remove extra LLMFullResponseEndFrame

Added: Additional DTMF frames

CHANGELOG.md

@@ -41,6 +41,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Changed
 
+- Added `organization` and `project` level authentication to
+  `OpenAILLMService`.
+
 - Improved the language checking logic in `ElevenLabsTTSService` and
   `ElevenLabsHttpTTSService` to properly handle language codes based on model
   compatibility, with appropriate warnings when language codes cannot be
@@ -50,6 +53,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   contain a combination of function calls, function call responses, system
   messages, or just messages.
 
+- `InputDTMFFrame` is now based on `DTMFFrame`. There's also a new
+  `OutputDTMFFrame` frame.
+
 ### Fixed
 
 - Fixed an issue where `ElevenLabsTTSService` messages would return a 1009
@@ -67,11 +73,12 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Other
 
-- Updated all examples to use `task.cancel()` instead of pushing an `EndFrame`
-  when a participant leaves/disconnects. If you push an `EndFrame` this will
-  cause the bot to run through everything that is internally queued (which could
-  take seconds). Instead, if a participant disconnects there is nothing else to
-  be sent and therefore we should stop immediately.
+- Updated examples to use `task.cancel()` to immediately exit the example when a
+  participant leaves or disconnects, instead of pushing an `EndFrame`. Pushing
+  an `EndFrame` causes the bot to run through everything that is internally
+  queued (which could take some seconds). Note that using `task.cancel()` might
+  not always be the best option and pushing an `EndFrame` could still be
+  desirable to make sure all the pipeline is flushed.
 
 ## [0.0.54] - 2025-01-27
 

src/pipecat/frames/frames.py

@@ -397,12 +397,26 @@ class TransportMessageFrame(DataFrame):
 
 
 @dataclass
-class InputDTMFFrame(DataFrame):
-    """A DTMF button input"""
+class DTMFFrame(DataFrame):
+    """A DTMF button frame"""
 
     button: KeypadEntry
 
 
+@dataclass
+class InputDTMFFrame(DTMFFrame):
+    """A DTMF button input"""
+
+    pass
+
+
+@dataclass
+class OutputDTMFFrame(DTMFFrame):
+    """A DTMF button output"""
+
+    pass
+
+
 #
 # System frames
 #

src/pipecat/services/cartesia.py

@@ -250,9 +250,7 @@ class CartesiaTTSService(WordTTSService, WebsocketService):
                 # because we are likely still playing out audio and need the
                 # timestamp to set send context frames.
                 self._context_id = None
-                await self.add_word_timestamps(
-                    [("TTSStoppedFrame", 0), ("LLMFullResponseEndFrame", 0), ("Reset", 0)]
-                )
+                await self.add_word_timestamps([("TTSStoppedFrame", 0), ("Reset", 0)])
             elif msg["type"] == "timestamps":
                 await self.add_word_timestamps(
                     list(zip(msg["word_timestamps"]["words"], msg["word_timestamps"]["start"]))

src/pipecat/services/elevenlabs.py

@@ -284,7 +284,7 @@ class ElevenLabsTTSService(WordTTSService, WebsocketService):
         if isinstance(frame, (TTSStoppedFrame, StartInterruptionFrame)):
             self._started = False
             if isinstance(frame, TTSStoppedFrame):
-                await self.add_word_timestamps([("LLMFullResponseEndFrame", 0), ("Reset", 0)])
+                await self.add_word_timestamps([("Reset", 0)])
 
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)

src/pipecat/services/openai.py

@@ -116,6 +116,8 @@ class BaseOpenAILLMService(LLMService):
         model: str,
         api_key=None,
         base_url=None,
+        organization=None,
+        project=None,
         params: InputParams = InputParams(),
         **kwargs,
     ):
@@ -131,12 +133,16 @@ class BaseOpenAILLMService(LLMService):
             "extra": params.extra if isinstance(params.extra, dict) else {},
         }
         self.set_model_name(model)
-        self._client = self.create_client(api_key=api_key, base_url=base_url, **kwargs)
+        self._client = self.create_client(
+            api_key=api_key, base_url=base_url, organization=organization, project=project, **kwargs
+        )
 
-    def create_client(self, api_key=None, base_url=None, **kwargs):
+    def create_client(self, api_key=None, base_url=None, organization=None, project=None, **kwargs):
         return AsyncOpenAI(
             api_key=api_key,
             base_url=base_url,
+            organization=organization,
+            project=project,
             http_client=DefaultAsyncHttpxClient(
                 limits=httpx.Limits(
                     max_keepalive_connections=100, max_connections=1000, keepalive_expiry=None