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import os
import openai
import streamlit as st
from dotenv import load_dotenv
from PIL import Image
from blip_model import extract_image_details
from gpt_model import generate_response
# Load environment variables from .env file
load_dotenv()
# Set OpenAI API key
openai.api_key = os.getenv('api_key')
# Initialize session state for image details
if "image_details" not in st.session_state:
st.session_state.image_details = ""
st.title("Image to Text Response with RAG")
# File uploader for image upload
uploaded_file = st.file_uploader("Upload an Image", type=["jpg", "jpeg", "png"])
if uploaded_file is not None:
if "uploaded_file" not in st.session_state or uploaded_file != st.session_state.uploaded_file:
st.session_state.uploaded_file = uploaded_file
# Clear previous messages
st.session_state.messages = []
# Show loading status while processing the image
with st.status("Processing image...", state="running"):
image = Image.open(uploaded_file)
st.session_state.image_details = extract_image_details(image)
st.success("Image processed successfully.")
else:
st.stop()
# Chat interface
if st.session_state.image_details:
st.write("### Ask a question about the image")
if "messages" not in st.session_state:
st.session_state.messages = []
# Display chat messages
for message in st.session_state.messages:
with st.chat_message(message["role"]):
st.write(message["content"])
# Chat input
prompt = st.chat_input("Ask something about the image")
if prompt:
# Add user message to session state
st.session_state.messages.append({"role": "user", "content": prompt})
# Generate response
response = generate_response([st.session_state.image_details], prompt)
st.session_state.messages.append({"role": "assistant", "content": response})
# Display user message
with st.chat_message("user"):
st.write(prompt)
# Display assistant message
with st.chat_message("assistant"):
st.write(response)
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