doubao_analyzer.py
12.4 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
# -*- coding: utf-8 -*-
"""
火山引擎豆包音乐分析器实现
"""
import os
import time
import logging
from typing import Dict, Any, Optional
from dotenv import load_dotenv
from pathlib import Path
import httpx
from .base import AudioAnalyzer
from .prompts import build_analyze_prompt, build_lyrics_prompt
_ROOT_DIR = Path(__file__).resolve().parents[2]
load_dotenv(_ROOT_DIR / ".env")
logger = logging.getLogger(__name__)
class DoubaoAnalyzer(AudioAnalyzer):
"""火山引擎豆包音乐分析器"""
def __init__(
self,
api_key: Optional[str] = None,
base_url: Optional[str] = None,
model: Optional[str] = None,
timeout: float = 60.0,
max_retries: int = 3,
):
"""
初始化豆包分析器
Args:
api_key: API Key(默认从环境变量读取 DOUBAO_API_KEY 或 ARK_API_KEY)
base_url: API 基础URL(默认: https://ark.cn-beijing.volces.com/api/v3)
model: 模型名称(默认: doubao-seed-1-8-251228)
timeout: 超时时间(秒)
max_retries: 最大重试次数
"""
self.api_key = api_key or os.getenv("DOUBAO_API_KEY", os.getenv("ARK_API_KEY"))
self.base_url = base_url or os.getenv(
"DOUBAO_BASE_URL", "https://ark.cn-beijing.volces.com/api/v3"
)
self.model = model or os.getenv("DOUBAO_MODEL", "doubao-seed-1-8-251228")
self.timeout = timeout
self.max_retries = max_retries
self._client = None
def _get_client(self) -> httpx.Client:
"""获取 HTTP 客户端"""
if self._client is None:
self._client = httpx.Client(
base_url=self.base_url,
timeout=self.timeout,
headers={
"Authorization": f"Bearer {self.api_key}",
"Content-Type": "application/json",
},
)
return self._client
def get_provider_name(self) -> str:
return "doubao"
def get_model_name(self) -> str:
return self.model
def analyze(
self,
metadata: Dict[str, Any],
music_url: str,
extract_lyrics: bool = False,
label_level: int = 0,
) -> Optional[Dict[str, Any]]:
"""
分析音乐
Args:
metadata: 音乐元数据
music_url: 音乐文件 URL
extract_lyrics: 是否识别歌词
label_level: 标签级别
Returns:
分析结果字典
"""
client = self._get_client()
if extract_lyrics:
return self._analyze_with_lyrics(client, metadata, music_url, label_level)
else:
return self._analyze_basic(client, metadata, music_url, label_level)
def _analyze_basic(
self,
client: httpx.Client,
metadata: Dict[str, Any],
music_url: str,
label_level: int = 0,
) -> Optional[Dict[str, Any]]:
"""基础分析(不含歌词)"""
system_prompt, user_prompt = build_analyze_prompt(
metadata=metadata,
include_lyrics=False,
label_level=label_level,
)
# 打印提示词到日志
logger.info(f"[DoubaoAnalyzer] System Prompt:\n{system_prompt}")
logger.info(f"[DoubaoAnalyzer] User Prompt:\n{user_prompt}")
messages = self._build_messages(system_prompt, user_prompt, music_url)
response = self._call_with_retry(client, messages)
if response is None:
return None
result = self._parse_response(response.get("content", ""))
if result is None:
return None
return self._normalize_result(result, self.model, response.get("usage"))
def _analyze_with_lyrics(
self,
client: httpx.Client,
metadata: Dict[str, Any],
music_url: str,
label_level: int = 0,
) -> Optional[Dict[str, Any]]:
"""分析(含歌词识别,需要两次调用)"""
# 第一次调用:基本信息(不含歌词)
system_prompt, user_prompt = build_analyze_prompt(
metadata=metadata,
include_lyrics=False,
label_level=label_level,
)
# 打印提示词到日志
logger.info(f"[DoubaoAnalyzer] System Prompt (with lyrics):\n{system_prompt}")
logger.info(f"[DoubaoAnalyzer] User Prompt (with lyrics):\n{user_prompt}")
messages_basic = self._build_messages(system_prompt, user_prompt, music_url)
response_basic = self._call_with_retry(client, messages_basic)
if response_basic is None:
return None
result = self._parse_response(response_basic.get("content", ""))
if result is None:
return None
# 第二次调用:歌词识别
lyrics_prompt = build_lyrics_prompt()
# 打印歌词识别提示词到日志
logger.info(f"[DoubaoAnalyzer] Lyrics Prompt:\n{lyrics_prompt}")
messages_lyrics = self._build_messages(
"请识别这段音频中的歌词内容", lyrics_prompt, music_url
)
response_lyrics = self._call_with_retry(client, messages_lyrics)
lyrics_result = None
if response_lyrics:
lyrics_result = self._parse_response(response_lyrics.get("content", ""))
if lyrics_result and "lyrics" in lyrics_result:
result["lyrics"] = lyrics_result["lyrics"]
# 合并 token 使用信息
usage = response_basic.get("usage", {})
if response_lyrics and response_lyrics.get("usage"):
usage_lyrics = response_lyrics["usage"]
usage = {
"prompt_tokens": usage.get("prompt_tokens", 0)
+ usage_lyrics.get("prompt_tokens", 0),
"completion_tokens": usage.get("completion_tokens", 0)
+ usage_lyrics.get("completion_tokens", 0),
"total_tokens": usage.get("total_tokens", 0)
+ usage_lyrics.get("total_tokens", 0),
}
return self._normalize_result(result, self.model, usage)
def _build_messages(
self,
system_prompt: str,
user_prompt: str,
music_url: str,
) -> list:
"""构建消息格式"""
return [
{
"role": "user",
"content": [
{"type": "video_url", "video_url": {"url": music_url}},
{"type": "text", "text": user_prompt},
],
}
]
def _call_with_retry(
self,
client: httpx.Client,
messages: list,
) -> Optional[Dict]:
"""带重试的 API 调用"""
endpoint = "/chat/completions"
data = {
"model": self.model,
"messages": messages,
"temperature": 0.7,
"max_tokens": 4000,
"stream": False,
}
for attempt in range(1, self.max_retries + 1):
try:
print(f" [Doubao] 调用模型 (尝试 {attempt}/{self.max_retries})...")
start_time = time.time()
response = client.post(endpoint, json=data)
response.raise_for_status()
end_time = time.time()
elapsed = end_time - start_time
print(f" [Doubao] 响应时间: {elapsed:.2f}s")
result = response.json()
content = (
result.get("choices", [{}])[0].get("message", {}).get("content", "")
)
usage = result.get("usage", {})
print(f" [Doubao] 响应: {content[:100]}...")
return {
"content": content,
"usage": {
"prompt_tokens": usage.get("prompt_tokens", 0),
"completion_tokens": usage.get("completion_tokens", 0),
"total_tokens": usage.get("total_tokens", 0),
},
}
except httpx.HTTPError as e:
error_type = type(e).__name__
print(f" [Doubao] HTTP 错误 ({error_type}): {e}")
if attempt < self.max_retries:
wait_time = attempt
print(f" 等待 {wait_time} 秒后重试...")
time.sleep(wait_time)
else:
print(f" 已达到最大重试次数")
return None
except Exception as e:
error_type = type(e).__name__
print(f" [Doubao] 错误 ({error_type}): {e}")
if attempt < self.max_retries:
wait_time = attempt
print(f" 等待 {wait_time} 秒后重试...")
time.sleep(wait_time)
else:
print(f" 已达到最大重试次数")
return None
return None
def test_doubao_audio_url_lyrics():
"""
测试豆包是否支持通过音频URL解析音频歌词
此测试用例用于验证豆包模型是否能够:
1. 接收音频URL作为输入
2. 解析音频内容
3. 识别并返回歌词
使用方法:
python -c "from app.middleware.music_analyze.doubao_analyzer import test_doubao_audio_url_lyrics; test_doubao_audio_url_lyrics()"
或者直接在命令行运行:
python app/middleware/music_analyze/doubao_analyzer.py
"""
import json
print("=" * 80)
print("测试豆包音频URL歌词解析功能")
print("=" * 80)
# 测试音频URL(使用一个公开可访问的音频文件)
# 注意:请替换为实际可访问的音频URL
test_audio_url = "https://hikoon-ai-test.oss-cn-hangzhou.aliyuncs.com/ai/cache/modelName/20260114/_s__e_1768376270519_rmab41.mp3"
print(f"\n测试音频URL: {test_audio_url}")
print("\n开始测试...")
try:
# 初始化分析器
analyzer = DoubaoAnalyzer()
# 测试元数据
metadata = {"title": "测试歌曲", "artist": "测试艺术家", "test": True}
print("\n1. 测试基础分析(不含歌词)...")
result_basic = analyzer.analyze(
metadata=metadata,
music_url=test_audio_url,
extract_lyrics=False,
label_level=0,
)
if result_basic:
print(" ✓ 基础分析成功")
print(f" - 曲风: {result_basic.get('genre', 'N/A')}")
print(f" - 语种: {result_basic.get('language', 'N/A')}")
print(f" - 情绪: {result_basic.get('emotion', 'N/A')}")
else:
print(" ✗ 基础分析失败")
print("\n2. 测试歌词识别(含歌词)...")
result_with_lyrics = analyzer.analyze(
metadata=metadata,
music_url=test_audio_url,
extract_lyrics=True,
label_level=0,
)
if result_with_lyrics:
print(" ✓ 歌词识别分析成功")
lyrics = result_with_lyrics.get("lyrics", [])
if lyrics:
print(f" ✓ 成功识别歌词,共 {len(lyrics)} 行")
print("\n 歌词预览(前5行):")
for i, line in enumerate(lyrics[:5], 1):
time_str = line.get("time", "N/A")
text = line.get("text", "")
print(f" [{i}] {time_str} - {text}")
if len(lyrics) > 5:
print(f" ... 还有 {len(lyrics) - 5} 行")
print("\n ✓ 测试通过:豆包支持音频URL解析歌词")
else:
print(" ⚠ 未识别到歌词(可能是纯音乐或无法识别)")
print("\n ! 测试结果:豆包支持音频URL解析,但未返回歌词")
# 输出完整结果
print("\n3. 完整分析结果:")
print(json.dumps(result_with_lyrics, ensure_ascii=False, indent=2))
else:
print(" ✗ 歌词识别分析失败")
print("\n ✗ 测试失败:豆包可能不支持音频URL解析")
print("\n" + "=" * 80)
print("测试完成")
print("=" * 80)
return result_with_lyrics
except Exception as e:
print(f"\n✗ 测试过程中发生错误: {e}")
import traceback
traceback.print_exc()
return None
if __name__ == "__main__":
test_doubao_audio_url_lyrics()