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app.py
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from dotenv import load_dotenv
import streamlit as st
import os
from PIL import Image
import google.generativeai as genai
# Load environment variables
load_dotenv()
# Configure Gemini API
genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
# ------------------ FUNCTIONS ------------------
def get_gemini_response(model_name, input_text, image, prompt):
"""Generate response using selected Gemini model"""
model = genai.GenerativeModel(model_name)
response = model.generate_content([input_text, image[0], prompt])
return response.text
def input_image_setup(uploaded_file):
"""Prepare image for Gemini API input"""
if uploaded_file is not None:
bytes_data = uploaded_file.getvalue()
image_parts = [
{
"mime_type": uploaded_file.type,
"data": bytes_data
}
]
return image_parts
else:
raise FileNotFoundError("No file uploaded")
# ------------------ STREAMLIT APP ------------------
st.set_page_config(page_title="Gemini Image Demo")
st.header("🧠 Gemini Multi-Doc Q&A Chatbot")
# Model selection
model_choice = st.selectbox(
"Choose a Gemini model:",
[
"gemini-2.5-pro",
"gemini-2.5-flash",
],
index=0
)
# Text input
input_text = st.text_input("Ask something about the image:", key="input")
# Image upload
uploaded_file = st.file_uploader("Upload an image...", type=["jpg", "jpeg", "png"])
image = ""
if uploaded_file is not None:
image = Image.open(uploaded_file)
st.image(image, caption="Uploaded Image", use_column_width=True)
# Button
submit = st.button("Generate Response")
# Instruction prompt
input_prompt = """
You are an expert in understanding invoices.
You will receive input images as invoices and answer questions based on the input image.
"""
# Generate response
if submit:
try:
image_data = input_image_setup(uploaded_file)
response = get_gemini_response(model_choice, input_text, image_data, input_prompt)
st.subheader("🧾 The Response:")
st.write(response)
except Exception as e:
st.error(f"⚠️ Error: {e}")