LangChain: Build 26 LLM Apps with OpenAI, Llama & DeepSeek

Unlock the Power of Generative AI with LangChain!

This comprehensive course dives deep into building cutting-edge AI applications using the most popular Large Language Models (LLMs) and the powerful LangChain framework. You'll gain hands-on experience with leading models like OpenAI, Llama 2, DeepSeek R1, and Hugging Face, mastering the art of creating intelligent and interactive systems.

What You'll Learn:

• LangChain Fundamentals: Become proficient with core LangChain components – LLM Wrappers, Prompt Templates, Chains, Agents, Memory, and Document Loaders. Understand how these elements work together to create sophisticated AI workflows.
• Embeddings & Vector Databases: Explore the crucial role of embeddings and vector databases in enhancing LLM capabilities for semantic search and knowledge retrieval.
• Building Generative AI Applications: Learn to create a wide range of applications, including:
  • Chatbots: Develop conversational AI experiences with Llama 2 and LangChain.
  • PDF Chat Applications: Enable users to interact with information directly within their PDF documents using LangChain and OpenAI.
  • Content Creation Tools: Automate the creation of YouTube scripts and MCQ quizzes using LangChain and OpenAI/Hugging Face.
  • Website Support Chatbots: Build intelligent chatbots to assist website visitors with finding relevant information.
  • YouTube Video Summarization: Effortlessly summarize YouTube videos with the combined power of LangChain and OpenAI.
  • Document Summarization: Summarize PDF files using LangChain, OpenAI, and Gradio for easy sharing.
  • Private AI: Create secure, offline chatbots with PrivateGPT.
  • Book & Document Question Answering: Build chatbots capable of answering questions about books and PDF files using LangChain, Llama 2, and Pinecone.
  • Multi-Document Chatbots: Develop chatbots that can understand and respond to queries based on multiple documents using Llama 2/OpenAI and ChromaDB.
  • Custom Website Chatbots: Create tailored chatbots for any website using LangChain, Llama 2/OpenAI, and FAISS.
  • Automatic Content Summarization (Flask API): Build a Flask API for automated content summarization using LangChain and Llama 2/OpenAI.
  • Task-Specific Model Training: Utilize GPT-LLM-Trainer to easily train custom models for specific tasks.
  • Medical Chatbots: Develop specialized chatbots for the healthcare industry using Llama2, Pinecone, and LangChain.
  • Fine-Tuning Llama 2: Learn to fine-tune the Llama 2 model on custom datasets with LangChain.
  • CSV Chat Applications: Enable users to chat with CSV files using LangChain and Llama 2.
  • PaLM 2 Integration: Build chatbots using PaLM 2, Pinecone, and LangChain.
  • DeepSeek R1 with Ollama: Create a Streamlit app using the DeepSeek R1 LLM (via Ollama).
  • Source Code Analysis: Analyze source code using LangChain, OpenAI, and ChromaDB.
  • Llama-Index & Google PaLM 2: Develop chatbots using Llama-Index and Google PaLM 2.
  • Gradio Web Apps: Create user-friendly web interfaces for your AI applications using Gradio.
  • Run Code Llama on CPU: Run Code Llama on CPU and build a web application with Gradio.
• Streamlit for Web App Development: Create powerful and intuitive web-based front-ends for your LLM applications using Streamlit in Python.

Who is this course for?

This course is designed for developers, data scientists, and AI enthusiasts who want to leverage the power of LLMs to build innovative applications. No prior LLM experience is required, but a basic understanding of Python is helpful.

By the end of this course, you will be able to:

• Confidently build and deploy generative AI applications using LangChain.
• Choose the right LLM for your specific needs (OpenAI, Llama 2, DeepSeek R1, Hugging Face).
• Create engaging