QA toàn hệ thống

System-wide QA xử lý câu hỏi dựa trên toàn bộ kho dữ liệu, yêu cầu retrieval và synthesis thông tin từ nhiều nguồn.

🎯 Đặc điểm

• Global scope: Tìm kiếm trên toàn bộ corpus
• Multi-document: Kết hợp thông tin từ nhiều tài liệu
• Complex reasoning: Yêu cầu suy luận phức tạp
• Comprehensive answers: Trả lời toàn diện

🔄 Process Flow

🛠️ Techniques

Multi-hop Reasoning

• Chain of thought: Step-by-step reasoning
• Evidence collection: Gather supporting facts
• Fact verification: Cross-reference information

Answer Synthesis

• Information fusion: Combine from multiple sources
• Conflict resolution: Handle contradictory information
• Confidence scoring: Rate answer reliability

Context Management

• Long context: Handle extensive retrieved information
• Context compression: Summarize relevant parts
• Memory mechanisms: Maintain conversation context

🤖 Model Requirements

Large Language Models

• High reasoning capacity: GPT-4, Claude, Gemini
• Long context windows: 32K-128K tokens
• Instruction following: Good at complex tasks

Specialized Models

• Legal reasoning: Fine-tuned cho legal QA
• Multi-document QA: Trained on complex datasets
• Uncertainty handling: Express confidence levels

📊 Challenges

Information Overload

• Too many results: Filter and prioritize
• Irrelevant information: Noise reduction
• Context limits: Fit within model constraints

Answer Quality

• Hallucinations: Avoid fabricated information
• Inconsistencies: Ensure factual accuracy
• Completeness: Provide comprehensive answers

🚀 Optimization

Retrieval Strategies

• Query decomposition: Break down complex queries
• Iterative retrieval: Refine search based on initial results
• Re-ranking: Improve result ordering

Answer Enhancement

• Citation: Reference source documents
• Explanation: Provide reasoning traces
• Confidence indicators: Show certainty levels

System-wide QA cung cấp khả năng trả lời câu hỏi phức tạp trên quy mô toàn hệ thống.