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mainpy load审核器

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jinye_huang 2025-05-10 20:12:49 +08:00
parent 0753c733db
commit 8dc8f32b87
3 changed files with 120 additions and 16 deletions
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6
main.py
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@ -89,7 +89,8 @@ def generate_content_and_posters_step(config, run_id, topics_list, output_handle
prompts_config=config.get("prompts_config"), # 新的配置方式
resource_dir_config=config.get("resource_dir", []),
topic_gen_num=config.get("num", 1), # Topic gen num/date used by topic prompts
topic_gen_date=config.get("date", "")
topic_gen_date=config.get("date", ""),
content_judger_system_prompt_path=config.get("content_judger_system_prompt") # 添加内容审核系统提示词路径
)
logging.info("PromptManager instance created for Step 2.")
except KeyError as e:
@ -137,7 +138,8 @@ def generate_content_and_posters_step(config, run_id, topics_list, output_handle
variants=content_variants,
temperature=content_temp,
top_p=content_top_p,
presence_penalty=content_presence_penalty
presence_penalty=content_presence_penalty,
enable_content_judge=config.get("enable_content_judge", False)
)
# if tweet_content_list: # generate_content_for_topic 现在返回 bool

6
poster_gen_config.json
View File

@ -1,6 +1,6 @@
{
"date": "5月15日",
"num": 5,
"num": 2,
"variants": 20,
"topic_temperature": 0.2,
"topic_top_p": 0.3,
@ -8,13 +8,15 @@
"content_temperature": 0.3,
"content_top_p": 0.5,
"content_presence_penalty": 1.2,
"model": "qwen3-30B-A3B",
"model": "qwenQWQ",
"api_url": "http://localhost:8000/v1/",
"api_key": "EMPTY",
"enable_content_judge":true,
"topic_system_prompt": "./SelectPrompt/systemPrompt.txt",
"topic_user_prompt": "./SelectPrompt/userPrompt.txt",
"content_system_prompt": "./genPrompts/systemPrompt.txt",
"poster_content_system_prompt": "./genPrompts/poster_content_systemPrompt.txt",
"content_judger_system_prompt": "./genPrompts/judgerSystemPrompt.txt",
"prompts_config": [
{
"type": "Style",

124
utils/tweet_generator.py
View File

@ -28,6 +28,7 @@ from utils import content_generator as core_contentGen
from core import poster_gen as core_posterGen
from core import simple_collage as core_simple_collage
from .output_handler import OutputHandler # <-- 添加导入
from utils.content_judger import ContentJudger # <-- 添加ContentJudger导入
class tweetTopic:
def __init__(self, index, date, logic, object, product, product_logic, style, style_logic, target_audience, target_audience_logic):
@ -372,7 +373,8 @@ def generate_content_for_topic(ai_agent: AI_Agent,
variants: int,
temperature: float,
top_p: float,
presence_penalty: float):
presence_penalty: float,
enable_content_judge: bool):
"""Generates all content variants for a single topic item and uses OutputHandler.
Args:
@ -384,6 +386,7 @@ def generate_content_for_topic(ai_agent: AI_Agent,
output_handler: An instance of OutputHandler to process results.
variants: Number of variants to generate.
temperature, top_p, presence_penalty: AI generation parameters.
enable_content_judge: Whether to enable content judge.
Returns:
bool: True if at least one variant was successfully generated and handled, False otherwise.
"""
@ -391,6 +394,81 @@ def generate_content_for_topic(ai_agent: AI_Agent,
success_flag = False # Track if any variant succeeded
# 使用传入的 variants 参数
# variants = config.get("variants", 1)
# 如果启用了内容审核，获取产品资料
product_info = None
content_judger = None
if enable_content_judge:
logging.info(f"内容审核功能已启用，准备获取产品资料...")
# 从topic_item中获取产品名称和对象名称
product_name = topic_item.get("product", "")
object_name = topic_item.get("object", "")
# 组合获取产品资料
product_info = ""
# 获取对象信息
if object_name:
# 通过PromptManager获取对象和产品资料
# 这一部分逻辑来自PromptManager.get_content_prompts中对object_info的构建
found_object_info = False
all_description_files = []
# 从resource_dir_config搜集所有可能的资源文件
for dir_info in prompt_manager.resource_dir_config:
if dir_info.get("type") in ["Object", "Description"]:
all_description_files.extend(dir_info.get("file_path", []))
# 尝试精确匹配对象资料
for file_path in all_description_files:
if object_name in os.path.basename(file_path):
from utils.resource_loader import ResourceLoader
info = ResourceLoader.load_file_content(file_path)
if info:
product_info += f"Object: {object_name}\n{info}\n\n"
logging.info(f"为内容审核找到对象'{object_name}'的资源文件: {file_path}")
found_object_info = True
break
# 如果未找到对象资料，记录警告但继续处理
if not found_object_info:
logging.warning(f"未能为内容审核找到对象'{object_name}'的资源文件")
# 获取产品信息
if product_name:
found_product_info = False
all_product_files = []
# 搜集所有可能的产品资源文件
for dir_info in prompt_manager.resource_dir_config:
if dir_info.get("type") == "Product":
all_product_files.extend(dir_info.get("file_path", []))
# 尝试精确匹配产品资料
for file_path in all_product_files:
if product_name in os.path.basename(file_path):
from utils.resource_loader import ResourceLoader
info = ResourceLoader.load_file_content(file_path)
if info:
product_info += f"Product: {product_name}\n{info}\n\n"
logging.info(f"为内容审核找到产品'{product_name}'的资源文件: {file_path}")
found_product_info = True
break
# 如果未找到产品资料，记录警告但继续处理
if not found_product_info:
logging.warning(f"未能为内容审核找到产品'{product_name}'的资源文件")
# 如果成功获取产品资料，初始化ContentJudger
if product_info:
logging.info("成功获取产品资料，初始化ContentJudger...")
# 从配置中读取系统提示词路径（脚本级别无法直接获取，需要传递）
# 使用ai_agent的model_name或api_url判断是否使用主AI模型，避免额外资源占用
content_judger_system_prompt_path = prompt_manager._system_prompt_cache.get("judger_system_prompt")
content_judger = ContentJudger(ai_agent, system_prompt_path=content_judger_system_prompt_path)
else:
logging.warning("未能获取产品资料，内容审核功能将被跳过")
enable_content_judge = False
for j in range(variants):
variant_index = j + 1
@ -417,6 +495,37 @@ def generate_content_for_topic(ai_agent: AI_Agent,
# 简化检查，只要content_json不是None就处理它
# 即使是空标题和内容也是有效的结果
if content_json is not None:
# 进行内容审核（如果启用且ContentJudger已初始化）
if enable_content_judge and content_judger and product_info:
logging.info(f" 对Topic {topic_index}, Variant {variant_index}进行内容审核...")
# 准备审核内容
content_to_judge = f"""title: {content_json.get('title', '')}
content: {content_json.get('content', '')}
"""
# 调用ContentJudger进行审核
try:
judged_result = content_judger.judge_content(product_info, content_to_judge)
if judged_result and isinstance(judged_result, dict):
if "title" in judged_result and "content" in judged_result:
# 使用审核后的内容替换原内容
logging.info(f" 内容审核成功，使用审核后的内容替换原内容")
content_json["title"] = judged_result["title"]
content_json["content"] = judged_result["content"]
# 添加审核标记
content_json["judged"] = True
# 可选：保存审核分析结果
if "不良内容分析" in judged_result:
content_json["judge_analysis"] = judged_result["不良内容分析"]
else:
logging.warning(f" 审核结果缺少title或content字段，保留原内容")
else:
logging.warning(f" 内容审核返回无效结果，保留原内容")
except Exception as judge_err:
logging.exception(f" 内容审核过程出错: {judge_err}，保留原内容")
# Use the output handler to process/save the result
output_handler.handle_content_variant(
run_id, topic_index, variant_index, content_json, prompt_data or ""
@ -528,8 +637,7 @@ def generate_posters_for_topic(topic_item: dict,
poster_gen_instance.set_text_bg_possibility(text_bg_possibility)
except Exception as e:
logging.exception("Error initializing generators for poster creation:")
return False
return False
# --- Setup: Paths and Object Name ---
object_name = topic_item.get("object", "")
if not object_name:
@ -805,12 +913,4 @@ def generate_posters_for_topic(topic_item: dict,
traceback.print_exc()
continue
return any_poster_attempted
# main 函数不再使用，注释掉或移除
# def main():
# """主函数入口"""
# # ... (旧的 main 函数逻辑)
#
# if __name__ == "__main__":
# main()
return any_poster_attempted