mcp-forge/docs/JUPYTER_IMPLEMENTATION_STATUS.md

265 lines
8.7 KiB
Markdown
Raw Normal View History

# Jupyter Backend Implementation Status
## Branch
`feature/real-jupyter-backend`
## Architecture Decision
**Decision**: 1:1 mapping - one container per session, one kernel per container
**Rationale**:
- Strongest isolation (processes, namespaces, resources)
- Easier debugging and resource tracking
- Clean lifecycle management
- Optional shared volumes for file exchange between sessions
**Components**:
- `jupyter-client`: Runs on host (MCP-Forge server)
- `ipykernel`: Runs in containers
- Communication: ZMQ protocol via Jupyter message protocol
## Implementation Progress
### ✅ Completed
1. **Core Architecture** ([kernel.py](../src/mcp_forge/execution/jupyter/kernel.py))
- Replaced mock exec() implementation with real Jupyter protocol
- `JupyterKernelManager` class with proper ZMQ communication
- `KernelInfo` dataclass with connection info and client
- Connection file generation
- Jupyter message protocol for code execution (execute_request, stream, execute_result)
2. **Kernel Lifecycle**
- `start_kernel()`: Container creation, kernel startup, client connection
- `shutdown_kernel()`: Graceful shutdown, container cleanup, connection file removal
- `restart_kernel()`: Stub implementation (needs KernelManager integration)
3. **Code Execution**
- `execute_code()`: Proper message protocol execution
- Output collection (stdout, stderr, result)
- Error handling with traceback capture
- Activity timestamp tracking
4. **Namespace Introspection**
- `inspect_namespace()`: List variables via introspection code
- `get_variable_info()`: Type, size, shape, repr extraction
5. **Resource Management**
- `cleanup_idle_kernels()`: Time-based cleanup
- Activity timestamp updates
6. **MCP Integration**
- `start_kernel()` accepts `injection_code` and `bridge_socket_path`
- Bridge socket mounted as volume in container (Unix domain socket)
- Injection code executed once on kernel startup (silent, no history)
- Error handling for injection failures
- Passed through SessionManager and JupyterBackend
7. **Network & Port Management**
- Host networking mode for ZMQ communication (`network_mode="host"`)
- Dynamic port allocation for 5 ZMQ channels (shell, iopub, stdin, control, hb)
- Port availability checking before allocation
- Port bindings tracked in ContainerConfig
- Connection file mounted into container at `/tmp/kernel-{id}.json`
8. **Kernel Readiness**
- `_wait_for_kernel_ready()`: Polls shell port until kernel responds
- Configurable timeout (default 30s) and poll interval (0.5s)
- Replaces simple sleep with proper port connectivity check
- Returns early when kernel is ready
9. **Error Handling**
- Tracks error messages from Jupyter kernel (msg_type='error')
- Returns `success=False` when errors occur
- Populates `error` field with traceback
- Sets appropriate exit codes
10. **Testing**
- Comprehensive mocking for ZMQ/Jupyter components
- Mocked BlockingKernelClient with message responses
- All 22 unit tests passing
- Tests cover: creation, execution, shutdown, namespace, cleanup
11. **Dependencies**
- `jupyter-client>=8.8.0` added to server dependencies
- `ipykernel` removed from server (will be in container image)
- `pyzmq>=27.1.0` for ZMQ support
7. **Documentation**
- [architecture1.md](../docs/architecture1.md) updated with Jupyter Backend section
- [todo.md](../docs/todo.md) Phase 2.2.1 updated with architecture details
- Architecture flow diagram and session mapping explanation
- [JUPYTER_IMPLEMENTATION_STATUS.md](../docs/JUPYTER_IMPLEMENTATION_STATUS.md) tracking document
### 🚧 In Progress / TODO
1. **Container Image**
- [ ] Add `ipykernel` to `mcp-forge/jupyter:latest` image
- [ ] Configure kernel to accept ZMQ connections
- [ ] Test kernel startup in isolation
2. **Restart Implementation**
- [ ] Use `KernelManager` instead of just `BlockingKernelClient`
- [ ] Proper restart via `KernelManager.restart_kernel()`
- [ ] Handle restart failures gracefully
3. **Error Handling Improvements**
- [ ] Port conflict resolution
- [ ] Kernel crash detection and recovery
- [ ] Connection timeout handling
- [ ] Invalid connection file handling
4. **Performance**
- [ ] Connection pooling/reuse consideration
- [ ] Batch message processing
- [ ] Async execution option
## Test Status
Current test results: **22 passed, 0 failed**
**All unit tests passing!**
Tests properly mock:
- ZMQ connection and port allocation
- Jupyter message protocol
- BlockingKernelClient operations
- Container manager operations
- File system operations
**Test Coverage**:
- ✅ Kernel creation and startup
- ✅ Code execution and results
- ✅ Namespace persistence
- ✅ Kernel shutdown and cleanup
- ✅ Error handling paths
- ✅ Multiple kernel isolation
- ✅ Idle kernel cleanup
- ✅ Variable introspection
**Required Actions for Integration Testing**:
1. Build container image with ipykernel
2. Test with real Podman containers
3. Verify actual ZMQ communication
4. Test with real code execution
## Known Issues
1. **Port Assignment**: Currently using `port: 0` (let ZMQ assign), but need to:
- Get assigned ports after socket binding
- Map container ports to host ports
- Update connection info with actual ports
2. **Connection File**: Generated on host, but needs to be:
- Mounted into container at known path
- Have correct host-accessible addresses
3. **Network Mode**: Need to determine:
- Host network mode (simpler, less isolated)
- Bridge network with port mapping (more isolated, more complex)
4. **Restart Logic**: `restart_kernel()` only updates timestamp:
- Need KernelManager integration
- Or implement shutdown + start approach
## Next Steps
1. **Immediate** (Core functionality):
```
1. Update container image with ipykernel
2. Test kernel startup with real container
3. Mock tests for unit testing
```
2. **Short-term** (Stability):
```
4. Implement proper kernel restart
5. Error handling improvements
6. Port conflict handling
```
3. **Medium-term** (Production-ready):
```
7. Implement restart via KernelManager
8. Integration test suite
9. Error handling improvements
10. Performance testing
```
## Architecture Diagrams
### Communication Flow
```
┌─────────────────────┐
│ MCP-Forge Server │
│ (Host Process) │
│ │
│ ┌─────────────────┐ │
│ │ jupyter-client │ │
│ │ │ │
│ │ BlockingKernel │ │
│ │ Client │ │
│ └────────┬────────┘ │
│ │ │
│ │ ZMQ │
│ │ (shell, │
│ │ iopub, │
│ │ stdin, │
│ │ control,│
│ │ hb) │
└──────────┼──────────┘
│ TCP ports
│ (mapped)
┌──────────┼──────────┐
│ Container│ │
│ ▼ │
│ ┌─────────────────┐ │
│ │ ipykernel │ │
│ │ │ │
│ │ Python REPL │ │
│ │ + ZMQ Server │ │
│ └─────────────────┘ │
│ │
│ Connection file: │
│ /tmp/kernel-X.json │
└─────────────────────┘
```
### Session-to-Kernel Mapping
```
Session A ──> Container A ──> Kernel A ──> Namespace A
Session B ──> Container B ──> Kernel B ──> Namespace B
Session C ──> Container C ──> Kernel C ──> Namespace C
Optional: Shared volume for file exchange
Container A ──┐
├──> /shared/session-group-1
Container B ──┘
Container C ──> /shared/session-group-2 (independent)
```
## References
- [Jupyter Client Documentation](https://jupyter-client.readthedocs.io/)
- [Jupyter Message Protocol](https://jupyter-client.readthedocs.io/en/stable/messaging.html)
- [ZMQ Guide](https://zeromq.org/socket-api/)
- [IPykernel Documentation](https://ipykernel.readthedocs.io/)
## Commit History
- `244a3e5` - Implement real Jupyter backend with jupyter-client
- Replaced mock exec() with real Jupyter protocol
- Added ZMQ communication
- Kernel lifecycle management
- Backed up old implementation
## Old Implementation
The previous mock implementation using `exec()` is preserved in:
- `src/mcp_forge/execution/jupyter/kernel_old.py`
This can be used for reference or comparison.