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feat: 支持展示工具使用过程

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This commit is contained in:
Soulter
2025-06-29 21:19:40 +08:00
parent 777c503002
commit 2f941de65b
6 changed files with 77 additions and 14 deletions
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astrbot/core/config/default.py
+8 -2
View File
@@ -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",
},
},
},
astrbot/core/message/message_event_result.py
+2
View File
@@ -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。
astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py
+13
View File
@@ -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。
astrbot/core/pipeline/process_stage/method/llm_request.py
+28 -12
View File
@@ -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,
astrbot/core/platform/sources/telegram/tg_event.py
+6
View File
@@ -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):
astrbot/core/platform/sources/webchat/webchat_event.py
+20
View File
@@ -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
)