Remove o3 integration tests, update README, add o3 responses example

Co-authored-by: alex <alex@agentops.ai>

Author: cursoragent

examples/openai/README.md

@@ -39,18 +39,16 @@ Example: `web_search`
 This example demonstrates:
 - Web search functionality
 
-### 5. o3 Responses API Integration
+### 5. o3 Responses API
 
-Example: `o3_responses_integration_test` and `test_o3_integration`
+Example: `o3_responses_example`
 
-These examples demonstrate:
+This example demonstrates:
 - OpenAI's o3 reasoning model with the Responses API
 - Tool calls and structured reasoning
 - Complex decision-making scenarios
 - AgentOps integration with reasoning models
 
-See `README_o3_integration.md` for detailed documentation.
-
 ## AgentOps Integration
 
 These examples show how to use AgentOps to monitor and analyze your AI applications. AgentOps automatically instruments your OpenAI calls to provide insights into performance, usage patterns, and model behavior.

examples/openai/README_o3_integration.md

@@ -1,12 +1,12 @@
-# OpenAI o3 Responses API Integration Test
+# OpenAI o3 Responses API Example
 #
 # This example demonstrates AgentOps integration with OpenAI's o3 reasoning model
 # through the Responses API. The o3 model excels at complex problem solving and
 # multi-step reasoning with tool calls.
 #
-# This test creates a simple decision-making agent that uses the o3 model to
+# This example creates a simple decision-making agent that uses the o3 model to
 # make choices based on available options, similar to the Pokémon battle example
-# but simplified for testing purposes.
+# but simplified.
 
 import openai
 import agentops
@@ -22,10 +22,10 @@
 os.environ["AGENTOPS_API_KEY"] = os.getenv("AGENTOPS_API_KEY", "your_api_key_here")
 
 # Initialize AgentOps
-agentops.init(trace_name="o3-responses-test", tags=["o3", "responses-api", "integration-test"])
+agentops.init(trace_name="o3-responses-example", tags=["o3", "responses-api"])
 tracer = agentops.start_trace(
-    trace_name="o3 Responses API Integration Test", 
-    tags=["o3", "responses-api", "integration-test"]
+    trace_name="o3 Responses API Example", 
+    tags=["o3", "responses-api"]
 )
 
 # Initialize OpenAI client
@@ -154,14 +154,14 @@ def make_decision(self, scenario: str, available_actions: List[str]) -> Dict[str
                 "scenario": scenario
             }
 
-def run_integration_test():
-    """Run the integration test with multiple scenarios."""
+def run_example():
+    """Run the example with multiple scenarios."""
 
     # Create the agent
     agent = O3DecisionAgent(model="o3")
 
-    # Test scenarios
-    test_scenarios = [
+    # Example scenarios
+    scenarios = [
         {
             "scenario": "You're in a battle and your opponent has a strong defensive position. You need to choose your next move carefully.",
             "actions": ["attack_aggressively", "defend_and_wait", "use_special_ability", "retreat_temporarily"]
@@ -178,14 +178,14 @@ def run_integration_test():
 
     results = []
 
-    for i, test_case in enumerate(test_scenarios, 1):
+    for i, scenario in enumerate(scenarios, 1):
         print(f"\n{'='*60}")
-        print(f"Test Case {i}")
+        print(f"Scenario {i}")
         print(f"{'='*60}")
 
         result = agent.make_decision(
-            scenario=test_case["scenario"],
-            available_actions=test_case["actions"]
+            scenario=scenario["scenario"],
+            available_actions=scenario["actions"]
         )
         results.append(result)
 
@@ -195,19 +195,19 @@ def run_integration_test():
     return results
 
 def main():
-    """Main function to run the integration test."""
-    print("Starting OpenAI o3 Responses API Integration Test")
+    """Main function to run the example."""
+    print("Starting OpenAI o3 Responses API Example")
     print("=" * 60)
 
     try:
-        results = run_integration_test()
+        results = run_example()
 
         print(f"\n{'='*60}")
-        print("Integration Test Summary")
+        print("Example Summary")
         print(f"{'='*60}")
 
         for i, result in enumerate(results, 1):
-            print(f"Test {i}: {result['action']}")
+            print(f"Scenario {i}: {result['action']}")
 
         # End the trace
         agentops.end_trace(tracer, end_state="Success")
@@ -220,13 +220,13 @@ def main():
         try:
             validation_result = agentops.validate_trace_spans(trace_context=tracer)
             agentops.print_validation_summary(validation_result)
-            print("✅ Integration test completed successfully!")
+            print("✅ Example completed successfully!")
         except agentops.ValidationError as e:
             print(f"❌ Error validating spans: {e}")
             raise
 
     except Exception as e:
-        print(f"❌ Integration test failed: {e}")
+        print(f"❌ Example failed: {e}")
         agentops.end_trace(tracer, end_state="Error")
         raise