Migrating to 1.0

Guide to upgrading your Pipecat application from 0.0.x to 1.0

Pipecat 1.0 removes many deprecated APIs from the 0.0.x series. If you were already using the non-deprecated replacements, most of these changes won’t affect you.

Before upgrading, search your codebase for the deprecated imports and patterns listed below to identify what needs to change.

Pipecat 1.0 requires Python 3.11 or later. Support for Python 3.10 has been dropped. Python 3.11 through 3.14 are supported.

Removed parameters are silently ignored, not errored. TransportParams and PipelineParams are Pydantic models that drop unknown fields, so leftover 0.0.x params like vad_analyzer, turn_analyzer, and allow_interruptions are accepted with no error or warning. Your app can start cleanly and look upgraded while turn detection is actually broken (missed user speech, no bot responses). Don’t rely on the app starting: delete these params from your transport/pipeline config and move them to LLMUserAggregatorParams as shown below.

1. Universal LLMContext

LLMContext is a universal context that works with all LLM providers. It allows you to dynamically switch LLMService at runtime, passing a compatible context between services. Pipecat maintains adapters for each LLM service, which are applied automatically at the time of inference.

Use the standard messages format along with FunctionSchema and ToolsSchema to define tools in a provider-agnostic way.

Before (1.0)

from pipecat.services.openai.llm import OpenAILLMService
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext

# Service-specific context
context = OpenAILLMContext(messages, tools)

# Service-specific aggregator factory
context_aggregator = llm.create_context_aggregator(context)

pipeline = Pipeline([
    transport.input(),
    stt,
    context_aggregator.user(),
    llm,
    tts,
    transport.output(),
    context_aggregator.assistant(),
])

After (1.0)

from pipecat.services.openai.llm import OpenAILLMService
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.adapters.schemas.function_schema import FunctionSchema
from pipecat.adapters.schemas.tools_schema import ToolsSchema

# Universal context — works with any LLM provider
tools = ToolsSchema(standard_tools=[
    FunctionSchema(
        name="get_weather",
        description="Get current weather",
        properties={"location": {"type": "string", "description": "City name"}},
        required=["location"],
    )
])
context = LLMContext(messages=messages, tools=tools)

# Universal aggregator
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context)

pipeline = Pipeline([
    transport.input(),
    stt,
    user_aggregator,
    llm,
    tts,
    transport.output(),
    assistant_aggregator,
])

What was removed

Removed	Replacement
OpenAILLMContext	LLMContext
OpenAILLMContextFrame	LLMContextFrame
AnthropicLLMContext	LLMContext
AWSBedrockLLMContext	LLMContext
GatedOpenAILLMContextAggregator	GatedLLMContextAggregator
llm.create_context_aggregator(context)	LLMContextAggregatorPair(context)
VisionImageFrame	LLMContext.add_image_frame_message()

2. Turn Management

Turn management was unified into the user context aggregator configuration. Strategies for interruptions, muting, and idle detection are now configured via LLMUserAggregatorParams.

Before (1.0)

from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.user_idle_processor import UserIdleProcessor

# Interruptions configured on the pipeline task
task = PipelineTask(
    pipeline,
    params=PipelineParams(allow_interruptions=True),
)

# Separate idle processor
idle = UserIdleProcessor(timeout=5.0, callback=handle_idle)

# STTMuteFilter
stt_mute_filter = STTMuteFilter(
    config=STTMuteConfig(strategies={STTMuteStrategy.FIRST_SPEECH})
)

pipeline = Pipeline([
    transport.input(),
    stt,
    stt_mute_filter,
    idle,
    context_aggregator.user(),
    llm,
    tts,
    transport.output(),
    context_aggregator.assistant(),
])

After (1.0)

from pipecat.processors.aggregators.llm_response_universal import (
    LLMContextAggregatorPair,
    LLMUserAggregatorParams,
)
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.turns.user_start import (
    TranscriptionUserTurnStartStrategy,
    VADUserTurnStartStrategy,
)
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies

# Everything configured on the aggregator
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
    context,
    user_params=LLMUserAggregatorParams(
        user_turn_strategies=UserTurnStrategies(
            start=[
                VADUserTurnStartStrategy(),
                TranscriptionUserTurnStartStrategy(),
            ],
            stop=[
                TurnAnalyzerUserTurnStopStrategy(
                    turn_analyzer=LocalSmartTurnAnalyzerV3()
                ),
            ],
        ),
        user_mute_strategies=[
            # Mute strategies
        ],
        user_turn_stop_timeout=5.0,
        user_idle_timeout=8.0,
        vad_analyzer=SileroVADAnalyzer(),
    ),
)

Where did allow_interruptions go? The allow_interruptions parameter was a legacy parameter used for non-voice AI applications. If you’re looking to prevent an interruption from occurring, consider using a user mute strategy instead. See the User Mute Strategies reference for more information.

What was removed

Removed	Replacement
PipelineParams.allow_interruptions	user_turn_strategies on LLMUserAggregatorParams
PipelineParams.interruption_strategies	user_turn_strategies on LLMUserAggregatorParams
UserResponseAggregator	LLMUserAggregator (created via LLMContextAggregatorPair)
UserIdleProcessor	user_idle_timeout on LLMUserAggregatorParams
STTMuteFilter	user_mute_strategies on LLMUserAggregatorParams
MinWordsInterruptionStrategy	MinWordsUserTurnStartStrategy
TranscriptionUserTurnStopStrategy	SpeechTimeoutUserTurnStopStrategy

3. VAD & Turn Analyzer Configuration

VAD and turn detection configuration moved from transport params to the user aggregator. Additionally, the VADParams default stops_secs changed from 0.8 to 0.2. This ensures that STT services create transcripts with optimal latency and sufficient silence padding.

The UserTurnStrategies (stop) now control how long to wait before the user’s turn has stopped:

• SpeechTimeoutUserTurnStopStrategy has a user_speech_timeout parameter that you can configure to control how long to wait before the user’s turn has stopped.
• TurnAnalyzerUserTurnStopStrategy uses the smart-turn model to dynamically modify the wait time. No configuration is required.

Before (1.0)

from pipecat.transports.services.daily import DailyParams, DailyTransport
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams

transport = DailyTransport(
    room_url,
    token,
    "Bot",
    DailyParams(
        vad_enabled=True,
        vad_audio_passthrough=True,
        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
    ),
)

After (1.0)

By default, the TurnAnalyzerUserTurnStopStrategy stop strategy is used, which includes the LocalSmartTurnAnalyzerV3 turn analyzer.

from pipecat.transports.daily.transport import DailyTransport, DailyParams
from pipecat.audio.vad.silero import SileroVADAnalyzer

transport = DailyTransport(
    room_url,
    token,
    "Bot",
    DailyParams(
        audio_in_enabled=True,
        audio_out_enabled=True,
    ),
)

# VAD is now configured on the aggregator
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
    context,
    user_params=LLMUserAggregatorParams(
        vad_analyzer=SileroVADAnalyzer(),
    ),
)

What was removed

Removed	Replacement
TransportParams.vad_analyzer	LLMUserAggregatorParams.vad_analyzer
TransportParams.vad_enabled	Removed (VAD is active when analyzer is set)
TransportParams.vad_audio_passthrough	Removed
TransportParams.turn_analyzer	UserTurnStrategies(stop=[TurnAnalyzerUserTurnStopStrategy()]) (now the default)
VADParams.stop_secs default (0.8)	Now defaults to 0.2; turn timing is controlled by stop strategies

4. Service Import Paths

All flat service imports have been removed. Services now use submodule imports.

Pattern change

# Before (1.0)
from pipecat.services.openai import OpenAILLMService

# After (1.0)
from pipecat.services.openai.llm import OpenAILLMService

Renamed/moved service modules

Old module	New module
pipecat.services.gemini_multimodal_live	pipecat.services.google.gemini_live
pipecat.services.aws_nova_sonic	pipecat.services.aws.nova_sonic
pipecat.services.openai_realtime	pipecat.services.openai.realtime
pipecat.services.riva (STT)	pipecat.services.nvidia.stt
pipecat.services.riva (TTS)	pipecat.services.nvidia.tts
pipecat.services.nim	pipecat.services.nvidia.llm

Removed service classes

These service have been removed.

Removed class	Replacement class
PollyTTSService	AWSPollyTTSService
OpenAIRealtimeBetaLLMService	OpenAIRealtimeLLMService
GoogleLLMOpenAIBetaService	GoogleLLMService

5. Transport Import Paths

Transport imports moved from services subdirectory to transport-specific subdirectories.

Old import	New import
pipecat.transports.services.daily	pipecat.transports.daily.transport
pipecat.transports.services.livekit	pipecat.transports.livekit.transport
pipecat.transports.network.websocket_server	pipecat.transports.websocket.server
pipecat.transports.network.websocket_client	pipecat.transports.websocket.client
pipecat.transports.network.fastapi_websocket	pipecat.transports.websocket.fastapi
pipecat.sync	pipecat.utils.sync

6. Frames

Several frame classes were renamed or removed. Update any direct references in your code.

Removed	Replacement
TransportMessageFrame	OutputTransportMessageFrame
TransportMessageUrgentFrame	OutputTransportMessageUrgentFrame
InputTransportMessageUrgentFrame	InputTransportMessageFrame
KeypadEntryFrame	DTMFFrame
StartInterruptionFrame	InterruptionFrame
BotInterruptionFrame	InterruptionWorkerFrame
TranscriptionMessage	Use events: on_user_turn_stopped, on_assistant_turn_stopped
TranscriptionUpdateFrame	Use events: on_user_turn_stopped, on_assistant_turn_stopped
DailyTransportMessageFrame	DailyOutputTransportMessageFrame
DailyTransportMessageUrgentFrame	DailyOutputTransportMessageUrgentFrame
LiveKitTransportMessageFrame	LiveKitOutputTransportMessageFrame
LiveKitTransportMessageUrgentFrame	LiveKitOutputTransportMessageUrgentFrame

7. Service-Specific Parameter Changes

Individual services renamed or removed configuration parameters. Find your service below to see what changed.

Service	Removed param	Replacement
DeepgramSTTService	url	base_url
DeepgramSTTService	vad_events	Removed
FishAudioTTSService	model	reference_id
GladiaSTTService	InputParams.language	Removed
GladiaSTTService	InputParams.confidence	Removed
GeminiTTSService	api_key	Removed
GeminiLiveLLMService	base_url	http_options
GoogleVertexLLMService	InputParams	Removed (project_id now required)
MiniMaxHttpTTSService	english_normalization	text_normalization
SimliVideoService	simli_config	api_key and face_id (required str)
AnthropicLLMService	enable_prompt_caching_beta	enable_prompt_caching
AWSNovaSonicLLMService	send_transcription_frames	Removed
OpenAIRealtimeLLMService	send_transcription_frames	Removed

8. Transport Parameters

All camera_* transport parameters were renamed to video_*. VAD-related transport params were removed — VAD is now configured on the user aggregator (see section 3).

Removed	Replacement
camera_in_enabled	video_in_enabled
camera_in_is_live	video_in_is_live
camera_in_width / camera_in_height	video_in_width / video_in_height
camera_out_enabled	video_out_enabled
camera_out_is_live	video_out_is_live
camera_out_width / camera_out_height	video_out_width / video_out_height
camera_out_bitrate	video_out_bitrate
camera_out_framerate	video_out_framerate
camera_out_codec	video_out_codec
vad_enabled	Removed
vad_audio_passthrough	Removed

9. Other API Changes

Smaller breaking changes across the rest of the API.

Pipeline

Removed	Replacement
PipelineParams.observers	Pass observers to PipelineTask constructor
PipelineTask.on_pipeline_ended	on_pipeline_finished
PipelineTask.on_pipeline_cancelled	on_pipeline_finished
PipelineTask.on_pipeline_stopped	on_pipeline_finished
DailyRunner.configure_with_args()	Use WorkerRunner with RunnerArguments

TTS service

Removed	Replacement
TTSService.say()	Push a TTSSpeakFrame
text_aggregator init param	Use LLMTextProcessor
text_filter init param	text_filters

Processors

Removed	Replacement
AudioBufferProcessor.user_continuous_stream	user_audio_passthrough
UserBotLatencyLogObserver	UserBotLatencyObserver (use on_latency_measured event)
TranscriptProcessor	Use events: on_user_turn_stopped, on_assistant_turn_stopped
add_pattern_pair()	add_pattern()

RTVI

• Deprecated RTVI models (RTVIConfig, RTVIServiceConfig) removed
• RTVIActionFrame removed
• RTVIProcessor.handle_function_call and handle_function_call_start removed

Other

Removed	Replacement
expect_stripped_words from LLMAssistantAggregatorParams	Removed
context field from UserImageRequestFrame	Removed
Old multi-parameter on_push_frame observer signature	Use new signature
pipecat.utils.tracing.class_decorators	Removed
NoisereduceFilter	Use KrispVivaFilter or other audio filters
KrispFilter	Use KrispVivaFilter
pipecat.turns.mute	pipecat.turns.user_mute