File size: 5,729 Bytes
38d8dc2 | 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 | import os
import openai
import threading
from concurrent.futures import ThreadPoolExecutor
from openai import APIError
API_KEY = os.getenv("DEEPSEEK_API_KEY", "your_api_key")
class ThreadSafeWriter:
"""线程安全写入器"""
def __init__(self, output_path: str):
self.file = open(output_path, 'a+', encoding='utf-8')
self.lock = threading.Lock()
self.counter = 0
def write_line(self, content: str):
with self.lock:
self.file.write(content + '\n')
self.file.flush()
self.counter += 1
def get_progress(self):
with self.lock:
return self.counter
def close(self):
self.file.close()
class DeepSeekBatchProcessor:
def __init__(self, max_workers: int = 100):
self.client = openai.OpenAI(
api_key=API_KEY,
base_url="https://api.deepseek.com/v1"
)
self.max_workers = max_workers
self.error_flag = threading.Event()
self.rate_limiter = threading.Semaphore(20)
def process_batch(self, batch, writer: ThreadSafeWriter):
"""批量处理，每个任务单独线程"""
futures = []
with ThreadPoolExecutor(max_workers=self.max_workers) as executor:
for line_num, line in batch:
if self.error_flag.is_set():
break
futures.append(
executor.submit(
self._process_single_line,
line_num,
line,
writer
)
)
for future in futures:
future.result()
def _process_single_line(self, line_num: int, line: str, writer: ThreadSafeWriter):
if self.error_flag.is_set():
return
# 支持英文冒号(:)和中文全角冒号(：)
separator = None
if ':' in line:
separator = ':'
elif '：' in line:
separator = '：'
if not separator:
print(f"\n行 {line_num} 格式错误")
writer.write_line(f"格式错误：{line}")
return
keywords_part, original_text = line.split(separator, 1)
# 这里只提取关键词部分（例如“风，雾，寂寞”）
keywords = [kw.strip() for kw in keywords_part.split("，") if kw.strip()]
if not keywords:
keywords = ["无关键词"]
# 构造提示：根据关键词生成诗歌
prompt = "请根据以下关键词写一首诗：" + "，".join(keywords)
messages = [{"role": "user", "content": prompt}]
retries = 0
while retries < 3 and not self.error_flag.is_set():
try:
with self.rate_limiter:
response = self.client.chat.completions.create(
model="deepseek-reasoner",
messages=messages,
temperature=0.1
)
# 提取返回中的思考过程和诗歌原文
reasoning_content = response.choices[0].message.reasoning_content.replace('\n', '').replace('\r', '')
poem_original = response.choices[0].message.content.replace('\n', '/').replace('\r', '')
# 拼接最终结果：关键词<think>思考过程</think>:诗歌原文
final_line = f"{'，'.join(keywords)}<think>{reasoning_content}</think>:{poem_original}"
writer.write_line(final_line)
progress = writer.get_progress()
print(f"\r已处理 {progress} 条", end='')
break
except APIError as e:
if e.status_code == 402:
print(f"\n行 {line_num} 处理失败：API余额不足")
self.error_flag.set()
return
elif e.status_code == 429:
print(f"\n行 {line_num} 速率受限，重试中...")
retries += 1
if retries >= 3:
print(f"\n行 {line_num} 重试次数耗尽")
else:
print(f"\n行 {line_num} API错误[{e.status_code}]：{e.message}")
return
except Exception as e:
print(f"\n行 {line_num} 处理异常：{str(e)}")
retries += 1
if retries >= 3:
print(f"\n行 {line_num} 重试次数耗尽")
if retries >= 3 and not self.error_flag.is_set():
writer.write_line(f"处理失败：{line}")
def process_first_1000_lines(input_path: str, output_path: str, max_workers: int = 100):
"""仅读取前1000行数据，并使用多线程处理"""
processor = DeepSeekBatchProcessor(max_workers)
writer = ThreadSafeWriter(output_path)
batch = []
try:
with open(input_path, 'r', encoding='utf-8') as f:
for line_num, line in enumerate(f, 1):
if not line.strip():
continue
batch.append( (line_num, line.strip()) )
if line_num >= 1000:
break
total = len(batch)
print(f"总数据量：{total} 条")
processor.process_batch(batch, writer)
print("\n处理完成！")
finally:
writer.close()
if __name__ == '__main__':
input_file = "data/DSdata.txt"
output_file = "data/CoTdata.txt"
process_first_1000_lines(input_file, output_file, max_workers=100)
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