Merge branch 'main' of https://github.com/Azeem-2/openai-agents-python

Author: Azeem-2

src/agents/__init__.py

@@ -106,6 +106,11 @@ def set_default_openai_key(key: str, use_for_tracing: bool = True) -> None:
             If False, you'll either need to set the OPENAI_API_KEY environment variable or call
             set_tracing_export_api_key() with the API key you want to use for tracing.
     """
+    try:
+        _config.set_default_openai_key(key)
+    except Exception as e:
+        logging.error(f"Error setting default OpenAI key: {e}")
+        raise
     _config.set_default_openai_key(key, use_for_tracing)
 
 
@@ -119,18 +124,34 @@ def set_default_openai_client(client: AsyncOpenAI, use_for_tracing: bool = True)
             you'll either need to set the OPENAI_API_KEY environment variable or call
             set_tracing_export_api_key() with the API key you want to use for tracing.
     """
-    _config.set_default_openai_client(client, use_for_tracing)
+    try:
+        _config.set_default_openai_client(client, use_for_tracing)
+    except Exception as e:
+        logging.error(f"Error setting default OpenAI client: {e}")
+        raise
 
 
 def set_default_openai_api(api: Literal["chat_completions", "responses"]) -> None:
     """Set the default API to use for OpenAI LLM requests. By default, we will use the responses API
     but you can set this to use the chat completions API instead.
     """
-    _config.set_default_openai_api(api)
+    try:
+        _config.set_default_openai_api(api)
+    except Exception as e:
+        logging.error(f"Error setting default OpenAI API: {e}")
+        raise
 
 
-def enable_verbose_stdout_logging():
+def enable_verbose_stdout_logging() -> None:
     """Enables verbose logging to stdout. This is useful for debugging."""
+    try:
+        for name in ["openai.agents", "openai.agents.tracing"]:
+            logger = logging.getLogger(name)
+            logger.setLevel(logging.DEBUG)
+            logger.addHandler(logging.StreamHandler(sys.stdout))
+    except Exception as e:
+        logging.error(f"Error enabling verbose stdout logging: {e}")
+        raise
     logger = logging.getLogger("openai.agents")
     logger.setLevel(logging.DEBUG)
     logger.addHandler(logging.StreamHandler(sys.stdout))

src/agents/_run_impl.py

@@ -2,7 +2,7 @@
 
 import asyncio
 from dataclasses import dataclass
-from typing import TYPE_CHECKING, Any
+from typing import TYPE_CHECKING, Any, Union, List
 
 from openai.types.responses import (
     ResponseComputerToolCall,
@@ -65,6 +65,7 @@
 
 
 class QueueCompleteSentinel:
+    """A sentinel value to indicate that the queue is complete."""
     pass
 
 
@@ -97,8 +98,7 @@ class ProcessedResponse:
     computer_actions: list[ToolRunComputerAction]
 
     def has_tools_to_run(self) -> bool:
-        # Handoffs, functions and computer actions need local processing
-        # Hosted tools have already run, so there's nothing to do.
+        """Check if there are any tools to run."""
         return any(
             [
                 self.handoffs,
@@ -151,6 +151,7 @@ def generated_items(self) -> list[RunItem]:
 def get_model_tracing_impl(
     tracing_disabled: bool, trace_include_sensitive_data: bool
 ) -> ModelTracing:
+    """Get the model tracing implementation based on the tracing configuration."""
     if tracing_disabled:
         return ModelTracing.DISABLED
     elif trace_include_sensitive_data:
@@ -176,6 +177,7 @@ async def execute_tools_and_side_effects(
         context_wrapper: RunContextWrapper[TContext],
         run_config: RunConfig,
     ) -> SingleStepResult:
+        """Execute tools and side effects for the current step."""
         # Make a copy of the generated items
         pre_step_items = list(pre_step_items)
 
@@ -271,6 +273,7 @@ def process_model_response(
         output_schema: AgentOutputSchema | None,
         handoffs: list[Handoff],
     ) -> ProcessedResponse:
+        """Process the model response and extract relevant information."""
         items: list[RunItem] = []
 
         run_handoffs = []
@@ -356,6 +359,7 @@ async def execute_function_tool_calls(
         context_wrapper: RunContextWrapper[TContext],
         config: RunConfig,
     ) -> list[RunItem]:
+        """Execute function tool calls."""
         async def run_single_tool(
             func_tool: FunctionTool, tool_call: ResponseFunctionToolCall
         ) -> str:
@@ -422,6 +426,7 @@ async def execute_computer_actions(
         context_wrapper: RunContextWrapper[TContext],
         config: RunConfig,
     ) -> list[RunItem]:
+        """Execute computer actions."""
         results: list[RunItem] = []
         # Need to run these serially, because each action can affect the computer state
         for action in actions:
@@ -451,6 +456,7 @@ async def execute_handoffs(
         context_wrapper: RunContextWrapper[TContext],
         run_config: RunConfig,
     ) -> SingleStepResult:
+        """Execute handoffs."""
         # If there is more than one handoff, add tool responses that reject those handoffs
         if len(run_handoffs) > 1:
             output_message = "Multiple handoffs detected, ignoring this one."
@@ -470,9 +476,20 @@ async def execute_handoffs(
         actual_handoff = run_handoffs[0]
         with handoff_span(from_agent=agent.name) as span_handoff:
             handoff = actual_handoff.handoff
-            new_agent: Agent[Any] = await handoff.on_invoke_handoff(
-                context_wrapper, actual_handoff.tool_call.arguments
-            )
+            try:
+                new_agent: Agent[Any] = await handoff.on_invoke_handoff(
+                    context_wrapper, actual_handoff.tool_call.arguments
+                )
+            except Exception as e:
+                _utils.attach_error_to_span(
+                    span_handoff,
+                    SpanError(
+                        message="Error invoking handoff",
+                        data={"error": str(e)},
+                    )
+                )
+                raise
+
             span_handoff.span_data.to_agent = new_agent.name
 
             # Append a tool output item for the handoff
@@ -568,6 +585,7 @@ async def execute_final_output(
         hooks: RunHooks[TContext],
         context_wrapper: RunContextWrapper[TContext],
     ) -> SingleStepResult:
+        """Execute final output."""
         # Run the on_end hooks
         await cls.run_final_output_hooks(agent, hooks, context_wrapper, final_output)
 
@@ -587,6 +605,7 @@ async def run_final_output_hooks(
         context_wrapper: RunContextWrapper[TContext],
         final_output: Any,
     ):
+        """Run the final output hooks."""
         await asyncio.gather(
             hooks.on_agent_end(context_wrapper, agent, final_output),
             agent.hooks.on_end(context_wrapper, agent, final_output)
@@ -602,8 +621,19 @@ async def run_single_input_guardrail(
         input: str | list[TResponseInputItem],
         context: RunContextWrapper[TContext],
     ) -> InputGuardrailResult:
+        """Run a single input guardrail."""
         with guardrail_span(guardrail.get_name()) as span_guardrail:
-            result = await guardrail.run(agent, input, context)
+            try:
+                result = await guardrail.run(agent, input, context)
+            except Exception as e:
+                _utils.attach_error_to_span(
+                    span_guardrail,
+                    SpanError(
+                        message="Error running input guardrail",
+                        data={"error": str(e)},
+                    )
+                )
+                raise
             span_guardrail.span_data.triggered = result.output.tripwire_triggered
             return result
 
@@ -615,8 +645,19 @@ async def run_single_output_guardrail(
         agent_output: Any,
         context: RunContextWrapper[TContext],
     ) -> OutputGuardrailResult:
+        """Run a single output guardrail."""
         with guardrail_span(guardrail.get_name()) as span_guardrail:
-            result = await guardrail.run(agent=agent, agent_output=agent_output, context=context)
+            try:
+                result = await guardrail.run(agent=agent, agent_output=agent_output, context=context)
+            except Exception as e:
+                _utils.attach_error_to_span(
+                    span_guardrail,
+                    SpanError(
+                        message="Error running output guardrail",
+                        data={"error": str(e)},
+                    )
+                )
+                raise
             span_guardrail.span_data.triggered = result.output.tripwire_triggered
             return result
 
@@ -626,6 +667,7 @@ def stream_step_result_to_queue(
         step_result: SingleStepResult,
         queue: asyncio.Queue[StreamEvent | QueueCompleteSentinel],
     ):
+        """Stream the step result to the queue."""
         for item in step_result.new_step_items:
             if isinstance(item, MessageOutputItem):
                 event = RunItemStreamEvent(item=item, name="message_output_created")
@@ -695,6 +737,7 @@ async def execute(
         context_wrapper: RunContextWrapper[TContext],
         config: RunConfig,
     ) -> RunItem:
+        """Execute a computer action."""
         output_func = (
             cls._get_screenshot_async(action.computer_tool.computer, action.tool_call)
             if isinstance(action.computer_tool.computer, AsyncComputer)
@@ -741,25 +784,29 @@ async def _get_screenshot_sync(
         computer: Computer,
         tool_call: ResponseComputerToolCall,
     ) -> str:
+        """Get a screenshot synchronously."""
         action = tool_call.action
-        if isinstance(action, ActionClick):
-            computer.click(action.x, action.y, action.button)
-        elif isinstance(action, ActionDoubleClick):
-            computer.double_click(action.x, action.y)
-        elif isinstance(action, ActionDrag):
-            computer.drag([(p.x, p.y) for p in action.path])
-        elif isinstance(action, ActionKeypress):
-            computer.keypress(action.keys)
-        elif isinstance(action, ActionMove):
-            computer.move(action.x, action.y)
-        elif isinstance(action, ActionScreenshot):
-            computer.screenshot()
-        elif isinstance(action, ActionScroll):
-            computer.scroll(action.x, action.y, action.scroll_x, action.scroll_y)
-        elif isinstance(action, ActionType):
-            computer.type(action.text)
-        elif isinstance(action, ActionWait):
-            computer.wait()
+        try:
+            if isinstance(action, ActionClick):
+                computer.click(action.x, action.y, action.button)
+            elif isinstance(action, ActionDoubleClick):
+                computer.double_click(action.x, action.y)
+            elif isinstance(action, ActionDrag):
+                computer.drag([(p.x, p.y) for p in action.path])
+            elif isinstance(action, ActionKeypress):
+                computer.keypress(action.keys)
+            elif isinstance(action, ActionMove):
+                computer.move(action.x, action.y)
+            elif isinstance(action, ActionScreenshot):
+                computer.screenshot()
+            elif isinstance(action, ActionScroll):
+                computer.scroll(action.x, action.y, action.scroll_x, action.scroll_y)
+            elif isinstance(action, ActionType):
+                computer.type(action.text)
+            elif isinstance(action, ActionWait):
+                computer.wait()
+        except Exception as e:
+            raise ModelBehaviorError(f"Error executing computer action: {e}")
 
         return computer.screenshot()
 
@@ -769,24 +816,28 @@ async def _get_screenshot_async(
         computer: AsyncComputer,
         tool_call: ResponseComputerToolCall,
     ) -> str:
+        """Get a screenshot asynchronously."""
         action = tool_call.action
-        if isinstance(action, ActionClick):
-            await computer.click(action.x, action.y, action.button)
-        elif isinstance(action, ActionDoubleClick):
-            await computer.double_click(action.x, action.y)
-        elif isinstance(action, ActionDrag):
-            await computer.drag([(p.x, p.y) for p in action.path])
-        elif isinstance(action, ActionKeypress):
-            await computer.keypress(action.keys)
-        elif isinstance(action, ActionMove):
-            await computer.move(action.x, action.y)
-        elif isinstance(action, ActionScreenshot):
-            await computer.screenshot()
-        elif isinstance(action, ActionScroll):
-            await computer.scroll(action.x, action.y, action.scroll_x, action.scroll_y)
-        elif isinstance(action, ActionType):
-            await computer.type(action.text)
-        elif isinstance(action, ActionWait):
-            await computer.wait()
+        try:
+            if isinstance(action, ActionClick):
+                await computer.click(action.x, action.y, action.button)
+            elif isinstance(action, ActionDoubleClick):
+                await computer.double_click(action.x, action.y)
+            elif isinstance(action, ActionDrag):
+                await computer.drag([(p.x, p.y) for p in action.path])
+            elif isinstance(action, ActionKeypress):
+                await computer.keypress(action.keys)
+            elif isinstance(action, ActionMove):
+                await computer.move(action.x, action.y)
+            elif isinstance(action, ActionScreenshot):
+                await computer.screenshot()
+            elif isinstance(action, ActionScroll):
+                await computer.scroll(action.x, action.y, action.scroll_x, action.scroll_y)
+            elif isinstance(action, ActionType):
+                await computer.type(action.text)
+            elif isinstance(action, ActionWait):
+                await computer.wait()
+        except Exception as e:
+            raise ModelBehaviorError(f"Error executing computer action: {e}")
 
         return await computer.screenshot()

src/agents/agent.py

@@ -132,28 +132,36 @@ def as_tool(
         async def run_agent(context: RunContextWrapper, input: str) -> str:
             from .run import Runner
 
-            output = await Runner.run(
-                starting_agent=self,
-                input=input,
-                context=context.context,
-            )
-            if custom_output_extractor:
-                return await custom_output_extractor(output)
-
-            return ItemHelpers.text_message_outputs(output.new_items)
+            try:
+                output = await Runner.run(
+                    starting_agent=self,
+                    input=input,
+                    context=context.context,
+                )
+                if custom_output_extractor:
+                    return await custom_output_extractor(output)
+
+                return ItemHelpers.text_message_outputs(output.new_items)
+            except Exception as e:
+                logger.error(f"Error running agent as tool: {e}")
+                raise
 
         return run_agent
 
     async def get_system_prompt(self, run_context: RunContextWrapper[TContext]) -> str | None:
         """Get the system prompt for the agent."""
-        if isinstance(self.instructions, str):
-            return self.instructions
-        elif callable(self.instructions):
-            if inspect.iscoroutinefunction(self.instructions):
-                return await cast(Awaitable[str], self.instructions(run_context, self))
-            else:
-                return cast(str, self.instructions(run_context, self))
-        elif self.instructions is not None:
-            logger.error(f"Instructions must be a string or a function, got {self.instructions}")
-
-        return None
+        try:
+            if isinstance(self.instructions, str):
+                return self.instructions
+            elif callable(self.instructions):
+                if inspect.iscoroutinefunction(self.instructions):
+                    return await cast(Awaitable[str], self.instructions(run_context, self))
+                else:
+                    return cast(str, self.instructions(run_context, self))
+            elif self.instructions is not None:
+                logger.error(f"Instructions must be a string or a function, got {self.instructions}")
+
+            return None
+        except Exception as e:
+            logger.error(f"Error getting system prompt: {e}")
+            raise