Analyzed and Enhanced RAG Pipeline for Contact Management

• Day: 2025-05-27
• Time: 03:30 to 04:00
• Project: CRM
• Workspace: WP 2: Operational
• Status: In Progress
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: RAG, Retrieval, Contact Management, Automation, Prompt Engineering

Description

Session Goal

The session aimed to analyze and enhance the Retrieval-Augmented Generation (RAG) pipeline for contact management queries, focusing on improving retrieval quality and prompt engineering.

Key Activities

• Analyzed the failure in the RAG pipeline for contact management queries, identifying issues in answer generation, retrieval quality, and prompt structure.
• Developed strategies for crafting retriever-friendly queries, emphasizing specific keywords and temporal anchors to enhance retrieval performance.
• Proposed the ‘Retriever-Bait Paragraph Strategy’ to improve retrieval performance using longer paragraphs and elaborate queries.
• Analyzed a successful retrieval phase, highlighting strong lexical overlap and temporal grounding, and suggested improvements.
• Outlined a systematic RAG-driven recovery plan to address unfinished projects using specific retriever prompts and post-processing strategies.

Achievements

• Identified key problems in the RAG pipeline and proposed actionable strategies to address them.
• Developed templates and strategies for query optimization and retrieval enhancement.

Pending Tasks

• Implement the proposed strategies and templates to test their effectiveness in real-world scenarios.
• Further explore the integration of fuzzy matching techniques to enhance retrieval quality.

Evidence

• source_file=2025-05-27.sessions.jsonl, line_number=9, event_count=0, session_id=db6ec972283b754b9b9c18705bdb577ff9c5eed27efb3b3bbdaa3b129babef79
• event_ids: []