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


Learn LangChain: Build #22 LLM Apps using OpenAI & Llama 2 | Udemy [Update 08/2023]
English | Size: 5.7 GB
Genre: eLearning

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

What you’ll 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

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 this course is for:

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