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