/website-testing-AI-agent

Primary LanguagePython

title app_file sdk sdk_version
website-testing-ai-agent
main.py
gradio
4.37.2

Test Case Generator with Groq and LangChain

This project is a web-based tool that analyzes uploaded images and generates detailed test cases using Groq's AI capabilities. The application is built with Gradio for user interaction, LangChain for AI-powered document and text processing, and the Groq API for model interactions.

1725784578139

Features

  • Image Upload and Encoding: Upload any image, and the application will resize it and encode it into a base64 format to be used in the model.
  • AI-Powered Analysis: Uses Groq's llama-3.1-70b-versatile model to analyze the uploaded image and generate test cases for its features.
  • Dynamic Test Case Generation: Provides a step-by-step test case for each functionality detected in the image.
  • User Queries: Allows additional queries from the user to provide context for more specific test cases.

Installation

  1. Clone the repository:

    git clone https://github.com/sksarvesh007/website-testing-AI-agent.git
cd website-testing-AI-agent

  2. Install dependencies: Make sure you have Python 3.x installed, and then install the required libraries using pip:

    pip install -r requirements.txt

  3. Set up environment variables: Create a .env file in the root of the project and add your Groq API key and Gemini api keys as well:

    GROQ_API_KEY=your_groq_api_key
GEMINI_API_KEY=your_gemini_api_key

  4. Download Gradio and LangChain dependencies: Ensure Gradio, PIL, and Groq API dependencies are installed.

    pip install -r requirements.txt

Usage

  1. Run the application: Start the application using the following command:

    python app.py

  2. Interact with the Interface:

    • Open the Gradio interface in your browser.
    • Upload an image and add a query to provide extra context about the image.
    • The application will analyze the image and return detailed test cases with pre-conditions, steps, and expected results.

Code Structure

  • app.py: The main application script.
  • encode_image(): This function takes an image, resizes it, and encodes it to base64 format.
  • analyze_image(): This function handles the interaction with Groq's API to generate test cases for the uploaded image.
  • gr.Interface(): This sets up the Gradio interface to accept images and user queries.

Example

  • Input: An image of a website and a query like "Describe the login functionality."
  • Output: A step-by-step guide on testing the login feature, including pre-conditions, test steps, and expected results.

How It Works

  1. Image Encoding: The uploaded image is resized and converted into a base64 string.
  2. Groq API Call: The encoded image and user query are sent to Google's (Gemini pro model) then to Groq's model (llama3.1 model) to generate a list of features in the image.
  3. Feature Test Case Generation: Based on the feature list, the model generates a detailed guide on how to test each feature, which is then displayed in the Gradio interface.