Update app.py

app.py

@@ -12,7 +12,7 @@ import io
 import speech_recognition as sr
 from gtts import gTTS
 import os
-import sounddevice as sd
+
 
 
 # Download NLTK resources
@@ -106,6 +106,32 @@ st.markdown("""
     </style>
     """, unsafe_allow_html=True)
 
+st.markdown("""
+    <script>
+    function startRecording() {
+        var recognition = new webkitSpeechRecognition() || new SpeechRecognition();
+        recognition.lang = 'en-US';
+        recognition.interimResults = false;
+        recognition.maxAlternatives = 1;
+        
+        recognition.onresult = function(event) {
+            var transcript = event.results[0][0].transcript;
+            var questionInput = document.getElementById("question_input");
+            questionInput.value = transcript;
+            questionInput.dispatchEvent(new Event('input', { bubbles: true }));
+        };
+
+        recognition.onerror = function(event) {
+            alert("Error occurred: " + event.error);
+        };
+
+        recognition.start();
+    }
+    </script>
+""", unsafe_allow_html=True)
+
+
+
 # App title and description
 st.title("📰 Daily Mirror News Analyzer")
 st.markdown("""
@@ -183,9 +209,11 @@ with tab2:
         st.warning("Please upload a CSV file.")
    
     
-    question = st.text_input("Enter your question:")
-
-    recognizer = sr.Recognizer()
+    # Input field for voice/text-based questions
+    question = st.text_input("Enter your question:", key="question_input")
+    
+    # Button to start voice recording
+    st.button("🎙 Speak", on_click=lambda: st.markdown('<script>startRecording()</script>', unsafe_allow_html=True))
 
  
     
@@ -202,30 +230,6 @@ with tab2:
 
             
 
-    if st.button("🎤 Ask Question via Mic"):
-        with sr.Microphone() as source:
-            st.info("Listening...")
-            try:
-                audio = recognizer.listen(source, timeout=5)
-                question = recognizer.recognize_google(audio)
-                st.success(f"Question: {question}")
-    
-                if uploaded_file is not None:
-                    context = ' '.join(df['content'].tolist())  # Extracted from uploaded news data
-                    qa_pipeline = load_qa_model()
-                    result = qa_pipeline(question=question, context=context)
-    
-                    st.subheader("📝 Answer")
-                    st.success(result['answer'])
-                    st.write(f"Confidence: {result['score']:.2f}")
-                else:
-                    st.warning("Please upload a CSV file first.")
-    
-            except sr.UnknownValueError:
-                st.error("Sorry, could not understand the question. Please try again.")
-            except sr.RequestError:
-                st.error("Speech Recognition API is unavailable.")
-       
             
 
 with tab3: