Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,47 @@
-import altair as alt
-import numpy as np
-import pandas as pd
+# app.py
 import streamlit as st
-
+from transformers import pipeline
+
+# -------------------------
+# Load model
+# -------------------------
+@st.cache_resource
+def load_model():
+    # Using FLAN-T5 (free, light, works well on Spaces CPU)
+    return pipeline(
+        "text2text-generation",
+        model="google/flan-t5-base"
+    )
+
+model = load_model()
+
+# -------------------------
+# Streamlit UI
+# -------------------------
+st.set_page_config(page_title="Prescription Chatbot", page_icon="💊")
+
+st.title("💊 Prescription Chatbot (Demo)")
+st.caption("Academic demo only — not medical advice")
+
+symptoms = st.text_area("Enter your symptoms:", "I have flu, body pain and runny nose")
+
+if st.button("Get Prescription"):
+    if symptoms.strip():
+        prompt = f"""
+You are a helpful medical-assistant for an academic demo only. 
+The patient reports: {symptoms}.
+
+Task: Provide a short structured response with:
+1. Most likely condition(s)
+2. Suggested non-prescription remedies
+3. Precautions and red-flags
+4. Disclaimer: This is a demo only — not medical advice.
 """
-# 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:
-"""
+        output = model(prompt, max_length=256, do_sample=False)
+        reply = output[0]["generated_text"].strip()
 
-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.subheader("Suggested Result (Demo)")
+        st.write(reply)
+    else:
+        st.warning("Please enter symptoms first.")