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    Llm Chat Replay

    chat replay visualizer for sesssions saved in your LLM. create transcripts using your LLM + MCP filesystem server, and replay them here, to share with others

    1 stars
    TypeScript
    Updated Nov 1, 2025

    Documentation

    LLM Chat Replay

    A React application that provides a visual replay of LLM chat transcripts with typing animation and playback controls. Created for AI assistant conversations (like Claude), but works with any markdown chat export using the specified format.

    Features

    • Drag and drop markdown file upload
    • Playback controls (play/pause)
    • Speed control (0.5x to 4x)
    • Progress bar scrubbing
    • Auto-scrolling chat window with smart scroll behavior
    • Distinct bubbles for Human and Assistant messages
    • Typing animation for Assistant responses
    • Automatically extracts and displays conversation title

    Demo

    Drop any markdown transcript with the following format:

    markdown
    # Title of Conversation
    
    **Human**: Your question or prompt here
    
    **Assistant**: The assistant's response here

    Getting Started

    Prerequisites

    • Node.js (v16+)
    • npm or yarn

    Installation

    bash
    git clone https://github.com/yourusername/llm-chat-replay.git
    cd llm-chat-replay
    npm install
    npm run dev

    Usage

    1. Launch the application using npm run dev

    2. Drop your saved markdown transcript file into the interface or click to browse

    3. Use playback controls to replay the conversation

    4. Adjust speed as needed using the controls below the chat

    5. Use the progress bar to jump to specific parts of the conversation

    Creating Compatible Transcripts

    When chatting with AI assistants, you can typically request a transcript export:

    code
    Ask the assistant: "please save the full transcript of this chat as a markdown file"

    Ensure the saved markdown file is formatted with "Human:" and "Assistant:" markers at the beginning of each message.

    Pre-prompt for Consistent Transcript Formatting

    For best results, add this pre-prompt to your AI assistant's settings to ensure properly formatted transcripts:

    code
    Here are instructions to add to your profile:
    
    When asked to save a chat or a transcript, here are some rules:
    
    Please save a complete, properly formatted transcript of our conversation to the filesystem using tools. When creating this transcript:
    
    1. Come up with a title for the chat, and add it to the document at the beginning as "# Title:  [title]"
    2. Format with `**Human**:` and `**Assistant**:` prefixes exactly as shown.. that's:
    	- Two asterisks (`**`)
    	- The identifier (Human or Assistant)
    	- Two asterisks (`**`)
    	- A colon (`:`)
    	- A space
    	- Then the message content
    3. Preserve all original text formatting, but avoid special characters that might break markdown
    4. For any file paths or code:
       - Place them on their own lines when possible
       - Wrap them in backticks like `this`
       - Avoid ending lines with underscores or other markdown-sensitive characters
    5. For function calls and results:
       - Format them as  relevant information
       - Format them as relevant information
       - Ensure they're on their own lines
       - summarize the function results and don't print the entire thing. resist having any markdown inside the function results, as it causes formatting errors.
    6. Maintain proper spacing between paragraphs
    7. Use standard markdown for any lists or formatting
    8. Save the file with a descriptive name in the format: chat_YYYYMMDD_topic_name.md
    
    Please ensure the transcript contains our complete conversation with all content preserved, and ready to be played back in the chat replay tool.
    
    ## Built With
    
    - React + Vite
    - TypeScript
    - Tailwind CSS
    - Typed.js for typing animation
    
    ## Contributing
    
    Contributions are welcome! Please feel free to submit a Pull Request.
    
    ## License
    
    This project is licensed under the MIT License - see the LICENSE file for details.

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