- Changed assertions in `test_llamacloud_basic_uses_cost_effective_tier` to check for `parse_page_with_llm` instead of `cost_effective` tier.
- Updated `test_llamacloud_premium_uses_agentic_plus_tier` to verify `parse_page_with_agent` instead of `agentic_plus` tier.
- Ensured that `tier` is no longer included in the call arguments.
- Introduced a `ProcessingMode` enum to differentiate between basic and premium processing modes.
- Updated `EtlRequest` to include a `processing_mode` field, defaulting to basic.
- Enhanced ETL pipeline services to utilize the selected processing mode for Azure Document Intelligence and LlamaCloud parsing.
- Modified various routes and services to handle processing mode, affecting document upload and indexing tasks.
- Improved error handling and logging to include processing mode details.
- Added tests to validate processing mode functionality and its impact on ETL operations.
- Added a static method `estimate_pages_from_metadata` to `PageLimitService` for estimating page counts based on file metadata.
- Integrated page limit checks in Google Drive, Dropbox, and OneDrive indexers to prevent exceeding user quotas during file indexing.
- Updated relevant indexing methods to utilize the new page estimation logic and enforce limits accordingly.
- Enhanced tests for page limit functionality, ensuring accurate estimation and enforcement across different file types.
- Updated maximum file size limit to 500 MB per file.
- Removed restrictions on the number of files per upload and total upload size.
- Enhanced handling of user-mentioning documents in the knowledge base search middleware.
- Improved document reading and processing logic to accommodate new features and optimizations.
- Introduced a new utility for parsing .xlsx files into markdown format, enhancing the ability to process Excel documents natively.
- Updated the Google Drive content extractor to utilize the new Excel parsing functionality, allowing for better handling of spreadsheet files.
- Enhanced file type detection and export logic to support various document formats, improving overall content extraction accuracy.
- Added unit tests to ensure the correctness of the new Excel parsing feature and its integration with existing content extraction workflows.
- Added logging to track the start and end of file download and export processes, improving visibility into execution time.
- Implemented per-thread HTTP transport for concurrent downloads and exports, ensuring thread safety.
- Refactored download and export methods to utilize resolved credentials, enhancing functionality.
- Updated unit tests to validate the new threading and logging features, ensuring robust parallel execution.
- Implemented per-thread HTTP transport for concurrent downloads to ensure thread safety.
- Refactored `download_file` and `download_file_to_disk` methods to utilize blocking calls on separate threads, improving performance during file operations.
- Added logging to track the start and end of download and export processes, providing better visibility into execution time.
- Updated unit tests to verify parallel execution of download and export operations, ensuring efficiency in handling multiple requests.
- Refactored Confluence and Jira indexers to utilize the shared IndexingPipelineService for improved document processing.
- Updated the `_build_connector_doc` function in both indexers to create ConnectorDocument instances with enhanced metadata and fallback summaries.
- Modified the `index_confluence_pages` and `index_jira_issues` functions to return a tuple of (indexed_count, skipped_count, warning_or_error_message) for better error handling and reporting.
- Added unit tests for both indexers to validate the new parallel processing logic and ensure correct document creation and indexing behavior.
- Refactored Linear and Notion indexers to utilize the shared IndexingPipelineService for improved document deduplication, summarization, chunking, and embedding with bounded parallel indexing.
- Updated the `_build_connector_doc` function in both indexers to create ConnectorDocument instances with enhanced metadata and fallback summaries.
- Modified the `index_linear_issues` and `index_notion_pages` functions to return a tuple of (indexed_count, skipped_count, warning_or_error_message) for better error handling and reporting.
- Added unit tests for both indexers to validate the new parallel processing logic and ensure correct document creation and indexing behavior.
- Introduced `index_google_drive_selected_files` function to enable indexing of multiple user-selected files in parallel, improving efficiency.
- Refactored existing indexing logic to handle batch processing, including error handling for individual file failures.
- Added unit tests for the new batch indexing functionality, ensuring robustness and proper error collection during the indexing process.
- Added `_download_files_parallel` function to enable concurrent downloading of files from Google Drive, improving efficiency in document processing.
- Introduced `_download_and_index` function to handle the parallel downloading and indexing phases, streamlining the overall workflow.
- Updated `_index_full_scan` and `_index_with_delta_sync` methods to utilize the new parallel downloading functionality, enhancing performance.
- Added unit tests to validate the new parallel downloading and indexing logic, ensuring robustness and error handling during document processing.
- Refactored Google Calendar and Gmail indexers to utilize the new `index_batch_parallel` method for concurrent document indexing, enhancing performance.
- Updated the indexing logic to replace serial processing with parallel execution, allowing for improved efficiency in handling multiple documents.
- Adjusted logging and error handling to accommodate the new parallel processing approach, ensuring robust operation during indexing.
- Enhanced unit tests to validate the functionality of the parallel indexing method and its integration with existing workflows.
- Added `index_batch_parallel` method to enable concurrent indexing of documents with bounded concurrency, improving performance and efficiency.
- Refactored existing indexing logic to utilize `asyncio.to_thread` for non-blocking execution of embedding and chunking functions.
- Introduced unit tests to validate the functionality of the new parallel indexing method, ensuring robustness and error handling during document processing.
- Introduced integration tests for Calendar, Drive, and Gmail indexers to ensure proper document creation and migration.
- Added tests for batch indexing functionality to validate the processing of multiple documents.
- Implemented tests for legacy document migration to verify updates to document types and hashes.
- Enhanced test coverage for the IndexingPipelineService to ensure robust functionality across various document types.
- Added `download_and_extract_content` function to extract content from Google Drive files as markdown.
- Updated Google Drive indexer to utilize the new content extraction method.
- Implemented document migration logic to update legacy Composio document types to their native Google types.
- Introduced identifier hashing for stable document identification.
- Improved file pre-filtering to handle unchanged and rename-only files efficiently.
