Integration and Execution of Abstract Processing Pipeline

📅 2025-02-08 — Session: Integration and Execution of Abstract Processing Pipeline

🕒 16:30–17:50
🏷️ Labels: Abstract Processing, AI, Pipeline, Error Handling, State Management
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The primary goal of this session was to integrate and execute an abstract processing pipeline using AI-driven tools for efficient research abstract management.

Key Activities

• Integrated abstract processing agents into the workflow, adapting existing classes and functions for abstract handling.
• Implemented the AbstractManager class for storing and retrieving abstracts in JSON format, ensuring no duplicates.
• Developed the AbstractsState class for managing the state of abstracts through processing stages.
• Adapted the ChunkHandler to AbstractProcessor for DOI-based abstract processing.
• Updated schemas and function mappings for AI agents, including the Abstract Reader and Screening Agent.
• Implemented the execution pipeline for the Abstract Reader and Screening Agent.
• Addressed network issues with CrossRef API by using a mock dataset.
• Updated AbstractsState and AbstractManager for AI output handling.
• Revised the process_abstracts function for improved error handling and state management.
• Fixed errors related to ValidationError and TypeError in class implementations.

Achievements

• Successfully executed a mock abstract processing and screening workflow.
• Established a comprehensive pipeline for fetching, processing, and displaying research abstracts.

Pending Tasks

• Validate and integrate the updated schemas and function mappings for AI agents.
• Further refine error handling mechanisms for robust pipeline execution.