56694a6dea
* conductor-checkpoint-start * conductor-checkpoint-msg_01VhH9TifDw4FVprrPE6tss4 * conductor-checkpoint-msg_018cUkkzZNp3RFrut99UPoAJ * conductor-checkpoint-msg_01S8GCTw5bowCWq4G2jATJ5s * conductor-checkpoint-msg_01NoAtvCjfekKvenbTgGZtzt * Fix critical issues in server container release workflow Address all issues identified by code review: 1. **Dockerfile now installs from PyPI** - Changed from building local source to installing graphiti-core from PyPI, ensuring container matches published package 2. **Fixed version extraction** - Handle workflow_run context where tags aren't available, with pyproject.toml fallback 3. **Added BUILD_DATE and VCS_REF** - Pass all required build arguments to populate OCI labels 4. **Improved pre-release detection** - Enhanced regex to catch all Python patterns (a1, b2, dev0, etc.) 5. **Fixed checkout configuration** - Added fetch-depth: 0 and proper ref for workflow_run trigger The container now truly uses the PyPI package, making the PyPI availability check meaningful. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * conductor-checkpoint-msg_01AuTTSKLm6XPqV4C5C2GL28 * Fix dependency installation order and optimize FalkorDB install Address additional review concerns: 1. **Fix dependency installation order** - Install server deps first with uv sync, then upgrade graphiti-core to desired PyPI version using --upgrade flag. This prevents stale uv.lock (pinned to 0.13.2) from downgrading our target version. 2. **Optimize FalkorDB installation** - Combine graphiti-core installation with FalkorDB extra in single command, avoiding redundant package reinstall. 3. **Add --upgrade flag** - Ensures the specific PyPI version takes precedence over lockfile version. The installation sequence is now: - uv sync (server deps + graphiti-core 0.13.2 from lock) - uv pip install --upgrade graphiti-core==TARGET_VERSION (upgrades to desired version) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> --------- Co-authored-by: Claude <noreply@anthropic.com>
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2.4 KiB
Markdown
78 lines
No EOL
2.4 KiB
Markdown
# graph-service
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Graph service is a fast api server implementing the [graphiti](https://github.com/getzep/graphiti) package.
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## Container Releases
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The FastAPI server container is automatically built and published to Docker Hub when a new `graphiti-core` version is released to PyPI.
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**Image:** `zepai/graphiti`
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**Available tags:**
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- `latest` - Latest stable release
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- `0.22.1` - Specific version (matches graphiti-core version)
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**Platforms:** linux/amd64, linux/arm64
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The automated release workflow:
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1. Triggers when `graphiti-core` PyPI release completes
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2. Waits for PyPI package availability
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3. Builds multi-platform Docker image
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4. Tags with version number and `latest`
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5. Pushes to Docker Hub
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Only stable releases are built automatically (pre-release versions are skipped).
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## Running Instructions
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1. Ensure you have Docker and Docker Compose installed on your system.
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2. Add `zepai/graphiti:latest` to your service setup
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3. Make sure to pass the following environment variables to the service
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```
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OPENAI_API_KEY=your_openai_api_key
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NEO4J_USER=your_neo4j_user
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NEO4J_PASSWORD=your_neo4j_password
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NEO4J_PORT=your_neo4j_port
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```
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4. This service depends on having access to a neo4j instance, you may wish to add a neo4j image to your service setup as well. Or you may wish to use neo4j cloud or a desktop version if running this locally.
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An example of docker compose setup may look like this:
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```yml
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version: '3.8'
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services:
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graph:
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image: zepai/graphiti:latest
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ports:
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- "8000:8000"
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environment:
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- OPENAI_API_KEY=${OPENAI_API_KEY}
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- NEO4J_URI=bolt://neo4j:${NEO4J_PORT}
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- NEO4J_USER=${NEO4J_USER}
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- NEO4J_PASSWORD=${NEO4J_PASSWORD}
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neo4j:
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image: neo4j:5.22.0
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ports:
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- "7474:7474" # HTTP
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- "${NEO4J_PORT}:${NEO4J_PORT}" # Bolt
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volumes:
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- neo4j_data:/data
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environment:
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- NEO4J_AUTH=${NEO4J_USER}/${NEO4J_PASSWORD}
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volumes:
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neo4j_data:
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```
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5. Once you start the service, it will be available at `http://localhost:8000` (or the port you have specified in the docker compose file).
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6. You may access the swagger docs at `http://localhost:8000/docs`. You may also access redocs at `http://localhost:8000/redoc`.
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7. You may also access the neo4j browser at `http://localhost:7474` (the port depends on the neo4j instance you are using). |