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3 Commits

Author SHA1 Message Date
James Hush
8bbfa829d3 Remove wait 2025-11-26 12:27:02 +01:00
James Hush
c2eb663bdc Add TurnAwareTranscriptProcessor for turn-based transcript tracking
- Implements TurnAwareTranscriptProcessor that combines user and assistant transcript tracking with turn boundary detection
- Correctly handles interruptions by capturing only what was actually spoken
- Emits on_turn_started and on_turn_ended events with accumulated transcripts
- Handles async frame processing with strategic delays to ensure proper text accumulation
- Adds comprehensive tests covering basic flow, interruptions, and multiple turns
- Includes documentation and usage examples
2025-11-26 12:26:25 +01:00
James Hush
bf055843e6 Fix race condition in DeepgramFluxSTTService reconnection
Moved _receive_task and _watchdog_task creation from _connect_websocket() to _connect() to prevent multiple coroutines from attempting to receive from the websocket simultaneously during reconnection.

Previously, when reconnection occurred, _connect_websocket() would be called while the existing _receive_task was still running, causing both to try to receive from the websocket. This resulted in the error: 'cannot call recv while another coroutine is already running recv or recv_streaming'.

Now tasks are created only once during initial connection, and reconnection only re-establishes the websocket connection itself. This matches the pattern used by other websocket services in the codebase.

Fixes issue reported in 0.0.95 where reconnection attempts would fail with recv errors.
2025-11-26 10:11:19 +01:00
378 changed files with 7310 additions and 18703 deletions

View File

@@ -21,20 +21,20 @@ jobs:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Install uv
uses: astral-sh/setup-uv@v3
with:
version: "latest"
- name: Set up Python
run: uv python install 3.12
run: uv python install 3.10
- name: Install development dependencies
run: uv sync --group dev
- name: Build project
run: uv build
- name: Install project in editable mode
run: uv pip install --editable .
run: uv pip install --editable .

View File

@@ -22,22 +22,22 @@ jobs:
steps:
- name: Checkout repo
uses: actions/checkout@v4
- name: Install uv
uses: astral-sh/setup-uv@v3
with:
version: "latest"
- name: Set up Python
run: uv python install 3.12
run: uv python install 3.10
- name: Install development dependencies
run: uv sync --group dev
- name: Ruff formatter
id: ruff-format
run: uv run ruff format --diff
- name: Ruff linter (all rules)
id: ruff-check
run: uv run ruff check
run: uv run ruff check

View File

@@ -1,174 +0,0 @@
name: Generate Changelog for Release
on:
workflow_dispatch:
inputs:
version:
description: "Release version (e.g., 0.0.97)"
required: true
type: string
date:
description: "Release date (YYYY-MM-DD format, defaults to today)"
required: false
type: string
default: ""
permissions:
contents: write
pull-requests: write
jobs:
generate-changelog:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.12"
- name: Install uv
uses: astral-sh/setup-uv@v4
with:
enable-cache: true
- name: Install dependencies
run: |
uv sync --group dev
- name: Set release date
id: set_date
run: |
if [ -z "${{ inputs.date }}" ]; then
RELEASE_DATE=$(date +%Y-%m-%d)
echo "Using today's date: $RELEASE_DATE"
else
RELEASE_DATE="${{ inputs.date }}"
echo "Using provided date: $RELEASE_DATE"
fi
echo "release_date=$RELEASE_DATE" >> $GITHUB_OUTPUT
- name: Validate inputs
run: |
# Validate version format (basic check)
if ! [[ "${{ inputs.version }}" =~ ^[0-9]+\.[0-9]+\.[0-9]+.*$ ]]; then
echo "Error: Version must be in format X.Y.Z (e.g., 0.0.97)"
exit 1
fi
# Validate date format if provided
if [ -n "${{ inputs.date }}" ]; then
if ! date -d "${{ inputs.date }}" >/dev/null 2>&1; then
# Try macOS date format
if ! date -j -f "%Y-%m-%d" "${{ inputs.date }}" >/dev/null 2>&1; then
echo "Error: Date must be in YYYY-MM-DD format (e.g., 2025-12-04)"
exit 1
fi
fi
fi
- name: Check for changelog fragments
id: check_fragments
run: |
FRAGMENT_COUNT=$(find changelog -name "*.md" ! -name "_template.md.j2" | wc -l | tr -d ' ')
echo "fragment_count=$FRAGMENT_COUNT" >> $GITHUB_OUTPUT
if [ "$FRAGMENT_COUNT" -eq "0" ]; then
echo "❌ Error: No changelog fragments found in changelog/"
echo ""
echo "Cannot create a release without changelog entries."
echo "Add changelog fragments to the changelog/ directory (e.g., 1234.added.md) and try again."
exit 1
fi
# Validate fragment types
VALID_TYPES="added changed deprecated removed fixed security"
INVALID_FRAGMENTS=""
for file in changelog/*.md; do
# Skip template
if [[ "$file" == "changelog/_template.md.j2" ]]; then
continue
fi
# Extract type from filename (e.g., 1234.added.md -> added)
filename=$(basename "$file")
# Handle both 1234.added.md and 1234.added.2.md patterns
type=$(echo "$filename" | sed -E 's/^[0-9]+\.([a-z]+)(\.[0-9]+)?\.md$/\1/')
# Check if type is valid
if ! echo "$VALID_TYPES" | grep -wq "$type"; then
INVALID_FRAGMENTS="$INVALID_FRAGMENTS\n - $filename (type: '$type')"
fi
done
if [ -n "$INVALID_FRAGMENTS" ]; then
echo "❌ Error: Invalid changelog fragment types found:"
echo -e "$INVALID_FRAGMENTS"
echo ""
echo "Valid types are: $VALID_TYPES"
echo "Example: 1234.added.md, 5678.fixed.md"
exit 1
fi
echo "✓ Found $FRAGMENT_COUNT changelog fragment(s)"
echo "has_fragments=true" >> $GITHUB_OUTPUT
- name: Preview changelog
run: |
echo "## Preview of changelog for version ${{ inputs.version }}"
echo ""
uv run towncrier build --draft --version "${{ inputs.version }}" --date "${{ steps.set_date.outputs.release_date }}"
- name: Build changelog
run: |
uv run towncrier build --version "${{ inputs.version }}" --date "${{ steps.set_date.outputs.release_date }}" --yes
- name: Create Pull Request
uses: peter-evans/create-pull-request@v7
with:
token: ${{ secrets.GITHUB_TOKEN }}
commit-message: "Update changelog for version ${{ inputs.version }}"
title: "Release ${{ inputs.version }} - Changelog Update"
body: |
## Changelog Update for Release ${{ inputs.version }}
This PR updates the CHANGELOG.md with all changes for version **${{ inputs.version }}**.
### Summary
- **Version:** ${{ inputs.version }}
- **Date:** ${{ steps.set_date.outputs.release_date }}
- **Fragments processed:** ${{ steps.check_fragments.outputs.fragment_count }}
### What this PR does
- ✅ Adds new release section to CHANGELOG.md
- ✅ Removes processed changelog fragments
- ✅ Ready to merge for release
### Next Steps
1. Review the changelog entries below
2. Make any necessary edits to CHANGELOG.md if needed
3. Merge this PR
4. Continue with your release process
---
<details>
<summary>📋 Preview of changes</summary>
The changelog has been updated with entries from the following fragments:
```bash
${{ steps.check_fragments.outputs.fragment_count }} fragments processed
```
</details>
branch: changelog-${{ inputs.version }}
delete-branch: true
labels: |
changelog
release

View File

@@ -50,6 +50,7 @@ jobs:
run: |
uv sync --group dev --all-extras \
--no-extra krisp \
--no-extra ultravox \
--no-extra local-smart-turn \
--no-extra moondream \
--no-extra mlx-whisper

View File

@@ -11,7 +11,7 @@ build:
jobs:
post_install:
- pip install uv
- UV_PROJECT_ENVIRONMENT=$READTHEDOCS_VIRTUALENV_PATH uv sync --group docs --all-extras --no-extra krisp --no-extra gstreamer --no-extra local_smart_turn --no-extra moondream --no-extra riva --no-extra mlx-whisper
- UV_PROJECT_ENVIRONMENT=$READTHEDOCS_VIRTUALENV_PATH uv sync --group docs --all-extras --no-extra krisp --no-extra gstreamer --no-extra ultravox --no-extra local_smart_turn --no-extra moondream --no-extra riva --no-extra mlx-whisper
sphinx:
configuration: docs/api/conf.py

View File

@@ -5,387 +5,10 @@ All notable changes to **Pipecat** will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
<!-- towncrier release notes start -->
## [0.0.98] - 2025-12-17
## [Unreleased]
### Added
- Added `RimeNonJsonTTSService` which supports non-JSON streaming mode. This
new class supports websocket streaming for the Arcana model.
(PR [#3085](https://github.com/pipecat-ai/pipecat/pull/3085))
- Added additional functionality related to "thinking", for Google and
Anthropic LLMs.
1. New typed parameters for Google and Anthropic LLMs that control the
models' thinking behavior (like how much thinking to do, and whether to
output thoughts or thought summaries):
- `AnthropicLLMService.ThinkingConfig`
- `GoogleLLMService.ThinkingConfig`
2. New frames for representing thoughts output by LLMs:
- `LLMThoughtStartFrame`
- `LLMThoughtTextFrame`
- `LLMThoughtEndFrame`
3. A generic mechanism for recording LLM thoughts to context, used
specifically to support Anthropic, whose thought signatures are expected
to appear alongside the text of the thoughts within assistant context
messages. See:
- `LLMThoughtEndFrame.signature`
- `LLMAssistantAggregator` handling of the above field
- `AnthropicLLMAdapter` handling of `"thought"` context messages
4. Google-specific logic for inserting thought signatures into the context,
to help maintain thinking continuity in a chain of LLM calls. See:
- `GoogleLLMService` sending `LLMMessagesAppendFrame`s to add
LLM-specific
`"thought_signature"` messages to context
- `GeminiLLMAdapter` handling of `"thought_signature"` messages
5. An expansion of `TranscriptProcessor` to process LLM thoughts in
addition to user and assistant utterances. See:
- `TranscriptProcessor(process_thoughts=True)` (defaults to `False`)
- `ThoughtTranscriptionMessage`, which is now also emitted with the
`"on_transcript_update"` event
(PR [#3175](https://github.com/pipecat-ai/pipecat/pull/3175))
- Data and control frames can now be marked as non-interruptible by using the
`UninterruptibleFrame` mixin. Frames marked as `UninterruptibleFrame` will
not be interrupted during processing, and any queued frames of this type will
be retained in the internal queues. This is useful when you need ordered
frames (data or control) that should not be discarded or cancelled due to
interruptions.
(PR [#3189](https://github.com/pipecat-ai/pipecat/pull/3189))
- Added `on_conversation_detected` event to `VoicemaiDetector`.
(PR [#3207](https://github.com/pipecat-ai/pipecat/pull/3207))
- Added `x-goog-api-client` header with Pipecat's version to all Google
services' requests.
(PR [#3208](https://github.com/pipecat-ai/pipecat/pull/3208))
- Added support for the HeyGen LiveAvatar API (see https://www.liveavatar.com/).
(PR [#3210](https://github.com/pipecat-ai/pipecat/pull/3210))
- Added to `AWSNovaSonicLLMService` functionality related to the new (and now
default) Nova 2 Sonic model (`"amazon.nova-2-sonic-v1:0"`):
- Added the `endpointing_sensitivity` parameter to control how quickly the
model decides the user has stopped speaking.
- Made the assistant-response-trigger hack a no-op. It's only needed for
the older Nova Sonic model.
(PR [#3212](https://github.com/pipecat-ai/pipecat/pull/3212))
- [Ultravox Realtime](https://docs.ultravox.ai) is now a supported
speech-to-speech service.
- Added `UltravoxRealtimeLLMService` for the integration.
- Added `49-ultravox-realtime.py` example (with tool calling).
(PR [#3227](https://github.com/pipecat-ai/pipecat/pull/3227))
- Added Daily PSTN dial-in support to the development runner with `--dialin`
flag. This includes:
- `/daily-dialin-webhook` endpoint that handles incoming Daily PSTN webhooks
- Automatic Daily room creation with SIP configuration
- `DialinSettings` and `DailyDialinRequest` types in `pipecat.runner.types`
for type-safe dial-in data
- The runner now mimics Pipecat Cloud's dial-in webhook handling for local
development
(PR [#3235](https://github.com/pipecat-ai/pipecat/pull/3235))
- Add Gladia session id to logs for `GladiaSTTService`.
(PR [#3236](https://github.com/pipecat-ai/pipecat/pull/3236))
- Added `InworldHttpTTSService` which uses Inworld's HTTP based TTS service in
either streaming or non-streaming mode. Note: This class was previously named
`InworldTTSService`.
(PR [#3239](https://github.com/pipecat-ai/pipecat/pull/3239))
- Added `language_hints_strict` parameter to `SonioxSTTService` to strictly
enforces language hints. This ensures that transcription occurs in the
specified language.
(PR [#3245](https://github.com/pipecat-ai/pipecat/pull/3245))
- Added Pipecat library version info to the `about` field in the `bot-ready`
RTVI message.
(PR [#3248](https://github.com/pipecat-ai/pipecat/pull/3248))
- Added `VisionFullResponseStartFrame`, `VisionFullResponseEndFrame` and
`VisionTextFrame`. This are used by vision services similar to LLM
services.
(PR [#3252](https://github.com/pipecat-ai/pipecat/pull/3252))
### Changed
- `FunctionCallInProgressFrame` and `FunctionCallResultFrame` have changed from
system frames to a control frame and a data frame, respectively, and are
now both marked as `UninterruptibleFrame`.
(PR [#3189](https://github.com/pipecat-ai/pipecat/pull/3189))
- `UserBotLatencyLogObserver` now uses `VADUserStartedSpeakingFrame` and
`VADUserStoppedSpeakingFrame` to determine latency from user stopped speaking
to bot started speaking.
(PR [#3206](https://github.com/pipecat-ai/pipecat/pull/3206))
- Updated `HeyGenVideoService` and `HeyGenTransport` to support both HeyGen
APIs (Interactive Avatar and Live Avatar).
Using them is as simple as specifying the `service_type` when creating the
`HeyGenVideoService` and the `HeyGenTransport`:
```python
heyGen = HeyGenVideoService(
api_key=os.getenv("HEYGEN_LIVE_AVATAR_API_KEY"),
service_type=ServiceType.LIVE_AVATAR,
session=session,
)
```
(PR [#3210](https://github.com/pipecat-ai/pipecat/pull/3210))
- Made `"amazon.nova-2-sonic-v1:0"` the new default model for
`AWSNovaSonicLLMService`.
(PR [#3212](https://github.com/pipecat-ai/pipecat/pull/3212))
- Updated the `run_inference` methods in the LLM service classes
(`AnthropicLLMService`, `AWSBedrockLLMService`, `GoogleLLMService`, and
`OpenAILLMService` and its base classes) to use the provided LLM
configuration parameters.
(PR [#3214](https://github.com/pipecat-ai/pipecat/pull/3214))
- Updated default models for:
- `GeminiLiveLLMService` to `gemini-2.5-flash-native-audio-preview-12-2025`.
- `GeminiLiveVertexLLMService` to `gemini-live-2.5-flash-native-audio`.
(PR [#3228](https://github.com/pipecat-ai/pipecat/pull/3228))
- Changed the `reason` field in `EndFrame`, `CancelFrame`, `EndTaskFrame`, and
`CancelTaskFrame` from `str` to `Any` to indicate that it can hold values
other than strings.
(PR [#3231](https://github.com/pipecat-ai/pipecat/pull/3231))
- Updated websocket STT services to use the `WebsocketSTTService` base class.
This base class manages the websocket connection and handles reconnects.
Updated services:
- `AssemblyAISTTService`
- `AWSTranscribeSTTService`
- `GladiaSTTService`
- `SonioxSTTService`
(PR [#3236](https://github.com/pipecat-ai/pipecat/pull/3236))
- Changed Inworld's TTS service implementations:
- Previously, the HTTP implementation was named `InworldTTSService`. That
has been moved to `InworldHttpTTSService`. This service now supports
word-timestamp alignment data in both streaming and non-streaming modes.
- Updated the `InworldTTSService` class to use Inworld's Websocket API.
This class now has support for word-timestamp alignment data and tracks
contexts for each user turn.
(PR [#3239](https://github.com/pipecat-ai/pipecat/pull/3239))
- ⚠️ Breaking change: `WordTTSService.start_word_timestamps()` and
`WordTTSService.reset_word_timestamps()` are now async.
(PR [#3240](https://github.com/pipecat-ai/pipecat/pull/3240))
- Updated the current RTVI version to 1.1.0 to reflect recent additions and
deprecations.
- New RTVI Messages: `send-text` and `bot-output`
- Deprecated Messages: `append-to-context` and `bot-transcription`
(PR [#3248](https://github.com/pipecat-ai/pipecat/pull/3248))
- `MoondreamService` now pushes `VisionFullResponseStartFrame`,
`VisionFullResponseEndFrame` and `VisionTextFrame`.
(PR [#3252](https://github.com/pipecat-ai/pipecat/pull/3252))
### Deprecated
- `FalSmartTurnAnalyzer` and `LocalSmartTurnAnalyzer` are deprecated and will
be removed in a future version. Use `LocalSmartTurnAnalyzerV3` instead.
(PR [#3219](https://github.com/pipecat-ai/pipecat/pull/3219))
### Removed
- Removed the deprecated VLLM-based open source Ultravox STT service.
(PR [#3227](https://github.com/pipecat-ai/pipecat/pull/3227))
### Fixed
- Fixed a bug in `AWSNovaSonicLLMService` where we would mishandle cancelled
tool calls in the context, resulting in errors.
(PR [#3212](https://github.com/pipecat-ai/pipecat/pull/3212))
- Better support conversation history with Gemini 2.5 Flash Image (model
"gemini-2.5-flash-image"). Prior to this fix, the model had no memory of
previous images it had generated, so it wouldn't be able to iterate on
them.
(PR [#3224](https://github.com/pipecat-ai/pipecat/pull/3224))
- Support conversations with Gemini 3 Pro Image (model
"gemini-3-pro-image-preview"). Prior to this fix, after the model generated
an image the conversation would not be able to progress.
(PR [#3224](https://github.com/pipecat-ai/pipecat/pull/3224))
- Fixed an issue where `ElevenLabsHttpTTSService` was not updating
voice settings when receiving a `TTSUpdateSettingsFrame`.
(PR [#3226](https://github.com/pipecat-ai/pipecat/pull/3226))
- Fixed the return type for `SmallWebRTCRequestHandler.handle_web_request()`
function.
(PR [#3230](https://github.com/pipecat-ai/pipecat/pull/3230))
- Fix a bug in LLM context audio content handling
(PR [#3234](https://github.com/pipecat-ai/pipecat/pull/3234))
- In `GladiaSTTService`, reset the `_bytes_sent` counter on connecting the
websocket. This avoids unnecessary audio buffer trimming.
(PR [#3236](https://github.com/pipecat-ai/pipecat/pull/3236))
- Fixed a TTS service word-timestamp issue that could cause generated
`TTSTextFrame` instances to have an incorrect pts (`pts = -1`).
(PR [#3240](https://github.com/pipecat-ai/pipecat/pull/3240))
- Fixed an issue in `SimpleTextAggreagtor` where spaces were not being stripped
before returning the aggregation. This resulted in an extra space for TTS
services that don't support word-timestamp alignment data.
(PR [#3247](https://github.com/pipecat-ai/pipecat/pull/3247))
## [0.0.97] - 2025-12-05
### Added
- Added new Gradium services, `GradiumSTTService` and `GradiumTTSService`, for
speech-to-text and text-to-speech functionality using Gradium's API.
- Additions for `AsyncAITTSService` and `AsyncAIHttpTTSService`:
- Added new `languages`: `pt`, `nl`, `ar`, `ru`, `ro`, `ja`, `he`, `hy`,
`tr`, `hi`, `zh`.
- Updated the default model to `asyncflow_multilingual_v1.0` for improved
accuracy and broader language coverage.
- Added optional tool and tool output filters for MCP services.
### Changed
- Updated Deepgram logging to include Deepgram request IDs for improved
debugging.
- Text Aggregation Improvements:
- **Breaking Change**: `BaseTextAggregator.aggregate()` now returns
`AsyncIterator[Aggregation]` instead of `Optional[Aggregation]`. This
enables the aggregator to return multiple results based on the provided
text.
- Refactored text aggregators to use inheritance: `SkipTagsAggregator` and
`PatternPairAggregator` now inherit from `SimpleTextAggregator`, reusing
the base class's sentence detection logic.
- Improved interruption handling to prevent bots from repeating themselves. LLM
services that return multiple sentences in a single response (e.g.,
`GoogleLLMService`) are now split into individual sentences before being sent
to TTS. This ensures interruptions occur at sentence boundaries, preventing
the bot from repeating content after being interrupted during long responses.
- Updated `AICFilter` to use Quail STT as the default model
(`AICModelType.QUAIL_STT`). Quail STT is optimized for human-to-machine
interaction (e.g., voice agents, speech-to-text) and operates at a native
sample rate of 16 kHz with fixed enhancement parameters.
- If an unexpected exception is caught, or if `FrameProcessor.push_error()` is
called with an exception, the file name and line number where the exception
occured are now logged.
- Updated Smart Turn model weights to v3.1.
- Smart Turn analyzer now uses the full context of the turn rather than just
the audio since VAD last triggered.
- Updated `CartesiaSTTService` to return the full transcription `result` in the
`TranscriptionFrame` and `InterimTranscriptionFrame`. This provides access to
word timestamp data.
- `HumeTTSService` changes:
- Added tracking headers (`X-Hume-Client-Name` and `X-Hume-Client-Version`)
to all requests made by `HumeTTSService` to the Hume API for better usage
tracking and analytics.
- Added `stop()` and `cancel()` cleanup methods to `HumeTTSService` to
properly close the HTTP client and prevent resource leaks.
### Deprecated
- NVIDIA Services name changes (all functionality is unchanged):
- `NimLLMService` is now deprecated, use `NvidiaLLMService` instead.
- `RivaSTTService` is now deprecated, use `NvidiaSTTService` instead.
- `RivaTTSService` is now deprecated, use `NvidiaTTSService` instead.
- Use `uv pip install pipecat-ai[nvidia]` instead of
`uv pip install pipecat-ai[riva]`
- The `noise_gate_enable` parameter in `AICFilter` is deprecated and no longer
has any effect. Noise gating is now handled automatically by the AIC VAD
system. Use `AICFilter.create_vad_analyzer()` for VAD functionality instead.
- Package `pipecat.sync` is deprecated, use `pipecat.utils.sync` instead.
### Fixed
- Fixed bug in `PatternPairAggregator` where pattern handlers could be called
multiple times for `KEEP` or `AGGREGATE` patterns.
- Fixed sentence aggregation to correctly handle ambiguous punctuation in
streaming text, such as currency ("$29.95") and abbreviations ("Mr. Smith").
- Fixed an issue in `AWSTranscribeSTTService` where the `region` arg was always
set to `us-east-1` when providing an AWS_REGION env var.
- Fixed an issue in `SarvamTTSService` where the last sentence was not being
spoken. Now, audio is flushed when the TTS services receives the
`LLMFullResponseEndFrame` or `EndFrame`.
- Fixed an issue in `DeepgramTTSService` where a `TTSStoppedFrame` was
incorrectly pushed after a functional call. This caused an issue with the
voice-ui-kit's conversational panel rending of the LLM output after a
function call.
- Fixed an issue where `LLMTextFrame.skip_tts` was being overwritten by LLM
services.
- Fixed an issue that caused `WebsocketService` instances to attempt
reconnection during shutdown.
- Fixed an issue in `ElevenLabsTTSService` where character usage metrics were
only reported on the first TTS generation per turn.
## [0.0.96] - 2025-11-26 🦃 "Happy Thanksgiving!" 🦃
### Added
- Added `AWSBedrockAgentCoreProcessor` to support invoking an AgentCore-hosted
agent in a Pipecat pipeline.
- Enhanced error handling across the framework:
- Added `on_error` callback to `FrameProcessor` for centralized error
handling.
- Renamed `push_error(error: ErrorFrame)` to `push_error_frame(error: ErrorFrame)`
for clarity.
- Added new `push_error` method for simplified error reporting:
```python
async def push_error(error_msg: str,
exception: Optional[Exception] = None,
fatal: bool = False)
```
- Standardized error logging by replacing `logger.exception` calls with
`logger.error` throughout the codebase.
- Added `cache_read_input_tokens`, `cache_creation_input_tokens` and
`reasoning_tokens` to OTel spans for LLM call
- Added `LiveKitRESTHelper` utility class for managing LiveKit rooms via REST API.
- Added `DeepgramSageMakerSTTService` which connects to a SageMaker hosted
@@ -465,18 +88,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
- Added new emotions: calm and fluent
- Added `enable_logging` to `SimliVideoService` input parameters. It's disabled
by default.
### Changed
- Updated `FishAudioTTSService` default model to `s1`.
- Updated `DeepgramTTSService` to use Deepgram's TTS websocket API. ⚠️ This is
a potential breaking change, which only affects you if you're self-hosting
`DeepgramTTSService`. The new service uses Websockets and improves TTFB
latency.
- Updated `daily-python` to 0.22.0.
- `BaseTextAggregator` changes:
@@ -634,11 +247,6 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
### Fixed
- Fixed an issue in `AWSBedrockLLMService` where the `aws_region` arg was
always set to `us-east-1` when providing an AWS_REGION env var.
- Fixed an issue with `DeepgramFluxSTTService` where it sometimes failed to reconnect.
- Fixed an issue in `ElevenLabsRealtimeSTTService` where dynamic language
updates were not working.

View File

@@ -79,7 +79,7 @@ Once your PR is submitted, post in the `#community-integrations` Discord channel
**Examples:**
- [NvidiaSTTService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/nvidia/stt.py)
- [RivaSTTService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/riva/stt.py)
- [FalSTTService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/fal/stt.py)
#### Key requirements:

View File

@@ -17,121 +17,24 @@ We welcome contributions of all kinds! Your help is appreciated. Follow these st
git checkout -b your-branch-name
```
4. **Make your changes**: Edit or add files as necessary.
5. **Add a changelog entry**: Create a changelog fragment file (see [Changelog Entries](#changelog-entries) below).
6. **Test your changes**: Ensure that your changes look correct and follow the style set in the codebase.
7. **Commit your changes**: Once you're satisfied with your changes, commit them with a meaningful message.
5. **Test your changes**: Ensure that your changes look correct and follow the style set in the codebase.
6. **Commit your changes**: Once you're satisfied with your changes, commit them with a meaningful message.
```bash
git commit -m "Description of your changes"
```
8. **Push your changes**: Push your branch to your forked repository.
7. **Push your changes**: Push your branch to your forked repository.
```bash
git push origin your-branch-name
```
9. **Submit a Pull Request (PR)**: Open a PR from your forked repository to the main branch of this repo.
8. **Submit a Pull Request (PR)**: Open a PR from your forked repository to the main branch of this repo.
> Important: Describe the changes you've made clearly!
Our maintainers will review your PR, and once everything is good, your contributions will be merged!
## Changelog Entries
Every pull request that makes a user-facing change should include a changelog entry. We use a changelog fragment system to avoid merge conflicts.
### Creating a Changelog Fragment
1. Create a new file in the `changelog/` directory with this naming pattern:
```
<PR_number>.<type>.md
```
2. Choose the appropriate type:
- `added.md` - New features
- `changed.md` - Changes in existing functionality
- `deprecated.md` - Soon-to-be removed features
- `removed.md` - Removed features
- `fixed.md` - Bug fixes
- `security.md` - Security fixes
3. Write your changelog entry as a Markdown bullet point. Include the `-` at the start:
**Example files:**
`changelog/1234.added.md`:
```markdown
- Added support for Anthropic Claude 3.5 Sonnet with improved streaming performance.
```
`changelog/5678.fixed.md`:
```markdown
- Fixed an issue where audio frames were dropped during high-load scenarios.
```
**For entries with nested bullets:**
`changelog/1234.changed.md`:
```markdown
- Updated service configuration:
- Changed default timeout to 30 seconds
- Added retry logic for failed connections
```
### Multiple Changes in One PR
**Different types of changes:** Create separate fragment files for each type:
```
changelog/1234.added.md
changelog/1234.fixed.md
```
**Multiple changes of the same type:** Create numbered fragment files:
```
changelog/1234.changed.md
changelog/1234.changed.2.md
```
**Related changes:** Use nested bullets in a single fragment:
```markdown
- Updated service configuration:
- Changed default timeout to 30 seconds
- Added retry logic for failed connections
```
**Rule of thumb:** One logical change per fragment file. If changes are unrelated, use separate files.
### Preview Your Changes
To see what your changelog entry will look like:
```bash
towncrier build --draft --version Unreleased
```
This won't modify any files, just show you a preview.
### When to Skip Changelog Entries
You can skip adding a changelog entry for:
- Documentation-only changes
- Internal refactoring with no user-facing impact
- Test-only changes
- CI/build configuration changes
If you're unsure whether your change needs a changelog entry, ask in your PR!
## Dependency Management
This project uses [uv](https://docs.astral.sh/uv/) for dependency management. The `uv.lock` file is committed to ensure reproducible builds.

View File

@@ -3,6 +3,7 @@
</div></h1>
[![PyPI](https://img.shields.io/pypi/v/pipecat-ai)](https://pypi.org/project/pipecat-ai) ![Tests](https://github.com/pipecat-ai/pipecat/actions/workflows/tests.yaml/badge.svg) [![codecov](https://codecov.io/gh/pipecat-ai/pipecat/graph/badge.svg?token=LNVUIVO4Y9)](https://codecov.io/gh/pipecat-ai/pipecat) [![Docs](https://img.shields.io/badge/Documentation-blue)](https://docs.pipecat.ai) [![Discord](https://img.shields.io/discord/1239284677165056021)](https://discord.gg/pipecat) [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/pipecat-ai/pipecat)
[![](https://getmanta.ai/api/badges?text=Manta%20Graph&link=manta)](https://getmanta.ai/pipecat)
# 🎙️ Pipecat: Real-Time Voice & Multimodal AI Agents
@@ -71,19 +72,19 @@ Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.yout
## 🧩 Available services
| Category | Services |
| ------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/server/services/stt/aws), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/stt/elevenlabs), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Gradium](https://docs.pipecat.ai/server/services/stt/gradium), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [NVIDIA Riva](https://docs.pipecat.ai/server/services/stt/riva), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [SambaNova (Whisper)](https://docs.pipecat.ai/server/services/stt/sambanova), [Sarvam](https://docs.pipecat.ai/server/services/stt/sarvam), [Soniox](https://docs.pipecat.ai/server/services/stt/soniox), [Speechmatics](https://docs.pipecat.ai/server/services/stt/speechmatics), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) |
| LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/server/services/llm/aws), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [Mistral](https://docs.pipecat.ai/server/services/llm/mistral), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/server/services/llm/sambanova) [Together AI](https://docs.pipecat.ai/server/services/llm/together) |
| Text-to-Speech | [Async](https://docs.pipecat.ai/server/services/tts/asyncai), [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [Gradium](https://docs.pipecat.ai/server/services/tts/gradium), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Hume](https://docs.pipecat.ai/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [Speechmatics](https://docs.pipecat.ai/server/services/tts/speechmatics), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) |
| Speech-to-Speech | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [Grok Voice Agent](https://docs.pipecat.ai/server/services/s2s/grok), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai), Ultravox, |
| Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local |
| Serializers | [Plivo](https://docs.pipecat.ai/server/utilities/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/utilities/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/utilities/serializers/telnyx) |
| Video | [HeyGen](https://docs.pipecat.ai/server/services/video/heygen), [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) |
| Memory | [mem0](https://docs.pipecat.ai/server/services/memory/mem0) |
| Vision & Image | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/fal), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream) |
| Audio Processing | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [ai-coustics](https://docs.pipecat.ai/server/utilities/audio/aic-filter) |
| Analytics & Metrics | [OpenTelemetry](https://docs.pipecat.ai/server/utilities/opentelemetry), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) |
| Category | Services |
| ------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/server/services/stt/aws), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/stt/elevenlabs), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [NVIDIA Riva](https://docs.pipecat.ai/server/services/stt/riva), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [SambaNova (Whisper)](https://docs.pipecat.ai/server/services/stt/sambanova), [Sarvam](https://docs.pipecat.ai/server/services/stt/sarvam), [Soniox](https://docs.pipecat.ai/server/services/stt/soniox), [Speechmatics](https://docs.pipecat.ai/server/services/stt/speechmatics), [Ultravox](https://docs.pipecat.ai/server/services/stt/ultravox), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) |
| LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/server/services/llm/aws), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [Mistral](https://docs.pipecat.ai/server/services/llm/mistral), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/server/services/llm/sambanova) [Together AI](https://docs.pipecat.ai/server/services/llm/together) |
| Text-to-Speech | [Async](https://docs.pipecat.ai/server/services/tts/asyncai), [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Hume](https://docs.pipecat.ai/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [Speechmatics](https://docs.pipecat.ai/server/services/tts/speechmatics), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) |
| Speech-to-Speech | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai) |
| Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local |
| Serializers | [Plivo](https://docs.pipecat.ai/server/utilities/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/utilities/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/utilities/serializers/telnyx) |
| Video | [HeyGen](https://docs.pipecat.ai/server/services/video/heygen), [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) |
| Memory | [mem0](https://docs.pipecat.ai/server/services/memory/mem0) |
| Vision & Image | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/fal), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream) |
| Audio Processing | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [ai-coustics](https://docs.pipecat.ai/server/utilities/audio/aic-filter) |
| Analytics & Metrics | [OpenTelemetry](https://docs.pipecat.ai/server/utilities/opentelemetry), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) |
📚 [View full services documentation →](https://docs.pipecat.ai/server/services/supported-services)
@@ -153,6 +154,7 @@ You can get started with Pipecat running on your local machine, then move your a
--no-extra gstreamer \
--no-extra krisp \
--no-extra local \
--no-extra ultravox # (ultravox not fully supported on macOS)
```
3. Install the git pre-commit hooks:

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@@ -1,40 +0,0 @@
- Introducing user and bot turn start strategies. Turn start strategies indicate when user and bot turns begin. In conversational agents, these are often referred to as start/stop speaking or turn-taking plans or policies.
User turn start strategies indicate when the user starts speaking (e.g. using VAD events or when a user says one or more words).
Bot turn start strategies indicate when the bot should start speaking (e.g. using an end-of-turn detection model or by observing incoming transcriptions).
A list of strategies can be specified for both the user and the bot; strategies are evaluated in order until one evaluates to true.
Available user turn start strategies:
- VADUserTurnStartStrategy
- TranscriptionUserTurnStartStrategy
- MinWordsUserTurnStartStrategy
Available bot turn start strategies:
- TranscriptionBotTurnStartStrategy
- TurnAnalyzerBotTurnStartStrategy
The default strategies are:
- user: [VADUserTurnStartStrategy, TranscriptionUserTurnStartStrategy]
- bot: [TranscriptionBotTurnStartStrategy]
Turn start strategies are configured when setting up `LLMContextAggregatorPair`. For example:
```python
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[
TurnAnalyzerBotTurnStartStrategy(
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams())
)
],
)
),
)
```
In order to use the turn start strategies you should update to the new universal `LLMContext` and `LLMContextAggregatorPair`.

View File

@@ -1 +0,0 @@
- ⚠️ `TransportParams.turn_analyzer` is deprecated and might result in unexpected behavior, use `LLMUserAggregator`'s new `turn_start_strategies` parameter instead.

View File

@@ -1 +0,0 @@
- `FrameProcessor.interruption_strategies` is deprecated, use `LLMUserAggregator`'s new `turn_start_strategies` parameter instead.

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@@ -1 +0,0 @@
- `EmulateUserStartedSpeakingFrame` and `EmulateUserStoppedSpeakingFrame` frames are deprecated.

View File

@@ -1 +0,0 @@
- Deprecated the `emulated` field in the `UserStartedSpeakingFrame` and `UserStoppedSpeakingFrame` frames.

View File

@@ -1 +0,0 @@
- The `LLMUserAggregatorParams` and `LLMAssistantAggregatorParams` classes in `pipecat.processors.aggregators.llm_response` are now deprecated. Use the new universal `LLMContext` and `LLMContextAggregatorPair` instead.

View File

@@ -1 +0,0 @@
- `pipecat.audio.interruptions.MinWordsInterruptionStrategy` is deprecated. Use `pipecat.turns.user.MinWordsUserTurnStartStrategy` with `LLMUserAggregator`'s new `turn_start_strategies` parameter instead.

View File

@@ -1 +0,0 @@
- Added `RNNoiseFilter` for real-time noise suppression using RNNoise neural network via pyrnnoise library.

View File

@@ -1,15 +0,0 @@
- Updated `SpeechmaticsSTTService` to use new Python Voice SDK with improved VAD,
Smart Turn capabilities, and brings dramatic improvements to latency without
any impact on accuracy. Use the `turn_detection_mode` parameter to control the
endpointing of speech, with `TurnDetectionMode.EXTERNAL` (default),
`TurnDetectionMode.ADAPTIVE`, or `TurnDetectionMode.SMART_TURN`.
```python
stt = SpeechmaticsSTTService(
api_key=os.getenv("SPEECHMATICS_API_KEY"),
params=SpeechmaticsSTTService.InputParams(
language=Language.EN,
turn_detection_mode=SpeechmaticsSTTService.TurnDetectionMode.ADAPTIVE,
speaker_active_format="<{speaker_id}>{text}</{speaker_id}>",
),
)
```

View File

@@ -1,4 +0,0 @@
- For `SpeechmaticsSTTService`, the `end_of_utterance_mode` parameter is deprecated.
Use the new `turn_detection_mode` parameter instead, with `TurnDetectionMode.EXTERNAL`,
`TurnDetectionMode.ADAPTIVE`, or `TurnDetectionMode.SMART_TURN`. The `enable_vad`
parameter is also deprecated and is inferred from the `turn_detection_mode`.

View File

@@ -1,2 +0,0 @@
- Improved error handling in `ElevenLabsRealtimeSTTService`
- Fixed an issue in `ElevenLabsRealtimeSTTService` causing an infinite loop that blocks the process if the websocket disconnects due to an error

View File

@@ -1 +0,0 @@
- `TranscriptionFrame` and `InterimTranscriptionFrame` produced by `DailyTransport` now include the transport source (i.e., the originating audio track).

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@@ -1 +0,0 @@
- `daily-python` updated to 0.23.0.

View File

@@ -1,15 +0,0 @@
- `OpenAILLMContext` and its associated things (context aggregators, etc.) are now deprecated in favor of the universal `LLMContext` and its associated things.
From the developer's point of view, switching to using `LLMContext` machinery will usually be a matter of going from this:
```python
context = OpenAILLMContext(messages, tools)
context_aggregator = llm.create_context_aggregator(context)
```
To this:
```
context = LLMContext(messages, tools)
context_aggregator = LLMContextAggregatorPair(context)
```

View File

@@ -1,8 +0,0 @@
- Added `GrokRealtimeLLMService` for xAI's Grok Voice Agent API with real-time voice conversations:
- Support for real-time audio streaming with WebSocket connection
- Built-in server-side VAD (Voice Activity Detection)
- Multiple voice options: Ara, Rex, Sal, Eve, Leo
- Built-in tools support: web_search, x_search, file_search
- Custom function calling with standard Pipecat tools schema
- Configurable audio formats (PCM at 8kHz-48kHz)

View File

@@ -1,4 +0,0 @@
- `LLMUserAggregator` now exposes the following events:
- `on_user_turn_started`: triggered when a user turn starts
- `on_bot_turn_started`: triggered when a user turn ends and a bot turn starts
- `on_user_turn_end_timeout`: triggered when a user turn does not stop and times out

View File

@@ -1,29 +0,0 @@
- Introducing user mute strategies. User mute strategies indicate when user input should be muted based on the current system state.
In conversational agents, user mute strategies are used to prevent user input from interrupting bot speech, tool execution, or other critical system operations.
A list of strategies can be specified; all strategies are evaluated for every frame so that each strategy can maintain its internal state. A user frame is muted if any of the configured strategies indicates it should be muted.
Available user mute strategies:
* `FirstSpeechUserMuteStrategy`
* `MuteUntilFirstBotCompleteUserMuteStrategy`
* `AlwaysUserMuteStrategy`
* `FunctionCallUserMuteStrategy`
User mute strategies replace the legacy `STTMuteFilter` and provide a more flexible and composable approach to muting user input.
User mute strategies are configured when setting up the `LLMContextAggregatorPair`. For example:
```python
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
user_mute_strategies=[
FirstSpeechUserMuteStrategy(),
]
),
)
```
In order to use user mute strategies you should update to the new universal `LLMContext` and `LLMContextAggregatorPair`.

View File

@@ -1 +0,0 @@
- `STTMuteFilter` is deprecated and will be removed in a future version. Use `LLMUserAggregator`'s new `user_mute_strategies` instead.

View File

@@ -1 +0,0 @@
- Fixed a bug in `STTMuteFilter` where the user was not always muted during function calls, especially when there were multiple simultaneous calls.

View File

@@ -1 +0,0 @@
- Fixed a `RNNoiseFilter` issue that would cause a "[Errno 12] Cannot allocate memory" error when processing silence audio frames.

View File

@@ -1 +0,0 @@
- Added an approximation of TTFB for Ultravox.

View File

@@ -1,16 +0,0 @@
{% for section, _ in sections.items() %}
{% if sections[section] %}
{% for category, val in definitions.items() if category in sections[section]%}
### {{ definitions[category]['name'] }}
{% for text, values in sections[section][category].items() %}
{{ text }}
(PR {{ values|join(', ') }})
{% endfor %}
{% endfor %}
{% else %}
No significant changes.
{% endif %}
{% endfor %}

View File

@@ -0,0 +1,103 @@
# TurnAwareTranscriptProcessor Example
## Overview
The `TurnAwareTranscriptProcessor` combines user and assistant transcript tracking with turn boundary detection. It correctly handles interruptions by only capturing what was actually spoken.
## Basic Usage
```python
from pipecat.processors.transcript_processor import TurnAwareTranscriptProcessor
# Create the processor
turn_processor = TurnAwareTranscriptProcessor()
# Register event handlers
@turn_processor.event_handler("on_turn_started")
async def handle_turn_started(processor, turn_number):
print(f"Turn {turn_number} started")
@turn_processor.event_handler("on_turn_ended")
async def handle_turn_ended(processor, turn_number, user_text, assistant_text, was_interrupted):
print(f"\nTurn {turn_number} ended:")
print(f" User said: {user_text}")
print(f" Assistant said: {assistant_text}")
print(f" Was interrupted: {was_interrupted}")
@turn_processor.event_handler("on_transcript_update")
async def handle_transcript_update(processor, frame):
for msg in frame.messages:
print(f"[{msg.role}]: {msg.content}")
# Add to pipeline
pipeline = Pipeline([
transport.input(),
stt,
turn_processor, # Process transcripts and track turns
context_aggregator.user(),
llm,
tts,
transport.output(),
context_aggregator.assistant(),
])
```
## Features
1. **Turn Boundary Detection**: Automatically detects when turns start and end based on user and bot speaking patterns
2. **Interruption Handling**: Correctly captures only what was actually spoken when interruptions occur
3. **Real-time Transcripts**: Emits transcript messages for both user and assistant speech
4. **Turn Events**: Provides start/end events with accumulated transcripts for each turn
## Events
### on_turn_started
Emitted when a new turn begins (user starts speaking).
**Handler signature**: `async def handler(processor, turn_number)`
### on_turn_ended
Emitted when a turn ends with accumulated transcripts.
**Handler signature**: `async def handler(processor, turn_number, user_transcript, assistant_transcript, was_interrupted)`
### on_transcript_update
Inherited from `BaseTranscriptProcessor`, emitted for individual transcript messages.
**Handler signature**: `async def handler(processor, frame)`
## Turn Logic
- Turns start when the user begins speaking (`UserStartedSpeakingFrame`)
- Turns end when:
- The user starts speaking again (previous turn ends, new turn starts)
- The bot is interrupted (`InterruptionFrame`)
- The pipeline ends (`EndFrame`/`CancelFrame`)
## Integration with OpenTelemetry
You can use turn events to enrich OpenTelemetry spans:
```python
from pipecat.utils.tracing.turn_trace_observer import TurnTraceObserver
turn_tracker = TurnTrackingObserver()
turn_tracer = TurnTraceObserver(turn_tracker)
turn_processor = TurnAwareTranscriptProcessor()
@turn_processor.event_handler("on_turn_ended")
async def add_transcripts_to_span(processor, turn_number, user_text, assistant_text, interrupted):
# Get current span and add transcript data
from opentelemetry import trace
current_span = trace.get_current_span()
if current_span:
current_span.set_attribute("turn.user_text", user_text)
current_span.set_attribute("turn.assistant_text", assistant_text)
```
## Notes
- The processor handles async frame processing correctly by delaying turn end until frames are processed
- Works with word-level timestamps from TTS services like Cartesia
- Accumulates both user (`TranscriptionFrame`) and assistant (`TTSTextFrame`) speech
- Emits individual transcript messages in addition to turn-level aggregation

View File

@@ -2,7 +2,7 @@
# Build docs using uv
echo "Installing dependencies with uv..."
uv sync --group docs --all-extras --no-extra krisp --no-extra gstreamer --no-extra local_smart_turn --no-extra moondream --no-extra riva --no-extra mlx-whisper
uv sync --group docs --all-extras --no-extra krisp --no-extra gstreamer --no-extra ultravox --no-extra local_smart_turn --no-extra moondream --no-extra riva --no-extra mlx-whisper
# Check if sphinx-build is available
if ! uv run sphinx-build --version &> /dev/null; then
@@ -24,4 +24,4 @@ if [ $? -eq 0 ]; then
else
echo "Documentation build failed!" >&2
exit 1
fi
fi

View File

@@ -61,6 +61,9 @@ autodoc_mock_imports = [
# OpenCV - sometimes has import issues during docs build
"cv2",
# Heavy ML packages excluded from ReadTheDocs
# ultravox dependencies
"vllm",
"vllm.engine.arg_utils",
# local-smart-turn dependencies
"coremltools",
"coremltools.models",
@@ -116,6 +119,7 @@ def import_core_modules():
"pipecat.observers",
"pipecat.runner",
"pipecat.serializers",
"pipecat.sync",
"pipecat.transcriptions",
"pipecat.utils",
]

View File

@@ -30,6 +30,7 @@ Quick Links
Runner <api/pipecat.runner>
Serializers <api/pipecat.serializers>
Services <api/pipecat.services>
Sync <api/pipecat.sync>
Transcriptions <api/pipecat.transcriptions>
Transports <api/pipecat.transports>
Utils <api/pipecat.utils>
Utils <api/pipecat.utils>

View File

@@ -73,9 +73,6 @@ GOOGLE_CLOUD_PROJECT_ID=...
GOOGLE_CLOUD_LOCATION=...
GOOGLE_TEST_CREDENTIALS=...
# Gradium
GRAPDIUM_API_KEY=...
# Grok
GROK_API_KEY=...
@@ -84,7 +81,6 @@ GROQ_API_KEY=...
# Heygen
HEYGEN_API_KEY=...
HEYGEN_LIVE_AVATAR_API_KEY=...
# Hume
HUME_API_KEY=...
@@ -191,11 +187,8 @@ TOGETHER_API_KEY=...
TWILIO_ACCOUNT_SID=...
TWILIO_AUTH_TOKEN=...
# Ultravox Realtime
ULTRAVOX_API_KEY=...
# WhatsApp
WHATSAPP_TOKEN=...
WHATSAPP_WEBHOOK_VERIFICATION_TOKEN=...
WHATSAPP_PHONE_NUMBER_ID=...
WHATSAPP_APP_SECRET=...
WHATSAPP_APP_SECRET=...

View File

@@ -15,7 +15,7 @@ from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.nvidia.tts import NvidiaTTSService
from pipecat.services.riva.tts import FastPitchTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
@@ -36,7 +36,7 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
tts = NvidiaTTSService(api_key=os.getenv("NVIDIA_API_KEY"))
tts = FastPitchTTSService(api_key=os.getenv("NVIDIA_API_KEY"))
task = PipelineTask(
Pipeline([tts, transport.output()]),

View File

@@ -17,6 +17,7 @@ from fastapi.responses import RedirectResponse
from loguru import logger
from pipecat_ai_small_webrtc_prebuilt.frontend import SmallWebRTCPrebuiltUI
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -25,18 +26,13 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.smallwebrtc.connection import IceServer, SmallWebRTCConnection
from pipecat.transports.smallwebrtc.transport import SmallWebRTCTransport
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -65,6 +61,7 @@ async def run_example(webrtc_connection: SmallWebRTCConnection):
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
)
@@ -85,14 +82,7 @@ async def run_example(webrtc_connection: SmallWebRTCConnection):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -12,6 +12,7 @@ import aiohttp
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -20,16 +21,11 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.daily import configure
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.daily.transport import DailyParams, DailyTransport
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -50,6 +46,7 @@ async def main():
audio_out_enabled=True,
transcription_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
)
@@ -68,14 +65,7 @@ async def main():
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -12,6 +12,7 @@ import sys
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -26,17 +27,12 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.livekit import configure
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.livekit.transport import LiveKitParams, LiveKitTransport
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -55,6 +51,7 @@ async def main():
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
)
@@ -78,14 +75,7 @@ async def main():
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -23,6 +23,7 @@ from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.sync_parallel_pipeline import SyncParallelPipeline
from pipecat.pipeline.task import PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.processors.aggregators.sentence import SentenceAggregator
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.runner.types import RunnerArguments

View File

@@ -26,6 +26,7 @@ from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.sync_parallel_pipeline import SyncParallelPipeline
from pipecat.pipeline.task import PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.processors.aggregators.sentence import SentenceAggregator
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.services.cartesia.tts import CartesiaHttpTTSService

View File

@@ -9,6 +9,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -23,10 +24,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
@@ -36,8 +34,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -70,16 +66,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -106,14 +105,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -10,6 +10,7 @@ from dotenv import load_dotenv
from loguru import logger
from PIL import Image
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -24,10 +25,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
@@ -36,8 +34,6 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -88,6 +84,7 @@ transport_params = {
video_out_width=1024,
video_out_height=1024,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
@@ -96,6 +93,7 @@ transport_params = {
video_out_width=1024,
video_out_height=1024,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -120,14 +118,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
image_sync_aggregator = ImageSyncAggregator(
os.path.join(os.path.dirname(__file__), "assets", "speaking.png"),

View File

@@ -9,6 +9,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -17,10 +18,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.cartesia.stt import CartesiaSTTService
@@ -29,8 +27,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -43,16 +39,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -77,14 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -9,6 +9,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -17,10 +18,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.cartesia.tts import CartesiaTTSService
@@ -29,8 +27,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -42,16 +38,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -76,14 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -15,10 +15,10 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
from pipecat.processors.aggregators.llm_response import (
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.openai.base_llm import BaseOpenAILLMService
@@ -76,7 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
4. Text-to-Speech (TTS)
- Low latency streaming audio synthesis
- Multiple voice options available including `sarah`, `theo`, `megan` and `jack`
- Multiple voice options available including `sarah`, `theo`, and `megan`
5. Configuration Options
- `operating_point` parameter defaults to `ENHANCED` for optimal accuracy
@@ -95,8 +95,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
api_key=os.getenv("SPEECHMATICS_API_KEY"),
params=SpeechmaticsSTTService.InputParams(
language=Language.EN,
turn_detection_mode=SpeechmaticsSTTService.TurnDetectionMode.ADAPTIVE,
# focus_speakers=["S1"],
enable_vad=True,
enable_diarization=True,
focus_speakers=["S1"],
end_of_utterance_silence_trigger=0.5,
speaker_active_format="<{speaker_id}>{text}</{speaker_id}>",
speaker_passive_format="<PASSIVE><{speaker_id}>{text}</{speaker_id}></PASSIVE>",
),
@@ -132,7 +134,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(enable_user_speaking_frames=False),
user_params=LLMUserAggregatorParams(aggregation_timeout=0.005),
)
pipeline = Pipeline(

View File

@@ -10,6 +10,7 @@ import aiohttp
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -18,10 +19,10 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
from pipecat.processors.aggregators.llm_response import (
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.openai.base_llm import BaseOpenAILLMService
@@ -32,8 +33,6 @@ from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -45,16 +44,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -73,7 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
TTS Features:
- Low latency streaming audio synthesis
- Multiple voice options available including `sarah`, `theo`, `megan` and `jack`
- Multiple voice options available including `sarah`, `theo`, and `megan`
For more information:
- STT: https://docs.speechmatics.com/rt-api-ref
@@ -86,6 +88,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
api_key=os.getenv("SPEECHMATICS_API_KEY"),
params=SpeechmaticsSTTService.InputParams(
language=Language.EN,
enable_diarization=True,
end_of_utterance_silence_trigger=0.5,
speaker_active_format="<{speaker_id}>{text}</{speaker_id}>",
),
)
@@ -119,11 +123,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
user_params=LLMUserAggregatorParams(aggregation_timeout=0.005),
)
pipeline = Pipeline(

View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -18,10 +19,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.cartesia.tts import CartesiaTTSService
@@ -30,8 +28,6 @@ from pipecat.services.soniox.stt import SonioxSTTService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -40,16 +36,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -76,14 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -4,72 +4,76 @@
# SPDX-License-Identifier: BSD 2-Clause License
#
import os
import aiohttp
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
from pipecat.frames.frames import LLMRunFrame, TTSTextFrame
from pipecat.observers.loggers.debug_log_observer import DebugLogObserver, FrameEndpoint
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.frameworks.rtvi import RTVIObserver, RTVIProcessor
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.inworld.tts import InworldHttpTTSService
from pipecat.services.inworld.tts import InworldTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_output import BaseOutputTransport
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info("Starting bot")
logger.info(f"Starting bot")
# Create an HTTP session
async with aiohttp.ClientSession() as session:
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = InworldHttpTTSService(
# Inworld TTS Service - Unified streaming and non-streaming
# Set streaming=True for real-time audio, streaming=False for complete audio generation
streaming = True # Toggle this to switch between modes
tts = InworldTTSService(
api_key=os.getenv("INWORLD_API_KEY", ""),
aiohttp_session=session,
voice_id="Ashley",
model="inworld-tts-1",
# Set to False for non-streaming mode or True for streaming mode.
streaming=True,
streaming=streaming, # True: real-time chunks, False: complete audio then playback
)
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
@@ -77,32 +81,22 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
messages = [
{
"role": "system",
"content": "You are a helpful AI demonstrating Inworld AI's TTS. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a friendly and helpful way.",
"content": "You are very knowledgable about dogs. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.",
},
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
rtvi = RTVIProcessor()
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[
transport.input(),
rtvi,
stt,
context_aggregator.user(),
llm,
tts,
transport.output(),
context_aggregator.assistant(),
transport.input(), # Transport user input
stt, # STT
context_aggregator.user(), # User responses
llm, # LLM
tts, # TTS
transport.output(), # Transport bot output
context_aggregator.assistant(), # Assistant spoken responses
]
)
@@ -112,27 +106,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
enable_metrics=True,
enable_usage_metrics=True,
),
observers=[
RTVIObserver(rtvi),
DebugLogObserver(
frame_types={
TTSTextFrame: (BaseOutputTransport, FrameEndpoint.SOURCE),
}
),
],
idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
)
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
logger.info("Client connected")
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info("Client disconnected")
logger.info(f"Client disconnected")
await task.cancel()
runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)

View File

@@ -1,149 +0,0 @@
#
# Copyright (c) 20242025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
from pipecat.frames.frames import LLMRunFrame, TTSTextFrame
from pipecat.observers.loggers.debug_log_observer import DebugLogObserver, FrameEndpoint
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.inworld.tts import InworldTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_output import BaseOutputTransport
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
),
}
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info("Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = InworldTTSService(
api_key=os.getenv("INWORLD_API_KEY", ""),
voice_id="Ashley",
model="inworld-tts-1",
temperature=1.1,
)
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
messages = [
{
"role": "system",
"content": "You are a helpful AI demonstrating Inworld AI's TTS. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a friendly and helpful way.",
},
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
rtvi = RTVIProcessor(config=RTVIConfig(config=[]))
pipeline = Pipeline(
[
transport.input(),
rtvi,
stt,
context_aggregator.user(),
llm,
tts,
transport.output(),
context_aggregator.assistant(),
]
)
task = PipelineTask(
pipeline,
params=PipelineParams(
enable_metrics=True,
enable_usage_metrics=True,
),
observers=[
RTVIObserver(rtvi),
DebugLogObserver(
frame_types={
TTSTextFrame: (BaseOutputTransport, FrameEndpoint.SOURCE),
}
),
],
idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
)
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
logger.info("Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info("Client disconnected")
await task.cancel()
runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
await runner.run(task)
async def bot(runner_args: RunnerArguments):
"""Main bot entry point compatible with Pipecat Cloud."""
transport = await create_transport(runner_args, transport_params)
await run_bot(transport, runner_args)
if __name__ == "__main__":
from pipecat.runner.run import main
main()

View File

@@ -11,6 +11,7 @@ import aiohttp
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -19,10 +20,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.asyncai.tts import AsyncAIHttpTTSService
@@ -31,8 +29,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -45,16 +41,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -82,14 +81,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -18,10 +19,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.asyncai.tts import AsyncAITTSService
@@ -30,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -44,16 +40,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -78,14 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -13,16 +13,15 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.filters.aic_filter import AICFilter
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.vad_analyzer import VADParams
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.processors.audio.audio_buffer_processor import AudioBufferProcessor
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
@@ -32,8 +31,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -63,6 +60,7 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=aic.create_vad_analyzer(lookback_buffer_size=6.0, sensitivity=6.0),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
audio_in_filter=aic,
)
)(_create_aic_filter()),
@@ -71,6 +69,7 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=aic.create_vad_analyzer(lookback_buffer_size=6.0, sensitivity=6.0),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
audio_in_filter=aic,
)
)(_create_aic_filter()),
@@ -79,6 +78,7 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=aic.create_vad_analyzer(lookback_buffer_size=6.0, sensitivity=6.0),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
audio_in_filter=aic,
)
)(_create_aic_filter()),
@@ -105,14 +105,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -9,6 +9,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -20,7 +21,6 @@ from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor
from pipecat.runner.types import RunnerArguments
@@ -32,8 +32,6 @@ from pipecat.transports.base_output import BaseOutputTransport
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -46,16 +44,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -81,14 +82,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
rtvi = RTVIProcessor(config=RTVIConfig(config=[]))

View File

@@ -15,6 +15,7 @@ from langchain_core.runnables.history import RunnableWithMessageHistory
from langchain_openai import ChatOpenAI
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -23,10 +24,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.processors.frameworks.langchain import LangchainProcessor
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
@@ -35,8 +33,6 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -58,16 +54,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -103,14 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
lc = LangchainProcessor(history_chain)
context = LLMContext()
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -17,7 +17,6 @@ from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_response_universal import (
LLMContext,
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
@@ -70,9 +69,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context, user_params=LLMUserAggregatorParams(enable_user_speaking_frames=False)
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -11,6 +11,7 @@ import aiohttp
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -19,10 +20,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.deepgram.stt import DeepgramSTTService
@@ -31,8 +29,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -45,16 +41,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -81,14 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -18,10 +19,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.aws.llm import AWSBedrockLLMService
@@ -30,8 +28,6 @@ from pipecat.services.deepgram.tts import DeepgramTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -44,16 +40,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -86,14 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -21,10 +21,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.deepgram.stt import DeepgramSTTService
@@ -76,10 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(enable_user_speaking_frames=False),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[
@@ -104,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
@stt.event_handler("on_speech_started")
async def on_speech_started(stt, *args, **kwargs):
await task.queue_frames([UserStartedSpeakingFrame(), InterruptionFrame()])
await task.queue_frames([InterruptionFrame(), UserStartedSpeakingFrame()])
@stt.event_handler("on_utterance_end")
async def on_utterance_end(stt, *args, **kwargs):

View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -18,10 +19,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.deepgram.stt import DeepgramSTTService
@@ -30,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -44,16 +40,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -75,14 +74,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -11,6 +11,7 @@ import aiohttp
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -19,10 +20,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.elevenlabs.stt import ElevenLabsSTTService
@@ -31,8 +29,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -45,16 +41,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -85,14 +84,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -18,10 +19,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.elevenlabs.stt import ElevenLabsRealtimeSTTService
@@ -30,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -44,16 +40,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -78,14 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -18,10 +19,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.deepgram.stt import DeepgramSTTService
@@ -30,8 +28,6 @@ from pipecat.services.playht.tts import PlayHTHttpTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -43,16 +39,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -78,14 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -18,10 +19,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.deepgram.stt import DeepgramSTTService
@@ -31,8 +29,6 @@ from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -44,16 +40,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -80,14 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -18,10 +19,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.azure.llm import AzureLLMService
@@ -30,8 +28,6 @@ from pipecat.services.azure.tts import AzureHttpTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -43,16 +39,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -84,14 +83,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -18,10 +19,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.azure.llm import AzureLLMService
@@ -30,8 +28,6 @@ from pipecat.services.azure.tts import AzureTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -43,16 +39,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -84,14 +83,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -18,10 +19,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.openai.llm import OpenAILLMService
@@ -30,8 +28,6 @@ from pipecat.services.openai.tts import OpenAITTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -43,16 +39,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -78,14 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -11,6 +11,7 @@ import time
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -19,10 +20,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.cartesia.tts import CartesiaTTSService
@@ -31,8 +29,6 @@ from pipecat.services.openpipe.llm import OpenPipeLLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -44,16 +40,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -83,14 +82,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -11,6 +11,7 @@ import aiohttp
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -19,10 +20,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.deepgram.stt import DeepgramSTTService
@@ -31,8 +29,6 @@ from pipecat.services.xtts.tts import XTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -44,16 +40,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -81,14 +80,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -18,10 +19,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.cartesia.tts import CartesiaTTSService
@@ -32,8 +30,6 @@ from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -45,16 +41,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -87,14 +86,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -19,10 +19,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.deepgram.stt import DeepgramSTTService
@@ -31,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -44,16 +39,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -75,14 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -18,10 +19,8 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response import LLMUserAggregatorParams
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.groq.llm import GroqLLMService
@@ -30,8 +29,6 @@ from pipecat.services.groq.tts import GroqTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -43,16 +40,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -77,12 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
context, user_params=LLMUserAggregatorParams(aggregation_timeout=0.05)
)
pipeline = Pipeline(

View File

@@ -8,17 +8,13 @@
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMMessagesAppendFrame
from pipecat.frames.frames import LLMMessagesAppendFrame, LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.processors.frameworks.strands_agents import StrandsAgentsProcessor
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
@@ -27,8 +23,6 @@ from pipecat.services.aws.tts import AWSPollyTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
# Strands agent setup
try:
@@ -77,9 +71,9 @@ def build_agent(model_id: str, max_tokens: int):
@tool
def check_weather(location: str) -> str:
if location.lower() == "san francisco":
return "The weather in San Francisco is sunny and 75 degrees."
return "The weather in San Francisco is sunny and 30 degrees."
elif location.lower() == "sydney":
return "The weather in Sydney is cloudy and 60 degrees."
return "The weather in Sydney is cloudy and 20 degrees."
else:
return "I'm not sure about the weather in that location."
@@ -120,14 +114,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
# Setup context aggregators for message handling
context = LLMContext()
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -8,6 +8,7 @@
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -16,10 +17,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.aws.llm import AWSBedrockLLMService
@@ -28,8 +26,6 @@ from pipecat.services.aws.tts import AWSPollyTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -41,16 +37,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -80,14 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -25,6 +25,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -33,10 +34,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.google.llm import GoogleLLMService
@@ -46,8 +44,6 @@ from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -62,6 +58,7 @@ transport_params = {
video_out_width=1024,
video_out_height=1024,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
@@ -70,6 +67,7 @@ transport_params = {
video_out_width=1024,
video_out_height=1024,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -91,7 +89,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
llm = GoogleLLMService(
api_key=os.getenv("GOOGLE_API_KEY"),
model="gemini-2.5-flash-image",
# model="gemini-3-pro-image-preview", # A more powerful model, but slower
)
messages = [
@@ -102,14 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -18,10 +19,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.google.llm import GoogleLLMService
@@ -31,8 +29,6 @@ from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -44,16 +40,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -107,14 +106,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[
@@ -144,7 +136,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
messages.append(
{
"role": "system",
"content": "You are an AI assistant. You can help with a variety of tasks. Introduce yourself and ask the user what they would like to know.",
"content": "Hello! I'm your AI assistant. I can help you with a variety of tasks. What would you like to know?",
}
)
await task.queue_frames([LLMRunFrame()])

View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -18,21 +19,16 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.google.llm import GoogleLLMService
from pipecat.services.google.stt import GoogleSTTService
from pipecat.services.google.tts import GoogleHttpTTSService
from pipecat.services.google.tts import GoogleHttpTTSService, GoogleTTSService
from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -44,16 +40,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -76,10 +75,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
llm = GoogleLLMService(
api_key=os.getenv("GOOGLE_API_KEY"),
model="gemini-2.5-flash",
# force a certain amount of thinking if you want it
# params=GoogleLLMService.InputParams(
# thinking=GoogleLLMService.ThinkingConfig(thinking_budget=4096)
# ),
# turn on thinking if you want it
# params=GoogleLLMService.InputParams(extra={"thinking_config": {"thinking_budget": 4096}}),)
)
messages = [
@@ -90,14 +87,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -18,10 +19,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.google.llm import GoogleLLMService
@@ -31,8 +29,6 @@ from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -44,16 +40,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -76,10 +75,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
llm = GoogleLLMService(
api_key=os.getenv("GOOGLE_API_KEY"),
model="gemini-2.5-flash",
# force a certain amount of thinking if you want it
# params=GoogleLLMService.InputParams(
# thinking=GoogleLLMService.ThinkingConfig(thinking_budget=4096)
# ),
# turn on thinking if you want it
# params=GoogleLLMService.InputParams(extra={"thinking_config": {"thinking_budget": 4096}}),)
)
messages = [
@@ -90,14 +87,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -18,10 +19,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.assemblyai.stt import AssemblyAISTTService
@@ -30,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -44,16 +40,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -80,14 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -11,6 +11,7 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.filters.krisp_viva_filter import KrispVivaFilter
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -19,10 +20,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.deepgram.stt import DeepgramSTTService
@@ -31,8 +29,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -44,18 +40,21 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
audio_in_filter=KrispVivaFilter(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
audio_in_filter=KrispVivaFilter(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
audio_in_filter=KrispVivaFilter(),
),
}
@@ -78,14 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -11,6 +11,7 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.filters.krisp_filter import KrispFilter
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -19,10 +20,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.deepgram.stt import DeepgramSTTService
@@ -31,8 +29,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -44,18 +40,21 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
audio_in_filter=KrispFilter(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
audio_in_filter=KrispFilter(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
audio_in_filter=KrispFilter(),
),
}
@@ -78,14 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -11,6 +11,7 @@ import aiohttp
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -19,10 +20,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.deepgram.stt import DeepgramSTTService
@@ -31,8 +29,6 @@ from pipecat.services.rime.tts import RimeHttpTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -45,16 +41,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -83,14 +82,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -18,10 +19,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.deepgram.stt import DeepgramSTTService
@@ -30,8 +28,6 @@ from pipecat.services.rime.tts import RimeTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -43,16 +39,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -77,14 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -18,20 +19,15 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.nvidia.llm import NvidiaLLMService
from pipecat.services.nvidia.stt import NvidiaSTTService
from pipecat.services.nvidia.tts import NvidiaTTSService
from pipecat.services.nim.llm import NimLLMService
from pipecat.services.riva.stt import RivaSTTService
from pipecat.services.riva.tts import RivaTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -43,16 +39,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -60,13 +59,11 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = NvidiaSTTService(api_key=os.getenv("NVIDIA_API_KEY"))
stt = RivaSTTService(api_key=os.getenv("NVIDIA_API_KEY"))
llm = NvidiaLLMService(
api_key=os.getenv("NVIDIA_API_KEY"), model="meta/llama-3.1-405b-instruct"
)
llm = NimLLMService(api_key=os.getenv("NVIDIA_API_KEY"), model="meta/llama-3.1-405b-instruct")
tts = NvidiaTTSService(api_key=os.getenv("NVIDIA_API_KEY"))
tts = RivaTTSService(api_key=os.getenv("NVIDIA_API_KEY"))
messages = [
{
@@ -76,14 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -12,6 +12,7 @@ from dotenv import load_dotenv
from google.genai.types import Content, Part
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -31,10 +32,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.processors.frame_processor import FrameProcessor
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
@@ -44,8 +42,6 @@ from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -205,16 +201,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -225,10 +224,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
llm = GoogleLLMService(
api_key=os.getenv("GOOGLE_API_KEY"),
model="gemini-2.5-flash",
# force a certain amount of thinking if you want it
# params=GoogleLLMService.InputParams(
# thinking=GoogleLLMService.ThinkingConfig(thinking_budget=4096)
# ),
# turn on thinking if you want it
# params=GoogleLLMService.InputParams(extra={"thinking_config": {"thinking_budget": 4096}}),
)
tts = GoogleTTSService(
@@ -249,14 +246,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
audio_collector = UserAudioCollector(context, context_aggregator.user())
pull_transcript_out_of_llm_output = TranscriptExtractor(context)
fixup_context_messages = TranscriptionContextFixup(context)

View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -18,10 +19,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.deepgram.stt import DeepgramSTTService
@@ -30,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -44,16 +40,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -78,14 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -4,36 +4,42 @@
# SPDX-License-Identifier: BSD 2-Clause License
#
import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.gradium.stt import GradiumSTTService
from pipecat.services.gradium.tts import GradiumTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.ultravox.stt import UltravoxSTTService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
# NOTE: This example requires GPU resources to run efficiently.
# The Ultravox model is compute-intensive and performs best with GPU acceleration.
# This can be deployed on cloud GPU providers like Cerebrium.ai for optimal performance.
# Want to initialize the ultravox processor since it takes time to load the model and dont
# want to load it every time the pipeline is run
ultravox_processor = UltravoxSTTService(
model_name="fixie-ai/ultravox-v0_5-llama-3_1-8b",
hf_token=os.getenv("HF_TOKEN"),
)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
@@ -42,16 +48,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -59,41 +68,17 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = GradiumSTTService(api_key=os.getenv("GRADIUM_API_KEY"))
tts = GradiumTTSService(
api_key=os.getenv("GRADIUM_API_KEY"),
voice_id="YTpq7expH9539ERJ",
)
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
messages = [
{
"role": "system",
"content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.",
},
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
tts = CartesiaTTSService(
api_key=os.environ.get("CARTESIA_API_KEY"),
voice_id="97f4b8fb-f2fe-444b-bb9a-c109783a857a",
)
pipeline = Pipeline(
[
transport.input(), # Transport user input
stt,
context_aggregator.user(), # User responses
llm, # LLM
ultravox_processor,
tts, # TTS
transport.output(), # Transport bot output
context_aggregator.assistant(), # Assistant spoken responses
]
)
@@ -109,9 +94,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -11,6 +11,7 @@ import aiohttp
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -19,10 +20,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.deepgram.stt import DeepgramSTTService
@@ -31,8 +29,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -45,16 +41,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -82,14 +81,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -18,10 +19,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.deepgram.stt import DeepgramSTTService
@@ -30,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -43,16 +39,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -77,14 +76,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -18,10 +19,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.cartesia.tts import CartesiaTTSService
@@ -30,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -44,16 +40,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -80,14 +79,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -11,6 +11,7 @@ import sys
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -19,16 +20,13 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -42,6 +40,7 @@ async def main():
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
)
)
@@ -62,14 +61,7 @@ async def main():
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -11,6 +11,7 @@ import aiohttp
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -19,10 +20,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.deepgram.stt import DeepgramSTTService
@@ -32,8 +30,6 @@ from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -46,16 +42,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -84,14 +83,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -11,6 +11,7 @@ import aiohttp
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -19,10 +20,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.openai.llm import OpenAILLMService
@@ -32,8 +30,6 @@ from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -46,16 +42,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -86,14 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -4,23 +4,24 @@
# SPDX-License-Identifier: BSD 2-Clause License
#
import asyncio
import os
import aiohttp
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
from pipecat.frames.frames import LLMRunFrame
from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.openai.llm import OpenAILLMService
@@ -29,8 +30,6 @@ from pipecat.services.sarvam.tts import SarvamTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -43,16 +42,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -80,14 +82,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -4,11 +4,14 @@
# SPDX-License-Identifier: BSD 2-Clause License
#
import io
import os
import re
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -21,10 +24,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
@@ -33,8 +33,6 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -85,12 +83,14 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -115,14 +115,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
metrics_frame_processor = MetricsFrameLogger()

View File

@@ -9,6 +9,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -17,10 +18,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.processors.filters.wake_check_filter import WakeCheckFilter
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
@@ -30,8 +28,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -43,16 +39,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -79,14 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
hey_robot_filter = WakeCheckFilter(["hey robot", "hey, robot"])
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -10,6 +10,7 @@ import wave
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -22,12 +23,9 @@ from pipecat.frames.frames import (
)
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.pipeline.task import PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.processors.logger import FrameLogger
from pipecat.runner.types import RunnerArguments
@@ -38,8 +36,6 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -93,16 +89,19 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -127,14 +126,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
out_sound = OutboundSoundEffectWrapper()
in_sound = InboundSoundEffectWrapper()
fl = FrameLogger("LLM Out")

View File

@@ -11,6 +11,7 @@ from dotenv import load_dotenv
from loguru import logger
from PIL import Image
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -19,10 +20,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.cartesia.tts import CartesiaTTSService
@@ -30,8 +28,6 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -44,11 +40,13 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -73,14 +71,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

View File

@@ -11,6 +11,7 @@ from dotenv import load_dotenv
from loguru import logger
from PIL import Image
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
@@ -19,10 +20,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.anthropic.llm import AnthropicLLMService
@@ -30,8 +28,6 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.turns.bot.turn_analyzer_bot_turn_start_strategy import TurnAnalyzerBotTurnStartStrategy
from pipecat.turns.turn_start_strategies import TurnStartStrategies
load_dotenv(override=True)
@@ -44,11 +40,13 @@ transport_params = {
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
@@ -73,14 +71,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
]
context = LLMContext(messages)
context_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
turn_start_strategies=TurnStartStrategies(
bot=[TurnAnalyzerBotTurnStartStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
),
),
)
context_aggregator = LLMContextAggregatorPair(context)
pipeline = Pipeline(
[

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