| import gradio as gr |
| from gradio_webrtc import WebRTC, StreamHandler, get_twilio_turn_credentials |
| import websockets.sync.client |
| import numpy as np |
| import json |
| import base64 |
| import os |
| from dotenv import load_dotenv |
|
|
| class GeminiConfig: |
| def __init__(self): |
| load_dotenv() |
| self.api_key = self._get_api_key() |
| self.host = 'generativelanguage.googleapis.com' |
| self.model = 'models/gemini-2.0-flash-exp' |
| self.ws_url = f'wss://{self.host}/ws/google.ai.generativelanguage.v1alpha.GenerativeService.BidiGenerateContent?key={self.api_key}' |
|
|
| def _get_api_key(self): |
| api_key = os.getenv('GOOGLE_API_KEY') |
| if not api_key: |
| raise ValueError("GOOGLE_API_KEY not found in environment variables. Please set it in your .env file.") |
| return api_key |
|
|
| class AudioProcessor: |
| @staticmethod |
| def encode_audio(data, sample_rate): |
| encoded = base64.b64encode(data.tobytes()).decode('UTF-8') |
| return { |
| 'realtimeInput': { |
| 'mediaChunks': [{ |
| 'mimeType': f'audio/pcm;rate={sample_rate}', |
| 'data': encoded, |
| }], |
| }, |
| } |
|
|
| @staticmethod |
| def process_audio_response(data): |
| audio_data = base64.b64decode(data) |
| return np.frombuffer(audio_data, dtype=np.int16) |
|
|
| class GeminiHandler(StreamHandler): |
| def __init__(self, |
| expected_layout="mono", |
| output_sample_rate=24000, |
| output_frame_size=480) -> None: |
| super().__init__(expected_layout, output_sample_rate, output_frame_size, |
| input_sample_rate=24000) |
| self.config = GeminiConfig() |
| self.ws = None |
| self.all_output_data = None |
| self.audio_processor = AudioProcessor() |
|
|
| def copy(self): |
| return GeminiHandler( |
| expected_layout=self.expected_layout, |
| output_sample_rate=self.output_sample_rate, |
| output_frame_size=self.output_frame_size |
| ) |
|
|
| def _initialize_websocket(self): |
| try: |
| self.ws = websockets.sync.client.connect( |
| self.config.ws_url, |
| timeout=30 |
| ) |
| initial_request = { |
| 'setup': { |
| 'model': self.config.model, |
| } |
| } |
| self.ws.send(json.dumps(initial_request)) |
| setup_response = json.loads(self.ws.recv()) |
| print(f"Setup response: {setup_response}") |
| except websockets.exceptions.WebSocketException as e: |
| print(f"WebSocket connection failed: {str(e)}") |
| self.ws = None |
| except Exception as e: |
| print(f"Setup failed: {str(e)}") |
| self.ws = None |
|
|
| def receive(self, frame: tuple[int, np.ndarray]) -> None: |
| try: |
| if not self.ws: |
| self._initialize_websocket() |
|
|
| _, array = frame |
| array = array.squeeze() |
| audio_message = self.audio_processor.encode_audio(array, self.output_sample_rate) |
| self.ws.send(json.dumps(audio_message)) |
| except Exception as e: |
| print(f"Error in receive: {str(e)}") |
| if self.ws: |
| self.ws.close() |
| self.ws = None |
|
|
| def _process_server_content(self, content): |
| for part in content.get('parts', []): |
| data = part.get('inlineData', {}).get('data', '') |
| if data: |
| audio_array = self.audio_processor.process_audio_response(data) |
| if self.all_output_data is None: |
| self.all_output_data = audio_array |
| else: |
| self.all_output_data = np.concatenate((self.all_output_data, audio_array)) |
| |
| while self.all_output_data.shape[-1] >= self.output_frame_size: |
| yield (self.output_sample_rate, |
| self.all_output_data[:self.output_frame_size].reshape(1, -1)) |
| self.all_output_data = self.all_output_data[self.output_frame_size:] |
|
|
| def generator(self): |
| while True: |
| if not self.ws: |
| print("WebSocket not connected") |
| yield None |
| continue |
|
|
| try: |
| message = self.ws.recv(timeout=5) |
| msg = json.loads(message) |
| |
| if 'serverContent' in msg: |
| content = msg['serverContent'].get('modelTurn', {}) |
| yield from self._process_server_content(content) |
| except TimeoutError: |
| print("Timeout waiting for server response") |
| yield None |
| except Exception as e: |
| print(f"Error in generator: {str(e)}") |
| yield None |
|
|
| def emit(self) -> tuple[int, np.ndarray] | None: |
| if not self.ws: |
| return None |
| if not hasattr(self, '_generator'): |
| self._generator = self.generator() |
| try: |
| return next(self._generator) |
| except StopIteration: |
| self.reset() |
| return None |
|
|
| def reset(self) -> None: |
| if hasattr(self, '_generator'): |
| delattr(self, '_generator') |
| self.all_output_data = None |
|
|
| def shutdown(self) -> None: |
| if self.ws: |
| self.ws.close() |
|
|
| def check_connection(self): |
| try: |
| if not self.ws or self.ws.closed: |
| self._initialize_websocket() |
| return True |
| except Exception as e: |
| print(f"Connection check failed: {str(e)}") |
| return False |
|
|
| class GeminiVoiceChat: |
| def __init__(self): |
| load_dotenv() |
| self.demo = self._create_interface() |
|
|
| def _create_interface(self): |
| with gr.Blocks() as demo: |
| gr.HTML(""" |
| <div style='text-align: center'> |
| <h1>Gemini 2.0 Voice Chat</h1> |
| <p>Speak with Gemini using real-time audio streaming</p> |
| </div> |
| """) |
| |
| webrtc = WebRTC( |
| label="Conversation", |
| modality="audio", |
| mode="send-receive", |
| rtc_configuration=get_twilio_turn_credentials() |
| ) |
| |
| webrtc.stream( |
| GeminiHandler(), |
| inputs=[webrtc], |
| outputs=[webrtc], |
| time_limit=90, |
| concurrency_limit=10 |
| ) |
| return demo |
|
|
| def launch(self): |
| self.demo.launch() |
| |
| def demo(): |
| chat = GeminiVoiceChat() |
| return chat.demo |
|
|
| |
| demo = demo() |