Adds support for Ollama embedding, enabling the use of Ollama as an embedding model for RAG.
This allows users to leverage Ollama's advanced embedding capabilities for better document understanding and retrieval.
Refactor embedding models and their handling to improve performance and simplify the process.
Add a new model selection mechanism, and enhance the UI for model selection, offering clearer and more user-friendly options for embedding models.
Refactor embeddings to use a common model for page assist and RAG, further improving performance and streamlining the workflow.
Adds support for LMStudio models, allowing users to access and use them within the application. This involves:
- Adding new functions to `db/models.ts` to handle LMStudio model IDs and fetch their information from the OpenAI API.
- Modifying the `ollamaFormatAllCustomModels` function to include LMStudio models in the list of available models.
- Introducing a timeout mechanism in `libs/openai.ts` to prevent API requests from hanging.
This change enhances the model selection experience, providing users with a wider range of models to choose from.
Removed a debugging `console.log` statement that was printing the `isCustom` variable and the model name. This statement was no longer necessary and was potentially causing issues.
The previous code used an empty string for the `apiKey` when no key was provided, which could lead to unexpected behavior. This commit replaces those with a temporary placeholder ("temp") to avoid potential errors and make the code more robust.
Adds support for OpenAI models, allowing users to leverage various OpenAI models directly from the application. This includes custom OpenAI models and OpenAI-specific configurations for seamless integration.
