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-`src/kernels/types.ts` - Added DeepnoteKernelConnectionMetadata to union types
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-`src/notebooks/serviceRegistry.node.ts` - Registered new services
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## Dependencies
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-`get-port`: For finding available ports
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- Existing VSCode notebook infrastructure
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- Existing kernel controller system
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- Python interpreter service
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- Jupyter server provider registry
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- JupyterLab session management
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## Technical Details
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### Server Provider Architecture
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The implementation uses VSCode's Jupyter server provider API to properly integrate Deepnote servers:
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1.**DeepnoteServerProvider** implements the `JupyterServerProvider` interface
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2. It registers with the `IJupyterServerProviderRegistry` during activation
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3. When a Deepnote server is started, it's registered with the provider using a unique handle
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4. The kernel infrastructure can then resolve the server connection through this provider
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5. This allows the kernel session factory to properly connect to the Deepnote server
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### Kernel Spec Resolution
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Instead of creating custom kernel specs, the implementation:
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1. Connects to the running Deepnote server using `JupyterLabHelper`
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2. Queries the server for available kernel specs via `getKernelSpecs()`
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3. Selects the first Python kernel spec (or falls back to `python3-venv`)
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4. Uses this existing spec when creating the kernel connection metadata
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5. This ensures compatibility with the Deepnote server's kernel configuration
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## Troubleshooting & Key Fixes
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### Issue 1: "Unable to get resolved server information"
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**Problem**: The kernel infrastructure couldn't resolve the server connection because the `serverProviderHandle` pointed to a non-existent server provider.
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**Solution**: Created `DeepnoteServerProvider` that implements the `JupyterServerProvider` interface and registered it with the `IJupyterServerProviderRegistry`. This allows the kernel session factory to properly resolve server connections.
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### Issue 2: "No such kernel named python31211jvsc74a57bd0..."
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**Problem**: The extension was creating a custom kernel spec name based on the interpreter hash, but this kernel spec didn't exist on the Deepnote server.
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**Solution**: Instead of creating a custom kernel spec, the implementation now:
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- Queries the Deepnote server for available kernel specs
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- Selects an existing Python kernel (typically `python3-venv`)
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- Uses this server-native kernel spec for the connection
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These changes ensure that Deepnote notebooks can execute cells properly by:
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1. Providing a valid server provider that can be resolved
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2. Using kernel specs that actually exist on the Deepnote server
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