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LangChain + MCP + RAG + Ollama = The Key To Powerful Agentic AI

2 min read

LangChain + MCP + RAG + Ollama = The Key To Powerful Agentic AI

AI Summary

Summary of Video: Creating a Multi-Agent Chatbot Using Langchain

Introduction

  • Quick tutorial on creating a multi-agent chatbot for business or personal use.
  • Discusses the significance of MCP, Rag, and web scraping tools.

Key Concepts

  • MCP (Multi-Context Protocol): Standardizes how applications provide context to LLMs. Useful for performing complex operations and integrating external tools.
  • Rag (Retrieval-Augmented Generation): Keeps information up-to-date, ideal for enterprise chatbots.
  • Combination of MCP and Rag enhances chatbot capabilities by integrating real-time data retrieval and contextual awareness.

Mistral Small 3.1

  • Newly released model designed for efficient, low-latency generative AI tasks.
  • Open source under Apache 2.0 license.
  • Supports image understanding and has a context length up to 128K tokens.

Chatbot Functionality

  • Demonstration of a live chatbot retrieving news about LLMs.
  • The chatbot calls web search, extracts URLs, fetches content asynchronously, and divides it into chunks for embedding.
  • Uses Mistral AI and Olama for embedding.
  • Error Handling: Modifies code to create fresh connections for each tool call to prevent errors.

Implementation Steps

  1. Installing Libraries: pip install requirements
  2. Code Initiation: Import relevant libraries (e.g., Firecrawl for markdown conversion).
  3. Web Search Tool: Create a tool for searching and validating URLs, integrating with Rag for relevant content.
  4. Async Retrieval: Fetches web content efficiently, handling errors and timeouts.
  5. Embedding Documents: Converts content into embeddings and stores for semantic retrieval.
  6. Search Functionality: Retrieves the top relevant chunks for answering user questions.

Conclusion

  • By the end of the video, viewers understand the differences between MCP and Rag, how to use both to create powerful chatbots, and the significance of real-time information updates.
  • Emphasis on the role of community support and future potential of MCP and Rag in dynamic AI applications.

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