#### Install Package
```bash
pip install webapp_builder
```
### Example Usage
```python
# Importing the CodeGenerator and ImageProcessor classes
from webapp_builder import CodeGenerator, ImageProcessor
from dotenv import load_dotenv, find_dotenv
import os
import openai
load_dotenv(find_dotenv())
# OpenAI API Key
api_key = os.getenv("OPENAI_API_KEY")
openai.api_key = api_key
# Create instances of the classes
code_generator = CodeGenerator()
image_processor = ImageProcessor()
# Example usage of CodeGenerator
code_text = "searchbar at the top right corner, navigation menu at the header, company logo at the top left corner. "
generated_code = code_generator.generate_code(code_text)
print(generated_code)
# Example usage of ImageProcessor
image_path = '/path/to_your_web_image_here/'
image_description = image_processor.get_image_description(image_path, api_key)
print(image_description)
```
For running the Streamlit app, you can create a separate Python script (let's call it `app_runner.py`) with the following content:
```python
# app_runner.py
from webapp_builder import main
from dotenv import load_dotenv, find_dotenv
import os
import openai
load_dotenv(find_dotenv())
# OpenAI API Key
api_key = os.getenv("OPENAI_API_KEY")
openai.api_key = api_key
if _name_ == "_main_":
main()
```
Then, you can run this script to launch the Streamlit app:
```bash
streamlit run app_runner.py
```
Ensure you have your OpenAI API key configured in your environment variables or pass it directly when calling methods that require it.
# web-app-builder--LLM
#### App Demo (Video Demo)
https://github.com/george-mountain/web-app-builder--LLM/assets/19597087/4541e5f5-844d-4862-8745-bac3436de6ec
# Web Builder App
Web Builder App is a Streamlit-based application that allows users to upload an image, generate code based on the contents of the image, and view the code implementation.
## Table of Contents
- [Data Flow Diagram](#data-flow-diagram)
- [Getting Started](#getting-started)
- [Prerequisites](#prerequisites)
- [Installation](#installation)
- [Usage](#usage)
- [Running the Application](#running-the-application)
- [License](#license)
## Data Flow Diagram
## Getting Started
### Prerequisites
Make sure you have the following software installed on your machine:
- Python 3.8 or later
- Pytorch Cuda: CUDA Version >=11.8. Install from here - [Pytorch CUDA Installation](https://pytorch.org/)
### Installation From Github
---
1. Clone the repository:
```bash
git clone https://github.com/your-username/web-builder-app.git
cd web-builder-app
```
2. Create a virtual environment:
```bash
python -m venv env
```
3. Activate the virtual environment:
- For Windows:
```bash
.\env\Scripts\activate
```
- For Linux/Mac:
```bash
source env/bin/activate
```
4. Install dependencies:
```bash
pip install -r requirements.txt
```
5. Create .env file:
Create .env file and place your API keys in the file. A sample of how to do this is seen on the .env file
6. Alternative installation from Github using pip:
You can install the project using pip by running the command below:
```bash
pip install git+https://github.com/george-mountain/web-app-builder--LLM
```
## Usage
### Running the Application
To run the application locally:
```bash
streamlit run main.py
```
Visit the provided URL in your web browser to interact with the application.
## License
This project is licensed under the MIT License - see the [LICENSE](https://opensource.org/license/mit/) file for details.
```
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