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
- Introduce a new `Session` model to store information about each program run, including command line arguments and environment details.
- Implement a `Trajectory` model to log significant events and errors during execution, enhancing debugging and monitoring capabilities.
- Update various repository classes to support session and trajectory management, allowing for better tracking of user interactions and system behavior.
- Modify existing functions to record relevant events in the trajectory, ensuring comprehensive logging of application activities.
- Enhance error handling by logging errors to the trajectory, providing insights into failures and system performance.
feat(vsc): add initial setup for VS Code extension "ra-aid" with essential files and configurations
chore(vsc): create tasks.json for managing build and watch tasks in VS Code
chore(vsc): add .vscodeignore to exclude unnecessary files from the extension package
docs(vsc): create CHANGELOG.md to document changes and updates for the extension
docs(vsc): add README.md with instructions and information about the extension
feat(vsc): include esbuild.js for building and bundling the extension
chore(vsc): add eslint.config.mjs for TypeScript linting configuration
chore(vsc): create package.json with dependencies and scripts for the extension
feat(vsc): implement extension logic in src/extension.ts with webview support
test(vsc): add initial test suite in extension.test.ts for extension functionality
chore(vsc): create tsconfig.json for TypeScript compiler options
docs(vsc): add vsc-extension-quickstart.md for guidance on extension development
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
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(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
refactor(agent_utils.py): import run_research_agent and run_web_research_agent from their respective modules to streamline the code structure and enhance clarity
This commit introduces a new `Trajectory` model to the database, which tracks the sequence of actions taken by agents, including tool executions and their results. The addition of the `TrajectoryRepository` allows for storing and retrieving these trajectories, enabling better analysis of agent behavior and debugging of issues.
Additionally, the commit refactors existing code to utilize the new repository and model, improving the overall architecture and maintainability of the codebase. This change is essential for enhancing the capabilities of the agent system and providing a more robust framework for future development.
style(agent_utils.py): format imports and code for better readability
refactor(agent_utils.py): standardize model name and cost calculation logic for clarity and maintainability
chore(anthropic_callback_handler.py): create a new file for the AnthropicCallbackHandler implementation and related functions
style(agent_utils.py): format imports and code for better readability
refactor(agent_utils.py): standardize model name and cost calculation logic for clarity and maintainability
chore(anthropic_callback_handler.py): create a new file for the AnthropicCallbackHandler implementation and related functions
* chore: refactor code for improved readability and maintainability
- Standardize variable naming conventions for consistency.
- Improve logging messages for better clarity and debugging.
- Remove unnecessary imports and clean up code structure.
- Enhance error handling and logging in various modules.
- Update comments and docstrings for better understanding.
- Optimize imports and organize them logically.
- Ensure consistent formatting across files for better readability.
- Refactor functions to reduce complexity and improve performance.
- Add missing type hints and annotations for better code clarity.
- Improve test coverage and organization in test files.
style(tests): apply consistent formatting and spacing in test files for improved readability and maintainability
* chore(tests): remove redundant test for ensure_tables_created with no models to streamline test suite and reduce maintenance overhead
* fix(memory.py): update is_binary_file function to correctly identify binary files by returning True for non-text mime types
Ariel Frischer
AI Christianson