- Add Key Features section to README.md
- Describe Rotation Models with weighted load balancing and automatic failover
- Describe Autoselect Models with AI-powered content analysis
- Update Rotation Endpoints with detailed model descriptions
- Update Autoselect Endpoints with detailed model descriptions
- Add comprehensive Rotation Models section to DOCUMENTATION.md
- Add comprehensive Autoselect Models section to DOCUMENTATION.md
- Include example use cases for both rotation and autoselect models
- Update overview with key features and capabilities
- Document fallback behavior to 'general' when autoselect can't choose a model

- Update version to 0.3.0 in setup.py, pyproject.toml, and aisbf/__init__.py

- Update host from 0.0.0.0 to 127.0.0.1 for localhost-only access
- Update port from 8000 to 17765
- Update log message to reflect new address

- Add prominent ABSOLUTELY CRITICAL section emphasizing ONLY output requirement
- Explicitly state NO additional text, explanations, or commentary
- Add repeated warnings about outputting nothing except the single tag
- Clarify that any extra text will cause system failure
- Add examples of what NOT to include in response

- 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.