o iC @sddlmZddlmZmZddlmZmZddlm Z m Z m Z ddl m Z ddlmZddlmZmZmZmZmZmZmZddlmZmZdd lmZmZdd lmZdd l m!Z!dd l"m#Z#dd l$m%Z%ddl&m'Z'ddl(m)Z)m*Z*ddl+m,Z,m-Z-ddl.m/Z/ddl0m1Z1ddl2m3Z3ddl4m5Z5m6Z6ddl7m8Z8m9Z9m:Z:erddl;mZ>m?Z?gdZ@edZA edZB edZC ededZD eGdd d eZEe Gd!d"d"eeDZFe Gd#d$d$eeeAeBeCe1e,fZGd%S)&) annotations)ABCabstractmethod) AsyncIteratorSequence)KW_ONLYField dataclass)cached_property) HTTPStatus) TYPE_CHECKINGAnyClassVarGenericProtocolTypeVarruntime_checkable) BaseModelValidationError)DeferredToolRequestsDeferredToolResults) AbstractAgent) Instructions)AbstractBuiltinTool) UserError) ModelMessage)KnownModelNameModel) OutputDataT OutputSpec) ModelSettings) AgentDepsT)AbstractToolset)RunUsage UsageLimits) NativeEventOnCompleteFunc UIEventStream)Request)ResponseStreamingResponse) UIAdapter StateHandler StateDeps RunInputTMessageTEventTStateT)boundc@s8eZdZUdZded<ed ddZejd d dZd S)r-zeProtocol for state handlers in agent runs. Requires the class to be a dataclass with a `state` field.zClassVar[dict[str, Field[Any]]]__dataclass_fields__returnr cCdS)z'Get the current state of the agent run.Nselfr7r7]/var/www/html/karishye-ai-python/venv/lib/python3.10/site-packages/pydantic_ai/ui/_adapter.pystateEzStateHandler.stater;NonecCr6)zSet the state of the agent run. This method is called to update the state of the agent run with the provided state. Args: state: The run state. Nr7)r9r;r7r7r:r;Js N)r5r )r;r r5r=)__name__ __module__ __qualname____doc____annotations__propertyr;setterr7r7r7r:r-=s  r-c@seZdZUdZded<dS)r.ahDependency type that holds state. This class is used to manage the state of an agent run. It allows setting the state of the agent run with a specific type of state model, which must be a subclass of `BaseModel`. The state is set using the `state` setter by the `Adapter` when the run starts. Implements the `StateHandler` protocol. r2r;N)r>r?r@rArBr7r7r7r:r.Ws  r.c@sFeZdZUdZded< ded< ded<dZd ed < edUddZeedVddZ eedWddZ edXddZ e edYddZ e dZd d!Ze d[d#d$Z d\d]d*d+Zd^d-d.Zd_d0d1Zdddddddddd2ddd3 d`dLdMZdddddddddd2ddddN dadOdPZedddddddddd2ddddQ dbdSdTZdS)cr,aBase class for UI adapters. This class is responsible for transforming agent run input received from the frontend into arguments for [`Agent.run_stream_events()`][pydantic_ai.Agent.run_stream_events], running the agent, and then transforming Pydantic AI events into protocol-specific events. The event stream transformation is handled by a protocol-specific [`UIEventStream`][pydantic_ai.ui.UIEventStream] subclass. &AbstractAgent[AgentDepsT, OutputDataT]agentr/ run_inputr_Nz str | Noneacceptrequestr)r5?UIAdapter[RunInputT, MessageT, EventT, AgentDepsT, OutputDataT]cs(||||IdH|jddS)z!Create an adapter from a request.NrI)rFrGrI)build_run_inputbodyheadersget)clsrJrFr7r7r: from_request{s  zUIAdapter.from_requestrMbytescCt)zABuild a protocol-specific run input object from the request body.NotImplementedError)rPrMr7r7r:rLzUIAdapter.build_run_inputmessagesSequence[MessageT]list[ModelMessage]cCrS)z?Transform protocol-specific messages into Pydantic AI messages.rT)rPrWr7r7r: load_messagesrVzUIAdapter.load_messages9UIEventStream[RunInputT, EventT, AgentDepsT, OutputDataT]cCrS)z3Build a protocol-specific event stream transformer.rTr8r7r7r:build_event_streamr<zUIAdapter.build_event_streamcCrS)z:Pydantic AI messages from the protocol-specific run input.rTr8r7r7r:rWrVzUIAdapter.messages"AbstractToolset[AgentDepsT] | NonecCr6)zIToolset representing frontend tools from the protocol-specific run input.Nr7r8r7r7r:toolsetr<zUIAdapter.toolsetdict[str, Any] | NonecCr6)z4Frontend state from the protocol-specific run input.Nr7r8r7r7r:r;r<zUIAdapter.statestreamAsyncIterator[NativeEvent] on_completeOnCompleteFunc[EventT] | NoneAsyncIterator[EventT]cCs|j||dS)aTransform a stream of Pydantic AI events into protocol-specific events. Args: stream: The stream of Pydantic AI events to transform. on_complete: Optional callback function called when the agent run completes successfully. The callback receives the completed [`AgentRunResult`][pydantic_ai.agent.AgentRunResult] and can optionally yield additional protocol-specific events. rb)r\transform_stream)r9r`rbr7r7r:rfs zUIAdapter.transform_streamAsyncIterator[str]cC||S)zEncode a stream of protocol-specific events as strings according to the `Accept` header value. Args: stream: The stream of protocol-specific events to encode. )r\ encode_streamr9r`r7r7r:rizUIAdapter.encode_streamr+cCrh)zGenerate a streaming response from a stream of protocol-specific events. Args: stream: The stream of protocol-specific events to encode. )r\streaming_responserjr7r7r:rlrkzUIAdapter.streaming_responseT output_typemessage_historydeferred_tool_resultsmodel instructionsdepsmodel_settings usage_limitsusage infer_nametoolsets builtin_toolsrnOutputSpec[Any] | NoneroSequence[ModelMessage] | NonerpDeferredToolResults | Nonerq#Model | KnownModelName | str | NonerrInstructions[AgentDepsT]rsr!rtModelSettings | NoneruUsageLimits | NonervRunUsage | Nonerwboolrx,Sequence[AbstractToolset[AgentDepsT]] | Nonery$Sequence[AbstractBuiltinTool] | Nonec Csg|pg|j}|j} | r|p|jjtg}g| pg| } t|tr=|jp'i}t|jtr7t |j |}n|}||_n|jrKt dt |j d|jj ||||||||| | | | d S)aRun the agent with the protocol-specific run input and stream Pydantic AI events. Args: 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. instructions: Optional additional instructions to use for this run. 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 to use for this run. z&State is provided but `deps` of type `zo` does not implement the `StateHandler` protocol: it needs to be a dataclass with a non-optional `state` field.) rnrorprqrsrtrrrurvrwrxry)rWr^rFrnr isinstancer-r;rtypemodel_validaterr>run_stream_events)r9rnrorprqrrrsrtrurvrwrxryr^ raw_stater;r7r7r:run_stream_natives:!   zUIAdapter.run_stream_native) rnrorprqrrrsrtrurvrwrxryrbc Cs,|j|j||||||||| | | | d | dS)aRun the agent with the protocol-specific run input and stream protocol-specific events. Args: 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. instructions: Optional additional instructions to use for this run. 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 to use 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 optionally yield additional protocol-specific events. rmre)rfr)r9rnrorprqrrrsrtrurvrwrxryrbr7r7r: run_stream s"$zUIAdapter.run_stream) rorprqrrrsrnrtrurvrwrxryrbr*cszddlm}Wnty}ztd|d}~wwz |j||dIdH}WntyC}z||dtjdWYd}~Sd}~ww||j ||||||| | | | | ||d S) a"Handle a protocol-specific HTTP request by running the agent and returning a streaming response of protocol-specific events. Args: request: The incoming Starlette/FastAPI request. 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. instructions: Optional additional instructions to use for this run. 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 to use 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 optionally yield additional protocol-specific events. Returns: A streaming Starlette response with protocol-specific events encoded per the request's `Accept` header value. r)r*uPlease install the `starlette` package to use `dispatch_request()` method, you can use the `ui` optional group — `pip install "pydantic-ai-slim[ui]"`N)rFzapplication/json)content media_type status_code) rorprsrnrqrrrtrurvrwrxryrb) starlette.responsesr* ImportErrorrQrjsonr UNPROCESSABLE_ENTITYrlr)rPrJrFrorprqrrrsrnrtrurvrwrxryrbr*eadapterr7r7r:dispatch_request?sL,zUIAdapter.dispatch_request)rJr)rFrEr5rK)rMrRr5r/)rWrXr5rY)r5r[)r5rY)r5r])r5r_)N)r`rarbrcr5rd)r`rdr5rg)r`rdr5r+)rnrzror{rpr|rqr}rrr~rsr!rtrrurrvrrwrrxrryrr5ra)rnrzror{rpr|rqr}rrr~rsr!rtrrurrvrrwrrxrryrrbrcr5rd) rJr)rFrEror{rpr|rqr}rrr~rsr!rnrzrtrrurrvrrwrrxrryrrbrcr5r*)r>r?r@rArBrI classmethodrQrrLrZr\r rWr^r;rfrirlrrrr7r7r7r:r,gs          G6r,N)H __future__rabcrrcollections.abcrr dataclassesrrr functoolsr httpr typingr r rrrrrpydanticrr pydantic_airrpydantic_ai.agentrpydantic_ai.agent.abstractrpydantic_ai.builtin_toolsrpydantic_ai.exceptionsrpydantic_ai.messagesrpydantic_ai.modelsrrpydantic_ai.outputrrpydantic_ai.settingsr pydantic_ai.toolsr!pydantic_ai.toolsetsr"pydantic_ai.usager#r$ _event_streamr&r'r(starlette.requestsr)rr*r+__all__r/r0r1r2r-r.r,r7r7r7r:sN   $           &