Agent conversation handling

examples/basic/agents_sdk.py

@@ -25,6 +25,7 @@
                     "categories": ["hate", "violence", "self-harm"],
                 },
             },
+            {"name": "Contains PII", "config": {"entities": ["US_SSN", "PHONE_NUMBER", "EMAIL_ADDRESS"]}},
         ],
     },
     "input": {
@@ -75,11 +76,15 @@ async def main() -> None:
             except EOFError:
                 print("\nExiting.")
                 break
-            except InputGuardrailTripwireTriggered:
+            except InputGuardrailTripwireTriggered as exc:
                 print("🛑 Input guardrail triggered!")
+                print(exc.guardrail_result.guardrail.name)
+                print(exc.guardrail_result.output.output_info)
                 continue
-            except OutputGuardrailTripwireTriggered:
+            except OutputGuardrailTripwireTriggered as exc:
                 print("🛑 Output guardrail triggered!")
+                print(exc.guardrail_result.guardrail.name)
+                print(exc.guardrail_result.output.output_info)
                 continue
 
 

src/guardrails/agents.py

@@ -257,7 +257,7 @@ async def tool_input_gr(data: ToolInputGuardrailData) -> ToolGuardrailFunctionOu
                     media_type="text/plain",
                     guardrails=[guardrail],
                     suppress_tripwire=True,
-                    stage_name=f"tool_input_{guardrail_name.lower().replace(' ', '_')}",
+                    stage_name="tool_input",
                     raise_guardrail_errors=raise_guardrail_errors,
                 )
 
@@ -312,7 +312,7 @@ async def tool_output_gr(data: ToolOutputGuardrailData) -> ToolGuardrailFunction
                     media_type="text/plain",
                     guardrails=[guardrail],
                     suppress_tripwire=True,
-                    stage_name=f"tool_output_{guardrail_name.lower().replace(' ', '_')}",
+                    stage_name="tool_output",
                     raise_guardrail_errors=raise_guardrail_errors,
                 )
 
@@ -338,6 +338,59 @@ async def tool_output_gr(data: ToolOutputGuardrailData) -> ToolGuardrailFunction
         return tool_output_gr
 
 
+def _extract_text_from_input(input_data: Any) -> str:
+    """Extract text from input_data, handling both string and conversation history formats.
+
+    The Agents SDK may pass input_data in different formats:
+    - String: Direct text input
+    - List of dicts: Conversation history with message objects
+
+    Args:
+        input_data: Input from Agents SDK (string or list of messages)
+
+    Returns:
+        Extracted text string from the latest user message
+    """
+    # If it's already a string, return it
+    if isinstance(input_data, str):
+        return input_data
+
+    # If it's a list (conversation history), extract the latest user message
+    if isinstance(input_data, list):
+        if len(input_data) == 0:
+            return ""  # Empty list returns empty string
+
+        # Iterate from the end to find the latest user message
+        for msg in reversed(input_data):
+            if isinstance(msg, dict):
+                role = msg.get("role")
+                if role == "user":
+                    content = msg.get("content")
+                    # Content can be a string or a list of content parts
+                    if isinstance(content, str):
+                        return content
+                    elif isinstance(content, list):
+                        # Extract text from content parts
+                        text_parts = []
+                        for part in content:
+                            if isinstance(part, dict):
+                                # Check for various text field names
+                                text = part.get("text") or part.get("input_text") or part.get("output_text")
+                                if text and isinstance(text, str):
+                                    text_parts.append(text)
+                        if text_parts:
+                            return " ".join(text_parts)
+                    # If content is something else, try to stringify it
+                    elif content is not None:
+                        return str(content)
+
+        # No user message found in list
+        return ""
+
+    # Fallback: convert to string
+    return str(input_data)
+
+
 def _create_agents_guardrails_from_config(
     config: str | Path | dict[str, Any], stages: list[str], guardrail_type: str = "input", context: Any = None, raise_guardrail_errors: bool = False
 ) -> list[Any]:
@@ -355,7 +408,7 @@ def _create_agents_guardrails_from_config(
             If False (default), treat guardrail errors as safe and continue execution.
 
     Returns:
-        List of guardrail functions that can be used with Agents SDK
+        List of guardrail functions (one per individual guardrail) ready for Agents SDK
 
     Raises:
         ImportError: If agents package is not available
@@ -372,17 +425,15 @@ def _create_agents_guardrails_from_config(
     # Load and parse the pipeline configuration
     pipeline = load_pipeline_bundles(config)
 
-    # Instantiate guardrails for requested stages and filter out tool-level guardrails
-    stage_guardrails = {}
+    # Collect all individual guardrails from requested stages (filter out tool-level)
+    all_guardrails = []
     for stage_name in stages:
         stage = getattr(pipeline, stage_name, None)
         if stage:
-            all_guardrails = instantiate_guardrails(stage, default_spec_registry)
+            stage_guardrails = instantiate_guardrails(stage, default_spec_registry)
             # Filter out tool-level guardrails - they're handled separately
-            _, agent_level_guardrails = _separate_tool_level_from_agent_level(all_guardrails)
-            stage_guardrails[stage_name] = agent_level_guardrails
-        else:
-            stage_guardrails[stage_name] = []
+            _, agent_level_guardrails = _separate_tool_level_from_agent_level(stage_guardrails)
+            all_guardrails.extend(agent_level_guardrails)
 
     # Create default context if none provided
     if context is None:
@@ -394,31 +445,30 @@ class DefaultContext:
 
         context = DefaultContext(guardrail_llm=AsyncOpenAI())
 
-    def _create_stage_guardrail(stage_name: str):
-        async def stage_guardrail(ctx: RunContextWrapper[None], agent: Agent, input_data: str) -> GuardrailFunctionOutput:
-            """Guardrail function for a specific pipeline stage."""
+    def _create_individual_guardrail(guardrail):
+        """Create a function for a single specific guardrail."""
+        async def single_guardrail(ctx: RunContextWrapper[None], agent: Agent, input_data: str) -> GuardrailFunctionOutput:
+            """Guardrail function for a specific guardrail check."""
             try:
-                # Get guardrails for this stage (already filtered to exclude prompt injection)
-                guardrails = stage_guardrails.get(stage_name, [])
-                if not guardrails:
-                    return GuardrailFunctionOutput(output_info=None, tripwire_triggered=False)
+                # Extract text from input_data (handle both string and conversation history formats)
+                text_data = _extract_text_from_input(input_data)
 
-                # Run the guardrails for this stage
+                # Run this single guardrail
                 results = await run_guardrails(
                     ctx=context,
-                    data=input_data,
+                    data=text_data,
                     media_type="text/plain",
-                    guardrails=guardrails,
+                    guardrails=[guardrail],  # Just this one guardrail
                     suppress_tripwire=True,  # We handle tripwires manually
-                    stage_name=stage_name,
+                    stage_name=guardrail_type,  # "input" or "output" - indicates which stage
                     raise_guardrail_errors=raise_guardrail_errors,
                 )
 
-                # Check if any tripwires were triggered
+                # Check if tripwire was triggered
                 for result in results:
                     if result.tripwire_triggered:
-                        guardrail_name = result.info.get("guardrail_name", "unknown") if isinstance(result.info, dict) else "unknown"
-                        return GuardrailFunctionOutput(output_info=f"Guardrail {guardrail_name} triggered tripwire", tripwire_triggered=True)
+                        # Return full metadata in output_info for consistency with tool guardrails
+                        return GuardrailFunctionOutput(output_info=result.info, tripwire_triggered=True)
 
                 return GuardrailFunctionOutput(output_info=None, tripwire_triggered=False)
 
@@ -428,24 +478,33 @@ async def stage_guardrail(ctx: RunContextWrapper[None], agent: Agent, input_data
                     raise e
                 else:
                     # Current behavior: treat errors as tripwires
-                    return GuardrailFunctionOutput(output_info=f"Error running {stage_name} guardrails: {str(e)}", tripwire_triggered=True)
+                    # Return structured error info for consistency
+                    return GuardrailFunctionOutput(
+                        output_info={
+                            "error": str(e),
+                            "guardrail_name": guardrail.definition.name,
+                        },
+                        tripwire_triggered=True,
+                    )
+
+        # Set the function name to the guardrail name (e.g., "Moderation" → "Moderation")
+        single_guardrail.__name__ = guardrail.definition.name.replace(" ", "_")
 
-        # Set the function name for debugging
-        stage_guardrail.__name__ = f"{stage_name}_guardrail"
-        return stage_guardrail
+        return single_guardrail
 
     guardrail_functions = []
 
-    for stage in stages:
-        stage_guardrail = _create_stage_guardrail(stage)
+    # Create one function per individual guardrail (Agents SDK runs them concurrently)
+    for guardrail in all_guardrails:
+        guardrail_func = _create_individual_guardrail(guardrail)
 
         # Decorate with the appropriate guardrail decorator
         if guardrail_type == "input":
-            stage_guardrail = input_guardrail(stage_guardrail)
+            guardrail_func = input_guardrail(guardrail_func)
         else:
-            stage_guardrail = output_guardrail(stage_guardrail)
+            guardrail_func = output_guardrail(guardrail_func)
 
-        guardrail_functions.append(stage_guardrail)
+        guardrail_functions.append(guardrail_func)
 
     return guardrail_functions