o i> @sdZddlmZddlmZmZddlmZddlm Z ddl m Z ddl m Z dd lmZmZdd lmZdd lmZdd lmZdd lmZddlmZmZz2ddlmZddlmZddl m!Z!ddl"m#Z#ddl$m%Z%m&Z&m'Z'm(Z(ddl)m*Z*ddl+m,Z,Wne-yZ.ze-de.dZ.[.wwgdZ/dddddddddddd d@d7d8Z0e%fdddddddddddd dAd>d?Z1dS)BzProvides an AG-UI protocol adapter for the Pydantic AI agent. This package provides seamless integration between pydantic-ai agents and ag-ui for building interactive AI applications with streaming event-based communication. ) annotations) AsyncIteratorSequence)Any)DeferredToolResults) AbstractAgent) ModelMessage)KnownModelNameModel) OutputSpec) ModelSettings) AgentDepsT)AbstractToolset)RunUsage UsageLimits) BaseEvent) RunAgentInput)Request)Response)SSE_CONTENT_TYPEOnCompleteFunc StateDeps StateHandler) AGUIAdapter)AGUIAppuPlease install the `ag-ui-protocol` and `starlette` packages to use `AGUIAdapter`, you can use the `ag-ui` optional group — `pip install "pydantic-ai-slim[ag-ui]"`N)rrrrrhandle_ag_ui_request run_ag_uiT output_typemessage_historydeferred_tool_resultsmodeldepsmodel_settings usage_limitsusage infer_nametoolsets on_completeagentAbstractAgent[AgentDepsT, Any]requestrrOutputSpec[Any] | Noner Sequence[ModelMessage] | Noner!DeferredToolResults | Noner"#Model | KnownModelName | str | Noner#rr$ModelSettings | Noner%UsageLimits | Noner&RunUsage | Noner'boolr(,Sequence[AbstractToolset[AgentDepsT]] | Noner) OnCompleteFunc[BaseEvent] | Nonereturnrc s0ttj|||||||||| | | | d IdHS)aHandle an AG-UI request by running the agent and returning a streaming response. Args: agent: The agent to run. request: The Starlette request (e.g. from FastAPI) containing the AG-UI run input. 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. 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. Returns: A streaming Starlette response with AG-UI protocol events. ) r*r#rr r!r"r$r%r&r'r(r)N)rrdispatch_request) r*r,rr r!r"r#r$r%r&r'r(r)r9W/var/www/html/karishye-ai-python/venv/lib/python3.10/site-packages/pydantic_ai/ag_ui.pyr3s ' r run_inputracceptstrAsyncIterator[str]c Cs4t|||d}||j||||||| | | | | d S)a+Run the agent with the AG-UI run input and stream AG-UI protocol events. Args: agent: The agent to run. run_input: The AG-UI run input containing thread_id, run_id, messages, etc. accept: The accept header value for the 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. 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. Yields: Streaming event chunks encoded as strings according to the accept header value. )r*r;r<r)r encode_stream run_stream)r*r;r<rr r!r"r#r$r%r&r'r(r)adapterr9r9r:rks )r)r*r+r,rrr-r r.r!r/r"r0r#rr$r1r%r2r&r3r'r4r(r5r)r6r7r)r*r+r;rr<r=rr-r r.r!r/r"r0r#rr$r1r%r2r&r3r'r4r(r5r)r6r7r>)2__doc__ __future__rcollections.abcrrtypingrrr*rmessagesr modelsr r outputr settingsr toolsrr(rr&rr ag_ui.corerag_ui.core.typesrstarlette.requestsrstarlette.responsesruirrrrui.ag_uir ui.ag_ui.appr ImportErrore__all__rrr9r9r9r:sp              ;