGHT_VERSION: Hindsight application version (default: latest)
|
||||
# - HINDSIGHT_DB_USER: PostgreSQL user (default: hindsight_user)
|
||||
# - HINDSIGHT_DB_NAME: PostgreSQL database name (default: hindsight_db)
|
||||
# - HINDSIGHT_DB_VERSION: PostgreSQL version (default: 18)
|
||||
# - SEAWEEDFS_S3_ACCESS_KEY: S3 access key (default: hindsight_s3_key)
|
||||
# - SEAWEEDFS_S3_SECRET_KEY: S3 secret key (default: hindsight_s3_secret)
|
||||
|
||||
services:
|
||||
db:
|
||||
image: pgvector/pgvector:pg${HINDSIGHT_DB_VERSION:-18}
|
||||
container_name: hindsight-db
|
||||
restart: always
|
||||
environment:
|
||||
POSTGRES_USER: ${HINDSIGHT_DB_USER:-hindsight_user}
|
||||
POSTGRES_PASSWORD: ${HINDSIGHT_DB_PASSWORD:?Please set the HINDSIGHT_DB_PASSWORD env variable}
|
||||
POSTGRES_DB: ${HINDSIGHT_DB_NAME:-hindsight_db}
|
||||
volumes:
|
||||
- pg_data:/var/lib/postgresql/${HINDSIGHT_DB_VERSION:-18}/docker
|
||||
networks:
|
||||
- hindsight-net
|
||||
|
||||
seaweedfs:
|
||||
image: chrislusf/seaweedfs:latest
|
||||
container_name: hindsight-seaweedfs
|
||||
restart: always
|
||||
# Single-node mode: master + volume + filer + S3 gateway all in one process
|
||||
command: >
|
||||
server
|
||||
-s3
|
||||
-s3.port=8333
|
||||
-s3.config=/etc/seaweedfs/s3.json
|
||||
-ip.bind=0.0.0.0
|
||||
volumes:
|
||||
- seaweedfs_data:/data
|
||||
- ./s3.json:/etc/seaweedfs/s3.json:ro
|
||||
# Expose S3 API port (uncomment to access from host)
|
||||
# ports:
|
||||
# - "8333:8333"
|
||||
networks:
|
||||
- hindsight-net
|
||||
|
||||
hindsight:
|
||||
image: ghcr.io/vectorize-io/hindsight:${HINDSIGHT_VERSION:-latest}
|
||||
container_name: hindsight-app
|
||||
ports:
|
||||
- "8888:8888"
|
||||
- "9999:9999"
|
||||
environment:
|
||||
- HINDSIGHT_API_LLM_API_KEY=${OPENAI_API_KEY?Please set the OPENAI_API_KEY env variable}
|
||||
- HINDSIGHT_API_DATABASE_URL=postgresql://${HINDSIGHT_DB_USER:-hindsight_user}:${HINDSIGHT_DB_PASSWORD:?Please set the HINDSIGHT_DB_PASSWORD env variable}@db:5432/${HINDSIGHT_DB_NAME:-hindsight_db}
|
||||
# S3 file storage configuration (SeaweedFS)
|
||||
- HINDSIGHT_API_FILE_STORAGE_TYPE=s3
|
||||
- HINDSIGHT_API_FILE_STORAGE_S3_BUCKET=hindsight
|
||||
- HINDSIGHT_API_FILE_STORAGE_S3_ENDPOINT=http://seaweedfs:8333
|
||||
- HINDSIGHT_API_FILE_STORAGE_S3_REGION=us-east-1
|
||||
- HINDSIGHT_API_FILE_STORAGE_S3_ACCESS_KEY_ID=${SEAWEEDFS_S3_ACCESS_KEY:-hindsight_s3_key}
|
||||
- HINDSIGHT_API_FILE_STORAGE_S3_SECRET_ACCESS_KEY=${SEAWEEDFS_S3_SECRET_KEY:-hindsight_s3_secret}
|
||||
depends_on:
|
||||
- db
|
||||
- seaweedfs
|
||||
networks:
|
||||
- hindsight-net
|
||||
|
||||
networks:
|
||||
hindsight-net:
|
||||
driver: bridge
|
||||
|
||||
volumes:
|
||||
pg_data:
|
||||
seaweedfs_data:
|
||||
@@ -0,0 +1,19 @@
|
||||
{
|
||||
"identities": [
|
||||
{
|
||||
"name": "hindsight",
|
||||
"credentials": [
|
||||
{
|
||||
"accessKey": "hindsight_s3_key",
|
||||
"secretKey": "hindsight_s3_secret"
|
||||
}
|
||||
],
|
||||
"actions": [
|
||||
"Admin",
|
||||
"Read",
|
||||
"Write",
|
||||
"List"
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,16 @@
|
||||
# Git
|
||||
.git
|
||||
.gitignore
|
||||
.gitattributes
|
||||
|
||||
# Docker
|
||||
docker-compose.yaml
|
||||
.dockerignore
|
||||
|
||||
# Documentation
|
||||
README.md
|
||||
*.md
|
||||
|
||||
# Environment
|
||||
.env
|
||||
.env.example
|
||||
@@ -0,0 +1,25 @@
|
||||
# PostgreSQL Configuration
|
||||
HINDSIGHT_DB_USER=hindsight_user
|
||||
HINDSIGHT_DB_PASSWORD=change-me-to-secure-password
|
||||
HINDSIGHT_DB_NAME=hindsight_db
|
||||
|
||||
# Hindsight Version
|
||||
HINDSIGHT_VERSION=latest
|
||||
|
||||
# LLM Configuration
|
||||
HINDSIGHT_API_LLM_PROVIDER=openai
|
||||
OPENAI_API_KEY=your-openai-api-key-here
|
||||
|
||||
# Alternative LLM providers (uncomment and configure as needed):
|
||||
# HINDSIGHT_API_LLM_PROVIDER=anthropic
|
||||
# ANTHROPIC_API_KEY=your-anthropic-api-key
|
||||
|
||||
# HINDSIGHT_API_LLM_PROVIDER=gemini
|
||||
# GEMINI_API_KEY=your-gemini-api-key
|
||||
|
||||
# HINDSIGHT_API_LLM_PROVIDER=groq
|
||||
# GROQ_API_KEY=your-groq-api-key
|
||||
|
||||
# Vector and Text Search (already configured in docker-compose.yaml)
|
||||
# HINDSIGHT_API_VECTOR_EXTENSION=pgvectorscale
|
||||
# HINDSIGHT_API_TEXT_SEARCH_EXTENSION=pg_textsearch
|
||||
@@ -0,0 +1,55 @@
|
||||
# PostgreSQL with pgvector, pgvectorscale, and pg_textsearch extensions
|
||||
# All three extensions from Timescale/pgvector for high-performance vector and text search
|
||||
# Note: Requires PostgreSQL 16+
|
||||
FROM postgres:17
|
||||
|
||||
# Install build dependencies and Rust toolchain
|
||||
RUN apt-get update && apt-get install -y \
|
||||
build-essential \
|
||||
git \
|
||||
postgresql-server-dev-17 \
|
||||
libpq-dev \
|
||||
cmake \
|
||||
curl \
|
||||
pkg-config \
|
||||
libssl-dev \
|
||||
&& rm -rf /var/lib/apt/lists/*
|
||||
|
||||
# Install Rust toolchain (required for pgvectorscale)
|
||||
RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
|
||||
ENV PATH="/root/.cargo/bin:${PATH}"
|
||||
|
||||
# Install pgvector (required by pgvectorscale)
|
||||
RUN cd /tmp && \
|
||||
git clone --branch v0.8.0 https://github.com/pgvector/pgvector.git && \
|
||||
cd pgvector && \
|
||||
make && \
|
||||
make install && \
|
||||
rm -rf /tmp/pgvector
|
||||
|
||||
# Install cargo-pgrx (PostgreSQL extension framework for Rust)
|
||||
RUN cargo install cargo-pgrx --version 0.12.5 --locked && \
|
||||
cargo pgrx init --pg17 /usr/bin/pg_config
|
||||
|
||||
# Install pgvectorscale (DiskANN index support)
|
||||
RUN cd /tmp && \
|
||||
git clone --branch 0.5.1 https://github.com/timescale/pgvectorscale.git && \
|
||||
cd pgvectorscale/pgvectorscale && \
|
||||
cargo pgrx install --release && \
|
||||
rm -rf /tmp/pgvectorscale
|
||||
|
||||
# Install pg_textsearch (BM25 text search)
|
||||
RUN cd /tmp && \
|
||||
git clone https://github.com/timescale/pg_textsearch.git && \
|
||||
cd pg_textsearch && \
|
||||
make && \
|
||||
make install && \
|
||||
rm -rf /tmp/pg_textsearch
|
||||
|
||||
# Clean up build dependencies (keep runtime dependencies)
|
||||
RUN apt-get purge -y --auto-remove git cmake curl && \
|
||||
rm -rf /root/.cargo/registry /root/.cargo/git
|
||||
|
||||
# Ensure extensions are preloaded (pg_textsearch requires preloading)
|
||||
RUN echo "shared_preload_libraries = 'pg_textsearch'" >> /usr/share/postgresql/postgresql.conf.sample
|
||||
|
||||
@@ -0,0 +1,101 @@
|
||||
# Hindsight with Timescale Extensions
|
||||
|
||||
This Docker Compose setup provides a complete Hindsight deployment with **Timescale extensions**:
|
||||
- **pgvectorscale** - DiskANN algorithm for disk-based scalable vector search
|
||||
- **pg_textsearch** - High-performance BM25 text search
|
||||
|
||||
Both extensions are from [Timescale](https://github.com/timescale) and provide production-grade performance.
|
||||
|
||||
## Prerequisites
|
||||
|
||||
- Docker and Docker Compose installed
|
||||
- OpenAI API key (or another LLM provider)
|
||||
|
||||
## Quick Start
|
||||
|
||||
```bash
|
||||
# Set environment variables
|
||||
export HINDSIGHT_DB_PASSWORD="your-secure-password"
|
||||
export OPENAI_API_KEY="your-openai-api-key"
|
||||
|
||||
# Build and start
|
||||
docker compose -f docker/docker-compose/timescale/docker-compose.yaml up -d --build
|
||||
|
||||
# Check logs
|
||||
|
||||
docker compose -f docker/docker-compose/timescale/docker-compose.yaml logs -f
|
||||
```
|
||||
|
||||
**Access:**
|
||||
- API: http://localhost:8888
|
||||
- Control Plane: http://localhost:9999
|
||||
|
||||
## Stop and Clean Up
|
||||
|
||||
```bash
|
||||
# Stop services
|
||||
docker compose -f docker/docker-compose/timescale/docker-compose.yaml down
|
||||
|
||||
# Remove volumes (deletes all data)
|
||||
docker compose -f docker/docker-compose/timescale/docker-compose.yaml down -v
|
||||
```
|
||||
|
||||
## Configuration
|
||||
|
||||
### Environment Variables
|
||||
|
||||
| Variable | Description | Default |
|
||||
|----------|-------------|---------|
|
||||
| `HINDSIGHT_DB_PASSWORD` | PostgreSQL password | `hindsight_password` |
|
||||
| `HINDSIGHT_DB_USER` | PostgreSQL username | `hindsight_user` |
|
||||
| `HINDSIGHT_DB_NAME` | Database name | `hindsight_db` |
|
||||
| `HINDSIGHT_VERSION` | Hindsight Docker image version | `latest` |
|
||||
| `OPENAI_API_KEY` | OpenAI API key | (required) |
|
||||
| `HINDSIGHT_API_LLM_PROVIDER` | LLM provider | `openai` |
|
||||
|
||||
### Why Timescale Extensions?
|
||||
|
||||
**pgvectorscale (DiskANN):**
|
||||
- 28x lower p95 latency vs dedicated vector databases
|
||||
- 16x higher query throughput at 99% recall
|
||||
- 60-75% cost reduction (disk is cheaper than RAM)
|
||||
- Best for large datasets (10M+ vectors)
|
||||
|
||||
**pg_textsearch (BM25):**
|
||||
- High-performance keyword retrieval
|
||||
- Native BM25 ranking algorithm
|
||||
- Optimized for full-text search
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
### Extensions not installed
|
||||
|
||||
Check if extensions are available:
|
||||
|
||||
```bash
|
||||
docker exec -it hindsight-db-timescale psql -U hindsight_user -d hindsight_db -c "\dx"
|
||||
```
|
||||
|
||||
You should see:
|
||||
- `vector` (pgvector)
|
||||
- `vectorscale` (pgvectorscale/DiskANN)
|
||||
- `pg_textsearch` (BM25 search)
|
||||
|
||||
### Build fails
|
||||
|
||||
If the Docker build fails during pgvectorscale compilation:
|
||||
|
||||
1. Ensure you have sufficient memory (recommended: 4GB+)
|
||||
2. Check Docker build logs for Rust compilation errors
|
||||
3. Try building with more resources: `docker compose build --no-cache --memory 4g`
|
||||
|
||||
### Port conflicts
|
||||
|
||||
If port 5438 is already in use, modify the `ports` section in docker-compose.yaml.
|
||||
|
||||
## Learn More
|
||||
|
||||
- [pgvectorscale GitHub](https://github.com/timescale/pgvectorscale)
|
||||
- [pg_textsearch GitHub](https://github.com/timescale/pg_textsearch)
|
||||
- [HNSW vs DiskANN](https://www.tigerdata.com/learn/hnsw-vs-diskann)
|
||||
- [Hindsight Documentation](https://hindsight.dev)
|
||||
@@ -0,0 +1,108 @@
|
||||
name: hindsight
|
||||
# Docker Compose file for Hindsight with Timescale extensions
|
||||
# - pgvectorscale: DiskANN vector search (disk-based, scalable)
|
||||
# - pg_textsearch: BM25 text search (high-performance keyword retrieval)
|
||||
#
|
||||
# Quick start:
|
||||
# docker compose -f docker/docker-compose/timescale/docker-compose.yaml up -d --build
|
||||
#
|
||||
# Required environment variables:
|
||||
# - HINDSIGHT_DB_PASSWORD: Password for the PostgreSQL user
|
||||
# - OPENAI_API_KEY (or configure another LLM provider)
|
||||
#
|
||||
# Optional environment variables with defaults:
|
||||
# - HINDSIGHT_VERSION: Hindsight application version (default: latest)
|
||||
# - HINDSIGHT_DB_USER: PostgreSQL user (default: hindsight_user)
|
||||
# - HINDSIGHT_DB_NAME: PostgreSQL database name (default: hindsight_db)
|
||||
|
||||
services:
|
||||
db:
|
||||
# Custom PostgreSQL image with Timescale extensions (pgvectorscale + pg_textsearch)
|
||||
build:
|
||||
context: .
|
||||
dockerfile: Dockerfile
|
||||
container_name: hindsight-db-timescale
|
||||
restart: always
|
||||
# Expose PostgreSQL port (using 5438 to avoid conflicts with other setups)
|
||||
ports:
|
||||
- "5438:5432"
|
||||
environment:
|
||||
POSTGRES_USER: ${HINDSIGHT_DB_USER:-hindsight_user}
|
||||
POSTGRES_PASSWORD: ${HINDSIGHT_DB_PASSWORD:-hindsight_password}
|
||||
POSTGRES_DB: ${HINDSIGHT_DB_NAME:-hindsight_db}
|
||||
volumes:
|
||||
- pg_data:/var/lib/postgresql/data
|
||||
networks:
|
||||
- hindsight-net
|
||||
# Health check to ensure database is ready
|
||||
healthcheck:
|
||||
test: ["CMD-SHELL", "pg_isready -U hindsight_user"]
|
||||
interval: 5s
|
||||
timeout: 5s
|
||||
retries: 5
|
||||
|
||||
timescale-init:
|
||||
build:
|
||||
context: .
|
||||
dockerfile: Dockerfile
|
||||
depends_on:
|
||||
db:
|
||||
condition: service_healthy
|
||||
environment:
|
||||
- PGPASSWORD=${HINDSIGHT_DB_PASSWORD:-hindsight_password}
|
||||
command: >
|
||||
bash -c "
|
||||
echo 'PostgreSQL is ready - creating hindsight_db database';
|
||||
psql -h hindsight-db-timescale -p 5432 -U hindsight_user -c 'CREATE DATABASE hindsight_db;' 2>/dev/null || echo 'Database already exists';
|
||||
echo 'Installing Timescale extensions...';
|
||||
echo '1/3: Installing pgvector (required by pgvectorscale)...';
|
||||
psql -h hindsight-db-timescale -p 5432 -U hindsight_user -d hindsight_db -c 'CREATE EXTENSION IF NOT EXISTS vector CASCADE;';
|
||||
echo '2/3: Installing pgvectorscale (DiskANN vector search)...';
|
||||
psql -h hindsight-db-timescale -p 5432 -U hindsight_user -d hindsight_db -c 'CREATE EXTENSION IF NOT EXISTS vectorscale CASCADE;';
|
||||
echo '3/3: Installing pg_textsearch (BM25 text search)...';
|
||||
psql -h hindsight-db-timescale -p 5432 -U hindsight_user -d hindsight_db -c 'CREATE EXTENSION IF NOT EXISTS pg_textsearch CASCADE;';
|
||||
echo '';
|
||||
echo '✅ Timescale extensions installed successfully';
|
||||
echo '';
|
||||
echo 'Installed extensions:';
|
||||
psql -h hindsight-db-timescale -p 5432 -U hindsight_user -d hindsight_db -c \"\\dx\" | grep -E '(vector|vectorscale|pg_textsearch)';
|
||||
"
|
||||
restart: "no"
|
||||
networks:
|
||||
- hindsight-net
|
||||
|
||||
hindsight:
|
||||
image: ghcr.io/vectorize-io/hindsight:${HINDSIGHT_VERSION:-latest}
|
||||
container_name: hindsight-app-timescale
|
||||
ports:
|
||||
- "8888:8888"
|
||||
- "9999:9999"
|
||||
environment:
|
||||
# LLM Configuration
|
||||
HINDSIGHT_API_LLM_PROVIDER: ${HINDSIGHT_API_LLM_PROVIDER:-openai}
|
||||
HINDSIGHT_API_LLM_API_KEY: ${OPENAI_API_KEY:-your-api-key}
|
||||
|
||||
# Database Configuration
|
||||
HINDSIGHT_API_DATABASE_URL: postgresql://${HINDSIGHT_DB_USER:-hindsight_user}:${HINDSIGHT_DB_PASSWORD:-hindsight_password}@db:5432/${HINDSIGHT_DB_NAME:-hindsight_db}
|
||||
|
||||
# Timescale Extensions
|
||||
# pgvectorscale: DiskANN algorithm for disk-based scalable vector search
|
||||
HINDSIGHT_API_VECTOR_EXTENSION: pgvectorscale
|
||||
# pg_textsearch: High-performance BM25 text search
|
||||
HINDSIGHT_API_TEXT_SEARCH_EXTENSION: pg_textsearch
|
||||
|
||||
depends_on:
|
||||
db:
|
||||
condition: service_healthy
|
||||
timescale-init:
|
||||
condition: service_completed_successfully
|
||||
networks:
|
||||
- hindsight-net
|
||||
|
||||
|
||||
networks:
|
||||
hindsight-net:
|
||||
driver: bridge
|
||||
|
||||
volumes:
|
||||
pg_data:
|
||||
@@ -0,0 +1,93 @@
|
||||
name: hindsight
|
||||
# Docker Compose file for Hindsight with PostgreSQL and vectorchord
|
||||
# docker compose -f docker/docker-compose/docker-compose.yaml down && sleep 2 && docker compose -f docker/docker-compose/docker-compose.yaml up -d
|
||||
# Make sure to set the required environment variables before running:
|
||||
# - HINDSIGHT_DB_PASSWORD: Password for the PostgreSQL user
|
||||
# - Configure LLM provider variables as needed (see below in the hindsight service)
|
||||
#
|
||||
# Usage:
|
||||
# docker compose up -d
|
||||
#
|
||||
# Optional environment variables with defaults:
|
||||
# - HINDSIGHT_VERSION: Hindsight application version (default: latest)
|
||||
# - HINDSIGHT_DB_USER: PostgreSQL user (default: hindsight_user)
|
||||
# - HINDSIGHT_DB_NAME: PostgreSQL database name (default: hindsight_db)
|
||||
# - HINDSIGHT_DB_VERSION: PostgreSQL version (default: 18)
|
||||
|
||||
services:
|
||||
db:
|
||||
# Use a PostgreSQL-Image with vectorchord extension pre-installed
|
||||
image: tensorchord/vchord-suite:pg${HINDSIGHT_DB_VERSION:-18-latest}
|
||||
container_name: hindsight-db
|
||||
restart: always
|
||||
# Expose PostgreSQL port
|
||||
ports:
|
||||
- "5436:5432"
|
||||
environment:
|
||||
POSTGRES_USER: ${HINDSIGHT_DB_USER:-hindsight_user}
|
||||
POSTGRES_PASSWORD: ${HINDSIGHT_DB_PASSWORD:-hindsight_password}
|
||||
POSTGRES_DB: ${HINDSIGHT_DB_NAME:-hindsight_db}
|
||||
volumes:
|
||||
- pg_data:/var/lib/postgresql/${HINDSIGHT_DB_VERSION:-18}/docker
|
||||
networks:
|
||||
- hindsight-net
|
||||
|
||||
vectorchord-init:
|
||||
image: tensorchord/vchord-suite:pg18-latest
|
||||
#container_name: vectorchord-init
|
||||
depends_on:
|
||||
- db
|
||||
environment:
|
||||
- PGPASSWORD=${HINDSIGHT_DB_PASSWORD:-hindsight_password}
|
||||
command: >
|
||||
bash -c "
|
||||
echo 'Waiting for PostgreSQL to be ready...';
|
||||
until pg_isready -h hindsight-db -p 5432 -U hindsight_user; do
|
||||
echo 'PostgreSQL is unavailable - sleeping';
|
||||
sleep 2;
|
||||
done;
|
||||
echo 'PostgreSQL is ready - creating hindsight_db database';
|
||||
psql -h hindsight-db -p 5432 -U hindsight_user -c 'CREATE DATABASE hindsight_db;' 2>/dev/null || echo 'Database already exists';
|
||||
echo 'Creating extensions in hindsight_db database';
|
||||
psql -h hindsight-db -p 5432 -U hindsight_user -d hindsight_db -c 'CREATE EXTENSION IF NOT EXISTS vchord CASCADE;';
|
||||
psql -h hindsight-db -p 5432 -U hindsight_user -d hindsight_db -c 'CREATE EXTENSION IF NOT EXISTS pg_tokenizer CASCADE;';
|
||||
psql -h hindsight-db -p 5432 -U hindsight_user -d hindsight_db -c 'CREATE EXTENSION IF NOT EXISTS vchord_bm25 CASCADE;';
|
||||
echo 'Creating llmlingua2 tokenizer';
|
||||
psql -h hindsight-db -p 5432 -U hindsight_user -d hindsight_db -c \"SELECT create_tokenizer('llmlingua2', \\$\\$ model = \\\"llmlingua2\\\" \\$\\$);\" 2>/dev/null || echo 'Tokenizer already exists or creation skipped';
|
||||
echo 'Database and extensions created successfully';
|
||||
"
|
||||
restart: "no"
|
||||
networks:
|
||||
- hindsight-net
|
||||
|
||||
hindsight:
|
||||
image: ghcr.io/vectorize-io/hindsight:${HINDSIGHT_VERSION:-latest}
|
||||
container_name: hindsight-app
|
||||
ports:
|
||||
- "8888:8888"
|
||||
- "9999:9999"
|
||||
environment:
|
||||
# LLM Configuration (uses OpenAI for testing vchord)
|
||||
# LLM configuration
|
||||
HINDSIGHT_API_LLM_PROVIDER: ${HINDSIGHT_API_LLM_PROVIDER:-openai}
|
||||
HINDSIGHT_API_LLM_API_KEY: ${OPENAI_API_KEY:-your-api-key}
|
||||
|
||||
# Database Configuration
|
||||
HINDSIGHT_API_DATABASE_URL: postgresql://${HINDSIGHT_DB_USER:-hindsight_user}:${HINDSIGHT_DB_PASSWORD:-hindsight_password}@db:5432/${HINDSIGHT_DB_NAME:-hindsight_db}
|
||||
|
||||
# Vector and Text Search Extensions
|
||||
HINDSIGHT_API_VECTOR_EXTENSION: vchord
|
||||
HINDSIGHT_API_TEXT_SEARCH_EXTENSION: vchord
|
||||
|
||||
depends_on:
|
||||
- db
|
||||
networks:
|
||||
- hindsight-net
|
||||
|
||||
|
||||
networks:
|
||||
hindsight-net:
|
||||
driver: bridge
|
||||
|
||||
volumes:
|
||||
pg_data:
|
||||
@@ -42,25 +42,22 @@ RUN apt-get update && apt-get install -y \
|
||||
&& pip install --no-cache-dir uv
|
||||
|
||||
# Copy dependency files and README (required by pyproject.toml)
|
||||
COPY hindsight-api/pyproject.toml ./api/
|
||||
COPY hindsight-api/README.md ./api/
|
||||
COPY hindsight-api-slim/pyproject.toml ./api/
|
||||
COPY hindsight-api-slim/README.md ./api/
|
||||
|
||||
WORKDIR /app/api
|
||||
|
||||
# Remove local ML model dependencies if INCLUDE_LOCAL_MODELS=false
|
||||
# This creates a smaller image when using external providers (TEI, OpenAI, Cohere)
|
||||
RUN if [ "$INCLUDE_LOCAL_MODELS" != "true" ]; then \
|
||||
echo "Removing local-models dependencies (sentence-transformers, torch, transformers)..." && \
|
||||
sed -i '/"sentence-transformers/d' pyproject.toml && \
|
||||
sed -i '/"transformers/d' pyproject.toml && \
|
||||
sed -i '/"torch/d' pyproject.toml; \
|
||||
# Sync dependencies using appropriate extras based on INCLUDE_LOCAL_MODELS
|
||||
# local-ml: torch, sentence-transformers, transformers, einops, flashrank, mlx (optional)
|
||||
# embedded-db: pg0-embedded (always included for embedded PostgreSQL support)
|
||||
RUN if [ "$INCLUDE_LOCAL_MODELS" = "true" ]; then \
|
||||
uv sync --extra local-ml --extra embedded-db; \
|
||||
else \
|
||||
uv sync --extra embedded-db; \
|
||||
fi
|
||||
|
||||
# Sync dependencies (will create lock file if needed)
|
||||
RUN uv sync
|
||||
|
||||
# Copy source code (alembic migrations are inside hindsight_api/)
|
||||
COPY hindsight-api/hindsight_api ./hindsight_api
|
||||
COPY hindsight-api-slim/hindsight_api ./hindsight_api
|
||||
|
||||
# Install the local package (uv sync only installed dependencies, not the package itself)
|
||||
RUN uv pip install -e .
|
||||
@@ -112,6 +109,10 @@ RUN rm -f package-lock.json && sed -i '/"@vectorize-io\/hindsight-client":/d' pa
|
||||
# Copy built SDK directly into node_modules (more reliable than npm link in Docker)
|
||||
COPY --from=sdk-builder /app/hindsight-clients/typescript ./node_modules/@vectorize-io/hindsight-client
|
||||
|
||||
# Accept base path as build argument for reverse proxy deployments
|
||||
# Usage: docker build --build-arg NEXT_PUBLIC_BASE_PATH=/hindsight ...
|
||||
ARG NEXT_PUBLIC_BASE_PATH=""
|
||||
|
||||
# Build Control Plane - run next build first, then custom standalone copy
|
||||
# (The build:standalone script expects a specific path structure that differs in Docker)
|
||||
RUN npm exec -- next build
|
||||
@@ -166,6 +167,11 @@ RUN chown -R hindsight:hindsight /app
|
||||
|
||||
USER hindsight
|
||||
|
||||
# Create pg0 data directory as hindsight user so that Docker seeds new named
|
||||
# volumes with correct ownership (UID 1000) on first use, avoiding the
|
||||
# "Permission denied" error when mounting a fresh root-owned volume.
|
||||
RUN mkdir -p /home/hindsight/.pg0
|
||||
|
||||
ENV PATH="/app/api/.venv/bin:${PATH}"
|
||||
|
||||
# Pre-download tiktoken encoding (ALWAYS - required for token counting even in air-gapped envs)
|
||||
@@ -317,6 +323,11 @@ RUN chown -R hindsight:hindsight /app
|
||||
|
||||
USER hindsight
|
||||
|
||||
# Create pg0 data directory as hindsight user so that Docker seeds new named
|
||||
# volumes with correct ownership (UID 1000) on first use, avoiding the
|
||||
# "Permission denied" error when mounting a fresh root-owned volume.
|
||||
RUN mkdir -p /home/hindsight/.pg0
|
||||
|
||||
ENV PATH="/app/api/.venv/bin:${PATH}"
|
||||
|
||||
# Pre-download tiktoken encoding (ALWAYS - required for token counting even in air-gapped envs)
|
||||
|
||||
@@ -77,18 +77,32 @@ PIDS=()
|
||||
# Start API if enabled
|
||||
if [ "$ENABLE_API" = "true" ]; then
|
||||
cd /app/api
|
||||
API_HEALTH_URL="${HINDSIGHT_API_HEALTH_URL:-http://localhost:8888/health}"
|
||||
API_STARTUP_WAIT_SECONDS="${HINDSIGHT_API_STARTUP_WAIT_SECONDS:-300}"
|
||||
|
||||
# Run API directly - Python's PYTHONUNBUFFERED=1 handles output buffering
|
||||
hindsight-api &
|
||||
API_PID=$!
|
||||
PIDS+=($API_PID)
|
||||
|
||||
# Wait for API to be ready
|
||||
for i in {1..60}; do
|
||||
if curl -sf http://localhost:8888/health &>/dev/null; then
|
||||
api_ready=false
|
||||
for ((i=1; i<=API_STARTUP_WAIT_SECONDS; i++)); do
|
||||
if ! kill -0 "$API_PID" 2>/dev/null; then
|
||||
wait "$API_PID"
|
||||
exit $?
|
||||
fi
|
||||
if curl -sf "$API_HEALTH_URL" &>/dev/null; then
|
||||
api_ready=true
|
||||
break
|
||||
fi
|
||||
sleep 1
|
||||
done
|
||||
|
||||
if [ "$api_ready" != "true" ]; then
|
||||
echo "❌ API did not become healthy within ${API_STARTUP_WAIT_SECONDS}s"
|
||||
exit 1
|
||||
fi
|
||||
else
|
||||
echo "API disabled (HINDSIGHT_ENABLE_API=false)"
|
||||
fi
|
||||
@@ -97,7 +111,8 @@ fi
|
||||
if [ "$ENABLE_CP" = "true" ]; then
|
||||
echo "🎛️ Starting Control Plane..."
|
||||
cd /app/control-plane
|
||||
PORT=9999 node server.js &
|
||||
export HOSTNAME="${HINDSIGHT_CP_HOSTNAME:-0.0.0.0}"
|
||||
PORT="${HINDSIGHT_CP_PORT:-9999}" node server.js &
|
||||
CP_PID=$!
|
||||
PIDS+=($CP_PID)
|
||||
else
|
||||
@@ -110,7 +125,7 @@ echo "✅ Hindsight is running!"
|
||||
echo ""
|
||||
echo "📍 Access:"
|
||||
if [ "$ENABLE_CP" = "true" ]; then
|
||||
echo " Control Plane: http://localhost:9999"
|
||||
echo " Control Plane: http://localhost:${HINDSIGHT_CP_PORT:-9999}"
|
||||
fi
|
||||
if [ "$ENABLE_API" = "true" ]; then
|
||||
echo " API: http://localhost:8888"
|
||||
|
||||
+44
-10
@@ -13,9 +13,9 @@
|
||||
# target - Optional: 'cp-only' for control plane, otherwise assumes API image (default: api)
|
||||
#
|
||||
# Environment variables:
|
||||
# GROQ_API_KEY - Required for API/standalone images (LLM verification)
|
||||
# HINDSIGHT_API_LLM_PROVIDER - LLM provider (default: groq)
|
||||
# HINDSIGHT_API_LLM_MODEL - LLM model (default: llama-3.3-70b-versatile)
|
||||
# HINDSIGHT_API_LLM_API_KEY - Required for API/standalone images (LLM verification)
|
||||
# HINDSIGHT_API_LLM_PROVIDER - LLM provider (default: openai)
|
||||
# HINDSIGHT_API_LLM_MODEL - LLM model (default: gpt-4o-mini)
|
||||
# HINDSIGHT_API_EMBEDDINGS_PROVIDER - Embeddings provider (optional, for slim images: openai, cohere, tei)
|
||||
# HINDSIGHT_API_EMBEDDINGS_OPENAI_API_KEY - OpenAI API key for embeddings (optional)
|
||||
# HINDSIGHT_API_RERANKER_PROVIDER - Reranker provider (optional, for slim images: cohere, tei)
|
||||
@@ -34,7 +34,7 @@
|
||||
# ./docker/test-image.sh hindsight-control-plane:test cp-only
|
||||
#
|
||||
# # Test slim image with external providers
|
||||
# export GROQ_API_KEY=gsk_xxx
|
||||
# export HINDSIGHT_API_LLM_API_KEY=sk_xxx
|
||||
# export HINDSIGHT_API_EMBEDDINGS_PROVIDER=openai
|
||||
# export HINDSIGHT_API_EMBEDDINGS_OPENAI_API_KEY=sk-xxx
|
||||
# export HINDSIGHT_API_RERANKER_PROVIDER=cohere
|
||||
@@ -49,6 +49,9 @@
|
||||
|
||||
set -euo pipefail
|
||||
|
||||
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
|
||||
REPO_ROOT="$(dirname "$SCRIPT_DIR")"
|
||||
|
||||
# Colors for output
|
||||
RED='\033[0;31m'
|
||||
GREEN='\033[0;32m'
|
||||
@@ -60,8 +63,8 @@ IMAGE="${1:-}"
|
||||
TARGET="${2:-api}"
|
||||
TIMEOUT="${SMOKE_TEST_TIMEOUT:-120}"
|
||||
CONTAINER_NAME="${SMOKE_TEST_CONTAINER_NAME:-hindsight-smoke-test}"
|
||||
LLM_PROVIDER="${HINDSIGHT_API_LLM_PROVIDER:-groq}"
|
||||
LLM_MODEL="${HINDSIGHT_API_LLM_MODEL:-llama-3.3-70b-versatile}"
|
||||
LLM_PROVIDER="${HINDSIGHT_API_LLM_PROVIDER:-openai}"
|
||||
LLM_MODEL="${HINDSIGHT_API_LLM_MODEL:-gpt-4o-mini}"
|
||||
|
||||
# Validate arguments
|
||||
if [ -z "$IMAGE" ]; then
|
||||
@@ -88,9 +91,9 @@ else
|
||||
fi
|
||||
|
||||
# Check for required environment variables
|
||||
if [ "$NEEDS_LLM" = true ] && [ -z "${GROQ_API_KEY:-}" ]; then
|
||||
echo -e "${RED}Error: GROQ_API_KEY environment variable is required for API/standalone images${NC}"
|
||||
echo "Set it with: export GROQ_API_KEY=your-api-key"
|
||||
if [ "$NEEDS_LLM" = true ] && [ "$LLM_PROVIDER" != "vertexai" ] && [ -z "${HINDSIGHT_API_LLM_API_KEY:-}" ]; then
|
||||
echo -e "${RED}Error: HINDSIGHT_API_LLM_API_KEY environment variable is required for API/standalone images${NC}"
|
||||
echo "Set it with: export HINDSIGHT_API_LLM_API_KEY=your-api-key"
|
||||
exit 2
|
||||
fi
|
||||
|
||||
@@ -123,9 +126,25 @@ else
|
||||
# Build docker run command with required and optional env vars
|
||||
DOCKER_CMD="docker run -d --name $CONTAINER_NAME"
|
||||
DOCKER_CMD="$DOCKER_CMD -e HINDSIGHT_API_LLM_PROVIDER=$LLM_PROVIDER"
|
||||
DOCKER_CMD="$DOCKER_CMD -e HINDSIGHT_API_LLM_API_KEY=${GROQ_API_KEY}"
|
||||
if [ -n "${HINDSIGHT_API_LLM_API_KEY:-}" ]; then
|
||||
DOCKER_CMD="$DOCKER_CMD -e HINDSIGHT_API_LLM_API_KEY=${HINDSIGHT_API_LLM_API_KEY}"
|
||||
fi
|
||||
DOCKER_CMD="$DOCKER_CMD -e HINDSIGHT_API_LLM_MODEL=$LLM_MODEL"
|
||||
|
||||
# Add Vertex AI config if provider is vertexai
|
||||
if [ "$LLM_PROVIDER" = "vertexai" ]; then
|
||||
if [ -n "${HINDSIGHT_API_LLM_VERTEXAI_SERVICE_ACCOUNT_KEY:-}" ]; then
|
||||
DOCKER_CMD="$DOCKER_CMD -v ${HINDSIGHT_API_LLM_VERTEXAI_SERVICE_ACCOUNT_KEY}:/tmp/gcp-credentials.json:ro"
|
||||
DOCKER_CMD="$DOCKER_CMD -e HINDSIGHT_API_LLM_VERTEXAI_SERVICE_ACCOUNT_KEY=/tmp/gcp-credentials.json"
|
||||
fi
|
||||
if [ -n "${HINDSIGHT_API_LLM_VERTEXAI_PROJECT_ID:-}" ]; then
|
||||
DOCKER_CMD="$DOCKER_CMD -e HINDSIGHT_API_LLM_VERTEXAI_PROJECT_ID=${HINDSIGHT_API_LLM_VERTEXAI_PROJECT_ID}"
|
||||
fi
|
||||
if [ -n "${HINDSIGHT_API_LLM_VERTEXAI_REGION:-}" ]; then
|
||||
DOCKER_CMD="$DOCKER_CMD -e HINDSIGHT_API_LLM_VERTEXAI_REGION=${HINDSIGHT_API_LLM_VERTEXAI_REGION}"
|
||||
fi
|
||||
fi
|
||||
|
||||
# Add optional embeddings provider config
|
||||
if [ -n "${HINDSIGHT_API_EMBEDDINGS_PROVIDER:-}" ]; then
|
||||
DOCKER_CMD="$DOCKER_CMD -e HINDSIGHT_API_EMBEDDINGS_PROVIDER=${HINDSIGHT_API_EMBEDDINGS_PROVIDER}"
|
||||
@@ -162,6 +181,21 @@ for i in $(seq 1 "$TIMEOUT"); do
|
||||
echo "=== Health Response ==="
|
||||
curl -s "http://localhost:${HEALTH_PORT}${HEALTH_PATH}" | python3 -m json.tool 2>/dev/null || curl -s "http://localhost:${HEALTH_PORT}${HEALTH_PATH}"
|
||||
echo ""
|
||||
|
||||
# Run retain/recall smoke test for API targets
|
||||
if [ "$TARGET" != "cp-only" ]; then
|
||||
echo ""
|
||||
echo "=== Retain/Recall Smoke Test ==="
|
||||
if ! "$REPO_ROOT/scripts/smoke-test-slim.sh" "http://localhost:${HEALTH_PORT}"; then
|
||||
echo ""
|
||||
echo "=== Container Logs (last 50 lines) ==="
|
||||
docker logs "$CONTAINER_NAME" 2>&1 | tail -50
|
||||
echo ""
|
||||
echo -e "${RED}Smoke test FAILED${NC}"
|
||||
exit 1
|
||||
fi
|
||||
fi
|
||||
|
||||
echo ""
|
||||
echo "=== Container Logs (last 50 lines) ==="
|
||||
docker logs "$CONTAINER_NAME" 2>&1 | tail -50
|
||||
|
||||
@@ -6,24 +6,17 @@
|
||||
# It expects API keys to be set in environment variables.
|
||||
#
|
||||
# Usage:
|
||||
# export GROQ_API_KEY=gsk_xxx
|
||||
# export OPENAI_API_KEY=sk-xxx
|
||||
# export COHERE_API_KEY=xxx
|
||||
# ./docker/test-slim-local.sh
|
||||
#
|
||||
# Or inline:
|
||||
# GROQ_API_KEY=gsk_xxx OPENAI_API_KEY=sk_xxx COHERE_API_KEY=xxx ./docker/test-slim-local.sh
|
||||
# OPENAI_API_KEY=sk_xxx COHERE_API_KEY=xxx ./docker/test-slim-local.sh
|
||||
#
|
||||
|
||||
set -euo pipefail
|
||||
|
||||
# Check for required API keys
|
||||
if [ -z "${GROQ_API_KEY:-}" ]; then
|
||||
echo "❌ Error: GROQ_API_KEY environment variable is required"
|
||||
echo "Set it with: export GROQ_API_KEY=gsk_xxx"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
if [ -z "${OPENAI_API_KEY:-}" ]; then
|
||||
echo "❌ Error: OPENAI_API_KEY environment variable is required"
|
||||
echo "Set it with: export OPENAI_API_KEY=sk-xxx"
|
||||
@@ -41,7 +34,10 @@ IMAGE="${1:-hindsight-slim:test}"
|
||||
echo "Testing image: $IMAGE"
|
||||
echo ""
|
||||
|
||||
# Set up external providers
|
||||
# Set up LLM and external providers
|
||||
export HINDSIGHT_API_LLM_PROVIDER=openai
|
||||
export HINDSIGHT_API_LLM_API_KEY=$OPENAI_API_KEY
|
||||
export HINDSIGHT_API_LLM_MODEL=gpt-4o-mini
|
||||
export HINDSIGHT_API_EMBEDDINGS_PROVIDER=openai
|
||||
export HINDSIGHT_API_EMBEDDINGS_OPENAI_API_KEY=$OPENAI_API_KEY
|
||||
export HINDSIGHT_API_RERANKER_PROVIDER=cohere
|
||||
|
||||
@@ -2,8 +2,8 @@ apiVersion: v2
|
||||
name: hindsight
|
||||
description: Hindsight helm chart
|
||||
type: application
|
||||
version: 0.4.10
|
||||
appVersion: "0.4.10"
|
||||
version: 0.4.19
|
||||
appVersion: "0.4.19"
|
||||
keywords:
|
||||
- ai
|
||||
- memory
|
||||
|
||||
@@ -0,0 +1,33 @@
|
||||
[build-system]
|
||||
requires = ["setuptools>=61"]
|
||||
build-backend = "setuptools.build_meta"
|
||||
|
||||
[project]
|
||||
name = "hindsight-all-slim"
|
||||
version = "0.4.19"
|
||||
description = "Hindsight: Agent Memory That Works Like Human Memory - Slim All-in-One Bundle"
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.11"
|
||||
dependencies = [
|
||||
"hindsight-api-slim>=0.4.17",
|
||||
"hindsight-client>=0.0.7",
|
||||
"hindsight-embed>=0.1.0",
|
||||
]
|
||||
|
||||
[tool.uv.sources]
|
||||
hindsight-api-slim = { workspace = true }
|
||||
hindsight-client = { workspace = true }
|
||||
hindsight-embed = { workspace = true }
|
||||
|
||||
[project.optional-dependencies]
|
||||
test = [
|
||||
"pytest>=7.0.0",
|
||||
"pytest-asyncio>=0.21.0",
|
||||
]
|
||||
|
||||
[tool.setuptools]
|
||||
packages = []
|
||||
|
||||
[tool.pytest.ini_options]
|
||||
asyncio_mode = "auto"
|
||||
asyncio_default_fixture_loop_scope = "function"
|
||||
@@ -0,0 +1,48 @@
|
||||
# hindsight-all
|
||||
|
||||
All-in-one package for Hindsight - Agent Memory That Works Like Human Memory
|
||||
|
||||
## Quick Start
|
||||
|
||||
```python
|
||||
from hindsight import start_server, HindsightClient
|
||||
|
||||
# Start server with embedded PostgreSQL
|
||||
server = start_server(
|
||||
llm_provider="groq",
|
||||
llm_api_key="your-api-key",
|
||||
llm_model="openai/gpt-oss-120b"
|
||||
)
|
||||
|
||||
# Create client
|
||||
client = HindsightClient(base_url=server.url)
|
||||
|
||||
# Store memories
|
||||
client.put(agent_id="assistant", content="User prefers Python for data analysis")
|
||||
|
||||
# Search memories
|
||||
results = client.search(agent_id="assistant", query="programming preferences")
|
||||
|
||||
# Generate contextual response
|
||||
response = client.think(agent_id="assistant", query="What languages should I recommend?")
|
||||
|
||||
# Stop server when done
|
||||
server.stop()
|
||||
```
|
||||
|
||||
## Using Context Manager
|
||||
|
||||
```python
|
||||
from hindsight import HindsightServer, HindsightClient
|
||||
|
||||
with HindsightServer(llm_provider="groq", llm_api_key="...") as server:
|
||||
client = HindsightClient(base_url=server.url)
|
||||
# ... use client ...
|
||||
# Server automatically stops
|
||||
```
|
||||
|
||||
## Installation
|
||||
|
||||
```bash
|
||||
pip install hindsight-all
|
||||
```
|
||||
@@ -0,0 +1,423 @@
|
||||
"""
|
||||
Wrapper for Hindsight client that adds API namespaces.
|
||||
|
||||
Provides organized access to different parts of the Hindsight API through
|
||||
namespaces like .banks, .mental_models, etc.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import Any
|
||||
|
||||
from hindsight_client import Hindsight
|
||||
|
||||
|
||||
class BanksAPI:
|
||||
"""Namespace for bank-related operations.
|
||||
|
||||
Provides methods to create, delete, and manage memory banks.
|
||||
"""
|
||||
|
||||
def __init__(self, client: Hindsight):
|
||||
self._client = client
|
||||
|
||||
def create(
|
||||
self,
|
||||
bank_id: str,
|
||||
name: str | None = None,
|
||||
mission: str | None = None,
|
||||
disposition: dict[str, Any] | None = None,
|
||||
) -> Any:
|
||||
"""Create a new bank.
|
||||
|
||||
Args:
|
||||
bank_id: Unique identifier for the bank.
|
||||
name: Optional display name for the bank.
|
||||
mission: Optional mission statement for the bank.
|
||||
disposition: Optional disposition configuration dict.
|
||||
|
||||
Returns:
|
||||
Bank creation response from the API.
|
||||
"""
|
||||
return self._client.create_bank(
|
||||
bank_id=bank_id,
|
||||
name=name,
|
||||
mission=mission,
|
||||
disposition=disposition,
|
||||
)
|
||||
|
||||
def delete(self, bank_id: str) -> Any:
|
||||
"""Delete a bank.
|
||||
|
||||
Args:
|
||||
bank_id: The ID of the bank to delete.
|
||||
|
||||
Returns:
|
||||
Deletion response from the API.
|
||||
"""
|
||||
return self._client.delete_bank(bank_id=bank_id)
|
||||
|
||||
def set_mission(self, bank_id: str, mission: str) -> Any:
|
||||
"""Set or update the mission for a bank.
|
||||
|
||||
Args:
|
||||
bank_id: The ID of the bank.
|
||||
mission: The mission statement to set.
|
||||
|
||||
Returns:
|
||||
API response confirming the update.
|
||||
"""
|
||||
return self._client.set_mission(bank_id=bank_id, mission=mission)
|
||||
|
||||
def set_disposition(self, bank_id: str, disposition: dict[str, Any]) -> Any:
|
||||
"""Set or update the disposition for a bank.
|
||||
|
||||
Args:
|
||||
bank_id: The ID of the bank.
|
||||
disposition: The disposition configuration dict.
|
||||
|
||||
Returns:
|
||||
API response confirming the update.
|
||||
"""
|
||||
return self._client.set_disposition(bank_id=bank_id, disposition=disposition)
|
||||
|
||||
def list(self) -> Any:
|
||||
"""List all banks.
|
||||
|
||||
Returns:
|
||||
List of banks from the API.
|
||||
"""
|
||||
from hindsight_client.hindsight_client import _run_async
|
||||
|
||||
return _run_async(self._client._banks_api.list_banks())
|
||||
|
||||
|
||||
class MentalModelsAPI:
|
||||
"""Namespace for mental model operations.
|
||||
|
||||
Mental models are reusable knowledge structures that guide agent behavior.
|
||||
"""
|
||||
|
||||
def __init__(self, client: Hindsight):
|
||||
self._client = client
|
||||
|
||||
def create(
|
||||
self,
|
||||
bank_id: str,
|
||||
name: str,
|
||||
content: str,
|
||||
tags: list[str] | None = None,
|
||||
) -> Any:
|
||||
"""Create a new mental model.
|
||||
|
||||
Args:
|
||||
bank_id: The ID of the bank to add the model to.
|
||||
name: Name for the mental model.
|
||||
content: The content/instructions for the mental model.
|
||||
tags: Optional list of tags for categorization.
|
||||
|
||||
Returns:
|
||||
Creation response from the API.
|
||||
"""
|
||||
return self._client.create_mental_model(
|
||||
bank_id=bank_id,
|
||||
name=name,
|
||||
content=content,
|
||||
tags=tags,
|
||||
)
|
||||
|
||||
def list(self, bank_id: str, tags: list[str] | None = None) -> Any:
|
||||
"""List all mental models for a bank.
|
||||
|
||||
Args:
|
||||
bank_id: The ID of the bank.
|
||||
tags: Optional filter by tags.
|
||||
|
||||
Returns:
|
||||
List of mental models.
|
||||
"""
|
||||
return self._client.list_mental_models(bank_id=bank_id, tags=tags)
|
||||
|
||||
def get(self, bank_id: str, mental_model_id: str) -> Any:
|
||||
"""Get a specific mental model.
|
||||
|
||||
Args:
|
||||
bank_id: The ID of the bank.
|
||||
mental_model_id: The ID of the mental model.
|
||||
|
||||
Returns:
|
||||
The mental model details.
|
||||
"""
|
||||
return self._client.get_mental_model(bank_id=bank_id, mental_model_id=mental_model_id)
|
||||
|
||||
def refresh(self, bank_id: str, mental_model_id: str) -> Any:
|
||||
"""Refresh a mental model.
|
||||
|
||||
Args:
|
||||
bank_id: The ID of the bank.
|
||||
mental_model_id: The ID of the mental model to refresh.
|
||||
|
||||
Returns:
|
||||
Refresh response from the API.
|
||||
"""
|
||||
return self._client.refresh_mental_model(bank_id=bank_id, mental_model_id=mental_model_id)
|
||||
|
||||
def update(
|
||||
self,
|
||||
bank_id: str,
|
||||
mental_model_id: str,
|
||||
name: str | None = None,
|
||||
content: str | None = None,
|
||||
tags: list[str] | None = None,
|
||||
) -> Any:
|
||||
"""Update a mental model.
|
||||
|
||||
Args:
|
||||
bank_id: The ID of the bank.
|
||||
mental_model_id: The ID of the mental model to update.
|
||||
name: Optional new name.
|
||||
content: Optional new content.
|
||||
tags: Optional new tags list.
|
||||
|
||||
Returns:
|
||||
Update response from the API.
|
||||
"""
|
||||
return self._client.update_mental_model(
|
||||
bank_id=bank_id,
|
||||
mental_model_id=mental_model_id,
|
||||
name=name,
|
||||
content=content,
|
||||
tags=tags,
|
||||
)
|
||||
|
||||
def delete(self, bank_id: str, mental_model_id: str) -> Any:
|
||||
"""Delete a mental model.
|
||||
|
||||
Args:
|
||||
bank_id: The ID of the bank.
|
||||
mental_model_id: The ID of the mental model to delete.
|
||||
|
||||
Returns:
|
||||
Deletion response from the API.
|
||||
"""
|
||||
return self._client.delete_mental_model(bank_id=bank_id, mental_model_id=mental_model_id)
|
||||
|
||||
|
||||
class DirectivesAPI:
|
||||
"""Namespace for directive operations.
|
||||
|
||||
Directives are explicit instructions that guide agent behavior.
|
||||
"""
|
||||
|
||||
def __init__(self, client: Hindsight):
|
||||
self._client = client
|
||||
|
||||
def create(
|
||||
self,
|
||||
bank_id: str,
|
||||
name: str,
|
||||
content: str,
|
||||
tags: list[str] | None = None,
|
||||
) -> Any:
|
||||
"""Create a new directive.
|
||||
|
||||
Args:
|
||||
bank_id: The ID of the bank to add the directive to.
|
||||
name: Name for the directive.
|
||||
content: The directive content/instructions.
|
||||
tags: Optional list of tags for categorization.
|
||||
|
||||
Returns:
|
||||
Creation response from the API.
|
||||
"""
|
||||
return self._client.create_directive(
|
||||
bank_id=bank_id,
|
||||
name=name,
|
||||
content=content,
|
||||
tags=tags,
|
||||
)
|
||||
|
||||
def list(self, bank_id: str, tags: list[str] | None = None) -> Any:
|
||||
"""List all directives for a bank.
|
||||
|
||||
Args:
|
||||
bank_id: The ID of the bank.
|
||||
tags: Optional filter by tags.
|
||||
|
||||
Returns:
|
||||
List of directives.
|
||||
"""
|
||||
return self._client.list_directives(bank_id=bank_id, tags=tags)
|
||||
|
||||
def get(self, bank_id: str, directive_id: str) -> Any:
|
||||
"""Get a specific directive.
|
||||
|
||||
Args:
|
||||
bank_id: The ID of the bank.
|
||||
directive_id: The ID of the directive.
|
||||
|
||||
Returns:
|
||||
The directive details.
|
||||
"""
|
||||
return self._client.get_directive(bank_id=bank_id, directive_id=directive_id)
|
||||
|
||||
def update(
|
||||
self,
|
||||
bank_id: str,
|
||||
directive_id: str,
|
||||
name: str | None = None,
|
||||
content: str | None = None,
|
||||
tags: list[str] | None = None,
|
||||
) -> Any:
|
||||
"""Update a directive.
|
||||
|
||||
Args:
|
||||
bank_id: The ID of the bank.
|
||||
directive_id: The ID of the directive to update.
|
||||
name: Optional new name.
|
||||
content: Optional new content.
|
||||
tags: Optional new tags list.
|
||||
|
||||
Returns:
|
||||
Update response from the API.
|
||||
"""
|
||||
return self._client.update_directive(
|
||||
bank_id=bank_id,
|
||||
directive_id=directive_id,
|
||||
name=name,
|
||||
content=content,
|
||||
tags=tags,
|
||||
)
|
||||
|
||||
def delete(self, bank_id: str, directive_id: str) -> Any:
|
||||
"""Delete a directive.
|
||||
|
||||
Args:
|
||||
bank_id: The ID of the bank.
|
||||
directive_id: The ID of the directive to delete.
|
||||
|
||||
Returns:
|
||||
Deletion response from the API.
|
||||
"""
|
||||
return self._client.delete_directive(bank_id=bank_id, directive_id=directive_id)
|
||||
|
||||
|
||||
class MemoriesAPI:
|
||||
"""Namespace for memory operations.
|
||||
|
||||
Provides methods to query and retrieve stored memories.
|
||||
"""
|
||||
|
||||
def __init__(self, client: Hindsight):
|
||||
self._client = client
|
||||
|
||||
def list(
|
||||
self,
|
||||
bank_id: str,
|
||||
type: str | None = None,
|
||||
search_query: str | None = None,
|
||||
limit: int = 100,
|
||||
offset: int = 0,
|
||||
) -> Any:
|
||||
"""List memories in a bank.
|
||||
|
||||
Args:
|
||||
bank_id: The ID of the bank to query.
|
||||
type: Optional filter by memory type.
|
||||
search_query: Optional search query for filtering.
|
||||
limit: Maximum number of results to return (default: 100).
|
||||
offset: Number of results to skip for pagination (default: 0).
|
||||
|
||||
Returns:
|
||||
List of memories matching the criteria.
|
||||
"""
|
||||
return self._client.list_memories(
|
||||
bank_id=bank_id,
|
||||
type=type,
|
||||
search_query=search_query,
|
||||
limit=limit,
|
||||
offset=offset,
|
||||
)
|
||||
|
||||
|
||||
class HindsightClient(Hindsight):
|
||||
"""
|
||||
Enhanced Hindsight client with organized API namespaces.
|
||||
|
||||
This wrapper extends the auto-generated Hindsight client with organized
|
||||
access to different parts of the API through namespaces.
|
||||
|
||||
Example:
|
||||
```python
|
||||
from hindsight import HindsightClient
|
||||
|
||||
client = HindsightClient(base_url="http://localhost:8888")
|
||||
|
||||
# Core operations (inherited from Hindsight)
|
||||
client.retain(bank_id="test", content="Hello")
|
||||
results = client.recall(bank_id="test", query="Hello")
|
||||
|
||||
# Organized API access through namespaces
|
||||
client.banks.create(bank_id="test", name="Test Bank")
|
||||
models = client.mental_models.list(bank_id="test")
|
||||
directives = client.directives.list(bank_id="test")
|
||||
memories = client.memories.list(bank_id="test")
|
||||
```
|
||||
|
||||
Attributes:
|
||||
banks: Namespace for bank management operations.
|
||||
mental_models: Namespace for mental model operations.
|
||||
directives: Namespace for directive operations.
|
||||
memories: Namespace for memory listing operations.
|
||||
"""
|
||||
|
||||
def __init__(self, *args: Any, **kwargs: Any) -> None:
|
||||
super().__init__(*args, **kwargs)
|
||||
self._banks_namespace: BanksAPI | None = None
|
||||
self._mental_models_namespace: MentalModelsAPI | None = None
|
||||
self._directives_namespace: DirectivesAPI | None = None
|
||||
self._memories_namespace: MemoriesAPI | None = None
|
||||
|
||||
@property
|
||||
def banks(self) -> BanksAPI:
|
||||
"""Access bank management operations.
|
||||
|
||||
Returns:
|
||||
BanksAPI instance for bank operations.
|
||||
"""
|
||||
if self._banks_namespace is None:
|
||||
self._banks_namespace = BanksAPI(self)
|
||||
return self._banks_namespace
|
||||
|
||||
@property
|
||||
def mental_models(self) -> MentalModelsAPI:
|
||||
"""Access mental model operations.
|
||||
|
||||
Returns:
|
||||
MentalModelsAPI instance for mental model operations.
|
||||
"""
|
||||
if self._mental_models_namespace is None:
|
||||
self._mental_models_namespace = MentalModelsAPI(self)
|
||||
return self._mental_models_namespace
|
||||
|
||||
@property
|
||||
def directives(self) -> DirectivesAPI:
|
||||
"""Access directive operations.
|
||||
|
||||
Returns:
|
||||
DirectivesAPI instance for directive operations.
|
||||
"""
|
||||
if self._directives_namespace is None:
|
||||
self._directives_namespace = DirectivesAPI(self)
|
||||
return self._directives_namespace
|
||||
|
||||
@property
|
||||
def memories(self) -> MemoriesAPI:
|
||||
"""Access memory listing operations.
|
||||
|
||||
Returns:
|
||||
MemoriesAPI instance for memory operations.
|
||||
"""
|
||||
if self._memories_namespace is None:
|
||||
self._memories_namespace = MemoriesAPI(self)
|
||||
return self._memories_namespace
|
||||
@@ -4,18 +4,18 @@ build-backend = "hatchling.build"
|
||||
|
||||
[project]
|
||||
name = "hindsight-all"
|
||||
version = "0.4.10"
|
||||
version = "0.4.19"
|
||||
description = "Hindsight: Agent Memory That Works Like Human Memory - All-in-One Bundle"
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.11"
|
||||
dependencies = [
|
||||
"hindsight-api>=0.0.7",
|
||||
"hindsight-api-slim[all]>=0.4.17",
|
||||
"hindsight-client>=0.0.7",
|
||||
"hindsight-embed>=0.1.0",
|
||||
]
|
||||
|
||||
[tool.uv.sources]
|
||||
hindsight-api = { workspace = true }
|
||||
hindsight-api-slim = { workspace = true }
|
||||
hindsight-client = { workspace = true }
|
||||
hindsight-embed = { workspace = true }
|
||||
|
||||
+4
-1
@@ -26,7 +26,10 @@ def llm_config():
|
||||
api_key = os.getenv("HINDSIGHT_LLM_API_KEY", "")
|
||||
model = os.getenv("HINDSIGHT_LLM_MODEL", "openai/gpt-oss-120b")
|
||||
|
||||
if not api_key:
|
||||
# vertexai uses GCP service account credentials (HINDSIGHT_API_LLM_VERTEXAI_*),
|
||||
# not a traditional API key
|
||||
providers_without_api_key = ("vertexai", "ollama")
|
||||
if not api_key and provider not in providers_without_api_key:
|
||||
raise Exception("LLM API key not configured. Set HINDSIGHT_LLM_API_KEY environment variable.")
|
||||
|
||||
return {
|
||||
@@ -0,0 +1,137 @@
|
||||
# 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
|
||||
|
||||
```bash
|
||||
pip install hindsight-api
|
||||
```
|
||||
|
||||
## Quick Start
|
||||
|
||||
### Run the Server
|
||||
|
||||
```bash
|
||||
# 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 `/mcp` for tool-use integration
|
||||
|
||||
### Use the Python API
|
||||
|
||||
```python
|
||||
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
|
||||
|
||||
```bash
|
||||
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
|
||||
|
||||
```bash
|
||||
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
|
||||
|
||||
```bash
|
||||
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:
|
||||
|
||||
```bash
|
||||
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](https://hindsight.vectorize.io)
|
||||
|
||||
- [Installation Guide](https://hindsight.vectorize.io/developer/installation)
|
||||
- [Configuration Reference](https://hindsight.vectorize.io/developer/configuration)
|
||||
- [API Reference](https://hindsight.vectorize.io/api-reference)
|
||||
- [Python SDK](https://hindsight.vectorize.io/sdks/python)
|
||||
|
||||
## License
|
||||
|
||||
Apache 2.0
|
||||
+1
-1
@@ -46,4 +46,4 @@ __all__ = [
|
||||
"RemoteTEICrossEncoder",
|
||||
"LLMConfig",
|
||||
]
|
||||
__version__ = "0.4.10"
|
||||
__version__ = "0.4.19"
|
||||
+81
-9
@@ -14,7 +14,8 @@ from typing import Any
|
||||
import asyncpg
|
||||
import typer
|
||||
|
||||
from ..config import HindsightConfig
|
||||
from ..config import DEFAULT_DATABASE_SCHEMA, HindsightConfig
|
||||
from ..extensions import TenantExtension, load_extension
|
||||
from ..pg0 import parse_pg0_url, resolve_database_url
|
||||
|
||||
|
||||
@@ -214,20 +215,81 @@ def restore(
|
||||
typer.echo("Restore complete")
|
||||
|
||||
|
||||
async def _run_migration(db_url: str, schema: str = "public") -> None:
|
||||
"""Resolve database URL and run migrations."""
|
||||
from ..migrations import run_migrations
|
||||
async def _run_migration(
|
||||
db_url: str,
|
||||
schema: str | None = None,
|
||||
base_schema: str = DEFAULT_DATABASE_SCHEMA,
|
||||
embedding_dimension: int | None = None,
|
||||
) -> list[str]:
|
||||
"""Resolve database URL and run migrations for one schema or all discovered schemas."""
|
||||
from ..migrations import (
|
||||
ensure_embedding_dimension,
|
||||
ensure_text_search_extension,
|
||||
ensure_vector_extension,
|
||||
run_migrations,
|
||||
)
|
||||
|
||||
is_pg0, instance_name, _ = parse_pg0_url(db_url)
|
||||
if is_pg0:
|
||||
typer.echo(f"Starting embedded PostgreSQL (instance: {instance_name})...")
|
||||
resolved_url = await resolve_database_url(db_url)
|
||||
run_migrations(resolved_url, schema=schema)
|
||||
|
||||
config = HindsightConfig.from_env()
|
||||
if schema:
|
||||
schemas = [schema]
|
||||
else:
|
||||
tenant_extension = load_extension("TENANT", TenantExtension)
|
||||
|
||||
schemas = [base_schema or DEFAULT_DATABASE_SCHEMA]
|
||||
if tenant_extension:
|
||||
tenants = await tenant_extension.list_tenants()
|
||||
schemas.extend(tenant.schema for tenant in tenants if tenant.schema)
|
||||
|
||||
# Preserve order while removing duplicates.
|
||||
schemas = list(dict.fromkeys(schemas))
|
||||
|
||||
for schema in schemas:
|
||||
run_migrations(resolved_url, schema=schema)
|
||||
|
||||
if embedding_dimension is not None:
|
||||
for schema in schemas:
|
||||
ensure_embedding_dimension(
|
||||
resolved_url,
|
||||
embedding_dimension,
|
||||
schema=schema,
|
||||
vector_extension=config.vector_extension,
|
||||
)
|
||||
|
||||
for schema in schemas:
|
||||
ensure_vector_extension(
|
||||
resolved_url,
|
||||
vector_extension=config.vector_extension,
|
||||
schema=schema,
|
||||
)
|
||||
|
||||
for schema in schemas:
|
||||
ensure_text_search_extension(
|
||||
resolved_url,
|
||||
text_search_extension=config.text_search_extension,
|
||||
schema=schema,
|
||||
)
|
||||
|
||||
return schemas
|
||||
|
||||
|
||||
@app.command(name="run-db-migration")
|
||||
def run_db_migration(
|
||||
schema: str = typer.Option("public", "--schema", "-s", help="Database schema to run migrations on"),
|
||||
schema: str | None = typer.Option(
|
||||
None,
|
||||
"--schema",
|
||||
"-s",
|
||||
help="Database schema to run migrations on. If omitted, migrate the base schema and all discovered tenant schemas.",
|
||||
),
|
||||
embedding_dimension: int | None = typer.Option(
|
||||
None,
|
||||
"--embedding-dimension",
|
||||
help="Expected embedding dimension to enforce after migrations. Omit to skip dimension sync.",
|
||||
),
|
||||
):
|
||||
"""Run database migrations to the latest version."""
|
||||
config = HindsightConfig.from_env()
|
||||
@@ -237,11 +299,21 @@ def run_db_migration(
|
||||
typer.echo("Set HINDSIGHT_API_DATABASE_URL environment variable.", err=True)
|
||||
raise typer.Exit(1)
|
||||
|
||||
typer.echo(f"Running database migrations (schema: {schema})...")
|
||||
if schema:
|
||||
typer.echo(f"Running database migrations for schema: {schema}...")
|
||||
else:
|
||||
typer.echo("Running database migrations for base schema and all discovered tenant schemas...")
|
||||
|
||||
asyncio.run(_run_migration(config.database_url, schema))
|
||||
schemas = asyncio.run(
|
||||
_run_migration(
|
||||
config.database_url,
|
||||
schema=schema,
|
||||
base_schema=config.database_schema,
|
||||
embedding_dimension=embedding_dimension,
|
||||
)
|
||||
)
|
||||
|
||||
typer.echo("Database migrations completed successfully")
|
||||
typer.echo(f"Database migrations completed successfully for {len(schemas)} schema(s)")
|
||||
|
||||
|
||||
async def _decommission_worker(db_url: str, worker_id: str, schema: str = "public") -> int:
|
||||
+168
-17
@@ -6,6 +6,7 @@ Create Date: 2025-11-27 11:54:19.228030
|
||||
|
||||
"""
|
||||
|
||||
import os
|
||||
from collections.abc import Sequence
|
||||
|
||||
import sqlalchemy as sa
|
||||
@@ -21,6 +22,96 @@ branch_labels: str | Sequence[str] | None = None
|
||||
depends_on: str | Sequence[str] | None = None
|
||||
|
||||
|
||||
def _detect_vector_extension() -> str:
|
||||
"""
|
||||
Detect or validate vector extension: 'pgvector', 'vchord', or 'pgvectorscale'.
|
||||
Respects HINDSIGHT_API_VECTOR_EXTENSION env var if set.
|
||||
"""
|
||||
conn = op.get_bind()
|
||||
vector_extension = os.getenv("HINDSIGHT_API_VECTOR_EXTENSION", "pgvector").lower()
|
||||
|
||||
# Validate configured extension is installed
|
||||
if vector_extension == "pgvectorscale":
|
||||
# pgvectorscale/DiskANN requires pgvector
|
||||
pgvector_check = conn.execute(text("SELECT 1 FROM pg_extension WHERE extname = 'vector'")).scalar()
|
||||
if not pgvector_check:
|
||||
raise RuntimeError(
|
||||
"DiskANN requires pgvector. Install with: CREATE EXTENSION vector; then vectorscale or pg_diskann CASCADE;"
|
||||
)
|
||||
# Check for either vectorscale (open source) or pg_diskann (Azure)
|
||||
vectorscale_check = conn.execute(text("SELECT 1 FROM pg_extension WHERE extname = 'vectorscale'")).scalar()
|
||||
pg_diskann_check = conn.execute(text("SELECT 1 FROM pg_extension WHERE extname = 'pg_diskann'")).scalar()
|
||||
|
||||
if vectorscale_check:
|
||||
return "pgvectorscale"
|
||||
elif pg_diskann_check:
|
||||
return "pg_diskann"
|
||||
else:
|
||||
raise RuntimeError(
|
||||
"Configured vector extension 'pgvectorscale' not found. Install either:\n"
|
||||
" - pgvectorscale: CREATE EXTENSION vectorscale CASCADE;\n"
|
||||
" - pg_diskann (Azure): CREATE EXTENSION pg_diskann CASCADE;"
|
||||
)
|
||||
elif vector_extension == "vchord":
|
||||
vchord_check = conn.execute(text("SELECT 1 FROM pg_extension WHERE extname = 'vchord'")).scalar()
|
||||
if not vchord_check:
|
||||
raise RuntimeError(
|
||||
"Configured vector extension 'vchord' not found. Install it with: CREATE EXTENSION vchord CASCADE;"
|
||||
)
|
||||
return "vchord"
|
||||
elif vector_extension == "pgvector":
|
||||
pgvector_check = conn.execute(text("SELECT 1 FROM pg_extension WHERE extname = 'vector'")).scalar()
|
||||
if not pgvector_check:
|
||||
raise RuntimeError(
|
||||
"Configured vector extension 'pgvector' not found. Install it with: CREATE EXTENSION vector;"
|
||||
)
|
||||
return "pgvector"
|
||||
else:
|
||||
raise ValueError(
|
||||
f"Invalid HINDSIGHT_API_VECTOR_EXTENSION: {vector_extension}. Must be 'pgvector', 'vchord', or 'pgvectorscale'"
|
||||
)
|
||||
|
||||
|
||||
def _detect_text_search_extension() -> str:
|
||||
"""
|
||||
Detect or validate text search extension: 'native', 'vchord', or 'pg_textsearch'.
|
||||
Respects HINDSIGHT_API_TEXT_SEARCH_EXTENSION env var.
|
||||
Creates the extension if needed.
|
||||
"""
|
||||
text_search_extension = os.getenv("HINDSIGHT_API_TEXT_SEARCH_EXTENSION", "native").lower()
|
||||
|
||||
if text_search_extension == "vchord":
|
||||
# Create vchord_bm25 extension if not exists
|
||||
try:
|
||||
op.execute("CREATE EXTENSION IF NOT EXISTS vchord_bm25 CASCADE")
|
||||
except Exception:
|
||||
# Extension might already exist or user lacks permissions - verify it exists
|
||||
conn = op.get_bind()
|
||||
result = conn.execute(text("SELECT 1 FROM pg_extension WHERE extname = 'vchord_bm25'")).fetchone()
|
||||
if not result:
|
||||
# Extension truly doesn't exist - re-raise the error
|
||||
raise
|
||||
return "vchord"
|
||||
elif text_search_extension == "pg_textsearch":
|
||||
# Create pg_textsearch extension if not exists
|
||||
try:
|
||||
op.execute("CREATE EXTENSION IF NOT EXISTS pg_textsearch CASCADE")
|
||||
except Exception:
|
||||
# Extension might already exist or user lacks permissions - verify it exists
|
||||
conn = op.get_bind()
|
||||
result = conn.execute(text("SELECT 1 FROM pg_extension WHERE extname = 'pg_textsearch'")).fetchone()
|
||||
if not result:
|
||||
# Extension truly doesn't exist - re-raise the error
|
||||
raise
|
||||
return "pg_textsearch"
|
||||
elif text_search_extension == "native":
|
||||
return "native"
|
||||
else:
|
||||
raise ValueError(
|
||||
f"Invalid HINDSIGHT_API_TEXT_SEARCH_EXTENSION: {text_search_extension}. Must be 'native', 'vchord', or 'pg_textsearch'"
|
||||
)
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
"""Upgrade schema - create all tables from scratch."""
|
||||
|
||||
@@ -166,11 +257,29 @@ def upgrade() -> None:
|
||||
)
|
||||
|
||||
# Add search_vector column for full-text search
|
||||
op.execute("""
|
||||
ALTER TABLE memory_units
|
||||
ADD COLUMN search_vector tsvector
|
||||
GENERATED ALWAYS AS (to_tsvector('english', COALESCE(text, '') || ' ' || COALESCE(context, ''))) STORED
|
||||
""")
|
||||
# Type depends on configured text search backend
|
||||
text_search_ext = _detect_text_search_extension()
|
||||
|
||||
if text_search_ext == "vchord":
|
||||
# VectorChord BM25: bm25vector type (no GENERATED - tokenization happens on INSERT)
|
||||
# Note: vchord_bm25 extension creates types in bm25_catalog schema
|
||||
op.execute("""
|
||||
ALTER TABLE memory_units
|
||||
ADD COLUMN search_vector bm25_catalog.bm25vector
|
||||
""")
|
||||
elif text_search_ext == "pg_textsearch":
|
||||
# Timescale pg_textsearch: dummy TEXT column for consistency (indexes operate on base columns directly)
|
||||
op.execute("""
|
||||
ALTER TABLE memory_units
|
||||
ADD COLUMN search_vector TEXT
|
||||
""")
|
||||
else: # native
|
||||
# Native PostgreSQL: tsvector with automatic generation
|
||||
op.execute("""
|
||||
ALTER TABLE memory_units
|
||||
ADD COLUMN search_vector tsvector
|
||||
GENERATED ALWAYS AS (to_tsvector('english', COALESCE(text, '') || ' ' || COALESCE(context, ''))) STORED
|
||||
""")
|
||||
|
||||
op.create_index("idx_memory_units_bank_id", "memory_units", ["bank_id"])
|
||||
op.create_index("idx_memory_units_document_id", "memory_units", ["document_id"])
|
||||
@@ -200,19 +309,61 @@ def upgrade() -> None:
|
||||
["bank_id", sa.text("event_date DESC")],
|
||||
postgresql_where=sa.text("fact_type = 'observation'"),
|
||||
)
|
||||
op.create_index(
|
||||
"idx_memory_units_embedding",
|
||||
"memory_units",
|
||||
["embedding"],
|
||||
postgresql_using="hnsw",
|
||||
postgresql_ops={"embedding": "vector_cosine_ops"},
|
||||
)
|
||||
# Create vector index - conditional based on available extension
|
||||
vector_ext = _detect_vector_extension()
|
||||
|
||||
# Create BM25 full-text search index on search_vector
|
||||
op.execute("""
|
||||
CREATE INDEX idx_memory_units_text_search ON memory_units
|
||||
USING gin(search_vector)
|
||||
""")
|
||||
if vector_ext == "pgvectorscale":
|
||||
# Use DiskANN index for pgvectorscale (disk-based, scalable)
|
||||
op.execute("""
|
||||
CREATE INDEX idx_memory_units_embedding ON memory_units
|
||||
USING diskann (embedding vector_cosine_ops)
|
||||
WITH (num_neighbors = 50)
|
||||
""")
|
||||
elif vector_ext == "pg_diskann":
|
||||
# Use DiskANN index for pg_diskann (Azure)
|
||||
op.execute("""
|
||||
CREATE INDEX idx_memory_units_embedding ON memory_units
|
||||
USING diskann (embedding vector_cosine_ops)
|
||||
WITH (max_neighbors = 50)
|
||||
""")
|
||||
elif vector_ext == "vchord":
|
||||
# Use vchordrq index for vchord (supports high-dimensional embeddings)
|
||||
op.execute("""
|
||||
CREATE INDEX idx_memory_units_embedding ON memory_units
|
||||
USING vchordrq (embedding vector_l2_ops)
|
||||
""")
|
||||
else: # pgvector
|
||||
# Use HNSW index for pgvector
|
||||
op.create_index(
|
||||
"idx_memory_units_embedding",
|
||||
"memory_units",
|
||||
["embedding"],
|
||||
postgresql_using="hnsw",
|
||||
postgresql_ops={"embedding": "vector_cosine_ops"},
|
||||
)
|
||||
|
||||
# Create full-text search index on search_vector
|
||||
# Index type depends on text search backend
|
||||
if text_search_ext == "vchord":
|
||||
# VectorChord BM25 index
|
||||
op.execute("""
|
||||
CREATE INDEX idx_memory_units_text_search ON memory_units
|
||||
USING bm25 (search_vector bm25_catalog.bm25_ops)
|
||||
""")
|
||||
elif text_search_ext == "pg_textsearch":
|
||||
# Timescale pg_textsearch BM25 index on text column
|
||||
# Note: pg_textsearch doesn't support expressions, so we index the main text column
|
||||
op.execute("""
|
||||
CREATE INDEX idx_memory_units_text_search ON memory_units
|
||||
USING bm25(text)
|
||||
WITH (text_config='english')
|
||||
""")
|
||||
else: # native
|
||||
# Native PostgreSQL GIN index
|
||||
op.execute("""
|
||||
CREATE INDEX idx_memory_units_text_search ON memory_units
|
||||
USING gin(search_vector)
|
||||
""")
|
||||
|
||||
op.execute("""
|
||||
CREATE MATERIALIZED VIEW memory_units_bm25 AS
|
||||
+70
@@ -0,0 +1,70 @@
|
||||
"""Add file_storage table for BYTEA-based file storage
|
||||
|
||||
Revision ID: a1b2c3d4e5f6
|
||||
Revises: y0t1u2v3w4x5
|
||||
Create Date: 2026-02-16
|
||||
|
||||
Creates a dedicated table for storing uploaded files using BYTEA.
|
||||
This provides zero-config file storage that "just works" for development
|
||||
and small deployments. For production/scale, use S3-compatible storage.
|
||||
|
||||
Files are stored in a separate table to avoid bloating the documents table.
|
||||
"""
|
||||
|
||||
from collections.abc import Sequence
|
||||
|
||||
from alembic import context, op
|
||||
|
||||
revision: str = "a1b2c3d4e5f6"
|
||||
down_revision: str | Sequence[str] | None = "y0t1u2v3w4x5"
|
||||
branch_labels: str | Sequence[str] | None = None
|
||||
depends_on: str | Sequence[str] | None = None
|
||||
|
||||
|
||||
def _get_schema_prefix() -> str:
|
||||
"""Get schema prefix for table names (required for multi-tenant support)."""
|
||||
schema = context.config.get_main_option("target_schema")
|
||||
return f'"{schema}".' if schema else ""
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
"""Create file_storage table for BYTEA storage."""
|
||||
schema = _get_schema_prefix()
|
||||
|
||||
# Create file_storage table (minimal: just key + data)
|
||||
op.execute(
|
||||
f"""
|
||||
CREATE TABLE IF NOT EXISTS {schema}file_storage (
|
||||
storage_key TEXT PRIMARY KEY,
|
||||
data BYTEA NOT NULL
|
||||
)
|
||||
"""
|
||||
)
|
||||
|
||||
# Add file tracking columns to documents table
|
||||
op.execute(
|
||||
f"""
|
||||
ALTER TABLE {schema}documents
|
||||
ADD COLUMN IF NOT EXISTS file_storage_key TEXT,
|
||||
ADD COLUMN IF NOT EXISTS file_original_name TEXT,
|
||||
ADD COLUMN IF NOT EXISTS file_content_type TEXT
|
||||
"""
|
||||
)
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
"""Remove file_storage table and related columns."""
|
||||
schema = _get_schema_prefix()
|
||||
|
||||
# Drop columns from documents table
|
||||
op.execute(
|
||||
f"""
|
||||
ALTER TABLE {schema}documents
|
||||
DROP COLUMN IF EXISTS file_storage_key,
|
||||
DROP COLUMN IF EXISTS file_original_name,
|
||||
DROP COLUMN IF EXISTS file_content_type
|
||||
"""
|
||||
)
|
||||
|
||||
# Drop file_storage table
|
||||
op.execute(f"DROP TABLE IF EXISTS {schema}file_storage")
|
||||
+88
@@ -0,0 +1,88 @@
|
||||
"""Add text_signals column to memory_units for enriched BM25 indexing.
|
||||
|
||||
text_signals stores a denormalized space-separated string of entity names
|
||||
(and future signals) to improve full-text search recall without polluting
|
||||
the stored fact text.
|
||||
|
||||
- vchord: text_signals included in tokenize() at insert time
|
||||
- native: search_vector GENERATED column regenerated to include text_signals
|
||||
- pg_textsearch: no change (index only supports a single base column)
|
||||
|
||||
Revision ID: a2b3c4d5e6f7
|
||||
Revises: z1u2v3w4x5y6
|
||||
Create Date: 2026-02-28
|
||||
"""
|
||||
|
||||
import os
|
||||
from collections.abc import Sequence
|
||||
|
||||
from alembic import context, op
|
||||
|
||||
revision: str = "a2b3c4d5e6f7"
|
||||
down_revision: str | Sequence[str] | None = "aa2b3c4d5e6f"
|
||||
branch_labels: str | Sequence[str] | None = None
|
||||
depends_on: str | Sequence[str] | None = None
|
||||
|
||||
|
||||
def _get_schema_prefix() -> str:
|
||||
schema = context.config.get_main_option("target_schema")
|
||||
return f'"{schema}".' if schema else ""
|
||||
|
||||
|
||||
def _detect_text_search_extension() -> str:
|
||||
return os.getenv("HINDSIGHT_API_TEXT_SEARCH_EXTENSION", "native").lower()
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
table = f"{schema}memory_units"
|
||||
text_search_ext = _detect_text_search_extension()
|
||||
|
||||
# Add text_signals column (nullable TEXT, populated at retain time)
|
||||
op.execute(f"ALTER TABLE {table} ADD COLUMN IF NOT EXISTS text_signals TEXT")
|
||||
|
||||
if text_search_ext == "native":
|
||||
# Native PostgreSQL: drop and recreate the GENERATED tsvector column to include text_signals
|
||||
op.execute(f"ALTER TABLE {table} DROP COLUMN IF EXISTS search_vector")
|
||||
op.execute(f"""
|
||||
ALTER TABLE {table}
|
||||
ADD COLUMN search_vector tsvector
|
||||
GENERATED ALWAYS AS (
|
||||
to_tsvector('english',
|
||||
COALESCE(text, '') || ' ' ||
|
||||
COALESCE(context, '') || ' ' ||
|
||||
COALESCE(text_signals, '')
|
||||
)
|
||||
) STORED
|
||||
""")
|
||||
# Recreate GIN index (was dropped with the column)
|
||||
op.execute(f"""
|
||||
CREATE INDEX IF NOT EXISTS idx_memory_units_text_search
|
||||
ON {table} USING gin(search_vector)
|
||||
""")
|
||||
|
||||
# vchord: tokenize() call in fact_storage.py is updated to include text_signals at insert time
|
||||
# pg_textsearch: no change — index operates on the base `text` column only
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
table = f"{schema}memory_units"
|
||||
text_search_ext = _detect_text_search_extension()
|
||||
|
||||
if text_search_ext == "native":
|
||||
op.execute(f"DROP INDEX IF EXISTS {schema}idx_memory_units_text_search")
|
||||
op.execute(f"ALTER TABLE {table} DROP COLUMN IF EXISTS search_vector")
|
||||
op.execute(f"""
|
||||
ALTER TABLE {table}
|
||||
ADD COLUMN search_vector tsvector
|
||||
GENERATED ALWAYS AS (
|
||||
to_tsvector('english', COALESCE(text, '') || ' ' || COALESCE(context, ''))
|
||||
) STORED
|
||||
""")
|
||||
op.execute(f"""
|
||||
CREATE INDEX idx_memory_units_text_search
|
||||
ON {table} USING gin(search_vector)
|
||||
""")
|
||||
|
||||
op.execute(f"ALTER TABLE {table} DROP COLUMN IF EXISTS text_signals")
|
||||
+54
@@ -0,0 +1,54 @@
|
||||
"""Add GIN index on source_memory_ids for observation lookup performance
|
||||
|
||||
Without this index, queries using the array overlap operator (&&) or array
|
||||
containment (@>) on source_memory_ids require a full sequential scan over all
|
||||
observation memory_units. At ~77k observations this was measured at 45ms per
|
||||
query, becoming a bottleneck during consolidation recall (57-64s timeouts) and
|
||||
user recall (18-27s average).
|
||||
|
||||
The GIN index reduces these queries to index scans: 45ms → 0.049ms (927x
|
||||
speedup). Recall dropped from 18-27s to ~6s, and consolidation recall
|
||||
stabilised from timeout to ~15s.
|
||||
|
||||
Created with CONCURRENTLY so the migration does not block reads or writes.
|
||||
CONCURRENTLY requires running outside a transaction block, so the migration
|
||||
emits an explicit COMMIT before the statement and uses IF NOT EXISTS for
|
||||
idempotency.
|
||||
|
||||
Revision ID: a2b3c4d5e6f8
|
||||
Revises: f7g8h9i0j1k2
|
||||
Create Date: 2026-03-04
|
||||
"""
|
||||
|
||||
from collections.abc import Sequence
|
||||
|
||||
from alembic import context, op
|
||||
|
||||
revision: str = "a2b3c4d5e6f8"
|
||||
down_revision: str | Sequence[str] | None = "f7g8h9i0j1k2"
|
||||
branch_labels: str | Sequence[str] | None = None
|
||||
depends_on: str | Sequence[str] | None = None
|
||||
|
||||
|
||||
def _get_schema_prefix() -> str:
|
||||
schema = context.config.get_main_option("target_schema")
|
||||
return f'"{schema}".' if schema else ""
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
|
||||
# CREATE INDEX CONCURRENTLY cannot run inside a transaction block.
|
||||
# Commit the current Alembic transaction first.
|
||||
op.execute("COMMIT")
|
||||
op.execute(
|
||||
f"CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_memory_units_source_memory_ids "
|
||||
f"ON {schema}memory_units USING GIN (source_memory_ids) "
|
||||
f"WHERE source_memory_ids IS NOT NULL"
|
||||
)
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
op.execute("COMMIT")
|
||||
op.execute(f"DROP INDEX CONCURRENTLY IF EXISTS {schema}idx_memory_units_source_memory_ids")
|
||||
+52
@@ -0,0 +1,52 @@
|
||||
"""Add consolidation_failed_at column to memory_units for tracking persistent LLM failures.
|
||||
|
||||
When all LLM retries are exhausted on a single-memory batch, the memory is marked
|
||||
with consolidation_failed_at instead of consolidated_at, so it is not silently lost
|
||||
and can be retried later via the API.
|
||||
|
||||
Revision ID: a3b4c5d6e7f8
|
||||
Revises: g7h8i9j0k1l2
|
||||
Create Date: 2026-03-17
|
||||
"""
|
||||
|
||||
from collections.abc import Sequence
|
||||
|
||||
from alembic import context, op
|
||||
|
||||
revision: str = "a3b4c5d6e7f8"
|
||||
down_revision: str | Sequence[str] | None = "g7h8i9j0k1l2"
|
||||
branch_labels: str | Sequence[str] | None = None
|
||||
depends_on: str | Sequence[str] | None = None
|
||||
|
||||
|
||||
def _get_schema_prefix() -> str:
|
||||
"""Get schema prefix for table names (required for multi-tenant support)."""
|
||||
schema = context.config.get_main_option("target_schema")
|
||||
return f'"{schema}".' if schema else ""
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
|
||||
op.execute(
|
||||
f"""
|
||||
ALTER TABLE {schema}memory_units
|
||||
ADD COLUMN IF NOT EXISTS consolidation_failed_at TIMESTAMPTZ DEFAULT NULL
|
||||
"""
|
||||
)
|
||||
|
||||
# Index to efficiently query memories that failed consolidation for a given bank
|
||||
op.execute(
|
||||
f"""
|
||||
CREATE INDEX IF NOT EXISTS idx_memory_units_consolidation_failed
|
||||
ON {schema}memory_units (bank_id, consolidation_failed_at)
|
||||
WHERE consolidation_failed_at IS NOT NULL AND fact_type IN ('experience', 'world')
|
||||
"""
|
||||
)
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
|
||||
op.execute(f"DROP INDEX IF EXISTS {schema}idx_memory_units_consolidation_failed")
|
||||
op.execute(f"ALTER TABLE {schema}memory_units DROP COLUMN IF EXISTS consolidation_failed_at")
|
||||
@@ -0,0 +1,36 @@
|
||||
"""Make event_date nullable in memory_units to support timestamp-free content
|
||||
|
||||
Revision ID: aa2b3c4d5e6f
|
||||
Revises: z1u2v3w4x5y6
|
||||
Create Date: 2026-03-02
|
||||
|
||||
When callers retain content without a timestamp (e.g. fictional documents, static text),
|
||||
the event_date column should be allowed to be NULL rather than defaulting to utcnow().
|
||||
"""
|
||||
|
||||
from collections.abc import Sequence
|
||||
|
||||
from alembic import context, op
|
||||
|
||||
revision: str = "aa2b3c4d5e6f"
|
||||
down_revision: str | Sequence[str] | None = "z1u2v3w4x5y6"
|
||||
branch_labels: str | Sequence[str] | None = None
|
||||
depends_on: str | Sequence[str] | None = None
|
||||
|
||||
|
||||
def _get_schema_prefix() -> str:
|
||||
"""Get schema prefix for table names (required for multi-tenant support)."""
|
||||
schema = context.config.get_main_option("target_schema")
|
||||
return f'"{schema}".' if schema else ""
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
op.execute(f"ALTER TABLE {schema}memory_units ALTER COLUMN event_date DROP NOT NULL")
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
# Backfill NULLs with now() before restoring the NOT NULL constraint
|
||||
op.execute(f"UPDATE {schema}memory_units SET event_date = now() WHERE event_date IS NULL")
|
||||
op.execute(f"ALTER TABLE {schema}memory_units ALTER COLUMN event_date SET NOT NULL")
|
||||
+68
@@ -0,0 +1,68 @@
|
||||
"""Add partial indexes on memory_units temporal date fields for fast temporal retrieval
|
||||
|
||||
Revision ID: b3c4d5e6f7g8
|
||||
Revises: c1a2b3d4e5f6
|
||||
Create Date: 2026-03-02
|
||||
|
||||
The temporal retrieval entry-point query filters memory_units by occurred_start,
|
||||
occurred_end, and mentioned_at using OR conditions. Without dedicated indexes the
|
||||
planner falls back to a sequential scan of all bank rows after applying the
|
||||
(bank_id, fact_type) index, then re-checks each date field.
|
||||
|
||||
These three partial indexes give the planner bitmap-index scan options for the
|
||||
three most common date predicates, dramatically reducing the row set before any
|
||||
embedding computation is required.
|
||||
|
||||
All indexes are created CONCURRENTLY so the migration does not block writes on
|
||||
memory_units during production deployments. CONCURRENTLY requires running outside
|
||||
a transaction block; see migrations.py for how this is handled safely.
|
||||
"""
|
||||
|
||||
from collections.abc import Sequence
|
||||
|
||||
from alembic import context, op
|
||||
|
||||
revision: str = "b3c4d5e6f7g8"
|
||||
down_revision: str | Sequence[str] | None = "c1a2b3d4e5f6"
|
||||
branch_labels: str | Sequence[str] | None = None
|
||||
depends_on: str | Sequence[str] | None = None
|
||||
|
||||
|
||||
def _get_schema_prefix() -> str:
|
||||
schema = context.config.get_main_option("target_schema")
|
||||
return f'"{schema}".' if schema else ""
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
# Partial index on occurred_start (covers "occurred_start BETWEEN $4 AND $5")
|
||||
op.execute("COMMIT")
|
||||
op.execute(
|
||||
f"CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_memory_units_bank_occurred_start "
|
||||
f"ON {schema}memory_units(bank_id, fact_type, occurred_start) "
|
||||
f"WHERE occurred_start IS NOT NULL"
|
||||
)
|
||||
# Partial index on occurred_end (covers "occurred_end BETWEEN $4 AND $5")
|
||||
op.execute("COMMIT")
|
||||
op.execute(
|
||||
f"CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_memory_units_bank_occurred_end "
|
||||
f"ON {schema}memory_units(bank_id, fact_type, occurred_end) "
|
||||
f"WHERE occurred_end IS NOT NULL"
|
||||
)
|
||||
# Partial index on mentioned_at (covers "mentioned_at BETWEEN $4 AND $5")
|
||||
op.execute("COMMIT")
|
||||
op.execute(
|
||||
f"CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_memory_units_bank_mentioned_at "
|
||||
f"ON {schema}memory_units(bank_id, fact_type, mentioned_at) "
|
||||
f"WHERE mentioned_at IS NOT NULL"
|
||||
)
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
op.execute("COMMIT")
|
||||
op.execute(f"DROP INDEX CONCURRENTLY IF EXISTS {schema}idx_memory_units_bank_mentioned_at")
|
||||
op.execute("COMMIT")
|
||||
op.execute(f"DROP INDEX CONCURRENTLY IF EXISTS {schema}idx_memory_units_bank_occurred_end")
|
||||
op.execute("COMMIT")
|
||||
op.execute(f"DROP INDEX CONCURRENTLY IF EXISTS {schema}idx_memory_units_bank_occurred_start")
|
||||
+34
@@ -0,0 +1,34 @@
|
||||
"""Backfill observation_scopes column if missing.
|
||||
|
||||
This migration ensures observation_scopes exists even on databases that had
|
||||
revision z1u2v3w4x5y6 applied when it referred to the old text_signals migration
|
||||
(before it was renamed to a2b3c4d5e6f7). The ADD COLUMN IF NOT EXISTS makes this
|
||||
a no-op on databases that already have the column.
|
||||
|
||||
Revision ID: b4c5d6e7f8a9
|
||||
Revises: a2b3c4d5e6f7
|
||||
Create Date: 2026-03-02
|
||||
"""
|
||||
|
||||
from collections.abc import Sequence
|
||||
|
||||
from alembic import context, op
|
||||
|
||||
revision: str = "b4c5d6e7f8a9"
|
||||
down_revision: str | Sequence[str] | None = "a2b3c4d5e6f7"
|
||||
branch_labels: str | Sequence[str] | None = None
|
||||
depends_on: str | Sequence[str] | None = None
|
||||
|
||||
|
||||
def _get_schema_prefix() -> str:
|
||||
schema = context.config.get_main_option("target_schema")
|
||||
return f'"{schema}".' if schema else ""
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
op.execute(f"ALTER TABLE {schema}memory_units ADD COLUMN IF NOT EXISTS observation_scopes JSONB")
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
pass # intentionally no-op — safe to leave the column in place
|
||||
+46
@@ -0,0 +1,46 @@
|
||||
"""Enable pg_trgm extension and add GIN trigram index on entities.canonical_name
|
||||
|
||||
Revision ID: c1a2b3d4e5f6
|
||||
Revises: b4c5d6e7f8a9
|
||||
Create Date: 2026-03-02
|
||||
|
||||
Index is created CONCURRENTLY so the migration does not block writes on entities
|
||||
during production deployments. CONCURRENTLY requires running outside a transaction
|
||||
block; see migrations.py for how this is handled safely.
|
||||
"""
|
||||
|
||||
from collections.abc import Sequence
|
||||
|
||||
from alembic import context, op
|
||||
|
||||
revision: str = "c1a2b3d4e5f6"
|
||||
down_revision: str | Sequence[str] | None = "b4c5d6e7f8a9"
|
||||
branch_labels: str | Sequence[str] | None = None
|
||||
depends_on: str | Sequence[str] | None = None
|
||||
|
||||
|
||||
def _get_schema_prefix() -> str:
|
||||
schema = context.config.get_main_option("target_schema")
|
||||
return f'"{schema}".' if schema else ""
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
# pg_trgm ships with every standard PostgreSQL installation as a contrib module.
|
||||
# It enables fast similarity lookups via GIN indexes, used for entity name matching.
|
||||
op.execute("CREATE EXTENSION IF NOT EXISTS pg_trgm")
|
||||
|
||||
schema = _get_schema_prefix()
|
||||
# GIN index on canonical_name enables sub-millisecond trigram similarity queries
|
||||
# (% operator, similarity()) instead of full-table scans across all bank entities.
|
||||
op.execute("COMMIT")
|
||||
op.execute(
|
||||
f"CREATE INDEX CONCURRENTLY IF NOT EXISTS entities_canonical_name_trgm_idx "
|
||||
f"ON {schema}entities USING GIN (canonical_name gin_trgm_ops)"
|
||||
)
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
op.execute("COMMIT")
|
||||
op.execute(f"DROP INDEX CONCURRENTLY IF EXISTS {schema}entities_canonical_name_trgm_idx")
|
||||
# Note: not dropping pg_trgm extension as other indexes may depend on it
|
||||
+30
@@ -0,0 +1,30 @@
|
||||
"""Add history column to mental_models
|
||||
|
||||
Revision ID: c3d4e5f6g7h8
|
||||
Revises: a2b3c4d5e6f7, a2b3c4d5e6f8
|
||||
Create Date: 2026-03-06
|
||||
"""
|
||||
|
||||
from collections.abc import Sequence
|
||||
|
||||
from alembic import context, op
|
||||
|
||||
revision: str = "c3d4e5f6g7h8"
|
||||
down_revision: str | Sequence[str] | None = ("a2b3c4d5e6f7", "a2b3c4d5e6f8")
|
||||
branch_labels: str | Sequence[str] | None = None
|
||||
depends_on: str | Sequence[str] | None = None
|
||||
|
||||
|
||||
def _get_schema_prefix() -> str:
|
||||
schema = context.config.get_main_option("target_schema")
|
||||
return f'"{schema}".' if schema else ""
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
op.execute(f"ALTER TABLE {schema}mental_models ADD COLUMN IF NOT EXISTS history JSONB DEFAULT '[]'::jsonb")
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
op.execute(f"ALTER TABLE {schema}mental_models DROP COLUMN IF EXISTS history")
|
||||
+83
@@ -0,0 +1,83 @@
|
||||
"""Add covering and composite indexes to speed up link expansion graph retrieval.
|
||||
|
||||
Two indexes target the two bottlenecks identified by EXPLAIN ANALYZE on a 17M-row
|
||||
memory_links table:
|
||||
|
||||
1. idx_memory_links_to_type_weight (to_unit_id, link_type, weight DESC)
|
||||
The semantic incoming direction — finding facts that consider seeds as their
|
||||
nearest neighbour — currently hits an expensive BitmapAnd of two separate
|
||||
bitmap scans (to_unit_id bitmap ∩ link_type bitmap). A composite index
|
||||
on (to_unit_id, link_type) turns this into a single index scan and reduces
|
||||
latency from ~36 ms to < 5 ms per query.
|
||||
|
||||
2. idx_memory_links_entity_covering (from_unit_id) INCLUDE (to_unit_id, entity_id)
|
||||
WHERE link_type = 'entity'
|
||||
The entity co-occurrence expansion uses COUNT(DISTINCT ml.entity_id) and
|
||||
joins on ml.to_unit_id. Without a covering index the planner must read
|
||||
~2 500 heap pages to fetch entity_id and to_unit_id after the bitmap index
|
||||
scan, adding ~230 ms of random I/O. INCLUDE adds those two columns to the
|
||||
index leaf pages so the entire query can be served from the index (index-only
|
||||
scan), eliminating the heap reads entirely.
|
||||
Partial index (WHERE link_type = 'entity') keeps index size ~40 % smaller.
|
||||
|
||||
Both indexes are created with CONCURRENTLY so the migration does not block
|
||||
concurrent reads or writes on memory_links. CONCURRENTLY requires running
|
||||
outside a transaction block, so the migration emits an explicit COMMIT before
|
||||
each statement and uses IF NOT EXISTS for idempotency.
|
||||
|
||||
Revision ID: d2e3f4a5b6c7
|
||||
Revises: b3c4d5e6f7g8
|
||||
Create Date: 2026-03-02
|
||||
"""
|
||||
|
||||
from collections.abc import Sequence
|
||||
|
||||
from alembic import context, op
|
||||
|
||||
revision: str = "d2e3f4a5b6c7"
|
||||
down_revision: str | Sequence[str] | None = "b3c4d5e6f7g8"
|
||||
branch_labels: str | Sequence[str] | None = None
|
||||
depends_on: str | Sequence[str] | None = None
|
||||
|
||||
|
||||
def _get_schema_prefix() -> str:
|
||||
schema = context.config.get_main_option("target_schema")
|
||||
return f'"{schema}".' if schema else ""
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
|
||||
# CREATE INDEX CONCURRENTLY cannot run inside a transaction block.
|
||||
# Commit the current Alembic transaction, then issue each CONCURRENTLY
|
||||
# statement in its own implicit autocommit transaction.
|
||||
# IF NOT EXISTS makes each statement idempotent if the migration is retried.
|
||||
|
||||
# Index for the semantic *incoming* direction in link_expansion_retrieval.py.
|
||||
# Replaces the BitmapAnd of idx_memory_links_to_unit ∩ idx_memory_links_link_type
|
||||
# with a single composite index scan.
|
||||
op.execute("COMMIT")
|
||||
op.execute(
|
||||
f"CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_memory_links_to_type_weight "
|
||||
f"ON {schema}memory_links(to_unit_id, link_type, weight DESC)"
|
||||
)
|
||||
|
||||
# Covering index for entity co-occurrence expansion.
|
||||
# Enables an index-only scan: entity_id and to_unit_id are read from the
|
||||
# index leaf pages instead of the heap, eliminating ~2 500 random heap-page
|
||||
# reads per expansion query.
|
||||
op.execute("COMMIT")
|
||||
op.execute(
|
||||
f"CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_memory_links_entity_covering "
|
||||
f"ON {schema}memory_links(from_unit_id) "
|
||||
f"INCLUDE (to_unit_id, entity_id) "
|
||||
f"WHERE link_type = 'entity'"
|
||||
)
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
op.execute("COMMIT")
|
||||
op.execute(f"DROP INDEX CONCURRENTLY IF EXISTS {schema}idx_memory_links_entity_covering")
|
||||
op.execute("COMMIT")
|
||||
op.execute(f"DROP INDEX CONCURRENTLY IF EXISTS {schema}idx_memory_links_to_type_weight")
|
||||
+53
@@ -0,0 +1,53 @@
|
||||
"""Recreate idx_memory_units_source_memory_ids GIN index with fastupdate=off
|
||||
|
||||
GIN indexes use a "fastupdate" pending list by default: small writes are
|
||||
buffered there and flushed to the main GIN tree in bulk. Flushing requires
|
||||
AccessExclusiveLock on the index. Under high insert concurrency (e.g. 8
|
||||
parallel pytest-xdist workers all calling retain_async) two transactions can
|
||||
each trigger a flush simultaneously and deadlock.
|
||||
|
||||
Disabling fastupdate makes every insert write directly to the GIN tree
|
||||
(slightly slower per insert, but no pending-list lock cycles).
|
||||
|
||||
Revision ID: d4e5f6g7h8i9
|
||||
Revises: d5e6f7a8b9c0
|
||||
Create Date: 2026-03-11
|
||||
"""
|
||||
|
||||
from collections.abc import Sequence
|
||||
|
||||
from alembic import context, op
|
||||
|
||||
revision: str = "d4e5f6g7h8i9"
|
||||
down_revision: str | Sequence[str] | None = "d5e6f7a8b9c0"
|
||||
branch_labels: str | Sequence[str] | None = None
|
||||
depends_on: str | Sequence[str] | None = None
|
||||
|
||||
|
||||
def _get_schema_prefix() -> str:
|
||||
schema = context.config.get_main_option("target_schema")
|
||||
return f'"{schema}".' if schema else ""
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
# DROP + CREATE CONCURRENTLY must run outside a transaction block.
|
||||
op.execute("COMMIT")
|
||||
op.execute(f"DROP INDEX CONCURRENTLY IF EXISTS {schema}idx_memory_units_source_memory_ids")
|
||||
op.execute(
|
||||
f"CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_memory_units_source_memory_ids "
|
||||
f"ON {schema}memory_units USING GIN (source_memory_ids) "
|
||||
f"WITH (fastupdate=off) "
|
||||
f"WHERE source_memory_ids IS NOT NULL"
|
||||
)
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
op.execute("COMMIT")
|
||||
op.execute(f"DROP INDEX CONCURRENTLY IF EXISTS {schema}idx_memory_units_source_memory_ids")
|
||||
op.execute(
|
||||
f"CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_memory_units_source_memory_ids "
|
||||
f"ON {schema}memory_units USING GIN (source_memory_ids) "
|
||||
f"WHERE source_memory_ids IS NOT NULL"
|
||||
)
|
||||
+131
@@ -0,0 +1,131 @@
|
||||
"""Add internal_id to banks and per-(bank, fact_type) partial HNSW indexes
|
||||
|
||||
Revision ID: d5e6f7a8b9c0
|
||||
Revises: a3b4c5d6e7f8
|
||||
Create Date: 2026-03-11
|
||||
|
||||
This migration:
|
||||
1. Adds internal_id UUID column to banks (stable identifier for index naming)
|
||||
2. Drops the global HNSW index (competes with per-bank partial indexes)
|
||||
3. Creates per-(bank_id, fact_type) partial HNSW indexes for all existing banks
|
||||
(new banks get indexes created at bank-creation time via bank_utils.create_bank_hnsw_indexes)
|
||||
|
||||
Why per-(bank, fact_type) indexes:
|
||||
- fact_type-only partial indexes are never chosen by the planner when bank_id is in the WHERE
|
||||
clause, because the idx_memory_units_bank_id B-tree index always wins at planning time.
|
||||
- Per-(bank, fact_type) partial indexes have both predicates matching → planner selects them.
|
||||
- The global HNSW index competes for larger partitions (world, observation) and must be dropped.
|
||||
|
||||
For large deployments, create indexes CONCURRENTLY before running this migration:
|
||||
SELECT internal_id, bank_id FROM banks;
|
||||
-- for each bank and each fact_type in (world, experience, observation):
|
||||
CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_mu_emb_{ft}_{uid16}
|
||||
ON memory_units USING hnsw (embedding vector_cosine_ops)
|
||||
WHERE fact_type = '{ft}' AND bank_id = '{bank_id}';
|
||||
DROP INDEX CONCURRENTLY IF EXISTS idx_memory_units_embedding;
|
||||
"""
|
||||
|
||||
from collections.abc import Sequence
|
||||
|
||||
from alembic import context, op
|
||||
from sqlalchemy import text
|
||||
|
||||
revision: str = "d5e6f7a8b9c0"
|
||||
down_revision: str | Sequence[str] | None = "c3d4e5f6g7h8"
|
||||
branch_labels: str | Sequence[str] | None = None
|
||||
depends_on: str | Sequence[str] | None = None
|
||||
|
||||
_HNSW_FACT_TYPES: dict[str, str] = {
|
||||
"world": "worl",
|
||||
"experience": "expr",
|
||||
"observation": "obsv",
|
||||
}
|
||||
|
||||
|
||||
def _get_schema_prefix() -> str:
|
||||
schema = context.config.get_main_option("target_schema")
|
||||
return f'"{schema}".' if schema else ""
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
|
||||
# 1. Add internal_id column to banks
|
||||
op.execute(
|
||||
f"ALTER TABLE {schema}banks ADD COLUMN IF NOT EXISTS internal_id UUID DEFAULT gen_random_uuid() NOT NULL"
|
||||
)
|
||||
op.execute(f"ALTER TABLE {schema}banks ADD CONSTRAINT banks_internal_id_unique UNIQUE (internal_id)")
|
||||
|
||||
# 2. Drop any fact_type-only partial HNSW indexes that may exist from prior migrations
|
||||
# (bank_id B-tree always wins over them when bank_id is in the WHERE clause)
|
||||
op.execute(f"DROP INDEX IF EXISTS {schema}idx_mu_emb_world")
|
||||
op.execute(f"DROP INDEX IF EXISTS {schema}idx_mu_emb_observation")
|
||||
op.execute(f"DROP INDEX IF EXISTS {schema}idx_mu_emb_experience")
|
||||
|
||||
# 4. Drop global HNSW index (competes with per-bank partial indexes)
|
||||
op.execute(f"DROP INDEX IF EXISTS {schema}idx_memory_units_embedding")
|
||||
|
||||
# 5. Create per-(bank, fact_type) partial HNSW indexes for all existing banks
|
||||
bind = op.get_bind()
|
||||
schema_name = context.config.get_main_option("target_schema")
|
||||
table_ref = f'"{schema_name}".memory_units' if schema_name else "memory_units"
|
||||
banks_ref = f'"{schema_name}".banks' if schema_name else "banks"
|
||||
|
||||
rows = bind.execute(text(f"SELECT bank_id, internal_id FROM {banks_ref}")).fetchall() # noqa: S608
|
||||
for row in rows:
|
||||
bank_id = row[0]
|
||||
internal_id = str(row[1]).replace("-", "")[:16]
|
||||
escaped_bank_id = bank_id.replace("'", "''")
|
||||
for ft, ft_short in _HNSW_FACT_TYPES.items():
|
||||
idx_name = f"idx_mu_emb_{ft_short}_{internal_id}"
|
||||
# Index name is schema-unqualified (indexes live in the schema of their table)
|
||||
bind.execute(
|
||||
text(
|
||||
f"CREATE INDEX IF NOT EXISTS {idx_name} "
|
||||
f"ON {table_ref} USING hnsw (embedding vector_cosine_ops) "
|
||||
f"WHERE fact_type = '{ft}' AND bank_id = '{escaped_bank_id}'"
|
||||
)
|
||||
)
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
|
||||
# Drop per-bank HNSW indexes (iterate existing banks)
|
||||
bind = op.get_bind()
|
||||
schema_name = context.config.get_main_option("target_schema")
|
||||
banks_ref = f'"{schema_name}".banks' if schema_name else "banks"
|
||||
|
||||
rows = bind.execute(text(f"SELECT internal_id FROM {banks_ref}")).fetchall() # noqa: S608
|
||||
for row in rows:
|
||||
internal_id = str(row[0]).replace("-", "")[:16]
|
||||
for ft_short in _HNSW_FACT_TYPES.values():
|
||||
idx_name = f"idx_mu_emb_{ft_short}_{internal_id}"
|
||||
bind.execute(text(f"DROP INDEX IF EXISTS {schema}{idx_name}"))
|
||||
|
||||
# Restore the global HNSW index
|
||||
table_ref = f'"{schema_name}".memory_units' if schema_name else "memory_units"
|
||||
op.execute(
|
||||
f"CREATE INDEX IF NOT EXISTS idx_memory_units_embedding ON {table_ref} USING hnsw (embedding vector_cosine_ops)"
|
||||
)
|
||||
|
||||
# Restore old fact_type-only partial indexes
|
||||
op.execute(
|
||||
f"CREATE INDEX IF NOT EXISTS idx_mu_emb_world "
|
||||
f"ON {table_ref} USING hnsw (embedding vector_cosine_ops) "
|
||||
f"WHERE fact_type = 'world'"
|
||||
)
|
||||
op.execute(
|
||||
f"CREATE INDEX IF NOT EXISTS idx_mu_emb_observation "
|
||||
f"ON {table_ref} USING hnsw (embedding vector_cosine_ops) "
|
||||
f"WHERE fact_type = 'observation'"
|
||||
)
|
||||
op.execute(
|
||||
f"CREATE INDEX IF NOT EXISTS idx_mu_emb_experience "
|
||||
f"ON {table_ref} USING hnsw (embedding vector_cosine_ops) "
|
||||
f"WHERE fact_type = 'experience'"
|
||||
)
|
||||
|
||||
# Drop internal_id column
|
||||
op.execute(f"ALTER TABLE {schema}banks DROP CONSTRAINT IF EXISTS banks_internal_id_unique")
|
||||
op.execute(f"ALTER TABLE {schema}banks DROP COLUMN IF EXISTS internal_id")
|
||||
@@ -0,0 +1,62 @@
|
||||
"""Add webhooks table and next_retry_at to async_operations.
|
||||
|
||||
Webhook deliveries are handled as async_operations tasks (operation_type='webhook_delivery')
|
||||
rather than a dedicated webhook_deliveries table.
|
||||
|
||||
Revision ID: e4f5a6b7c8d9
|
||||
Revises: d2e3f4a5b6c7
|
||||
Create Date: 2026-03-04
|
||||
"""
|
||||
|
||||
from collections.abc import Sequence
|
||||
|
||||
from alembic import context, op
|
||||
|
||||
revision: str = "e4f5a6b7c8d9"
|
||||
down_revision: str | Sequence[str] | None = "d2e3f4a5b6c7"
|
||||
branch_labels: str | Sequence[str] | None = None
|
||||
depends_on: str | Sequence[str] | None = None
|
||||
|
||||
|
||||
def _get_schema_prefix() -> str:
|
||||
schema = context.config.get_main_option("target_schema")
|
||||
return f'"{schema}".' if schema else ""
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
|
||||
op.execute(
|
||||
f"""
|
||||
CREATE TABLE IF NOT EXISTS {schema}webhooks (
|
||||
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||
bank_id TEXT,
|
||||
url TEXT NOT NULL,
|
||||
secret TEXT,
|
||||
event_types TEXT[] NOT NULL DEFAULT '{{}}',
|
||||
enabled BOOLEAN NOT NULL DEFAULT TRUE,
|
||||
created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
|
||||
updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW()
|
||||
)
|
||||
"""
|
||||
)
|
||||
|
||||
# Index for bank-scoped webhook lookup
|
||||
op.execute(f"CREATE INDEX IF NOT EXISTS idx_webhooks_bank_id ON {schema}webhooks(bank_id)")
|
||||
|
||||
# Add next_retry_at to async_operations for task-owned retry scheduling
|
||||
op.execute(f"ALTER TABLE {schema}async_operations ADD COLUMN IF NOT EXISTS next_retry_at TIMESTAMPTZ NULL")
|
||||
|
||||
# Index for polling: status + next_retry_at
|
||||
op.execute(
|
||||
f"CREATE INDEX IF NOT EXISTS idx_async_operations_status_retry "
|
||||
f"ON {schema}async_operations(status, next_retry_at)"
|
||||
)
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
op.execute(f"DROP INDEX IF EXISTS {schema}idx_async_operations_status_retry")
|
||||
op.execute(f"ALTER TABLE {schema}async_operations DROP COLUMN IF EXISTS next_retry_at")
|
||||
op.execute(f"DROP INDEX IF EXISTS {schema}idx_webhooks_bank_id")
|
||||
op.execute(f"DROP TABLE IF EXISTS {schema}webhooks")
|
||||
+73
@@ -0,0 +1,73 @@
|
||||
"""Add CASCADE DELETE FK from async_operations and webhooks to banks.
|
||||
|
||||
When a bank is deleted, all its async_operations and webhooks rows are
|
||||
automatically deleted by the database. This ensures that any in-flight
|
||||
worker tasks detect the deletion via _check_op_alive() and abort early.
|
||||
|
||||
Revision ID: e5f6g7h8i9j0
|
||||
Revises: d4e5f6g7h8i9
|
||||
Create Date: 2026-03-11
|
||||
"""
|
||||
|
||||
from collections.abc import Sequence
|
||||
|
||||
from alembic import context, op
|
||||
|
||||
revision: str = "e5f6g7h8i9j0"
|
||||
down_revision: str | Sequence[str] | None = "d4e5f6g7h8i9"
|
||||
branch_labels: str | Sequence[str] | None = None
|
||||
depends_on: str | Sequence[str] | None = None
|
||||
|
||||
|
||||
def _get_schema_prefix() -> str:
|
||||
schema = context.config.get_main_option("target_schema")
|
||||
return f'"{schema}".' if schema else ""
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
|
||||
# Remove orphaned async_operations rows whose bank no longer exists
|
||||
# (can happen because there was no FK before this migration).
|
||||
op.execute(
|
||||
f"""
|
||||
DELETE FROM {schema}async_operations
|
||||
WHERE bank_id IS NOT NULL
|
||||
AND bank_id NOT IN (SELECT bank_id FROM {schema}banks)
|
||||
"""
|
||||
)
|
||||
|
||||
# Remove orphaned webhooks rows whose bank no longer exists.
|
||||
op.execute(
|
||||
f"""
|
||||
DELETE FROM {schema}webhooks
|
||||
WHERE bank_id IS NOT NULL
|
||||
AND bank_id NOT IN (SELECT bank_id FROM {schema}banks)
|
||||
"""
|
||||
)
|
||||
|
||||
# Add FK with ON DELETE CASCADE so that deleting a bank automatically
|
||||
# cleans up all its pending/processing operations and webhook configs.
|
||||
op.execute(
|
||||
f"""
|
||||
ALTER TABLE {schema}async_operations
|
||||
ADD CONSTRAINT fk_async_operations_bank_id
|
||||
FOREIGN KEY (bank_id) REFERENCES {schema}banks(bank_id)
|
||||
ON DELETE CASCADE
|
||||
"""
|
||||
)
|
||||
|
||||
op.execute(
|
||||
f"""
|
||||
ALTER TABLE {schema}webhooks
|
||||
ADD CONSTRAINT fk_webhooks_bank_id
|
||||
FOREIGN KEY (bank_id) REFERENCES {schema}banks(bank_id)
|
||||
ON DELETE CASCADE
|
||||
"""
|
||||
)
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
op.execute(f"ALTER TABLE {schema}async_operations DROP CONSTRAINT IF EXISTS fk_async_operations_bank_id")
|
||||
op.execute(f"ALTER TABLE {schema}webhooks DROP CONSTRAINT IF EXISTS fk_webhooks_bank_id")
|
||||
+38
@@ -0,0 +1,38 @@
|
||||
"""chunk_fk_cascade_delete
|
||||
|
||||
Revision ID: f6g7h8i9j0k1
|
||||
Revises: e5f6g7h8i9j0
|
||||
Create Date: 2026-03-16 00:00:00.000000
|
||||
|
||||
"""
|
||||
|
||||
from collections.abc import Sequence
|
||||
|
||||
from alembic import op
|
||||
|
||||
# revision identifiers, used by Alembic.
|
||||
revision: str = "f6g7h8i9j0k1"
|
||||
down_revision: str | Sequence[str] | None = "e5f6g7h8i9j0"
|
||||
branch_labels: str | Sequence[str] | None = None
|
||||
depends_on: str | Sequence[str] | None = None
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
"""Change memory_units.chunk_id FK from SET NULL to CASCADE.
|
||||
|
||||
When a document is deleted the CASCADE reaches chunks first; with SET NULL
|
||||
the memory_units rows survived with chunk_id = NULL, leaving ghost records.
|
||||
Switching to CASCADE ensures they are removed together with their chunk.
|
||||
"""
|
||||
op.drop_constraint("memory_units_chunk_fkey", "memory_units", type_="foreignkey")
|
||||
op.create_foreign_key(
|
||||
"memory_units_chunk_fkey", "memory_units", "chunks", ["chunk_id"], ["chunk_id"], ondelete="CASCADE"
|
||||
)
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
"""Revert to SET NULL behaviour."""
|
||||
op.drop_constraint("memory_units_chunk_fkey", "memory_units", type_="foreignkey")
|
||||
op.create_foreign_key(
|
||||
"memory_units_chunk_fkey", "memory_units", "chunks", ["chunk_id"], ["chunk_id"], ondelete="SET NULL"
|
||||
)
|
||||
+33
@@ -0,0 +1,33 @@
|
||||
"""Add http_config JSONB column to webhooks table.
|
||||
|
||||
Stores HTTP delivery configuration (method, timeout, headers, params) as a
|
||||
single JSONB column rather than separate columns.
|
||||
|
||||
Revision ID: f7g8h9i0j1k2
|
||||
Revises: e4f5a6b7c8d9
|
||||
Create Date: 2026-03-04
|
||||
"""
|
||||
|
||||
from collections.abc import Sequence
|
||||
|
||||
from alembic import context, op
|
||||
|
||||
revision: str = "f7g8h9i0j1k2"
|
||||
down_revision: str | Sequence[str] | None = "e4f5a6b7c8d9"
|
||||
branch_labels: str | Sequence[str] | None = None
|
||||
depends_on: str | Sequence[str] | None = None
|
||||
|
||||
|
||||
def _get_schema_prefix() -> str:
|
||||
schema = context.config.get_main_option("target_schema")
|
||||
return f'"{schema}".' if schema else ""
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
op.execute(f"ALTER TABLE {schema}webhooks ADD COLUMN IF NOT EXISTS http_config JSONB NOT NULL DEFAULT '{{}}'")
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
op.execute(f"ALTER TABLE {schema}webhooks DROP COLUMN IF EXISTS http_config")
|
||||
+71
@@ -0,0 +1,71 @@
|
||||
"""backsweep_orphan_memory_units
|
||||
|
||||
Two-pass cleanup of memory_units rows that were never removed by earlier bugs:
|
||||
|
||||
Pass 1 — any fact_type, bank gone:
|
||||
memory_units whose bank_id no longer exists in banks. These accumulate when
|
||||
a bank is deleted without a proper cascade (no FK from memory_units to banks
|
||||
exists in the schema).
|
||||
|
||||
Pass 2 — observations only, all sources gone:
|
||||
observation rows whose bank still exists but every source_memory_id points
|
||||
to a deleted memory unit. These were left behind before PR #580 fixed the
|
||||
chunk FK cascade and before delete_document() called
|
||||
_delete_stale_observations_for_memories.
|
||||
|
||||
Revision ID: g7h8i9j0k1l2
|
||||
Revises: f6g7h8i9j0k1
|
||||
Create Date: 2026-03-16
|
||||
"""
|
||||
|
||||
from collections.abc import Sequence
|
||||
|
||||
from alembic import context, op
|
||||
|
||||
revision: str = "g7h8i9j0k1l2"
|
||||
down_revision: str | Sequence[str] | None = "f6g7h8i9j0k1"
|
||||
branch_labels: str | Sequence[str] | None = None
|
||||
depends_on: str | Sequence[str] | None = None
|
||||
|
||||
|
||||
def _get_schema_prefix() -> str:
|
||||
schema = context.config.get_main_option("target_schema")
|
||||
return f'"{schema}".' if schema else ""
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
mu = f"{schema}memory_units"
|
||||
banks = f"{schema}banks"
|
||||
|
||||
# Pass 1: delete all memory_units (any fact_type) whose bank no longer exists.
|
||||
# There is no FK from memory_units to banks, so these never cascade away.
|
||||
op.execute(
|
||||
f"""
|
||||
DELETE FROM {mu}
|
||||
WHERE NOT EXISTS (
|
||||
SELECT 1 FROM {banks} b WHERE b.bank_id = {mu}.bank_id
|
||||
)
|
||||
"""
|
||||
)
|
||||
|
||||
# Pass 2: delete orphaned observations whose bank still exists but every
|
||||
# source_memory_id refers to a now-deleted memory unit (or the array is
|
||||
# empty). Observations with at least one surviving source are left alone.
|
||||
op.execute(
|
||||
f"""
|
||||
DELETE FROM {mu} orphan
|
||||
WHERE orphan.fact_type = 'observation'
|
||||
AND NOT EXISTS (
|
||||
SELECT 1
|
||||
FROM {mu} src
|
||||
WHERE src.id = ANY(orphan.source_memory_ids)
|
||||
AND src.bank_id = orphan.bank_id
|
||||
)
|
||||
"""
|
||||
)
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
# Deleted rows cannot be restored.
|
||||
pass
|
||||
+317
@@ -0,0 +1,317 @@
|
||||
"""learnings_and_pinned_reflections
|
||||
|
||||
Revision ID: n9i0j1k2l3m4
|
||||
Revises: m8h9i0j1k2l3
|
||||
Create Date: 2026-01-21 00:00:00.000000
|
||||
|
||||
This migration:
|
||||
1. Creates the 'learnings' table for automatic bottom-up consolidation
|
||||
2. Creates the 'pinned_reflections' table for user-curated living documents
|
||||
3. Adds consolidation tracking columns to the 'banks' table
|
||||
"""
|
||||
|
||||
import os
|
||||
from collections.abc import Sequence
|
||||
|
||||
from alembic import context, op
|
||||
from sqlalchemy import text
|
||||
|
||||
# revision identifiers, used by Alembic.
|
||||
revision: str = "n9i0j1k2l3m4"
|
||||
down_revision: str | Sequence[str] | None = "m8h9i0j1k2l3"
|
||||
branch_labels: str | Sequence[str] | None = None
|
||||
depends_on: str | Sequence[str] | None = None
|
||||
|
||||
|
||||
def _get_schema_prefix() -> str:
|
||||
"""Get schema prefix for table names (required for multi-tenant support)."""
|
||||
schema = context.config.get_main_option("target_schema")
|
||||
return f'"{schema}".' if schema else ""
|
||||
|
||||
|
||||
def _detect_vector_extension() -> str:
|
||||
"""
|
||||
Detect or validate vector extension: 'pgvector', 'vchord', or 'pgvectorscale'.
|
||||
Respects HINDSIGHT_API_VECTOR_EXTENSION env var if set.
|
||||
"""
|
||||
conn = op.get_bind()
|
||||
vector_extension = os.getenv("HINDSIGHT_API_VECTOR_EXTENSION", "pgvector").lower()
|
||||
|
||||
# Validate configured extension is installed
|
||||
if vector_extension == "pgvectorscale":
|
||||
# pgvectorscale/DiskANN requires pgvector
|
||||
pgvector_check = conn.execute(text("SELECT 1 FROM pg_extension WHERE extname = 'vector'")).scalar()
|
||||
if not pgvector_check:
|
||||
raise RuntimeError(
|
||||
"DiskANN requires pgvector. Install with: CREATE EXTENSION vector; then vectorscale or pg_diskann CASCADE;"
|
||||
)
|
||||
# Check for either vectorscale (open source) or pg_diskann (Azure)
|
||||
vectorscale_check = conn.execute(text("SELECT 1 FROM pg_extension WHERE extname = 'vectorscale'")).scalar()
|
||||
pg_diskann_check = conn.execute(text("SELECT 1 FROM pg_extension WHERE extname = 'pg_diskann'")).scalar()
|
||||
|
||||
if vectorscale_check:
|
||||
return "pgvectorscale"
|
||||
elif pg_diskann_check:
|
||||
return "pg_diskann"
|
||||
else:
|
||||
raise RuntimeError(
|
||||
"Configured vector extension 'pgvectorscale' not found. Install either:\n"
|
||||
" - pgvectorscale: CREATE EXTENSION vectorscale CASCADE;\n"
|
||||
" - pg_diskann (Azure): CREATE EXTENSION pg_diskann CASCADE;"
|
||||
)
|
||||
elif vector_extension == "vchord":
|
||||
vchord_check = conn.execute(text("SELECT 1 FROM pg_extension WHERE extname = 'vchord'")).scalar()
|
||||
if not vchord_check:
|
||||
raise RuntimeError(
|
||||
"Configured vector extension 'vchord' not found. Install it with: CREATE EXTENSION vchord CASCADE;"
|
||||
)
|
||||
return "vchord"
|
||||
elif vector_extension == "pgvector":
|
||||
pgvector_check = conn.execute(text("SELECT 1 FROM pg_extension WHERE extname = 'vector'")).scalar()
|
||||
if not pgvector_check:
|
||||
raise RuntimeError(
|
||||
"Configured vector extension 'pgvector' not found. Install it with: CREATE EXTENSION vector;"
|
||||
)
|
||||
return "pgvector"
|
||||
else:
|
||||
raise ValueError(
|
||||
f"Invalid HINDSIGHT_API_VECTOR_EXTENSION: {vector_extension}. Must be 'pgvector', 'vchord', or 'pgvectorscale'"
|
||||
)
|
||||
|
||||
|
||||
def _detect_text_search_extension() -> str:
|
||||
"""
|
||||
Detect or validate text search extension: 'native', 'vchord', or 'pg_textsearch'.
|
||||
Respects HINDSIGHT_API_TEXT_SEARCH_EXTENSION env var.
|
||||
Creates the extension if needed.
|
||||
"""
|
||||
text_search_extension = os.getenv("HINDSIGHT_API_TEXT_SEARCH_EXTENSION", "native").lower()
|
||||
|
||||
if text_search_extension == "vchord":
|
||||
# Create vchord_bm25 extension if not exists
|
||||
try:
|
||||
op.execute("CREATE EXTENSION IF NOT EXISTS vchord_bm25 CASCADE")
|
||||
except Exception:
|
||||
# Extension might already exist or user lacks permissions - verify it exists
|
||||
conn = op.get_bind()
|
||||
result = conn.execute(text("SELECT 1 FROM pg_extension WHERE extname = 'vchord_bm25'")).fetchone()
|
||||
if not result:
|
||||
# Extension truly doesn't exist - re-raise the error
|
||||
raise
|
||||
return "vchord"
|
||||
elif text_search_extension == "pg_textsearch":
|
||||
# Create pg_textsearch extension if not exists
|
||||
try:
|
||||
op.execute("CREATE EXTENSION IF NOT EXISTS pg_textsearch CASCADE")
|
||||
except Exception:
|
||||
# Extension might already exist or user lacks permissions - verify it exists
|
||||
conn = op.get_bind()
|
||||
result = conn.execute(text("SELECT 1 FROM pg_extension WHERE extname = 'pg_textsearch'")).fetchone()
|
||||
if not result:
|
||||
# Extension truly doesn't exist - re-raise the error
|
||||
raise
|
||||
return "pg_textsearch"
|
||||
elif text_search_extension == "native":
|
||||
return "native"
|
||||
else:
|
||||
raise ValueError(
|
||||
f"Invalid HINDSIGHT_API_TEXT_SEARCH_EXTENSION: {text_search_extension}. Must be 'native', 'vchord', or 'pg_textsearch'"
|
||||
)
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
"""Create learnings and pinned_reflections tables."""
|
||||
schema = _get_schema_prefix()
|
||||
|
||||
# Detect which vector extension is available
|
||||
vector_ext = _detect_vector_extension()
|
||||
|
||||
# Detect which text search extension to use
|
||||
text_search_ext = _detect_text_search_extension()
|
||||
|
||||
# 1. Create learnings table
|
||||
op.execute(f"""
|
||||
CREATE TABLE {schema}learnings (
|
||||
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||
bank_id VARCHAR(64) NOT NULL,
|
||||
text TEXT NOT NULL,
|
||||
proof_count INT NOT NULL DEFAULT 1,
|
||||
history JSONB DEFAULT '[]'::jsonb,
|
||||
mission_context VARCHAR(64),
|
||||
pre_mission_change BOOLEAN DEFAULT FALSE,
|
||||
embedding vector(384),
|
||||
tags VARCHAR[] DEFAULT ARRAY[]::VARCHAR[],
|
||||
created_at TIMESTAMP WITH TIME ZONE NOT NULL DEFAULT now(),
|
||||
updated_at TIMESTAMP WITH TIME ZONE NOT NULL DEFAULT now()
|
||||
)
|
||||
""")
|
||||
|
||||
# Add foreign key constraint
|
||||
op.execute(f"""
|
||||
ALTER TABLE {schema}learnings
|
||||
ADD CONSTRAINT fk_learnings_bank_id
|
||||
FOREIGN KEY (bank_id) REFERENCES {schema}banks(bank_id) ON DELETE CASCADE
|
||||
""")
|
||||
|
||||
# Indexes for learnings
|
||||
op.execute(f"CREATE INDEX idx_learnings_bank_id ON {schema}learnings(bank_id)")
|
||||
|
||||
# Create vector index based on detected extension
|
||||
if vector_ext == "pgvectorscale":
|
||||
op.execute(f"""
|
||||
CREATE INDEX idx_learnings_embedding ON {schema}learnings
|
||||
USING diskann (embedding vector_cosine_ops)
|
||||
WITH (num_neighbors = 50)
|
||||
""")
|
||||
elif vector_ext == "pg_diskann":
|
||||
op.execute(f"""
|
||||
CREATE INDEX idx_learnings_embedding ON {schema}learnings
|
||||
USING diskann (embedding vector_cosine_ops)
|
||||
WITH (max_neighbors = 50)
|
||||
""")
|
||||
elif vector_ext == "vchord":
|
||||
op.execute(f"""
|
||||
CREATE INDEX idx_learnings_embedding ON {schema}learnings
|
||||
USING vchordrq (embedding vector_l2_ops)
|
||||
""")
|
||||
else: # pgvector
|
||||
op.execute(f"""
|
||||
CREATE INDEX idx_learnings_embedding ON {schema}learnings
|
||||
USING hnsw (embedding vector_cosine_ops)
|
||||
""")
|
||||
|
||||
op.execute(f"CREATE INDEX idx_learnings_tags ON {schema}learnings USING GIN(tags)")
|
||||
|
||||
# Full-text search for learnings
|
||||
if text_search_ext == "vchord":
|
||||
# VectorChord BM25: bm25vector type (no GENERATED - tokenization happens on INSERT)
|
||||
# Note: vchord_bm25 extension creates types in bm25_catalog schema
|
||||
op.execute(f"""
|
||||
ALTER TABLE {schema}learnings ADD COLUMN search_vector bm25_catalog.bm25vector
|
||||
""")
|
||||
op.execute(f"""
|
||||
CREATE INDEX idx_learnings_text_search ON {schema}learnings
|
||||
USING bm25 (search_vector bm25_catalog.bm25_ops)
|
||||
""")
|
||||
elif text_search_ext == "pg_textsearch":
|
||||
# Timescale pg_textsearch: dummy TEXT column for consistency (indexes operate on base columns directly)
|
||||
op.execute(f"""
|
||||
ALTER TABLE {schema}learnings ADD COLUMN search_vector TEXT
|
||||
""")
|
||||
op.execute(f"""
|
||||
CREATE INDEX idx_learnings_text_search ON {schema}learnings
|
||||
USING bm25(text) WITH (text_config='english')
|
||||
""")
|
||||
else: # native
|
||||
# Native PostgreSQL: tsvector with automatic generation
|
||||
op.execute(f"""
|
||||
ALTER TABLE {schema}learnings ADD COLUMN search_vector tsvector
|
||||
GENERATED ALWAYS AS (to_tsvector('english', text)) STORED
|
||||
""")
|
||||
op.execute(f"CREATE INDEX idx_learnings_text_search ON {schema}learnings USING gin(search_vector)")
|
||||
|
||||
# 2. Create pinned_reflections table
|
||||
op.execute(f"""
|
||||
CREATE TABLE {schema}pinned_reflections (
|
||||
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||
bank_id VARCHAR(64) NOT NULL,
|
||||
name VARCHAR(256) NOT NULL,
|
||||
source_query TEXT NOT NULL,
|
||||
content TEXT NOT NULL,
|
||||
embedding vector(384),
|
||||
tags VARCHAR[] DEFAULT ARRAY[]::VARCHAR[],
|
||||
last_refreshed_at TIMESTAMP WITH TIME ZONE NOT NULL DEFAULT now(),
|
||||
created_at TIMESTAMP WITH TIME ZONE NOT NULL DEFAULT now()
|
||||
)
|
||||
""")
|
||||
|
||||
# Add foreign key constraint
|
||||
op.execute(f"""
|
||||
ALTER TABLE {schema}pinned_reflections
|
||||
ADD CONSTRAINT fk_pinned_reflections_bank_id
|
||||
FOREIGN KEY (bank_id) REFERENCES {schema}banks(bank_id) ON DELETE CASCADE
|
||||
""")
|
||||
|
||||
# Indexes for pinned_reflections
|
||||
op.execute(f"CREATE INDEX idx_pinned_reflections_bank_id ON {schema}pinned_reflections(bank_id)")
|
||||
|
||||
# Create vector index based on detected extension
|
||||
if vector_ext == "pgvectorscale":
|
||||
op.execute(f"""
|
||||
CREATE INDEX idx_pinned_reflections_embedding ON {schema}pinned_reflections
|
||||
USING diskann (embedding vector_cosine_ops)
|
||||
WITH (num_neighbors = 50)
|
||||
""")
|
||||
elif vector_ext == "pg_diskann":
|
||||
op.execute(f"""
|
||||
CREATE INDEX idx_pinned_reflections_embedding ON {schema}pinned_reflections
|
||||
USING diskann (embedding vector_cosine_ops)
|
||||
WITH (max_neighbors = 50)
|
||||
""")
|
||||
elif vector_ext == "vchord":
|
||||
op.execute(f"""
|
||||
CREATE INDEX idx_pinned_reflections_embedding ON {schema}pinned_reflections
|
||||
USING vchordrq (embedding vector_l2_ops)
|
||||
""")
|
||||
else: # pgvector
|
||||
op.execute(f"""
|
||||
CREATE INDEX idx_pinned_reflections_embedding ON {schema}pinned_reflections
|
||||
USING hnsw (embedding vector_cosine_ops)
|
||||
""")
|
||||
|
||||
op.execute(f"CREATE INDEX idx_pinned_reflections_tags ON {schema}pinned_reflections USING GIN(tags)")
|
||||
|
||||
# Full-text search for pinned_reflections
|
||||
if text_search_ext == "vchord":
|
||||
# VectorChord BM25: bm25vector type (no GENERATED - tokenization happens on INSERT/UPDATE)
|
||||
# Note: vchord_bm25 extension creates types in bm25_catalog schema
|
||||
op.execute(f"""
|
||||
ALTER TABLE {schema}pinned_reflections ADD COLUMN search_vector bm25_catalog.bm25vector
|
||||
""")
|
||||
op.execute(f"""
|
||||
CREATE INDEX idx_pinned_reflections_text_search ON {schema}pinned_reflections
|
||||
USING bm25 (search_vector bm25_catalog.bm25_ops)
|
||||
""")
|
||||
elif text_search_ext == "pg_textsearch":
|
||||
# Timescale pg_textsearch: dummy TEXT column for consistency (indexes operate on base columns directly)
|
||||
op.execute(f"""
|
||||
ALTER TABLE {schema}pinned_reflections ADD COLUMN search_vector TEXT
|
||||
""")
|
||||
op.execute(f"""
|
||||
CREATE INDEX idx_pinned_reflections_text_search ON {schema}pinned_reflections
|
||||
USING bm25(content)
|
||||
WITH (text_config='english')
|
||||
""")
|
||||
else: # native
|
||||
# Native PostgreSQL: tsvector with automatic generation
|
||||
op.execute(f"""
|
||||
ALTER TABLE {schema}pinned_reflections ADD COLUMN search_vector tsvector
|
||||
GENERATED ALWAYS AS (to_tsvector('english', COALESCE(name, '') || ' ' || content)) STORED
|
||||
""")
|
||||
op.execute(f"""
|
||||
CREATE INDEX idx_pinned_reflections_text_search ON {schema}pinned_reflections
|
||||
USING gin(search_vector)
|
||||
""")
|
||||
|
||||
# 3. Add consolidation tracking columns to banks table
|
||||
op.execute(f"""
|
||||
ALTER TABLE {schema}banks
|
||||
ADD COLUMN IF NOT EXISTS last_consolidated_at TIMESTAMP WITH TIME ZONE
|
||||
""")
|
||||
op.execute(f"""
|
||||
ALTER TABLE {schema}banks
|
||||
ADD COLUMN IF NOT EXISTS mission_changed_at TIMESTAMP WITH TIME ZONE
|
||||
""")
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
"""Drop learnings and pinned_reflections tables."""
|
||||
schema = _get_schema_prefix()
|
||||
|
||||
# Drop tables
|
||||
op.execute(f"DROP TABLE IF EXISTS {schema}learnings CASCADE")
|
||||
op.execute(f"DROP TABLE IF EXISTS {schema}pinned_reflections CASCADE")
|
||||
|
||||
# Remove columns from banks
|
||||
op.execute(f"ALTER TABLE {schema}banks DROP COLUMN IF EXISTS last_consolidated_at")
|
||||
op.execute(f"ALTER TABLE {schema}banks DROP COLUMN IF EXISTS mission_changed_at")
|
||||
+64
@@ -0,0 +1,64 @@
|
||||
"""Add config JSONB column to banks table for hierarchical configuration
|
||||
|
||||
Revision ID: x9s0t1u2v3w4
|
||||
Revises: w8r9s0t1u2v3
|
||||
Create Date: 2026-02-09
|
||||
|
||||
This migration adds a `config` JSONB column to the banks table to support
|
||||
per-bank configuration overrides. This enables hierarchical configuration where:
|
||||
- Global config is loaded from environment variables
|
||||
- Tenant config is provided via TenantExtension
|
||||
- Bank config overrides are stored in banks.config JSONB column
|
||||
|
||||
The config column stores overrides for hierarchical fields (LLM settings,
|
||||
retention parameters, retrieval settings, etc.) in Python field name format.
|
||||
"""
|
||||
|
||||
from collections.abc import Sequence
|
||||
|
||||
import sqlalchemy as sa
|
||||
from alembic import context, op
|
||||
from sqlalchemy.dialects.postgresql import JSONB
|
||||
|
||||
revision: str = "x9s0t1u2v3w4"
|
||||
down_revision: str | Sequence[str] | None = "w8r9s0t1u2v3"
|
||||
branch_labels: str | Sequence[str] | None = None
|
||||
depends_on: str | Sequence[str] | None = None
|
||||
|
||||
|
||||
def _get_schema_prefix() -> str:
|
||||
"""Get schema prefix for table names (required for multi-tenant support)."""
|
||||
schema = context.config.get_main_option("target_schema")
|
||||
return f'"{schema}".' if schema else ""
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
"""Add config JSONB column to banks table with GIN index."""
|
||||
schema = _get_schema_prefix()
|
||||
|
||||
# Add config column to banks table
|
||||
op.execute(f"""
|
||||
ALTER TABLE {schema}banks
|
||||
ADD COLUMN config JSONB NOT NULL DEFAULT '{{}}'::jsonb
|
||||
""")
|
||||
|
||||
# Add GIN index for efficient JSONB queries
|
||||
op.execute(f"""
|
||||
CREATE INDEX idx_banks_config
|
||||
ON {schema}banks
|
||||
USING gin(config)
|
||||
""")
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
"""Remove config column and index from banks table."""
|
||||
schema = _get_schema_prefix()
|
||||
|
||||
# Drop index first
|
||||
op.execute(f"DROP INDEX IF EXISTS {schema}idx_banks_config")
|
||||
|
||||
# Drop column
|
||||
op.execute(f"""
|
||||
ALTER TABLE {schema}banks
|
||||
DROP COLUMN IF EXISTS config
|
||||
""")
|
||||
+49
@@ -0,0 +1,49 @@
|
||||
"""Add GIN index on async_operations.result_metadata for parent_operation_id queries
|
||||
|
||||
Revision ID: y0t1u2v3w4x5
|
||||
Revises: x9s0t1u2v3w4
|
||||
Create Date: 2026-02-13
|
||||
|
||||
This migration adds a GIN index on the result_metadata JSONB column in the
|
||||
async_operations table to support efficient queries for child operations by
|
||||
parent_operation_id.
|
||||
|
||||
The index enables fast lookups when querying for child operations:
|
||||
SELECT * FROM async_operations
|
||||
WHERE result_metadata::jsonb @> '{"parent_operation_id": "uuid"}'::jsonb
|
||||
"""
|
||||
|
||||
from collections.abc import Sequence
|
||||
|
||||
from alembic import context, op
|
||||
|
||||
revision: str = "y0t1u2v3w4x5"
|
||||
down_revision: str | Sequence[str] | None = "x9s0t1u2v3w4"
|
||||
branch_labels: str | Sequence[str] | None = None
|
||||
depends_on: str | Sequence[str] | None = None
|
||||
|
||||
|
||||
def _get_schema_prefix() -> str:
|
||||
"""Get schema prefix for table names (required for multi-tenant support)."""
|
||||
schema = context.config.get_main_option("target_schema")
|
||||
return f'"{schema}".' if schema else ""
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
"""Add GIN index on result_metadata for efficient parent_operation_id queries."""
|
||||
schema = _get_schema_prefix()
|
||||
|
||||
# Add GIN index for JSONB containment queries (@> operator)
|
||||
op.execute(f"""
|
||||
CREATE INDEX IF NOT EXISTS idx_async_operations_result_metadata
|
||||
ON {schema}async_operations
|
||||
USING gin(result_metadata)
|
||||
""")
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
"""Remove GIN index on result_metadata."""
|
||||
schema = _get_schema_prefix()
|
||||
|
||||
# Drop index
|
||||
op.execute(f"DROP INDEX IF EXISTS {schema}idx_async_operations_result_metadata")
|
||||
+35
@@ -0,0 +1,35 @@
|
||||
"""Add observation_scopes column to memory_units table
|
||||
|
||||
Revision ID: z1u2v3w4x5y6
|
||||
Revises: a1b2c3d4e5f6
|
||||
Create Date: 2026-02-25
|
||||
|
||||
Adds observation_scopes JSONB column to memory_units to control how observations
|
||||
are scoped during consolidation. Accepts "per_tag", "combined", or an explicit
|
||||
list of tag-set lists for custom multi-pass consolidation.
|
||||
"""
|
||||
|
||||
from collections.abc import Sequence
|
||||
|
||||
from alembic import context, op
|
||||
|
||||
revision: str = "z1u2v3w4x5y6"
|
||||
down_revision: str | Sequence[str] | None = "a1b2c3d4e5f6"
|
||||
branch_labels: str | Sequence[str] | None = None
|
||||
depends_on: str | Sequence[str] | None = None
|
||||
|
||||
|
||||
def _get_schema_prefix() -> str:
|
||||
"""Get schema prefix for table names (required for multi-tenant support)."""
|
||||
schema = context.config.get_main_option("target_schema")
|
||||
return f'"{schema}".' if schema else ""
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
op.execute(f"ALTER TABLE {schema}memory_units ADD COLUMN IF NOT EXISTS observation_scopes JSONB")
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
schema = _get_schema_prefix()
|
||||
op.execute(f"ALTER TABLE {schema}memory_units DROP COLUMN IF EXISTS observation_scopes")
|
||||
+1634
-245
File diff suppressed because it is too large
Load Diff
+142
-28
@@ -8,12 +8,48 @@ from contextvars import ContextVar
|
||||
from fastmcp import FastMCP
|
||||
|
||||
from hindsight_api import MemoryEngine
|
||||
from hindsight_api.config import _get_raw_config
|
||||
from hindsight_api.engine.memory_engine import _current_schema
|
||||
from hindsight_api.extensions import MCPExtension, load_extension
|
||||
from hindsight_api.extensions.tenant import AuthenticationError
|
||||
from hindsight_api.mcp_tools import MCPToolsConfig, register_mcp_tools
|
||||
from hindsight_api.models import RequestContext
|
||||
|
||||
# All tools available in the system (explicit list — no wildcards)
|
||||
_ALL_TOOLS: frozenset[str] = frozenset(
|
||||
{
|
||||
"retain",
|
||||
"recall",
|
||||
"reflect",
|
||||
"list_banks",
|
||||
"create_bank",
|
||||
"list_mental_models",
|
||||
"get_mental_model",
|
||||
"create_mental_model",
|
||||
"update_mental_model",
|
||||
"delete_mental_model",
|
||||
"refresh_mental_model",
|
||||
"list_directives",
|
||||
"create_directive",
|
||||
"delete_directive",
|
||||
"list_memories",
|
||||
"get_memory",
|
||||
"delete_memory",
|
||||
"list_documents",
|
||||
"get_document",
|
||||
"delete_document",
|
||||
"list_operations",
|
||||
"get_operation",
|
||||
"cancel_operation",
|
||||
"list_tags",
|
||||
"get_bank",
|
||||
"get_bank_stats",
|
||||
"update_bank",
|
||||
"delete_bank",
|
||||
"clear_memories",
|
||||
}
|
||||
)
|
||||
|
||||
# Configure logging from HINDSIGHT_API_LOG_LEVEL environment variable
|
||||
_log_level_str = os.environ.get("HINDSIGHT_API_LOG_LEVEL", "info").lower()
|
||||
_log_level_map = {
|
||||
@@ -78,21 +114,15 @@ def create_mcp_server(memory: MemoryEngine, multi_bank: bool = True) -> FastMCP:
|
||||
If False, only expose bank-scoped tools without bank_id parameters.
|
||||
|
||||
Returns:
|
||||
Configured FastMCP server instance with stateless_http enabled
|
||||
Configured FastMCP server instance
|
||||
"""
|
||||
# Use stateless_http=True for Claude Code compatibility
|
||||
mcp = FastMCP("hindsight-mcp-server", stateless_http=True)
|
||||
mcp = FastMCP("hindsight-mcp-server")
|
||||
|
||||
# Configure and register tools using shared module
|
||||
config = MCPToolsConfig(
|
||||
bank_id_resolver=get_current_bank_id,
|
||||
api_key_resolver=get_current_api_key, # Propagate API key for tenant auth
|
||||
tenant_id_resolver=get_current_tenant_id, # Propagate tenant_id for usage metering
|
||||
api_key_id_resolver=get_current_api_key_id, # Propagate api_key_id for usage metering
|
||||
include_bank_id_param=multi_bank,
|
||||
tools=None
|
||||
if multi_bank
|
||||
else {
|
||||
global_config = _get_raw_config()
|
||||
|
||||
# Tools available for this mode (multi-bank exposes all tools; single-bank excludes bank-management tools)
|
||||
_SINGLE_BANK_TOOLS: frozenset[str] = frozenset(
|
||||
{
|
||||
"retain",
|
||||
"recall",
|
||||
"reflect",
|
||||
@@ -102,8 +132,40 @@ def create_mcp_server(memory: MemoryEngine, multi_bank: bool = True) -> FastMCP:
|
||||
"update_mental_model",
|
||||
"delete_mental_model",
|
||||
"refresh_mental_model",
|
||||
}, # Scoped tools for single-bank mode (excludes bank management: list_banks, create_bank)
|
||||
retain_fire_and_forget=False, # HTTP MCP supports sync/async modes
|
||||
"list_directives",
|
||||
"create_directive",
|
||||
"delete_directive",
|
||||
"list_memories",
|
||||
"get_memory",
|
||||
"delete_memory",
|
||||
"list_documents",
|
||||
"get_document",
|
||||
"delete_document",
|
||||
"list_operations",
|
||||
"get_operation",
|
||||
"cancel_operation",
|
||||
"list_tags",
|
||||
"get_bank",
|
||||
"update_bank",
|
||||
"delete_bank",
|
||||
"clear_memories",
|
||||
}
|
||||
)
|
||||
base_tools: frozenset[str] | None = None if multi_bank else _SINGLE_BANK_TOOLS
|
||||
|
||||
# Apply global mcp_enabled_tools filter (env-level allowlist)
|
||||
if global_config.mcp_enabled_tools is not None:
|
||||
allowed = frozenset(global_config.mcp_enabled_tools)
|
||||
base_tools = (base_tools if base_tools is not None else _ALL_TOOLS) & allowed
|
||||
|
||||
# Configure and register tools using shared module
|
||||
config = MCPToolsConfig(
|
||||
bank_id_resolver=get_current_bank_id,
|
||||
api_key_resolver=get_current_api_key, # Propagate API key for tenant auth
|
||||
tenant_id_resolver=get_current_tenant_id, # Propagate tenant_id for usage metering
|
||||
api_key_id_resolver=get_current_api_key_id, # Propagate api_key_id for usage metering
|
||||
include_bank_id_param=multi_bank,
|
||||
tools=base_tools,
|
||||
)
|
||||
|
||||
register_mcp_tools(mcp, memory, config)
|
||||
@@ -114,9 +176,39 @@ def create_mcp_server(memory: MemoryEngine, multi_bank: bool = True) -> FastMCP:
|
||||
logger.info(f"Loading MCP extension: {mcp_extension.__class__.__name__}")
|
||||
mcp_extension.register_tools(mcp, memory)
|
||||
|
||||
# Make all tools tolerant of extra arguments from LLMs (e.g., "explanation")
|
||||
_make_tools_tolerant(mcp)
|
||||
|
||||
return mcp
|
||||
|
||||
|
||||
def _make_tools_tolerant(mcp: FastMCP) -> None:
|
||||
"""Wrap all tool run methods to strip unknown arguments before validation.
|
||||
|
||||
LLMs frequently add extra fields like "explanation" or "reasoning" to tool calls.
|
||||
FastMCP's Pydantic TypeAdapter rejects these with "Unexpected keyword argument".
|
||||
This wraps each tool's run() to filter arguments to only known parameters.
|
||||
"""
|
||||
try:
|
||||
for name, tool in mcp._tool_manager._tools.items():
|
||||
if hasattr(tool, "parameters") and tool.parameters:
|
||||
allowed = set(tool.parameters.get("properties", {}).keys())
|
||||
original_run = tool.run
|
||||
|
||||
async def _tolerant_run(arguments, _allowed=allowed, _orig=original_run):
|
||||
extra_keys = set(arguments.keys()) - _allowed
|
||||
if extra_keys:
|
||||
logger.debug(f"Stripping unknown arguments from tool call: {extra_keys}")
|
||||
arguments = {k: v for k, v in arguments.items() if k in _allowed}
|
||||
return await _orig(arguments)
|
||||
|
||||
# FunctionTool is a Pydantic model with extra='forbid', so use
|
||||
# object.__setattr__ to bypass Pydantic's setter validation.
|
||||
object.__setattr__(tool, "run", _tolerant_run)
|
||||
except (AttributeError, KeyError) as e:
|
||||
logger.warning(f"Could not make tools tolerant of extra arguments: {e}")
|
||||
|
||||
|
||||
class MCPMiddleware:
|
||||
"""ASGI middleware that intercepts MCP requests and routes to appropriate MCP server.
|
||||
|
||||
@@ -142,6 +234,11 @@ class MCPMiddleware:
|
||||
- No bank management tools (list_banks, create_bank)
|
||||
- Recommended for agent isolation
|
||||
|
||||
Bank ID resolution priority:
|
||||
1. URL path (e.g., /mcp/{bank_id}/) → single-bank mode
|
||||
2. X-Bank-Id header → multi-bank mode
|
||||
3. HINDSIGHT_MCP_BANK_ID env var → multi-bank mode (default: "default")
|
||||
|
||||
Examples:
|
||||
# Single-bank mode (recommended for agent isolation)
|
||||
claude mcp add --transport http my-agent http://localhost:8888/mcp/my-agent-bank/ \\
|
||||
@@ -176,9 +273,9 @@ class MCPMiddleware:
|
||||
else:
|
||||
# Create servers internally (for direct construction / tests)
|
||||
self.multi_bank_server = create_mcp_server(memory, multi_bank=True)
|
||||
self.multi_bank_app = self.multi_bank_server.http_app(path="/")
|
||||
self.multi_bank_app = self.multi_bank_server.http_app(path="/", stateless_http=True)
|
||||
self.single_bank_server = create_mcp_server(memory, multi_bank=False)
|
||||
self.single_bank_app = self.single_bank_server.http_app(path="/")
|
||||
self.single_bank_app = self.single_bank_server.http_app(path="/", stateless_http=True)
|
||||
|
||||
def _get_header(self, scope: dict, name: str) -> str | None:
|
||||
"""Extract a header value from ASGI scope."""
|
||||
@@ -234,7 +331,7 @@ class MCPMiddleware:
|
||||
auth_tenant_id = auth_context.tenant_id
|
||||
auth_api_key_id = auth_context.api_key_id
|
||||
except AuthenticationError as e:
|
||||
await self._send_error(send, 401, str(e))
|
||||
await self._send_error(send, 401, str(e), extra_headers=e.headers)
|
||||
return
|
||||
|
||||
# Set schema from tenant context so downstream DB queries use the correct schema
|
||||
@@ -242,20 +339,25 @@ class MCPMiddleware:
|
||||
_current_schema.set(tenant_context.schema_name) if tenant_context and tenant_context.schema_name else None
|
||||
)
|
||||
|
||||
# Try to get bank_id from header first (for Claude Code compatibility)
|
||||
bank_id = self._get_header(scope, "X-Bank-Id")
|
||||
# Resolve bank_id: path takes priority over header.
|
||||
# Path = user's explicit connection endpoint (e.g., /mcp/my-bank/).
|
||||
# X-Bank-Id header = per-request override for multi-bank mode only.
|
||||
bank_id = None
|
||||
bank_id_from_path = False
|
||||
|
||||
# If no header, try to extract from path: /{bank_id}/...
|
||||
new_path = path
|
||||
if not bank_id and path.startswith("/") and len(path) > 1:
|
||||
|
||||
# First, try to extract from path: /{bank_id}/...
|
||||
if path.startswith("/") and len(path) > 1:
|
||||
parts = path[1:].split("/", 1)
|
||||
if parts[0]:
|
||||
# First segment looks like a bank_id
|
||||
bank_id = parts[0]
|
||||
bank_id_from_path = True
|
||||
new_path = "/" + parts[1] if len(parts) > 1 else "/"
|
||||
|
||||
# If no path-based bank_id, try X-Bank-Id header (multi-bank mode)
|
||||
if not bank_id:
|
||||
bank_id = self._get_header(scope, "X-Bank-Id")
|
||||
|
||||
# Fall back to default bank_id
|
||||
if not bank_id:
|
||||
bank_id = DEFAULT_BANK_ID
|
||||
@@ -279,6 +381,15 @@ class MCPMiddleware:
|
||||
# Clear root_path since we're passing directly to the app
|
||||
new_scope["root_path"] = ""
|
||||
|
||||
# Ensure Accept header includes required MIME types for MCP SDK.
|
||||
# Some clients (e.g., Claude Code) don't send Accept, causing
|
||||
# the SDK to reject with 406 Not Acceptable.
|
||||
accept_header = self._get_header(new_scope, "accept")
|
||||
if not accept_header or "text/event-stream" not in accept_header:
|
||||
headers = [(k, v) for k, v in new_scope.get("headers", []) if k.lower() != b"accept"]
|
||||
headers.append((b"accept", b"application/json, text/event-stream"))
|
||||
new_scope["headers"] = headers
|
||||
|
||||
# Wrap send to rewrite the SSE endpoint URL to include bank_id if using path-based routing.
|
||||
# Only rewrite SSE (text/event-stream) responses to avoid corrupting tool results
|
||||
# that might contain the literal string "data: /messages".
|
||||
@@ -311,14 +422,17 @@ class MCPMiddleware:
|
||||
if schema_token is not None:
|
||||
_current_schema.reset(schema_token)
|
||||
|
||||
async def _send_error(self, send, status: int, message: str):
|
||||
async def _send_error(self, send, status: int, message: str, extra_headers: dict[str, str] | None = None):
|
||||
"""Send an error response."""
|
||||
body = json.dumps({"error": message}).encode()
|
||||
headers = [(b"content-type", b"application/json")]
|
||||
for key, value in (extra_headers or {}).items():
|
||||
headers.append((key.encode(), value.encode()))
|
||||
await send(
|
||||
{
|
||||
"type": "http.response.start",
|
||||
"status": status,
|
||||
"headers": [(b"content-type", b"application/json")],
|
||||
"headers": headers,
|
||||
}
|
||||
)
|
||||
await send(
|
||||
@@ -339,9 +453,9 @@ def create_mcp_servers(memory: MemoryEngine):
|
||||
Tuple of (multi_bank_server, single_bank_server, multi_bank_app, single_bank_app)
|
||||
"""
|
||||
multi_bank_server = create_mcp_server(memory, multi_bank=True)
|
||||
multi_bank_app = multi_bank_server.http_app(path="/")
|
||||
multi_bank_app = multi_bank_server.http_app(path="/", stateless_http=True)
|
||||
|
||||
single_bank_server = create_mcp_server(memory, multi_bank=False)
|
||||
single_bank_app = single_bank_server.http_app(path="/")
|
||||
single_bank_app = single_bank_server.http_app(path="/", stateless_http=True)
|
||||
|
||||
return multi_bank_server, single_bank_server, multi_bank_app, single_bank_app
|
||||
@@ -86,6 +86,8 @@ def print_startup_info(
|
||||
reranker_provider: str,
|
||||
mcp_enabled: bool = False,
|
||||
version: str | None = None,
|
||||
vector_extension: str | None = None,
|
||||
text_search_extension: str | None = None,
|
||||
):
|
||||
"""Print styled startup information."""
|
||||
print(color_start("Starting Hindsight API..."))
|
||||
@@ -96,6 +98,8 @@ def print_startup_info(
|
||||
print(f" {dim('LLM:')} {color(f'{llm_provider} / {llm_model}', 0.6)}")
|
||||
print(f" {dim('Embeddings:')} {color(embeddings_provider, 0.8)}")
|
||||
print(f" {dim('Reranker:')} {color(reranker_provider, 1.0)}")
|
||||
extensions = f"{vector_extension or 'default'} (vector) / {text_search_extension or 'default'} (text)"
|
||||
print(f" {dim('Extensions:')} {color(extensions, 0.4)}")
|
||||
if mcp_enabled:
|
||||
print(f" {dim('MCP:')} {color_end('enabled at /mcp')}")
|
||||
print()
|
||||
+619
-11
@@ -8,8 +8,9 @@ import json
|
||||
import logging
|
||||
import os
|
||||
import sys
|
||||
from dataclasses import dataclass
|
||||
from dataclasses import dataclass, field, fields
|
||||
from datetime import datetime, timezone
|
||||
from typing import Any
|
||||
|
||||
from dotenv import find_dotenv, load_dotenv
|
||||
|
||||
@@ -18,6 +19,103 @@ load_dotenv(find_dotenv(usecwd=True), override=True)
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class ConfigFieldAccessError(AttributeError):
|
||||
"""Raised when trying to access a bank-configurable field from global config."""
|
||||
|
||||
pass
|
||||
|
||||
|
||||
class StaticConfigProxy:
|
||||
"""
|
||||
Proxy that wraps HindsightConfig and only allows access to static (non-configurable) fields.
|
||||
|
||||
Raises ConfigFieldAccessError when trying to access configurable fields that vary per-bank.
|
||||
Forces developers to use get_resolved_config(bank_id, context) for bank-specific settings.
|
||||
"""
|
||||
|
||||
def __init__(self, config: "HindsightConfig"):
|
||||
object.__setattr__(self, "_config", config)
|
||||
object.__setattr__(self, "_configurable_fields", HindsightConfig.get_configurable_fields())
|
||||
|
||||
def __getattribute__(self, name: str):
|
||||
if name.startswith("_"):
|
||||
return object.__getattribute__(self, name)
|
||||
|
||||
configurable_fields = object.__getattribute__(self, "_configurable_fields")
|
||||
if name in configurable_fields:
|
||||
raise ConfigFieldAccessError(
|
||||
f"Field '{name}' is bank-configurable and cannot be accessed from global config. "
|
||||
f"Use ConfigResolver.resolve_full_config(bank_id, context) to get bank-specific config. "
|
||||
f"This prevents accidentally using global defaults when bank-specific overrides exist."
|
||||
)
|
||||
|
||||
config = object.__getattribute__(self, "_config")
|
||||
return getattr(config, name)
|
||||
|
||||
def __setattr__(self, name: str, value):
|
||||
raise AttributeError("Config is read-only. Modifications must go through ConfigResolver.")
|
||||
|
||||
|
||||
# Configuration field markers for hierarchical configuration
|
||||
def hierarchical(default_value):
|
||||
"""
|
||||
Mark a config field as hierarchical (can be overridden per-tenant/bank).
|
||||
|
||||
Hierarchical fields can be customized at the tenant or bank level via database
|
||||
configuration. Examples: LLM settings, retention parameters, retrieval settings.
|
||||
"""
|
||||
return field(default=default_value, metadata={"hierarchical": True})
|
||||
|
||||
|
||||
def static(default_value):
|
||||
"""
|
||||
Mark a config field as static (server-level only, cannot be overridden).
|
||||
|
||||
Static fields are infrastructure-level settings that affect the entire server
|
||||
and cannot vary per tenant or bank. Examples: database URL, API port, worker settings.
|
||||
"""
|
||||
return field(default=default_value, metadata={"hierarchical": False})
|
||||
|
||||
|
||||
# Configuration key normalization utilities
|
||||
def normalize_config_key(key: str) -> str:
|
||||
"""
|
||||
Convert environment variable format to Python field name format.
|
||||
|
||||
Examples:
|
||||
HINDSIGHT_API_LLM_PROVIDER -> llm_provider
|
||||
LLM_MODEL -> llm_model
|
||||
llm_model -> llm_model (already normalized)
|
||||
|
||||
Args:
|
||||
key: Environment variable name or Python field name
|
||||
|
||||
Returns:
|
||||
Normalized Python field name (lowercase snake_case)
|
||||
"""
|
||||
if key.startswith("HINDSIGHT_API_"):
|
||||
key = key[len("HINDSIGHT_API_") :]
|
||||
return key.lower()
|
||||
|
||||
|
||||
def normalize_config_dict(config: dict[str, Any]) -> dict[str, Any]:
|
||||
"""
|
||||
Normalize all keys in a config dict to Python field names.
|
||||
|
||||
Allows users to provide config overrides in either format:
|
||||
- Python field format: {"llm_provider": "openai"}
|
||||
- Env var format: {"HINDSIGHT_API_LLM_PROVIDER": "openai"}
|
||||
|
||||
Args:
|
||||
config: Dict with env var or Python field names as keys
|
||||
|
||||
Returns:
|
||||
Dict with all keys normalized to Python field names
|
||||
"""
|
||||
return {normalize_config_key(k): v for k, v in config.items()}
|
||||
|
||||
|
||||
# Environment variable names
|
||||
ENV_DATABASE_URL = "HINDSIGHT_API_DATABASE_URL"
|
||||
ENV_DATABASE_SCHEMA = "HINDSIGHT_API_DATABASE_SCHEMA"
|
||||
@@ -31,6 +129,11 @@ ENV_LLM_INITIAL_BACKOFF = "HINDSIGHT_API_LLM_INITIAL_BACKOFF"
|
||||
ENV_LLM_MAX_BACKOFF = "HINDSIGHT_API_LLM_MAX_BACKOFF"
|
||||
ENV_LLM_TIMEOUT = "HINDSIGHT_API_LLM_TIMEOUT"
|
||||
ENV_LLM_GROQ_SERVICE_TIER = "HINDSIGHT_API_LLM_GROQ_SERVICE_TIER"
|
||||
ENV_LLM_OPENAI_SERVICE_TIER = "HINDSIGHT_API_LLM_OPENAI_SERVICE_TIER"
|
||||
|
||||
# Defaults for service tiers
|
||||
DEFAULT_LLM_GROQ_SERVICE_TIER = "auto" # "on_demand", "flex", or "auto"
|
||||
DEFAULT_LLM_OPENAI_SERVICE_TIER = None # None (default) or "flex" (50% cheaper)
|
||||
|
||||
# Per-operation LLM configuration (optional, falls back to global LLM config)
|
||||
ENV_RETAIN_LLM_PROVIDER = "HINDSIGHT_API_RETAIN_LLM_PROVIDER"
|
||||
@@ -90,6 +193,15 @@ ENV_EMBEDDINGS_LITELLM_MODEL = "HINDSIGHT_API_EMBEDDINGS_LITELLM_MODEL"
|
||||
ENV_RERANKER_LITELLM_API_BASE = "HINDSIGHT_API_RERANKER_LITELLM_API_BASE"
|
||||
ENV_RERANKER_LITELLM_API_KEY = "HINDSIGHT_API_RERANKER_LITELLM_API_KEY"
|
||||
ENV_RERANKER_LITELLM_MODEL = "HINDSIGHT_API_RERANKER_LITELLM_MODEL"
|
||||
ENV_RERANKER_LITELLM_MAX_TOKENS_PER_DOC = "HINDSIGHT_API_RERANKER_LITELLM_MAX_TOKENS_PER_DOC"
|
||||
|
||||
# LiteLLM SDK configuration (direct API access, no proxy needed)
|
||||
ENV_EMBEDDINGS_LITELLM_SDK_API_KEY = "HINDSIGHT_API_EMBEDDINGS_LITELLM_SDK_API_KEY"
|
||||
ENV_EMBEDDINGS_LITELLM_SDK_MODEL = "HINDSIGHT_API_EMBEDDINGS_LITELLM_SDK_MODEL"
|
||||
ENV_EMBEDDINGS_LITELLM_SDK_API_BASE = "HINDSIGHT_API_EMBEDDINGS_LITELLM_SDK_API_BASE"
|
||||
ENV_RERANKER_LITELLM_SDK_API_KEY = "HINDSIGHT_API_RERANKER_LITELLM_SDK_API_KEY"
|
||||
ENV_RERANKER_LITELLM_SDK_MODEL = "HINDSIGHT_API_RERANKER_LITELLM_SDK_MODEL"
|
||||
ENV_RERANKER_LITELLM_SDK_API_BASE = "HINDSIGHT_API_RERANKER_LITELLM_SDK_API_BASE"
|
||||
|
||||
# Deprecated: Legacy shared LiteLLM config (for backward compatibility)
|
||||
ENV_LITELLM_API_BASE = "HINDSIGHT_API_LITELLM_API_BASE"
|
||||
@@ -100,6 +212,9 @@ ENV_RERANKER_LOCAL_MODEL = "HINDSIGHT_API_RERANKER_LOCAL_MODEL"
|
||||
ENV_RERANKER_LOCAL_FORCE_CPU = "HINDSIGHT_API_RERANKER_LOCAL_FORCE_CPU"
|
||||
ENV_RERANKER_LOCAL_MAX_CONCURRENT = "HINDSIGHT_API_RERANKER_LOCAL_MAX_CONCURRENT"
|
||||
ENV_RERANKER_LOCAL_TRUST_REMOTE_CODE = "HINDSIGHT_API_RERANKER_LOCAL_TRUST_REMOTE_CODE"
|
||||
ENV_RERANKER_LOCAL_FP16 = "HINDSIGHT_API_RERANKER_LOCAL_FP16"
|
||||
ENV_RERANKER_LOCAL_BUCKET_BATCHING = "HINDSIGHT_API_RERANKER_LOCAL_BUCKET_BATCHING"
|
||||
ENV_RERANKER_LOCAL_BATCH_SIZE = "HINDSIGHT_API_RERANKER_LOCAL_BATCH_SIZE"
|
||||
ENV_RERANKER_TEI_URL = "HINDSIGHT_API_RERANKER_TEI_URL"
|
||||
ENV_RERANKER_TEI_BATCH_SIZE = "HINDSIGHT_API_RERANKER_TEI_BATCH_SIZE"
|
||||
ENV_RERANKER_TEI_MAX_CONCURRENT = "HINDSIGHT_API_RERANKER_TEI_MAX_CONCURRENT"
|
||||
@@ -107,18 +222,27 @@ ENV_RERANKER_MAX_CANDIDATES = "HINDSIGHT_API_RERANKER_MAX_CANDIDATES"
|
||||
ENV_RERANKER_FLASHRANK_MODEL = "HINDSIGHT_API_RERANKER_FLASHRANK_MODEL"
|
||||
ENV_RERANKER_FLASHRANK_CACHE_DIR = "HINDSIGHT_API_RERANKER_FLASHRANK_CACHE_DIR"
|
||||
|
||||
# ZeroEntropy configuration (reranker only)
|
||||
ENV_RERANKER_ZEROENTROPY_API_KEY = "HINDSIGHT_API_RERANKER_ZEROENTROPY_API_KEY"
|
||||
ENV_RERANKER_ZEROENTROPY_MODEL = "HINDSIGHT_API_RERANKER_ZEROENTROPY_MODEL"
|
||||
|
||||
ENV_VECTOR_EXTENSION = "HINDSIGHT_API_VECTOR_EXTENSION"
|
||||
ENV_TEXT_SEARCH_EXTENSION = "HINDSIGHT_API_TEXT_SEARCH_EXTENSION"
|
||||
|
||||
ENV_HOST = "HINDSIGHT_API_HOST"
|
||||
ENV_PORT = "HINDSIGHT_API_PORT"
|
||||
ENV_BASE_PATH = "HINDSIGHT_API_BASE_PATH"
|
||||
ENV_LOG_LEVEL = "HINDSIGHT_API_LOG_LEVEL"
|
||||
ENV_LOG_FORMAT = "HINDSIGHT_API_LOG_FORMAT"
|
||||
ENV_WORKERS = "HINDSIGHT_API_WORKERS"
|
||||
ENV_MCP_ENABLED = "HINDSIGHT_API_MCP_ENABLED"
|
||||
ENV_MCP_ENABLED_TOOLS = "HINDSIGHT_API_MCP_ENABLED_TOOLS"
|
||||
ENV_ENABLE_BANK_CONFIG_API = "HINDSIGHT_API_ENABLE_BANK_CONFIG_API"
|
||||
ENV_GRAPH_RETRIEVER = "HINDSIGHT_API_GRAPH_RETRIEVER"
|
||||
ENV_MPFP_TOP_K_NEIGHBORS = "HINDSIGHT_API_MPFP_TOP_K_NEIGHBORS"
|
||||
ENV_RECALL_MAX_CONCURRENT = "HINDSIGHT_API_RECALL_MAX_CONCURRENT"
|
||||
ENV_RECALL_CONNECTION_BUDGET = "HINDSIGHT_API_RECALL_CONNECTION_BUDGET"
|
||||
ENV_MCP_LOCAL_BANK_ID = "HINDSIGHT_API_MCP_LOCAL_BANK_ID"
|
||||
ENV_MCP_INSTRUCTIONS = "HINDSIGHT_API_MCP_INSTRUCTIONS"
|
||||
ENV_RECALL_MAX_QUERY_TOKENS = "HINDSIGHT_API_RECALL_MAX_QUERY_TOKENS"
|
||||
ENV_MENTAL_MODEL_REFRESH_CONCURRENCY = "HINDSIGHT_API_MENTAL_MODEL_REFRESH_CONCURRENCY"
|
||||
|
||||
# OpenTelemetry tracing configuration
|
||||
@@ -133,17 +257,61 @@ ENV_LLM_VERTEXAI_PROJECT_ID = "HINDSIGHT_API_LLM_VERTEXAI_PROJECT_ID"
|
||||
ENV_LLM_VERTEXAI_REGION = "HINDSIGHT_API_LLM_VERTEXAI_REGION"
|
||||
ENV_LLM_VERTEXAI_SERVICE_ACCOUNT_KEY = "HINDSIGHT_API_LLM_VERTEXAI_SERVICE_ACCOUNT_KEY"
|
||||
|
||||
# Gemini safety settings
|
||||
ENV_LLM_GEMINI_SAFETY_SETTINGS = "HINDSIGHT_API_LLM_GEMINI_SAFETY_SETTINGS"
|
||||
|
||||
# Retain settings
|
||||
ENV_RETAIN_MAX_COMPLETION_TOKENS = "HINDSIGHT_API_RETAIN_MAX_COMPLETION_TOKENS"
|
||||
ENV_RETAIN_CHUNK_SIZE = "HINDSIGHT_API_RETAIN_CHUNK_SIZE"
|
||||
ENV_RETAIN_EXTRACT_CAUSAL_LINKS = "HINDSIGHT_API_RETAIN_EXTRACT_CAUSAL_LINKS"
|
||||
ENV_RETAIN_EXTRACTION_MODE = "HINDSIGHT_API_RETAIN_EXTRACTION_MODE"
|
||||
ENV_RETAIN_MISSION = "HINDSIGHT_API_RETAIN_MISSION"
|
||||
ENV_RETAIN_CUSTOM_INSTRUCTIONS = "HINDSIGHT_API_RETAIN_CUSTOM_INSTRUCTIONS"
|
||||
ENV_RETAIN_DEFAULT_STRATEGY = "HINDSIGHT_API_RETAIN_DEFAULT_STRATEGY"
|
||||
ENV_RETAIN_BATCH_TOKENS = "HINDSIGHT_API_RETAIN_BATCH_TOKENS"
|
||||
ENV_RETAIN_ENTITY_LOOKUP = "HINDSIGHT_API_RETAIN_ENTITY_LOOKUP"
|
||||
ENV_RETAIN_BATCH_ENABLED = "HINDSIGHT_API_RETAIN_BATCH_ENABLED"
|
||||
ENV_RETAIN_BATCH_POLL_INTERVAL_SECONDS = "HINDSIGHT_API_RETAIN_BATCH_POLL_INTERVAL_SECONDS"
|
||||
|
||||
# File storage configuration
|
||||
ENV_FILE_STORAGE_TYPE = "HINDSIGHT_API_FILE_STORAGE_TYPE"
|
||||
ENV_FILE_STORAGE_S3_BUCKET = "HINDSIGHT_API_FILE_STORAGE_S3_BUCKET"
|
||||
ENV_FILE_STORAGE_S3_REGION = "HINDSIGHT_API_FILE_STORAGE_S3_REGION"
|
||||
ENV_FILE_STORAGE_S3_ENDPOINT = "HINDSIGHT_API_FILE_STORAGE_S3_ENDPOINT"
|
||||
ENV_FILE_STORAGE_S3_ACCESS_KEY_ID = "HINDSIGHT_API_FILE_STORAGE_S3_ACCESS_KEY_ID"
|
||||
ENV_FILE_STORAGE_S3_SECRET_ACCESS_KEY = "HINDSIGHT_API_FILE_STORAGE_S3_SECRET_ACCESS_KEY"
|
||||
ENV_FILE_STORAGE_GCS_BUCKET = "HINDSIGHT_API_FILE_STORAGE_GCS_BUCKET"
|
||||
ENV_FILE_STORAGE_GCS_SERVICE_ACCOUNT_KEY = "HINDSIGHT_API_FILE_STORAGE_GCS_SERVICE_ACCOUNT_KEY"
|
||||
ENV_FILE_STORAGE_AZURE_CONTAINER = "HINDSIGHT_API_FILE_STORAGE_AZURE_CONTAINER"
|
||||
ENV_FILE_STORAGE_AZURE_ACCOUNT_NAME = "HINDSIGHT_API_FILE_STORAGE_AZURE_ACCOUNT_NAME"
|
||||
ENV_FILE_STORAGE_AZURE_ACCOUNT_KEY = "HINDSIGHT_API_FILE_STORAGE_AZURE_ACCOUNT_KEY"
|
||||
ENV_FILE_PARSER = "HINDSIGHT_API_FILE_PARSER"
|
||||
ENV_FILE_PARSER_ALLOWLIST = "HINDSIGHT_API_FILE_PARSER_ALLOWLIST"
|
||||
ENV_FILE_PARSER_IRIS_TOKEN = "HINDSIGHT_API_FILE_PARSER_IRIS_TOKEN"
|
||||
ENV_FILE_PARSER_IRIS_ORG_ID = "HINDSIGHT_API_FILE_PARSER_IRIS_ORG_ID"
|
||||
ENV_FILE_CONVERSION_MAX_BATCH_SIZE_MB = "HINDSIGHT_API_FILE_CONVERSION_MAX_BATCH_SIZE_MB"
|
||||
ENV_FILE_CONVERSION_MAX_BATCH_SIZE = "HINDSIGHT_API_FILE_CONVERSION_MAX_BATCH_SIZE"
|
||||
ENV_ENABLE_FILE_UPLOAD_API = "HINDSIGHT_API_ENABLE_FILE_UPLOAD_API"
|
||||
ENV_FILE_DELETE_AFTER_RETAIN = "HINDSIGHT_API_FILE_DELETE_AFTER_RETAIN"
|
||||
|
||||
# Observations settings (consolidated knowledge from facts)
|
||||
ENV_ENABLE_OBSERVATIONS = "HINDSIGHT_API_ENABLE_OBSERVATIONS"
|
||||
ENV_CONSOLIDATION_BATCH_SIZE = "HINDSIGHT_API_CONSOLIDATION_BATCH_SIZE"
|
||||
ENV_CONSOLIDATION_LLM_BATCH_SIZE = "HINDSIGHT_API_CONSOLIDATION_LLM_BATCH_SIZE"
|
||||
ENV_CONSOLIDATION_MAX_TOKENS = "HINDSIGHT_API_CONSOLIDATION_MAX_TOKENS"
|
||||
ENV_CONSOLIDATION_SOURCE_FACTS_MAX_TOKENS = "HINDSIGHT_API_CONSOLIDATION_SOURCE_FACTS_MAX_TOKENS"
|
||||
ENV_CONSOLIDATION_SOURCE_FACTS_MAX_TOKENS_PER_OBSERVATION = (
|
||||
"HINDSIGHT_API_CONSOLIDATION_SOURCE_FACTS_MAX_TOKENS_PER_OBSERVATION"
|
||||
)
|
||||
ENV_OBSERVATIONS_MISSION = "HINDSIGHT_API_OBSERVATIONS_MISSION"
|
||||
ENV_ENABLE_OBSERVATION_HISTORY = "HINDSIGHT_API_ENABLE_OBSERVATION_HISTORY"
|
||||
ENV_ENABLE_MENTAL_MODEL_HISTORY = "HINDSIGHT_API_ENABLE_MENTAL_MODEL_HISTORY"
|
||||
|
||||
# Webhook configuration (global, static - server-level only)
|
||||
ENV_WEBHOOK_URL = "HINDSIGHT_API_WEBHOOK_URL"
|
||||
ENV_WEBHOOK_SECRET = "HINDSIGHT_API_WEBHOOK_SECRET"
|
||||
ENV_WEBHOOK_EVENT_TYPES = "HINDSIGHT_API_WEBHOOK_EVENT_TYPES"
|
||||
ENV_WEBHOOK_DELIVERY_POLL_INTERVAL_SECONDS = "HINDSIGHT_API_WEBHOOK_DELIVERY_POLL_INTERVAL_SECONDS"
|
||||
|
||||
# Optimization flags
|
||||
ENV_SKIP_LLM_VERIFICATION = "HINDSIGHT_API_SKIP_LLM_VERIFICATION"
|
||||
@@ -169,6 +337,13 @@ ENV_WORKER_CONSOLIDATION_MAX_SLOTS = "HINDSIGHT_API_WORKER_CONSOLIDATION_MAX_SLO
|
||||
|
||||
# Reflect agent settings
|
||||
ENV_REFLECT_MAX_ITERATIONS = "HINDSIGHT_API_REFLECT_MAX_ITERATIONS"
|
||||
ENV_REFLECT_MAX_CONTEXT_TOKENS = "HINDSIGHT_API_REFLECT_MAX_CONTEXT_TOKENS"
|
||||
ENV_REFLECT_MISSION = "HINDSIGHT_API_REFLECT_MISSION"
|
||||
|
||||
# Disposition settings
|
||||
ENV_DISPOSITION_SKEPTICISM = "HINDSIGHT_API_DISPOSITION_SKEPTICISM"
|
||||
ENV_DISPOSITION_LITERALISM = "HINDSIGHT_API_DISPOSITION_LITERALISM"
|
||||
ENV_DISPOSITION_EMPATHY = "HINDSIGHT_API_DISPOSITION_EMPATHY"
|
||||
|
||||
# Default values
|
||||
DEFAULT_DATABASE_URL = "pg0"
|
||||
@@ -177,18 +352,19 @@ DEFAULT_LLM_PROVIDER = "openai"
|
||||
|
||||
# Provider-specific default models
|
||||
PROVIDER_DEFAULT_MODELS = {
|
||||
"openai": "o3-mini",
|
||||
"openai": "gpt-4o-mini",
|
||||
"anthropic": "claude-haiku-4-5-20251001",
|
||||
"gemini": "gemini-2.5-flash",
|
||||
"groq": "openai/gpt-oss-120b",
|
||||
"minimax": "MiniMax-M2.7",
|
||||
"ollama": "gemma3:12b",
|
||||
"lmstudio": "local-model",
|
||||
"vertexai": "gemini-2.0-flash-001",
|
||||
"vertexai": "google/gemini-2.5-flash-lite",
|
||||
"openai-codex": "gpt-5.2-codex",
|
||||
"claude-code": "claude-sonnet-4-5-20250929",
|
||||
"mock": "mock-model",
|
||||
}
|
||||
DEFAULT_LLM_MODEL = "o3-mini" # Fallback if provider not in table
|
||||
DEFAULT_LLM_MODEL = "gpt-4o-mini" # Fallback if provider not in table
|
||||
DEFAULT_LLM_MAX_CONCURRENT = 32
|
||||
DEFAULT_LLM_MAX_RETRIES = 10 # Max retry attempts for LLM API calls
|
||||
DEFAULT_LLM_INITIAL_BACKOFF = 1.0 # Initial backoff in seconds for retry exponential backoff
|
||||
@@ -200,6 +376,9 @@ DEFAULT_LLM_VERTEXAI_PROJECT_ID = None # Required for Vertex AI
|
||||
DEFAULT_LLM_VERTEXAI_REGION = "us-central1"
|
||||
DEFAULT_LLM_VERTEXAI_SERVICE_ACCOUNT_KEY = None # Optional, uses ADC if not set
|
||||
|
||||
# Gemini safety settings defaults
|
||||
DEFAULT_LLM_GEMINI_SAFETY_SETTINGS = None # None = use Gemini default safety settings
|
||||
|
||||
DEFAULT_EMBEDDINGS_PROVIDER = "local"
|
||||
DEFAULT_EMBEDDINGS_LOCAL_MODEL = "BAAI/bge-small-en-v1.5"
|
||||
DEFAULT_EMBEDDINGS_LOCAL_FORCE_CPU = False # Force CPU mode for local embeddings (avoids MPS/XPC issues on macOS)
|
||||
@@ -214,6 +393,9 @@ DEFAULT_RERANKER_LOCAL_MAX_CONCURRENT = 4 # Limit concurrent CPU-bound rerankin
|
||||
DEFAULT_RERANKER_LOCAL_TRUST_REMOTE_CODE = (
|
||||
False # Security: disabled by default, required for some models like jina-reranker-v2
|
||||
)
|
||||
DEFAULT_RERANKER_LOCAL_FP16 = False # FP16 inference: opt-in, faster on MPS/CUDA (not CPU)
|
||||
DEFAULT_RERANKER_LOCAL_BUCKET_BATCHING = False # Length-sorted bucket batching: opt-in, 36-54% speedup
|
||||
DEFAULT_RERANKER_LOCAL_BATCH_SIZE = 32 # Batch size for local reranker predict() calls
|
||||
DEFAULT_RERANKER_TEI_BATCH_SIZE = 128
|
||||
DEFAULT_RERANKER_TEI_MAX_CONCURRENT = 8
|
||||
DEFAULT_RERANKER_MAX_CANDIDATES = 300
|
||||
@@ -223,22 +405,38 @@ DEFAULT_RERANKER_FLASHRANK_CACHE_DIR = None # Use default cache directory
|
||||
DEFAULT_EMBEDDINGS_COHERE_MODEL = "embed-english-v3.0"
|
||||
DEFAULT_RERANKER_COHERE_MODEL = "rerank-english-v3.0"
|
||||
|
||||
DEFAULT_RERANKER_ZEROENTROPY_MODEL = "zerank-2"
|
||||
|
||||
# Vector extension (pgvector, vchord, or pgvectorscale)
|
||||
DEFAULT_VECTOR_EXTENSION = "pgvector" # Options: "pgvector", "vchord", "pgvectorscale"
|
||||
|
||||
# Text search extension (native PostgreSQL, vchord BM25, or Timescale pg_textsearch)
|
||||
DEFAULT_TEXT_SEARCH_EXTENSION = "native" # Options: "native", "vchord", "pg_textsearch"
|
||||
|
||||
# LiteLLM defaults
|
||||
DEFAULT_LITELLM_API_BASE = "http://localhost:4000"
|
||||
DEFAULT_EMBEDDINGS_LITELLM_MODEL = "text-embedding-3-small"
|
||||
DEFAULT_RERANKER_LITELLM_MODEL = "cohere/rerank-english-v3.0"
|
||||
DEFAULT_RERANKER_LITELLM_MAX_TOKENS_PER_DOC: int | None = None
|
||||
|
||||
# LiteLLM SDK defaults
|
||||
DEFAULT_EMBEDDINGS_LITELLM_SDK_MODEL = "cohere/embed-english-v3.0"
|
||||
DEFAULT_RERANKER_LITELLM_SDK_MODEL = "cohere/rerank-english-v3.0"
|
||||
|
||||
DEFAULT_HOST = "0.0.0.0"
|
||||
DEFAULT_PORT = 8888
|
||||
DEFAULT_BASE_PATH = "" # Empty string = root path
|
||||
DEFAULT_LOG_LEVEL = "info"
|
||||
DEFAULT_LOG_FORMAT = "text" # Options: "text", "json"
|
||||
DEFAULT_WORKERS = 1
|
||||
DEFAULT_MCP_ENABLED = True
|
||||
DEFAULT_MCP_ENABLED_TOOLS: list[str] | None = None # None = all tools enabled
|
||||
DEFAULT_ENABLE_BANK_CONFIG_API = True
|
||||
DEFAULT_GRAPH_RETRIEVER = "link_expansion" # Options: "link_expansion", "mpfp", "bfs"
|
||||
DEFAULT_MPFP_TOP_K_NEIGHBORS = 20 # Fan-out limit per node in MPFP graph traversal
|
||||
DEFAULT_RECALL_MAX_CONCURRENT = 32 # Max concurrent recall operations per worker
|
||||
DEFAULT_RECALL_CONNECTION_BUDGET = 4 # Max concurrent DB connections per recall operation
|
||||
DEFAULT_MCP_LOCAL_BANK_ID = "mcp"
|
||||
DEFAULT_RECALL_MAX_QUERY_TOKENS = 500 # Maximum tokens allowed in recall query
|
||||
DEFAULT_MENTAL_MODEL_REFRESH_CONCURRENCY = 8 # Max concurrent mental model refreshes
|
||||
|
||||
# Retain settings
|
||||
@@ -246,13 +444,39 @@ DEFAULT_RETAIN_MAX_COMPLETION_TOKENS = 64000 # Max tokens for fact extraction L
|
||||
DEFAULT_RETAIN_CHUNK_SIZE = 3000 # Max chars per chunk for fact extraction
|
||||
DEFAULT_RETAIN_EXTRACT_CAUSAL_LINKS = True # Extract causal links between facts
|
||||
DEFAULT_RETAIN_EXTRACTION_MODE = "concise" # Extraction mode: "concise", "verbose", or "custom"
|
||||
RETAIN_EXTRACTION_MODES = ("concise", "verbose", "custom") # Allowed extraction modes
|
||||
RETAIN_EXTRACTION_MODES = ("concise", "verbose", "custom", "verbatim", "chunks") # Allowed extraction modes
|
||||
DEFAULT_RETAIN_MISSION = None # Declarative spec of what to retain (injected into any extraction mode)
|
||||
DEFAULT_RETAIN_CUSTOM_INSTRUCTIONS = None # Custom extraction guidelines (only used when mode="custom")
|
||||
DEFAULT_RETAIN_DEFAULT_STRATEGY = None # Default strategy name (None = no strategy override)
|
||||
DEFAULT_RETAIN_STRATEGIES: dict | None = None # Named retain strategies (dict of name → config overrides)
|
||||
DEFAULT_RETAIN_BATCH_TOKENS = 10_000 # ~40KB of text # Max chars per sub-batch for async retain auto-splitting
|
||||
DEFAULT_RETAIN_ENTITY_LOOKUP = "trigram" # "full" or "trigram"
|
||||
DEFAULT_RETAIN_BATCH_ENABLED = False # Use LLM Batch API for fact extraction (only when async=True)
|
||||
DEFAULT_RETAIN_BATCH_POLL_INTERVAL_SECONDS = 60 # Batch API polling interval in seconds
|
||||
|
||||
# File storage defaults
|
||||
DEFAULT_FILE_STORAGE_TYPE = "native" # PostgreSQL BYTEA storage
|
||||
DEFAULT_FILE_PARSER = "markitdown" # Default parser fallback chain (comma-separated, e.g. "iris,markitdown")
|
||||
DEFAULT_FILE_PARSER_ALLOWLIST = None # Allowlist of parsers clients may request (None = all registered parsers)
|
||||
DEFAULT_FILE_CONVERSION_MAX_BATCH_SIZE_MB = 100 # Max total batch size in MB (all files combined)
|
||||
DEFAULT_FILE_CONVERSION_MAX_BATCH_SIZE = 10 # Max files per batch upload
|
||||
DEFAULT_ENABLE_FILE_UPLOAD_API = True # Enable file upload endpoint
|
||||
DEFAULT_FILE_DELETE_AFTER_RETAIN = True # Delete file bytes after retain (saves storage)
|
||||
|
||||
# Observations defaults (consolidated knowledge from facts)
|
||||
DEFAULT_ENABLE_OBSERVATIONS = True # Observations enabled by default
|
||||
DEFAULT_ENABLE_OBSERVATION_HISTORY = True # Observation history tracking enabled by default
|
||||
DEFAULT_ENABLE_MENTAL_MODEL_HISTORY = True # Mental model history tracking enabled by default
|
||||
DEFAULT_CONSOLIDATION_BATCH_SIZE = 50 # Memories to load per batch (internal memory optimization)
|
||||
DEFAULT_CONSOLIDATION_MAX_TOKENS = 1024 # Max tokens for recall when finding related observations
|
||||
DEFAULT_CONSOLIDATION_LLM_BATCH_SIZE = 8 # Facts per LLM call (1 = no batching; >1 = batch mode)
|
||||
DEFAULT_CONSOLIDATION_MAX_TOKENS = 512 # Max tokens for recall when finding related observations
|
||||
DEFAULT_CONSOLIDATION_SOURCE_FACTS_MAX_TOKENS = (
|
||||
-1
|
||||
) # Total token budget for source facts in consolidation recall (-1 = unlimited)
|
||||
DEFAULT_CONSOLIDATION_SOURCE_FACTS_MAX_TOKENS_PER_OBSERVATION = (
|
||||
256 # Max tokens of source facts per observation in consolidation prompt (-1 = unlimited)
|
||||
)
|
||||
DEFAULT_OBSERVATIONS_MISSION = None # Declarative spec of what observations are for this bank
|
||||
|
||||
# Database migrations
|
||||
DEFAULT_RUN_MIGRATIONS_ON_STARTUP = True
|
||||
@@ -274,6 +498,12 @@ DEFAULT_WORKER_CONSOLIDATION_MAX_SLOTS = 2 # Max concurrent consolidation tasks
|
||||
|
||||
# Reflect agent settings
|
||||
DEFAULT_REFLECT_MAX_ITERATIONS = 10 # Max tool call iterations before forcing response
|
||||
DEFAULT_REFLECT_MAX_CONTEXT_TOKENS = 100_000 # Max accumulated context tokens before forcing final prompt
|
||||
|
||||
# Disposition defaults (None = not set, fall back to bank DB value or 3)
|
||||
DEFAULT_DISPOSITION_SKEPTICISM = None
|
||||
DEFAULT_DISPOSITION_LITERALISM = None
|
||||
DEFAULT_DISPOSITION_EMPATHY = None
|
||||
|
||||
# OpenTelemetry tracing configuration
|
||||
DEFAULT_OTEL_TRACES_ENABLED = False # Disabled by default for backward compatibility
|
||||
@@ -303,6 +533,12 @@ Use this tool PROACTIVELY to:
|
||||
# Default embedding dimension (used by initial migration, adjusted at runtime)
|
||||
EMBEDDING_DIMENSION = DEFAULT_EMBEDDING_DIMENSION
|
||||
|
||||
# Webhook configuration defaults
|
||||
DEFAULT_WEBHOOK_URL = None # None = no global webhook configured
|
||||
DEFAULT_WEBHOOK_SECRET = None # None = no signing
|
||||
DEFAULT_WEBHOOK_EVENT_TYPES = "consolidation.completed" # Comma-separated; default = all supported events
|
||||
DEFAULT_WEBHOOK_DELIVERY_POLL_INTERVAL_SECONDS = 30 # How often to poll for pending deliveries
|
||||
|
||||
|
||||
class JsonFormatter(logging.Formatter):
|
||||
"""JSON formatter for structured logging.
|
||||
@@ -334,6 +570,11 @@ class JsonFormatter(logging.Formatter):
|
||||
return json.dumps(log_entry)
|
||||
|
||||
|
||||
def _parse_str_list(value: str) -> list[str]:
|
||||
"""Parse a comma-separated string into a non-empty list of stripped tokens."""
|
||||
return [v.strip() for v in value.split(",") if v.strip()]
|
||||
|
||||
|
||||
def _validate_extraction_mode(mode: str) -> str:
|
||||
"""Validate and normalize extraction mode."""
|
||||
mode_lower = mode.lower()
|
||||
@@ -358,6 +599,8 @@ class HindsightConfig:
|
||||
# Database
|
||||
database_url: str
|
||||
database_schema: str
|
||||
vector_extension: str # "pgvector" or "vchord"
|
||||
text_search_extension: str # "native" or "vchord"
|
||||
|
||||
# LLM (default, used as fallback for per-operation config)
|
||||
llm_provider: str
|
||||
@@ -369,12 +612,17 @@ class HindsightConfig:
|
||||
llm_initial_backoff: float
|
||||
llm_max_backoff: float
|
||||
llm_timeout: float
|
||||
llm_groq_service_tier: str # Groq: "on_demand", "flex", or "auto"
|
||||
llm_openai_service_tier: str | None # OpenAI: None (default) or "flex" (50% cheaper)
|
||||
|
||||
# Vertex AI configuration
|
||||
llm_vertexai_project_id: str | None
|
||||
llm_vertexai_region: str
|
||||
llm_vertexai_service_account_key: str | None
|
||||
|
||||
# Gemini safety settings (None = use Gemini defaults; list of dicts with category/threshold)
|
||||
llm_gemini_safety_settings: list | None
|
||||
|
||||
# Per-operation LLM configuration (None = use default LLM config)
|
||||
retain_llm_provider: str | None
|
||||
retain_llm_api_key: str | None
|
||||
@@ -419,6 +667,9 @@ class HindsightConfig:
|
||||
embeddings_litellm_api_base: str
|
||||
embeddings_litellm_api_key: str | None
|
||||
embeddings_litellm_model: str
|
||||
embeddings_litellm_sdk_api_key: str | None
|
||||
embeddings_litellm_sdk_model: str
|
||||
embeddings_litellm_sdk_api_base: str | None
|
||||
|
||||
# Reranker
|
||||
reranker_provider: str
|
||||
@@ -426,6 +677,9 @@ class HindsightConfig:
|
||||
reranker_local_force_cpu: bool
|
||||
reranker_local_max_concurrent: int
|
||||
reranker_local_trust_remote_code: bool
|
||||
reranker_local_fp16: bool
|
||||
reranker_local_bucket_batching: bool
|
||||
reranker_local_batch_size: int
|
||||
reranker_tei_url: str | None
|
||||
reranker_tei_batch_size: int
|
||||
reranker_tei_max_concurrent: int
|
||||
@@ -436,19 +690,29 @@ class HindsightConfig:
|
||||
reranker_litellm_api_base: str
|
||||
reranker_litellm_api_key: str | None
|
||||
reranker_litellm_model: str
|
||||
reranker_litellm_max_tokens_per_doc: int | None
|
||||
reranker_litellm_sdk_api_key: str | None
|
||||
reranker_litellm_sdk_model: str
|
||||
reranker_litellm_sdk_api_base: str | None
|
||||
reranker_zeroentropy_api_key: str | None
|
||||
reranker_zeroentropy_model: str
|
||||
|
||||
# Server
|
||||
host: str
|
||||
port: int
|
||||
base_path: str
|
||||
log_level: str
|
||||
log_format: str
|
||||
mcp_enabled: bool
|
||||
mcp_enabled_tools: list[str] | None # None = all tools; explicit list = allowlist
|
||||
enable_bank_config_api: bool
|
||||
|
||||
# Recall
|
||||
graph_retriever: str
|
||||
mpfp_top_k_neighbors: int
|
||||
recall_max_concurrent: int
|
||||
recall_connection_budget: int
|
||||
recall_max_query_tokens: int
|
||||
mental_model_refresh_concurrency: int
|
||||
|
||||
# Retain settings
|
||||
@@ -456,12 +720,61 @@ class HindsightConfig:
|
||||
retain_chunk_size: int
|
||||
retain_extract_causal_links: bool
|
||||
retain_extraction_mode: str
|
||||
retain_mission: str | None
|
||||
retain_custom_instructions: str | None
|
||||
retain_default_strategy: str | None
|
||||
retain_strategies: dict | None
|
||||
retain_batch_tokens: int
|
||||
retain_batch_enabled: bool
|
||||
retain_batch_poll_interval_seconds: int
|
||||
retain_entity_lookup: str # "full" or "trigram"
|
||||
|
||||
# File storage (static - server-level only)
|
||||
file_storage_type: str # "native" (PostgreSQL) or "s3" (S3-compatible)
|
||||
file_storage_s3_bucket: str | None # S3 bucket name (required for s3 storage)
|
||||
file_storage_s3_region: str | None # S3 region (optional, uses SDK default)
|
||||
file_storage_s3_endpoint: str | None # S3 endpoint URL (for MinIO, R2, etc.)
|
||||
file_storage_s3_access_key_id: str | None # S3 access key (optional, uses env/IAM)
|
||||
file_storage_s3_secret_access_key: str | None # S3 secret key (optional, uses env/IAM)
|
||||
file_storage_gcs_bucket: str | None # GCS bucket name (required for gcs storage)
|
||||
file_storage_gcs_service_account_key: str | None # GCS service account key JSON (optional, uses ADC)
|
||||
file_storage_azure_container: str | None # Azure container name (required for azure storage)
|
||||
file_storage_azure_account_name: str | None # Azure storage account name
|
||||
file_storage_azure_account_key: str | None # Azure storage account key
|
||||
file_parser: list[str] # Ordered fallback chain of parsers (e.g. ["iris", "markitdown"])
|
||||
file_parser_allowlist: list[str] | None # Parsers clients may request (None = all registered)
|
||||
file_parser_iris_token: str | None # Vectorize API token for iris parser (VECTORIZE_TOKEN)
|
||||
file_parser_iris_org_id: str | None # Vectorize org ID for iris parser (VECTORIZE_ORG_ID)
|
||||
file_conversion_max_batch_size_mb: int # Max total batch size in MB (all files combined)
|
||||
file_conversion_max_batch_size: int # Max files per request
|
||||
enable_file_upload_api: bool
|
||||
file_delete_after_retain: bool
|
||||
|
||||
# Observations settings (consolidated knowledge from facts)
|
||||
enable_observations: bool
|
||||
enable_observation_history: bool
|
||||
enable_mental_model_history: bool
|
||||
consolidation_batch_size: int
|
||||
consolidation_llm_batch_size: int
|
||||
consolidation_max_tokens: int
|
||||
consolidation_source_facts_max_tokens: int
|
||||
consolidation_source_facts_max_tokens_per_observation: int
|
||||
observations_mission: str | None
|
||||
|
||||
# Entity labels (controlled vocabulary of key:value classification labels extracted at retain time)
|
||||
# List of label group dicts: [{key, description, type, optional, values: [{value, description}]}]
|
||||
entity_labels: list | None
|
||||
# Whether to extract regular named entities alongside entity labels (default: True)
|
||||
# When False: only label entities are extracted (or no entities at all if no labels configured)
|
||||
entities_allow_free_form: bool
|
||||
|
||||
# Reflect agent settings
|
||||
reflect_mission: str | None
|
||||
|
||||
# Disposition settings (hierarchical - can be overridden per bank; None = fall back to DB)
|
||||
disposition_skepticism: int | None
|
||||
disposition_literalism: int | None
|
||||
disposition_empathy: int | None
|
||||
|
||||
# Optimization flags
|
||||
skip_llm_verification: bool
|
||||
@@ -487,6 +800,7 @@ class HindsightConfig:
|
||||
|
||||
# Reflect agent settings
|
||||
reflect_max_iterations: int
|
||||
reflect_max_context_tokens: int
|
||||
|
||||
# OpenTelemetry tracing configuration
|
||||
otel_traces_enabled: bool
|
||||
@@ -495,8 +809,146 @@ class HindsightConfig:
|
||||
otel_service_name: str
|
||||
otel_deployment_environment: str
|
||||
|
||||
# Webhook configuration (static - server-level only, not per-bank)
|
||||
webhook_url: str | None # Global webhook URL (None = disabled)
|
||||
webhook_secret: str | None # HMAC signing secret (None = unsigned)
|
||||
webhook_event_types: list[str] # Event types to deliver globally
|
||||
webhook_delivery_poll_interval_seconds: int # How often the delivery worker polls
|
||||
|
||||
# Class-level sets for configuration categorization
|
||||
|
||||
# CREDENTIAL_FIELDS: Never exposed via API, never configurable per-tenant/bank
|
||||
_CREDENTIAL_FIELDS = {
|
||||
# API Keys
|
||||
"llm_api_key",
|
||||
"retain_llm_api_key",
|
||||
"reflect_llm_api_key",
|
||||
"consolidation_llm_api_key",
|
||||
# Base URLs (could expose infrastructure)
|
||||
"llm_base_url",
|
||||
"retain_llm_base_url",
|
||||
"reflect_llm_base_url",
|
||||
"consolidation_llm_base_url",
|
||||
"embeddings_tei_base_url",
|
||||
"reranker_tei_base_url",
|
||||
"reranker_cohere_base_url",
|
||||
# Service Account Keys
|
||||
"llm_vertexai_service_account_key",
|
||||
# File storage credentials
|
||||
"file_storage_s3_access_key_id",
|
||||
"file_storage_s3_secret_access_key",
|
||||
"file_storage_gcs_service_account_key",
|
||||
"file_storage_azure_account_key",
|
||||
# File parser credentials
|
||||
"file_parser_iris_token",
|
||||
}
|
||||
|
||||
# CONFIGURABLE_FIELDS: Safe behavioral settings that can be customized per-tenant/bank
|
||||
# These fields are manually tagged as safe to expose and modify.
|
||||
# Excludes credentials, infrastructure config, provider/model selection, and performance tuning.
|
||||
_CONFIGURABLE_FIELDS = {
|
||||
# MCP tool access control
|
||||
"mcp_enabled_tools",
|
||||
# Retention settings (behavioral)
|
||||
"retain_chunk_size",
|
||||
"retain_extraction_mode",
|
||||
"retain_mission",
|
||||
"retain_custom_instructions",
|
||||
"retain_default_strategy",
|
||||
"retain_strategies",
|
||||
# Entity labels (controlled vocabulary for entity classification)
|
||||
"entity_labels",
|
||||
"entities_allow_free_form",
|
||||
# Consolidation settings
|
||||
"enable_observations",
|
||||
"consolidation_llm_batch_size",
|
||||
"consolidation_source_facts_max_tokens",
|
||||
"consolidation_source_facts_max_tokens_per_observation",
|
||||
"observations_mission",
|
||||
# Reflect settings
|
||||
"reflect_mission",
|
||||
# Disposition settings
|
||||
"disposition_skepticism",
|
||||
"disposition_literalism",
|
||||
"disposition_empathy",
|
||||
# Gemini safety settings (controls content filtering for Gemini/VertexAI providers)
|
||||
"llm_gemini_safety_settings",
|
||||
}
|
||||
|
||||
@property
|
||||
def file_conversion_max_batch_size_bytes(self) -> int:
|
||||
"""Get maximum total batch size in bytes."""
|
||||
return self.file_conversion_max_batch_size_mb * 1024 * 1024
|
||||
|
||||
@classmethod
|
||||
def get_configurable_fields(cls) -> set[str]:
|
||||
"""
|
||||
Get set of field names that are configurable per-tenant/bank via API.
|
||||
|
||||
Configurable fields are manually tagged behavioral settings that are safe
|
||||
to expose and modify (e.g., retain_chunk_size, custom_instructions).
|
||||
Excludes credentials, infrastructure config, and provider/model selection.
|
||||
|
||||
Returns:
|
||||
Set of configurable field names
|
||||
"""
|
||||
return cls._CONFIGURABLE_FIELDS.copy()
|
||||
|
||||
@classmethod
|
||||
def get_credential_fields(cls) -> set[str]:
|
||||
"""
|
||||
Get set of field names that are credentials (NEVER exposed via API).
|
||||
|
||||
Credential fields include API keys, base URLs, and service account keys.
|
||||
These must never be returned in API responses or accepted in updates.
|
||||
|
||||
Returns:
|
||||
Set of credential field names
|
||||
"""
|
||||
return cls._CREDENTIAL_FIELDS.copy()
|
||||
|
||||
@classmethod
|
||||
def get_hierarchical_fields(cls) -> set[str]:
|
||||
"""
|
||||
DEPRECATED: Use get_configurable_fields() instead.
|
||||
|
||||
Kept for backward compatibility during migration.
|
||||
"""
|
||||
return cls.get_configurable_fields()
|
||||
|
||||
@classmethod
|
||||
def get_static_fields(cls) -> set[str]:
|
||||
"""
|
||||
Get set of field names that are static (server-level only).
|
||||
|
||||
Static fields are infrastructure-level settings that cannot vary
|
||||
per tenant or bank. These include database config, API port, worker settings, etc.
|
||||
Also includes credential fields which are never configurable.
|
||||
|
||||
Returns:
|
||||
Set of static field names
|
||||
"""
|
||||
# Get all field names from dataclass
|
||||
all_fields = {f.name for f in fields(cls)}
|
||||
# Static fields = all fields - configurable fields
|
||||
return all_fields - cls._CONFIGURABLE_FIELDS
|
||||
|
||||
def validate(self) -> None:
|
||||
"""Validate configuration values and raise errors for invalid combinations."""
|
||||
# Validate vector_extension
|
||||
valid_extensions = ("pgvector", "vchord", "pgvectorscale")
|
||||
if self.vector_extension not in valid_extensions:
|
||||
raise ValueError(
|
||||
f"Invalid vector_extension: {self.vector_extension}. Must be one of: {', '.join(valid_extensions)}"
|
||||
)
|
||||
|
||||
# Validate text_search_extension
|
||||
valid_text_search = ("native", "vchord", "pg_textsearch")
|
||||
if self.text_search_extension not in valid_text_search:
|
||||
raise ValueError(
|
||||
f"Invalid text_search_extension: {self.text_search_extension}. Must be one of: {', '.join(valid_text_search)}"
|
||||
)
|
||||
|
||||
# RETAIN_MAX_COMPLETION_TOKENS must be greater than RETAIN_CHUNK_SIZE
|
||||
# to ensure the LLM has enough output capacity to extract facts from chunks
|
||||
if self.retain_max_completion_tokens <= self.retain_chunk_size:
|
||||
@@ -522,6 +974,8 @@ class HindsightConfig:
|
||||
# Database
|
||||
database_url=os.getenv(ENV_DATABASE_URL, DEFAULT_DATABASE_URL),
|
||||
database_schema=os.getenv(ENV_DATABASE_SCHEMA, DEFAULT_DATABASE_SCHEMA),
|
||||
vector_extension=os.getenv(ENV_VECTOR_EXTENSION, DEFAULT_VECTOR_EXTENSION).lower(),
|
||||
text_search_extension=os.getenv(ENV_TEXT_SEARCH_EXTENSION, DEFAULT_TEXT_SEARCH_EXTENSION).lower(),
|
||||
# LLM
|
||||
llm_provider=llm_provider,
|
||||
llm_api_key=os.getenv(ENV_LLM_API_KEY),
|
||||
@@ -532,11 +986,15 @@ class HindsightConfig:
|
||||
llm_initial_backoff=float(os.getenv(ENV_LLM_INITIAL_BACKOFF, str(DEFAULT_LLM_INITIAL_BACKOFF))),
|
||||
llm_max_backoff=float(os.getenv(ENV_LLM_MAX_BACKOFF, str(DEFAULT_LLM_MAX_BACKOFF))),
|
||||
llm_timeout=float(os.getenv(ENV_LLM_TIMEOUT, str(DEFAULT_LLM_TIMEOUT))),
|
||||
llm_groq_service_tier=os.getenv(ENV_LLM_GROQ_SERVICE_TIER, DEFAULT_LLM_GROQ_SERVICE_TIER),
|
||||
llm_openai_service_tier=os.getenv(ENV_LLM_OPENAI_SERVICE_TIER, DEFAULT_LLM_OPENAI_SERVICE_TIER),
|
||||
# Vertex AI
|
||||
llm_vertexai_project_id=os.getenv(ENV_LLM_VERTEXAI_PROJECT_ID) or DEFAULT_LLM_VERTEXAI_PROJECT_ID,
|
||||
llm_vertexai_region=os.getenv(ENV_LLM_VERTEXAI_REGION, DEFAULT_LLM_VERTEXAI_REGION),
|
||||
llm_vertexai_service_account_key=os.getenv(ENV_LLM_VERTEXAI_SERVICE_ACCOUNT_KEY)
|
||||
or DEFAULT_LLM_VERTEXAI_SERVICE_ACCOUNT_KEY,
|
||||
# Gemini safety settings (JSON-encoded list of {category, threshold} dicts)
|
||||
llm_gemini_safety_settings=json.loads(os.getenv(ENV_LLM_GEMINI_SAFETY_SETTINGS, "null")),
|
||||
# Per-operation LLM config (None = use default)
|
||||
retain_llm_provider=os.getenv(ENV_RETAIN_LLM_PROVIDER) or None,
|
||||
retain_llm_api_key=os.getenv(ENV_RETAIN_LLM_API_KEY) or None,
|
||||
@@ -630,6 +1088,12 @@ class HindsightConfig:
|
||||
or os.getenv(ENV_LITELLM_API_BASE, DEFAULT_LITELLM_API_BASE),
|
||||
embeddings_litellm_api_key=os.getenv(ENV_EMBEDDINGS_LITELLM_API_KEY) or os.getenv(ENV_LITELLM_API_KEY),
|
||||
embeddings_litellm_model=os.getenv(ENV_EMBEDDINGS_LITELLM_MODEL, DEFAULT_EMBEDDINGS_LITELLM_MODEL),
|
||||
# LiteLLM SDK embeddings (direct API access)
|
||||
embeddings_litellm_sdk_api_key=os.getenv(ENV_EMBEDDINGS_LITELLM_SDK_API_KEY),
|
||||
embeddings_litellm_sdk_model=os.getenv(
|
||||
ENV_EMBEDDINGS_LITELLM_SDK_MODEL, DEFAULT_EMBEDDINGS_LITELLM_SDK_MODEL
|
||||
),
|
||||
embeddings_litellm_sdk_api_base=os.getenv(ENV_EMBEDDINGS_LITELLM_SDK_API_BASE) or None,
|
||||
# Reranker
|
||||
reranker_provider=os.getenv(ENV_RERANKER_PROVIDER, DEFAULT_RERANKER_PROVIDER),
|
||||
reranker_local_model=os.getenv(ENV_RERANKER_LOCAL_MODEL, DEFAULT_RERANKER_LOCAL_MODEL),
|
||||
@@ -644,6 +1108,15 @@ class HindsightConfig:
|
||||
ENV_RERANKER_LOCAL_TRUST_REMOTE_CODE, str(DEFAULT_RERANKER_LOCAL_TRUST_REMOTE_CODE)
|
||||
).lower()
|
||||
in ("true", "1"),
|
||||
reranker_local_fp16=os.getenv(ENV_RERANKER_LOCAL_FP16, str(DEFAULT_RERANKER_LOCAL_FP16)).lower()
|
||||
in ("true", "1"),
|
||||
reranker_local_bucket_batching=os.getenv(
|
||||
ENV_RERANKER_LOCAL_BUCKET_BATCHING, str(DEFAULT_RERANKER_LOCAL_BUCKET_BATCHING)
|
||||
).lower()
|
||||
in ("true", "1"),
|
||||
reranker_local_batch_size=int(
|
||||
os.getenv(ENV_RERANKER_LOCAL_BATCH_SIZE, str(DEFAULT_RERANKER_LOCAL_BATCH_SIZE))
|
||||
),
|
||||
reranker_tei_url=os.getenv(ENV_RERANKER_TEI_URL),
|
||||
reranker_tei_batch_size=int(os.getenv(ENV_RERANKER_TEI_BATCH_SIZE, str(DEFAULT_RERANKER_TEI_BATCH_SIZE))),
|
||||
reranker_tei_max_concurrent=int(
|
||||
@@ -659,12 +1132,28 @@ class HindsightConfig:
|
||||
or os.getenv(ENV_LITELLM_API_BASE, DEFAULT_LITELLM_API_BASE),
|
||||
reranker_litellm_api_key=os.getenv(ENV_RERANKER_LITELLM_API_KEY) or os.getenv(ENV_LITELLM_API_KEY),
|
||||
reranker_litellm_model=os.getenv(ENV_RERANKER_LITELLM_MODEL, DEFAULT_RERANKER_LITELLM_MODEL),
|
||||
reranker_litellm_max_tokens_per_doc=int(v)
|
||||
if (v := os.getenv(ENV_RERANKER_LITELLM_MAX_TOKENS_PER_DOC))
|
||||
else DEFAULT_RERANKER_LITELLM_MAX_TOKENS_PER_DOC,
|
||||
# LiteLLM SDK reranker (direct API access)
|
||||
reranker_litellm_sdk_api_key=os.getenv(ENV_RERANKER_LITELLM_SDK_API_KEY),
|
||||
reranker_litellm_sdk_model=os.getenv(ENV_RERANKER_LITELLM_SDK_MODEL, DEFAULT_RERANKER_LITELLM_SDK_MODEL),
|
||||
reranker_litellm_sdk_api_base=os.getenv(ENV_RERANKER_LITELLM_SDK_API_BASE) or None,
|
||||
# ZeroEntropy reranker
|
||||
reranker_zeroentropy_api_key=os.getenv(ENV_RERANKER_ZEROENTROPY_API_KEY),
|
||||
reranker_zeroentropy_model=os.getenv(ENV_RERANKER_ZEROENTROPY_MODEL, DEFAULT_RERANKER_ZEROENTROPY_MODEL),
|
||||
# Server
|
||||
host=os.getenv(ENV_HOST, DEFAULT_HOST),
|
||||
port=int(os.getenv(ENV_PORT, DEFAULT_PORT)),
|
||||
base_path=os.getenv(ENV_BASE_PATH, DEFAULT_BASE_PATH),
|
||||
log_level=os.getenv(ENV_LOG_LEVEL, DEFAULT_LOG_LEVEL),
|
||||
log_format=os.getenv(ENV_LOG_FORMAT, DEFAULT_LOG_FORMAT).lower(),
|
||||
mcp_enabled=os.getenv(ENV_MCP_ENABLED, str(DEFAULT_MCP_ENABLED)).lower() == "true",
|
||||
mcp_enabled_tools=[t.strip() for t in os.getenv(ENV_MCP_ENABLED_TOOLS).split(",") if t.strip()]
|
||||
if os.getenv(ENV_MCP_ENABLED_TOOLS)
|
||||
else DEFAULT_MCP_ENABLED_TOOLS,
|
||||
enable_bank_config_api=os.getenv(ENV_ENABLE_BANK_CONFIG_API, str(DEFAULT_ENABLE_BANK_CONFIG_API)).lower()
|
||||
== "true",
|
||||
# Recall
|
||||
graph_retriever=os.getenv(ENV_GRAPH_RETRIEVER, DEFAULT_GRAPH_RETRIEVER),
|
||||
mpfp_top_k_neighbors=int(os.getenv(ENV_MPFP_TOP_K_NEIGHBORS, str(DEFAULT_MPFP_TOP_K_NEIGHBORS))),
|
||||
@@ -672,6 +1161,7 @@ class HindsightConfig:
|
||||
recall_connection_budget=int(
|
||||
os.getenv(ENV_RECALL_CONNECTION_BUDGET, str(DEFAULT_RECALL_CONNECTION_BUDGET))
|
||||
),
|
||||
recall_max_query_tokens=int(os.getenv(ENV_RECALL_MAX_QUERY_TOKENS, str(DEFAULT_RECALL_MAX_QUERY_TOKENS))),
|
||||
mental_model_refresh_concurrency=int(
|
||||
os.getenv(ENV_MENTAL_MODEL_REFRESH_CONCURRENCY, str(DEFAULT_MENTAL_MODEL_REFRESH_CONCURRENCY))
|
||||
),
|
||||
@@ -690,15 +1180,78 @@ class HindsightConfig:
|
||||
retain_extraction_mode=_validate_extraction_mode(
|
||||
os.getenv(ENV_RETAIN_EXTRACTION_MODE, DEFAULT_RETAIN_EXTRACTION_MODE)
|
||||
),
|
||||
retain_mission=os.getenv(ENV_RETAIN_MISSION) or DEFAULT_RETAIN_MISSION,
|
||||
retain_custom_instructions=os.getenv(ENV_RETAIN_CUSTOM_INSTRUCTIONS) or DEFAULT_RETAIN_CUSTOM_INSTRUCTIONS,
|
||||
retain_default_strategy=os.getenv(ENV_RETAIN_DEFAULT_STRATEGY) or DEFAULT_RETAIN_DEFAULT_STRATEGY,
|
||||
retain_strategies=DEFAULT_RETAIN_STRATEGIES,
|
||||
retain_batch_tokens=int(os.getenv(ENV_RETAIN_BATCH_TOKENS, str(DEFAULT_RETAIN_BATCH_TOKENS))),
|
||||
retain_entity_lookup=os.getenv(ENV_RETAIN_ENTITY_LOOKUP, DEFAULT_RETAIN_ENTITY_LOOKUP),
|
||||
retain_batch_enabled=os.getenv(ENV_RETAIN_BATCH_ENABLED, str(DEFAULT_RETAIN_BATCH_ENABLED)).lower()
|
||||
== "true",
|
||||
retain_batch_poll_interval_seconds=int(
|
||||
os.getenv(ENV_RETAIN_BATCH_POLL_INTERVAL_SECONDS, str(DEFAULT_RETAIN_BATCH_POLL_INTERVAL_SECONDS))
|
||||
),
|
||||
# File storage
|
||||
file_storage_type=os.getenv(ENV_FILE_STORAGE_TYPE, DEFAULT_FILE_STORAGE_TYPE),
|
||||
file_storage_s3_bucket=os.getenv(ENV_FILE_STORAGE_S3_BUCKET) or None,
|
||||
file_storage_s3_region=os.getenv(ENV_FILE_STORAGE_S3_REGION) or None,
|
||||
file_storage_s3_endpoint=os.getenv(ENV_FILE_STORAGE_S3_ENDPOINT) or None,
|
||||
file_storage_s3_access_key_id=os.getenv(ENV_FILE_STORAGE_S3_ACCESS_KEY_ID) or None,
|
||||
file_storage_s3_secret_access_key=os.getenv(ENV_FILE_STORAGE_S3_SECRET_ACCESS_KEY) or None,
|
||||
file_storage_gcs_bucket=os.getenv(ENV_FILE_STORAGE_GCS_BUCKET) or None,
|
||||
file_storage_gcs_service_account_key=os.getenv(ENV_FILE_STORAGE_GCS_SERVICE_ACCOUNT_KEY) or None,
|
||||
file_storage_azure_container=os.getenv(ENV_FILE_STORAGE_AZURE_CONTAINER) or None,
|
||||
file_storage_azure_account_name=os.getenv(ENV_FILE_STORAGE_AZURE_ACCOUNT_NAME) or None,
|
||||
file_storage_azure_account_key=os.getenv(ENV_FILE_STORAGE_AZURE_ACCOUNT_KEY) or None,
|
||||
file_parser=_parse_str_list(os.getenv(ENV_FILE_PARSER, DEFAULT_FILE_PARSER)),
|
||||
file_parser_allowlist=_parse_str_list(os.getenv(ENV_FILE_PARSER_ALLOWLIST))
|
||||
if os.getenv(ENV_FILE_PARSER_ALLOWLIST)
|
||||
else None,
|
||||
file_parser_iris_token=os.getenv(ENV_FILE_PARSER_IRIS_TOKEN) or None,
|
||||
file_parser_iris_org_id=os.getenv(ENV_FILE_PARSER_IRIS_ORG_ID) or None,
|
||||
file_conversion_max_batch_size_mb=int(
|
||||
os.getenv(ENV_FILE_CONVERSION_MAX_BATCH_SIZE_MB, str(DEFAULT_FILE_CONVERSION_MAX_BATCH_SIZE_MB))
|
||||
),
|
||||
file_conversion_max_batch_size=int(
|
||||
os.getenv(ENV_FILE_CONVERSION_MAX_BATCH_SIZE, str(DEFAULT_FILE_CONVERSION_MAX_BATCH_SIZE))
|
||||
),
|
||||
enable_file_upload_api=os.getenv(ENV_ENABLE_FILE_UPLOAD_API, str(DEFAULT_ENABLE_FILE_UPLOAD_API)).lower()
|
||||
== "true",
|
||||
file_delete_after_retain=os.getenv(
|
||||
ENV_FILE_DELETE_AFTER_RETAIN, str(DEFAULT_FILE_DELETE_AFTER_RETAIN)
|
||||
).lower()
|
||||
== "true",
|
||||
# Observations settings (consolidated knowledge from facts)
|
||||
enable_observations=os.getenv(ENV_ENABLE_OBSERVATIONS, str(DEFAULT_ENABLE_OBSERVATIONS)).lower() == "true",
|
||||
enable_observation_history=os.getenv(
|
||||
ENV_ENABLE_OBSERVATION_HISTORY, str(DEFAULT_ENABLE_OBSERVATION_HISTORY)
|
||||
).lower()
|
||||
== "true",
|
||||
enable_mental_model_history=os.getenv(
|
||||
ENV_ENABLE_MENTAL_MODEL_HISTORY, str(DEFAULT_ENABLE_MENTAL_MODEL_HISTORY)
|
||||
).lower()
|
||||
== "true",
|
||||
consolidation_batch_size=int(
|
||||
os.getenv(ENV_CONSOLIDATION_BATCH_SIZE, str(DEFAULT_CONSOLIDATION_BATCH_SIZE))
|
||||
),
|
||||
consolidation_llm_batch_size=int(
|
||||
os.getenv(ENV_CONSOLIDATION_LLM_BATCH_SIZE, str(DEFAULT_CONSOLIDATION_LLM_BATCH_SIZE))
|
||||
),
|
||||
consolidation_max_tokens=int(
|
||||
os.getenv(ENV_CONSOLIDATION_MAX_TOKENS, str(DEFAULT_CONSOLIDATION_MAX_TOKENS))
|
||||
),
|
||||
consolidation_source_facts_max_tokens=int(
|
||||
os.getenv(ENV_CONSOLIDATION_SOURCE_FACTS_MAX_TOKENS, str(DEFAULT_CONSOLIDATION_SOURCE_FACTS_MAX_TOKENS))
|
||||
),
|
||||
consolidation_source_facts_max_tokens_per_observation=int(
|
||||
os.getenv(
|
||||
ENV_CONSOLIDATION_SOURCE_FACTS_MAX_TOKENS_PER_OBSERVATION,
|
||||
str(DEFAULT_CONSOLIDATION_SOURCE_FACTS_MAX_TOKENS_PER_OBSERVATION),
|
||||
)
|
||||
),
|
||||
observations_mission=os.getenv(ENV_OBSERVATIONS_MISSION) or DEFAULT_OBSERVATIONS_MISSION,
|
||||
entity_labels=None,
|
||||
entities_allow_free_form=True,
|
||||
# Database migrations
|
||||
run_migrations_on_startup=os.getenv(ENV_RUN_MIGRATIONS_ON_STARTUP, "true").lower() == "true",
|
||||
# Database connection pool
|
||||
@@ -718,6 +1271,20 @@ class HindsightConfig:
|
||||
),
|
||||
# Reflect agent settings
|
||||
reflect_max_iterations=int(os.getenv(ENV_REFLECT_MAX_ITERATIONS, str(DEFAULT_REFLECT_MAX_ITERATIONS))),
|
||||
reflect_max_context_tokens=int(
|
||||
os.getenv(ENV_REFLECT_MAX_CONTEXT_TOKENS, str(DEFAULT_REFLECT_MAX_CONTEXT_TOKENS))
|
||||
),
|
||||
reflect_mission=os.getenv(ENV_REFLECT_MISSION) or None,
|
||||
# Disposition settings (None = fall back to DB value)
|
||||
disposition_skepticism=int(os.getenv(ENV_DISPOSITION_SKEPTICISM))
|
||||
if os.getenv(ENV_DISPOSITION_SKEPTICISM)
|
||||
else DEFAULT_DISPOSITION_SKEPTICISM,
|
||||
disposition_literalism=int(os.getenv(ENV_DISPOSITION_LITERALISM))
|
||||
if os.getenv(ENV_DISPOSITION_LITERALISM)
|
||||
else DEFAULT_DISPOSITION_LITERALISM,
|
||||
disposition_empathy=int(os.getenv(ENV_DISPOSITION_EMPATHY))
|
||||
if os.getenv(ENV_DISPOSITION_EMPATHY)
|
||||
else DEFAULT_DISPOSITION_EMPATHY,
|
||||
# OpenTelemetry tracing configuration
|
||||
otel_traces_enabled=os.getenv(ENV_OTEL_TRACES_ENABLED, str(DEFAULT_OTEL_TRACES_ENABLED)).lower()
|
||||
in ("true", "1", "yes"),
|
||||
@@ -725,6 +1292,20 @@ class HindsightConfig:
|
||||
otel_exporter_otlp_headers=os.getenv(ENV_OTEL_EXPORTER_OTLP_HEADERS) or None,
|
||||
otel_service_name=os.getenv(ENV_OTEL_SERVICE_NAME, DEFAULT_OTEL_SERVICE_NAME),
|
||||
otel_deployment_environment=os.getenv(ENV_OTEL_DEPLOYMENT_ENVIRONMENT, DEFAULT_OTEL_DEPLOYMENT_ENVIRONMENT),
|
||||
# Webhook configuration (static, server-level only)
|
||||
webhook_url=os.getenv(ENV_WEBHOOK_URL) or DEFAULT_WEBHOOK_URL,
|
||||
webhook_secret=os.getenv(ENV_WEBHOOK_SECRET) or DEFAULT_WEBHOOK_SECRET,
|
||||
webhook_event_types=[
|
||||
t.strip()
|
||||
for t in os.getenv(ENV_WEBHOOK_EVENT_TYPES, DEFAULT_WEBHOOK_EVENT_TYPES).split(",")
|
||||
if t.strip()
|
||||
],
|
||||
webhook_delivery_poll_interval_seconds=int(
|
||||
os.getenv(
|
||||
ENV_WEBHOOK_DELIVERY_POLL_INTERVAL_SECONDS,
|
||||
str(DEFAULT_WEBHOOK_DELIVERY_POLL_INTERVAL_SECONDS),
|
||||
)
|
||||
),
|
||||
)
|
||||
config.validate()
|
||||
return config
|
||||
@@ -805,8 +1386,35 @@ class HindsightConfig:
|
||||
_config_cache: HindsightConfig | None = None
|
||||
|
||||
|
||||
def get_config() -> HindsightConfig:
|
||||
"""Get the cached configuration, loading from environment on first call."""
|
||||
def get_config() -> StaticConfigProxy:
|
||||
"""
|
||||
Get global configuration with ONLY static (non-configurable) fields accessible.
|
||||
|
||||
This returns a proxy that prevents access to bank-configurable fields
|
||||
(like enable_observations, retain_chunk_size, etc.).
|
||||
|
||||
For bank-specific configuration, use:
|
||||
config_resolver.resolve_full_config(bank_id, context)
|
||||
|
||||
This design prevents accidentally using global defaults when bank-specific
|
||||
overrides exist.
|
||||
|
||||
Returns:
|
||||
StaticConfigProxy that only exposes static infrastructure fields
|
||||
|
||||
Raises:
|
||||
ConfigFieldAccessError: If you try to access a bank-configurable field
|
||||
"""
|
||||
return StaticConfigProxy(_get_raw_config())
|
||||
|
||||
|
||||
def _get_raw_config() -> HindsightConfig:
|
||||
"""
|
||||
Get raw config (internal use only).
|
||||
|
||||
INTERNAL USE ONLY. Do not use this directly in application code.
|
||||
Use get_config() for static fields or ConfigResolver.resolve_full_config() for bank-specific config.
|
||||
"""
|
||||
global _config_cache
|
||||
if _config_cache is None:
|
||||
_config_cache = HindsightConfig.from_env()
|
||||
@@ -0,0 +1,315 @@
|
||||
"""
|
||||
Configuration resolution with hierarchical overrides.
|
||||
|
||||
Resolves config values through the hierarchy:
|
||||
Global (env vars) → Tenant config (via extension) → Bank config (database)
|
||||
|
||||
Config values are resolved on every request to ensure consistency across
|
||||
multiple API servers.
|
||||
"""
|
||||
|
||||
import json
|
||||
import logging
|
||||
from dataclasses import asdict, replace
|
||||
from typing import Any
|
||||
|
||||
import asyncpg
|
||||
|
||||
from hindsight_api.config import HindsightConfig, _get_raw_config, normalize_config_dict
|
||||
from hindsight_api.engine.memory_engine import fq_table
|
||||
from hindsight_api.extensions.tenant import TenantExtension
|
||||
from hindsight_api.models import RequestContext
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class ConfigResolver:
|
||||
"""Resolves hierarchical configuration with tenant/bank overrides."""
|
||||
|
||||
def __init__(self, pool: asyncpg.Pool, tenant_extension: TenantExtension | None = None):
|
||||
"""
|
||||
Initialize config resolver.
|
||||
|
||||
Args:
|
||||
pool: Database connection pool
|
||||
tenant_extension: Optional tenant extension for tenant-level config and permissions
|
||||
"""
|
||||
self.pool = pool
|
||||
self.tenant_extension = tenant_extension
|
||||
self._global_config = _get_raw_config()
|
||||
self._configurable_fields = HindsightConfig.get_configurable_fields()
|
||||
self._credential_fields = HindsightConfig.get_credential_fields()
|
||||
|
||||
async def resolve_full_config(self, bank_id: str, context: RequestContext | None = None) -> HindsightConfig:
|
||||
"""
|
||||
Resolve full HindsightConfig for a bank with hierarchical overrides applied.
|
||||
|
||||
This is for INTERNAL USE ONLY. Returns the complete config object with all fields
|
||||
including credentials and static fields. Use get_bank_config() for API responses.
|
||||
|
||||
Resolution order:
|
||||
1. Global config (from environment variables)
|
||||
2. Tenant config overrides (from TenantExtension.get_tenant_config())
|
||||
3. Bank config overrides (from banks.config JSONB)
|
||||
|
||||
Args:
|
||||
bank_id: Bank identifier
|
||||
context: Request context for tenant config resolution
|
||||
|
||||
Returns:
|
||||
Complete HindsightConfig with hierarchical overrides applied
|
||||
"""
|
||||
# Start with global config (all fields)
|
||||
config_dict = asdict(self._global_config)
|
||||
|
||||
# Load tenant config overrides (if tenant extension available)
|
||||
if self.tenant_extension and context:
|
||||
try:
|
||||
tenant_overrides = await self.tenant_extension.get_tenant_config(context)
|
||||
if tenant_overrides:
|
||||
# Normalize keys and filter to configurable fields only
|
||||
normalized_tenant = normalize_config_dict(tenant_overrides)
|
||||
configurable_tenant = {k: v for k, v in normalized_tenant.items() if k in self._configurable_fields}
|
||||
config_dict.update(configurable_tenant)
|
||||
logger.debug(
|
||||
f"Applied tenant config overrides for bank {bank_id}: {list(configurable_tenant.keys())}"
|
||||
)
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to load tenant config for bank {bank_id}: {e}")
|
||||
|
||||
# Load bank config overrides
|
||||
bank_overrides = await self._load_bank_config(bank_id)
|
||||
if bank_overrides:
|
||||
config_dict.update(bank_overrides)
|
||||
logger.debug(f"Applied bank config overrides for bank {bank_id}: {list(bank_overrides.keys())}")
|
||||
|
||||
# Return full config object (dataclass doesn't have __init__ that accepts kwargs, so we update the object)
|
||||
# Create a new config instance by copying the global config and updating fields
|
||||
resolved_config = HindsightConfig(**config_dict)
|
||||
return resolved_config
|
||||
|
||||
async def get_bank_config(self, bank_id: str, context: RequestContext | None = None) -> dict[str, Any]:
|
||||
"""
|
||||
Get fully resolved config for a bank (filtered by permissions).
|
||||
|
||||
Resolution order:
|
||||
1. Global config (from environment variables)
|
||||
2. Tenant config overrides (from TenantExtension.get_tenant_config())
|
||||
3. Bank config overrides (from banks.config JSONB)
|
||||
|
||||
Note: Config is resolved on every call (not cached) to ensure consistency
|
||||
across multiple API servers.
|
||||
|
||||
SECURITY:
|
||||
- Only returns configurable fields (excludes static/infrastructure fields)
|
||||
- Filters out ALL credential fields (API keys, base URLs, etc.)
|
||||
- Further filtered by tenant/bank permissions if extension provides them
|
||||
|
||||
Args:
|
||||
bank_id: Bank identifier
|
||||
context: Request context for tenant config resolution and permissions
|
||||
|
||||
Returns:
|
||||
Dict of allowed configurable fields only (never includes credentials or static fields)
|
||||
"""
|
||||
# Resolve full config with all hierarchical overrides
|
||||
resolved_config = await self.resolve_full_config(bank_id, context)
|
||||
config_dict = asdict(resolved_config)
|
||||
|
||||
# SECURITY: Filter to only configurable fields (exclude static/infrastructure)
|
||||
filtered = {k: v for k, v in config_dict.items() if k in self._configurable_fields}
|
||||
|
||||
# SECURITY: Remove ALL credential fields (API keys, base URLs, etc.)
|
||||
filtered = {k: v for k, v in filtered.items() if k not in self._credential_fields}
|
||||
|
||||
# PERMISSIONS: Further filter based on tenant/bank permissions
|
||||
if self.tenant_extension and context:
|
||||
try:
|
||||
allowed_fields = await self.tenant_extension.get_allowed_config_fields(context, bank_id)
|
||||
if allowed_fields is not None: # None means "allow all"
|
||||
filtered = {k: v for k, v in filtered.items() if k in allowed_fields}
|
||||
logger.debug(
|
||||
f"Applied permission filter for bank {bank_id}: allowed={len(allowed_fields)} fields, "
|
||||
f"returned={len(filtered)} fields"
|
||||
)
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to load permissions for bank {bank_id}: {e}")
|
||||
|
||||
return filtered
|
||||
|
||||
async def _load_bank_config(self, bank_id: str) -> dict[str, Any]:
|
||||
"""
|
||||
Load bank config overrides from banks.config JSONB column.
|
||||
|
||||
Args:
|
||||
bank_id: Bank identifier
|
||||
|
||||
Returns:
|
||||
Dict of config overrides (only configurable fields, normalized keys)
|
||||
"""
|
||||
try:
|
||||
async with self.pool.acquire() as conn:
|
||||
row = await conn.fetchrow(
|
||||
f"""
|
||||
SELECT config FROM {fq_table("banks")} WHERE bank_id = $1
|
||||
""",
|
||||
bank_id,
|
||||
)
|
||||
|
||||
if row and row["config"]:
|
||||
config_data = row["config"]
|
||||
|
||||
# Handle case where JSONB is returned as JSON string
|
||||
if isinstance(config_data, str):
|
||||
config_data = json.loads(config_data)
|
||||
|
||||
# Normalize keys (handle both env var format and Python field format)
|
||||
normalized = normalize_config_dict(config_data)
|
||||
|
||||
# Only return overrides for configurable fields
|
||||
return {k: v for k, v in normalized.items() if k in self._configurable_fields}
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to load bank config for {bank_id}: {e}")
|
||||
|
||||
return {}
|
||||
|
||||
async def update_bank_config(
|
||||
self, bank_id: str, updates: dict[str, Any], context: RequestContext | None = None
|
||||
) -> None:
|
||||
"""
|
||||
Update bank configuration overrides (with permission checking).
|
||||
|
||||
Args:
|
||||
bank_id: Bank identifier
|
||||
updates: Dict of config field names to new values.
|
||||
Keys can be in env var format (HINDSIGHT_API_LLM_PROVIDER)
|
||||
or Python field format (llm_provider).
|
||||
Only configurable fields are allowed.
|
||||
context: Request context for permission checking
|
||||
|
||||
Raises:
|
||||
ValueError: If attempting to override invalid/disallowed fields
|
||||
"""
|
||||
# Normalize keys
|
||||
normalized_updates = normalize_config_dict(updates)
|
||||
|
||||
# SECURITY: Reject credential fields explicitly
|
||||
credential_attempts = set(normalized_updates.keys()) & self._credential_fields
|
||||
if credential_attempts:
|
||||
raise ValueError(
|
||||
f"Cannot set credential fields via API: {sorted(credential_attempts)}. "
|
||||
f"Credentials (API keys, base URLs) must be set at server level only."
|
||||
)
|
||||
|
||||
# Validate all fields are configurable
|
||||
invalid_fields = set(normalized_updates.keys()) - self._configurable_fields
|
||||
if invalid_fields:
|
||||
static_fields = HindsightConfig.get_static_fields()
|
||||
invalid_static = invalid_fields & static_fields
|
||||
if invalid_static:
|
||||
raise ValueError(
|
||||
f"Cannot override static (server-level) fields: {sorted(invalid_static)}. "
|
||||
f"Only configurable fields can be overridden per-bank. "
|
||||
f"Configurable fields include: {sorted(list(self._configurable_fields)[:10])}... "
|
||||
f"(total: {len(self._configurable_fields)} fields)"
|
||||
)
|
||||
else:
|
||||
raise ValueError(
|
||||
f"Unknown configuration fields: {sorted(invalid_fields)}. "
|
||||
f"Valid configurable fields: {sorted(list(self._configurable_fields)[:10])}..."
|
||||
)
|
||||
|
||||
# PERMISSIONS: Check tenant/bank permissions
|
||||
if self.tenant_extension and context:
|
||||
try:
|
||||
allowed_fields = await self.tenant_extension.get_allowed_config_fields(context, bank_id)
|
||||
if allowed_fields is not None: # None means "allow all"
|
||||
disallowed = set(normalized_updates.keys()) - allowed_fields
|
||||
if disallowed:
|
||||
raise ValueError(
|
||||
f"Not allowed to modify fields: {sorted(disallowed)}. "
|
||||
f"Your permissions allow: {sorted(list(allowed_fields)[:10])}..."
|
||||
if allowed_fields
|
||||
else "Not allowed to modify fields: {sorted(disallowed)}. "
|
||||
"Your permissions do not allow any config modifications."
|
||||
)
|
||||
except ValueError:
|
||||
raise # Re-raise permission errors
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to check permissions for bank {bank_id}: {e}")
|
||||
# Continue without permission check (fail open for backward compatibility)
|
||||
|
||||
# Validate retain_strategies: reject empty string keys
|
||||
if "retain_strategies" in normalized_updates and normalized_updates["retain_strategies"]:
|
||||
empty_keys = [k for k in normalized_updates["retain_strategies"] if not str(k).strip()]
|
||||
if empty_keys:
|
||||
raise ValueError(
|
||||
"Strategy names must not be empty strings. Remove entries with empty names before saving."
|
||||
)
|
||||
|
||||
# Merge with existing config (JSONB || operator)
|
||||
async with self.pool.acquire() as conn:
|
||||
await conn.execute(
|
||||
f"""
|
||||
UPDATE {fq_table("banks")}
|
||||
SET config = config || $1::jsonb,
|
||||
updated_at = now()
|
||||
WHERE bank_id = $2
|
||||
""",
|
||||
json.dumps(normalized_updates),
|
||||
bank_id,
|
||||
)
|
||||
|
||||
logger.info(f"Updated bank config for {bank_id}: {list(normalized_updates.keys())}")
|
||||
|
||||
async def reset_bank_config(self, bank_id: str) -> None:
|
||||
"""
|
||||
Reset bank configuration to defaults (remove all overrides).
|
||||
|
||||
Args:
|
||||
bank_id: Bank identifier
|
||||
"""
|
||||
async with self.pool.acquire() as conn:
|
||||
await conn.execute(
|
||||
f"""
|
||||
UPDATE {fq_table("banks")}
|
||||
SET config = '{{}}'::jsonb,
|
||||
updated_at = now()
|
||||
WHERE bank_id = $1
|
||||
""",
|
||||
bank_id,
|
||||
)
|
||||
|
||||
logger.info(f"Reset bank config for {bank_id} to defaults")
|
||||
|
||||
|
||||
def apply_strategy(config: HindsightConfig, strategy_name: str) -> HindsightConfig:
|
||||
"""
|
||||
Apply a named retain strategy's overrides on top of a resolved config.
|
||||
|
||||
A strategy is a named set of hierarchical field overrides stored in
|
||||
config.retain_strategies. Any field in _HIERARCHICAL_FIELDS can be
|
||||
overridden, including retain_extraction_mode, retain_chunk_size,
|
||||
entity_labels, entities_allow_free_form, etc.
|
||||
|
||||
Unknown strategy names log a warning and return config unchanged.
|
||||
Unknown or non-hierarchical fields in the strategy are silently ignored.
|
||||
"""
|
||||
strategies = config.retain_strategies or {}
|
||||
if strategy_name not in strategies:
|
||||
logger.warning(f"Unknown retain strategy '{strategy_name}', using resolved config as-is")
|
||||
return config
|
||||
|
||||
overrides = strategies[strategy_name]
|
||||
if not isinstance(overrides, dict):
|
||||
logger.warning(f"Retain strategy '{strategy_name}' is not a dict, skipping")
|
||||
return config
|
||||
|
||||
configurable = HindsightConfig.get_configurable_fields()
|
||||
filtered = {k: v for k, v in overrides.items() if k in configurable}
|
||||
|
||||
if not filtered:
|
||||
return config
|
||||
|
||||
logger.debug(f"Applying retain strategy '{strategy_name}': {list(filtered.keys())}")
|
||||
return replace(config, **filtered)
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user