app.py

import streamlit as st
from PIL import Image
from io import BytesIO
import requests
import os
from dotenv import load_dotenv
from groq import Groq

# Load environment variables from .env file
load_dotenv()

# Retrieve API URL and key from environment variables
API_URL = "https://vanceai.com/image-enhancer/?source=recomm"  # Replace with actual VanceAI API URL if different
API_KEY = "915a4d81c8c13b0e2a27a165f26159c2"  # Your VanceAI API key

# Streamlit UI
st.title("Image Enhancement Tool")

# Upload image
uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])

if uploaded_file is not None:
    # Open and display the uploaded image
    image = Image.open(uploaded_file)
    st.image(image, caption="Uploaded Image.", use_column_width=True)

    if st.button("Enhance Image"):
        # Convert image to bytes
        buffered = BytesIO()
        image.save(buffered, format="JPEG")
        img_bytes = buffered.getvalue()

        # Prepare the request
        headers = {
            "Authorization": f"Bearer {API_KEY}"
        }
        files = {
            "image": ("image.jpg", img_bytes, "image/jpeg")  # Adjust file name and type if needed
        }

        # Send the request to the image enhancement API
        try:
            response = requests.post(API_URL, headers=headers, files=files)
            response.raise_for_status()  # Raises HTTPError for bad responses

            # Convert the response content back to an image
            enhanced_image = Image.open(BytesIO(response.content))
            st.image(enhanced_image, caption="Enhanced Image", use_column_width=True)
        except requests.exceptions.RequestException as e:
            st.error(f"An error occurred: {str(e)}")

           



# Load environment variables from .env file
load_dotenv()

# Groq API Key
GROQ_API_KEY = os.getenv("IMAGE_ENHANCEMENT_API_KEY")

client = Groq(
    api_key=GROQ_API_KEY,
)

# Example usage
chat_completion = client.chat.completions.create(
    messages=[
        {
            "role": "user",
            "content": "Explain the importance of fast language models",
        }
    ],
    model="mixtral-8x7b-32768",
)

print(chat_completion.choices[0].message.content)