更改generator的返回值为一个数据模型稳定api

src/plugin_system/apis/generator_api.py

@@ -21,6 +21,7 @@ from src.plugin_system.base.component_types import ActionInfo
 if TYPE_CHECKING:
     from src.common.data_models.info_data_model import ActionPlannerInfo
     from src.common.data_models.database_data_model import DatabaseMessages
+    from src.common.data_models.llm_data_model import LLMGenerationDataModel
 
 install(extra_lines=3)
 
@@ -85,11 +86,9 @@ async def generate_reply(
     enable_tool: bool = False,
     enable_splitter: bool = True,
     enable_chinese_typo: bool = True,
-    return_prompt: bool = False,
     request_type: str = "generator_api",
     from_plugin: bool = True,
-    return_expressions: bool = False,
-) -> Tuple[bool, List[Tuple[str, Any]], Optional[str], Optional[List[int]]]:
+) -> Tuple[bool, Optional["LLMGenerationDataModel"]]:
     """生成回复
 
     Args:
@@ -117,7 +116,7 @@ async def generate_reply(
         replyer = get_replyer(chat_stream, chat_id, request_type=request_type)
         if not replyer:
             logger.error("[GeneratorAPI] 无法获取回复器")
-            return False, [], None, None
+            return False, None
 
         if not extra_info and action_data:
             extra_info = action_data.get("extra_info", "")
@@ -126,7 +125,7 @@ async def generate_reply(
             reply_reason = action_data.get("reason", "")
 
         # 调用回复器生成回复
-        success, llm_response_dict, prompt, selected_expressions = await replyer.generate_reply_with_context(
+        success, llm_response = await replyer.generate_reply_with_context(
             extra_info=extra_info,
             available_actions=available_actions,
             chosen_actions=chosen_actions,
@@ -138,43 +137,27 @@ async def generate_reply(
         )
         if not success:
             logger.warning("[GeneratorAPI] 回复生成失败")
-            return False, [], None, None
-        assert llm_response_dict is not None, "llm_response_dict不应为None"  # 虽然说不会出现llm_response为空的情况
-        if content := llm_response_dict.get("content", ""):
+            return False, None
+        if content := llm_response.content:
             reply_set = process_human_text(content, enable_splitter, enable_chinese_typo)
         else:
             reply_set = []
+        llm_response.reply_set = reply_set
         logger.debug(f"[GeneratorAPI] 回复生成成功，生成了 {len(reply_set)} 个回复项")
 
-        # if return_prompt:
-        #     if return_expressions:
-        #         return success, reply_set, prompt, selected_expressions
-        #     else:
-        #         return success, reply_set, prompt, None
-        # else:
-        #     if return_expressions:
-        #         return success, reply_set, (None, selected_expressions)
-        #     else:
-        #         return success, reply_set, None
-        return (
-            success,
-            reply_set,
-            prompt if return_prompt else None,
-            selected_expressions if return_expressions else None,
-        )
+        return success, llm_response
 
     except ValueError as ve:
         raise ve
 
     except UserWarning as uw:
         logger.warning(f"[GeneratorAPI] 中断了生成: {uw}")
-        return False, [], None, None
+        return False, None
 
     except Exception as e:
         logger.error(f"[GeneratorAPI] 生成回复时出错: {e}")
         logger.error(traceback.format_exc())
-        return False, [], None, None
-
+        return False, None
 
 async def rewrite_reply(
     chat_stream: Optional[ChatStream] = None,
@@ -185,9 +168,8 @@ async def rewrite_reply(
     raw_reply: str = "",
     reason: str = "",
     reply_to: str = "",
-    return_prompt: bool = False,
     request_type: str = "generator_api",
-) -> Tuple[bool, List[Tuple[str, Any]], Optional[str]]:
+) -> Tuple[bool, Optional["LLMGenerationDataModel"]]:
     """重写回复
 
     Args:
@@ -210,7 +192,7 @@ async def rewrite_reply(
         replyer = get_replyer(chat_stream, chat_id, request_type=request_type)
         if not replyer:
             logger.error("[GeneratorAPI] 无法获取回复器")
-            return False, [], None
+            return False, None
 
         logger.info("[GeneratorAPI] 开始重写回复")
 
@@ -221,29 +203,28 @@ async def rewrite_reply(
             reply_to = reply_to or reply_data.get("reply_to", "")
 
         # 调用回复器重写回复
-        success, content, prompt = await replyer.rewrite_reply_with_context(
+        success, llm_response = await replyer.rewrite_reply_with_context(
             raw_reply=raw_reply,
             reason=reason,
             reply_to=reply_to,
-            return_prompt=return_prompt,
         )
         reply_set = []
-        if content:
+        if success and llm_response and (content := llm_response.content):
             reply_set = process_human_text(content, enable_splitter, enable_chinese_typo)
-
+        llm_response.reply_set = reply_set
         if success:
             logger.info(f"[GeneratorAPI] 重写回复成功，生成了 {len(reply_set)} 个回复项")
         else:
             logger.warning("[GeneratorAPI] 重写回复失败")
 
-        return success, reply_set, prompt if return_prompt else None
+        return success, llm_response
 
     except ValueError as ve:
         raise ve
 
     except Exception as e:
         logger.error(f"[GeneratorAPI] 重写回复时出错: {e}")
-        return False, [], None
+        return False, None
 
 
 def process_human_text(content: str, enable_splitter: bool, enable_chinese_typo: bool) -> List[Tuple[str, Any]]: