app.py

app.py

@@ -0,0 +1,20 @@
+import streamlit as st
+from transformers import pipeline
+
+# Load open-source model (BioGPT for medical Q&A)
+@st.cache_resource
+def load_model():
+    return pipeline("text-generation", model="microsoft/BioGPT-Large")
+
+st.set_page_config(page_title="Prescription Bot", page_icon="💊", layout="centered")
+
+st.title("💊 AI Prescription Assistant")
+st.write("Describe your symptoms, and I will suggest possible advice and treatment.")
+
+user_input = st.text_area("📝 Your symptoms:")
+
+if st.button("Get Prescription") and user_input:
+    generator = load_model()
+    response = generator(user_input, max_length=200, do_sample=True, temperature=0.7)
+    st.markdown("### 🩺 Suggested Advice")
+    st.write(response[0]['generated_text'])