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YouTube Q&A Assistant

YouTube Q&A Assistant is a Python application that extracts available YouTube captions and uses retrieval-augmented generation to answer questions, summarize videos, surface key takeaways and search transcript topics.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

YouTube Q&A Assistant — OpenViST project profile in RAG & Knowledge Systems.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when a YouTube video has captions and you want to query or review its content through a transcript rather than watch or search the full video manually.

Who it is for

  • Viewers who want to ask questions about a video without searching through it manually
  • Researchers and learners who need transcript-based summaries, takeaways or topic discovery
  • Developers looking for a Python example of a transcript-focused RAG application

Documented uses

  • Ask questions about information discussed in a YouTube video
  • Generate a structured summary or a list of key points
  • Find relevant transcript passages through semantic search
  • Identify topics in a video and receive short descriptions
Before you choose

Requirements & limits

  • The app requires an OpenRouter API key for its language-model connection.
  • The documented stack includes Streamlit, LangChain, ChromaDB, Hugging Face MiniLM embeddings and the YouTube Transcript API.
  • Captions are required; the transcript loader can fall back to available caption languages.
  • Processing a new video recreates the local ChromaDB folder.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up the app locally

Install the Python project, configure its OpenRouter key and start the Streamlit interface.

Before you start

  • Python environment capable of creating a virtual environment
  • OpenRouter API key

Steps

  1. Clone the repository and change into its directory.

  2. Create and activate a virtual environment.

  3. Install dependencies with pip install -r requirements.txt.

  4. Create a .env file from .env.example and add OPENROUTER_API_KEY.

  5. Start the interface with streamlit run app.py.

Expected outcome

The local Streamlit application starts with its video input and chat interface.

Guide limitations

  • A video needs an available transcript; processing fails when no transcript is available.
  • The ChromaDB folder is recreated when processing a new video.
Documentation 1 ↗
COMPARE OPTIONS

Compare options for Retrieval-augmented applications

These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.

ProjectDocumented purposePlatformAccess and requirements
YouTube Q&A AssistantAsk questions about information discussed in a YouTube videoWeb
Rag Powered AI Assistant Transforming Data Retrieval And Analysis Across The Web And PdfsRetrieve relevant passages from web and PDF content to answer a question.Web
LangChain in Supabase Edge FunctionsInitialize and start a Supabase project locally.Cloud, Server
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
14 October 2026
Original website title
AbdulRehman393/youtube-qa-assistant · Official homepage title · retained in its source language
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