Chatfuro

Create, manage, and deploy Retrieval-Augmented Generation (RAG) chatbots with ease.

Chatfuro is an open-source platform that enables you to build AI-powered chatbots trained on your own data and deploy them across websites and applications with minimal setup.Chatfuro

Create, manage, and deploy Retrieval-Augmented Generation (RAG) chatbots with ease.

Chatfuro is an open-source platform that enables you to build AI-powered chatbots trained on your own data and deploy them across websites and applications with minimal setup.

About the Project

Chatfuro is a full-stack chatbot platform designed to simplify the creation and deployment of AI-driven conversational assistants. It allows users to train chatbots directly from documents, websites, and structured data, without requiring deep AI or ML expertise.

The platform supports end-to-end chatbot lifecycle management—from data ingestion and training to deployment, monitoring, and live human handoff—making it suitable for customer support, marketing, lead generation, and internal knowledge assistants.

Significance

Traditional chatbot solutions often require:

• Custom ML pipelines
• Manual embedding workflows
• Complex infrastructure setup

Chatfuro addresses these challenges by:

• Providing a zero-code chatbot creation experience
• Leveraging RAG-based architecture for accurate, context-aware responses
• Offering production-ready deployment options such as iframes and widgets
• Supporting live agent intervention when AI responses are insufficient

This makes Chatfuro particularly valuable for teams looking to scale conversational support while retaining human control when needed.

Features

Core Capabilities

• RAG-based AI Chatbots trained on your own documents and websites
• Zero-code chatbot creation
• Smart follow-up questions to guide user conversations
• Live agent chat support
• Rich content responses (videos, images, documents, links)

Data & Training

• Train chatbots using:
  • PDFs, DOCs, Excel files, Markdown
  • Website URLs and sitemaps
  • Rich media references
• Vector-based semantic search using Qdrant

Deployment & Management

• Embed chatbots as: -Iframes
  • Website widgets
• Built-in chatbot sharing and deployment
• Agent management and delegated access
• Chat history and conversation management

Analytics & Monitoring

• Advanced dashboard for chatbot performance
• Conversation tracking and metrics
• Lead capture and collaboration tools

Screenshots

Integrations

Chatfuro integrates with a variety of platforms to fit into existing workflows:

• Website Integration Embed chatbots directly into any website using iframe or script-based widgets.
• API Access Programmatic access to Chatfuro functionality via REST APIs.

Suitable for automation, custom workflows, and advanced integrations.

Once you spin up the application API Documentation will be available at: https://localhost:5000/api-docs/

• WordPress Easily integrate Chatfuro chatbots into WordPress sites.

• Zapier Connect Chatfuro to 5,000+ applications using Zapier. Automate workflows such as lead capture, notifications, and CRM updates.

🔗 Zapier Integration: https://zapier.com/developer/public-invite/190531/ce83a1e523cdf23e106133d1e02ef06c/

Usage

Prerequisites

• Docker & Docker Compose
• Node.js
• OpenAI API key
• Auth0 credentials
• MongoDB instance
• Qdrant

Downloading the Project

git clone https://github.com/nivethithanm/chatfuro-app.git
cd chatfuro-app

Environment Setup

1. Locate .env.example files under app and api folders.
2. Create corresponding .env files:

cp .env.example .envcp .env.example .env

3. Add valid credentials for:

• OpenAI (GPT-3.5)
• Auth0
• MongoDB
• Qdrant Cloud

Running the Application

docker compose up -d

Accessing the Services

Chatfuro UI: http://localhost:8080

API Documentation: http://localhost:5000

License

This project is open-source and available under the MIT license.