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feat：合并normal和focus的prompt构建

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This commit is contained in:
SengokuCola
2025-07-01 12:27:14 +08:00
parent 100f9c24ab
commit a1a81194f1
12 changed files with 444 additions and 739 deletions
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120
src/plugin_system/apis/generator_api.py
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@@ -8,10 +8,12 @@
success, reply_set = await generator_api.generate_reply(chat_stream, action_data, reasoning)
"""
from typing import Tuple, Any, Dict, List
from typing import Tuple, Any, Dict, List, Optional
from src.common.logger import get_logger
from src.chat.replyer.default_generator import DefaultReplyer
from src.chat.message_receive.chat_stream import get_chat_manager
from src.chat.message_receive.chat_stream import ChatStream
from src.chat.utils.utils import process_llm_response
from src.chat.replyer.replyer_manager import replyer_manager
logger = get_logger("generator_api")
@@ -21,46 +23,36 @@ logger = get_logger("generator_api")
# =============================================================================
def get_replyer(chat_stream=None, chat_id: str = None) -> DefaultReplyer:
def get_replyer(
chat_stream: Optional[ChatStream] = None,
chat_id: Optional[str] = None,
model_configs: Optional[List[Dict[str, Any]]] = None,
request_type: str = "replyer"
) -> Optional[DefaultReplyer]:
"""获取回复器对象
优先使用chat_stream，如果没有则使用chat_id直接查找
优先使用chat_stream，如果没有则使用chat_id直接查找。
使用 ReplyerManager 来管理实例，避免重复创建。
Args:
chat_stream: 聊天流对象（优先）
chat_id: 聊天ID（实际上就是stream_id）
model_configs: 模型配置列表
request_type: 请求类型
Returns:
Optional[Any]: 回复器对象，如果获取失败则返回None
Optional[DefaultReplyer]: 回复器对象，如果获取失败则返回None
"""
try:
# 优先使用聊天流
if chat_stream:
logger.debug("[GeneratorAPI] 使用聊天流获取回复器")
return DefaultReplyer(chat_stream=chat_stream)
# 使用chat_id直接查找（chat_id即为stream_id）
if chat_id:
logger.debug("[GeneratorAPI] 使用chat_id获取回复器")
chat_manager = get_chat_manager()
if not chat_manager:
logger.warning("[GeneratorAPI] 无法获取聊天管理器")
return None
# 直接使用chat_id作为stream_id查找
target_stream = chat_manager.get_stream(chat_id)
if target_stream is None:
logger.warning(f"[GeneratorAPI] 未找到匹配的聊天流 chat_id={chat_id}")
return None
return DefaultReplyer(chat_stream=target_stream)
logger.warning("[GeneratorAPI] 缺少必要参数，无法获取回复器")
return None
logger.debug(f"[GeneratorAPI] 正在获取回复器，chat_id: {chat_id}, chat_stream: {'有' if chat_stream else '无'}")
return replyer_manager.get_replyer(
chat_stream=chat_stream,
chat_id=chat_id,
model_configs=model_configs,
request_type=request_type
)
except Exception as e:
logger.error(f"[GeneratorAPI] 获取回复器失败: {e}")
logger.error(f"[GeneratorAPI] 获取回复器时发生意外错误: {e}", exc_info=True)
return None
@@ -71,10 +63,18 @@ def get_replyer(chat_stream=None, chat_id: str = None) -> DefaultReplyer:
async def generate_reply(
chat_stream=None,
action_data: Dict[str, Any] = None,
chat_id: str = None,
action_data: Dict[str, Any] = None,
reply_to: str = "",
relation_info: str = "",
structured_info: str = "",
extra_info: str = "",
available_actions: List[str] = None,
enable_splitter: bool = True,
enable_chinese_typo: bool = True,
return_prompt: bool = False,
model_configs: Optional[List[Dict[str, Any]]] = None,
request_type: str = "",
) -> Tuple[bool, List[Tuple[str, Any]]]:
"""生成回复
@@ -84,13 +84,13 @@ async def generate_reply(
chat_id: 聊天ID（备用）
enable_splitter: 是否启用消息分割器
enable_chinese_typo: 是否启用错字生成器
return_prompt: 是否返回提示词
Returns:
Tuple[bool, List[Tuple[str, Any]]]: (是否成功, 回复集合)
"""
try:
# 获取回复器
replyer = get_replyer(chat_stream, chat_id)
replyer = get_replyer(chat_stream, chat_id, model_configs=model_configs, request_type=request_type)
if not replyer:
logger.error("[GeneratorAPI] 无法获取回复器")
return False, []
@@ -98,16 +98,26 @@ async def generate_reply(
logger.info("[GeneratorAPI] 开始生成回复")
# 调用回复器生成回复
success, reply_set = await replyer.generate_reply_with_context(
reply_data=action_data or {}, enable_splitter=enable_splitter, enable_chinese_typo=enable_chinese_typo
success, content, prompt = await replyer.generate_reply_with_context(
reply_data=action_data or {},
reply_to=reply_to,
relation_info=relation_info,
structured_info=structured_info,
extra_info=extra_info,
available_actions=available_actions,
)
reply_set = await process_human_text(content, enable_splitter, enable_chinese_typo)
if success:
logger.info(f"[GeneratorAPI] 回复生成成功，生成了 {len(reply_set)} 个回复项")
else:
logger.warning("[GeneratorAPI] 回复生成失败")
return success, reply_set or []
if return_prompt:
return success, reply_set or [], prompt
else:
return success, reply_set or []
except Exception as e:
logger.error(f"[GeneratorAPI] 生成回复时出错: {e}")
@@ -120,6 +130,7 @@ async def rewrite_reply(
chat_id: str = None,
enable_splitter: bool = True,
enable_chinese_typo: bool = True,
model_configs: Optional[List[Dict[str, Any]]] = None,
) -> Tuple[bool, List[Tuple[str, Any]]]:
"""重写回复
@@ -135,7 +146,7 @@ async def rewrite_reply(
"""
try:
# 获取回复器
replyer = get_replyer(chat_stream, chat_id)
replyer = get_replyer(chat_stream, chat_id, model_configs=model_configs)
if not replyer:
logger.error("[GeneratorAPI] 无法获取回复器")
return False, []
@@ -143,9 +154,11 @@ async def rewrite_reply(
logger.info("[GeneratorAPI] 开始重写回复")
# 调用回复器重写回复
success, reply_set = await replyer.rewrite_reply_with_context(
reply_data=reply_data or {}, enable_splitter=enable_splitter, enable_chinese_typo=enable_chinese_typo
success, content = await replyer.rewrite_reply_with_context(
reply_data=reply_data or {}
)
reply_set = await process_human_text(content, enable_splitter, enable_chinese_typo)
if success:
logger.info(f"[GeneratorAPI] 重写回复成功，生成了 {len(reply_set)} 个回复项")
@@ -157,3 +170,30 @@ async def rewrite_reply(
except Exception as e:
logger.error(f"[GeneratorAPI] 重写回复时出错: {e}")
return False, []
async def process_human_text(
content:str,
enable_splitter:bool,
enable_chinese_typo:bool
) -> List[Tuple[str, Any]]:
"""将文本处理为更拟人化的文本
Args:
content: 文本内容
enable_splitter: 是否启用消息分割器
enable_chinese_typo: 是否启用错字生成器
"""
try:
processed_response = process_llm_response(content, enable_splitter, enable_chinese_typo)
reply_set = []
for str in processed_response:
reply_seg = ("text", str)
reply_set.append(reply_seg)
return reply_set
except Exception as e:
logger.error(f"[GeneratorAPI] 处理人形文本时出错: {e}")
return []