feat(anthropic_token_limiter.py): add get_model_name_from_chat_model function to extract model name from BaseChatModel instances
style(anthropic_token_limiter.py): format code for better readability and consistency in function definitions and logging messages
fix(anthropic_token_limiter): refactor get_model_token_limit to use the new get_provider_and_model_for_agent_type function for cleaner code
test(anthropic_token_limiter): add unit tests for get_provider_and_model_for_agent_type and adjust_claude_37_token_limit functions to ensure correctness and coverage
feat(agent_utils.py): add model detection utilities for Claude 3.7 models
fix(agent_utils.py): update get_model_token_limit to handle Claude 3.7 token limits correctly
test(model_detection.py): add unit tests for model detection utilities
chore(agent_utils.py): remove deprecated is_anthropic_claude function and related tests
style(agent_utils.py): format code for better readability and consistency
chore(anthropic_message_utils.py): remove debug print statements to clean up code and improve readability
chore(anthropic_token_limiter.py): remove debug print statements and replace with logging for better monitoring
test(test_anthropic_token_limiter.py): update tests to verify correct behavior of sonnet_35_state_modifier without patching internal logic
chore(anthropic_token_limiter.py): remove import of fix_anthropic_message_content as it is no longer needed
test: add unit tests for has_tool_use and is_tool_pair functions to ensure correct functionality
test: enhance test coverage for anthropic_trim_messages with tool use scenarios to validate message handling
fix(agent_utils.py): remove debug print statement for max_input_tokens to clean up code
refactor(anthropic_token_limiter.py): update state_modifier to use anthropic_trim_messages for better token management and maintain message structure
feat(anthropic_token_limiter.py): add convert_message_to_litellm_format function to standardize message format for litellm
fix(anthropic_token_limiter.py): update wrapped_token_counter to handle only BaseMessage objects and improve token counting logic
chore(anthropic_token_limiter.py): add debug print statements to track token counts before and after trimming messages
feat(main.py): add DEFAULT_MODEL constant to centralize model configuration
feat(main.py): enhance logging and error handling for better debugging
feat(main.py): implement state_modifier for managing token limits in agent state
feat(anthropic_token_limiter.py): create utilities for handling token limits with Anthropic models
feat(output.py): add print_messages_compact function for debugging message output
test(anthropic_token_limiter.py): add unit tests for token limit utilities and state management
Ariel Frischer