- Properly serialize Stream chunks to JSON format
- Convert ChatCompletionChunk objects using model_dump()
- Apply fix to both RequestHandler and AutoselectHandler streaming methods
- Resolves socket.send() exceptions during streaming

- Fixed AttributeError when stream=True is passed to OpenAI client
- Changed return type to Union[Dict, object] to support streaming
- Added conditional check to return Stream object for streaming requests
- Bumped version to 0.2.7

- Add successful_model variable to track which model actually worked
- Update successful_model when request succeeds in retry loop
- Log which model was successfully used
- Prevents KeyError when trying to access provider_id from selected_model
- Ensures proper model tracking across retry attempts

- Try up to 2 different models when a request fails or times out
- Track which models have been tried to avoid repeating failures
- Log each attempt with attempt number and model details
- Record failures and rate limit providers automatically
- Provide detailed error logging for each failed attempt
- Return comprehensive error message when all retries are exhausted
- Include last error in final error response for debugging

- Validate that all providers referenced in rotations exist in providers.json
- Log visible warnings with !!! CONFIGURATION WARNING !!! markers
- Show available providers when a referenced provider is missing
- Indicate that missing providers will be skipped during requests
- Provide guidance on how to fix the configuration issue
- Log successful validation with checkmarks for available providers

- Check if provider exists in configuration before creating handler
- Log error with available providers when provider is not found
- Skip providers that don't exist instead of crashing
- Prevents AttributeError when rotation references non-existent provider

- Add GET /api/autoselect endpoint to list all available autoselect configurations
- Add POST /api/autoselect/chat/completions endpoint for autoselect chat completions
- Model name in request now selects the specific autoselect configuration
- Add GET /api/autoselect/models endpoint to list all models across all autoselect configurations
- Maintain backward compatibility with existing /api/{provider_id} endpoints
- Follows same pattern as rotation endpoints for consistency

- Add GET /api/rotations endpoint to list all available rotations
- Add POST /api/rotations/chat/completions endpoint for rotation chat completions
- Model name in request now selects the specific rotation (coding, general, etc.)
- Add GET /api/rotations/models endpoint to list all models across all rotations
- Update root endpoint to show available rotations and autoselect options
- Maintain backward compatibility with existing /api/{provider_id} endpoints

Provider State Logging (providers.py):
- Add detailed logging when provider failures are recorded
- Show failure count and remaining failures before disable
- Log provider disable events with cooldown period details
- Log provider re-enable events after successful requests
- Track and display previous failure counts

Autoselect Model Selection Logging (handlers.py):
- Add detailed logging for autoselect model selection process
- Show available models and their descriptions
- Display user prompt information and length
- Log AI model selection request and response
- Show model validation and fallback logic
- Indicate whether selection was AI-selected or fallback
- Add logging for both streaming and non-streaming requests
- Display final model choice with selection method

- Add detailed logging for provider scanning process
- Show which providers are skipped and why (rate limited/deactivated)
- Display model details including weight, rate limit, and provider
- Add priority-based selection visualization
- Show sorted models by weight in descending order
- Indicate whether selection was random or deterministic
- Add clear section headers for different stages of selection
- Provide final selection summary with all relevant details

- Weight now acts as priority instead of frequency
- Higher weight models always take precedence over lower weight models
- Random selection only occurs when multiple models have the same highest weight
- Providers that are rate limited/deactivated are automatically skipped
- Ensures deterministic model selection based on priority

- Add connection health check before making requests
- Test Ollama availability with /api/tags endpoint
- Improve timeout configuration with separate connect/read/write/pool timeouts
- Add logging of available models from Ollama
- Provide clear error message if Ollama is not accessible

- Set timeout to 300 seconds (5 minutes) for total request
- Set connect timeout to 60 seconds
- This fixes httpx.ReadTimeout errors with Ollama cloud models
- Cloud models may take longer to respond than local instances

- Add explicit stream: False to Ollama requests
- Add robust JSON parsing to handle multiple JSON objects in response
- Add detailed logging of raw response content for debugging
- Parse multiple JSON objects line by line and use the last one
- This fixes JSONDecodeError when Ollama returns multiple chunks

- Add rate_limit field to ProviderConfig model with default value 0.0
- This fixes AttributeError when BaseProviderHandler tries to access rate_limit
- The providers.json file already contains rate_limit for all providers

- Add detailed debug logging throughout the codebase to track model and provider selection
- Fix OllamaProviderHandler to accept optional api_key parameter for cloud models
- Add logging in main.py, handlers.py, providers.py, and config.py
- Add catch-all endpoint for invalid routes with helpful error messages
- Create DEBUG_GUIDE.md with comprehensive documentation
- Enhance error messages to show available providers/rotations/autoselect

Debug logging now shows:
- Request path and provider ID
- Available configurations
- Provider config and handler selection
- Model selection process
- Rate limiting application
- Request/response details

This helps diagnose issues with model and provider selection.

- Move cli.py from aisbf/ to root directory to prevent package imports
- Update setup.py entry point from aisbf.cli:main to cli:main
- Update pyproject.toml to include cli.py as a py-module
- Update MANIFEST.in to include cli.py in distribution
- Update cli.py to look for aisbf.sh in /usr/local/share/aisbf/ or ~/.local/share/aisbf/
- Add KeyboardInterrupt handler for graceful Ctrl-C exit
- Update setup.py data_files to install aisbf.sh in correct directory

- Fixed aisbf script installation and syntax errors
- Added aisbf.sh to data_files for pip package distribution
- Updated _install_aisbf_script to copy from share directory

- Added aisbf.sh to data_files so it's included in pip package
- Updated _install_aisbf_script to copy from share directory instead of source
- This ensures aisbf.sh is available when installing from pip

- Modified setup.py to copy aisbf.sh instead of generating script
- Updated aisbf.sh to install aisbf package in venv
- Fixed double braces syntax error in bash script
- Added aisbf package to data_files for installation

- Added logging module with rotating file handlers to main.py
- Log files stored in /var/log/aisbf when launched by root
- Log files stored in ~/.local/var/log/aisbf when launched by user
- Automatic log directory creation if it doesn't exist
- Rotating file handlers with 50MB max file size and 5 backup files
- Separate log files for general logs (aisbf.log) and error logs (aisbf_error.log)
- stdout and stderr output duplicated to rotating log files
- Console logging for immediate feedback
- Updated aisbf.sh script to redirect output to log files
- Updated setup.py to include logging configuration in installed script
- Updated CHANGELOG.md with logging feature documentation

- Changed system installation path from /usr/local/share/aisbf to /usr/share/aisbf
- Updated aisbf.sh script to dynamically determine correct paths at runtime
- Script now checks for /usr/share/aisbf first, then falls back to ~/.local/share/aisbf
- Updated setup.py to install script with dynamic path detection
- Updated config.py to check for /usr/share/aisbf instead of /usr/local/share/aisbf
- Updated AI.PROMPT documentation to reflect new installation paths
- Script creates venv in appropriate location based on installation type
- Ensures proper main.py location is used regardless of who launches the script

- Add data_files to setup.py for installing main.py, requirements.txt, and JSON configs
- Update aisbf script to create venv in share directory if it doesn't exist
- Fix pyproject.toml warnings: add dynamic fields, update license format, remove deprecated classifier
- Update MANIFEST.in to include pyproject.toml
- Remove manual file copying from setup.py (now handled by data_files)
- Remove unused imports (shutil, subprocess)

- Add pyproject.toml for modern packaging configuration
- Add MANIFEST.in for package distribution manifest
- Add build.sh script for automated package building
- Add clean.sh script for cleaning build artifacts
- Add PYPI.md with comprehensive PyPI publishing guide
- Update setup.py to install main.py to share directory
- Update setup.py metadata (license, author email, repository URL)
- Update .gitignore to include PyPI build artifacts (*.tar.gz, *.whl)
- Update README.md with PyPI installation and build instructions
- Update DOCUMENTATION.md with PyPI packaging section
- Update AI.PROMPT with PyPI packaging changes
- All scripts include proper GPL license headers

The package is now ready for PyPI publication with custom install logic intact.

Remove useless endpoints and add kilocode ones

See merge request !1