graph LR
Document_Acquisition_Tools["Document Acquisition Tools"]
Document_Segmentation_Core["Document Segmentation Core"]
Document_Segmentation_Agent["Document Segmentation Agent"]
Document_Segmentation_Agent -- "initiates acquisition via" --> Document_Acquisition_Tools
Document_Segmentation_Agent -- "delegates tasks to" --> Document_Segmentation_Core
Document_Acquisition_Tools -- "provides documents to" --> Document_Segmentation_Agent
Document_Segmentation_Core -- "returns results to" --> Document_Segmentation_Agent
The Document Processing Agents subsystem is responsible for the entire lifecycle of external document handling, from acquisition and preprocessing to segmentation and analysis. It acts as a self-contained unit for transforming raw external documents into structured, segmented information usable by other agents in the system.
Responsible for retrieving raw documents from various external sources (e.g., PDF files, Git repositories) and converting them into a standardized, processable format suitable for further analysis.
Related Classes/Methods:
/home/ubuntu/CodeBoarding/repo/DeepCode/tools/pdf_downloader.py/home/ubuntu/CodeBoarding/repo/DeepCode/tools/git_command.py/home/ubuntu/CodeBoarding/repo/DeepCode/tools/pdf_converter.py
Provides the core functionalities for in-depth analysis and intelligent segmentation of document content. This includes detecting document types, determining optimal segmentation strategies, and applying various algorithms for semantic chunking and preserving algorithm integrity.
Related Classes/Methods:
Acts as a specialized agent within the multi-agent system, orchestrating the entire document segmentation workflow. It manages the lifecycle of document processing, from initiating acquisition to delegating segmentation tasks and validating the output.
Related Classes/Methods: