Update app.py

app.py

@@ -56,38 +56,41 @@ from fpdf import FPDF
 recognizer = sr.Recognizer()
 engine = pyttsx3.init()
 
+# Function to listen to voice input
 def listen_to_voice():
     """Listen to audio and convert to text."""
-    with sr.Microphone() as source:
-        st.write("Listening for symptoms (speak now)...")
-        try:
+    try:
+        with sr.Microphone() as source:
+            st.write("Listening for symptoms (speak now)...")
             audio = recognizer.listen(source, timeout=5, phrase_time_limit=10)
             text = recognizer.recognize_google(audio)
             st.write(f"You said: {text}")
             return text
-        except sr.UnknownValueError:
-            st.write("Sorry, I did not understand the audio.")
-            return ""
-        except sr.RequestError as e:
-            st.write(f"Could not request results from Google Speech Recognition service; {e}")
-            return ""
-        except Exception as e:
-            st.write(f"Error: {str(e)}")
-            return ""
-
+    except sr.UnknownValueError:
+        st.write("Sorry, I did not understand the audio.")
+        return ""
+    except sr.RequestError as e:
+        st.write(f"Could not request results from Google Speech Recognition service; {e}")
+        return ""
+    except Exception as e:
+        st.write(f"Error: {str(e)}")
+        return ""
+
+# Text-to-speech function
 def tts(text):
     """Convert text to speech."""
     engine.say(text)
     engine.runAndWait()
 
+# Dummy disease prediction based on symptoms
 def predict_disease(symptoms):
     """Mock prediction of disease based on symptoms."""
-    # Dummy response for demo purposes
     if 'fever' in symptoms.lower():
         return "You might have the flu."
     else:
         return "No prediction available."
 
+# Function to generate PDF
 def generate_pdf(content):
     """Generate PDF with the given content."""
     pdf = FPDF()
@@ -99,19 +102,23 @@ def generate_pdf(content):
     pdf.output(pdf_file)
     return pdf_file
 
-# Streamlit App
-st.title("Medical Assistance for Doctors (Voice and Text)")
+# Streamlit App Interface
+st.title("Medical Assistance for Doctors")
 
-# Step 1: Doctor inputs symptoms through voice or typing
+# Step 1: Input Symptoms via Text Box with a voice input icon
 st.header("Enter Symptoms")
-symptoms = ""
-if st.button("Use Voice Input for Symptoms"):
-    symptoms = listen_to_voice()
 
-typed_symptoms = st.text_area("Or Enter Symptoms Using Keyboard:", symptoms)
-if typed_symptoms:
-    symptoms = typed_symptoms
+# Display a text input box with a microphone button next to it
+col1, col2 = st.columns([5, 1])  # Create a layout with 5:1 ratio for text input and button
+
+with col1:
+    symptoms = st.text_area("Enter Symptoms Using Keyboard:")
+
+with col2:
+    if st.button("🎤"):
+        symptoms = listen_to_voice()  # Capture voice input when the mic icon is pressed
 
+# Display entered symptoms
 if symptoms:
     st.write(f"Entered Symptoms: {symptoms}")
 
@@ -120,42 +127,47 @@ if st.button("Predict Disease"):
     prediction = predict_disease(symptoms)
     st.write(f"Prediction: {prediction}")
     
-    # Step 3: Allow editing through text or voice
+    # Step 3: Edit Response via Voice or Text
     st.header("Edit Response (Optional)")
-    if st.button("Edit Response Using Voice"):
-        edited_response = listen_to_voice()
-        if edited_response:
-            prediction = edited_response
-    else:
+    
+    # Mic button for editing response through voice
+    col3, col4 = st.columns([5, 1])
+    
+    with col3:
         edited_response = st.text_area("Or Edit Response Using Keyboard:", prediction)
-        if edited_response:
-            prediction = edited_response
-
-    # Final Response
+    
+    with col4:
+        if st.button("🎤 Edit by Voice"):
+            edited_response = listen_to_voice()  # Voice editing
+            
+    if edited_response:
+        prediction = edited_response
+
+    # Display the final response
     st.write(f"Final Response: {prediction}")
     
-    # Option to listen to the final response
+    # Text-to-speech option for the final response
     if st.button("Play Final Response"):
         tts(prediction)
 
-    # Step 4: Generate PDF
-    st.header("Generate PDF Report")
+    # Step 4: Generate and Download PDF
+    st.header("Generate and Download PDF Report")
     content = f"Symptoms: {symptoms}\nPrediction: {prediction}"
+
     if st.button("Generate PDF"):
         pdf_file = generate_pdf(content)
         st.success(f"PDF report generated successfully: {pdf_file}")
 
-    # Step 5: Download PDF
-    with open(pdf_file, "rb") as file:
-        st.download_button(
-            label="Download Medical Report",
-            data=file,
-            file_name="medical_report.pdf",
-            mime="application/pdf"
-        )
+        # Option to download the PDF file
+        with open(pdf_file, "rb") as file:
+            st.download_button(
+                label="Download Medical Report",
+                data=file,
+                file_name="medical_report.pdf",
+                mime="application/pdf"
+            )
 
 # Run Streamlit App
 if __name__ == "__main__":
     st.write("Welcome to the medical assistance system.")
 
-