Building a Question Answering PDF Chatbot in 5 Steps

🤖 This video is about creating a question answering PDF chatbot using LangChain, OpenAI, Panel, and HuggingFace.

💡 The process involves uploading a PDF file, setting up OpenAI API, and entering questions to get answers.

📚 The chatbot can provide relevant information from the PDF and return the answer along with source text chunks.

🔑 The video demonstrates how to build a question answering PDF chatbot using LangChain, OpenAI, Panel, and HuggingFace.

⚙️ The process involves selecting a PDF file, entering a password, and setting up widgets for the prompt, run button, advanced settings, chain type, and number of chunks.

📚 The chatbot can be customized using different widgets and is runnable on the web using Pile Died and Pi script.

📚 The video demonstrates how to build a question answering PDF chatbot using LangChain, OpenAI, Panel, and HuggingFace.

💡 The five steps for building the chatbot include understanding widgets, defining a question answering function, splitting documents into chunks, creating vector stores, and using the retriever interface.

🔑 The function takes input from a PDF loader, allows for different file types, performs a similarity search, and utilizes a language model to answer questions.

📚 The video explains the process of building a question answering PDF chatbot using LangChain, OpenAI, Panel, and HuggingFace.

💼 The transcription mentions the steps involved in integrating the question answering function into the chatbot interface and saving the chat history.

💻 The speaker also covers the process of defining the OpenAI API key, saving the PDF file, and running the question answering function with the selected file and prompt text.

📦 The video discusses the process of building a question answering PDF chatbot using LangChain, OpenAI, Panel, and HuggingFace.

💡 The steps involved in building the chatbot include defining widgets, creating a question answering function, creating a panel object, and binding the run button with the QA result function.

🔗 The chatbot allows users to input questions and receive relevant answers from a language model using the source text from multiple documents.

💡 The video demonstrates the process of building a question answering PDF chatbot using LangChain, OpenAI, Panel, and HuggingFace.

💻 The five steps involved in creating the chatbot are: setting up the widget box, defining the layout with Markdown, adding necessary widgets and API keys, serving the app, and deploying the app to a hosting platform.

📦 The video also provides information on the required packages and the file structure, including the requirements.txt file and the Notebook file.

✨ The video demonstrates the 5 steps to build a question answering PDF chatbot using LangChain, OpenAI, Panel, and HuggingFace.

💻 The Docker file is used to set up the environment, install necessary packages, and copy the code into the working directory.

🚀 The panel app runs the chatbot on a specified address and port, allowing users to interact with it through a separate page.