remove test files from main
This commit is contained in:
0Xiao0
188
test_agent.py
188
test_agent.py
@ -1,188 +0,0 @@
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import asyncio
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import requests
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import logging
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from pathlib import Path
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import uuid
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import wave
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import numpy as np
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from datetime import datetime
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from livekit import rtc
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from livekit.rtc import AudioSource, AudioFrame, LocalAudioTrack
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
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)
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logger = logging.getLogger("test-agent")
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TOKEN_URL = "http://localhost:8000/getToken"
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WS_URL = "wss://esp32-vt80c4y6.livekit.cloud"
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ROOM_NAME = "test-room20"
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WAV_FILE = "2food.wav"
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TEST_TIMEOUT = 30
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class TestState:
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def __init__(self):
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self.agent_connected = False
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self.tts_received = False
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self.tts_count = 0
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test_state = TestState()
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def get_token(agent_name="my-agent"):
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try:
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resp = requests.get(
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TOKEN_URL,
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params={
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"room": ROOM_NAME,
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"identity": f"test-{uuid.uuid4().hex[:6]}",
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"agent_name": agent_name,
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},
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timeout=5
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)
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resp.raise_for_status()
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return resp.json()["token"]
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except Exception as e:
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logger.error(f"❌ 获取token失败: {e}")
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raise
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async def publish_wav(room, wav_path):
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wav_path = Path(wav_path)
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if not wav_path.exists():
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logger.error(f"❌ WAV文件不存在: {wav_path}")
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raise FileNotFoundError(f"文件不存在: {wav_path}")
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logger.info(f"📂 开始上传: {wav_path}")
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with wave.open(str(wav_path), "rb") as wf:
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sample_rate = wf.getframerate()
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num_channels = wf.getnchannels()
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sample_width = wf.getsampwidth()
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logger.info(f"📊 WAV信息: {sample_rate}Hz, {num_channels}ch, {sample_width*8}bit")
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source = AudioSource(sample_rate, num_channels)
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track = LocalAudioTrack.create_audio_track("mic", source)
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await room.local_participant.publish_track(track)
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logger.info("📡 已发布音轨")
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frame_duration = 0.02
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samples_per_frame = int(sample_rate * frame_duration)
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while True:
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data = wf.readframes(samples_per_frame)
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if not data:
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break
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audio = np.frombuffer(data, dtype=np.int16)
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if len(audio) == 0:
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continue
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samples_per_channel = len(audio) // num_channels
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frame = AudioFrame(
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data=data,
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sample_rate=sample_rate,
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num_channels=num_channels,
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samples_per_channel=samples_per_channel,
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)
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await source.capture_frame(frame)
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await asyncio.sleep(frame_duration)
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logger.info("✅ WAV推流完成")
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async def test_agent():
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try:
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logger.info("🔑 正在获取token...")
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token = get_token()
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logger.info("✅ Token获取成功")
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room = rtc.Room()
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@room.on("participant_connected")
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def on_participant_connected(participant):
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logger.info(f"✅ 参与者加入: {participant.identity}")
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if "agent" in participant.identity.lower():
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test_state.agent_connected = True
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logger.info("🎉 Agent已连接！")
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@room.on("participant_disconnected")
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def on_participant_disconnected(participant):
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logger.info(f"❌ 参与者离开: {participant.identity}")
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@room.on("track_subscribed")
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def on_track_subscribed(track, publication, participant):
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if track.kind == rtc.TrackKind.KIND_AUDIO:
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test_state.tts_count += 1
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logger.info(f"🎵 收到TTS音频! (第 {test_state.tts_count} 次)")
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test_state.tts_received = True
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logger.info(f"🔌 正在连接房间 {ROOM_NAME}...")
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await room.connect(WS_URL, token)
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logger.info("✅ 已连接到房间")
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logger.info(f"🆔 本地参与者ID: {room.local_participant.identity}")
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logger.info("⏳ 等待Agent连接...")
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for i in range(10):
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if test_state.agent_connected:
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break
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await asyncio.sleep(1)
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if not test_state.agent_connected:
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logger.warning("⚠️ Agent未连接")
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return False
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logger.info("🎙️ 正在上传测试音频...")
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await publish_wav(room, WAV_FILE)
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logger.info("⏳ 等待Agent响应...")
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for i in range(TEST_TIMEOUT):
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if test_state.tts_received:
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logger.info("✅ 收到Agent TTS响应!")
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break
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if i % 5 == 0:
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logger.info(f" 等待中... ({i+1}/{TEST_TIMEOUT}秒)")
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await asyncio.sleep(1)
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await asyncio.sleep(2)
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logger.info("\n" + "="*60)
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logger.info("✅ 测试结果")
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logger.info("="*60)
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logger.info(f"Agent连接: {'✅' if test_state.agent_connected else '❌'}")
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logger.info(f"收到TTS响应: {'✅' if test_state.tts_received else '❌'}")
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logger.info(f"TTS音频次数: {test_state.tts_count} 次")
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logger.info("="*60)
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await room.disconnect()
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logger.info("✅ 已断开连接\n")
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return test_state.agent_connected and test_state.tts_received
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except Exception as e:
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logger.error(f"❌ 测试失败: {e}", exc_info=True)
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return False
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async def main():
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logger.info("🚀 开始测试custom_agent...\n")
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success = await test_agent()
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if success:
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logger.info("✅ 测试成功！custom_agent 正常工作")
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logger.info("💡 提示: Agent内部的转录和响应日志只能在Agent自身看到，")
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logger.info(" 或通过 agent-starter-react 这样的客户端交互查看")
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return 0
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else:
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logger.error("❌ 测试失败")
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return 1
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if __name__ == "__main__":
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exit_code = asyncio.run(main())
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exit(exit_code)
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55
test_asr.py
55
test_asr.py
@ -1,55 +0,0 @@
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import asyncio
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import logging
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import wave
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from asr import BlackboxSTT
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from livekit import rtc
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# 设置日志级别以查看输出
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger("test-asr")
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async def test():
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# 替换为你本地的一个音频文件路径
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audio_path = "/home/verachen/Music/voice/2food.wav"
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# 初始化 ASR
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stt = BlackboxSTT(url="http://10.6.80.21:5003/asr-blackbox", model_name="sensevoice")
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print(f"Testing ASR connectivity with file: {audio_path}")
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try:
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# 读取音频文件
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with wave.open(audio_path, "rb") as wf:
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frames = wf.readframes(wf.getnframes())
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# 简单构造一个 AudioBuffer (假设是单声道 16kHz)
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# 实际上 BlackboxSTT._recognize_impl 会用 combine_audio_frames(buffer).to_wav_bytes()
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# 所以我们需要传递一个包含 AudioFrame 的 list
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# 这里我们模拟一个 Frame
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frame = rtc.AudioFrame(
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data=frames,
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sample_rate=wf.getframerate(),
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num_channels=wf.getnchannels(),
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samples_per_channel=wf.getnframes(),
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)
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# 调用 recognize
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result = await stt.recognize(buffer=[frame])
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if result.alternatives:
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print("\n--- ASR Result ---")
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print(f"Text: {result.alternatives[0].text}")
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print("------------------\n")
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else:
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print("ASR returned no text.")
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except FileNotFoundError:
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print(f"Error: Audio file not found at {audio_path}")
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except Exception as e:
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print(f"An error occurred: {e}")
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if __name__ == "__main__":
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asyncio.run(test())
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130
test_livekit.py
130
test_livekit.py
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import asyncio
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import requests
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from livekit import rtc
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import wave
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import numpy as np
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from livekit.rtc import AudioSource, AudioFrame, LocalAudioTrack
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TOKEN_URL = "http://localhost:8000/getToken"
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WS_URL = "wss://esp32-vt80c4y6.livekit.cloud" # 你的 LiveKit Server 地址
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ROOM_NAME = "test-room20"
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import uuid
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IDENTITY = f"uv-{uuid.uuid4().hex[:6]}"
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# IDENTITY = "test-user0"
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def get_token():
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resp = requests.get(
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TOKEN_URL,
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params={
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"room": ROOM_NAME,
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"identity": IDENTITY,
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"agent_name": "my-agent", # 关键！！！
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},
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)
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data = resp.json()
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return data["token"]
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async def main():
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token = get_token()
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room = rtc.Room()
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@room.on("participant_connected")
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def on_participant_connected(participant):
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print(f"✅ 有人加入房间: {participant.identity}")
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@room.on("participant_disconnected")
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def on_participant_disconnected(participant):
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print(f"❌ 有人离开房间: {participant.identity}")
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print("🔌 正在连接房间...")
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await room.connect(WS_URL, token)
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print("✅ 已连接房间:", ROOM_NAME)
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print("当前房间成员：")
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for p in room.remote_participants.values():
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print(" -", p.identity)
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@room.on("data_received")
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def on_data_received(data, participant, kind, topic):
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try:
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msg = data.decode()
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print(f"📩 来自 {participant.identity}: {msg}")
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except:
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print("📩 收到二进制数据")
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@room.on("track_subscribed")
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def on_track_subscribed(track, publication, participant):
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print(f"🎧 订阅轨道: {participant.identity}")
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if track.kind == rtc.TrackKind.KIND_AUDIO:
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print("👉 TTS 音频来了")
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# 等一下确保连接稳定
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await asyncio.sleep(1)
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await room.local_participant.publish_data(
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b"hello",
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reliable=True,
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topic="chat"
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)
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# 上传 wav
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await publish_wav(room, "2food.wav")
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await room.disconnect()
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async def publish_wav(room, wav_path):
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print("🎵 开始上传本地 wav:", wav_path)
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wf = wave.open(wav_path, "rb")
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sample_rate = wf.getframerate()
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num_channels = wf.getnchannels()
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sample_width = wf.getsampwidth()
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print(f"📊 WAV信息: {sample_rate}Hz, {num_channels}ch, {sample_width*8}bit")
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# 创建音频源
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source = AudioSource(sample_rate, num_channels)
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# 创建本地音轨
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track = LocalAudioTrack.create_audio_track("mic", source)
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# 发布轨道
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await room.local_participant.publish_track(track)
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print("📡 已发布音轨")
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frame_duration = 0.02 # 20ms
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samples_per_frame = int(sample_rate * frame_duration)
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while True:
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data = wf.readframes(samples_per_frame)
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if not data:
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break
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# 用于计算长度
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audio = np.frombuffer(data, dtype=np.int16)
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if len(audio) == 0:
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continue
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samples_per_channel = len(audio) // num_channels
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frame = AudioFrame(
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data=data, # ✅ 关键：用 bytes
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sample_rate=sample_rate,
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num_channels=num_channels,
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samples_per_channel=samples_per_channel,
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)
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await source.capture_frame(frame)
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await asyncio.sleep(frame_duration)
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print("✅ wav 推流结束")
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if __name__ == "__main__":
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asyncio.run(main())
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@ -1,71 +0,0 @@
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import asyncio
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import os
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import logging
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from dotenv import load_dotenv
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from livekit.agents.llm import ChatContext
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from livekit.plugins import openai
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||||||
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||||||
# Configure logging to see what's happening
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||||||
logging.basicConfig(level=logging.INFO)
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||||||
logger = logging.getLogger("test-minimax")
|
|
||||||
|
|
||||||
async def test_minimax():
|
|
||||||
print("Loading .env...")
|
|
||||||
load_dotenv()
|
|
||||||
|
|
||||||
# Configuration from environment or defaults from custom_agent.py
|
|
||||||
MINIMAX_BASE_URL = os.getenv("MINIMAX_LLM_BASE_URL", "https://oai.bwgdi.com/v1")
|
|
||||||
MINIMAX_MODEL = os.getenv("MINIMAX_LLM_MODEL", "MiniMaxAI")
|
|
||||||
# Using the hardcoded key from custom_agent.py as a fallback if not in .env
|
|
||||||
API_KEY = os.getenv("MINIMAX_API_KEY", "sk-orez64WkG1NkfksB5j_hGA")
|
|
||||||
|
|
||||||
import httpx
|
|
||||||
from openai import AsyncClient as OpenAIAsyncClient
|
|
||||||
|
|
||||||
print(f"Connecting to Minimax at {MINIMAX_BASE_URL} using model {MINIMAX_MODEL}")
|
|
||||||
|
|
||||||
# Create a custom HTTP client that disables SSL verification
|
|
||||||
http_client = httpx.AsyncClient(verify=False)
|
|
||||||
|
|
||||||
# Create the OpenAI AsyncClient with the custom HTTP client
|
|
||||||
openai_client = OpenAIAsyncClient(
|
|
||||||
api_key=API_KEY,
|
|
||||||
base_url=MINIMAX_BASE_URL,
|
|
||||||
http_client=http_client,
|
|
||||||
)
|
|
||||||
|
|
||||||
llm = openai.LLM(
|
|
||||||
model=MINIMAX_MODEL,
|
|
||||||
client=openai_client,
|
|
||||||
)
|
|
||||||
|
|
||||||
print("Creating ChatContext...")
|
|
||||||
chat_ctx = ChatContext()
|
|
||||||
chat_ctx.add_message(
|
|
||||||
content="Hello! Can you introduce yourself? Please reply in Chinese.",
|
|
||||||
role="user",
|
|
||||||
)
|
|
||||||
|
|
||||||
print(f"\n--- Testing Streaming Chat ---")
|
|
||||||
print(f"Request: {chat_ctx.items[-1].content}")
|
|
||||||
print("Response: ", end="", flush=True)
|
|
||||||
|
|
||||||
try:
|
|
||||||
print("\nCalling llm.chat()...")
|
|
||||||
stream = llm.chat(chat_ctx=chat_ctx)
|
|
||||||
print("Iterating over stream...")
|
|
||||||
async for chunk in stream:
|
|
||||||
if chunk.delta and chunk.delta.content:
|
|
||||||
print(chunk.delta.content, end="", flush=True)
|
|
||||||
print("\n--- Test Completed Successfully ---")
|
|
||||||
except Exception as e:
|
|
||||||
logger.error(f"\nTest failed with error: {e}")
|
|
||||||
|
|
||||||
if __name__ == "__main__":
|
|
||||||
print("Starting...")
|
|
||||||
try:
|
|
||||||
asyncio.run(asyncio.wait_for(test_minimax(), timeout=30))
|
|
||||||
except asyncio.TimeoutError:
|
|
||||||
print("\nTest timed out after 30 seconds.")
|
|
||||||
except Exception as e:
|
|
||||||
print(f"\nAn error occurred: {e}")
|
|
||||||
@ -1,66 +0,0 @@
|
|||||||
import asyncio
|
|
||||||
import logging
|
|
||||||
import os
|
|
||||||
|
|
||||||
from tts import BlackboxTTS
|
|
||||||
|
|
||||||
logging.basicConfig(level=logging.INFO)
|
|
||||||
|
|
||||||
|
|
||||||
async def test_tts():
|
|
||||||
# Use the URL from the user's curl command
|
|
||||||
url = "http://10.6.80.21:5002/tts-blackbox"
|
|
||||||
|
|
||||||
# Check if we have a real wav file to test with
|
|
||||||
# In the earlier find_by_name, we found tests/change-sophie.wav
|
|
||||||
prompt_wav = "/home/verachen/Music/voice/2food.wav"
|
|
||||||
if not os.path.exists(prompt_wav):
|
|
||||||
prompt_wav = "/home/verachen/Music/voice/2food.wav" # fallback to the one in curl
|
|
||||||
|
|
||||||
print(f"Testing BlackboxTTS with URL: {url}")
|
|
||||||
print(f"Using prompt wav: {prompt_wav}")
|
|
||||||
|
|
||||||
blackbox_tts = BlackboxTTS(
|
|
||||||
url=url,
|
|
||||||
model_name="voxcpmtts",
|
|
||||||
prompt_wav_path=prompt_wav,
|
|
||||||
params={
|
|
||||||
"streaming": "false",
|
|
||||||
"prompt_text": "澳门有乜嘢好食嘅",
|
|
||||||
"cfg_value": "2.0",
|
|
||||||
"inference_timesteps": "10",
|
|
||||||
"do_normalize": "true",
|
|
||||||
"denoise": "true",
|
|
||||||
"retry_badcase": "true",
|
|
||||||
"retry_badcase_max_times": "3",
|
|
||||||
"retry_badcase_ratio_threshold": "6.0",
|
|
||||||
},
|
|
||||||
)
|
|
||||||
|
|
||||||
text = "你好，这是一段测试文本"
|
|
||||||
print(f"Synthesizing text: {text}")
|
|
||||||
|
|
||||||
try:
|
|
||||||
stream = blackbox_tts.synthesize(text)
|
|
||||||
audio_frame = await stream.collect()
|
|
||||||
|
|
||||||
print("Successfully synthesized audio!")
|
|
||||||
print(
|
|
||||||
f"Audio duration: {audio_frame.sample_rate * len(audio_frame.data) / (audio_frame.num_channels * 2)} samples?"
|
|
||||||
)
|
|
||||||
# Actually AudioFrame has duration or samples
|
|
||||||
print(f"Samples: {len(audio_frame.data) // 2}")
|
|
||||||
|
|
||||||
# Save to file for manual check if possible
|
|
||||||
with open("test_output.wav", "wb") as f:
|
|
||||||
# This won't be a valid WAV yet if it's just raw PCM,
|
|
||||||
# but if collect() returns combined frames, we can use to_wav_bytes()
|
|
||||||
f.write(audio_frame.to_wav_bytes())
|
|
||||||
print("Saved output to test_output.wav")
|
|
||||||
|
|
||||||
except Exception as e:
|
|
||||||
print(f"TTS test failed: {e}")
|
|
||||||
|
|
||||||
|
|
||||||
if __name__ == "__main__":
|
|
||||||
asyncio.run(test_tts())
|
|
||||||
Reference in New Issue
Block a user