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https://github.com/markusbegerow/local-llm-chat-vscode-openmetadata

Chat with OpenMetadata using local LLMs (OpenAI, Ollama, or custom endpoints)
https://github.com/markusbegerow/local-llm-chat-vscode-openmetadata

ai chat code-assistant llm ollama openmetadata vscode vscode-extension

Last synced: 22 days ago
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Chat with OpenMetadata using local LLMs (OpenAI, Ollama, or custom endpoints)

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README 

          
# Local LLM for OpenMetadata



A VS Code extension that brings AI-powered data discovery to your IDE using **your choice** of LLM provider. Chat with your OpenMetadata catalog using OpenAI, Ollama, or any custom endpoint.



vs-code-openmetadata



## Key Features



- **Multiple LLM Providers**: Choose between OpenAI, Ollama, or custom OpenAI-compatible endpoints

- **Complete Privacy**: Use local models with Ollama for offline, private data analysis

- **Flexible Configuration**: Switch between providers without code changes

- **Natural Language Search**: Ask questions like "show me customer tables" or search by keywords

- **AI-Powered Insights**: Get intelligent analysis of your datasets and data quality

- **Interactive Data Lineage**: Visualize upstream and downstream table relationships

- **Column Details**: Explore table schemas with expandable column information



## Requirements



1. **OpenMetadata Server**: Running locally at http://localhost:8585

   - Use the [OpenMetadata Docker setup](https://docs.open-metadata.org/latest/quick-start/local-docker-deployment)

   - Load sample data for testing



2. **LLM Provider** (choose one):

   - **OpenAI**: Get an API key from [platform.openai.com](https://platform.openai.com/api-keys)

   - **Ollama**: Install [Ollama](https://ollama.ai/) and pull a model (e.g., `ollama pull llama2`)

   - **Custom**: Any OpenAI-compatible API endpoint



## Installation & Setup



### Option 1: Build from Source



**1. Clone and Install**

```bash

cd /path/to/your/workspace

git clone  local-llm-chat-vscode-openmetadata

cd local-llm-chat-vscode-openmetadata

npm install

```



**2. Configure Your LLM Provider**



Open VS Code settings (`Ctrl+,` or `Cmd+,`) and configure your preferred provider:



#### For OpenAI:

```json

{

  "openmetadataExplorer.llm.provider": "openai",

  "openmetadataExplorer.llm.openai.apiKey": "sk-your-api-key-here",

  "openmetadataExplorer.llm.openai.model": "gpt-4o",

  "openmetadataExplorer.openmetadataUrl": "http://localhost:8585",

  "openmetadataExplorer.openmetadataAuthToken": "YOUR_BOT_TOKEN"

}

```



#### For Ollama:

```json

{

  "openmetadataExplorer.llm.provider": "ollama",

  "openmetadataExplorer.llm.ollama.endpoint": "http://localhost:11434",

  "openmetadataExplorer.llm.ollama.model": "llama2",

  "openmetadataExplorer.openmetadataUrl": "http://localhost:8585",

  "openmetadataExplorer.openmetadataAuthToken": "YOUR_BOT_TOKEN"

}

```



#### For Custom Endpoint (e.g., LM Studio, LocalAI):

```json

{

  "openmetadataExplorer.llm.provider": "custom",

  "openmetadataExplorer.llm.custom.endpoint": "http://localhost:1234/v1",

  "openmetadataExplorer.llm.custom.apiKey": "optional-api-key",

  "openmetadataExplorer.llm.custom.model": "model-name",

  "openmetadataExplorer.openmetadataUrl": "http://localhost:8585",

  "openmetadataExplorer.openmetadataAuthToken": "YOUR_BOT_TOKEN"

}

```



**3. Get OpenMetadata Bot Token**

1. Open http://localhost:8585 and login (default: admin/admin)

2. Go to **Settings** → **Bots**

3. Click **Add Bot** with these details:

   - Name: `vscode-llm-bot`

   - Description: `Bot for VS Code LLM extension`

4. Click **Generate Token** and copy the JWT token (starts with `eyJ`)

5. Assign **Data Consumer** role to the bot



**4. Run in Debug Mode**

1. Press `F5` to launch the extension in a new VS Code window

2. Look for **OPEN METADATA** panel at the bottom

3. Verify connection and start searching



### Option 2: Package and Install



**1. Build the Extension**

```bash

npm run compile

npm run package

```



**2. Install the VSIX**

- Open Command Palette (`Ctrl+Shift+P` or `Cmd+Shift+P`)

- Type: `Extensions: Install from VSIX...`

- Select the generated `.vsix` file

- Reload when prompted



**3. Configure as shown in Option 1, step 2**



## How to Use



### Search Your Data

- **Keyword Search**: Type table names like "customer" or "orders"

- **Natural Language**: Ask questions like "show me customer data"

- **Browse Results**: Click on tables to see column details and AI insights



### View Data Lineage

1. Search for any table

2. Click **View Lineage** on the table card

3. Use the interactive graph:

   - Click **+** buttons to expand upstream/downstream relationships

   - Click **-** buttons to collapse connections

   - Drag nodes to reposition them

   - Zoom with mouse wheel



### Example Searches

- `customer` - Find customer-related tables

- `orders` - Discover transaction data

- `sales` - Locate revenue tables

- `product` - Find catalog information



## LLM Provider Comparison



| Feature | OpenAI | Ollama | Custom |

|---------|---------|---------|---------|

| **Speed** | Fast (cloud) | Medium-Fast (local) | Varies |

| **Privacy** | Cloud-based | 100% Local | Depends |

| **Cost** | Pay-per-use | Free | Varies |

| **Setup** | API key only | Install + model | Varies |

| **Offline** | ❌ No | ✅ Yes | Depends |

| **Quality** | Excellent | Good | Varies |



### Recommended Models



**OpenAI:**

- `gpt-4o` - Best quality, faster than GPT-4

- `gpt-4` - High quality, slower

- `gpt-3.5-turbo` - Fast and cheap

- `o1-preview` - Advanced reasoning

- `o1-mini` - Cost-effective reasoning



**Ollama:**

- `llama2` - General purpose, 7B parameters

- `mistral` - Fast and capable

- `codellama` - Optimized for code/data

- `llama3` - Latest Llama model



**Custom:**

- Any OpenAI-compatible API endpoint works

- Examples: LM Studio, LocalAI, vLLM, Text Generation WebUI



## Development



### Build Commands

```bash

# Development build with watch

npm run watch



# Production build

npm run compile



# Package for distribution

npm run package

```



### Project Structure

```

src/

├── extension.ts                 # Extension entry point

├── OpenMetadataExplorerProvider.ts  # Main provider

├── services/

│   ├── OpenAIService.ts        # OpenAI integration

│   ├── LocalLLMService.ts      # Ollama/Custom integration

│   ├── UnifiedLLMService.ts    # LLM orchestrator

│   ├── OpenMetadataService.ts  # OpenMetadata API

│   └── LineageService.ts       # Data lineage

└── webview/

    ├── App.tsx                  # Main React app

    └── components/              # React components

```



### Key Service Files



**UnifiedLLMService.ts**

- Orchestrates between OpenAI, Ollama, and custom endpoints

- Handles provider selection and initialization

- Provides unified interface for all LLM operations



**OpenAIService.ts**

- Direct integration with OpenAI API

- Supports chat completions format

- Handles API key validation



**LocalLLMService.ts**

- OpenAI-compatible format for Ollama

- Fallback to legacy formats for compatibility

- Flexible response parsing



## Configuration Reference



### OpenMetadata Settings



| Setting | Description | Default |

|---------|-------------|---------|

| `openmetadataExplorer.openmetadataUrl` | OpenMetadata server URL | `http://localhost:8585` |

| `openmetadataExplorer.openmetadataAuthToken` | OpenMetadata bot JWT token | (empty) |



### LLM Provider Settings



| Setting | Description | Default |

|---------|-------------|---------|

| `openmetadataExplorer.llm.provider` | LLM provider (openai/ollama/custom) | `openai` |



### OpenAI Settings



| Setting | Description | Default |

|---------|-------------|---------|

| `openmetadataExplorer.llm.openai.apiKey` | OpenAI API key | (empty) |

| `openmetadataExplorer.llm.openai.model` | OpenAI model name | `gpt-4o` |

| `openmetadataExplorer.llm.openai.baseUrl` | OpenAI API base URL | `https://api.openai.com/v1` |



### Ollama Settings



| Setting | Description | Default |

|---------|-------------|---------|

| `openmetadataExplorer.llm.ollama.endpoint` | Ollama API endpoint | `http://localhost:11434` |

| `openmetadataExplorer.llm.ollama.model` | Ollama model name | `llama2` |



### Custom Endpoint Settings



| Setting | Description | Default |

|---------|-------------|---------|

| `openmetadataExplorer.llm.custom.endpoint` | Custom API endpoint | (empty) |

| `openmetadataExplorer.llm.custom.apiKey` | Custom API key (if required) | (empty) |

| `openmetadataExplorer.llm.custom.model` | Custom model name | (empty) |



## Troubleshooting



### OpenAI Issues

- **"API key invalid"**: Check your API key at platform.openai.com

- **"Rate limit exceeded"**: Wait a moment or upgrade your OpenAI plan

- **"Model not found"**: Verify the model name (gpt-4o, gpt-4, etc.)



### Ollama Issues

- **"Connection refused"**: Make sure Ollama is running (`ollama serve`)

- **"Model not found"**: Pull the model first (`ollama pull llama2`)

- **Slow responses**: Use a smaller model or upgrade your hardware



### OpenMetadata Issues

- **"Connection failed"**: Verify OpenMetadata is running at the configured URL

- **"Authentication failed"**: Check your bot token is valid and not expired

- **"No tables found"**: Ensure sample data is loaded in OpenMetadata



## Current Status



**Version 1.0.0** - Initial Release

- OpenAI, Ollama, and custom endpoint support

- Natural language search with AI insights

- Interactive data lineage visualization

- Professional UI optimized for developers



**Planned Features**

- Column-level lineage relationships

- Data quality monitoring integration

- Advanced search filters and exports

- Streaming responses for better UX

- Multi-turn conversations



## Contributing



Contributions are welcome! Please feel free to submit a Pull Request.



1. Fork the repository

2. Create your feature branch (`git checkout -b feature/amazing-feature`)

3. Commit your changes (`git commit -m 'Add amazing feature'`)

4. Push to the branch (`git push origin feature/amazing-feature`)

5. Open a Pull Request



## License



This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.



## Acknowledgments



- Thanks to the Ollama team for making local LLMs accessible

- LM Studio for providing an excellent local inference platform

- The VS Code extension API team for comprehensive documentation



## 🙋‍♂️ Get Involved



If you encounter any issues or have questions:

- 🐛 [Report bugs](https://github.com/markusbegerow/local-llm-chat-vscode-openmetadata/issues)

- 💡 [Request features](https://github.com/markusbegerow/local-llm-chat-vscode-openmetadata/issues)

- ⭐ Star the repo if you find it useful!



## ☕ Support the Project



If you like this project, support further development with a repost or coffee:



  



[![Buy Me a Coffee](https://img.shields.io/badge/☕-Buy%20me%20a%20coffee-yellow)](https://paypal.me/MarkusBegerow?country.x=DE&locale.x=de_DE)



## 📬 Contact



- 🧑‍💻 [Markus Begerow](https://linkedin.com/in/markusbegerow)

- 💾 [GitHub](https://github.com/markusbegerow)

- ✉️ [Twitter](https://x.com/markusbegerow)



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**Privacy Notice**: This extension operates entirely locally. No data is sent to external servers unless you explicitly configure it to use a remote API endpoint.