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import streamlit as st
import subprocess
from PIL import Image
import requests
from io import BytesIO
from transformers import AutoModel, AutoTokenizer
import torch
torch.cuda.empty_cache()
# Load the model and tokenizer on CPU
model = AutoModel.from_pretrained('openbmb/MiniCPM-Llama3-V-2_5-int4', trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained('openbmb/MiniCPM-Llama3-V-2_5-int4', trust_remote_code=True)
model.eval()
# Title of the app
st.title("Streamlit App with Image URL and Prompts")
# Text area for image URL
image_url = st.text_area("Enter Image URL:")
# Text area for system prompt input
system_prompt = st.text_area("Enter System Prompt:")
# Text area for user prompt input
question = st.text_area("Enter User Prompt:")
# Button to submit and display the image
if st.button("Submit"):
if image_url:
try:
subprocess.run(['wget', image_url, "-O", 'flowchart.png'])
response = requests.get(image_url)
img = Image.open(BytesIO(response.content))
st.image(img, caption="Image from URL")
except Exception as e:
st.error(f"Error loading image. Please submit another image URL with a .png or .jpg extension: {e}")
else:
st.warning("Please enter an image URL.")
# Model code
if system_prompt and question:
image = Image.open('flowchart.png').convert('RGB')
msgs = [{'role': 'user', 'content': question}]
res = model.chat(
image=image,
msgs=msgs,
tokenizer=tokenizer,
sampling=True, # if sampling=False, beam_search will be used by default
temperature=0.7,
system_prompt=system_prompt # pass system_prompt if needed
)
st.text_area("Output:", value=res, height=200)
else:
st.warning("Please enter both system prompt and user prompt.")
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