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import streamlit as st
import requests
import base64
import os
# Function to convert image to base64
def convert_image_to_base64(image):
image_bytes = image.read()
encoded_image = base64.b64encode(image_bytes).decode("utf-8")
return encoded_image
# Function to generate a caption using Nebius API
def generate_caption(encoded_image):
API_URL = "https://api.studio.nebius.ai/v1/chat/completions"
API_KEY = os.environ.get("NEBIUS_API_KEY")
headers = {
"Authorization": f"Bearer {API_KEY}",
"Content-Type": "application/json"
}
payload = {
"model": "Qwen/Qwen2-VL-7B-Instruct",
"messages": [
{
"role": "system",
"content": """You are an image to prompt converter. Your work is to observe each and every detail of the image and craft a detailed prompt under 75 words in this format: [image content/subject, description of action, state, and mood], [art form, style], [artist/photographer reference if needed], [additional settings such as camera and lens settings, lighting, colors, effects, texture, background, rendering]."""
},
{
"role": "user",
"content": "write a detailed caption for this image"
}
],
"image": {
"type": "image_url",
"image_url": {
"url": f"data:image/png;base64,{encoded_image}"
}
},
"temperature": 0
}
response = requests.post(API_URL, headers=headers, json=payload)
if response.status_code == 200:
result = response.json()
caption = result.get("choices", [{}])[0].get("message", {}).get("content", "No caption generated.")
return caption
else:
st.error(f"API Error {response.status_code}: {response.text}")
return None
# Streamlit app
def main():
st.set_page_config(page_title="Image to Caption Converter", layout="centered", initial_sidebar_state="collapsed")
st.title("🖼️ Image to Caption Converter")
st.markdown("Upload an image and let the AI generate a detailed caption for it.")
uploaded_file = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
if uploaded_file:
# Display the uploaded image
st.image(uploaded_file, caption="Uploaded Image", use_container_width=True)
# Convert image to base64 and get caption
if st.button("Generate Caption"):
with st.spinner("Generating caption..."):
encoded_image = convert_image_to_base64(uploaded_file)
caption = generate_caption(encoded_image)
if caption:
st.subheader("Generated Caption:")
st.text_area("", caption, height=100, key="caption_area")
# Copy button
st.button("Copy to Clipboard", on_click=lambda: st.session_state.update({"caption": caption}))
if __name__ == "__main__":
main()
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