Setting
Guide to Setting AI
1. Enable AI
1. Enable AI
- Locate the “Use AI” toggle in the settings.
- Switch it to the enabled state (purple).
2. Select the Model Provider
2. Select the Model Provider
- Choose the AI model provider from the “Model Provider” dropdown menu:
- If using OpenAI, ensure “OpenAI” is selected.
- If using Ollama, ensure “Ollama” is selected.
3. Select the AI Model
3. Select the AI Model
- Choose a suitable model for your task from the “AI Model” dropdown.
4. Set the Embedding Model
4. Set the Embedding Model
- Select the embedding model from the “Embedding Model” dropdown.
5. Input the API Key
5. Input the API Key
- Enter your OpenAI API key in the “API Key” input field:
- Ensure that your key is correct and has the necessary permissions.
6. Set the API Endpoint
6. Set the API Endpoint
- Configure the API endpoint in the “API Endpoint” input field:
- Ensure the address is valid and matches your API configuration.
7. Rebuild the Embedding Index
7. Rebuild the Embedding Index
- If you need to rebuild the embedding index:
- Click the “Rebuild” button to regenerate the embeddings.
- If a forced rebuild is required, click “Force Rebuild.”
Ensure the correctness of the API key and endpoint to avoid functionality issues.
By following the steps above, you can configure and start using the AI features.
Advanced
Parameters Explained
Top K
Top K
- Determines the number of most relevant chunks to consider
- Range: 1-20 (recommended: 2-5)
- Higher values include more context but may reduce relevance
Score
Score
- Minimum similarity score threshold for context inclusion
- Range: 0.0-2.0 (recommended: 0.7-0.9)
- Higher values ensure more relevant matches
- Lower values include more potential matches
Embedding Lambda
Embedding Lambda
- Controls the balance between semantic and lexical similarity
- Range: 0.0-1.0 (recommended: 0.2-0.4)
- Higher values favor semantic meaning
- Lower values favor exact word matches
Best Practices
For optimal results:
- Start with default values (Top K: 2, Score: 0.8, Lambda: 0.3)
- Adjust gradually based on response quality
- Monitor response relevance and accuracy
Extreme parameter values may lead to:
- Very limited or irrelevant responses
- Increased processing time
- Reduced accuracy