Update requirements.txt

requirements.txt

@@ -1,12 +1,139 @@
-streamlit==1.28.0
-requests>=2.31.0
-transformers
-transformers>=4.25.0
-torch>=1.10.0
-accelerate>=0.18.0
-huggingface_hub==0.25.2
-python-dotenv>=1.0.0
-
-numpy>=1.24.0
-audio-recorder-streamlit
-torchaudio>=2.0.0
+import gradio as gr
+import speech_recognition as sr
+from time import time
+import threading
+from pydub import AudioSegment
+from pydub.playback import play
+import io
+
+# Global variables
+is_recording = False
+start_beep = AudioSegment.silent(duration=200).append(AudioSegment.from_wav(io.BytesIO(b''), crossfade=100)
+end_beep = AudioSegment.silent(duration=200).append(AudioSegment.from_wav(io.BytesIO(b'')), crossfade=100)
+
+def play_start_sound():
+    try:
+        play(start_beep)
+    except:
+        pass
+
+def play_end_sound():
+    try:
+        play(end_beep)
+    except:
+        pass
+
+def start_recording(audio_time_limit):
+    global is_recording
+    is_recording = True
+    recognizer = sr.Recognizer()
+    microphone = sr.Microphone()
+    
+    play_start_sound()
+    
+    with microphone as source:
+        recognizer.adjust_for_ambient_noise(source, duration=0.5)
+        try:
+            audio = recognizer.listen(source, timeout=3, phrase_time_limit=audio_time_limit)
+            text = recognizer.recognize_google(audio)
+            return text
+        except sr.WaitTimeoutError:
+            return ""
+        except sr.UnknownValueError:
+            return ""
+        except Exception as e:
+            print(f"Error: {str(e)}")
+            return ""
+        finally:
+            play_end_sound()
+            is_recording = False
+
+def transcribe_audio(audio_time_limit=10):
+    def execute_recording():
+        nonlocal result
+        result = start_recording(audio_time_limit)
+    
+    result = ""
+    recording_thread = threading.Thread(target=execute_recording)
+    recording_thread.start()
+    
+    start_time = time()
+    while is_recording and (time() - start_time) < audio_time_limit:
+        time_elapsed = time() - start_time
+        time_left = max(0, audio_time_limit - time_elapsed)
+        progress = 1 - (time_left / audio_time_limit)
+        yield {"__type__": "update", "value": f"🎤 Recording... {time_left:.1f}s left", "visible": True}, {"__type__": "update", "value": "", "visible": True}
+        gr.sleep(0.1)
+    
+    recording_thread.join()
+    yield {"__type__": "update", "value": "✅ Done!", "visible": True}, {"__type__": "update", "value": result, "visible": True}
+
+def create_ui():
+    css = """
+    .mic-button {
+        background: linear-gradient(45deg, #FF3366, #BA265D) !important;
+        border: none !important;
+        color: white !important;
+        padding: 12px !important;
+        border-radius: 50% !important;
+        height: 50px !important;
+        width: 50px !important;
+        margin-left: 10px !important;
+    }
+    .mic-button:hover {
+        transform: scale(1.05) !important;
+    }
+    .input-with-mic {
+        display: flex !important;
+        align-items: center !important;
+        gap: 10px !important;
+    }
+    .status-message {
+        font-style: italic;
+        color: #666;
+        margin-top: 5px;
+    }
+    """
+    
+    with gr.Blocks(css=css) as demo:
+        gr.Markdown("## 🎤 Speech to Text Converter")
+        
+        with gr.Group():
+            with gr.Row():
+                text_input = gr.Textbox(
+                    label="Your Input",
+                    placeholder="Click the mic button and speak...",
+                    elem_classes=["input-box"],
+                    scale=9
+                )
+                mic_button = gr.Button(
+                    "🎤",
+                    elem_classes=["mic-button"],
+                    scale=1
+                )
+            
+            status_display = gr.Textbox(
+                label="Status",
+                visible=False,
+                interactive=False,
+                elem_classes=["status-message"]
+            )
+        
+        mic_button.click(
+            fn=transcribe_audio,
+            inputs=[gr.Slider(5, 30, value=10, label="Recording time limit (seconds)")],
+            outputs=[status_display, text_input],
+            show_progress="hidden"
+        )
+        
+        gr.Examples(
+            examples=["Hello world", "How are you today?", "Please convert my speech to text"],
+            inputs=text_input,
+            label="Try these examples:"
+        )
+    
+    return demo
+
+if __name__ == "__main__":
+    demo = create_ui()
+    demo.launch(debug=True)