app.py

# app.py
import requests
import gradio as gr

# Hugging Face Inference API configuration
HF_API_KEY = "your_huggingface_api_key"  # Replace with your Hugging Face API key
HF_API_URL = f"https://api-inference.huggingface.co/models/codeparrot/codeparrot-small"

# Groq API configuration
GROQ_API_KEY = "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"
GROQ_API_URL = "https://api.groq.com/v1/completions"

# Function to query Hugging Face Inference API
def query_huggingface(prompt):
    try:
        headers = {
            "Authorization": f"Bearer {HF_API_KEY}",
            "Content-Type": "application/json"
        }
        data = {
            "inputs": prompt,
            "parameters": {
                "max_length": 150  # Limit the length of the generated text
            }
        }
        response = requests.post(HF_API_URL, headers=headers, json=data, timeout=30)  # Add timeout
        response.raise_for_status()  # Raise an error for bad responses (4xx, 5xx)
        return response.json()[0]["generated_text"]
    except Exception as e:
        return f"Error querying Hugging Face API: {str(e)}"

# Function to query Groq API
def query_groq(prompt):
    try:
        headers = {
            "Authorization": f"Bearer {GROQ_API_KEY}",
            "Content-Type": "application/json"
        }
        data = {
            "prompt": prompt,
            "max_tokens": 150
        }
        response = requests.post(GROQ_API_URL, headers=headers, json=data, timeout=10)  # Add timeout
        response.raise_for_status()  # Raise an error for bad responses (4xx, 5xx)
        return response.json()["choices"][0]["text"]
    except Exception as e:
        return f"Error querying Groq API: {str(e)}"

# Function to generate smart contract code
def generate_smart_contract(language, requirements):
    try:
        # Create a prompt for the model
        prompt = f"Generate a {language} smart contract with the following requirements: {requirements}"
        
        # Use Hugging Face Inference API to generate code
        generated_code = query_huggingface(prompt)
        
        # Enhance the code using Groq API
        enhanced_code = query_groq(generated_code)
        
        return enhanced_code
    except Exception as e:
        return f"Error generating smart contract: {str(e)}"

# Custom CSS for a 3D CGI Figma-like feel
custom_css = """
body {
    font-family: 'Helvetica Neue', Helvetica, Arial, sans-serif;
    background: linear-gradient(135deg, #1e3c72 0%, #2a5298 100%);
    color: #fff;
    perspective: 1000px;
    overflow: hidden;
}

.gradio-container {
    background: rgba(255, 255, 255, 0.1);
    border-radius: 15px;
    padding: 20px;
    box-shadow: 0 4px 30px rgba(0, 0, 0, 0.1);
    backdrop-filter: blur(10px);
    border: 1px solid rgba(255, 255, 255, 0.3);
    transform-style: preserve-3d;
    transform: rotateY(0deg) rotateX(0deg);
    transition: transform 0.5s ease;
}

.gradio-container:hover {
    transform: rotateY(10deg) rotateX(10deg);
}

.gradio-input, .gradio-output {
    background: rgba(255, 255, 255, 0.2);
    border: none;
    border-radius: 10px;
    padding: 10px;
    color: #fff;
    transform-style: preserve-3d;
    transition: transform 0.3s ease;
}

.gradio-input:focus, .gradio-output:focus {
    background: rgba(255, 255, 255, 0.3);
    outline: none;
    transform: translateZ(20px);
}

.gradio-button {
    background: linear-gradient(135deg, #6a11cb 0%, #2575fc 100%);
    border: none;
    border-radius: 10px;
    color: #fff;
    padding: 10px 20px;
    font-size: 16px;
    cursor: pointer;
    transition: background 0.3s ease, transform 0.3s ease;
    transform-style: preserve-3d;
}

.gradio-button:hover {
    background: linear-gradient(135deg, #2575fc 0%, #6a11cb 100%);
    transform: translateZ(10px);
}

h1 {
    text-align: center;
    font-size: 2.5em;
    margin-bottom: 20px;
    color: white; /* White title color */
    transform-style: preserve-3d;
    transform: translateZ(30px);
}

@keyframes float {
    0% {
        transform: translateY(0) translateZ(0);
    }
    50% {
        transform: translateY(-10px) translateZ(10px);
    }
    100% {
        transform: translateY(0) translateZ(0);
    }
}

.gradio-container {
    animation: float 4s ease-in-out infinite;
}
"""

# Gradio interface for the app
def generate_contract(language, requirements):
    return generate_smart_contract(language, requirements)

# Dropdown options for programming languages
languages = ["Solidity", "Vyper", "Rust", "JavaScript", "Python"]

interface = gr.Interface(
    fn=generate_contract,
    inputs=[
        gr.Dropdown(label="Programming Language", choices=languages, value="Solidity"),  # Dropdown menu
        gr.Textbox(label="Requirements", placeholder="e.g., ERC20 token with minting functionality")
    ],
    outputs=gr.Textbox(label="Generated Smart Contract"),
    title="Smart Contract Generator",
    description="Generate smart contracts using AI.",
    css=custom_css
)

# Launch the Gradio app
if __name__ == "__main__":
    interface.launch()