feat: 解藕chat的处理器和请求器 (#772)

pkg/command/operators/default.py

@@ -24,7 +24,7 @@ class DefaultOperator(operator.CommandOperator):
 
             content = ""
             for msg in prompt.messages:
-                content += f"  {msg.role}: {msg.content}"
+                content += f"  {msg.readable_str()}\n"
 
             reply_str += f"名称: {prompt.name}\n内容: \n{content}\n\n"
 
@@ -45,18 +45,18 @@ class DefaultSetOperator(operator.CommandOperator):
         context: entities.ExecuteContext
     ) -> typing.AsyncGenerator[entities.CommandReturn, None]:
             
-            if len(context.crt_params) == 0:
+        if len(context.crt_params) == 0:
-                yield entities.CommandReturn(error=errors.ParamNotEnoughError('请提供情景预设名称'))
+            yield entities.CommandReturn(error=errors.ParamNotEnoughError('请提供情景预设名称'))
-            else:
+        else:
-                prompt_name = context.crt_params[0]
+            prompt_name = context.crt_params[0]
-        
+    
-                try:
+            try:
-                    prompt = await self.ap.prompt_mgr.get_prompt_by_prefix(prompt_name)
+                prompt = await self.ap.prompt_mgr.get_prompt_by_prefix(prompt_name)
-                    if prompt is None:
+                if prompt is None:
-                        yield entities.CommandReturn(error=errors.CommandError("设置当前会话默认情景预设失败: 未找到情景预设 {}".format(prompt_name)))
+                    yield entities.CommandReturn(error=errors.CommandError("设置当前会话默认情景预设失败: 未找到情景预设 {}".format(prompt_name)))
-                    else:
+                else:
-                        context.session.use_prompt_name = prompt.name
+                    context.session.use_prompt_name = prompt.name
-                        yield entities.CommandReturn(text=f"已设置当前会话默认情景预设为 {prompt_name}, !reset 后生效")
+                    yield entities.CommandReturn(text=f"已设置当前会话默认情景预设为 {prompt_name}, !reset 后生效")
-                except Exception as e:
+            except Exception as e:
-                    traceback.print_exc()
+                traceback.print_exc()
-                    yield entities.CommandReturn(error=errors.CommandError("设置当前会话默认情景预设失败: "+str(e)))
+                yield entities.CommandReturn(error=errors.CommandError("设置当前会话默认情景预设失败: "+str(e)))

pkg/command/operators/last.py

@@ -30,7 +30,7 @@ class LastOperator(operator.CommandOperator):
                         context.session.using_conversation = context.session.conversations[index-1]
                         time_str = context.session.using_conversation.create_time.strftime("%Y-%m-%d %H:%M:%S")
 
-                        yield entities.CommandReturn(text=f"已切换到上一个对话: {index} {time_str}: {context.session.using_conversation.messages[0].content}")
+                        yield entities.CommandReturn(text=f"已切换到上一个对话: {index} {time_str}: {context.session.using_conversation.messages[0].readable_str()}")
                         return
         else:
             yield entities.CommandReturn(error=errors.CommandOperationError('当前没有对话'))

pkg/pipeline/bansess/bansess.py

@@ -8,7 +8,10 @@ from ...config import manager as cfg_mgr
 
 @stage.stage_class('BanSessionCheckStage')
 class BanSessionCheckStage(stage.PipelineStage):
-    """访问控制处理阶段"""
+    """访问控制处理阶段
+    
+    仅检查query中群号或个人号是否在访问控制列表中。
+    """
 
     async def initialize(self):
         pass

pkg/pipeline/cntfilter/cntfilter.py

@@ -14,7 +14,18 @@ from .filters import cntignore, banwords, baiduexamine
 @stage.stage_class('PostContentFilterStage')
 @stage.stage_class('PreContentFilterStage')
 class ContentFilterStage(stage.PipelineStage):
-    """内容过滤阶段"""
+    """内容过滤阶段
+    
+    前置：
+        检查消息是否符合规则，不符合则拦截。
+        改写：
+            message_chain
+
+    后置：
+        检查AI回复消息是否符合规则，可能进行改写，不符合则拦截。
+        改写：
+            query.resp_messages
+    """
 
     filter_chain: list[filter_model.ContentFilter]
 

pkg/pipeline/cntfilter/filters/banwords.py

@@ -8,7 +8,7 @@ from ....config import manager as cfg_mgr
 
 @filter_model.filter_class("ban-word-filter")
 class BanWordFilter(filter_model.ContentFilter):
-    """根据内容禁言"""
+    """根据内容过滤"""
 
     async def initialize(self):
         pass

pkg/pipeline/longtext/longtext.py

@@ -16,6 +16,9 @@ from ...config import manager as cfg_mgr
 @stage.stage_class("LongTextProcessStage")
 class LongTextProcessStage(stage.PipelineStage):
     """长消息处理阶段
+
+    改写：
+        - resp_message_chain
     """
 
     strategy_impl: strategy.LongTextStrategy

pkg/pipeline/preproc/preproc.py

@@ -9,6 +9,16 @@ from ...plugin import events
 @stage.stage_class("PreProcessor")
 class PreProcessor(stage.PipelineStage):
     """请求预处理阶段
+
+    签出会话、prompt、上文、模型、内容函数。
+
+    改写：
+        - session
+        - prompt
+        - messages
+        - user_message
+        - use_model
+        - use_funcs
     """
 
     async def process(
@@ -27,7 +37,7 @@ class PreProcessor(stage.PipelineStage):
         query.prompt = conversation.prompt.copy()
         query.messages = conversation.messages.copy()
 
-        query.user_message = llm_entities.Message(
+        query.user_message = llm_entities.Message(  # TODO 适配多模态输入
             role='user',
             content=str(query.message_chain).strip()
         )
@@ -37,11 +47,10 @@ class PreProcessor(stage.PipelineStage):
         query.use_funcs = conversation.use_funcs
 
         # =========== 触发事件 PromptPreProcessing
-        session = query.session
 
         event_ctx = await self.ap.plugin_mgr.emit_event(
             event=events.PromptPreProcessing(
-                session_name=f'{session.launcher_type.value}_{session.launcher_id}',
+                session_name=f'{query.session.launcher_type.value}_{query.session.launcher_id}',
                 default_prompt=query.prompt.messages,
                 prompt=query.messages,
                 query=query

pkg/pipeline/process/handlers/chat.py

@@ -3,6 +3,7 @@ from __future__ import annotations
 import typing
 import time
 import traceback
+import json
 
 import mirai
 
@@ -70,17 +71,13 @@ class ChatMessageHandler(handler.MessageHandler):
                     mirai.Plain(event_ctx.event.alter)
                 ])
 
-            query.messages.append(
-                query.user_message
-            )
-
             text_length = 0
 
             start_time = time.time()
 
             try:
 
-                async for result in query.use_model.requester.request(query):
+                async for result in self.runner(query):
                     query.resp_messages.append(result)
 
                     self.ap.logger.info(f'对话({query.query_id})响应: {self.cut_str(result.readable_str())}')
@@ -115,4 +112,65 @@ class ChatMessageHandler(handler.MessageHandler):
                     model_name=query.use_model.name,
                     response_seconds=int(time.time() - start_time),
                     retry_times=-1,
-                )
+                )
+
+    async def runner(
+        self,
+        query: core_entities.Query,
+    ) -> typing.AsyncGenerator[llm_entities.Message, None]:
+        """执行一个请求处理过程中的LLM接口请求、函数调用的循环
+        
+        这是临时处理方案，后续可能改为使用LangChain或者自研的工作流处理器
+        """
+        await query.use_model.requester.preprocess(query)
+
+        pending_tool_calls = []
+
+        req_messages = query.prompt.messages.copy() + query.messages.copy() + [query.user_message]
+
+        # 首次请求
+        msg = await query.use_model.requester.call(query.use_model, req_messages, query.use_funcs)
+
+        yield msg
+
+        pending_tool_calls = msg.tool_calls
+
+        req_messages.append(msg)
+
+        # 持续请求，只要还有待处理的工具调用就继续处理调用
+        while pending_tool_calls:
+            for tool_call in pending_tool_calls:
+                try:
+                    func = tool_call.function
+                    
+                    parameters = json.loads(func.arguments)
+
+                    func_ret = await self.ap.tool_mgr.execute_func_call(
+                        query, func.name, parameters
+                    )
+
+                    msg = llm_entities.Message(
+                        role="tool", content=json.dumps(func_ret, ensure_ascii=False), tool_call_id=tool_call.id
+                    )
+
+                    yield msg
+
+                    req_messages.append(msg)
+                except Exception as e:
+                    # 工具调用出错，添加一个报错信息到 req_messages
+                    err_msg = llm_entities.Message(
+                        role="tool", content=f"err: {e}", tool_call_id=tool_call.id
+                    )
+
+                    yield err_msg
+
+                    req_messages.append(err_msg)
+
+            # 处理完所有调用，再次请求
+            msg = await query.use_model.requester.call(query.use_model, req_messages, query.use_funcs)
+
+            yield msg
+
+            pending_tool_calls = msg.tool_calls
+
+            req_messages.append(msg)

pkg/pipeline/process/process.py

@@ -11,7 +11,13 @@ from ...config import manager as cfg_mgr
 
 @stage.stage_class("MessageProcessor")
 class Processor(stage.PipelineStage):
-    """请求实际处理阶段"""
+    """请求实际处理阶段
+    
+    通过命令处理器和聊天处理器处理消息。
+
+    改写：
+        - resp_messages
+    """
 
     cmd_handler: handler.MessageHandler
 

pkg/pipeline/ratelimit/ratelimit.py

@@ -11,7 +11,10 @@ from ...core import entities as core_entities
 @stage.stage_class("RequireRateLimitOccupancy")
 @stage.stage_class("ReleaseRateLimitOccupancy")
 class RateLimit(stage.PipelineStage):
-    """限速器控制阶段"""
+    """限速器控制阶段
+    
+    不改写query，只检查是否需要限速。
+    """
 
     algo: algo.ReteLimitAlgo
 

pkg/pipeline/resprule/resprule.py

@@ -14,9 +14,12 @@ from ...config import manager as cfg_mgr
 @stage.stage_class("GroupRespondRuleCheckStage")
 class GroupRespondRuleCheckStage(stage.PipelineStage):
     """群组响应规则检查器
+
+    仅检查群消息是否符合规则。
     """
 
     rule_matchers: list[rule.GroupRespondRule]
+    """检查器实例"""
 
     async def initialize(self):
         """初始化检查器
@@ -31,7 +34,7 @@ class GroupRespondRuleCheckStage(stage.PipelineStage):
 
     async def process(self, query: core_entities.Query, stage_inst_name: str) -> entities.StageProcessResult:
         
-        if query.launcher_type.value != 'group':
+        if query.launcher_type.value != 'group':  # 只处理群消息
             return entities.StageProcessResult(
                 result_type=entities.ResultType.CONTINUE,
                 new_query=query

pkg/pipeline/stagemgr.py

@@ -17,17 +17,17 @@ from .ratelimit import ratelimit
 
 # 请求处理阶段顺序
 stage_order = [
-    "GroupRespondRuleCheckStage",
+    "GroupRespondRuleCheckStage",  # 群响应规则检查
-    "BanSessionCheckStage",
+    "BanSessionCheckStage",  # 封禁会话检查
-    "PreContentFilterStage",
+    "PreContentFilterStage",  # 内容过滤前置阶段
-    "PreProcessor",
+    "PreProcessor",  # 预处理器
-    "RequireRateLimitOccupancy",
+    "RequireRateLimitOccupancy",  # 请求速率限制占用
-    "MessageProcessor",
+    "MessageProcessor",  # 处理器
-    "ReleaseRateLimitOccupancy",
+    "ReleaseRateLimitOccupancy",  # 释放速率限制占用
-    "PostContentFilterStage",
+    "PostContentFilterStage",  # 内容过滤后置阶段
-    "ResponseWrapper",
+    "ResponseWrapper",  # 响应包装器
-    "LongTextProcessStage",
+    "LongTextProcessStage",  # 长文本处理
-    "SendResponseBackStage",
+    "SendResponseBackStage",  # 发送响应
 ]
 
 

pkg/pipeline/wrapper/wrapper.py

@@ -14,6 +14,13 @@ from ...plugin import events
 
 @stage.stage_class("ResponseWrapper")
 class ResponseWrapper(stage.PipelineStage):
+    """回复包装阶段
+
+    把回复的 message 包装成人类识读的形式。
+    
+    改写：
+        - resp_message_chain
+    """
 
     async def initialize(self):
         pass
@@ -128,4 +135,4 @@ class ResponseWrapper(stage.PipelineStage):
                             yield entities.StageProcessResult(
                                 result_type=entities.ResultType.CONTINUE,
                                 new_query=query
-                            )
+                            )

pkg/provider/entities.py

@@ -21,6 +21,16 @@ class ToolCall(pydantic.BaseModel):
     function: FunctionCall
 
 
+class Content(pydantic.BaseModel):
+
+    type: str
+    """内容类型"""
+
+    text: typing.Optional[str] = None
+
+    image_url: typing.Optional[str] = None
+
+
 class Message(pydantic.BaseModel):
     """消息"""
 
@@ -33,9 +43,6 @@ class Message(pydantic.BaseModel):
     content: typing.Optional[str] | typing.Optional[mirai.MessageChain] = None
     """内容"""
 
-    function_call: typing.Optional[FunctionCall] = None
-    """函数调用，不再受支持，请使用tool_calls"""
-
     tool_calls: typing.Optional[list[ToolCall]] = None
     """工具调用"""
 
@@ -43,9 +50,7 @@ class Message(pydantic.BaseModel):
 
     def readable_str(self) -> str:
         if self.content is not None:
-            return str(self.content)
+            return str(self.role) + ": " + str(self.content)
-        elif self.function_call is not None:
-            return f'{self.function_call.name}({self.function_call.arguments})'
         elif self.tool_calls is not None:
             return f'调用工具: {self.tool_calls[0].id}'
         else:

pkg/provider/modelmgr/api.py

@@ -6,6 +6,8 @@ import typing
 from ...core import app
 from ...core import entities as core_entities
 from .. import entities as llm_entities
+from . import entities as modelmgr_entities
+from ..tools import entities as tools_entities
 
 
 preregistered_requesters: list[typing.Type[LLMAPIRequester]] = []
@@ -33,20 +35,31 @@ class LLMAPIRequester(metaclass=abc.ABCMeta):
     async def initialize(self):
         pass
 
-    @abc.abstractmethod
+    async def preprocess(
-    async def request(
         self,
         query: core_entities.Query,
-    ) -> typing.AsyncGenerator[llm_entities.Message, None]:
+    ):
-        """请求API
+        """预处理
+        
+        在这里处理特定API对Query对象的兼容性问题。
+        """
+        pass
 
-        对话前文可以从 query 对象中获取。
+    @abc.abstractmethod
-        可以多次yield消息对象。
+    async def call(
+        self,
+        model: modelmgr_entities.LLMModelInfo,
+        messages: typing.List[llm_entities.Message],
+        funcs: typing.List[tools_entities.LLMFunction] = None,
+    ) -> llm_entities.Message:
+        """调用API
 
         Args:
-            query (core_entities.Query): 本次请求的上下文对象
+            model (modelmgr_entities.LLMModelInfo): 使用的模型信息
+            messages (typing.List[llm_entities.Message]): 消息对象列表
+            funcs (typing.List[tools_entities.LLMFunction], optional): 使用的工具函数列表. Defaults to None.
 
-        Yields:
+        Returns:
-            pkg.provider.entities.Message: 返回消息对象
+            llm_entities.Message: 返回消息对象
         """
-        raise NotImplementedError
+        pass

pkg/provider/modelmgr/apis/anthropicmsgs.py

@@ -27,20 +27,22 @@ class AnthropicMessages(api.LLMAPIRequester):
             proxies=self.ap.proxy_mgr.get_forward_proxies()
         )
 
-    async def request(
+    async def call(
         self,
-        query: core_entities.Query,
+        model: entities.LLMModelInfo,
-    ) -> typing.AsyncGenerator[llm_entities.Message, None]:
+        messages: typing.List[llm_entities.Message],
-        self.client.api_key = query.use_model.token_mgr.get_token()
+        funcs: typing.List[tools_entities.LLMFunction] = None,
+    ) -> llm_entities.Message:
+        self.client.api_key = model.token_mgr.get_token()
 
         args = self.ap.provider_cfg.data['requester']['anthropic-messages']['args'].copy()
-        args["model"] = query.use_model.name if query.use_model.model_name is None else query.use_model.model_name
+        args["model"] = model.name if model.model_name is None else model.model_name
 
-        req_messages = [  # req_messages 仅用于类内，外部同步由 query.messages 进行
+        req_messages = [
-            m.dict(exclude_none=True) for m in query.prompt.messages if m.content.strip() != ""
+            m.dict(exclude_none=True) for m in messages if m.content.strip() != ""
-        ] + [m.dict(exclude_none=True) for m in query.messages]
+        ]
 
-        # 删除所有 role=system & content='' 的消息
+        # 删除所有 role=system & content='' 的消息  
         req_messages = [
             m for m in req_messages if not (m["role"] == "system" and m["content"].strip() == "")
         ]
@@ -64,10 +66,9 @@ class AnthropicMessages(api.LLMAPIRequester):
         args["messages"] = req_messages
 
         try:
-
             resp = await self.client.messages.create(**args)
 
-            yield llm_entities.Message(
+            return llm_entities.Message(
                 content=resp.content[0].text,
                 role=resp.role
             )
@@ -79,4 +80,4 @@ class AnthropicMessages(api.LLMAPIRequester):
             if 'model: ' in str(e):
                 raise errors.RequesterError(f'模型无效: {e.message}')
             else:
-                raise errors.RequesterError(f'请求地址无效: {e.message}')
+                raise errors.RequesterError(f'请求地址无效: {e.message}')

pkg/provider/modelmgr/apis/chatcmpl.py

@@ -84,73 +84,19 @@ class OpenAIChatCompletions(api.LLMAPIRequester):
         message = await self._make_msg(resp)
 
         return message
-
+    
-    async def _request(
+    async def call(
-        self, query: core_entities.Query
+        self,
-    ) -> typing.AsyncGenerator[llm_entities.Message, None]:
+        model: entities.LLMModelInfo,
-        """请求"""
+        messages: typing.List[llm_entities.Message],
-
+        funcs: typing.List[tools_entities.LLMFunction] = None,
-        pending_tool_calls = []
+    ) -> llm_entities.Message:
-
         req_messages = [  # req_messages 仅用于类内，外部同步由 query.messages 进行
-            m.dict(exclude_none=True) for m in query.prompt.messages if m.content.strip() != ""
+            m.dict(exclude_none=True) for m in messages
-        ] + [m.dict(exclude_none=True) for m in query.messages]
+        ]
 
-        # req_messages.append({"role": "user", "content": str(query.message_chain)})
-
-        # 首次请求
-        msg = await self._closure(req_messages, query.use_model, query.use_funcs)
-
-        yield msg
-
-        pending_tool_calls = msg.tool_calls
-
-        req_messages.append(msg.dict(exclude_none=True))
-
-        # 持续请求，只要还有待处理的工具调用就继续处理调用
-        while pending_tool_calls:
-            for tool_call in pending_tool_calls:
-                try:
-                    func = tool_call.function
-
-                    parameters = json.loads(func.arguments)
-
-                    func_ret = await self.ap.tool_mgr.execute_func_call(
-                        query, func.name, parameters
-                    )
-
-                    msg = llm_entities.Message(
-                        role="tool", content=json.dumps(func_ret, ensure_ascii=False), tool_call_id=tool_call.id
-                    )
-
-                    yield msg
-
-                    req_messages.append(msg.dict(exclude_none=True))
-                except Exception as e:
-                    # 出错，添加一个报错信息到 req_messages
-                    err_msg = llm_entities.Message(
-                        role="tool", content=f"err: {e}", tool_call_id=tool_call.id
-                    )
-
-                    yield err_msg
-
-                    req_messages.append(
-                        err_msg.dict(exclude_none=True)
-                    )
-
-            # 处理完所有调用，继续请求
-            msg = await self._closure(req_messages, query.use_model, query.use_funcs)
-
-            yield msg
-
-            pending_tool_calls = msg.tool_calls
-
-            req_messages.append(msg.dict(exclude_none=True))
-
-    async def request(self, query: core_entities.Query) -> AsyncGenerator[llm_entities.Message, None]:
         try:
-            async for msg in self._request(query):
+            return await self._closure(req_messages, model, funcs)
-                yield msg
         except asyncio.TimeoutError:
             raise errors.RequesterError('请求超时')
         except openai.BadRequestError as e:
@@ -163,6 +109,6 @@ class OpenAIChatCompletions(api.LLMAPIRequester):
         except openai.NotFoundError as e:
             raise errors.RequesterError(f'请求路径错误: {e.message}')
         except openai.RateLimitError as e:
-            raise errors.RequesterError(f'请求过于频繁: {e.message}')
+            raise errors.RequesterError(f'请求过于频繁或余额不足: {e.message}')
         except openai.APIError as e:
             raise errors.RequesterError(f'请求错误: {e.message}')