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import streamlit as st
from dotenv import load_dotenv
import os
from groq import Groq
import base64
from PIL import Image
import io
# Set page config
st.set_page_config(
page_title="Image Analysis with AI",
page_icon="🖼️",
layout="centered"
)
# Add title and description
st.title("AI Image Analysis")
st.markdown("Upload an image or provide an image URL to get AI-generated commentary.")
# Load environment variables
load_dotenv()
# Initialize Groq client with the correct configuration
api_key = os.getenv("GROQ_API_KEY")
if not api_key:
st.error("Please set your GROQ_API_KEY in the .env file")
st.stop()
client = Groq(
api_key=api_key
)
# Create input field for image URL
image_url = st.text_input("Enter Image URL", "https://static.seekingalpha.com/uploads/2016/1/19/saupload_fredgraph.jpg")
# Add a file uploader
uploaded_file = st.file_uploader("Or upload an image", type=["jpg", "jpeg", "png"])
def get_image_url():
if uploaded_file is not None:
# Convert uploaded file to base64
image = Image.open(uploaded_file)
buffered = io.BytesIO()
image.save(buffered, format="PNG")
img_str = base64.b64encode(buffered.getvalue()).decode()
return f"data:image/png;base64,{img_str}"
return image_url
# Add a button to trigger analysis
if st.button("Analyze Image"):
try:
# Show loading spinner
with st.spinner("Analyzing image..."):
current_image_url = get_image_url()
# Create the completion request
completion = client.chat.completions.create(
model="meta-llama/llama-4-scout-17b-16e-instruct", # Updated model name
messages=[
{
"role": "user",
"content": [
{
"type": "text",
"text": "Write a detailed commentary on the trend observed in the image?"
},
{
"type": "image_url",
"image_url": {
"url": current_image_url
}
}
]
}
],
temperature=1,
max_tokens=300, # Updated parameter name
top_p=1,
stream=False
)
# Display the image
if uploaded_file is not None:
st.image(uploaded_file, caption="Analyzed Image", use_column_width=True)
else:
st.image(image_url, caption="Analyzed Image", use_column_width=True)
# Display the analysis
st.subheader("AI Analysis")
st.write(completion.choices[0].message.content)
except Exception as e:
st.error(f"An error occurred: {str(e)}")
# Add footer
st.markdown("---")
st.markdown("Built with Streamlit and Groq AI") |