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*Title: How to Develop a Chat App from KZitem Videos Using LangChain and GPT-4 Omni Model | Tutorial 97*
*Description:*
Welcome back to the Total Technology Zone! This is Ronnie, and you're watching Tutorial 97. In today's project, we're diving into how to develop a chat application using LangChain and GPT-4 Omni Model, capable of interacting with KZitem videos. This project is perfect for showcasing your skills on your resume and impressing potential employers.
*Project Highlights:*
1. *Introduction:*
- Overview of the project's objectives: developing a chat application from KZitem videos using LangChain and GPT-4 Omni Model.
- Discussing the importance of such projects for resume building and job interviews.
2. *Project Steps:*
- *Streamlit UI Development:*
- Setting up a Streamlit application to input a KZitem video URL.
- *Audio Extraction:*
- Extracting and downloading the audio from the video URL.
- *Splitting Audio:*
- Splitting the downloaded MP3 audio file into multiple smaller MP3 files for easier processing.
- *Transcript Generation:*
- Generating transcripts for each split audio file using the OpenAI Whisper model.
- *Combining Transcripts:*
- Combining all generated transcripts into a single text file.
- *Vector Database Setup:*
- Splitting the text file into chunks and loading them as embeddings into a Chroma vector database.
- *Building the Chat Interface:*
- Creating a retrieval-based Q&A system to interact with the vector database and answer user questions.
3. *Code Walkthrough:*
- Detailed explanation of the code for each step, including:
- Importing necessary libraries.
- Setting up the Streamlit UI.
- Extracting audio from KZitem videos.
- Splitting audio files.
- Generating transcripts.
- Combining transcripts into a single text file.
- Loading data into a vector database.
- Creating a chat interface for user interaction.
4. *Demonstration:*
- Live demonstration of the application.
- Entering a KZitem video URL and observing the entire process from audio extraction to chat interaction.
- Asking questions to the chat app and receiving answers based on the video content.
5. *Challenges and Solutions:*
- Discussing potential challenges faced during the project and how they were overcome.
- Handling large audio files and managing transcript generation within API limits.
6. *Conclusion and Next Steps:*
- Recap of the project’s key points.
- Encouragement to implement similar projects for enhancing technical skills.
- Invitation for feedback and suggestions for future tutorials.
*Additional Resources:*
- *GitHub Repository:* Access the source code for this project to follow along and implement it yourself. (Link to be provided in the video description)
- *Related Tutorials:*
- Tutorial 96: Document Tagging Using LangChain and GPT-4 Omni Model
- Tutorial 95: Generating Synthetic Data Using LangChain and GPT-4 Omni Model
- Tutorial 94: Chat and Plot with Your Excel File Using LangChain and GPT-4 Omni Model
*About the Host:*
Ronnie is dedicated to providing practical, use-case-driven tutorials to help you enhance your tech skills and tackle real-world challenges. Stay tuned for more insightful tutorials and advanced tech solutions!
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