Learn LangChain: Build #22 LLM Apps using OpenAI & Llama 2

Build Real World LLM powered applications with LangChain, OpenAI, Llama2, Hugging Face. Create Web Apps with Streamlit.

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Learn LangChain: Build #22 LLM Apps using OpenAI & Llama 2

What You Will Learn!

  • Master the basics of LangChain and the fundamentals of Large Language Models (LLMs)
  • How to Use LangChain, OpenAI, Llama 2, Hugging Face to Build LLM-Powered Applications.
  • Learn about LangChain components, including LLM wrappers, prompt templates, chains, agents, memory and document loaders
  • Learn to apply LLM techniques to personal documents and projects
  • Learn how to use embeddings and vector data stores.
  • Learn about FAISS and Similarity Search.
  • Learn about Pinecone and ChromaDB
  • Project: Create a Simple Chatbot with Llama 2 and LangChain
  • Project: Quiz MCQ Creator Application
  • Project: YouTube Script Writing Application
  • Project: PDF Chat App (GUI) | ChatGPT for Your PDF File
  • Project: Chat with Multiple PDF Documents | Streamlit Application
  • Project: Summarize PDF Using LangChain, OpenAI & Gradio
  • Project: YouTube Video Summarizer
  • Project: PrivateGPT- Chat with your Files Offline and Free
  • Project: Support Chat Bot For Your Website
  • Project: Question a Book with (LangChain + Llama 2 + Pinecone)
  • Project: Create a chatbot to chat with multiple documents including pdf, .docs, .txt using Llama 2 , LangChain/ OpenAI and ChromaDB
  • Project: Create a Custom Chatbot for any Website with LangChain and Llama 2/ OpenAI
  • Project: Creating a Flask API for Automatic Content Summarization using LangChain and Llama 2/ Open AI
  • Fine-Tune Llama 2 Model with LangChain on Custom Dataset
  • Introducing 'GPT-LLM-Trainer' — the world's simplest way to train a task-specific model. Just input your idea, and let the AI do the rest.
  • Project: Create a Medical Chatbot with Llama2, Pinecone and LangChain
  • Project: ChatCSV App - Chat with CSV files using LangChain and Llama 2
  • Project: Chat with Multiple PDFs using Llama 2, Pinecone and LangChain
  • Project: Source Code Analysis with LangChain, OpenAI and ChromaDB
  • Project: Run Code Llama on CPU and Create a Web App with Gradio
  • Run PaLM 2 in Google Colab | How to use Free Google PaLM API
  • Project: Chat with Multiple PDFs using PaLM 2, Pinecone and LangChain
  • Project: Streamlit App | Chat with Multiple PDFs using PaLM 2, FAISS and LangChain
  • Project: Chat with Your Documents using Llama-Index and Google PaLM 2

Description

Master LangChain, OpenAI, Llama 2 and Hugging Face. Learn to Create hands-on generative LLM-powered applications with LangChain.

Create powerful web-based front-ends for your LLM Application using Streamlit.

By the end of this course, you will have a solid understanding of the fundamentals of LangChain OpenAI, Llama 2 and HuggingFace. You'll also be able to create modern front-ends using Streamlit in Python.


Dive into hands-on projects that will shape your expertise, including:

Project 1: Create a Simple Chatbot with Llama 2 and LangChain
Project 2: PDF Chat App (GUI) | ChatGPT for Your PDF File - Streamlit Application to chat with your PDF file using LangChain and OpenAI.

Project 3: YouTube Script Writing App - Effortlessly create title and script for the YouTube video using LangChain and OpenAI

Project 4:  MCQ Quiz Creator App - Seamlessly create multiple-choice quizzes for your students using LangChain and OpenAI/ Hugging Face

Project 5: Chat with Multiple PDF Documents | Streamlit Application- Chat with your PDF files using LangChain and OpenAI.

Project 6: Support Chat Bot For Your Website - Helps your visitors/customers to find the relevant data or blog links that can be useful to them.

Project 7: YouTube Video Summarizer - YouTube Video Summarizer, powered by the dynamic duo of LangChain and OpenAI! In this groundbreaking tool, we have harnessed the cutting-edge capabilities of language processing technology to transform the way you consume YouTube content.

Project 8: Summarize PDF Using LangChain,  OpenAI  and Gradio:  Summarize PDF files using Lang Chain and OpenAI  and create a sharable web interface using Gradio

Project 9: PrivateGPT- Chat with your Files Offline and Free

Project 10: Question a Book with (LangChain + Llama 2 + Pinecone):  Create a chatbot to chat with Books or with  PDF files. using  LangChain, Llama 2 Model and Pinecone as vector store.

Project 11: Chat with Multiple Documents with Llama 2/ OpenAI and ChromaDB: Create a chatbot to chat with multiple documents including pdf, .docs, .txt using LangChain, Llama 2/ OpenAI  and ChromaDB as our vector database.

Project 12: Create a Custom Chatbot for any Website with LangChain and Llama 2/ OpenAI: Create a chatbot for your own or for any website using LangChain, Llama 2/ OpenAI and FAISS as the vector store / vector database

Project 13: Creating a Flask API for Automatic Content Summarization using LangChain and Llama 2/ Open AI

Project 14: Introducing 'GPT-LLM-Trainer' — the world's simplest way to train a task-specific model.  Just input your idea, and let the AI do the rest.

Project 15: Create a Medical Chatbot with Llama2, Pinecone and LangChain

Project 16: Fine-Tune Llama 2 Model with LangChain on Custom Dataset

Project 17: ChatCSV App - Chat with CSV files using LangChain and Llama 2

Project 18: Chat with Multiple PDFs using Llama 2, Pinecone and LangChain

Project 19: Run Code Llama on CPU and Create a Web App with Gradio

Project 20: Source Code Analysis with LangChain, OpenAI and ChromaDB

Project 21: Chat with Multiple PDFs using PaLM 2, Pinecone and LangChain

Project 22: Streamlit App | Chat with Multiple PDFs using PaLM 2, FAISS and LangChain

Project 23: Chat with Your  Documents using Llama-Index and Google PaLM 2

Course Content:

In this course, we will explore the capabilities of LangChain, to build scalable and performant AI applications.

You will gain in-depth knowledge of LangChain components, including LLM wrappers, Prompt Template, Chains, Agents, Memory and Document Loaders. Additionally, we will delve into embeddings and vector databases


Who Should Attend!

  • Anyone who is excited to build AI powered LLM apps using Langchain
  • AI Enthusiast

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Subscribers

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Lectures

56

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