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增加了多阶段模型参数的单独读取

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jinye_huang 2025-07-09 14:51:02 +08:00
parent 5fd1e2fd85
commit d4d23068e5
12 changed files with 95 additions and 22 deletions
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6
config/ai_model.json
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@ -2,9 +2,9 @@
"model": "qwen-plus",
"api_url": "https://dashscope.aliyuncs.com/compatible-mode/v1",
"api_key": "sk-bd5ee62703bc41fc9b8a55d748dc1eb8",
"temperature": 0.8,
"top_p": 0.5,
"presence_penalty": 1.1,
"temperature": 0.3,
"top_p": 0.4,
"presence_penalty": 1.2,
"timeout": 120,
"max_retries": 3
}

12
config/content_gen.json
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@ -3,5 +3,15 @@
"content_user_prompt": "resource/prompt/generateContent/user.txt",
"judger_system_prompt": "resource/prompt/judgeContent/system.txt",
"judger_user_prompt": "resource/prompt/judgeContent/user.txt",
"enable_content_judge": true
"enable_content_judge": true,
"model": {
"temperature": 0.3,
"top_p": 0.5,
"presence_penalty": 1.2
},
"judger_model": {
"temperature": 0.2,
"top_p": 0.3,
"presence_penalty": 0.8
}
}

2
config/resource.json
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@ -16,7 +16,7 @@
"refer_list": [
{ "path": "resource/prompt/Refer/2025各月节日宣传节点时间表.md", "sampling_rate": 1, "step": "topic" },
{ "path": "resource/prompt/Refer/标题参考格式.json", "sampling_rate": 0.25, "step": "content" },
{ "path": "resource/prompt/Refer/正文范文参考.json", "sampling_rate": 0.25, "step": "content" }
{ "path": "resource/prompt/Refer/正文范文参考.json", "sampling_rate": 0.5, "step": "content" }
]
},
"object": {

6
config/topic_gen.json
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@ -1,7 +1,11 @@
{
"topic_system_prompt": "resource/prompt/generateTopics/system.txt",
"topic_user_prompt": "resource/prompt/generateTopics/user.txt",
"model": {},
"model": {
"temperature": 0.2,
"top_p": 0.3,
"presence_penalty": 1.5
},
"topic": {
"date": "2024-07-20",
"num": 5,

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core/ai/__pycache__/ai_agent.cpython-312.pyc
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34
core/ai/ai_agent.py
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@ -45,7 +45,9 @@ class AIAgent:
# self.tokenizer = tiktoken.get_encoding("cl100k_base")
async def generate_text(
self, system_prompt: str, user_prompt: str, use_stream: bool = False
self, system_prompt: str, user_prompt: str, use_stream: bool = False,
temperature: Optional[float] = None, top_p: Optional[float] = None,
presence_penalty: Optional[float] = None, stage: str = ""
) -> Tuple[str, int, int, float]:
"""
生成文本 (支持流式和非流式)
@ -54,6 +56,10 @@ class AIAgent:
system_prompt: 系统提示
user_prompt: 用户提示
use_stream: 是否流式返回
temperature: 温度参数，控制随机性
top_p: Top-p采样参数
presence_penalty: 存在惩罚参数
stage: 当前所处阶段，用于日志记录
Returns:
一个元组 (generated_text, input_tokens, output_tokens, time_cost)
@ -63,8 +69,17 @@ class AIAgent:
{"role": "user", "content": user_prompt}
]
# 使用传入的参数或默认配置
temp = temperature if temperature is not None else self.config.temperature
tp = top_p if top_p is not None else self.config.top_p
pp = presence_penalty if presence_penalty is not None else self.config.presence_penalty
# 记录使用的模型参数
stage_info = f"[{stage}]" if stage else ""
logger.info(f"{stage_info} 使用模型参数: temperature={temp:.2f}, top_p={tp:.2f}, presence_penalty={pp:.2f}")
input_tokens = self.count_tokens(system_prompt + user_prompt)
logger.info(f"开始生成任务... 输入token数: {input_tokens}")
logger.info(f"{stage_info} 开始生成任务... 输入token数: {input_tokens}")
last_exception = None
backoff_time = 1.0 # Start with 1 second
@ -75,9 +90,9 @@ class AIAgent:
response = await self.client.chat.completions.create(
model=self.config.model,
messages=messages,
temperature=self.config.temperature,
top_p=self.config.top_p,
presence_penalty=self.config.presence_penalty,
temperature=temp,
top_p=tp,
presence_penalty=pp,
stream=use_stream
)
@ -90,26 +105,27 @@ class AIAgent:
# 简化处理：流式模式下，我们返回拼接后的完整文本
full_text = "".join([chunk for chunk in self._process_stream(response)])
output_tokens = self.count_tokens(full_text)
logger.info(f"{stage_info} 任务完成，耗时 {time_cost:.2f} 秒. 输出token数: {output_tokens}")
return full_text, input_tokens, output_tokens, time_cost
else:
output_text = response.choices[0].message.content.strip()
output_tokens = self.count_tokens(output_text)
logger.info(f"任务完成，耗时 {time_cost:.2f} 秒. 输出token数: {output_tokens}")
logger.info(f"{stage_info} 任务完成，耗时 {time_cost:.2f} 秒. 输出token数: {output_tokens}")
return output_text, input_tokens, output_tokens, time_cost
except (APITimeoutError, APIConnectionError) as e:
last_exception = RetryableError(f"AI模型连接或超时错误: {e}")
logger.warning(f"尝试 {attempt + 1}/{self.config.max_retries} 失败: {last_exception}. "
logger.warning(f"{stage_info} 尝试 {attempt + 1}/{self.config.max_retries} 失败: {last_exception}. "
f"将在 {backoff_time:.1f} 秒后重试...")
time.sleep(backoff_time)
backoff_time *= 2 # Exponential backoff
except (RateLimitError, APIStatusError) as e:
last_exception = NonRetryableError(f"AI模型API错误 (不可重试): {e}")
logger.error(f"发生不可重试的API错误: {last_exception}")
logger.error(f"{stage_info} 发生不可重试的API错误: {last_exception}")
break # Do not retry on these errors
except Exception as e:
last_exception = AIModelError(f"调用AI模型时发生未知错误: {e}")
logger.error(f"发生未知错误: {last_exception}\n{traceback.format_exc()}")
logger.error(f"{stage_info} 发生未知错误: {last_exception}\n{traceback.format_exc()}")
break
raise AIModelError(f"AI模型调用在 {self.config.max_retries} 次重试后失败") from last_exception

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utils/tweet/__pycache__/content_generator.cpython-312.pyc
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utils/tweet/__pycache__/content_judger.cpython-312.pyc
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utils/tweet/__pycache__/topic_generator.cpython-312.pyc
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21
utils/tweet/content_generator.py
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@ -10,7 +10,7 @@ import json
from typing import Dict, Any
from core.ai import AIAgent
from core.config import ConfigManager, GenerateTopicConfig
from core.config import ConfigManager, GenerateTopicConfig, GenerateContentConfig
from utils.prompts import ContentPromptBuilder
from utils.file_io import OutputManager
@ -22,7 +22,9 @@ class ContentGenerator:
def __init__(self, ai_agent: AIAgent, config_manager: ConfigManager, output_manager: OutputManager):
self.ai_agent = ai_agent
self.config: GenerateTopicConfig = config_manager.get_config('topic_gen', GenerateTopicConfig)
self.config_manager = config_manager
self.topic_config = config_manager.get_config('topic_gen', GenerateTopicConfig)
self.content_config = config_manager.get_config('content_gen', GenerateContentConfig)
self.output_manager = output_manager
self.prompt_builder = ContentPromptBuilder(config_manager)
@ -49,12 +51,25 @@ class ContentGenerator:
self.output_manager.save_text(system_prompt, "content_system_prompt.txt", subdir=output_dir.name)
self.output_manager.save_text(user_prompt, "content_user_prompt.txt", subdir=output_dir.name)
# 获取模型参数
model_params = {}
if hasattr(self.content_config, 'model') and isinstance(self.content_config.model, dict):
model_params = {
'temperature': self.content_config.model.get('temperature'),
'top_p': self.content_config.model.get('top_p'),
'presence_penalty': self.content_config.model.get('presence_penalty')
}
# 移除None值
model_params = {k: v for k, v in model_params.items() if v is not None}
# 2. 调用AI
try:
raw_result, _, _, _ = await self.ai_agent.generate_text(
system_prompt=system_prompt,
user_prompt=user_prompt,
use_stream=False
use_stream=False,
stage="内容生成",
**model_params
)
self.output_manager.save_text(raw_result, "content_raw_response.txt", subdir=output_dir.name)
except Exception as e:

21
utils/tweet/content_judger.py
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@ -11,7 +11,7 @@ from json_repair import loads as json_repair_loads
from typing import Dict, Any
from core.ai import AIAgent
from core.config import ConfigManager, GenerateTopicConfig
from core.config import ConfigManager, GenerateTopicConfig, GenerateContentConfig
from utils.prompts import JudgerPromptBuilder
logger = logging.getLogger(__name__)
@ -30,7 +30,9 @@ class ContentJudger:
output_manager: 输出管理器，用于保存提示词和响应
"""
self.ai_agent = ai_agent
self.config: GenerateTopicConfig = config_manager.get_config('topic_gen', GenerateTopicConfig)
self.config_manager = config_manager
self.topic_config = config_manager.get_config('topic_gen', GenerateTopicConfig)
self.content_config = config_manager.get_config('content_gen', GenerateContentConfig)
self.prompt_builder = JudgerPromptBuilder(config_manager)
self.output_manager = output_manager
@ -63,12 +65,25 @@ class ContentJudger:
self.output_manager.save_text(system_prompt, f"{topic_dir}/judger_system_prompt.txt")
self.output_manager.save_text(user_prompt, f"{topic_dir}/judger_user_prompt.txt")
# 获取模型参数
model_params = {}
if hasattr(self.content_config, 'judger_model') and isinstance(self.content_config.judger_model, dict):
model_params = {
'temperature': self.content_config.judger_model.get('temperature'),
'top_p': self.content_config.judger_model.get('top_p'),
'presence_penalty': self.content_config.judger_model.get('presence_penalty')
}
# 移除None值
model_params = {k: v for k, v in model_params.items() if v is not None}
# 2. 调用AI进行审核
try:
raw_result, _, _, _ = await self.ai_agent.generate_text(
system_prompt=system_prompt,
user_prompt=user_prompt,
use_stream=False
use_stream=False,
stage="内容审核",
**model_params
)
# 保存原始响应

15
utils/tweet/topic_generator.py
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@ -55,12 +55,25 @@ class TopicGenerator:
self.output_manager.save_text(system_prompt, "topic_system_prompt.txt")
self.output_manager.save_text(user_prompt, "topic_user_prompt.txt")
# 获取模型参数
model_params = {}
if hasattr(self.config, 'model') and isinstance(self.config.model, dict):
model_params = {
'temperature': self.config.model.get('temperature'),
'top_p': self.config.model.get('top_p'),
'presence_penalty': self.config.model.get('presence_penalty')
}
# 移除None值
model_params = {k: v for k, v in model_params.items() if v is not None}
# 2. 调用AI生成
try:
raw_result, _, _, _ = await self.ai_agent.generate_text(
system_prompt=system_prompt,
user_prompt=user_prompt,
use_stream=False # 选题生成通常不需要流式输出
use_stream=False, # 选题生成通常不需要流式输出
stage="选题生成",
**model_params
)
self.output_manager.save_text(raw_result, "topics_raw_response.txt")
except Exception as e: