How do I deploy Extract Chat - chat with firecrawl on Railway?

You can deploy Extract Chat - chat with firecrawl on Railway by clicking the "Deploy Now" button on this page. Railway will automatically set up all the necessary services and configurations for you.

What are the system requirements?

Railway handles all the infrastructure requirements. You only need a web browser to deploy and manage your application.

Is this template free to use?

Yes, this template is free to use within your existing Railway account.

Can I customize this template?

Yes, you can fully customize this template. After deployment, you will have full control of what you've deployed in your Railway project.

How do I get support for this template?

You can get support through our community forum: extract-chat-7103749b, or click "Get template help" for this template for more assistance.

Deploy Extract Chat - chat with firecrawl

Extract.chat: AI Chatbot with Firecrawl Integration Extract.chat is an AI-powered chatbot application that enables real-time data extraction and search capabilities through Firecrawl integration. This project is a fork of Vercel's AI Chatbot, enhanced with specialized tools for retrieving and analyzing information from websites. Project Overview Extract.chat combines the power of Next.js, AI SDK, and Firecrawl to create a versatile chatbot that can not only engage in conversations but also fetch and extract structured data from the web in real-time. Short description (75 characters): Web-enabled AI assistant that searches and extracts structured data from websites. Key Features Core Functionality

Firecrawl Integration: Search the web for information and extract structured data from multiple websites Next.js App Router: Advanced routing with React Server Components (RSCs) and Server Actions AI SDK Integration: Unified API for generating text, structured objects, and tool calls with LLMs User Authentication: Secure login/registration system with anonymous access option Document Creation: Generate and manipulate text, code, and spreadsheet documents

Technical Highlights

Data Persistence: PostgreSQL database integration for chat history and user data File Storage: Vercel Blob support for efficient file handling Responsive UI: Modern interface built with shadcn/ui and Tailwind CSS Real-time Streaming: Server-sent events for responsive chat interactions

Architecture The application follows a modern web architecture:

Frontend: React-based UI with Next.js App Router Backend: Server-side functions for authentication, chat processing, and database operations AI Integration: Connection to AI models via the AI SDK Web Integration: Firecrawl API for searching and extracting data from websites Database: Vercel Postgres for data persistence

Deployment Requirements To deploy Extract.chat, you'll need:

Environment Variables:

OPENAI_API_KEY: API key for OpenAI AUTH_SECRET: A secret for authentication BLOB_READ_WRITE_TOKEN: Vercel Blob storage token POSTGRES_URL: Connection string for Postgres database FIRECRAWL_API_KEY: API key for Firecrawl service

Vercel Account: For hosting and database integration Node.js environment: For local development

Getting Started

Clone the repository Install dependencies: pnpm install Set up environment variables in .env.local Start the development server: pnpm dev

Customization Options

AI Model: Configured to use OpenAI gpt-4o by default, but can be switched to other providers UI Appearance: Customizable with Tailwind CSS Authentication Flow: Modifiable login/register processes

Use Cases

Research Assistant: Quickly gather information from multiple websites Data Extraction: Pull structured data from web pages Content Creation: Generate documents and code with AI assistance Knowledge Base: Create and maintain a personal knowledge repository