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Merge branch 'main' into fix/mcp-allowed-tools-empty-list-handling
This commit is contained in:
Giles Odigwe
GitHub
@@ -56,7 +56,7 @@ agent_framework/
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- **`AgentMiddleware`** - Intercepts agent `run()` calls
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- **`ChatMiddleware`** - Intercepts chat client `get_response()` calls
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- **`FunctionMiddleware`** - Intercepts function/tool invocations
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- **`AgentContext`** / **`ChatContext`** / **`FunctionInvocationContext`** - Context objects passed through middleware
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- **`AgentContext`** / **`ChatContext`** / **`FunctionInvocationContext`** - Context objects passed through middleware. A tool can declare a `FunctionInvocationContext` parameter to receive it; `context.tools` is the live, mutable tools list for the run, and `context.add_tools(...)` / `context.remove_tools(...)` enable progressive tool exposure (changes apply on the next function-calling iteration).
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### Sessions (`_sessions.py`)
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@@ -58,6 +58,7 @@ class ExperimentalFeature(str, Enum):
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FOUNDRY_PREVIEW_TOOLS = "FOUNDRY_PREVIEW_TOOLS"
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FUNCTIONAL_WORKFLOWS = "FUNCTIONAL_WORKFLOWS"
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HARNESS = "HARNESS"
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PROGRESSIVE_TOOLS = "PROGRESSIVE_TOOLS"
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SKILLS = "SKILLS"
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TO_PROMPT_AGENT = "TO_PROMPT_AGENT"
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@@ -11,6 +11,7 @@ from enum import Enum
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from typing import TYPE_CHECKING, Any, Generic, Literal, TypeAlias, cast, overload
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from ._clients import SupportsChatGetResponse
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from ._feature_stage import ExperimentalFeature, experimental
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from ._types import (
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AgentResponse,
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AgentResponseUpdate,
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@@ -214,6 +215,12 @@ class FunctionInvocationContext:
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result: Function execution result. Can be observed after calling ``call_next()``
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to see the actual execution result or can be set to override the execution result.
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kwargs: Additional runtime keyword arguments forwarded to the function invocation.
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tools: The live, mutable list of tools available to the model for the current
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agent run, or ``None`` when the function is invoked outside of a
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function-calling loop (for example via ``FunctionTool.invoke`` directly).
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Tools can add or remove tools during execution using :meth:`add_tools`
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and :meth:`remove_tools` (progressive tool exposure). Mutations take
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effect on the **next** model iteration, not the in-flight batch.
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Examples:
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.. code-block:: python
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@@ -232,6 +239,18 @@ class FunctionInvocationContext:
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# Continue execution
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await call_next()
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Progressive tool exposure from inside a tool:
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.. code-block:: python
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from agent_framework import FunctionInvocationContext, tool
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@tool(approval_mode="never_require")
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def load_math_tools(ctx: FunctionInvocationContext) -> str:
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ctx.add_tools([factorial, fibonacci])
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return "Math tools are now available."
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"""
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def __init__(
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@@ -242,6 +261,7 @@ class FunctionInvocationContext:
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metadata: Mapping[str, Any] | None = None,
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result: Any = None,
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kwargs: Mapping[str, Any] | None = None,
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tools: list[ToolTypes] | None = None,
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) -> None:
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"""Initialize the FunctionInvocationContext.
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@@ -252,6 +272,9 @@ class FunctionInvocationContext:
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metadata: Metadata dictionary for sharing data between function middleware.
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result: Function execution result.
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kwargs: Additional runtime keyword arguments forwarded to the function invocation.
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tools: The live, mutable list of tools for the current agent run. When provided,
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this is the same list object the model sees on the next iteration, so
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appending or removing tools changes the model's available tools.
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"""
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self.function = function
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self.arguments = arguments
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@@ -259,6 +282,96 @@ class FunctionInvocationContext:
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self.metadata: dict[str, Any] = dict(metadata) if metadata is not None else {}
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self.result = result
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self.kwargs: dict[str, Any] = dict(kwargs) if kwargs is not None else {}
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self.tools = tools
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@experimental(feature_id=ExperimentalFeature.PROGRESSIVE_TOOLS)
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def add_tools(
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self,
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tools: ToolTypes | Callable[..., Any] | Sequence[ToolTypes | Callable[..., Any]],
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) -> None:
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"""Add one or more tools to the current agent run (progressive tool exposure).
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Callable inputs are converted to :class:`FunctionTool`, and tool collections are
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flattened, using the same normalization as the rest of the framework. Added tools
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become available to the model on the **next** iteration of the function-calling
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loop; they do not affect tool calls already requested in the in-flight batch.
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Adding a tool whose name already exists is a no-op when it is the same object, and
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raises ``ValueError`` when it is a different object with a duplicate name.
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Args:
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tools: A single tool/callable or a sequence of tools/callables to add.
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Raises:
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RuntimeError: If the context has no live tools list (for example when the
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function is invoked outside of a function-calling loop).
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ValueError: If a different tool with a duplicate name is added.
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"""
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from ._tools import _append_unique_tools, normalize_tools # type: ignore[reportPrivateUsage]
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if self.tools is None:
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raise RuntimeError(
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"Cannot add tools: this FunctionInvocationContext is not bound to a live "
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"agent run. add_tools is only available for functions invoked within an "
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"agent's function-calling loop."
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)
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# Validate the whole batch against a throwaway copy first, so a duplicate-name
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# clash partway through the batch raises before the live tool list is mutated
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# (all-or-nothing semantics).
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merged = _append_unique_tools(list(self.tools), normalize_tools(tools))
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self.tools[:] = merged
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@experimental(feature_id=ExperimentalFeature.PROGRESSIVE_TOOLS)
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def remove_tools(
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self,
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tools: ToolTypes | Callable[..., Any] | Sequence[ToolTypes | Callable[..., Any]] | str | Sequence[str],
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) -> None:
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"""Remove one or more tools from the current agent run (progressive tool exposure).
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Tools may be specified by name, by tool object, or by the original callable. Names
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that are not currently present are ignored. Removals take effect on the **next**
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iteration of the function-calling loop; tool calls already requested in the
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in-flight batch still execute.
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Args:
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tools: A tool name, tool/callable, or a sequence of any of these to remove.
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Raises:
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RuntimeError: If the context has no live tools list (for example when the
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function is invoked outside of a function-calling loop).
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"""
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from ._tools import _get_tool_name, normalize_tools # type: ignore[reportPrivateUsage]
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if self.tools is None:
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raise RuntimeError(
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"Cannot remove tools: this FunctionInvocationContext is not bound to a live "
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"agent run. remove_tools is only available for functions invoked within an "
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"agent's function-calling loop."
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)
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names_to_remove: set[str] = set()
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raw_items: list[Any]
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if isinstance(tools, str):
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raw_items = [tools]
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elif isinstance(tools, Sequence) and not isinstance(tools, (bytes, bytearray)):
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raw_items = list(cast("Sequence[Any]", tools))
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else:
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raw_items = [tools]
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for item in raw_items:
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if isinstance(item, str):
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names_to_remove.add(item)
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continue
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for normalized in normalize_tools(item):
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if name := _get_tool_name(normalized): # type: ignore[reportPrivateUsage]
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names_to_remove.add(name)
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if not names_to_remove:
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return
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self.tools[:] = [
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tool
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for tool in self.tools
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if _get_tool_name(tool) not in names_to_remove # type: ignore[reportPrivateUsage]
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]
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class ChatContext:
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@@ -1418,6 +1418,7 @@ async def _auto_invoke_function(
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sequence_index: int | None = None,
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request_index: int | None = None,
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middleware_pipeline: FunctionMiddlewarePipeline | None = None,
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live_tools: list[ToolTypes] | None = None,
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) -> Content:
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"""Invoke a function call requested by the agent, applying middleware that is defined.
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@@ -1432,6 +1433,8 @@ async def _auto_invoke_function(
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sequence_index: The index of the function call in the sequence.
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request_index: The index of the request iteration.
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middleware_pipeline: Optional middleware pipeline to apply during execution.
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live_tools: The live, mutable tools list for the current agent run, exposed on
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the FunctionInvocationContext so tools can add/remove tools at runtime.
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Returns:
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The function result content.
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@@ -1523,6 +1526,7 @@ async def _auto_invoke_function(
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arguments=args,
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session=invocation_session,
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kwargs=runtime_kwargs.copy(),
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tools=live_tools,
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)
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function_result = await tool.invoke(
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arguments=args,
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@@ -1537,6 +1541,10 @@ async def _auto_invoke_function(
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except UserInputRequiredException:
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raise
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except Exception as exc:
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logger.warning(
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f"Function '{tool.name}' raised an exception; returning an error result to the "
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f"model. Set include_detailed_errors=True for the full detail. Exception: {exc!r}"
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)
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message = "Error: Function failed."
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if config.get("include_detailed_errors", False):
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message = f"{message} Exception: {exc}"
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@@ -1552,6 +1560,7 @@ async def _auto_invoke_function(
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arguments=args,
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session=invocation_session,
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kwargs=runtime_kwargs.copy(),
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tools=live_tools,
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)
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call_id = function_call_content.call_id
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@@ -1608,6 +1617,10 @@ async def _auto_invoke_function(
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except UserInputRequiredException:
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raise
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except Exception as exc:
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logger.warning(
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f"Function '{tool.name}' raised an exception; returning an error result to the "
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f"model. Set include_detailed_errors=True for the full detail. Exception: {exc!r}"
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)
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message = "Error: Function failed."
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if config.get("include_detailed_errors", False):
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message = f"{message} Exception: {exc}"
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@@ -1659,6 +1672,9 @@ async def _try_execute_function_calls(
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from ._types import Content
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tool_map = _get_tool_map(tools)
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# The live tools list (when tools is the run-local list) is exposed on the
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# FunctionInvocationContext so tools can add/remove tools during the run.
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live_tools: list[ToolTypes] | None = cast("list[ToolTypes]", tools) if isinstance(tools, list) else None
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approval_tools = [tool_name for tool_name, tool in tool_map.items() if tool.approval_mode == "always_require"]
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logger.debug(
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"_try_execute_function_calls: tool_map keys=%s, approval_tools=%s",
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@@ -1733,6 +1749,7 @@ async def _try_execute_function_calls(
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request_index=attempt_idx,
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middleware_pipeline=middleware_pipeline,
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config=config,
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live_tools=live_tools,
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)
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return (result, False)
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except MiddlewareTermination as exc:
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@@ -2371,6 +2388,13 @@ class FunctionInvocationLayer(Generic[OptionsCoT]):
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function_invocation_kwargs=function_invocation_kwargs,
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client_kwargs=filtered_kwargs,
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)
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# Establish a single, run-local mutable tools list so that tools can add or remove
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# tools during the run (progressive tool exposure). A fresh list is created via
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# normalize_tools so the caller's original tools container is never mutated, while
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# the same list object is shared with the model (options["tools"]) and the tool map
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# rebuilt on every loop iteration.
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if mutable_options.get("tools"):
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mutable_options["tools"] = normalize_tools(mutable_options["tools"])
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if not stream:
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async def _get_response() -> ChatResponse[Any]:
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@@ -3975,3 +3975,425 @@ async def test_user_input_request_empty_contents_returns_fallback(chat_client_ba
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]
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assert len(function_results) >= 1
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assert any("user input" in (fr.result or "").lower() for fr in function_results)
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# region Progressive tool exposure (FunctionInvocationContext.add_tools / remove_tools)
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def _pte_function_call_response(call_id: str, name: str, arguments: str = "{}") -> ChatResponse:
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return ChatResponse(
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messages=Message(
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role="assistant",
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contents=[Content.from_function_call(call_id=call_id, name=name, arguments=arguments)],
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)
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)
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def _pte_text_response(text: str = "done") -> ChatResponse:
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return ChatResponse(messages=Message(role="assistant", contents=[text]))
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@tool(name="factorial", approval_mode="never_require")
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def _pte_factorial(n: int) -> int:
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"""Compute the factorial of n."""
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result = 1
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for value in range(2, n + 1):
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result *= value
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return result
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async def test_context_exposes_live_tools(chat_client_base: SupportsChatGetResponse):
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from agent_framework import FunctionTool
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seen_names: list[str] = []
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@tool(name="inspect_tools", approval_mode="never_require")
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def inspect_tools(ctx: FunctionInvocationContext) -> str:
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assert ctx.tools is not None
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seen_names.extend(t.name for t in ctx.tools if isinstance(t, FunctionTool))
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return "inspected"
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chat_client_base.run_responses = [
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_pte_function_call_response("1", "inspect_tools"),
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_pte_text_response(),
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]
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await chat_client_base.get_response(
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[Message(role="user", contents=["hi"])],
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options={"tool_choice": "auto", "tools": [inspect_tools]},
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)
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assert "inspect_tools" in seen_names
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|
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async def test_add_tools_available_next_iteration(chat_client_base: SupportsChatGetResponse):
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exec_counter = 0
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|
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@tool(name="factorial", approval_mode="never_require")
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def factorial(n: int) -> int:
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nonlocal exec_counter
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exec_counter += 1
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return 120
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|
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@tool(name="load_math", approval_mode="never_require")
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def load_math(ctx: FunctionInvocationContext) -> str:
|
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ctx.add_tools(factorial)
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return "math tools loaded"
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chat_client_base.function_invocation_configuration["max_iterations"] = 3 # type: ignore[attr-defined]
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chat_client_base.run_responses = [
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_pte_function_call_response("1", "load_math"),
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_pte_function_call_response("2", "factorial", '{"n": 5}'),
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_pte_text_response(),
|
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]
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response = await chat_client_base.get_response(
|
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[Message(role="user", contents=["compute 5!"])],
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options={"tool_choice": "auto", "tools": [load_math]},
|
||||
)
|
||||
assert exec_counter == 1
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||||
assert response.messages[-1].text == "done"
|
||||
|
||||
|
||||
async def test_add_tools_model_sees_added_tools_in_options(chat_client_base: SupportsChatGetResponse):
|
||||
from agent_framework import FunctionTool
|
||||
|
||||
recorded: list[list[str]] = []
|
||||
client_cls = type(chat_client_base)
|
||||
original = client_cls._get_non_streaming_response
|
||||
|
||||
async def recording(self: Any, *, messages: Any, options: dict[str, Any], **kwargs: Any) -> ChatResponse:
|
||||
tools = options.get("tools") or []
|
||||
recorded.append([t.name for t in tools if isinstance(t, FunctionTool)])
|
||||
return await original(self, messages=messages, options=options, **kwargs)
|
||||
|
||||
@tool(name="load_math", approval_mode="never_require")
|
||||
def load_math(ctx: FunctionInvocationContext) -> str:
|
||||
ctx.add_tools(_pte_factorial)
|
||||
return "loaded"
|
||||
|
||||
chat_client_base.function_invocation_configuration["max_iterations"] = 3 # type: ignore[attr-defined]
|
||||
chat_client_base.run_responses = [
|
||||
_pte_function_call_response("1", "load_math"),
|
||||
_pte_function_call_response("2", "factorial", '{"n": 5}'),
|
||||
_pte_text_response(),
|
||||
]
|
||||
monkey = pytest.MonkeyPatch()
|
||||
monkey.setattr(client_cls, "_get_non_streaming_response", recording)
|
||||
try:
|
||||
await chat_client_base.get_response(
|
||||
[Message(role="user", contents=["compute 5!"])],
|
||||
options={"tool_choice": "auto", "tools": [load_math]},
|
||||
)
|
||||
finally:
|
||||
monkey.undo()
|
||||
|
||||
assert recorded[0] == ["load_math"]
|
||||
assert "factorial" in recorded[1]
|
||||
|
||||
|
||||
async def test_remove_tools_next_iteration(chat_client_base: SupportsChatGetResponse):
|
||||
from agent_framework import FunctionTool
|
||||
|
||||
recorded: list[list[str]] = []
|
||||
client_cls = type(chat_client_base)
|
||||
original = client_cls._get_non_streaming_response
|
||||
|
||||
async def recording(self: Any, *, messages: Any, options: dict[str, Any], **kwargs: Any) -> ChatResponse:
|
||||
tools = options.get("tools") or []
|
||||
recorded.append([t.name for t in tools if isinstance(t, FunctionTool)])
|
||||
return await original(self, messages=messages, options=options, **kwargs)
|
||||
|
||||
@tool(name="get_weather", approval_mode="never_require")
|
||||
def get_weather(location: str) -> str:
|
||||
return "sunny"
|
||||
|
||||
@tool(name="drop_weather", approval_mode="never_require")
|
||||
def drop_weather(ctx: FunctionInvocationContext) -> str:
|
||||
ctx.remove_tools("get_weather")
|
||||
return "removed"
|
||||
|
||||
chat_client_base.function_invocation_configuration["max_iterations"] = 3 # type: ignore[attr-defined]
|
||||
chat_client_base.run_responses = [
|
||||
_pte_function_call_response("1", "drop_weather"),
|
||||
_pte_text_response(),
|
||||
]
|
||||
monkey = pytest.MonkeyPatch()
|
||||
monkey.setattr(client_cls, "_get_non_streaming_response", recording)
|
||||
try:
|
||||
await chat_client_base.get_response(
|
||||
[Message(role="user", contents=["hi"])],
|
||||
options={"tool_choice": "auto", "tools": [get_weather, drop_weather]},
|
||||
)
|
||||
finally:
|
||||
monkey.undo()
|
||||
|
||||
assert set(recorded[0]) == {"get_weather", "drop_weather"}
|
||||
assert "get_weather" not in recorded[1]
|
||||
|
||||
|
||||
async def test_add_tools_does_not_mutate_caller_tools_list(chat_client_base: SupportsChatGetResponse):
|
||||
@tool(name="load_math", approval_mode="never_require")
|
||||
def load_math(ctx: FunctionInvocationContext) -> str:
|
||||
ctx.add_tools(_pte_factorial)
|
||||
return "loaded"
|
||||
|
||||
original_tools: list[Any] = [load_math]
|
||||
chat_client_base.function_invocation_configuration["max_iterations"] = 3 # type: ignore[attr-defined]
|
||||
chat_client_base.run_responses = [
|
||||
_pte_function_call_response("1", "load_math"),
|
||||
_pte_text_response(),
|
||||
]
|
||||
await chat_client_base.get_response(
|
||||
[Message(role="user", contents=["hi"])],
|
||||
options={"tool_choice": "auto", "tools": original_tools},
|
||||
)
|
||||
assert original_tools == [load_math]
|
||||
|
||||
|
||||
async def test_add_tools_persists_across_iterations(chat_client_base: SupportsChatGetResponse):
|
||||
from agent_framework import FunctionTool
|
||||
|
||||
recorded: list[list[str]] = []
|
||||
client_cls = type(chat_client_base)
|
||||
original = client_cls._get_non_streaming_response
|
||||
|
||||
async def recording(self: Any, *, messages: Any, options: dict[str, Any], **kwargs: Any) -> ChatResponse:
|
||||
tools = options.get("tools") or []
|
||||
recorded.append([t.name for t in tools if isinstance(t, FunctionTool)])
|
||||
return await original(self, messages=messages, options=options, **kwargs)
|
||||
|
||||
@tool(name="load_math", approval_mode="never_require")
|
||||
def load_math(ctx: FunctionInvocationContext) -> str:
|
||||
ctx.add_tools(_pte_factorial)
|
||||
return "loaded"
|
||||
|
||||
chat_client_base.function_invocation_configuration["max_iterations"] = 4 # type: ignore[attr-defined]
|
||||
chat_client_base.run_responses = [
|
||||
_pte_function_call_response("1", "load_math"),
|
||||
_pte_function_call_response("2", "factorial", '{"n": 5}'),
|
||||
_pte_function_call_response("3", "factorial", '{"n": 3}'),
|
||||
_pte_text_response(),
|
||||
]
|
||||
monkey = pytest.MonkeyPatch()
|
||||
monkey.setattr(client_cls, "_get_non_streaming_response", recording)
|
||||
try:
|
||||
await chat_client_base.get_response(
|
||||
[Message(role="user", contents=["hi"])],
|
||||
options={"tool_choice": "auto", "tools": [load_math]},
|
||||
)
|
||||
finally:
|
||||
monkey.undo()
|
||||
|
||||
assert "factorial" in recorded[1]
|
||||
assert "factorial" in recorded[2]
|
||||
|
||||
|
||||
async def test_add_tools_through_function_middleware(chat_client_base: SupportsChatGetResponse):
|
||||
exec_counter = 0
|
||||
|
||||
class PassthroughMiddleware(FunctionMiddleware):
|
||||
async def process(self, context: FunctionInvocationContext, call_next: Any) -> None:
|
||||
await call_next()
|
||||
|
||||
@tool(name="factorial", approval_mode="never_require")
|
||||
def factorial(n: int) -> int:
|
||||
nonlocal exec_counter
|
||||
exec_counter += 1
|
||||
return 120
|
||||
|
||||
@tool(name="load_math", approval_mode="never_require")
|
||||
def load_math(ctx: FunctionInvocationContext) -> str:
|
||||
ctx.add_tools(factorial)
|
||||
return "loaded"
|
||||
|
||||
chat_client_base.function_invocation_configuration["max_iterations"] = 3 # type: ignore[attr-defined]
|
||||
chat_client_base.run_responses = [
|
||||
_pte_function_call_response("1", "load_math"),
|
||||
_pte_function_call_response("2", "factorial", '{"n": 5}'),
|
||||
_pte_text_response(),
|
||||
]
|
||||
await chat_client_base.get_response(
|
||||
[Message(role="user", contents=["hi"])],
|
||||
options={"tool_choice": "auto", "tools": [load_math]},
|
||||
middleware=[PassthroughMiddleware()],
|
||||
)
|
||||
assert exec_counter == 1
|
||||
|
||||
|
||||
async def test_add_tools_with_approval_required_tool(chat_client_base: SupportsChatGetResponse):
|
||||
@tool(name="secure_tool", approval_mode="always_require")
|
||||
def secure_tool(value: str) -> str:
|
||||
return f"secure: {value}"
|
||||
|
||||
@tool(name="load_secure", approval_mode="never_require")
|
||||
def load_secure(ctx: FunctionInvocationContext) -> str:
|
||||
ctx.add_tools(secure_tool)
|
||||
return "loaded"
|
||||
|
||||
chat_client_base.function_invocation_configuration["max_iterations"] = 3 # type: ignore[attr-defined]
|
||||
chat_client_base.run_responses = [
|
||||
_pte_function_call_response("1", "load_secure"),
|
||||
_pte_function_call_response("2", "secure_tool", '{"value": "x"}'),
|
||||
_pte_text_response(),
|
||||
]
|
||||
response = await chat_client_base.get_response(
|
||||
[Message(role="user", contents=["hi"])],
|
||||
options={"tool_choice": "auto", "tools": [load_secure]},
|
||||
)
|
||||
assert any(item.type == "function_approval_request" for msg in response.messages for item in msg.contents)
|
||||
|
||||
|
||||
async def test_add_tools_accepts_plain_callable(chat_client_base: SupportsChatGetResponse):
|
||||
exec_counter = 0
|
||||
|
||||
def plain_factorial(n: int) -> int:
|
||||
"""Compute factorial."""
|
||||
nonlocal exec_counter
|
||||
exec_counter += 1
|
||||
return 120
|
||||
|
||||
@tool(name="load_math", approval_mode="never_require")
|
||||
def load_math(ctx: FunctionInvocationContext) -> str:
|
||||
ctx.add_tools(plain_factorial)
|
||||
return "loaded"
|
||||
|
||||
chat_client_base.function_invocation_configuration["max_iterations"] = 3 # type: ignore[attr-defined]
|
||||
chat_client_base.run_responses = [
|
||||
_pte_function_call_response("1", "load_math"),
|
||||
_pte_function_call_response("2", "plain_factorial", '{"n": 5}'),
|
||||
_pte_text_response(),
|
||||
]
|
||||
await chat_client_base.get_response(
|
||||
[Message(role="user", contents=["hi"])],
|
||||
options={"tool_choice": "auto", "tools": [load_math]},
|
||||
)
|
||||
assert exec_counter == 1
|
||||
|
||||
|
||||
async def test_add_tools_streaming(chat_client_base: SupportsChatGetResponse):
|
||||
exec_counter = 0
|
||||
|
||||
@tool(name="factorial", approval_mode="never_require")
|
||||
def factorial(n: int) -> int:
|
||||
nonlocal exec_counter
|
||||
exec_counter += 1
|
||||
return 120
|
||||
|
||||
@tool(name="load_math", approval_mode="never_require")
|
||||
def load_math(ctx: FunctionInvocationContext) -> str:
|
||||
ctx.add_tools(factorial)
|
||||
return "loaded"
|
||||
|
||||
chat_client_base.function_invocation_configuration["max_iterations"] = 3 # type: ignore[attr-defined]
|
||||
chat_client_base.streaming_responses = [
|
||||
[
|
||||
ChatResponseUpdate(
|
||||
contents=[Content.from_function_call(call_id="1", name="load_math", arguments="{}")],
|
||||
role="assistant",
|
||||
)
|
||||
],
|
||||
[
|
||||
ChatResponseUpdate(
|
||||
contents=[Content.from_function_call(call_id="2", name="factorial", arguments='{"n": 5}')],
|
||||
role="assistant",
|
||||
)
|
||||
],
|
||||
[ChatResponseUpdate(contents=[Content.from_text("done")], role="assistant", finish_reason="stop")],
|
||||
]
|
||||
async for _ in chat_client_base.get_response(
|
||||
[Message(role="user", contents=["hi"])],
|
||||
stream=True,
|
||||
options={"tool_choice": "auto", "tools": [load_math]},
|
||||
):
|
||||
pass
|
||||
assert exec_counter == 1
|
||||
|
||||
|
||||
def test_add_tools_duplicate_same_object_is_noop():
|
||||
@tool(name="dup", approval_mode="never_require")
|
||||
def dup(x: int) -> int:
|
||||
return x
|
||||
|
||||
ctx = FunctionInvocationContext(function=dup, arguments={}, tools=[dup])
|
||||
ctx.add_tools(dup)
|
||||
assert ctx.tools is not None
|
||||
assert len(ctx.tools) == 1
|
||||
|
||||
|
||||
def test_add_tools_duplicate_name_different_object_raises():
|
||||
@tool(name="dup", approval_mode="never_require")
|
||||
def dup_a(x: int) -> int:
|
||||
return x
|
||||
|
||||
@tool(name="dup", approval_mode="never_require")
|
||||
def dup_b(x: int) -> int:
|
||||
return x
|
||||
|
||||
ctx = FunctionInvocationContext(function=dup_a, arguments={}, tools=[dup_a])
|
||||
with pytest.raises(ValueError):
|
||||
ctx.add_tools(dup_b)
|
||||
|
||||
|
||||
def test_add_tools_batch_with_duplicate_is_atomic():
|
||||
"""A duplicate-name clash partway through a batch must leave the live list unchanged."""
|
||||
|
||||
@tool(name="existing", approval_mode="never_require")
|
||||
def existing(x: int) -> int:
|
||||
return x
|
||||
|
||||
@tool(name="fresh", approval_mode="never_require")
|
||||
def fresh(x: int) -> int:
|
||||
return x
|
||||
|
||||
@tool(name="existing", approval_mode="never_require")
|
||||
def clashing(x: int) -> int:
|
||||
return x
|
||||
|
||||
ctx = FunctionInvocationContext(function=existing, arguments={}, tools=[existing])
|
||||
with pytest.raises(ValueError):
|
||||
ctx.add_tools([fresh, clashing])
|
||||
assert ctx.tools is not None
|
||||
# The valid "fresh" tool must not have been committed before the clash raised.
|
||||
assert ctx.tools == [existing]
|
||||
|
||||
|
||||
def test_remove_tools_by_name_and_object():
|
||||
@tool(name="a", approval_mode="never_require")
|
||||
def a(x: int) -> int:
|
||||
return x
|
||||
|
||||
@tool(name="b", approval_mode="never_require")
|
||||
def b(x: int) -> int:
|
||||
return x
|
||||
|
||||
ctx = FunctionInvocationContext(function=a, arguments={}, tools=[a, b])
|
||||
ctx.remove_tools("a")
|
||||
assert ctx.tools is not None
|
||||
assert [t.name for t in ctx.tools] == ["b"]
|
||||
ctx.remove_tools(b)
|
||||
assert ctx.tools == []
|
||||
|
||||
|
||||
def test_remove_tools_unknown_name_is_noop():
|
||||
@tool(name="a", approval_mode="never_require")
|
||||
def a(x: int) -> int:
|
||||
return x
|
||||
|
||||
ctx = FunctionInvocationContext(function=a, arguments={}, tools=[a])
|
||||
ctx.remove_tools("nonexistent")
|
||||
assert ctx.tools is not None
|
||||
assert [t.name for t in ctx.tools] == ["a"]
|
||||
|
||||
|
||||
def test_progressive_tools_helpers_raise_without_live_tools():
|
||||
@tool(name="a", approval_mode="never_require")
|
||||
def a(x: int) -> int:
|
||||
return x
|
||||
|
||||
ctx = FunctionInvocationContext(function=a, arguments={})
|
||||
assert ctx.tools is None
|
||||
with pytest.raises(RuntimeError):
|
||||
ctx.add_tools(a)
|
||||
with pytest.raises(RuntimeError):
|
||||
ctx.remove_tools("a")
|
||||
|
||||
|
||||
# endregion
|
||||
|
||||
@@ -0,0 +1,75 @@
|
||||
# Tools
|
||||
|
||||
Samples that show how to define, configure, and control function tools for an
|
||||
agent — from basic declarations to approvals, invocation limits, session
|
||||
injection, and dynamic (progressive) tool exposure.
|
||||
|
||||
## Function tools
|
||||
|
||||
| File | Demonstrates |
|
||||
|------|--------------|
|
||||
| [`function_tool_with_explicit_schema.py`](function_tool_with_explicit_schema.py) | Defining a tool with an explicit JSON schema. |
|
||||
| [`function_tool_declaration_only.py`](function_tool_declaration_only.py) | A declaration-only tool (schema without a local implementation). |
|
||||
| [`function_tool_with_kwargs.py`](function_tool_with_kwargs.py) | Passing extra keyword arguments into a tool. |
|
||||
| [`function_tool_from_dict_with_dependency_injection.py`](function_tool_from_dict_with_dependency_injection.py) | Dependency injection into a tool defined from a dict. |
|
||||
| [`function_tool_with_session_injection.py`](function_tool_with_session_injection.py) | Injecting the session into a tool. |
|
||||
| [`tool_in_class.py`](tool_in_class.py) | Using a method on a class as a tool. |
|
||||
| [`agent_as_tool_with_session_propagation.py`](agent_as_tool_with_session_propagation.py) | Exposing an agent as a tool with session propagation. |
|
||||
|
||||
## Approvals & invocation control
|
||||
|
||||
| File | Demonstrates |
|
||||
|------|--------------|
|
||||
| [`function_tool_with_approval.py`](function_tool_with_approval.py) | Requiring human approval before a tool runs. |
|
||||
| [`function_tool_with_approval_and_sessions.py`](function_tool_with_approval_and_sessions.py) | Tool approvals combined with sessions. |
|
||||
| [`function_invocation_configuration.py`](function_invocation_configuration.py) | Configuring function-invocation settings (e.g. max iterations). |
|
||||
| [`control_total_tool_executions.py`](control_total_tool_executions.py) | All the ways to cap how many times tools run. |
|
||||
| [`function_tool_with_max_invocations.py`](function_tool_with_max_invocations.py) | Limiting the number of invocations per tool. |
|
||||
| [`function_tool_with_max_exceptions.py`](function_tool_with_max_exceptions.py) | Limiting the number of exceptions a tool may raise. |
|
||||
| [`function_tool_recover_from_failures.py`](function_tool_recover_from_failures.py) | Returning errors so the agent can recover from tool failures. |
|
||||
|
||||
## Progressive tool exposure (dynamic loading)
|
||||
|
||||
| File | Demonstrates |
|
||||
|------|--------------|
|
||||
| [`dynamic_tool_exposure.py`](dynamic_tool_exposure.py) | A "loader" tool that adds more tools at runtime via `FunctionInvocationContext`. |
|
||||
|
||||
Frontloading a model with hundreds of tools hurts tool-selection accuracy,
|
||||
bloats context, and raises cost. Instead, start with a small set of loader
|
||||
tools and let the model pull in more on demand. Inside a tool, the injected
|
||||
`ctx: FunctionInvocationContext` exposes a live `ctx.tools` list plus
|
||||
`ctx.add_tools(...)` / `ctx.remove_tools(...)` helpers. Tools added or removed
|
||||
take effect on the **next iteration** of the function-calling loop.
|
||||
|
||||
> [!NOTE]
|
||||
> Progressive tool exposure applies to the standard function-calling loop. It
|
||||
> does **not** apply to CodeAct providers (`agent-framework-monty`,
|
||||
> `agent-framework-hyperlight`). In CodeAct the model only sees a single
|
||||
> `execute_code` tool, and host tools are exposed *inside the sandbox* as typed
|
||||
> Python functions rather than as model tool-schemas. Host tools there are
|
||||
> invoked without a `FunctionInvocationContext`, so `ctx.add_tools()` is not
|
||||
> available; the helpers fail fast with a clear `RuntimeError` instead of
|
||||
> silently doing nothing. To change a CodeAct agent's tool set, use the
|
||||
> provider's own `add_tools` / `remove_tool` / `clear_tools` methods (applied
|
||||
> between runs). The recommended provider-driven path for Monty and Hyperlight
|
||||
> is shown in [`../context_providers/code_act/`](../context_providers/code_act/)
|
||||
> ([`code_act.py`](../context_providers/code_act/code_act.py) for Hyperlight,
|
||||
> [`monty_code_act.py`](../context_providers/code_act/monty_code_act.py) for
|
||||
> Monty).
|
||||
|
||||
## Local shell & code interpreters
|
||||
|
||||
| Path | Demonstrates |
|
||||
|------|--------------|
|
||||
| [`local_shell_with_allowlist.py`](local_shell_with_allowlist.py) | `LocalShellTool` restricted by a strict command allow-list. |
|
||||
| [`local_shell_with_environment_provider.py`](local_shell_with_environment_provider.py) | `LocalShellTool` wired with a `ShellEnvironmentProvider`. |
|
||||
| [`local_code_interpreter/`](local_code_interpreter/) | Hyperlight-backed sandboxed code interpreter (standalone tool — *extra* pattern). |
|
||||
| [`monty_code_interpreter/`](monty_code_interpreter/) | Monty-backed sandboxed code interpreter (standalone tool — *extra* pattern). |
|
||||
|
||||
> [!TIP]
|
||||
> The `local_code_interpreter/` and `monty_code_interpreter/` samples show the
|
||||
> standalone-tool wiring and are provided as *extra* reference. For most
|
||||
> Monty/Hyperlight use cases the **recommended** path is the provider-driven
|
||||
> CodeAct setup in
|
||||
> [`../context_providers/code_act/`](../context_providers/code_act/), which adds
|
||||
> dynamic tool / capability management.
|
||||
@@ -0,0 +1,79 @@
|
||||
# Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
import asyncio
|
||||
from typing import Annotated
|
||||
|
||||
from agent_framework import Agent, FunctionInvocationContext, tool
|
||||
from agent_framework.openai import OpenAIChatClient
|
||||
from dotenv import load_dotenv
|
||||
from pydantic import Field
|
||||
|
||||
# Load environment variables from .env file
|
||||
load_dotenv()
|
||||
|
||||
"""
|
||||
Dynamic Tool Exposure (Progressive Tool Loading) Example
|
||||
|
||||
This example demonstrates "progressive tool exposure": a tool that adds more tools to
|
||||
the agent at runtime, in the same run, via ``FunctionInvocationContext``.
|
||||
|
||||
Frontloading a model with hundreds of tools hurts tool-selection accuracy, bloats
|
||||
context, and raises cost. Instead, you can start with a small set of "loader" tools and
|
||||
let the model pull in additional tools on demand. Tools added with ``ctx.add_tools(...)``
|
||||
(or removed with ``ctx.remove_tools(...)``) become available to the model on the next
|
||||
iteration of the function-calling loop.
|
||||
"""
|
||||
|
||||
|
||||
# These math tools are not registered on the agent up front. They are added on demand by
|
||||
# the ``load_math_tools`` tool below, and only then become callable by the model.
|
||||
@tool(approval_mode="never_require")
|
||||
def factorial(n: Annotated[int, Field(description="A non-negative integer.")]) -> str:
|
||||
"""Compute the factorial of n."""
|
||||
if n < 0:
|
||||
return "Error: n must be a non-negative integer."
|
||||
result = 1
|
||||
for value in range(2, n + 1):
|
||||
result *= value
|
||||
return f"{n}! = {result}"
|
||||
|
||||
|
||||
@tool(approval_mode="never_require")
|
||||
def fibonacci(n: Annotated[int, Field(description="The 0-based index in the Fibonacci sequence.")]) -> str:
|
||||
"""Compute the n-th Fibonacci number."""
|
||||
if n < 0:
|
||||
return "Error: n must be a non-negative integer."
|
||||
a, b = 0, 1
|
||||
for _ in range(n):
|
||||
a, b = b, a + b
|
||||
return f"fib({n}) = {a}"
|
||||
|
||||
|
||||
# The only tool the agent starts with. When called, it exposes the math tools above so the
|
||||
# model can use them on the next turn. Note the ``ctx`` parameter is injected by the
|
||||
# framework and is not visible to the model.
|
||||
@tool(approval_mode="never_require")
|
||||
def load_math_tools(ctx: FunctionInvocationContext) -> str:
|
||||
"""Load additional math tools (factorial, fibonacci) so they can be used."""
|
||||
ctx.add_tools([factorial, fibonacci])
|
||||
return "Loaded math tools: factorial, fibonacci. You can now call them."
|
||||
|
||||
|
||||
async def main() -> None:
|
||||
agent = Agent(
|
||||
client=OpenAIChatClient(),
|
||||
name="MathAgent",
|
||||
instructions=(
|
||||
"You are a math assistant. If you need math capabilities that are not yet "
|
||||
"available, call load_math_tools first, then use the newly available tools."
|
||||
),
|
||||
tools=[load_math_tools],
|
||||
)
|
||||
|
||||
# The agent starts with only ``load_math_tools``. To answer the question it must first
|
||||
# load the math tools, then call ``factorial`` on the next iteration.
|
||||
print(f"Agent: {await agent.run('What is 5 factorial?')}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
Generated
+102
-9
@@ -562,7 +562,7 @@ requires-dist = [
|
||||
{ name = "agent-framework-core", editable = "packages/core" },
|
||||
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Reference in New Issue
Block a user