LangGraph + Corrective RAG + Local LLM = Powerful Rag Chatbot

---

---

AI Summary

Summary: Corrective Retrieval Augmented Generation (CRAG)

• AI Chatbot Concerns
  • AI chatbots can hallucinate, providing incorrect or made-up answers.
  • Unpredictability persists despite effective prompting.
• Corrective Retrieval Augmented Generation (CRAG) Overview
  • CRAG is a framework that enhances text generation model accuracy.
  • It combines retrieval, evaluation, corrective actions, web searches, and generative model integration.
  • CRAG grades documents for relevance and seeks additional data if needed.
• CRAG Process
  • A retrieval evaluator assesses the quality of information.
  • Corrective actions are based on the evaluation:
    • Correct: Documents are refined for precise knowledge.
    • Incorrect: Inaccurate documents are discarded and replaced with web search results.
    • Ambiguous: A soft action combines elements of correct and incorrect actions.
• Differences Between RAG and CRAG
  • RAG integrates external knowledge into the generation process.
  • CRAG evaluates, refines, and integrates knowledge for improved accuracy.
• Implementation Steps
  • Install requirements and import necessary libraries.
  • Set up the environment for local or API model use.
  • Load and index documents for retrieval.
  • Define GraphState class and retrieve function.
  • Implement generate function with corrective algorithm.
  • Create transform query function for context alignment.
  • Use web search for additional information if needed.
  • Develop decide to generate function for agent’s decision-making.
  • Establish a state graph workflow with stages for retrieval, grading, and generation.
• Application Usage
  • Prepare inputs with a question and choose local or API model.
  • Stream inputs through the application and print results.
• Conclusion
  • CRAG is a cutting-edge framework that addresses issues with inaccurate or irrelevant information in text generation.
  • It aims to improve the accuracy and robustness of AI chatbots and text generators.
• Engagement
  • The video encourages following, subscribing, liking, and checking out previous content for more AI news and updates.