Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,93 @@
-import altair as alt
-import numpy as np
-import pandas as pd
+# app.py
+
 import streamlit as st
+from PIL import Image
+import io
+
+import torch
+from transformers import AutoModel, AutoTokenizer
+
+@st.cache_resource(show_spinner=True)
+def load_model():
+    model = AutoModel.from_pretrained("openbmb/MiniCPM-V", trust_remote_code=True, torch_dtype=torch.bfloat16)
+    tokenizer = AutoTokenizer.from_pretrained("openbmb/MiniCPM-V", trust_remote_code=True)
+    # send to GPU/CPU as per availability
+    if torch.cuda.is_available():
+        model = model.to(device='cuda', dtype=torch.bfloat16)
+    else:
+        model = model.to(device='cpu')
+    model.eval()
+    return model, tokenizer
+
+model, tokenizer = load_model()
+
+st.set_page_config(page_title="MiniCPM-V Chat", layout="wide")
+st.title("📄 MiniCPM-V Chat — Image/Text → Markdown / Chat")
+
+if "history" not in st.session_state:
+    st.session_state.history = []
+
+# Sidebar: upload or text input
+with st.sidebar:
+    uploaded_file = st.file_uploader("Upload image / pdf-page (image) or enter text:", type=["jpg","jpeg","png","pdf","txt"])
+    text_input = st.text_area("Or paste text here:")
+
+# Main chat interface
+for msg in st.session_state.history:
+    with st.chat_message(msg["role"]):
+        st.markdown(msg["content"])
+
+def run_minicpm_v(input_image=None, input_text=None, history=None):
+    """
+    input_image: PIL.Image or None
+    input_text: str or None
+    history: list of prior messages (role, content)
+    """
+    msgs = []
+    if history:
+        msgs = history.copy()
+    # Compose new user message
+    user_content = ""
+    if input_image is not None:
+        user_content = "[Image Uploaded]\n"  # or some marker + optional prompt
+    if input_text:
+        user_content += input_text
+    msgs.append({"role": "user", "content": user_content})
+
+    # Run the multimodal chat
+    res, context, _ = model.chat(
+        image=input_image,
+        msgs=msgs,
+        context=None,
+        tokenizer=tokenizer,
+        sampling=True,
+        temperature=0.7,
+    )
+    return res
+
+if uploaded_file is not None or text_input:
+    with st.chat_message("user"):
+        if uploaded_file is not None:
+            st.image(uploaded_file, caption="Uploaded")
+        if text_input:
+            st.markdown(text_input)
+    # Process input
+    input_image = None
+    input_text = None
+    if uploaded_file is not None:
+        # try open as image
+        try:
+            input_image = Image.open(uploaded_file).convert("RGB")
+        except Exception as e:
+            st.error("Could not open uploaded file as image.")
+    if text_input:
+        input_text = text_input
+
+    with st.spinner("Thinking..."):
+        reply = run_minicpm_v(input_image=input_image, input_text=input_text, history=st.session_state.history)
+
+    st.session_state.history.append({"role": "assistant", "content": reply})
+    with st.chat_message("assistant"):
+        st.markdown(reply)
 
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+st.chat_input(placeholder="Send more text or upload another file…")  # optional extra prompt