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import streamlit as st
from groq import Groq
from PIL import Image
import base64
import io
import os
# Page Config
st.set_page_config(
page_title="AI Cooking Assistant",
page_icon="🍳",
layout="centered"
)
# Title
st.title("🍳 AI Cooking Assistant")
st.write("Upload ingredients image and get recipe suggestions")
# Load API Key
GROQ_API_KEY = os.getenv("GROQ_API_KEY")
if not GROQ_API_KEY:
st.error("❌ Please add GROQ_API_KEY in Hugging Face Secrets")
st.stop()
# Initialize Groq Client
client = Groq(api_key=GROQ_API_KEY)
# Convert Image to Base64
def image_to_base64(image):
buffer = io.BytesIO()
image.save(buffer, format="PNG")
return base64.b64encode(buffer.getvalue()).decode()
# File Uploader
uploaded_file = st.file_uploader(
"Upload Image of Ingredients",
type=["jpg", "jpeg", "png"]
)
if uploaded_file:
# Show Image
image = Image.open(uploaded_file)
st.image(image, caption="Uploaded Image")
if st.button("🍽️ Generate Recipe"):
with st.spinner("Analyzing ingredients..."):
# Convert image
img_base64 = image_to_base64(image)
# Prompt
prompt = """
You are a professional chef AI.
Look at the image and identify ingredients.
Then suggest:
1. Dish name
2. Ingredients list
3. Step-by-step recipe
4. Cooking tips
"""
# Call LLaMA Vision Model
response = client.chat.completions.create(
# model="llama-3.2-90b-vision-preview",
model = "meta-llama/llama-4-scout-17b-16e-instruct",
messages=[
{
"role": "user",
"content": [
{"type": "text", "text": prompt},
{
"type": "image_url",
"image_url": {
"url": f"data:image/png;base64,{img_base64}"
}
}
]
}
],
max_tokens=800
)
result = response.choices[0].message.content
# Display Output
st.subheader("🍲 Suggested Recipe")
st.write(result)
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