From 94ee8ea297e12a8a00af2b762a25e3701009dfb4 Mon Sep 17 00:00:00 2001 From: Soulter <905617992@qq.com> Date: Thu, 26 Jun 2025 19:36:47 +0800 Subject: [PATCH 01/23] =?UTF-8?q?feat:=20=E6=94=AF=E6=8C=81=E5=A4=9A?= =?UTF-8?q?=E8=BD=AE=E6=AC=A1=E5=B7=A5=E5=85=B7=E8=B0=83=E7=94=A8=E5=B9=B6?= =?UTF-8?q?=E4=B8=94=E5=AD=98=E5=82=A8=E5=88=B0=E6=95=B0=E6=8D=AE=E5=BA=93?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 移除了 llm tuner 适配器 --- astrbot/core/config/default.py | 11 - astrbot/core/message/message_event_result.py | 11 +- astrbot/core/pipeline/context.py | 96 +++ .../process_stage/agent_runner/base.py | 43 ++ .../agent_runner/tool_loop_agent.py | 276 +++++++++ .../process_stage/method/llm_request.py | 566 ++++-------------- .../process_stage/method/star_request.py | 2 +- astrbot/core/pipeline/stage.py | 73 +-- astrbot/core/provider/entities.py | 18 +- astrbot/core/provider/manager.py | 5 - astrbot/core/provider/provider.py | 12 +- .../core/provider/sources/anthropic_source.py | 315 +++++++--- .../core/provider/sources/gemini_source.py | 18 +- .../core/provider/sources/llmtuner_source.py | 134 ----- .../core/provider/sources/openai_source.py | 29 +- dashboard/src/views/ProviderPage.vue | 1 - dump_plugins.py | 82 +++ 17 files changed, 882 insertions(+), 810 deletions(-) create mode 100644 astrbot/core/pipeline/process_stage/agent_runner/base.py create mode 100644 astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py delete mode 100644 astrbot/core/provider/sources/llmtuner_source.py create mode 100644 dump_plugins.py diff --git a/astrbot/core/config/default.py b/astrbot/core/config/default.py index a08a94543..17cfbd39e 100644 --- a/astrbot/core/config/default.py +++ b/astrbot/core/config/default.py @@ -774,17 +774,6 @@ CONFIG_METADATA_2 = { "model": "deepseek/deepseek-r1", }, }, - "LLMTuner": { - "id": "llmtuner_default", - "type": "llm_tuner", - "provider_type": "chat_completion", - "enable": True, - "base_model_path": "", - "adapter_model_path": "", - "llmtuner_template": "", - "finetuning_type": "lora", - "quantization_bit": 4, - }, "Dify": { "id": "dify_app_default", "type": "dify", diff --git a/astrbot/core/message/message_event_result.py b/astrbot/core/message/message_event_result.py index 28c92fa89..c5123bca3 100644 --- a/astrbot/core/message/message_event_result.py +++ b/astrbot/core/message/message_event_result.py @@ -98,6 +98,15 @@ class MessageChain: self.chain.append(Image.fromFileSystem(path)) return self + def base64_image(self, base64_str: str): + """添加一条图片消息（base64 编码字符串）到消息链 `chain` 中。 + Example: + + CommandResult().base64_image("iVBORw0KGgoAAAANSUhEUgAAAAUA...") + """ + self.chain.append(Image.fromBase64(base64_str)) + return self + def use_t2i(self, use_t2i: bool): """设置是否使用文本转图片服务。 @@ -157,7 +166,7 @@ class ResultContentType(enum.Enum): """普通的消息结果""" STREAMING_RESULT = enum.auto() """调用 LLM 产生的流式结果""" - STREAMING_FINISH= enum.auto() + STREAMING_FINISH = enum.auto() """流式输出完成""" diff --git a/astrbot/core/pipeline/context.py b/astrbot/core/pipeline/context.py index eb5ffb1cd..64a8762ed 100644 --- a/astrbot/core/pipeline/context.py +++ b/astrbot/core/pipeline/context.py @@ -1,6 +1,14 @@ +import inspect +import traceback +import typing as T from dataclasses import dataclass from astrbot.core.config.astrbot_config import AstrBotConfig +from astrbot.core.platform.astr_message_event import AstrMessageEvent from astrbot.core.star import PluginManager +from astrbot.api import logger +from astrbot.core.star.star_handler import star_handlers_registry, EventType +from astrbot.core.star.star import star_map +from astrbot.core.message.message_event_result import MessageEventResult, CommandResult @dataclass @@ -9,3 +17,91 @@ class PipelineContext: astrbot_config: AstrBotConfig # AstrBot 配置对象 plugin_manager: PluginManager # 插件管理器对象 + + async def call_event_hook( + self, + event: AstrMessageEvent, + hook_type: EventType, + *args, + ): + platform_id = event.get_platform_id() + handlers = star_handlers_registry.get_handlers_by_event_type( + hook_type, platform_id=platform_id + ) + for handler in handlers: + try: + logger.debug( + f"hook(on_llm_request) -> {star_map[handler.handler_module_path].name} - {handler.handler_name}" + ) + await handler.handler(event, *args) + except BaseException: + logger.error(traceback.format_exc()) + + if event.is_stopped(): + logger.info( + f"{star_map[handler.handler_module_path].name} - {handler.handler_name} 终止了事件传播。" + ) + return + + async def call_handler( + self, + event: AstrMessageEvent, + handler: T.Awaitable, + *args, + **kwargs, + ) -> T.AsyncGenerator[None, None]: + """执行事件处理函数并处理其返回结果 + + 该方法负责调用处理函数并处理不同类型的返回值。它支持两种类型的处理函数: + 1. 异步生成器: 实现洋葱模型，每次 yield 都会将控制权交回上层 + 2. 协程: 执行一次并处理返回值 + + Args: + ctx (PipelineContext): 消息管道上下文对象 + event (AstrMessageEvent): 事件对象 + handler (Awaitable): 事件处理函数 + + Returns: + AsyncGenerator[None, None]: 异步生成器，用于在管道中传递控制流 + """ + ready_to_call = None # 一个协程或者异步生成器 + + trace_ = None + + try: + ready_to_call = handler(event, *args, **kwargs) + except TypeError as _: + # 向下兼容 + trace_ = traceback.format_exc() + # 以前的 handler 会额外传入一个参数, 但是 context 对象实际上在插件实例中有一份 + ready_to_call = handler(event, self.plugin_manager.context, *args, **kwargs) + + if isinstance(ready_to_call, T.AsyncGenerator): + _has_yielded = False + try: + async for ret in ready_to_call: + # 这里逐步执行异步生成器, 对于每个 yield 返回的 ret, 执行下面的代码 + # 返回值只能是 MessageEventResult 或者 None（无返回值） + _has_yielded = True + if isinstance(ret, (MessageEventResult, CommandResult)): + # 如果返回值是 MessageEventResult, 设置结果并继续 + event.set_result(ret) + yield + else: + # 如果返回值是 None, 则不设置结果并继续 + # 继续执行后续阶段 + yield ret + if not _has_yielded: + # 如果这个异步生成器没有执行到 yield 分支 + yield + except Exception as e: + logger.error(f"Previous Error: {trace_}") + raise e + elif inspect.iscoroutine(ready_to_call): + # 如果只是一个协程, 直接执行 + ret = await ready_to_call + if isinstance(ret, (MessageEventResult, CommandResult)): + event.set_result(ret) + yield + else: + yield ret diff --git a/astrbot/core/pipeline/process_stage/agent_runner/base.py b/astrbot/core/pipeline/process_stage/agent_runner/base.py new file mode 100644 index 000000000..fd3c7d4ae --- /dev/null +++ b/astrbot/core/pipeline/process_stage/agent_runner/base.py @@ -0,0 +1,43 @@ +import abc +import typing as T +from dataclasses import dataclass +from astrbot.core.provider.entities import LLMResponse + + +@dataclass +class AgentResponse: + type: str + data: dict + + +class BaseAgentRunner: + @abc.abstractmethod + async def reset(self) -> None: + """ + Reset the agent to its initial state. + This method should be called before starting a new run. + """ + ... + + @abc.abstractmethod + async def step(self) -> T.AsyncGenerator[AgentResponse, None]: + """ + Process a single step of the agent. + """ + ... + + @abc.abstractmethod + def done(self) -> bool: + """ + Check if the agent has completed its task. + Returns True if the agent is done, False otherwise. + """ + ... + + @abc.abstractmethod + def get_final_llm_resp(self) -> LLMResponse | None: + """ + Get the final observation from the agent. + This method should be called after the agent is done. + """ + ... diff --git a/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py b/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py new file mode 100644 index 000000000..d26701d6b --- /dev/null +++ b/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py @@ -0,0 +1,276 @@ +import sys +import traceback +import typing as T +from .base import BaseAgentRunner, AgentResponse +from ...context import PipelineContext +from astrbot.core.provider.provider import Provider +from astrbot.core.platform.astr_message_event import AstrMessageEvent +from astrbot.core.message.message_event_result import ( + MessageChain, +) +from astrbot.core.provider.entities import ( + ProviderRequest, + LLMResponse, + ToolCallMessageSegment, + AssistantMessageSegment, + ToolCallsResult, +) +from mcp.types import ( + TextContent, + ImageContent, + EmbeddedResource, + TextResourceContents, + BlobResourceContents, +) +from astrbot.core.star.star_handler import EventType +from astrbot import logger + +if sys.version_info >= (3, 12): + from typing import override +else: + from typing_extensions import override + + +# TODO: +# 1. 处理平台不兼容的处理器 + + +class ToolLoopAgent(BaseAgentRunner): + def __init__( + self, provider: Provider, event: AstrMessageEvent, pipeline_ctx: PipelineContext + ) -> None: + self.provider = provider + self.req = None + self.event = event + self.pipeline_ctx = pipeline_ctx + + @override + async def reset(self, req: ProviderRequest, streaming: bool) -> None: + self.req = req + self.streaming = streaming + self.final_llm_resp = None + self.is_done = False + + @override + async def step(self): + """ + Process a single step of the agent. + This method should return the result of the step. + """ + if not self.req: + raise ValueError("Request is not set. Please call reset() first.") + + # 执行 LLM 请求 + llm_resp_result = None + if self.streaming: + stream = self.provider.text_chat_stream(**self.req.__dict__) + async for llm_response in stream: # type: ignore + assert isinstance(llm_response, LLMResponse) + if llm_response.is_chunk: + if llm_response.result_chain: + yield AgentResponse( + type="streaming_delta", + data={ + "chain": llm_response.result_chain.chain, + }, + ) + else: + yield AgentResponse( + type="streaming_delta", + data={ + "chain": MessageChain().message( + llm_response.completion_text + ), + }, + ) + else: + llm_resp_result = llm_response + else: + llm_resp_result = await self.provider.text_chat(**self.req.__dict__) + + if not llm_resp_result: + return + + # 执行事件钩子 + await self.pipeline_ctx.call_event_hook( + self.event, EventType.OnLLMResponseEvent, self.final_llm_resp + ) + + # 处理 LLM 响应 + llm_resp = llm_resp_result + logger.info(f"LLMResp: {llm_resp}") + if llm_resp.role == "err": + # 如果 LLM 响应错误，直接返回错误信息 + self.final_llm_resp = llm_resp + self.is_done = True + yield AgentResponse( + type="err", + data={ + "chain": MessageChain().message( + f"LLM 响应错误: {llm_resp.completion_text or '未知错误'}" + ), + }, + ) + + if not llm_resp.tools_call_name: + # 如果没有工具调用，结束 Agent Loop + self.final_llm_resp = llm_resp + self.is_done = True + + # 返回 LLM 结果 + if llm_resp.result_chain: + yield AgentResponse( + type="llm_result", + data={ + "chain": llm_resp.result_chain.chain, + }, + ) + elif llm_resp.completion_text: + yield AgentResponse( + type="llm_result", + data={ + "chain": MessageChain().message(llm_resp.completion_text), + }, + ) + + # 如果有工具调用，还需处理工具调用 + if llm_resp.tools_call_name: + tool_call_result_blocks = [] + async for result in self._handle_function_tools(self.req, llm_resp): + if isinstance(result, list): + tool_call_result_blocks = result + elif isinstance(result, MessageChain): + yield AgentResponse( + type="tool_call_result", + data={ + "chain": result.chain, + }, + ) + # 将结果添加到上下文中 + tool_calls_result = ToolCallsResult( + tool_calls_info=AssistantMessageSegment( + role="assistant", tool_calls=llm_resp.to_openai_tool_calls() + ), + tool_calls_result=tool_call_result_blocks, + ) + self.req.append_tool_calls_result(tool_calls_result) + + logger.info("done: %s", self.is_done) + + async def _handle_function_tools( + self, + req: ProviderRequest, + llm_response: LLMResponse, + ) -> T.AsyncGenerator[MessageChain | list[ToolCallMessageSegment], None]: + """处理函数工具调用。""" + tool_call_result_blocks: list[ToolCallMessageSegment] = [] + logger.info(f"Agent 使用工具: {llm_response.tools_call_name}") + + # 执行函数调用 + for func_tool_name, func_tool_args, func_tool_id in zip( + llm_response.tools_call_name, + llm_response.tools_call_args, + llm_response.tools_call_ids, + ): + try: + func_tool = req.func_tool.get_func(func_tool_name) + if func_tool.origin == "mcp": + logger.info( + f"从 MCP 服务 {func_tool.mcp_server_name} 调用工具函数：{func_tool.name}，参数：{func_tool_args}" + ) + client = req.func_tool.mcp_client_dict[func_tool.mcp_server_name] + res = await client.session.call_tool(func_tool.name, func_tool_args) + if not res: + continue + if isinstance(res.content[0], TextContent): + tool_call_result_blocks.append( + ToolCallMessageSegment( + role="tool", + tool_call_id=func_tool_id, + content=res.content[0].text, + ) + ) + elif isinstance(res.content[0], ImageContent): + tool_call_result_blocks.append( + ToolCallMessageSegment( + role="tool", + tool_call_id=func_tool_id, + content="返回了图片(已直接发送给用户)", + ) + ) + yield MessageChain().base64_image(res.content[0].data) + elif isinstance(res.content[0], EmbeddedResource): + resource = res.content[0].resource + if isinstance(resource, TextResourceContents): + tool_call_result_blocks.append( + ToolCallMessageSegment( + role="tool", + tool_call_id=func_tool_id, + content=resource.text, + ) + ) + elif ( + isinstance(resource, BlobResourceContents) + and resource.mimeType + and resource.mimeType.startswith("image/") + ): + tool_call_result_blocks.append( + ToolCallMessageSegment( + role="tool", + tool_call_id=func_tool_id, + content="返回了图片(已直接发送给用户)", + ) + ) + yield MessageChain().base64_image(res.content[0].data) + else: + tool_call_result_blocks.append( + ToolCallMessageSegment( + role="tool", + tool_call_id=func_tool_id, + content="返回的数据类型不受支持", + ) + ) + else: + logger.info(f"使用工具：{func_tool_name}，参数：{func_tool_args}") + # 尝试调用工具函数 + wrapper = self.pipeline_ctx.call_handler( + self.event, func_tool.handler, **func_tool_args + ) + async for resp in wrapper: + if resp is not None: + # Tool 返回结果 + tool_call_result_blocks.append( + ToolCallMessageSegment( + role="tool", + tool_call_id=func_tool_id, + content=resp, + ) + ) + else: + # Tool 直接请求发送消息给用户 + # 这里我们将直接结束 Agent Loop。 + self.is_done = True + if res := self.event.get_result(): + if res.chain: + yield MessageChain(chain=res.chain) + + self.event.clear_result() + except BaseException as e: + logger.warning(traceback.format_exc()) + tool_call_result_blocks.append( + ToolCallMessageSegment( + role="tool", + tool_call_id=func_tool_id, + content=f"error: {str(e)}", + ) + ) + + # 处理函数调用响应 + if tool_call_result_blocks: + yield tool_call_result_blocks + + def done(self) -> bool: + return self.is_done + + def get_final_llm_resp(self) -> LLMResponse | None: + return self.final_llm_resp diff --git a/astrbot/core/pipeline/process_stage/method/llm_request.py b/astrbot/core/pipeline/process_stage/method/llm_request.py index 549440ee3..7d5fa8135 100644 --- a/astrbot/core/pipeline/process_stage/method/llm_request.py +++ b/astrbot/core/pipeline/process_stage/method/llm_request.py @@ -3,6 +3,7 @@ """ import traceback +import copy import asyncio import json from typing import Union, AsyncGenerator @@ -20,39 +21,25 @@ from astrbot.core.utils.metrics import Metric from astrbot.core.provider.entities import ( ProviderRequest, LLMResponse, - ToolCallMessageSegment, - AssistantMessageSegment, - ToolCallsResult, -) -from astrbot.core.star.star_handler import star_handlers_registry, EventType -from astrbot.core.star.star import star_map -from mcp.types import ( - TextContent, - ImageContent, - EmbeddedResource, - TextResourceContents, - BlobResourceContents, ) +from astrbot.core.star.star_handler import EventType from astrbot.core import web_chat_back_queue +from ..agent_runner.tool_loop_agent import ToolLoopAgent class LLMRequestSubStage(Stage): async def initialize(self, ctx: PipelineContext) -> None: self.ctx = ctx - self.bot_wake_prefixs = ctx.astrbot_config["wake_prefix"] # list - self.provider_wake_prefix = ctx.astrbot_config["provider_settings"][ - "wake_prefix" - ] # str - self.max_context_length = ctx.astrbot_config["provider_settings"][ - "max_context_length" - ] # int - self.dequeue_context_length = min( - max(1, ctx.astrbot_config["provider_settings"]["dequeue_context_length"]), + conf = ctx.astrbot_config + self.bot_wake_prefixs: list[str] = conf["wake_prefix"] # list + self.provider_wake_prefix: str = conf["provider_settings"]["wake_prefix"] # str + self.max_context_length = conf["provider_settings"]["max_context_length"] # int + self.dequeue_context_length: int = min( + max(1, conf["provider_settings"]["dequeue_context_length"]), self.max_context_length - 1, - ) # int - self.streaming_response = ctx.astrbot_config["provider_settings"][ - "streaming_response" - ] # bool + ) + self.streaming_response: bool = conf["provider_settings"]["streaming_response"] + self.max_step: int = conf["provider_settings"].get("max_agent_step", 10) for bwp in self.bot_wake_prefixs: if self.provider_wake_prefix.startswith(bwp): @@ -83,10 +70,7 @@ class LLMRequestSubStage(Stage): ) if req.conversation: - all_contexts = json.loads(req.conversation.history) - req.contexts = self._process_tool_message_pairs( - all_contexts, remove_tags=True - ) + req.contexts = json.loads(req.conversation.history) else: req = ProviderRequest(prompt="", image_urls=[]) @@ -127,26 +111,7 @@ class LLMRequestSubStage(Stage): return # 执行请求 LLM 前事件钩子。 - # 装饰 system_prompt 等功能 - # 获取当前平台ID - platform_id = event.get_platform_id() - handlers = star_handlers_registry.get_handlers_by_event_type( - EventType.OnLLMRequestEvent, platform_id=platform_id - ) - for handler in handlers: - try: - logger.debug( - f"hook(on_llm_request) -> {star_map[handler.handler_module_path].name} - {handler.handler_name}" - ) - await handler.handler(event, req) - except BaseException: - logger.error(traceback.format_exc()) - - if event.is_stopped(): - logger.info( - f"{star_map[handler.handler_module_path].name} - {handler.handler_name} 终止了事件传播。" - ) - return + await self.ctx.call_event_hook(event, EventType.OnLLMRequestEvent, req) if isinstance(req.contexts, str): req.contexts = json.loads(req.contexts) @@ -176,77 +141,46 @@ class LLMRequestSubStage(Stage): if not req.session_id: req.session_id = event.unified_msg_origin - async def requesting(req: ProviderRequest): - try: - need_loop = True - while need_loop: - need_loop = False - logger.debug(f"提供商请求 Payload: {req}") + # Call Agent + tool_loop_agent = ToolLoopAgent( + provider=provider, + event=event, + pipeline_ctx=self.ctx, + ) + await tool_loop_agent.reset(req=req, streaming=self.streaming_response) - final_llm_response = None - - if self.streaming_response: - stream = provider.text_chat_stream(**req.__dict__) - async for llm_response in stream: - if llm_response.is_chunk: - if llm_response.result_chain: - yield llm_response.result_chain # MessageChain - else: - yield MessageChain().message( - llm_response.completion_text - ) - else: - final_llm_response = llm_response - else: - final_llm_response = await provider.text_chat( - **req.__dict__ - ) # 请求 LLM - - if not final_llm_response: - raise Exception("LLM response is None.") - - # 执行 LLM 响应后的事件钩子。 - handlers = star_handlers_registry.get_handlers_by_event_type( - EventType.OnLLMResponseEvent + async def requesting(): + step_idx = 0 + while step_idx < self.max_step: + step_idx += 1 + try: + async for resp in tool_loop_agent.step(): + if not self.streaming_response: + content_typ = ( + ResultContentType.LLM_RESULT + if resp.type == "llm_resp" + else ResultContentType.GENERAL_RESULT + ) + event.set_result( + MessageEventResult( + chain=resp.data["chain"], + result_content_type=content_typ, + ) + ) + yield + event.clear_result() + else: + yield resp.data["chain"] + if tool_loop_agent.done(): + break + except Exception as e: + logger.error(traceback.format_exc()) + event.set_result( + MessageEventResult().message( + f"AstrBot 请求失败。\n错误类型: {type(e).__name__}\n错误信息: {str(e)}" + ) ) - for handler in handlers: - try: - logger.debug( - f"hook(on_llm_response) -> {star_map[handler.handler_module_path].name} - {handler.handler_name}" - ) - await handler.handler(event, final_llm_response) - except BaseException: - logger.error(traceback.format_exc()) - - if event.is_stopped(): - logger.info( - f"{star_map[handler.handler_module_path].name} - {handler.handler_name} 终止了事件传播。" - ) - return - - if self.streaming_response: - # 流式输出的处理 - async for result in self._handle_llm_stream_response( - event, req, final_llm_response - ): - if isinstance(result, ProviderRequest): - # 有函数工具调用并且返回了结果，我们需要再次请求 LLM - req = result - need_loop = True - else: - yield - else: - # 非流式输出的处理 - async for result in self._handle_llm_response( - event, req, final_llm_response - ): - if isinstance(result, ProviderRequest): - # 有函数工具调用并且返回了结果，我们需要再次请求 LLM - req = result - need_loop = True - else: - yield - + return asyncio.create_task( Metric.upload( llm_tick=1, @@ -255,44 +189,38 @@ class LLMRequestSubStage(Stage): ) ) - # 保存到历史记录 - await self._save_to_history(event, req, final_llm_response) - - except BaseException as e: - logger.error(traceback.format_exc()) - event.set_result( - MessageEventResult().message( - f"AstrBot 请求失败。\n错误类型: {type(e).__name__}\n错误信息: {str(e)}" - ) - ) - - if not self.streaming_response: - event.set_extra("tool_call_result", None) - async for _ in requesting(req): - yield - else: + if self.streaming_response: + # 流式响应 event.set_result( MessageEventResult() .set_result_content_type(ResultContentType.STREAMING_RESULT) - .set_async_stream(requesting(req)) + .set_async_stream(requesting()) ) - # 这里使用yield来暂停当前阶段，等待流式输出完成后继续处理 yield - - if event.get_extra("tool_call_result"): - event.set_result(event.get_extra("tool_call_result")) - event.set_extra("tool_call_result", None) + if tool_loop_agent.done(): + if final_llm_resp := tool_loop_agent.get_final_llm_resp(): + if final_llm_resp.completion_text: + chain = ( + MessageChain().message(final_llm_resp.completion_text).chain + ) + else: + chain = final_llm_resp.result_chain.chain + event.set_result( + MessageEventResult( + chain=chain, + result_content_type=ResultContentType.STREAMING_FINISH, + ) + ) + else: + async for _ in requesting(): yield - # 暂时直接发出去 - if img_b64 := event.get_extra("tool_call_img_respond"): - await event.send(MessageChain(chain=[Image.fromBase64(img_b64)])) - event.set_extra("tool_call_img_respond", None) - + # 异步处理 WebChat 特殊情况 if event.get_platform_name() == "webchat": - # 异步处理 WebChat 特殊情况 asyncio.create_task(self._handle_webchat(event, req)) + await self._save_to_history(event, req, tool_loop_agent.get_final_llm_resp()) + async def _handle_webchat(self, event: AstrMessageEvent, req: ProviderRequest): """处理 WebChat 平台的特殊情况，包括第一次 LLM 对话时总结对话内容生成 title""" conversation = await self.conv_manager.get_conversation( @@ -305,10 +233,6 @@ class LLMRequestSubStage(Stage): return provider = self.ctx.plugin_manager.context.get_using_provider() cleaned_text = "User: " + latest_pair[0].get("content", "").strip() - # if len(latest_pair) > 1: - # cleaned_text += ( - # "\nAssistant: " + latest_pair[1].get("content", "").strip() - # ) logger.debug(f"WebChat 对话标题生成请求，清理后的文本: {cleaned_text}") llm_resp = await provider.text_chat( system_prompt="You are expert in summarizing user's query.", @@ -349,322 +273,34 @@ class LLMRequestSubStage(Stage): } ) - async def _handle_llm_response( - self, - event: AstrMessageEvent, - req: ProviderRequest, - llm_response: LLMResponse, - ) -> AsyncGenerator[Union[None, ProviderRequest], None]: - """处理非流式 LLM 响应。 - - Returns: - AsyncGenerator[Union[None, ProviderRequest], None]: 如果返回 ProviderRequest，表示需要再次调用 LLM - - Yields: - Iterator[Union[None, ProviderRequest]]: 将 event 交付给下一个 stage 或者返回 ProviderRequest 表示需要再次调用 LLM - """ - if llm_response.role == "assistant": - # text completion - if llm_response.result_chain: - event.set_result( - MessageEventResult( - chain=llm_response.result_chain.chain - ).set_result_content_type(ResultContentType.LLM_RESULT) - ) - else: - event.set_result( - MessageEventResult() - .message(llm_response.completion_text) - .set_result_content_type(ResultContentType.LLM_RESULT) - ) - elif llm_response.role == "err": - event.set_result( - MessageEventResult().message( - f"AstrBot 请求失败。\n错误信息: {llm_response.completion_text}" - ) - ) - elif llm_response.role == "tool": - # 处理函数工具调用 - async for result in self._handle_function_tools(event, req, llm_response): - yield result - - async def _handle_llm_stream_response( - self, - event: AstrMessageEvent, - req: ProviderRequest, - llm_response: LLMResponse, - ) -> AsyncGenerator[Union[None, ProviderRequest], None]: - """处理流式 LLM 响应。 - - 专门用于处理流式输出完成后的响应，与非流式响应处理分离。 - - Returns: - AsyncGenerator[Union[None, ProviderRequest], None]: 如果返回 ProviderRequest，表示需要再次调用 LLM - - Yields: - Iterator[Union[None, ProviderRequest]]: 将 event 交付给下一个 stage 或者返回 ProviderRequest 表示需要再次调用 LLM - """ - if llm_response.role == "assistant": - # text completion - if llm_response.result_chain: - event.set_result( - MessageEventResult( - chain=llm_response.result_chain.chain - ).set_result_content_type(ResultContentType.STREAMING_FINISH) - ) - else: - event.set_result( - MessageEventResult() - .message(llm_response.completion_text) - .set_result_content_type(ResultContentType.STREAMING_FINISH) - ) - elif llm_response.role == "err": - event.set_result( - MessageEventResult().message( - f"AstrBot 请求失败。\n错误信息: {llm_response.completion_text}" - ) - ) - elif llm_response.role == "tool": - # 处理函数工具调用 - async for result in self._handle_function_tools(event, req, llm_response): - yield result - - async def _handle_function_tools( - self, - event: AstrMessageEvent, - req: ProviderRequest, - llm_response: LLMResponse, - ) -> AsyncGenerator[Union[None, ProviderRequest], None]: - """处理函数工具调用。 - - Returns: - AsyncGenerator[Union[None, ProviderRequest], None]: 如果返回 ProviderRequest，表示需要再次调用 LLM - """ - # function calling - tool_call_result: list[ToolCallMessageSegment] = [] - logger.info( - f"触发 {len(llm_response.tools_call_name)} 个函数调用: {llm_response.tools_call_name}" - ) - for func_tool_name, func_tool_args, func_tool_id in zip( - llm_response.tools_call_name, - llm_response.tools_call_args, - llm_response.tools_call_ids, - ): - try: - func_tool = req.func_tool.get_func(func_tool_name) - if func_tool.origin == "mcp": - logger.info( - f"从 MCP 服务 {func_tool.mcp_server_name} 调用工具函数：{func_tool.name}，参数：{func_tool_args}" - ) - client = req.func_tool.mcp_client_dict[func_tool.mcp_server_name] - res = await client.session.call_tool(func_tool.name, func_tool_args) - if res: - # TODO 仅对ImageContent | EmbeddedResource进行了简单的Fallback - if isinstance(res.content[0], TextContent): - tool_call_result.append( - ToolCallMessageSegment( - role="tool", - tool_call_id=func_tool_id, - content=res.content[0].text, - ) - ) - elif isinstance(res.content[0], ImageContent): - tool_call_result.append( - ToolCallMessageSegment( - role="tool", - tool_call_id=func_tool_id, - content="返回了图片(已直接发送给用户)", - ) - ) - event.set_extra( - "tool_call_img_respond", - res.content[0].data, - ) - elif isinstance(res.content[0], EmbeddedResource): - resource = res.content[0].resource - if isinstance(resource, TextResourceContents): - tool_call_result.append( - ToolCallMessageSegment( - role="tool", - tool_call_id=func_tool_id, - content=resource.text, - ) - ) - elif ( - isinstance(resource, BlobResourceContents) - and resource.mimeType - and resource.mimeType.startswith("image/") - ): - tool_call_result.append( - ToolCallMessageSegment( - role="tool", - tool_call_id=func_tool_id, - content="返回了图片(已直接发送给用户)", - ) - ) - event.set_extra( - "tool_call_img_respond", - res.content[0].data, - ) - else: - tool_call_result.append( - ToolCallMessageSegment( - role="tool", - tool_call_id=func_tool_id, - content="返回的数据类型不受支持", - ) - ) - else: - # 获取处理器，过滤掉平台不兼容的处理器 - platform_id = event.get_platform_id() - star_md = star_map.get(func_tool.handler_module_path) - if ( - star_md - and platform_id in star_md.supported_platforms - and not star_md.supported_platforms[platform_id] - ): - logger.debug( - f"处理器 {func_tool_name}({star_md.name}) 在当前平台不兼容或者被禁用，跳过执行" - ) - # 直接跳过，不添加任何消息到tool_call_result - continue - - logger.info( - f"调用工具函数：{func_tool_name}，参数：{func_tool_args}" - ) - # 尝试调用工具函数 - wrapper = self._call_handler( - self.ctx, event, func_tool.handler, **func_tool_args - ) - async for resp in wrapper: - if resp is not None: # 有 return 返回 - tool_call_result.append( - ToolCallMessageSegment( - role="tool", - tool_call_id=func_tool_id, - content=resp, - ) - ) - else: - res = event.get_result() - if res and res.chain: - event.set_extra("tool_call_result", res) - yield # 有生成器返回 - event.clear_result() # 清除上一个 handler 的结果 - except BaseException as e: - logger.warning(traceback.format_exc()) - tool_call_result.append( - ToolCallMessageSegment( - role="tool", - tool_call_id=func_tool_id, - content=f"error: {str(e)}", - ) - ) - if tool_call_result: - # 函数调用结果 - req.func_tool = None # 暂时不支持递归工具调用 - assistant_msg_seg = AssistantMessageSegment( - role="assistant", tool_calls=llm_response.to_openai_tool_calls() - ) - # 在多轮 Tool 调用的情况下，这里始终保持最新的 Tool 调用结果，减少上下文长度。 - req.tool_calls_result = ToolCallsResult( - tool_calls_info=assistant_msg_seg, - tool_calls_result=tool_call_result, - ) - yield req # 再次执行 LLM 请求 - else: - if llm_response.completion_text: - event.set_result( - MessageEventResult().message(llm_response.completion_text) - ) - async def _save_to_history( - self, event: AstrMessageEvent, req: ProviderRequest, llm_response: LLMResponse + self, + event: AstrMessageEvent, + req: ProviderRequest, + llm_response: LLMResponse | None, ): - if not req or not req.conversation or not llm_response: + if ( + not req + or not req.conversation + or not llm_response + or llm_response.role != "assistant" + ): return - if llm_response.role == "assistant": - # 文本回复 - contexts = req.contexts.copy() - contexts.append(await req.assemble_context()) - - # 记录并标记函数调用结果 - if req.tool_calls_result: - tool_calls_messages = req.tool_calls_result.to_openai_messages() - - # 添加标记 - for message in tool_calls_messages: - message["_tool_call_history"] = True - - processed_tool_messages = self._process_tool_message_pairs( - tool_calls_messages, remove_tags=False - ) - - contexts.extend(processed_tool_messages) - - contexts.append( - {"role": "assistant", "content": llm_response.completion_text} - ) - contexts_to_save = list( - filter(lambda item: "_no_save" not in item, contexts) - ) - await self.conv_manager.update_conversation( - event.unified_msg_origin, req.conversation.cid, history=contexts_to_save - ) - - def _process_tool_message_pairs(self, messages, remove_tags=True): - """处理工具调用消息，确保assistant和tool消息成对出现 - - Args: - messages (list): 消息列表 - remove_tags (bool): 是否移除_tool_call_history标记 - - Returns: - list: 处理后的消息列表，保证了assistant和对应tool消息的成对出现 - """ - result = [] - i = 0 - - while i < len(messages): - current_msg = messages[i] - - # 普通消息直接添加 - if "_tool_call_history" not in current_msg: - result.append(current_msg.copy() if remove_tags else current_msg) - i += 1 - continue - - # 工具调用消息成对处理 - if current_msg.get("role") == "assistant" and "tool_calls" in current_msg: - assistant_msg = current_msg.copy() - - if remove_tags and "_tool_call_history" in assistant_msg: - del assistant_msg["_tool_call_history"] - - related_tools = [] - j = i + 1 - while ( - j < len(messages) - and messages[j].get("role") == "tool" - and "_tool_call_history" in messages[j] - ): - tool_msg = messages[j].copy() - - if remove_tags: - del tool_msg["_tool_call_history"] - - related_tools.append(tool_msg) - j += 1 - - # 成对的时候添加到结果 - if related_tools: - result.append(assistant_msg) - result.extend(related_tools) - - i = j # 跳过已处理 - else: - # 单独的tool消息 - i += 1 - - return result + # 历史上下文 + messages = copy.deepcopy(req.contexts) + # 这一轮对话请求的用户输入 + messages.append(await req.assemble_context()) + # 这一轮对话的 LLM 响应 + if req.tool_calls_result: + if not isinstance(req.tool_calls_result, list): + messages.extend(req.tool_calls_result.to_openai_messages()) + elif isinstance(req.tool_calls_result, list): + for tcr in req.tool_calls_result: + messages.extend(tcr.to_openai_messages()) + messages.append({"role": "assistant", "content": llm_response.completion_text}) + messages = list(filter(lambda item: "_no_save" not in item, messages)) + await self.conv_manager.update_conversation( + event.unified_msg_origin, req.conversation.cid, history=messages + ) + logger.debug(f"messages persisted: {messages}") diff --git a/astrbot/core/pipeline/process_stage/method/star_request.py b/astrbot/core/pipeline/process_stage/method/star_request.py index c7817e49c..00f58d55b 100644 --- a/astrbot/core/pipeline/process_stage/method/star_request.py +++ b/astrbot/core/pipeline/process_stage/method/star_request.py @@ -50,7 +50,7 @@ class StarRequestSubStage(Stage): logger.debug( f"plugin -> {star_map.get(handler.handler_module_path).name} - {handler.handler_name}" ) - wrapper = self._call_handler(self.ctx, event, handler.handler, **params) + wrapper = self.ctx.call_handler(event, handler.handler, **params) async for ret in wrapper: yield ret event.clear_result() # 清除上一个 handler 的结果 diff --git a/astrbot/core/pipeline/stage.py b/astrbot/core/pipeline/stage.py index c7d4ff792..b41794733 100644 --- a/astrbot/core/pipeline/stage.py +++ b/astrbot/core/pipeline/stage.py @@ -1,12 +1,8 @@ from __future__ import annotations import abc -import inspect -import traceback -from astrbot.api import logger -from typing import List, AsyncGenerator, Union, Awaitable +from typing import List, AsyncGenerator, Union from astrbot.core.platform.astr_message_event import AstrMessageEvent from .context import PipelineContext -from astrbot.core.message.message_event_result import MessageEventResult, CommandResult registered_stages: List[Stage] = [] # 维护了所有已注册的 Stage 实现类 @@ -41,70 +37,3 @@ class Stage(abc.ABC): Union[None, AsyncGenerator[None, None]]: 处理结果，可能是 None 或者异步生成器, 如果为 None 则表示不需要继续处理, 如果为异步生成器则表示需要继续处理(进入下一个阶段) """ raise NotImplementedError - - async def _call_handler( - self, - ctx: PipelineContext, - event: AstrMessageEvent, - handler: Awaitable, - *args, - **kwargs, - ) -> AsyncGenerator[None, None]: - """执行事件处理函数并处理其返回结果 - - 该方法负责调用处理函数并处理不同类型的返回值。它支持两种类型的处理函数: - 1. 异步生成器: 实现洋葱模型，每次yield都会将控制权交回上层 - 2. 协程: 执行一次并处理返回值 - - Args: - ctx (PipelineContext): 消息管道上下文对象 - event (AstrMessageEvent): 待处理的事件对象 - handler (Awaitable): 事件处理函数 - *args: 传递给handler的位置参数 - **kwargs: 传递给handler的关键字参数 - - Returns: - AsyncGenerator[None, None]: 异步生成器，用于在管道中传递控制流 - """ - ready_to_call = None # 一个协程或者异步生成器(async def) - - trace_ = None - - try: - ready_to_call = handler(event, *args, **kwargs) - except TypeError as _: - # 向下兼容 - trace_ = traceback.format_exc() - # 以前的handler会额外传入一个参数, 但是context对象实际上在插件实例中有一份 - ready_to_call = handler(event, ctx.plugin_manager.context, *args, **kwargs) - - if isinstance(ready_to_call, AsyncGenerator): - # 如果是一个异步生成器, 进入洋葱模型 - _has_yielded = False # 是否返回过值 - try: - async for ret in ready_to_call: - # 这里逐步执行异步生成器, 对于每个yield返回的ret, 执行下面的代码 - # 返回值只能是 MessageEventResult 或者 None（无返回值） - _has_yielded = True - if isinstance(ret, (MessageEventResult, CommandResult)): - # 如果返回值是 MessageEventResult, 设置结果并继续 - event.set_result(ret) - yield # 传递控制权给上一层的process函数 - else: - # 如果返回值是 None, 则不设置结果并继续 - # 继续执行后续阶段 - yield ret # 传递控制权给上一层的process函数 - if not _has_yielded: - # 如果这个异步生成器没有执行到yield分支 - yield - except Exception as e: - logger.error(f"Previous Error: {trace_}") - raise e - elif inspect.iscoroutine(ready_to_call): - # 如果只是一个协程, 直接执行 - ret = await ready_to_call - if isinstance(ret, (MessageEventResult, CommandResult)): - event.set_result(ret) - yield # 传递控制权给上一层的process函数 - else: - yield ret # 传递控制权给上一层的process函数 diff --git a/astrbot/core/provider/entities.py b/astrbot/core/provider/entities.py index e01e46cf9..7dd96e8d0 100644 --- a/astrbot/core/provider/entities.py +++ b/astrbot/core/provider/entities.py @@ -95,19 +95,19 @@ class ProviderRequest: """提示词""" session_id: str = "" """会话 ID""" - image_urls: List[str] = None + image_urls: list[str] = field(default_factory=list) """图片 URL 列表""" - func_tool: FuncCall = None + func_tool: FuncCall | None = None """可用的函数工具""" - contexts: List = None + contexts: list[dict] = field(default_factory=list) """上下文。格式与 openai 的上下文格式一致： 参考 https://platform.openai.com/docs/api-reference/chat/create#chat-create-messages """ system_prompt: str = "" """系统提示词""" - conversation: Conversation = None + conversation: Conversation | None = None - tool_calls_result: ToolCallsResult = None + tool_calls_result: list[ToolCallsResult] | ToolCallsResult | None = None """附加的上次请求后工具调用的结果。参考: https://platform.openai.com/docs/guides/function-calling#handling-function-calls""" def __repr__(self): @@ -116,6 +116,14 @@ class ProviderRequest: def __str__(self): return self.__repr__() + def append_tool_calls_result(self, tool_calls_result: ToolCallsResult): + """添加工具调用结果到请求中""" + if not self.tool_calls_result: + self.tool_calls_result = [] + if isinstance(self.tool_calls_result, ToolCallsResult): + self.tool_calls_result = [self.tool_calls_result] + self.tool_calls_result.append(tool_calls_result) + def _print_friendly_context(self): """打印友好的消息上下文。将 image_url 的值替换为 """ if not self.contexts: diff --git a/astrbot/core/provider/manager.py b/astrbot/core/provider/manager.py index 5886b8083..0dd108474 100644 --- a/astrbot/core/provider/manager.py +++ b/astrbot/core/provider/manager.py @@ -190,11 +190,6 @@ class ProviderManager: from .sources.anthropic_source import ( ProviderAnthropic as ProviderAnthropic, ) - case "llm_tuner": - logger.info("加载 LLM Tuner 工具 ...") - from .sources.llmtuner_source import ( - LLMTunerModelLoader as LLMTunerModelLoader, - ) case "dify": from .sources.dify_source import ProviderDify as ProviderDify case "dashscope": diff --git a/astrbot/core/provider/provider.py b/astrbot/core/provider/provider.py index c285ebd42..2cc956ae1 100644 --- a/astrbot/core/provider/provider.py +++ b/astrbot/core/provider/provider.py @@ -86,11 +86,11 @@ class Provider(AbstractProvider): self, prompt: str, session_id: str = None, - image_urls: List[str] = None, + image_urls: list[str] = None, func_tool: FuncCall = None, - contexts: List = None, + contexts: list = None, system_prompt: str = None, - tool_calls_result: ToolCallsResult = None, + tool_calls_result: ToolCallsResult | list[ToolCallsResult] = None, **kwargs, ) -> LLMResponse: """获得 LLM 的文本对话结果。会使用当前的模型进行对话。 @@ -114,11 +114,11 @@ class Provider(AbstractProvider): self, prompt: str, session_id: str = None, - image_urls: List[str] = None, + image_urls: list[str] = None, func_tool: FuncCall = None, - contexts: List = None, + contexts: list = None, system_prompt: str = None, - tool_calls_result: ToolCallsResult = None, + tool_calls_result: ToolCallsResult | list[ToolCallsResult] = None, **kwargs, ) -> AsyncGenerator[LLMResponse, None]: """获得 LLM 的流式文本对话结果。会使用当前的模型进行对话。在生成的最后会返回一次完整的结果。 diff --git a/astrbot/core/provider/sources/anthropic_source.py b/astrbot/core/provider/sources/anthropic_source.py index c3ad45868..f40daa5ec 100644 --- a/astrbot/core/provider/sources/anthropic_source.py +++ b/astrbot/core/provider/sources/anthropic_source.py @@ -1,3 +1,6 @@ +import json +import anthropic +import base64 from typing import List from mimetypes import guess_type @@ -10,15 +13,14 @@ from astrbot.api.provider import Provider, Personality from astrbot import logger from astrbot.core.provider.func_tool_manager import FuncCall from ..register import register_provider_adapter -from astrbot.core.message.message_event_result import MessageChain -from astrbot.core.provider.entities import LLMResponse, ToolCallsResult -from .openai_source import ProviderOpenAIOfficial +from astrbot.core.provider.entities import LLMResponse +from typing import AsyncGenerator @register_provider_adapter( "anthropic_chat_completion", "Anthropic Claude API 提供商适配器" ) -class ProviderAnthropic(ProviderOpenAIOfficial): +class ProviderAnthropic(Provider): def __init__( self, provider_config: dict, @@ -27,9 +29,7 @@ class ProviderAnthropic(ProviderOpenAIOfficial): persistant_history=True, default_persona: Personality = None, ) -> None: - # Skip OpenAI's __init__ and call Provider's __init__ directly - Provider.__init__( - self, + super().__init__( provider_config, provider_settings, persistant_history, @@ -51,10 +51,63 @@ class ProviderAnthropic(ProviderOpenAIOfficial): self.set_model(provider_config["model_config"]["model"]) + def _prepare_payload(self, messages: list[dict]): + """准备 Anthropic API 的请求 payload + + Args: + messages: OpenAI 格式的消息列表，包含用户输入和系统提示等信息 + Returns: + system_prompt: 系统提示内容 + new_messages: 处理后的消息列表，去除系统提示 + """ + system_prompt = "" + new_messages = [] + for message in messages: + if message["role"] == "system": + system_prompt = message["content"] + elif message["role"] == "assistant": + blocks = [] + if isinstance(message["content"], str): + blocks.append({"type": "text", "text": message["content"]}) + if "tool_calls" in message: + for tool_call in message["tool_calls"]: + blocks.append( # noqa: PERF401 + { + "type": "tool_use", + "name": tool_call["function"]["name"], + "input": json.loads(tool_call["function"]["arguments"]) + if isinstance(tool_call["function"]["arguments"], str) + else tool_call["function"]["arguments"], + "id": tool_call["id"], + } + ) + new_messages.append( + { + "role": "assistant", + "content": blocks, + } + ) + elif message["role"] == "tool": + new_messages.append( + { + "role": "user", + "content": [ + { + "type": "tool_result", + "tool_use_id": message["tool_call_id"], + "content": message["content"], + } + ], + } + ) + else: + new_messages.append(message) + + return system_prompt, new_messages + async def _query(self, payloads: dict, tools: FuncCall) -> LLMResponse: if tools: - tool_list = tools.get_func_desc_anthropic_style() - if tool_list: + if tool_list := tools.get_func_desc_anthropic_style(): payloads["tools"] = tool_list completion = await self.client.messages.create(**payloads, stream=False) @@ -64,70 +117,157 @@ class ProviderAnthropic(ProviderOpenAIOfficial): if len(completion.content) == 0: raise Exception("API 返回的 completion 为空。") - # TODO: 如果进行函数调用，思维链被截断，用户可能需要思维链的内容 - # 选最后一条消息，如果要进行函数调用，anthropic会先返回文本消息的思维链，然后再返回函数调用请求 - content = completion.content[-1] - llm_response = LLMResponse("assistant") + llm_response = LLMResponse(role="assistant") - if content.type == "text": - # text completion - completion_text = str(content.text).strip() - # llm_response.completion_text = completion_text - llm_response.result_chain = MessageChain().message(completion_text) - - # Anthropic每次只返回一个函数调用 - if completion.stop_reason == "tool_use": - # tools call (function calling) - args_ls = [] - func_name_ls = [] - tool_use_ids = [] - func_name_ls.append(content.name) - args_ls.append(content.input) - tool_use_ids.append(content.id) - llm_response.role = "tool" - llm_response.tools_call_args = args_ls - llm_response.tools_call_name = func_name_ls - llm_response.tools_call_ids = tool_use_ids + for content_block in completion.content: + if content_block.type == "text": + completion_text = str(content_block.text).strip() + llm_response.completion_text = completion_text + if content_block.type == "tool_use": + llm_response.tools_call_args.append(content_block.input) + llm_response.tools_call_name.append(content_block.name) + llm_response.tools_call_ids.append(content_block.id) + # TODO(Soulter): 处理 end_turn 情况 if not llm_response.completion_text and not llm_response.tools_call_args: - logger.error(f"API 返回的 completion 无法解析：{completion}。") - raise Exception(f"API 返回的 completion 无法解析：{completion}。") - - llm_response.raw_completion = completion + raise Exception(f"Anthropic API 返回的 completion 无法解析：{completion}。") return llm_response + async def _query_stream( + self, payloads: dict, tools: FuncCall + ) -> AsyncGenerator[LLMResponse, None]: + if tools: + if tool_list := tools.get_func_desc_anthropic_style(): + payloads["tools"] = tool_list + + # 用于累积工具调用信息 + tool_use_buffer = {} + # 用于累积最终结果 + final_text = "" + final_tool_calls = [] + + async with self.client.messages.stream(**payloads) as stream: + assert isinstance(stream, anthropic.AsyncMessageStream) + async for event in stream: + if event.type == "content_block_start": + if event.content_block.type == "text": + # 文本块开始 + yield LLMResponse( + role="assistant", completion_text="", is_chunk=True + ) + elif event.content_block.type == "tool_use": + # 工具使用块开始，初始化缓冲区 + tool_use_buffer[event.index] = { + "id": event.content_block.id, + "name": event.content_block.name, + "input": {}, + } + + elif event.type == "content_block_delta": + if event.delta.type == "text_delta": + # 文本增量 + final_text += event.delta.text + yield LLMResponse( + role="assistant", + completion_text=event.delta.text, + is_chunk=True, + ) + elif event.delta.type == "input_json_delta": + # 工具调用参数增量 + if event.index in tool_use_buffer: + # 累积 JSON 输入 + if "input_json" not in tool_use_buffer[event.index]: + tool_use_buffer[event.index]["input_json"] = "" + tool_use_buffer[event.index]["input_json"] += ( + event.delta.partial_json + ) + + elif event.type == "content_block_stop": + # 内容块结束 + if event.index in tool_use_buffer: + # 解析完整的工具调用 + tool_info = tool_use_buffer[event.index] + try: + if "input_json" in tool_info: + tool_info["input"] = json.loads(tool_info["input_json"]) + + # 添加到最终结果 + final_tool_calls.append( + { + "id": tool_info["id"], + "name": tool_info["name"], + "input": tool_info["input"], + } + ) + + yield LLMResponse( + role="tool", + completion_text="", + tools_call_args=[tool_info["input"]], + tools_call_name=[tool_info["name"]], + tools_call_ids=[tool_info["id"]], + is_chunk=True, + ) + except json.JSONDecodeError: + # JSON 解析失败，跳过这个工具调用 + logger.warning(f"工具调用参数 JSON 解析失败: {tool_info}") + + # 清理缓冲区 + del tool_use_buffer[event.index] + + # 返回最终的完整结果 + final_response = LLMResponse( + role="assistant", completion_text=final_text, is_chunk=False + ) + + if final_tool_calls: + final_response.tools_call_args = [ + call["input"] for call in final_tool_calls + ] + final_response.tools_call_name = [call["name"] for call in final_tool_calls] + final_response.tools_call_ids = [call["id"] for call in final_tool_calls] + + yield final_response + async def text_chat( self, - prompt: str, - session_id: str = None, - image_urls: List[str] = [], - func_tool: FuncCall = None, + prompt, + session_id = None, + image_urls = [], + func_tool = None, contexts=None, system_prompt=None, - tool_calls_result: ToolCallsResult = None, + tool_calls_result = None, **kwargs, ) -> LLMResponse: if contexts is None: contexts = [] - if not prompt: - prompt = "" - new_record = await self.assemble_context(prompt, image_urls) context_query = [*contexts, new_record] + if system_prompt: + context_query.insert(0, {"role": "system", "content": system_prompt}) for part in context_query: if "_no_save" in part: del part["_no_save"] + # tool calls result if tool_calls_result: - # 暂时这样写。 - prompt += f"Here are the related results via using tools: {str(tool_calls_result.tool_calls_result)}" + if not isinstance(tool_calls_result, list): + context_query.extend(tool_calls_result.to_openai_messages()) + else: + for tcr in tool_calls_result: + context_query.extend(tcr.to_openai_messages()) + + system_prompt, new_messages = self._prepare_payload(context_query) model_config = self.provider_config.get("model_config", {}) + model_config["model"] = self.get_model() + + payloads = {"messages": new_messages, **model_config} - payloads = {"messages": context_query, **model_config} # Anthropic has a different way of handling system prompts if system_prompt: payloads["system"] = system_prompt @@ -135,32 +275,9 @@ class ProviderAnthropic(ProviderOpenAIOfficial): llm_response = None try: llm_response = await self._query(payloads, func_tool) - except Exception as e: - if "maximum context length" in str(e): - retry_cnt = 20 - while retry_cnt > 0: - logger.warning( - f"上下文长度超过限制。尝试弹出最早的记录然后重试。当前记录条数: {len(context_query)}" - ) - try: - await self.pop_record(context_query) - response = await self.client.messages.create( - messages=context_query, **model_config - ) - llm_response = LLMResponse("assistant") - llm_response.result_chain = MessageChain().message(response.content[0].text) - llm_response.raw_completion = response - return llm_response - except Exception as e: - if "maximum context length" in str(e): - retry_cnt -= 1 - else: - raise e - return LLMResponse("err", "err: 请尝试 /reset 清除会话记录。") - else: - logger.error(f"发生了错误。Provider 配置如下: {model_config}") - raise e + logger.error(f"发生了错误。Provider 配置如下: {model_config}") + raise e return llm_response @@ -175,21 +292,34 @@ class ProviderAnthropic(ProviderOpenAIOfficial): tool_calls_result=None, **kwargs, ): - # raise NotImplementedError("This method is not implemented yet.") - # 调用 text_chat 模拟流式 - llm_response = await self.text_chat( - prompt=prompt, - session_id=session_id, - image_urls=image_urls, - func_tool=func_tool, - contexts=contexts, - system_prompt=system_prompt, - tool_calls_result=tool_calls_result, - ) - llm_response.is_chunk = True - yield llm_response - llm_response.is_chunk = False - yield llm_response + if contexts is None: + contexts = [] + new_record = await self.assemble_context(prompt, image_urls) + context_query = [*contexts, new_record] + if system_prompt: + context_query.insert(0, {"role": "system", "content": system_prompt}) + + for part in context_query: + if "_no_save" in part: + del part["_no_save"] + + # tool calls result + if tool_calls_result: + context_query.extend(tool_calls_result.to_openai_messages()) + + system_prompt, new_messages = self._prepare_payload(context_query) + + model_config = self.provider_config.get("model_config", {}) + model_config["model"] = self.get_model() + + payloads = {"messages": new_messages, **model_config} + + # Anthropic has a different way of handling system prompts + if system_prompt: + payloads["system"] = system_prompt + + async for llm_response in self._query_stream(payloads, func_tool): + yield llm_response async def assemble_context(self, text: str, image_urls: List[str] = None): """组装上下文，支持文本和图片""" @@ -232,3 +362,14 @@ class ProviderAnthropic(ProviderOpenAIOfficial): ) return {"role": "user", "content": content} + + async def encode_image_bs64(self, image_url: str) -> str: + """ + 将图片转换为 base64 + """ + if image_url.startswith("base64://"): + return image_url.replace("base64://", "data:image/jpeg;base64,") + with open(image_url, "rb") as f: + image_bs64 = base64.b64encode(f.read()).decode("utf-8") + return "data:image/jpeg;base64," + image_bs64 + return "" diff --git a/astrbot/core/provider/sources/gemini_source.py b/astrbot/core/provider/sources/gemini_source.py index c16b39415..b08705907 100644 --- a/astrbot/core/provider/sources/gemini_source.py +++ b/astrbot/core/provider/sources/gemini_source.py @@ -506,12 +506,12 @@ class ProviderGoogleGenAI(Provider): async def text_chat( self, prompt: str, - session_id: str = None, - image_urls: list[str] = None, - func_tool: FuncCall = None, - contexts: list = None, - system_prompt: str = None, - tool_calls_result: ToolCallsResult = None, + session_id = None, + image_urls = None, + func_tool = None, + contexts = None, + system_prompt = None, + tool_calls_result = None, **kwargs, ) -> LLMResponse: if contexts is None: @@ -527,7 +527,11 @@ class ProviderGoogleGenAI(Provider): # tool calls result if tool_calls_result: - context_query.extend(tool_calls_result.to_openai_messages()) + if not isinstance(tool_calls_result, list): + context_query.extend(tool_calls_result.to_openai_messages()) + else: + for tcr in tool_calls_result: + context_query.extend(tcr.to_openai_messages()) model_config = self.provider_config.get("model_config", {}) model_config["model"] = self.get_model() diff --git a/astrbot/core/provider/sources/llmtuner_source.py b/astrbot/core/provider/sources/llmtuner_source.py deleted file mode 100644 index 8648512d0..000000000 --- a/astrbot/core/provider/sources/llmtuner_source.py +++ /dev/null @@ -1,134 +0,0 @@ -import os -from llmtuner.chat import ChatModel -from typing import List -from .. import Provider -from ..entities import LLMResponse -from ..func_tool_manager import FuncCall -from astrbot.core.db import BaseDatabase -from ..register import register_provider_adapter - - -@register_provider_adapter( - "llm_tuner", "LLMTuner 适配器, 用于装载使用 LlamaFactory 微调后的模型" -) -class LLMTunerModelLoader(Provider): - def __init__( - self, - provider_config: dict, - provider_settings: dict, - db_helper: BaseDatabase, - persistant_history=True, - default_persona=None, - ) -> None: - super().__init__( - provider_config, - provider_settings, - persistant_history, - db_helper, - default_persona, - ) - if not os.path.exists(provider_config["base_model_path"]) or not os.path.exists( - provider_config["adapter_model_path"] - ): - raise FileNotFoundError("模型文件路径不存在。") - self.base_model_path = provider_config["base_model_path"] - self.adapter_model_path = provider_config["adapter_model_path"] - self.model = ChatModel( - { - "model_name_or_path": self.base_model_path, - "adapter_name_or_path": self.adapter_model_path, - "template": provider_config["llmtuner_template"], - "finetuning_type": provider_config["finetuning_type"], - "quantization_bit": provider_config["quantization_bit"], - } - ) - self.set_model( - os.path.basename(self.base_model_path) - + "_" - + os.path.basename(self.adapter_model_path) - ) - - async def assemble_context(self, text: str, image_urls: List[str] = None): - """ - 组装上下文。 - """ - return {"role": "user", "content": text} - - async def text_chat( - self, - prompt: str, - session_id: str = None, - image_urls: List[str] = None, - func_tool: FuncCall = None, - contexts: List = None, - system_prompt: str = None, - **kwargs, - ) -> LLMResponse: - if contexts is None: - contexts = [] - system_prompt = "" - new_record = {"role": "user", "content": prompt} - query_context = [*contexts, new_record] - - # 提取出系统提示 - system_idxs = [] - for idx, context in enumerate(query_context): - if context["role"] == "system": - system_idxs.append(idx) - - if "_no_save" in context: - del context["_no_save"] - - for idx in reversed(system_idxs): - system_prompt += " " + query_context.pop(idx)["content"] - - conf = { - "messages": query_context, - "system": system_prompt, - } - if func_tool: - tool_list = func_tool.get_func_desc_openai_style() - if tool_list: - conf["tools"] = tool_list - - responses = await self.model.achat(**conf) - - llm_response = LLMResponse("assistant", responses[-1].response_text) - - return llm_response - - async def text_chat_stream( - self, - prompt, - session_id=None, - image_urls=..., - func_tool=None, - contexts=..., - system_prompt=None, - tool_calls_result=None, - **kwargs, - ): - # raise NotImplementedError("This method is not implemented yet.") - # 调用 text_chat 模拟流式 - llm_response = await self.text_chat( - prompt=prompt, - session_id=session_id, - image_urls=image_urls, - func_tool=func_tool, - contexts=contexts, - system_prompt=system_prompt, - tool_calls_result=tool_calls_result, - ) - llm_response.is_chunk = True - yield llm_response - llm_response.is_chunk = False - yield llm_response - - async def get_current_key(self): - return "none" - - async def set_key(self, key): - pass - - async def get_models(self): - return [self.get_model()] diff --git a/astrbot/core/provider/sources/openai_source.py b/astrbot/core/provider/sources/openai_source.py index 15104db3c..10db3c31a 100644 --- a/astrbot/core/provider/sources/openai_source.py +++ b/astrbot/core/provider/sources/openai_source.py @@ -9,7 +9,6 @@ import astrbot.core.message.components as Comp from openai import AsyncOpenAI, AsyncAzureOpenAI from openai.types.chat.chat_completion import ChatCompletion -# from openai.types.chat.chat_completion_chunk import ChatCompletionChunk from openai._exceptions import NotFoundError, UnprocessableEntityError from openai.lib.streaming.chat._completions import ChatCompletionStreamState from astrbot.core.utils.io import download_image_by_url @@ -224,12 +223,10 @@ class ProviderOpenAIOfficial(Provider): async def _prepare_chat_payload( self, prompt: str, - session_id: str = None, - image_urls: list[str] = None, - func_tool: FuncCall = None, - contexts: list = None, - system_prompt: str = None, - tool_calls_result: ToolCallsResult = None, + image_urls: list[str] | None = None, + contexts: list | None = None, + system_prompt: str | None = None, + tool_calls_result: ToolCallsResult | list[ToolCallsResult] | None = None, **kwargs, ) -> tuple: """准备聊天所需的有效载荷和上下文""" @@ -246,14 +243,20 @@ class ProviderOpenAIOfficial(Provider): # tool calls result if tool_calls_result: - context_query.extend(tool_calls_result.to_openai_messages()) + if isinstance(tool_calls_result, ToolCallsResult): + context_query.extend(tool_calls_result.to_openai_messages()) + else: + for tcr in tool_calls_result: + context_query.extend(tcr.to_openai_messages()) model_config = self.provider_config.get("model_config", {}) model_config["model"] = self.get_model() payloads = {"messages": context_query, **model_config} - return payloads, context_query, func_tool + logger.debug(f"payloads: {payloads}") + + return payloads, context_query async def _handle_api_error( self, @@ -352,11 +355,9 @@ class ProviderOpenAIOfficial(Provider): tool_calls_result=None, **kwargs, ) -> LLMResponse: - payloads, context_query, func_tool = await self._prepare_chat_payload( + payloads, context_query = await self._prepare_chat_payload( prompt, - session_id, image_urls, - func_tool, contexts, system_prompt, tool_calls_result, @@ -422,11 +423,9 @@ class ProviderOpenAIOfficial(Provider): **kwargs, ) -> AsyncGenerator[LLMResponse, None]: """流式对话，与服务商交互并逐步返回结果""" - payloads, context_query, func_tool = await self._prepare_chat_payload( + payloads, context_query = await self._prepare_chat_payload( prompt, - session_id, image_urls, - func_tool, contexts, system_prompt, tool_calls_result, diff --git a/dashboard/src/views/ProviderPage.vue b/dashboard/src/views/ProviderPage.vue index 220393dea..44e7f8206 100644 --- a/dashboard/src/views/ProviderPage.vue +++ b/dashboard/src/views/ProviderPage.vue @@ -414,7 +414,6 @@ export default { "anthropic_chat_completion": "chat_completion", "googlegenai_chat_completion": "chat_completion", "zhipu_chat_completion": "chat_completion", - "llm_tuner": "chat_completion", "dify": "chat_completion", "dashscope": "chat_completion", "openai_whisper_api": "speech_to_text", diff --git a/dump_plugins.py b/dump_plugins.py new file mode 100644 index 000000000..efe34b230 --- /dev/null +++ b/dump_plugins.py @@ -0,0 +1,82 @@ +import urllib.request +import json + +# --- 配置 --- +REPO_OWNER = "AstrBotDevs" +REPO_NAME = "AstrBot" +START_ISSUE_NUMBER = 970 +LABEL_TO_FIND = "plugin-publish" +OUTPUT_FILENAME = "plugin_publish_issues.txt" +ISSUE_STATE = "closed" # 只筛选状态为 closed 的 Issue + + +def fetch_and_format_issues( + repo_owner, repo_name, start_issue_number, label_name, output_file, issue_state +): + api_url = f"https://api.github.com/repos/{repo_owner}/{repo_name}/issues?state={issue_state}&labels={label_name}&sort=created&direction=asc&per_page=100" + headers = {"Accept": "application/vnd.github+json"} + found_issues = [] + page = 1 + + while True: + request_url = f"{api_url}&page={page}" + request = urllib.request.Request(request_url, headers=headers) + try: + with urllib.request.urlopen(request) as response: + data = json.loads(response.read().decode("utf-8")) + if not data: + break # 没有更多 Issues 了 + + for issue in data: + issue_number = issue.get("number") + if issue_number is not None and issue_number >= start_issue_number: + title = issue.get("title", "No Title") + author = issue.get("user", {}).get("login", "Unknown") + found_issues.append(f"{title} by @{author} in #{issue_number}") + + # 检查是否有下一页 + if "Link" in response.headers: + links = response.headers["Link"].split(",") + next_page_exists = False + for link in links: + if 'rel="next"' in link: + next_page_exists = True + break + if not next_page_exists: + break + page += 1 + else: + break # 没有 Link header，假设没有更多页了 + + except urllib.error.HTTPError as e: + print(f"HTTP Error: {e.code} - {e.reason}") + return + except urllib.error.URLError as e: + print(f"URL Error: {e.reason}") + return + except json.JSONDecodeError: + print("Error decoding JSON response.") + return + + if found_issues: + with open(output_file, "w", encoding="utf-8") as f: + for line in found_issues: + f.write(line + "\n") + print( + f"已找到 {len(found_issues)} 个状态为 '{issue_state}'，带有 '{label_name}' 标签且 Issue Number 大于等于 {start_issue_number} 的 Issues，并已保存到 '{output_file}'。" + ) + else: + print( + f"未找到任何状态为 '{issue_state}'，带有 '{label_name}' 标签且 Issue Number 大于等于 {start_issue_number} 的 Issues。" + ) + + +if __name__ == "__main__": + fetch_and_format_issues( + REPO_OWNER, + REPO_NAME, + START_ISSUE_NUMBER, + LABEL_TO_FIND, + OUTPUT_FILENAME, + ISSUE_STATE, + ) From a55a07c5ffac41fc6e9187408c906389a0b3f451 Mon Sep 17 00:00:00 2001 From: Soulter <905617992@qq.com> Date: Sun, 29 Jun 2025 14:43:36 +0800 Subject: [PATCH 02/23] remove: useless provider init params --- astrbot/core/provider/manager.py | 2 -- astrbot/core/provider/provider.py | 7 ++----- .../core/provider/sources/anthropic_source.py | 21 +++++++------------ .../core/provider/sources/dashscope_source.py | 7 +------ astrbot/core/provider/sources/dify_source.py | 13 ++++-------- .../core/provider/sources/gemini_source.py | 13 ++++-------- .../core/provider/sources/openai_source.py | 13 ++++-------- astrbot/core/provider/sources/zhipu_source.py | 5 ----- 8 files changed, 23 insertions(+), 58 deletions(-) diff --git a/astrbot/core/provider/manager.py b/astrbot/core/provider/manager.py index 0dd108474..2abe59d65 100644 --- a/astrbot/core/provider/manager.py +++ b/astrbot/core/provider/manager.py @@ -325,8 +325,6 @@ class ProviderManager: inst = provider_metadata.cls_type( provider_config, self.provider_settings, - self.db_helper, - self.provider_settings.get("persistant_history", True), self.selected_default_persona, ) diff --git a/astrbot/core/provider/provider.py b/astrbot/core/provider/provider.py index 2cc956ae1..1ecca3537 100644 --- a/astrbot/core/provider/provider.py +++ b/astrbot/core/provider/provider.py @@ -1,6 +1,5 @@ import abc from typing import List -from astrbot.core.db import BaseDatabase from typing import TypedDict, AsyncGenerator from astrbot.core.provider.func_tool_manager import FuncCall from astrbot.core.provider.entities import LLMResponse, ToolCallsResult @@ -53,15 +52,13 @@ class Provider(AbstractProvider): self, provider_config: dict, provider_settings: dict, - persistant_history: bool = True, - db_helper: BaseDatabase = None, - default_persona: Personality = None, + default_persona: Personality | None = None, ) -> None: super().__init__(provider_config) self.provider_settings = provider_settings - self.curr_personality: Personality = default_persona + self.curr_personality = default_persona """维护了当前的使用的 persona，即人格。可能为 None""" @abc.abstractmethod diff --git a/astrbot/core/provider/sources/anthropic_source.py b/astrbot/core/provider/sources/anthropic_source.py index f40daa5ec..18b4cfead 100644 --- a/astrbot/core/provider/sources/anthropic_source.py +++ b/astrbot/core/provider/sources/anthropic_source.py @@ -8,8 +8,7 @@ from anthropic import AsyncAnthropic from anthropic.types import Message from astrbot.core.utils.io import download_image_by_url -from astrbot.core.db import BaseDatabase -from astrbot.api.provider import Provider, Personality +from astrbot.api.provider import Provider from astrbot import logger from astrbot.core.provider.func_tool_manager import FuncCall from ..register import register_provider_adapter @@ -23,17 +22,13 @@ from typing import AsyncGenerator class ProviderAnthropic(Provider): def __init__( self, - provider_config: dict, - provider_settings: dict, - db_helper: BaseDatabase, - persistant_history=True, - default_persona: Personality = None, + provider_config, + provider_settings, + default_persona=None, ) -> None: super().__init__( provider_config, provider_settings, - persistant_history, - db_helper, default_persona, ) @@ -234,12 +229,12 @@ class ProviderAnthropic(Provider): async def text_chat( self, prompt, - session_id = None, - image_urls = [], - func_tool = None, + session_id=None, + image_urls=[], + func_tool=None, contexts=None, system_prompt=None, - tool_calls_result = None, + tool_calls_result=None, **kwargs, ) -> LLMResponse: if contexts is None: diff --git a/astrbot/core/provider/sources/dashscope_source.py b/astrbot/core/provider/sources/dashscope_source.py index f719190a1..3498f8346 100644 --- a/astrbot/core/provider/sources/dashscope_source.py +++ b/astrbot/core/provider/sources/dashscope_source.py @@ -5,7 +5,6 @@ from typing import List from .. import Provider, Personality from ..entities import LLMResponse from ..func_tool_manager import FuncCall -from astrbot.core.db import BaseDatabase from ..register import register_provider_adapter from astrbot.core.message.message_event_result import MessageChain from .openai_source import ProviderOpenAIOfficial @@ -19,16 +18,12 @@ class ProviderDashscope(ProviderOpenAIOfficial): self, provider_config: dict, provider_settings: dict, - db_helper: BaseDatabase, - persistant_history=False, - default_persona: Personality = None, + default_persona: Personality | None = None, ) -> None: Provider.__init__( self, provider_config, provider_settings, - persistant_history, - db_helper, default_persona, ) self.api_key = provider_config.get("dashscope_api_key", "") diff --git a/astrbot/core/provider/sources/dify_source.py b/astrbot/core/provider/sources/dify_source.py index 348c3e72c..81c910d66 100644 --- a/astrbot/core/provider/sources/dify_source.py +++ b/astrbot/core/provider/sources/dify_source.py @@ -1,10 +1,9 @@ import astrbot.core.message.components as Comp import os from typing import List -from .. import Provider, Personality +from .. import Provider from ..entities import LLMResponse from ..func_tool_manager import FuncCall -from astrbot.core.db import BaseDatabase from ..register import register_provider_adapter from astrbot.core.utils.dify_api_client import DifyAPIClient from astrbot.core.utils.io import download_image_by_url, download_file @@ -17,17 +16,13 @@ from astrbot.core.utils.astrbot_path import get_astrbot_data_path class ProviderDify(Provider): def __init__( self, - provider_config: dict, - provider_settings: dict, - db_helper: BaseDatabase, - persistant_history=False, - default_persona: Personality = None, + provider_config, + provider_settings, + default_persona = None, ) -> None: super().__init__( provider_config, provider_settings, - persistant_history, - db_helper, default_persona, ) self.api_key = provider_config.get("dify_api_key", "") diff --git a/astrbot/core/provider/sources/gemini_source.py b/astrbot/core/provider/sources/gemini_source.py index b08705907..31c1695f5 100644 --- a/astrbot/core/provider/sources/gemini_source.py +++ b/astrbot/core/provider/sources/gemini_source.py @@ -12,8 +12,7 @@ from google.genai.errors import APIError import astrbot.core.message.components as Comp from astrbot import logger -from astrbot.api.provider import Personality, Provider -from astrbot.core.db import BaseDatabase +from astrbot.api.provider import Provider from astrbot.core.message.message_event_result import MessageChain from astrbot.core.provider.entities import LLMResponse, ToolCallsResult from astrbot.core.provider.func_tool_manager import FuncCall @@ -52,17 +51,13 @@ class ProviderGoogleGenAI(Provider): def __init__( self, - provider_config: dict, - provider_settings: dict, - db_helper: BaseDatabase, - persistant_history=True, - default_persona: Personality = None, + provider_config, + provider_settings, + default_persona = None, ) -> None: super().__init__( provider_config, provider_settings, - persistant_history, - db_helper, default_persona, ) self.api_keys: list = provider_config.get("key", []) diff --git a/astrbot/core/provider/sources/openai_source.py b/astrbot/core/provider/sources/openai_source.py index 10db3c31a..6fffa13ee 100644 --- a/astrbot/core/provider/sources/openai_source.py +++ b/astrbot/core/provider/sources/openai_source.py @@ -14,8 +14,7 @@ from openai.lib.streaming.chat._completions import ChatCompletionStreamState from astrbot.core.utils.io import download_image_by_url from astrbot.core.message.message_event_result import MessageChain -from astrbot.core.db import BaseDatabase -from astrbot.api.provider import Provider, Personality +from astrbot.api.provider import Provider from astrbot import logger from astrbot.core.provider.func_tool_manager import FuncCall from typing import List, AsyncGenerator @@ -29,17 +28,13 @@ from astrbot.core.provider.entities import LLMResponse, ToolCallsResult class ProviderOpenAIOfficial(Provider): def __init__( self, - provider_config: dict, - provider_settings: dict, - db_helper: BaseDatabase, - persistant_history=True, - default_persona: Personality = None, + provider_config, + provider_settings, + default_persona = None, ) -> None: super().__init__( provider_config, provider_settings, - persistant_history, - db_helper, default_persona, ) self.chosen_api_key = None diff --git a/astrbot/core/provider/sources/zhipu_source.py b/astrbot/core/provider/sources/zhipu_source.py index e7e9d4a14..428dee8f4 100644 --- a/astrbot/core/provider/sources/zhipu_source.py +++ b/astrbot/core/provider/sources/zhipu_source.py @@ -1,4 +1,3 @@ -from astrbot.core.db import BaseDatabase from astrbot import logger from astrbot.core.provider.func_tool_manager import FuncCall from typing import List @@ -13,15 +12,11 @@ class ProviderZhipu(ProviderOpenAIOfficial): self, provider_config: dict, provider_settings: dict, - db_helper: BaseDatabase, - persistant_history=True, default_persona=None, ) -> None: super().__init__( provider_config, provider_settings, - db_helper, - persistant_history, default_persona, ) From 20b760529e975e1277462eb79732c1c6dfcfb9a2 Mon Sep 17 00:00:00 2001 From: Soulter <905617992@qq.com> Date: Sun, 29 Jun 2025 15:33:08 +0800 Subject: [PATCH 03/23] fix: anthropic api error when using tools --- .../process_stage/agent_runner/base.py | 6 ++- .../agent_runner/tool_loop_agent.py | 40 +++++++++---------- .../process_stage/method/llm_request.py | 4 +- astrbot/core/provider/entities.py | 4 +- astrbot/core/provider/provider.py | 1 + .../core/provider/sources/anthropic_source.py | 21 +++++++++- 6 files changed, 47 insertions(+), 29 deletions(-) diff --git a/astrbot/core/pipeline/process_stage/agent_runner/base.py b/astrbot/core/pipeline/process_stage/agent_runner/base.py index fd3c7d4ae..d694d767a 100644 --- a/astrbot/core/pipeline/process_stage/agent_runner/base.py +++ b/astrbot/core/pipeline/process_stage/agent_runner/base.py @@ -2,12 +2,16 @@ import abc import typing as T from dataclasses import dataclass from astrbot.core.provider.entities import LLMResponse +from ....message.message_event_result import MessageChain +class AgentResponseData(T.TypedDict): + chain: MessageChain + @dataclass class AgentResponse: type: str - data: dict + data: AgentResponseData class BaseAgentRunner: diff --git a/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py b/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py index d26701d6b..d6d3add83 100644 --- a/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py +++ b/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py @@ -1,7 +1,7 @@ import sys import traceback import typing as T -from .base import BaseAgentRunner, AgentResponse +from .base import BaseAgentRunner, AgentResponse, AgentResponseData from ...context import PipelineContext from astrbot.core.provider.provider import Provider from astrbot.core.platform.astr_message_event import AstrMessageEvent @@ -70,18 +70,16 @@ class ToolLoopAgent(BaseAgentRunner): if llm_response.result_chain: yield AgentResponse( type="streaming_delta", - data={ - "chain": llm_response.result_chain.chain, - }, + data=AgentResponseData(chain=llm_response.result_chain), ) else: yield AgentResponse( type="streaming_delta", - data={ - "chain": MessageChain().message( + data=AgentResponseData( + chain=MessageChain().message( llm_response.completion_text - ), - }, + ) + ), ) else: llm_resp_result = llm_response @@ -105,11 +103,11 @@ class ToolLoopAgent(BaseAgentRunner): self.is_done = True yield AgentResponse( type="err", - data={ - "chain": MessageChain().message( + data=AgentResponseData( + chain=MessageChain().message( f"LLM 响应错误: {llm_resp.completion_text or '未知错误'}" - ), - }, + ) + ), ) if not llm_resp.tools_call_name: @@ -121,16 +119,14 @@ class ToolLoopAgent(BaseAgentRunner): if llm_resp.result_chain: yield AgentResponse( type="llm_result", - data={ - "chain": llm_resp.result_chain.chain, - }, + data=AgentResponseData(chain=llm_resp.result_chain), ) elif llm_resp.completion_text: yield AgentResponse( type="llm_result", - data={ - "chain": MessageChain().message(llm_resp.completion_text), - }, + data=AgentResponseData( + chain=MessageChain().message(llm_resp.completion_text) + ), ) # 如果有工具调用，还需处理工具调用 @@ -142,14 +138,14 @@ class ToolLoopAgent(BaseAgentRunner): elif isinstance(result, MessageChain): yield AgentResponse( type="tool_call_result", - data={ - "chain": result.chain, - }, + data=AgentResponseData(chain=result), ) # 将结果添加到上下文中 tool_calls_result = ToolCallsResult( tool_calls_info=AssistantMessageSegment( - role="assistant", tool_calls=llm_resp.to_openai_tool_calls() + role="assistant", + tool_calls=llm_resp.to_openai_tool_calls(), + content=llm_resp.completion_text, ), tool_calls_result=tool_call_result_blocks, ) diff --git a/astrbot/core/pipeline/process_stage/method/llm_request.py b/astrbot/core/pipeline/process_stage/method/llm_request.py index 7d5fa8135..26d0877d1 100644 --- a/astrbot/core/pipeline/process_stage/method/llm_request.py +++ b/astrbot/core/pipeline/process_stage/method/llm_request.py @@ -163,14 +163,14 @@ class LLMRequestSubStage(Stage): ) event.set_result( MessageEventResult( - chain=resp.data["chain"], + chain=resp.data["chain"].chain, result_content_type=content_typ, ) ) yield event.clear_result() else: - yield resp.data["chain"] + yield resp.data["chain"].chain if tool_loop_agent.done(): break except Exception as e: diff --git a/astrbot/core/provider/entities.py b/astrbot/core/provider/entities.py index 7dd96e8d0..abb01960c 100644 --- a/astrbot/core/provider/entities.py +++ b/astrbot/core/provider/entities.py @@ -58,7 +58,7 @@ class AssistantMessageSegment: """OpenAI 格式的上下文中 role 为 assistant 的消息段。参考: https://platform.openai.com/docs/guides/function-calling""" content: str = None - tool_calls: List[ChatCompletionMessageToolCall | Dict] = None + tool_calls: List[ChatCompletionMessageToolCall | Dict] = field(default_factory=list) role: str = "assistant" def to_dict(self): @@ -67,7 +67,7 @@ class AssistantMessageSegment: } if self.content: ret["content"] = self.content - elif self.tool_calls: + if self.tool_calls: ret["tool_calls"] = self.tool_calls return ret diff --git a/astrbot/core/provider/provider.py b/astrbot/core/provider/provider.py index 1ecca3537..cfe5748da 100644 --- a/astrbot/core/provider/provider.py +++ b/astrbot/core/provider/provider.py @@ -4,6 +4,7 @@ from typing import TypedDict, AsyncGenerator from astrbot.core.provider.func_tool_manager import FuncCall from astrbot.core.provider.entities import LLMResponse, ToolCallsResult from dataclasses import dataclass +from deprecated import deprecated class Personality(TypedDict): diff --git a/astrbot/core/provider/sources/anthropic_source.py b/astrbot/core/provider/sources/anthropic_source.py index 18b4cfead..83ba58cc5 100644 --- a/astrbot/core/provider/sources/anthropic_source.py +++ b/astrbot/core/provider/sources/anthropic_source.py @@ -32,9 +32,9 @@ class ProviderAnthropic(Provider): default_persona, ) - self.chosen_api_key = None + self.chosen_api_key: str = "" self.api_keys: List = provider_config.get("key", []) - self.chosen_api_key = self.api_keys[0] if len(self.api_keys) > 0 else None + self.chosen_api_key = self.api_keys[0] if len(self.api_keys) > 0 else "" self.base_url = provider_config.get("api_base", "https://api.anthropic.com") self.timeout = provider_config.get("timeout", 120) if isinstance(self.timeout, str): @@ -97,6 +97,9 @@ class ProviderAnthropic(Provider): ) else: new_messages.append(message) + + logger.debug(f"message: {messages}") + logger.debug(f"new message: {new_messages}") return system_prompt, new_messages @@ -368,3 +371,17 @@ class ProviderAnthropic(Provider): image_bs64 = base64.b64encode(f.read()).decode("utf-8") return "data:image/jpeg;base64," + image_bs64 return "" + + def get_current_key(self) -> str: + return self.chosen_api_key + + async def get_models(self) -> List[str]: + models_str = [] + models = await self.client.models.list() + models = sorted(models.data, key=lambda x: x.id) + for model in models: + models_str.append(model.id) + return models_str + + def set_key(self, key: str): + self.chosen_api_key = key From 4e3d5641c813b490f2d9b162e71d7fa146a2cd23 Mon Sep 17 00:00:00 2001 From: Soulter <905617992@qq.com> Date: Sun, 29 Jun 2025 15:51:56 +0800 Subject: [PATCH 04/23] chore: code quality --- .../agent_runner/tool_loop_agent.py | 49 ++++++++++--------- astrbot/core/provider/provider.py | 1 - .../core/provider/sources/anthropic_source.py | 5 +- .../core/provider/sources/openai_source.py | 2 - 4 files changed, 28 insertions(+), 29 deletions(-) diff --git a/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py b/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py index d6d3add83..9e31ed3ae 100644 --- a/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py +++ b/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py @@ -51,6 +51,15 @@ class ToolLoopAgent(BaseAgentRunner): self.final_llm_resp = None self.is_done = False + async def _iter_llm_responses(self) -> T.AsyncGenerator[LLMResponse, None]: + """Yields chunks *and* a final LLMResponse.""" + if self.streaming: + stream = self.provider.text_chat_stream(**self.req.__dict__) + async for resp in stream: # type: ignore + yield resp + else: + yield await self.provider.text_chat(**self.req.__dict__) + @override async def step(self): """ @@ -62,29 +71,25 @@ class ToolLoopAgent(BaseAgentRunner): # 执行 LLM 请求 llm_resp_result = None - if self.streaming: - stream = self.provider.text_chat_stream(**self.req.__dict__) - async for llm_response in stream: # type: ignore - assert isinstance(llm_response, LLMResponse) - if llm_response.is_chunk: - if llm_response.result_chain: - yield AgentResponse( - type="streaming_delta", - data=AgentResponseData(chain=llm_response.result_chain), - ) - else: - yield AgentResponse( - type="streaming_delta", - data=AgentResponseData( - chain=MessageChain().message( - llm_response.completion_text - ) - ), - ) + + async for llm_response in self._iter_llm_responses(): + assert isinstance(llm_response, LLMResponse) + if llm_response.is_chunk: + if llm_response.result_chain: + yield AgentResponse( + type="streaming_delta", + data=AgentResponseData(chain=llm_response.result_chain), + ) else: - llm_resp_result = llm_response - else: - llm_resp_result = await self.provider.text_chat(**self.req.__dict__) + yield AgentResponse( + type="streaming_delta", + data=AgentResponseData( + chain=MessageChain().message(llm_response.completion_text) + ), + ) + continue + llm_resp_result = llm_response + break # got final response if not llm_resp_result: return diff --git a/astrbot/core/provider/provider.py b/astrbot/core/provider/provider.py index cfe5748da..1ecca3537 100644 --- a/astrbot/core/provider/provider.py +++ b/astrbot/core/provider/provider.py @@ -4,7 +4,6 @@ from typing import TypedDict, AsyncGenerator from astrbot.core.provider.func_tool_manager import FuncCall from astrbot.core.provider.entities import LLMResponse, ToolCallsResult from dataclasses import dataclass -from deprecated import deprecated class Personality(TypedDict): diff --git a/astrbot/core/provider/sources/anthropic_source.py b/astrbot/core/provider/sources/anthropic_source.py index 83ba58cc5..a53250fb7 100644 --- a/astrbot/core/provider/sources/anthropic_source.py +++ b/astrbot/core/provider/sources/anthropic_source.py @@ -97,9 +97,6 @@ class ProviderAnthropic(Provider): ) else: new_messages.append(message) - - logger.debug(f"message: {messages}") - logger.debug(f"new message: {new_messages}") return system_prompt, new_messages @@ -233,7 +230,7 @@ class ProviderAnthropic(Provider): self, prompt, session_id=None, - image_urls=[], + image_urls=None, func_tool=None, contexts=None, system_prompt=None, diff --git a/astrbot/core/provider/sources/openai_source.py b/astrbot/core/provider/sources/openai_source.py index 6fffa13ee..ef6131d8c 100644 --- a/astrbot/core/provider/sources/openai_source.py +++ b/astrbot/core/provider/sources/openai_source.py @@ -249,8 +249,6 @@ class ProviderOpenAIOfficial(Provider): payloads = {"messages": context_query, **model_config} - logger.debug(f"payloads: {payloads}") - return payloads, context_query async def _handle_api_error( From 8e9c7544cf5dffe04ad9bf64a04314380d318bcc Mon Sep 17 00:00:00 2001 From: Soulter <905617992@qq.com> Date: Sun, 29 Jun 2025 15:54:32 +0800 Subject: [PATCH 05/23] fix: update type check for async generator in PipelineContext --- astrbot/core/pipeline/context.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/astrbot/core/pipeline/context.py b/astrbot/core/pipeline/context.py index 64a8762ed..d98f7c341 100644 --- a/astrbot/core/pipeline/context.py +++ b/astrbot/core/pipeline/context.py @@ -76,7 +76,7 @@ class PipelineContext: # 以前的 handler 会额外传入一个参数, 但是 context 对象实际上在插件实例中有一份 ready_to_call = handler(event, self.plugin_manager.context, *args, **kwargs) - if isinstance(ready_to_call, T.AsyncGenerator): + if inspect.isasyncgen(ready_to_call): _has_yielded = False try: async for ret in ready_to_call: From 5f1dfa75995636b24208cf815635e4d07148d74a Mon Sep 17 00:00:00 2001 From: Soulter <905617992@qq.com> Date: Sun, 29 Jun 2025 15:58:22 +0800 Subject: [PATCH 06/23] fix: handle LLM response and execute event hook in ToolLoopAgent --- .../process_stage/agent_runner/tool_loop_agent.py | 13 +++++++------ 1 file changed, 7 insertions(+), 6 deletions(-) diff --git a/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py b/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py index 9e31ed3ae..07b808925 100644 --- a/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py +++ b/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py @@ -89,19 +89,15 @@ class ToolLoopAgent(BaseAgentRunner): ) continue llm_resp_result = llm_response - break # got final response + break # got final response if not llm_resp_result: return - # 执行事件钩子 - await self.pipeline_ctx.call_event_hook( - self.event, EventType.OnLLMResponseEvent, self.final_llm_resp - ) - # 处理 LLM 响应 llm_resp = llm_resp_result logger.info(f"LLMResp: {llm_resp}") + if llm_resp.role == "err": # 如果 LLM 响应错误，直接返回错误信息 self.final_llm_resp = llm_resp @@ -120,6 +116,11 @@ class ToolLoopAgent(BaseAgentRunner): self.final_llm_resp = llm_resp self.is_done = True + # 执行事件钩子 + await self.pipeline_ctx.call_event_hook( + self.event, EventType.OnLLMResponseEvent, llm_resp + ) + # 返回 LLM 结果 if llm_resp.result_chain: yield AgentResponse( From efef34c01e2a4910f1650b5114a5b623aedfc255 Mon Sep 17 00:00:00 2001 From: Raven95676 Date: Sun, 29 Jun 2025 16:06:44 +0800 Subject: [PATCH 07/23] style: format code --- .../process_stage/agent_runner/base.py | 1 + .../core/provider/sources/gemini_source.py | 31 +++++++++---------- 2 files changed, 16 insertions(+), 16 deletions(-) diff --git a/astrbot/core/pipeline/process_stage/agent_runner/base.py b/astrbot/core/pipeline/process_stage/agent_runner/base.py index d694d767a..c2fb1e79d 100644 --- a/astrbot/core/pipeline/process_stage/agent_runner/base.py +++ b/astrbot/core/pipeline/process_stage/agent_runner/base.py @@ -8,6 +8,7 @@ from ....message.message_event_result import MessageChain class AgentResponseData(T.TypedDict): chain: MessageChain + @dataclass class AgentResponse: type: str diff --git a/astrbot/core/provider/sources/gemini_source.py b/astrbot/core/provider/sources/gemini_source.py index 31c1695f5..e1d1f11bd 100644 --- a/astrbot/core/provider/sources/gemini_source.py +++ b/astrbot/core/provider/sources/gemini_source.py @@ -53,7 +53,7 @@ class ProviderGoogleGenAI(Provider): self, provider_config, provider_settings, - default_persona = None, + default_persona=None, ) -> None: super().__init__( provider_config, @@ -259,12 +259,10 @@ class ProviderGoogleGenAI(Provider): contents.append(content_cls(parts=part)) gemini_contents: list[types.Content] = [] - native_tool_enabled = any( - [ - self.provider_config.get("gm_native_coderunner", False), - self.provider_config.get("gm_native_search", False), - ] - ) + native_tool_enabled = any([ + self.provider_config.get("gm_native_coderunner", False), + self.provider_config.get("gm_native_search", False), + ]) for message in payloads["messages"]: role, content = message["role"], message.get("content") @@ -501,12 +499,12 @@ class ProviderGoogleGenAI(Provider): async def text_chat( self, prompt: str, - session_id = None, - image_urls = None, - func_tool = None, - contexts = None, - system_prompt = None, - tool_calls_result = None, + session_id=None, + image_urls=None, + func_tool=None, + contexts=None, + system_prompt=None, + tool_calls_result=None, **kwargs, ) -> LLMResponse: if contexts is None: @@ -630,9 +628,10 @@ class ProviderGoogleGenAI(Provider): if not image_data: logger.warning(f"图片 {image_url} 得到的结果为空，将忽略。") continue - user_content["content"].append( - {"type": "image_url", "image_url": {"url": image_data}} - ) + user_content["content"].append({ + "type": "image_url", + "image_url": {"url": image_data}, + }) return user_content else: return {"role": "user", "content": text} From b516fb05506d2b5ef8179922963fe3b3c898c6a3 Mon Sep 17 00:00:00 2001 From: Soulter <905617992@qq.com> Date: Sun, 29 Jun 2025 16:12:40 +0800 Subject: [PATCH 08/23] chore: remove dump_plugins.py --- dump_plugins.py | 82 ------------------------------------------------- 1 file changed, 82 deletions(-) delete mode 100644 dump_plugins.py diff --git a/dump_plugins.py b/dump_plugins.py deleted file mode 100644 index efe34b230..000000000 --- a/dump_plugins.py +++ /dev/null @@ -1,82 +0,0 @@ -import urllib.request -import json - -# --- 配置 --- -REPO_OWNER = "AstrBotDevs" -REPO_NAME = "AstrBot" -START_ISSUE_NUMBER = 970 -LABEL_TO_FIND = "plugin-publish" -OUTPUT_FILENAME = "plugin_publish_issues.txt" -ISSUE_STATE = "closed" # 只筛选状态为 closed 的 Issue - - -def fetch_and_format_issues( - repo_owner, repo_name, start_issue_number, label_name, output_file, issue_state -): - api_url = f"https://api.github.com/repos/{repo_owner}/{repo_name}/issues?state={issue_state}&labels={label_name}&sort=created&direction=asc&per_page=100" - headers = {"Accept": "application/vnd.github+json"} - found_issues = [] - page = 1 - - while True: - request_url = f"{api_url}&page={page}" - request = urllib.request.Request(request_url, headers=headers) - try: - with urllib.request.urlopen(request) as response: - data = json.loads(response.read().decode("utf-8")) - if not data: - break # 没有更多 Issues 了 - - for issue in data: - issue_number = issue.get("number") - if issue_number is not None and issue_number >= start_issue_number: - title = issue.get("title", "No Title") - author = issue.get("user", {}).get("login", "Unknown") - found_issues.append(f"{title} by @{author} in #{issue_number}") - - # 检查是否有下一页 - if "Link" in response.headers: - links = response.headers["Link"].split(",") - next_page_exists = False - for link in links: - if 'rel="next"' in link: - next_page_exists = True - break - if not next_page_exists: - break - page += 1 - else: - break # 没有 Link header，假设没有更多页了 - - except urllib.error.HTTPError as e: - print(f"HTTP Error: {e.code} - {e.reason}") - return - except urllib.error.URLError as e: - print(f"URL Error: {e.reason}") - return - except json.JSONDecodeError: - print("Error decoding JSON response.") - return - - if found_issues: - with open(output_file, "w", encoding="utf-8") as f: - for line in found_issues: - f.write(line + "\n") - print( - f"已找到 {len(found_issues)} 个状态为 '{issue_state}'，带有 '{label_name}' 标签且 Issue Number 大于等于 {start_issue_number} 的 Issues，并已保存到 '{output_file}'。" - ) - else: - print( - f"未找到任何状态为 '{issue_state}'，带有 '{label_name}' 标签且 Issue Number 大于等于 {start_issue_number} 的 Issues。" - ) - - -if __name__ == "__main__": - fetch_and_format_issues( - REPO_OWNER, - REPO_NAME, - START_ISSUE_NUMBER, - LABEL_TO_FIND, - OUTPUT_FILENAME, - ISSUE_STATE, - ) From 8b2fc29d5bba62335c5ab8a13b10179a07e77f64 Mon Sep 17 00:00:00 2001 From: Raven95676 Date: Sun, 29 Jun 2025 16:13:15 +0800 Subject: [PATCH 09/23] chore: remove accidentally committed file --- dump_plugins.py | 82 ------------------------------------------------- 1 file changed, 82 deletions(-) delete mode 100644 dump_plugins.py diff --git a/dump_plugins.py b/dump_plugins.py deleted file mode 100644 index efe34b230..000000000 --- a/dump_plugins.py +++ /dev/null @@ -1,82 +0,0 @@ -import urllib.request -import json - -# --- 配置 --- -REPO_OWNER = "AstrBotDevs" -REPO_NAME = "AstrBot" -START_ISSUE_NUMBER = 970 -LABEL_TO_FIND = "plugin-publish" -OUTPUT_FILENAME = "plugin_publish_issues.txt" -ISSUE_STATE = "closed" # 只筛选状态为 closed 的 Issue - - -def fetch_and_format_issues( - repo_owner, repo_name, start_issue_number, label_name, output_file, issue_state -): - api_url = f"https://api.github.com/repos/{repo_owner}/{repo_name}/issues?state={issue_state}&labels={label_name}&sort=created&direction=asc&per_page=100" - headers = {"Accept": "application/vnd.github+json"} - found_issues = [] - page = 1 - - while True: - request_url = f"{api_url}&page={page}" - request = urllib.request.Request(request_url, headers=headers) - try: - with urllib.request.urlopen(request) as response: - data = json.loads(response.read().decode("utf-8")) - if not data: - break # 没有更多 Issues 了 - - for issue in data: - issue_number = issue.get("number") - if issue_number is not None and issue_number >= start_issue_number: - title = issue.get("title", "No Title") - author = issue.get("user", {}).get("login", "Unknown") - found_issues.append(f"{title} by @{author} in #{issue_number}") - - # 检查是否有下一页 - if "Link" in response.headers: - links = response.headers["Link"].split(",") - next_page_exists = False - for link in links: - if 'rel="next"' in link: - next_page_exists = True - break - if not next_page_exists: - break - page += 1 - else: - break # 没有 Link header，假设没有更多页了 - - except urllib.error.HTTPError as e: - print(f"HTTP Error: {e.code} - {e.reason}") - return - except urllib.error.URLError as e: - print(f"URL Error: {e.reason}") - return - except json.JSONDecodeError: - print("Error decoding JSON response.") - return - - if found_issues: - with open(output_file, "w", encoding="utf-8") as f: - for line in found_issues: - f.write(line + "\n") - print( - f"已找到 {len(found_issues)} 个状态为 '{issue_state}'，带有 '{label_name}' 标签且 Issue Number 大于等于 {start_issue_number} 的 Issues，并已保存到 '{output_file}'。" - ) - else: - print( - f"未找到任何状态为 '{issue_state}'，带有 '{label_name}' 标签且 Issue Number 大于等于 {start_issue_number} 的 Issues。" - ) - - -if __name__ == "__main__": - fetch_and_format_issues( - REPO_OWNER, - REPO_NAME, - START_ISSUE_NUMBER, - LABEL_TO_FIND, - OUTPUT_FILENAME, - ISSUE_STATE, - ) From efa45e6203e52012894c60cfeff4128a73654506 Mon Sep 17 00:00:00 2001 From: Soulter <905617992@qq.com> Date: Sun, 29 Jun 2025 16:35:41 +0800 Subject: [PATCH 10/23] fix: validate and repair message contexts in LLMRequestSubStage --- .../process_stage/method/llm_request.py | 20 +++++++++++++++++++ 1 file changed, 20 insertions(+) diff --git a/astrbot/core/pipeline/process_stage/method/llm_request.py b/astrbot/core/pipeline/process_stage/method/llm_request.py index 26d0877d1..1134a19e2 100644 --- a/astrbot/core/pipeline/process_stage/method/llm_request.py +++ b/astrbot/core/pipeline/process_stage/method/llm_request.py @@ -141,6 +141,9 @@ class LLMRequestSubStage(Stage): if not req.session_id: req.session_id = event.unified_msg_origin + # fix messages + req.contexts = self.fix_messages(req.contexts) + # Call Agent tool_loop_agent = ToolLoopAgent( provider=provider, @@ -304,3 +307,20 @@ class LLMRequestSubStage(Stage): event.unified_msg_origin, req.conversation.cid, history=messages ) logger.debug(f"messages persisted: {messages}") + + def fix_messages(self, messages: list[dict]) -> list[dict]: + """验证并且修复上下文""" + fixed_messages = [] + for message in messages: + if message.get("role") == "tool": + # tool block 前面必须要有 user 和 assistant block + if len(fixed_messages) < 2: + # 这种情况可能是上下文被截断导致的 + # 我们直接将之前的上下文都清空 + fixed_messages = [] + else: + fixed_messages.append(message) + else: + fixed_messages.append(message) + return fixed_messages + From e9b23f68fd87f5a9aba0850125d965b2c7b62373 Mon Sep 17 00:00:00 2001 From: Raven95676 Date: Sun, 29 Jun 2025 17:19:53 +0800 Subject: [PATCH 11/23] perf: add AgentState Enum for improved state management --- .../process_stage/agent_runner/base.py | 9 +++++ .../agent_runner/tool_loop_agent.py | 33 ++++++++++++------- .../process_stage/method/llm_request.py | 13 +++----- 3 files changed, 35 insertions(+), 20 deletions(-) diff --git a/astrbot/core/pipeline/process_stage/agent_runner/base.py b/astrbot/core/pipeline/process_stage/agent_runner/base.py index c2fb1e79d..431a95ca6 100644 --- a/astrbot/core/pipeline/process_stage/agent_runner/base.py +++ b/astrbot/core/pipeline/process_stage/agent_runner/base.py @@ -3,6 +3,15 @@ import typing as T from dataclasses import dataclass from astrbot.core.provider.entities import LLMResponse from ....message.message_event_result import MessageChain +from enum import Enum, auto + + +class AgentState(Enum): + """Agent 状态枚举""" + IDLE = auto() # 初始状态 + RUNNING = auto() # 运行中 + DONE = auto() # 完成 + ERROR = auto() # 错误状态 class AgentResponseData(T.TypedDict): diff --git a/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py b/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py index 07b808925..04fda3c1c 100644 --- a/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py +++ b/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py @@ -1,7 +1,7 @@ import sys import traceback import typing as T -from .base import BaseAgentRunner, AgentResponse, AgentResponseData +from .base import BaseAgentRunner, AgentResponse, AgentResponseData, AgentState from ...context import PipelineContext from astrbot.core.provider.provider import Provider from astrbot.core.platform.astr_message_event import AstrMessageEvent @@ -43,13 +43,22 @@ class ToolLoopAgent(BaseAgentRunner): self.req = None self.event = event self.pipeline_ctx = pipeline_ctx + self._state = AgentState.IDLE + self.final_llm_resp = None + self.streaming = False @override async def reset(self, req: ProviderRequest, streaming: bool) -> None: self.req = req self.streaming = streaming self.final_llm_resp = None - self.is_done = False + self._state = AgentState.IDLE + + def _transition_state(self, new_state: AgentState) -> None: + """转换 Agent 状态""" + if self._state != new_state: + logger.info(f"Agent state transition: {self._state} -> {new_state}") + self._state = new_state async def _iter_llm_responses(self) -> T.AsyncGenerator[LLMResponse, None]: """Yields chunks *and* a final LLMResponse.""" @@ -69,7 +78,8 @@ class ToolLoopAgent(BaseAgentRunner): if not self.req: raise ValueError("Request is not set. Please call reset() first.") - # 执行 LLM 请求 + # 开始处理，转换到运行状态 + self._transition_state(AgentState.RUNNING) llm_resp_result = None async for llm_response in self._iter_llm_responses(): @@ -99,9 +109,9 @@ class ToolLoopAgent(BaseAgentRunner): logger.info(f"LLMResp: {llm_resp}") if llm_resp.role == "err": - # 如果 LLM 响应错误，直接返回错误信息 + # 如果 LLM 响应错误，转换到错误状态 self.final_llm_resp = llm_resp - self.is_done = True + self._transition_state(AgentState.ERROR) yield AgentResponse( type="err", data=AgentResponseData( @@ -112,9 +122,9 @@ class ToolLoopAgent(BaseAgentRunner): ) if not llm_resp.tools_call_name: - # 如果没有工具调用，结束 Agent Loop + # 如果没有工具调用，转换到完成状态 self.final_llm_resp = llm_resp - self.is_done = True + self._transition_state(AgentState.DONE) # 执行事件钩子 await self.pipeline_ctx.call_event_hook( @@ -157,8 +167,6 @@ class ToolLoopAgent(BaseAgentRunner): ) self.req.append_tool_calls_result(tool_calls_result) - logger.info("done: %s", self.is_done) - async def _handle_function_tools( self, req: ProviderRequest, @@ -251,13 +259,13 @@ class ToolLoopAgent(BaseAgentRunner): else: # Tool 直接请求发送消息给用户 # 这里我们将直接结束 Agent Loop。 - self.is_done = True + self._transition_state(AgentState.DONE) if res := self.event.get_result(): if res.chain: yield MessageChain(chain=res.chain) self.event.clear_result() - except BaseException as e: + except Exception as e: logger.warning(traceback.format_exc()) tool_call_result_blocks.append( ToolCallMessageSegment( @@ -272,7 +280,8 @@ class ToolLoopAgent(BaseAgentRunner): yield tool_call_result_blocks def done(self) -> bool: - return self.is_done + """检查 Agent 是否已完成工作""" + return self._state in (AgentState.DONE, AgentState.ERROR) def get_final_llm_resp(self) -> LLMResponse | None: return self.final_llm_resp diff --git a/astrbot/core/pipeline/process_stage/method/llm_request.py b/astrbot/core/pipeline/process_stage/method/llm_request.py index 1134a19e2..1ede6313e 100644 --- a/astrbot/core/pipeline/process_stage/method/llm_request.py +++ b/astrbot/core/pipeline/process_stage/method/llm_request.py @@ -268,13 +268,11 @@ class LLMRequestSubStage(Stage): cid=cid, title=title, ) - web_chat_back_queue.put_nowait( - { - "type": "update_title", - "cid": cid, - "data": title, - } - ) + web_chat_back_queue.put_nowait({ + "type": "update_title", + "cid": cid, + "data": title, + }) async def _save_to_history( self, @@ -323,4 +321,3 @@ class LLMRequestSubStage(Stage): else: fixed_messages.append(message) return fixed_messages - From 777c50300298f05a3f4cd7fde69b03989a2ce95c Mon Sep 17 00:00:00 2001 From: Raven95676 Date: Sun, 29 Jun 2025 17:32:53 +0800 Subject: [PATCH 12/23] perf: change logging level to debug for agent state transitions and LLM responses --- .../pipeline/process_stage/agent_runner/tool_loop_agent.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py b/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py index 04fda3c1c..27ce6ae0a 100644 --- a/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py +++ b/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py @@ -57,7 +57,7 @@ class ToolLoopAgent(BaseAgentRunner): def _transition_state(self, new_state: AgentState) -> None: """转换 Agent 状态""" if self._state != new_state: - logger.info(f"Agent state transition: {self._state} -> {new_state}") + logger.debug(f"Agent state transition: {self._state} -> {new_state}") self._state = new_state async def _iter_llm_responses(self) -> T.AsyncGenerator[LLMResponse, None]: @@ -106,7 +106,7 @@ class ToolLoopAgent(BaseAgentRunner): # 处理 LLM 响应 llm_resp = llm_resp_result - logger.info(f"LLMResp: {llm_resp}") + logger.debug(f"LLMResp: {llm_resp}") if llm_resp.role == "err": # 如果 LLM 响应错误，转换到错误状态 From 2f941de65bb5f0df86f60f7f1d7d012790669b36 Mon Sep 17 00:00:00 2001 From: Soulter <905617992@qq.com> Date: Sun, 29 Jun 2025 21:19:40 +0800 Subject: [PATCH 13/23] =?UTF-8?q?feat:=20=E6=94=AF=E6=8C=81=E5=B1=95?= =?UTF-8?q?=E7=A4=BA=E5=B7=A5=E5=85=B7=E4=BD=BF=E7=94=A8=E8=BF=87=E7=A8=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- astrbot/core/config/default.py | 10 ++++- astrbot/core/message/message_event_result.py | 2 + .../agent_runner/tool_loop_agent.py | 13 ++++++ .../process_stage/method/llm_request.py | 40 +++++++++++++------ .../platform/sources/telegram/tg_event.py | 6 +++ .../platform/sources/webchat/webchat_event.py | 20 ++++++++++ 6 files changed, 77 insertions(+), 14 deletions(-) diff --git a/astrbot/core/config/default.py b/astrbot/core/config/default.py index 17cfbd39e..30d028e34 100644 --- a/astrbot/core/config/default.py +++ b/astrbot/core/config/default.py @@ -61,6 +61,7 @@ DEFAULT_CONFIG = { "max_context_length": -1, "dequeue_context_length": 1, "streaming_response": False, + "show_tool_use_status": False, "streaming_segmented": False, "separate_provider": False, }, @@ -445,7 +446,7 @@ CONFIG_METADATA_2 = { "ignore_bot_self_message": { "description": "是否忽略机器人自身的消息", "type": "bool", - "hint": "某些平台如 gewechat 会将自身账号在其他 APP 端发送的消息也当做消息事件下发导致给自己发消息时唤醒机器人", + "hint": "某些平台会将自身账号在其他 APP 端发送的消息也当做消息事件下发导致给自己发消息时唤醒机器人", }, "ignore_at_all": { "description": "是否忽略 @ 全体成员", @@ -1692,10 +1693,15 @@ CONFIG_METADATA_2 = { "type": "bool", "hint": "启用后，将会流式输出 LLM 的响应。目前仅支持 OpenAI API提供商 以及 Telegram、QQ Official 私聊 两个平台", }, + "show_tool_use_status": { + "description": "函数调用状态输出", + "type": "bool", + "hint": "在触发函数调用时输出其函数名和内容。", + }, "streaming_segmented": { "description": "不支持流式回复的平台分段输出", "type": "bool", - "hint": "启用后，若平台不支持流式回复，会分段输出。目前仅支持 aiocqhttp 和 gewechat 两个平台，不支持或无需使用流式分段输出的平台会静默忽略此选项", + "hint": "启用后，若平台不支持流式回复，会分段输出。目前仅支持 aiocqhttp 两个平台，不支持或无需使用流式分段输出的平台会静默忽略此选项", }, }, }, diff --git a/astrbot/core/message/message_event_result.py b/astrbot/core/message/message_event_result.py index c5123bca3..7bfdd34c8 100644 --- a/astrbot/core/message/message_event_result.py +++ b/astrbot/core/message/message_event_result.py @@ -24,6 +24,8 @@ class MessageChain: chain: List[BaseMessageComponent] = field(default_factory=list) use_t2i_: Optional[bool] = None # None 为跟随用户设置 + type: Optional[str] = None + """消息链承载的消息的类型。可选，用于让消息平台区分不同业务场景的消息链。""" def message(self, message: str): """添加一条文本消息到消息链 `chain` 中。 diff --git a/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py b/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py index 27ce6ae0a..3163e02e4 100644 --- a/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py +++ b/astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py @@ -148,6 +148,13 @@ class ToolLoopAgent(BaseAgentRunner): # 如果有工具调用，还需处理工具调用 if llm_resp.tools_call_name: tool_call_result_blocks = [] + for tool_call_name in llm_resp.tools_call_name: + yield AgentResponse( + type="tool_call", + data=AgentResponseData( + chain=MessageChain().message(f"🔨 调用工具: {tool_call_name}") + ), + ) async for result in self._handle_function_tools(self.req, llm_resp): if isinstance(result, list): tool_call_result_blocks = result @@ -183,6 +190,8 @@ class ToolLoopAgent(BaseAgentRunner): llm_response.tools_call_ids, ): try: + if not req.func_tool: + return func_tool = req.func_tool.get_func(func_tool_name) if func_tool.origin == "mcp": logger.info( @@ -200,6 +209,7 @@ class ToolLoopAgent(BaseAgentRunner): content=res.content[0].text, ) ) + yield MessageChain().message(res.content[0].text) elif isinstance(res.content[0], ImageContent): tool_call_result_blocks.append( ToolCallMessageSegment( @@ -219,6 +229,7 @@ class ToolLoopAgent(BaseAgentRunner): content=resource.text, ) ) + yield MessageChain().message(resource.text) elif ( isinstance(resource, BlobResourceContents) and resource.mimeType @@ -240,6 +251,7 @@ class ToolLoopAgent(BaseAgentRunner): content="返回的数据类型不受支持", ) ) + yield MessageChain().message("返回的数据类型不受支持。") else: logger.info(f"使用工具：{func_tool_name}，参数：{func_tool_args}") # 尝试调用工具函数 @@ -256,6 +268,7 @@ class ToolLoopAgent(BaseAgentRunner): content=resp, ) ) + yield MessageChain().message(resp) else: # Tool 直接请求发送消息给用户 # 这里我们将直接结束 Agent Loop。 diff --git a/astrbot/core/pipeline/process_stage/method/llm_request.py b/astrbot/core/pipeline/process_stage/method/llm_request.py index 1ede6313e..e2a506ca7 100644 --- a/astrbot/core/pipeline/process_stage/method/llm_request.py +++ b/astrbot/core/pipeline/process_stage/method/llm_request.py @@ -31,15 +31,17 @@ class LLMRequestSubStage(Stage): async def initialize(self, ctx: PipelineContext) -> None: self.ctx = ctx conf = ctx.astrbot_config + settings = conf["provider_settings"] self.bot_wake_prefixs: list[str] = conf["wake_prefix"] # list - self.provider_wake_prefix: str = conf["provider_settings"]["wake_prefix"] # str - self.max_context_length = conf["provider_settings"]["max_context_length"] # int + self.provider_wake_prefix: str = settings["wake_prefix"] # str + self.max_context_length = settings["max_context_length"] # int self.dequeue_context_length: int = min( - max(1, conf["provider_settings"]["dequeue_context_length"]), + max(1, settings["dequeue_context_length"]), self.max_context_length - 1, ) - self.streaming_response: bool = conf["provider_settings"]["streaming_response"] - self.max_step: int = conf["provider_settings"].get("max_agent_step", 10) + self.streaming_response: bool = settings["streaming_response"] + self.max_step: int = settings.get("max_agent_step", 10) + self.show_tool_use: bool = settings.get("show_tool_use_status", True) for bwp in self.bot_wake_prefixs: if self.provider_wake_prefix.startswith(bwp): @@ -158,10 +160,17 @@ class LLMRequestSubStage(Stage): step_idx += 1 try: async for resp in tool_loop_agent.step(): + if resp.type == "tool_call_result": + continue # 跳过工具调用结果 + if resp.type == "tool_call": + if self.show_tool_use or event.get_platform_name() == "webchat": + await event.send(resp.data["chain"]) + continue + if not self.streaming_response: content_typ = ( ResultContentType.LLM_RESULT - if resp.type == "llm_resp" + if resp.type == "llm_result" else ResultContentType.GENERAL_RESULT ) event.set_result( @@ -173,9 +182,14 @@ class LLMRequestSubStage(Stage): yield event.clear_result() else: - yield resp.data["chain"].chain + if resp.type == "streaming_delta": + yield resp.data["chain"] # MessageChain if tool_loop_agent.done(): break + if self.streaming_response: + # 用来标记流式响应结束 + yield MessageChain(chain=[], type="break") + except Exception as e: logger.error(traceback.format_exc()) event.set_result( @@ -268,11 +282,13 @@ class LLMRequestSubStage(Stage): cid=cid, title=title, ) - web_chat_back_queue.put_nowait({ - "type": "update_title", - "cid": cid, - "data": title, - }) + web_chat_back_queue.put_nowait( + { + "type": "update_title", + "cid": cid, + "data": title, + } + ) async def _save_to_history( self, diff --git a/astrbot/core/platform/sources/telegram/tg_event.py b/astrbot/core/platform/sources/telegram/tg_event.py index 30be7d4ff..a47e4328e 100644 --- a/astrbot/core/platform/sources/telegram/tg_event.py +++ b/astrbot/core/platform/sources/telegram/tg_event.py @@ -158,6 +158,12 @@ class TelegramPlatformEvent(AstrMessageEvent): async for chain in generator: if isinstance(chain, MessageChain): + if chain.type == "break": + # 分割符 + message_id = None # 重置消息 ID + delta = "" # 重置 delta + continue + # 处理消息链中的每个组件 for i in chain.chain: if isinstance(i, Plain): diff --git a/astrbot/core/platform/sources/webchat/webchat_event.py b/astrbot/core/platform/sources/webchat/webchat_event.py index 76b5dc85d..cdf80f6ef 100644 --- a/astrbot/core/platform/sources/webchat/webchat_event.py +++ b/astrbot/core/platform/sources/webchat/webchat_event.py @@ -96,6 +96,14 @@ class WebChatMessageEvent(AstrMessageEvent): return data async def send(self, message: MessageChain): + await web_chat_back_queue.put( + { + "type": "end", + "data": "", + "streaming": False, + "cid": self.session_id.split("!")[-1], + } + ) await WebChatMessageEvent._send(message, session_id=self.session_id) await web_chat_back_queue.put( { @@ -110,6 +118,18 @@ class WebChatMessageEvent(AstrMessageEvent): async def send_streaming(self, generator, use_fallback: bool = False): final_data = "" async for chain in generator: + if chain.type == "break": + # 分割符 + await web_chat_back_queue.put( + { + "type": "end", + "data": final_data, + "streaming": True, + "cid": self.session_id.split("!")[-1], + } + ) + final_data = "" + continue final_data += await WebChatMessageEvent._send( chain, session_id=self.session_id, streaming=True ) From 5e1e2d1a4f49fedfbc0b220a5e82914f2113be0c Mon Sep 17 00:00:00 2001 From: Soulter <905617992@qq.com> Date: Sun, 29 Jun 2025 21:19:52 +0800 Subject: [PATCH 14/23] =?UTF-8?q?perf:=20=E4=BC=98=E5=8C=96=20ChatPage=20U?= =?UTF-8?q?I?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- dashboard/src/theme/DarkTheme.ts | 3 ++- dashboard/src/theme/LightTheme.ts | 3 ++- dashboard/src/types/themeTypes/ThemeType.ts | 1 + dashboard/src/views/ChatPage.vue | 22 ++++++++------------- 4 files changed, 13 insertions(+), 16 deletions(-) diff --git a/dashboard/src/theme/DarkTheme.ts b/dashboard/src/theme/DarkTheme.ts index 9276c8f98..5906eca32 100644 --- a/dashboard/src/theme/DarkTheme.ts +++ b/dashboard/src/theme/DarkTheme.ts @@ -39,7 +39,8 @@ const PurpleThemeDark: ThemeTypes = { background: '#111111', overlay: '#111111aa', codeBg: '#282833', - code: '#ffffffdd' + code: '#ffffffdd', + chatMessageBubble: '#2d2e30', } }; diff --git a/dashboard/src/theme/LightTheme.ts b/dashboard/src/theme/LightTheme.ts index 35aa1339a..a555fddd7 100644 --- a/dashboard/src/theme/LightTheme.ts +++ b/dashboard/src/theme/LightTheme.ts @@ -39,7 +39,8 @@ const PurpleTheme: ThemeTypes = { background: '#f9fafcf4', overlay: '#ffffffaa', codeBg: '#f5f0ff', - code: '#673ab7' + code: '#673ab7', + chatMessageBubble: '#e7ebf4', } }; diff --git a/dashboard/src/types/themeTypes/ThemeType.ts b/dashboard/src/types/themeTypes/ThemeType.ts index 69b00a1ab..f5e2e5491 100644 --- a/dashboard/src/types/themeTypes/ThemeType.ts +++ b/dashboard/src/types/themeTypes/ThemeType.ts @@ -35,5 +35,6 @@ export type ThemeTypes = { secondary200?: string; codeBg?: string; code?: string; + chatMessageBubble?: string; }; }; diff --git a/dashboard/src/views/ChatPage.vue b/dashboard/src/views/ChatPage.vue index fadba8aac..c47509ab5 100644 --- a/dashboard/src/views/ChatPage.vue +++ b/dashboard/src/views/ChatPage.vue @@ -175,7 +175,7 @@
-
+
{{ msg.message }} @@ -195,15 +195,12 @@
- - -
- - ✨ + + ✨
@@ -1574,28 +1571,25 @@ export default { } .message-bubble { - padding: 12px 16px; - border-radius: 18px; + padding: 8px 16px; + border-radius: 12px; max-width: 80%; - box-shadow: 0 1px 2px rgba(0, 0, 0, 0.1); } .user-bubble { - background-color: var(--v-theme-background); + background-color: var(--v-theme-chatMessageBubble); color: var(--v-theme-primaryText); - border-top-right-radius: 4px; } .bot-bubble { - background-color: var(--v-theme-surface); border: 1px solid var(--v-theme-border); color: var(--v-theme-primaryText); - border-top-left-radius: 4px; } .user-avatar, .bot-avatar { - align-self: flex-end; + align-self: flex-start; + margin-top: 12px; } /* 附件样式 */ From 8203fdb4f053dbb760e6e4abd3b5fbcc05f5e0f4 Mon Sep 17 00:00:00 2001 From: Soulter <905617992@qq.com> Date: Sun, 29 Jun 2025 21:35:39 +0800 Subject: [PATCH 15/23] fix: webchat show tool call --- .../core/pipeline/process_stage/method/llm_request.py | 7 ++++--- .../core/platform/sources/webchat/webchat_event.py | 11 ++--------- 2 files changed, 6 insertions(+), 12 deletions(-) diff --git a/astrbot/core/pipeline/process_stage/method/llm_request.py b/astrbot/core/pipeline/process_stage/method/llm_request.py index e2a506ca7..2ebe4bd42 100644 --- a/astrbot/core/pipeline/process_stage/method/llm_request.py +++ b/astrbot/core/pipeline/process_stage/method/llm_request.py @@ -163,7 +163,11 @@ class LLMRequestSubStage(Stage): if resp.type == "tool_call_result": continue # 跳过工具调用结果 if resp.type == "tool_call": + if self.streaming_response: + # 用来标记流式响应需要分节 + yield MessageChain(chain=[], type="break") if self.show_tool_use or event.get_platform_name() == "webchat": + resp.data["chain"].type = "tool_call" await event.send(resp.data["chain"]) continue @@ -186,9 +190,6 @@ class LLMRequestSubStage(Stage): yield resp.data["chain"] # MessageChain if tool_loop_agent.done(): break - if self.streaming_response: - # 用来标记流式响应结束 - yield MessageChain(chain=[], type="break") except Exception as e: logger.error(traceback.format_exc()) diff --git a/astrbot/core/platform/sources/webchat/webchat_event.py b/astrbot/core/platform/sources/webchat/webchat_event.py index cdf80f6ef..111027a5c 100644 --- a/astrbot/core/platform/sources/webchat/webchat_event.py +++ b/astrbot/core/platform/sources/webchat/webchat_event.py @@ -35,6 +35,7 @@ class WebChatMessageEvent(AstrMessageEvent): "cid": cid, "data": data, "streaming": streaming, + "chain_type": message.type, } ) elif isinstance(comp, Image): @@ -96,14 +97,6 @@ class WebChatMessageEvent(AstrMessageEvent): return data async def send(self, message: MessageChain): - await web_chat_back_queue.put( - { - "type": "end", - "data": "", - "streaming": False, - "cid": self.session_id.split("!")[-1], - } - ) await WebChatMessageEvent._send(message, session_id=self.session_id) await web_chat_back_queue.put( { @@ -118,7 +111,7 @@ class WebChatMessageEvent(AstrMessageEvent): async def send_streaming(self, generator, use_fallback: bool = False): final_data = "" async for chain in generator: - if chain.type == "break": + if chain.type == "break" and final_data: # 分割符 await web_chat_back_queue.put( { From 9bf8aadca986b7a2660781c68369a040b8f8686a Mon Sep 17 00:00:00 2001 From: Soulter <905617992@qq.com> Date: Sun, 29 Jun 2025 21:52:45 +0800 Subject: [PATCH 16/23] =?UTF-8?q?=F0=9F=93=A6=20release:=20v3.5.18?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- astrbot/core/config/default.py | 2 +- changelogs/v3.5.18.md | 18 ++++++++++++++++++ pyproject.toml | 2 +- 3 files changed, 20 insertions(+), 2 deletions(-) create mode 100644 changelogs/v3.5.18.md diff --git a/astrbot/core/config/default.py b/astrbot/core/config/default.py index 222fa64d6..edf42992f 100644 --- a/astrbot/core/config/default.py +++ b/astrbot/core/config/default.py @@ -6,7 +6,7 @@ import os from astrbot.core.utils.astrbot_path import get_astrbot_data_path -VERSION = "3.5.17" +VERSION = "3.5.18" DB_PATH = os.path.join(get_astrbot_data_path(), "data_v3.db") # 默认配置 diff --git a/changelogs/v3.5.18.md b/changelogs/v3.5.18.md new file mode 100644 index 000000000..d9eaa6de8 --- /dev/null +++ b/changelogs/v3.5.18.md @@ -0,0 +1,18 @@ +# What's Changed + +> 重构了大模型请求部分，如果发现此部分使用时有问题请提交 issue + +1. 修复: 安装插件按钮被删除、无法自定义安装插件 +2. 修复: 环境变量中的代理地址无法生效 +1. 修复: randomize jwt secret +2. 修复: 在 Node 消息段发送简单文本信息的问题 +1. 修复: QQ 官方机器人适配器使用 SessionController(会话控制)功能时机器人回复消息无法发送到聊天平台 +4. 修复: Discord 适配器无法优雅重载 +1. 修复: Telegram 适配器无法主动回复 +1. 修复: 仪表盘的『插件配置』中不显示代码编辑器 +3. 新增: Gemini TTS API +1. 新增: 允许 html_render 方法传入 Playwright.screenshot 配置参数 +1. 优化: 修复 CommandFilter 支持对布尔类型进行解析 +4. 新增: WechatPadPro 发送 TTS 时 添加对 MP3 格式音频支持 +1. 重构: 将大模型请求部分抽象成 AgentRunner，提高可读性和可扩展性，工具调用结果支持持久化保存到数据库，完善 Agent 的多轮工具调用能力。 +1. 移除: LLMTuner 模型提供商适配器。请使用 Ollama 来加载微调模型 \ No newline at end of file diff --git a/pyproject.toml b/pyproject.toml index e12abbcdd..558193bf7 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [project] name = "AstrBot" -version = "3.5.17" +version = "3.5.18" description = "易上手的多平台 LLM 聊天机器人及开发框架" readme = "README.md" requires-python = ">=3.10" From 7cfcba29a6b8dac54724debbc6256722d194d2d8 Mon Sep 17 00:00:00 2001 From: Soulter <905617992@qq.com> Date: Sun, 29 Jun 2025 21:55:13 +0800 Subject: [PATCH 17/23] feat: add loading state for dashboard update process --- .../src/layouts/full/vertical-header/VerticalHeader.vue | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) diff --git a/dashboard/src/layouts/full/vertical-header/VerticalHeader.vue b/dashboard/src/layouts/full/vertical-header/VerticalHeader.vue index 22ac90006..1612afcb8 100644 --- a/dashboard/src/layouts/full/vertical-header/VerticalHeader.vue +++ b/dashboard/src/layouts/full/vertical-header/VerticalHeader.vue @@ -29,7 +29,7 @@ let dashboardCurrentVersion = ref(''); let version = ref(''); let releases = ref([]); let devCommits = ref([]); - +let updatingDashboardLoading = ref(false); let installLoading = ref(false); let tab = ref(0); @@ -217,6 +217,7 @@ function switchVersion(version: string) { } function updateDashboard() { + updatingDashboardLoading.value = true; updateStatus.value = t('core.header.updateDialog.status.updating'); axios.post('/api/update/dashboard') .then((res) => { @@ -230,7 +231,9 @@ function updateDashboard() { .catch((err) => { console.log(err); updateStatus.value = err - }); + }).finally(() => { + updatingDashboardLoading.value = false; + }); } function toggleDarkMode() { @@ -416,7 +419,7 @@ commonStore.getStartTime();
+ :disabled="!dashboardHasNewVersion" :loading="updatingDashboardLoading"> {{ t('core.header.updateDialog.dashboardUpdate.downloadAndUpdate') }}
From 39a9d7765ac4fa555aec6af772beca18351f7a92 Mon Sep 17 00:00:00 2001 From: railgun19457 Date: Mon, 30 Jun 2025 00:21:28 +0800 Subject: [PATCH 18/23] =?UTF-8?q?=E4=BF=AE=E6=94=B9=E4=BA=86=E4=B8=80?= =?UTF-8?q?=E5=AF=B9=E5=A4=A7=E6=8B=AC=E5=8F=B7?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- astrbot/core/config/default.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/astrbot/core/config/default.py b/astrbot/core/config/default.py index edf42992f..fc304d587 100644 --- a/astrbot/core/config/default.py +++ b/astrbot/core/config/default.py @@ -13,7 +13,7 @@ DB_PATH = os.path.join(get_astrbot_data_path(), "data_v3.db") DEFAULT_CONFIG = { "config_version": 2, "platform_settings": { - "plugin_enable": [], + "plugin_enable": {}, "unique_session": False, "rate_limit": { "time": 60, From c36142deafc72a673be48cf1a358a022440a173d Mon Sep 17 00:00:00 2001 From: Soulter <905617992@qq.com> Date: Mon, 30 Jun 2025 15:20:29 +0800 Subject: [PATCH 19/23] perf: chatpage UI --- dashboard/src/theme/LightTheme.ts | 2 +- dashboard/src/views/ChatPage.vue | 334 +++++++++++------------------- 2 files changed, 118 insertions(+), 218 deletions(-) diff --git a/dashboard/src/theme/LightTheme.ts b/dashboard/src/theme/LightTheme.ts index a555fddd7..94e011867 100644 --- a/dashboard/src/theme/LightTheme.ts +++ b/dashboard/src/theme/LightTheme.ts @@ -20,7 +20,7 @@ const PurpleTheme: ThemeTypes = { lightsuccess: '#b9f6ca', lighterror: '#f9d8d8', lightwarning: '#fff8e1', - primaryText: '#000000dd', + primaryText: '#1b1c1d', secondaryText: '#000000aa', darkprimary: '#1565c0', darksecondary: '#4527a0', diff --git a/dashboard/src/views/ChatPage.vue b/dashboard/src/views/ChatPage.vue index c47509ab5..2954153ae 100644 --- a/dashboard/src/views/ChatPage.vue +++ b/dashboard/src/views/ChatPage.vue @@ -3,13 +3,16 @@
-
+
AstrBot Logo - AstrBot + AstrBot
- +
{{ tm('actions.newChat') }} + v-if="!sidebarCollapsed" prepend-icon="mdi-plus" + style="background-color: transparent !important; border-radius: 4px;">{{ + tm('actions.newChat') }}
@@ -29,11 +34,12 @@
-
- + + style="background-color: transparent;" @update:selected="getConversationMessages"> {{ item.title @@ -62,42 +68,13 @@
-
-
- {{ tm('conversation.systemStatus') }} -
-
- - - {{ tm('conversation.llmService') }} - - - - - {{ tm('conversation.speechToText') }} - -
- - +
+
+ @click="deleteConversation(currCid)" color="error" density="comfortable" + size="small"> mdi-delete {{ tm('actions.deleteChat') }} @@ -111,14 +88,18 @@
-

{{ getCurrentConversation.title || tm('conversation.newConversation') }}

-
{{ formatDate(getCurrentConversation.updated_at) }}
+

{{ getCurrentConversation.title || + tm('conversation.newConversation') + }}

+
{{ formatDate(getCurrentConversation.updated_at) }} +
@@ -131,7 +112,8 @@ @@ -175,8 +157,9 @@
-
-
+
+
{{ msg.message }} @@ -212,34 +195,21 @@
- - - - - +
+ +
+ + +
+
@@ -260,16 +230,17 @@
+
- + {{ tm('actions.editTitle') }} - + @@ -277,9 +248,9 @@ {{ t('core.common.save') }} - + - + mdi-information-outline {{ tm('connection.title') }} @@ -293,13 +264,8 @@
{{ tm('connection.message') }}
- - + +
{{ tm('connection.reasons') }}
@@ -310,12 +276,7 @@ - +
{{ tm('connection.notice') }}
@@ -324,12 +285,7 @@ - + {{ tm('connection.understand') }} @@ -337,15 +293,10 @@ - + - {{ connectionStatusColor === 'success' ? 'mdi-check-circle' : - connectionStatusColor === 'warning' ? 'mdi-alert-circle' : 'mdi-information' }} + {{ connectionStatusColor === 'success' ? 'mdi-check-circle' : + connectionStatusColor === 'warning' ? 'mdi-alert-circle' : 'mdi-information' }} {{ connectionStatusMessage }} @@ -374,10 +325,10 @@ export default { type: Boolean, default: false } - }, setup() { + }, setup() { const { t } = useI18n(); const { tm } = useModuleI18n('features/chat'); - + return { t, tm, @@ -410,7 +361,7 @@ export default { eventSourceReader: null, sseReconnecting: false, // 添加重连状态标志 - + // // Ctrl键长按相关变量 ctrlKeyDown: false, ctrlKeyTimer: null, @@ -437,7 +388,7 @@ export default { connectionStatusColor: 'info', } }, - + computed: { isDark() { return useCustomizerStore().uiTheme === 'PurpleThemeDark'; @@ -455,13 +406,13 @@ export default { immediate: true, handler(to, from) { console.log('Route changed:', to.path, 'from:', from?.path); // 如果是从不同的路由模式切换（chat <-> chatbox），重新建立SSE连接 - if (from && + if (from && ((from.path.startsWith('/chat') && to.path.startsWith('/chatbox')) || - (from.path.startsWith('/chatbox') && to.path.startsWith('/chat')))) { + (from.path.startsWith('/chatbox') && to.path.startsWith('/chat')))) { console.log('Route mode changed, reconnecting SSE...'); this.reconnectSSE(); } - + // Check if the route matches /chat/ or /chatbox/ pattern if (to.path.startsWith('/chat/') || to.path.startsWith('/chatbox/')) { const pathCid = to.path.split('/')[2]; @@ -481,7 +432,7 @@ export default { } } }, - + // Watch for conversations loaded to handle pending cid conversations: { handler(newConversations) { @@ -527,7 +478,7 @@ export default { beforeUnmount() { this.disconnectSSE(); - + // 移除keyup事件监听 document.removeEventListener('keyup', this.handleInputKeyUp); @@ -538,7 +489,7 @@ export default { // Cleanup blob URLs this.cleanupMediaCache(); - }, + }, methods: { // 显示连接冲突对话框 showConnectionConflictDialog() { @@ -658,7 +609,7 @@ export default { } this.eventSourceReader = null; } - + if (this.eventSource) { try { this.eventSource.cancel(); @@ -676,33 +627,33 @@ export default { console.log('SSE reconnection already in progress'); return; } - + this.sseReconnecting = true; console.log('Reconnecting SSE...'); this.disconnectSSE(); - + // 等待更长时间确保后端连接完全清理 await new Promise(resolve => setTimeout(resolve, 1000)); - + this.startListeningEvent(); }, async startListeningEvent() { // 确保之前的连接已断开 this.disconnectSSE(); - + // 如果正在重连过程中，等待一下 if (this.sseReconnecting) { await new Promise(resolve => setTimeout(resolve, 500)); } - + let retryCount = 0; const maxRetries = 3; - + while (retryCount < maxRetries) { try { console.log(`尝试建立SSE连接 (${retryCount + 1}/${maxRetries})`); - + const response = await fetch('/api/chat/listen', { method: 'GET', headers: { @@ -716,13 +667,13 @@ export default { } const reader = response.body.getReader(); - const decoder = new TextDecoder(); + const decoder = new TextDecoder(); this.eventSource = reader; this.eventSourceReader = reader; this.sseReconnecting = false; let in_streaming = false; - let message_obj = null; + let message_obj = null; console.log('SSE连接已建立'); // 显示连接成功状态 if (retryCount > 0) { @@ -856,28 +807,28 @@ export default { break; } } - + // 如果成功连接并正常结束，跳出重试循环 break; - + } catch (error) { console.error(`SSE连接错误 (尝试 ${retryCount + 1}):`, error); - - retryCount++; + + retryCount++; if (error.message === 'CONNECTION_CONFLICT' && retryCount < maxRetries) { console.log(`连接冲突，等待 ${2000 * retryCount}ms 后重试...`); this.showConnectionStatus(`${this.tm('connection.status.reconnecting')} (${retryCount}/${maxRetries})`, 'warning'); await new Promise(resolve => setTimeout(resolve, 2000 * retryCount)); continue; } - + if (retryCount >= maxRetries) { console.error('SSE连接重试次数已达上限'); this.showConnectionStatus(this.tm('connection.status.failed'), 'error'); this.sseReconnecting = false; break; } - + // 等待一段时间后重试 await new Promise(resolve => setTimeout(resolve, 1000 * retryCount)); } finally { @@ -885,7 +836,7 @@ export default { this.eventSourceReader = null; } } - + this.sseReconnecting = false; }, @@ -981,7 +932,7 @@ export default { getConversations() { axios.get('/api/chat/conversations').then(response => { this.conversations = response.data.data; - + // If there's a pending conversation ID from the route if (this.pendingCid) { const conversation = this.conversations.find(c => c.cid === this.pendingCid); @@ -1000,7 +951,7 @@ export default { getConversationMessages(cid) { if (!cid[0]) return; - + // Update the URL to reflect the selected conversation if (this.$route.path !== `/chat/${cid[0]}` && this.$route.path !== `/chatbox/${cid[0]}`) { if (this.$route.path.startsWith('/chatbox')) { @@ -1010,7 +961,7 @@ export default { } } - + axios.get('/api/chat/get_conversation?conversation_id=' + cid[0]).then(async response => { this.currCid = cid[0]; let message = JSON.parse(response.data.data.history); @@ -1098,9 +1049,9 @@ export default { // 检查是否可以发送消息 canSendMessage() { - return (this.prompt && this.prompt.trim()) || - this.stagedImagesName.length > 0 || - this.stagedAudioUrl; + return (this.prompt && this.prompt.trim()) || + this.stagedImagesName.length > 0 || + this.stagedAudioUrl; }, async sendMessage() { @@ -1180,11 +1131,11 @@ export default { const container = this.$refs.messageContainer; container.scrollTop = container.scrollHeight; }); - }, + }, handleInputKeyDown(e) { if (e.ctrlKey && e.keyCode === 66) { // Ctrl+B组合键 e.preventDefault(); // 防止默认行为 - + // 防止重复触发 if (this.ctrlKeyDown) return; @@ -1197,7 +1148,7 @@ export default { } }, this.ctrlKeyLongPressThreshold); } - }, + }, handleInputKeyUp(e) { if (e.keyCode === 66) { // B键释放 this.ctrlKeyDown = false; @@ -1305,26 +1256,27 @@ export default { opacity: 0; } - -/* 聊天页面布局 */ .chat-page-card { - margin-bottom: 16px; width: 100%; - height: 100%; - border-radius: 16px; + height: calc(100vh - 84px); + max-height: 100%; box-shadow: 0 4px 12px rgba(0, 0, 0, 0.05) !important; + overflow: hidden; } .chat-page-container { width: 100%; height: 100%; - max-height: calc(100vh - 120px); + max-height: 100%; padding: 0; + overflow: hidden; } .chat-layout { height: 100%; + max-height: 100%; display: flex; + overflow: hidden; } .sidebar-panel { @@ -1334,29 +1286,11 @@ export default { flex-direction: column; padding: 0; border-right: 1px solid rgba(0, 0, 0, 0.05); - background-color: var(--v-theme-containerBg); height: 100%; + max-height: 100%; position: relative; transition: all 0.3s ease; overflow: hidden; - /* 防止内容溢出 */ -} - -.sidebar-panel ::-webkit-scrollbar { - width: 6px; -} - -.sidebar-panel ::-webkit-scrollbar-track { - background: transparent; -} - -.sidebar-panel ::-webkit-scrollbar-thumb { - background-color: rgba(0, 0, 0, 0.2); - border-radius: 3px; -} - -.sidebar-panel ::-webkit-scrollbar-thumb:hover { - background-color: rgba(0, 0, 0, 0.3); } /* 侧边栏折叠状态 */ @@ -1439,7 +1373,7 @@ export default { .status-chips .v-chip { flex: 1 1 0; justify-content: center; - opacity: 0.7; /* Make border and text slightly transparent */ + opacity: 0.7; } .status-chip { @@ -1467,7 +1401,8 @@ export default { } .delete-btn-container { - /* margin-top: -8px; */ /* Removed for better layout practices */ + /* margin-top: -8px; */ + /* Removed for better layout practices */ } .expand-enter-active, @@ -1492,20 +1427,24 @@ export default { transition: opacity 0.25s ease; } -/* 聊天内容区域 */ .chat-content-panel { height: 100%; + max-height: 100%; width: 100%; display: flex; flex-direction: column; + overflow: hidden; } .messages-container { - height: calc(100% - 80px); + height: 100%; + max-height: 100%; overflow-y: auto; padding: 16px; display: flex; flex-direction: column; + flex: 1; + min-height: 0; } /* 欢迎页样式 */ @@ -1577,8 +1516,9 @@ export default { } .user-bubble { - background-color: var(--v-theme-chatMessageBubble); color: var(--v-theme-primaryText); + padding: 12px 16px; + font-size: 16px; } .bot-bubble { @@ -1633,17 +1573,8 @@ export default { background-color: var(--v-theme-surface); position: relative; border-top: 1px solid var(--v-theme-border); -} - -.message-input { - border-radius: 24px; - max-width: 900px; - margin: 0 auto; -} - -.send-btn, -.record-btn { - margin-left: 4px; + flex-shrink: 0; + /* 防止输入区域被压缩 */ } /* 附件预览区 */ @@ -1797,38 +1728,7 @@ export default { border-bottom: 1px solid var(--v-theme-border); width: 100%; padding-right: 32px; -} - -.conversation-header-content { - display: flex; - flex-direction: column; -} - -.conversation-header-title { - font-size: 18px; - font-weight: 600; - margin: 0; - color: var(--v-theme-primaryText); -} - -.conversation-header-time { - font-size: 12px; - color: var(--v-theme-secondaryText); - margin-top: 4px; -} - -.conversation-header-actions { - display: flex; - align-items: center; -} - -.fullscreen-icon { - opacity: 0.7; - transition: opacity 0.2s; - cursor: pointer; -} - -.fullscreen-icon:hover { - opacity: 1; + flex-shrink: 0; + /* 防止header被压缩 */ } \ No newline at end of file From 7acb45b157a0dc1a83425648c53308912272d361 Mon Sep 17 00:00:00 2001 From: Soulter <37870767+Soulter@users.noreply.github.com> Date: Tue, 1 Jul 2025 11:35:14 +0800 Subject: [PATCH 20/23] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index ca7a45eb3..5b904a178 100644 --- a/README.md +++ b/README.md @@ -16,7 +16,7 @@ _✨ 易上手的多平台 LLM 聊天机器人及开发框架 ✨_ QQ_community Telegram_community [![wakatime](https://wakatime.com/badge/user/915e5316-99c6-4563-a483-ef186cf000c9/project/018e705a-a1a7-409a-a849-3013485e6c8e.svg?style=for-the-badge&color=76bad9)](https://wakatime.com/badge/user/915e5316-99c6-4563-a483-ef186cf000c9/project/018e705a-a1a7-409a-a849-3013485e6c8e) -![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fstats&query=v&label=7%E6%97%A5%E6%B4%BB%E8%B7%83%E9%87%8F&cacheSeconds=3600&style=for-the-badge&color=3b618e) +![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fstats&query=v&label=7日消息量&cacheSeconds=3600&style=for-the-badge&color=3b618e) ![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fplugin-num&query=%24.result&suffix=%E4%B8%AA&style=for-the-badge&label=%E6%8F%92%E4%BB%B6%E5%B8%82%E5%9C%BA&cacheSeconds=3600) English ｜ From 68e8e1f70b79371f3efd0a34b6f4bbdce5405318 Mon Sep 17 00:00:00 2001 From: Raven95676 Date: Tue, 1 Jul 2025 12:40:52 +0800 Subject: [PATCH 21/23] =?UTF-8?q?feat:=20=E9=9B=86=E6=88=90r1=5Ffilter?= =?UTF-8?q?=E8=87=B3=E6=A1=86=E6=9E=B6?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- astrbot/core/config/default.py | 6 +++ packages/thinking_filter/main.py | 70 ++++++++++++++++++++++++++++++++ 2 files changed, 76 insertions(+) create mode 100644 packages/thinking_filter/main.py diff --git a/astrbot/core/config/default.py b/astrbot/core/config/default.py index fc304d587..4a75a11bc 100644 --- a/astrbot/core/config/default.py +++ b/astrbot/core/config/default.py @@ -54,6 +54,7 @@ DEFAULT_CONFIG = { "wake_prefix": "", "web_search": False, "web_search_link": False, + "display_reasoning_text": False, "identifier": False, "datetime_system_prompt": True, "default_personality": "default", @@ -1652,6 +1653,11 @@ CONFIG_METADATA_2 = { "obvious_hint": True, "hint": "开启后，将会传入网页搜索结果的链接给模型，并引导模型输出引用链接。", }, + "display_reasoning_text": { + "description": "显示思考内容", + "type": "bool", + "hint": "开启后，将在回复中显示模型的思考过程。", + }, "identifier": { "description": "启动识别群员", "type": "bool", diff --git a/packages/thinking_filter/main.py b/packages/thinking_filter/main.py new file mode 100644 index 000000000..eb36a107f --- /dev/null +++ b/packages/thinking_filter/main.py @@ -0,0 +1,70 @@ +import re +from astrbot.api.event import filter, AstrMessageEvent +from astrbot.api.star import Context, Star, register +from astrbot.api.provider import LLMResponse +from openai.types.chat.chat_completion import ChatCompletion + + +@register( + "thinking_filter", + "Soulter", + "可选择是否过滤推理模型的思考内容", + "1.0.0", + "https://astrbot.app", +) +class R1Filter(Star): + def __init__(self, context: Context): + super().__init__(context) + self.display_reasoning_text = ( + self.context.get_config() + .get("provider_settings", {}) + .get("display_reasoning_text", False) + ) + + @filter.on_llm_response() + async def resp(self, event: AstrMessageEvent, response: LLMResponse): + if self.display_reasoning_text: + if ( + response + and response.raw_completion + and isinstance(response.raw_completion, ChatCompletion) + ): + if ( + len(response.raw_completion.choices) + and response.raw_completion.choices[0].message + ): + message = response.raw_completion.choices[0].message + reasoning_content = "" # 初始化 reasoning_content + + # 检查 Groq deepseek-r1-distill-llama-70b模型的 'reasoning' 属性 + if hasattr(message, "reasoning") and message.reasoning: + reasoning_content = message.reasoning + # 检查 DeepSeek deepseek-reasoner模型的 'reasoning_content' + elif ( + hasattr(message, "reasoning_content") + and message.reasoning_content + ): + reasoning_content = message.reasoning_content + + if reasoning_content: + response.completion_text = ( + f"🤔思考：{reasoning_content}\n\n{message.content}" + ) + else: + response.completion_text = message.content + + else: + # DeepSeek 官方的模型的思考存在了 reason_content 字段因此不需要过滤 + completion_text = response.completion_text + # 适配 ollama deepseek-r1 模型 + if r"" in completion_text or r"" in completion_text: + completion_text = re.sub( + r".*?", "", completion_text, flags=re.DOTALL + ).strip() + # 可能有单标签情况 + completion_text = ( + completion_text.replace(r"", "") + .replace(r"", "") + .strip() + ) + response.completion_text = completion_text From d03d0354370c6a241af16a6d7da0f2a68256286a Mon Sep 17 00:00:00 2001 From: Raven95676 Date: Tue, 1 Jul 2025 13:53:22 +0800 Subject: [PATCH 22/23] =?UTF-8?q?perf:=20=E5=90=88=E5=B9=B6=E5=B5=8C?= =?UTF-8?q?=E5=A5=97=E7=9A=84if=E6=9D=A1=E4=BB=B6?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- packages/thinking_filter/main.py | 51 ++++++++++++++++---------------- 1 file changed, 26 insertions(+), 25 deletions(-) diff --git a/packages/thinking_filter/main.py b/packages/thinking_filter/main.py index eb36a107f..26c2db9b9 100644 --- a/packages/thinking_filter/main.py +++ b/packages/thinking_filter/main.py @@ -24,47 +24,48 @@ class R1Filter(Star): @filter.on_llm_response() async def resp(self, event: AstrMessageEvent, response: LLMResponse): if self.display_reasoning_text: + # 显示推理内容的处理逻辑 if ( response and response.raw_completion and isinstance(response.raw_completion, ChatCompletion) + and len(response.raw_completion.choices) > 0 + and response.raw_completion.choices[0].message ): - if ( - len(response.raw_completion.choices) - and response.raw_completion.choices[0].message + message = response.raw_completion.choices[0].message + reasoning_content = "" # 初始化 reasoning_content + + # 检查 Groq deepseek-r1-distill-llama-70b 模型的 'reasoning' 属性 + if hasattr(message, "reasoning") and message.reasoning: + reasoning_content = message.reasoning + # 检查 DeepSeek deepseek-reasoner 模型的 'reasoning_content' + elif ( + hasattr(message, "reasoning_content") and message.reasoning_content ): - message = response.raw_completion.choices[0].message - reasoning_content = "" # 初始化 reasoning_content - - # 检查 Groq deepseek-r1-distill-llama-70b模型的 'reasoning' 属性 - if hasattr(message, "reasoning") and message.reasoning: - reasoning_content = message.reasoning - # 检查 DeepSeek deepseek-reasoner模型的 'reasoning_content' - elif ( - hasattr(message, "reasoning_content") - and message.reasoning_content - ): - reasoning_content = message.reasoning_content - - if reasoning_content: - response.completion_text = ( - f"🤔思考：{reasoning_content}\n\n{message.content}" - ) - else: - response.completion_text = message.content + reasoning_content = message.reasoning_content + if reasoning_content: + response.completion_text = ( + f"🤔思考：{reasoning_content}\n\n{message.content}" + ) + else: + response.completion_text = message.content else: - # DeepSeek 官方的模型的思考存在了 reason_content 字段因此不需要过滤 + # 过滤推理标签的处理逻辑 completion_text = response.completion_text - # 适配 ollama deepseek-r1 模型 + + # 检查并移除 标签 if r"" in completion_text or r"" in completion_text: + # 移除配对的标签及其内容 completion_text = re.sub( r".*?", "", completion_text, flags=re.DOTALL ).strip() - # 可能有单标签情况 + + # 移除可能残留的单个标签 completion_text = ( completion_text.replace(r"", "") .replace(r"", "") .strip() ) + response.completion_text = completion_text From 30e8ea7fd807090f7a4c1731940549e224bcd471 Mon Sep 17 00:00:00 2001 From: Soulter <37870767+Soulter@users.noreply.github.com> Date: Tue, 1 Jul 2025 16:59:58 +0800 Subject: [PATCH 23/23] chore: add deploy badge --- README.md | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 5b904a178..40a3e95f1 100644 --- a/README.md +++ b/README.md @@ -111,10 +111,14 @@ uvx astrbot init 或者请参阅官方文档 [通过源码部署 AstrBot](https://astrbot.app/deploy/astrbot/cli.html) 。 -#### Replit 部署 +#### 在 Replit 上部署 [![Run on Repl.it](https://repl.it/badge/github/Soulter/AstrBot)](https://repl.it/github/Soulter/AstrBot) +#### 在 雨云 上部署 + +[![Deploy on RainYun](https://rainyun-apps.cn-nb1.rains3.com/materials/deploy-on-rainyun-en.svg)](https://app.rainyun.com/apps/rca/store/5994?ref=NjU1ODg0) + ## ⚡ 消息平台支持情况 | 平台 | 支持性 |