o iO@sLUddlmZddlmZmZmZddlmZm Z m Z ddl m Z m Z mZmZmZmZmZddlmZmZddlmZmZddlmZmZddlmZmZmZd d l m!Z!m"Z"d d l#m$Z$m%Z%d d l&m'Z'd d l(m)Z)m*Z*m+Z+dZ,edddZ- ee%e$ge.fee%e$gee.fBege.fBegee.fBZ/de0d< eee%e$e-fe fZ1de0d< ee-e fZ2de0d< e1e$e-fe2e-BZ3de0d< ee%e$dgedfZ4de0d< ee%e$e5dgedfZ6de0d< edZ7de0d< e ddGd d!d!Z8e ddGd"d#d#Z9e Gd$d%d%Z:dCd*d+Z;e e9e:Bed,fZ e ddGd2d3d3Z?ed4Z@Gd5d6d6eZAed7eBdd8ZC e d9d:Gd;d<dZGde0d?< e d9dd@GdAddZHdBS)D) annotations) AwaitableCallableSequence)KW_ONLY dataclassfield) AnnotatedAny ConcatenateGenericLiteral TypeAliascast) DiscriminatorTag)GenerateJsonSchemaJsonSchemaValue)SchemaValidator core_schema) ParamSpecSelfTypeVar)_function_schema_utils) AgentDepsT RunContext) ModelRetry)RetryPromptPart ToolCallPart ToolReturn)rDocstringFormatrSystemPromptFuncToolFuncContext ToolFuncPlainToolFuncEither ToolParamsToolPrepareFuncToolsPrepareFuncToolObjectJsonSchemaToolDefinitionDeferredToolRequestsDeferredToolResults ToolApproved ToolDeniedr'.defaultrr#r$r%r&r,ToolDefinition | Noner(zlist[ToolDefinition] | Noner))googlenumpysphinxautor"T)kw_onlyc@s8eZdZUdZeedZded< eedZded<dS)r-aTool calls that require approval or external execution. This can be used as an agent's `output_type` and will be used as the output of the agent run if the model called any deferred tools. Results can be passed to the next agent run using a [`DeferredToolResults`][pydantic_ai.tools.DeferredToolResults] object with the same tool call IDs. See [deferred tools docs](../deferred-tools.md#deferred-tools) for more information. default_factoryzlist[ToolCallPart]calls approvalsN) __name__ __module__ __qualname____doc__rlistr;__annotations__r<rCrCW/var/www/html/karishye-ai-python/venv/lib/python3.10/site-packages/pydantic_ai/tools.pyr-s  r-c@s,eZdZUdZdZded< dZded<dS)r/z[Indicates that a tool call has been approved and that the tool function should be executed.Ndict[str, Any] | None override_argsz tool-approvedzLiteral['tool-approved']kind)r=r>r?r@rFrBrGrCrCrCrDr/s  r/c@s4eZdZUdZdZded< ded<dZded <d S) r0zeIndicates that a tool call has been denied and that a denial message should be returned to the model.zThe tool call was denied.strmessager_z tool-deniedzLiteral['tool-denied']rGN)r=r>r?r@rIrBrGrCrCrCrDr0s  r0xr return str | NonecCsjt|trd|vrtt|dSd|vrtt|dSdSt|dr(tt|jSt|dr3tt|jSdS)NrG part_kind) isinstancedictrrHhasattrrGrN)rKrCrCrD(_deferred_tool_call_result_discriminators    rRrGDeferredToolApprovalResultz tool-returnz model-retryz retry-promptDeferredToolCallResultc@s8eZdZUdZeedZded< eedZded<dS)r.a[Results for deferred tool calls from a previous run that required approval or external execution. 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Example usage: ```python {noqa="I001"} from pydantic_ai import Agent, RunContext, Tool async def my_tool(ctx: RunContext[int], x: int, y: int) -> str: return f'{ctx.deps} {x} {y}' agent = Agent('test', tools=[Tool(my_tool)]) ``` or with a custom prepare method: ```python {noqa="I001"} from pydantic_ai import Agent, RunContext, Tool from pydantic_ai.tools import ToolDefinition async def my_tool(ctx: RunContext[int], x: int, y: int) -> str: return f'{ctx.deps} {x} {y}' async def prep_my_tool( ctx: RunContext[int], tool_def: ToolDefinition ) -> ToolDefinition | None: # only register the tool if `deps == 42` if ctx.deps == 42: return tool_def agent = Agent('test', tools=[Tool(my_tool, prepare=prep_my_tool)]) ``` Args: function: The Python function to call as the tool. takes_ctx: Whether the function takes a [`RunContext`][pydantic_ai.tools.RunContext] first argument, this is inferred if unset. max_retries: Maximum number of retries allowed for this tool, set to the agent default if `None`. name: Name of the tool, inferred from the function if `None`. description: Description of the tool, inferred from the function if `None`. prepare: custom method to prepare the tool definition for each step, return `None` to omit this tool from a given step. This is useful if you want to customise a tool at call time, or omit it completely from a step. See [`ToolPrepareFunc`][pydantic_ai.tools.ToolPrepareFunc]. docstring_format: The format of the docstring, see [`DocstringFormat`][pydantic_ai.tools.DocstringFormat]. Defaults to `'auto'`, such that the format is inferred from the structure of the docstring. require_parameter_descriptions: If True, raise an error if a parameter description is missing. Defaults to False. schema_generator: The JSON schema generator class to use. Defaults to `GenerateToolJsonSchema`. strict: Whether to enforce JSON schema compliance (only affects OpenAI). See [`ToolDefinition`][pydantic_ai.tools.ToolDefinition] for more info. sequential: Whether the function requires a sequential/serial execution environment. Defaults to False. requires_approval: Whether this tool requires human-in-the-loop approval. Defaults to False. See the [tools documentation](../deferred-tools.md#human-in-the-loop-tool-approval) for more info. metadata: Optional metadata for the tool. This is not sent to the model but can be used for filtering and tool behavior customization. function_schema: The function schema to use for the tool. If not provided, it will be generated. )rxrrN)rvrrrxrzr=r{r|r~rrrrrr)rdrvrxrzr{r|r~rrrrrrrrrCrCrD__init__s&J   z Tool.__init__Callable[..., Any]rerrLrc Cs:tj||ttd||t|d}|||||||dS)awCreates a Pydantic tool from a function and a JSON schema. Args: function: The function to call. This will be called with keywords only, and no validation of the arguments will be performed. name: The unique name of the tool that clearly communicates its purpose description: Used to tell the model how/when/why to use the tool. 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