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import streamlit as st
import requests
import base64
# FastAPI endpoint
API_URL = "https://dvorakinnovationai-revel-rizz-api.hf.space/api/reply-generator"
# API_URL = "http://127.0.0.1:8000//api/reply-generator"
st.set_page_config(page_title="Reply Generator", page_icon="💬", layout="centered")
st.title("Reply Generator")
st.write("Upload image of chat , ask a question, and get AI-powered replies.")
# Upload image
uploaded_file = st.file_uploader("Upload an image (JPG/PNG)", type=["jpg", "jpeg", "png"])
# User query input
# Tones (multi-select)
available_tones = ["formal", "casual", "friendly", "professional", "humorous"]
tones = st.multiselect("Select tones (optional)", available_tones)
# Button to trigger API
if st.button("Generate Reply"):
if uploaded_file is None:
st.error("⚠️ Please upload an image first.")
else:
try:
# Convert image to base64
image_bytes = uploaded_file.read()
image_base64 = base64.b64encode(image_bytes).decode("utf-8")
payload = {
"image_base64": image_base64,
"tones": tones if tones else None,
}
with st.spinner("⏳ Generating reply..."):
response = requests.post(API_URL, json=payload)
if response.status_code == 200:
data = response.json()
st.success("✅ Reply generated successfully!")
st.write("### Response:")
st.json(response.json())
else:
st.error(f"❌ Error: {response.status_code} - {response.text}")
except Exception as e:
st.error(f"🚨 An error occurred: {str(e)}")
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