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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="π¨") | |
##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="π¨") | |
#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) |