Create app.py

app.py

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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).to('cpu')
+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.")