diff --git a/python/packages/core/agent_framework/_tools.py b/python/packages/core/agent_framework/_tools.py index df0608e614..91dac40fc7 100644 --- a/python/packages/core/agent_framework/_tools.py +++ b/python/packages/core/agent_framework/_tools.py @@ -2164,15 +2164,11 @@ async def _get_response() -> ChatResponse: # Error threshold reached: force a final non-tool turn so # function_call_output items are submitted before exit. mutable_options["tool_choice"] = "none" - elif ( - max_function_calls is not None - and total_function_calls >= max_function_calls - ): + elif max_function_calls is not None and total_function_calls >= max_function_calls: # Best-effort limit: checked after each batch of parallel calls completes, # so the current batch always runs to completion even if it overshoots. logger.info( - "Maximum function calls reached (%d/%d). " - "Stopping further function calls for this request.", + "Maximum function calls reached (%d/%d). Stopping further function calls for this request.", total_function_calls, max_function_calls, ) @@ -2302,15 +2298,11 @@ async def _stream() -> AsyncIterable[ChatResponseUpdate]: mutable_options["tool_choice"] = "none" elif result["action"] != "continue": return - elif ( - max_function_calls is not None - and total_function_calls >= max_function_calls - ): + elif max_function_calls is not None and total_function_calls >= max_function_calls: # Best-effort limit: checked after each batch of parallel calls completes, # so the current batch always runs to completion even if it overshoots. logger.info( - "Maximum function calls reached (%d/%d). " - "Stopping further function calls for this request.", + "Maximum function calls reached (%d/%d). Stopping further function calls for this request.", total_function_calls, max_function_calls, ) diff --git a/python/packages/core/pyproject.toml b/python/packages/core/pyproject.toml index 9b0c9e60a8..09ccda3c18 100644 --- a/python/packages/core/pyproject.toml +++ b/python/packages/core/pyproject.toml @@ -34,7 +34,8 @@ dependencies = [ # connectors and functions "openai>=1.99.0", "azure-identity>=1,<2", - "azure-ai-projects >= 2.0.0b3", + # Pinned to 2.0.0b3 - breaking changes in 2.0.0b4, unpin once upgrades complete + "azure-ai-projects == 2.0.0b3", "mcp[ws]>=1.24.0,<2", "packaging>=24.1", ] diff --git a/python/packages/declarative/agent_framework_declarative/_workflows/__init__.py b/python/packages/declarative/agent_framework_declarative/_workflows/__init__.py index af3e196e3a..2968f2b3f9 100644 --- a/python/packages/declarative/agent_framework_declarative/_workflows/__init__.py +++ b/python/packages/declarative/agent_framework_declarative/_workflows/__init__.py @@ -34,7 +34,6 @@ AgentResult, ExternalLoopState, InvokeAzureAgentExecutor, - InvokeToolExecutor, ) from ._executors_basic import ( BASIC_ACTION_EXECUTORS, @@ -68,6 +67,17 @@ RequestExternalInputExecutor, WaitForInputExecutor, ) +from ._executors_tools import ( + FUNCTION_TOOL_REGISTRY_KEY, + TOOL_ACTION_EXECUTORS, + TOOL_APPROVAL_STATE_KEY, + BaseToolExecutor, + InvokeFunctionToolExecutor, + ToolApprovalRequest, + ToolApprovalResponse, + ToolApprovalState, + ToolInvocationResult, +) from ._factory import DeclarativeWorkflowError, WorkflowFactory from ._state import WorkflowState @@ -79,6 +89,9 @@ "CONTROL_FLOW_EXECUTORS", "DECLARATIVE_STATE_KEY", "EXTERNAL_INPUT_EXECUTORS", + "FUNCTION_TOOL_REGISTRY_KEY", + "TOOL_ACTION_EXECUTORS", + "TOOL_APPROVAL_STATE_KEY", "TOOL_REGISTRY_KEY", "ActionComplete", "ActionTrigger", @@ -86,6 +99,7 @@ "AgentExternalInputResponse", "AgentResult", "AppendValueExecutor", + "BaseToolExecutor", "BreakLoopExecutor", "ClearAllVariablesExecutor", "ConfirmationExecutor", @@ -107,7 +121,7 @@ "ForeachInitExecutor", "ForeachNextExecutor", "InvokeAzureAgentExecutor", - "InvokeToolExecutor", + "InvokeFunctionToolExecutor", "JoinExecutor", "LoopControl", "LoopIterationResult", @@ -119,6 +133,10 @@ "SetTextVariableExecutor", "SetValueExecutor", "SetVariableExecutor", + "ToolApprovalRequest", + "ToolApprovalResponse", + "ToolApprovalState", + "ToolInvocationResult", "WaitForInputExecutor", "WorkflowFactory", "WorkflowState", diff --git a/python/packages/declarative/agent_framework_declarative/_workflows/_declarative_builder.py b/python/packages/declarative/agent_framework_declarative/_workflows/_declarative_builder.py index c5552c0e85..65e129d921 100644 --- a/python/packages/declarative/agent_framework_declarative/_workflows/_declarative_builder.py +++ b/python/packages/declarative/agent_framework_declarative/_workflows/_declarative_builder.py @@ -13,6 +13,7 @@ from __future__ import annotations +import logging from typing import Any from agent_framework import ( @@ -38,6 +39,10 @@ SwitchEvaluatorExecutor, ) from ._executors_external_input import EXTERNAL_INPUT_EXECUTORS +from ._executors_tools import TOOL_ACTION_EXECUTORS, InvokeFunctionToolExecutor + +logger = logging.getLogger(__name__) + # Combined mapping of all action kinds to executor classes ALL_ACTION_EXECUTORS = { @@ -45,6 +50,7 @@ **CONTROL_FLOW_EXECUTORS, **AGENT_ACTION_EXECUTORS, **EXTERNAL_INPUT_EXECUTORS, + **TOOL_ACTION_EXECUTORS, } # Action kinds that terminate control flow (no fall-through to successor) @@ -78,6 +84,7 @@ "RequestHumanInput": ["variable"], "WaitForHumanInput": ["variable"], "EmitEvent": ["event"], + "InvokeFunctionTool": ["functionName"], } # Alternate field names that satisfy required field requirements @@ -118,6 +125,7 @@ def __init__( yaml_definition: dict[str, Any], workflow_id: str | None = None, agents: dict[str, Any] | None = None, + tools: dict[str, Any] | None = None, checkpoint_storage: Any | None = None, validate: bool = True, max_iterations: int | None = None, @@ -128,6 +136,7 @@ def __init__( yaml_definition: The parsed YAML workflow definition workflow_id: Optional ID for the workflow (defaults to name from YAML) agents: Registry of agent instances by name (for InvokeAzureAgent actions) + tools: Registry of tool/function instances by name (for InvokeFunctionTool actions) checkpoint_storage: Optional checkpoint storage for pause/resume support validate: Whether to validate the workflow definition before building (default: True) max_iterations: Maximum runner supersteps. Falls back to the YAML ``maxTurns`` @@ -138,6 +147,7 @@ def __init__( self._executors: dict[str, Any] = {} # id -> executor self._action_index = 0 # Counter for generating unique IDs self._agents = agents or {} # Agent registry for agent executors + self._tools = tools or {} # Tool registry for tool executors self._checkpoint_storage = checkpoint_storage self._pending_gotos: list[tuple[Any, str]] = [] # (goto_executor, target_id) self._validate = validate @@ -423,8 +433,13 @@ def _create_executor_for_action( executor_class = ALL_ACTION_EXECUTORS.get(kind) if executor_class is None: - # Unknown action type - skip with warning - # In production, might want to log this + # Unknown action type - log warning and skip + logger.warning( + "Unknown action kind '%s' encountered at index %d - action will be skipped. Available action kinds: %s", + kind, + self._action_index, + list(ALL_ACTION_EXECUTORS.keys()), + ) return None # Create the executor with ID @@ -437,10 +452,12 @@ def _create_executor_for_action( action_id = f"{parent_id}_{kind}_{self._action_index}" if parent_id else f"{kind}_{self._action_index}" self._action_index += 1 - # Pass agents to agent-related executors + # Pass agents/tools to specialized executors executor: Any if kind in ("InvokeAzureAgent",): executor = InvokeAzureAgentExecutor(action_def, id=action_id, agents=self._agents) + elif kind == "InvokeFunctionTool": + executor = InvokeFunctionToolExecutor(action_def, id=action_id, tools=self._tools) else: executor = executor_class(action_def, id=action_id) self._executors[action_id] = executor diff --git a/python/packages/declarative/agent_framework_declarative/_workflows/_executors_agents.py b/python/packages/declarative/agent_framework_declarative/_workflows/_executors_agents.py index 96f8991d17..c2fded5fb8 100644 --- a/python/packages/declarative/agent_framework_declarative/_workflows/_executors_agents.py +++ b/python/packages/declarative/agent_framework_declarative/_workflows/_executors_agents.py @@ -1019,75 +1019,7 @@ async def handle_external_input_response( await ctx.send_message(ActionComplete()) -class InvokeToolExecutor(DeclarativeActionExecutor): - """Executor that invokes a registered tool/function. - - Tools are simpler than agents - they take input, perform an action, - and return a result synchronously (or with a simple async call). - """ - - @handler - async def handle_action( - self, - trigger: Any, - ctx: WorkflowContext[ActionComplete], - ) -> None: - """Handle the tool invocation.""" - state = await self._ensure_state_initialized(ctx, trigger) - - tool_name = self._action_def.get("tool") or self._action_def.get("toolName", "") - input_expr = self._action_def.get("input") - output_property = self._action_def.get("output", {}).get("property") or self._action_def.get("resultProperty") - parameters = self._action_def.get("parameters", {}) - - # Get tools registry - try: - tool_registry: dict[str, Any] | None = ctx.state.get(TOOL_REGISTRY_KEY) - except KeyError: - tool_registry = {} - - tool: Any = tool_registry.get(tool_name) if tool_registry else None - - if tool is None: - error_msg = f"Tool '{tool_name}' not found in registry" - if output_property: - state.set(output_property, {"error": error_msg}) - await ctx.send_message(ActionComplete()) - return - - # Build parameters - params: dict[str, Any] = {} - for param_name, param_expression in parameters.items(): - params[param_name] = state.eval_if_expression(param_expression) - - # Add main input if specified - if input_expr: - params["input"] = state.eval_if_expression(input_expr) - - try: - # Invoke the tool - if callable(tool): - from inspect import isawaitable - - result = tool(**params) - if isawaitable(result): - result = await result - - # Store result - if output_property: - state.set(output_property, result) - - except Exception as e: - if output_property: - state.set(output_property, {"error": str(e)}) - await ctx.send_message(ActionComplete()) - return - - await ctx.send_message(ActionComplete()) - - # Mapping of agent action kinds to executor classes AGENT_ACTION_EXECUTORS: dict[str, type[DeclarativeActionExecutor]] = { "InvokeAzureAgent": InvokeAzureAgentExecutor, - "InvokeTool": InvokeToolExecutor, } diff --git a/python/packages/declarative/agent_framework_declarative/_workflows/_executors_tools.py b/python/packages/declarative/agent_framework_declarative/_workflows/_executors_tools.py new file mode 100644 index 0000000000..829d48103f --- /dev/null +++ b/python/packages/declarative/agent_framework_declarative/_workflows/_executors_tools.py @@ -0,0 +1,711 @@ +# Copyright (c) Microsoft. All rights reserved. + +"""Tool invocation executors for declarative workflows. + +Provides base abstractions and concrete executors for invoking various tool types +(functions, APIs, MCP servers, etc.) with support for approval flows and structured output. + +This module is designed for extensibility: +- BaseToolExecutor provides common patterns (registry lookup, approval flow, output formatting) +- Concrete executors (InvokeFunctionToolExecutor) implement tool-specific invocation logic +- New tool types can be added by subclassing BaseToolExecutor +""" + +import json +import logging +import uuid +from abc import abstractmethod +from dataclasses import dataclass, field +from inspect import isawaitable +from typing import Any + +from agent_framework import ( + Content, + Message, + WorkflowContext, + handler, + response_handler, +) + +from ._declarative_base import ( + ActionComplete, + DeclarativeActionExecutor, + DeclarativeWorkflowState, +) +from ._executors_agents import TOOL_REGISTRY_KEY + +logger = logging.getLogger(__name__) + +# Registry key for function tools in State - reuse existing key so functions registered +# at runtime are discoverable by both agent-based and function-based tool executors. +FUNCTION_TOOL_REGISTRY_KEY = TOOL_REGISTRY_KEY + +# State key prefix for storing approval state during yield/resume. +# The executor's ID is appended to create a per-executor key. +TOOL_APPROVAL_STATE_KEY = "_tool_approval_state" + + +# ============================================================================ +# Request/Response Types for Approval Flow +# ============================================================================ + + +@dataclass +class ToolApprovalRequest: + """Request for approval before invoking a tool. + + Emitted when requireApproval=true, signaling that the workflow should yield + and wait for user approval before invoking the tool. + + This follows the same pattern as AgentExternalInputRequest from _executors_agents.py, + allowing consistent handling of human-in-loop scenarios across agents and tools. + + Attributes: + request_id: Unique identifier for this approval request. + function_name: Evaluated function name to be invoked. + arguments: Evaluated arguments to be passed to the function. + """ + + request_id: str + function_name: str + arguments: dict[str, Any] + + +@dataclass +class ToolApprovalResponse: + """Response to a ToolApprovalRequest. + + Provided by the caller to approve or reject tool invocation. + + Attributes: + approved: Whether the tool invocation was approved. + reason: Optional reason for rejection. + """ + + approved: bool + reason: str | None = None + + +# ============================================================================ +# State Types for Approval Flow +# ============================================================================ + + +@dataclass +class ToolApprovalState: + """State saved during approval yield for resumption. + + Stored in State under a per-executor key when requireApproval=true. + Retrieved by handle_approval_response() to continue execution. + """ + + function_name: str + arguments: dict[str, Any] + output_messages_var: str | None + output_result_var: str | None + auto_send: bool + + +# ============================================================================ +# Result Types +# ============================================================================ + + +@dataclass +class ToolInvocationResult: + """Result from a tool invocation. + + Attributes: + success: Whether the invocation succeeded. + result: The return value from the tool (if successful). + error: Error message (if failed). + messages: Message list format for conversation history. + rejected: Whether the invocation was rejected during approval. + rejection_reason: Reason for rejection. + """ + + success: bool + result: Any = None + error: str | None = None + messages: list[Message] = field(default_factory=list) + rejected: bool = False + rejection_reason: str | None = None + + +# ============================================================================ +# Helper Functions +# ============================================================================ + + +def _normalize_variable_path(variable: str) -> str: + """Normalize variable names to ensure they have a scope prefix. + + Args: + variable: Variable name like 'Local.X' or 'weatherResult' + + Returns: + The variable path with a scope prefix (defaults to Local if none provided) + """ + if variable.startswith(("Local.", "System.", "Workflow.", "Agent.", "Conversation.")): + return variable + if "." in variable: + return variable + return "Local." + variable + + +# ============================================================================ +# Base Tool Executor (Abstract) +# ============================================================================ + + +class BaseToolExecutor(DeclarativeActionExecutor): + """Base class for tool invocation executors. + + Provides common functionality for all tool-like executors: + - Tool registry lookup (State + WorkflowFactory registration) + - Approval flow (request_info pattern with yield/resume) + - Output formatting (messages as Message list + result variable) + - Error handling (stores error in output, doesn't raise) + + Subclasses must implement: + - _invoke_tool(): Perform the actual tool invocation + + YAML Schema (common fields): + kind: + id: unique_id + functionName: function_to_call # required, supports =expression syntax + requireApproval: true # optional, default=false + arguments: # optional dictionary + param1: value1 + param2: =Local.dynamicValue + output: + messages: Local.toolCallMessages # Message list + result: Local.toolResult + autoSend: true # optional, default=true + """ + + def __init__( + self, + action_def: dict[str, Any], + *, + id: str | None = None, + tools: dict[str, Any] | None = None, + ): + """Initialize the tool executor. + + Args: + action_def: The action definition from YAML + id: Optional executor ID + tools: Registry of tool instances by name (from WorkflowFactory) + """ + super().__init__(action_def, id=id) + self._tools = tools or {} + + @abstractmethod + async def _invoke_tool( + self, + tool: Any, + function_name: str, + arguments: dict[str, Any], + state: DeclarativeWorkflowState, + ) -> Any: + """Invoke the tool with the given arguments. + + Args: + tool: The tool instance to invoke + function_name: Function/method name to call + arguments: Arguments to pass + state: Workflow state + + Returns: + The result from the tool invocation + + Raises: + Any exception from the tool invocation + """ + pass + + def _get_tool( + self, + function_name: str, + ctx: WorkflowContext[Any, Any], + ) -> Any | None: + """Get tool from registry. + + Checks both WorkflowFactory registry (self._tools) and State registry. + + Args: + function_name: Name of the function + ctx: Workflow context + + Returns: + The tool/function, or None if not found + """ + # Check WorkflowFactory registry first (passed in constructor) + tool = self._tools.get(function_name) + if tool is not None: + return tool + + # Check State registry (for runtime registration) + try: + tool_registry: dict[str, Any] | None = ctx.state.get(FUNCTION_TOOL_REGISTRY_KEY) + if tool_registry: + return tool_registry.get(function_name) + except KeyError: + logger.debug( + "%s: tool registry key '%s' not found in state " + "(this is normal if tools are only registered via WorkflowFactory)", + self.__class__.__name__, + FUNCTION_TOOL_REGISTRY_KEY, + ) + + return None + + def _get_output_config(self) -> tuple[str | None, str | None, bool]: + """Parse output configuration from action definition. + + Returns: + Tuple of (messages_var, result_var, auto_send) + """ + output_config = self._action_def.get("output", {}) + + if not isinstance(output_config, dict): + return None, None, True + + messages_var = output_config.get("messages") + result_var = output_config.get("result") + auto_send = bool(output_config.get("autoSend", True)) + + return ( + str(messages_var) if messages_var else None, + str(result_var) if result_var else None, + auto_send, + ) + + def _store_result( + self, + result: ToolInvocationResult, + state: DeclarativeWorkflowState, + messages_var: str | None, + result_var: str | None, + ) -> None: + """Store tool invocation result in workflow state. + + Args: + result: The tool invocation result + state: Workflow state + messages_var: Variable path for messages output + result_var: Variable path for result output + """ + # Store messages if variable specified + if messages_var: + path = _normalize_variable_path(messages_var) + state.set(path, result.messages) + + # Store result if variable specified + if result_var: + path = _normalize_variable_path(result_var) + if result.rejected: + state.set( + path, + { + "approved": False, + "rejected": True, + "reason": result.rejection_reason, + }, + ) + elif result.success: + state.set(path, result.result) + else: + state.set( + path, + { + "error": result.error, + }, + ) + + async def _format_messages( + self, + function_name: str, + arguments: dict[str, Any], + result: Any, + ) -> list[Message]: + """Format tool invocation as Message list. + + Creates tool call + tool result message pair for conversation history, + following the same format as agent tool calls. + + Args: + function_name: Function name invoked + arguments: Arguments passed + result: Result from invocation + + Returns: + List of Message objects [tool_call_message, tool_result_message] + """ + call_id = str(uuid.uuid4()) + + # Safely serialize arguments to JSON + try: + arguments_str = json.dumps(arguments) if isinstance(arguments, dict) else str(arguments) + except (TypeError, ValueError) as e: + logger.warning(f"Failed to serialize arguments to JSON: {e}") + arguments_str = str(arguments) + + # Tool call message (from assistant) + tool_call_content = Content.from_function_call( + call_id=call_id, + name=function_name, + arguments=arguments_str, + ) + tool_call_message = Message( + role="assistant", + contents=[tool_call_content], + ) + + # Safely serialize result to JSON + try: + result_str = json.dumps(result) if not isinstance(result, str) else result + except (TypeError, ValueError) as e: + logger.warning(f"Failed to serialize result to JSON: {e}") + result_str = str(result) + + tool_result_content = Content.from_function_result( + call_id=call_id, + result=result_str, + ) + tool_result_message = Message( + role="tool", + contents=[tool_result_content], + ) + + return [tool_call_message, tool_result_message] + + async def _execute_tool_invocation( + self, + function_name: str, + arguments: dict[str, Any], + state: DeclarativeWorkflowState, + ctx: WorkflowContext[Any, Any], + ) -> ToolInvocationResult: + """Execute the tool invocation. + + Args: + function_name: Function to invoke + arguments: Arguments to pass + state: Workflow state + ctx: Workflow context + + Returns: + ToolInvocationResult with outcome + """ + # Get tool from registry + tool = self._get_tool(function_name, ctx) + if tool is None: + error_msg = f"Function '{function_name}' not found in registry" + logger.error(f"{self.__class__.__name__}: {error_msg}") + return ToolInvocationResult( + success=False, + error=error_msg, + ) + + try: + # Invoke the tool (subclass implements this) + result_value = await self._invoke_tool( + tool=tool, + function_name=function_name, + arguments=arguments, + state=state, + ) + + # Format as messages for conversation history + messages = await self._format_messages( + function_name=function_name, + arguments=arguments, + result=result_value, + ) + + return ToolInvocationResult( + success=True, + result=result_value, + messages=messages, + ) + + except Exception as e: + logger.error( + "%s: error invoking function '%s': %s: %s", + self.__class__.__name__, + function_name, + type(e).__name__, + e, + exc_info=True, + ) + return ToolInvocationResult( + success=False, + error=f"{type(e).__name__}: {e}", + ) + + @handler + async def handle_action( + self, + trigger: Any, + ctx: WorkflowContext[ActionComplete, str], + ) -> None: + """Handle the tool invocation with optional approval flow. + + When requireApproval=true: + 1. Saves invocation state to State (keyed by executor ID) + 2. Emits ToolApprovalRequest via ctx.request_info() + 3. Workflow yields (returns without ActionComplete) + 4. Resumes in handle_approval_response() when user responds + """ + state = await self._ensure_state_initialized(ctx, trigger) + + # Parse output configuration early so we can store errors + messages_var, result_var, auto_send = self._get_output_config() + + # Get and evaluate function name (required) + function_name_expr = self._action_def.get("functionName") + if not function_name_expr: + error_msg = f"Action '{self.id}' is missing required 'functionName' field" + logger.error(f"{self.__class__.__name__}: {error_msg}") + if result_var: + state.set(_normalize_variable_path(result_var), {"error": error_msg}) + await ctx.send_message(ActionComplete()) + return + + function_name = state.eval_if_expression(function_name_expr) + if not function_name: + error_msg = f"Action '{self.id}': functionName expression evaluated to empty" + logger.error(f"{self.__class__.__name__}: {error_msg}") + if result_var: + state.set(_normalize_variable_path(result_var), {"error": error_msg}) + await ctx.send_message(ActionComplete()) + return + function_name = str(function_name) + + # Evaluate arguments + arguments_def = self._action_def.get("arguments", {}) + arguments: dict[str, Any] = {} + if arguments_def is not None and not isinstance(arguments_def, dict): + logger.warning( + "%s: 'arguments' must be a dictionary, got %s - ignoring", + self.__class__.__name__, + type(arguments_def).__name__, + ) + elif isinstance(arguments_def, dict): + for key, value in arguments_def.items(): + arguments[key] = state.eval_if_expression(value) + + # Check if approval is required + require_approval = self._action_def.get("requireApproval", False) + + if require_approval: + # Save state for resumption (keyed by executor ID to avoid collisions) + approval_state = ToolApprovalState( + function_name=function_name, + arguments=arguments, + output_messages_var=messages_var, + output_result_var=result_var, + auto_send=auto_send, + ) + approval_key = f"{TOOL_APPROVAL_STATE_KEY}_{self.id}" + ctx.state.set(approval_key, approval_state) + + # Emit approval request - workflow yields here + request = ToolApprovalRequest( + request_id=str(uuid.uuid4()), + function_name=function_name, + arguments=arguments, + ) + logger.info(f"{self.__class__.__name__}: requesting approval for '{function_name}'") + await ctx.request_info(request, ToolApprovalResponse) + # Workflow yields - will resume in handle_approval_response + return + + # No approval required - invoke directly + result = await self._execute_tool_invocation( + function_name=function_name, + arguments=arguments, + state=state, + ctx=ctx, + ) + + self._store_result(result, state, messages_var, result_var) + if auto_send and result.success and result.result is not None: + await ctx.yield_output(str(result.result)) + await ctx.send_message(ActionComplete()) + + @response_handler + async def handle_approval_response( + self, + original_request: ToolApprovalRequest, + response: ToolApprovalResponse, + ctx: WorkflowContext[ActionComplete, str], + ) -> None: + """Handle response to a ToolApprovalRequest. + + Called when the workflow resumes after yielding for approval. + Either executes the tool (if approved) or stores rejection status. + """ + state = self._get_state(ctx.state) + approval_key = f"{TOOL_APPROVAL_STATE_KEY}_{self.id}" + + # Retrieve saved invocation state + try: + approval_state: ToolApprovalState = ctx.state.get(approval_key) + except KeyError: + error_msg = "Approval state not found, cannot resume tool invocation" + logger.error(f"{self.__class__.__name__}: {error_msg}") + # Try to store error - get output config from action def as fallback + _, result_var, _ = self._get_output_config() + if result_var and state: + state.set(_normalize_variable_path(result_var), {"error": error_msg}) + await ctx.send_message(ActionComplete()) + return + + # Clean up approval state + try: + ctx.state.delete(approval_key) + except KeyError: + logger.warning(f"{self.__class__.__name__}: approval state already deleted") + + function_name = approval_state.function_name + arguments = approval_state.arguments + messages_var = approval_state.output_messages_var + result_var = approval_state.output_result_var + auto_send = approval_state.auto_send + + # Check if approved + if not response.approved: + logger.info(f"{self.__class__.__name__}: tool invocation rejected: {response.reason}") + + # Store rejection status (don't raise error) + result = ToolInvocationResult( + success=False, + rejected=True, + rejection_reason=response.reason, + messages=[ + Message( + role="assistant", + text=f"Function '{function_name}' was rejected: {response.reason or 'No reason provided'}", + ) + ], + ) + self._store_result(result, state, messages_var, result_var) + await ctx.send_message(ActionComplete()) + return + + # Approved - execute the invocation + result = await self._execute_tool_invocation( + function_name=function_name, + arguments=arguments, + state=state, + ctx=ctx, + ) + + self._store_result(result, state, messages_var, result_var) + if auto_send and result.success and result.result is not None: + await ctx.yield_output(str(result.result)) + await ctx.send_message(ActionComplete()) + + +# ============================================================================ +# Function Tool Executor (Concrete) +# ============================================================================ + + +class InvokeFunctionToolExecutor(BaseToolExecutor): + """Executor that invokes a Python function as a tool. + + This executor supports invoking registered Python functions with: + - Expression evaluation for functionName and arguments + - Optional approval flow (yield/resume pattern) + - Async function support + - Message list output for conversation history + + YAML Schema: + kind: InvokeFunctionTool + id: invoke_function_example + functionName: get_weather # required, supports =expression syntax + requireApproval: true # optional, default=false + arguments: # optional dictionary + location: =Local.location + unit: F + output: + messages: Local.weatherToolCallItems # Message list + result: Local.WeatherInfo + autoSend: true # optional, default=true + + Tool Registration: + Tools can be registered via: + 1. WorkflowFactory.register_tool("name", func) - preferred + 2. Setting FUNCTION_TOOL_REGISTRY_KEY in State at runtime + + Examples: + .. code-block:: python + + from agent_framework_declarative import WorkflowFactory + + + def get_weather(location: str, unit: str = "F") -> dict: + return {"temp": 72, "unit": unit, "location": location} + + + async def fetch_data(url: str) -> dict: + # async function example + return {"data": "..."} + + + factory = ( + WorkflowFactory().register_tool("get_weather", get_weather).register_tool("fetch_data", fetch_data) + ) + + workflow = factory.create_workflow_from_yaml_path("workflow.yaml") + """ + + async def _invoke_tool( + self, + tool: Any, + function_name: str, + arguments: dict[str, Any], + state: DeclarativeWorkflowState, + ) -> Any: + """Invoke the function tool. + + Supports: + - Direct callable functions + - Async functions (via inspect.isawaitable) + + Args: + tool: The tool/function to invoke + function_name: Name of the function (for error messages) + arguments: Arguments to pass to the function + state: Workflow state (not used for function tools) + + Returns: + The result from the function invocation + + Raises: + ValueError: If the tool is not callable + """ + if not callable(tool): + raise ValueError(f"Function '{function_name}' is not callable") + + # Invoke the function + result = tool(**arguments) + + # Handle async functions + if isawaitable(result): + result = await result + + return result + + +# ============================================================================ +# Executor Registry Export +# ============================================================================ + +TOOL_ACTION_EXECUTORS: dict[str, type[DeclarativeActionExecutor]] = { + "InvokeFunctionTool": InvokeFunctionToolExecutor, +} diff --git a/python/packages/declarative/agent_framework_declarative/_workflows/_factory.py b/python/packages/declarative/agent_framework_declarative/_workflows/_factory.py index 1b22a9679d..4d6f3fa35b 100644 --- a/python/packages/declarative/agent_framework_declarative/_workflows/_factory.py +++ b/python/packages/declarative/agent_framework_declarative/_workflows/_factory.py @@ -141,6 +141,7 @@ def __init__( self._agent_factory = agent_factory or AgentFactory(env_file_path=env_file) self._agents: dict[str, SupportsAgentRun | AgentExecutor] = dict(agents) if agents else {} self._bindings: dict[str, Any] = dict(bindings) if bindings else {} + self._tools: dict[str, Any] = {} # Tool registry for InvokeFunctionTool actions self._checkpoint_storage = checkpoint_storage self._max_iterations = max_iterations @@ -377,12 +378,13 @@ def _create_workflow( if description: normalized_def["description"] = description - # Build the graph-based workflow, passing agents for InvokeAzureAgent executors + # Build the graph-based workflow, passing agents and tools for specialized executors try: graph_builder = DeclarativeWorkflowBuilder( normalized_def, workflow_id=name, agents=agents, + tools=self._tools, checkpoint_storage=self._checkpoint_storage, max_iterations=self._max_iterations, ) @@ -390,9 +392,10 @@ def _create_workflow( except ValueError as e: raise DeclarativeWorkflowError(f"Failed to build graph-based workflow: {e}") from e - # Store agents and bindings for reference (executors already have them) + # Store agents, bindings, and tools for reference (executors already have them) workflow._declarative_agents = agents # type: ignore[attr-defined] workflow._declarative_bindings = self._bindings # type: ignore[attr-defined] + workflow._declarative_tools = self._tools # type: ignore[attr-defined] # Store input schema if defined in workflow definition # This allows DevUI to generate proper input forms @@ -598,9 +601,66 @@ def send_email(to: str, subject: str, body: str) -> bool: workflow = factory.create_workflow_from_yaml_path("workflow.yaml") """ + if not callable(func): + raise TypeError(f"Expected a callable for binding '{name}', got {type(func).__name__}") self._bindings[name] = func return self + def register_tool(self, name: str, func: Any) -> WorkflowFactory: + """Register a function with the factory for use in InvokeFunctionTool actions. + + Registered functions are available to InvokeFunctionTool actions by name via the functionName field. + This method supports fluent chaining. + + Args: + name: The name to register the function under. Must match the functionName + referenced in InvokeFunctionTool actions. + func: The function to register (can be sync or async). + + Returns: + Self for method chaining. + + Examples: + .. code-block:: python + + from agent_framework_declarative import WorkflowFactory + + + def get_weather(location: str, unit: str = "F") -> dict: + return {"temp": 72, "unit": unit, "location": location} + + + async def fetch_data(url: str) -> dict: + # Async function example + return {"data": "..."} + + + # Register functions for use in InvokeFunctionTool workflow actions + factory = ( + WorkflowFactory().register_tool("get_weather", get_weather).register_tool("fetch_data", fetch_data) + ) + + workflow = factory.create_workflow_from_yaml_path("workflow.yaml") + + The workflow YAML can then reference these tools: + + .. code-block:: yaml + + actions: + - kind: InvokeFunctionTool + id: call_weather + functionName: get_weather + arguments: + location: =Local.city + unit: F + output: + result: Local.weatherData + """ + if not callable(func): + raise TypeError(f"Expected a callable for tool '{name}', got {type(func).__name__}") + self._tools[name] = func + return self + def _convert_inputs_to_json_schema(self, inputs_def: dict[str, Any]) -> dict[str, Any]: """Convert a declarative inputs definition to JSON Schema. diff --git a/python/packages/declarative/tests/test_declarative_loader.py b/python/packages/declarative/tests/test_declarative_loader.py index bd58e0044a..aee0d762d9 100644 --- a/python/packages/declarative/tests/test_declarative_loader.py +++ b/python/packages/declarative/tests/test_declarative_loader.py @@ -961,6 +961,423 @@ def test_mcp_tool_with_remote_connection_with_endpoint(self): assert mcp_tool.get("project_connection_id") == "my-oauth-connection" +class TestAgentFactoryFilePath: + """Tests for AgentFactory file path operations.""" + + def test_create_agent_from_yaml_path_file_not_found(self, tmp_path): + """Test that nonexistent file raises DeclarativeLoaderError.""" + from agent_framework_declarative import AgentFactory + from agent_framework_declarative._loader import DeclarativeLoaderError + + factory = AgentFactory() + with pytest.raises(DeclarativeLoaderError, match="YAML file not found"): + factory.create_agent_from_yaml_path(tmp_path / "nonexistent.yaml") + + def test_create_agent_from_yaml_path_with_string_path(self, tmp_path): + """Test create_agent_from_yaml_path accepts string path.""" + from unittest.mock import MagicMock + + from agent_framework_declarative import AgentFactory + + yaml_file = tmp_path / "agent.yaml" + yaml_file.write_text(""" +kind: Prompt +name: FileAgent +instructions: Test agent from file +""") + + mock_client = MagicMock() + factory = AgentFactory(client=mock_client) + agent = factory.create_agent_from_yaml_path(str(yaml_file)) + + assert agent.name == "FileAgent" + + def test_create_agent_from_yaml_path_with_path_object(self, tmp_path): + """Test create_agent_from_yaml_path accepts Path object.""" + from unittest.mock import MagicMock + + from agent_framework_declarative import AgentFactory + + yaml_file = tmp_path / "agent.yaml" + yaml_file.write_text(""" +kind: Prompt +name: PathAgent +instructions: Test agent from Path +""") + + mock_client = MagicMock() + factory = AgentFactory(client=mock_client) + agent = factory.create_agent_from_yaml_path(yaml_file) + + assert agent.name == "PathAgent" + + +class TestAgentFactoryAsyncMethods: + """Tests for AgentFactory async methods.""" + + @pytest.mark.asyncio + async def test_create_agent_from_yaml_path_async_file_not_found(self, tmp_path): + """Test async version raises DeclarativeLoaderError for nonexistent file.""" + from agent_framework_declarative import AgentFactory + from agent_framework_declarative._loader import DeclarativeLoaderError + + factory = AgentFactory() + with pytest.raises(DeclarativeLoaderError, match="YAML file not found"): + await factory.create_agent_from_yaml_path_async(tmp_path / "nonexistent.yaml") + + @pytest.mark.asyncio + async def test_create_agent_from_yaml_async_with_client(self): + """Test async creation with pre-configured client.""" + from unittest.mock import MagicMock + + from agent_framework_declarative import AgentFactory + + yaml_content = """ +kind: Prompt +name: AsyncAgent +instructions: Test async agent +""" + + mock_client = MagicMock() + factory = AgentFactory(client=mock_client) + agent = await factory.create_agent_from_yaml_async(yaml_content) + + assert agent.name == "AsyncAgent" + + @pytest.mark.asyncio + async def test_create_agent_from_dict_async_with_client(self): + """Test async dict creation with pre-configured client.""" + from unittest.mock import MagicMock + + from agent_framework_declarative import AgentFactory + + agent_def = { + "kind": "Prompt", + "name": "AsyncDictAgent", + "instructions": "Test async dict agent", + } + + mock_client = MagicMock() + factory = AgentFactory(client=mock_client) + agent = await factory.create_agent_from_dict_async(agent_def) + + assert agent.name == "AsyncDictAgent" + + @pytest.mark.asyncio + async def test_create_agent_from_dict_async_invalid_kind_raises(self): + """Test that async version also raises for non-PromptAgent.""" + from agent_framework_declarative import AgentFactory + from agent_framework_declarative._loader import DeclarativeLoaderError + + agent_def = { + "kind": "Resource", + "name": "NotAnAgent", + } + + factory = AgentFactory() + with pytest.raises(DeclarativeLoaderError, match="Only definitions for a PromptAgent are supported"): + await factory.create_agent_from_dict_async(agent_def) + + @pytest.mark.asyncio + async def test_create_agent_from_yaml_path_async_with_string_path(self, tmp_path): + """Test async version accepts string path.""" + from unittest.mock import MagicMock + + from agent_framework_declarative import AgentFactory + + yaml_file = tmp_path / "async_agent.yaml" + yaml_file.write_text(""" +kind: Prompt +name: AsyncPathAgent +instructions: Test async path agent +""") + + mock_client = MagicMock() + factory = AgentFactory(client=mock_client) + agent = await factory.create_agent_from_yaml_path_async(str(yaml_file)) + + assert agent.name == "AsyncPathAgent" + + +class TestAgentFactoryProviderLookup: + """Tests for provider configuration lookup.""" + + def test_provider_lookup_error_for_unknown_provider(self): + """Test that unknown provider raises ProviderLookupError.""" + + from agent_framework_declarative import AgentFactory + from agent_framework_declarative._loader import ProviderLookupError + + yaml_content = """ +kind: Prompt +name: TestAgent +instructions: Test agent +model: + id: test-model + provider: UnknownProvider + apiType: UnknownApiType +""" + + factory = AgentFactory() + with pytest.raises(ProviderLookupError, match="Unsupported provider type"): + factory.create_agent_from_yaml(yaml_content) + + def test_additional_mappings_override_default(self): + """Test that additional_mappings can extend provider configurations.""" + from agent_framework_declarative import AgentFactory + + # Define a custom provider mapping + custom_mappings = { + "CustomProvider.Chat": { + "package": "agent_framework.openai", + "name": "OpenAIChatClient", + "model_id_field": "model_id", + }, + } + + factory = AgentFactory(additional_mappings=custom_mappings) + + # The custom mapping should be available + assert "CustomProvider.Chat" in factory.additional_mappings + + +class TestAgentFactoryConnectionHandling: + """Tests for connection handling in AgentFactory.""" + + def test_reference_connection_requires_connections_dict(self): + """Test that ReferenceConnection without connections dict raises.""" + from agent_framework_declarative import AgentFactory + + yaml_content = """ +kind: Prompt +name: TestAgent +instructions: Test agent +model: + id: gpt-4 + provider: OpenAI + apiType: Chat + connection: + kind: reference + name: my-connection +""" + + factory = AgentFactory() # No connections provided + with pytest.raises(ValueError, match="Connections must be provided to resolve ReferenceConnection"): + factory.create_agent_from_yaml(yaml_content) + + def test_reference_connection_not_found_raises(self): + """Test that missing ReferenceConnection raises.""" + from agent_framework_declarative import AgentFactory + + yaml_content = """ +kind: Prompt +name: TestAgent +instructions: Test agent +model: + id: gpt-4 + provider: OpenAI + apiType: Chat + connection: + kind: reference + name: missing-connection +""" + + factory = AgentFactory(connections={"other-connection": "value"}) + with pytest.raises(ValueError, match="not found in provided connections"): + factory.create_agent_from_yaml(yaml_content) + + def test_model_without_id_uses_provided_client(self): + """Test that model without id uses the provided chat_client.""" + from unittest.mock import MagicMock + + from agent_framework_declarative import AgentFactory + + yaml_content = """ +kind: Prompt +name: TestAgent +instructions: Test agent +model: + provider: OpenAI +""" + + mock_client = MagicMock() + factory = AgentFactory(client=mock_client) + agent = factory.create_agent_from_yaml(yaml_content) + + assert agent is not None + + def test_model_without_id_and_no_client_raises(self): + """Test that model without id and no client raises.""" + from agent_framework_declarative import AgentFactory + from agent_framework_declarative._loader import DeclarativeLoaderError + + yaml_content = """ +kind: Prompt +name: TestAgent +instructions: Test agent +model: + provider: OpenAI +""" + + factory = AgentFactory() # No chat_client + with pytest.raises(DeclarativeLoaderError, match="ChatClient must be provided"): + factory.create_agent_from_yaml(yaml_content) + + +class TestAgentFactoryChatOptions: + """Tests for chat options parsing.""" + + def test_parse_chat_options_with_all_fields(self): + """Test parsing all ModelOptions fields into chat options dict.""" + from agent_framework_declarative._loader import AgentFactory + from agent_framework_declarative._models import Model, ModelOptions + + factory = AgentFactory() + + # Create a Model with all options set + options = ModelOptions( + temperature=0.7, + maxOutputTokens=1000, + topP=0.9, + frequencyPenalty=0.5, + presencePenalty=0.3, + seed=42, + stopSequences=["STOP", "END"], + allowMultipleToolCalls=True, + ) + options.additionalProperties["chatToolMode"] = "auto" + + model = Model(id="gpt-4", options=options) + + # Parse the options + chat_options = factory._parse_chat_options(model) + + # Verify all options are parsed correctly + assert chat_options.get("temperature") == 0.7 + assert chat_options.get("max_tokens") == 1000 + assert chat_options.get("top_p") == 0.9 + assert chat_options.get("frequency_penalty") == 0.5 + assert chat_options.get("presence_penalty") == 0.3 + assert chat_options.get("seed") == 42 + assert chat_options.get("stop") == ["STOP", "END"] + assert chat_options.get("allow_multiple_tool_calls") is True + assert chat_options.get("tool_choice") == "auto" + + def test_parse_chat_options_empty_model(self): + """Test that missing model options returns empty dict.""" + from agent_framework_declarative._loader import AgentFactory + + factory = AgentFactory() + result = factory._parse_chat_options(None) + assert result == {} + + def test_parse_chat_options_with_additional_properties(self): + """Test that additional properties are passed through.""" + from agent_framework_declarative._loader import AgentFactory + from agent_framework_declarative._models import Model, ModelOptions + + factory = AgentFactory() + + # Create a Model with additional properties + options = ModelOptions(temperature=0.5) + options.additionalProperties["customOption"] = "customValue" + + model = Model(id="gpt-4", options=options) + + # Parse the options + chat_options = factory._parse_chat_options(model) + + # Verify additional properties are preserved + assert "additional_chat_options" in chat_options + assert chat_options["additional_chat_options"].get("customOption") == "customValue" + + +class TestAgentFactoryToolParsing: + """Tests for tool parsing edge cases.""" + + def test_parse_tools_returns_none_for_empty_list(self): + """Test that empty tools list returns None.""" + from agent_framework_declarative._loader import AgentFactory + + factory = AgentFactory() + result = factory._parse_tools(None) + assert result is None + + result = factory._parse_tools([]) + assert result is None + + def test_parse_function_tool_with_bindings(self): + """Test parsing FunctionTool with bindings.""" + from unittest.mock import MagicMock + + from agent_framework_declarative import AgentFactory + + yaml_content = """ +kind: Prompt +name: TestAgent +instructions: Test agent +tools: + - kind: function + name: my_function + description: A test function + bindings: + - name: my_binding +""" + + def my_function(): + return "result" + + mock_client = MagicMock() + factory = AgentFactory(client=mock_client, bindings={"my_binding": my_function}) + agent = factory.create_agent_from_yaml(yaml_content) + + # Should have parsed the tool with binding + tools = agent.default_options.get("tools", []) + assert len(tools) == 1 + + def test_parse_file_search_tool_with_all_options(self): + """Test parsing FileSearchTool with ranker and filters.""" + from unittest.mock import MagicMock + + from agent_framework_declarative import AgentFactory + + yaml_content = """ +kind: Prompt +name: TestAgent +instructions: Test agent +tools: + - kind: file_search + name: search + description: Search files + vectorStoreIds: + - vs_123 + ranker: semantic + scoreThreshold: 0.8 + maximumResultCount: 10 + filters: + type: document +""" + + mock_client = MagicMock() + factory = AgentFactory(client=mock_client) + agent = factory.create_agent_from_yaml(yaml_content) + + # Verify a file search tool was parsed + tools = agent.default_options.get("tools", []) + assert len(tools) == 1 + + def test_parse_unsupported_tool_kind_raises(self): + """Test that unsupported tool kind raises ValueError.""" + from agent_framework_declarative._loader import AgentFactory + from agent_framework_declarative._models import CustomTool + + factory = AgentFactory() + custom_tool = CustomTool(kind="custom", name="test") + + with pytest.raises(ValueError, match="Unsupported tool kind"): + factory._parse_tool(custom_tool) + + class TestProviderResponseFormat: """response_format from outputSchema must be passed inside default_options.""" diff --git a/python/packages/declarative/tests/test_function_tool_executor.py b/python/packages/declarative/tests/test_function_tool_executor.py new file mode 100644 index 0000000000..f11b356865 --- /dev/null +++ b/python/packages/declarative/tests/test_function_tool_executor.py @@ -0,0 +1,1378 @@ +# Copyright (c) Microsoft. All rights reserved. + +"""Tests for InvokeFunctionTool executor. + +These tests verify: +- Basic function invocation (sync and async) +- Expression evaluation for functionName and arguments +- Output formatting (messages and result) +- Error handling (function not found, execution errors) +- WorkflowFactory registration +- Approval flow (requireApproval=true with yield/resume) +- Variable path normalization +- Non-callable tool error handling +- JSON serialization fallbacks +""" + +import sys +from typing import Any +from unittest.mock import AsyncMock, MagicMock + +import pytest + +try: + import powerfx # noqa: F401 + + _powerfx_available = True +except (ImportError, RuntimeError): + _powerfx_available = False + +pytestmark = pytest.mark.skipif( + not _powerfx_available or sys.version_info >= (3, 14), + reason="PowerFx engine not available (requires dotnet runtime)", +) + +from agent_framework_declarative._workflows import ( # noqa: E402 + DECLARATIVE_STATE_KEY, + FUNCTION_TOOL_REGISTRY_KEY, + TOOL_APPROVAL_STATE_KEY, + ActionComplete, + ActionTrigger, + DeclarativeWorkflowBuilder, + InvokeFunctionToolExecutor, + ToolApprovalRequest, + ToolApprovalResponse, + ToolApprovalState, + ToolInvocationResult, + WorkflowFactory, +) +from agent_framework_declarative._workflows._executors_tools import ( # noqa: E402 + _normalize_variable_path, +) + + +class TestInvokeFunctionToolExecutor: + """Tests for InvokeFunctionToolExecutor.""" + + @pytest.mark.asyncio + async def test_basic_sync_function_invocation(self): + """Test invoking a simple synchronous function.""" + + def get_weather(location: str, unit: str = "F") -> dict: + return {"temp": 72, "unit": unit, "location": location} + + yaml_def = { + "name": "function_tool_test", + "actions": [ + {"kind": "SetValue", "id": "set_location", "path": "Local.city", "value": "Seattle"}, + { + "kind": "InvokeFunctionTool", + "id": "call_weather", + "functionName": "get_weather", + "arguments": {"location": "=Local.city", "unit": "C"}, + "output": {"result": "Local.weatherData"}, + }, + # Use SendActivity to output the result so we can check it + {"kind": "SendActivity", "id": "output_location", "activity": {"text": "=Local.weatherData.location"}}, + {"kind": "SendActivity", "id": "output_unit", "activity": {"text": "=Local.weatherData.unit"}}, + ], + } + + builder = DeclarativeWorkflowBuilder(yaml_def, tools={"get_weather": get_weather}) + workflow = builder.build() + + events = await workflow.run({}) + outputs = events.get_outputs() + + # Verify the function was called with correct arguments + assert "Seattle" in outputs # location + assert "C" in outputs # unit + + @pytest.mark.asyncio + async def test_async_function_invocation(self): + """Test invoking an async function.""" + + async def fetch_data(url: str) -> dict: + return {"url": url, "status": "success"} + + yaml_def = { + "name": "async_function_test", + "actions": [ + { + "kind": "InvokeFunctionTool", + "id": "fetch", + "functionName": "fetch_data", + "arguments": {"url": "https://example.com/api"}, + "output": {"result": "Local.response"}, + }, + {"kind": "SendActivity", "id": "output_url", "activity": {"text": "=Local.response.url"}}, + {"kind": "SendActivity", "id": "output_status", "activity": {"text": "=Local.response.status"}}, + ], + } + + builder = DeclarativeWorkflowBuilder(yaml_def, tools={"fetch_data": fetch_data}) + workflow = builder.build() + + events = await workflow.run({}) + outputs = events.get_outputs() + + assert "https://example.com/api" in outputs + assert "success" in outputs + + @pytest.mark.asyncio + async def test_expression_function_name(self): + """Test dynamic function name via expression.""" + + def tool_a() -> str: + return "result_a" + + def tool_b() -> str: + return "result_b" + + yaml_def = { + "name": "dynamic_function_name_test", + "actions": [ + {"kind": "SetValue", "id": "set_tool", "path": "Local.toolName", "value": "tool_b"}, + { + "kind": "InvokeFunctionTool", + "id": "dynamic_call", + "functionName": "=Local.toolName", + "arguments": {}, + "output": {"result": "Local.result"}, + }, + {"kind": "SendActivity", "id": "output", "activity": {"text": "=Local.result"}}, + ], + } + + builder = DeclarativeWorkflowBuilder(yaml_def, tools={"tool_a": tool_a, "tool_b": tool_b}) + workflow = builder.build() + + events = await workflow.run({}) + outputs = events.get_outputs() + + assert "result_b" in outputs + + @pytest.mark.asyncio + async def test_function_not_found(self): + """Test error handling when function is not in registry.""" + yaml_def = { + "name": "function_not_found_test", + "actions": [ + { + "kind": "InvokeFunctionTool", + "id": "call_missing", + "functionName": "nonexistent_function", + "arguments": {}, + "output": {"result": "Local.result"}, + }, + # Check if error is stored + {"kind": "SendActivity", "id": "output", "activity": {"text": "=Local.result.error"}}, + ], + } + + builder = DeclarativeWorkflowBuilder(yaml_def, tools={}) # Empty registry + workflow = builder.build() + + events = await workflow.run({}) + outputs = events.get_outputs() + + # Result should contain error info + assert "not found" in outputs[0].lower() + + @pytest.mark.asyncio + async def test_function_execution_error(self): + """Test error handling when function raises exception.""" + + def failing_function() -> str: + raise ValueError("Intentional test error") + + yaml_def = { + "name": "function_error_test", + "actions": [ + { + "kind": "InvokeFunctionTool", + "id": "call_failing", + "functionName": "failing_function", + "arguments": {}, + "output": {"result": "Local.result"}, + }, + {"kind": "SendActivity", "id": "output", "activity": {"text": "=Local.result.error"}}, + ], + } + + builder = DeclarativeWorkflowBuilder(yaml_def, tools={"failing_function": failing_function}) + workflow = builder.build() + + events = await workflow.run({}) + outputs = events.get_outputs() + + # Result should contain error info + assert "Intentional test error" in outputs[0] + + @pytest.mark.asyncio + async def test_function_with_no_output_config(self): + """Test that function works even without output configuration.""" + + counter = {"value": 0} + + def increment() -> int: + counter["value"] += 1 + return counter["value"] + + yaml_def = { + "name": "no_output_test", + "actions": [ + { + "kind": "InvokeFunctionTool", + "id": "increment_call", + "functionName": "increment", + "arguments": {}, + # No output configuration + }, + {"kind": "SendActivity", "id": "done", "activity": {"text": "Done"}}, + ], + } + + builder = DeclarativeWorkflowBuilder(yaml_def, tools={"increment": increment}) + workflow = builder.build() + + events = await workflow.run({}) + outputs = events.get_outputs() + + # Workflow should complete + assert "Done" in outputs + # Function should have been called + assert counter["value"] == 1 + + +class TestInvokeFunctionToolWithWorkflowFactory: + """Tests for InvokeFunctionTool with WorkflowFactory registration.""" + + @pytest.mark.asyncio + async def test_register_tool_method(self): + """Test registering tools via WorkflowFactory.register_tool().""" + + def multiply(a: int, b: int) -> int: + return a * b + + yaml_content = """ +name: factory_tool_test +actions: + - kind: InvokeFunctionTool + id: multiply_call + functionName: multiply + arguments: + a: 6 + b: 7 + output: + result: Local.product + - kind: SendActivity + id: output + activity: + text: =Local.product +""" + factory = WorkflowFactory().register_tool("multiply", multiply) + workflow = factory.create_workflow_from_yaml(yaml_content) + + events = await workflow.run({}) + outputs = events.get_outputs() + + # PowerFx outputs integers as floats, so we check for 42 or 42.0 + assert any("42" in out for out in outputs) + + @pytest.mark.asyncio + async def test_fluent_registration(self): + """Test fluent chaining for tool registration.""" + + def add(a: int, b: int) -> int: + return a + b + + def subtract(a: int, b: int) -> int: + return a - b + + yaml_content = """ +name: fluent_test +actions: + - kind: InvokeFunctionTool + id: add_call + functionName: add + arguments: + a: 10 + b: 5 + output: + result: Local.sum + - kind: InvokeFunctionTool + id: subtract_call + functionName: subtract + arguments: + a: 10 + b: 5 + output: + result: Local.diff + - kind: SendActivity + id: output_sum + activity: + text: =Local.sum + - kind: SendActivity + id: output_diff + activity: + text: =Local.diff +""" + factory = WorkflowFactory().register_tool("add", add).register_tool("subtract", subtract) + + workflow = factory.create_workflow_from_yaml(yaml_content) + + events = await workflow.run({}) + outputs = events.get_outputs() + + # PowerFx outputs integers as floats, so we check for 15 or 15.0 + assert any("15" in out for out in outputs) # sum + assert any("5" in out for out in outputs) # diff + + +class TestToolInvocationResult: + """Tests for ToolInvocationResult dataclass.""" + + def test_success_result(self): + """Test creating a successful result.""" + result = ToolInvocationResult( + success=True, + result={"data": "value"}, + messages=[], + ) + assert result.success is True + assert result.result == {"data": "value"} + assert result.rejected is False + assert result.error is None + + def test_error_result(self): + """Test creating an error result.""" + result = ToolInvocationResult( + success=False, + error="Function failed", + ) + assert result.success is False + assert result.error == "Function failed" + assert result.result is None + + def test_rejected_result(self): + """Test creating a rejected result.""" + result = ToolInvocationResult( + success=False, + rejected=True, + rejection_reason="User denied approval", + ) + assert result.success is False + assert result.rejected is True + assert result.rejection_reason == "User denied approval" + + +class TestToolApprovalTypes: + """Tests for approval-related dataclasses.""" + + def test_approval_request(self): + """Test creating an approval request.""" + request = ToolApprovalRequest( + request_id="test-123", + function_name="dangerous_operation", + arguments={"target": "production"}, + ) + assert request.request_id == "test-123" + assert request.function_name == "dangerous_operation" + assert request.arguments == {"target": "production"} + + def test_approval_response_approved(self): + """Test creating an approved response.""" + response = ToolApprovalResponse(approved=True) + assert response.approved is True + assert response.reason is None + + def test_approval_response_rejected(self): + """Test creating a rejected response.""" + response = ToolApprovalResponse(approved=False, reason="Not authorized") + assert response.approved is False + assert response.reason == "Not authorized" + + def test_approval_state(self): + """Test creating approval state for yield/resume.""" + state = ToolApprovalState( + function_name="delete_user", + arguments={"user_id": "123"}, + output_messages_var="Local.messages", + output_result_var="Local.result", + auto_send=True, + ) + assert state.function_name == "delete_user" + assert state.arguments == {"user_id": "123"} + assert state.output_messages_var == "Local.messages" + assert state.output_result_var == "Local.result" + assert state.auto_send is True + + +class TestInvokeFunctionToolEdgeCases: + """Tests for edge cases and error handling.""" + + def test_missing_function_name_field_raises_validation_error(self): + """Test that missing functionName raises validation error at build time.""" + yaml_def = { + "name": "missing_function_name_test", + "actions": [ + { + "kind": "InvokeFunctionTool", + "id": "no_name", + # Missing functionName field + "arguments": {}, + }, + ], + } + + builder = DeclarativeWorkflowBuilder(yaml_def, tools={}) + + # Should raise validation error + with pytest.raises(ValueError, match="missing required field 'functionName'"): + builder.build() + + @pytest.mark.asyncio + async def test_empty_function_name_expression(self): + """Test handling when functionName expression evaluates to empty.""" + yaml_def = { + "name": "empty_function_name_test", + "actions": [ + {"kind": "SetValue", "id": "set_empty", "path": "Local.toolName", "value": ""}, + { + "kind": "InvokeFunctionTool", + "id": "empty_name", + "functionName": "=Local.toolName", + "arguments": {}, + }, + {"kind": "SendActivity", "id": "done", "activity": {"text": "Completed"}}, + ], + } + + builder = DeclarativeWorkflowBuilder(yaml_def, tools={}) + workflow = builder.build() + + events = await workflow.run({}) + outputs = events.get_outputs() + + # Should complete without crashing + assert "Completed" in outputs + + @pytest.mark.asyncio + async def test_messages_output_configuration(self): + """Test that messages output stores Message list.""" + + def simple_func(x: int) -> int: + return x * 2 + + yaml_def = { + "name": "messages_output_test", + "actions": [ + { + "kind": "InvokeFunctionTool", + "id": "call_func", + "functionName": "simple_func", + "arguments": {"x": 5}, + "output": { + "messages": "Local.toolMessages", + "result": "Local.result", + }, + }, + {"kind": "SendActivity", "id": "output_result", "activity": {"text": "=Local.result"}}, + ], + } + + builder = DeclarativeWorkflowBuilder(yaml_def, tools={"simple_func": simple_func}) + workflow = builder.build() + + events = await workflow.run({}) + outputs = events.get_outputs() + + # Result should be doubled + assert any("10" in out for out in outputs) + + @pytest.mark.asyncio + async def test_function_returning_none(self): + """Test handling function that returns None.""" + + def returns_none() -> None: + pass + + yaml_def = { + "name": "returns_none_test", + "actions": [ + { + "kind": "InvokeFunctionTool", + "id": "call_none", + "functionName": "returns_none", + "arguments": {}, + "output": {"result": "Local.result"}, + }, + {"kind": "SendActivity", "id": "done", "activity": {"text": "Completed"}}, + ], + } + + builder = DeclarativeWorkflowBuilder(yaml_def, tools={"returns_none": returns_none}) + workflow = builder.build() + + events = await workflow.run({}) + outputs = events.get_outputs() + + assert "Completed" in outputs + + @pytest.mark.asyncio + async def test_function_with_complex_return_type(self): + """Test function returning complex nested data.""" + + def complex_return() -> dict: + return { + "nested": { + "array": [1, 2, 3], + "string": "test", + }, + "boolean": True, + "number": 42.5, + } + + yaml_def = { + "name": "complex_return_test", + "actions": [ + { + "kind": "InvokeFunctionTool", + "id": "call_complex", + "functionName": "complex_return", + "arguments": {}, + "output": {"result": "Local.data"}, + }, + {"kind": "SendActivity", "id": "output", "activity": {"text": "=Local.data.nested.string"}}, + ], + } + + builder = DeclarativeWorkflowBuilder(yaml_def, tools={"complex_return": complex_return}) + workflow = builder.build() + + events = await workflow.run({}) + outputs = events.get_outputs() + + assert "test" in outputs + + @pytest.mark.asyncio + async def test_function_with_list_argument(self): + """Test passing list as argument.""" + + def sum_list(numbers: list) -> int: + return sum(numbers) + + yaml_def = { + "name": "list_argument_test", + "actions": [ + {"kind": "SetValue", "id": "set_list", "path": "Local.numbers", "value": [1, 2, 3, 4, 5]}, + { + "kind": "InvokeFunctionTool", + "id": "call_sum", + "functionName": "sum_list", + "arguments": {"numbers": "=Local.numbers"}, + "output": {"result": "Local.total"}, + }, + {"kind": "SendActivity", "id": "output", "activity": {"text": "=Local.total"}}, + ], + } + + builder = DeclarativeWorkflowBuilder(yaml_def, tools={"sum_list": sum_list}) + workflow = builder.build() + + events = await workflow.run({}) + outputs = events.get_outputs() + + assert any("15" in out for out in outputs) + + @pytest.mark.asyncio + async def test_auto_send_disabled(self): + """Test autoSend=false prevents automatic output yielding.""" + + def echo_id(msg: str) -> str: + return msg + + yaml_def = { + "name": "auto_send_disabled_test", + "actions": [ + { + "kind": "InvokeFunctionTool", + "id": "call_no_auto_send", + "functionName": "echo_id", + "arguments": {"msg": "hello"}, + "output": {"result": "Local.result", "autoSend": False}, + }, + {"kind": "SendActivity", "id": "output", "activity": {"text": "=Local.result"}}, + ], + } + + builder = DeclarativeWorkflowBuilder(yaml_def, tools={"echo_id": echo_id}) + workflow = builder.build() + + events = await workflow.run({}) + outputs = events.get_outputs() + + # Result should still be available via explicit SendActivity + assert "hello" in outputs + + @pytest.mark.asyncio + async def test_function_with_only_result_output(self): + """Test output config with only result, no messages.""" + + def double(x: int) -> int: + return x * 2 + + yaml_def = { + "name": "result_only_test", + "actions": [ + { + "kind": "InvokeFunctionTool", + "id": "call_double", + "functionName": "double", + "arguments": {"x": 21}, + "output": {"result": "Local.doubled"}, + }, + {"kind": "SendActivity", "id": "output", "activity": {"text": "=Local.doubled"}}, + ], + } + + builder = DeclarativeWorkflowBuilder(yaml_def, tools={"double": double}) + workflow = builder.build() + + events = await workflow.run({}) + outputs = events.get_outputs() + + assert any("42" in out for out in outputs) + + @pytest.mark.asyncio + async def test_function_with_only_messages_output(self): + """Test output config with only messages, no result.""" + + def simple() -> str: + return "done" + + yaml_def = { + "name": "messages_only_test", + "actions": [ + { + "kind": "InvokeFunctionTool", + "id": "call_simple", + "functionName": "simple", + "arguments": {}, + "output": {"messages": "Local.msgs"}, + }, + {"kind": "SendActivity", "id": "done", "activity": {"text": "Completed"}}, + ], + } + + builder = DeclarativeWorkflowBuilder(yaml_def, tools={"simple": simple}) + workflow = builder.build() + + events = await workflow.run({}) + outputs = events.get_outputs() + + assert "Completed" in outputs + + @pytest.mark.asyncio + async def test_function_string_return(self): + """Test function that returns a simple string.""" + + def greet(name: str) -> str: + return f"Hello, {name}!" + + yaml_def = { + "name": "string_return_test", + "actions": [ + { + "kind": "InvokeFunctionTool", + "id": "call_greet", + "functionName": "greet", + "arguments": {"name": "World"}, + "output": {"result": "Local.greeting"}, + }, + {"kind": "SendActivity", "id": "output", "activity": {"text": "=Local.greeting"}}, + ], + } + + builder = DeclarativeWorkflowBuilder(yaml_def, tools={"greet": greet}) + workflow = builder.build() + + events = await workflow.run({}) + outputs = events.get_outputs() + + assert "Hello, World!" in outputs + + +class TestInvokeFunctionToolBuilder: + """Tests for InvokeFunctionTool executor registration in builder.""" + + def test_executor_registered_in_all_executors(self): + """Test that InvokeFunctionTool is registered in ALL_ACTION_EXECUTORS.""" + from agent_framework_declarative._workflows import ALL_ACTION_EXECUTORS + + assert "InvokeFunctionTool" in ALL_ACTION_EXECUTORS + assert ALL_ACTION_EXECUTORS["InvokeFunctionTool"] == InvokeFunctionToolExecutor + + def test_builder_creates_tool_executor(self): + """Test that builder creates InvokeFunctionToolExecutor for InvokeFunctionTool actions.""" + + def dummy() -> str: + return "test" + + yaml_def = { + "name": "builder_test", + "actions": [ + { + "kind": "InvokeFunctionTool", + "id": "my_tool", + "functionName": "dummy", + "arguments": {}, + }, + ], + } + + builder = DeclarativeWorkflowBuilder(yaml_def, tools={"dummy": dummy}) + _ = builder.build() + + # Verify the executor was created + assert "my_tool" in builder._executors + executor = builder._executors["my_tool"] + assert isinstance(executor, InvokeFunctionToolExecutor) + + +# ============================================================================ +# Helper: Mock State and Context +# ============================================================================ + + +@pytest.fixture +def mock_state() -> MagicMock: + """Create a mock state with sync get/set/delete methods.""" + mock_state = MagicMock() + mock_state._data = {} + + def mock_get(key: str, default: Any = None) -> Any: + if key not in mock_state._data: + if default is not None: + return default + raise KeyError(key) + return mock_state._data[key] + + def mock_set(key: str, value: Any) -> None: + mock_state._data[key] = value + + def mock_has(key: str) -> bool: + return key in mock_state._data + + def mock_delete(key: str) -> None: + if key in mock_state._data: + del mock_state._data[key] + else: + raise KeyError(key) + + mock_state.get = MagicMock(side_effect=mock_get) + mock_state.set = MagicMock(side_effect=mock_set) + mock_state.has = MagicMock(side_effect=mock_has) + mock_state.delete = MagicMock(side_effect=mock_delete) + + return mock_state + + +@pytest.fixture +def mock_context(mock_state: MagicMock) -> MagicMock: + """Create a mock workflow context.""" + ctx = MagicMock() + ctx.state = mock_state + ctx.send_message = AsyncMock() + ctx.yield_output = AsyncMock() + ctx.request_info = AsyncMock() + return ctx + + +# ============================================================================ +# _normalize_variable_path unit tests (lines 153-155) +# ============================================================================ + + +class TestNormalizeVariablePath: + """Tests for _normalize_variable_path helper.""" + + def test_known_prefix_local(self): + assert _normalize_variable_path("Local.myVar") == "Local.myVar" + + def test_known_prefix_system(self): + assert _normalize_variable_path("System.ConversationId") == "System.ConversationId" + + def test_known_prefix_workflow(self): + assert _normalize_variable_path("Workflow.Inputs.x") == "Workflow.Inputs.x" + + def test_known_prefix_agent(self): + assert _normalize_variable_path("Agent.LastResponse") == "Agent.LastResponse" + + def test_known_prefix_conversation(self): + assert _normalize_variable_path("Conversation.messages") == "Conversation.messages" + + def test_dotted_unknown_prefix(self): + """Dotted path without a known prefix is returned as-is.""" + assert _normalize_variable_path("Custom.myVar") == "Custom.myVar" + + def test_bare_name_gets_local_prefix(self): + """Bare name without any dots defaults to Local. prefix.""" + assert _normalize_variable_path("weatherResult") == "Local.weatherResult" + + def test_bare_name_with_underscore(self): + assert _normalize_variable_path("my_var") == "Local.my_var" + + +# ============================================================================ +# Non-dict output config (line 275) +# ============================================================================ + + +class TestNonDictOutputConfig: + """Tests for non-dict output config handling.""" + + @pytest.mark.asyncio + async def test_output_as_string_is_ignored(self): + """When output is a string instead of dict, both vars should be None.""" + + def noop() -> str: + return "done" + + action_def = { + "kind": "InvokeFunctionTool", + "id": "test_nondictoutput", + "functionName": "noop", + "arguments": {}, + "output": "Local.result", # wrong: should be dict + } + + executor = InvokeFunctionToolExecutor(action_def, tools={"noop": noop}) + messages_var, result_var, auto_send = executor._get_output_config() + assert messages_var is None + assert result_var is None + assert auto_send is True + + @pytest.mark.asyncio + async def test_output_as_list_is_ignored(self): + """When output is a list instead of dict, both vars should be None.""" + + def noop() -> str: + return "done" + + action_def = { + "kind": "InvokeFunctionTool", + "id": "test_listoutput", + "functionName": "noop", + "arguments": {}, + "output": ["Local.result"], + } + + executor = InvokeFunctionToolExecutor(action_def, tools={"noop": noop}) + messages_var, result_var, auto_send = executor._get_output_config() + assert messages_var is None + assert result_var is None + assert auto_send is True + + +# ============================================================================ +# Non-callable tool error (line 696) +# ============================================================================ + + +class TestNonCallableTool: + """Tests for non-callable tool invocation.""" + + @pytest.mark.asyncio + async def test_non_callable_stores_error(self): + """Non-callable tool should produce an error result.""" + yaml_def = { + "name": "non_callable_test", + "actions": [ + { + "kind": "InvokeFunctionTool", + "id": "call_noncallable", + "functionName": "not_a_func", + "arguments": {}, + "output": {"result": "Local.result"}, + }, + {"kind": "SendActivity", "id": "output", "activity": {"text": "=Local.result.error"}}, + ], + } + + builder = DeclarativeWorkflowBuilder(yaml_def, tools={"not_a_func": "i_am_a_string"}) + workflow = builder.build() + + events = await workflow.run({}) + outputs = events.get_outputs() + + assert any("not callable" in out.lower() for out in outputs) + + +# ============================================================================ +# Non-dict arguments warning (line 491) +# ============================================================================ + + +class TestNonDictArguments: + """Tests for non-dict arguments handling.""" + + @pytest.mark.asyncio + async def test_non_dict_arguments_ignored(self): + """When arguments is not a dict, it should be ignored with a warning.""" + + def no_args_needed() -> str: + return "ok" + + yaml_def = { + "name": "nondict_args_test", + "actions": [ + { + "kind": "InvokeFunctionTool", + "id": "call_with_bad_args", + "functionName": "no_args_needed", + "arguments": "invalid_string_args", + "output": {"result": "Local.result"}, + }, + {"kind": "SendActivity", "id": "output", "activity": {"text": "=Local.result"}}, + ], + } + + builder = DeclarativeWorkflowBuilder(yaml_def, tools={"no_args_needed": no_args_needed}) + workflow = builder.build() + + events = await workflow.run({}) + outputs = events.get_outputs() + + assert "ok" in outputs + + +# ============================================================================ +# JSON serialization fallbacks (lines 351-353, 369-371) +# ============================================================================ + + +class TestFormatMessagesSerialization: + """Tests for JSON serialization fallbacks in _format_messages.""" + + @pytest.mark.asyncio + async def test_non_serializable_result_uses_str_fallback(self): + """When the function returns a non-JSON-serializable object, str() is used.""" + + class CustomObj: + def __str__(self): + return "custom_string_repr" + + def returns_custom() -> object: + return CustomObj() + + yaml_def = { + "name": "nonserializable_result_test", + "actions": [ + { + "kind": "InvokeFunctionTool", + "id": "call_custom", + "functionName": "returns_custom", + "arguments": {}, + "output": {"messages": "Local.msgs", "result": "Local.result"}, + }, + {"kind": "SendActivity", "id": "done", "activity": {"text": "Done"}}, + ], + } + + builder = DeclarativeWorkflowBuilder(yaml_def, tools={"returns_custom": returns_custom}) + workflow = builder.build() + + events = await workflow.run({}) + outputs = events.get_outputs() + + # Should complete without crashing + assert "Done" in outputs + + @pytest.mark.asyncio + async def test_format_messages_directly_with_non_serializable(self): + """Directly test _format_messages with non-serializable arguments and result.""" + + class Unserializable: + def __str__(self): + return "unserializable_obj" + + action_def = { + "kind": "InvokeFunctionTool", + "id": "test_serialize", + "functionName": "dummy", + } + executor = InvokeFunctionToolExecutor(action_def, tools={}) + + # Non-serializable arguments + messages = await executor._format_messages( + function_name="test_func", + arguments={"obj": Unserializable()}, + result=Unserializable(), + ) + + # Should produce 2 messages (tool_call + tool_result) without crashing + assert len(messages) == 2 + assert messages[0].role == "assistant" + assert messages[1].role == "tool" + + +# ============================================================================ +# Approval flow tests (lines 512-532, 557-613) +# ============================================================================ + + +class TestApprovalFlow: + """Tests for the requireApproval=true flow with yield/resume pattern.""" + + def _init_state(self, mock_state: MagicMock) -> None: + """Pre-populate the state with declarative workflow data so _ensure_state_initialized works.""" + from agent_framework_declarative._workflows import DECLARATIVE_STATE_KEY + + mock_state._data[DECLARATIVE_STATE_KEY] = { + "Inputs": {}, + "Outputs": {}, + "Local": {}, + "System": { + "ConversationId": "test-conv", + "LastMessage": {"Text": "", "Id": ""}, + "LastMessageText": "", + "LastMessageId": "", + }, + "Agent": {}, + "Conversation": {"messages": [], "history": []}, + } + + @pytest.mark.asyncio + async def test_approval_required_emits_request(self, mock_state, mock_context): + """When requireApproval=true, handle_action should emit ToolApprovalRequest and return.""" + self._init_state(mock_state) + + def my_tool(x: int) -> int: + return x * 2 + + action_def = { + "kind": "InvokeFunctionTool", + "id": "approval_test", + "functionName": "my_tool", + "requireApproval": True, + "arguments": {"x": 5}, + "output": {"result": "Local.result"}, + } + + executor = InvokeFunctionToolExecutor(action_def, tools={"my_tool": my_tool}) + + await executor.handle_action(ActionTrigger(), mock_context) + + # Should have called request_info with ToolApprovalRequest + mock_context.request_info.assert_called_once() + request = mock_context.request_info.call_args[0][0] + assert isinstance(request, ToolApprovalRequest) + assert request.function_name == "my_tool" + assert request.arguments == {"x": 5} + + # Should NOT have sent ActionComplete (workflow yields) + mock_context.send_message.assert_not_called() + + # Approval state should be saved in state + approval_key = f"{TOOL_APPROVAL_STATE_KEY}_approval_test" + saved_state = mock_state._data[approval_key] + assert isinstance(saved_state, ToolApprovalState) + assert saved_state.function_name == "my_tool" + assert saved_state.arguments == {"x": 5} + + @pytest.mark.asyncio + async def test_approval_response_approved(self, mock_state, mock_context): + """When approval response is approved, the tool should be invoked.""" + self._init_state(mock_state) + + call_log = [] + + def my_tool(x: int) -> int: + call_log.append(x) + return x * 2 + + action_def = { + "kind": "InvokeFunctionTool", + "id": "approval_approved", + "functionName": "my_tool", + "requireApproval": True, + "arguments": {"x": 7}, + "output": {"result": "Local.result"}, + } + + executor = InvokeFunctionToolExecutor(action_def, tools={"my_tool": my_tool}) + + # Pre-populate approval state (simulating what handle_action stores) + approval_key = f"{TOOL_APPROVAL_STATE_KEY}_approval_approved" + mock_state._data[approval_key] = ToolApprovalState( + function_name="my_tool", + arguments={"x": 7}, + output_messages_var=None, + output_result_var="Local.result", + auto_send=True, + ) + + # Simulate the response + original_request = ToolApprovalRequest( + request_id="req-123", + function_name="my_tool", + arguments={"x": 7}, + ) + response = ToolApprovalResponse(approved=True) + + await executor.handle_approval_response(original_request, response, mock_context) + + # Tool should have been called + assert call_log == [7] + + # ActionComplete should have been sent + mock_context.send_message.assert_called_once() + sent = mock_context.send_message.call_args[0][0] + assert isinstance(sent, ActionComplete) + + # Approval state should be cleaned up + assert approval_key not in mock_state._data + + @pytest.mark.asyncio + async def test_approval_response_rejected(self, mock_state, mock_context): + """When approval response is rejected, rejection status should be stored.""" + self._init_state(mock_state) + + def my_tool(x: int) -> int: + raise AssertionError("Should not be called when rejected") + + action_def = { + "kind": "InvokeFunctionTool", + "id": "approval_rejected", + "functionName": "my_tool", + "requireApproval": True, + "arguments": {"x": 5}, + "output": {"result": "Local.result"}, + } + + executor = InvokeFunctionToolExecutor(action_def, tools={"my_tool": my_tool}) + + # Pre-populate approval state + approval_key = f"{TOOL_APPROVAL_STATE_KEY}_approval_rejected" + mock_state._data[approval_key] = ToolApprovalState( + function_name="my_tool", + arguments={"x": 5}, + output_messages_var=None, + output_result_var="Local.result", + auto_send=True, + ) + + original_request = ToolApprovalRequest( + request_id="req-456", + function_name="my_tool", + arguments={"x": 5}, + ) + response = ToolApprovalResponse(approved=False, reason="Not authorized") + + await executor.handle_approval_response(original_request, response, mock_context) + + # ActionComplete should have been sent + mock_context.send_message.assert_called_once() + + # Result var should contain rejection info + state_data = mock_state._data.get(DECLARATIVE_STATE_KEY, {}) + local_data = state_data.get("Local", {}) + result = local_data.get("result") + assert result is not None + assert result["rejected"] is True + assert result["reason"] == "Not authorized" + assert result["approved"] is False + + @pytest.mark.asyncio + async def test_approval_response_missing_state(self, mock_state, mock_context): + """When approval state is missing on resume, should log error and complete.""" + self._init_state(mock_state) + + action_def = { + "kind": "InvokeFunctionTool", + "id": "missing_state_test", + "functionName": "my_tool", + "requireApproval": True, + "output": {"result": "Local.result"}, + } + + executor = InvokeFunctionToolExecutor(action_def, tools={}) + + # Don't populate approval state - simulate missing state + original_request = ToolApprovalRequest( + request_id="req-789", + function_name="my_tool", + arguments={}, + ) + response = ToolApprovalResponse(approved=True) + + await executor.handle_approval_response(original_request, response, mock_context) + + # Should still send ActionComplete + mock_context.send_message.assert_called_once() + sent = mock_context.send_message.call_args[0][0] + assert isinstance(sent, ActionComplete) + + +# ============================================================================ +# State registry tool lookup (lines 255-257) +# ============================================================================ + + +class TestStateRegistryLookup: + """Tests for tool lookup from State registry.""" + + @pytest.mark.asyncio + async def test_tool_found_in_state_registry(self, mock_state, mock_context): + """Tool should be found from State registry when not in constructor tools.""" + self._init_state(mock_state) + + def state_registered_tool() -> str: + return "from_state" + + # Register tool in State registry + mock_state._data[FUNCTION_TOOL_REGISTRY_KEY] = {"state_tool": state_registered_tool} + + action_def = { + "kind": "InvokeFunctionTool", + "id": "state_lookup", + "functionName": "state_tool", + "arguments": {}, + "output": {"result": "Local.result"}, + } + + # Empty constructor tools - should fall back to State registry + executor = InvokeFunctionToolExecutor(action_def, tools={}) + + tool = executor._get_tool("state_tool", mock_context) + assert tool is state_registered_tool + + def _init_state(self, mock_state: MagicMock) -> None: + from agent_framework_declarative._workflows import DECLARATIVE_STATE_KEY + + mock_state._data[DECLARATIVE_STATE_KEY] = { + "Inputs": {}, + "Outputs": {}, + "Local": {}, + "System": { + "ConversationId": "test-conv", + "LastMessage": {"Text": "", "Id": ""}, + "LastMessageText": "", + "LastMessageId": "", + }, + "Agent": {}, + "Conversation": {"messages": [], "history": []}, + } + + @pytest.mark.asyncio + async def test_tool_not_found_in_state_registry_key_error(self, mock_state, mock_context): + """When State registry key doesn't exist, should return None.""" + # Don't populate FUNCTION_TOOL_REGISTRY_KEY - will raise KeyError + + action_def = { + "kind": "InvokeFunctionTool", + "id": "missing_registry", + "functionName": "missing", + } + + executor = InvokeFunctionToolExecutor(action_def, tools={}) + + tool = executor._get_tool("missing", mock_context) + assert tool is None + + @pytest.mark.asyncio + async def test_tool_not_in_registry_returns_none(self, mock_state, mock_context): + """When State registry exists but tool isn't in it, should return None.""" + mock_state._data[FUNCTION_TOOL_REGISTRY_KEY] = {"other_tool": lambda: None} + + action_def = { + "kind": "InvokeFunctionTool", + "id": "wrong_name", + "functionName": "missing", + } + + executor = InvokeFunctionToolExecutor(action_def, tools={}) + + tool = executor._get_tool("missing", mock_context) + assert tool is None + + +# ============================================================================ +# Missing/empty functionName at runtime (lines 470-475, 482) +# ============================================================================ + + +class TestMissingFunctionNameRuntime: + """Tests for missing/empty functionName at runtime with result_var.""" + + def _init_state(self, mock_state: MagicMock) -> None: + from agent_framework_declarative._workflows import DECLARATIVE_STATE_KEY + + mock_state._data[DECLARATIVE_STATE_KEY] = { + "Inputs": {}, + "Outputs": {}, + "Local": {}, + "System": { + "ConversationId": "test-conv", + "LastMessage": {"Text": "", "Id": ""}, + "LastMessageText": "", + "LastMessageId": "", + }, + "Agent": {}, + "Conversation": {"messages": [], "history": []}, + } + + @pytest.mark.asyncio + async def test_missing_function_name_stores_error_in_result_var(self, mock_state, mock_context): + """Missing functionName should store error in result_var and complete.""" + self._init_state(mock_state) + + action_def = { + "kind": "InvokeFunctionTool", + "id": "no_name", + # No functionName field + "output": {"result": "Local.errorResult"}, + } + + executor = InvokeFunctionToolExecutor(action_def, tools={}) + + await executor.handle_action(ActionTrigger(), mock_context) + + # Should send ActionComplete + mock_context.send_message.assert_called_once() + sent = mock_context.send_message.call_args[0][0] + assert isinstance(sent, ActionComplete) + + # Error should be stored in result_var + state_data = mock_state._data.get("_declarative_workflow_state", {}) + local_data = state_data.get("Local", {}) + assert "error" in local_data.get("errorResult", {}) + + @pytest.mark.asyncio + async def test_empty_function_name_with_result_var(self, mock_state, mock_context): + """Empty functionName expression should store error in result_var.""" + self._init_state(mock_state) + + # Pre-set an empty value for toolName + mock_state._data["_declarative_workflow_state"]["Local"]["toolName"] = "" + + action_def = { + "kind": "InvokeFunctionTool", + "id": "empty_name", + "functionName": "=Local.toolName", + "output": {"result": "Local.errorResult"}, + } + + executor = InvokeFunctionToolExecutor(action_def, tools={}) + + await executor.handle_action(ActionTrigger(), mock_context) + + # Should send ActionComplete + mock_context.send_message.assert_called_once() + + # Error should be stored in result_var + state_data = mock_state._data.get("_declarative_workflow_state", {}) + local_data = state_data.get("Local", {}) + assert "error" in local_data.get("errorResult", {}) diff --git a/python/packages/declarative/tests/test_graph_coverage.py b/python/packages/declarative/tests/test_graph_coverage.py index a8115e832d..2088162a28 100644 --- a/python/packages/declarative/tests/test_graph_coverage.py +++ b/python/packages/declarative/tests/test_graph_coverage.py @@ -21,6 +21,15 @@ LoopIterationResult, ) +try: + import powerfx # noqa: F401 + + _powerfx_available = True +except (ImportError, RuntimeError): + _powerfx_available = False + +_requires_powerfx = pytest.mark.skipif(not _powerfx_available, reason="PowerFx engine not available") + # --------------------------------------------------------------------------- # Fixtures # --------------------------------------------------------------------------- @@ -250,6 +259,7 @@ async def test_eval_non_string_returns_as_is(self, mock_state): result = state.eval([1, 2, 3]) # type: ignore[arg-type] assert result == [1, 2, 3] + @_requires_powerfx async def test_eval_simple_and_operator(self, mock_state): """Test simple And operator evaluation.""" state = DeclarativeWorkflowState(mock_state) @@ -264,6 +274,7 @@ async def test_eval_simple_and_operator(self, mock_state): result = state.eval("=Local.a And Local.b") assert result is True + @_requires_powerfx async def test_eval_simple_or_operator(self, mock_state): """Test simple Or operator evaluation.""" state = DeclarativeWorkflowState(mock_state) @@ -278,6 +289,7 @@ async def test_eval_simple_or_operator(self, mock_state): result = state.eval("=Local.a Or Local.b") assert result is False + @_requires_powerfx async def test_eval_negation(self, mock_state): """Test negation (!) evaluation.""" state = DeclarativeWorkflowState(mock_state) @@ -287,6 +299,7 @@ async def test_eval_negation(self, mock_state): result = state.eval("=!Local.flag") assert result is False + @_requires_powerfx async def test_eval_not_function(self, mock_state): """Test Not() function evaluation.""" state = DeclarativeWorkflowState(mock_state) @@ -296,6 +309,7 @@ async def test_eval_not_function(self, mock_state): result = state.eval("=Not(Local.flag)") assert result is False + @_requires_powerfx async def test_eval_comparison_operators(self, mock_state): """Test comparison operators.""" state = DeclarativeWorkflowState(mock_state) @@ -310,6 +324,7 @@ async def test_eval_comparison_operators(self, mock_state): assert state.eval("=Local.x <> Local.y") is True assert state.eval("=Local.x = 5") is True + @_requires_powerfx async def test_eval_arithmetic_operators(self, mock_state): """Test arithmetic operators.""" state = DeclarativeWorkflowState(mock_state) @@ -322,6 +337,7 @@ async def test_eval_arithmetic_operators(self, mock_state): assert state.eval("=Local.x * Local.y") == 30 assert state.eval("=Local.x / Local.y") == pytest.approx(3.333, rel=0.01) + @_requires_powerfx async def test_eval_string_literal(self, mock_state): """Test string literal evaluation.""" state = DeclarativeWorkflowState(mock_state) @@ -330,6 +346,7 @@ async def test_eval_string_literal(self, mock_state): result = state.eval('="hello world"') assert result == "hello world" + @_requires_powerfx async def test_eval_float_literal(self, mock_state): """Test float literal evaluation.""" from decimal import Decimal @@ -341,6 +358,7 @@ async def test_eval_float_literal(self, mock_state): # Accepts both float (Python fallback) and Decimal (pythonnet/PowerFx) assert result == 3.14 or result == Decimal("3.14") + @_requires_powerfx async def test_eval_variable_reference_with_namespace_mappings(self, mock_state): """Test variable reference with PowerFx symbols.""" state = DeclarativeWorkflowState(mock_state) @@ -355,6 +373,7 @@ async def test_eval_variable_reference_with_namespace_mappings(self, mock_state) result = state.eval("=Workflow.Inputs.query") assert result == "test" + @_requires_powerfx async def test_eval_if_expression_with_dict(self, mock_state): """Test eval_if_expression recursively evaluates dicts.""" state = DeclarativeWorkflowState(mock_state) @@ -364,6 +383,7 @@ async def test_eval_if_expression_with_dict(self, mock_state): result = state.eval_if_expression({"greeting": "=Local.name", "static": "hello"}) assert result == {"greeting": "Alice", "static": "hello"} + @_requires_powerfx async def test_eval_if_expression_with_list(self, mock_state): """Test eval_if_expression recursively evaluates lists.""" state = DeclarativeWorkflowState(mock_state) @@ -449,6 +469,7 @@ async def test_set_variable_executor_with_nested_variable(self, mock_context, mo result = state.get("Local.nested") assert result == 42 + @_requires_powerfx async def test_set_text_variable_executor(self, mock_context, mock_state): """Test SetTextVariableExecutor.""" from agent_framework_declarative._workflows._executors_basic import ( @@ -591,6 +612,7 @@ async def test_send_activity_with_string_activity(self, mock_context, mock_state mock_context.yield_output.assert_called_once_with("Plain text message") + @_requires_powerfx async def test_send_activity_with_expression(self, mock_context, mock_state): """Test SendActivityExecutor evaluates expressions.""" from agent_framework_declarative._workflows._executors_basic import ( @@ -909,6 +931,7 @@ async def test_agent_executor_get_output_config_full(self, mock_context, mock_st assert result_prop == "Local.result" assert auto_send is False + @_requires_powerfx async def test_agent_executor_build_input_text_from_string_messages(self, mock_context, mock_state): """Test _build_input_text with string messages expression.""" from agent_framework_declarative._workflows._executors_agents import ( @@ -925,6 +948,7 @@ async def test_agent_executor_build_input_text_from_string_messages(self, mock_c input_text = await executor._build_input_text(state, {}, "=Local.userInput") assert input_text == "Hello agent!" + @_requires_powerfx async def test_agent_executor_build_input_text_from_message_list(self, mock_context, mock_state): """Test _build_input_text extracts text from message list.""" from agent_framework_declarative._workflows._executors_agents import ( @@ -948,6 +972,7 @@ async def test_agent_executor_build_input_text_from_message_list(self, mock_cont input_text = await executor._build_input_text(state, {}, "=Conversation.messages") assert input_text == "Last message" + @_requires_powerfx async def test_agent_executor_build_input_text_from_message_with_text_attr(self, mock_context, mock_state): """Test _build_input_text extracts text from message with text attribute.""" from agent_framework_declarative._workflows._executors_agents import ( @@ -1120,83 +1145,6 @@ class MockResult: parsed = state.get("Local.Parsed") assert parsed == {"status": "ok", "count": 42} - async def test_invoke_tool_executor_not_found(self, mock_context, mock_state): - """Test InvokeToolExecutor when tool not found.""" - from agent_framework_declarative._workflows._executors_agents import ( - InvokeToolExecutor, - ) - - state = DeclarativeWorkflowState(mock_state) - state.initialize() - - action_def = { - "kind": "InvokeTool", - "tool": "MissingTool", - "resultProperty": "Local.result", - } - executor = InvokeToolExecutor(action_def) - - await executor.handle_action(ActionTrigger(), mock_context) - - result = state.get("Local.result") - assert result == {"error": "Tool 'MissingTool' not found in registry"} - - async def test_invoke_tool_executor_sync_tool(self, mock_context, mock_state): - """Test InvokeToolExecutor with synchronous tool.""" - from agent_framework_declarative._workflows._executors_agents import ( - TOOL_REGISTRY_KEY, - InvokeToolExecutor, - ) - - def my_tool(x: int, y: int) -> int: - return x + y - - mock_state._data[TOOL_REGISTRY_KEY] = {"add": my_tool} - - state = DeclarativeWorkflowState(mock_state) - state.initialize() - - action_def = { - "kind": "InvokeTool", - "tool": "add", - "parameters": {"x": 5, "y": 3}, - "resultProperty": "Local.result", - } - executor = InvokeToolExecutor(action_def) - - await executor.handle_action(ActionTrigger(), mock_context) - - result = state.get("Local.result") - assert result == 8 - - async def test_invoke_tool_executor_async_tool(self, mock_context, mock_state): - """Test InvokeToolExecutor with asynchronous tool.""" - from agent_framework_declarative._workflows._executors_agents import ( - TOOL_REGISTRY_KEY, - InvokeToolExecutor, - ) - - async def my_async_tool(input: str) -> str: - return f"Processed: {input}" - - mock_state._data[TOOL_REGISTRY_KEY] = {"process": my_async_tool} - - state = DeclarativeWorkflowState(mock_state) - state.initialize() - - action_def = { - "kind": "InvokeTool", - "tool": "process", - "input": "test data", - "resultProperty": "Local.result", - } - executor = InvokeToolExecutor(action_def) - - await executor.handle_action(ActionTrigger(), mock_context) - - result = state.get("Local.result") - assert result == "Processed: test data" - # --------------------------------------------------------------------------- # Control Flow Executors Tests - Additional coverage @@ -1206,6 +1154,7 @@ async def my_async_tool(input: str) -> str: class TestControlFlowCoverage: """Tests for control flow executors covering uncovered code paths.""" + @_requires_powerfx async def test_foreach_with_source_alias(self, mock_context, mock_state): """Test ForeachInitExecutor with 'source' alias (interpreter mode).""" from agent_framework_declarative._workflows._executors_control_flow import ( @@ -1268,6 +1217,7 @@ async def test_foreach_next_continues_iteration(self, mock_context, mock_state): assert msg.current_index == 1 assert msg.current_item == "b" + @_requires_powerfx async def test_switch_evaluator_with_value_cases(self, mock_context, mock_state): """Test SwitchEvaluatorExecutor with value/cases schema.""" from agent_framework_declarative._workflows._executors_control_flow import ( @@ -1295,6 +1245,7 @@ async def test_switch_evaluator_with_value_cases(self, mock_context, mock_state) assert msg.matched is True assert msg.branch_index == 1 # Second case matched + @_requires_powerfx async def test_switch_evaluator_default_case(self, mock_context, mock_state): """Test SwitchEvaluatorExecutor falls through to default.""" from agent_framework_declarative._workflows._executors_control_flow import ( @@ -1554,6 +1505,7 @@ async def test_end_conversation_executor(self, mock_context, mock_state): # Should NOT send any message mock_context.send_message.assert_not_called() + @_requires_powerfx async def test_condition_group_evaluator_first_match(self, mock_context, mock_state): """Test ConditionGroupEvaluatorExecutor returns first match.""" from agent_framework_declarative._workflows._executors_control_flow import ( @@ -1579,6 +1531,7 @@ async def test_condition_group_evaluator_first_match(self, mock_context, mock_st assert msg.matched is True assert msg.branch_index == 1 # Second condition (x > 5) is first match + @_requires_powerfx async def test_condition_group_evaluator_no_match(self, mock_context, mock_state): """Test ConditionGroupEvaluatorExecutor with no matches.""" from agent_framework_declarative._workflows._executors_control_flow import ( @@ -1603,6 +1556,7 @@ async def test_condition_group_evaluator_no_match(self, mock_context, mock_state assert msg.matched is False assert msg.branch_index == -1 + @_requires_powerfx async def test_condition_group_evaluator_boolean_true_condition(self, mock_context, mock_state): """Test ConditionGroupEvaluatorExecutor with boolean True condition.""" from agent_framework_declarative._workflows._executors_control_flow import ( @@ -1626,6 +1580,7 @@ async def test_condition_group_evaluator_boolean_true_condition(self, mock_conte assert msg.matched is True assert msg.branch_index == 1 + @_requires_powerfx async def test_if_condition_evaluator_true(self, mock_context, mock_state): """Test IfConditionEvaluatorExecutor with true condition.""" from agent_framework_declarative._workflows._executors_control_flow import ( @@ -1646,6 +1601,7 @@ async def test_if_condition_evaluator_true(self, mock_context, mock_state): assert msg.matched is True assert msg.branch_index == 0 # Then branch + @_requires_powerfx async def test_if_condition_evaluator_false(self, mock_context, mock_state): """Test IfConditionEvaluatorExecutor with false condition.""" from agent_framework_declarative._workflows._executors_control_flow import ( @@ -1894,6 +1850,7 @@ async def test_question_executor_with_choices(self, mock_context, mock_state): class TestAgentExternalLoopCoverage: """Tests for agent executor external loop handling.""" + @_requires_powerfx async def test_agent_executor_with_external_loop(self, mock_context, mock_state): """Test agent executor with external loop that triggers.""" from unittest.mock import patch @@ -1996,39 +1953,13 @@ async def test_agent_executor_string_result(self, mock_context, mock_state): result = state.get("Local.result") assert result == "Direct string response" - async def test_invoke_tool_with_error(self, mock_context, mock_state): - """Test InvokeToolExecutor handles tool errors.""" - from agent_framework_declarative._workflows._executors_agents import ( - TOOL_REGISTRY_KEY, - InvokeToolExecutor, - ) - - def failing_tool(**kwargs): - raise ValueError("Tool error") - - mock_state._data[TOOL_REGISTRY_KEY] = {"bad_tool": failing_tool} - - state = DeclarativeWorkflowState(mock_state) - state.initialize() - - action_def = { - "kind": "InvokeTool", - "tool": "bad_tool", - "resultProperty": "Local.result", - } - executor = InvokeToolExecutor(action_def) - - await executor.handle_action(ActionTrigger(), mock_context) - - result = state.get("Local.result") - assert result == {"error": "Tool error"} - # --------------------------------------------------------------------------- # PowerFx Functions Coverage # --------------------------------------------------------------------------- +@_requires_powerfx class TestPowerFxFunctionsCoverage: """Tests for PowerFx function evaluation coverage.""" @@ -2784,6 +2715,7 @@ def test_validation_in_foreach_body(self): assert "activity" in str(exc_info.value) +@_requires_powerfx class TestExpressionEdgeCases: """Tests for expression evaluation edge cases.""" @@ -2808,6 +2740,7 @@ async def test_multiplication_normal(self, mock_state): assert result == 42 +@_requires_powerfx class TestLongMessageTextHandling: """Tests for handling long MessageText results that exceed PowerFx limits.""" diff --git a/python/packages/declarative/tests/test_graph_executors.py b/python/packages/declarative/tests/test_graph_executors.py index 412ef12f76..14ed33db51 100644 --- a/python/packages/declarative/tests/test_graph_executors.py +++ b/python/packages/declarative/tests/test_graph_executors.py @@ -7,7 +7,16 @@ import pytest -from agent_framework_declarative._workflows import ( +try: + import powerfx # noqa: F401 + + _powerfx_available = True +except (ImportError, RuntimeError): + _powerfx_available = False + +_requires_powerfx = pytest.mark.skipif(not _powerfx_available, reason="PowerFx engine not available") + +from agent_framework_declarative._workflows import ( # noqa: E402 ALL_ACTION_EXECUTORS, DECLARATIVE_STATE_KEY, ActionComplete, @@ -99,6 +108,7 @@ async def test_append_value(self, mock_state): result = state.get("Local.items") assert result == ["first", "second"] + @_requires_powerfx @pytest.mark.asyncio async def test_eval_expression(self, mock_state): """Test evaluating expressions.""" @@ -196,6 +206,7 @@ async def test_send_activity_executor(self, mock_context, mock_state): # Note: ConditionEvaluatorExecutor tests removed - conditions are now evaluated on edges + @_requires_powerfx async def test_foreach_init_with_items(self, mock_context, mock_state): """Test ForeachInitExecutor with items.""" state = DeclarativeWorkflowState(mock_state) @@ -529,6 +540,7 @@ async def test_confirmation_executor(self, mock_context, mock_state): assert "continue" in request.message.lower() +@_requires_powerfx class TestParseValueExecutor: """Tests for the ParseValue action executor.""" diff --git a/python/packages/declarative/tests/test_graph_workflow_integration.py b/python/packages/declarative/tests/test_graph_workflow_integration.py index b7bd08e60a..d0cba5148b 100644 --- a/python/packages/declarative/tests/test_graph_workflow_integration.py +++ b/python/packages/declarative/tests/test_graph_workflow_integration.py @@ -9,13 +9,27 @@ - Pause/resume capabilities """ +import sys + import pytest -from agent_framework_declarative._workflows import ( +try: + import powerfx # noqa: F401 + + _powerfx_available = True +except (ImportError, RuntimeError): + _powerfx_available = False + +pytestmark = pytest.mark.skipif( + not _powerfx_available or sys.version_info >= (3, 14), + reason="PowerFx engine not available (requires dotnet runtime)", +) + +from agent_framework_declarative._workflows import ( # noqa: E402 ActionTrigger, DeclarativeWorkflowBuilder, ) -from agent_framework_declarative._workflows._factory import WorkflowFactory +from agent_framework_declarative._workflows._factory import WorkflowFactory # noqa: E402 class TestGraphBasedWorkflowExecution: diff --git a/python/packages/declarative/tests/test_powerfx_functions.py b/python/packages/declarative/tests/test_powerfx_functions.py index 050fa96786..6c9752f79c 100644 --- a/python/packages/declarative/tests/test_powerfx_functions.py +++ b/python/packages/declarative/tests/test_powerfx_functions.py @@ -237,6 +237,444 @@ def test_all_functions_registered(self): "Lower", "Concat", "Search", + "If", + "Or", + "And", + "Not", + "AgentMessage", + "ForAll", ] for name in expected: assert name in CUSTOM_FUNCTIONS + + +class TestMessageTextEdgeCases: + """Additional tests for message_text edge cases.""" + + def test_message_text_dict_with_text_attr_content(self): + """Test message with content that has text attribute.""" + + class ContentWithText: # noqa: B903 + def __init__(self, text: str): + self.text = text + + msg = {"role": "assistant", "content": ContentWithText("Hello from text attr")} + assert message_text(msg) == "Hello from text attr" + + def test_message_text_dict_content_non_string(self): + """Test message with non-string content.""" + msg = {"role": "assistant", "content": 42} + assert message_text(msg) == "42" + + def test_message_text_list_with_string_items(self): + """Test message_text with list of strings.""" + result = message_text(["Hello", "World"]) + assert result == "Hello World" + + def test_message_text_list_with_content_objects(self): + """Test message_text with list items having content attribute.""" + + class MessageObj: # noqa: B903 + def __init__(self, content: str): + self.content = content + + msgs = [MessageObj("Hello"), MessageObj("World")] + result = message_text(msgs) + assert result == "Hello World" + + def test_message_text_list_with_content_text_attr(self): + """Test message_text with content having text attribute.""" + + class ContentWithText: # noqa: B903 + def __init__(self, text: str): + self.text = text + + class MessageObj: + def __init__(self, content): + self.content = content + + msgs = [MessageObj(ContentWithText("Part1")), MessageObj(ContentWithText("Part2"))] + result = message_text(msgs) + assert result == "Part1 Part2" + + def test_message_text_list_with_non_string_content(self): + """Test message_text with non-string content in dicts.""" + msgs = [{"content": 123}, {"content": 456}] + result = message_text(msgs) + assert result == "123 456" + + def test_message_text_object_with_text_attr(self): + """Test message_text with object having text attribute.""" + + class ObjWithText: + text = "Direct text" + + result = message_text(ObjWithText()) + assert result == "Direct text" + + def test_message_text_object_with_content_attr(self): + """Test message_text with object having content attribute.""" + + class ObjWithContent: + content = "Direct content" + + result = message_text(ObjWithContent()) + assert result == "Direct content" + + def test_message_text_object_with_non_string_content(self): + """Test message_text with object having non-string content.""" + + class ObjWithContent: + content = None + + result = message_text(ObjWithContent()) + assert result == "" + + def test_message_text_list_with_empty_content_object(self): + """Test message with content object that evaluates to empty.""" + + class MessageObj: + content = None + + result = message_text([MessageObj()]) + assert result == "" + + +class TestAgentMessage: + """Tests for agent_message function.""" + + def test_agent_message_creates_dict(self): + """Test that AgentMessage creates correct dict.""" + from agent_framework_declarative._workflows._powerfx_functions import agent_message + + msg = agent_message("Hello") + assert msg == {"role": "assistant", "content": "Hello"} + + def test_agent_message_with_none(self): + """Test AgentMessage with None.""" + from agent_framework_declarative._workflows._powerfx_functions import agent_message + + msg = agent_message(None) + assert msg == {"role": "assistant", "content": ""} + + +class TestIfFunc: + """Tests for if_func conditional function.""" + + def test_if_true_condition(self): + """Test If with true condition.""" + from agent_framework_declarative._workflows._powerfx_functions import if_func + + assert if_func(True, "yes", "no") == "yes" + + def test_if_false_condition(self): + """Test If with false condition.""" + from agent_framework_declarative._workflows._powerfx_functions import if_func + + assert if_func(False, "yes", "no") == "no" + + def test_if_truthy_value(self): + """Test If with truthy value.""" + from agent_framework_declarative._workflows._powerfx_functions import if_func + + assert if_func(1, "yes", "no") == "yes" + assert if_func("non-empty", "yes", "no") == "yes" + + def test_if_falsy_value(self): + """Test If with falsy value.""" + from agent_framework_declarative._workflows._powerfx_functions import if_func + + assert if_func(0, "yes", "no") == "no" + assert if_func("", "yes", "no") == "no" + assert if_func(None, "yes", "no") == "no" + + def test_if_no_false_value(self): + """Test If with no false value defaults to None.""" + from agent_framework_declarative._workflows._powerfx_functions import if_func + + assert if_func(False, "yes") is None + + +class TestOrFunc: + """Tests for or_func function.""" + + def test_or_all_false(self): + """Test Or with all false values.""" + from agent_framework_declarative._workflows._powerfx_functions import or_func + + assert or_func(False, False, False) is False + + def test_or_one_true(self): + """Test Or with one true value.""" + from agent_framework_declarative._workflows._powerfx_functions import or_func + + assert or_func(False, True, False) is True + + def test_or_all_true(self): + """Test Or with all true values.""" + from agent_framework_declarative._workflows._powerfx_functions import or_func + + assert or_func(True, True, True) is True + + def test_or_empty(self): + """Test Or with no arguments.""" + from agent_framework_declarative._workflows._powerfx_functions import or_func + + assert or_func() is False + + +class TestAndFunc: + """Tests for and_func function.""" + + def test_and_all_true(self): + """Test And with all true values.""" + from agent_framework_declarative._workflows._powerfx_functions import and_func + + assert and_func(True, True, True) is True + + def test_and_one_false(self): + """Test And with one false value.""" + from agent_framework_declarative._workflows._powerfx_functions import and_func + + assert and_func(True, False, True) is False + + def test_and_all_false(self): + """Test And with all false values.""" + from agent_framework_declarative._workflows._powerfx_functions import and_func + + assert and_func(False, False, False) is False + + def test_and_empty(self): + """Test And with no arguments.""" + from agent_framework_declarative._workflows._powerfx_functions import and_func + + assert and_func() is True + + +class TestNotFunc: + """Tests for not_func function.""" + + def test_not_true(self): + """Test Not with true.""" + from agent_framework_declarative._workflows._powerfx_functions import not_func + + assert not_func(True) is False + + def test_not_false(self): + """Test Not with false.""" + from agent_framework_declarative._workflows._powerfx_functions import not_func + + assert not_func(False) is True + + def test_not_truthy(self): + """Test Not with truthy values.""" + from agent_framework_declarative._workflows._powerfx_functions import not_func + + assert not_func(1) is False + assert not_func("text") is False + + def test_not_falsy(self): + """Test Not with falsy values.""" + from agent_framework_declarative._workflows._powerfx_functions import not_func + + assert not_func(0) is True + assert not_func("") is True + assert not_func(None) is True + + +class TestIsBlankEdgeCases: + """Additional tests for is_blank edge cases.""" + + def test_is_blank_empty_dict(self): + """Test that empty dict is blank.""" + assert is_blank({}) is True + + def test_is_blank_non_empty_dict(self): + """Test that non-empty dict is not blank.""" + assert is_blank({"key": "value"}) is False + + +class TestCountRowsEdgeCases: + """Additional tests for count_rows edge cases.""" + + def test_count_rows_dict(self): + """Test counting dict items.""" + assert count_rows({"a": 1, "b": 2, "c": 3}) == 3 + + def test_count_rows_tuple(self): + """Test counting tuple items.""" + assert count_rows((1, 2, 3, 4)) == 4 + + def test_count_rows_non_iterable(self): + """Test counting non-iterable returns 0.""" + assert count_rows(42) == 0 + assert count_rows("string") == 0 + + +class TestFirstLastEdgeCases: + """Additional tests for first/last edge cases.""" + + def test_first_none(self): + """Test first with None.""" + assert first(None) is None + + def test_last_none(self): + """Test last with None.""" + assert last(None) is None + + def test_first_tuple(self): + """Test first with tuple.""" + assert first((1, 2, 3)) == 1 + + def test_last_tuple(self): + """Test last with tuple.""" + assert last((1, 2, 3)) == 3 + + +class TestFindEdgeCases: + """Additional tests for find edge cases.""" + + def test_find_none_substring(self): + """Test find with None substring.""" + assert find(None, "text") is None + + def test_find_none_text(self): + """Test find with None text.""" + assert find("sub", None) is None + + def test_find_both_none(self): + """Test find with both None.""" + assert find(None, None) is None + + +class TestLowerEdgeCases: + """Additional tests for lower edge cases.""" + + def test_lower_none(self): + """Test lower with None.""" + assert lower(None) == "" + + +class TestConcatStrings: + """Tests for concat_strings function.""" + + def test_concat_strings_basic(self): + """Test basic string concatenation.""" + from agent_framework_declarative._workflows._powerfx_functions import concat_strings + + assert concat_strings("Hello", " ", "World") == "Hello World" + + def test_concat_strings_with_none(self): + """Test concat with None values.""" + from agent_framework_declarative._workflows._powerfx_functions import concat_strings + + assert concat_strings("Hello", None, "World") == "HelloWorld" + + def test_concat_strings_empty(self): + """Test concat with no arguments.""" + from agent_framework_declarative._workflows._powerfx_functions import concat_strings + + assert concat_strings() == "" + + +class TestConcatTextEdgeCases: + """Additional tests for concat_text edge cases.""" + + def test_concat_text_none(self): + """Test concat_text with None.""" + assert concat_text(None) == "" + + def test_concat_text_non_list(self): + """Test concat_text with non-list.""" + assert concat_text("single value") == "single value" + + def test_concat_text_with_field_attr(self): + """Test concat_text with field as object attribute.""" + + class Item: # noqa: B903 + def __init__(self, name: str): + self.name = name + + items = [Item("Alice"), Item("Bob")] + assert concat_text(items, field="name", separator=", ") == "Alice, Bob" + + def test_concat_text_with_none_values(self): + """Test concat_text with None values in list.""" + items = [{"name": "Alice"}, {"name": None}, {"name": "Bob"}] + result = concat_text(items, field="name", separator=", ") + assert result == "Alice, , Bob" + + +class TestForAll: + """Tests for for_all function.""" + + def test_for_all_with_list_of_dicts(self): + """Test ForAll with list of dictionaries.""" + from agent_framework_declarative._workflows._powerfx_functions import for_all + + items = [{"name": "Alice"}, {"name": "Bob"}] + result = for_all(items, "expression") + assert result == items + + def test_for_all_with_non_dict_items(self): + """Test ForAll with non-dict items.""" + from agent_framework_declarative._workflows._powerfx_functions import for_all + + items = [1, 2, 3] + result = for_all(items, "expression") + assert result == [1, 2, 3] + + def test_for_all_with_none(self): + """Test ForAll with None.""" + from agent_framework_declarative._workflows._powerfx_functions import for_all + + assert for_all(None, "expression") == [] + + def test_for_all_with_non_list(self): + """Test ForAll with non-list.""" + from agent_framework_declarative._workflows._powerfx_functions import for_all + + assert for_all("not a list", "expression") == [] + + def test_for_all_empty_list(self): + """Test ForAll with empty list.""" + from agent_framework_declarative._workflows._powerfx_functions import for_all + + assert for_all([], "expression") == [] + + +class TestSearchTableEdgeCases: + """Additional tests for search_table edge cases.""" + + def test_search_table_none(self): + """Test search_table with None.""" + assert search_table(None, "value", "column") == [] + + def test_search_table_non_list(self): + """Test search_table with non-list.""" + assert search_table("not a list", "value", "column") == [] + + def test_search_table_with_object_attr(self): + """Test search_table with object attributes.""" + + class Item: # noqa: B903 + def __init__(self, name: str): + self.name = name + + items = [Item("Alice"), Item("Bob"), Item("Charlie")] + result = search_table(items, "Bob", "name") + assert len(result) == 1 + assert result[0].name == "Bob" + + def test_search_table_no_matching_column(self): + """Test search_table when items don't have the column.""" + items = [{"other": "value"}] + result = search_table(items, "value", "name") + assert result == [] + + def test_search_table_empty_value(self): + """Test search_table with empty search value.""" + items = [{"name": "Alice"}, {"name": "Bob"}] + result = search_table(items, "", "name") + # Empty string matches everything + assert len(result) == 2 diff --git a/python/packages/declarative/tests/test_powerfx_yaml_compatibility.py b/python/packages/declarative/tests/test_powerfx_yaml_compatibility.py index 72b2d398c5..9591dc05cb 100644 --- a/python/packages/declarative/tests/test_powerfx_yaml_compatibility.py +++ b/python/packages/declarative/tests/test_powerfx_yaml_compatibility.py @@ -20,7 +20,16 @@ import pytest -from agent_framework_declarative._workflows._declarative_base import ( +try: + import powerfx # noqa: F401 + + _powerfx_available = True +except (ImportError, RuntimeError): + _powerfx_available = False + +pytestmark = pytest.mark.skipif(not _powerfx_available, reason="PowerFx engine not available") + +from agent_framework_declarative._workflows._declarative_base import ( # noqa: E402 DeclarativeWorkflowState, ) diff --git a/python/packages/declarative/tests/test_workflow_factory.py b/python/packages/declarative/tests/test_workflow_factory.py index abdd56e6f8..25c1249a50 100644 --- a/python/packages/declarative/tests/test_workflow_factory.py +++ b/python/packages/declarative/tests/test_workflow_factory.py @@ -9,6 +9,15 @@ WorkflowFactory, ) +try: + import powerfx # noqa: F401 + + _powerfx_available = True +except (ImportError, RuntimeError): + _powerfx_available = False + +_requires_powerfx = pytest.mark.skipif(not _powerfx_available, reason="PowerFx engine not available") + class TestWorkflowFactoryValidation: """Tests for workflow definition validation.""" @@ -58,6 +67,7 @@ def test_valid_minimal_workflow(self): assert workflow.name == "minimal-workflow" +@_requires_powerfx class TestWorkflowFactoryExecution: """Tests for workflow execution.""" @@ -204,6 +214,7 @@ def test_load_from_file(self, tmp_path): assert workflow.name == "file-workflow" +@_requires_powerfx class TestDisplayNameMetadata: """Tests for displayName metadata support.""" @@ -231,3 +242,662 @@ async def test_action_with_display_name(self): # Should execute successfully with displayName metadata assert len(outputs) >= 1 + + +class TestWorkflowFactoryToolRegistration: + """Tests for tool registration.""" + + def test_register_tool_basic(self): + """Test registering a tool.""" + + def my_tool(x: int) -> int: + return x * 2 + + factory = WorkflowFactory() + result = factory.register_tool("my_tool", my_tool) + + # Should return self for fluent chaining + assert result is factory + assert "my_tool" in factory._tools + assert factory._tools["my_tool"](5) == 10 + + def test_register_multiple_tools(self): + """Test registering multiple tools with fluent chaining.""" + + def add(a: int, b: int) -> int: + return a + b + + def multiply(a: int, b: int) -> int: + return a * b + + factory = WorkflowFactory().register_tool("add", add).register_tool("multiply", multiply) + + assert "add" in factory._tools + assert "multiply" in factory._tools + assert factory._tools["add"](2, 3) == 5 + assert factory._tools["multiply"](2, 3) == 6 + + def test_register_tool_non_callable_raises(self): + """Test that register_tool raises TypeError for non-callable.""" + factory = WorkflowFactory() + + with pytest.raises(TypeError, match="Expected a callable for tool"): + factory.register_tool("bad_tool", "not_a_function") + + def test_register_binding_non_callable_raises(self): + """Test that register_binding raises TypeError for non-callable.""" + factory = WorkflowFactory() + + with pytest.raises(TypeError, match="Expected a callable for binding"): + factory.register_binding("bad_binding", 42) + + +class TestWorkflowFactoryEdgeCases: + """Tests for edge cases in workflow factory.""" + + def test_empty_actions_list(self): + """Test workflow with empty actions list.""" + factory = WorkflowFactory() + with pytest.raises(DeclarativeWorkflowError, match="actions"): + factory.create_workflow_from_yaml(""" +name: empty-actions +actions: [] +""") + + def test_unknown_action_kind(self): + """Test workflow with unknown action kind.""" + factory = WorkflowFactory() + with pytest.raises((DeclarativeWorkflowError, ValueError)): + factory.create_workflow_from_yaml(""" +name: unknown-action +actions: + - kind: UnknownActionType + value: test +""") + + def test_workflow_with_description(self): + """Test workflow with description field.""" + factory = WorkflowFactory() + workflow = factory.create_workflow_from_yaml(""" +name: described-workflow +description: This is a test workflow +actions: + - kind: SetValue + path: Local.x + value: 1 +""") + + assert workflow is not None + assert workflow.name == "described-workflow" + + @_requires_powerfx + @pytest.mark.asyncio + async def test_workflow_with_expression_value(self): + """Test workflow with expression-based value.""" + factory = WorkflowFactory() + workflow = factory.create_workflow_from_yaml(""" +name: expression-test +actions: + - kind: SetValue + path: Local.x + value: 5 + - kind: SetValue + path: Local.y + value: =Local.x + - kind: SendActivity + activity: + text: =Local.y +""") + + result = await workflow.run({}) + outputs = result.get_outputs() + + assert any("5" in str(o) for o in outputs) + + @_requires_powerfx + @pytest.mark.asyncio + async def test_workflow_with_nested_if(self): + """Test workflow with nested If statements.""" + factory = WorkflowFactory() + workflow = factory.create_workflow_from_yaml(""" +name: nested-if-test +actions: + - kind: SetValue + path: Local.level + value: 2 + - kind: If + condition: true + then: + - kind: If + condition: true + then: + - kind: SendActivity + activity: + text: Nested condition passed +""") + + result = await workflow.run({}) + outputs = result.get_outputs() + + assert any("Nested condition passed" in str(o) for o in outputs) + + def test_load_from_string_path(self, tmp_path): + """Test loading a workflow from a string file path.""" + workflow_file = tmp_path / "workflow.yaml" + workflow_file.write_text(""" +name: string-path-workflow +actions: + - kind: SetValue + path: Local.loaded + value: true +""") + + factory = WorkflowFactory() + # Pass as string instead of Path object + workflow = factory.create_workflow_from_yaml_path(str(workflow_file)) + + assert workflow is not None + assert workflow.name == "string-path-workflow" + + +@_requires_powerfx +class TestWorkflowFactorySwitch: + """Tests for Switch/Case action.""" + + @pytest.mark.asyncio + async def test_switch_with_matching_case(self): + """Test Switch with a matching case.""" + factory = WorkflowFactory() + workflow = factory.create_workflow_from_yaml(""" +name: switch-test +actions: + - kind: SetValue + path: Local.color + value: red + - kind: Switch + value: =Local.color + cases: + - match: red + actions: + - kind: SendActivity + activity: + text: Color is red + - match: blue + actions: + - kind: SendActivity + activity: + text: Color is blue +""") + + result = await workflow.run({}) + outputs = result.get_outputs() + + assert any("Color is red" in str(o) for o in outputs) + + @pytest.mark.asyncio + async def test_switch_with_default(self): + """Test Switch falling through to default.""" + factory = WorkflowFactory() + workflow = factory.create_workflow_from_yaml(""" +name: switch-default-test +actions: + - kind: SetValue + path: Local.color + value: green + - kind: Switch + value: =Local.color + cases: + - match: red + actions: + - kind: SendActivity + activity: + text: Red + - match: blue + actions: + - kind: SendActivity + activity: + text: Blue + default: + - kind: SendActivity + activity: + text: Unknown color +""") + + result = await workflow.run({}) + outputs = result.get_outputs() + + assert any("Unknown color" in str(o) for o in outputs) + + +@_requires_powerfx +class TestWorkflowFactoryMultipleActionTypes: + """Tests for workflows with multiple action types.""" + + @pytest.mark.asyncio + async def test_set_multiple_variables(self): + """Test SetMultipleVariables action.""" + factory = WorkflowFactory() + workflow = factory.create_workflow_from_yaml(""" +name: multi-set-test +actions: + - kind: SetMultipleVariables + variables: + - path: Local.a + value: 1 + - path: Local.b + value: 2 + - path: Local.c + value: 3 + - kind: SendActivity + activity: + text: Done +""") + + result = await workflow.run({}) + outputs = result.get_outputs() + + assert any("Done" in str(o) for o in outputs) + + @pytest.mark.asyncio + async def test_append_value(self): + """Test AppendValue action.""" + factory = WorkflowFactory() + workflow = factory.create_workflow_from_yaml(""" +name: append-test +actions: + - kind: SetValue + path: Local.list + value: [] + - kind: AppendValue + path: Local.list + value: first + - kind: AppendValue + path: Local.list + value: second + - kind: SendActivity + activity: + text: Done +""") + + result = await workflow.run({}) + outputs = result.get_outputs() + + assert any("Done" in str(o) for o in outputs) + + @pytest.mark.asyncio + async def test_emit_event(self): + """Test EmitEvent action.""" + factory = WorkflowFactory() + workflow = factory.create_workflow_from_yaml(""" +name: emit-event-test +actions: + - kind: EmitEvent + event: + name: test_event + data: + message: Hello + - kind: SendActivity + activity: + text: Event emitted +""") + + result = await workflow.run({}) + outputs = result.get_outputs() + + # Workflow should complete + assert any("Event emitted" in str(o) for o in outputs) + + +class TestWorkflowFactoryYamlErrors: + """Tests for YAML parsing error handling.""" + + def test_invalid_yaml_raises(self): + """Test that invalid YAML raises DeclarativeWorkflowError.""" + factory = WorkflowFactory() + with pytest.raises(DeclarativeWorkflowError, match="Invalid YAML"): + factory.create_workflow_from_yaml(""" +name: broken-yaml +actions: + - kind: SetValue + path: Local.x + value: [unclosed bracket +""") + + def test_non_dict_workflow_raises(self): + """Test that non-dict workflow definition raises error.""" + factory = WorkflowFactory() + with pytest.raises(DeclarativeWorkflowError, match="must be a dictionary"): + factory.create_workflow_from_yaml("- just a list item") + + +class TestWorkflowFactoryTriggerFormat: + """Tests for trigger-based workflow format.""" + + def test_trigger_based_workflow(self): + """Test workflow with trigger-based format.""" + factory = WorkflowFactory() + workflow = factory.create_workflow_from_yaml(""" +kind: Workflow +trigger: + kind: OnConversationStart + id: my_trigger + actions: + - kind: SetValue + path: Local.x + value: 1 +""") + + assert workflow is not None + assert workflow.name == "my_trigger" + + def test_trigger_workflow_without_id(self): + """Test trigger workflow without id uses default name.""" + factory = WorkflowFactory() + workflow = factory.create_workflow_from_yaml(""" +kind: Workflow +trigger: + kind: OnConversationStart + actions: + - kind: SetValue + path: Local.x + value: 1 +""") + + assert workflow is not None + assert workflow.name == "declarative_workflow" + + +class TestWorkflowFactoryAgentCreation: + """Tests for agent creation from definitions.""" + + def test_agent_creation_with_file_reference(self, tmp_path): + """Test creating agent from file reference.""" + from unittest.mock import MagicMock + + from agent_framework_declarative import AgentFactory + + # Create a minimal agent YAML file (using Prompt kind) + agent_file = tmp_path / "test_agent.yaml" + agent_file.write_text(""" +kind: Prompt +name: TestAgent +description: A test agent +instructions: You are a test agent. +""") + + # Create a mock client and agent factory + mock_client = MagicMock() + mock_agent = MagicMock() + mock_agent.name = "TestAgent" + mock_client.create_agent.return_value = mock_agent + + agent_factory = AgentFactory(client=mock_client) + + # Create workflow that references the agent + workflow_file = tmp_path / "workflow.yaml" + workflow_file.write_text(f""" +kind: Workflow +agents: + TestAgent: + file: {agent_file.name} +actions: + - kind: SetValue + path: Local.x + value: 1 +""") + + factory = WorkflowFactory(agent_factory=agent_factory) + workflow = factory.create_workflow_from_yaml_path(workflow_file) + + assert workflow is not None + assert "TestAgent" in workflow._declarative_agents + + def test_agent_connection_definition_raises(self): + """Test that connection-based agent definition raises error.""" + factory = WorkflowFactory() + with pytest.raises(DeclarativeWorkflowError, match="Connection-based agents"): + factory.create_workflow_from_yaml(""" +kind: Workflow +agents: + MyAgent: + connection: azure-connection +actions: + - kind: SetValue + path: Local.x + value: 1 +""") + + def test_invalid_agent_definition_raises(self): + """Test that invalid agent definition raises error.""" + factory = WorkflowFactory() + with pytest.raises(DeclarativeWorkflowError, match="Invalid agent definition"): + factory.create_workflow_from_yaml(""" +kind: Workflow +agents: + MyAgent: + unknown_field: value +actions: + - kind: SetValue + path: Local.x + value: 1 +""") + + def test_preregistered_agent_not_overwritten(self): + """Test that pre-registered agents are not overwritten by definitions.""" + + class MockAgent: + name = "PreregisteredAgent" + + factory = WorkflowFactory(agents={"TestAgent": MockAgent()}) + workflow = factory.create_workflow_from_yaml(""" +kind: Workflow +agents: + TestAgent: + kind: Agent + name: OverrideAttempt +actions: + - kind: SetValue + path: Local.x + value: 1 +""") + + assert workflow._declarative_agents["TestAgent"].name == "PreregisteredAgent" + + +class TestWorkflowFactoryInputSchema: + """Tests for input schema conversion.""" + + def test_inputs_to_json_schema_basic(self): + """Test basic input schema conversion.""" + factory = WorkflowFactory() + workflow = factory.create_workflow_from_yaml(""" +name: input-schema-test +inputs: + name: + type: string + description: The user's name + age: + type: integer + description: The user's age +actions: + - kind: SetValue + path: Local.x + value: 1 +""") + + schema = workflow.input_schema + assert schema["type"] == "object" + assert "name" in schema["properties"] + assert "age" in schema["properties"] + assert schema["properties"]["name"]["type"] == "string" + assert schema["properties"]["age"]["type"] == "integer" + assert "name" in schema["required"] + assert "age" in schema["required"] + + def test_inputs_schema_with_optional_field(self): + """Test input schema with optional field.""" + factory = WorkflowFactory() + workflow = factory.create_workflow_from_yaml(""" +name: optional-input-test +inputs: + required_field: + type: string + required: true + optional_field: + type: string + required: false +actions: + - kind: SetValue + path: Local.x + value: 1 +""") + + schema = workflow.input_schema + assert "required_field" in schema["required"] + assert "optional_field" not in schema["required"] + + def test_inputs_schema_with_default_value(self): + """Test input schema with default value.""" + factory = WorkflowFactory() + workflow = factory.create_workflow_from_yaml(""" +name: default-input-test +inputs: + greeting: + type: string + default: Hello +actions: + - kind: SetValue + path: Local.x + value: 1 +""") + + schema = workflow.input_schema + assert schema["properties"]["greeting"]["default"] == "Hello" + + def test_inputs_schema_with_enum(self): + """Test input schema with enum values.""" + factory = WorkflowFactory() + workflow = factory.create_workflow_from_yaml(""" +name: enum-input-test +inputs: + color: + type: string + enum: + - red + - green + - blue +actions: + - kind: SetValue + path: Local.x + value: 1 +""") + + schema = workflow.input_schema + assert schema["properties"]["color"]["enum"] == ["red", "green", "blue"] + + def test_inputs_schema_type_mappings(self): + """Test various type mappings in input schema.""" + factory = WorkflowFactory() + workflow = factory.create_workflow_from_yaml(""" +name: type-mapping-test +inputs: + str_field: + type: str + int_field: + type: int + float_field: + type: float + bool_field: + type: bool + list_field: + type: list + dict_field: + type: dict +actions: + - kind: SetValue + path: Local.x + value: 1 +""") + + schema = workflow.input_schema + assert schema["properties"]["str_field"]["type"] == "string" + assert schema["properties"]["int_field"]["type"] == "integer" + assert schema["properties"]["float_field"]["type"] == "number" + assert schema["properties"]["bool_field"]["type"] == "boolean" + assert schema["properties"]["list_field"]["type"] == "array" + assert schema["properties"]["dict_field"]["type"] == "object" + + def test_inputs_schema_simple_format(self): + """Test simple input format (field: type).""" + factory = WorkflowFactory() + workflow = factory.create_workflow_from_yaml(""" +name: simple-input-test +inputs: + name: string + count: integer +actions: + - kind: SetValue + path: Local.x + value: 1 +""") + + schema = workflow.input_schema + assert schema["properties"]["name"]["type"] == "string" + assert schema["properties"]["count"]["type"] == "integer" + assert "name" in schema["required"] + assert "count" in schema["required"] + + +class TestWorkflowFactoryChaining: + """Tests for fluent method chaining.""" + + def test_fluent_agent_registration(self): + """Test fluent agent registration.""" + + class MockAgent1: + name = "Agent1" + + class MockAgent2: + name = "Agent2" + + factory = WorkflowFactory().register_agent("agent1", MockAgent1()).register_agent("agent2", MockAgent2()) + + assert "agent1" in factory._agents + assert "agent2" in factory._agents + + def test_fluent_binding_registration(self): + """Test fluent binding registration.""" + + def func1(): + return 1 + + def func2(): + return 2 + + factory = WorkflowFactory().register_binding("func1", func1).register_binding("func2", func2) + + assert "func1" in factory._bindings + assert "func2" in factory._bindings + + def test_fluent_mixed_registration(self): + """Test mixed fluent registration.""" + + class MockAgent: + name = "Agent" + + def my_tool(): + return "tool" + + def my_binding(): + return "binding" + + factory = ( + WorkflowFactory() + .register_agent("agent", MockAgent()) + .register_tool("tool", my_tool) + .register_binding("binding", my_binding) + ) + + assert "agent" in factory._agents + assert "tool" in factory._tools + assert "binding" in factory._bindings diff --git a/python/packages/declarative/tests/test_workflow_state.py b/python/packages/declarative/tests/test_workflow_state.py index d1b6002381..c72d85d1ab 100644 --- a/python/packages/declarative/tests/test_workflow_state.py +++ b/python/packages/declarative/tests/test_workflow_state.py @@ -225,6 +225,335 @@ def test_reset_local_preserves_other_state(self): assert state.get("Workflow.Outputs.result") == "done" +class TestWorkflowStateEvalSimple: + """Tests for _eval_simple fallback PowerFx evaluation.""" + + def test_negation_prefix(self): + """Test negation with ! prefix.""" + state = WorkflowState() + state.set("Local.value", True) + assert state._eval_simple("!Local.value") is False + state.set("Local.value", False) + assert state._eval_simple("!Local.value") is True + + def test_not_function(self): + """Test Not() function.""" + state = WorkflowState() + state.set("Local.flag", True) + assert state._eval_simple("Not(Local.flag)") is False + state.set("Local.flag", False) + assert state._eval_simple("Not(Local.flag)") is True + + def test_and_operator(self): + """Test And operator.""" + state = WorkflowState() + state.set("Local.a", True) + state.set("Local.b", True) + assert state._eval_simple("Local.a And Local.b") is True + state.set("Local.b", False) + assert state._eval_simple("Local.a And Local.b") is False + + def test_or_operator(self): + """Test Or operator.""" + state = WorkflowState() + state.set("Local.a", False) + state.set("Local.b", False) + assert state._eval_simple("Local.a Or Local.b") is False + state.set("Local.b", True) + assert state._eval_simple("Local.a Or Local.b") is True + + def test_or_operator_double_pipe(self): + """Test || operator.""" + state = WorkflowState() + state.set("Local.x", False) + state.set("Local.y", True) + assert state._eval_simple("Local.x || Local.y") is True + + def test_less_than(self): + """Test < comparison.""" + state = WorkflowState() + state.set("Local.num", 5) + assert state._eval_simple("Local.num < 10") is True + assert state._eval_simple("Local.num < 3") is False + + def test_greater_than(self): + """Test > comparison.""" + state = WorkflowState() + state.set("Local.num", 5) + assert state._eval_simple("Local.num > 3") is True + assert state._eval_simple("Local.num > 10") is False + + def test_less_than_or_equal(self): + """Test <= comparison.""" + state = WorkflowState() + state.set("Local.num", 5) + assert state._eval_simple("Local.num <= 5") is True + assert state._eval_simple("Local.num <= 4") is False + + def test_greater_than_or_equal(self): + """Test >= comparison.""" + state = WorkflowState() + state.set("Local.num", 5) + assert state._eval_simple("Local.num >= 5") is True + assert state._eval_simple("Local.num >= 6") is False + + def test_not_equal(self): + """Test <> comparison.""" + state = WorkflowState() + state.set("Local.val", "hello") + assert state._eval_simple('Local.val <> "world"') is True + assert state._eval_simple('Local.val <> "hello"') is False + + def test_equal(self): + """Test = comparison.""" + state = WorkflowState() + state.set("Local.val", "test") + assert state._eval_simple('Local.val = "test"') is True + assert state._eval_simple('Local.val = "other"') is False + + def test_addition_numeric(self): + """Test + operator with numbers.""" + state = WorkflowState() + state.set("Local.a", 3) + state.set("Local.b", 4) + assert state._eval_simple("Local.a + Local.b") == 7.0 + + def test_addition_string_concat(self): + """Test + operator falls back to string concat.""" + state = WorkflowState() + state.set("Local.a", "hello") + state.set("Local.b", "world") + assert state._eval_simple("Local.a + Local.b") == "helloworld" + + def test_addition_with_none(self): + """Test + treats None as 0.""" + state = WorkflowState() + state.set("Local.a", 5) + # Local.b doesn't exist, so it's None + assert state._eval_simple("Local.a + Local.b") == 5.0 + + def test_subtraction(self): + """Test - operator.""" + state = WorkflowState() + state.set("Local.a", 10) + state.set("Local.b", 3) + assert state._eval_simple("Local.a - Local.b") == 7.0 + + def test_subtraction_with_none(self): + """Test - treats None as 0.""" + state = WorkflowState() + state.set("Local.a", 5) + assert state._eval_simple("Local.a - Local.missing") == 5.0 + + def test_multiplication(self): + """Test * operator.""" + state = WorkflowState() + state.set("Local.a", 4) + state.set("Local.b", 5) + assert state._eval_simple("Local.a * Local.b") == 20.0 + + def test_multiplication_with_none(self): + """Test * treats None as 0.""" + state = WorkflowState() + state.set("Local.a", 5) + assert state._eval_simple("Local.a * Local.missing") == 0.0 + + def test_division(self): + """Test / operator.""" + state = WorkflowState() + state.set("Local.a", 20) + state.set("Local.b", 4) + assert state._eval_simple("Local.a / Local.b") == 5.0 + + def test_division_by_zero(self): + """Test / by zero returns None.""" + state = WorkflowState() + state.set("Local.a", 10) + state.set("Local.b", 0) + assert state._eval_simple("Local.a / Local.b") is None + + def test_string_literal_double_quotes(self): + """Test string literal with double quotes.""" + state = WorkflowState() + assert state._eval_simple('"hello world"') == "hello world" + + def test_string_literal_single_quotes(self): + """Test string literal with single quotes.""" + state = WorkflowState() + assert state._eval_simple("'hello world'") == "hello world" + + def test_integer_literal(self): + """Test integer literal.""" + state = WorkflowState() + assert state._eval_simple("42") == 42 + + def test_float_literal(self): + """Test float literal.""" + state = WorkflowState() + assert state._eval_simple("3.14") == 3.14 + + def test_boolean_true_literal(self): + """Test true literal (case insensitive).""" + state = WorkflowState() + assert state._eval_simple("true") is True + assert state._eval_simple("True") is True + assert state._eval_simple("TRUE") is True + + def test_boolean_false_literal(self): + """Test false literal (case insensitive).""" + state = WorkflowState() + assert state._eval_simple("false") is False + assert state._eval_simple("False") is False + assert state._eval_simple("FALSE") is False + + def test_variable_reference(self): + """Test simple variable reference.""" + state = WorkflowState() + state.set("Local.myvar", "myvalue") + assert state._eval_simple("Local.myvar") == "myvalue" + + def test_unknown_expression_returned_as_is(self): + """Test that unknown expressions are returned as-is.""" + state = WorkflowState() + result = state._eval_simple("unknown_identifier") + assert result == "unknown_identifier" + + def test_agent_namespace_reference(self): + """Test Agent namespace variable reference.""" + state = WorkflowState() + state.set_agent_result(text="agent response") + assert state._eval_simple("Agent.text") == "agent response" + + def test_conversation_namespace_reference(self): + """Test Conversation namespace variable reference.""" + state = WorkflowState() + state.add_conversation_message({"role": "user", "content": "hello"}) + result = state._eval_simple("Conversation.messages") + assert len(result) == 1 + + def test_workflow_inputs_reference(self): + """Test Workflow.Inputs reference.""" + state = WorkflowState(inputs={"name": "test"}) + assert state._eval_simple("Workflow.Inputs.name") == "test" + + +class TestWorkflowStateParseFunctionArgs: + """Tests for _parse_function_args helper.""" + + def test_simple_args(self): + """Test parsing simple comma-separated args.""" + state = WorkflowState() + args = state._parse_function_args("1, 2, 3") + assert args == ["1", "2", "3"] + + def test_string_args_with_commas(self): + """Test parsing string args containing commas.""" + state = WorkflowState() + args = state._parse_function_args('"hello, world", "another"') + assert args == ['"hello, world"', '"another"'] + + def test_nested_function_args(self): + """Test parsing nested function calls.""" + state = WorkflowState() + args = state._parse_function_args("Concat(a, b), c") + assert args == ["Concat(a, b)", "c"] + + def test_empty_args(self): + """Test parsing empty args string.""" + state = WorkflowState() + args = state._parse_function_args("") + assert args == [] + + def test_single_arg(self): + """Test parsing single argument.""" + state = WorkflowState() + args = state._parse_function_args("single") + assert args == ["single"] + + def test_deeply_nested_parens(self): + """Test parsing deeply nested parentheses.""" + state = WorkflowState() + args = state._parse_function_args("Func1(Func2(a, b)), c") + assert args == ["Func1(Func2(a, b))", "c"] + + +class TestWorkflowStateEvalIfExpression: + """Tests for eval_if_expression method.""" + + def test_dict_values_evaluated(self): + """Test that dict values are recursively evaluated.""" + state = WorkflowState() + state.set("Local.name", "World") + result = state.eval_if_expression({"greeting": "=Local.name", "static": "value"}) + assert result == {"greeting": "World", "static": "value"} + + def test_list_values_evaluated(self): + """Test that list values are recursively evaluated.""" + state = WorkflowState() + state.set("Local.val", 42) + result = state.eval_if_expression(["=Local.val", "static"]) + assert result == [42, "static"] + + def test_nested_dict_in_list(self): + """Test nested dict in list is evaluated.""" + state = WorkflowState() + state.set("Local.x", 10) + result = state.eval_if_expression([{"key": "=Local.x"}]) + assert result == [{"key": 10}] + + +class TestWorkflowStateSetErrors: + """Tests for set() error handling.""" + + def test_set_workflow_directly_raises(self): + """Test that setting Workflow directly raises error.""" + state = WorkflowState() + with pytest.raises(ValueError, match="Cannot set 'Workflow' directly"): + state.set("Workflow", "value") + + def test_set_unknown_workflow_namespace_raises(self): + """Test that setting unknown Workflow sub-namespace raises.""" + state = WorkflowState() + with pytest.raises(ValueError, match="Unknown Workflow namespace"): + state.set("Workflow.Unknown.path", "value") + + def test_set_namespace_root_raises(self): + """Test that setting namespace root raises error.""" + state = WorkflowState() + with pytest.raises(ValueError, match="Cannot replace entire namespace"): + state.set("Local", "value") + + +class TestWorkflowStateGetEdgeCases: + """Tests for get() edge cases.""" + + def test_get_empty_path(self): + """Test get with empty path returns default.""" + state = WorkflowState() + assert state.get("", "default") == "default" + + def test_get_unknown_namespace(self): + """Test get from unknown namespace returns default.""" + state = WorkflowState() + assert state.get("Unknown.path") is None + assert state.get("Unknown.path", "fallback") == "fallback" + + def test_get_with_object_attribute(self): + """Test get navigates object attributes.""" + state = WorkflowState() + + class MockObj: + attr = "attribute_value" + + state.set("Local.obj", MockObj()) + assert state.get("Local.obj.attr") == "attribute_value" + + def test_get_unknown_workflow_subspace(self): + """Test get from unknown Workflow sub-namespace.""" + state = WorkflowState() + assert state.get("Workflow.Unknown.path") is None + + class TestWorkflowStateConversationIdInit: """Tests that WorkflowState generates a real UUID for System.ConversationId.""" diff --git a/python/samples/03-workflows/README.md b/python/samples/03-workflows/README.md index b72cdce54d..c5abe202ac 100644 --- a/python/samples/03-workflows/README.md +++ b/python/samples/03-workflows/README.md @@ -127,16 +127,18 @@ Orchestration-focused samples (Sequential, Concurrent, Handoff, GroupChat, Magen YAML-based declarative workflows allow you to define multi-agent orchestration patterns without writing Python code. See the [declarative workflows README](./declarative/README.md) for more details on YAML workflow syntax and available actions. -| Sample | File | Concepts | -| -------------------- | ------------------------------------------------------------------------ | ------------------------------------------------------------- | -| Conditional Workflow | [declarative/conditional_workflow/](./declarative/conditional_workflow/) | Nested conditional branching based on user input | -| Customer Support | [declarative/customer_support/](./declarative/customer_support/) | Multi-agent customer support with routing | -| Deep Research | [declarative/deep_research/](./declarative/deep_research/) | Research workflow with planning, searching, and synthesis | -| Function Tools | [declarative/function_tools/](./declarative/function_tools/) | Invoking Python functions from declarative workflows | -| Human-in-Loop | [declarative/human_in_loop/](./declarative/human_in_loop/) | Interactive workflows that request user input | -| Marketing | [declarative/marketing/](./declarative/marketing/) | Marketing content generation workflow | -| Simple Workflow | [declarative/simple_workflow/](./declarative/simple_workflow/) | Basic workflow with variable setting, conditionals, and loops | -| Student Teacher | [declarative/student_teacher/](./declarative/student_teacher/) | Student-teacher interaction pattern | +| Sample | File | Concepts | +|---|---|---| +| Agent to Function Tool | [declarative/agent_to_function_tool/](./declarative/agent_to_function_tool/) | Chain agent output to InvokeFunctionTool actions | +| Conditional Workflow | [declarative/conditional_workflow/](./declarative/conditional_workflow/) | Nested conditional branching based on user input | +| Customer Support | [declarative/customer_support/](./declarative/customer_support/) | Multi-agent customer support with routing | +| Deep Research | [declarative/deep_research/](./declarative/deep_research/) | Research workflow with planning, searching, and synthesis | +| Function Tools | [declarative/function_tools/](./declarative/function_tools/) | Invoking Python functions from declarative workflows | +| Human-in-Loop | [declarative/human_in_loop/](./declarative/human_in_loop/) | Interactive workflows that request user input | +| Invoke Function Tool | [declarative/invoke_function_tool/](./declarative/invoke_function_tool/) | Call registered Python functions with InvokeFunctionTool | +| Marketing | [declarative/marketing/](./declarative/marketing/) | Marketing content generation workflow | +| Simple Workflow | [declarative/simple_workflow/](./declarative/simple_workflow/) | Basic workflow with variable setting, conditionals, and loops | +| Student Teacher | [declarative/student_teacher/](./declarative/student_teacher/) | Student-teacher interaction pattern | ### resources diff --git a/python/samples/03-workflows/declarative/README.md b/python/samples/03-workflows/declarative/README.md index 290a297042..defd909b40 100644 --- a/python/samples/03-workflows/declarative/README.md +++ b/python/samples/03-workflows/declarative/README.md @@ -69,6 +69,9 @@ actions: - `InvokeAzureAgent` - Call an Azure AI agent - `InvokePromptAgent` - Call a local prompt agent +### Tool Invocation +- `InvokeFunctionTool` - Call a registered Python function + ### Human-in-Loop - `Question` - Request user input - `WaitForInput` - Pause for external input diff --git a/python/samples/03-workflows/declarative/agent_to_function_tool/main.py b/python/samples/03-workflows/declarative/agent_to_function_tool/main.py new file mode 100644 index 0000000000..55ba77c073 --- /dev/null +++ b/python/samples/03-workflows/declarative/agent_to_function_tool/main.py @@ -0,0 +1,261 @@ +# Copyright (c) Microsoft. All rights reserved. + +"""Agent to Function Tool sample - demonstrates chaining agent output to function tools. + +This sample shows how to: +1. Use InvokeAzureAgent to analyze user input with an AI model +2. Pass the agent's structured output to InvokeFunctionTool actions +3. Chain multiple function tools to process and transform data + +The workflow: +1. Takes a user order request as input +2. Uses an Azure agent to extract structured order data (item, quantity, details) +3. Passes the extracted data to a function tool that calculates the order total +4. Uses another function tool to format the final confirmation message + +Run with: + python -m samples.03-workflows.declarative.agent_to_function_tool.main +""" + +import asyncio +from pathlib import Path +from typing import Any + +from agent_framework.azure import AzureOpenAIChatClient +from agent_framework.declarative import WorkflowFactory +from azure.identity import AzureCliCredential +from pydantic import BaseModel, Field + +# Pricing data for the order calculation +ITEM_PRICES = { + "pizza": {"small": 10.99, "medium": 14.99, "large": 18.99, "default": 14.99}, + "burger": {"small": 6.99, "medium": 8.99, "large": 10.99, "default": 8.99}, + "salad": {"small": 7.99, "medium": 9.99, "large": 11.99, "default": 9.99}, + "sandwich": {"small": 6.99, "medium": 8.99, "large": 10.99, "default": 8.99}, + "pasta": {"small": 11.99, "medium": 14.99, "large": 17.99, "default": 14.99}, +} + +EXTRAS_PRICES = { + "extra cheese": 2.00, + "bacon": 2.50, + "avocado": 1.50, + "mushrooms": 1.00, + "pepperoni": 2.00, +} + +# Agent instructions for order analysis +ORDER_ANALYSIS_INSTRUCTIONS = """You are an order analysis assistant. Analyze the customer's order request and extract: +- item: what they want to order (e.g., "pizza", "burger", "salad") +- quantity: how many (as a number, default to 1 if not specified) +- details: any special requests, modifications, or size (e.g., "large", "extra cheese") +- delivery_address: where to deliver (if mentioned, otherwise empty string) + +Always respond with valid JSON matching the required format.""" + + +# Pydantic model for structured agent output +class OrderAnalysis(BaseModel): + """Structured output from the order analysis agent.""" + + item: str = Field(description="The food item being ordered (e.g., pizza, burger)") + quantity: int = Field(description="Number of items ordered", default=1) + details: str = Field(description="Special requests, size, or modifications") + delivery_address: str = Field(description="Delivery address if provided, empty string otherwise", default="") + + +def calculate_order_total(order_data: dict[str, Any]) -> dict[str, Any]: + """Calculate the total cost of an order based on the agent's structured analysis. + + Args: + order_data: Structured dict from the agent containing order analysis. + + Returns: + Dictionary with pricing breakdown. + """ + # Handle case where order_data might be None or invalid + if not order_data or not isinstance(order_data, dict): + return { + "error": f"Invalid order data: {order_data}", + "subtotal": 0.0, + "tax": 0.0, + "delivery_fee": 0.0, + "total": 0.0, + } + + item = str(order_data.get("item", "")).lower() + quantity = int(order_data.get("quantity", 1)) + details = str(order_data.get("details", "")).lower() + has_delivery = bool(order_data.get("delivery_address")) + + # Determine size from details + size = "default" + for s in ["small", "medium", "large"]: + if s in details: + size = s + break + + # Get base price for item + item_key = None + for key in ITEM_PRICES: + if key in item: + item_key = key + break + + unit_price = ITEM_PRICES[item_key].get(size, ITEM_PRICES[item_key]["default"]) if item_key else 12.99 + + # Calculate extras + extras_total = 0.0 + applied_extras: list[dict[str, Any]] = [] + for extra, price in EXTRAS_PRICES.items(): + if extra in details: + extras_total += price * quantity + applied_extras.append({"name": extra, "price": price}) + + # Calculate totals + subtotal = (unit_price * quantity) + extras_total + tax = round(subtotal * 0.08, 2) # 8% tax + delivery_fee = 5.00 if has_delivery else 0.0 + total = round(subtotal + tax + delivery_fee, 2) + + return { + "item": item, + "quantity": quantity, + "size": size if size != "default" else "regular", + "unit_price": unit_price, + "extras": applied_extras, + "extras_total": extras_total, + "subtotal": round(subtotal, 2), + "tax": tax, + "delivery_fee": delivery_fee, + "total": total, + "has_delivery": has_delivery, + } + + +def format_order_confirmation(order_data: dict[str, Any], order_calculation: dict[str, Any]) -> str: + """Format a human-readable order confirmation message. + + Args: + order_data: Structured dict from the agent with order details. + order_calculation: Pricing calculation from calculate_order_total. + + Returns: + Formatted confirmation message. + """ + calc = order_calculation + + # Handle error case + if "error" in calc: + return f"Sorry, we couldn't process your order: {calc['error']}" + + # Build the confirmation message + qty = int(calc.get("quantity", 1)) + size = calc.get("size", "regular").title() + item = calc.get("item", "item").title() + lines = [ + "=" * 50, + "ORDER CONFIRMATION", + "=" * 50, + "", + f"Item: {qty}x {size} {item}", + f"Unit Price: ${calc.get('unit_price', 0):.2f}", + ] + + # Add extras if any + extras = calc.get("extras", []) + if extras: + lines.append("\nExtras:") + for extra in extras: + lines.append(f" + {extra['name'].title()}: ${extra['price']:.2f} each") + lines.append(f" Extras Total: ${calc.get('extras_total', 0):.2f}") + + lines.extend([ + "", + "-" * 30, + f"Subtotal: ${calc.get('subtotal', 0):.2f}", + f"Tax (8%): ${calc.get('tax', 0):.2f}", + ]) + + if calc.get("has_delivery"): + delivery_address = order_data.get("delivery_address", "Address provided") if order_data else "Address provided" + lines.extend([ + f"Delivery Fee: ${calc.get('delivery_fee', 0):.2f}", + f"Delivery To: {delivery_address}", + ]) + + lines.extend([ + "-" * 30, + f"TOTAL: ${calc.get('total', 0):.2f}", + "=" * 50, + "", + "Thank you for your order!", + ]) + + return "\n".join(lines) + + +async def main(): + """Run the agent to function tool workflow.""" + # Create Azure OpenAI client + chat_client = AzureOpenAIChatClient(credential=AzureCliCredential()) + + # Create the order analysis agent with structured output + order_analysis_agent = chat_client.as_agent( + name="OrderAnalysisAgent", + instructions=ORDER_ANALYSIS_INSTRUCTIONS, + default_options={"response_format": OrderAnalysis}, + ) + + # Agent registry + agents = { + "OrderAnalysisAgent": order_analysis_agent, + } + + # Get the path to the workflow YAML file + workflow_path = Path(__file__).parent / "workflow.yaml" + + # Create the workflow factory with agents and tools + factory = ( + WorkflowFactory(agents=agents) + .register_tool("calculate_order_total", calculate_order_total) + .register_tool("format_order_confirmation", format_order_confirmation) + ) + + # Create the workflow from the YAML definition + workflow = factory.create_workflow_from_yaml_path(workflow_path) + + print("=" * 60) + print("Agent to Function Tool Workflow Demo") + print("=" * 60) + print() + print("This workflow demonstrates:") + print(" 1. Using InvokeAzureAgent to analyze user input") + print(" 2. Passing agent's structured output to InvokeFunctionTool") + print(" 3. Chaining multiple function tools together") + print() + + # Test with different order inputs + test_queries = [ + "I want to order 3 large pizzas with extra cheese for delivery to 123 Main St", + "2 medium burgers with bacon please", + "Can I get a small salad with avocado and mushrooms, pick up", + ] + + for query in test_queries: + print("-" * 60) + print(f"Input: {query}") + print("-" * 60) + + # Run the workflow with streaming to capture output + try: + async for event in workflow.run(query, stream=True): + if event.type == "output" and isinstance(event.data, str): + print(event.data, end="", flush=True) + except Exception as e: + print(f"\nWorkflow error: {type(e).__name__}: {e}") + + print("\n") + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/python/samples/03-workflows/declarative/agent_to_function_tool/workflow.yaml b/python/samples/03-workflows/declarative/agent_to_function_tool/workflow.yaml new file mode 100644 index 0000000000..92e127bc12 --- /dev/null +++ b/python/samples/03-workflows/declarative/agent_to_function_tool/workflow.yaml @@ -0,0 +1,56 @@ +# Agent to Function Tool Workflow +# +# This workflow demonstrates chaining an agent invocation with a function tool. +# The agent analyzes user input, and the function tool processes the agent's output. +# +# Flow: +# 1. Receive user query +# 2. Invoke an Azure agent to analyze the query and extract structured data +# 3. Pass the agent's structured output to a function tool for processing +# 4. Return the final result +# +# Example input: +# I want to order 3 large pizzas with extra cheese for delivery to 123 Main St + +kind: Workflow +trigger: + + kind: OnConversationStart + id: agent_to_function_tool_demo + actions: + + # Invoke the order analysis agent to extract structured order data + - kind: InvokeAzureAgent + id: analyze_order + agent: + name: OrderAnalysisAgent + input: + messages: =Workflow.Inputs.input + output: + response: Local.agentResponse + responseObject: Local.orderData + + # Invoke a function tool to calculate order total using the agent's output + - kind: InvokeFunctionTool + id: calculate_order + functionName: calculate_order_total + arguments: + order_data: =Local.orderData + output: + result: Local.orderCalculation + + # Invoke another function tool to format the final confirmation + - kind: InvokeFunctionTool + id: format_confirmation + functionName: format_order_confirmation + arguments: + order_data: =Local.orderData + order_calculation: =Local.orderCalculation + output: + result: Local.confirmation + + # Send the final confirmation to the user + - kind: SendActivity + id: send_confirmation + activity: + text: =Local.confirmation diff --git a/python/samples/03-workflows/declarative/invoke_function_tool/main.py b/python/samples/03-workflows/declarative/invoke_function_tool/main.py new file mode 100644 index 0000000000..a6b251ca53 --- /dev/null +++ b/python/samples/03-workflows/declarative/invoke_function_tool/main.py @@ -0,0 +1,116 @@ +# Copyright (c) Microsoft. All rights reserved. + +"""Invoke Function Tool sample - demonstrates InvokeFunctionTool workflow actions. + +This sample shows how to: +1. Define Python functions that can be called from workflows +2. Register functions with WorkflowFactory.register_tool() +3. Use the InvokeFunctionTool action in YAML to invoke registered functions +4. Pass arguments using expression syntax (=Local.variable) +5. Capture function output in workflow variables + +Run with: + python -m samples.03-workflows.declarative.invoke_function_tool.main +""" + +import asyncio +from pathlib import Path +from typing import Any + +from agent_framework.declarative import WorkflowFactory + + +# Define the function tools that will be registered with the workflow +def get_weather(location: str, unit: str = "F") -> dict[str, Any]: + """Get weather information for a location. + + This is a mock function that returns simulated weather data. + In a real application, this would call a weather API. + + Args: + location: The city or location to get weather for. + unit: Temperature unit ("F" for Fahrenheit, "C" for Celsius). + + Returns: + Dictionary with weather information. + """ + # Simulated weather data + weather_data = { + "Seattle": {"temp": 55, "condition": "rainy"}, + "New York": {"temp": 70, "condition": "partly cloudy"}, + "Los Angeles": {"temp": 85, "condition": "sunny"}, + "Chicago": {"temp": 60, "condition": "windy"}, + } + + data = weather_data.get(location, {"temp": 72, "condition": "unknown"}) + + # Convert to Celsius if requested + temp = data["temp"] + if unit.upper() == "C": + temp = round((temp - 32) * 5 / 9) # type: ignore + + return { + "location": location, + "temp": temp, + "unit": unit.upper(), + "condition": data["condition"], + } + + +def format_message(template: str, data: dict[str, Any]) -> str: + """Format a message template with data. + + Args: + template: A string template with {key} placeholders. + data: Dictionary of values to substitute. + + Returns: + Formatted message string. + """ + try: + return template.format(**data) + except KeyError as e: + return f"Error formatting message: missing key {e}" + + +async def main(): + """Run the invoke function tool workflow.""" + # Get the path to the workflow YAML file + workflow_path = Path(__file__).parent / "workflow.yaml" + + # Create the workflow factory and register our tool functions + factory = ( + WorkflowFactory().register_tool("get_weather", get_weather).register_tool("format_message", format_message) + ) + + # Create the workflow from the YAML definition + workflow = factory.create_workflow_from_yaml_path(workflow_path) + + print("=" * 60) + print("Invoke Function Tool Workflow Demo") + print("=" * 60) + + # Test with different inputs - both location and unit must be provided + # as the workflow expects them in Workflow.Inputs + test_inputs = [ + {"location": "Seattle", "unit": "F"}, + {"location": "New York", "unit": "C"}, + {"location": "Los Angeles", "unit": "F"}, + {"location": "Chicago", "unit": "C"}, + ] + + for inputs in test_inputs: + print(f"\nInput: {inputs}") + print("-" * 40) + + # Run the workflow + events = await workflow.run(inputs) + + # Get the outputs + outputs = events.get_outputs() + for output in outputs: + print(f"Output: {output}") + + +if __name__ == "__main__": + asyncio.run(main()) diff --git 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