up

app.py

@@ -1,7 +1,11 @@
 import streamlit as st
 import fitz  # PyMuPDF
 from transformers import pipeline
-from datetime import datetime
+from gtts import gTTS
+import base64
+import os
+from fpdf import FPDF
+import urllib.parse
 
 # Streamlit page setup
 st.set_page_config(page_title="Health Report Analyzer", page_icon="🩺")
@@ -18,64 +22,98 @@ def extract_text(file):
         text += page.get_text()
     return text
 
-# Load models from HuggingFace
+# Load Hugging Face model for medical explanation
 @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
+def load_explainer():
+    return pipeline("text2text-generation", model="google/flan-t5-base")
+
+# Text-to-Speech helper
+def text_to_speech_base64(text):
+    tts = gTTS(text)
+    tts.save("response.mp3")
+    with open("response.mp3", "rb") as audio_file:
+        audio_bytes = audio_file.read()
+    b64 = base64.b64encode(audio_bytes).decode()
+    audio_html = f"""
+    <audio controls autoplay>
+        <source src="data:audio/mp3;base64,{b64}" type="audio/mp3">
+        Your browser does not support the audio element.
+    </audio>
+    """
+    return audio_html
+
+# PDF Export helper
+def generate_pdf(name, explanation_text):
+    pdf = FPDF()
+    pdf.add_page()
+    pdf.set_font("Arial", "B", 16)
+    pdf.cell(200, 10, "Medical Explanation", ln=True, align="C")
+    pdf.ln(10)
+    pdf.set_font("Arial", size=12)
+    pdf.multi_cell(0, 10, explanation_text)
+    filename = f"{name.replace(' ', '_')}_Explanation.pdf"
+    pdf.output(filename)
+    return filename
 
 # 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)
-
-        # Store in session
-        st.session_state['summary'] = summary
-        st.session_state['explanation'] = explanation
-
-    # AI Chatbot
-    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("Please generate the summary and explanation first to enable the chatbot.")
+    st.success("Health Report Uploaded Successfully!")
+
+    st.markdown("### 📄 Health Report Content")
+    st.write(text_data)
+
+    explainer = load_explainer()
+    st.session_state['report_text'] = text_data
+
+    st.subheader("💬 Ask About Any Medical Term or Part of the Report")
+
+    user_question = st.text_input("Enter a medical term or question (e.g. 'CT scan', 'Explain creatinine'):")    
+
+    if st.button("Get AI Explanation") and user_question:
+        with st.spinner("Thinking..."):
+
+            prompt = (
+                f"You are a helpful medical assistant. "
+                f"Please explain the following medical term or phrase in very simple words, "
+                f"as if you're talking to someone with no medical background.\n\n"
+                f"Health Report Content:\n{st.session_state['report_text']}\n\n"
+                f"Term or Question: {user_question}\n\n"
+                f"Give a clear, beginner-friendly explanation."
+            )
+
+            response = explainer(prompt)[0]['generated_text']
+
+        st.success("Explanation:")
+        st.write(response)
+
+        st.markdown("🔊 **Hear the Explanation**")
+        audio_html = text_to_speech_base64(response)
+        st.markdown(audio_html, unsafe_allow_html=True)
+
+        if os.path.exists("response.mp3"):
+            os.remove("response.mp3")
+
+        st.markdown("---")
+        st.subheader("📤 Export or Share This Explanation")
+
+        user_name = st.text_input("Enter your name to personalize export", value="Patient")
+
+        # PDF Export
+        if st.button("📄 Download as PDF"):
+            pdf_file = generate_pdf(user_name, response)
+            with open(pdf_file, "rb") as f:
+                st.download_button("Download PDF", f, file_name=pdf_file, mime="application/pdf")
+            os.remove(pdf_file)
+
+        # WhatsApp Share
+        whatsapp_msg = urllib.parse.quote(f"Hey! I just got this medical explanation:\n\n{response}")
+        whatsapp_url = f"https://wa.me/?text={whatsapp_msg}"
+        st.markdown(f"[💬 Share via WhatsApp]({whatsapp_url})", unsafe_allow_html=True)
+
+        # Email Copy
+        st.markdown("📧 Copy this text for email:")
+        st.code(f"Subject: Medical Report Explanation\n\nHello,\n\nI wanted to share this:\n\n{response}", language="text")
 
 else:
     st.info("Upload a PDF Health Report to begin.")