u

app.py

@@ -1,25 +1,80 @@
-# Chatbot Section
-st.subheader("AI Chatbot: Ask Anything About Your Report or Medical Terms")
-
-if 'summary' in st.session_state and 'explanation' in st.session_state:
-    user_question = st.text_input("Ask a question (e.g. 'meaning of CT scan', 'explain cholecystectomy'):")
-
-    if st.button("Get AI Answer") and user_question:
-        with st.spinner("Thinking..."):
-            context = st.session_state['summary'] + "\n" + st.session_state['explanation']
-            prompt = (
-                f"You are a helpful medical assistant. "
-                f"If the report context below doesn't help, use your general medical knowledge.\n\n"
-                f"Context:\n{context}\n\n"
-                f"Question: What is the meaning of '{user_question}'?\n"
-                f"Explain it simply as if talking to a non-medical person."
-            )
-            response = explainer(prompt)[0]['generated_text']
-
-        st.success("AI's Response:")
-        st.write(response)
-
-        if len(response.strip()) < 10:
-            st.info("The report might not contain this term, but the AI gave a general medical explanation.")
+import streamlit as st
+import fitz  # PyMuPDF
+from transformers import pipeline
+from datetime import datetime
+
+st.set_page_config(page_title="Health Report Analyzer", page_icon="🩺")
+st.title("🩺 Health Report Analyzer")
+
+# Upload PDF
+uploaded_file = st.file_uploader("Upload a Health Report (PDF only)", type="pdf")
+
+# Extract text from PDF
+def extract_text(file):
+    doc = fitz.open(stream=file.read(), filetype="pdf")
+    text = ""
+    for page in doc:
+        text += page.get_text()
+    return text
+
+# Load Hugging Face Models
+@st.cache_resource
+def load_models():
+    summarizer = pipeline("summarization", model="philschmid/bart-large-cnn-samsum")
+    explainer = pipeline("text2text-generation", model="google/flan-t5-base")
+    return summarizer, explainer
+
+# MAIN LOGIC
+if uploaded_file:
+    text_data = extract_text(uploaded_file)
+    st.success("PDF Text Extracted Successfully!")
+    st.text_area("Extracted Text", text_data, height=300)
+
+    summarizer, explainer = load_models()
+
+    if st.button("Summarize & Explain"):
+        with st.spinner("Generating Summary & Explanation..."):
+            chunks = [text_data[i:i+1000] for i in range(0, len(text_data), 1000)]
+            
+            summary = ""
+            for chunk in chunks:
+                result = summarizer(chunk, max_length=300, min_length=80, do_sample=False)
+                summary += result[0]['summary_text'] + " "
+
+            explanation = explainer(f"Explain in simple words: {summary}")[0]['generated_text']
+
+        st.subheader("Summary")
+        st.write(summary)
+
+        st.subheader("Explanation")
+        st.write(explanation)
+
+        st.session_state['summary'] = summary
+        st.session_state['explanation'] = explanation
+
+    # Chatbot Section
+    st.subheader("AI Chatbot: Ask Anything About Your Report or Medical Terms")
+
+    if 'summary' in st.session_state and 'explanation' in st.session_state:
+        user_question = st.text_input("Ask a question (e.g. 'meaning of CT scan', 'explain cholecystectomy'):")
+
+        if st.button("Get AI Answer") and user_question:
+            with st.spinner("Thinking..."):
+                context = st.session_state['summary'] + "\n" + st.session_state['explanation']
+                prompt = (
+                    f"You are a helpful medical assistant. "
+                    f"If the report context below doesn't help, use your general medical knowledge.\n\n"
+                    f"Context:\n{context}\n\n"
+                    f"Question: What is the meaning of '{user_question}'?\n"
+                    f"Explain it simply as if talking to a non-medical person."
+                )
+                response = explainer(prompt)[0]['generated_text']
+
+            st.success("AI's Response:")
+            st.write(response)
+
+    else:
+        st.info("Generate Summary & Explanation to activate chatbot.")
+
 else:
-    st.info("Generate Summary & Explanation to activate chatbot.")
+    st.info("Upload a PDF Health Report to begin.")