OKi3TSrSSKJr SSKrSSKJr SSKJrJrJ r J r J r SSK J r SSKJrJr SSKJrJr SS KJr SS KJrJrJrJrJrJr SS KJr \(aSS KJ r J!r! SS K"J#r# \RH"\%5r&Sr'\"SS55r(SSjr)SSjr*"SS\\\\\45r+g)z#LLM-based tool selector middleware.) annotationsN) dataclass) TYPE_CHECKING AnnotatedAnyLiteralUnion) BaseChatModel) AIMessage HumanMessage)Field TypeAdapter) TypedDict)AgentMiddleware AgentStateContextT ModelRequest ModelResponse ResponseT)init_chat_model) AwaitableCallable)BaseToolzNYour goal is to select the most relevant tools for answering the user's query.cL\rSrSr%SrS\S'S\S'S\S'S \S 'S \S 'S rg)_SelectionRequest$z#Prepared inputs for tool selection.list[BaseTool]available_toolsstrsystem_messager last_user_messager model list[str]valid_tool_namesN__name__ __module__ __qualname____firstlineno____doc____annotations____static_attributes__r%l/var/www/html/dynamic-report/venv/lib/python3.13/site-packages/langchain/agents/middleware/tool_selection.pyrr$s#-#### r.rc  U(d Sn[U5eUVs/sH0n[[UR[ UR S94PM2 nn[ [U5nSn"SS[5n[U5$s snf)aCreate a structured output schema for tool selection. Args: tools: Available tools to include in the schema. Returns: `TypeAdapter` for a schema where each tool name is a `Literal` with its description. Raises: AssertionError: If `tools` is empty. z&Invalid usage: tools must be non-empty) descriptionz2Tools to use. Place the most relevant tools first.c$\rSrSr%SrS\S'Srg)>_create_tool_selection_response..ToolSelectionResponseIzUse to select relevant tools.zCAnnotated[list[selected_tool_type], Field(description=description)]toolsr%Nr&r%r.r/ToolSelectionResponser3Is +RRr.r6) AssertionErrorrrnamer r1r tuplerr)r5msgtoolliteralsselected_tool_typer1r6s r/_create_tool_selection_responser>/s 6S!! X]W\t '$))$e8H8H&IIJW\ uX/FKS S , --s7Bc2SRSU55$)z~Format tools as markdown list. Args: tools: Tools to format. Returns: Markdown string with each tool on a new line.  c3Z# UH!nSURSUR3v M# g7f)z- z: N)r8r1).0r;s r/ $_render_tool_list..Zs(Ledr$))Bt'7'7&89es)+)joinr5s r/_render_tool_listrGQs 99LeL LLr.c^\rSrSrSrS\SSS.S U4SjjjrS SjrS SjrSSjr SS jr S r U=r $)LLMToolSelectorMiddleware]a8Uses an LLM to select relevant tools before calling the main model. When an agent has many tools available, this middleware filters them down to only the most relevant ones for the user's query. This reduces token usage and helps the main model focus on the right tools. Examples: !!! example "Limit to 3 tools" ```python from langchain.agents.middleware import LLMToolSelectorMiddleware middleware = LLMToolSelectorMiddleware(max_tools=3) agent = create_agent( model="openai:gpt-4o", tools=[tool1, tool2, tool3, tool4, tool5], middleware=[middleware], ) ``` !!! example "Use a smaller model for selection" ```python middleware = LLMToolSelectorMiddleware(model="openai:gpt-4o-mini", max_tools=2) ``` N)r" system_prompt max_toolsalways_includec>[TU]5 X lX0lU=(d /Ul[ U[ [S545(aXlg[U5Ulg)a5Initialize the tool selector. Args: model: Model to use for selection. If not provided, uses the agent's main model. Can be a model identifier string or `BaseChatModel` instance. system_prompt: Instructions for the selection model. max_tools: Maximum number of tools to select. If the model selects more, only the first `max_tools` will be used. If not specified, there is no limit. always_include: Tool names to always include regardless of selection. These do not count against the `max_tools` limit. N) super__init__rKrLrM isinstancer typer"r)selfr"rKrLrM __class__s r/rP"LLMToolSelectorMiddleware.__init__zsO4 *",2 emT$Z8 9 9/4J(/DJr.cUR(a[UR5S:XagURVs/sHn[U[5(aMUPM nnUR(aaUVs1sHo"R iM nnURVs/sH oUU;dM UPM nnU(aSUS[ U53n[U5eUVs/sH o"R UR;dMUPM" nnU(dgURn URbU SURS3- n [UR5Hn [U [5(dMU n O Sn[U5eUR=(d URn UVs/sHo"R PM n n[UU U U U S9$s snfs snfs snfs snfs snf) aGPrepare inputs for tool selection. Args: request: the model request. Returns: `SelectionRequest` with prepared inputs, or `None` if no selection is needed. Raises: ValueError: If tools in `always_include` are not found in the request. AssertionError: If no user message is found in the request messages. rNz.Tools in always_include not found in request: z. Available tools: z IMPORTANT: List the tool names in order of relevance, with the most relevant first. If you exceed the maximum number of tools, only the first z will be used.z)No user message found in request messages)rr r!r"r$)r5lenrQdictrMr8sorted ValueErrorrKrLreversedmessagesr r7r"r)rSrequestr; base_toolsavailable_tool_namesr8 missing_toolsr:rr messager!r"r$s r/_prepare_selection_request4LLMToolSelectorMiddleware._prepare_selection_requests"}}GMM 2a 7(/}}S}tJtT> % "#'..!1A N  0 01G'<00$+!2 >C % % +gmm2AB/$II/B +)/-   [T$F`6Cs/F;F;4G G&GG 6G Gc/n/nUSH[nXs;aURU5 MXu;dM"URb[U5UR:dMJURU5 M] U(aSU3n[U5eUV s/sHoRU;dMU PM n n UR V s/sH8n [ U [5(aMU RUR;dM6U PM: n n U RU 5 UR V s/sHn [ U [5(dMU PM n n UR/U QU QS9$s sn fs sn fs sn f)zBProcess the selection response and return filtered `ModelRequest`.r5zModel selected invalid tools: rF) appendrLrWrZr8r5rQrXrMextendoverride) rSresponserr$r]selected_tool_namesinvalid_tool_selections tool_namer:r;selected_toolsalways_included_toolsprovider_toolss r/_process_selection_response5LLMToolSelectorMiddleware._process_selection_responsesV*,"$!'*I0'..y93&#.A*BT^^*S#**95+ #23J2KLCS/ !-* ,T =P0PD_ *  1 %dD) .2ii4;N;N.N % 1 34,3==S=4JtTr json_schemar"with_structured_outputinvoker r!rQrXrRr7ror$ rSr]handlerselection_request type_adapterschemastructured_modelrhr:modified_requests r/wrap_model_call)LLMToolSelectorMiddleware.wrap_model_calls$!;;GD  $7# #77H7X7XY ))+,22II&Q#**!.?.N.NO!33  (D))0h0@AC % %;; 779J9[9[]d '((r.c # URU5nUcU"U5IShvN $[UR5nUR5nURR U5nUR SURS.UR/5IShvN n[U[5(dS[U53n[U5eURXsRURU5n U"U 5IShvN $NNkN7f)rrNrsrtrw)rbr>rrxr"ryainvoker r!rQrXrRr7ror$r{s r/awrap_model_call*LLMToolSelectorMiddleware.awrap_model_call=s$!;;GD  $ )) )77H7X7XY ))+,22II&Q)11!.?.N.NO!33   (D))0h0@AC % %;; 779J9[9[]d -...+* /s5 DC>A1DDA$D9D:DDD)rMrLr"rK) r"zstr | BaseChatModel | NonerKrrLz int | NonerMzlist[str] | NonereturnNone)r]ModelRequest[ContextT]rz_SelectionRequest | None) rhzdict[str, Any]rrr$r#r]rrr)r]rr|z-12 $+/ "0*"0 "0  "0 ) "0 "0"0HH -H !H T(J (J((J$ (J ( (J (JT))'))N)) . ))V)/')/Y)/ . )/)/r.rI)r5rrzTypeAdapter[Any])r5rrr),r+ __future__rlogging dataclassesrtypingrrrrr *langchain_core.language_models.chat_modelsr langchain_core.messagesr r pydanticr rtyping_extensionsr!langchain.agents.middleware.typesrrrrrrlangchain.chat_models.basercollections.abcrrlangchain.toolsr getLoggerr'loggerrrr>rGrIr%r.r/rs)"!@@D;''73(   8 $U      .D MI/ 90ExQZ0Z [I/r.