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Chat with URL API

Welcome to the Chat with URL API! This API uses various tools and libraries to fetch content from a URL, process it, and generate responses using OpenAI's language models. It supports both GET and POST requests.

Chat with URL

Table of Contents

Getting Started

To get started with this API, follow these steps:

  1. Clone the repository:

    git clone https://github.com/RaheesAhmed/chat-with-url.git
cd chat-with-url

  2. Install the dependencies:

    npm install

  3. Set up the environment variables:

    Create a .env file in the root of your project and add your OpenAI API key:

    OPENAI_API_KEY=your_openai_api_key

  4. Run the development server:

    npm run dev

  5. Open your browser:

    Go to http://localhost:3000 to see the API in action.

Environment Variables

  • OPENAI_API_KEY: Your OpenAI API key. This is required for accessing OpenAI's models.

Endpoints

GET /api

Returns a welcome message.

Response

{
  "response": "Welcome to Chat with URL...."
}

POST /api

Processes the content from a given URL and generates a response using OpenAI's language models.

Request Parameters query (string): The question or query you want to ask based on the URL content. url (string): The URL of the content you want to process. model (string, optional): The OpenAI model to use (default is gpt-3.5-turbo). temperature (number, optional): The temperature for the OpenAI model (default is 0.7). maxTokens (number, optional): The maximum number of tokens for the OpenAI model (default is 1000). chunkSize (number, optional): The chunk size for splitting the content (default is 1000). chunkOverlap (number, optional): The chunk overlap for splitting the content (default is 200).

Response

The response will contain the generated answer based on the input query and URL content.

{
  "result": "Your generated answer based on the query and URL content."
}

Example Usage

curl -X POST http://localhost:3000/api -H "Content-Type: application/json" -d '{
  "query": "What is the main topic of the article?",
  "url": "https://example.com/article",
  "model": "gpt-3.5-turbo",
  "temperature": 0.7,
  "maxTokens": 1000,
  "chunkSize": 1000,
  "chunkOverlap": 200,
}'

Response

{
  "result": "The main topic of the article is about..."
}

Error Handling

Errors are logged to the console, and the API returns a JSON response with the error message and a status code of 500.

Dependencies

next: The React framework for building server-side rendered applications. @langchain/core: Core utilities for building language chain applications. @langchain/community: Community utilities for building language chain applications. cheerio: Fast, flexible, and lean implementation of core jQuery designed specifically for the server. dotenv: Loads environment variables from a .env file. openai: OpenAI API client. langchain: Language chain utilities and components.

License

This project is licensed under the MIT License.License.md