278 lines
12 KiB
Python
278 lines
12 KiB
Python
from fastapi import FastAPI, WebSocket, WebSocketDisconnect
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import uvicorn
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import asyncio
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import os
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import subprocess
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import struct
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from dotenv import load_dotenv
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import dashscope
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from dashscope.audio.asr import Recognition, RecognitionCallback, RecognitionResult
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import json
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# 加载环境变量
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load_dotenv()
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dashscope.api_key = os.getenv("DASHSCOPE_API_KEY")
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app = FastAPI()
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# 存储接收到的音频数据
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audio_buffer = bytearray()
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RECORDING_RAW_FILE = "received_audio.raw"
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RECORDING_MP3_FILE = "received_audio.mp3"
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VOLUME_GAIN = 10.0 # 放大倍数
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FONT_FILE = "GB2312-16.bin"
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class MyRecognitionCallback(RecognitionCallback):
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def __init__(self, websocket: WebSocket, loop: asyncio.AbstractEventLoop):
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self.websocket = websocket
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self.loop = loop
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def on_open(self) -> None:
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print("ASR Session started")
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def on_close(self) -> None:
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print("ASR Session closed")
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def on_event(self, result: RecognitionResult) -> None:
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if result.get_sentence():
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text = result.get_sentence()['text']
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print(f"ASR Result: {text}")
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# 将识别结果发送回客户端
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try:
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asyncio.run_coroutine_threadsafe(
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self.websocket.send_text(f"ASR:{text}"),
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self.loop
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)
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except Exception as e:
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print(f"Failed to send ASR result to client: {e}")
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def process_chunk_32_to_16(chunk_bytes, gain=1.0):
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processed_chunk = bytearray()
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# Iterate 4 bytes at a time
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for i in range(0, len(chunk_bytes), 4):
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if i+3 < len(chunk_bytes):
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# 取 chunk[i+2] 和 chunk[i+3] 组成 16-bit signed int
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sample = struct.unpack_from('<h', chunk_bytes, i+2)[0]
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# 放大音量
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sample = int(sample * gain)
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# 限幅 (Clamping) 防止溢出爆音
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if sample > 32767: sample = 32767
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elif sample < -32768: sample = -32768
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# 重新打包为 16-bit little-endian
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processed_chunk.extend(struct.pack('<h', sample))
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return processed_chunk
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@app.websocket("/ws/audio")
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async def websocket_endpoint(websocket: WebSocket):
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global audio_buffer
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await websocket.accept()
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print("Client connected")
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recognition = None
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processed_buffer = bytearray()
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loop = asyncio.get_running_loop()
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try:
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while True:
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# 接收消息 (可能是文本指令或二进制音频数据)
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try:
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message = await websocket.receive()
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except RuntimeError as e:
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if "Cannot call \"receive\" once a disconnect message has been received" in str(e):
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print("Client disconnected (RuntimeError caught)")
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break
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raise e
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if "text" in message:
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text = message["text"]
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print(f"Received text: {text}")
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if text == "START_RECORDING":
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print("Start recording...")
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audio_buffer = bytearray() # 清空缓冲区
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processed_buffer = bytearray()
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# 启动实时语音识别
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try:
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callback = MyRecognitionCallback(websocket, loop)
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recognition = Recognition(
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model='paraformer-realtime-v2',
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format='pcm',
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sample_rate=16000,
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callback=callback
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)
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recognition.start()
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print("DashScope ASR started")
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except Exception as e:
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print(f"Failed to start ASR: {e}")
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recognition = None
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elif text == "STOP_RECORDING":
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print(f"Stop recording. Total raw bytes: {len(audio_buffer)}")
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# 停止语音识别
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if recognition:
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try:
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recognition.stop()
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print("DashScope ASR stopped")
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except Exception as e:
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print(f"Error stopping ASR: {e}")
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recognition = None
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# 使用实时处理过的音频数据
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processed_audio = processed_buffer
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print(f"Processed audio size: {len(processed_audio)} bytes (Gain: {VOLUME_GAIN}x)")
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# 2. 保存原始 RAW 文件 (16-bit PCM)
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with open(RECORDING_RAW_FILE, "wb") as f:
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f.write(processed_audio)
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# 3. 转换为 MP3 并保存 (使用 ffmpeg 命令行，避免 Python 3.13 audioop 问题)
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try:
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# ffmpeg -y -f s16le -ar 16000 -ac 1 -i received_audio.raw received_audio.mp3
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cmd = [
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"ffmpeg",
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"-y", # 覆盖输出文件
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"-f", "s16le", # 输入格式: signed 16-bit little endian
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"-ar", "16000", # 输入采样率
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"-ac", "1", # 输入声道数
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"-i", RECORDING_RAW_FILE,
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RECORDING_MP3_FILE
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]
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print(f"Running command: {' '.join(cmd)}")
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# Use asyncio.create_subprocess_exec instead of subprocess.run to avoid blocking the event loop
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process = await asyncio.create_subprocess_exec(
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*cmd,
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stdout=asyncio.subprocess.PIPE,
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stderr=asyncio.subprocess.PIPE
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)
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stdout, stderr = await process.communicate()
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if process.returncode != 0:
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raise subprocess.CalledProcessError(process.returncode, cmd, output=stdout, stderr=stderr)
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print(f"Saved MP3 to {RECORDING_MP3_FILE}")
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except subprocess.CalledProcessError as e:
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print(f"Error converting to MP3: {e}")
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# stderr might be bytes
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error_msg = e.stderr.decode() if isinstance(e.stderr, bytes) else str(e.stderr)
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print(f"FFmpeg stderr: {error_msg}")
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except FileNotFoundError:
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print("Error: ffmpeg not found. Please install ffmpeg.")
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except Exception as e:
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print(f"Error converting to MP3: {e}")
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# 4. 发送回客户端播放
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print("Sending audio back...")
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await websocket.send_text("START_PLAYBACK")
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# 分块发送
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chunk_size = 4096
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for i in range(0, len(processed_audio), chunk_size):
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chunk = processed_audio[i:i+chunk_size]
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await websocket.send_bytes(chunk)
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# 小延时，避免发送过快导致 ESP32 缓冲区溢出
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# 4096 bytes / 32000 bytes/s (16k*2) = ~0.128s
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# 0.04s 约为 3 倍速发送，既保证缓冲又不至于拥塞
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await asyncio.sleep(0.04)
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await websocket.send_text("STOP_PLAYBACK")
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print("Audio sent back finished.")
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elif text.startswith("GET_FONT:"):
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# 格式: GET_FONT:0xA1A1
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try:
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print(f"Font Request Received: {text}")
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hex_code = text.split(":")[1]
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code = int(hex_code, 16)
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# 计算偏移量
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# GB2312 编码范围：0xA1A1 - 0xFEFE
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# 区码：高字节 - 0xA0
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# 位码：低字节 - 0xA0
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area = (code >> 8) - 0xA0
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index = (code & 0xFF) - 0xA0
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if area >= 1 and index >= 1:
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offset = ((area - 1) * 94 + (index - 1)) * 32
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# 读取字体文件
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# 注意：这里为了简单，每次都打开文件。如果并发高，应该缓存文件句柄或内容。
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# 假设字体文件在当前目录或上级目录
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# Prioritize finding the file in the script's directory
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script_dir = os.path.dirname(os.path.abspath(__file__))
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font_path = os.path.join(script_dir, FONT_FILE)
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# Fallback: check one level up
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if not os.path.exists(font_path):
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font_path = os.path.join(script_dir, "..", FONT_FILE)
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# Fallback: check current working directory
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if not os.path.exists(font_path):
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font_path = FONT_FILE
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if os.path.exists(font_path):
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print(f"Reading font from: {font_path} (Offset: {offset})")
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with open(font_path, "rb") as f:
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f.seek(offset)
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font_data = f.read(32)
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if len(font_data) == 32:
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import binascii
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hex_data = binascii.hexlify(font_data).decode('utf-8')
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response = f"FONT_DATA:{hex_code}:{hex_data}"
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print(f"Sending Font Response: {response[:30]}...")
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await websocket.send_text(response)
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else:
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print(f"Error: Read {len(font_data)} bytes for font data (expected 32)")
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else:
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print(f"Font file not found: {font_path}")
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else:
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print(f"Invalid GB2312 code: {hex_code} (Area: {area}, Index: {index})")
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except Exception as e:
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print(f"Error handling GET_FONT: {e}")
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elif "bytes" in message:
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# 接收音频数据并追加到缓冲区
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data = message["bytes"]
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audio_buffer.extend(data)
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# 实时处理并发送给 ASR
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pcm_chunk = process_chunk_32_to_16(data, VOLUME_GAIN)
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processed_buffer.extend(pcm_chunk)
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if recognition:
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try:
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recognition.send_audio_frame(pcm_chunk)
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except Exception as e:
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print(f"Error sending audio frame to ASR: {e}")
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except WebSocketDisconnect:
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print("Client disconnected")
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if recognition:
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try:
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recognition.stop()
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except:
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pass
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except Exception as e:
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print(f"Error: {e}")
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if recognition:
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try:
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recognition.stop()
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except:
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pass
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if __name__ == "__main__":
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# 获取本机IP，方便ESP32连接
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import socket
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hostname = socket.gethostname()
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local_ip = socket.gethostbyname(hostname)
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print(f"Server running on ws://{local_ip}:8000/ws/audio")
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uvicorn.run(app, host="0.0.0.0", port=8000)
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