LangChain | MultiQueryRetriever: Better RAG with Automated Query Generation | Video #43 скачать в хорошем качестве

LangChain | MultiQueryRetriever: Better RAG with Automated Query Generation | Video #43

Is a single search query enough? 🕵️‍♂️ In Video #43 of our LangChain Full Course, we explore the MultiQueryRetriever—a game-changer for retrieval accuracy. This is one of the most powerful techniques for improving RAG performance! The MultiQueryRetriever solves a massive problem: users often ask questions in a different way than the documents are written. FAISS vector store is used in this practical By using an LLM to generate multiple "perspectives" of the same question, you ensure that even if one query misses the mark, the others will catch the right documents. Standard RAG systems rely on a single user query, which can be prone to "distance-based" failures if the user's wording doesn't perfectly match the document. The MultiQueryRetriever automates prompt tuning by using an LLM to generate multiple variations of the same question from different angles. It then retrieves documents for all those queries and takes a unique union, significantly increasing the chances of finding the exact answer your user needs. [Image: Diagram showing 1 Question → LLM → 3 Variations → Vector DB → Combined Unique Documents] ✅ In this advanced retrieval session, we cover: The "Vocabulary Gap": Why the way users ask questions often fails standard similarity search. How Multi-Query Works: The process of query generation, parallel retrieval, and deduplication. Simple Implementation: Using MultiQueryRetriever.from_llm() to get started in seconds. Customizing the Prompt: How to write your own prompt template to control how the LLM rephrases questions. Logging the Magic: How to enable logging to actually see the alternative queries your AI is creating. Why this matters: This is "Advanced RAG" made simple. By generating multiple perspectives, you overcome the limitations of simple vector search and build a system that is far more robust against poorly phrased or ambiguous questions. Follow the Full Course Playlist here:    • LangChain Full Course: Step-by-Step Tutori...   #LangChain #MultiQueryRetriever #RAG #AIArchitecture #PromptTuning #SemanticSearch #OpenAI #VectorDatabase #PythonAI #GenerativeAI #LLM #AITutorial #DataEngineering