diff --git a/examples/foundational/45-openai-agent-basic.py b/examples/foundational/45-openai-agent-basic.py
index 6d7456b7e..dc821add8 100644
--- a/examples/foundational/45-openai-agent-basic.py
+++ b/examples/foundational/45-openai-agent-basic.py
@@ -172,7 +172,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
                     "I can help you with weather information, share interesting facts, "
                     "or just have a conversation. What would you like to know?"
                 ),
-                EndFrame(),
+                # Don't send EndFrame() here - that closes the pipeline!
+                # The conversation should continue after the greeting
             ]
         )
 
diff --git a/src/pipecat/services/openai_agent/agent_service.py b/src/pipecat/services/openai_agent/agent_service.py
index 5a6461cdc..49d63a039 100644
--- a/src/pipecat/services/openai_agent/agent_service.py
+++ b/src/pipecat/services/openai_agent/agent_service.py
@@ -288,6 +288,8 @@ class OpenAIAgentService(AIService):
                 self._agent, input_text, context=self._session_config
             )
 
+            has_streaming_deltas = False
+
             # Process the stream events
             async for event in result.stream_events():
                 if event.type == "raw_response_event":
@@ -296,19 +298,23 @@ class OpenAIAgentService(AIService):
                     if hasattr(event.data, "delta") and getattr(event.data, "delta", None):
                         delta_text = getattr(event.data, "delta", "")
                         if delta_text:
+                            has_streaming_deltas = True
+                            self._accumulated_text += delta_text
                             await self.push_frame(LLMTextFrame(text=delta_text))
 
                 elif event.type == "run_item_stream_event":
                     # Handle completed items
                     if event.item.type == "message_output_item":
-                        # Get the complete message text
-                        message_text = self._extract_message_text(event.item)
-                        if message_text and message_text != self._accumulated_text:
-                            # Send any new text that wasn't already streamed
-                            new_text = message_text[len(self._accumulated_text) :]
-                            if new_text:
-                                await self.push_frame(LLMTextFrame(text=new_text))
-                            self._accumulated_text = message_text
+                        # Only process complete message if we didn't get streaming deltas
+                        if not has_streaming_deltas:
+                            message_text = self._extract_message_text(event.item)
+                            logger.debug(
+                                f"Processing complete message (no deltas): {message_text[:50]}..."
+                                if len(message_text) > 50
+                                else f"Processing complete message: {message_text}"
+                            )
+                            if message_text:
+                                await self.push_frame(LLMTextFrame(text=message_text))
 
                     elif event.item.type == "tool_call_item":
                         # Use getattr for safe attribute access
@@ -359,8 +365,27 @@ class OpenAIAgentService(AIService):
             The extracted text content.
         """
         try:
-            # Handle different message item formats
-            if hasattr(item, "content"):
+            # Handle OpenAI Agents SDK MessageOutputItem format
+            if hasattr(item, "raw_item") and hasattr(item.raw_item, "content"):
+                content = item.raw_item.content
+                if isinstance(content, list):
+                    text_parts = []
+                    for content_part in content:
+                        if hasattr(content_part, "text"):
+                            text_parts.append(content_part.text)
+                        elif (
+                            isinstance(content_part, dict)
+                            and content_part.get("type") == "output_text"
+                        ):
+                            text_parts.append(content_part.get("text", ""))
+                        elif isinstance(content_part, dict) and content_part.get("type") == "text":
+                            text_parts.append(content_part.get("text", ""))
+                    return "".join(text_parts)
+                elif isinstance(content, str):
+                    return content
+
+            # Handle direct content attribute
+            elif hasattr(item, "content"):
                 if isinstance(item.content, str):
                     return item.content
                 elif isinstance(item.content, list):
@@ -373,8 +398,9 @@ class OpenAIAgentService(AIService):
                             text_parts.append(content_part)
                     return "".join(text_parts)
 
-            # Fallback: try to get text through string conversion
-            return str(item)
+            # If no text content found, return empty string instead of str(item)
+            logger.debug(f"No extractable text content found in item: {type(item)}")
+            return ""
 
         except Exception as e:
             logger.warning(f"Could not extract text from message item: {e}")