o i @s~dZddlmZddlmZmZmZddlmZddl m Z m Z ddl m Z ddlmZddlmZdd lmZdd lmZdd lmZmZdd lmZmZdd lmZddlmZddl m!Z!ddl"m#Z#m$Z$ddl%m&Z&m'Z'ddl(m)Z)z(ddl*m+Z+ddl,m-Z-ddl.m/Z/ddl0m1Z1ddl2m3Z3ddl4m5Z5m6Z6Wne7yZ8ze7de8dZ8[8wwGddde eefe+Z9dS)z2AG-UI protocol integration for Pydantic AI agents.) annotations)CallableMappingSequence)replace)AnyGeneric)Self)DeferredToolResults) AbstractAgent)AbstractBuiltinTool) ModelMessage)KnownModelNameModel) OutputDataT OutputSpec) ModelSettings) AgentDepsT)AbstractToolset)RunUsage UsageLimits)OnCompleteFunc StateHandler) AGUIAdapter) Starlette) Middleware)Request)Response) BaseRoute)ExceptionHandlerLifespanuPlease install the `starlette` package to use `AGUIApp`, you can use the `ag-ui` optional group — `pip install "pydantic-ai-slim[ag-ui]"`NcsLeZdZdZddddddddddddddddddddd0fd.d/ZZS)1AGUIAppzLASGI application for running Pydantic AI agents with AG-UI protocol support.NTF) output_typemessage_historydeferred_tool_resultsmodeldepsmodel_settings usage_limitsusage infer_nametoolsets builtin_tools on_completedebugroutes middlewareexception_handlers on_startup on_shutdownlifespanagent&AbstractAgent[AgentDepsT, OutputDataT]r$OutputSpec[Any] | Noner%Sequence[ModelMessage] | Noner&DeferredToolResults | Noner'#Model | KnownModelName | str | Noner(rr)ModelSettings | Noner*UsageLimits | Noner+RunUsage | Noner,boolr-,Sequence[AbstractToolset[AgentDepsT]] | Noner.$Sequence[AbstractBuiltinTool] | Noner/OnCompleteFunc[Any] | Noner0r1Sequence[BaseRoute] | Noner2Sequence[Middleware] | Noner3%Mapping[Any, ExceptionHandler] | Noner4"Sequence[Callable[[], Any]] | Noner5r6Lifespan[Self] | NonereturnNonecsXtj|||||||dd  f dd }|jjd|d gd d S) asAn ASGI application that handles every request by running the agent and streaming the response. Note that the `deps` will be the same for each request, with the exception of the frontend state that's injected into the `state` field of a `deps` object that implements the [`StateHandler`][pydantic_ai.ui.StateHandler] protocol. To provide different `deps` for each request (e.g. based on the authenticated user), use [`AGUIAdapter.run_stream()`][pydantic_ai.ui.ag_ui.AGUIAdapter.run_stream] or [`AGUIAdapter.dispatch_request()`][pydantic_ai.ui.ag_ui.AGUIAdapter.dispatch_request] instead. Args: agent: The agent to run. output_type: Custom output type to use for this run, `output_type` may only be used if the agent has no output validators since output validators would expect an argument that matches the agent's output type. message_history: History of the conversation so far. deferred_tool_results: Optional results for deferred tool calls in the message history. model: Optional model to use for this run, required if `model` was not set when creating the agent. deps: Optional dependencies to use for this run. model_settings: Optional settings to use for this model's request. usage_limits: Optional limits on model request count or token usage. usage: Optional usage to start with, useful for resuming a conversation or agents used in tools. infer_name: Whether to try to infer the agent name from the call frame if it's not set. toolsets: Optional additional toolsets for this run. builtin_tools: Optional additional builtin tools for this run. on_complete: Optional callback function called when the agent run completes successfully. The callback receives the completed [`AgentRunResult`][pydantic_ai.agent.AgentRunResult] and can access `all_messages()` and other result data. debug: Boolean indicating if debug tracebacks should be returned on errors. routes: A list of routes to serve incoming HTTP and WebSocket requests. middleware: A list of middleware to run for every request. A starlette application will always automatically include two middleware classes. `ServerErrorMiddleware` is added as the very outermost middleware, to handle any uncaught errors occurring anywhere in the entire stack. `ExceptionMiddleware` is added as the very innermost middleware, to deal with handled exception cases occurring in the routing or endpoints. exception_handlers: A mapping of either integer status codes, or exception class types onto callables which handle the exceptions. Exception handler callables should be of the form `handler(request, exc) -> response` and may be either standard functions, or async functions. on_startup: A list of callables to run on application startup. Startup handler callables do not take any arguments, and may be either standard functions, or async functions. on_shutdown: A list of callables to run on application shutdown. Shutdown handler callables do not take any arguments, and may be either standard functions, or async functions. lifespan: A lifespan context function, which can be used to perform startup and shutdown tasks. This is a newer style that replaces the `on_startup` and `on_shutdown` handlers. Use one or the other, not both. )r0r1r2r3r4r5r6requestrrIrcsHttr ttttfj|   dIdHS)z7Endpoint to run the agent with the provided input data.) r7r$r%r&r'r(r)r*r+r,r-r.r/N) isinstancerrrrrdispatch_request)rK r7r.r&r(r,r%r'r)r/r$r-r+r*^/var/www/html/karishye-ai-python/venv/lib/python3.10/site-packages/pydantic_ai/ui/ag_ui/app.py run_agent{s&   z#AGUIApp.__init__..run_agent/POST)methodsN)rKrrIr)super__init__router add_route)selfr7r$r%r&r'r(r)r*r+r,r-r.r/r0r1r2r3r4r5r6rQ __class__rNrPrV*sG& zAGUIApp.__init__)*r7r8r$r9r%r:r&r;r'r<r(rr)r=r*r>r+r?r,r@r-rAr.rBr/rCr0r@r1rDr2rEr3rFr4rGr5rGr6rHrIrJ)__name__ __module__ __qualname____doc__rV __classcell__rOrOrZrPr#'s,r#):r_ __future__rcollections.abcrrr dataclassesrtypingrrtyping_extensionsr pydantic_air pydantic_ai.agentr pydantic_ai.builtin_toolsr pydantic_ai.messagesr pydantic_ai.modelsrrpydantic_ai.outputrrpydantic_ai.settingsrpydantic_ai.toolsrpydantic_ai.toolsetsrpydantic_ai.usagerrrr_adapterrstarlette.applicationsrstarlette.middlewarerstarlette.requestsrstarlette.responsesrstarlette.routingr starlette.typesr!r" ImportErrorer#rOrOrOrPsD