Interact with any YouTube video by chatting with its transcript. Instantly extract and query video content to get concise, AI-powered answers to your questions about the video.
Flows
Below is a complete list of all prompts used in this flow to achieve its functionality. Prompts are the instructions given to the AI model to generate responses or perform actions. They guide the AI in understanding user intent and generating relevant outputs.
Agent that calls tools and uses a custom system prompt to guide the LLM in answering questions about YouTube video transcripts.
You're a professional YouTube researcher and personal assistant. You are given a YouTube URL. When given a YouTube video URL, extract the transcript and use it to answer user queries. Provide concise answers in a friendly tone. If the answer isn't in the transcript, let the user know, and do not try to hallucinate answers.
Below is a complete list of all components used in this flow to achieve its functionality. Components are the building blocks of every AI Flow. They allow you to create complex interactions and automate tasks by connecting various functionalities. Each component serves a specific purpose, such as handling user input, processing data, or integrating with external services.
The Chat Opened Trigger component detects when a chat session starts, enabling workflows to respond instantly as soon as a user opens the chat. It initiates flows with the initial chat message, making it essential for building responsive, interactive chatbots.
The Message Widget component displays custom messages within your workflow. Ideal for welcoming users, providing instructions, or showing any important information, it supports Markdown formatting and can be set to appear only once per session.
Discover the Chat Output component in FlowHunt—finalize chatbot responses with flexible, multi-part outputs. Essential for seamless flow completion and creating advanced, interactive AI chatbots.
The Chat History component in FlowHunt enables chatbots to remember previous messages, ensuring coherent conversations and improved customer experience while optimizing memory and token usage.
The Chat Input component in FlowHunt initiates user interactions by capturing messages from the Playground. It serves as the starting point for flows, enabling the workflow to process both text and file-based inputs.
Explore the Tool Calling Agent in FlowHunt—an advanced workflow component that enables AI agents to intelligently select and use external tools to answer complex queries. Perfect for building smart AI solutions that require dynamic tool usage, iterative reasoning, and integration with multiple resources.
Unlock web content in your workflows with the URL Retriever component. Effortlessly extract and process the text and metadata from any list of URLs—including web articles, documents, and more. Supports advanced options like OCR for images, selective metadata extraction, and customizable caching, making it ideal for building knowledge-rich AI flows and automations.
Flow description
This workflow enables users to interactively chat with the transcript of any YouTube video. By simply providing a YouTube URL, users can ask questions and receive concise answers based on the video’s transcript. This system is designed to make long-form video content easily accessible and searchable through conversational AI.
| Step | Component | Purpose |
|---|---|---|
| 1. Chat Start | ChatOpenedTrigger, MessageWidget | Greet user and provide instructions |
| 2. User Input | ChatInput, ChatHistory | Receive user queries and remember conversation history |
| 3. Transcript Fetch | URLContent | Extract transcript from YouTube video |
| 4. Q&A Agent | ToolCallingAgent | Answer user questions using the transcript and chat context |
| 5. Output | ChatOutput | Display messages and answers to the user |
This workflow brings powerful automation and AI-driven conversation to YouTube video content, making it a valuable tool for educators, researchers, students, and content consumers who want to extract value from video without manual effort. It can be easily scaled and generalized for various types of video content, maximizing productivity and accessibility.
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