Dev

[severian42]

Updates

This pull request introduces several significant updates and improvements to the GraphRAG-Local-UI project:

Major Changes

1. Local Model Support Enhancement: Improved compatibility with local models, particularly for embedding. Added a note that embedding providers using a /v1/embeddings endpoint work best currently.

2. Indexing Process Overhaul:

   • Significant updates to the indexing workflow to better handle various LLM and embedder configurations.
   • Improved error handling and logging for easier debugging of indexing issues.

3. Configuration Updates:

   • Added example configuration files and environment variable templates.
   • Updated settings.yaml and added settings-example.yaml for easier setup.

4. Input Processing:

   • Removed outdated input files.
   • Added a new sample document about tree frog adhesion biomimetics.

5. Output Structure Reorganization:

   • Implemented a new structure for output artifacts and reports.
   • Added new output folders with updated artifacts and logs.

6. Caching Mechanism:

   • Implemented caching for text embeddings and summarizations to improve performance.

7. UI and Visualization Improvements:

   • Enhanced graph visualization capabilities.
   • Updated the app.py file with new functionalities for the interactive UI.

Minor Changes

1. Updated README.md with more detailed information about the project status, installation process, and known issues.
2. Refined error messages and logging throughout the codebase.
3. Updated default configuration values in graphrag/config/defaults.py.

Bug Fixes

1. Addressed several issues in the indexing process, particularly related to empty nodes/data frames when unpacking.
2. Fixed encoding/UTF errors that were occurring on Windows systems.

Development Notes

• This update represents a major work in progress. Users should expect some instability and potential bugs, especially in the indexing process.
• The changes aim to make the application more robust with local LLMs, but further testing and refinement are needed.
• Feedback and bug reports from users are highly encouraged to help improve the system.

Next Steps

• Continue stabilizing the indexing process.
• Further optimize the workflow for various LLM and embedder configurations.
• Enhance documentation and user guides.
• Address any new issues that arise from these changes.