import streamlit as st import os import pathlib import textwrap from PIL import Image import google.generativeai as genai os.getenv("GOOGLE_API_KEY") genai.configure(api_key=os.getenv("GOOGLE_API_KEY")) ## Function to load OpenAI model and get respones def get_gemini_response(input,image,prompt): model = genai.GenerativeModel('gemini-pro-vision') response = model.generate_content([input,image[0],prompt]) return response.text def input_image_setup(uploaded_file): # Check if a file has been uploaded if uploaded_file is not None: # Read the file into bytes bytes_data = uploaded_file.getvalue() image_parts = [ { "mime_type": uploaded_file.type, # Get the mime type of the uploaded file "data": bytes_data } ] return image_parts else: raise FileNotFoundError("No file uploaded") ##initialize our streamlit app st.set_page_config(page_title="Image description APP") st.header("Image description Application 🤖💬") input=st.text_input("Input Prompt: ",key="input") uploaded_file = st.file_uploader("Choose 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) submit=st.button("Tell me about the image") input_prompt = """ You are an expert in nutritionist where you need to see the food items from the image and calculate the total calories, also provide the details of every food items with calories intake is below format 1. Item 1 - no of calories 2. Item 2 - no of calories ---- ---- """ ## If ask button is clicked if submit: image_data = input_image_setup(uploaded_file) response=get_gemini_response(input_prompt,image_data,input) st.subheader("The Response is") st.write(response)