Best Practices for Optimizing LLMs (Prompt Engineering, RAG and Fine-tuning)

• The Optimization Strategies
• Typical Optimization Pipeline
• Comparison of Optimisation Approaches
• OpenAI RAG Use Case

RAG Evaluation Metrics

• How to Evaluate RAG
• Generation Evaluation
• Retrieval Evaluation

Challenges in the Application and Implementation of RAG

• Data Retrieval and Processing
• Generation Optimisation and Model Design
• Domain Knowledge and Model Adaptation
• Scaling and Performance Optimisation

Challenges in the Commercialization of Large Language Models

• Current Solutions for Rapid Commercial Deployment: RAG
• Challenges in the Commercialization of LLM
• Generation and Retrieval
• Use Case: Implementation of an Intelligent Customer Service System

RAG Workflow

• Raw Data Processing Flow
• RAG Process in Q&A Scenarios
• RAG Optimization Points
• RAG Optimization: Query / Retriever / Ranking / Indexing Optimization