From 6849af2bad40662b6bc290c363e971aa190a50fb Mon Sep 17 00:00:00 2001 From: Soulter <37870767+Soulter@users.noreply.github.com> Date: Sat, 15 Nov 2025 18:59:17 +0800 Subject: [PATCH] refactor: LLM response handling with reasoning content (#3632) * refactor: LLM response handling with reasoning content - Added a `show_reasoning` parameter to `run_agent` to control the display of reasoning content. - Updated `LLMResponse` to include a `reasoning_content` field for storing reasoning text. - Modified `WebChatMessageEvent` to handle and send reasoning content in streaming responses. - Implemented reasoning extraction in various provider sources (e.g., OpenAI, Gemini). - Updated the chat interface to display reasoning content in a collapsible format. - Removed the deprecated `thinking_filter` package and its associated logic. - Updated localization files to include new reasoning-related strings. * feat: add Groq chat completion provider and associated configurations * Update astrbot/core/provider/sources/gemini_source.py Co-authored-by: sourcery-ai[bot] <58596630+sourcery-ai[bot]@users.noreply.github.com> --------- Co-authored-by: sourcery-ai[bot] <58596630+sourcery-ai[bot]@users.noreply.github.com> --- astrbot/api/all.py | 3 +- astrbot/api/provider/__init__.py | 3 +- .../agent/runners/tool_loop_agent_runner.py | 16 +- astrbot/core/config/default.py | 17 ++ .../process_stage/method/llm_request.py | 25 ++- .../platform/sources/webchat/webchat_event.py | 9 +- astrbot/core/provider/__init__.py | 4 +- astrbot/core/provider/entities.py | 19 +- astrbot/core/provider/manager.py | 3 +- astrbot/core/provider/provider.py | 6 - .../core/provider/sources/anthropic_source.py | 2 - astrbot/core/provider/sources/coze_source.py | 2 - .../core/provider/sources/dashscope_source.py | 4 +- astrbot/core/provider/sources/dify_source.py | 2 - .../core/provider/sources/gemini_source.py | 34 ++- astrbot/core/provider/sources/groq_source.py | 15 ++ .../core/provider/sources/openai_source.py | 78 +++++-- astrbot/core/provider/sources/zhipu_source.py | 7 +- astrbot/dashboard/routes/chat.py | 2 + dashboard/src/components/chat/Chat.vue | 28 +-- dashboard/src/components/chat/MessageList.vue | 97 +++++++- .../src/i18n/locales/en-US/features/chat.json | 3 + .../src/i18n/locales/zh-CN/features/chat.json | 3 + dashboard/src/utils/providerUtils.js | 1 + packages/astrbot/main.py | 13 +- packages/thinking_filter/main.py | 208 ------------------ packages/thinking_filter/metadata.yaml | 5 - 27 files changed, 308 insertions(+), 301 deletions(-) create mode 100644 astrbot/core/provider/sources/groq_source.py delete mode 100644 packages/thinking_filter/main.py delete mode 100644 packages/thinking_filter/metadata.yaml diff --git a/astrbot/api/all.py b/astrbot/api/all.py index 2463dbc2b..df3e1170f 100644 --- a/astrbot/api/all.py +++ b/astrbot/api/all.py @@ -36,7 +36,8 @@ from astrbot.core.star.config import * # provider -from astrbot.core.provider import Provider, Personality, ProviderMetaData +from astrbot.core.provider import Provider, ProviderMetaData +from astrbot.core.db.po import Personality # platform from astrbot.core.platform import ( diff --git a/astrbot/api/provider/__init__.py b/astrbot/api/provider/__init__.py index 2008c7bcf..f62b340f8 100644 --- a/astrbot/api/provider/__init__.py +++ b/astrbot/api/provider/__init__.py @@ -1,4 +1,5 @@ -from astrbot.core.provider import Personality, Provider, STTProvider +from astrbot.core.db.po import Personality +from astrbot.core.provider import Provider, STTProvider from astrbot.core.provider.entities import ( LLMResponse, ProviderMetaData, diff --git a/astrbot/core/agent/runners/tool_loop_agent_runner.py b/astrbot/core/agent/runners/tool_loop_agent_runner.py index 23071d446..de27ed1ac 100644 --- a/astrbot/core/agent/runners/tool_loop_agent_runner.py +++ b/astrbot/core/agent/runners/tool_loop_agent_runner.py @@ -96,13 +96,22 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]): type="streaming_delta", data=AgentResponseData(chain=llm_response.result_chain), ) - else: + elif llm_response.completion_text: yield AgentResponse( type="streaming_delta", data=AgentResponseData( chain=MessageChain().message(llm_response.completion_text), ), ) + elif llm_response.reasoning_content: + yield AgentResponse( + type="streaming_delta", + data=AgentResponseData( + chain=MessageChain(type="reasoning").message( + llm_response.reasoning_content, + ), + ), + ) continue llm_resp_result = llm_response break # got final response @@ -156,13 +165,16 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]): yield AgentResponse( type="tool_call", data=AgentResponseData( - chain=MessageChain().message(f"🔨 调用工具: {tool_call_name}"), + chain=MessageChain(type="tool_call").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 elif isinstance(result, MessageChain): + result.type = "tool_call_result" yield AgentResponse( type="tool_call_result", data=AgentResponseData(chain=result), diff --git a/astrbot/core/config/default.py b/astrbot/core/config/default.py index 7cd024e70..e9b5613f4 100644 --- a/astrbot/core/config/default.py +++ b/astrbot/core/config/default.py @@ -880,6 +880,23 @@ CONFIG_METADATA_2 = { "custom_extra_body": {}, "modalities": ["text", "tool_use"], }, + "Groq": { + "id": "groq_default", + "provider": "groq", + "type": "groq_chat_completion", + "provider_type": "chat_completion", + "enable": True, + "key": [], + "api_base": "https://api.groq.com/openai/v1", + "timeout": 120, + "model_config": { + "model": "openai/gpt-oss-20b", + "temperature": 0.4, + }, + "custom_headers": {}, + "custom_extra_body": {}, + "modalities": ["text", "tool_use"], + }, "302.AI": { "id": "302ai", "provider": "302ai", diff --git a/astrbot/core/pipeline/process_stage/method/llm_request.py b/astrbot/core/pipeline/process_stage/method/llm_request.py index 69bf31a55..424e845dd 100644 --- a/astrbot/core/pipeline/process_stage/method/llm_request.py +++ b/astrbot/core/pipeline/process_stage/method/llm_request.py @@ -295,7 +295,8 @@ async def run_agent( max_step: int = 30, show_tool_use: bool = True, stream_to_general: bool = False, -) -> AsyncGenerator[MessageChain, None]: + show_reasoning: bool = False, +) -> AsyncGenerator[MessageChain | None, None]: step_idx = 0 astr_event = agent_runner.run_context.context.event while step_idx < max_step: @@ -308,7 +309,6 @@ async def run_agent( msg_chain = resp.data["chain"] if msg_chain.type == "tool_direct_result": # tool_direct_result 用于标记 llm tool 需要直接发送给用户的内容 - resp.data["chain"].type = "tool_call_result" await astr_event.send(resp.data["chain"]) continue # 对于其他情况，暂时先不处理 @@ -317,8 +317,7 @@ async def run_agent( if agent_runner.streaming: # 用来标记流式响应需要分节 yield MessageChain(chain=[], type="break") - if show_tool_use or astr_event.get_platform_name() == "webchat": - resp.data["chain"].type = "tool_call" + if show_tool_use: await astr_event.send(resp.data["chain"]) continue @@ -340,6 +339,10 @@ async def run_agent( yield astr_event.clear_result() elif resp.type == "streaming_delta": + chain = resp.data["chain"] + if chain.type == "reasoning" and not show_reasoning: + # display the reasoning content only when configured + continue yield resp.data["chain"] # MessageChain if agent_runner.done(): break @@ -375,6 +378,7 @@ class LLMRequestSubStage(Stage): if isinstance(self.max_step, bool): # workaround: #2622 self.max_step = 30 self.show_tool_use: bool = settings.get("show_tool_use_status", True) + self.show_reasoning = settings.get("display_reasoning_text", False) for bwp in self.bot_wake_prefixs: if self.provider_wake_prefix.startswith(bwp): @@ -733,7 +737,12 @@ class LLMRequestSubStage(Stage): MessageEventResult() .set_result_content_type(ResultContentType.STREAMING_RESULT) .set_async_stream( - run_agent(agent_runner, self.max_step, self.show_tool_use), + run_agent( + agent_runner, + self.max_step, + self.show_tool_use, + show_reasoning=self.show_reasoning, + ), ), ) yield @@ -757,7 +766,11 @@ class LLMRequestSubStage(Stage): ) else: async for _ in run_agent( - agent_runner, self.max_step, self.show_tool_use, stream_to_general + agent_runner, + self.max_step, + self.show_tool_use, + stream_to_general, + show_reasoning=self.show_reasoning, ): yield diff --git a/astrbot/core/platform/sources/webchat/webchat_event.py b/astrbot/core/platform/sources/webchat/webchat_event.py index 4d4d3b59e..4ced79b19 100644 --- a/astrbot/core/platform/sources/webchat/webchat_event.py +++ b/astrbot/core/platform/sources/webchat/webchat_event.py @@ -109,6 +109,7 @@ class WebChatMessageEvent(AstrMessageEvent): async def send_streaming(self, generator, use_fallback: bool = False): final_data = "" + reasoning_content = "" cid = self.session_id.split("!")[-1] web_chat_back_queue = webchat_queue_mgr.get_or_create_back_queue(cid) async for chain in generator: @@ -124,16 +125,22 @@ class WebChatMessageEvent(AstrMessageEvent): ) final_data = "" continue - final_data += await WebChatMessageEvent._send( + + r = await WebChatMessageEvent._send( chain, session_id=self.session_id, streaming=True, ) + if chain.type == "reasoning": + reasoning_content += chain.get_plain_text() + else: + final_data += r await web_chat_back_queue.put( { "type": "complete", # complete means we return the final result "data": final_data, + "reasoning": reasoning_content, "streaming": True, "cid": cid, }, diff --git a/astrbot/core/provider/__init__.py b/astrbot/core/provider/__init__.py index abbe08234..812e02171 100644 --- a/astrbot/core/provider/__init__.py +++ b/astrbot/core/provider/__init__.py @@ -1,4 +1,4 @@ from .entities import ProviderMetaData -from .provider import Personality, Provider, STTProvider +from .provider import Provider, STTProvider -__all__ = ["Personality", "Provider", "ProviderMetaData", "STTProvider"] +__all__ = ["Provider", "ProviderMetaData", "STTProvider"] diff --git a/astrbot/core/provider/entities.py b/astrbot/core/provider/entities.py index 2ddbfc3ac..beab707bc 100644 --- a/astrbot/core/provider/entities.py +++ b/astrbot/core/provider/entities.py @@ -194,25 +194,28 @@ class ProviderRequest: @dataclass class LLMResponse: role: str - """角色, assistant, tool, err""" + """The role of the message, e.g., assistant, tool, err""" result_chain: MessageChain | None = None - """返回的消息链""" + """A chain of message components representing the text completion from LLM.""" tools_call_args: list[dict[str, Any]] = field(default_factory=list) - """工具调用参数""" + """Tool call arguments.""" tools_call_name: list[str] = field(default_factory=list) - """工具调用名称""" + """Tool call names.""" tools_call_ids: list[str] = field(default_factory=list) - """工具调用 ID""" + """Tool call IDs.""" + reasoning_content: str = "" + """The reasoning content extracted from the LLM, if any.""" raw_completion: ( ChatCompletion | GenerateContentResponse | AnthropicMessage | None ) = None - _new_record: dict[str, Any] | None = None + """The raw completion response from the LLM provider.""" _completion_text: str = "" + """The plain text of the completion.""" is_chunk: bool = False - """是否是流式输出的单个 Chunk""" + """Indicates if the response is a chunked response.""" def __init__( self, @@ -226,7 +229,6 @@ class LLMResponse: | GenerateContentResponse | AnthropicMessage | None = None, - _new_record: dict[str, Any] | None = None, is_chunk: bool = False, ): """初始化 LLMResponse @@ -254,7 +256,6 @@ class LLMResponse: self.tools_call_name = tools_call_name self.tools_call_ids = tools_call_ids self.raw_completion = raw_completion - self._new_record = _new_record self.is_chunk = is_chunk @property diff --git a/astrbot/core/provider/manager.py b/astrbot/core/provider/manager.py index 0984138ae..320c98d4e 100644 --- a/astrbot/core/provider/manager.py +++ b/astrbot/core/provider/manager.py @@ -241,6 +241,8 @@ class ProviderManager: ) case "zhipu_chat_completion": from .sources.zhipu_source import ProviderZhipu as ProviderZhipu + case "groq_chat_completion": + from .sources.groq_source import ProviderGroq as ProviderGroq case "anthropic_chat_completion": from .sources.anthropic_source import ( ProviderAnthropic as ProviderAnthropic, @@ -396,7 +398,6 @@ class ProviderManager: inst = cls_type( provider_config, self.provider_settings, - self.selected_default_persona, ) if getattr(inst, "initialize", None): diff --git a/astrbot/core/provider/provider.py b/astrbot/core/provider/provider.py index 00ac0f14c..3ae5f2bd9 100644 --- a/astrbot/core/provider/provider.py +++ b/astrbot/core/provider/provider.py @@ -4,7 +4,6 @@ from collections.abc import AsyncGenerator from astrbot.core.agent.message import Message from astrbot.core.agent.tool import ToolSet -from astrbot.core.db.po import Personality from astrbot.core.provider.entities import ( LLMResponse, ProviderMeta, @@ -52,15 +51,10 @@ class Provider(AbstractProvider): self, provider_config: dict, provider_settings: dict, - default_persona: Personality | None = None, ) -> None: super().__init__(provider_config) - self.provider_settings = provider_settings - self.curr_personality = default_persona - """维护了当前的使用的 persona，即人格。可能为 None""" - @abc.abstractmethod def get_current_key(self) -> str: raise NotImplementedError diff --git a/astrbot/core/provider/sources/anthropic_source.py b/astrbot/core/provider/sources/anthropic_source.py index 77c85cef4..f05d205c7 100644 --- a/astrbot/core/provider/sources/anthropic_source.py +++ b/astrbot/core/provider/sources/anthropic_source.py @@ -25,12 +25,10 @@ class ProviderAnthropic(Provider): self, provider_config, provider_settings, - default_persona=None, ) -> None: super().__init__( provider_config, provider_settings, - default_persona, ) self.chosen_api_key: str = "" diff --git a/astrbot/core/provider/sources/coze_source.py b/astrbot/core/provider/sources/coze_source.py index 23a8b3b76..6f1355bf7 100644 --- a/astrbot/core/provider/sources/coze_source.py +++ b/astrbot/core/provider/sources/coze_source.py @@ -20,12 +20,10 @@ class ProviderCoze(Provider): self, provider_config, provider_settings, - default_persona=None, ) -> None: super().__init__( provider_config, provider_settings, - default_persona, ) self.api_key = provider_config.get("coze_api_key", "") if not self.api_key: diff --git a/astrbot/core/provider/sources/dashscope_source.py b/astrbot/core/provider/sources/dashscope_source.py index 9b262c001..7c690e048 100644 --- a/astrbot/core/provider/sources/dashscope_source.py +++ b/astrbot/core/provider/sources/dashscope_source.py @@ -8,7 +8,7 @@ from dashscope.app.application_response import ApplicationResponse from astrbot.core import logger, sp from astrbot.core.message.message_event_result import MessageChain -from .. import Personality, Provider +from .. import Provider from ..entities import LLMResponse from ..register import register_provider_adapter from .openai_source import ProviderOpenAIOfficial @@ -20,13 +20,11 @@ class ProviderDashscope(ProviderOpenAIOfficial): self, provider_config: dict, provider_settings: dict, - default_persona: Personality | None = None, ) -> None: Provider.__init__( self, provider_config, provider_settings, - default_persona, ) self.api_key = provider_config.get("dashscope_api_key", "") if not self.api_key: diff --git a/astrbot/core/provider/sources/dify_source.py b/astrbot/core/provider/sources/dify_source.py index 9f9f146aa..7850a982c 100644 --- a/astrbot/core/provider/sources/dify_source.py +++ b/astrbot/core/provider/sources/dify_source.py @@ -18,12 +18,10 @@ class ProviderDify(Provider): self, provider_config, provider_settings, - default_persona=None, ) -> None: super().__init__( provider_config, provider_settings, - default_persona, ) self.api_key = provider_config.get("dify_api_key", "") if not self.api_key: diff --git a/astrbot/core/provider/sources/gemini_source.py b/astrbot/core/provider/sources/gemini_source.py index c3c9253a5..b9159eec9 100644 --- a/astrbot/core/provider/sources/gemini_source.py +++ b/astrbot/core/provider/sources/gemini_source.py @@ -53,12 +53,10 @@ class ProviderGoogleGenAI(Provider): self, provider_config, provider_settings, - default_persona=None, ) -> None: super().__init__( provider_config, provider_settings, - default_persona, ) self.api_keys: list = super().get_keys() self.chosen_api_key: str = self.api_keys[0] if len(self.api_keys) > 0 else "" @@ -326,8 +324,18 @@ class ProviderGoogleGenAI(Provider): return gemini_contents - @staticmethod + def _extract_reasoning_content(self, candidate: types.Candidate) -> str: + """Extract reasoning content from candidate parts""" + if not candidate.content or not candidate.content.parts: + return "" + + thought_buf: list[str] = [ + (p.text or "") for p in candidate.content.parts if p.thought + ] + return "".join(thought_buf).strip() + def _process_content_parts( + self, candidate: types.Candidate, llm_response: LLMResponse, ) -> MessageChain: @@ -358,6 +366,11 @@ class ProviderGoogleGenAI(Provider): logger.warning(f"收到的 candidate.content.parts 为空: {candidate}") raise Exception("API 返回的 candidate.content.parts 为空。") + # 提取 reasoning content + reasoning = self._extract_reasoning_content(candidate) + if reasoning: + llm_response.reasoning_content = reasoning + chain = [] part: types.Part @@ -515,6 +528,7 @@ class ProviderGoogleGenAI(Provider): # Accumulate the complete response text for the final response accumulated_text = "" + accumulated_reasoning = "" final_response = None async for chunk in result: @@ -539,9 +553,19 @@ class ProviderGoogleGenAI(Provider): yield llm_response return + _f = False + + # 提取 reasoning content + reasoning = self._extract_reasoning_content(chunk.candidates[0]) + if reasoning: + _f = True + accumulated_reasoning += reasoning + llm_response.reasoning_content = reasoning if chunk.text: + _f = True accumulated_text += chunk.text llm_response.result_chain = MessageChain(chain=[Comp.Plain(chunk.text)]) + if _f: yield llm_response if chunk.candidates[0].finish_reason: @@ -559,6 +583,10 @@ class ProviderGoogleGenAI(Provider): if not final_response: final_response = LLMResponse("assistant", is_chunk=False) + # Set the complete accumulated reasoning in the final response + if accumulated_reasoning: + final_response.reasoning_content = accumulated_reasoning + # Set the complete accumulated text in the final response if accumulated_text: final_response.result_chain = MessageChain( diff --git a/astrbot/core/provider/sources/groq_source.py b/astrbot/core/provider/sources/groq_source.py new file mode 100644 index 000000000..fcc8f238f --- /dev/null +++ b/astrbot/core/provider/sources/groq_source.py @@ -0,0 +1,15 @@ +from ..register import register_provider_adapter +from .openai_source import ProviderOpenAIOfficial + + +@register_provider_adapter( + "groq_chat_completion", "Groq Chat Completion Provider Adapter" +) +class ProviderGroq(ProviderOpenAIOfficial): + def __init__( + self, + provider_config: dict, + provider_settings: dict, + ) -> None: + super().__init__(provider_config, provider_settings) + self.reasoning_key = "reasoning" diff --git a/astrbot/core/provider/sources/openai_source.py b/astrbot/core/provider/sources/openai_source.py index 823287b6f..87e2eeaab 100644 --- a/astrbot/core/provider/sources/openai_source.py +++ b/astrbot/core/provider/sources/openai_source.py @@ -4,12 +4,14 @@ import inspect import json import os import random +import re from collections.abc import AsyncGenerator from openai import AsyncAzureOpenAI, AsyncOpenAI from openai._exceptions import NotFoundError, UnprocessableEntityError from openai.lib.streaming.chat._completions import ChatCompletionStreamState from openai.types.chat.chat_completion import ChatCompletion +from openai.types.chat.chat_completion_chunk import ChatCompletionChunk import astrbot.core.message.components as Comp from astrbot import logger @@ -28,17 +30,8 @@ from ..register import register_provider_adapter "OpenAI API Chat Completion 提供商适配器", ) class ProviderOpenAIOfficial(Provider): - def __init__( - self, - provider_config, - provider_settings, - default_persona=None, - ) -> None: - super().__init__( - provider_config, - provider_settings, - default_persona, - ) + def __init__(self, provider_config, provider_settings) -> None: + super().__init__(provider_config, provider_settings) self.chosen_api_key = None self.api_keys: list = super().get_keys() self.chosen_api_key = self.api_keys[0] if len(self.api_keys) > 0 else None @@ -53,9 +46,8 @@ class ProviderOpenAIOfficial(Provider): for key in self.custom_headers: self.custom_headers[key] = str(self.custom_headers[key]) - # 适配 azure openai #332 if "api_version" in provider_config: - # 使用 azure api + # Using Azure OpenAI API self.client = AsyncAzureOpenAI( api_key=self.chosen_api_key, api_version=provider_config.get("api_version", None), @@ -64,7 +56,7 @@ class ProviderOpenAIOfficial(Provider): timeout=self.timeout, ) else: - # 使用 openai api + # Using OpenAI Official API self.client = AsyncOpenAI( api_key=self.chosen_api_key, base_url=provider_config.get("api_base", None), @@ -80,6 +72,8 @@ class ProviderOpenAIOfficial(Provider): model = model_config.get("model", "unknown") self.set_model(model) + self.reasoning_key = "reasoning_content" + def _maybe_inject_xai_search(self, payloads: dict, **kwargs): """当开启 xAI 原生搜索时，向请求体注入 Live Search 参数。 @@ -157,7 +151,7 @@ class ProviderOpenAIOfficial(Provider): logger.debug(f"completion: {completion}") - llm_response = await self.parse_openai_completion(completion, tools) + llm_response = await self._parse_openai_completion(completion, tools) return llm_response @@ -210,36 +204,78 @@ class ProviderOpenAIOfficial(Provider): if len(chunk.choices) == 0: continue delta = chunk.choices[0].delta - # 处理文本内容 + logger.debug(f"chunk delta: {delta}") + # handle the content delta + reasoning = self._extract_reasoning_content(chunk) + _y = False + if reasoning: + llm_response.reasoning_content = reasoning + _y = True if delta.content: completion_text = delta.content llm_response.result_chain = MessageChain( chain=[Comp.Plain(completion_text)], ) + _y = True + if _y: yield llm_response final_completion = state.get_final_completion() - llm_response = await self.parse_openai_completion(final_completion, tools) + llm_response = await self._parse_openai_completion(final_completion, tools) yield llm_response - async def parse_openai_completion( + def _extract_reasoning_content( + self, + completion: ChatCompletion | ChatCompletionChunk, + ) -> str: + """Extract reasoning content from OpenAI ChatCompletion if available.""" + reasoning_text = "" + if len(completion.choices) == 0: + return reasoning_text + if isinstance(completion, ChatCompletion): + choice = completion.choices[0] + reasoning_attr = getattr(choice.message, self.reasoning_key, None) + if reasoning_attr: + reasoning_text = str(reasoning_attr) + elif isinstance(completion, ChatCompletionChunk): + delta = completion.choices[0].delta + reasoning_attr = getattr(delta, self.reasoning_key, None) + if reasoning_attr: + reasoning_text = str(reasoning_attr) + return reasoning_text + + async def _parse_openai_completion( self, completion: ChatCompletion, tools: ToolSet | None ) -> LLMResponse: - """解析 OpenAI 的 ChatCompletion 响应""" + """Parse OpenAI ChatCompletion into LLMResponse""" llm_response = LLMResponse("assistant") if len(completion.choices) == 0: raise Exception("API 返回的 completion 为空。") choice = completion.choices[0] + # parse the text completion if choice.message.content is not None: # text completion completion_text = str(choice.message.content).strip() + # specially, some providers may set tags around reasoning content in the completion text, + # we use regex to remove them, and store then in reasoning_content field + reasoning_pattern = re.compile(r"(.*?)", re.DOTALL) + matches = reasoning_pattern.findall(completion_text) + if matches: + llm_response.reasoning_content = "\n".join( + [match.strip() for match in matches], + ) + completion_text = reasoning_pattern.sub("", completion_text).strip() llm_response.result_chain = MessageChain().message(completion_text) + # parse the reasoning content if any + # the priority is higher than the tag extraction + llm_response.reasoning_content = self._extract_reasoning_content(completion) + + # parse tool calls if any if choice.message.tool_calls and tools is not None: - # tools call (function calling) args_ls = [] func_name_ls = [] tool_call_ids = [] @@ -265,11 +301,11 @@ class ProviderOpenAIOfficial(Provider): llm_response.tools_call_name = func_name_ls llm_response.tools_call_ids = tool_call_ids + # specially handle finish reason if choice.finish_reason == "content_filter": raise Exception( "API 返回的 completion 由于内容安全过滤被拒绝(非 AstrBot)。", ) - if llm_response.completion_text is None 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}。") diff --git a/astrbot/core/provider/sources/zhipu_source.py b/astrbot/core/provider/sources/zhipu_source.py index e7b6ee4f4..ed4bc0bf8 100644 --- a/astrbot/core/provider/sources/zhipu_source.py +++ b/astrbot/core/provider/sources/zhipu_source.py @@ -12,10 +12,5 @@ class ProviderZhipu(ProviderOpenAIOfficial): self, provider_config: dict, provider_settings: dict, - default_persona=None, ) -> None: - super().__init__( - provider_config, - provider_settings, - default_persona, - ) + super().__init__(provider_config, provider_settings) diff --git a/astrbot/dashboard/routes/chat.py b/astrbot/dashboard/routes/chat.py index d7afcbc17..56946550a 100644 --- a/astrbot/dashboard/routes/chat.py +++ b/astrbot/dashboard/routes/chat.py @@ -204,6 +204,8 @@ class ChatRoute(Route): ): # 追加机器人消息 new_his = {"type": "bot", "message": result_text} + if "reasoning" in result: + new_his["reasoning"] = result["reasoning"] await self.platform_history_mgr.insert( platform_id="webchat", user_id=webchat_conv_id, diff --git a/dashboard/src/components/chat/Chat.vue b/dashboard/src/components/chat/Chat.vue index 26c7df563..d671b15b7 100644 --- a/dashboard/src/components/chat/Chat.vue +++ b/dashboard/src/components/chat/Chat.vue @@ -146,21 +146,6 @@ Hello, I'm AstrBot ⭐ -
- {{ t('core.common.type') }} - help - {{ tm('shortcuts.help') }} 😊 -
-
- {{ t('core.common.longPress') }} - Ctrl + B - {{ tm('shortcuts.voiceRecord') }} 🎤 -
-
- {{ t('core.common.press') }} - Ctrl + V - {{ tm('shortcuts.pasteImage') }} 🏞️ -
@@ -1031,17 +1016,26 @@ export default { "content": bot_resp }); } else if (chunk_json.type === 'plain') { + const chain_type = chunk_json.chain_type || 'normal'; + if (!in_streaming) { message_obj = { type: 'bot', - message: this.ref(chunk_json.data), + message: this.ref(chain_type === 'reasoning' ? '' : chunk_json.data), + reasoning: this.ref(chain_type === 'reasoning' ? chunk_json.data : ''), } this.messages.push({ "content": message_obj }); in_streaming = true; } else { - message_obj.message.value += chunk_json.data; + if (chain_type === 'reasoning') { + // Append to reasoning content + message_obj.reasoning.value += chunk_json.data; + } else { + // Append to normal message + message_obj.message.value += chunk_json.data; + } } } else if (chunk_json.type === 'update_title') { // 更新对话标题 diff --git a/dashboard/src/components/chat/MessageList.vue b/dashboard/src/components/chat/MessageList.vue index 7ab592497..9cd69241f 100644 --- a/dashboard/src/components/chat/MessageList.vue +++ b/dashboard/src/components/chat/MessageList.vue @@ -37,6 +37,19 @@
+ +
+
+ + {{ isReasoningExpanded(index) ? 'mdi-chevron-down' : 'mdi-chevron-right' }} + + {{ tm('reasoning.thinking') }} +
+
+
+
+
+
@@ -125,7 +138,8 @@ export default { copiedMessages: new Set(), isUserNearBottom: true, scrollThreshold: 1, - scrollTimer: null + scrollTimer: null, + expandedReasoning: new Set(), // Track which reasoning blocks are expanded }; }, mounted() { @@ -142,6 +156,22 @@ export default { } }, methods: { + // Toggle reasoning expansion state + toggleReasoning(messageIndex) { + if (this.expandedReasoning.has(messageIndex)) { + this.expandedReasoning.delete(messageIndex); + } else { + this.expandedReasoning.add(messageIndex); + } + // Force reactivity + this.expandedReasoning = new Set(this.expandedReasoning); + }, + + // Check if reasoning is expanded + isReasoningExpanded(messageIndex) { + return this.expandedReasoning.has(messageIndex); + }, + // 复制代码到剪贴板 copyCodeToClipboard(code) { navigator.clipboard.writeText(code).then(() => { @@ -348,7 +378,7 @@ export default { @keyframes fadeIn { from { opacity: 0; - transform: translateY(10px); + transform: translateY(0); } to { @@ -539,6 +569,69 @@ export default { .fade-in { animation: fadeIn 0.3s ease-in-out; } + +/* Reasoning 区块样式 */ +.reasoning-container { + margin-bottom: 12px; + margin-top: 6px; + border: 1px solid var(--v-theme-border); + border-radius: 8px; + overflow: hidden; + width: fit-content; +} + +.v-theme--dark .reasoning-container { + background-color: rgba(103, 58, 183, 0.08); +} + +.reasoning-header { + display: inline-flex; + align-items: center; + padding: 8px 8px; + cursor: pointer; + user-select: none; + transition: background-color 0.2s ease; + border-radius: 8px; +} + +.reasoning-header:hover { + background-color: rgba(103, 58, 183, 0.08); +} + +.v-theme--dark .reasoning-header:hover { + background-color: rgba(103, 58, 183, 0.15); +} + +.reasoning-icon { + margin-right: 6px; + color: var(--v-theme-secondary); + transition: transform 0.2s ease; +} + +.reasoning-label { + font-size: 13px; + font-weight: 500; + color: var(--v-theme-secondary); + letter-spacing: 0.3px; +} + +.reasoning-content { + padding: 0px 12px; + border-top: 1px solid var(--v-theme-border); + color: gray; + animation: fadeIn 0.2s ease-in-out; + font-style: italic; +} + +.reasoning-text { + font-size: 14px; + line-height: 1.6; + color: var(--v-theme-secondaryText); +} + +.v-theme--dark .reasoning-text { + opacity: 0.85; +}