diff --git a/test_agent.py b/test_agent.py deleted file mode 100644 index dc1d1cb..0000000 --- a/test_agent.py +++ /dev/null @@ -1,188 +0,0 @@ -import asyncio -import requests -import logging -from pathlib import Path -import uuid -import wave -import numpy as np -from datetime import datetime -from livekit import rtc -from livekit.rtc import AudioSource, AudioFrame, LocalAudioTrack - -logging.basicConfig( - level=logging.INFO, - format='%(asctime)s - %(name)s - %(levelname)s - %(message)s' -) -logger = logging.getLogger("test-agent") - -TOKEN_URL = "http://localhost:8000/getToken" -WS_URL = "wss://esp32-vt80c4y6.livekit.cloud" -ROOM_NAME = "test-room20" -WAV_FILE = "2food.wav" -TEST_TIMEOUT = 30 - -class TestState: - def __init__(self): - self.agent_connected = False - self.tts_received = False - self.tts_count = 0 - -test_state = TestState() - - -def get_token(agent_name="my-agent"): - try: - resp = requests.get( - TOKEN_URL, - params={ - "room": ROOM_NAME, - "identity": f"test-{uuid.uuid4().hex[:6]}", - "agent_name": agent_name, - }, - timeout=5 - ) - resp.raise_for_status() - return resp.json()["token"] - except Exception as e: - logger.error(f"❌ 获取token失败: {e}") - raise - - -async def publish_wav(room, wav_path): - wav_path = Path(wav_path) - if not wav_path.exists(): - logger.error(f"❌ WAV文件不存在: {wav_path}") - raise FileNotFoundError(f"文件不存在: {wav_path}") - - logger.info(f"📂 开始上传: {wav_path}") - - with wave.open(str(wav_path), "rb") as wf: - sample_rate = wf.getframerate() - num_channels = wf.getnchannels() - sample_width = wf.getsampwidth() - - logger.info(f"📊 WAV信息: {sample_rate}Hz, {num_channels}ch, {sample_width*8}bit") - - source = AudioSource(sample_rate, num_channels) - track = LocalAudioTrack.create_audio_track("mic", source) - - await room.local_participant.publish_track(track) - logger.info("📡 已发布音轨") - - frame_duration = 0.02 - samples_per_frame = int(sample_rate * frame_duration) - - while True: - data = wf.readframes(samples_per_frame) - if not data: - break - - audio = np.frombuffer(data, dtype=np.int16) - if len(audio) == 0: - continue - - samples_per_channel = len(audio) // num_channels - - frame = AudioFrame( - data=data, - sample_rate=sample_rate, - num_channels=num_channels, - samples_per_channel=samples_per_channel, - ) - - await source.capture_frame(frame) - await asyncio.sleep(frame_duration) - - logger.info("✅ WAV推流完成") - - -async def test_agent(): - try: - logger.info("🔑 正在获取token...") - token = get_token() - logger.info("✅ Token获取成功") - - room = rtc.Room() - - @room.on("participant_connected") - def on_participant_connected(participant): - logger.info(f"✅ 参与者加入: {participant.identity}") - if "agent" in participant.identity.lower(): - test_state.agent_connected = True - logger.info("🎉 Agent已连接！") - - @room.on("participant_disconnected") - def on_participant_disconnected(participant): - logger.info(f"❌ 参与者离开: {participant.identity}") - - @room.on("track_subscribed") - def on_track_subscribed(track, publication, participant): - if track.kind == rtc.TrackKind.KIND_AUDIO: - test_state.tts_count += 1 - logger.info(f"🎵 收到TTS音频! (第 {test_state.tts_count} 次)") - test_state.tts_received = True - - logger.info(f"🔌 正在连接房间 {ROOM_NAME}...") - await room.connect(WS_URL, token) - logger.info("✅ 已连接到房间") - logger.info(f"🆔 本地参与者ID: {room.local_participant.identity}") - - logger.info("⏳ 等待Agent连接...") - for i in range(10): - if test_state.agent_connected: - break - await asyncio.sleep(1) - - if not test_state.agent_connected: - logger.warning("⚠️ Agent未连接") - return False - - logger.info("🎙️ 正在上传测试音频...") - await publish_wav(room, WAV_FILE) - - logger.info("⏳ 等待Agent响应...") - for i in range(TEST_TIMEOUT): - if test_state.tts_received: - logger.info("✅ 收到Agent TTS响应!") - break - if i % 5 == 0: - logger.info(f" 等待中... ({i+1}/{TEST_TIMEOUT}秒)") - await asyncio.sleep(1) - - await asyncio.sleep(2) - - logger.info("\n" + "="*60) - logger.info("✅ 测试结果") - logger.info("="*60) - logger.info(f"Agent连接: {'✅' if test_state.agent_connected else '❌'}") - logger.info(f"收到TTS响应: {'✅' if test_state.tts_received else '❌'}") - logger.info(f"TTS音频次数: {test_state.tts_count} 次") - logger.info("="*60) - - await room.disconnect() - logger.info("✅ 已断开连接\n") - - return test_state.agent_connected and test_state.tts_received - - except Exception as e: - logger.error(f"❌ 测试失败: {e}", exc_info=True) - return False - - -async def main(): - logger.info("🚀 开始测试custom_agent...\n") - success = await test_agent() - - if success: - logger.info("✅ 测试成功！custom_agent 正常工作") - logger.info("💡 提示: Agent内部的转录和响应日志只能在Agent自身看到，") - logger.info(" 或通过 agent-starter-react 这样的客户端交互查看") - return 0 - else: - logger.error("❌ 测试失败") - return 1 - - -if __name__ == "__main__": - exit_code = asyncio.run(main()) - exit(exit_code) \ No newline at end of file diff --git a/test_asr.py b/test_asr.py deleted file mode 100644 index 2af0b62..0000000 --- a/test_asr.py +++ /dev/null @@ -1,55 +0,0 @@ -import asyncio -import logging -import wave - -from asr import BlackboxSTT -from livekit import rtc - -# 设置日志级别以查看输出 -logging.basicConfig(level=logging.INFO) -logger = logging.getLogger("test-asr") - - -async def test(): - # 替换为你本地的一个音频文件路径 - audio_path = "/home/verachen/Music/voice/2food.wav" - - # 初始化 ASR - stt = BlackboxSTT(url="http://10.6.80.21:5003/asr-blackbox", model_name="sensevoice") - - print(f"Testing ASR connectivity with file: {audio_path}") - - try: - # 读取音频文件 - with wave.open(audio_path, "rb") as wf: - frames = wf.readframes(wf.getnframes()) - # 简单构造一个 AudioBuffer (假设是单声道 16kHz) - # 实际上 BlackboxSTT._recognize_impl 会用 combine_audio_frames(buffer).to_wav_bytes() - # 所以我们需要传递一个包含 AudioFrame 的 list - - # 这里我们模拟一个 Frame - frame = rtc.AudioFrame( - data=frames, - sample_rate=wf.getframerate(), - num_channels=wf.getnchannels(), - samples_per_channel=wf.getnframes(), - ) - - # 调用 recognize - result = await stt.recognize(buffer=[frame]) - - if result.alternatives: - print("\n--- ASR Result ---") - print(f"Text: {result.alternatives[0].text}") - print("------------------\n") - else: - print("ASR returned no text.") - - except FileNotFoundError: - print(f"Error: Audio file not found at {audio_path}") - except Exception as e: - print(f"An error occurred: {e}") - - -if __name__ == "__main__": - asyncio.run(test()) diff --git a/test_livekit.py b/test_livekit.py deleted file mode 100644 index 4009dfa..0000000 --- a/test_livekit.py +++ /dev/null @@ -1,130 +0,0 @@ -import asyncio -import requests -from livekit import rtc - -import wave -import numpy as np -from livekit.rtc import AudioSource, AudioFrame, LocalAudioTrack - -TOKEN_URL = "http://localhost:8000/getToken" -WS_URL = "wss://esp32-vt80c4y6.livekit.cloud" # 你的 LiveKit Server 地址 - -ROOM_NAME = "test-room20" -import uuid -IDENTITY = f"uv-{uuid.uuid4().hex[:6]}" -# IDENTITY = "test-user0" - - -def get_token(): - resp = requests.get( - TOKEN_URL, - params={ - "room": ROOM_NAME, - "identity": IDENTITY, - "agent_name": "my-agent", # 关键！！！ - }, - ) - data = resp.json() - return data["token"] - - -async def main(): - token = get_token() - - room = rtc.Room() - - @room.on("participant_connected") - def on_participant_connected(participant): - print(f"✅ 有人加入房间: {participant.identity}") - - @room.on("participant_disconnected") - def on_participant_disconnected(participant): - print(f"❌ 有人离开房间: {participant.identity}") - - print("🔌 正在连接房间...") - await room.connect(WS_URL, token) - - print("✅ 已连接房间:", ROOM_NAME) - print("当前房间成员：") - for p in room.remote_participants.values(): - print(" -", p.identity) - - @room.on("data_received") - def on_data_received(data, participant, kind, topic): - try: - msg = data.decode() - print(f"📩 来自 {participant.identity}: {msg}") - except: - print("📩 收到二进制数据") - - @room.on("track_subscribed") - def on_track_subscribed(track, publication, participant): - print(f"🎧 订阅轨道: {participant.identity}") - - if track.kind == rtc.TrackKind.KIND_AUDIO: - print("👉 TTS 音频来了") - - # 等一下确保连接稳定 - await asyncio.sleep(1) - await room.local_participant.publish_data( - b"hello", - reliable=True, - topic="chat" - ) - # 上传 wav - await publish_wav(room, "2food.wav") - - await room.disconnect() - - -async def publish_wav(room, wav_path): - print("🎵 开始上传本地 wav:", wav_path) - - wf = wave.open(wav_path, "rb") - - sample_rate = wf.getframerate() - num_channels = wf.getnchannels() - sample_width = wf.getsampwidth() - - print(f"📊 WAV信息: {sample_rate}Hz, {num_channels}ch, {sample_width*8}bit") - - # 创建音频源 - source = AudioSource(sample_rate, num_channels) - - # 创建本地音轨 - track = LocalAudioTrack.create_audio_track("mic", source) - - # 发布轨道 - await room.local_participant.publish_track(track) - print("📡 已发布音轨") - - frame_duration = 0.02 # 20ms - samples_per_frame = int(sample_rate * frame_duration) - - while True: - data = wf.readframes(samples_per_frame) - if not data: - break - - # 用于计算长度 - audio = np.frombuffer(data, dtype=np.int16) - - if len(audio) == 0: - continue - - samples_per_channel = len(audio) // num_channels - - frame = AudioFrame( - data=data, # ✅ 关键：用 bytes - sample_rate=sample_rate, - num_channels=num_channels, - samples_per_channel=samples_per_channel, - ) - - await source.capture_frame(frame) - await asyncio.sleep(frame_duration) - print("✅ wav 推流结束") - - -if __name__ == "__main__": - asyncio.run(main()) \ No newline at end of file diff --git a/test_minimax.py b/test_minimax.py deleted file mode 100644 index d64edff..0000000 --- a/test_minimax.py +++ /dev/null @@ -1,71 +0,0 @@ -import asyncio -import os -import logging -from dotenv import load_dotenv -from livekit.agents.llm import ChatContext -from livekit.plugins import openai - -# Configure logging to see what's happening -logging.basicConfig(level=logging.INFO) -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}") diff --git a/test_voxcpm.py b/test_voxcpm.py deleted file mode 100644 index 59e58c7..0000000 --- a/test_voxcpm.py +++ /dev/null @@ -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())