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from dotenv import load_dotenv
load_dotenv() # take environment variables from .env.
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")
st.error('Please upload an image', icon="🚨")
##initialize our streamlit app
st.set_page_config(page_title="Image Chat")
st.header("Upload an Image and begin to chat")
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)
# input=st.text_input("Input Prompt: ",key="input")
# if input is None:
# st.error('Please add an input', icon="🚨")
#submit=st.button("Run")
input_prompt = """
Analyze the image and give user a very descriptive information on the details in the image
"""
## If ask button is clicked
if 'messages' not in st.session_state:
st.session_state['messages'] = [] #[{"role": "assistant", "content": "How can I help you?"}]
for msg in st.session_state.messages:
st.chat_message(msg["role"]).write(msg["content"])
if prompt := st.chat_input():
# if not openai_api_key:
# st.info("Please add your OpenAI API key to continue.")
# st.stop()
#client = OpenAI(api_key=openai_api_key)
#client = OpenAI()
image_data = input_image_setup(uploaded_file)
st.session_state.messages.append({"role": "user", "content": prompt})
st.chat_message("user").write(prompt)
#response = client.chat.completions.create(model="google/gemma-2b-it", messages=st.session_state.messages)
response=get_gemini_response(input_prompt,image_data,prompt)
msg = response #response.choices[0].message.content
st.session_state.messages.append({"role": "assistant", "content": msg})
st.chat_message("assistant").write(msg) |