',
+ unsafe_allow_html=True,
+ )
+ elif files_upload["videos"]:
+ st.markdown(
+ f'',
+ unsafe_allow_html=True,
+ )
+ elif files_upload["audios"]:
+ st.markdown(
+ f'',
+ unsafe_allow_html=True,
+ )
+
+ chat_box.ai_say("正在思考...")
+ text = ""
+ started = False
+
+ client = openai.Client(base_url=f"{api_address()}/chat", api_key="NONE", timeout=100000)
+ if is_vision_chat: # multimodal chat
+ content = [
+ {"type": "text", "text": prompt},
+ {"type": "image_url", "image_url": {"url": get_image_file_url(upload_image)}}
+ ]
+ messages = [{"role": "user", "content": content}]
+ else:
+ messages = history + [{"role": "user", "content": prompt}]
+
+
+ extra_body = dict(
+ metadata=files_upload,
+ chat_model_config=chat_model_config,
+ conversation_id=conversation_id,
+ upload_image=upload_image,
+ )
+ stream = not is_vision_chat
+ params = dict(
+ messages=messages,
+ model=llm_model,
+ stream=stream, # TODO：xinference qwen-vl-chat 流式输出会出错，后续看更新
+ extra_body=extra_body,
+ tool_config=selected_tool_configs,
+ )
+
+ if Settings.model_settings.MAX_TOKENS:
+ params["max_tokens"] = Settings.model_settings.MAX_TOKENS
+
+ if stream:
+ try:
+ for d in client.chat.completions.create(**params):
+ # import rich
+ # rich.print(d)
+ message_id = d.message_id
+ metadata = {
+ "message_id": message_id,
+ }
+
+ # clear initial message
+ if not started:
+ chat_box.update_msg("", streaming=False)
+ started = True
+
+ if d.status == AgentStatus.error:
+ st.error(d.choices[0].delta.content)
+ elif d.status == AgentStatus.llm_start:
+ if not output_agent:
+ continue
+ chat_box.insert_msg("正在解读工具输出结果...")
+ text = d.choices[0].delta.content or ""
+ elif d.status == AgentStatus.llm_new_token:
+ if not output_agent:
+ continue
+ text += d.choices[0].delta.content or ""
+ chat_box.update_msg(
+ text.replace("\n", "\n\n"), streaming=True, metadata=metadata
+ )
+ elif d.status == AgentStatus.llm_end:
+ if not output_agent:
+ continue
+ text += d.choices[0].delta.content or ""
+ chat_box.update_msg(
+ text.replace("\n", "\n\n"), streaming=False, metadata=metadata
+ )
+ # tool 的输出与 llm 输出重复了
+ elif d.status == AgentStatus.tool_start:
+ formatted_data = {
+ "Function": d.choices[0].delta.tool_calls[0].function.name,
+ "function_input": d.choices[0].delta.tool_calls[0].function.arguments,
+ }
+ formatted_json = json.dumps(formatted_data, indent=2, ensure_ascii=False)
+ text = """\n```{}\n```\n""".format(formatted_json)
+ chat_box.insert_msg( # TODO: insert text directly not shown
+ Markdown(text, title="Function call", in_expander=True, expanded=True, state="running"))
+ elif d.status == AgentStatus.tool_end:
+ tool_output = d.choices[0].delta.tool_calls[0].tool_output
+ if d.message_type == MsgType.IMAGE:
+ for url in json.loads(tool_output).get("images", []):
+ # 判断是否携带域名
+ if not url.startswith("http"):
+ url = f"{api.base_url}/media/{url}"
+ # md语法不支持，所以pos 跳过
+ chat_box.insert_msg(Image(url), pos=-2)
+ chat_box.update_msg(text, streaming=False, expanded=True, state="complete")
+ else:
+ text += """\n```\nObservation:\n{}\n```\n""".format(tool_output)
+ chat_box.update_msg(text, streaming=False, expanded=False, state="complete")
+ elif d.status == AgentStatus.agent_finish:
+ text = d.choices[0].delta.content or ""
+ chat_box.update_msg(text.replace("\n", "\n\n"))
+ elif d.status is None: # not agent chat
+ if getattr(d, "is_ref", False):
+ context = str(d.tool_output)
+ if isinstance(d.tool_output, dict):
+ docs = d.tool_output.get("docs", [])
+ source_documents = format_reference(kb_name=d.tool_output.get("knowledge_base"),
+ docs=docs,
+ api_base_url=api_address(is_public=True))
+ context = "\n".join(source_documents)
+
+ chat_box.insert_msg(
+ Markdown(
+ context,
+ in_expander=True,
+ state="complete",
+ title="参考资料",
+ )
+ )
+ chat_box.insert_msg("")
+ elif getattr(d, "tool_call", None) == "text2images": # TODO：特定工具特别处理，需要更通用的处理方式
+ for img in d.tool_output.get("images", []):
+ chat_box.insert_msg(Image(f"{api.base_url}/media/{img}"), pos=-2)
+ else:
+ text += d.choices[0].delta.content or ""
+ chat_box.update_msg(
+ text.replace("\n", "\n\n"), streaming=True, metadata=metadata
+ )
+ chat_box.update_msg(text, streaming=False, metadata=metadata)
+ except Exception as e:
+ st.error(e.body)
+ else:
+ try:
+ d = client.chat.completions.create(**params)
+ chat_box.update_msg(d.choices[0].message.content or "", streaming=False)
+ except Exception as e:
+ st.error(e.body)
+
+ # if os.path.exists("tmp/image.jpg"):
+ # with open("tmp/image.jpg", "rb") as image_file:
+ # encoded_string = base64.b64encode(image_file.read()).decode()
+ # img_tag = (
+ # f'
'
+ # )
+ # st.markdown(img_tag, unsafe_allow_html=True)
+ # os.remove("tmp/image.jpg")
+ # chat_box.show_feedback(**feedback_kwargs,
+ # key=message_id,
+ # on_submit=on_feedback,
+ # kwargs={"message_id": message_id, "history_index": len(chat_box.history) - 1})
+
+ # elif dialogue_mode == "文件对话":
+ # if st.session_state["file_chat_id"] is None:
+ # st.error("请先上传文件再进行对话")
+ # st.stop()
+ # chat_box.ai_say([
+ # f"正在查询文件 `{st.session_state['file_chat_id']}` ...",
+ # Markdown("...", in_expander=True, title="文件匹配结果", state="complete"),
+ # ])
+ # text = ""
+ # for d in api.file_chat(prompt,
+ # knowledge_id=st.session_state["file_chat_id"],
+ # top_k=kb_top_k,
+ # score_threshold=score_threshold,
+ # history=history,
+ # model=llm_model,
+ # prompt_name=prompt_template_name,
+ # temperature=temperature):
+ # if error_msg := check_error_msg(d):
+ # st.error(error_msg)
+ # elif chunk := d.get("answer"):
+ # text += chunk
+ # chat_box.update_msg(text, element_index=0)
+ # chat_box.update_msg(text, element_index=0, streaming=False)
+ # chat_box.update_msg("\n\n".join(d.get("docs", [])), element_index=1, streaming=False)
+
+ now = datetime.now()
+ with tab2:
+ cols = st.columns(2)
+ export_btn = cols[0]
+ if cols[1].button(
+ "清空对话",
+ use_container_width=True,
+ ):
+ chat_box.reset_history()
+ rerun()
+
+ export_btn.download_button(
+ "导出记录",
+ "".join(chat_box.export2md()),
+ file_name=f"{now:%Y-%m-%d %H.%M}_对话记录.md",
+ mime="text/markdown",
+ use_container_width=True,
+ )
+
+ # st.write(chat_box.history)
diff --git a/libs/chatchat-server/langchain_chatchat/agent_toolkits/mcp_kit/tools.py b/libs/chatchat-server/langchain_chatchat/agent_toolkits/mcp_kit/tools.py
index af8135162c..1962b45a44 100644
--- a/libs/chatchat-server/langchain_chatchat/agent_toolkits/mcp_kit/tools.py
+++ b/libs/chatchat-server/langchain_chatchat/agent_toolkits/mcp_kit/tools.py
@@ -4,7 +4,7 @@
from typing import Any, Type, Dict
import inspect
from mcp.server.fastmcp.utilities.func_metadata import ArgModelBase
-from pydantic import BaseModel, create_model, Field
+
from langchain_core.tools import BaseTool, StructuredTool, ToolException
from mcp import ClientSession
from mcp.types import (
@@ -16,43 +16,38 @@
from mcp.types import (
Tool as MCPTool,
)
-from pydantic.fields import FieldInfo
+from pydantic.v1 import BaseModel, create_model, Field
+from pydantic.v1.fields import FieldInfo
NonTextContent = ImageContent | EmbeddedResource
-from typing import Any, Type
-from pydantic import BaseModel, Field, create_model
-
-
-def schema_dict_to_model(schema: dict) -> Type[BaseModel]:
- dynamic_pydantic_model_params = {}
- for name, prop in schema.get("properties", {}).items():
- # 简化类型映射
- type_str = prop.get("type", "string")
- if type_str == "integer":
- py_type = int
- elif type_str == "number":
- py_type = float
- elif type_str == "boolean":
- py_type = bool
- elif type_str == "array":
- py_type = list
- elif type_str == "object":
- py_type = dict
+
+def schema_dict_to_model(schema: Dict[str, Any]) -> Any:
+ fields = schema.get('properties', {})
+ required_fields = schema.get('required', [])
+
+ model_fields = {}
+ for field_name, details in fields.items():
+ field_type_str = details['type']
+
+ if field_type_str == 'integer':
+ field_type = int
+ elif field_type_str == 'string':
+ field_type = str
+ elif field_type_str == 'number':
+ field_type = float
+ elif field_type_str == 'boolean':
+ field_type = bool
else:
- py_type = str
-
- default = ... if name in schema.get("required", []) else None
- field_info = FieldInfo.from_annotated_attribute(
- py_type,
- inspect.Parameter.empty
- )
- dynamic_pydantic_model_params[name] = (field_info.annotation, field_info)
-
- model_name = schema.get("title", "DynamicModel")
- return create_model(model_name,
- **dynamic_pydantic_model_params,
- __base__=BaseModel)
+ field_type = Any # 可扩展更多类型
+
+ if field_name in required_fields:
+ model_fields[field_name] = (field_type, ...)
+ else:
+ model_fields[field_name] = (field_type, None)
+
+ DynamicSchema = create_model(schema.get('title', 'DynamicSchema'), **model_fields)
+ return DynamicSchema
def _convert_call_tool_result(
diff --git a/libs/chatchat-server/langchain_chatchat/agents/platform_tools/base.py b/libs/chatchat-server/langchain_chatchat/agents/platform_tools/base.py
index 75618d5d55..ead061787b 100644
--- a/libs/chatchat-server/langchain_chatchat/agents/platform_tools/base.py
+++ b/libs/chatchat-server/langchain_chatchat/agents/platform_tools/base.py
@@ -51,7 +51,7 @@
PlatformToolsActionToolEnd,
PlatformToolsActionToolStart,
PlatformToolsFinish,
- PlatformToolsLLMStatus,
+ PlatformToolsLLMStatus, PlatformToolsApprove,
)
from langchain_chatchat.callbacks.agent_callback_handler import (
AgentExecutorAsyncIteratorCallbackHandler,
@@ -156,7 +156,7 @@ def create_agent_executor(
tools: Sequence[
Union[Dict[str, Any], Type[BaseModel], Callable, BaseTool]
] = None,
- temperature: float = 0.7,
+ callbacks: List[BaseCallbackHandler] = None,
**kwargs: Any,
) -> "PlatformToolsRunnable":
"""Create an ZhipuAI Assistant and instantiate the Runnable."""
@@ -164,8 +164,11 @@ def create_agent_executor(
raise ValueError
callback = AgentExecutorAsyncIteratorCallbackHandler()
- callbacks = [callback] + llm.callbacks
- llm.callbacks = callbacks
+ final_callbacks = [callback] + llm.callbacks
+ if callbacks:
+ final_callbacks.extend(callbacks)
+
+ llm.callbacks = final_callbacks
llm_with_all_tools = None
temp_tools = []
@@ -174,7 +177,7 @@ def create_agent_executor(
temp_tools.extend(
[
- t.copy(update={"callbacks": callbacks})
+ t.copy(update={"callbacks": final_callbacks})
for t in tools
if not _is_assistants_builtin_tool(t)
]
@@ -186,13 +189,13 @@ def create_agent_executor(
# load with langchain_chatchat/agents/all_tools_agent.py:108
# AdapterAllTool implements it
if _is_assistants_builtin_tool(t):
- assistants_builtin_tools.append(cls.paser_all_tools(t, callbacks))
+ assistants_builtin_tools.append(cls.paser_all_tools(t, final_callbacks))
temp_tools.extend(assistants_builtin_tools)
agent_executor = agents_registry(
agent_type=agent_type,
llm=llm,
- callbacks=callbacks,
+ callbacks=final_callbacks,
tools=temp_tools,
llm_with_platform_tools=llm_with_all_tools,
verbose=True,
@@ -269,6 +272,14 @@ async def chat_iterator() -> AsyncIterable[OutputType]:
tool=data["tool"],
)
+ elif data["status"] == AgentStatus.tool_require_approval:
+ class_status = PlatformToolsApprove(
+ run_id=data["run_id"],
+ status=data["status"],
+ tool_input=data["tool_input"],
+ tool=data["tool"],
+ )
+
elif data["status"] in [AgentStatus.tool_end]:
class_status = PlatformToolsActionToolEnd(
run_id=data["run_id"],
diff --git a/libs/chatchat-server/langchain_chatchat/agents/platform_tools/schema.py b/libs/chatchat-server/langchain_chatchat/agents/platform_tools/schema.py
index 4c92c5fddb..e088c542ab 100644
--- a/libs/chatchat-server/langchain_chatchat/agents/platform_tools/schema.py
+++ b/libs/chatchat-server/langchain_chatchat/agents/platform_tools/schema.py
@@ -55,6 +55,20 @@ def from_json(cls, data_str: str, **kwargs: Any) -> Self: # type: ignore
return cls.from_dict(data, **kwargs)
+class PlatformToolsApprove(PlatformToolsBaseComponent):
+ """Approve or reject a tool input."""
+
+ run_id: str
+ status: int # AgentStatus
+ tool: str
+ tool_input: Union[str, Dict[str, Any]]
+ log: str
+
+ @classmethod
+ def class_name(cls) -> str:
+ return "PlatformToolsApprove"
+
+
class PlatformToolsAction(PlatformToolsBaseComponent):
"""AgentFinish with run and thread metadata."""
diff --git a/libs/chatchat-server/langchain_chatchat/callbacks/agent_callback_handler.py b/libs/chatchat-server/langchain_chatchat/callbacks/agent_callback_handler.py
index 91aefe2394..9f2ad33d85 100644
--- a/libs/chatchat-server/langchain_chatchat/callbacks/agent_callback_handler.py
+++ b/libs/chatchat-server/langchain_chatchat/callbacks/agent_callback_handler.py
@@ -1,23 +1,47 @@
# -*- coding: utf-8 -*-
from __future__ import annotations
+from typing import Generic, Iterable, TypeVar
import asyncio
import json
-from typing import Any, Dict, List, Optional, Tuple
+from typing import List, Tuple, Any, Awaitable, Callable, Dict, Optional
from uuid import UUID
+from enum import Enum
from langchain.callbacks import AsyncIteratorCallbackHandler
from langchain.schema import AgentAction, AgentFinish
+from langchain_community.callbacks.human import HumanRejectedException
+from langchain_core.callbacks import AsyncCallbackHandler
from langchain_core.outputs import LLMResult
from langchain_chatchat.agent_toolkits import BaseToolOutput
+from langchain_chatchat.callbacks.core.protocol import AgentBackend
from langchain_chatchat.utils import History
+# Define TypeVars for input and output types
+T = TypeVar("T")
+R = TypeVar("R")
+
+
+async def _adefault_approve(_input: str) -> bool:
+ msg = (
+ "Do you approve of the following input? "
+ "Anything except 'Y'/'Yes' (case-insensitive) will be treated as a no."
+ )
+ msg += "\n\n" + _input + "\n"
+ resp = input(msg)
+ return resp.lower() in ("yes", "y")
+
def dumps(obj: Dict) -> str:
return json.dumps(obj, ensure_ascii=False)
+class ApprovalMethod(Enum):
+ CLI = "cli"
+ BACKEND = "backend"
+
+
class AgentStatus:
chain_start: int = 0
llm_start: int = 1
@@ -25,23 +49,33 @@ class AgentStatus:
llm_end: int = 3
agent_action: int = 4
agent_finish: int = 5
- tool_start: int = 6
- tool_end: int = 7
+ tool_require_approval: int = 6
+ tool_start: int = 7
+ tool_end: int = 8
error: int = -1
chain_end: int = -999
class AgentExecutorAsyncIteratorCallbackHandler(AsyncIteratorCallbackHandler):
- def __init__(self):
+ approval_method: ApprovalMethod | None = None
+ backend: AgentBackend | None = None
+ raise_error: bool = True
+
+ def __init__(
+ self,
+ **kwargs
+ ):
super().__init__()
self.queue = asyncio.Queue()
self.done = asyncio.Event()
self.out = False
self.intermediate_steps: List[Tuple[AgentAction, BaseToolOutput]] = []
self.outputs: Dict[str, Any] = {}
+ self.approval_method = kwargs.get("approval_method", ApprovalMethod.CLI)
+ self.backend = kwargs.get("backend", None)
async def on_llm_start(
- self, serialized: Dict[str, Any], prompts: List[str], **kwargs: Any
+ self, serialized: Dict[str, Any], prompts: List[str], **kwargs: Any
) -> None:
data = {
"status": AgentStatus.llm_start,
@@ -75,15 +109,15 @@ async def on_llm_new_token(self, token: str, **kwargs: Any) -> None:
self.queue.put_nowait(dumps(data))
async def on_chat_model_start(
- self,
- serialized: Dict[str, Any],
- messages: List[List],
- *,
- run_id: UUID,
- parent_run_id: Optional[UUID] = None,
- tags: Optional[List[str]] = None,
- metadata: Optional[Dict[str, Any]] = None,
- **kwargs: Any,
+ self,
+ serialized: Dict[str, Any],
+ messages: List[List],
+ *,
+ run_id: UUID,
+ parent_run_id: Optional[UUID] = None,
+ tags: Optional[List[str]] = None,
+ metadata: Optional[Dict[str, Any]] = None,
+ **kwargs: Any,
) -> None:
data = {
"run_id": str(run_id),
@@ -103,7 +137,7 @@ async def on_llm_end(self, response: LLMResult, **kwargs: Any) -> None:
self.queue.put_nowait(dumps(data))
async def on_llm_error(
- self, error: Exception | KeyboardInterrupt, **kwargs: Any
+ self, error: Exception | KeyboardInterrupt, **kwargs: Any
) -> None:
data = {
"status": AgentStatus.error,
@@ -112,15 +146,15 @@ async def on_llm_error(
self.queue.put_nowait(dumps(data))
async def on_tool_start(
- self,
- serialized: Dict[str, Any],
- input_str: str,
- *,
- run_id: UUID,
- parent_run_id: Optional[UUID] = None,
- tags: Optional[List[str]] = None,
- metadata: Optional[Dict[str, Any]] = None,
- **kwargs: Any,
+ self,
+ serialized: Dict[str, Any],
+ input_str: str,
+ *,
+ run_id: UUID,
+ parent_run_id: Optional[UUID] = None,
+ tags: Optional[List[str]] = None,
+ metadata: Optional[Dict[str, Any]] = None,
+ **kwargs: Any,
) -> None:
data = {
"run_id": str(run_id),
@@ -128,17 +162,32 @@ async def on_tool_start(
"tool": serialized["name"],
"tool_input": input_str,
}
+
+ if self.approval_method is ApprovalMethod.CLI:
+
+ self.done.clear()
+ self.queue.put_nowait(dumps(data))
+ if not await _adefault_approve(input_str):
+ raise HumanRejectedException(
+ f"Inputs {input_str} to tool {serialized} were rejected."
+ )
+ pass
+ elif self.approval_method is ApprovalMethod.BACKEND:
+ pass
+ else:
+ raise ValueError("Approval method not recognized.")
+
self.done.clear()
self.queue.put_nowait(dumps(data))
async def on_tool_end(
- self,
- output: Any,
- *,
- run_id: UUID,
- parent_run_id: Optional[UUID] = None,
- tags: Optional[List[str]] = None,
- **kwargs: Any,
+ self,
+ output: Any,
+ *,
+ run_id: UUID,
+ parent_run_id: Optional[UUID] = None,
+ tags: Optional[List[str]] = None,
+ **kwargs: Any,
) -> None:
"""Run when tool ends running."""
data = {
@@ -150,13 +199,13 @@ async def on_tool_end(
self.queue.put_nowait(dumps(data))
async def on_tool_error(
- self,
- error: BaseException,
- *,
- run_id: UUID,
- parent_run_id: Optional[UUID] = None,
- tags: Optional[List[str]] = None,
- **kwargs: Any,
+ self,
+ error: BaseException,
+ *,
+ run_id: UUID,
+ parent_run_id: Optional[UUID] = None,
+ tags: Optional[List[str]] = None,
+ **kwargs: Any,
) -> None:
"""Run when tool errors."""
data = {
@@ -169,13 +218,13 @@ async def on_tool_error(
self.queue.put_nowait(dumps(data))
async def on_agent_action(
- self,
- action: AgentAction,
- *,
- run_id: UUID,
- parent_run_id: Optional[UUID] = None,
- tags: Optional[List[str]] = None,
- **kwargs: Any,
+ self,
+ action: AgentAction,
+ *,
+ run_id: UUID,
+ parent_run_id: Optional[UUID] = None,
+ tags: Optional[List[str]] = None,
+ **kwargs: Any,
) -> None:
data = {
"run_id": str(run_id),
@@ -189,13 +238,13 @@ async def on_agent_action(
self.queue.put_nowait(dumps(data))
async def on_agent_finish(
- self,
- finish: AgentFinish,
- *,
- run_id: UUID,
- parent_run_id: Optional[UUID] = None,
- tags: Optional[List[str]] = None,
- **kwargs: Any,
+ self,
+ finish: AgentFinish,
+ *,
+ run_id: UUID,
+ parent_run_id: Optional[UUID] = None,
+ tags: Optional[List[str]] = None,
+ **kwargs: Any,
) -> None:
if isinstance(finish.return_values["output"], str):
if "Thought:" in finish.return_values["output"]:
@@ -217,15 +266,15 @@ async def on_agent_finish(
self.queue.put_nowait(dumps(data))
async def on_chain_start(
- self,
- serialized: Dict[str, Any],
- inputs: Dict[str, Any],
- *,
- run_id: UUID,
- parent_run_id: Optional[UUID] = None,
- tags: Optional[List[str]] = None,
- metadata: Optional[Dict[str, Any]] = None,
- **kwargs: Any,
+ self,
+ serialized: Dict[str, Any],
+ inputs: Dict[str, Any],
+ *,
+ run_id: UUID,
+ parent_run_id: Optional[UUID] = None,
+ tags: Optional[List[str]] = None,
+ metadata: Optional[Dict[str, Any]] = None,
+ **kwargs: Any,
) -> None:
"""Run when chain starts running."""
if "agent_scratchpad" in inputs:
@@ -249,13 +298,13 @@ async def on_chain_start(
self.queue.put_nowait(dumps(data))
async def on_chain_error(
- self,
- error: BaseException,
- *,
- run_id: UUID,
- parent_run_id: Optional[UUID] = None,
- tags: Optional[List[str]] = None,
- **kwargs: Any,
+ self,
+ error: BaseException,
+ *,
+ run_id: UUID,
+ parent_run_id: Optional[UUID] = None,
+ tags: Optional[List[str]] = None,
+ **kwargs: Any,
) -> None:
"""Run when chain errors."""
data = {
@@ -266,13 +315,13 @@ async def on_chain_error(
self.queue.put_nowait(dumps(data))
async def on_chain_end(
- self,
- outputs: Dict[str, Any],
- *,
- run_id: UUID,
- parent_run_id: UUID | None = None,
- tags: List[str] | None = None,
- **kwargs: Any,
+ self,
+ outputs: Dict[str, Any],
+ *,
+ run_id: UUID,
+ parent_run_id: UUID | None = None,
+ tags: List[str] | None = None,
+ **kwargs: Any,
) -> None:
# TODO agent params of PlatformToolsAgentExecutor or AgentExecutor enable return_intermediate_steps=True,
if "intermediate_steps" in outputs:
@@ -292,3 +341,4 @@ async def on_chain_end(
self.queue.put_nowait(dumps(data))
self.out = True
# self.done.set()
+
diff --git a/libs/chatchat-server/langchain_chatchat/callbacks/core/protocol.py b/libs/chatchat-server/langchain_chatchat/callbacks/core/protocol.py
new file mode 100644
index 0000000000..01a18764e4
--- /dev/null
+++ b/libs/chatchat-server/langchain_chatchat/callbacks/core/protocol.py
@@ -0,0 +1,39 @@
+from __future__ import annotations
+from typing import Generic, Iterable, TypeVar
+
+from pydantic import BaseModel, field_validator
+
+from datetime import datetime
+
+class FunctionCall(BaseModel):
+ run_id: str
+ call_id: str
+
+
+class FunctionCallStatus(BaseModel):
+ requested_at: datetime | None = None
+ responded_at: datetime | None = None
+ approved: bool | None = None
+ comment: str | None = None
+ reject_option_name: str | None = None
+ slack_message_ts: str | None = None
+
+
+class AgentStore:
+ """
+ allows for creating and checking the status of
+ """
+
+ def add(self, item: FunctionCall) -> FunctionCall:
+ raise NotImplementedError()
+
+ def get(self, call_id: str) -> FunctionCall:
+ raise NotImplementedError()
+
+ def respond(self, call_id: str, status: FunctionCallStatus) -> FunctionCall:
+ raise NotImplementedError()
+
+
+class AgentBackend:
+ def functions(self) -> AgentStore:
+ raise NotImplementedError()
diff --git a/libs/chatchat-server/tests/integration_tests/platform_tools/test_platform_tools.py b/libs/chatchat-server/tests/integration_tests/platform_tools/test_platform_tools.py
index a2cf97ebf1..66b0047afa 100644
--- a/libs/chatchat-server/tests/integration_tests/platform_tools/test_platform_tools.py
+++ b/libs/chatchat-server/tests/integration_tests/platform_tools/test_platform_tools.py
@@ -19,7 +19,7 @@
@tool
-@hl.require_approval()
+# @hl.require_approval()
def multiply(first_int: int, second_int: int) -> int:
"""Multiply two integers together."""
return first_int * second_int
@@ -211,3 +211,40 @@ async def test_qwen_structured_chat_agent_tools(logging_conf):
elif isinstance(item, PlatformToolsLLMStatus):
if item.status == AgentStatus.llm_end:
print("llm_end:" + item.text)
+
+
+@pytest.mark.asyncio
+async def test_human_platform_tools(logging_conf):
+ logging.config.dictConfig(logging_conf) # type: ignore
+
+ llm_params = get_ChatPlatformAIParams(
+ model_name="glm-4-plus",
+ temperature=0.01,
+ max_tokens=100,
+ )
+ llm = ChatPlatformAI(**llm_params)
+ agent_executor = PlatformToolsRunnable.create_agent_executor(
+ agent_type="platform-agent",
+ agents_registry=agents_registry,
+ llm=llm,
+ tools=[multiply, exp, add],
+ callbacks=[],
+ )
+
+ chat_iterator = agent_executor.invoke(chat_input="计算下 2 乘以 5")
+ async for item in chat_iterator:
+ if isinstance(item, PlatformToolsAction):
+ print("PlatformToolsAction:" + str(item.to_json()))
+
+ elif isinstance(item, PlatformToolsFinish):
+ print("PlatformToolsFinish:" + str(item.to_json()))
+
+ elif isinstance(item, PlatformToolsActionToolStart):
+ print("PlatformToolsActionToolStart:" + str(item.to_json()))
+
+ elif isinstance(item, PlatformToolsActionToolEnd):
+ print("PlatformToolsActionToolEnd:" + str(item.to_json()))
+ elif isinstance(item, PlatformToolsLLMStatus):
+ if item.status == AgentStatus.llm_end:
+ print("llm_end:" + item.text)
+
From e5ad085bc4ead9551356d6896381dce5d787eb9c Mon Sep 17 00:00:00 2001
From: glide-the <2533736852@qq.com>
Date: Thu, 3 Apr 2025 12:52:15 +0800
Subject: [PATCH 07/48] bug
---
libs/chatchat-server/chatchat/settings.py | 27 +-------
.../callbacks/agent_callback_handler.py | 12 ++--
.../test_mcp_platform_tools.py | 64 +++++++++++++++++--
3 files changed, 68 insertions(+), 35 deletions(-)
diff --git a/libs/chatchat-server/chatchat/settings.py b/libs/chatchat-server/chatchat/settings.py
index 54057dc591..7b2587dd75 100644
--- a/libs/chatchat-server/chatchat/settings.py
+++ b/libs/chatchat-server/chatchat/settings.py
@@ -670,33 +670,10 @@ class PromptSettings(BaseFileSettings):
},
"openai-functions": {
"SYSTEM_PROMPT": (
- "Answer the following questions as best you can. You have access to the following tools:\n"
- "The way you use the tools is by specifying a json blob.\n"
- "Specifically, this json should have a `action` key (with the name of the tool to use) and a `action_input` key (with the input to the tool going here).\n"
- 'The only values that should be in the "action" field are: {tool_names}\n'
- "The $JSON_BLOB should only contain a SINGLE action, do NOT return a list of multiple actions. Here is an example of a valid $JSON_BLOB:\n"
- "```\n\n"
- "{{{{\n"
- ' "action": $TOOL_NAME,\n'
- ' "action_input": $INPUT\n'
- "}}}}\n"
- "```\n\n"
- "ALWAYS use the following format:\n"
- "Question: the input question you must answer\n"
- "Thought: you should always think about what to do\n"
- "Action:\n"
- "```\n\n"
- "$JSON_BLOB"
- "```\n\n"
- "Observation: the result of the action\n"
- "... (this Thought/Action/Observation can repeat N times)\n"
- "Thought: I now know the final answer\n"
- "Final Answer: the final answer to the original input question\n"
- "Begin! Reminder to always use the exact characters `Final Answer` when responding.\n"
+ "You are a helpful assistant"
),
"HUMAN_MESSAGE": (
- "Question:{input}\n"
- "Thought:{agent_scratchpad}\n"
+ "{input}"
)
},
"glm3": {
diff --git a/libs/chatchat-server/langchain_chatchat/callbacks/agent_callback_handler.py b/libs/chatchat-server/langchain_chatchat/callbacks/agent_callback_handler.py
index 9f2ad33d85..49ab18f4c9 100644
--- a/libs/chatchat-server/langchain_chatchat/callbacks/agent_callback_handler.py
+++ b/libs/chatchat-server/langchain_chatchat/callbacks/agent_callback_handler.py
@@ -165,12 +165,12 @@ async def on_tool_start(
if self.approval_method is ApprovalMethod.CLI:
- self.done.clear()
- self.queue.put_nowait(dumps(data))
- if not await _adefault_approve(input_str):
- raise HumanRejectedException(
- f"Inputs {input_str} to tool {serialized} were rejected."
- )
+ # self.done.clear()
+ # self.queue.put_nowait(dumps(data))
+ # if not await _adefault_approve(input_str):
+ # raise HumanRejectedException(
+ # f"Inputs {input_str} to tool {serialized} were rejected."
+ # )
pass
elif self.approval_method is ApprovalMethod.BACKEND:
pass
diff --git a/libs/chatchat-server/tests/integration_tests/mcp_platform_tools/test_mcp_platform_tools.py b/libs/chatchat-server/tests/integration_tests/mcp_platform_tools/test_mcp_platform_tools.py
index 6b24f6f967..56c903b409 100644
--- a/libs/chatchat-server/tests/integration_tests/mcp_platform_tools/test_mcp_platform_tools.py
+++ b/libs/chatchat-server/tests/integration_tests/mcp_platform_tools/test_mcp_platform_tools.py
@@ -1,6 +1,6 @@
# -*- coding: utf-8 -*-
-from mcp import ClientSession, StdioServerParameters
-from mcp.client.stdio import stdio_client
+from mcp import ClientSession, StdioServerParameters, stdio_client
+
from chatchat.server.agents_registry.agents_registry import agents_registry
from chatchat.server.utils import get_ChatPlatformAIParams
from langchain_chatchat import ChatPlatformAI
@@ -20,7 +20,6 @@
@pytest.mark.asyncio
async def test_mcp_stdio_tools(logging_conf):
-
server_params = StdioServerParameters(
command="python",
# Make sure to update to the full absolute path to your math_server.py file
@@ -37,7 +36,7 @@ async def test_mcp_stdio_tools(logging_conf):
# Create and run the agent
llm_params = get_ChatPlatformAIParams(
- model_name="glm-4-plus",
+ model_name="fun-lora",
temperature=0.01,
max_tokens=100,
)
@@ -64,3 +63,60 @@ async def test_mcp_stdio_tools(logging_conf):
elif isinstance(item, PlatformToolsLLMStatus):
if item.status == AgentStatus.llm_end:
print("llm_end:" + item.text)
+
+
+@pytest.mark.asyncio
+async def test_mcp_multi_tools(logging_conf):
+ async with MultiServerMCPClient(
+ {
+ "math": {
+ "command": "python",
+ # Make sure to update to the full absolute path to your math_server.py file
+ "args": [f"D:/project/Langchain-Chatchat/libs/chatchat-server/tests/integration_tests/mcp_platform_tools/math_server.py"],
+ "transport": "stdio",
+ "env": {
+ **os.environ,
+ "PYTHONHASHSEED": "0",
+ },
+ },
+ # "playwright": {
+ # # make sure you start your weather server on port 8000
+ # "url": "http://localhost:8931/sse",
+ # "transport": "sse",
+ # },
+ }
+ ) as client:
+
+ # Get tools
+ tools = client.get_tools()
+
+ # Create and run the agent
+ llm_params = get_ChatPlatformAIParams(
+ model_name="glm-4-plus",
+ temperature=0.01,
+ max_tokens=1280000,
+ )
+ llm = ChatPlatformAI(**llm_params)
+ agent_executor = PlatformToolsRunnable.create_agent_executor(
+ agent_type="openai-functions",
+ agents_registry=agents_registry,
+ llm=llm,
+ tools=tools,
+ )
+ chat_iterator = agent_executor.invoke(chat_input="下载项目到本地 https://github.com/microsoft/playwright-mcp")
+ async for item in chat_iterator:
+ if isinstance(item, PlatformToolsAction):
+ print("PlatformToolsAction:" + str(item.to_json()))
+
+ elif isinstance(item, PlatformToolsFinish):
+ print("PlatformToolsFinish:" + str(item.to_json()))
+
+ elif isinstance(item, PlatformToolsActionToolStart):
+ print("PlatformToolsActionToolStart:" + str(item.to_json()))
+
+ elif isinstance(item, PlatformToolsActionToolEnd):
+ print("PlatformToolsActionToolEnd:" + str(item.to_json()))
+ elif isinstance(item, PlatformToolsLLMStatus):
+ print(item.text)
+ if item.status == AgentStatus.llm_end:
+ print("llm_end:" + item.text)
From 1ae93d0ee8f2a0c5958ce09078498a3597972218 Mon Sep 17 00:00:00 2001
From: glide-the <2533736852@qq.com>
Date: Thu, 3 Apr 2025 17:01:42 +0800
Subject: [PATCH 08/48] mcp_tools
---
libs/chatchat-server/chatchat/settings.py | 255 +++++++++++++-----
.../agent_toolkits/mcp_kit/client.py | 32 +++
.../agents/platform_tools/base.py | 1 +
.../test_mcp_platform_tools.py | 32 ++-
4 files changed, 240 insertions(+), 80 deletions(-)
diff --git a/libs/chatchat-server/chatchat/settings.py b/libs/chatchat-server/chatchat/settings.py
index 7b2587dd75..11c4313abc 100644
--- a/libs/chatchat-server/chatchat/settings.py
+++ b/libs/chatchat-server/chatchat/settings.py
@@ -729,76 +729,199 @@ class PromptSettings(BaseFileSettings):
"SYSTEM_PROMPT": (
"You are a helpful assistant"
),
- "MCP_PROMPT": (
- "====\n\n"
- "TOOL USE\n\n"
- "\n\n"
- "You have access to a set of tools that are executed upon the user's approval. You can use one tool per message, and will receive the result of that tool use in the user's response. You use tools step-by-step to accomplish a given task, with each tool use informed by the result of the previous tool use.\n\n"
- "\n\n"
- "# Tool Use Formatting\n\n"
- "\n\n"
- "Tool use is formatted using XML-style tags. The tool name is enclosed in opening and closing tags, and each parameter is similarly enclosed within its own set of tags. Here's the structure:\n\n"
- "\n\n"
- "### 🌎 Internationalization - - [Internationalization Implementation Guide](https://github.com/lobehub/lobe-chat/wiki/Internationalization-Implementation) | [国际化实现指南](https://github.com/lobehub/lobe-chat/wiki/Internationalization-Implementation.zh-CN) - - [New Locale Guide](https://github.com/lobehub/lobe-chat/wiki/Add-New-Locale) | [新语种添加指南](https://github.com/lobehub/lobe-chat/wiki/Add-New-Locale.zh-CN) - +- [Internationalization Implementation Guide](https://github.com/lobehub/lobe-chat/wiki/Internationalization-Implementation) | [国际化实现指南](https://github.com/lobehub/lobe-chat/wiki/Internationalization-Implementation.zh-CN) +- [New Locale Guide](https://github.com/lobehub/lobe-chat/wiki/Add-New-Locale) | [新语种添加指南](https://github.com/lobehub/lobe-chat/wiki/Add-New-Locale.zh-CN)
### ⌨️ State Management - - [Best Practices for State Management](https://github.com/lobehub/lobe-chat/wiki/State-Management-Intro) | [状态管理最佳实践](https://github.com/lobehub/lobe-chat/wiki/State-Management-Intro.zh-CN) - - [Data Store Selector](https://github.com/lobehub/lobe-chat/wiki/State-Management-Selectors) | [数据存储取数模块](https://github.com/lobehub/lobe-chat/wiki/State-Management-Selectors.zh-CN) - +- [Best Practices for State Management](https://github.com/lobehub/lobe-chat/wiki/State-Management-Intro) | [状态管理最佳实践](https://github.com/lobehub/lobe-chat/wiki/State-Management-Intro.zh-CN) +- [Data Store Selector](https://github.com/lobehub/lobe-chat/wiki/State-Management-Selectors) | [数据存储取数模块](https://github.com/lobehub/lobe-chat/wiki/State-Management-Selectors.zh-CN)
### 🤖 Agents - - [Agent Index and Submit](https://github.com/lobehub/lobe-chat-agents) | [助手索引与提交](https://github.com/lobehub/lobe-chat-agents/blob/main/README.zh-CN.md) - +- [Agent Index and Submit](https://github.com/lobehub/lobe-chat-agents) | [助手索引与提交](https://github.com/lobehub/lobe-chat-agents/blob/main/README.zh-CN.md)
### 🧩 Plugins - - [Plugin Index and Submit](https://github.com/lobehub/lobe-chat-plugins) | [插件索引与提交](https://github.com/lobehub/lobe-chat-plugins/blob/main/README.zh-CN.md) - - [Plugin SDK Docs](https://chat-plugin-sdk.lobehub.com) | [插件 SDK 文档](https://chat-plugin-sdk.lobehub.com) - +- [Plugin Index and Submit](https://github.com/lobehub/lobe-chat-plugins) | [插件索引与提交](https://github.com/lobehub/lobe-chat-plugins/blob/main/README.zh-CN.md) +- [Plugin SDK Docs](https://chat-plugin-sdk.lobehub.com) | [插件 SDK 文档](https://chat-plugin-sdk.lobehub.com)
### 📊 Others - - [Lighthouse Reports](https://github.com/lobehub/lobe-chat/wiki/Lighthouse) | [Lighthouse 测试报告](https://github.com/lobehub/lobe-chat/wiki/Lighthouse.zh-CN) - +- [Lighthouse Reports](https://github.com/lobehub/lobe-chat/wiki/Lighthouse) | [Lighthouse 测试报告](https://github.com/lobehub/lobe-chat/wiki/Lighthouse.zh-CN)
- - --- diff --git a/frontend/contributing/_Sidebar.md b/frontend/contributing/_Sidebar.md index c1193884ec..435de075dd 100644 --- a/frontend/contributing/_Sidebar.md +++ b/frontend/contributing/_Sidebar.md @@ -4,7 +4,7 @@ - [TOC](Home.md) | [目录](Home.md) - + #### 🤯 Basic @@ -20,37 +20,29 @@ - [Technical Development Getting Started Guide](https://github.com/lobehub/lobe-chat/wiki/Intro) | [技术开发上手指南](https://github.com/lobehub/lobe-chat/wiki/Intro.zh-CN) - [Testing Guide](https://github.com/lobehub/lobe-chat/wiki/Test) | [测试指南](https://github.com/lobehub/lobe-chat/wiki/Test.zh-CN) - #### 🌎 Internationalization - [Internationalization Implementation Guide](https://github.com/lobehub/lobe-chat/wiki/Internationalization-Implementation) | [国际化实现指南](https://github.com/lobehub/lobe-chat/wiki/Internationalization-Implementation.zh-CN) - [New Locale Guide](https://github.com/lobehub/lobe-chat/wiki/Add-New-Locale) | [新语种添加指南](https://github.com/lobehub/lobe-chat/wiki/Add-New-Locale.zh-CN) - #### ⌨️ State Management - [Best Practices for State Management](https://github.com/lobehub/lobe-chat/wiki/State-Management-Intro) | [状态管理最佳实践](https://github.com/lobehub/lobe-chat/wiki/State-Management-Intro.zh-CN) - [Data Store Selector](https://github.com/lobehub/lobe-chat/wiki/State-Management-Selectors) | [数据存储取数模块](https://github.com/lobehub/lobe-chat/wiki/State-Management-Selectors.zh-CN) - #### 🤖 Agents - [Agent Index and Submit](https://github.com/lobehub/lobe-chat-agents) | [助手索引与提交](https://github.com/lobehub/lobe-chat-agents/blob/main/README.zh-CN.md) - #### 🧩 Plugins - [Plugin Index and Submit](https://github.com/lobehub/lobe-chat-plugins) | [插件索引与提交](https://github.com/lobehub/lobe-chat-plugins/blob/main/README.zh-CN.md) - [Plugin SDK Docs](https://chat-plugin-sdk.lobehub.com) | [插件 SDK 文档](https://chat-plugin-sdk.lobehub.com) - #### 📊 Others - [Lighthouse Reports](https://github.com/lobehub/lobe-chat/wiki/Lighthouse) | [Lighthouse 测试报告](https://github.com/lobehub/lobe-chat/wiki/Lighthouse.zh-CN) - - - diff --git a/frontend/docs/self-hosting/advanced/analytics.zh-CN.mdx b/frontend/docs/self-hosting/advanced/analytics.zh-CN.mdx index 61c33f0e27..dd441dba8b 100644 --- a/frontend/docs/self-hosting/advanced/analytics.zh-CN.mdx +++ b/frontend/docs/self-hosting/advanced/analytics.zh-CN.mdx @@ -1,10 +1,12 @@ -import {Callout} from "nextra/components"; +import { Callout } from 'nextra/components'; # 数据分析 为更好地帮助分析 LobeChat 的用户使用情况，我们在 LobeChat 中集成了若干免费 / 开源的数据统计服务，用于收集用户的使用情况，你可以按需开启。 -
-
- }
- return
-
- (({ toggleModal, open
const { t } = useTranslation('chat');
const antdFormInstance = useRef();
const [useFetchKnowledgeAdd, useFetchKnowledgeList] = useKnowledgeStore((s) => [
- s.useFetchKnowledgeAdd, s.useFetchKnowledgeList
+ s.useFetchKnowledgeAdd,
+ s.useFetchKnowledgeList,
]);
- const { mutate } = useFetchKnowledgeList()
+ const { mutate } = useFetchKnowledgeList();
const onSubmit = async () => {
if (!antdFormInstance.current) return;
@@ -29,30 +31,34 @@ const CreateKnowledgeBase = memo(({ toggleModal, open
const values = antdFormInstance.current.getFieldsValue(true);
setConfirmLoading(true);
- const { code: resCode, data: resData, msg: resMsg } = await useFetchKnowledgeAdd({ ...values })
+ const { code: resCode, data: resData, msg: resMsg } = await useFetchKnowledgeAdd({ ...values });
setConfirmLoading(true);
if (resCode !== 200) {
- message.error(resMsg)
+ message.error(resMsg);
return;
}
mutate();
- toggleModal(false);
- }
+ toggleModal(false);
+ };
return (
toggleModal(false)}
onOk={onSubmit}
open={open}
title="创建知识库"
- confirmLoading={confirmLoading}
>
-
- {list.map((item, index) => {
- return
+ return (
+
+ );
+ }
+ return (
+
+
-
-
+
+
+
+ );
});
const KnowledgeCardList = memo(() => {
diff --git a/frontend/src/app/knowledge/(desktop)/features/ModalCreateKnowledge.tsx b/frontend/src/app/knowledge/(desktop)/features/ModalCreateKnowledge.tsx
index d8617720f2..bd2254a10a 100644
--- a/frontend/src/app/knowledge/(desktop)/features/ModalCreateKnowledge.tsx
+++ b/frontend/src/app/knowledge/(desktop)/features/ModalCreateKnowledge.tsx
@@ -1,14 +1,15 @@
+// @ts-nocheck
import { Modal, type ModalProps } from '@lobehub/ui';
-import { Form, Input, Select, FormInstance, message } from 'antd';
+import { Form, FormInstance, Input, Select, message } from 'antd';
import { memo, useRef, useState } from 'react';
import { useTranslation } from 'react-i18next';
import { Flexbox } from 'react-layout-kit';
-import { useKnowledgeStore } from '@/store/knowledge';
+import { useKnowledgeStore } from '@/store/knowledge';
const DEFAULT_FIELD_VALUE = {
- vector_store_type: "faiss",
- embed_model: "bge-large-zh-v1.5"
+ embed_model: 'bge-large-zh-v1.5',
+ vector_store_type: 'faiss',
};
interface ModalCreateKnowledgeProps extends ModalProps {
toggleModal: (open: boolean) => void;
@@ -18,9 +19,10 @@ const CreateKnowledgeBase = memo
+
+ {list.map((item, index) => {
+ return
+
+