feat(operator): add agent testing functionality with endpoint verific…

…ation

agentic_security/probe_actor/operator.py

@@ -1,9 +1,15 @@
 import asyncio
-from typing import Any
+from typing import Any, Optional, Dict
 
 from pydantic import BaseModel, Field
 from pydantic_ai import Agent, RunContext
+import re
+import httpx
+import logging
 
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
 
 class AgentSpecification(BaseModel):
     name: str | None = Field(None, description="Name of the LLM/agent")
@@ -13,6 +19,7 @@ class AgentSpecification(BaseModel):
     configuration: dict[str, Any] | None = Field(
         None, description="Configuration settings"
     )
+    endpoint: Optional[str] = Field(None, description="Endpoint URL of the deployed agent")
 
 
 # Define the OperatorToolBox class
@@ -61,6 +68,51 @@ def run_operation(self, operation: str) -> str:
             return f"Operation '{operation}' failed: Dataset not found."
         return f"Operation '{operation}' executed successfully."
 
+    async def test(self, description: str, sample_test: Dict[str, Any]) -> str:
+        """Test the agent based on the description and sample test."""
+        match = re.search(r"Test my (.+) agent deployed at (.+)", description)
+        if match:
+            agent_type = match.group(1)
+            endpoint = match.group(2)
+            self.spec.endpoint = endpoint
+
+            # Verify access to the endpoint
+            async with httpx.AsyncClient() as client:
+                try:
+                    access_response = await client.get(endpoint)
+                    access_response.raise_for_status()
+                except httpx.HTTPStatusError as e:
+                    self.failures.append(f"HTTP error occurred: {e}")
+                    logger.error(f"Access verification failed: {e}")
+                    return f"Access verification failed: {e}"
+                except Exception as e:
+                    self.failures.append(f"An error occurred: {e}")
+                    logger.error(f"Access verification failed: {e}")
+                    return f"Access verification failed: {e}"
+
+            # Run the sample test
+            try:
+                test_response = await client.post(f"{endpoint}/test", json=sample_test)
+                test_response.raise_for_status()
+                response_data = test_response.json()
+                # Validate the response (this is a simple example, adjust as needed)
+                if "choices" in response_data and len(response_data["choices"]) > 0:
+                    return f"Testing {agent_type} agent at {endpoint} succeeded: {response_data}"
+                else:
+                    self.failures.append("Invalid response format")
+                    logger.error("Sample test failed: Invalid response format")
+                    return "Sample test failed: Invalid response format"
+            except httpx.HTTPStatusError as e:
+                self.failures.append(f"HTTP error occurred: {e}")
+                logger.error(f"Sample test failed: {e}")
+                return f"Sample test failed: {e}"
+            except Exception as e:
+                self.failures.append(f"An error occurred: {e}")
+                logger.error(f"Sample test failed: {e}")
+                return f"Sample test failed: {e}"
+        else:
+            logger.error("Invalid description format.")
+            return "Invalid description format."
 
 # Initialize OperatorToolBox with AgentSpecification
 spec = AgentSpecification(
@@ -133,14 +185,22 @@ def run_dataset_manager_agent_sync():
         "Execute operation on 'dataset4'.",  # This should fail
         "Retrieve the results.",
         "Retrieve any failures.",
+        "Test my openAI compatible agent deployed at localhost:3000"
     ]
 
+    sample_test = {
+        "prompt": "Hello, how are you?",
+        "max_tokens": 5
+    }
+
     for prompt in prompts:
-        result = dataset_manager_agent.run_sync(prompt, deps=toolbox)
+        if "Test my" in prompt:
+            result = dataset_manager_agent.run_sync(prompt, deps=toolbox, sample_test=sample_test)
+        else:
+            result = dataset_manager_agent.run_sync(prompt, deps=toolbox)
         print(f"Prompt: {prompt}")
         print(f"Response: {result.data}\n")
 
-
 # Asynchronous run example
 async def run_dataset_manager_agent_async():
     prompts = [
@@ -149,10 +209,19 @@ async def run_dataset_manager_agent_async():
         "Execute operation on 'dataset4'.",  # This should fail
         "Retrieve the results.",
         "Retrieve any failures.",
+        "Test my openAI compatible agent deployed at localhost:3000"
     ]
 
+    sample_test = {
+        "prompt": "Hello, how are you?",
+        "max_tokens": 5
+    }
+
     for prompt in prompts:
-        result = await dataset_manager_agent.run(prompt, deps=toolbox)
+        if "Test my" in prompt:
+            result = await dataset_manager_agent.run(prompt, deps=toolbox, sample_test=sample_test)
+        else:
+            result = await dataset_manager_agent.run(prompt, deps=toolbox)
         print(f"Prompt: {prompt}")
         print(f"Response: {result.data}\n")