examples: deprecate start_callback from LLMService.register_function()

examples/foundational/14-function-calling.py

@@ -30,13 +30,8 @@ logger.remove(0)
 logger.add(sys.stderr, level="DEBUG")
 
 
-async def start_fetch_weather(function_name, llm, context):
-    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
-    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
-    logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
-
-
 async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
     await result_callback({"conditions": "nice", "temperature": "75"})
 
 
@@ -62,9 +57,10 @@ async def main():
         )
 
         llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
-        # Register a function_name of None to get all functions
+
+        # You can also register a function_name of None to get all functions
         # sent to the same callback with an additional function_name parameter.
-        llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
+        llm.register_function("get_current_weather", fetch_weather_from_api)
 
         weather_function = FunctionSchema(
             name="get_current_weather",

examples/foundational/14c-function-calling-together.py

@@ -31,13 +31,8 @@ logger.remove(0)
 logger.add(sys.stderr, level="DEBUG")
 
 
-async def start_fetch_weather(function_name, llm, context):
-    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
-    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
-    logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
-
-
 async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
     await result_callback({"conditions": "nice", "temperature": "75"})
 
 
@@ -66,9 +61,9 @@ async def main():
             api_key=os.getenv("TOGETHER_API_KEY"),
             model="meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo",
         )
-        # Register a function_name of None to get all functions
+        # You can also register a function_name of None to get all functions
         # sent to the same callback with an additional function_name parameter.
-        llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
+        llm.register_function("get_current_weather", fetch_weather_from_api)
 
         weather_function = FunctionSchema(
             name="get_current_weather",

examples/foundational/14e-function-calling-gemini.py

@@ -33,13 +33,8 @@ logger.add(sys.stderr, level="DEBUG")
 video_participant_id = None
 
 
-async def start_fetch_weather(function_name, llm, context):
-    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
-    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
-    logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
-
-
 async def get_weather(function_name, tool_call_id, arguments, llm, context, result_callback):
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
     location = arguments["location"]
     await result_callback(f"The weather in {location} is currently 72 degrees and sunny.")
 
@@ -72,7 +67,7 @@ async def main():
         )
 
         llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"), model="gemini-2.0-flash-001")
-        llm.register_function("get_weather", get_weather, start_fetch_weather)
+        llm.register_function("get_weather", get_weather)
         llm.register_function("get_image", get_image)
 
         weather_function = FunctionSchema(

examples/foundational/14f-function-calling-groq.py

@@ -31,13 +31,8 @@ logger.remove(0)
 logger.add(sys.stderr, level="DEBUG")
 
 
-async def start_fetch_weather(function_name, llm, context):
-    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
-    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
-    logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
-
-
 async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
     await result_callback({"conditions": "nice", "temperature": "75"})
 
 
@@ -65,9 +60,9 @@ async def main():
         )
 
         llm = GroqLLMService(api_key=os.getenv("GROQ_API_KEY"), model="llama-3.3-70b-versatile")
-        # Register a function_name of None to get all functions
+        # You can also register a function_name of None to get all functions
         # sent to the same callback with an additional function_name parameter.
-        llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
+        llm.register_function("get_current_weather", fetch_weather_from_api)
 
         weather_function = FunctionSchema(
             name="get_current_weather",

examples/foundational/14g-function-calling-grok.py

@@ -16,7 +16,6 @@ from runner import configure
 from pipecat.adapters.schemas.function_schema import FunctionSchema
 from pipecat.adapters.schemas.tools_schema import ToolsSchema
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -31,12 +30,6 @@ logger.remove(0)
 logger.add(sys.stderr, level="DEBUG")
 
 
-async def start_fetch_weather(function_name, llm, context):
-    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
-    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
-    logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
-
-
 async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
     await result_callback({"conditions": "nice", "temperature": "75"})
 
@@ -63,9 +56,9 @@ async def main():
         )
 
         llm = GrokLLMService(api_key=os.getenv("GROK_API_KEY"))
-        # Register a function_name of None to get all functions
+        # You can also register a function_name of None to get all functions
         # sent to the same callback with an additional function_name parameter.
-        llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
+        llm.register_function("get_current_weather", fetch_weather_from_api)
 
         weather_function = FunctionSchema(
             name="get_current_weather",

examples/foundational/14h-function-calling-azure.py

@@ -31,13 +31,8 @@ logger.remove(0)
 logger.add(sys.stderr, level="DEBUG")
 
 
-async def start_fetch_weather(function_name, llm, context):
-    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
-    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
-    logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
-
-
 async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
     await result_callback({"conditions": "nice", "temperature": "75"})
 
 
@@ -67,9 +62,9 @@ async def main():
             endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"),
             model=os.getenv("AZURE_CHATGPT_MODEL"),
         )
-        # Register a function_name of None to get all functions
+        # You can also register a function_name of None to get all functions
         # sent to the same callback with an additional function_name parameter.
-        llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
+        llm.register_function("get_current_weather", fetch_weather_from_api)
 
         weather_function = FunctionSchema(
             name="get_current_weather",

examples/foundational/14i-function-calling-fireworks.py

@@ -31,13 +31,8 @@ logger.remove(0)
 logger.add(sys.stderr, level="DEBUG")
 
 
-async def start_fetch_weather(function_name, llm, context):
-    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
-    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
-    logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
-
-
 async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
     await result_callback({"conditions": "nice", "temperature": "75"})
 
 
@@ -64,11 +59,11 @@ async def main():
 
         llm = FireworksLLMService(
             api_key=os.getenv("FIREWORKS_API_KEY"),
-            model="accounts/fireworks/models/firefunction-v2",
+            model="accounts/fireworks/models/llama-v3p1-405b-instruct",
         )
-        # Register a function_name of None to get all functions
+        # You can also register a function_name of None to get all functions
         # sent to the same callback with an additional function_name parameter.
-        llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
+        llm.register_function("get_current_weather", fetch_weather_from_api)
 
         weather_function = FunctionSchema(
             name="get_current_weather",

examples/foundational/14j-function-calling-nim.py

@@ -31,13 +31,8 @@ logger.remove(0)
 logger.add(sys.stderr, level="DEBUG")
 
 
-async def start_fetch_weather(function_name, llm, context):
-    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
-    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
-    logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
-
-
 async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
     await result_callback({"conditions": "nice", "temperature": "75"})
 
 
@@ -66,9 +61,9 @@ async def main():
         llm = NimLLMService(
             api_key=os.getenv("NVIDIA_API_KEY"), model="meta/llama-3.3-70b-instruct"
         )
-        # Register a function_name of None to get all functions
+        # You can also register a function_name of None to get all functions
         # sent to the same callback with an additional function_name parameter.
-        llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
+        llm.register_function("get_current_weather", fetch_weather_from_api)
 
         weather_function = FunctionSchema(
             name="get_current_weather",

examples/foundational/14k-function-calling-cerebras.py

@@ -31,13 +31,8 @@ logger.remove(0)
 logger.add(sys.stderr, level="DEBUG")
 
 
-async def start_fetch_weather(function_name, llm, context):
-    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
-    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
-    logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
-
-
 async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
     await result_callback({"conditions": "nice", "temperature": "75"})
 
 
@@ -63,9 +58,9 @@ async def main():
         )
 
         llm = CerebrasLLMService(api_key=os.getenv("CEREBRAS_API_KEY"), model="llama-3.3-70b")
-        # Register a function_name of None to get all functions
+        # You can also register a function_name of None to get all functions
         # sent to the same callback with an additional function_name parameter.
-        llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
+        llm.register_function("get_current_weather", fetch_weather_from_api)
 
         weather_function = FunctionSchema(
             name="get_current_weather",

examples/foundational/14l-function-calling-deepseek.py

@@ -31,13 +31,8 @@ logger.remove(0)
 logger.add(sys.stderr, level="DEBUG")
 
 
-async def start_fetch_weather(function_name, llm, context):
-    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
-    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
-    logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
-
-
 async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
     await result_callback({"conditions": "nice", "temperature": "75"})
 
 
@@ -63,9 +58,9 @@ async def main():
         )
 
         llm = DeepSeekLLMService(api_key=os.getenv("DEEPSEEK_API_KEY"), model="deepseek-chat")
-        # Register a function_name of None to get all functions
+        # You can also register a function_name of None to get all functions
         # sent to the same callback with an additional function_name parameter.
-        llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
+        llm.register_function("get_current_weather", fetch_weather_from_api)
 
         weather_function = FunctionSchema(
             name="get_current_weather",

examples/foundational/14m-function-calling-openrouter.py

@@ -31,13 +31,8 @@ logger.remove(0)
 logger.add(sys.stderr, level="DEBUG")
 
 
-async def start_fetch_weather(function_name, llm, context):
-    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
-    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
-    logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
-
-
 async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
     await result_callback({"conditions": "nice", "temperature": "75"})
 
 
@@ -67,9 +62,9 @@ async def main():
         llm = OpenRouterLLMService(
             api_key=os.getenv("OPENROUTER_API_KEY"), model="openai/gpt-4o-2024-11-20"
         )
-        # Register a function_name of None to get all functions
+        # You can also register a function_name of None to get all functions
         # sent to the same callback with an additional function_name parameter.
-        llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
+        llm.register_function("get_current_weather", fetch_weather_from_api)
 
         weather_function = FunctionSchema(
             name="get_current_weather",

examples/foundational/14o-function-calling-gemini-openai-format.py

@@ -31,13 +31,8 @@ logger.remove(0)
 logger.add(sys.stderr, level="DEBUG")
 
 
-async def start_fetch_weather(function_name, llm, context):
-    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
-    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
-    logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
-
-
 async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
     await result_callback({"conditions": "nice", "temperature": "75"})
 
 
@@ -63,11 +58,9 @@ async def main():
         )
 
         llm = GoogleLLMOpenAIBetaService(api_key=os.getenv("GEMINI_API_KEY"))
-        # Register a function_name of None to get all functions
+        # You can aslo register a function_name of None to get all functions
         # sent to the same callback with an additional function_name parameter.
-        llm.register_function(
+        llm.register_function("get_current_weather", fetch_weather_from_api)
-            "get_current_weather", fetch_weather_from_api, start_callback=start_fetch_weather
-        )
 
         weather_function = FunctionSchema(
             name="get_current_weather",

examples/foundational/14p-function-calling-gemini-vertex-ai.py

@@ -31,13 +31,8 @@ logger.remove(0)
 logger.add(sys.stderr, level="DEBUG")
 
 
-async def start_fetch_weather(function_name, llm, context):
-    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
-    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
-    logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
-
-
 async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
     await result_callback({"conditions": "nice", "temperature": "75"})
 
 
@@ -68,11 +63,9 @@ async def main():
                 project_id="<google-project-id>",
             )
         )
-        # Register a function_name of None to get all functions
+        # You can aslo register a function_name of None to get all functions
         # sent to the same callback with an additional function_name parameter.
-        llm.register_function(
+        llm.register_function("get_current_weather", fetch_weather_from_api)
-            "get_current_weather", fetch_weather_from_api, start_callback=start_fetch_weather
-        )
 
         weather_function = FunctionSchema(
             name="get_current_weather",

examples/foundational/22b-natural-conversation-proposal.py

@@ -199,13 +199,8 @@ class OutputGate(FrameProcessor):
                 break
 
 
-async def start_fetch_weather(function_name, llm, context):
-    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
-    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
-    logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
-
-
 async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
     await result_callback({"conditions": "nice", "temperature": "75"})
 
 
@@ -239,9 +234,9 @@ async def main():
 
         # This is the regular LLM.
         llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
-        # Register a function_name of None to get all functions
+        # You can also register a function_name of None to get all functions
         # sent to the same callback with an additional function_name parameter.
-        llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
+        llm.register_function("get_current_weather", fetch_weather_from_api)
 
         tools = [
             ChatCompletionToolParam(

examples/foundational/22c-natural-conversation-mixed-llms.py

@@ -403,13 +403,8 @@ class OutputGate(FrameProcessor):
                 break
 
 
-async def start_fetch_weather(function_name, llm, context):
-    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
-    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
-    logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
-
-
 async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
     await result_callback({"conditions": "nice", "temperature": "75"})
 
 
@@ -451,7 +446,7 @@ async def main():
         )
         # Register a function_name of None to get all functions
         # sent to the same callback with an additional function_name parameter.
-        llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
+        llm.register_function("get_current_weather", fetch_weather_from_api)
 
         tools = [
             ChatCompletionToolParam(

examples/foundational/24-stt-mute-filter.py

@@ -30,10 +30,6 @@ logger.remove(0)
 logger.add(sys.stderr, level="DEBUG")
 
 
-async def start_fetch_weather(function_name, llm, context):
-    logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
-
-
 async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
     # Add a delay to test interruption during function calls
     logger.info("Weather API call starting...")
@@ -72,7 +68,7 @@ async def main():
         tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-helios-en")
 
         llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
-        llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
+        llm.register_function("get_current_weather", fetch_weather_from_api)
 
         tools = [
             ChatCompletionToolParam(

examples/patient-intake/bot.py

@@ -142,7 +142,9 @@ class IntakeProcessor:
                 ]
             )
 
-    async def start_prescriptions(self, function_name, llm, context):
+    async def list_prescriptions(
+        self, function_name, tool_call_id, args, llm, context, result_callback
+    ):
         print(f"!!! doing start prescriptions")
         # Move on to allergies
         context.set_tools(
@@ -182,9 +184,12 @@ class IntakeProcessor:
         print(f"!!! about to await llm process frame in start prescrpitions")
         await llm.queue_frame(OpenAILLMContextFrame(context), FrameDirection.DOWNSTREAM)
         print(f"!!! past await process frame in start prescriptions")
+        await self.save_data(args, result_callback)
 
-    async def start_allergies(self, function_name, llm, context):
+    async def list_allergies(
-        print("!!! doing start allergies")
+        self, function_name, tool_call_id, args, llm, context, result_callback
+    ):
+        print("!!! doing list allergies")
         # Move on to conditions
         context.set_tools(
             [
@@ -221,8 +226,11 @@ class IntakeProcessor:
             }
         )
         await llm.queue_frame(OpenAILLMContextFrame(context), FrameDirection.DOWNSTREAM)
+        await self.save_data(args, result_callback)
 
-    async def start_conditions(self, function_name, llm, context):
+    async def list_conditions(
+        self, function_name, tool_call_id, args, llm, context, result_callback
+    ):
         print("!!! doing start conditions")
         # Move on to visit reasons
         context.set_tools(
@@ -260,8 +268,11 @@ class IntakeProcessor:
             }
         )
         await llm.queue_frame(OpenAILLMContextFrame(context), FrameDirection.DOWNSTREAM)
+        await self.save_data(args, result_callback)
 
-    async def start_visit_reasons(self, function_name, llm, context):
+    async def list_visit_reasons(
+        self, function_name, tool_call_id, args, llm, context, result_callback
+    ):
         print("!!! doing start visit reasons")
         # move to finish call
         context.set_tools([])
@@ -269,8 +280,9 @@ class IntakeProcessor:
             {"role": "system", "content": "Now, thank the user and end the conversation."}
         )
         await llm.queue_frame(OpenAILLMContextFrame(context), FrameDirection.DOWNSTREAM)
+        await self.save_data(args, result_callback)
 
-    async def save_data(self, function_name, tool_call_id, args, llm, context, result_callback):
+    async def save_data(self, args, result_callback):
         logger.info(f"!!! Saving data: {args}")
         # Since this is supposed to be "async", returning None from the callback
         # will prevent adding anything to context or re-prompting
@@ -319,18 +331,10 @@ async def main():
 
         intake = IntakeProcessor(context)
         llm.register_function("verify_birthday", intake.verify_birthday)
-        llm.register_function(
+        llm.register_function("list_prescriptions", intake.list_prescriptions)
-            "list_prescriptions", intake.save_data, start_callback=intake.start_prescriptions
+        llm.register_function("list_allergies", intake.list_allergies)
-        )
+        llm.register_function("list_conditions", intake.list_conditions)
-        llm.register_function(
+        llm.register_function("list_visit_reasons", intake.list_visit_reasons)
-            "list_allergies", intake.save_data, start_callback=intake.start_allergies
-        )
-        llm.register_function(
-            "list_conditions", intake.save_data, start_callback=intake.start_conditions
-        )
-        llm.register_function(
-            "list_visit_reasons", intake.save_data, start_callback=intake.start_visit_reasons
-        )
 
         fl = FrameLogger("LLM Output")