Showing posts with label search technology. Show all posts
Showing posts with label search technology. Show all posts

Friday, August 11, 2023

🚀 Unleashing the Power of Search and AI: Crafting the Ultimate Question Answering System!


 Embarking on an Exciting Journey 🌟

Ever wondered how to fuse search with AI to build an intelligent question-answering system? Buckle up! Here's your step-by-step guide!


Step 1: Forge Your Knowledge Arsenal 📚

📰 Gather Texts: Assemble a collection of relevant texts—newspapers, Wikipedia pages, journals, and more.

✂️ Chunk it Down: Slice those lengthy documents into snackable paragraphs[^3^].

🧙 Transform with Langchain: Using Langchain and text-embedding-ada-002, transform the chunks into magical vectors.

🗄️ Store the Wisdom: Tuck those chunks and vectors into a database for later retrieval.


Step 2: Implement a Smart Search 🎯

🧠 Question Vector: Turn your user's question into a search-ready vector.

🔍 Find the Matches: Retrieve the most similar chunks by comparing embeddings[^15^].

🎛️ Fine-Tune: Adjust the number of chunks, the model, and similarity metric as needed.


 Step 3: Craft the Perfect Query 📝

🔗 Combine Chunks: Stitch together the question and retrieved chunks.

🎨 Format: Add explanations, formatting, and stay within model limits (e.g., 4096 tokens).


Step 4: Get the Answer 📩

💬 Ask the AI: Send your crafted message to a conversational AI like GPT-3[^16^].

📜 Retrieve: Get the AI's response and present it as the final answer.

🚀 Upgrade: If needed, escalate to a more capable model, like GPT-4.


Next Steps 🛠️

📈 Scale Your System: Build a robust corpus, implement efficient search infrastructure, and optimize your queries.

Enhance Quality: Improve answers with better prompting, examples, etc.


Dig Deeper with These References 📖

Introduction to Langchain: [Langchain Technology Overview]🌐

 Introduction to Text Embeddings with the OpenAI API 📘

Langchain  🧮

 

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