ChatMate - Your AI-Powered Chatbot
@Pratham-Jain-3903
关于 ChatMate - Your AI-Powered Chatbot
frontend for generic MCP server based chatbot
基本信息
配置
工具
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概览
What is ChatMate - Your AI-Powered Chatbot?
ChatMate is a Next.js application that provides a chatbot interface with local conversation storage, API integration for backend queries, conversation history in a sidebar, and user authentication. It leverages Genkit for AI-powered features such as conversation summarization and text-to-speech.
How to use ChatMate - Your AI-Powered Chatbot?
Clone the repository, install dependencies (npm install or yarn install), set environment variables (GOOGLE_GENAI_API_KEY, GOOGLE_CLOUD_PROJECT, GOOGLE_CLOUD_LOCATION), configure Firebase for authentication, then run npm run dev or yarn dev and open http://localhost:9002.
Key features of ChatMate - Your AI-Powered Chatbot
- Secure user authentication and authorization.
- Collapsible sidebar for easy access to conversation history.
- Conversations stored locally on the user's device.
- Queries sent to the backend API for processing.
- AI-powered summarization of the last 10 messages.
- Text-to-speech and voice input for accessibility.
- Toggle between light and dark theme modes.
Use cases of ChatMate - Your AI-Powered Chatbot
- Customer care agent for Luminous Power Technologies.
- Accessible chat with text-to-speech and voice input.
- AI conversation summarization for quick context.
- Local first chat with optional backend API queries.
FAQ from ChatMate - Your AI-Powered Chatbot
What are the runtime dependencies?
Node.js version 18 or higher, npm or yarn, and the Genkit CLI installed globally (npm install -g genkit-cli).
Where is conversation data stored?
Conversations are persisted in the Browser’s localStorage to retain state across sessions.
How is user authentication handled?
Authentication is provided by Firebase services and NextAuth.js, with options such as Google Sign-In.
How are AI features implemented?
AI features (answer generation, summarization, conversation naming, TTS, transcription) are implemented using Genkit flows that interact with a configured AI model API (e.g., Gemini).
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