This commit replaces the print statement with a logger.info call in the initialize_services function, enhancing the logging practices for better error tracking and consistency across the codebase. This change aligns with the project's focus on robust async coding and well-documented code.
This commit streamlines the LangflowFileService by removing direct HTTP client usage in favor of a centralized API client for handling requests. It enhances the upload and delete file methods to improve code organization and maintainability. Additionally, it updates logging practices for better error visibility, ensuring adherence to robust async coding standards and documentation practices.
This commit updates the settings for LANGFLOW_INGEST_FLOW_ID to remove reliance on a deprecated environment variable. It introduces a new Langflow HTTP client for making API requests and adds a centralized method for handling Langflow API requests, improving code organization and maintainability. The changes enhance the robustness of the async code while ensuring proper documentation practices are followed.
This commit simplifies the state update logic in the KnowledgeSourcesPage component by using conditional chaining to set various settings from the backend response. It removes the unnecessary settingsLoaded state, streamlining the code for better readability and maintainability while adhering to robust coding practices.
This commit refactors the KnowledgeSourcesPage component to include a new ingestion settings section, allowing users to configure document processing parameters such as chunk size and overlap. It also improves the connector management interface by integrating async fetching of connector statuses and enhancing error handling. The changes aim to provide a more robust and user-friendly experience while maintaining well-documented code practices.
This commit replaces the print statement for error traceback with a structured logging approach using the logger. This change enhances error visibility and aligns with best practices for robust and well-documented async code.
This commit adds functionality to retrieve and set ingestion-specific defaults from the Langflow API based on the flow configuration. It includes error handling for the API call and updates the settings with values for chunk size, chunk overlap, separator, and embedding model based on the flow data. This enhancement improves the flexibility and robustness of the ingestion process.
This commit introduces a new JSON configuration file for the OpenSearch ingestion flow, detailing the data processing pipeline. The flow includes components for splitting text, generating embeddings, and ingesting data into OpenSearch, enhancing the capabilities for Retrieval Augmented Generation (RAG) tasks. The configuration is designed to support various input types and provides detailed metadata for each component, ensuring robust and well-documented integration.
🚀 (frontend): Implement support for process.env.PORT to run app on a configurable port
🔧 (frontend): Change port variable case from lowercase 'port' to uppercase 'PORT' for better semantics
📝 (frontend): Add comments to clarify the purpose of loading conversation data only when user explicitly selects a conversation
📝 (frontend): Add comments to explain the logic for loading conversation data based on certain conditions
📝 (frontend): Add comments to describe the purpose of handling new conversation creation and resetting messages
📝 (frontend): Add comments to explain the logic for loading conversation data when conversationData changes
📝 (frontend): Add comments to clarify the purpose of loading conversations from the backend
📝 (frontend): Add comments to describe the logic for silent refresh to update data without loading states
📝 (frontend): Add comments to explain the purpose of starting a new conversation and creating a placeholder conversation
📝 (frontend): Add comments to clarify the logic for forking from a response and starting a new conversation
📝 (frontend): Add comments to describe the purpose of adding a conversation document and clearing conversation documents
📝 (frontend): Add comments to explain the logic for using a timeout to debounce multiple rapid refresh calls
📝 (frontend): Add comments to clarify the purpose of cleaning up timeout on unmount
📝 (frontend): Add comments to describe the logic for handling new conversation creation and resetting state
📝 (frontend): Add comments to explain the logic for forking from a response and starting a new conversation
📝 (frontend): Add comments to clarify the purpose of using useMemo for optimizing performance in ChatProvider
📝 (frontend): Add comments to describe the logic for using useMemo in the ChatProvider component
📝 (frontend): Add comments to explain the purpose of the useChat custom hook
📝 (frontend): Add comments to clarify the error message when useChat is not used within a ChatProvider
📝 (services): Update ChatService to fetch Langflow history with flow_id parameter for better control
