* - Add support for documentation content exceeding token limits via two phase operation:
1. Ask LLM to rank headings which are most likely to contain an answer to a user question
2. Provide the corresponding files for the LLM to search for an answer.
- Refactor of help_docs to make the code more readable
- For the purpose of getting canonical path: git providers to use default branch and not the PR's source branch.
- Refactor of token counting and making it clear on when an estimate factor will be used.
* Code review changes:
1. Correctly handle exception during retry_with_fallback_models (to allow fallback model to run in case of failure)
2. Better naming for default_branch in bitbucket cloud provider
1. Code Formatting:
- Standardized Python code formatting across multiple files to align with PEP 8 guidelines. This includes adjustments to whitespace, line breaks, and inline comments.
2. Configuration Loader Enhancements:
- Enhanced the `get_settings` function in `config_loader.py` to provide more robust handling of settings retrieval. Added detailed documentation to improve code maintainability and clarity.
3. Model Addition in __init__.py:
- Added a new model "ollama/llama3" with a token limit to the MAX_TOKENS dictionary in `__init__.py` to support new AI capabilities and configurations.
Add ignore.toml, configuration for ignoring files
Add file_filter.py, for matching files against glob/regex patterns
Update relevant code to use file filter
+Tests
