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Able to detect the error but button is not visible need to check and integrate it with the ai
- Introduced `ai_config.py` for API key setup and configuration. - Added `jupyter-ai-demo.ipynb` to showcase Jupyter AI extension features, including chat commands, inline code completion, and magic commands.
- Added a new JSON file for supported models, replacing the previous TypeScript model configuration. - Updated the model selection component to utilize the new supported models configuration. - Removed the old model configuration file to streamline the codebase.
- Added logging for the creation of the OAuth token manager instance. - Implemented an asynchronous initialization function for the OAuth manager with error handling to log any failures during the process. - Scheduled the OAuth manager initialization task with appropriate logging for better traceability.
- Enhanced the initialization process with better error logging and handling. - Introduced a method to pre-configure supported models from a JSON file. - Updated session creation and refresh logic to include detailed logging for better traceability. - Replaced hardcoded token usage with a warning for development mode. - Improved token persistence and error handling during session management.
- Added logic to update existing keys in completions and embeddings fields with new settings. - Improved logging to reflect the number of models configured and existing keys updated. - Ensured that configuration updates are properly saved and logged for better traceability.
- Introduced HR_CONFIG for managing different environment settings. - Added asynchronous methods to retrieve Krakend host and Portkey configuration based on the environment. - Updated the initialization process to dynamically set configuration values for the OAuthTokenManager. - Removed hardcoded values in favor of dynamic configuration for improved flexibility.
…n is called correctly during initialization
- Removed dependency on external JSON file for supported models. - Introduced hardcoded model options with detailed descriptions for each model. - Updated provider ID to 'openai-chat-custom' for clarity.
- Replaced the development hardcoded token with a new hardcoded token for production use. - Ensured that the configuration for fields is always initialized in the model configuration process.
- Added `_auto_learn_on_startup` method to trigger auto-learning from the project root directory during extension initialization. - Updated embedding handling in `LearnChatHandler` to return both embeddings and metadata for proper FAISS indexing. - Introduced new configuration files for indices and metadata to support the updated learning process.
…ooks - Replaced MarkdownTextSplitter with MarkdownHeaderTextSplitter and added PythonCodeTextSplitter for improved handling of markdown and code cells. - Implemented a new splitting strategy that first divides markdown cells by headings and then by size, while ensuring code cells are split with respect to function/class boundaries. - Updated the split_text method to return stable pure text chunks from notebook cells.
- Introduced a new JSON configuration file to define model and embeddings provider settings for Jupyter AI. - Configured multiple OpenAI model options with API base URLs and headers. - Included fields for completions and embeddings to streamline integration with OpenAI services.
- Added multiple PNG images to the KT directory for visual representation in the documentation. - Created a new markdown file (KT.md) to provide a comprehensive overview of the project structure, integration, and key functionalities of the Jupyter AI extension. - Included detailed explanations of the frontend and backend architecture, network communication, LLM integration, and command handling for better understanding and contribution guidance.
…ling and functionality - Removed unused ChatMessageHeader imports and commented out code in ChatMessages and PendingMessages components. - Enhanced styling in ChatMessages to differentiate between human and agent messages with conditional formatting. - Adjusted padding in ScrollContainer of ChatBody for better layout. - Cleaned up state management in PendingMessages by commenting out unused timestamp logic.
- Introduced a new development configuration file (dev-config.json) to define model and embeddings provider settings specifically for development purposes. - Added a new constant for the development config path in config_manager.py to facilitate easy access to the development configuration. - Configured multiple OpenAI model options with API base URLs for streamlined integration during development.
- Added a new development configuration file (dev-config.json) to the .gitignore for better management of sensitive data. - Modified config_manager.py to set the configuration path based on the development environment using the is_dev() utility. - Adjusted extension.py to conditionally schedule OAuth manager initialization based on the development environment, enhancing flexibility during development.
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