[全量] 初始化项目代码、配置、文档及Agent协同harness

langchain-chat/server/chat/rew_rewrite.py

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+from fastapi import Body
+from configs import LLM_MODELS, TEMPERATURE, MAX_TOKENS
+from server.chat.policy_fun_iast import get_llm_model_response
+from typing import Optional
+from langchain.chains import LLMChain
+from langchain.prompts import ChatPromptTemplate
+from server.chat.utils import History
+from server.utils import wrap_done, get_ChatOpenAI, get_prompt_template
+from langchain.callbacks import AsyncIteratorCallbackHandler
+import asyncio
+from server.knowledge_base.kb_service.base import TextRank
+from configs.basic_config import *
+
+async def rew_rewrite(
+    context: str = Body(..., description="当前已撰写的全文", examples=[""]),
+    paragraph_content: str = Body(..., description="用户框选的段落", examples=[""]),
+    previous_text: str = Body(..., description="用户框选段落的前文", examples=[""]),
+    following_text: str = Body(..., description="用户框选段落的后文", examples=[""]),
+    con_direction: Optional[str] = Body("", description="用户输入的重写指令", examples=[""]),
+    stream: bool = Body(False, description="是否流式输出", examples=[False]),
+    temperature: float = Body(TEMPERATURE, description="LLM 采样温度", ge=0.0, le=2.0),
+    max_tokens: Optional[int] = Body(MAX_TOKENS, description="限制LLM生成Token数量，默认None代表模型最大值"),
+    prompt_name: str = Body("rew_rewrite"),
+):
+    logger.info(f"开始重写...")
+
+    # 定义生成摘要的函数
+    def generate_summary(text: str) -> str:
+        """使用 TextRank 生成文本摘要"""
+        summary = TextRank(text, num_sentences=80)  # 生成80句话的摘要
+        return summary
+
+    # 根据上下文长度决定是否生成摘要
+    if len(context) >= 30000:
+        context_summary = generate_summary(context)
+        logger.info(f"生成撰写文稿的摘要: %s", context_summary)
+    else:
+        context_summary = context  # 直接使用原文
+        logger.info(f"撰写文稿小于30000字符，使用原文")
+
+    # 调用模型生成重写内容
+    try:
+        rew_rewrite_content = get_llm_model_response(
+            strategy_name="rew_rewrite",
+            llm_model_name=LLM_MODELS[0],
+            template_prompt_name="rew_rewrite",
+            prompt_param_dict={
+                "context": context_summary,  # 使用摘要或原文
+                "paragraph_content": paragraph_content,
+                "con_direction": con_direction,
+                "previous_text": previous_text,
+                "following_text": following_text
+            },
+            temperature=TEMPERATURE,
+            max_tokens=MAX_TOKENS
+        )
+        # logger.info("生成的重写内容: %s", rew_rewrite_content)
+    except Exception as e:
+        logger.error("生成重写内容时出错: %s", e)
+        return (f"出错了。。请重试。。")
+    logger.info("重写内容: %s", rew_rewrite_content)
+    return rew_rewrite_content
+    # # 如果 previous_text 和 following_text 存在空值，直接返回 rew_rewrite_content
+    # if not previous_text or not following_text:
+    #     logger.info("上文或下文为空，直接返回生成的内容。。")
+    #     final_content = rew_rewrite_content
+    # else:
+    #     # 定义内容检查函数
+    #     def rew_rewrite_check(rew_rewrite_content: str) -> str:
+    #         logger.info("对文章重写内容进行行文检查。。")
+    #         logger.info("检查前的重写内容: %s", rew_rewrite_content)            
+    #         try:
+    #             rew_rewrite_check_content = get_llm_model_response(
+    #                     strategy_name="rew_rewrite_check",
+    #                     llm_model_name=LLM_MODELS[0],
+    #                     template_prompt_name="rew_rewrite_check",
+    #                     prompt_param_dict={
+    #                         "previous_text": previous_text,
+    #                         "following_text": following_text,
+    #                         "rew_rewrite_content": rew_rewrite_content,  # 使用生成的 rew_rewrite_content
+    #                     },
+    #                     temperature=temperature,
+    #                     max_tokens=max_tokens
+    #                 )
+    #             logger.info("检查后的重写内容: %s", rew_rewrite_check_content)
+    #             return rew_rewrite_check_content
+    #         except Exception as e:
+    #             logger.error("检查重写内容时出错: %s", e)
+    #             return (f"出错了。。请重试。。")
+
+    #     # 调用内容检查函数
+    #     final_content = rew_rewrite_check(rew_rewrite_content)
+
+    # # 返回最终生成的字符串
+    # return final_content