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 LangChainProject 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 OpenAIProject 4: MCQ Quiz Creator App - Seamlessly create multiple-choice quizzes for your students using LangChain and OpenAI/ Hugging FaceProject 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 GradioProject 9: PrivateGPT- Chat with your Files Offline and FreeProject 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 AIProject 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 LangChainProject 16: Fine-Tune Llama 2 Model with LangChain on Custom DatasetProject 17: ChatCSV App - Chat with CSV files using LangChain and Llama 2Project 18: Chat with Multiple PDFs using Llama 2, Pinecone and LangChainProject 19: Run Code Llama on CPU and Create a Web App with GradioProject 20: Source Code Analysis with LangChain, OpenAI and ChromaDBProject 21: Chat with Multiple PDFs using PaLM 2, Pinecone and LangChainProject 22: Streamlit App Chat with Multiple PDFs using PaLM 2, FAISS and LangChainProject 23: Chat with Your Documents using Llama-Index and Google PaLM 2Course 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
