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import streamlit as st
from PIL import Image
import google.generativeai as genai
import os
MODEL_ID = "gemini-2.0-flash-exp"
api_key = os.getenv("GEMINI_API_KEY")
model_id = MODEL_ID
genai.configure(api_key=api_key)
# Initialize chat history
if "messages" not in st.session_state:
st.session_state.messages = []
if "model" not in st.session_state:
st.session_state.model = genai.GenerativeModel(MODEL_ID)
model = st.session_state.model
# Function to reset chat history
def reset_chat():
st.session_state.messages = []
model.start_chat()
# Streamlit app
st.title("Gemini Image Chat")
# File uploader with allowed types
uploaded_file = st.file_uploader("Choose an image or PDF...", type=["jpg", "jpeg", "png", "pdf"])
if uploaded_file is not None:
# Determine file type
file_type = uploaded_file.type
if file_type.startswith('image'):
# Display the uploaded image
image = Image.open(uploaded_file)
st.image(image, caption="Uploaded Image.", use_container_width=True)
mime_type = "image/jpeg" # Use a consistent MIME type for images
elif file_type == 'application/pdf':
# Display a message for PDF upload
st.write("PDF file uploaded. You can ask questions about its content.")
mime_type = "application/pdf"
else:
st.error("Unsupported file type. Please upload an image or PDF.")
st.stop()
# Reset chat history when a new file is uploaded
reset_chat()
# Text input for user prompt
user_input = st.text_input("Enter your prompt:")
# Send button
if st.button("Send"):
if user_input:
# Add user message to chat history
st.session_state.messages.append({"role": "user", "content": user_input})
# Display chat history
for message in st.session_state.messages:
with st.chat_message(message["role"]):
st.markdown(message["content"])
with st.spinner("Processing..."):
# Upload the file with the correct MIME type
file_data = genai.upload_file(uploaded_file, mime_type=mime_type)
# Send file and prompt to Gemini API
response = model.generate_content(
[
user_input,
file_data
]
)
# Add Gemini response to chat history
st.session_state.messages.append({"role": "assistant", "content": response.text})
# Display Gemini response
with st.chat_message("assistant"):
st.markdown(response.text) |