Compare commits
1 Commits
mb/runner-
...
hush/usage
| Author | SHA1 | Date | |
|---|---|---|---|
|
cb6e86e69f |
150
CHANGELOG.md
150
CHANGELOG.md
@@ -7,167 +7,17 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
|
||||
|
||||
## [Unreleased]
|
||||
|
||||
### Changed
|
||||
|
||||
- `FunctionFilter` now has a `filter_system_frames` arg, which controls whether
|
||||
or not SystemFrames are filtered.
|
||||
|
||||
- Upgraded `aws_sdk_bedrock_runtime` to v0.1.1 to resolve potential CPU issues
|
||||
when running `AWSNovaSonicLLMService`.
|
||||
|
||||
### Fixed
|
||||
|
||||
- Fixed an issue in `ServiceSwitcher` where the `STTService`s would result in
|
||||
all STT services producing `TranscriptionFrame`s.
|
||||
|
||||
## [0.0.91] - 2025-10-21
|
||||
|
||||
### Added
|
||||
|
||||
- It is now possible to start a bot from the `/start` endpoint when using the
|
||||
runner Daily's transport. This follows the Pipecat Cloud format with
|
||||
`createDailyRoom` and `body` fields in the POST request body.
|
||||
|
||||
- Added an ellipsis character (`…`) to the end of sentence detection in the
|
||||
string utils.
|
||||
|
||||
- Expanded support for universal `LLMContext` to `AWSNovaSonicLLMService`.
|
||||
As a reminder, the context-setup pattern when using `LLMContext` is:
|
||||
|
||||
```python
|
||||
context = LLMContext(messages, tools)
|
||||
context_aggregator = LLMContextAggregatorPair(context)
|
||||
```
|
||||
|
||||
(Note that even though `AWSNovaSonicLLMService` now supports the universal
|
||||
`LLMContext`, it is not meant to be swapped out for another LLM service at
|
||||
runtime.)
|
||||
|
||||
Worth noting: whether or not you use the new context-setup pattern with
|
||||
`AWSNovaSonicLLMService`, some types have changed under the hood:
|
||||
|
||||
```python
|
||||
## BEFORE:
|
||||
|
||||
# Context aggregator type
|
||||
context_aggregator: AWSNovaSonicContextAggregatorPair
|
||||
|
||||
# Context frame type
|
||||
frame: OpenAILLMContextFrame
|
||||
|
||||
# Context type
|
||||
context: AWSNovaSonicLLMContext
|
||||
# or
|
||||
context: OpenAILLMContext
|
||||
|
||||
## AFTER:
|
||||
|
||||
# Context aggregator type
|
||||
context_aggregator: LLMContextAggregatorPair
|
||||
|
||||
# Context frame type
|
||||
frame: LLMContextFrame
|
||||
|
||||
# Context type
|
||||
context: LLMContext
|
||||
```
|
||||
|
||||
- Added support for `bulbul:v3` model in `SarvamTTSService` and
|
||||
`SarvamHttpTTSService`.
|
||||
|
||||
- Added `keyterms_prompt` parameter to `AssemblyAIConnectionParams`.
|
||||
|
||||
- Added `speech_model` parameter to `AssemblyAIConnectionParams` to access the
|
||||
multilingual model.
|
||||
|
||||
- Added support for trickle ICE to the `SmallWebRTCTransport`.
|
||||
|
||||
- Added support for updating `OpenAITTSService` settings (`instructions` and
|
||||
`speed`) at runtime via `TTSUpdateSettingsFrame`.
|
||||
|
||||
- Added `--whatsapp` flag to runner to better surface WhatsApp transport logs.
|
||||
|
||||
- Added `on_connected` and `on_disconnected` events to TTS and STT
|
||||
websocket-based services.
|
||||
|
||||
- Added an `aggregate_sentences` arg in `ElevenLabsHttpTTSService`, where the
|
||||
default value is True.
|
||||
|
||||
- Added a `room_properties` arg to the Daily runner's `configure()` method,
|
||||
allowing `DailyRoomProperties` to be provided.
|
||||
|
||||
- The runner `--folder` argument now supports downloading files from
|
||||
subdirectories.
|
||||
|
||||
### Changed
|
||||
|
||||
- `RunnerArguments` now include the `body` field, so there's no need to add it
|
||||
to subclasses. Also, all `RunnerArguments` fields are now keyword-only.
|
||||
|
||||
- `CartesiaSTTService` now inherits from `WebsocketSTTService`.
|
||||
|
||||
- Package upgrades:
|
||||
|
||||
- `daily-python` upgraded to 0.20.0.
|
||||
- `openai` upgraded to support up to 2.x.x.
|
||||
- `openpipe` upgraded to support up to 5.x.x.
|
||||
|
||||
- `SpeechmaticsSTTService` updated dependencies for `speechmatics-rt>=0.5.0`.
|
||||
|
||||
### Deprecated
|
||||
|
||||
- The `send_transcription_frames` argument to `AWSNovaSonicLLMService` is
|
||||
deprecated. Transcription frames are now always sent. They go upstream, to be
|
||||
handled by the user context aggregator. See "Added" section for details.
|
||||
|
||||
- Types in `pipecat.services.aws.nova_sonic.context` have been deprecated due
|
||||
to changes to support `LLMContext`. See "Changed" section for details.
|
||||
|
||||
### Fixed
|
||||
|
||||
- Fixed an issue where the `RTVIProcessor` was sending duplicate
|
||||
`UserStartedSpeakingFrame` and `UserStoppedSpeakingFrame` messages.
|
||||
|
||||
- Fixed an issue in `AWSBedrockLLMService` where both `temperature` and `top_p`
|
||||
were always sent together, causing conflicts with models like Claude Sonnet 4.5
|
||||
that don't allow both parameters simultaneously. The service now only includes
|
||||
inference parameters that are explicitly set, and `InputParams` defaults have
|
||||
been changed to `None` to rely on AWS Bedrock's built-in model defaults.
|
||||
|
||||
- Fixed an issue in `RivaSegmentedSTTService` where a runtime error occurred due
|
||||
to a mismatch in the `_handle_transcription` method's signature.
|
||||
|
||||
- Fixed multiple pipeline task cancellation issues. `asyncio.CancelledError` is
|
||||
now handled properly in `PipelineTask` making it possible to cancel an asyncio
|
||||
task that it's executing a `PipelineRunner` cleanly. Also,
|
||||
`PipelineTask.cancel()` does not block anymore waiting for the `CancelFrame`
|
||||
to reach the end of the pipeline (going back to the behavior in < 0.0.83).
|
||||
|
||||
- Fixed an issue in `ElevenLabsTTSService` and `ElevenLabsHttpTTSService` where
|
||||
the Flash models would split words, resulting in a space being inserted
|
||||
between words.
|
||||
|
||||
- Fixed an issue where audio filters' `stop()` would not be called when using
|
||||
`CancelFrame`.
|
||||
|
||||
- Fixed an issue in `ElevenLabsHttpTTSService`, where
|
||||
`apply_text_normalization` was incorrectly set as a query parameter. It's now
|
||||
being added as a request parameter.
|
||||
|
||||
- Fixed an issue where `RimeHttpTTSService` and `PiperTTSService` could generate
|
||||
incorrectly 16-bit aligned audio frames, potentially leading to internal
|
||||
errors or static audio.
|
||||
|
||||
- Fixed an issue in `SpeechmaticsSTTService` where `AdditionalVocabEntry` items
|
||||
needed to have `sounds_like` for the session to start.
|
||||
|
||||
### Other
|
||||
|
||||
- Added foundational example `47-sentry-metrics.py`, demonstrating how to use the
|
||||
`SentryMetrics` processor.
|
||||
|
||||
- Added foundational example `14x-function-calling-openpipe.py`.
|
||||
|
||||
## [0.0.90] - 2025-10-10
|
||||
|
||||
### Added
|
||||
|
||||
30
README.md
30
README.md
@@ -44,10 +44,6 @@ Looking to build structured conversations? Check out [Pipecat Flows](https://git
|
||||
|
||||
Want to build beautiful and engaging experiences? Checkout the [Voice UI Kit](https://github.com/pipecat-ai/voice-ui-kit), a collection of components, hooks and templates for building voice AI applications quickly.
|
||||
|
||||
### 🛠️ Create and deploy projects
|
||||
|
||||
Create a new project in under a minute with the [Pipecat CLI](https://github.com/pipecat-ai/pipecat-cli). Then use the CLI to monitor and deploy your agent to production.
|
||||
|
||||
### 🔍 Debugging
|
||||
|
||||
Looking for help debugging your pipeline and processors? Check out [Whisker](https://github.com/pipecat-ai/whisker), a real-time Pipecat debugger.
|
||||
@@ -67,24 +63,24 @@ Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.yout
|
||||
<a href="https://github.com/pipecat-ai/pipecat-examples/tree/main/storytelling-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat-examples/main/storytelling-chatbot/image.png" width="400" /></a>
|
||||
<br/>
|
||||
<a href="https://github.com/pipecat-ai/pipecat-examples/tree/main/translation-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat-examples/main/translation-chatbot/image.png" width="400" /></a>
|
||||
<a href="https://github.com/pipecat-ai/pipecat/blob/main/examples/foundational/12-describe-video.py"><img src="https://github.com/pipecat-ai/pipecat/blob/main/examples/foundational/assets/moondream.png" width="400" /></a>
|
||||
<a href="https://github.com/pipecat-ai/pipecat-examples/tree/main/moondream-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat-examples/main/moondream-chatbot/image.png" width="400" /></a>
|
||||
</p>
|
||||
|
||||
## 🧩 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), [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), [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) |
|
||||
| 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), [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), [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) |
|
||||
| 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)
|
||||
|
||||
|
||||
184
env.example
184
env.example
@@ -4,9 +4,6 @@ AICOUSTICS_LICENSE_KEY=...
|
||||
# Anthropic
|
||||
ANTHROPIC_API_KEY=...
|
||||
|
||||
# Assembly AI
|
||||
ASSEMBLYAI_API_KEY=...
|
||||
|
||||
# Async
|
||||
ASYNCAI_API_KEY=...
|
||||
ASYNCAI_VOICE_ID=...
|
||||
@@ -24,19 +21,12 @@ AZURE_CHATGPT_API_KEY=...
|
||||
AZURE_CHATGPT_ENDPOINT=https://...
|
||||
AZURE_CHATGPT_MODEL=...
|
||||
|
||||
AZURE_REALTIME_API_KEY=...
|
||||
AZURE_REALTIME_BASE_URL=...
|
||||
|
||||
AZURE_DALLE_API_KEY=...
|
||||
AZURE_DALLE_ENDPOINT=https://...
|
||||
AZURE_DALLE_MODEL=...
|
||||
|
||||
# Cartesia
|
||||
CARTESIA_API_KEY=...
|
||||
CARTESIA_VOICE_ID=...
|
||||
|
||||
# Cerebras
|
||||
CEREBRAS_API_KEY=...
|
||||
|
||||
# Daily
|
||||
DAILY_API_KEY=...
|
||||
@@ -45,75 +35,42 @@ DAILY_SAMPLE_ROOM_URL=https://...
|
||||
# Deepgram
|
||||
DEEPGRAM_API_KEY=...
|
||||
|
||||
# DeepSeek
|
||||
DEEPSEEK_API_KEY=...
|
||||
|
||||
# ElevenLabs
|
||||
ELEVENLABS_API_KEY=...
|
||||
ELEVENLABS_VOICE_ID=...
|
||||
|
||||
# Neuphonic
|
||||
NEUPHONIC_API_KEY=...
|
||||
|
||||
# Fal
|
||||
FAL_KEY=...
|
||||
|
||||
# Fireworks
|
||||
FIREWORKS_API_KEY=...
|
||||
|
||||
# Fish Audio
|
||||
FISH_API_KEY=...
|
||||
|
||||
# Gladia
|
||||
GLADIA_API_KEY=...
|
||||
GLADIA_REGION=...
|
||||
|
||||
# Google
|
||||
GOOGLE_API_KEY=...
|
||||
GOOGLE_VERTEX_TEST_CREDENTIALS=...
|
||||
GOOGLE_CLOUD_PROJECT_ID=...
|
||||
GOOGLE_CLOUD_LOCATION=...
|
||||
GOOGLE_TEST_CREDENTIALS=...
|
||||
|
||||
# Grok
|
||||
GROK_API_KEY=...
|
||||
|
||||
# Groq
|
||||
GROQ_API_KEY=...
|
||||
|
||||
# Heygen
|
||||
HEYGEN_API_KEY=...
|
||||
GOOGLE_VERTEX_TEST_CREDENTIALS=...
|
||||
|
||||
# Hume
|
||||
HUME_API_KEY=...
|
||||
HUME_VOICE_ID=...
|
||||
|
||||
# Inworld
|
||||
INWORLD_API_KEY=...
|
||||
|
||||
# Krisp
|
||||
KRISP_MODEL_PATH=...
|
||||
|
||||
# Krisp Viva
|
||||
KRISP_VIVA_MODEL_PATH=...
|
||||
|
||||
# LiveKit
|
||||
LIVEKIT_API_KEY=...
|
||||
LIVEKIT_API_SECRET=...
|
||||
|
||||
# LMNT
|
||||
LMNT_API_KEY=...
|
||||
LMNT_VOICE_ID=...
|
||||
|
||||
# MiniMax
|
||||
MINIMAX_API_KEY=...
|
||||
MINIMAX_GROUP_ID=...
|
||||
# Perplexity
|
||||
PERPLEXITY_API_KEY=...
|
||||
|
||||
# Mistral
|
||||
MISTRAL_API_KEY=...
|
||||
|
||||
# Neuphonic
|
||||
NEUPHONIC_API_KEY=...
|
||||
|
||||
# NVIDIA
|
||||
NVIDIA_API_KEY=...
|
||||
# PlayHT
|
||||
PLAYHT_USER_ID=...
|
||||
PLAYHT_API_KEY=...
|
||||
|
||||
# OpenAI
|
||||
OPENAI_API_KEY=...
|
||||
@@ -121,73 +78,92 @@ OPENAI_API_KEY=...
|
||||
# OpenPipe
|
||||
OPENPIPE_API_KEY=...
|
||||
|
||||
# OpenRouter
|
||||
OPENROUTER_API_KEY=...
|
||||
|
||||
# Perplexity
|
||||
PERPLEXITY_API_KEY=...
|
||||
|
||||
# Picovoice Koala
|
||||
KOALA_ACCESS_KEY=...
|
||||
|
||||
# Piper
|
||||
PIPER_BASE_URL=...
|
||||
|
||||
# PlayHT
|
||||
PLAYHT_USER_ID=...
|
||||
PLAYHT_API_KEY=...
|
||||
|
||||
# Plivo
|
||||
PLIVO_AUTH_ID=...
|
||||
PLIVO_AUTH_TOKEN=...
|
||||
|
||||
# Qwen
|
||||
QWEN_API_KEY=...
|
||||
|
||||
# Rime
|
||||
RIME_API_KEY=...
|
||||
RIME_VOICE_ID=...
|
||||
|
||||
# SambaNova
|
||||
SAMBANOVA_API_KEY=...
|
||||
|
||||
# Sarvam AI
|
||||
SARVAM_API_KEY=...
|
||||
|
||||
# Sentry
|
||||
SENTRY_DSN=...
|
||||
# Tavus
|
||||
TAVUS_API_KEY=...
|
||||
TAVUS_REPLICA_ID=...
|
||||
TAVUS_PERSONA_ID=...
|
||||
|
||||
# Simli
|
||||
SIMLI_API_KEY=...
|
||||
SIMLI_FACE_ID=...
|
||||
|
||||
# Smart turn
|
||||
LOCAL_SMART_TURN_MODEL_PATH=...
|
||||
FAL_SMART_TURN_API_KEY=...
|
||||
# Krisp
|
||||
KRISP_MODEL_PATH=...
|
||||
|
||||
# Soniox
|
||||
SONIOX_API_KEY=...
|
||||
# Krisp Viva
|
||||
KRISP_VIVA_MODEL_PATH=...
|
||||
|
||||
# Speechmatics
|
||||
SPEECHMATICS_API_KEY=...
|
||||
# DeepSeek
|
||||
DEEPSEEK_API_KEY=...
|
||||
|
||||
# Tavus
|
||||
TAVUS_API_KEY=...
|
||||
TAVUS_REPLICA_ID=...
|
||||
# Groq
|
||||
GROQ_API_KEY=...
|
||||
|
||||
# Telnyx
|
||||
TELNYX_API_KEY=...
|
||||
TELNYX_ACCOUNT_SID=...
|
||||
# Grok
|
||||
GROK_API_KEY=...
|
||||
|
||||
# Inworld
|
||||
INWORLD_API_KEY=...
|
||||
|
||||
# Together.ai
|
||||
TOGETHER_API_KEY=...
|
||||
|
||||
# Cerebras
|
||||
CEREBRAS_API_KEY=...
|
||||
|
||||
# Fish Audio
|
||||
FISH_API_KEY=...
|
||||
|
||||
# Assembly AI
|
||||
ASSEMBLYAI_API_KEY=...
|
||||
|
||||
# OpenRouter
|
||||
OPENROUTER_API_KEY=...
|
||||
|
||||
# Piper
|
||||
PIPER_BASE_URL=...
|
||||
|
||||
# Smart turn
|
||||
LOCAL_SMART_TURN_MODEL_PATH=...
|
||||
FAL_SMART_TURN_API_KEY=...
|
||||
|
||||
# Twilio
|
||||
TWILIO_ACCOUNT_SID=...
|
||||
TWILIO_AUTH_TOKEN=...
|
||||
|
||||
# MiniMax
|
||||
MINIMAX_API_KEY=...
|
||||
MINIMAX_GROUP_ID=...
|
||||
|
||||
# Sarvam AI
|
||||
SARVAM_API_KEY=...
|
||||
|
||||
# Soniox
|
||||
SONIOX_API_KEY=
|
||||
|
||||
# Speechmatics
|
||||
SPEECHMATICS_API_KEY=...
|
||||
|
||||
# SambaNova
|
||||
SAMBANOVA_API_KEY=...
|
||||
|
||||
# Sentry
|
||||
SENTRY_DSN=...
|
||||
|
||||
# Heygen
|
||||
HEYGEN_API_KEY=...
|
||||
|
||||
# Mistral
|
||||
MISTRAL_API_KEY=...
|
||||
|
||||
# NVIDIA
|
||||
NVIDIA_API_KEY=...
|
||||
|
||||
# Qwen
|
||||
QWEN_API_KEY=...
|
||||
|
||||
# WhatsApp
|
||||
WHATSAPP_TOKEN=...
|
||||
WHATSAPP_WEBHOOK_VERIFICATION_TOKEN=...
|
||||
WHATSAPP_PHONE_NUMBER_ID=...
|
||||
WHATSAPP_APP_SECRET=...
|
||||
WHATSAPP_TOKEN=
|
||||
WHATSAPP_WEBHOOK_VERIFICATION_TOKEN=
|
||||
WHATSAPP_PHONE_NUMBER_ID=
|
||||
WHATSAPP_APP_SECRET=
|
||||
@@ -21,8 +21,8 @@ from pipecat.processors.aggregators.llm_context import LLMContext
|
||||
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
|
||||
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 BaseTransport, TransportParams
|
||||
from pipecat.transports.daily.transport import DailyParams
|
||||
@@ -58,7 +58,7 @@ transport_params = {
|
||||
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
logger.info(f"Starting bot")
|
||||
|
||||
stt = CartesiaSTTService(api_key=os.getenv("CARTESIA_API_KEY"))
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
|
||||
@@ -67,8 +67,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
|
||||
llm = AWSBedrockLLMService(
|
||||
aws_region="us-west-2",
|
||||
model="us.anthropic.claude-haiku-4-5-20251001-v1:0",
|
||||
params=AWSBedrockLLMService.InputParams(temperature=0.8),
|
||||
model="us.anthropic.claude-3-5-haiku-20241022-v1:0",
|
||||
params=AWSBedrockLLMService.InputParams(temperature=0.8, latency="optimized"),
|
||||
)
|
||||
|
||||
messages = [
|
||||
|
||||
147
examples/foundational/08-bots-arguing.py
Normal file
147
examples/foundational/08-bots-arguing.py
Normal file
@@ -0,0 +1,147 @@
|
||||
import asyncio
|
||||
import logging
|
||||
import os
|
||||
from typing import Tuple
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
|
||||
from pipecat.frames.frames import AudioFrame, EndFrame, ImageFrame, LLMContextFrame, TextFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.processors.aggregators import SentenceAggregator
|
||||
from pipecat.processors.aggregators.llm_context import LLMContext
|
||||
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
|
||||
from pipecat.runner.daily import configure
|
||||
from pipecat.services.azure import AzureLLMService, AzureTTSService
|
||||
from pipecat.services.elevenlabs import ElevenLabsTTSService
|
||||
from pipecat.services.fal import FalImageGenService
|
||||
from pipecat.transports.daily.transport import DailyTransport
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logging.basicConfig(format=f"%(levelno)s %(asctime)s %(message)s")
|
||||
logger = logging.getLogger("pipecat")
|
||||
logger.setLevel(logging.DEBUG)
|
||||
|
||||
|
||||
async def main():
|
||||
async with aiohttp.ClientSession() as session:
|
||||
(room_url, _) = await configure(session)
|
||||
|
||||
transport = DailyTransport(
|
||||
room_url,
|
||||
None,
|
||||
"Respond bot",
|
||||
duration_minutes=10,
|
||||
mic_enabled=True,
|
||||
mic_sample_rate=16000,
|
||||
camera_enabled=True,
|
||||
camera_width=1024,
|
||||
camera_height=1024,
|
||||
)
|
||||
|
||||
llm = AzureLLMService(
|
||||
api_key=os.getenv("AZURE_CHATGPT_API_KEY"),
|
||||
endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"),
|
||||
model=os.getenv("AZURE_CHATGPT_MODEL"),
|
||||
)
|
||||
tts1 = AzureTTSService(
|
||||
api_key=os.getenv("AZURE_SPEECH_API_KEY"),
|
||||
region=os.getenv("AZURE_SPEECH_REGION"),
|
||||
)
|
||||
tts2 = ElevenLabsTTSService(
|
||||
api_key=os.getenv("ELEVENLABS_API_KEY"),
|
||||
voice_id="jBpfuIE2acCO8z3wKNLl",
|
||||
)
|
||||
dalle = FalImageGenService(
|
||||
params=FalImageGenService.InputParams(image_size="1024x1024"),
|
||||
aiohttp_session=session,
|
||||
key=os.getenv("FAL_KEY"),
|
||||
)
|
||||
|
||||
bot1_messages = [
|
||||
{
|
||||
"role": "system",
|
||||
"content": "You are a stern librarian. You strongly believe that a hot dog is a sandwich. Start by stating this fact in a few sentences, then be prepared to debate this with the user. You shouldn't ever compromise on the fundamental truth that a hot dog is a sandwich. Your responses should only be a few sentences long.",
|
||||
},
|
||||
]
|
||||
bot2_messages = [
|
||||
{
|
||||
"role": "system",
|
||||
"content": "You are a silly cat, and you strongly believe that a hot dog is not a sandwich. Debate this with the user, only responding with a few sentences. Don't ever accept that a hot dog is a sandwich.",
|
||||
},
|
||||
]
|
||||
|
||||
async def get_text_and_audio(messages) -> Tuple[str, bytearray]:
|
||||
"""This function streams text from the LLM and uses the TTS service to convert
|
||||
that text to speech as it's received.
|
||||
"""
|
||||
source_queue = asyncio.Queue()
|
||||
sink_queue = asyncio.Queue()
|
||||
sentence_aggregator = SentenceAggregator()
|
||||
pipeline = Pipeline([llm, sentence_aggregator, tts1], source_queue, sink_queue)
|
||||
|
||||
await source_queue.put(LLMContextFrame(LLMContext(messages)))
|
||||
await source_queue.put(EndFrame())
|
||||
await pipeline.run_pipeline()
|
||||
|
||||
message = ""
|
||||
all_audio = bytearray()
|
||||
while sink_queue.qsize():
|
||||
frame = sink_queue.get_nowait()
|
||||
if isinstance(frame, TextFrame):
|
||||
message += frame.text
|
||||
elif isinstance(frame, AudioFrame):
|
||||
all_audio.extend(frame.audio)
|
||||
|
||||
return (message, all_audio)
|
||||
|
||||
async def get_bot1_statement():
|
||||
message, audio = await get_text_and_audio(bot1_messages)
|
||||
|
||||
bot1_messages.append({"role": "assistant", "content": message})
|
||||
bot2_messages.append({"role": "user", "content": message})
|
||||
|
||||
return audio
|
||||
|
||||
async def get_bot2_statement():
|
||||
message, audio = await get_text_and_audio(bot2_messages)
|
||||
|
||||
bot2_messages.append({"role": "assistant", "content": message})
|
||||
bot1_messages.append({"role": "user", "content": message})
|
||||
|
||||
return audio
|
||||
|
||||
async def argue():
|
||||
for i in range(100):
|
||||
print(f"In iteration {i}")
|
||||
|
||||
bot1_description = "A woman conservatively dressed as a librarian in a library surrounded by books, cartoon, serious, highly detailed"
|
||||
|
||||
(audio1, image_data1) = await asyncio.gather(
|
||||
get_bot1_statement(), dalle.run_image_gen(bot1_description)
|
||||
)
|
||||
await transport.send_queue.put(
|
||||
[
|
||||
ImageFrame(image_data1[1], image_data1[2]),
|
||||
AudioFrame(audio1),
|
||||
]
|
||||
)
|
||||
|
||||
bot2_description = "A cat dressed in a hot dog costume, cartoon, bright colors, funny, highly detailed"
|
||||
|
||||
(audio2, image_data2) = await asyncio.gather(
|
||||
get_bot2_statement(), dalle.run_image_gen(bot2_description)
|
||||
)
|
||||
await transport.send_queue.put(
|
||||
[
|
||||
ImageFrame(image_data2[1], image_data2[2]),
|
||||
AudioFrame(audio2),
|
||||
]
|
||||
)
|
||||
|
||||
await asyncio.gather(transport.run(), argue())
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
@@ -1,170 +0,0 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# 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
|
||||
from pipecat.frames.frames import (
|
||||
Frame,
|
||||
LLMRunFrame,
|
||||
MetricsFrame,
|
||||
)
|
||||
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.frame_processor import FrameDirection, FrameProcessor
|
||||
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.base_transport import BaseTransport, TransportParams
|
||||
from pipecat.transports.daily.transport import DailyParams
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
|
||||
def format_metrics(metrics, indent=0):
|
||||
lines = []
|
||||
tab = "\t" * indent
|
||||
|
||||
for metric in metrics:
|
||||
lines.append(tab + type(metric).__name__)
|
||||
for field, value in vars(metric).items():
|
||||
if hasattr(value, "__dict__") and not isinstance(
|
||||
value, (str, int, float, bool, type(None))
|
||||
):
|
||||
lines.append(f"{tab}\t{field}={type(value).__name__}")
|
||||
for k, v in vars(value).items():
|
||||
lines.append(f"{tab}\t\t{k}={repr(v)}")
|
||||
else:
|
||||
lines.append(f"{tab}\t{field}={repr(value)}")
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
class MetricsFrameLogger(FrameProcessor):
|
||||
"""MetricsFrameLogger formats and logs all MetericsFrames"""
|
||||
|
||||
def __init__(self, **kwargs):
|
||||
super().__init__(**kwargs)
|
||||
|
||||
async def process_frame(self, frame: Frame, direction: FrameDirection):
|
||||
await super().process_frame(frame, direction)
|
||||
|
||||
if isinstance(frame, MetricsFrame):
|
||||
logger.info(f"{frame.name}\n {format_metrics(frame.data)}")
|
||||
await self.push_frame(frame, direction)
|
||||
|
||||
# ALWAYS push all frames
|
||||
else:
|
||||
# SUPER IMPORTANT: always push every frame!
|
||||
await self.push_frame(frame, direction)
|
||||
|
||||
|
||||
# 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()),
|
||||
),
|
||||
"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()),
|
||||
),
|
||||
}
|
||||
|
||||
|
||||
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
logger.info(f"Starting bot")
|
||||
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||||
)
|
||||
|
||||
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 converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
|
||||
},
|
||||
]
|
||||
|
||||
context = LLMContext(messages)
|
||||
context_aggregator = LLMContextAggregatorPair(context)
|
||||
|
||||
metrics_frame_processor = MetricsFrameLogger()
|
||||
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
transport.input(),
|
||||
stt,
|
||||
context_aggregator.user(),
|
||||
llm,
|
||||
tts,
|
||||
transport.output(),
|
||||
context_aggregator.assistant(),
|
||||
metrics_frame_processor, # pretty print metrics frames
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
params=PipelineParams(
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
),
|
||||
idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
|
||||
)
|
||||
|
||||
@transport.event_handler("on_client_connected")
|
||||
async def on_client_connected(transport, client):
|
||||
logger.info(f"Client connected: {client}")
|
||||
# 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(f"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()
|
||||
@@ -48,7 +48,10 @@ transport_params = {
|
||||
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
logger.info(f"Starting bot")
|
||||
|
||||
stt = CartesiaSTTService(api_key=os.getenv("CARTESIA_API_KEY"))
|
||||
stt = CartesiaSTTService(
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
base_url=os.getenv("CARTESIA_BASE_URL"),
|
||||
)
|
||||
|
||||
tl = TranscriptionLogger()
|
||||
|
||||
|
||||
@@ -79,8 +79,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
|
||||
llm = AWSBedrockLLMService(
|
||||
aws_region="us-west-2",
|
||||
model="us.anthropic.claude-haiku-4-5-20251001-v1:0",
|
||||
params=AWSBedrockLLMService.InputParams(temperature=0.8),
|
||||
model="us.anthropic.claude-3-5-haiku-20241022-v1:0",
|
||||
params=AWSBedrockLLMService.InputParams(temperature=0.8, latency="optimized"),
|
||||
)
|
||||
|
||||
# You can also register a function_name of None to get all functions
|
||||
|
||||
@@ -1,182 +0,0 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import os
|
||||
import time
|
||||
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
|
||||
from pipecat.adapters.schemas.function_schema import FunctionSchema
|
||||
from pipecat.adapters.schemas.tools_schema import ToolsSchema
|
||||
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, TTSSpeakFrame
|
||||
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.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.llm_service import FunctionCallParams
|
||||
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
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
|
||||
async def fetch_weather_from_api(params: FunctionCallParams):
|
||||
await params.result_callback({"conditions": "nice", "temperature": "75"})
|
||||
|
||||
|
||||
async def fetch_restaurant_recommendation(params: FunctionCallParams):
|
||||
await params.result_callback({"name": "The Golden Dragon"})
|
||||
|
||||
|
||||
# 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(f"Starting bot")
|
||||
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||||
)
|
||||
|
||||
timestamp = int(time.time())
|
||||
llm = OpenPipeLLMService(
|
||||
api_key=os.getenv("OPENAI_API_KEY"),
|
||||
openpipe_api_key=os.getenv("OPENPIPE_API_KEY"),
|
||||
tags={"conversation_id": f"pipecat-{timestamp}"},
|
||||
)
|
||||
|
||||
# You can also register a function_name of None to get all functions
|
||||
# sent to the same callback with an additional function_name parameter.
|
||||
llm.register_function("get_current_weather", fetch_weather_from_api)
|
||||
llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation)
|
||||
|
||||
@llm.event_handler("on_function_calls_started")
|
||||
async def on_function_calls_started(service, function_calls):
|
||||
await tts.queue_frame(TTSSpeakFrame("Let me check on that."))
|
||||
|
||||
weather_function = FunctionSchema(
|
||||
name="get_current_weather",
|
||||
description="Get the current weather",
|
||||
properties={
|
||||
"location": {
|
||||
"type": "string",
|
||||
"description": "The city and state, e.g. San Francisco, CA",
|
||||
},
|
||||
"format": {
|
||||
"type": "string",
|
||||
"enum": ["celsius", "fahrenheit"],
|
||||
"description": "The temperature unit to use. Infer this from the user's location.",
|
||||
},
|
||||
},
|
||||
required=["location", "format"],
|
||||
)
|
||||
restaurant_function = FunctionSchema(
|
||||
name="get_restaurant_recommendation",
|
||||
description="Get a restaurant recommendation",
|
||||
properties={
|
||||
"location": {
|
||||
"type": "string",
|
||||
"description": "The city and state, e.g. San Francisco, CA",
|
||||
},
|
||||
},
|
||||
required=["location"],
|
||||
)
|
||||
tools = ToolsSchema(standard_tools=[weather_function, restaurant_function])
|
||||
|
||||
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 converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
|
||||
},
|
||||
]
|
||||
|
||||
context = LLMContext(messages, tools)
|
||||
context_aggregator = LLMContextAggregatorPair(context)
|
||||
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
transport.input(),
|
||||
stt,
|
||||
context_aggregator.user(),
|
||||
llm,
|
||||
tts,
|
||||
transport.output(),
|
||||
context_aggregator.assistant(),
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
params=PipelineParams(
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
),
|
||||
idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
|
||||
)
|
||||
|
||||
@transport.event_handler("on_client_connected")
|
||||
async def on_client_connected(transport, client):
|
||||
logger.info(f"Client connected")
|
||||
# Kick off the conversation.
|
||||
await task.queue_frames([LLMRunFrame()])
|
||||
|
||||
@transport.event_handler("on_client_disconnected")
|
||||
async def on_client_disconnected(transport, client):
|
||||
logger.info(f"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()
|
||||
156
examples/foundational/18-openai-realtime-usage.py
Normal file
156
examples/foundational/18-openai-realtime-usage.py
Normal file
@@ -0,0 +1,156 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
"""Example: Print OpenAI Realtime API Token Usage Statistics
|
||||
|
||||
This example demonstrates how to access and print token usage statistics
|
||||
from the OpenAI Realtime API, including detailed breakdowns of input/output
|
||||
tokens, cached tokens, and audio/text token usage.
|
||||
"""
|
||||
|
||||
import os
|
||||
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.audio.vad.vad_analyzer import VADParams
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.runner.types import RunnerArguments
|
||||
from pipecat.runner.utils import create_transport
|
||||
from pipecat.services.openai.realtime.llm import OpenAIRealtimeLLMService
|
||||
from pipecat.transports.base_transport import BaseTransport, TransportParams
|
||||
from pipecat.transports.daily.transport import DailyParams
|
||||
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
# We store functions so objects don't get instantiated until 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)),
|
||||
),
|
||||
"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):
|
||||
"""Main function demonstrating usage statistics tracking."""
|
||||
logger.info(f"Starting bot")
|
||||
|
||||
# Initialize the OpenAI Realtime service
|
||||
llm = OpenAIRealtimeLLMService(
|
||||
api_key=os.getenv("OPENAI_API_KEY") or "",
|
||||
model="gpt-4o-realtime-preview-2024-12-17",
|
||||
)
|
||||
|
||||
# To access usage statistics, we wrap the internal response handler
|
||||
# This is the cleanest way to intercept usage data from the realtime API
|
||||
original_handler = llm._handle_evt_response_done
|
||||
|
||||
async def custom_response_done_handler(evt):
|
||||
"""Custom handler that prints usage stats before calling original handler."""
|
||||
# Print usage statistics if available
|
||||
if evt.response.usage:
|
||||
usage = evt.response.usage
|
||||
|
||||
logger.info("\n" + "=" * 50)
|
||||
logger.info("📊 TOKEN USAGE STATISTICS")
|
||||
logger.info("=" * 50)
|
||||
logger.info(f"Total tokens: {usage.total_tokens}")
|
||||
logger.info(f"Input tokens: {usage.input_tokens}")
|
||||
logger.info(f"Output tokens: {usage.output_tokens}")
|
||||
|
||||
# Input token details
|
||||
if usage.input_token_details:
|
||||
logger.info(f"\n📥 Input token breakdown:")
|
||||
logger.info(f" • Cached tokens: {usage.input_token_details.cached_tokens}")
|
||||
logger.info(f" • Text tokens: {usage.input_token_details.text_tokens}")
|
||||
logger.info(f" • Audio tokens: {usage.input_token_details.audio_tokens}")
|
||||
|
||||
# Cached token details if available
|
||||
if usage.input_token_details.cached_tokens_details:
|
||||
logger.info(
|
||||
f" • Cached text tokens: {usage.input_token_details.cached_tokens_details.text_tokens}"
|
||||
)
|
||||
logger.info(
|
||||
f" • Cached audio tokens: {usage.input_token_details.cached_tokens_details.audio_tokens}"
|
||||
)
|
||||
|
||||
# Output token details
|
||||
if usage.output_token_details:
|
||||
logger.info(f"\n📤 Output token breakdown:")
|
||||
logger.info(f" • Text tokens: {usage.output_token_details.text_tokens}")
|
||||
logger.info(f" • Audio tokens: {usage.output_token_details.audio_tokens}")
|
||||
|
||||
logger.info("=" * 50 + "\n")
|
||||
|
||||
# Call the original handler to maintain normal functionality
|
||||
await original_handler(evt)
|
||||
|
||||
# Replace the handler with our custom one
|
||||
llm._handle_evt_response_done = custom_response_done_handler
|
||||
|
||||
# Create pipeline
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
transport.input(),
|
||||
llm,
|
||||
transport.output(),
|
||||
]
|
||||
)
|
||||
|
||||
# Create task
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
params=PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
),
|
||||
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("🎤 Speak into your microphone to interact with the assistant")
|
||||
logger.info("📊 Usage statistics will be printed after each response")
|
||||
|
||||
@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()
|
||||
@@ -72,6 +72,7 @@ async def save_conversation(params: FunctionCallParams):
|
||||
)
|
||||
try:
|
||||
with open(filename, "w") as file:
|
||||
# todo: extract 'system' into the first message in the list
|
||||
messages = params.context.get_messages()
|
||||
# remove the last message, which is the instruction we just gave to save the conversation
|
||||
messages.pop()
|
||||
|
||||
@@ -90,6 +90,7 @@ async def save_conversation(params: FunctionCallParams):
|
||||
)
|
||||
try:
|
||||
with open(filename, "w") as file:
|
||||
# todo: extract 'system' into the first message in the list
|
||||
messages = params.context.get_messages()
|
||||
# remove the last message (the instruction to save the context)
|
||||
messages.pop()
|
||||
|
||||
@@ -20,8 +20,6 @@ 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
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.runner.types import RunnerArguments
|
||||
from pipecat.runner.utils import create_transport
|
||||
@@ -77,7 +75,7 @@ async def save_conversation(params: FunctionCallParams):
|
||||
filename = f"{BASE_FILENAME}{timestamp}.json"
|
||||
try:
|
||||
with open(filename, "w") as file:
|
||||
messages = params.context.get_messages()
|
||||
messages = params.context.get_messages_for_persistent_storage()
|
||||
# remove the last few messages. in reverse order, they are:
|
||||
# - the in progress save tool call
|
||||
# - the invocation of the save tool call
|
||||
@@ -225,13 +223,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
llm.register_function("get_saved_conversation_filenames", get_saved_conversation_filenames)
|
||||
llm.register_function("load_conversation", load_conversation)
|
||||
|
||||
context = LLMContext(
|
||||
context = OpenAILLMContext(
|
||||
messages=[
|
||||
{"role": "system", "content": f"{system_instruction}"},
|
||||
],
|
||||
tools=tools,
|
||||
)
|
||||
context_aggregator = LLMContextAggregatorPair(context)
|
||||
context_aggregator = llm.create_context_aggregator(context)
|
||||
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
|
||||
@@ -18,8 +18,7 @@ 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
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.runner.types import RunnerArguments
|
||||
from pipecat.runner.utils import create_transport
|
||||
from pipecat.services.aws.nova_sonic.llm import AWSNovaSonicLLMService
|
||||
@@ -120,7 +119,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
llm.register_function("get_current_weather", fetch_weather_from_api)
|
||||
|
||||
# Set up context and context management.
|
||||
context = LLMContext(
|
||||
# AWSNovaSonicService will adapt OpenAI LLM context objects with standard message format to
|
||||
# what's expected by Nova Sonic.
|
||||
context = OpenAILLMContext(
|
||||
messages=[
|
||||
{"role": "system", "content": f"{system_instruction}"},
|
||||
{
|
||||
@@ -130,7 +131,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
],
|
||||
tools=tools,
|
||||
)
|
||||
context_aggregator = LLMContextAggregatorPair(context)
|
||||
context_aggregator = llm.create_context_aggregator(context)
|
||||
|
||||
# Build the pipeline
|
||||
pipeline = Pipeline(
|
||||
|
||||
@@ -1,142 +0,0 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import os
|
||||
|
||||
import sentry_sdk
|
||||
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
|
||||
from pipecat.processors.metrics.sentry import SentryMetrics
|
||||
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.base_transport import BaseTransport, TransportParams
|
||||
from pipecat.transports.daily.transport import DailyParams
|
||||
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
|
||||
|
||||
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(f"Starting bot")
|
||||
|
||||
# Initialize Sentry
|
||||
sentry_sdk.init(
|
||||
dsn=os.getenv("SENTRY_DSN"),
|
||||
traces_sample_rate=1.0,
|
||||
)
|
||||
|
||||
stt = DeepgramSTTService(
|
||||
api_key=os.getenv("DEEPGRAM_API_KEY"),
|
||||
metrics=SentryMetrics(),
|
||||
)
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||||
metrics=SentryMetrics(),
|
||||
)
|
||||
|
||||
llm = OpenAILLMService(
|
||||
api_key=os.getenv("OPENAI_API_KEY"),
|
||||
metrics=SentryMetrics(),
|
||||
)
|
||||
|
||||
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 converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
|
||||
},
|
||||
]
|
||||
|
||||
context = LLMContext(messages)
|
||||
context_aggregator = LLMContextAggregatorPair(context)
|
||||
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
transport.input(), # Transport user input
|
||||
stt,
|
||||
context_aggregator.user(), # User responses
|
||||
llm, # LLM
|
||||
tts, # TTS
|
||||
transport.output(), # Transport bot output
|
||||
context_aggregator.assistant(), # Assistant spoken responses
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
params=PipelineParams(
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
),
|
||||
idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
|
||||
)
|
||||
|
||||
@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):
|
||||
logger.info(f"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()
|
||||
@@ -1,153 +0,0 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
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, ManuallySwitchServiceFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.service_switcher import ServiceSwitcher, ServiceSwitcherStrategyManual
|
||||
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.runner.types import RunnerArguments
|
||||
from pipecat.runner.utils import create_transport
|
||||
from pipecat.services.cartesia.stt import CartesiaSTTService
|
||||
from pipecat.services.cartesia.tts import CartesiaTTSService
|
||||
from pipecat.services.deepgram.stt import DeepgramSTTService
|
||||
from pipecat.services.deepgram.tts import DeepgramTTSService
|
||||
from pipecat.services.google.llm import GoogleLLMService
|
||||
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
|
||||
|
||||
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(f"Starting bot")
|
||||
|
||||
stt_cartesia = CartesiaSTTService(api_key=os.getenv("CARTESIA_API_KEY"))
|
||||
stt_deepgram = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
stt_switcher = ServiceSwitcher(
|
||||
services=[stt_cartesia, stt_deepgram], strategy_type=ServiceSwitcherStrategyManual
|
||||
)
|
||||
|
||||
tts_cartesia = CartesiaTTSService(
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121",
|
||||
)
|
||||
tts_deepgram = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
tts_switcher = ServiceSwitcher(
|
||||
services=[tts_cartesia, tts_deepgram], strategy_type=ServiceSwitcherStrategyManual
|
||||
)
|
||||
|
||||
llm_openai = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
|
||||
llm_google = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"))
|
||||
llm_switcher = ServiceSwitcher(
|
||||
services=[llm_openai, llm_google], strategy_type=ServiceSwitcherStrategyManual
|
||||
)
|
||||
|
||||
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 converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
|
||||
},
|
||||
]
|
||||
|
||||
context = LLMContext(messages)
|
||||
context_aggregator = LLMContextAggregatorPair(context)
|
||||
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
transport.input(), # Transport user input
|
||||
stt_switcher,
|
||||
context_aggregator.user(), # User responses
|
||||
llm_switcher, # LLM
|
||||
tts_switcher, # TTS
|
||||
transport.output(), # Transport bot output
|
||||
context_aggregator.assistant(), # Assistant spoken responses
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
params=PipelineParams(
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
),
|
||||
idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
|
||||
)
|
||||
|
||||
@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()])
|
||||
await asyncio.sleep(15)
|
||||
print(f"Switching to {stt_deepgram}")
|
||||
await task.queue_frames([ManuallySwitchServiceFrame(service=stt_deepgram)])
|
||||
await asyncio.sleep(15)
|
||||
print(f"Switching to {llm_google}")
|
||||
await task.queue_frames([ManuallySwitchServiceFrame(service=llm_google)])
|
||||
await asyncio.sleep(15)
|
||||
print(f"Switching to {tts_deepgram}")
|
||||
await task.queue_frames([ManuallySwitchServiceFrame(service=tts_deepgram)])
|
||||
|
||||
@transport.event_handler("on_client_disconnected")
|
||||
async def on_client_disconnected(transport, client):
|
||||
logger.info(f"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()
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 1.1 MiB |
@@ -73,13 +73,13 @@ Transform your local bot into a production-ready service. Pipecat Cloud handles
|
||||
|
||||
1. [Sign up for Pipecat Cloud](https://pipecat.daily.co/sign-up).
|
||||
|
||||
2. Install the Pipecat CLI:
|
||||
2. Install the Pipecat Cloud CLI:
|
||||
|
||||
```bash
|
||||
uv tool install pipecat-ai-cli
|
||||
uv add pipecatcloud
|
||||
```
|
||||
|
||||
> 💡 Tip: You can run the `pipecat` CLI using the `pc` alias.
|
||||
> 💡 Tip: You can run the `pipecatcloud` CLI using the `pcc` alias.
|
||||
|
||||
3. Set up Docker for building your bot image:
|
||||
|
||||
@@ -113,22 +113,12 @@ secret_set = "quickstart-secrets"
|
||||
|
||||
> 💡 Tip: [Set up `image_credentials`](https://docs.pipecat.ai/deployment/pipecat-cloud/fundamentals/secrets#image-pull-secrets) in your TOML file for authenticated image pulls
|
||||
|
||||
### Log in to Pipecat Cloud
|
||||
|
||||
To start using the CLI, authenticate to Pipecat Cloud:
|
||||
|
||||
```bash
|
||||
pipecat cloud auth login
|
||||
```
|
||||
|
||||
You'll be presented with a link that you can click to authenticate your client.
|
||||
|
||||
### Configure secrets
|
||||
|
||||
Upload your API keys to Pipecat Cloud's secure storage:
|
||||
|
||||
```bash
|
||||
pipecat cloud secrets set quickstart-secrets --file .env
|
||||
uv run pcc secrets set quickstart-secrets --file .env
|
||||
```
|
||||
|
||||
This creates a secret set called `quickstart-secrets` (matching your TOML file) and uploads all your API keys from `.env`.
|
||||
@@ -138,13 +128,13 @@ This creates a secret set called `quickstart-secrets` (matching your TOML file)
|
||||
Build your Docker image and push to Docker Hub:
|
||||
|
||||
```bash
|
||||
pipecat cloud docker build-push
|
||||
uv run pcc docker build-push
|
||||
```
|
||||
|
||||
Deploy to Pipecat Cloud:
|
||||
|
||||
```bash
|
||||
pipecat cloud deploy
|
||||
uv run pcc deploy
|
||||
```
|
||||
|
||||
### Connect to your agent
|
||||
|
||||
@@ -1,11 +1,6 @@
|
||||
agent_name = "quickstart"
|
||||
image = "your_username/quickstart:0.1"
|
||||
secret_set = "quickstart-secrets"
|
||||
agent_profile = "agent-1x"
|
||||
|
||||
# RECOMMENDED: Set an image pull secret:
|
||||
# https://docs.pipecat.ai/deployment/pipecat-cloud/fundamentals/secrets#image-pull-secrets
|
||||
# image_credentials = "your_image_pull_secret"
|
||||
|
||||
[scaling]
|
||||
min_agents = 1
|
||||
|
||||
@@ -4,14 +4,13 @@ version = "0.1.0"
|
||||
description = "Quickstart example for building voice AI bots with Pipecat"
|
||||
requires-python = ">=3.10"
|
||||
dependencies = [
|
||||
"pipecat-ai[webrtc,daily,silero,deepgram,openai,cartesia,local-smart-turn-v3,runner]",
|
||||
"pipecat-ai-cli"
|
||||
"pipecat-ai[webrtc,daily,silero,deepgram,openai,cartesia,local-smart-turn-v3,runner]>=0.0.86",
|
||||
"pipecatcloud>=0.2.4"
|
||||
]
|
||||
|
||||
[dependency-groups]
|
||||
dev = [
|
||||
"pyright>=1.1.404,<2",
|
||||
"ruff>=0.12.11,<1",
|
||||
"ruff~=0.12.1",
|
||||
]
|
||||
|
||||
[tool.ruff]
|
||||
|
||||
@@ -34,7 +34,7 @@ dependencies = [
|
||||
"pyloudnorm~=0.1.1",
|
||||
"resampy~=0.4.3",
|
||||
"soxr~=0.5.0",
|
||||
"openai>=1.74.0,<3",
|
||||
"openai>=1.74.0,<=1.99.1",
|
||||
# Pinning numba to resolve package dependencies
|
||||
"numba==0.61.2",
|
||||
"wait_for2>=0.4.1; python_version<'3.12'",
|
||||
@@ -50,12 +50,12 @@ anthropic = [ "anthropic~=0.49.0" ]
|
||||
assemblyai = [ "pipecat-ai[websockets-base]" ]
|
||||
asyncai = [ "pipecat-ai[websockets-base]" ]
|
||||
aws = [ "aioboto3~=15.0.0", "pipecat-ai[websockets-base]" ]
|
||||
aws-nova-sonic = [ "aws_sdk_bedrock_runtime~=0.1.1; python_version>='3.12'" ]
|
||||
aws-nova-sonic = [ "aws_sdk_bedrock_runtime~=0.1.0; python_version>='3.12'" ]
|
||||
azure = [ "azure-cognitiveservices-speech~=1.42.0"]
|
||||
cartesia = [ "cartesia~=2.0.3", "pipecat-ai[websockets-base]" ]
|
||||
cerebras = []
|
||||
deepseek = []
|
||||
daily = [ "daily-python~=0.20.0" ]
|
||||
daily = [ "daily-python~=0.19.9" ]
|
||||
deepgram = [ "deepgram-sdk~=4.7.0" ]
|
||||
elevenlabs = [ "pipecat-ai[websockets-base]" ]
|
||||
fal = [ "fal-client~=0.5.9" ]
|
||||
@@ -84,7 +84,7 @@ nim = []
|
||||
neuphonic = [ "pipecat-ai[websockets-base]" ]
|
||||
noisereduce = [ "noisereduce~=3.0.3" ]
|
||||
openai = [ "pipecat-ai[websockets-base]" ]
|
||||
openpipe = [ "openpipe>=4.50.0,<6" ]
|
||||
openpipe = [ "openpipe~=4.50.0" ]
|
||||
openrouter = []
|
||||
perplexity = []
|
||||
playht = [ "pipecat-ai[websockets-base]" ]
|
||||
@@ -102,7 +102,7 @@ silero = [ "onnxruntime>=1.20.1,<2" ]
|
||||
simli = [ "simli-ai~=0.1.10"]
|
||||
soniox = [ "pipecat-ai[websockets-base]" ]
|
||||
soundfile = [ "soundfile~=0.13.0" ]
|
||||
speechmatics = [ "speechmatics-rt>=0.5.0" ]
|
||||
speechmatics = [ "speechmatics-rt>=0.4.0" ]
|
||||
strands = [ "strands-agents>=1.9.1,<2" ]
|
||||
tavus=[]
|
||||
together = []
|
||||
|
||||
@@ -136,7 +136,6 @@ TESTS_14 = [
|
||||
("14r-function-calling-aws.py", PROMPT_WEATHER, EVAL_WEATHER, BOT_SPEAKS_FIRST),
|
||||
("14v-function-calling-openai.py", PROMPT_WEATHER, EVAL_WEATHER, BOT_SPEAKS_FIRST),
|
||||
("14w-function-calling-mistral.py", PROMPT_WEATHER, EVAL_WEATHER, BOT_SPEAKS_FIRST),
|
||||
("14x-function-calling-openpipe.py", PROMPT_WEATHER, EVAL_WEATHER, BOT_SPEAKS_FIRST),
|
||||
# Currently not working.
|
||||
# ("14c-function-calling-together.py", PROMPT_WEATHER, EVAL_WEATHER, BOT_SPEAKS_FIRST),
|
||||
# ("14l-function-calling-deepseek.py", PROMPT_WEATHER, EVAL_WEATHER, BOT_SPEAKS_FIRST),
|
||||
|
||||
@@ -6,47 +6,13 @@
|
||||
|
||||
"""AWS Nova Sonic LLM adapter for Pipecat."""
|
||||
|
||||
import copy
|
||||
import json
|
||||
from dataclasses import dataclass
|
||||
from enum import Enum
|
||||
from typing import Any, Dict, List, Optional, TypedDict
|
||||
|
||||
from loguru import logger
|
||||
from typing import Any, Dict, List, TypedDict
|
||||
|
||||
from pipecat.adapters.base_llm_adapter import BaseLLMAdapter
|
||||
from pipecat.adapters.schemas.function_schema import FunctionSchema
|
||||
from pipecat.adapters.schemas.tools_schema import ToolsSchema
|
||||
from pipecat.processors.aggregators.llm_context import LLMContext, LLMContextMessage
|
||||
|
||||
|
||||
class Role(Enum):
|
||||
"""Roles supported in AWS Nova Sonic conversations.
|
||||
|
||||
Parameters:
|
||||
SYSTEM: System-level messages (not used in conversation history).
|
||||
USER: Messages sent by the user.
|
||||
ASSISTANT: Messages sent by the assistant.
|
||||
TOOL: Messages sent by tools (not used in conversation history).
|
||||
"""
|
||||
|
||||
SYSTEM = "SYSTEM"
|
||||
USER = "USER"
|
||||
ASSISTANT = "ASSISTANT"
|
||||
TOOL = "TOOL"
|
||||
|
||||
|
||||
@dataclass
|
||||
class AWSNovaSonicConversationHistoryMessage:
|
||||
"""A single message in AWS Nova Sonic conversation history.
|
||||
|
||||
Parameters:
|
||||
role: The role of the message sender (USER or ASSISTANT only).
|
||||
text: The text content of the message.
|
||||
"""
|
||||
|
||||
role: Role # only USER and ASSISTANT
|
||||
text: str
|
||||
from pipecat.processors.aggregators.llm_context import LLMContext
|
||||
|
||||
|
||||
class AWSNovaSonicLLMInvocationParams(TypedDict):
|
||||
@@ -55,9 +21,7 @@ class AWSNovaSonicLLMInvocationParams(TypedDict):
|
||||
This is a placeholder until support for universal LLMContext machinery is added for AWS Nova Sonic.
|
||||
"""
|
||||
|
||||
system_instruction: Optional[str]
|
||||
messages: List[AWSNovaSonicConversationHistoryMessage]
|
||||
tools: List[Dict[str, Any]]
|
||||
pass
|
||||
|
||||
|
||||
class AWSNovaSonicLLMAdapter(BaseLLMAdapter[AWSNovaSonicLLMInvocationParams]):
|
||||
@@ -70,7 +34,7 @@ class AWSNovaSonicLLMAdapter(BaseLLMAdapter[AWSNovaSonicLLMInvocationParams]):
|
||||
@property
|
||||
def id_for_llm_specific_messages(self) -> str:
|
||||
"""Get the identifier used in LLMSpecificMessage instances for AWS Nova Sonic."""
|
||||
return "aws-nova-sonic"
|
||||
raise NotImplementedError("Universal LLMContext is not yet supported for AWS Nova Sonic.")
|
||||
|
||||
def get_llm_invocation_params(self, context: LLMContext) -> AWSNovaSonicLLMInvocationParams:
|
||||
"""Get AWS Nova Sonic-specific LLM invocation parameters from a universal LLM context.
|
||||
@@ -83,13 +47,7 @@ class AWSNovaSonicLLMAdapter(BaseLLMAdapter[AWSNovaSonicLLMInvocationParams]):
|
||||
Returns:
|
||||
Dictionary of parameters for invoking AWS Nova Sonic's LLM API.
|
||||
"""
|
||||
messages = self._from_universal_context_messages(self.get_messages(context))
|
||||
return {
|
||||
"system_instruction": messages.system_instruction,
|
||||
"messages": messages.messages,
|
||||
# NOTE: LLMContext's tools are guaranteed to be a ToolsSchema (or NOT_GIVEN)
|
||||
"tools": self.from_standard_tools(context.tools) or [],
|
||||
}
|
||||
raise NotImplementedError("Universal LLMContext is not yet supported for AWS Nova Sonic.")
|
||||
|
||||
def get_messages_for_logging(self, context) -> List[Dict[str, Any]]:
|
||||
"""Get messages from a universal LLM context in a format ready for logging about AWS Nova Sonic.
|
||||
@@ -104,75 +62,7 @@ class AWSNovaSonicLLMAdapter(BaseLLMAdapter[AWSNovaSonicLLMInvocationParams]):
|
||||
Returns:
|
||||
List of messages in a format ready for logging about AWS Nova Sonic.
|
||||
"""
|
||||
return self._from_universal_context_messages(self.get_messages(context)).messages
|
||||
|
||||
@dataclass
|
||||
class ConvertedMessages:
|
||||
"""Container for Google-formatted messages converted from universal context."""
|
||||
|
||||
messages: List[AWSNovaSonicConversationHistoryMessage]
|
||||
system_instruction: Optional[str] = None
|
||||
|
||||
def _from_universal_context_messages(
|
||||
self, universal_context_messages: List[LLMContextMessage]
|
||||
) -> ConvertedMessages:
|
||||
system_instruction = None
|
||||
messages = []
|
||||
|
||||
# Bail if there are no messages
|
||||
if not universal_context_messages:
|
||||
return self.ConvertedMessages()
|
||||
|
||||
universal_context_messages = copy.deepcopy(universal_context_messages)
|
||||
|
||||
# If we have a "system" message as our first message, let's pull that out into "instruction"
|
||||
if universal_context_messages[0].get("role") == "system":
|
||||
system = universal_context_messages.pop(0)
|
||||
content = system.get("content")
|
||||
if isinstance(content, str):
|
||||
system_instruction = content
|
||||
elif isinstance(content, list):
|
||||
system_instruction = content[0].get("text")
|
||||
if system_instruction:
|
||||
self._system_instruction = system_instruction
|
||||
|
||||
# Process remaining messages to fill out conversation history.
|
||||
# Nova Sonic supports "user" and "assistant" messages in history.
|
||||
for universal_context_message in universal_context_messages:
|
||||
message = self._from_universal_context_message(universal_context_message)
|
||||
if message:
|
||||
messages.append(message)
|
||||
|
||||
return self.ConvertedMessages(messages=messages, system_instruction=system_instruction)
|
||||
|
||||
def _from_universal_context_message(self, message) -> AWSNovaSonicConversationHistoryMessage:
|
||||
"""Convert standard message format to Nova Sonic format.
|
||||
|
||||
Args:
|
||||
message: Standard message dictionary to convert.
|
||||
|
||||
Returns:
|
||||
Nova Sonic conversation history message, or None if not convertible.
|
||||
"""
|
||||
role = message.get("role")
|
||||
if message.get("role") == "user" or message.get("role") == "assistant":
|
||||
content = message.get("content")
|
||||
if isinstance(message.get("content"), list):
|
||||
content = ""
|
||||
for c in message.get("content"):
|
||||
if c.get("type") == "text":
|
||||
content += " " + c.get("text")
|
||||
else:
|
||||
logger.error(
|
||||
f"Unhandled content type in context message: {c.get('type')} - {message}"
|
||||
)
|
||||
# There won't be content if this is an assistant tool call entry.
|
||||
# We're ignoring those since they can't be loaded into AWS Nova Sonic conversation
|
||||
# history
|
||||
if content:
|
||||
return AWSNovaSonicConversationHistoryMessage(role=Role[role.upper()], text=content)
|
||||
# NOTE: we're ignoring messages with role "tool" since they can't be loaded into AWS Nova
|
||||
# Sonic conversation history
|
||||
raise NotImplementedError("Universal LLMContext is not yet supported for AWS Nova Sonic.")
|
||||
|
||||
@staticmethod
|
||||
def _to_aws_nova_sonic_function_format(function: FunctionSchema) -> Dict[str, Any]:
|
||||
|
||||
@@ -14,41 +14,20 @@ from pipecat.services.llm_service import LLMService
|
||||
|
||||
|
||||
class LLMSwitcher(ServiceSwitcher[StrategyType]):
|
||||
"""A pipeline that switches between different LLMs at runtime.
|
||||
|
||||
Example::
|
||||
|
||||
llm_switcher = LLMSwitcher(
|
||||
llms=[openai_llm, anthropic_llm],
|
||||
strategy_type=ServiceSwitcherStrategyManual
|
||||
)
|
||||
"""
|
||||
"""A pipeline that switches between different LLMs at runtime."""
|
||||
|
||||
def __init__(self, llms: List[LLMService], strategy_type: Type[StrategyType]):
|
||||
"""Initialize the service switcher with a list of LLMs and a switching strategy.
|
||||
|
||||
Args:
|
||||
llms: List of LLM services to switch between.
|
||||
strategy_type: The strategy class to use for switching between LLMs.
|
||||
"""
|
||||
"""Initialize the service switcher with a list of LLMs and a switching strategy."""
|
||||
super().__init__(llms, strategy_type)
|
||||
|
||||
@property
|
||||
def llms(self) -> List[LLMService]:
|
||||
"""Get the list of LLMs managed by this switcher.
|
||||
|
||||
Returns:
|
||||
List of LLM services managed by this switcher.
|
||||
"""
|
||||
"""Get the list of LLMs managed by this switcher."""
|
||||
return self.services
|
||||
|
||||
@property
|
||||
def active_llm(self) -> Optional[LLMService]:
|
||||
"""Get the currently active LLM.
|
||||
|
||||
Returns:
|
||||
The currently active LLM service, or None if no LLM is active.
|
||||
"""
|
||||
"""Get the currently active LLM, if any."""
|
||||
return self.strategy.active_service
|
||||
|
||||
async def run_inference(self, context: LLMContext) -> Optional[str]:
|
||||
|
||||
@@ -70,15 +70,11 @@ class PipelineRunner(BaseObject):
|
||||
"""
|
||||
logger.debug(f"Runner {self} started running {task}")
|
||||
self._tasks[task.name] = task
|
||||
|
||||
# PipelineTask handles asyncio.CancelledError to shutdown the pipeline
|
||||
# properly and re-raises it in case there's more cleanup to do.
|
||||
params = PipelineTaskParams(loop=self._loop)
|
||||
try:
|
||||
params = PipelineTaskParams(loop=self._loop)
|
||||
await task.run(params)
|
||||
except asyncio.CancelledError:
|
||||
pass
|
||||
|
||||
await self._cancel()
|
||||
del self._tasks[task.name]
|
||||
|
||||
# Cleanup base object.
|
||||
|
||||
@@ -21,22 +21,10 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
|
||||
|
||||
|
||||
class ServiceSwitcherStrategy:
|
||||
"""Base class for service switching strategies.
|
||||
|
||||
Note:
|
||||
Strategy classes are instantiated internally by ServiceSwitcher.
|
||||
Developers should pass the strategy class (not an instance) to ServiceSwitcher.
|
||||
"""
|
||||
"""Base class for service switching strategies."""
|
||||
|
||||
def __init__(self, services: List[FrameProcessor]):
|
||||
"""Initialize the service switcher strategy with a list of services.
|
||||
|
||||
Note:
|
||||
This is called internally by ServiceSwitcher. Do not instantiate directly.
|
||||
|
||||
Args:
|
||||
services: List of frame processors to switch between.
|
||||
"""
|
||||
"""Initialize the service switcher strategy with a list of services."""
|
||||
self.services = services
|
||||
self.active_service: Optional[FrameProcessor] = None
|
||||
|
||||
@@ -58,24 +46,10 @@ class ServiceSwitcherStrategyManual(ServiceSwitcherStrategy):
|
||||
|
||||
This strategy allows the user to manually select which service is active.
|
||||
The initial active service is the first one in the list.
|
||||
|
||||
Example::
|
||||
|
||||
stt_switcher = ServiceSwitcher(
|
||||
services=[stt_1, stt_2],
|
||||
strategy_type=ServiceSwitcherStrategyManual
|
||||
)
|
||||
"""
|
||||
|
||||
def __init__(self, services: List[FrameProcessor]):
|
||||
"""Initialize the manual service switcher strategy with a list of services.
|
||||
|
||||
Note:
|
||||
This is called internally by ServiceSwitcher. Do not instantiate directly.
|
||||
|
||||
Args:
|
||||
services: List of frame processors to switch between.
|
||||
"""
|
||||
"""Initialize the manual service switcher strategy with a list of services."""
|
||||
super().__init__(services)
|
||||
self.active_service = services[0] if services else None
|
||||
|
||||
@@ -111,12 +85,7 @@ class ServiceSwitcher(ParallelPipeline, Generic[StrategyType]):
|
||||
"""A pipeline that switches between different services at runtime."""
|
||||
|
||||
def __init__(self, services: List[FrameProcessor], strategy_type: Type[StrategyType]):
|
||||
"""Initialize the service switcher with a list of services and a switching strategy.
|
||||
|
||||
Args:
|
||||
services: List of frame processors to switch between.
|
||||
strategy_type: The strategy class to use for switching between services.
|
||||
"""
|
||||
"""Initialize the service switcher with a list of services and a switching strategy."""
|
||||
strategy = strategy_type(services)
|
||||
super().__init__(*self._make_pipeline_definitions(services, strategy))
|
||||
self.services = services
|
||||
@@ -131,20 +100,14 @@ class ServiceSwitcher(ParallelPipeline, Generic[StrategyType]):
|
||||
active_service: FrameProcessor,
|
||||
direction: FrameDirection,
|
||||
):
|
||||
"""Initialize the service switcher filter with a strategy and direction.
|
||||
|
||||
Args:
|
||||
wrapped_service: The service that this filter wraps.
|
||||
active_service: The currently active service.
|
||||
direction: The direction of frame flow to filter.
|
||||
"""
|
||||
self._wrapped_service = wrapped_service
|
||||
self._active_service = active_service
|
||||
"""Initialize the service switcher filter with a strategy and direction."""
|
||||
|
||||
async def filter(_: Frame) -> bool:
|
||||
return self._wrapped_service == self._active_service
|
||||
|
||||
super().__init__(filter, direction, filter_system_frames=True)
|
||||
super().__init__(filter, direction)
|
||||
self._wrapped_service = wrapped_service
|
||||
self._active_service = active_service
|
||||
|
||||
async def process_frame(self, frame, direction):
|
||||
"""Process a frame through the filter, handling special internal filter-updating frames."""
|
||||
|
||||
@@ -269,9 +269,6 @@ class PipelineTask(BasePipelineTask):
|
||||
# StopFrame) has been received at the end of the pipeline.
|
||||
self._pipeline_end_event = asyncio.Event()
|
||||
|
||||
# This event is set when the pipeline truly finishes.
|
||||
self._pipeline_finished_event = asyncio.Event()
|
||||
|
||||
# This is the final pipeline. It is composed of a source processor,
|
||||
# followed by the user pipeline, and ending with a sink processor. The
|
||||
# source allows us to receive and react to upstream frames, and the sink
|
||||
@@ -404,7 +401,11 @@ class PipelineTask(BasePipelineTask):
|
||||
await self.queue_frame(EndFrame())
|
||||
|
||||
async def cancel(self):
|
||||
"""Request the running pipeline to cancel."""
|
||||
"""Immediately stop the running pipeline.
|
||||
|
||||
Cancels all running tasks and stops frame processing without
|
||||
waiting for completion.
|
||||
"""
|
||||
if not self._finished:
|
||||
await self._cancel()
|
||||
|
||||
@@ -416,38 +417,51 @@ class PipelineTask(BasePipelineTask):
|
||||
"""
|
||||
if self.has_finished():
|
||||
return
|
||||
|
||||
# Setup processors.
|
||||
await self._setup(params)
|
||||
|
||||
# Create all main tasks and wait for the main push task. This is the
|
||||
# task that pushes frames to the very beginning of our pipeline (i.e. to
|
||||
# our controlled source processor).
|
||||
await self._create_tasks()
|
||||
|
||||
cleanup_pipeline = True
|
||||
try:
|
||||
# Wait for pipeline to finish.
|
||||
await self._wait_for_pipeline_finished()
|
||||
# Setup processors.
|
||||
await self._setup(params)
|
||||
|
||||
# Create all main tasks and wait of the main push task. This is the
|
||||
# task that pushes frames to the very beginning of our pipeline (our
|
||||
# controlled source processor).
|
||||
push_task = await self._create_tasks()
|
||||
await push_task
|
||||
|
||||
# We have already cleaned up the pipeline inside the task.
|
||||
cleanup_pipeline = False
|
||||
|
||||
# Pipeline has finished nicely.
|
||||
self._finished = True
|
||||
except asyncio.CancelledError:
|
||||
logger.debug(f"Pipeline task {self} got cancelled from outside...")
|
||||
# We have been cancelled from outside, let's just cancel everything.
|
||||
await self._cancel()
|
||||
# Wait again for pipeline to finish. This time we have really
|
||||
# cancelled, so it should really finish.
|
||||
await self._wait_for_pipeline_finished()
|
||||
# Re-raise in case there's more cleanup to do.
|
||||
# Raise exception back to the pipeline runner so it can cancel this
|
||||
# task properly.
|
||||
raise
|
||||
finally:
|
||||
# We can reach this point for different reasons:
|
||||
#
|
||||
# 1. The pipeline task has finished (try case).
|
||||
# 2. By an asyncio task cancellation (except case).
|
||||
logger.debug(f"Pipeline task {self} is finishing...")
|
||||
await self._cancel_tasks()
|
||||
if self._check_dangling_tasks:
|
||||
self._print_dangling_tasks()
|
||||
self._finished = True
|
||||
logger.debug(f"Pipeline task {self} has finished")
|
||||
# 1. The task has finished properly (e.g. `EndFrame`).
|
||||
# 2. By calling `PipelineTask.cancel()`.
|
||||
# 3. By asyncio task cancellation.
|
||||
#
|
||||
# Case (1) will execute the code below without issues because
|
||||
# `self._finished` is true.
|
||||
#
|
||||
# Case (2) will execute the code below without issues because
|
||||
# `self._cancelled` is true.
|
||||
#
|
||||
# Case (3) will raise the exception above (because we are cancelling
|
||||
# the asyncio task). This will be then captured by the
|
||||
# `PipelineRunner` which will call `PipelineTask.cancel()` and
|
||||
# therefore becoming case (2).
|
||||
if self._finished or self._cancelled:
|
||||
logger.debug(f"Pipeline task {self} is finishing cleanup...")
|
||||
await self._cancel_tasks()
|
||||
await self._cleanup(cleanup_pipeline)
|
||||
if self._check_dangling_tasks:
|
||||
self._print_dangling_tasks()
|
||||
self._finished = True
|
||||
logger.debug(f"Pipeline task {self} has finished")
|
||||
|
||||
async def queue_frame(self, frame: Frame):
|
||||
"""Queue a single frame to be pushed down the pipeline.
|
||||
@@ -475,7 +489,19 @@ class PipelineTask(BasePipelineTask):
|
||||
if not self._cancelled:
|
||||
logger.debug(f"Cancelling pipeline task {self}")
|
||||
self._cancelled = True
|
||||
await self.queue_frame(CancelFrame())
|
||||
cancel_frame = CancelFrame()
|
||||
# Make sure everything is cleaned up downstream. This is sent
|
||||
# out-of-band from the main streaming task which is what we want since
|
||||
# we want to cancel right away.
|
||||
await self._pipeline.queue_frame(cancel_frame)
|
||||
# Wait for CancelFrame to make it through the pipeline.
|
||||
await self._wait_for_pipeline_end(cancel_frame)
|
||||
# Only cancel the push task, we don't want to be able to process any
|
||||
# other frame after cancel. Everything else will be cancelled in
|
||||
# run().
|
||||
if self._process_push_task:
|
||||
await self._task_manager.cancel_task(self._process_push_task)
|
||||
self._process_push_task = None
|
||||
|
||||
async def _create_tasks(self):
|
||||
"""Create and start all pipeline processing tasks."""
|
||||
@@ -577,17 +603,6 @@ class PipelineTask(BasePipelineTask):
|
||||
|
||||
self._pipeline_end_event.clear()
|
||||
|
||||
# We are really done.
|
||||
self._pipeline_finished_event.set()
|
||||
|
||||
async def _wait_for_pipeline_finished(self):
|
||||
await self._pipeline_finished_event.wait()
|
||||
self._pipeline_finished_event.clear()
|
||||
# Make sure we wait for the main task to complete.
|
||||
if self._process_push_task:
|
||||
await self._process_push_task
|
||||
self._process_push_task = None
|
||||
|
||||
async def _setup(self, params: PipelineTaskParams):
|
||||
"""Set up the pipeline task and all processors."""
|
||||
mgr_params = TaskManagerParams(loop=params.loop)
|
||||
|
||||
@@ -15,10 +15,9 @@ service-specific adapter.
|
||||
"""
|
||||
|
||||
import base64
|
||||
import copy
|
||||
import io
|
||||
from dataclasses import dataclass
|
||||
from typing import TYPE_CHECKING, Any, List, Optional, TypeAlias, Union
|
||||
from typing import Any, List, Optional, TypeAlias, Union
|
||||
|
||||
from loguru import logger
|
||||
from openai._types import NOT_GIVEN as OPEN_AI_NOT_GIVEN
|
||||
@@ -32,9 +31,6 @@ from PIL import Image
|
||||
from pipecat.adapters.schemas.tools_schema import ToolsSchema
|
||||
from pipecat.frames.frames import AudioRawFrame
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
|
||||
# "Re-export" types from OpenAI that we're using as universal context types.
|
||||
# NOTE: if universal message types need to someday diverge from OpenAI's, we
|
||||
# should consider managing our own definitions. But we should do so carefully,
|
||||
@@ -69,26 +65,6 @@ class LLMContext:
|
||||
and content formatting.
|
||||
"""
|
||||
|
||||
@staticmethod
|
||||
def from_openai_context(openai_context: "OpenAILLMContext") -> "LLMContext":
|
||||
"""Create a universal LLM context from an OpenAI-specific context.
|
||||
|
||||
NOTE: this should only be used internally, for facilitating migration
|
||||
from OpenAILLMContext to LLMContext. New user code should use
|
||||
LLMContext directly.
|
||||
|
||||
Args:
|
||||
openai_context: The OpenAI LLM context to convert.
|
||||
|
||||
Returns:
|
||||
New LLMContext instance with converted messages and settings.
|
||||
"""
|
||||
return LLMContext(
|
||||
messages=openai_context.get_messages(),
|
||||
tools=openai_context.tools,
|
||||
tool_choice=openai_context.tool_choice,
|
||||
)
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
messages: Optional[List[LLMContextMessage]] = None,
|
||||
@@ -106,19 +82,6 @@ class LLMContext:
|
||||
self._tools: ToolsSchema | NotGiven = LLMContext._normalize_and_validate_tools(tools)
|
||||
self._tool_choice: LLMContextToolChoice | NotGiven = tool_choice
|
||||
|
||||
@property
|
||||
def messages(self) -> List[LLMContextMessage]:
|
||||
"""Get the current messages list.
|
||||
|
||||
NOTE: This is equivalent to calling `get_messages()` with no filter. If
|
||||
you want to filter out LLM-specific messages that don't pertain to your
|
||||
LLM, use `get_messages()` directly.
|
||||
|
||||
Returns:
|
||||
List of conversation messages.
|
||||
"""
|
||||
return self.get_messages()
|
||||
|
||||
def get_messages(self, llm_specific_filter: Optional[str] = None) -> List[LLMContextMessage]:
|
||||
"""Get the current messages list.
|
||||
|
||||
@@ -126,8 +89,7 @@ class LLMContext:
|
||||
llm_specific_filter: Optional filter to return LLM-specific
|
||||
messages for the given LLM, in addition to the standard
|
||||
messages. If messages end up being filtered, an error will be
|
||||
logged; this is intended to catch accidental use of
|
||||
incompatible LLM-specific messages.
|
||||
logged.
|
||||
|
||||
Returns:
|
||||
List of conversation messages.
|
||||
|
||||
@@ -12,7 +12,7 @@ allowing for flexible frame filtering logic in processing pipelines.
|
||||
|
||||
from typing import Awaitable, Callable
|
||||
|
||||
from pipecat.frames.frames import CancelFrame, EndFrame, Frame, StartFrame, SystemFrame
|
||||
from pipecat.frames.frames import EndFrame, Frame, SystemFrame
|
||||
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
|
||||
|
||||
|
||||
@@ -28,7 +28,6 @@ class FunctionFilter(FrameProcessor):
|
||||
self,
|
||||
filter: Callable[[Frame], Awaitable[bool]],
|
||||
direction: FrameDirection = FrameDirection.DOWNSTREAM,
|
||||
filter_system_frames: bool = False,
|
||||
):
|
||||
"""Initialize the function filter.
|
||||
|
||||
@@ -37,32 +36,22 @@ class FunctionFilter(FrameProcessor):
|
||||
frame should pass through, False otherwise.
|
||||
direction: The direction to apply filtering. Only frames moving in
|
||||
this direction will be filtered. Defaults to DOWNSTREAM.
|
||||
filter_system_frames: Whether to filter system frames. Defaults to False.
|
||||
"""
|
||||
super().__init__()
|
||||
self._filter = filter
|
||||
self._direction = direction
|
||||
self._filter_system_frames = filter_system_frames
|
||||
|
||||
#
|
||||
# Frame processor
|
||||
#
|
||||
|
||||
# Ignore system frames, end frames and frames that are not following the
|
||||
# direction of this gate
|
||||
def _should_passthrough_frame(self, frame, direction):
|
||||
"""Check if a frame should pass through without filtering."""
|
||||
# Always passthrough frames in the wrong direction
|
||||
if direction != self._direction:
|
||||
return True
|
||||
|
||||
# Always passthrough lifecycle frames
|
||||
if isinstance(frame, (StartFrame, EndFrame, CancelFrame)):
|
||||
return True
|
||||
|
||||
# If not filtering system frames, passthrough all other system frames
|
||||
if not self._filter_system_frames and isinstance(frame, SystemFrame):
|
||||
return True
|
||||
|
||||
return False
|
||||
# Ignore system frames, end frames and frames that are not following the
|
||||
# direction of this gate
|
||||
return isinstance(frame, (SystemFrame, EndFrame)) or direction != self._direction
|
||||
|
||||
async def process_frame(self, frame: Frame, direction: FrameDirection):
|
||||
"""Process a frame through the filter.
|
||||
|
||||
@@ -1018,7 +1018,6 @@ class RTVIObserver(BaseObserver):
|
||||
|
||||
if (
|
||||
isinstance(frame, (UserStartedSpeakingFrame, UserStoppedSpeakingFrame))
|
||||
and (direction == FrameDirection.DOWNSTREAM)
|
||||
and self._params.user_speaking_enabled
|
||||
):
|
||||
await self._handle_interruptions(frame)
|
||||
|
||||
@@ -76,14 +76,12 @@ class DailyRoomConfig(BaseModel):
|
||||
async def configure(
|
||||
aiohttp_session: aiohttp.ClientSession,
|
||||
*,
|
||||
api_key: Optional[str] = None,
|
||||
room_exp_duration: Optional[float] = 2.0,
|
||||
token_exp_duration: Optional[float] = 2.0,
|
||||
sip_caller_phone: Optional[str] = None,
|
||||
sip_enable_video: Optional[bool] = False,
|
||||
sip_num_endpoints: Optional[int] = 1,
|
||||
sip_codecs: Optional[Dict[str, List[str]]] = None,
|
||||
room_properties: Optional[DailyRoomProperties] = None,
|
||||
) -> DailyRoomConfig:
|
||||
"""Configure Daily room URL and token with optional SIP capabilities.
|
||||
|
||||
@@ -93,7 +91,6 @@ async def configure(
|
||||
|
||||
Args:
|
||||
aiohttp_session: HTTP session for making API requests.
|
||||
api_key: Daily API key.
|
||||
room_exp_duration: Room expiration time in hours.
|
||||
token_exp_duration: Token expiration time in hours.
|
||||
sip_caller_phone: Phone number or identifier for SIP display name.
|
||||
@@ -102,10 +99,6 @@ async def configure(
|
||||
sip_num_endpoints: Number of allowed SIP endpoints.
|
||||
sip_codecs: Codecs to support for audio and video. If None, uses Daily defaults.
|
||||
Example: {"audio": ["OPUS"], "video": ["H264"]}
|
||||
room_properties: Optional DailyRoomProperties to use instead of building from
|
||||
individual parameters. When provided, this overrides room_exp_duration and
|
||||
SIP-related parameters. If not provided, properties are built from the
|
||||
individual parameters as before.
|
||||
|
||||
Returns:
|
||||
DailyRoomConfig: Object with room_url, token, and optional sip_endpoint.
|
||||
@@ -122,48 +115,18 @@ async def configure(
|
||||
# SIP-enabled room
|
||||
sip_config = await configure(session, sip_caller_phone="+15551234567")
|
||||
print(f"SIP endpoint: {sip_config.sip_endpoint}")
|
||||
|
||||
# Custom room properties with recording enabled
|
||||
custom_props = DailyRoomProperties(
|
||||
enable_recording="cloud",
|
||||
max_participants=2,
|
||||
)
|
||||
config = await configure(session, room_properties=custom_props)
|
||||
"""
|
||||
# Check for required API key
|
||||
api_key = api_key or os.getenv("DAILY_API_KEY")
|
||||
api_key = os.getenv("DAILY_API_KEY")
|
||||
if not api_key:
|
||||
raise Exception(
|
||||
"DAILY_API_KEY environment variable is required. "
|
||||
"Get your API key from https://dashboard.daily.co/developers"
|
||||
)
|
||||
|
||||
# Warn if both room_properties and individual parameters are provided
|
||||
if room_properties is not None:
|
||||
individual_params_provided = any(
|
||||
[
|
||||
room_exp_duration != 2.0,
|
||||
token_exp_duration != 2.0,
|
||||
sip_caller_phone is not None,
|
||||
sip_enable_video is not False,
|
||||
sip_num_endpoints != 1,
|
||||
sip_codecs is not None,
|
||||
]
|
||||
)
|
||||
if individual_params_provided:
|
||||
logger.warning(
|
||||
"Both room_properties and individual parameters (room_exp_duration, token_exp_duration, "
|
||||
"sip_*) were provided. The room_properties will be used and individual parameters "
|
||||
"will be ignored."
|
||||
)
|
||||
|
||||
# Determine if SIP mode is enabled
|
||||
sip_enabled = sip_caller_phone is not None
|
||||
|
||||
# If room_properties is provided, check if it has SIP configuration
|
||||
if room_properties and room_properties.sip:
|
||||
sip_enabled = True
|
||||
|
||||
daily_rest_helper = DailyRESTHelper(
|
||||
daily_api_key=api_key,
|
||||
daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
|
||||
@@ -187,29 +150,27 @@ async def configure(
|
||||
room_name = f"{room_prefix}-{uuid.uuid4().hex[:8]}"
|
||||
logger.info(f"Creating new Daily room: {room_name}")
|
||||
|
||||
# Use provided room_properties or build from parameters
|
||||
if room_properties is None:
|
||||
# Calculate expiration time
|
||||
expiration_time = time.time() + (room_exp_duration * 60 * 60)
|
||||
# Calculate expiration time
|
||||
expiration_time = time.time() + (room_exp_duration * 60 * 60)
|
||||
|
||||
# Create room properties
|
||||
room_properties = DailyRoomProperties(
|
||||
exp=expiration_time,
|
||||
eject_at_room_exp=True,
|
||||
# Create room properties
|
||||
room_properties = DailyRoomProperties(
|
||||
exp=expiration_time,
|
||||
eject_at_room_exp=True,
|
||||
)
|
||||
|
||||
# Add SIP configuration if enabled
|
||||
if sip_enabled:
|
||||
sip_params = DailyRoomSipParams(
|
||||
display_name=sip_caller_phone,
|
||||
video=sip_enable_video,
|
||||
sip_mode="dial-in",
|
||||
num_endpoints=sip_num_endpoints,
|
||||
codecs=sip_codecs,
|
||||
)
|
||||
|
||||
# Add SIP configuration if enabled
|
||||
if sip_enabled:
|
||||
sip_params = DailyRoomSipParams(
|
||||
display_name=sip_caller_phone,
|
||||
video=sip_enable_video,
|
||||
sip_mode="dial-in",
|
||||
num_endpoints=sip_num_endpoints,
|
||||
codecs=sip_codecs,
|
||||
)
|
||||
room_properties.sip = sip_params
|
||||
room_properties.enable_dialout = True # Enable outbound calls if needed
|
||||
room_properties.start_video_off = not sip_enable_video # Voice-only by default
|
||||
room_properties.sip = sip_params
|
||||
room_properties.enable_dialout = True # Enable outbound calls if needed
|
||||
room_properties.start_video_off = not sip_enable_video # Voice-only by default
|
||||
|
||||
# Create room parameters
|
||||
room_params = DailyRoomParams(name=room_name, properties=room_properties)
|
||||
|
||||
@@ -70,19 +70,16 @@ import asyncio
|
||||
import mimetypes
|
||||
import os
|
||||
import sys
|
||||
import uuid
|
||||
from contextlib import asynccontextmanager
|
||||
from http import HTTPMethod
|
||||
from pathlib import Path
|
||||
from typing import Any, Dict, List, Optional, TypedDict
|
||||
from typing import Optional
|
||||
|
||||
import aiohttp
|
||||
from fastapi.responses import FileResponse, Response
|
||||
from fastapi.responses import FileResponse
|
||||
from loguru import logger
|
||||
|
||||
from pipecat.runner.types import (
|
||||
DailyRunnerArguments,
|
||||
RunnerArguments,
|
||||
SmallWebRTCRunnerArguments,
|
||||
WebSocketRunnerArguments,
|
||||
)
|
||||
@@ -169,7 +166,6 @@ def _create_server_app(
|
||||
host: str = "localhost",
|
||||
proxy: str,
|
||||
esp32_mode: bool = False,
|
||||
whatsapp_enabled: bool = False,
|
||||
folder: Optional[str] = None,
|
||||
):
|
||||
"""Create FastAPI app with transport-specific routes."""
|
||||
@@ -186,8 +182,7 @@ def _create_server_app(
|
||||
# Set up transport-specific routes
|
||||
if transport_type == "webrtc":
|
||||
_setup_webrtc_routes(app, esp32_mode=esp32_mode, host=host, folder=folder)
|
||||
if whatsapp_enabled:
|
||||
_setup_whatsapp_routes(app)
|
||||
_setup_whatsapp_routes(app)
|
||||
elif transport_type == "daily":
|
||||
_setup_daily_routes(app)
|
||||
elif transport_type in TELEPHONY_TRANSPORTS:
|
||||
@@ -205,10 +200,8 @@ def _setup_webrtc_routes(
|
||||
try:
|
||||
from pipecat_ai_small_webrtc_prebuilt.frontend import SmallWebRTCPrebuiltUI
|
||||
|
||||
from pipecat.transports.smallwebrtc.connection import IceServer, SmallWebRTCConnection
|
||||
from pipecat.transports.smallwebrtc.connection import SmallWebRTCConnection
|
||||
from pipecat.transports.smallwebrtc.request_handler import (
|
||||
IceCandidate,
|
||||
SmallWebRTCPatchRequest,
|
||||
SmallWebRTCRequest,
|
||||
SmallWebRTCRequestHandler,
|
||||
)
|
||||
@@ -216,16 +209,6 @@ def _setup_webrtc_routes(
|
||||
logger.error(f"WebRTC transport dependencies not installed: {e}")
|
||||
return
|
||||
|
||||
class IceConfig(TypedDict):
|
||||
iceServers: List[IceServer]
|
||||
|
||||
class StartBotResult(TypedDict, total=False):
|
||||
sessionId: str
|
||||
iceConfig: Optional[IceConfig]
|
||||
|
||||
# In-memory store of active sessions: session_id -> session info
|
||||
active_sessions: Dict[str, Dict[str, Any]] = {}
|
||||
|
||||
# Mount the frontend
|
||||
app.mount("/client", SmallWebRTCPrebuiltUI)
|
||||
|
||||
@@ -271,74 +254,6 @@ def _setup_webrtc_routes(
|
||||
)
|
||||
return answer
|
||||
|
||||
@app.patch("/api/offer")
|
||||
async def ice_candidate(request: SmallWebRTCPatchRequest):
|
||||
"""Handle WebRTC new ice candidate requests."""
|
||||
logger.debug(f"Received patch request: {request}")
|
||||
await small_webrtc_handler.handle_patch_request(request)
|
||||
return {"status": "success"}
|
||||
|
||||
@app.post("/start")
|
||||
async def rtvi_start(request: Request):
|
||||
"""Mimic Pipecat Cloud's /start endpoint."""
|
||||
# Parse the request body
|
||||
try:
|
||||
request_data = await request.json()
|
||||
logger.debug(f"Received request: {request_data}")
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to parse request body: {e}")
|
||||
request_data = {}
|
||||
|
||||
# Store session info immediately in memory, replicate the behavior expected on Pipecat Cloud
|
||||
session_id = str(uuid.uuid4())
|
||||
active_sessions[session_id] = request_data
|
||||
|
||||
result: StartBotResult = {"sessionId": session_id}
|
||||
if request_data.get("enableDefaultIceServers"):
|
||||
result["iceConfig"] = IceConfig(
|
||||
iceServers=[IceServer(urls="stun:stun.l.google.com:19302")]
|
||||
)
|
||||
|
||||
return result
|
||||
|
||||
@app.api_route(
|
||||
"/sessions/{session_id}/{path:path}",
|
||||
methods=["GET", "POST", "PUT", "PATCH", "DELETE"],
|
||||
)
|
||||
async def proxy_request(
|
||||
session_id: str, path: str, request: Request, background_tasks: BackgroundTasks
|
||||
):
|
||||
"""Mimic Pipecat Cloud's proxy."""
|
||||
active_session = active_sessions.get(session_id)
|
||||
if active_session is None:
|
||||
return Response(content="Invalid or not-yet-ready session_id", status_code=404)
|
||||
|
||||
if path.endswith("api/offer"):
|
||||
# Parse the request body and convert to SmallWebRTCRequest
|
||||
try:
|
||||
request_data = await request.json()
|
||||
if request.method == HTTPMethod.POST.value:
|
||||
webrtc_request = SmallWebRTCRequest(
|
||||
sdp=request_data["sdp"],
|
||||
type=request_data["type"],
|
||||
pc_id=request_data.get("pc_id"),
|
||||
restart_pc=request_data.get("restart_pc"),
|
||||
request_data=request_data,
|
||||
)
|
||||
return await offer(webrtc_request, background_tasks)
|
||||
elif request.method == HTTPMethod.PATCH.value:
|
||||
patch_request = SmallWebRTCPatchRequest(
|
||||
pc_id=request_data["pc_id"],
|
||||
candidates=[IceCandidate(**c) for c in request_data.get("candidates", [])],
|
||||
)
|
||||
return await ice_candidate(patch_request)
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to parse WebRTC request: {e}")
|
||||
return Response(content="Invalid WebRTC request", status_code=400)
|
||||
|
||||
logger.info(f"Received request for path: {path}")
|
||||
return Response(status_code=200)
|
||||
|
||||
@asynccontextmanager
|
||||
async def smallwebrtc_lifespan(app: FastAPI):
|
||||
"""Manage FastAPI application lifecycle and cleanup connections."""
|
||||
@@ -374,29 +289,6 @@ def _add_lifespan_to_app(app: FastAPI, new_lifespan):
|
||||
|
||||
def _setup_whatsapp_routes(app: FastAPI):
|
||||
"""Set up WebRTC-specific routes."""
|
||||
WHATSAPP_APP_SECRET = os.getenv("WHATSAPP_APP_SECRET")
|
||||
WHATSAPP_PHONE_NUMBER_ID = os.getenv("WHATSAPP_PHONE_NUMBER_ID")
|
||||
WHATSAPP_TOKEN = os.getenv("WHATSAPP_TOKEN")
|
||||
WHATSAPP_WEBHOOK_VERIFICATION_TOKEN = os.getenv("WHATSAPP_WEBHOOK_VERIFICATION_TOKEN")
|
||||
|
||||
if not all(
|
||||
[
|
||||
WHATSAPP_APP_SECRET,
|
||||
WHATSAPP_PHONE_NUMBER_ID,
|
||||
WHATSAPP_TOKEN,
|
||||
WHATSAPP_WEBHOOK_VERIFICATION_TOKEN,
|
||||
]
|
||||
):
|
||||
logger.error(
|
||||
"""Missing required environment variables for WhatsApp transport:
|
||||
WHATSAPP_APP_SECRET
|
||||
WHATSAPP_PHONE_NUMBER_ID
|
||||
WHATSAPP_TOKEN
|
||||
WHATSAPP_WEBHOOK_VERIFICATION_TOKEN
|
||||
"""
|
||||
)
|
||||
return
|
||||
|
||||
try:
|
||||
from pipecat_ai_small_webrtc_prebuilt.frontend import SmallWebRTCPrebuiltUI
|
||||
|
||||
@@ -408,7 +300,24 @@ def _setup_whatsapp_routes(app: FastAPI):
|
||||
from pipecat.transports.whatsapp.api import WhatsAppWebhookRequest
|
||||
from pipecat.transports.whatsapp.client import WhatsAppClient
|
||||
except ImportError as e:
|
||||
logger.error(f"WhatsApp transport dependencies not installed: {e}")
|
||||
logger.error(f"WebRTC transport dependencies not installed: {e}")
|
||||
return
|
||||
|
||||
WHATSAPP_TOKEN = os.getenv("WHATSAPP_TOKEN")
|
||||
WHATSAPP_PHONE_NUMBER_ID = os.getenv("WHATSAPP_PHONE_NUMBER_ID")
|
||||
WHATSAPP_WEBHOOK_VERIFICATION_TOKEN = os.getenv("WHATSAPP_WEBHOOK_VERIFICATION_TOKEN")
|
||||
WHATSAPP_APP_SECRET = os.getenv("WHATSAPP_APP_SECRET")
|
||||
|
||||
if not all(
|
||||
[
|
||||
WHATSAPP_TOKEN,
|
||||
WHATSAPP_PHONE_NUMBER_ID,
|
||||
WHATSAPP_WEBHOOK_VERIFICATION_TOKEN,
|
||||
]
|
||||
):
|
||||
logger.debug(
|
||||
"Missing required environment variables for WhatsApp transport. Keeping it disabled."
|
||||
)
|
||||
return
|
||||
|
||||
# Global WhatsApp client instance
|
||||
@@ -530,9 +439,9 @@ def _setup_daily_routes(app: FastAPI):
|
||||
"""Set up Daily-specific routes."""
|
||||
|
||||
@app.get("/")
|
||||
async def create_room_and_start_agent():
|
||||
async def start_agent():
|
||||
"""Launch a Daily bot and redirect to room."""
|
||||
print("Starting bot with Daily transport and redirecting to Daily room")
|
||||
print("Starting bot with Daily transport")
|
||||
|
||||
import aiohttp
|
||||
|
||||
@@ -547,11 +456,11 @@ def _setup_daily_routes(app: FastAPI):
|
||||
asyncio.create_task(bot_module.bot(runner_args))
|
||||
return RedirectResponse(room_url)
|
||||
|
||||
@app.post("/start")
|
||||
async def start_agent(request: Request):
|
||||
"""Handler for /start endpoints.
|
||||
async def _handle_rtvi_request(request: Request):
|
||||
"""Common handler for both /start and /connect endpoints.
|
||||
|
||||
Expects POST body like::
|
||||
|
||||
{
|
||||
"createDailyRoom": true,
|
||||
"dailyRoomProperties": { "start_video_off": true },
|
||||
@@ -568,32 +477,47 @@ def _setup_daily_routes(app: FastAPI):
|
||||
logger.error(f"Failed to parse request body: {e}")
|
||||
request_data = {}
|
||||
|
||||
create_daily_room = request_data.get("createDailyRoom", False)
|
||||
body = request_data.get("body", {})
|
||||
# Extract the body data that should be passed to the bot
|
||||
# This mimics Pipecat Cloud's behavior
|
||||
bot_body = request_data.get("body", {})
|
||||
|
||||
bot_module = _get_bot_module()
|
||||
|
||||
result = None
|
||||
if create_daily_room:
|
||||
import aiohttp
|
||||
|
||||
from pipecat.runner.daily import configure
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
room_url, token = await configure(session)
|
||||
runner_args = DailyRunnerArguments(room_url=room_url, token=token, body=body)
|
||||
result = {
|
||||
"dailyRoom": room_url,
|
||||
"dailyToken": token,
|
||||
"sessionId": str(uuid.uuid4()),
|
||||
}
|
||||
# Log the extracted body data for debugging
|
||||
if bot_body:
|
||||
logger.info(f"Extracted body data for bot: {bot_body}")
|
||||
else:
|
||||
runner_args = RunnerArguments(body=body)
|
||||
logger.debug("No body data provided in request")
|
||||
|
||||
# Start the bot in the background
|
||||
asyncio.create_task(bot_module.bot(runner_args))
|
||||
import aiohttp
|
||||
|
||||
return result
|
||||
from pipecat.runner.daily import configure
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
room_url, token = await configure(session)
|
||||
|
||||
# Start the bot in the background with extracted body data
|
||||
bot_module = _get_bot_module()
|
||||
runner_args = DailyRunnerArguments(room_url=room_url, token=token, body=bot_body)
|
||||
asyncio.create_task(bot_module.bot(runner_args))
|
||||
# Match PCC /start endpoint response format:
|
||||
return {"dailyRoom": room_url, "dailyToken": token}
|
||||
|
||||
@app.post("/start")
|
||||
async def rtvi_start(request: Request):
|
||||
"""Launch a Daily bot and return connection info for RTVI clients."""
|
||||
return await _handle_rtvi_request(request)
|
||||
|
||||
@app.post("/connect")
|
||||
async def rtvi_connect(request: Request):
|
||||
"""Launch a Daily bot and return connection info for RTVI clients.
|
||||
|
||||
.. deprecated:: 0.0.78
|
||||
Use /start instead. This endpoint will be removed in a future version.
|
||||
"""
|
||||
logger.warning(
|
||||
"DEPRECATED: /connect endpoint is deprecated. Please use /start instead. "
|
||||
"This endpoint will be removed in a future version."
|
||||
)
|
||||
return await _handle_rtvi_request(request)
|
||||
|
||||
|
||||
def _setup_telephony_routes(app: FastAPI, *, transport_type: str, proxy: str):
|
||||
@@ -652,6 +576,8 @@ def _setup_telephony_routes(app: FastAPI, *, transport_type: str, proxy: str):
|
||||
async def _run_daily_direct():
|
||||
"""Run Daily bot with direct connection (no FastAPI server)."""
|
||||
try:
|
||||
import aiohttp
|
||||
|
||||
from pipecat.runner.daily import configure
|
||||
except ImportError as e:
|
||||
logger.error("Daily transport dependencies not installed.")
|
||||
@@ -763,12 +689,6 @@ def main():
|
||||
parser.add_argument(
|
||||
"--verbose", "-v", action="count", default=0, help="Increase logging verbosity"
|
||||
)
|
||||
parser.add_argument(
|
||||
"--whatsapp",
|
||||
action="store_true",
|
||||
default=False,
|
||||
help="Ensure requried WhatsApp environment variables are present",
|
||||
)
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
@@ -788,6 +708,10 @@ def main():
|
||||
logger.error("For ESP32, you need to specify `--host IP` so we can do SDP munging.")
|
||||
return
|
||||
|
||||
if args.transport in TELEPHONY_TRANSPORTS and not args.proxy:
|
||||
logger.error(f"For telephony transports, you need to specify `--proxy PROXY`.")
|
||||
return
|
||||
|
||||
# Log level
|
||||
logger.remove()
|
||||
logger.add(sys.stderr, level="TRACE" if args.verbose else "DEBUG")
|
||||
@@ -807,11 +731,10 @@ def main():
|
||||
print()
|
||||
if args.esp32:
|
||||
print(f"🚀 Bot ready! (ESP32 mode)")
|
||||
elif args.whatsapp:
|
||||
print(f"🚀 Bot ready! (WhatsApp)")
|
||||
print(f" → Open http://{args.host}:{args.port}/client in your browser")
|
||||
else:
|
||||
print(f"🚀 Bot ready!")
|
||||
print(f" → Open http://{args.host}:{args.port}/client in your browser")
|
||||
print(f" → Open http://{args.host}:{args.port}/client in your browser")
|
||||
print()
|
||||
elif args.transport == "daily":
|
||||
print()
|
||||
@@ -829,7 +752,6 @@ def main():
|
||||
host=args.host,
|
||||
proxy=args.proxy,
|
||||
esp32_mode=args.esp32,
|
||||
whatsapp_enabled=args.whatsapp,
|
||||
folder=args.folder,
|
||||
)
|
||||
|
||||
|
||||
@@ -20,11 +20,9 @@ from fastapi import WebSocket
|
||||
class RunnerArguments:
|
||||
"""Base class for runner session arguments."""
|
||||
|
||||
# Use kw_only so subclasses don't need to worry about ordering.
|
||||
handle_sigint: bool = field(init=False, kw_only=True)
|
||||
handle_sigterm: bool = field(init=False, kw_only=True)
|
||||
pipeline_idle_timeout_secs: int = field(init=False, kw_only=True)
|
||||
body: Optional[Any] = field(default_factory=dict, kw_only=True)
|
||||
handle_sigint: bool = field(init=False)
|
||||
handle_sigterm: bool = field(init=False)
|
||||
pipeline_idle_timeout_secs: int = field(init=False)
|
||||
|
||||
def __post_init__(self):
|
||||
self.handle_sigint = False
|
||||
@@ -44,6 +42,7 @@ class DailyRunnerArguments(RunnerArguments):
|
||||
|
||||
room_url: str
|
||||
token: Optional[str] = None
|
||||
body: Optional[Any] = field(default_factory=dict)
|
||||
|
||||
|
||||
@dataclass
|
||||
@@ -56,6 +55,7 @@ class WebSocketRunnerArguments(RunnerArguments):
|
||||
"""
|
||||
|
||||
websocket: WebSocket
|
||||
body: Optional[Any] = field(default_factory=dict)
|
||||
|
||||
|
||||
@dataclass
|
||||
|
||||
@@ -108,8 +108,6 @@ class AssemblyAIConnectionParams(BaseModel):
|
||||
end_of_turn_confidence_threshold: Confidence threshold for end-of-turn detection.
|
||||
min_end_of_turn_silence_when_confident: Minimum silence duration when confident about end-of-turn.
|
||||
max_turn_silence: Maximum silence duration before forcing end-of-turn.
|
||||
keyterms_prompt: List of key terms to guide transcription. Will be JSON serialized before sending.
|
||||
speech_model: Select between English and multilingual models. Defaults to "universal-streaming-english".
|
||||
"""
|
||||
|
||||
sample_rate: int = 16000
|
||||
@@ -119,7 +117,3 @@ class AssemblyAIConnectionParams(BaseModel):
|
||||
end_of_turn_confidence_threshold: Optional[float] = None
|
||||
min_end_of_turn_silence_when_confident: Optional[int] = None
|
||||
max_turn_silence: Optional[int] = None
|
||||
keyterms_prompt: Optional[List[str]] = None
|
||||
speech_model: Literal["universal-streaming-english", "universal-streaming-multilingual"] = (
|
||||
"universal-streaming-english"
|
||||
)
|
||||
|
||||
@@ -174,16 +174,11 @@ class AssemblyAISTTService(STTService):
|
||||
|
||||
def _build_ws_url(self) -> str:
|
||||
"""Build WebSocket URL with query parameters using urllib.parse.urlencode."""
|
||||
params = {}
|
||||
for k, v in self._connection_params.model_dump().items():
|
||||
if v is not None:
|
||||
if k == "keyterms_prompt":
|
||||
params[k] = json.dumps(v)
|
||||
elif isinstance(v, bool):
|
||||
params[k] = str(v).lower()
|
||||
else:
|
||||
params[k] = v
|
||||
|
||||
params = {
|
||||
k: str(v).lower() if isinstance(v, bool) else v
|
||||
for k, v in self._connection_params.model_dump().items()
|
||||
if v is not None
|
||||
}
|
||||
if params:
|
||||
query_string = urlencode(params)
|
||||
return f"{self._api_endpoint_base_url}?{query_string}"
|
||||
@@ -202,8 +197,6 @@ class AssemblyAISTTService(STTService):
|
||||
)
|
||||
self._connected = True
|
||||
self._receive_task = self.create_task(self._receive_task_handler())
|
||||
|
||||
await self._call_event_handler("on_connected")
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to connect to AssemblyAI: {e}")
|
||||
self._connected = False
|
||||
@@ -245,7 +238,6 @@ class AssemblyAISTTService(STTService):
|
||||
self._websocket = None
|
||||
self._connected = False
|
||||
self._receive_task = None
|
||||
await self._call_event_handler("on_disconnected")
|
||||
|
||||
async def _receive_task_handler(self):
|
||||
"""Handle incoming WebSocket messages."""
|
||||
|
||||
@@ -235,8 +235,6 @@ class AsyncAITTSService(InterruptibleTTSService):
|
||||
}
|
||||
|
||||
await self._get_websocket().send(json.dumps(init_msg))
|
||||
|
||||
await self._call_event_handler("on_connected")
|
||||
except Exception as e:
|
||||
logger.error(f"{self} initialization error: {e}")
|
||||
self._websocket = None
|
||||
@@ -254,7 +252,6 @@ class AsyncAITTSService(InterruptibleTTSService):
|
||||
finally:
|
||||
self._websocket = None
|
||||
self._started = False
|
||||
await self._call_event_handler("on_disconnected")
|
||||
|
||||
def _get_websocket(self):
|
||||
if self._websocket:
|
||||
|
||||
@@ -720,11 +720,11 @@ class AWSBedrockLLMService(LLMService):
|
||||
additional_model_request_fields: Additional model-specific parameters.
|
||||
"""
|
||||
|
||||
max_tokens: Optional[int] = Field(default=None, ge=1)
|
||||
temperature: Optional[float] = Field(default=None, ge=0.0, le=1.0)
|
||||
top_p: Optional[float] = Field(default=None, ge=0.0, le=1.0)
|
||||
max_tokens: Optional[int] = Field(default_factory=lambda: 4096, ge=1)
|
||||
temperature: Optional[float] = Field(default_factory=lambda: 0.7, ge=0.0, le=1.0)
|
||||
top_p: Optional[float] = Field(default_factory=lambda: 0.999, ge=0.0, le=1.0)
|
||||
stop_sequences: Optional[List[str]] = Field(default_factory=lambda: [])
|
||||
latency: Optional[str] = Field(default=None)
|
||||
latency: Optional[str] = Field(default_factory=lambda: "standard")
|
||||
additional_model_request_fields: Optional[Dict[str, Any]] = Field(default_factory=dict)
|
||||
|
||||
def __init__(
|
||||
@@ -801,24 +801,6 @@ class AWSBedrockLLMService(LLMService):
|
||||
"""
|
||||
return True
|
||||
|
||||
def _build_inference_config(self) -> Dict[str, Any]:
|
||||
"""Build inference config with only the parameters that are set.
|
||||
|
||||
This prevents conflicts with models (e.g., Claude Sonnet 4.5) that don't
|
||||
allow certain parameter combinations like temperature and top_p together.
|
||||
|
||||
Returns:
|
||||
Dictionary containing only the inference parameters that are not None.
|
||||
"""
|
||||
inference_config = {}
|
||||
if self._settings["max_tokens"] is not None:
|
||||
inference_config["maxTokens"] = self._settings["max_tokens"]
|
||||
if self._settings["temperature"] is not None:
|
||||
inference_config["temperature"] = self._settings["temperature"]
|
||||
if self._settings["top_p"] is not None:
|
||||
inference_config["topP"] = self._settings["top_p"]
|
||||
return inference_config
|
||||
|
||||
async def run_inference(self, context: LLMContext | OpenAILLMContext) -> Optional[str]:
|
||||
"""Run a one-shot, out-of-band (i.e. out-of-pipeline) inference with the given LLM context.
|
||||
|
||||
@@ -844,16 +826,16 @@ class AWSBedrockLLMService(LLMService):
|
||||
model_id = self.model_name
|
||||
|
||||
# Prepare request parameters
|
||||
inference_config = self._build_inference_config()
|
||||
|
||||
request_params = {
|
||||
"modelId": model_id,
|
||||
"messages": messages,
|
||||
"inferenceConfig": {
|
||||
"maxTokens": 8192,
|
||||
"temperature": 0.7,
|
||||
"topP": 0.9,
|
||||
},
|
||||
}
|
||||
|
||||
if inference_config:
|
||||
request_params["inferenceConfig"] = inference_config
|
||||
|
||||
if system:
|
||||
request_params["system"] = system
|
||||
|
||||
@@ -992,20 +974,21 @@ class AWSBedrockLLMService(LLMService):
|
||||
tools = params_from_context["tools"]
|
||||
tool_choice = params_from_context["tool_choice"]
|
||||
|
||||
# Set up inference config - only include parameters that are set
|
||||
inference_config = self._build_inference_config()
|
||||
# Set up inference config
|
||||
inference_config = {
|
||||
"maxTokens": self._settings["max_tokens"],
|
||||
"temperature": self._settings["temperature"],
|
||||
"topP": self._settings["top_p"],
|
||||
}
|
||||
|
||||
# Prepare request parameters
|
||||
request_params = {
|
||||
"modelId": self.model_name,
|
||||
"messages": messages,
|
||||
"inferenceConfig": inference_config,
|
||||
"additionalModelRequestFields": self._settings["additional_model_request_fields"],
|
||||
}
|
||||
|
||||
# Only add inference config if it has parameters
|
||||
if inference_config:
|
||||
request_params["inferenceConfig"] = inference_config
|
||||
|
||||
# Add system message
|
||||
if system:
|
||||
request_params["system"] = system
|
||||
|
||||
@@ -8,77 +8,8 @@
|
||||
|
||||
This module provides specialized context aggregators and message handling for AWS Nova Sonic,
|
||||
including conversation history management and role-specific message processing.
|
||||
|
||||
.. deprecated:: 0.0.91
|
||||
AWS Nova Sonic no longer uses types from this module under the hood.
|
||||
It now uses `LLMContext` and `LLMContextAggregatorPair`.
|
||||
Using the new patterns should allow you to not need types from this module.
|
||||
|
||||
BEFORE:
|
||||
```
|
||||
# Setup
|
||||
context = OpenAILLMContext(messages, tools)
|
||||
context_aggregator = llm.create_context_aggregator(context)
|
||||
|
||||
# Context frame type
|
||||
frame: OpenAILLMContextFrame
|
||||
|
||||
# Context type
|
||||
context: AWSNovaSonicLLMContext
|
||||
# or
|
||||
context: OpenAILLMContext
|
||||
```
|
||||
|
||||
AFTER:
|
||||
```
|
||||
# Setup
|
||||
context = LLMContext(messages, tools)
|
||||
context_aggregator = LLMContextAggregatorPair(context)
|
||||
|
||||
# Context frame type
|
||||
frame: LLMContextFrame
|
||||
|
||||
# Context type
|
||||
context: LLMContext
|
||||
```
|
||||
"""
|
||||
|
||||
import warnings
|
||||
|
||||
with warnings.catch_warnings():
|
||||
warnings.simplefilter("always")
|
||||
warnings.warn(
|
||||
"Types in pipecat.services.aws.nova_sonic.context (or "
|
||||
"pipecat.services.aws_nova_sonic.context) are deprecated. \n"
|
||||
"AWS Nova Sonic no longer uses types from this module under the hood. \n"
|
||||
"It now uses `LLMContext` and `LLMContextAggregatorPair`. \n"
|
||||
"Using the new patterns should allow you to not need types from this module.\n\n"
|
||||
"BEFORE:\n"
|
||||
"```\n"
|
||||
"# Setup\n"
|
||||
"context = OpenAILLMContext(messages, tools)\n"
|
||||
"context_aggregator = llm.create_context_aggregator(context)\n\n"
|
||||
"# Context frame type\n"
|
||||
"frame: OpenAILLMContextFrame\n\n"
|
||||
"# Context type\n"
|
||||
"context: AWSNovaSonicLLMContext\n"
|
||||
"# or\n"
|
||||
"context: OpenAILLMContext\n\n"
|
||||
"```\n\n"
|
||||
"AFTER:\n"
|
||||
"```\n"
|
||||
"# Setup\n"
|
||||
"context = LLMContext(messages, tools)\n"
|
||||
"context_aggregator = LLMContextAggregatorPair(context)\n\n"
|
||||
"# Context frame type\n"
|
||||
"frame: LLMContextFrame\n\n"
|
||||
"# Context type\n"
|
||||
"context: LLMContext\n\n"
|
||||
"```",
|
||||
DeprecationWarning,
|
||||
stacklevel=2,
|
||||
)
|
||||
|
||||
import copy
|
||||
from dataclasses import dataclass, field
|
||||
from enum import Enum
|
||||
|
||||
@@ -25,7 +25,7 @@ from loguru import logger
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
from pipecat.adapters.schemas.tools_schema import ToolsSchema
|
||||
from pipecat.adapters.services.aws_nova_sonic_adapter import AWSNovaSonicLLMAdapter, Role
|
||||
from pipecat.adapters.services.aws_nova_sonic_adapter import AWSNovaSonicLLMAdapter
|
||||
from pipecat.frames.frames import (
|
||||
BotStoppedSpeakingFrame,
|
||||
CancelFrame,
|
||||
@@ -33,30 +33,35 @@ from pipecat.frames.frames import (
|
||||
Frame,
|
||||
FunctionCallFromLLM,
|
||||
InputAudioRawFrame,
|
||||
InterruptionFrame,
|
||||
InterimTranscriptionFrame,
|
||||
LLMContextFrame,
|
||||
LLMFullResponseEndFrame,
|
||||
LLMFullResponseStartFrame,
|
||||
LLMTextFrame,
|
||||
StartFrame,
|
||||
TranscriptionFrame,
|
||||
TTSAudioRawFrame,
|
||||
TTSStartedFrame,
|
||||
TTSStoppedFrame,
|
||||
TTSTextFrame,
|
||||
UserStartedSpeakingFrame,
|
||||
UserStoppedSpeakingFrame,
|
||||
)
|
||||
from pipecat.processors.aggregators.llm_context import LLMContext
|
||||
from pipecat.processors.aggregators.llm_response import (
|
||||
LLMAssistantAggregatorParams,
|
||||
LLMUserAggregatorParams,
|
||||
)
|
||||
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
|
||||
from pipecat.processors.aggregators.openai_llm_context import (
|
||||
OpenAILLMContext,
|
||||
OpenAILLMContextFrame,
|
||||
)
|
||||
from pipecat.processors.frame_processor import FrameDirection
|
||||
from pipecat.services.aws.nova_sonic.context import (
|
||||
AWSNovaSonicAssistantContextAggregator,
|
||||
AWSNovaSonicContextAggregatorPair,
|
||||
AWSNovaSonicLLMContext,
|
||||
AWSNovaSonicUserContextAggregator,
|
||||
Role,
|
||||
)
|
||||
from pipecat.services.aws.nova_sonic.frames import AWSNovaSonicFunctionCallResultFrame
|
||||
from pipecat.services.llm_service import LLMService
|
||||
from pipecat.utils.time import time_now_iso8601
|
||||
|
||||
@@ -212,11 +217,6 @@ class AWSNovaSonicLLMService(LLMService):
|
||||
system_instruction: System-level instruction for the model.
|
||||
tools: Available tools/functions for the model to use.
|
||||
send_transcription_frames: Whether to emit transcription frames.
|
||||
|
||||
.. deprecated:: 0.0.91
|
||||
This parameter is deprecated and will be removed in a future version.
|
||||
Transcription frames are always sent.
|
||||
|
||||
**kwargs: Additional arguments passed to the parent LLMService.
|
||||
"""
|
||||
super().__init__(**kwargs)
|
||||
@@ -230,20 +230,8 @@ class AWSNovaSonicLLMService(LLMService):
|
||||
self._params = params or Params()
|
||||
self._system_instruction = system_instruction
|
||||
self._tools = tools
|
||||
|
||||
if not send_transcription_frames:
|
||||
import warnings
|
||||
|
||||
with warnings.catch_warnings():
|
||||
warnings.simplefilter("always")
|
||||
warnings.warn(
|
||||
"`send_transcription_frames` is deprecated and will be removed in a future version. "
|
||||
"Transcription frames are always sent.",
|
||||
DeprecationWarning,
|
||||
stacklevel=2,
|
||||
)
|
||||
|
||||
self._context: Optional[LLMContext] = None
|
||||
self._send_transcription_frames = send_transcription_frames
|
||||
self._context: Optional[AWSNovaSonicLLMContext] = None
|
||||
self._stream: Optional[
|
||||
DuplexEventStream[
|
||||
InvokeModelWithBidirectionalStreamInput,
|
||||
@@ -256,17 +244,12 @@ class AWSNovaSonicLLMService(LLMService):
|
||||
self._input_audio_content_name: Optional[str] = None
|
||||
self._content_being_received: Optional[CurrentContent] = None
|
||||
self._assistant_is_responding = False
|
||||
self._may_need_repush_assistant_text = False
|
||||
self._ready_to_send_context = False
|
||||
self._handling_bot_stopped_speaking = False
|
||||
self._triggering_assistant_response = False
|
||||
self._waiting_for_trigger_transcription = False
|
||||
self._disconnecting = False
|
||||
self._connected_time: Optional[float] = None
|
||||
self._wants_connection = False
|
||||
self._user_text_buffer = ""
|
||||
self._assistant_text_buffer = ""
|
||||
self._completed_tool_calls = set()
|
||||
|
||||
file_path = files("pipecat.services.aws.nova_sonic").joinpath("ready.wav")
|
||||
with wave.open(file_path.open("rb"), "rb") as wav_file:
|
||||
@@ -319,12 +302,12 @@ class AWSNovaSonicLLMService(LLMService):
|
||||
logger.debug("Resetting conversation")
|
||||
await self._handle_bot_stopped_speaking(delay_to_catch_trailing_assistant_text=False)
|
||||
|
||||
# Grab context to carry through disconnect/reconnect
|
||||
# Carry over previous context through disconnect
|
||||
context = self._context
|
||||
|
||||
await self._disconnect()
|
||||
self._context = context
|
||||
|
||||
await self._start_connecting()
|
||||
await self._handle_context(context)
|
||||
|
||||
#
|
||||
# frame processing
|
||||
@@ -339,35 +322,28 @@ class AWSNovaSonicLLMService(LLMService):
|
||||
"""
|
||||
await super().process_frame(frame, direction)
|
||||
|
||||
if isinstance(frame, (LLMContextFrame, OpenAILLMContextFrame)):
|
||||
context = (
|
||||
frame.context
|
||||
if isinstance(frame, LLMContextFrame)
|
||||
else LLMContext.from_openai_context(frame.context)
|
||||
if isinstance(frame, OpenAILLMContextFrame):
|
||||
await self._handle_context(frame.context)
|
||||
elif isinstance(frame, LLMContextFrame):
|
||||
raise NotImplementedError(
|
||||
"Universal LLMContext is not yet supported for AWS Nova Sonic."
|
||||
)
|
||||
await self._handle_context(context)
|
||||
elif isinstance(frame, InputAudioRawFrame):
|
||||
await self._handle_input_audio_frame(frame)
|
||||
elif isinstance(frame, BotStoppedSpeakingFrame):
|
||||
await self._handle_bot_stopped_speaking(delay_to_catch_trailing_assistant_text=True)
|
||||
elif isinstance(frame, InterruptionFrame):
|
||||
await self._handle_interruption_frame()
|
||||
elif isinstance(frame, AWSNovaSonicFunctionCallResultFrame):
|
||||
await self._handle_function_call_result(frame)
|
||||
|
||||
await self.push_frame(frame, direction)
|
||||
|
||||
async def _handle_context(self, context: LLMContext):
|
||||
if self._disconnecting:
|
||||
return
|
||||
|
||||
async def _handle_context(self, context: OpenAILLMContext):
|
||||
if not self._context:
|
||||
# We got our initial context
|
||||
# Try to finish connecting
|
||||
self._context = context
|
||||
# We got our initial context - try to finish connecting
|
||||
self._context = AWSNovaSonicLLMContext.upgrade_to_nova_sonic(
|
||||
context, self._system_instruction
|
||||
)
|
||||
await self._finish_connecting_if_context_available()
|
||||
else:
|
||||
# We got an updated context
|
||||
# Send results for any newly-completed function calls
|
||||
await self._process_completed_function_calls(send_new_results=True)
|
||||
|
||||
async def _handle_input_audio_frame(self, frame: InputAudioRawFrame):
|
||||
# Wait until we're done sending the assistant response trigger audio before sending audio
|
||||
@@ -417,9 +393,9 @@ class AWSNovaSonicLLMService(LLMService):
|
||||
else:
|
||||
await finalize_assistant_response()
|
||||
|
||||
async def _handle_interruption_frame(self):
|
||||
if self._assistant_is_responding:
|
||||
self._may_need_repush_assistant_text = True
|
||||
async def _handle_function_call_result(self, frame: AWSNovaSonicFunctionCallResultFrame):
|
||||
result = frame.result_frame
|
||||
await self._send_tool_result(tool_call_id=result.tool_call_id, result=result.result)
|
||||
|
||||
#
|
||||
# LLM communication: lifecycle
|
||||
@@ -455,17 +431,6 @@ class AWSNovaSonicLLMService(LLMService):
|
||||
logger.error(f"{self} initialization error: {e}")
|
||||
await self._disconnect()
|
||||
|
||||
async def _process_completed_function_calls(self, send_new_results: bool):
|
||||
# Check for set of completed function calls in the context
|
||||
for message in self._context.get_messages():
|
||||
if message.get("role") and message.get("content") != "IN_PROGRESS":
|
||||
tool_call_id = message.get("tool_call_id")
|
||||
if tool_call_id and tool_call_id not in self._completed_tool_calls:
|
||||
# Found a newly-completed function call - send the result to the service
|
||||
if send_new_results:
|
||||
await self._send_tool_result(tool_call_id, message.get("content"))
|
||||
self._completed_tool_calls.add(tool_call_id)
|
||||
|
||||
async def _finish_connecting_if_context_available(self):
|
||||
# We can only finish connecting once we've gotten our initial context and we're ready to
|
||||
# send it
|
||||
@@ -474,38 +439,30 @@ class AWSNovaSonicLLMService(LLMService):
|
||||
|
||||
logger.info("Finishing connecting (setting up session)...")
|
||||
|
||||
# Initialize our bookkeeping of already-completed tool calls in the
|
||||
# context
|
||||
await self._process_completed_function_calls(send_new_results=False)
|
||||
|
||||
# Read context
|
||||
adapter: AWSNovaSonicLLMAdapter = self.get_llm_adapter()
|
||||
llm_connection_params = adapter.get_llm_invocation_params(self._context)
|
||||
history = self._context.get_messages_for_initializing_history()
|
||||
|
||||
# Send prompt start event, specifying tools.
|
||||
# Tools from context take priority over self._tools.
|
||||
tools = (
|
||||
llm_connection_params["tools"]
|
||||
if llm_connection_params["tools"]
|
||||
else adapter.from_standard_tools(self._tools)
|
||||
self._context.tools
|
||||
if self._context.tools
|
||||
else self.get_llm_adapter().from_standard_tools(self._tools)
|
||||
)
|
||||
logger.debug(f"Using tools: {tools}")
|
||||
await self._send_prompt_start_event(tools)
|
||||
|
||||
# Send system instruction.
|
||||
# Instruction from context takes priority over self._system_instruction.
|
||||
system_instruction = (
|
||||
llm_connection_params["system_instruction"]
|
||||
if llm_connection_params["system_instruction"]
|
||||
else self._system_instruction
|
||||
)
|
||||
logger.debug(f"Using system instruction: {system_instruction}")
|
||||
if system_instruction:
|
||||
await self._send_text_event(text=system_instruction, role=Role.SYSTEM)
|
||||
# (NOTE: this prioritizing occurred automatically behind the scenes: the context was
|
||||
# initialized with self._system_instruction and then updated itself from its messages when
|
||||
# get_messages_for_initializing_history() was called).
|
||||
logger.debug(f"Using system instruction: {history.system_instruction}")
|
||||
if history.system_instruction:
|
||||
await self._send_text_event(text=history.system_instruction, role=Role.SYSTEM)
|
||||
|
||||
# Send conversation history
|
||||
for message in llm_connection_params["messages"]:
|
||||
# logger.debug(f"Seeding conversation history with message: {message}")
|
||||
for message in history.messages:
|
||||
await self._send_text_event(text=message.text, role=message.role)
|
||||
|
||||
# Start audio input
|
||||
@@ -535,12 +492,9 @@ class AWSNovaSonicLLMService(LLMService):
|
||||
await self._send_session_end_events()
|
||||
self._client = None
|
||||
|
||||
# Clean up context
|
||||
self._context = None
|
||||
|
||||
# Clean up stream
|
||||
if self._stream:
|
||||
await self._stream.close()
|
||||
await self._stream.input_stream.close()
|
||||
self._stream = None
|
||||
|
||||
# NOTE: see explanation of HACK, below
|
||||
@@ -556,23 +510,15 @@ class AWSNovaSonicLLMService(LLMService):
|
||||
self._receive_task = None
|
||||
|
||||
# Reset remaining connection-specific state
|
||||
# Should be all private state except:
|
||||
# - _wants_connection
|
||||
# - _assistant_response_trigger_audio
|
||||
self._prompt_name = None
|
||||
self._input_audio_content_name = None
|
||||
self._content_being_received = None
|
||||
self._assistant_is_responding = False
|
||||
self._may_need_repush_assistant_text = False
|
||||
self._ready_to_send_context = False
|
||||
self._handling_bot_stopped_speaking = False
|
||||
self._triggering_assistant_response = False
|
||||
self._waiting_for_trigger_transcription = False
|
||||
self._disconnecting = False
|
||||
self._connected_time = None
|
||||
self._user_text_buffer = ""
|
||||
self._assistant_text_buffer = ""
|
||||
self._completed_tool_calls = set()
|
||||
|
||||
logger.info("Finished disconnecting")
|
||||
except Exception as e:
|
||||
@@ -880,10 +826,6 @@ class AWSNovaSonicLLMService(LLMService):
|
||||
# Handle the LLM completion ending
|
||||
await self._handle_completion_end_event(event_json)
|
||||
except Exception as e:
|
||||
if self._disconnecting:
|
||||
# Errors are kind of expected while disconnecting, so just
|
||||
# ignore them and do nothing
|
||||
return
|
||||
logger.error(f"{self} error processing responses: {e}")
|
||||
if self._wants_connection:
|
||||
await self.reset_conversation()
|
||||
@@ -1014,7 +956,7 @@ class AWSNovaSonicLLMService(LLMService):
|
||||
async def _report_assistant_response_started(self):
|
||||
logger.debug("Assistant response started")
|
||||
|
||||
# Report the start of the assistant response.
|
||||
# Report that the assistant has started their response.
|
||||
await self.push_frame(LLMFullResponseStartFrame())
|
||||
|
||||
# Report that equivalent of TTS (this is a speech-to-speech model) started
|
||||
@@ -1026,16 +968,23 @@ class AWSNovaSonicLLMService(LLMService):
|
||||
|
||||
logger.debug(f"Assistant response text added: {text}")
|
||||
|
||||
# Report the text of the assistant response.
|
||||
# Report some text added to the ongoing assistant response
|
||||
await self.push_frame(LLMTextFrame(text))
|
||||
|
||||
# Report some text added to the *equivalent* of TTS (this is a speech-to-speech model)
|
||||
await self.push_frame(TTSTextFrame(text))
|
||||
|
||||
# HACK: here we're also buffering the assistant text ourselves as a
|
||||
# backup rather than relying solely on the assistant context aggregator
|
||||
# to do it, because the text arrives from Nova Sonic only after all the
|
||||
# assistant audio frames have been pushed, meaning that if an
|
||||
# interruption frame were to arrive we would lose all of it (the text
|
||||
# frames sitting in the queue would be wiped).
|
||||
self._assistant_text_buffer += text
|
||||
# TODO: this is a (hopefully temporary) HACK. Here we directly manipulate the context rather
|
||||
# than relying on the frames pushed to the assistant context aggregator. The pattern of
|
||||
# receiving full-sentence text after the assistant has spoken does not easily fit with the
|
||||
# Pipecat expectation of chunks of text streaming in while the assistant is speaking.
|
||||
# Interruption handling was especially challenging. Rather than spend days trying to fit a
|
||||
# square peg in a round hole, I decided on this hack for the time being. We can most cleanly
|
||||
# abandon this hack if/when AWS Nova Sonic implements streaming smaller text chunks
|
||||
# interspersed with audio. Note that when we move away from this hack, we need to make sure
|
||||
# that on an interruption we avoid sending LLMFullResponseEndFrame, which gets the
|
||||
# LLMAssistantContextAggregator into a bad state.
|
||||
self._context.buffer_assistant_text(text)
|
||||
|
||||
async def _report_assistant_response_ended(self):
|
||||
if not self._context: # should never happen
|
||||
@@ -1043,34 +992,14 @@ class AWSNovaSonicLLMService(LLMService):
|
||||
|
||||
logger.debug("Assistant response ended")
|
||||
|
||||
# If an interruption frame arrived while the assistant was responding
|
||||
# we may have lost all of the assistant text (see HACK, above), so
|
||||
# re-push it downstream to the aggregator now.
|
||||
if self._may_need_repush_assistant_text:
|
||||
# Just in case, check that assistant text hasn't already made it
|
||||
# into the context (sometimes it does, despite the interruption).
|
||||
messages = self._context.get_messages()
|
||||
last_message = messages[-1] if messages else None
|
||||
if (
|
||||
not last_message
|
||||
or last_message.get("role") != "assistant"
|
||||
or last_message.get("content") != self._assistant_text_buffer
|
||||
):
|
||||
# We also need to re-push the LLMFullResponseStartFrame since the
|
||||
# TTSTextFrame would be ignored otherwise (the interruption frame
|
||||
# would have cleared the assistant aggregator state).
|
||||
await self.push_frame(LLMFullResponseStartFrame())
|
||||
await self.push_frame(TTSTextFrame(self._assistant_text_buffer))
|
||||
self._may_need_repush_assistant_text = False
|
||||
|
||||
# Report the end of the assistant response.
|
||||
# Report that the assistant has finished their response.
|
||||
await self.push_frame(LLMFullResponseEndFrame())
|
||||
|
||||
# Report that equivalent of TTS (this is a speech-to-speech model) stopped.
|
||||
await self.push_frame(TTSStoppedFrame())
|
||||
|
||||
# Clear out the buffered assistant text
|
||||
self._assistant_text_buffer = ""
|
||||
# For an explanation of this hack, see _report_assistant_response_text_added.
|
||||
self._context.flush_aggregated_assistant_text()
|
||||
|
||||
#
|
||||
# user transcription reporting
|
||||
@@ -1087,67 +1016,33 @@ class AWSNovaSonicLLMService(LLMService):
|
||||
|
||||
logger.debug(f"User transcription text added: {text}")
|
||||
|
||||
# HACK: here we're buffering the user text ourselves rather than
|
||||
# relying on the upstream user context aggregator to do it, because the
|
||||
# text arrives in fairly large chunks spaced fairly far apart in time.
|
||||
# That means the user text would be split between different messages in
|
||||
# context. Even if we sent placeholder InterimTranscriptionFrames in
|
||||
# between each TranscriptionFrame to tell the aggregator to hold off on
|
||||
# finalizing the user message, the aggregator would likely get the last
|
||||
# chunk too late.
|
||||
self._user_text_buffer += f" {text}" if self._user_text_buffer else text
|
||||
# Manually add new user transcription text to context.
|
||||
# We can't rely on the user context aggregator to do this since it's upstream from the LLM.
|
||||
self._context.buffer_user_text(text)
|
||||
|
||||
# Report that some new user transcription text is available.
|
||||
if self._send_transcription_frames:
|
||||
await self.push_frame(
|
||||
InterimTranscriptionFrame(text=text, user_id="", timestamp=time_now_iso8601())
|
||||
)
|
||||
|
||||
async def _report_user_transcription_ended(self):
|
||||
if not self._context: # should never happen
|
||||
return
|
||||
|
||||
# Manually add user transcription to context (if any has been buffered).
|
||||
# We can't rely on the user context aggregator to do this since it's upstream from the LLM.
|
||||
transcription = self._context.flush_aggregated_user_text()
|
||||
|
||||
if not transcription:
|
||||
return
|
||||
|
||||
logger.debug(f"User transcription ended")
|
||||
|
||||
# Report to the upstream user context aggregator that some new user
|
||||
# transcription text is available.
|
||||
|
||||
# HACK: Check if this transcription was triggered by our own
|
||||
# assistant response trigger. If so, we need to wrap it with
|
||||
# UserStarted/StoppedSpeakingFrames; otherwise the user aggregator
|
||||
# would fire an EmulatedUserStartedSpeakingFrame, which would
|
||||
# trigger an interruption, which would prevent us from writing the
|
||||
# assistant response to context.
|
||||
#
|
||||
# Sending an EmulateUserStartedSpeakingFrame ourselves doesn't
|
||||
# work: it just causes the interruption we're trying to avoid.
|
||||
#
|
||||
# Setting enable_emulated_vad_interruptions also doesn't work: at
|
||||
# the time the user aggregator receives the TranscriptionFrame, it
|
||||
# doesn't yet know the assistant has started responding, so it
|
||||
# doesn't know that emulating the user starting to speak would
|
||||
# cause an interruption.
|
||||
should_wrap_in_user_started_stopped_speaking_frames = (
|
||||
self._waiting_for_trigger_transcription
|
||||
and self._user_text_buffer.strip().lower() == "ready"
|
||||
)
|
||||
|
||||
# Start wrapping the upstream transcription in UserStarted/StoppedSpeakingFrames if needed
|
||||
if should_wrap_in_user_started_stopped_speaking_frames:
|
||||
logger.debug(
|
||||
"Wrapping assistant response trigger transcription with upstream UserStarted/StoppedSpeakingFrames"
|
||||
if self._send_transcription_frames:
|
||||
await self.push_frame(
|
||||
TranscriptionFrame(text=transcription, user_id="", timestamp=time_now_iso8601())
|
||||
)
|
||||
await self.push_frame(UserStartedSpeakingFrame(), direction=FrameDirection.UPSTREAM)
|
||||
|
||||
# Send the transcription upstream for the user context aggregator
|
||||
frame = TranscriptionFrame(
|
||||
text=self._user_text_buffer, user_id="", timestamp=time_now_iso8601()
|
||||
)
|
||||
await self.push_frame(frame, direction=FrameDirection.UPSTREAM)
|
||||
|
||||
# Finish wrapping the upstream transcription in UserStarted/StoppedSpeakingFrames if needed
|
||||
if should_wrap_in_user_started_stopped_speaking_frames:
|
||||
await self.push_frame(UserStoppedSpeakingFrame(), direction=FrameDirection.UPSTREAM)
|
||||
|
||||
# Clear out the buffered user text
|
||||
self._user_text_buffer = ""
|
||||
|
||||
# We're no longer waiting for a trigger transcription
|
||||
self._waiting_for_trigger_transcription = False
|
||||
|
||||
#
|
||||
# context
|
||||
@@ -1159,26 +1054,23 @@ class AWSNovaSonicLLMService(LLMService):
|
||||
*,
|
||||
user_params: LLMUserAggregatorParams = LLMUserAggregatorParams(),
|
||||
assistant_params: LLMAssistantAggregatorParams = LLMAssistantAggregatorParams(),
|
||||
) -> LLMContextAggregatorPair:
|
||||
) -> AWSNovaSonicContextAggregatorPair:
|
||||
"""Create context aggregator pair for managing conversation context.
|
||||
|
||||
NOTE: this method exists only for backward compatibility. New code
|
||||
should instead do:
|
||||
context = LLMContext(...)
|
||||
context_aggregator = LLMContextAggregatorPair(context)
|
||||
|
||||
Args:
|
||||
context: The OpenAI LLM context.
|
||||
context: The OpenAI LLM context to upgrade.
|
||||
user_params: Parameters for the user context aggregator.
|
||||
assistant_params: Parameters for the assistant context aggregator.
|
||||
|
||||
Returns:
|
||||
A pair of user and assistant context aggregators.
|
||||
"""
|
||||
context = LLMContext.from_openai_context(context)
|
||||
return LLMContextAggregatorPair(
|
||||
context, user_params=user_params, assistant_params=assistant_params
|
||||
)
|
||||
context.set_llm_adapter(self.get_llm_adapter())
|
||||
|
||||
user = AWSNovaSonicUserContextAggregator(context=context, params=user_params)
|
||||
assistant = AWSNovaSonicAssistantContextAggregator(context=context, params=assistant_params)
|
||||
|
||||
return AWSNovaSonicContextAggregatorPair(user, assistant)
|
||||
|
||||
#
|
||||
# assistant response trigger (HACK)
|
||||
@@ -1216,8 +1108,6 @@ class AWSNovaSonicLLMService(LLMService):
|
||||
try:
|
||||
logger.debug("Sending assistant response trigger...")
|
||||
|
||||
self._waiting_for_trigger_transcription = True
|
||||
|
||||
chunk_duration = 0.02 # what we might get from InputAudioRawFrame
|
||||
chunk_size = int(
|
||||
chunk_duration
|
||||
|
||||
@@ -286,7 +286,6 @@ class AWSTranscribeSTTService(STTService):
|
||||
|
||||
logger.info(f"{self} Successfully connected to AWS Transcribe")
|
||||
|
||||
await self._call_event_handler("on_connected")
|
||||
except Exception as e:
|
||||
logger.error(f"{self} Failed to connect to AWS Transcribe: {e}")
|
||||
await self._disconnect()
|
||||
@@ -311,7 +310,6 @@ class AWSTranscribeSTTService(STTService):
|
||||
logger.warning(f"{self} Error closing WebSocket connection: {e}")
|
||||
finally:
|
||||
self._ws_client = None
|
||||
await self._call_event_handler("on_disconnected")
|
||||
|
||||
def language_to_service_language(self, language: Language) -> str | None:
|
||||
"""Convert internal language enum to AWS Transcribe language code.
|
||||
|
||||
@@ -8,14 +8,18 @@
|
||||
|
||||
This module provides specialized context aggregators and message handling for AWS Nova Sonic,
|
||||
including conversation history management and role-specific message processing.
|
||||
|
||||
.. deprecated:: 0.0.91
|
||||
AWS Nova Sonic no longer uses types from this module under the hood.
|
||||
It now uses `LLMContext` and `LLMContextAggregatorPair`.
|
||||
Using the new patterns should allow you to not need types from this module.
|
||||
|
||||
See deprecation warning in pipecat.services.aws.nova_sonic.context for more
|
||||
details.
|
||||
"""
|
||||
|
||||
import warnings
|
||||
|
||||
from pipecat.services.aws.nova_sonic.context import *
|
||||
|
||||
with warnings.catch_warnings():
|
||||
warnings.simplefilter("always")
|
||||
warnings.warn(
|
||||
"Types in pipecat.services.aws_nova_sonic.context are deprecated. "
|
||||
"Please use the equivalent types from "
|
||||
"pipecat.services.aws.nova_sonic.context instead.",
|
||||
DeprecationWarning,
|
||||
stacklevel=2,
|
||||
)
|
||||
|
||||
@@ -28,12 +28,13 @@ from pipecat.frames.frames import (
|
||||
UserStoppedSpeakingFrame,
|
||||
)
|
||||
from pipecat.processors.frame_processor import FrameDirection
|
||||
from pipecat.services.stt_service import WebsocketSTTService
|
||||
from pipecat.services.stt_service import STTService
|
||||
from pipecat.transcriptions.language import Language
|
||||
from pipecat.utils.time import time_now_iso8601
|
||||
from pipecat.utils.tracing.service_decorators import traced_stt
|
||||
|
||||
try:
|
||||
import websockets
|
||||
from websockets.asyncio.client import connect as websocket_connect
|
||||
from websockets.protocol import State
|
||||
except ModuleNotFoundError as e:
|
||||
@@ -123,7 +124,7 @@ class CartesiaLiveOptions:
|
||||
return cls(**json.loads(json_str))
|
||||
|
||||
|
||||
class CartesiaSTTService(WebsocketSTTService):
|
||||
class CartesiaSTTService(STTService):
|
||||
"""Speech-to-text service using Cartesia Live API.
|
||||
|
||||
Provides real-time speech transcription through WebSocket connection
|
||||
@@ -175,7 +176,8 @@ class CartesiaSTTService(WebsocketSTTService):
|
||||
self.set_model_name(merged_options.model)
|
||||
self._api_key = api_key
|
||||
self._base_url = base_url or "api.cartesia.ai"
|
||||
self._receive_task = None
|
||||
self._connection = None
|
||||
self._receiver_task = None
|
||||
|
||||
def can_generate_metrics(self) -> bool:
|
||||
"""Check if the service can generate processing metrics.
|
||||
@@ -212,27 +214,6 @@ class CartesiaSTTService(WebsocketSTTService):
|
||||
await super().cancel(frame)
|
||||
await self._disconnect()
|
||||
|
||||
async def start_metrics(self):
|
||||
"""Start performance metrics collection for transcription processing."""
|
||||
await self.start_ttfb_metrics()
|
||||
await self.start_processing_metrics()
|
||||
|
||||
async def process_frame(self, frame: Frame, direction: FrameDirection):
|
||||
"""Process incoming frames and handle speech events.
|
||||
|
||||
Args:
|
||||
frame: The frame to process.
|
||||
direction: Direction of frame flow in the pipeline.
|
||||
"""
|
||||
await super().process_frame(frame, direction)
|
||||
|
||||
if isinstance(frame, UserStartedSpeakingFrame):
|
||||
await self.start_metrics()
|
||||
elif isinstance(frame, UserStoppedSpeakingFrame):
|
||||
# Send finalize command to flush the transcription session
|
||||
if self._websocket and self._websocket.state is State.OPEN:
|
||||
await self._websocket.send("finalize")
|
||||
|
||||
async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]:
|
||||
"""Process audio data for speech-to-text transcription.
|
||||
|
||||
@@ -243,71 +224,45 @@ class CartesiaSTTService(WebsocketSTTService):
|
||||
None - transcription results are handled via WebSocket responses.
|
||||
"""
|
||||
# If the connection is closed, due to timeout, we need to reconnect when the user starts speaking again
|
||||
if not self._websocket or self._websocket.state is State.CLOSED:
|
||||
if not self._connection or self._connection.state is State.CLOSED:
|
||||
await self._connect()
|
||||
|
||||
await self._websocket.send(audio)
|
||||
await self._connection.send(audio)
|
||||
yield None
|
||||
|
||||
async def _connect(self):
|
||||
await self._connect_websocket()
|
||||
params = self._settings.to_dict()
|
||||
ws_url = f"wss://{self._base_url}/stt/websocket?{urllib.parse.urlencode(params)}"
|
||||
logger.debug(f"Connecting to Cartesia: {ws_url}")
|
||||
headers = {"Cartesia-Version": "2025-04-16", "X-API-Key": self._api_key}
|
||||
|
||||
if self._websocket and not self._receive_task:
|
||||
self._receive_task = asyncio.create_task(self._receive_task_handler(self._report_error))
|
||||
|
||||
async def _disconnect(self):
|
||||
if self._receive_task:
|
||||
await self.cancel_task(self._receive_task)
|
||||
self._receive_task = None
|
||||
|
||||
await self._disconnect_websocket()
|
||||
|
||||
async def _connect_websocket(self):
|
||||
try:
|
||||
if self._websocket and self._websocket.state is State.OPEN:
|
||||
return
|
||||
logger.debug("Connecting to Cartesia STT")
|
||||
|
||||
params = self._settings.to_dict()
|
||||
ws_url = f"wss://{self._base_url}/stt/websocket?{urllib.parse.urlencode(params)}"
|
||||
headers = {"Cartesia-Version": "2025-04-16", "X-API-Key": self._api_key}
|
||||
|
||||
self._websocket = await websocket_connect(ws_url, additional_headers=headers)
|
||||
await self._call_event_handler("on_connected")
|
||||
self._connection = await websocket_connect(ws_url, additional_headers=headers)
|
||||
# Setup the receiver task to handle the incoming messages from the Cartesia server
|
||||
if self._receiver_task is None or self._receiver_task.done():
|
||||
self._receiver_task = asyncio.create_task(self._receive_messages())
|
||||
logger.debug(f"Connected to Cartesia")
|
||||
except Exception as e:
|
||||
logger.error(f"{self}: unable to connect to Cartesia: {e}")
|
||||
|
||||
async def _disconnect_websocket(self):
|
||||
try:
|
||||
if self._websocket and self._websocket.state is State.OPEN:
|
||||
logger.debug("Disconnecting from Cartesia STT")
|
||||
await self._websocket.close()
|
||||
except Exception as e:
|
||||
logger.error(f"{self} error closing websocket: {e}")
|
||||
finally:
|
||||
self._websocket = None
|
||||
await self._call_event_handler("on_disconnected")
|
||||
|
||||
def _get_websocket(self):
|
||||
if self._websocket:
|
||||
return self._websocket
|
||||
raise Exception("Websocket not connected")
|
||||
|
||||
async def _process_messages(self):
|
||||
async for message in self._get_websocket():
|
||||
try:
|
||||
data = json.loads(message)
|
||||
await self._process_response(data)
|
||||
except json.JSONDecodeError:
|
||||
logger.warning(f"Received non-JSON message: {message}")
|
||||
|
||||
async def _receive_messages(self):
|
||||
while True:
|
||||
await self._process_messages()
|
||||
# Cartesia times out after 5 minutes of innactivity (no keepalive
|
||||
# mechanism is available). So, we try to reconnect.
|
||||
logger.debug(f"{self} Cartesia connection was disconnected (timeout?), reconnecting")
|
||||
await self._connect_websocket()
|
||||
try:
|
||||
while True:
|
||||
if not self._connection or self._connection.state is State.CLOSED:
|
||||
break
|
||||
|
||||
message = await self._connection.recv()
|
||||
try:
|
||||
data = json.loads(message)
|
||||
await self._process_response(data)
|
||||
except json.JSONDecodeError:
|
||||
logger.warning(f"Received non-JSON message: {message}")
|
||||
except asyncio.CancelledError:
|
||||
pass
|
||||
except websockets.exceptions.ConnectionClosed as e:
|
||||
logger.debug(f"WebSocket connection closed: {e}")
|
||||
except Exception as e:
|
||||
logger.error(f"Error in message receiver: {e}")
|
||||
|
||||
async def _process_response(self, data):
|
||||
if "type" in data:
|
||||
@@ -361,3 +316,41 @@ class CartesiaSTTService(WebsocketSTTService):
|
||||
language,
|
||||
)
|
||||
)
|
||||
|
||||
async def _disconnect(self):
|
||||
if self._receiver_task:
|
||||
self._receiver_task.cancel()
|
||||
try:
|
||||
await self._receiver_task
|
||||
except asyncio.CancelledError:
|
||||
pass
|
||||
except Exception as e:
|
||||
logger.exception(f"Unexpected exception while cancelling task: {e}")
|
||||
self._receiver_task = None
|
||||
|
||||
if self._connection and self._connection.state is State.OPEN:
|
||||
logger.debug("Disconnecting from Cartesia")
|
||||
|
||||
await self._connection.close()
|
||||
self._connection = None
|
||||
|
||||
async def start_metrics(self):
|
||||
"""Start performance metrics collection for transcription processing."""
|
||||
await self.start_ttfb_metrics()
|
||||
await self.start_processing_metrics()
|
||||
|
||||
async def process_frame(self, frame: Frame, direction: FrameDirection):
|
||||
"""Process incoming frames and handle speech events.
|
||||
|
||||
Args:
|
||||
frame: The frame to process.
|
||||
direction: Direction of frame flow in the pipeline.
|
||||
"""
|
||||
await super().process_frame(frame, direction)
|
||||
|
||||
if isinstance(frame, UserStartedSpeakingFrame):
|
||||
await self.start_metrics()
|
||||
elif isinstance(frame, UserStoppedSpeakingFrame):
|
||||
# Send finalize command to flush the transcription session
|
||||
if self._connection and self._connection.state is State.OPEN:
|
||||
await self._connection.send("finalize")
|
||||
|
||||
@@ -344,11 +344,10 @@ class CartesiaTTSService(AudioContextWordTTSService):
|
||||
try:
|
||||
if self._websocket and self._websocket.state is State.OPEN:
|
||||
return
|
||||
logger.debug("Connecting to Cartesia TTS")
|
||||
logger.debug("Connecting to Cartesia")
|
||||
self._websocket = await websocket_connect(
|
||||
f"{self._url}?api_key={self._api_key}&cartesia_version={self._cartesia_version}"
|
||||
)
|
||||
await self._call_event_handler("on_connected")
|
||||
except Exception as e:
|
||||
logger.error(f"{self} initialization error: {e}")
|
||||
self._websocket = None
|
||||
@@ -366,7 +365,6 @@ class CartesiaTTSService(AudioContextWordTTSService):
|
||||
finally:
|
||||
self._context_id = None
|
||||
self._websocket = None
|
||||
await self._call_event_handler("on_disconnected")
|
||||
|
||||
def _get_websocket(self):
|
||||
if self._websocket:
|
||||
|
||||
@@ -205,7 +205,6 @@ class DeepgramFluxSTTService(WebsocketSTTService):
|
||||
additional_headers={"Authorization": f"Token {self._api_key}"},
|
||||
)
|
||||
logger.debug("Connected to Deepgram Flux Websocket")
|
||||
await self._call_event_handler("on_connected")
|
||||
except Exception as e:
|
||||
logger.error(f"{self} initialization error: {e}")
|
||||
self._websocket = None
|
||||
@@ -226,9 +225,6 @@ class DeepgramFluxSTTService(WebsocketSTTService):
|
||||
await self._websocket.close()
|
||||
except Exception as e:
|
||||
logger.error(f"{self} error closing websocket: {e}")
|
||||
finally:
|
||||
self._websocket = None
|
||||
await self._call_event_handler("on_disconnected")
|
||||
|
||||
async def _send_close_stream(self) -> None:
|
||||
"""Sends a CloseStream control message to the Deepgram Flux WebSocket API.
|
||||
|
||||
@@ -168,24 +168,16 @@ def build_elevenlabs_voice_settings(
|
||||
|
||||
|
||||
def calculate_word_times(
|
||||
alignment_info: Mapping[str, Any],
|
||||
cumulative_time: float,
|
||||
partial_word: str = "",
|
||||
partial_word_start_time: float = 0.0,
|
||||
) -> tuple[List[Tuple[str, float]], str, float]:
|
||||
alignment_info: Mapping[str, Any], cumulative_time: float
|
||||
) -> List[Tuple[str, float]]:
|
||||
"""Calculate word timestamps from character alignment information.
|
||||
|
||||
Args:
|
||||
alignment_info: Character alignment data from ElevenLabs API.
|
||||
cumulative_time: Base time offset for this chunk.
|
||||
partial_word: Partial word carried over from previous chunk.
|
||||
partial_word_start_time: Start time of the partial word.
|
||||
|
||||
Returns:
|
||||
Tuple of (word_times, new_partial_word, new_partial_word_start_time):
|
||||
- word_times: List of (word, timestamp) tuples for complete words
|
||||
- new_partial_word: Incomplete word at end of chunk (empty if chunk ends with space)
|
||||
- new_partial_word_start_time: Start time of the incomplete word
|
||||
List of (word, timestamp) tuples.
|
||||
"""
|
||||
chars = alignment_info["chars"]
|
||||
char_start_times_ms = alignment_info["charStartTimesMs"]
|
||||
@@ -194,37 +186,41 @@ def calculate_word_times(
|
||||
logger.error(
|
||||
f"calculate_word_times: length mismatch - chars={len(chars)}, times={len(char_start_times_ms)}"
|
||||
)
|
||||
return ([], partial_word, partial_word_start_time)
|
||||
return []
|
||||
|
||||
# Build words and track their start positions
|
||||
words = []
|
||||
word_start_times = []
|
||||
current_word = partial_word # Start with any partial word from previous chunk
|
||||
word_start_time = partial_word_start_time if partial_word else None
|
||||
word_start_indices = []
|
||||
current_word = ""
|
||||
word_start_index = None
|
||||
|
||||
for i, char in enumerate(chars):
|
||||
if char == " ":
|
||||
# End of current word
|
||||
if current_word: # Only add non-empty words
|
||||
words.append(current_word)
|
||||
word_start_times.append(word_start_time)
|
||||
word_start_indices.append(word_start_index)
|
||||
current_word = ""
|
||||
word_start_time = None
|
||||
word_start_index = None
|
||||
else:
|
||||
# Building a word
|
||||
if word_start_time is None: # First character of new word
|
||||
# Convert from milliseconds to seconds and add cumulative offset
|
||||
word_start_time = cumulative_time + (char_start_times_ms[i] / 1000.0)
|
||||
if word_start_index is None: # First character of new word
|
||||
word_start_index = i
|
||||
current_word += char
|
||||
|
||||
# Build result for complete words
|
||||
word_times = list(zip(words, word_start_times))
|
||||
# Handle the last word if there's no trailing space
|
||||
if current_word and word_start_index is not None:
|
||||
words.append(current_word)
|
||||
word_start_indices.append(word_start_index)
|
||||
|
||||
# Return any incomplete word at the end of this chunk
|
||||
new_partial_word = current_word if current_word else ""
|
||||
new_partial_word_start_time = word_start_time if word_start_time is not None else 0.0
|
||||
# Calculate timestamps for each word
|
||||
word_times = []
|
||||
for word, start_idx in zip(words, word_start_indices):
|
||||
# Convert from milliseconds to seconds and add cumulative offset
|
||||
start_time_seconds = cumulative_time + (char_start_times_ms[start_idx] / 1000.0)
|
||||
word_times.append((word, start_time_seconds))
|
||||
|
||||
return (word_times, new_partial_word, new_partial_word_start_time)
|
||||
return word_times
|
||||
|
||||
|
||||
class ElevenLabsTTSService(AudioContextWordTTSService):
|
||||
@@ -336,9 +332,6 @@ class ElevenLabsTTSService(AudioContextWordTTSService):
|
||||
# there's an interruption or TTSStoppedFrame.
|
||||
self._started = False
|
||||
self._cumulative_time = 0
|
||||
# Track partial words that span across alignment chunks
|
||||
self._partial_word = ""
|
||||
self._partial_word_start_time = 0.0
|
||||
|
||||
# Context management for v1 multi API
|
||||
self._context_id = None
|
||||
@@ -528,7 +521,6 @@ class ElevenLabsTTSService(AudioContextWordTTSService):
|
||||
url, max_size=16 * 1024 * 1024, additional_headers={"xi-api-key": self._api_key}
|
||||
)
|
||||
|
||||
await self._call_event_handler("on_connected")
|
||||
except Exception as e:
|
||||
logger.error(f"{self} initialization error: {e}")
|
||||
self._websocket = None
|
||||
@@ -551,7 +543,6 @@ class ElevenLabsTTSService(AudioContextWordTTSService):
|
||||
self._started = False
|
||||
self._context_id = None
|
||||
self._websocket = None
|
||||
await self._call_event_handler("on_disconnected")
|
||||
|
||||
def _get_websocket(self):
|
||||
if self._websocket:
|
||||
@@ -579,8 +570,6 @@ class ElevenLabsTTSService(AudioContextWordTTSService):
|
||||
logger.error(f"Error closing context on interruption: {e}")
|
||||
self._context_id = None
|
||||
self._started = False
|
||||
self._partial_word = ""
|
||||
self._partial_word_start_time = 0.0
|
||||
|
||||
async def _receive_messages(self):
|
||||
"""Handle incoming WebSocket messages from ElevenLabs."""
|
||||
@@ -620,14 +609,7 @@ class ElevenLabsTTSService(AudioContextWordTTSService):
|
||||
|
||||
if msg.get("alignment"):
|
||||
alignment = msg["alignment"]
|
||||
word_times, self._partial_word, self._partial_word_start_time = (
|
||||
calculate_word_times(
|
||||
alignment,
|
||||
self._cumulative_time,
|
||||
self._partial_word,
|
||||
self._partial_word_start_time,
|
||||
)
|
||||
)
|
||||
word_times = calculate_word_times(alignment, self._cumulative_time)
|
||||
|
||||
if word_times:
|
||||
await self.add_word_timestamps(word_times)
|
||||
@@ -701,8 +683,6 @@ class ElevenLabsTTSService(AudioContextWordTTSService):
|
||||
yield TTSStartedFrame()
|
||||
self._started = True
|
||||
self._cumulative_time = 0
|
||||
self._partial_word = ""
|
||||
self._partial_word_start_time = 0.0
|
||||
# If a context ID does not exist, create a new one and
|
||||
# register it. If an ID exists, that means the Pipeline is
|
||||
# configured for allow_interruptions=False, so continue
|
||||
@@ -776,7 +756,6 @@ class ElevenLabsHttpTTSService(WordTTSService):
|
||||
base_url: str = "https://api.elevenlabs.io",
|
||||
sample_rate: Optional[int] = None,
|
||||
params: Optional[InputParams] = None,
|
||||
aggregate_sentences: Optional[bool] = True,
|
||||
**kwargs,
|
||||
):
|
||||
"""Initialize the ElevenLabs HTTP TTS service.
|
||||
@@ -789,11 +768,10 @@ class ElevenLabsHttpTTSService(WordTTSService):
|
||||
base_url: Base URL for ElevenLabs HTTP API.
|
||||
sample_rate: Audio sample rate. If None, uses default.
|
||||
params: Additional input parameters for voice customization.
|
||||
aggregate_sentences: Whether to aggregate sentences within the TTSService.
|
||||
**kwargs: Additional arguments passed to the parent service.
|
||||
"""
|
||||
super().__init__(
|
||||
aggregate_sentences=aggregate_sentences,
|
||||
aggregate_sentences=True,
|
||||
push_text_frames=False,
|
||||
push_stop_frames=True,
|
||||
sample_rate=sample_rate,
|
||||
@@ -831,10 +809,6 @@ class ElevenLabsHttpTTSService(WordTTSService):
|
||||
# Store previous text for context within a turn
|
||||
self._previous_text = ""
|
||||
|
||||
# Track partial words that span across alignment chunks
|
||||
self._partial_word = ""
|
||||
self._partial_word_start_time = 0.0
|
||||
|
||||
def language_to_service_language(self, language: Language) -> Optional[str]:
|
||||
"""Convert pipecat Language to ElevenLabs language code.
|
||||
|
||||
@@ -862,8 +836,6 @@ class ElevenLabsHttpTTSService(WordTTSService):
|
||||
self._cumulative_time = 0
|
||||
self._started = False
|
||||
self._previous_text = ""
|
||||
self._partial_word = ""
|
||||
self._partial_word_start_time = 0.0
|
||||
logger.debug(f"{self}: Reset internal state")
|
||||
|
||||
async def start(self, frame: StartFrame):
|
||||
@@ -898,13 +870,11 @@ class ElevenLabsHttpTTSService(WordTTSService):
|
||||
def calculate_word_times(self, alignment_info: Mapping[str, Any]) -> List[Tuple[str, float]]:
|
||||
"""Calculate word timing from character alignment data.
|
||||
|
||||
This method handles partial words that may span across multiple alignment chunks.
|
||||
|
||||
Args:
|
||||
alignment_info: Character timing data from ElevenLabs.
|
||||
|
||||
Returns:
|
||||
List of (word, timestamp) pairs for complete words in this chunk.
|
||||
List of (word, timestamp) pairs.
|
||||
|
||||
Example input data::
|
||||
|
||||
@@ -930,28 +900,30 @@ class ElevenLabsHttpTTSService(WordTTSService):
|
||||
# Build the words and find their start times
|
||||
words = []
|
||||
word_start_times = []
|
||||
# Start with any partial word from previous chunk
|
||||
current_word = self._partial_word
|
||||
word_start_time = self._partial_word_start_time if self._partial_word else None
|
||||
current_word = ""
|
||||
first_char_idx = -1
|
||||
|
||||
for i, char in enumerate(chars):
|
||||
if char == " ":
|
||||
if current_word: # Only add non-empty words
|
||||
words.append(current_word)
|
||||
word_start_times.append(word_start_time)
|
||||
current_word = ""
|
||||
word_start_time = None
|
||||
else:
|
||||
if word_start_time is None: # First character of a new word
|
||||
# Use time of the first character of the word, offset by cumulative time
|
||||
word_start_time = self._cumulative_time + char_start_times[i]
|
||||
word_start_times.append(
|
||||
self._cumulative_time + char_start_times[first_char_idx]
|
||||
)
|
||||
current_word = ""
|
||||
first_char_idx = -1
|
||||
else:
|
||||
if not current_word: # This is the first character of a new word
|
||||
first_char_idx = i
|
||||
current_word += char
|
||||
|
||||
# Store any incomplete word at the end of this chunk
|
||||
self._partial_word = current_word if current_word else ""
|
||||
self._partial_word_start_time = word_start_time if word_start_time is not None else 0.0
|
||||
# Don't forget the last word if there's no trailing space
|
||||
if current_word and first_char_idx >= 0:
|
||||
words.append(current_word)
|
||||
word_start_times.append(self._cumulative_time + char_start_times[first_char_idx])
|
||||
|
||||
# Create word-time pairs for complete words only
|
||||
# Create word-time pairs
|
||||
word_times = list(zip(words, word_start_times))
|
||||
|
||||
return word_times
|
||||
@@ -987,9 +959,6 @@ class ElevenLabsHttpTTSService(WordTTSService):
|
||||
if self._voice_settings:
|
||||
payload["voice_settings"] = self._voice_settings
|
||||
|
||||
if self._settings["apply_text_normalization"] is not None:
|
||||
payload["apply_text_normalization"] = self._settings["apply_text_normalization"]
|
||||
|
||||
language = self._settings["language"]
|
||||
if self._model_name in ELEVENLABS_MULTILINGUAL_MODELS and language:
|
||||
payload["language_code"] = language
|
||||
@@ -1010,6 +979,8 @@ class ElevenLabsHttpTTSService(WordTTSService):
|
||||
}
|
||||
if self._settings["optimize_streaming_latency"] is not None:
|
||||
params["optimize_streaming_latency"] = self._settings["optimize_streaming_latency"]
|
||||
if self._settings["apply_text_normalization"] is not None:
|
||||
params["apply_text_normalization"] = self._settings["apply_text_normalization"]
|
||||
|
||||
try:
|
||||
await self.start_ttfb_metrics()
|
||||
@@ -1070,14 +1041,6 @@ class ElevenLabsHttpTTSService(WordTTSService):
|
||||
logger.error(f"Error processing response: {e}", exc_info=True)
|
||||
continue
|
||||
|
||||
# After processing all chunks, emit any remaining partial word
|
||||
# since this is the end of the utterance
|
||||
if self._partial_word:
|
||||
final_word_time = [(self._partial_word, self._partial_word_start_time)]
|
||||
await self.add_word_timestamps(final_word_time)
|
||||
self._partial_word = ""
|
||||
self._partial_word_start_time = 0.0
|
||||
|
||||
# After processing all chunks, add the total utterance duration
|
||||
# to the cumulative time to ensure next utterance starts after this one
|
||||
if utterance_duration > 0:
|
||||
|
||||
@@ -225,8 +225,6 @@ class FishAudioTTSService(InterruptibleTTSService):
|
||||
start_message = {"event": "start", "request": {"text": "", **self._settings}}
|
||||
await self._websocket.send(ormsgpack.packb(start_message))
|
||||
logger.debug("Sent start message to Fish Audio")
|
||||
|
||||
await self._call_event_handler("on_connected")
|
||||
except Exception as e:
|
||||
logger.error(f"Fish Audio initialization error: {e}")
|
||||
self._websocket = None
|
||||
@@ -247,7 +245,6 @@ class FishAudioTTSService(InterruptibleTTSService):
|
||||
self._request_id = None
|
||||
self._started = False
|
||||
self._websocket = None
|
||||
await self._call_event_handler("on_disconnected")
|
||||
|
||||
async def flush_audio(self):
|
||||
"""Flush any buffered audio by sending a flush event to Fish Audio."""
|
||||
|
||||
@@ -730,8 +730,6 @@ class GoogleSTTService(STTService):
|
||||
self._request_queue = asyncio.Queue()
|
||||
self._streaming_task = self.create_task(self._stream_audio())
|
||||
|
||||
await self._call_event_handler("on_connected")
|
||||
|
||||
async def _disconnect(self):
|
||||
"""Clean up streaming recognition resources."""
|
||||
if self._streaming_task:
|
||||
@@ -739,8 +737,6 @@ class GoogleSTTService(STTService):
|
||||
await self.cancel_task(self._streaming_task)
|
||||
self._streaming_task = None
|
||||
|
||||
await self._call_event_handler("on_disconnected")
|
||||
|
||||
async def _request_generator(self):
|
||||
"""Generates requests for the streaming recognize method."""
|
||||
recognizer_path = f"projects/{self._project_id}/locations/{self._location}/recognizers/_"
|
||||
|
||||
@@ -222,7 +222,6 @@ class LmntTTSService(InterruptibleTTSService):
|
||||
# Send initialization message
|
||||
await self._websocket.send(json.dumps(init_msg))
|
||||
|
||||
await self._call_event_handler("on_connected")
|
||||
except Exception as e:
|
||||
logger.error(f"{self} initialization error: {e}")
|
||||
self._websocket = None
|
||||
@@ -244,7 +243,6 @@ class LmntTTSService(InterruptibleTTSService):
|
||||
finally:
|
||||
self._started = False
|
||||
self._websocket = None
|
||||
await self._call_event_handler("on_disconnected")
|
||||
|
||||
def _get_websocket(self):
|
||||
"""Get the WebSocket connection if available."""
|
||||
|
||||
@@ -293,8 +293,6 @@ class NeuphonicTTSService(InterruptibleTTSService):
|
||||
headers = {"x-api-key": self._api_key}
|
||||
|
||||
self._websocket = await websocket_connect(url, additional_headers=headers)
|
||||
|
||||
await self._call_event_handler("on_connected")
|
||||
except Exception as e:
|
||||
logger.error(f"{self} initialization error: {e}")
|
||||
self._websocket = None
|
||||
@@ -313,7 +311,6 @@ class NeuphonicTTSService(InterruptibleTTSService):
|
||||
finally:
|
||||
self._started = False
|
||||
self._websocket = None
|
||||
await self._call_event_handler("on_disconnected")
|
||||
|
||||
async def _receive_messages(self):
|
||||
"""Receive and process messages from Neuphonic WebSocket."""
|
||||
|
||||
@@ -14,7 +14,6 @@ from typing import AsyncGenerator, Dict, Literal, Optional
|
||||
|
||||
from loguru import logger
|
||||
from openai import AsyncOpenAI, BadRequestError
|
||||
from pydantic import BaseModel
|
||||
|
||||
from pipecat.frames.frames import (
|
||||
ErrorFrame,
|
||||
@@ -56,17 +55,6 @@ class OpenAITTSService(TTSService):
|
||||
|
||||
OPENAI_SAMPLE_RATE = 24000 # OpenAI TTS always outputs at 24kHz
|
||||
|
||||
class InputParams(BaseModel):
|
||||
"""Input parameters for OpenAI TTS configuration.
|
||||
|
||||
Parameters:
|
||||
instructions: Instructions to guide voice synthesis behavior.
|
||||
speed: Voice speed control (0.25 to 4.0, default 1.0).
|
||||
"""
|
||||
|
||||
instructions: Optional[str] = None
|
||||
speed: Optional[float] = None
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
*,
|
||||
@@ -77,7 +65,6 @@ class OpenAITTSService(TTSService):
|
||||
sample_rate: Optional[int] = None,
|
||||
instructions: Optional[str] = None,
|
||||
speed: Optional[float] = None,
|
||||
params: Optional[InputParams] = None,
|
||||
**kwargs,
|
||||
):
|
||||
"""Initialize OpenAI TTS service.
|
||||
@@ -90,11 +77,7 @@ class OpenAITTSService(TTSService):
|
||||
sample_rate: Output audio sample rate in Hz. If None, uses OpenAI's default 24kHz.
|
||||
instructions: Optional instructions to guide voice synthesis behavior.
|
||||
speed: Voice speed control (0.25 to 4.0, default 1.0).
|
||||
params: Optional synthesis controls (acting instructions, speed, ...).
|
||||
**kwargs: Additional keyword arguments passed to TTSService.
|
||||
|
||||
.. deprecated:: 0.0.91
|
||||
The `instructions` and `speed` parameters are deprecated, use `InputParams` instead.
|
||||
"""
|
||||
if sample_rate and sample_rate != self.OPENAI_SAMPLE_RATE:
|
||||
logger.warning(
|
||||
@@ -103,26 +86,12 @@ class OpenAITTSService(TTSService):
|
||||
)
|
||||
super().__init__(sample_rate=sample_rate, **kwargs)
|
||||
|
||||
self._speed = speed
|
||||
self.set_model_name(model)
|
||||
self.set_voice(voice)
|
||||
self._instructions = instructions
|
||||
self._client = AsyncOpenAI(api_key=api_key, base_url=base_url)
|
||||
|
||||
if instructions or speed:
|
||||
import warnings
|
||||
|
||||
with warnings.catch_warnings():
|
||||
warnings.simplefilter("always")
|
||||
warnings.warn(
|
||||
"The `instructions` and `speed` parameters are deprecated, use `InputParams` instead.",
|
||||
DeprecationWarning,
|
||||
stacklevel=2,
|
||||
)
|
||||
|
||||
self._settings = {
|
||||
"instructions": params.instructions if params else instructions,
|
||||
"speed": params.speed if params else speed,
|
||||
}
|
||||
|
||||
def can_generate_metrics(self) -> bool:
|
||||
"""Check if this service can generate processing metrics.
|
||||
|
||||
@@ -175,11 +144,11 @@ class OpenAITTSService(TTSService):
|
||||
"response_format": "pcm",
|
||||
}
|
||||
|
||||
if self._settings["instructions"]:
|
||||
create_params["instructions"] = self._settings["instructions"]
|
||||
if self._instructions:
|
||||
create_params["instructions"] = self._instructions
|
||||
|
||||
if self._settings["speed"]:
|
||||
create_params["speed"] = self._settings["speed"]
|
||||
if self._speed:
|
||||
create_params["speed"] = self._speed
|
||||
|
||||
async with self._client.audio.speech.with_streaming_response.create(
|
||||
**create_params
|
||||
|
||||
@@ -269,8 +269,6 @@ class PlayHTTTSService(InterruptibleTTSService):
|
||||
raise ValueError("WebSocket URL is not a string")
|
||||
|
||||
self._websocket = await websocket_connect(self._websocket_url)
|
||||
|
||||
await self._call_event_handler("on_connected")
|
||||
except ValueError as e:
|
||||
logger.error(f"{self} initialization error: {e}")
|
||||
self._websocket = None
|
||||
@@ -293,7 +291,6 @@ class PlayHTTTSService(InterruptibleTTSService):
|
||||
finally:
|
||||
self._request_id = None
|
||||
self._websocket = None
|
||||
await self._call_event_handler("on_disconnected")
|
||||
|
||||
async def _get_websocket_url(self):
|
||||
"""Retrieve WebSocket URL from PlayHT API."""
|
||||
|
||||
@@ -255,8 +255,6 @@ class RimeTTSService(AudioContextWordTTSService):
|
||||
url = f"{self._url}?{params}"
|
||||
headers = {"Authorization": f"Bearer {self._api_key}"}
|
||||
self._websocket = await websocket_connect(url, additional_headers=headers)
|
||||
|
||||
await self._call_event_handler("on_connected")
|
||||
except Exception as e:
|
||||
logger.error(f"{self} initialization error: {e}")
|
||||
self._websocket = None
|
||||
@@ -274,7 +272,6 @@ class RimeTTSService(AudioContextWordTTSService):
|
||||
finally:
|
||||
self._context_id = None
|
||||
self._websocket = None
|
||||
await self._call_event_handler("on_disconnected")
|
||||
|
||||
def _get_websocket(self):
|
||||
"""Get active websocket connection or raise exception."""
|
||||
|
||||
@@ -583,9 +583,7 @@ class RivaSegmentedSTTService(SegmentedSTTService):
|
||||
self._config.language_code = self._language
|
||||
|
||||
@traced_stt
|
||||
async def _handle_transcription(
|
||||
self, transcript: str, is_final: bool, language: Optional[Language] = None
|
||||
):
|
||||
async def _handle_transcription(self, transcript: str, language: Optional[Language] = None):
|
||||
"""Handle a transcription result with tracing."""
|
||||
pass
|
||||
|
||||
|
||||
@@ -76,29 +76,17 @@ class SarvamHttpTTSService(TTSService):
|
||||
|
||||
Example::
|
||||
|
||||
tts = SarvamHttpTTSService(
|
||||
tts = SarvamTTSService(
|
||||
api_key="your-api-key",
|
||||
voice_id="anushka",
|
||||
model="bulbul:v2",
|
||||
aiohttp_session=session,
|
||||
params=SarvamHttpTTSService.InputParams(
|
||||
params=SarvamTTSService.InputParams(
|
||||
language=Language.HI,
|
||||
pitch=0.1,
|
||||
pace=1.2
|
||||
)
|
||||
)
|
||||
|
||||
# For bulbul v3 beta with any speaker:
|
||||
tts_v3 = SarvamHttpTTSService(
|
||||
api_key="your-api-key",
|
||||
voice_id="speaker_name",
|
||||
model="bulbul:v3,
|
||||
aiohttp_session=session,
|
||||
params=SarvamHttpTTSService.InputParams(
|
||||
language=Language.HI,
|
||||
temperature=0.8
|
||||
)
|
||||
)
|
||||
"""
|
||||
|
||||
class InputParams(BaseModel):
|
||||
@@ -117,14 +105,6 @@ class SarvamHttpTTSService(TTSService):
|
||||
pace: Optional[float] = Field(default=1.0, ge=0.3, le=3.0)
|
||||
loudness: Optional[float] = Field(default=1.0, ge=0.1, le=3.0)
|
||||
enable_preprocessing: Optional[bool] = False
|
||||
temperature: Optional[float] = Field(
|
||||
default=0.6,
|
||||
ge=0.01,
|
||||
le=1.0,
|
||||
description="Controls the randomness of the output for bulbul v3 beta. "
|
||||
"Lower values make the output more focused and deterministic, while "
|
||||
"higher values make it more random. Range: 0.01 to 1.0. Default: 0.6.",
|
||||
)
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
@@ -144,7 +124,7 @@ class SarvamHttpTTSService(TTSService):
|
||||
api_key: Sarvam AI API subscription key.
|
||||
aiohttp_session: Shared aiohttp session for making requests.
|
||||
voice_id: Speaker voice ID (e.g., "anushka", "meera"). Defaults to "anushka".
|
||||
model: TTS model to use ("bulbul:v2" or "bulbul:v3-beta" or "bulbul:v3"). Defaults to "bulbul:v2".
|
||||
model: TTS model to use ("bulbul:v1" or "bulbul:v2"). Defaults to "bulbul:v2".
|
||||
base_url: Sarvam AI API base URL. Defaults to "https://api.sarvam.ai".
|
||||
sample_rate: Audio sample rate in Hz (8000, 16000, 22050, 24000). If None, uses default.
|
||||
params: Additional voice and preprocessing parameters. If None, uses defaults.
|
||||
@@ -158,32 +138,16 @@ class SarvamHttpTTSService(TTSService):
|
||||
self._base_url = base_url
|
||||
self._session = aiohttp_session
|
||||
|
||||
# Build base settings common to all models
|
||||
self._settings = {
|
||||
"language": (
|
||||
self.language_to_service_language(params.language) if params.language else "en-IN"
|
||||
),
|
||||
"pitch": params.pitch,
|
||||
"pace": params.pace,
|
||||
"loudness": params.loudness,
|
||||
"enable_preprocessing": params.enable_preprocessing,
|
||||
}
|
||||
|
||||
# Add model-specific parameters
|
||||
if model in ("bulbul:v3-beta", "bulbul:v3"):
|
||||
self._settings.update(
|
||||
{
|
||||
"temperature": getattr(params, "temperature", 0.6),
|
||||
"model": model,
|
||||
}
|
||||
)
|
||||
else:
|
||||
self._settings.update(
|
||||
{
|
||||
"pitch": params.pitch,
|
||||
"pace": params.pace,
|
||||
"loudness": params.loudness,
|
||||
"model": model,
|
||||
}
|
||||
)
|
||||
|
||||
self.set_model_name(model)
|
||||
self.set_voice(voice_id)
|
||||
|
||||
@@ -311,18 +275,6 @@ class SarvamTTSService(InterruptibleTTSService):
|
||||
pace=1.2
|
||||
)
|
||||
)
|
||||
|
||||
# For bulbul v3 beta with any speaker and temperature:
|
||||
# Note: pace and loudness are not supported for bulbul v3 and bulbul v3 beta
|
||||
tts_v3 = SarvamTTSService(
|
||||
api_key="your-api-key",
|
||||
voice_id="speaker_name",
|
||||
model="bulbul:v3",
|
||||
params=SarvamTTSService.InputParams(
|
||||
language=Language.HI,
|
||||
temperature=0.8
|
||||
)
|
||||
)
|
||||
"""
|
||||
|
||||
class InputParams(BaseModel):
|
||||
@@ -358,14 +310,6 @@ class SarvamTTSService(InterruptibleTTSService):
|
||||
output_audio_codec: Optional[str] = "linear16"
|
||||
output_audio_bitrate: Optional[str] = "128k"
|
||||
language: Optional[Language] = Language.EN
|
||||
temperature: Optional[float] = Field(
|
||||
default=0.6,
|
||||
ge=0.01,
|
||||
le=1.0,
|
||||
description="Controls the randomness of the output for bulbul v3 beta. "
|
||||
"Lower values make the output more focused and deterministic, while "
|
||||
"higher values make it more random. Range: 0.01 to 1.0. Default: 0.6.",
|
||||
)
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
@@ -385,7 +329,6 @@ class SarvamTTSService(InterruptibleTTSService):
|
||||
Args:
|
||||
api_key: Sarvam API key for authenticating TTS requests.
|
||||
model: Identifier of the Sarvam speech model (default "bulbul:v2").
|
||||
Supports "bulbul:v2", "bulbul:v3-beta" and "bulbul:v3".
|
||||
voice_id: Voice identifier for synthesis (default "anushka").
|
||||
url: WebSocket URL for connecting to the TTS backend (default production URL).
|
||||
aiohttp_session: Optional shared aiohttp session. To maintain backward compatibility.
|
||||
@@ -428,12 +371,15 @@ class SarvamTTSService(InterruptibleTTSService):
|
||||
self._api_key = api_key
|
||||
self.set_model_name(model)
|
||||
self.set_voice(voice_id)
|
||||
# Build base settings common to all models
|
||||
# Configuration parameters
|
||||
self._settings = {
|
||||
"target_language_code": (
|
||||
self.language_to_service_language(params.language) if params.language else "en-IN"
|
||||
),
|
||||
"pitch": params.pitch,
|
||||
"pace": params.pace,
|
||||
"speaker": voice_id,
|
||||
"loudness": params.loudness,
|
||||
"speech_sample_rate": 0,
|
||||
"enable_preprocessing": params.enable_preprocessing,
|
||||
"min_buffer_size": params.min_buffer_size,
|
||||
@@ -441,24 +387,6 @@ class SarvamTTSService(InterruptibleTTSService):
|
||||
"output_audio_codec": params.output_audio_codec,
|
||||
"output_audio_bitrate": params.output_audio_bitrate,
|
||||
}
|
||||
|
||||
# Add model-specific parameters
|
||||
if model in ("bulbul:v3-beta", "bulbul:v3"):
|
||||
self._settings.update(
|
||||
{
|
||||
"temperature": getattr(params, "temperature", 0.6),
|
||||
"model": model,
|
||||
}
|
||||
)
|
||||
else:
|
||||
self._settings.update(
|
||||
{
|
||||
"pitch": params.pitch,
|
||||
"pace": params.pace,
|
||||
"loudness": params.loudness,
|
||||
"model": model,
|
||||
}
|
||||
)
|
||||
self._started = False
|
||||
|
||||
self._receive_task = None
|
||||
@@ -597,7 +525,6 @@ class SarvamTTSService(InterruptibleTTSService):
|
||||
logger.debug("Connected to Sarvam TTS Websocket")
|
||||
await self._send_config()
|
||||
|
||||
await self._call_event_handler("on_connected")
|
||||
except Exception as e:
|
||||
logger.error(f"{self} initialization error: {e}")
|
||||
self._websocket = None
|
||||
@@ -629,10 +556,6 @@ class SarvamTTSService(InterruptibleTTSService):
|
||||
await self._websocket.close()
|
||||
except Exception as e:
|
||||
logger.error(f"{self} error closing websocket: {e}")
|
||||
finally:
|
||||
self._started = False
|
||||
self._websocket = None
|
||||
await self._call_event_handler("on_disconnected")
|
||||
|
||||
def _get_websocket(self):
|
||||
if self._websocket:
|
||||
|
||||
@@ -577,7 +577,6 @@ class SpeechmaticsSTTService(STTService):
|
||||
),
|
||||
)
|
||||
logger.debug(f"{self} Connected to Speechmatics STT service")
|
||||
await self._call_event_handler("on_connected")
|
||||
except Exception as e:
|
||||
logger.error(f"{self} Error connecting to Speechmatics: {e}")
|
||||
self._client = None
|
||||
@@ -596,7 +595,6 @@ class SpeechmaticsSTTService(STTService):
|
||||
logger.error(f"{self} Error closing Speechmatics client: {e}")
|
||||
finally:
|
||||
self._client = None
|
||||
await self._call_event_handler("on_disconnected")
|
||||
|
||||
def _process_config(self) -> None:
|
||||
"""Create a formatted STT transcription config.
|
||||
@@ -620,7 +618,7 @@ class SpeechmaticsSTTService(STTService):
|
||||
transcription_config.additional_vocab = [
|
||||
{
|
||||
"content": e.content,
|
||||
**({"sounds_like": e.sounds_like} if e.sounds_like else {}),
|
||||
"sounds_like": e.sounds_like,
|
||||
}
|
||||
for e in self._params.additional_vocab
|
||||
]
|
||||
|
||||
@@ -35,25 +35,6 @@ class STTService(AIService):
|
||||
Provides common functionality for STT services including audio passthrough,
|
||||
muting, settings management, and audio processing. Subclasses must implement
|
||||
the run_stt method to provide actual speech recognition.
|
||||
|
||||
Event handlers:
|
||||
on_connected: Called when connected to the STT service.
|
||||
on_connected: Called when disconnected from the STT service.
|
||||
on_connection_error: Called when a connection to the STT service error occurs.
|
||||
|
||||
Example::
|
||||
|
||||
@stt.event_handler("on_connected")
|
||||
async def on_connected(stt: STTService):
|
||||
logger.debug(f"STT connected")
|
||||
|
||||
@stt.event_handler("on_disconnected")
|
||||
async def on_disconnected(stt: STTService):
|
||||
logger.debug(f"STT disconnected")
|
||||
|
||||
@stt.event_handler("on_connection_error")
|
||||
async def on_connection_error(stt: STTService, error: str):
|
||||
logger.error(f"STT connection error: {error}")
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
@@ -81,10 +62,6 @@ class STTService(AIService):
|
||||
self._muted: bool = False
|
||||
self._user_id: str = ""
|
||||
|
||||
self._register_event_handler("on_connected")
|
||||
self._register_event_handler("on_disconnected")
|
||||
self._register_event_handler("on_connection_error")
|
||||
|
||||
@property
|
||||
def is_muted(self) -> bool:
|
||||
"""Check if the STT service is currently muted.
|
||||
@@ -315,6 +292,15 @@ class WebsocketSTTService(STTService, WebsocketService):
|
||||
|
||||
Combines STT functionality with websocket connectivity, providing automatic
|
||||
error handling and reconnection capabilities.
|
||||
|
||||
Event handlers:
|
||||
on_connection_error: Called when a websocket connection error occurs.
|
||||
|
||||
Example::
|
||||
|
||||
@stt.event_handler("on_connection_error")
|
||||
async def on_connection_error(stt: STTService, error: str):
|
||||
logger.error(f"STT connection error: {error}")
|
||||
"""
|
||||
|
||||
def __init__(self, *, reconnect_on_error: bool = True, **kwargs):
|
||||
@@ -326,6 +312,7 @@ class WebsocketSTTService(STTService, WebsocketService):
|
||||
"""
|
||||
STTService.__init__(self, **kwargs)
|
||||
WebsocketService.__init__(self, reconnect_on_error=reconnect_on_error, **kwargs)
|
||||
self._register_event_handler("on_connection_error")
|
||||
|
||||
async def _report_error(self, error: ErrorFrame):
|
||||
await self._call_event_handler("on_connection_error", error.error)
|
||||
|
||||
@@ -59,25 +59,6 @@ class TTSService(AIService):
|
||||
Provides common functionality for TTS services including text aggregation,
|
||||
filtering, audio generation, and frame management. Supports configurable
|
||||
sentence aggregation, silence insertion, and frame processing control.
|
||||
|
||||
Event handlers:
|
||||
on_connected: Called when connected to the STT service.
|
||||
on_connected: Called when disconnected from the STT service.
|
||||
on_connection_error: Called when a connection to the STT service error occurs.
|
||||
|
||||
Example::
|
||||
|
||||
@tts.event_handler("on_connected")
|
||||
async def on_connected(tts: TTSService):
|
||||
logger.debug(f"TTS connected")
|
||||
|
||||
@tts.event_handler("on_disconnected")
|
||||
async def on_disconnected(tts: TTSService):
|
||||
logger.debug(f"TTS disconnected")
|
||||
|
||||
@tts.event_handler("on_connection_error")
|
||||
async def on_connection_error(stt: TTSService, error: str):
|
||||
logger.error(f"TTS connection error: {error}")
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
@@ -162,10 +143,6 @@ class TTSService(AIService):
|
||||
|
||||
self._processing_text: bool = False
|
||||
|
||||
self._register_event_handler("on_connected")
|
||||
self._register_event_handler("on_disconnected")
|
||||
self._register_event_handler("on_connection_error")
|
||||
|
||||
@property
|
||||
def sample_rate(self) -> int:
|
||||
"""Get the current sample rate for audio output.
|
||||
@@ -649,6 +626,7 @@ class WebsocketTTSService(TTSService, WebsocketService):
|
||||
"""
|
||||
TTSService.__init__(self, **kwargs)
|
||||
WebsocketService.__init__(self, reconnect_on_error=reconnect_on_error, **kwargs)
|
||||
self._register_event_handler("on_connection_error")
|
||||
|
||||
async def _report_error(self, error: ErrorFrame):
|
||||
await self._call_event_handler("on_connection_error", error.error)
|
||||
@@ -700,6 +678,15 @@ class WebsocketWordTTSService(WordTTSService, WebsocketService):
|
||||
"""Base class for websocket-based TTS services that support word timestamps.
|
||||
|
||||
Combines word timestamp functionality with websocket connectivity.
|
||||
|
||||
Event handlers:
|
||||
on_connection_error: Called when a websocket connection error occurs.
|
||||
|
||||
Example::
|
||||
|
||||
@tts.event_handler("on_connection_error")
|
||||
async def on_connection_error(tts: TTSService, error: str):
|
||||
logger.error(f"TTS connection error: {error}")
|
||||
"""
|
||||
|
||||
def __init__(self, *, reconnect_on_error: bool = True, **kwargs):
|
||||
@@ -711,6 +698,7 @@ class WebsocketWordTTSService(WordTTSService, WebsocketService):
|
||||
"""
|
||||
WordTTSService.__init__(self, **kwargs)
|
||||
WebsocketService.__init__(self, reconnect_on_error=reconnect_on_error, **kwargs)
|
||||
self._register_event_handler("on_connection_error")
|
||||
|
||||
async def _report_error(self, error: ErrorFrame):
|
||||
await self._call_event_handler("on_connection_error", error.error)
|
||||
|
||||
@@ -232,9 +232,6 @@ class BaseInputTransport(FrameProcessor):
|
||||
"""
|
||||
# Cancel and wait for the audio input task to finish.
|
||||
await self._cancel_audio_task()
|
||||
# Stop audio filter.
|
||||
if self._params.audio_in_filter:
|
||||
await self._params.audio_in_filter.stop()
|
||||
|
||||
async def set_transport_ready(self, frame: StartFrame):
|
||||
"""Called when the transport is ready to stream.
|
||||
|
||||
@@ -293,15 +293,15 @@ class BaseOutputTransport(FrameProcessor):
|
||||
"""
|
||||
await super().process_frame(frame, direction)
|
||||
|
||||
#
|
||||
# System frames (like InterruptionFrame) are pushed immediately. Other
|
||||
# frames require order so they are put in the sink queue.
|
||||
#
|
||||
if isinstance(frame, StartFrame):
|
||||
# Push StartFrame before start(), because we want StartFrame to be
|
||||
# processed by every processor before any other frame is processed.
|
||||
await self.push_frame(frame, direction)
|
||||
await self.start(frame)
|
||||
elif isinstance(frame, EndFrame):
|
||||
await self.stop(frame)
|
||||
# Keep pushing EndFrame down so all the pipeline stops nicely.
|
||||
await self.push_frame(frame, direction)
|
||||
elif isinstance(frame, CancelFrame):
|
||||
await self.cancel(frame)
|
||||
await self.push_frame(frame, direction)
|
||||
@@ -314,6 +314,21 @@ class BaseOutputTransport(FrameProcessor):
|
||||
await self.write_dtmf(frame)
|
||||
elif isinstance(frame, SystemFrame):
|
||||
await self.push_frame(frame, direction)
|
||||
# Control frames.
|
||||
elif isinstance(frame, EndFrame):
|
||||
await self.stop(frame)
|
||||
# Keep pushing EndFrame down so all the pipeline stops nicely.
|
||||
await self.push_frame(frame, direction)
|
||||
elif isinstance(frame, MixerControlFrame):
|
||||
await self._handle_frame(frame)
|
||||
# Other frames.
|
||||
elif isinstance(frame, OutputAudioRawFrame):
|
||||
await self._handle_frame(frame)
|
||||
elif isinstance(frame, (OutputImageRawFrame, SpriteFrame)):
|
||||
await self._handle_frame(frame)
|
||||
# TODO(aleix): Images and audio should support presentation timestamps.
|
||||
elif frame.pts:
|
||||
await self._handle_frame(frame)
|
||||
elif direction == FrameDirection.UPSTREAM:
|
||||
await self.push_frame(frame, direction)
|
||||
else:
|
||||
@@ -395,13 +410,6 @@ class BaseOutputTransport(FrameProcessor):
|
||||
|
||||
# Indicates if the bot is currently speaking.
|
||||
self._bot_speaking = False
|
||||
# Last time a BotSpeakingFrame was pushed.
|
||||
self._bot_speaking_frame_time = 0
|
||||
# How often a BotSpeakingFrame should be pushed (value should be
|
||||
# lower than the audio chunks).
|
||||
self._bot_speaking_frame_period = 0.2
|
||||
# Last time the bot actually spoke.
|
||||
self._bot_speech_last_time = 0
|
||||
|
||||
self._audio_task: Optional[asyncio.Task] = None
|
||||
self._video_task: Optional[asyncio.Task] = None
|
||||
@@ -593,71 +601,39 @@ class BaseOutputTransport(FrameProcessor):
|
||||
|
||||
async def _bot_started_speaking(self):
|
||||
"""Handle bot started speaking event."""
|
||||
if self._bot_speaking:
|
||||
return
|
||||
if not self._bot_speaking:
|
||||
logger.debug(
|
||||
f"Bot{f' [{self._destination}]' if self._destination else ''} started speaking"
|
||||
)
|
||||
|
||||
logger.debug(
|
||||
f"Bot{f' [{self._destination}]' if self._destination else ''} started speaking"
|
||||
)
|
||||
downstream_frame = BotStartedSpeakingFrame()
|
||||
downstream_frame.transport_destination = self._destination
|
||||
upstream_frame = BotStartedSpeakingFrame()
|
||||
upstream_frame.transport_destination = self._destination
|
||||
await self._transport.push_frame(downstream_frame)
|
||||
await self._transport.push_frame(upstream_frame, FrameDirection.UPSTREAM)
|
||||
|
||||
downstream_frame = BotStartedSpeakingFrame()
|
||||
downstream_frame.transport_destination = self._destination
|
||||
upstream_frame = BotStartedSpeakingFrame()
|
||||
upstream_frame.transport_destination = self._destination
|
||||
await self._transport.push_frame(downstream_frame)
|
||||
await self._transport.push_frame(upstream_frame, FrameDirection.UPSTREAM)
|
||||
|
||||
self._bot_speaking = True
|
||||
self._bot_speaking = True
|
||||
|
||||
async def _bot_stopped_speaking(self):
|
||||
"""Handle bot stopped speaking event."""
|
||||
if not self._bot_speaking:
|
||||
return
|
||||
if self._bot_speaking:
|
||||
logger.debug(
|
||||
f"Bot{f' [{self._destination}]' if self._destination else ''} stopped speaking"
|
||||
)
|
||||
|
||||
logger.debug(
|
||||
f"Bot{f' [{self._destination}]' if self._destination else ''} stopped speaking"
|
||||
)
|
||||
downstream_frame = BotStoppedSpeakingFrame()
|
||||
downstream_frame.transport_destination = self._destination
|
||||
upstream_frame = BotStoppedSpeakingFrame()
|
||||
upstream_frame.transport_destination = self._destination
|
||||
await self._transport.push_frame(downstream_frame)
|
||||
await self._transport.push_frame(upstream_frame, FrameDirection.UPSTREAM)
|
||||
|
||||
downstream_frame = BotStoppedSpeakingFrame()
|
||||
downstream_frame.transport_destination = self._destination
|
||||
upstream_frame = BotStoppedSpeakingFrame()
|
||||
upstream_frame.transport_destination = self._destination
|
||||
await self._transport.push_frame(downstream_frame)
|
||||
await self._transport.push_frame(upstream_frame, FrameDirection.UPSTREAM)
|
||||
self._bot_speaking = False
|
||||
|
||||
self._bot_speaking = False
|
||||
|
||||
# Clean audio buffer (there could be tiny left overs if not multiple
|
||||
# to our output chunk size).
|
||||
self._audio_buffer = bytearray()
|
||||
|
||||
async def _bot_currently_speaking(self):
|
||||
"""Handle bot speaking event."""
|
||||
await self._bot_started_speaking()
|
||||
|
||||
diff_time = time.time() - self._bot_speaking_frame_time
|
||||
if diff_time >= self._bot_speaking_frame_period:
|
||||
await self._transport.push_frame(BotSpeakingFrame())
|
||||
await self._transport.push_frame(BotSpeakingFrame(), FrameDirection.UPSTREAM)
|
||||
self._bot_speaking_frame_time = time.time()
|
||||
|
||||
self._bot_speech_last_time = time.time()
|
||||
|
||||
async def _maybe_bot_currently_speaking(self, frame: SpeechOutputAudioRawFrame):
|
||||
if not is_silence(frame.audio):
|
||||
await self._bot_currently_speaking()
|
||||
else:
|
||||
silence_duration = time.time() - self._bot_speech_last_time
|
||||
if silence_duration > BOT_VAD_STOP_SECS:
|
||||
await self._bot_stopped_speaking()
|
||||
|
||||
async def _handle_bot_speech(self, frame: Frame):
|
||||
# TTS case.
|
||||
if isinstance(frame, TTSAudioRawFrame):
|
||||
await self._bot_currently_speaking()
|
||||
# Speech stream case.
|
||||
elif isinstance(frame, SpeechOutputAudioRawFrame):
|
||||
await self._maybe_bot_currently_speaking(frame)
|
||||
# Clean audio buffer (there could be tiny left overs if not multiple
|
||||
# to our output chunk size).
|
||||
self._audio_buffer = bytearray()
|
||||
|
||||
async def _handle_frame(self, frame: Frame):
|
||||
"""Handle various frame types with appropriate processing.
|
||||
@@ -665,9 +641,7 @@ class BaseOutputTransport(FrameProcessor):
|
||||
Args:
|
||||
frame: The frame to handle.
|
||||
"""
|
||||
if isinstance(frame, OutputAudioRawFrame):
|
||||
await self._handle_bot_speech(frame)
|
||||
elif isinstance(frame, OutputImageRawFrame):
|
||||
if isinstance(frame, OutputImageRawFrame):
|
||||
await self._set_video_image(frame)
|
||||
elif isinstance(frame, SpriteFrame):
|
||||
await self._set_video_images(frame.images)
|
||||
@@ -731,7 +705,39 @@ class BaseOutputTransport(FrameProcessor):
|
||||
|
||||
async def _audio_task_handler(self):
|
||||
"""Main audio processing task handler."""
|
||||
# Push a BotSpeakingFrame every 200ms, we don't really need to push it
|
||||
# at every audio chunk. If the audio chunk is bigger than 200ms, push at
|
||||
# every audio chunk.
|
||||
TOTAL_CHUNK_MS = self._params.audio_out_10ms_chunks * 10
|
||||
BOT_SPEAKING_CHUNK_PERIOD = max(int(200 / TOTAL_CHUNK_MS), 1)
|
||||
bot_speaking_counter = 0
|
||||
speech_last_speaking_time = 0
|
||||
|
||||
async for frame in self._next_frame():
|
||||
# Notify the bot started speaking upstream if necessary and that
|
||||
# it's actually speaking.
|
||||
is_speaking = False
|
||||
if isinstance(frame, TTSAudioRawFrame):
|
||||
is_speaking = True
|
||||
elif isinstance(frame, SpeechOutputAudioRawFrame):
|
||||
if not is_silence(frame.audio):
|
||||
is_speaking = True
|
||||
speech_last_speaking_time = time.time()
|
||||
else:
|
||||
silence_duration = time.time() - speech_last_speaking_time
|
||||
if silence_duration > BOT_VAD_STOP_SECS:
|
||||
await self._bot_stopped_speaking()
|
||||
|
||||
if is_speaking:
|
||||
await self._bot_started_speaking()
|
||||
if bot_speaking_counter % BOT_SPEAKING_CHUNK_PERIOD == 0:
|
||||
await self._transport.push_frame(BotSpeakingFrame())
|
||||
await self._transport.push_frame(
|
||||
BotSpeakingFrame(), FrameDirection.UPSTREAM
|
||||
)
|
||||
bot_speaking_counter = 0
|
||||
bot_speaking_counter += 1
|
||||
|
||||
# No need to push EndFrame, it's pushed from process_frame().
|
||||
if isinstance(frame, EndFrame):
|
||||
break
|
||||
|
||||
@@ -689,8 +689,3 @@ class SmallWebRTCConnection(BaseObject):
|
||||
)()
|
||||
if track:
|
||||
track.set_enabled(signalling_message.enabled)
|
||||
|
||||
async def add_ice_candidate(self, candidate):
|
||||
"""Handle incoming ICE candidates."""
|
||||
logger.debug(f"Adding remote candidate: {candidate}")
|
||||
await self.pc.addIceCandidate(candidate)
|
||||
|
||||
@@ -14,7 +14,6 @@ from dataclasses import dataclass
|
||||
from enum import Enum
|
||||
from typing import Any, Awaitable, Callable, Dict, List, Optional
|
||||
|
||||
from aiortc.sdp import candidate_from_sdp
|
||||
from fastapi import HTTPException
|
||||
from loguru import logger
|
||||
|
||||
@@ -40,34 +39,6 @@ class SmallWebRTCRequest:
|
||||
request_data: Optional[Any] = None
|
||||
|
||||
|
||||
@dataclass
|
||||
class IceCandidate:
|
||||
"""The remote ice candidate object received from the peer connection.
|
||||
|
||||
Parameters:
|
||||
candidate: The ice candidate patch SDP string (Session Description Protocol).
|
||||
sdp_mid: The SDP mid for the candidate patch.
|
||||
sdp_mline_index: The SDP mline index for the candidate patch.
|
||||
"""
|
||||
|
||||
candidate: str
|
||||
sdp_mid: str
|
||||
sdp_mline_index: int
|
||||
|
||||
|
||||
@dataclass
|
||||
class SmallWebRTCPatchRequest:
|
||||
"""Small WebRTC transport session arguments for the runner.
|
||||
|
||||
Parameters:
|
||||
pc_id: Identifier for the peer connection.
|
||||
candidates: A list of ICE candidate patches.
|
||||
"""
|
||||
|
||||
pc_id: str
|
||||
candidates: List[IceCandidate]
|
||||
|
||||
|
||||
class ConnectionMode(Enum):
|
||||
"""Enum defining the connection handling modes."""
|
||||
|
||||
@@ -226,19 +197,6 @@ class SmallWebRTCRequestHandler:
|
||||
logger.debug(f"SmallWebRTC request details: {request}")
|
||||
raise
|
||||
|
||||
async def handle_patch_request(self, request: SmallWebRTCPatchRequest):
|
||||
"""Handle a SmallWebRTC patch candidate request."""
|
||||
peer_connection = self._pcs_map.get(request.pc_id)
|
||||
|
||||
if not peer_connection:
|
||||
raise HTTPException(status_code=404, detail="Peer connection not found")
|
||||
|
||||
for c in request.candidates:
|
||||
candidate = candidate_from_sdp(c.candidate)
|
||||
candidate.sdpMid = c.sdp_mid
|
||||
candidate.sdpMLineIndex = c.sdp_mline_index
|
||||
await peer_connection.add_ice_candidate(candidate)
|
||||
|
||||
async def close(self):
|
||||
"""Clear the connection map."""
|
||||
coros = [pc.disconnect() for pc in self._pcs_map.values()]
|
||||
|
||||
@@ -47,7 +47,6 @@ SENTENCE_ENDING_PUNCTUATION: FrozenSet[str] = frozenset(
|
||||
"!",
|
||||
"?",
|
||||
";",
|
||||
"…",
|
||||
# East Asian punctuation (Chinese (Traditional & Simplified), Japanese, Korean)
|
||||
"。", # Ideographic full stop
|
||||
"？", # Full-width question mark
|
||||
|
||||
@@ -254,7 +254,7 @@ class TestPipelineTask(unittest.IsolatedAsyncioTestCase):
|
||||
|
||||
try:
|
||||
await asyncio.wait_for(
|
||||
task.run(PipelineTaskParams(loop=asyncio.get_event_loop())),
|
||||
asyncio.shield(task.run(PipelineTaskParams(loop=asyncio.get_event_loop()))),
|
||||
timeout=1.0,
|
||||
)
|
||||
except asyncio.TimeoutError:
|
||||
@@ -290,7 +290,7 @@ class TestPipelineTask(unittest.IsolatedAsyncioTestCase):
|
||||
await task.queue_frame(TextFrame(text="Hello!"))
|
||||
try:
|
||||
await asyncio.wait_for(
|
||||
task.run(PipelineTaskParams(loop=asyncio.get_event_loop())),
|
||||
asyncio.shield(task.run(PipelineTaskParams(loop=asyncio.get_event_loop()))),
|
||||
timeout=1.0,
|
||||
)
|
||||
except asyncio.TimeoutError:
|
||||
@@ -301,8 +301,11 @@ class TestPipelineTask(unittest.IsolatedAsyncioTestCase):
|
||||
identity = IdentityFilter()
|
||||
pipeline = Pipeline([identity])
|
||||
task = PipelineTask(pipeline, idle_timeout_secs=0.2)
|
||||
# This shouldn't freeze, so nothing to check really.
|
||||
await task.run(PipelineTaskParams(loop=asyncio.get_event_loop()))
|
||||
try:
|
||||
await task.run(PipelineTaskParams(loop=asyncio.get_event_loop()))
|
||||
assert False
|
||||
except asyncio.CancelledError:
|
||||
assert True
|
||||
|
||||
async def test_no_idle_task(self):
|
||||
identity = IdentityFilter()
|
||||
@@ -310,7 +313,7 @@ class TestPipelineTask(unittest.IsolatedAsyncioTestCase):
|
||||
task = PipelineTask(pipeline, idle_timeout_secs=0.2, cancel_on_idle_timeout=False)
|
||||
try:
|
||||
await asyncio.wait_for(
|
||||
task.run(PipelineTaskParams(loop=asyncio.get_event_loop())),
|
||||
asyncio.shield(task.run(PipelineTaskParams(loop=asyncio.get_event_loop()))),
|
||||
timeout=0.3,
|
||||
)
|
||||
except asyncio.TimeoutError:
|
||||
@@ -329,7 +332,11 @@ class TestPipelineTask(unittest.IsolatedAsyncioTestCase):
|
||||
),
|
||||
idle_timeout_secs=0.3,
|
||||
)
|
||||
await task.run(PipelineTaskParams(loop=asyncio.get_event_loop()))
|
||||
try:
|
||||
await task.run(PipelineTaskParams(loop=asyncio.get_event_loop()))
|
||||
assert False
|
||||
except asyncio.CancelledError:
|
||||
assert True
|
||||
|
||||
async def test_idle_task_event_handler_no_frames(self):
|
||||
identity = IdentityFilter()
|
||||
@@ -344,8 +351,11 @@ class TestPipelineTask(unittest.IsolatedAsyncioTestCase):
|
||||
idle_timeout = True
|
||||
await task.cancel()
|
||||
|
||||
await task.run(PipelineTaskParams(loop=asyncio.get_event_loop()))
|
||||
assert idle_timeout
|
||||
try:
|
||||
await task.run(PipelineTaskParams(loop=asyncio.get_event_loop()))
|
||||
assert False
|
||||
except asyncio.CancelledError:
|
||||
assert idle_timeout
|
||||
|
||||
async def test_idle_task_event_handler_quiet_user(self):
|
||||
identity = IdentityFilter()
|
||||
@@ -406,15 +416,12 @@ class TestPipelineTask(unittest.IsolatedAsyncioTestCase):
|
||||
asyncio.create_task(delayed_frames()),
|
||||
]
|
||||
|
||||
_, pending = await asyncio.wait(tasks, return_when=asyncio.FIRST_COMPLETED)
|
||||
await asyncio.wait(tasks, return_when=asyncio.FIRST_COMPLETED)
|
||||
|
||||
diff_time = time.time() - start_time
|
||||
|
||||
self.assertGreater(diff_time, sleep_time_secs * 3)
|
||||
|
||||
# Wait for the pending tasks to complete.
|
||||
await asyncio.gather(*pending)
|
||||
|
||||
async def test_task_cancel_timeout(self):
|
||||
class CancelFilter(FrameProcessor):
|
||||
def __init__(self, **kwargs):
|
||||
|
||||
@@ -7,12 +7,10 @@
|
||||
"""Unit tests for ServiceSwitcher and related components."""
|
||||
|
||||
import unittest
|
||||
from dataclasses import dataclass
|
||||
|
||||
from pipecat.frames.frames import (
|
||||
Frame,
|
||||
ManuallySwitchServiceFrame,
|
||||
SystemFrame,
|
||||
TextFrame,
|
||||
)
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
@@ -54,13 +52,6 @@ class MockFrameProcessor(FrameProcessor):
|
||||
self.frame_count = 0
|
||||
|
||||
|
||||
@dataclass
|
||||
class DummySystemFrame(SystemFrame):
|
||||
"""A dummy system frame for testing purposes."""
|
||||
|
||||
text: str = ""
|
||||
|
||||
|
||||
class TestServiceSwitcherStrategyManual(unittest.IsolatedAsyncioTestCase):
|
||||
"""Test cases for ServiceSwitcherStrategyManual."""
|
||||
|
||||
@@ -149,22 +140,14 @@ class TestServiceSwitcher(unittest.IsolatedAsyncioTestCase):
|
||||
# Send some test frames
|
||||
frames_to_send = [
|
||||
TextFrame(text="Hello 1"),
|
||||
DummySystemFrame(text="System Message 1"),
|
||||
TextFrame(text="Hello 2"),
|
||||
DummySystemFrame(text="System Message 2"),
|
||||
TextFrame(text="Hello 3"),
|
||||
]
|
||||
|
||||
await run_test(
|
||||
switcher,
|
||||
frames_to_send=frames_to_send,
|
||||
expected_down_frames=[
|
||||
DummySystemFrame,
|
||||
DummySystemFrame,
|
||||
TextFrame,
|
||||
TextFrame,
|
||||
TextFrame,
|
||||
],
|
||||
expected_down_frames=[TextFrame, TextFrame, TextFrame],
|
||||
expected_up_frames=[], # Expect no error frames
|
||||
)
|
||||
|
||||
@@ -173,13 +156,7 @@ class TestServiceSwitcher(unittest.IsolatedAsyncioTestCase):
|
||||
text_frames = [f for f in self.service1.processed_frames if isinstance(f, TextFrame)]
|
||||
self.assertEqual(len(text_frames), 3)
|
||||
|
||||
# Only service1 should have processed the system frames
|
||||
system_frames = [
|
||||
f for f in self.service1.processed_frames if isinstance(f, DummySystemFrame)
|
||||
]
|
||||
self.assertEqual(len(system_frames), 2)
|
||||
|
||||
# Check that other services don't receive text frames (they still get StartFrame/EndFrame)
|
||||
# Check that other services don't receive text frames (they might get StartFrame/EndFrame)
|
||||
service2_text_frames = [
|
||||
f for f in self.service2.processed_frames if isinstance(f, TextFrame)
|
||||
]
|
||||
@@ -189,24 +166,10 @@ class TestServiceSwitcher(unittest.IsolatedAsyncioTestCase):
|
||||
self.assertEqual(len(service2_text_frames), 0)
|
||||
self.assertEqual(len(service3_text_frames), 0)
|
||||
|
||||
# Check that other services don't receive dummy system frames (they still get StartFrame/EndFrame)
|
||||
service2_system_frames = [
|
||||
f for f in self.service2.processed_frames if isinstance(f, DummySystemFrame)
|
||||
]
|
||||
service3_system_frames = [
|
||||
f for f in self.service3.processed_frames if isinstance(f, DummySystemFrame)
|
||||
]
|
||||
self.assertEqual(len(service2_system_frames), 0)
|
||||
self.assertEqual(len(service3_system_frames), 0)
|
||||
|
||||
# Verify the actual text frames processed
|
||||
for i, frame in enumerate(text_frames):
|
||||
self.assertEqual(frame.text, f"Hello {i + 1}")
|
||||
|
||||
# Verify the actual system frames processed
|
||||
for i, frame in enumerate(system_frames):
|
||||
self.assertEqual(frame.text, f"System Message {i + 1}")
|
||||
|
||||
async def test_service_switching(self):
|
||||
"""Test that after service switching using ManuallySwitchServiceFrame, the new active service receives frames while others don't."""
|
||||
switcher = ServiceSwitcher(self.services, ServiceSwitcherStrategyManual)
|
||||
|
||||
423
uv.lock
generated
423
uv.lock
generated
@@ -410,16 +410,16 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "aws-sdk-bedrock-runtime"
|
||||
version = "0.1.1"
|
||||
version = "0.1.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "smithy-aws-core", extra = ["eventstream", "json"], marker = "python_full_version >= '3.12'" },
|
||||
{ name = "smithy-core", marker = "python_full_version >= '3.12'" },
|
||||
{ name = "smithy-http", extra = ["awscrt"], marker = "python_full_version >= '3.12'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/1d/78/48574454b3cac869df67665e4a403ebfc3abfcfba2c2ff01ccfd67d55f8f/aws_sdk_bedrock_runtime-0.1.1.tar.gz", hash = "sha256:c896f99e675c3a1ab600633a07b785f3dc9fe8ab94f640b1f992b63da2dfc784", size = 82446, upload-time = "2025-10-21T20:25:25.845Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/84/e1/39971b907c83a7525bab112c9b395e1bb6d4bc23bc1712d6d7a050662217/aws_sdk_bedrock_runtime-0.1.0.tar.gz", hash = "sha256:bd062de5a48404f64e1dfe6fb8841fbbf68e8f1798c357d14eb427274cb96a2b", size = 85419, upload-time = "2025-09-29T19:40:01.855Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/83/07/62c0b70223d178c138f29124ac2f7973a6ba803abc7735b6a01a85217f3d/aws_sdk_bedrock_runtime-0.1.1-py3-none-any.whl", hash = "sha256:c0336b377b2112cf88197d3d44302fbeb3efb1101989fa49ae55e78f49cfe345", size = 74954, upload-time = "2025-10-21T20:25:24.973Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/3d/e1/5b36bffe85010cdcd44730d1c2d5244653d57c002f440141d7fc3b9f1347/aws_sdk_bedrock_runtime-0.1.0-py3-none-any.whl", hash = "sha256:aac6ff47069d456ca5e23083d96a01e3e0cbc215414e6753c289d7d9efef3335", size = 78853, upload-time = "2025-09-29T19:40:00.341Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -433,31 +433,31 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "awscrt"
|
||||
version = "0.28.2"
|
||||
version = "0.28.1"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/d4/1b/a885a699217967c3ff0e1c49ac5b1e2a050d1a8b87d1e85e958a56e3d3f5/awscrt-0.28.2.tar.gz", hash = "sha256:9715a888f2042e710dc8aeb355963a29b77e7a4cc25a14659cebd21a5fa476c1", size = 37894849, upload-time = "2025-10-14T19:06:16.867Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/a0/1c/5c9e6a7375c2a1355aadeb2d06c96c95934ec37ff29ebaab2919f59c3ff1/awscrt-0.28.1.tar.gz", hash = "sha256:70a28fd6ff3e0abb7854ea8a9133bc9e5de681a0d9bdbd8a599a23d13a448685", size = 37956730, upload-time = "2025-09-19T00:58:31.564Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/73/b4/1a566e493bdfa6e918ba78bcd2e45dda99a25407a4fd974db2666228d154/awscrt-0.28.2-cp310-cp310-macosx_10_15_universal2.whl", hash = "sha256:bec19c0dd780293a26c809aabb9f7675b28cb3a1bf05b4a5bc9f28d5ced75a81", size = 3380735, upload-time = "2025-10-14T19:05:16.58Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/1f/53/6602a87aead1d413c7bd77d059b301745146635cda99ee2a61ec0d23691e/awscrt-0.28.2-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:01f33076759ba6285f25ccc6016355607df2e715d0bab3a1ef2416b87a6c3ade", size = 3827084, upload-time = "2025-10-14T19:05:19.335Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/d8/62/61fe39ae5950ad00e10dcbf6e4f4f344dc93957757160c0000390331a11b/awscrt-0.28.2-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:2b5c807b9972795ce54c05aea6918c60983c51d879ebbff7a67adb8b0d28a121", size = 4092678, upload-time = "2025-10-14T19:05:20.8Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/25/7d/e38f18cfb203e8f09842c0e3f422992887ce285ecc3bf18816d559a13c80/awscrt-0.28.2-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:bf4ff9c8c6a233246320c2d41d939b6e25cdae97728d827186e4771a9edda688", size = 3749978, upload-time = "2025-10-14T19:05:22.16Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/16/6f/e8a3c0daed8f7b60c76fc2721bd4e83580ddecace24e0cb0ebb99564f699/awscrt-0.28.2-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:0c738b83b66d1a8b43089556247fbe4adf2b73d610c7938d3bae1718a0fe8b1d", size = 3977237, upload-time = "2025-10-14T19:05:23.368Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/92/3d/8400203f02dd924bcc8255703179b0c26efd03c84f838db6f026fcef9ba6/awscrt-0.28.2-cp310-cp310-win32.whl", hash = "sha256:23c30004c736a2f826a32c9720f1ccf71e8e4deb8535da5915d6073604853098", size = 3919413, upload-time = "2025-10-14T19:05:24.477Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/c0/5e/b5ccf377880a70425b100f1e5f5ba516ff75e291585b3dc129239fbd1ec3/awscrt-0.28.2-cp310-cp310-win_amd64.whl", hash = "sha256:859ae8a195d51f15b631147d6792953a563bfe0a1cc7a75b6750977634de54b8", size = 4056024, upload-time = "2025-10-14T19:05:25.956Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/ed/79/94e9f0ee7c60ec6233c7ad6293589c56d5145172e49eb5328eda37d3fdd1/awscrt-0.28.2-cp311-abi3-macosx_10_15_universal2.whl", hash = "sha256:025eab99b58586d8c95f8fafe1f4695ad477eda20d1207240ee4f8ee79742059", size = 3381061, upload-time = "2025-10-14T19:05:27.187Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/2d/b8/0da80dd58682ddf3ec204e877d5891198654647c085e65b6b8eacd214edb/awscrt-0.28.2-cp311-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:e5c18d035d6cd92228e1db2f043517c1bcf9e0f6430c0af60cc34257dcca092c", size = 3788011, upload-time = "2025-10-14T19:05:28.768Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/d6/d2/f51cf4364364399fe90d557e2fed14c1f114720191a5825898b1242bd607/awscrt-0.28.2-cp311-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:c75f077e90d0220a49b75a9bca914e5aa1a3c8f28af6bce4d0332be0b98dd3cb", size = 4055226, upload-time = "2025-10-14T19:05:30.054Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/41/47/0fde8738a8c76de278ce431d8468ef18aeaca424329decca9ad5092df812/awscrt-0.28.2-cp311-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:1432c5c59a7e36b33eb2746cfbf30058f19ed43f2c117863897681f70bc246ba", size = 3692839, upload-time = "2025-10-14T19:05:31.471Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/18/25/cb3762f6b47fe503eea7f337eca7cfd044ab28bcc2452fbf298c6492ec8b/awscrt-0.28.2-cp311-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:f96703c30b22ba1e43e1bb2fe996ac7af513bea411c54dbf09a3a1af329b9a76", size = 3918023, upload-time = "2025-10-14T19:05:33.162Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/95/0a/0b609acd45dbb83c04c7ecb8c7c789f5c15bbdd422129360bde093bc4a99/awscrt-0.28.2-cp311-abi3-win32.whl", hash = "sha256:3e94f63497b454d30892d7a7ce917a451c6f33590964d3a475d93f93b20083b6", size = 3917048, upload-time = "2025-10-14T19:05:34.745Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/d1/38/bf33abd6d09c8572f8e09488db2b0a60124767d7f5d6d9a33cf8b051b7af/awscrt-0.28.2-cp311-abi3-win_amd64.whl", hash = "sha256:3e094772b1f6fd0f8c5f7cf37655d0984739f99493f66f534979a2a7bb7fc9f6", size = 4052877, upload-time = "2025-10-14T19:05:36.01Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/10/71/4be198e472d95702434cee1f9dd889c56e22bea8554b466fad754148fd24/awscrt-0.28.2-cp313-abi3-macosx_10_15_universal2.whl", hash = "sha256:5fda9e7d0eb800491fadebe2b6c2560ac2f5742b60f4106440dca4b49da7fb03", size = 3379585, upload-time = "2025-10-14T19:05:37.225Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/43/09/77084249d07dca71352341ad3fbcfa75deaccf25bd65f9fdbb36ce1f978b/awscrt-0.28.2-cp313-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:994a795bdc83344922a15891abb30155ec292093e856eef3929dd63dd6cadaca", size = 3779843, upload-time = "2025-10-14T19:05:38.774Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/a6/bb/fcee9365e58e5860582398317571a9a5517da258cd81c3d987b9882f61d4/awscrt-0.28.2-cp313-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:28537c4517168927ef74aa007a2e0c9f436921227934d82da31e9a1cec7e0c4a", size = 4049154, upload-time = "2025-10-14T19:05:40.301Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/ba/8e/ac92b2707dbe05e56d0dd5af73cb4e07a3da4aee66936071123966523759/awscrt-0.28.2-cp313-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:b9fc6be63832da3ff244d56c7d9a43326d89d79e68162419c35f33e6ad033be0", size = 3683672, upload-time = "2025-10-14T19:05:41.536Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/ef/d0/15308ec37e762691f5d1871b0f1a6e462da8e421c6c38d6724e3cf0994b2/awscrt-0.28.2-cp313-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:efb57103a368de1d33148cb70a382c4f82ac376c744de9484e0f621cef8313f3", size = 3912823, upload-time = "2025-10-14T19:05:43.781Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/bc/cd/7693b1d72069908b7a3ee30e4ef2b5fc8f54948a96397729277cb0b0c7b4/awscrt-0.28.2-cp313-abi3-win32.whl", hash = "sha256:594dc61f4f0c1c9fb7292364d25c21810b3608cd67c0de78a032ad48f7bfd88c", size = 3911514, upload-time = "2025-10-14T19:05:45.019Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/93/d6/5d8545c967690f03d55d44ed56ceff26d88363cd7d0435fd80a1c843ac2a/awscrt-0.28.2-cp313-abi3-win_amd64.whl", hash = "sha256:a17f0ab9dc5e5301da0fb00ccc4511a136d13abbd4a9564827547333fcd7ba16", size = 4047912, upload-time = "2025-10-14T19:05:46.302Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/2d/75/dd62276f2907a9ffcf9f8f780c08ce9938bd0550a15c887db198b47f24d3/awscrt-0.28.1-cp310-cp310-macosx_10_15_universal2.whl", hash = "sha256:47f885104065918d311102e2b08b943966717c0f3b0c5de5908d2fd08de32198", size = 3376838, upload-time = "2025-09-19T00:57:32.988Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/a7/93/562709cdf13a7606548426ecc31326ba3f6839f91e98a1e9230208308afb/awscrt-0.28.1-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:3df2316e77ad88c456b7eb2c9928007d379ed892154c1969d35b98653617e576", size = 3821522, upload-time = "2025-09-19T00:57:35.456Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/43/f0/6c6ff81f5a4c6d085eb450854149087bf9240c37c467c747521f47901b32/awscrt-0.28.1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:3a060d930939f142345f46a344e19ffc0dada657b04d02216b8adffba550c0a0", size = 4087344, upload-time = "2025-09-19T00:57:36.62Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/37/0a/71c097505add4ceea4ac05153311715acb7489cd82ec69db4570130f4698/awscrt-0.28.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:43f81ca6bfe85c38ad9765605aaaa646a1ed6fd7210dbedf67c113dd245f425e", size = 3745148, upload-time = "2025-09-19T00:57:38Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/79/1b/2b02b705a47b64e6c4d401087ddd30d4ad9af70172812ae8c62fb2b7a70c/awscrt-0.28.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:fc8e2307d9dbe76842015a14701ff7e9cf2619d674621b2d55b769414e17b3fc", size = 3972439, upload-time = "2025-09-19T00:57:39.74Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/f1/19/429c81c7a0d81a5edce9cc6d9a878c8b65d8b5b69fa5a2725a6e0b1380c1/awscrt-0.28.1-cp310-cp310-win32.whl", hash = "sha256:6e7b094587e5332d428300340dcc18794a1fcfa76d636f216fc0f5c8405ba604", size = 3915231, upload-time = "2025-09-19T00:57:41.096Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/83/81/769ad51fc6dcfd8bf9e0aa59c252013da0eb9e32c050ecbd1fc25f71689a/awscrt-0.28.1-cp310-cp310-win_amd64.whl", hash = "sha256:ac02f10f7384fdb68187f8d5d94743a271b16fa94be81481ce7684942f6a4b35", size = 4051668, upload-time = "2025-09-19T00:57:42.696Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/9e/55/0ee537d146f24d6e76eaf02d462a83c572788233603bb9bda969fbf23307/awscrt-0.28.1-cp311-abi3-macosx_10_15_universal2.whl", hash = "sha256:cb36052f9aa34e77687a8037559bbea331fc9d5d77cd71ab0cf4e6d72af73f72", size = 3376673, upload-time = "2025-09-19T00:57:43.875Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/f0/54/12700a4b9545680baa3e2d4d0e543bb4775a639df56ee51cbb29b71e0947/awscrt-0.28.1-cp311-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:fc59829152a5806eb2708aca5c5084c11dd18ecbe765e03eb314d5a360eeaa62", size = 3782870, upload-time = "2025-09-19T00:57:45.737Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/1d/e7/7b189ace9e187b9b55ed4a6ec9a451579b2f16bd01d402f79a19cc8e1603/awscrt-0.28.1-cp311-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:d2f20bc774599b9d85ce66689415da529ddd1d2215da818e005deedc4688fe61", size = 4048789, upload-time = "2025-09-19T00:57:47.327Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/9c/e0/2e5472019906dfcc5fadcdba4bad9e69dabb95bbc0c110cfe555ee8461dc/awscrt-0.28.1-cp311-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:491b8b9c73a288cfd5e0cbdac16aabb5313d5cfc33bbe461763a5ddc26624f70", size = 3687832, upload-time = "2025-09-19T00:57:48.563Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/71/f2/7e05d371bb888ee9f15e83d189287838f7b6ea40dfc91eacb3acd24b8529/awscrt-0.28.1-cp311-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:4c6c7125b7e9fcc999eb685d1cace8d4f2ffc63f8f3d8ef7f77e1a97d9552863", size = 3913378, upload-time = "2025-09-19T00:57:50.185Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/79/6b/a542a65a22edb85d64742970c21721e66e0f9f67911a11c7a5c3626a1b17/awscrt-0.28.1-cp311-abi3-win32.whl", hash = "sha256:1dcb33d7cf8f69881ac6ef75a5b9b40816be58678b1bb07ccbe0230281bdbc81", size = 3912809, upload-time = "2025-09-19T00:57:51.797Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/df/64/16cc8a0011e3ca5dda13605befa7e6db29bfb3073c67f6e8dad90be0a8ae/awscrt-0.28.1-cp311-abi3-win_amd64.whl", hash = "sha256:670caaf556876913bcfb9d8183d43d67a6c7b52998f2f398abd1c21632a006f8", size = 4048979, upload-time = "2025-09-19T00:57:53.061Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/ca/ac/debbd3a2f03c5953b56b1c3b321bab16293f857ea3005e3f7e5dded5e0b2/awscrt-0.28.1-cp313-abi3-macosx_10_15_universal2.whl", hash = "sha256:22311d25135b937ee5617e35a6554961727527dcfa3e06efdefe187a6abe65c4", size = 3375565, upload-time = "2025-09-19T00:57:54.598Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/ea/4f/9388917ad45c043acd7c4ab2c28b9e2b5ddf29e21a82bfc01a7626c18c04/awscrt-0.28.1-cp313-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:e58740cf0e41552fdf7909e10814b312ab090ebe54741354a61507e0c6d4ebfd", size = 3775366, upload-time = "2025-09-19T00:57:56.238Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/8a/e3/3ef301cdef76b22ce14b041e04c6cf65ba4491d00e9f5b400c0699f6c63e/awscrt-0.28.1-cp313-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:9e69f163a207a8b172abbfea1f51045301ed1ac8bbaf76958a6b5e81d72e5b89", size = 4043403, upload-time = "2025-09-19T00:57:57.4Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/60/9c/4f89922333724c4da851752549ca97dd147420734ef6c4ece56d5dd65e09/awscrt-0.28.1-cp313-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:592f4b234ecafa6cde86e55e42c4fe84c4e1ffe9fb11b0a8b8f0ffb8c62fa2cc", size = 3678742, upload-time = "2025-09-19T00:57:59.055Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/0e/d4/adb97ba5f888ed201aa1f9e9f8d6cfc0dbaf80f0e937b3acb7411febdaa8/awscrt-0.28.1-cp313-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:b16321f1d2bf5b4991a213059c1b5dc07954edfc424d154b093824465ec94ce2", size = 3908438, upload-time = "2025-09-19T00:58:00.71Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/41/ac/600ea0a6f4ba6543c50417c8e78b09f2cd73dd0f0d4c3e9e52220a8badbe/awscrt-0.28.1-cp313-abi3-win32.whl", hash = "sha256:3e0a23635aa75b4af163ff9bf5a0873928369b1ac32c8b1351741a95472ccf71", size = 3907625, upload-time = "2025-09-19T00:58:03.235Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/9e/24/d22c7197b1e53c76b5eb71d640a4728b9b7621075d8dbcc054e16b5b98f0/awscrt-0.28.1-cp313-abi3-win_amd64.whl", hash = "sha256:9849c88ca0830396724acf988e2759895118fe7dd2a23dab21978c8600d01a11", size = 4043878, upload-time = "2025-09-19T00:58:04.595Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -569,30 +569,6 @@ wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/39/54/db7a801933dd2537f5376fb8a9e28caff488ef5c2d61f3a8fced55fe6336/blake3-1.0.7-cp313-cp313t-musllinux_1_1_x86_64.whl", hash = "sha256:d9046bb1e22a8607e1d0d7c3ff47e56e0a197c988502df4bf4d78563f3e9fe2c", size = 553411, upload-time = "2025-09-29T16:40:45.667Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/2c/08/949cf68d16d1f731d502968bb1486e1a4bf7ef032c38fbc2ef26a2353494/blake3-1.0.7-cp313-cp313t-win32.whl", hash = "sha256:bd2f638bcc00fc09ce985ea3c642d45940e1eda198ab1f4b90cfdecbebbc9315", size = 227049, upload-time = "2025-09-29T16:40:47.446Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/f2/ae/6783a5ca6235024e00a1e92ab6ca2cd855f4c61c763cf8d6d643846d110c/blake3-1.0.7-cp313-cp313t-win_amd64.whl", hash = "sha256:cb3aa1db14231c2ef0ec5acd805505ce128c39ffa510deb3384eed96fe4addcb", size = 214101, upload-time = "2025-09-29T16:40:48.656Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/32/aa/99b4b6c22972b9a854f77d97846a717448a77d079e4bd38e46a3f8ecea76/blake3-1.0.7-cp314-cp314-macosx_10_12_x86_64.whl", hash = "sha256:f7db997205aa420d59fb5639346e40beafb9c09252e2ec6efedca8f230f7520c", size = 346664, upload-time = "2025-10-11T18:02:54.609Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/f9/44/e98bc5450be415a335a191b154e299e335046d11fe9514d93961902b7aed/blake3-1.0.7-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:19afec6e276f3bc154541248d92b1ecb198af2ee920025f7ce521028f9a69d8b", size = 324576, upload-time = "2025-10-11T18:02:57.062Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/74/25/23a39913c8424ac3df705ed71a00efe34cc1cdbd4588ed6eaf458ea9d7ef/blake3-1.0.7-cp314-cp314-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:006a11bbba65a95e88ddc069cca751c8812fd144d582715eeea512452fdbe80d", size = 370545, upload-time = "2025-10-11T18:02:59.824Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/db/83/9f53a86de9a5999b043febfd84765d240014da42055aeac06d1005b20b07/blake3-1.0.7-cp314-cp314-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:7febeffdc8412fed105ca517cee641ac521fb9cfb750bf7e27a5cdf3ddf74a08", size = 374370, upload-time = "2025-10-11T18:03:01.412Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/c4/4c/3290aa4fb7483975a7b3322a73692aa3cf491a77ce7ac61c216c71c6f834/blake3-1.0.7-cp314-cp314-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6c032ce7c52b71015651c0abe9fe599aa2669e6be578aa17d5f993dc93373401", size = 447808, upload-time = "2025-10-11T18:03:02.893Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/66/26/92b6e15552865416aae1aedad8b9b4d8b47ca9b73d25373622b1798c05a9/blake3-1.0.7-cp314-cp314-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5b81455f7d24b58fe26be037cc3854c28ea6eb3671ceab3b1ec0b1239aeb6fef", size = 506118, upload-time = "2025-10-11T18:03:04.51Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/1b/ef/f158fc43a03fd366bc428a52a845bd0f884e518deda901c9216bd469867e/blake3-1.0.7-cp314-cp314-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:41b0127b0e7c8610054c421959dbe7140a81ac2c88fa9e099994fbaa529af3c1", size = 393239, upload-time = "2025-10-11T18:03:07.102Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/10/49/2a56ce897ec7ed0e25953b3873da271ea60cc107ae02ecc6655252e554c7/blake3-1.0.7-cp314-cp314-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4755ca95b4114b629d8f3570bc661916d211d52d47f57ff70e9687377ab39cb9", size = 386267, upload-time = "2025-10-11T18:03:08.904Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/d9/c4/ee4c03ea419198b91c889ef173015b5d637a390d3f7d63cb70033a7201d6/blake3-1.0.7-cp314-cp314-musllinux_1_1_aarch64.whl", hash = "sha256:8abe929cfd27b375e02e3dd7a690192fa4efecc52ef510df91ef01651ef08dc7", size = 549641, upload-time = "2025-10-11T18:03:10.64Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/b2/cc/a918d6649b56fe705133e06d9958d90978aad30063d42cca4dfe23db16e9/blake3-1.0.7-cp314-cp314-musllinux_1_1_x86_64.whl", hash = "sha256:dd607eb5ad5a9b44ff62243759aa0af4085f6f43c9b01f503561a70da63e3b94", size = 553691, upload-time = "2025-10-11T18:03:12.108Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/fd/9f/568546f555fd1555d4867c497e9413f67bf769d076e773b9ca9e07a0b6f6/blake3-1.0.7-cp314-cp314-win32.whl", hash = "sha256:a51684d1f346e7680f7c244c25b0e279e3b297f1938126e4ea8e32425ea269f5", size = 227552, upload-time = "2025-10-11T18:03:13.468Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/97/2b/d4ef7365d9f601c8a127b5993f2662d45d2cb6d430bf3dbbb7a6f0b33639/blake3-1.0.7-cp314-cp314-win_amd64.whl", hash = "sha256:a6a481719e28e2c61aafd4273d32663365d97613341b72fcdf2f6afbd426319b", size = 214719, upload-time = "2025-10-11T18:03:14.835Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/2f/53/f697cc34e382a225d163ea0c6a35c7eb4cfd1011e85db6610adfac98e522/blake3-1.0.7-cp314-cp314t-macosx_10_12_x86_64.whl", hash = "sha256:daa8933cd7db19143bd6b59f7ac4c7c7446767d7b2c3a748a4559aa483275fa2", size = 347071, upload-time = "2025-10-11T18:03:16.637Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/4c/85/836dcb5c5709c2331f02ce065f7ebfaae710a6c1768cdc47ee3197645f98/blake3-1.0.7-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:24074adfffffe0fa7a7dd930cc608d6e965e70306e2c1e14d412e29ec94fa360", size = 324341, upload-time = "2025-10-11T18:03:18.073Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/6d/48/36b2c25007933619ce60e24b9f360baaa77d08939284045476c8e157fe62/blake3-1.0.7-cp314-cp314t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dce6e6f03de2674f9860cf330d8a4fcdb63a60659435e5e31d72d174fc102d8e", size = 370140, upload-time = "2025-10-11T18:03:19.582Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/70/82/8a8977e5d56b9fb719033940c8ce34afc733190d34ab868a647a9af7b584/blake3-1.0.7-cp314-cp314t-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:e783f33d53a2de8d2ab845235dd53393d521b5e4a76c23d03e77e472266359d3", size = 373022, upload-time = "2025-10-11T18:03:21.143Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/e2/c4/44017ba40804a528568b35a36c05187786830c4d891c5540d59a121a7cec/blake3-1.0.7-cp314-cp314t-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:782784aef18eb61f4ce8bf2b9506b7d90f0d183176b453345b221837a18041b7", size = 447243, upload-time = "2025-10-11T18:03:22.707Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/78/c1/4fa20e68624784082734d31b8c9c80ad226658c024e61b9f9b6751ba0a4a/blake3-1.0.7-cp314-cp314t-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:6062122e77f40e3733cac2ef3f25e0fc7f555e352fe6f513f8404ad11dc69974", size = 506149, upload-time = "2025-10-11T18:03:24.424Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/8e/63/af65466e27e7b92800a068afaee11b2fa071e34a7f5900f8e13832f18185/blake3-1.0.7-cp314-cp314t-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6c2614bc9d69fd6067571f3bb37b3b07a6b86a56167553ad4784a3c508771f39", size = 393243, upload-time = "2025-10-11T18:03:25.872Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/f3/82/54a4807a3243d0e094ada9d65687aeb40059587e374b3beb9c89f6552c9b/blake3-1.0.7-cp314-cp314t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d6df2bd56c43bdeb6699d4af0a0dd0d77537d95cb4a5dde4b39ed6e54cc725d6", size = 386318, upload-time = "2025-10-11T18:03:27.338Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/42/e8/32b56531b5d9da67e476735ceaec7c3bf89310629abeeafb03c724145c88/blake3-1.0.7-cp314-cp314t-musllinux_1_1_aarch64.whl", hash = "sha256:8b635cf4350caf459ecb335b32be622068423245bda457d5bc159106eb20f912", size = 548945, upload-time = "2025-10-11T18:03:28.779Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/ad/50/33b1aca708be629e285a537f1adf34dfcabc4c30b28c436361323d11f593/blake3-1.0.7-cp314-cp314t-musllinux_1_1_x86_64.whl", hash = "sha256:f96a685775f87ddf75ff495dc9698703268c66c170caca977347427ef8d52324", size = 553564, upload-time = "2025-10-11T18:03:30.247Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/fe/07/8b17cbf40ccd9afeed6ae9f55018181786b30ff4e079ac8bf4ca4799e47b/blake3-1.0.7-cp314-cp314t-win32.whl", hash = "sha256:0633b7d9bad87dc7fce545042353f2e056604d993f71d1dce666a9f5edc13e05", size = 227345, upload-time = "2025-10-11T18:03:31.933Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/d9/8a/ab9de8a73616350759356a483f440212bc2a22fc9aaa77cabbf06c3483db/blake3-1.0.7-cp314-cp314t-win_amd64.whl", hash = "sha256:5e356daa0089968dc1ff1d0d112e7cc1700533441d8f30ae99f835a94dc8b0f3", size = 213964, upload-time = "2025-10-11T18:03:33.919Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -891,16 +867,16 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "compressed-tensors"
|
||||
version = "0.10.1"
|
||||
version = "0.10.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "pydantic" },
|
||||
{ name = "torch" },
|
||||
{ name = "transformers" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/40/eb/2229523a539e8074b238c225d168f734f6f056ab4ea2278eefe752f4a6f3/compressed_tensors-0.10.1.tar.gz", hash = "sha256:f99ce620ddcf8a657eaa7995daf5faa8e988d4b4cadc595bf2c4ff9346c2c19a", size = 126778, upload-time = "2025-06-06T18:25:16.538Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/c0/86/d43d369abc81ec63ec7b8f6f27fc8b113ea0fd18a4116ae12063387b8b34/compressed_tensors-0.10.2.tar.gz", hash = "sha256:6de13ac535d7ffdd8890fad3d229444c33076170acaa8fab6bab8ecfa96c1d8f", size = 173459, upload-time = "2025-06-23T13:19:06.135Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/5b/07/e70a0b9efc24a32740396c404e7213c62b8aeb4a577ed5a3f191f8d7806b/compressed_tensors-0.10.1-py3-none-any.whl", hash = "sha256:b8890735522c119900e8d4192cced0b0f70a98440ae070448cb699165c404659", size = 116998, upload-time = "2025-06-06T18:25:14.54Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/43/ac/56bb4b6b3150783119479e2f05e32ebfc39ca6ff8e6fcd45eb178743b39e/compressed_tensors-0.10.2-py3-none-any.whl", hash = "sha256:e1b4d9bc2006e3fd3a938e59085f318fdb280c5af64688a4792bf1bc263e579d", size = 169030, upload-time = "2025-06-23T13:19:03.487Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -1282,13 +1258,13 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "daily-python"
|
||||
version = "0.20.0"
|
||||
version = "0.19.9"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/9b/02/ce81ebf11a04cd133a5539e08f85060574711fff05a1d6ad29705f0755c1/daily_python-0.20.0-cp37-abi3-macosx_10_15_x86_64.whl", hash = "sha256:7da3f1df8cd9ef7f7fcc96ce688348dc903f62d82b6dd155a53bc64b7a74f3a7", size = 13259887, upload-time = "2025-10-16T22:14:12.262Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/4a/1e/51f06f3486c978e1184af2271e800ce6a6e8a8f95d61ee6624bae88ae9cd/daily_python-0.20.0-cp37-abi3-macosx_11_0_arm64.whl", hash = "sha256:d02fd7b8c8079ceaa550ef23db052cdf70a8ffaf8ab6a8bc1a1e97bf0b939464", size = 11642453, upload-time = "2025-10-16T22:14:14.477Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/71/c9/f767f0b479abd39330569ad61fb9db4661aae56cd74bb27c6f3483595463/daily_python-0.20.0-cp37-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:a5c8718982c221dc18b41fb0692c9f8435f115f72e74994c94d3b9c6dad7c534", size = 13634216, upload-time = "2025-10-16T22:14:16.235Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/e8/10/5c6d7b000bee36c2a0587a092a34c7486d2de831fc8e44ed42b16a6bd99f/daily_python-0.20.0-cp37-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:ca9132aef1bdb5be663d1894b440dab1f998ebb3f45dfc31d44effabded4bc08", size = 14282189, upload-time = "2025-10-16T22:14:18.229Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/22/85/6064c3225e5b190e522e8f3bc6a460efc5e3e6632f16fd5f9799c44ba57a/daily_python-0.19.9-cp37-abi3-macosx_10_15_x86_64.whl", hash = "sha256:cbc558ad7d49e79b550bf7567b9ceae75e2864d4fcaf41c90377b620e38a2461", size = 13365213, upload-time = "2025-09-06T00:31:00.224Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/23/58/af986c6881180a46a7b60dd418ce58d6d7c0c4ffc48d261748067c679317/daily_python-0.19.9-cp37-abi3-macosx_11_0_arm64.whl", hash = "sha256:446bb9ee848d88bc68ca29a2216793c9b5ebaf5991bf604daf76f7c5a53d5919", size = 11711673, upload-time = "2025-09-06T00:31:02.526Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/9d/48/1cad4c3e92cdb5ef06467d972c76a510fe5e807513334b10ad7f8c21bf74/daily_python-0.19.9-cp37-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:2facaf82b614404c642c70bbf0874fb045d8ad46400acb051470cd4df93cb4db", size = 13679393, upload-time = "2025-09-06T00:31:04.999Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/3c/e9/354f4699619e83d13e266256b2352b21741ac527e3e5ab5f2264d5c482cd/daily_python-0.19.9-cp37-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:ffc205efca7b47739efd358febab17577248c8db2ebc4d17d819307a83b9eefc", size = 14221932, upload-time = "2025-09-06T00:31:07.471Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -2750,7 +2726,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "langchain-core"
|
||||
version = "0.3.79"
|
||||
version = "0.3.77"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "jsonpatch" },
|
||||
@@ -2761,23 +2737,23 @@ dependencies = [
|
||||
{ name = "tenacity" },
|
||||
{ name = "typing-extensions" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/c8/99/f926495f467e0f43289f12e951655d267d1eddc1136c3cf4dd907794a9a7/langchain_core-0.3.79.tar.gz", hash = "sha256:024ba54a346dd9b13fb8b2342e0c83d0111e7f26fa01f545ada23ad772b55a60", size = 580895, upload-time = "2025-10-09T21:59:08.359Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/40/cc/786184e5f6a921a2aa4d2ac51d3adf0cd037289f3becff39644bee9654ee/langchain_core-0.3.77.tar.gz", hash = "sha256:1d6f2ad6bb98dd806c6c66a822fa93808d821e9f0348b28af0814b3a149830e7", size = 580255, upload-time = "2025-10-01T14:34:37.368Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/fc/71/46b0efaf3fc6ad2c2bd600aef500f1cb2b7038a4042f58905805630dd29d/langchain_core-0.3.79-py3-none-any.whl", hash = "sha256:92045bfda3e741f8018e1356f83be203ec601561c6a7becfefe85be5ddc58fdb", size = 449779, upload-time = "2025-10-09T21:59:06.493Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/64/18/e7462ae0ce57caa9f6d5d975dca861e9a751e5ca253d60a809e0d833eac3/langchain_core-0.3.77-py3-none-any.whl", hash = "sha256:9966dfe3d8365847c5fb85f97dd20e3e21b1904ae87cfd9d362b7196fb516637", size = 449525, upload-time = "2025-10-01T14:34:35.672Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "langchain-openai"
|
||||
version = "0.3.29"
|
||||
version = "0.3.23"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
{ name = "openai" },
|
||||
{ name = "tiktoken" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/5b/56/2e2010d15118ac52760f92ebf6ce75b3508e7a1023107ea04233fd6263e0/langchain_openai-0.3.29.tar.gz", hash = "sha256:83a0455f8ce874aa1806131ca3b4db08e482be037b7457a9b3ca21a213d2ab47", size = 766499, upload-time = "2025-08-08T15:12:32.402Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/74/f1/575120e829430f9bdcfc2c5c4121f04b1b5a143d96e572ff32399b787ef2/langchain_openai-0.3.23.tar.gz", hash = "sha256:73411c06e04bc145db7146a6fcf33dd0f1a85130499dcae988829a4441ddaa66", size = 647923, upload-time = "2025-06-13T14:24:31.388Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/ac/f2/a6a73beec15e90605e6a24c4498a8592d79a72c8e81c18ed0f5e9b7308e9/langchain_openai-0.3.29-py3-none-any.whl", hash = "sha256:71ae6791b3e017ec892a8062f993edc882c6665fd8385aa66e9dc3bff8205996", size = 74316, upload-time = "2025-08-08T15:12:30.794Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/71/65/88060305d5d627841bc8da7e9fb31fb603e5b103b4e5ec5b4d1a7edfbc3b/langchain_openai-0.3.23-py3-none-any.whl", hash = "sha256:624794394482c0923823f0aac44979968d77fdcfa810e42d4b0abd8096199a40", size = 65392, upload-time = "2025-06-13T14:24:30.263Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -3233,6 +3209,23 @@ wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/4b/b4/b61eeb92c424947675492dec3a411bdbeae307dfd78162d65ab47e8c3b4f/mlx-0.29.2-cp313-cp313-manylinux_2_35_x86_64.whl", hash = "sha256:c3b9a9aee13f346d060966472954eebe99d9f1b295c9a237c9a000f1ef9adf2c", size = 648709, upload-time = "2025-09-26T22:26:03.452Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "mlx-lm"
|
||||
version = "0.28.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "jinja2" },
|
||||
{ name = "mlx" },
|
||||
{ name = "numpy" },
|
||||
{ name = "protobuf" },
|
||||
{ name = "pyyaml" },
|
||||
{ name = "transformers" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/1c/d7/fdde445c7bd443a2ed23badda6064f1477c4051543922106f365e94082cd/mlx_lm-0.28.2.tar.gz", hash = "sha256:d28752635ed5c89ff2b41361916c928e6b16f765c07b2908044e1dcaf921ed9b", size = 209374, upload-time = "2025-10-02T14:23:57.497Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/f2/1c/89e0f60d45e364de8507065f73aeb8d2fd810d6cb95a9a512880b09399d5/mlx_lm-0.28.2-py3-none-any.whl", hash = "sha256:1501529e625d0d648216f7bb543b8b449d5fd17bd598f635536dbc1fbde6d1d6", size = 284600, upload-time = "2025-10-02T14:23:56.395Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "mlx-metal"
|
||||
version = "0.29.2"
|
||||
@@ -3858,7 +3851,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "openai"
|
||||
version = "1.97.1"
|
||||
version = "1.74.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "anyio" },
|
||||
@@ -3870,9 +3863,9 @@ dependencies = [
|
||||
{ name = "tqdm" },
|
||||
{ name = "typing-extensions" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/a6/57/1c471f6b3efb879d26686d31582997615e969f3bb4458111c9705e56332e/openai-1.97.1.tar.gz", hash = "sha256:a744b27ae624e3d4135225da9b1c89c107a2a7e5bc4c93e5b7b5214772ce7a4e", size = 494267, upload-time = "2025-07-22T13:10:12.607Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/75/86/c605a6e84da0248f2cebfcd864b5a6076ecf78849245af5e11d2a5ec7977/openai-1.74.0.tar.gz", hash = "sha256:592c25b8747a7cad33a841958f5eb859a785caea9ee22b9e4f4a2ec062236526", size = 427571, upload-time = "2025-04-14T16:45:25.062Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/ee/35/412a0e9c3f0d37c94ed764b8ac7adae2d834dbd20e69f6aca582118e0f55/openai-1.97.1-py3-none-any.whl", hash = "sha256:4e96bbdf672ec3d44968c9ea39d2c375891db1acc1794668d8149d5fa6000606", size = 764380, upload-time = "2025-07-22T13:10:10.689Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/a9/91/8c150f16a96367e14bd7d20e86e0bbbec3080e3eb593e63f21a7f013f8e4/openai-1.74.0-py3-none-any.whl", hash = "sha256:aff3e0f9fb209836382ec112778667027f4fd6ae38bdb2334bc9e173598b092a", size = 644790, upload-time = "2025-04-14T16:45:23.041Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -3911,7 +3904,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "openpipe"
|
||||
version = "5.0.0"
|
||||
version = "4.50.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "anthropic" },
|
||||
@@ -3920,9 +3913,9 @@ dependencies = [
|
||||
{ name = "openai" },
|
||||
{ name = "python-dateutil" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/7c/34/b487bc0ff60d3ed634e6f7bc34b5138f04e6ae319cc6578001822df93901/openpipe-5.0.0.tar.gz", hash = "sha256:040acc526fece42ba505fcedd8cd584f42482c9bd01f16b2538c9ea9c82882f4", size = 98910, upload-time = "2025-07-31T01:36:29.482Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/ec/0b/5ac4afd2253e058463fe46b44ebdf9cf153af343b457f13e9e592943c16d/openpipe-4.50.0.tar.gz", hash = "sha256:a2b1bf7a30a8d4c2cf45b85c749839ea9811e36f9d03916df8ffa343d9193a0e", size = 98954, upload-time = "2025-04-15T18:13:36.935Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/7a/5e/516010c25a32884a87e1f8303a292f3981fa382cc7570a9ed88fb28681d5/openpipe-5.0.0-py3-none-any.whl", hash = "sha256:c04af7afb4d9bcd52e1250757dd93d0e0ed19c9ff4b524f131dd94aadf4c1a9b", size = 439951, upload-time = "2025-07-31T01:36:28.003Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/92/39/04870a3157d4ad6e8b1671f584da3e064750ccd64aa08339c6fc6dbd3a1c/openpipe-4.50.0-py3-none-any.whl", hash = "sha256:2071c3edbba3e08ceb977ad8c12d407f4da86c0c3815447fa33674d918276e5e", size = 440892, upload-time = "2025-04-15T18:13:35.258Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -3938,67 +3931,6 @@ wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/91/48/28ed9e55dcf2f453128df738210a980e09f4e468a456fa3c763dbc8be70a/opentelemetry_api-1.37.0-py3-none-any.whl", hash = "sha256:accf2024d3e89faec14302213bc39550ec0f4095d1cf5ca688e1bfb1c8612f47", size = 65732, upload-time = "2025-09-11T10:28:41.826Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "opentelemetry-exporter-otlp"
|
||||
version = "1.37.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "opentelemetry-exporter-otlp-proto-grpc" },
|
||||
{ name = "opentelemetry-exporter-otlp-proto-http" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/64/df/47fde1de15a3d5ad410e98710fac60cd3d509df5dc7ec1359b71d6bf7e70/opentelemetry_exporter_otlp-1.37.0.tar.gz", hash = "sha256:f85b1929dd0d750751cc9159376fb05aa88bb7a08b6cdbf84edb0054d93e9f26", size = 6145, upload-time = "2025-09-11T10:29:03.075Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/f5/23/7e35e41111e3834d918e414eca41555d585e8860c9149507298bb3b9b061/opentelemetry_exporter_otlp-1.37.0-py3-none-any.whl", hash = "sha256:bd44592c6bc7fc3e5c0a9b60f2ee813c84c2800c449e59504ab93f356cc450fc", size = 7019, upload-time = "2025-09-11T10:28:44.094Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "opentelemetry-exporter-otlp-proto-common"
|
||||
version = "1.37.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "opentelemetry-proto" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/dc/6c/10018cbcc1e6fff23aac67d7fd977c3d692dbe5f9ef9bb4db5c1268726cc/opentelemetry_exporter_otlp_proto_common-1.37.0.tar.gz", hash = "sha256:c87a1bdd9f41fdc408d9cc9367bb53f8d2602829659f2b90be9f9d79d0bfe62c", size = 20430, upload-time = "2025-09-11T10:29:03.605Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/08/13/b4ef09837409a777f3c0af2a5b4ba9b7af34872bc43609dda0c209e4060d/opentelemetry_exporter_otlp_proto_common-1.37.0-py3-none-any.whl", hash = "sha256:53038428449c559b0c564b8d718df3314da387109c4d36bd1b94c9a641b0292e", size = 18359, upload-time = "2025-09-11T10:28:44.939Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "opentelemetry-exporter-otlp-proto-grpc"
|
||||
version = "1.37.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "googleapis-common-protos" },
|
||||
{ name = "grpcio" },
|
||||
{ name = "opentelemetry-api" },
|
||||
{ name = "opentelemetry-exporter-otlp-proto-common" },
|
||||
{ name = "opentelemetry-proto" },
|
||||
{ name = "opentelemetry-sdk" },
|
||||
{ name = "typing-extensions" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/d1/11/4ad0979d0bb13ae5a845214e97c8d42da43980034c30d6f72d8e0ebe580e/opentelemetry_exporter_otlp_proto_grpc-1.37.0.tar.gz", hash = "sha256:f55bcb9fc848ce05ad3dd954058bc7b126624d22c4d9e958da24d8537763bec5", size = 24465, upload-time = "2025-09-11T10:29:04.172Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/39/17/46630b74751031a658706bef23ac99cdc2953cd3b2d28ec90590a0766b3e/opentelemetry_exporter_otlp_proto_grpc-1.37.0-py3-none-any.whl", hash = "sha256:aee5104835bf7993b7ddaaf380b6467472abaedb1f1dbfcc54a52a7d781a3890", size = 19305, upload-time = "2025-09-11T10:28:45.776Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "opentelemetry-exporter-otlp-proto-http"
|
||||
version = "1.37.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "googleapis-common-protos" },
|
||||
{ name = "opentelemetry-api" },
|
||||
{ name = "opentelemetry-exporter-otlp-proto-common" },
|
||||
{ name = "opentelemetry-proto" },
|
||||
{ name = "opentelemetry-sdk" },
|
||||
{ name = "requests" },
|
||||
{ name = "typing-extensions" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/5d/e3/6e320aeb24f951449e73867e53c55542bebbaf24faeee7623ef677d66736/opentelemetry_exporter_otlp_proto_http-1.37.0.tar.gz", hash = "sha256:e52e8600f1720d6de298419a802108a8f5afa63c96809ff83becb03f874e44ac", size = 17281, upload-time = "2025-09-11T10:29:04.844Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/e9/e9/70d74a664d83976556cec395d6bfedd9b85ec1498b778367d5f93e373397/opentelemetry_exporter_otlp_proto_http-1.37.0-py3-none-any.whl", hash = "sha256:54c42b39945a6cc9d9a2a33decb876eabb9547e0dcb49df090122773447f1aef", size = 19576, upload-time = "2025-09-11T10:28:46.726Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "opentelemetry-instrumentation"
|
||||
version = "0.58b0"
|
||||
@@ -4028,18 +3960,6 @@ wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/a5/54/add1076cb37980e617723a96e29c84006983e8ad6fc589dde7f69ddc57d4/opentelemetry_instrumentation_threading-0.58b0-py3-none-any.whl", hash = "sha256:eacc072881006aceb5b9b6831bcdce718c67ef6f31ac0b32bd6a23a94d979b4a", size = 9312, upload-time = "2025-09-11T11:41:58.603Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "opentelemetry-proto"
|
||||
version = "1.37.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "protobuf" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/dd/ea/a75f36b463a36f3c5a10c0b5292c58b31dbdde74f6f905d3d0ab2313987b/opentelemetry_proto-1.37.0.tar.gz", hash = "sha256:30f5c494faf66f77faeaefa35ed4443c5edb3b0aa46dad073ed7210e1a789538", size = 46151, upload-time = "2025-09-11T10:29:11.04Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/c4/25/f89ea66c59bd7687e218361826c969443c4fa15dfe89733f3bf1e2a9e971/opentelemetry_proto-1.37.0-py3-none-any.whl", hash = "sha256:8ed8c066ae8828bbf0c39229979bdf583a126981142378a9cbe9d6fd5701c6e2", size = 72534, upload-time = "2025-09-11T10:28:56.831Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "opentelemetry-sdk"
|
||||
version = "1.37.0"
|
||||
@@ -4067,15 +3987,6 @@ wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/07/90/68152b7465f50285d3ce2481b3aec2f82822e3f52e5152eeeaf516bab841/opentelemetry_semantic_conventions-0.58b0-py3-none-any.whl", hash = "sha256:5564905ab1458b96684db1340232729fce3b5375a06e140e8904c78e4f815b28", size = 207954, upload-time = "2025-09-11T10:28:59.218Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "opentelemetry-semantic-conventions-ai"
|
||||
version = "0.4.13"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/ba/e6/40b59eda51ac47009fb47afcdf37c6938594a0bd7f3b9fadcbc6058248e3/opentelemetry_semantic_conventions_ai-0.4.13.tar.gz", hash = "sha256:94efa9fb4ffac18c45f54a3a338ffeb7eedb7e1bb4d147786e77202e159f0036", size = 5368, upload-time = "2025-08-22T10:14:17.387Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/35/b5/cf25da2218910f0d6cdf7f876a06bed118c4969eacaf60a887cbaef44f44/opentelemetry_semantic_conventions_ai-0.4.13-py3-none-any.whl", hash = "sha256:883a30a6bb5deaec0d646912b5f9f6dcbb9f6f72557b73d0f2560bf25d13e2d5", size = 6080, upload-time = "2025-08-22T10:14:16.477Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "orjson"
|
||||
version = "3.11.3"
|
||||
@@ -4633,11 +4544,11 @@ requires-dist = [
|
||||
{ name = "aiortc", marker = "extra == 'webrtc'", specifier = ">=1.13.0,<2" },
|
||||
{ name = "anthropic", marker = "extra == 'anthropic'", specifier = "~=0.49.0" },
|
||||
{ name = "audioop-lts", marker = "python_full_version >= '3.13'", specifier = "~=0.2.1" },
|
||||
{ name = "aws-sdk-bedrock-runtime", marker = "python_full_version >= '3.12' and extra == 'aws-nova-sonic'", specifier = "~=0.1.1" },
|
||||
{ name = "aws-sdk-bedrock-runtime", marker = "python_full_version >= '3.12' and extra == 'aws-nova-sonic'", specifier = "~=0.1.0" },
|
||||
{ name = "azure-cognitiveservices-speech", marker = "extra == 'azure'", specifier = "~=1.42.0" },
|
||||
{ name = "cartesia", marker = "extra == 'cartesia'", specifier = "~=2.0.3" },
|
||||
{ name = "coremltools", marker = "extra == 'local-smart-turn'", specifier = ">=8.0" },
|
||||
{ name = "daily-python", marker = "extra == 'daily'", specifier = "~=0.20.0" },
|
||||
{ name = "daily-python", marker = "extra == 'daily'", specifier = "~=0.19.9" },
|
||||
{ name = "deepgram-sdk", marker = "extra == 'deepgram'", specifier = "~=4.7.0" },
|
||||
{ name = "docstring-parser", specifier = "~=0.16" },
|
||||
{ name = "einops", marker = "extra == 'moondream'", specifier = "~=0.8.0" },
|
||||
@@ -4668,9 +4579,9 @@ requires-dist = [
|
||||
{ name = "nvidia-riva-client", marker = "extra == 'riva'", specifier = "~=2.21.1" },
|
||||
{ name = "onnxruntime", marker = "extra == 'local-smart-turn-v3'", specifier = ">=1.20.1,<2" },
|
||||
{ name = "onnxruntime", marker = "extra == 'silero'", specifier = ">=1.20.1,<2" },
|
||||
{ name = "openai", specifier = ">=1.74.0,<3" },
|
||||
{ name = "openai", specifier = ">=1.74.0,<=1.99.1" },
|
||||
{ name = "opencv-python", marker = "extra == 'webrtc'", specifier = ">=4.11.0.86,<5" },
|
||||
{ name = "openpipe", marker = "extra == 'openpipe'", specifier = ">=4.50.0,<6" },
|
||||
{ name = "openpipe", marker = "extra == 'openpipe'", specifier = "~=4.50.0" },
|
||||
{ name = "opentelemetry-api", marker = "extra == 'tracing'", specifier = ">=1.33.0" },
|
||||
{ name = "opentelemetry-instrumentation", marker = "extra == 'tracing'", specifier = ">=0.54b0" },
|
||||
{ name = "opentelemetry-sdk", marker = "extra == 'tracing'", specifier = ">=1.33.0" },
|
||||
@@ -4708,7 +4619,7 @@ requires-dist = [
|
||||
{ name = "simli-ai", marker = "extra == 'simli'", specifier = "~=0.1.10" },
|
||||
{ name = "soundfile", marker = "extra == 'soundfile'", specifier = "~=0.13.0" },
|
||||
{ name = "soxr", specifier = "~=0.5.0" },
|
||||
{ name = "speechmatics-rt", marker = "extra == 'speechmatics'", specifier = ">=0.5.0" },
|
||||
{ name = "speechmatics-rt", marker = "extra == 'speechmatics'", specifier = ">=0.4.0" },
|
||||
{ name = "strands-agents", marker = "extra == 'strands'", specifier = ">=1.9.1,<2" },
|
||||
{ name = "tenacity", marker = "extra == 'livekit'", specifier = ">=8.2.3,<10.0.0" },
|
||||
{ name = "timm", marker = "extra == 'moondream'", specifier = "~=1.0.13" },
|
||||
@@ -5050,6 +4961,172 @@ wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/a5/8b/7f9a061c1cc2b230f9ac02a6003fcd14c85ce1828013aecbaf45aa988d20/PyAudio-0.2.14-cp313-cp313-win_amd64.whl", hash = "sha256:692d8c1446f52ed2662120bcd9ddcb5aa2b71f38bda31e58b19fb4672fffba69", size = 173655, upload-time = "2024-11-20T19:12:13.616Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "pybase64"
|
||||
version = "1.4.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/04/14/43297a7b7f0c1bf0c00b596f754ee3ac946128c64d21047ccf9c9bbc5165/pybase64-1.4.2.tar.gz", hash = "sha256:46cdefd283ed9643315d952fe44de80dc9b9a811ce6e3ec97fd1827af97692d0", size = 137246, upload-time = "2025-07-27T13:08:57.808Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/f3/6d/0a7159c24ed35c8b9190b148376ad9b96598354f94ede29df74861da9ec6/pybase64-1.4.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:82b4593b480773b17698fef33c68bae0e1c474ba07663fad74249370c46b46c9", size = 38240, upload-time = "2025-07-27T13:02:17.876Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/86/2e/dad4cd832a90a49d98867e824180585e7c928504987d37304bccae11a314/pybase64-1.4.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:a126f29d29cb4a498db179135dbf955442a0de5b00f374523f5dcceb9074ff58", size = 31658, upload-time = "2025-07-27T13:02:20.823Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/1d/d8/30ea35dc2c8c568be93e1379efcaa35092e37efa2ce7f1985ccc63babee7/pybase64-1.4.2-cp310-cp310-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:1eef93c29cc5567480d168f9cc1ebd3fc3107c65787aed2019a8ea68575a33e0", size = 65963, upload-time = "2025-07-27T13:02:22.376Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/f6/da/1c22f2a21d6bb9ec2a214d15ae02d5b20a95335de218a0ecbf769c535a5c/pybase64-1.4.2-cp310-cp310-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:17b871a34aaeb0644145cb6bf28feb163f593abea11aec3dbcc34a006edfc828", size = 68887, upload-time = "2025-07-27T13:02:23.606Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/ac/8d/e04d489ba99b444ce94b4d5b232365d00b0f0e8564275d7ba7434dcabe72/pybase64-1.4.2-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:1f734e16293637a35d282ce594eb05a7a90ea3ae2bc84a3496a5df9e6b890725", size = 57503, upload-time = "2025-07-27T13:02:24.83Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/7e/b8/5ec9c334f30cf898709a084d596bf4b47aec2e07870f07bac5cf39754eca/pybase64-1.4.2-cp310-cp310-manylinux2014_armv7l.manylinux_2_17_armv7l.whl", hash = "sha256:22bd38db2d990d5545dde83511edeec366630d00679dbd945472315c09041dc6", size = 54517, upload-time = "2025-07-27T13:02:26.006Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/b9/5a/6e4424ecca041e53aa7c14525f99edd43d0117c23c5d9cb14e931458a536/pybase64-1.4.2-cp310-cp310-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:dc65cee686dda72007b7541b2014f33ee282459c781b9b61305bd8b9cfadc8e1", size = 57167, upload-time = "2025-07-27T13:02:27.47Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/5f/d0/13f1a9467cf565eecc21dce89fb0723458d8c563d2ccfb99b96e8318dfd5/pybase64-1.4.2-cp310-cp310-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:1e79641c420a22e49c67c046895efad05bf5f8b1dbe0dd78b4af3ab3f2923fe2", size = 57718, upload-time = "2025-07-27T13:02:28.631Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/3e/34/d80335c36ad9400b18b4f92e9f680cf7646102fe4919f7bce5786a2ccb7b/pybase64-1.4.2-cp310-cp310-manylinux_2_31_riscv64.whl", hash = "sha256:12f5e7db522ef780a8b333dab5f7d750d270b23a1684bc2235ba50756c7ba428", size = 53021, upload-time = "2025-07-27T13:02:29.823Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/68/57/504ff75f7c78df28be126fe6634083d28d7f84c17e04a74a7dcb50ab2377/pybase64-1.4.2-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:a618b1e1a63e75dd40c2a397d875935ed0835464dc55cb1b91e8f880113d0444", size = 56306, upload-time = "2025-07-27T13:02:31.314Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/bf/bc/2d21cda8b73c8c9f5cd3d7e6e26dd6dfc96491052112f282332a3d5bf1d9/pybase64-1.4.2-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:89b0a51702c7746fa914e75e680ad697b979cdead6b418603f56a6fc9de2f50f", size = 50101, upload-time = "2025-07-27T13:02:32.662Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/88/6d/51942e7737bb0711ca3e55db53924fd7f07166d79da5508ab8f5fd5972a8/pybase64-1.4.2-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:c5161b8b82f8ba5dbbc3f76e0270622a2c2fdb9ffaf092d8f774ad7ec468c027", size = 66555, upload-time = "2025-07-27T13:02:34.122Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/b6/c8/c46024d196402e7be4d3fad85336863a34816c3436c51fcf9c7c0781bf11/pybase64-1.4.2-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:2168de920c9b1e57850e9ff681852923a953601f73cc96a0742a42236695c316", size = 55684, upload-time = "2025-07-27T13:02:35.427Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/6a/c5/953782c9d599ff5217ee87f19e317c494cd4840afcab4c48f99cb78ca201/pybase64-1.4.2-cp310-cp310-musllinux_1_2_riscv64.whl", hash = "sha256:7a1e3dc977562abe40ab43483223013be71b215a5d5f3c78a666e70a5076eeec", size = 52475, upload-time = "2025-07-27T13:02:36.634Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/05/fb/57d36173631aab67ca4558cdbde1047fc67a09b77f9c53addd57c7e9fdd4/pybase64-1.4.2-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:4cf1e8a57449e48137ef4de00a005e24c3f1cffc0aafc488e36ceb5bb2cbb1da", size = 53943, upload-time = "2025-07-27T13:02:37.777Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/75/73/23e5bb0bffac0cabe2d11d1c618f6ef73da9f430da03c5249931e3c49b63/pybase64-1.4.2-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:d8e1a381ba124f26a93d5925efbf6e6c36287fc2c93d74958e8b677c30a53fc0", size = 68411, upload-time = "2025-07-27T13:02:39.302Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/ce/e7/0d5c99e5e61ff5e46949a0128b49fc2c47afc0d2b815333459b17aa9d467/pybase64-1.4.2-cp310-cp310-win32.whl", hash = "sha256:8fdd9c5b60ec9a1db854f5f96bba46b80a9520069282dc1d37ff433eb8248b1f", size = 33614, upload-time = "2025-07-27T13:02:40.478Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/23/40/879b6de61d7c07a2cbf76b75e9739c4938c3a1f66ac03243f2ff7ec9fb6b/pybase64-1.4.2-cp310-cp310-win_amd64.whl", hash = "sha256:37a6c73f14c6539c0ad1aebf0cce92138af25c99a6e7aee637d9f9fc634c8a40", size = 35790, upload-time = "2025-07-27T13:02:41.864Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/d2/e2/75cec12880ce3f47a79a2b9a0cdc766dc0429a7ce967bb3ab3a4b55a7f6b/pybase64-1.4.2-cp310-cp310-win_arm64.whl", hash = "sha256:b3280d03b7b361622c469d005cc270d763d9e29d0a490c26addb4f82dfe71a79", size = 30900, upload-time = "2025-07-27T13:02:43.022Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/da/fb/edaa56bbf04715efc3c36966cc0150e01d7a8336c3da182f850b7fd43d32/pybase64-1.4.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:26284ef64f142067293347bcc9d501d2b5d44b92eab9d941cb10a085fb01c666", size = 38238, upload-time = "2025-07-27T13:02:44.224Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/28/a4/ca1538e9adf08f5016b3543b0060c18aea9a6e805dd20712a197c509d90d/pybase64-1.4.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:52dd32fe5cbfd8af8f3f034a4a65ee61948c72e5c358bf69d59543fc0dbcf950", size = 31659, upload-time = "2025-07-27T13:02:45.445Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/0b/8f/f9b49926a60848ba98350dd648227ec524fb78340b47a450c4dbaf24b1bb/pybase64-1.4.2-cp311-cp311-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:37f133e8c96427995480bb6d396d9d49e949a3e829591845bb6a5a7f215ca177", size = 68318, upload-time = "2025-07-27T13:02:46.644Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/29/9b/6ed2dd2bc8007f33b8316d6366b0901acbdd5665b419c2893b3dd48708de/pybase64-1.4.2-cp311-cp311-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:a6ee3874b0abbdd4c903d3989682a3f016fd84188622879f6f95a5dc5718d7e5", size = 71357, upload-time = "2025-07-27T13:02:47.937Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/fb/69/be9ac8127da8d8339db7129683bd2975cecb0bf40a82731e1a492577a177/pybase64-1.4.2-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:5c69f177b1e404b22b05802127d6979acf4cb57f953c7de9472410f9c3fdece7", size = 59817, upload-time = "2025-07-27T13:02:49.163Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/f4/a2/e3e09e000b509609276ee28b71beb0b61462d4a43b3e0db0a44c8652880c/pybase64-1.4.2-cp311-cp311-manylinux2014_armv7l.manylinux_2_17_armv7l.whl", hash = "sha256:80c817e88ef2ca3cc9a285fde267690a1cb821ce0da4848c921c16f0fec56fda", size = 56639, upload-time = "2025-07-27T13:02:50.384Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/01/70/ad7eff88aa4f1be06db705812e1f01749606933bf8fe9df553bb04b703e6/pybase64-1.4.2-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:7a4bb6e7e45bfdaea0f2aaf022fc9a013abe6e46ccea31914a77e10f44098688", size = 59368, upload-time = "2025-07-27T13:02:51.883Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/9d/82/0cd1b4bcd2a4da7805cfa04587be783bf9583b34ac16cadc29cf119a4fa2/pybase64-1.4.2-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:2710a80d41a2b41293cb0e5b84b5464f54aa3f28f7c43de88784d2d9702b8a1c", size = 59981, upload-time = "2025-07-27T13:02:53.16Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/3c/4c/8029a03468307dfaf0f9694d31830487ee43af5f8a73407004907724e8ac/pybase64-1.4.2-cp311-cp311-manylinux_2_31_riscv64.whl", hash = "sha256:aa6122c8a81f6597e1c1116511f03ed42cf377c2100fe7debaae7ca62521095a", size = 54908, upload-time = "2025-07-27T13:02:54.363Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/a1/8b/70bd0fe659e242efd0f60895a8ce1fe88e3a4084fd1be368974c561138c9/pybase64-1.4.2-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:b7e22b02505d64db308e9feeb6cb52f1d554ede5983de0befa59ac2d2ffb6a5f", size = 58650, upload-time = "2025-07-27T13:02:55.905Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/64/ca/9c1d23cbc4b9beac43386a32ad53903c816063cef3f14c10d7c3d6d49a23/pybase64-1.4.2-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:edfe4a3c8c4007f09591f49b46a89d287ef5e8cd6630339536fe98ff077263c2", size = 52323, upload-time = "2025-07-27T13:02:57.192Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/aa/29/a6292e9047248c8616dc53131a49da6c97a61616f80e1e36c73d7ef895fe/pybase64-1.4.2-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:b79b4a53dd117ffbd03e96953f2e6bd2827bfe11afeb717ea16d9b0893603077", size = 68979, upload-time = "2025-07-27T13:02:58.594Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/c2/e0/cfec7b948e170395d8e88066e01f50e71195db9837151db10c14965d6222/pybase64-1.4.2-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:fd9afa7a61d89d170607faf22287290045757e782089f0357b8f801d228d52c3", size = 58037, upload-time = "2025-07-27T13:02:59.753Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/74/7e/0ac1850198c9c35ef631174009cee576f4d8afff3bf493ce310582976ab4/pybase64-1.4.2-cp311-cp311-musllinux_1_2_riscv64.whl", hash = "sha256:5c17b092e4da677a595178d2db17a5d2fafe5c8e418d46c0c4e4cde5adb8cff3", size = 54416, upload-time = "2025-07-27T13:03:00.978Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/1b/45/b0b037f27e86c50e62d927f0bc1bde8b798dd55ab39197b116702e508d05/pybase64-1.4.2-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:120799274cf55f3f5bb8489eaa85142f26170564baafa7cf3e85541c46b6ab13", size = 56257, upload-time = "2025-07-27T13:03:02.201Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/d2/0d/5034598aac56336d88fd5aaf6f34630330643b51d399336b8c788d798fc5/pybase64-1.4.2-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:522e4e712686acec2d25de9759dda0b0618cb9f6588523528bc74715c0245c7b", size = 70889, upload-time = "2025-07-27T13:03:03.437Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/8a/3b/0645f21bb08ecf45635b624958b5f9e569069d31ecbf125dc7e0e5b83f60/pybase64-1.4.2-cp311-cp311-win32.whl", hash = "sha256:bfd828792982db8d787515535948c1e340f1819407c8832f94384c0ebeaf9d74", size = 33631, upload-time = "2025-07-27T13:03:05.194Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/8f/08/24f8103c1f19e78761026cdd9f3b3be73239bc19cf5ab6fef0e8042d0bc6/pybase64-1.4.2-cp311-cp311-win_amd64.whl", hash = "sha256:7a9e89d40dbf833af481d1d5f1a44d173c9c4b56a7c8dba98e39a78ee87cfc52", size = 35781, upload-time = "2025-07-27T13:03:06.779Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/66/cd/832fb035a0ea7eb53d776a5cfa961849e22828f6dfdfcdb9eb43ba3c0166/pybase64-1.4.2-cp311-cp311-win_arm64.whl", hash = "sha256:ce5809fa90619b03eab1cd63fec142e6cf1d361731a9b9feacf27df76c833343", size = 30903, upload-time = "2025-07-27T13:03:07.903Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/28/6d/11ede991e800797b9f5ebd528013b34eee5652df93de61ffb24503393fa5/pybase64-1.4.2-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:db2c75d1388855b5a1015b65096d7dbcc708e7de3245dcbedeb872ec05a09326", size = 38326, upload-time = "2025-07-27T13:03:09.065Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/fe/84/87f1f565f42e2397e2aaa2477c86419f5173c3699881c42325c090982f0a/pybase64-1.4.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:6b621a972a01841368fdb9dedc55fd3c6e0c7217d0505ba3b1ebe95e7ef1b493", size = 31661, upload-time = "2025-07-27T13:03:10.295Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/cb/2a/a24c810e7a61d2cc6f73fe9ee4872a03030887fa8654150901b15f376f65/pybase64-1.4.2-cp312-cp312-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:f48c32ac6a16cbf57a5a96a073fef6ff7e3526f623cd49faa112b7f9980bafba", size = 68192, upload-time = "2025-07-27T13:03:11.467Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/ee/87/d9baf98cbfc37b8657290ad4421f3a3c36aa0eafe4872c5859cfb52f3448/pybase64-1.4.2-cp312-cp312-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:ace8b23093a6bb862477080d9059b784096ab2f97541e8bfc40d42f062875149", size = 71587, upload-time = "2025-07-27T13:03:12.719Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/0b/89/3df043cc56ef3b91b7aa0c26ae822a2d7ec8da0b0fd7c309c879b0eb5988/pybase64-1.4.2-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:1772c7532a7fb6301baea3dd3e010148dbf70cd1136a83c2f5f91bdc94822145", size = 59910, upload-time = "2025-07-27T13:03:14.266Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/75/4f/6641e9edf37aeb4d4524dc7ba2168eff8d96c90e77f6283c2be3400ab380/pybase64-1.4.2-cp312-cp312-manylinux2014_armv7l.manylinux_2_17_armv7l.whl", hash = "sha256:f86f7faddcba5cbfea475f8ab96567834c28bf09ca6c7c3d66ee445adac80d8f", size = 56701, upload-time = "2025-07-27T13:03:15.6Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/2d/7f/20d8ac1046f12420a0954a45a13033e75f98aade36eecd00c64e3549b071/pybase64-1.4.2-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:0b8c8e275b5294089f314814b4a50174ab90af79d6a4850f6ae11261ff6a7372", size = 59288, upload-time = "2025-07-27T13:03:16.823Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/17/ea/9c0ca570e3e50b3c6c3442e280c83b321a0464c86a9db1f982a4ff531550/pybase64-1.4.2-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:864d85a0470c615807ae8b97d724d068b940a2d10ac13a5f1b9e75a3ce441758", size = 60267, upload-time = "2025-07-27T13:03:18.132Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/f9/ac/46894929d71ccedebbfb0284173b0fea96bc029cd262654ba8451a7035d6/pybase64-1.4.2-cp312-cp312-manylinux_2_31_riscv64.whl", hash = "sha256:47254d97ed2d8351e30ecfdb9e2414547f66ba73f8a09f932c9378ff75cd10c5", size = 54801, upload-time = "2025-07-27T13:03:19.669Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/6a/1e/02c95218ea964f0b2469717c2c69b48e63f4ca9f18af01a5b2a29e4c1216/pybase64-1.4.2-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:264b65ecc4f0ee73f3298ab83bbd8008f7f9578361b8df5b448f985d8c63e02a", size = 58599, upload-time = "2025-07-27T13:03:20.951Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/15/45/ccc21004930789b8fb439d43e3212a6c260ccddb2bf450c39a20db093f33/pybase64-1.4.2-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:fbcc2b30cd740c16c9699f596f22c7a9e643591311ae72b1e776f2d539e9dd9d", size = 52388, upload-time = "2025-07-27T13:03:23.064Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/c4/45/22e46e549710c4c237d77785b6fb1bc4c44c288a5c44237ba9daf5c34b82/pybase64-1.4.2-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:cda9f79c22d51ee4508f5a43b673565f1d26af4330c99f114e37e3186fdd3607", size = 68802, upload-time = "2025-07-27T13:03:24.673Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/55/0c/232c6261b81296e5593549b36e6e7884a5da008776d12665923446322c36/pybase64-1.4.2-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:0c91c6d2a7232e2a1cd10b3b75a8bb657defacd4295a1e5e80455df2dfc84d4f", size = 57841, upload-time = "2025-07-27T13:03:25.948Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/20/8a/b35a615ae6f04550d696bb179c414538b3b477999435fdd4ad75b76139e4/pybase64-1.4.2-cp312-cp312-musllinux_1_2_riscv64.whl", hash = "sha256:a370dea7b1cee2a36a4d5445d4e09cc243816c5bc8def61f602db5a6f5438e52", size = 54320, upload-time = "2025-07-27T13:03:27.495Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/d3/a9/8bd4f9bcc53689f1b457ecefed1eaa080e4949d65a62c31a38b7253d5226/pybase64-1.4.2-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:9aa4de83f02e462a6f4e066811c71d6af31b52d7484de635582d0e3ec3d6cc3e", size = 56482, upload-time = "2025-07-27T13:03:28.942Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/75/e5/4a7735b54a1191f61c3f5c2952212c85c2d6b06eb5fb3671c7603395f70c/pybase64-1.4.2-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:83a1c2f9ed00fee8f064d548c8654a480741131f280e5750bb32475b7ec8ee38", size = 70959, upload-time = "2025-07-27T13:03:30.171Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/d3/67/e2b6cb32c782e12304d467418e70da0212567f42bd4d3b5eb1fdf64920ad/pybase64-1.4.2-cp312-cp312-win32.whl", hash = "sha256:a6e5688b18d558e8c6b8701cc8560836c4bbeba61d33c836b4dba56b19423716", size = 33683, upload-time = "2025-07-27T13:03:31.775Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/4f/bc/d5c277496063a09707486180f17abbdbdebbf2f5c4441b20b11d3cb7dc7c/pybase64-1.4.2-cp312-cp312-win_amd64.whl", hash = "sha256:c995d21b8bd08aa179cd7dd4db0695c185486ecc72da1e8f6c37ec86cadb8182", size = 35817, upload-time = "2025-07-27T13:03:32.99Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/e6/69/e4be18ae685acff0ae77f75d4586590f29d2cd187bf603290cf1d635cad4/pybase64-1.4.2-cp312-cp312-win_arm64.whl", hash = "sha256:e254b9258c40509c2ea063a7784f6994988f3f26099d6e08704e3c15dfed9a55", size = 30900, upload-time = "2025-07-27T13:03:34.499Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/f4/56/5337f27a8b8d2d6693f46f7b36bae47895e5820bfa259b0072574a4e1057/pybase64-1.4.2-cp313-cp313-android_21_arm64_v8a.whl", hash = "sha256:0f331aa59549de21f690b6ccc79360ffed1155c3cfbc852eb5c097c0b8565a2b", size = 33888, upload-time = "2025-07-27T13:03:35.698Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/4c/09/f3f4b11fc9beda7e8625e29fb0f549958fcbb34fea3914e1c1d95116e344/pybase64-1.4.2-cp313-cp313-android_21_x86_64.whl", hash = "sha256:9dad20bf1f3ed9e6fe566c4c9d07d9a6c04f5a280daebd2082ffb8620b0a880d", size = 40796, upload-time = "2025-07-27T13:03:36.927Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/e3/ff/470768f0fe6de0aa302a8cb1bdf2f9f5cffc3f69e60466153be68bc953aa/pybase64-1.4.2-cp313-cp313-ios_13_0_arm64_iphoneos.whl", hash = "sha256:69d3f0445b0faeef7bb7f93bf8c18d850785e2a77f12835f49e524cc54af04e7", size = 30914, upload-time = "2025-07-27T13:03:38.475Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/75/6b/d328736662665e0892409dc410353ebef175b1be5eb6bab1dad579efa6df/pybase64-1.4.2-cp313-cp313-ios_13_0_arm64_iphonesimulator.whl", hash = "sha256:2372b257b1f4dd512f317fb27e77d313afd137334de64c87de8374027aacd88a", size = 31380, upload-time = "2025-07-27T13:03:39.7Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/ca/96/7ff718f87c67f4147c181b73d0928897cefa17dc75d7abc6e37730d5908f/pybase64-1.4.2-cp313-cp313-ios_13_0_x86_64_iphonesimulator.whl", hash = "sha256:fb794502b4b1ec91c4ca5d283ae71aef65e3de7721057bd9e2b3ec79f7a62d7d", size = 38230, upload-time = "2025-07-27T13:03:41.637Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/4d/58/a3307b048d799ff596a3c7c574fcba66f9b6b8c899a3c00a698124ca7ad5/pybase64-1.4.2-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:d5c532b03fd14a5040d6cf6571299a05616f925369c72ddf6fe2fb643eb36fed", size = 38319, upload-time = "2025-07-27T13:03:42.847Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/08/a7/0bda06341b0a2c830d348c6e1c4d348caaae86c53dc9a046e943467a05e9/pybase64-1.4.2-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:0f699514dc1d5689ca9cf378139e0214051922732f9adec9404bc680a8bef7c0", size = 31655, upload-time = "2025-07-27T13:03:44.426Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/87/df/e1d6e8479e0c5113c2c63c7b44886935ce839c2d99884c7304ca9e86547c/pybase64-1.4.2-cp313-cp313-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:cd3e8713cbd32c8c6aa935feaf15c7670e2b7e8bfe51c24dc556811ebd293a29", size = 68232, upload-time = "2025-07-27T13:03:45.729Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/71/ab/db4dbdfccb9ca874d6ce34a0784761471885d96730de85cee3d300381529/pybase64-1.4.2-cp313-cp313-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:d377d48acf53abf4b926c2a7a24a19deb092f366a04ffd856bf4b3aa330b025d", size = 71608, upload-time = "2025-07-27T13:03:47.01Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/11/e9/508df958563951045d728bbfbd3be77465f9231cf805cb7ccaf6951fc9f1/pybase64-1.4.2-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:d83c076e78d619b9e1dd674e2bf5fb9001aeb3e0b494b80a6c8f6d4120e38cd9", size = 59912, upload-time = "2025-07-27T13:03:48.277Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/f2/58/7f2cef1ceccc682088958448d56727369de83fa6b29148478f4d2acd107a/pybase64-1.4.2-cp313-cp313-manylinux2014_armv7l.manylinux_2_17_armv7l.whl", hash = "sha256:ab9cdb6a8176a5cb967f53e6ad60e40c83caaa1ae31c5e1b29e5c8f507f17538", size = 56413, upload-time = "2025-07-27T13:03:49.908Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/08/7c/7e0af5c5728fa7e2eb082d88eca7c6bd17429be819d58518e74919d42e66/pybase64-1.4.2-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:adf0c103ad559dbfb9fe69edfd26a15c65d9c991a5ab0a25b04770f9eb0b9484", size = 59311, upload-time = "2025-07-27T13:03:51.238Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/03/8b/09825d0f37e45b9a3f546e5f990b6cf2dd838e54ea74122c2464646e0c77/pybase64-1.4.2-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:0d03ef2f253d97ce0685d3624bf5e552d716b86cacb8a6c971333ba4b827e1fc", size = 60282, upload-time = "2025-07-27T13:03:52.56Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/9c/3f/3711d2413f969bfd5b9cc19bc6b24abae361b7673ff37bcb90c43e199316/pybase64-1.4.2-cp313-cp313-manylinux_2_31_riscv64.whl", hash = "sha256:e565abf906efee76ae4be1aef5df4aed0fda1639bc0d7732a3dafef76cb6fc35", size = 54845, upload-time = "2025-07-27T13:03:54.167Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/c6/3c/4c7ce1ae4d828c2bb56d144322f81bffbaaac8597d35407c3d7cbb0ff98f/pybase64-1.4.2-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:e3c6a5f15fd03f232fc6f295cce3684f7bb08da6c6d5b12cc771f81c9f125cc6", size = 58615, upload-time = "2025-07-27T13:03:55.494Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/f5/8f/c2fc03bf4ed038358620065c75968a30184d5d3512d09d3ef9cc3bd48592/pybase64-1.4.2-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:bad9e3db16f448728138737bbd1af9dc2398efd593a8bdd73748cc02cd33f9c6", size = 52434, upload-time = "2025-07-27T13:03:56.808Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/e2/0a/757d6df0a60327c893cfae903e15419914dd792092dc8cc5c9523d40bc9b/pybase64-1.4.2-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:2683ef271328365c31afee0ed8fa29356fb8fb7c10606794656aa9ffb95e92be", size = 68824, upload-time = "2025-07-27T13:03:58.735Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/a0/14/84abe2ed8c29014239be1cfab45dfebe5a5ca779b177b8b6f779bd8b69da/pybase64-1.4.2-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:265b20089cd470079114c09bb74b101b3bfc3c94ad6b4231706cf9eff877d570", size = 57898, upload-time = "2025-07-27T13:04:00.379Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/7e/c6/d193031f90c864f7b59fa6d1d1b5af41f0f5db35439988a8b9f2d1b32a13/pybase64-1.4.2-cp313-cp313-musllinux_1_2_riscv64.whl", hash = "sha256:e53173badead10ef8b839aa5506eecf0067c7b75ad16d9bf39bc7144631f8e67", size = 54319, upload-time = "2025-07-27T13:04:01.742Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/cb/37/ec0c7a610ff8f994ee6e0c5d5d66b6b6310388b96ebb347b03ae39870fdf/pybase64-1.4.2-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:5823b8dcf74da7da0f761ed60c961e8928a6524e520411ad05fe7f9f47d55b40", size = 56472, upload-time = "2025-07-27T13:04:03.089Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/c4/5a/e585b74f85cedd261d271e4c2ef333c5cfce7e80750771808f56fee66b98/pybase64-1.4.2-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:1237f66c54357d325390da60aa5e21c6918fbcd1bf527acb9c1f4188c62cb7d5", size = 70966, upload-time = "2025-07-27T13:04:04.361Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/ad/20/1b2fdd98b4ba36008419668c813025758214c543e362c66c49214ecd1127/pybase64-1.4.2-cp313-cp313-win32.whl", hash = "sha256:b0b851eb4f801d16040047f6889cca5e9dfa102b3e33f68934d12511245cef86", size = 33681, upload-time = "2025-07-27T13:04:06.126Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/ff/64/3df4067d169c047054889f34b5a946cbe3785bca43404b93c962a5461a41/pybase64-1.4.2-cp313-cp313-win_amd64.whl", hash = "sha256:19541c6e26d17d9522c02680fe242206ae05df659c82a657aabadf209cd4c6c7", size = 35822, upload-time = "2025-07-27T13:04:07.752Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/d1/fd/db505188adf812e60ee923f196f9deddd8a1895b2b29b37f5db94afc3b1c/pybase64-1.4.2-cp313-cp313-win_arm64.whl", hash = "sha256:77a191863d576c0a5dd81f8a568a5ca15597cc980ae809dce62c717c8d42d8aa", size = 30899, upload-time = "2025-07-27T13:04:09.062Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/d9/27/5f5fecd206ec1e06e1608a380af18dcb76a6ab08ade6597a3251502dcdb2/pybase64-1.4.2-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:2e194bbabe3fdf9e47ba9f3e157394efe0849eb226df76432126239b3f44992c", size = 38677, upload-time = "2025-07-27T13:04:10.334Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/bf/0f/abe4b5a28529ef5f74e8348fa6a9ef27d7d75fbd98103d7664cf485b7d8f/pybase64-1.4.2-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:39aef1dadf4a004f11dd09e703abaf6528a87c8dbd39c448bb8aebdc0a08c1be", size = 32066, upload-time = "2025-07-27T13:04:11.641Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/ac/7e/ea0ce6a7155cada5526017ec588b6d6185adea4bf9331565272f4ef583c2/pybase64-1.4.2-cp313-cp313t-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:91cb920c7143e36ec8217031282c8651da3b2206d70343f068fac0e7f073b7f9", size = 72300, upload-time = "2025-07-27T13:04:12.969Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/45/2d/e64c7a056c9ec48dfe130d1295e47a8c2b19c3984488fc08e5eaa1e86c88/pybase64-1.4.2-cp313-cp313t-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:6958631143fb9e71f9842000da042ec2f6686506b6706e2dfda29e97925f6aa0", size = 75520, upload-time = "2025-07-27T13:04:14.374Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/43/e0/e5f93b2e1cb0751a22713c4baa6c6eaf5f307385e369180486c8316ed21e/pybase64-1.4.2-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:dc35f14141ef3f1ac70d963950a278a2593af66fe5a1c7a208e185ca6278fa25", size = 65384, upload-time = "2025-07-27T13:04:16.204Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/ff/23/8c645a1113ad88a1c6a3d0e825e93ef8b74ad3175148767853a0a4d7626e/pybase64-1.4.2-cp313-cp313t-manylinux2014_armv7l.manylinux_2_17_armv7l.whl", hash = "sha256:5d949d2d677859c3a8507e1b21432a039d2b995e0bd3fe307052b6ded80f207a", size = 60471, upload-time = "2025-07-27T13:04:17.947Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/8b/81/edd0f7d8b0526b91730a0dd4ce6b4c8be2136cd69d424afe36235d2d2a06/pybase64-1.4.2-cp313-cp313t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:09caacdd3e15fe7253a67781edd10a6a918befab0052a2a3c215fe5d1f150269", size = 63945, upload-time = "2025-07-27T13:04:19.383Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/a5/a5/edc224cd821fd65100b7af7c7e16b8f699916f8c0226c9c97bbae5a75e71/pybase64-1.4.2-cp313-cp313t-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:e44b0e793b23f28ea0f15a9754bd0c960102a2ac4bccb8fafdedbd4cc4d235c0", size = 64858, upload-time = "2025-07-27T13:04:20.807Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/11/3b/92853f968f1af7e42b7e54d21bdd319097b367e7dffa2ca20787361df74c/pybase64-1.4.2-cp313-cp313t-manylinux_2_31_riscv64.whl", hash = "sha256:849f274d0bcb90fc6f642c39274082724d108e41b15f3a17864282bd41fc71d5", size = 58557, upload-time = "2025-07-27T13:04:22.229Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/76/09/0ec6bd2b2303b0ea5c6da7535edc9a608092075ef8c0cdd96e3e726cd687/pybase64-1.4.2-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:528dba7ef1357bd7ce1aea143084501f47f5dd0fff7937d3906a68565aa59cfe", size = 63624, upload-time = "2025-07-27T13:04:23.952Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/73/6e/52cb1ced2a517a3118b2e739e9417432049013ac7afa15d790103059e8e4/pybase64-1.4.2-cp313-cp313t-musllinux_1_2_armv7l.whl", hash = "sha256:1da54be743d9a68671700cfe56c3ab8c26e8f2f5cc34eface905c55bc3a9af94", size = 56174, upload-time = "2025-07-27T13:04:25.419Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/5b/9d/820fe79347467e48af985fe46180e1dd28e698ade7317bebd66de8a143f5/pybase64-1.4.2-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:9b07c0406c3eaa7014499b0aacafb21a6d1146cfaa85d56f0aa02e6d542ee8f3", size = 72640, upload-time = "2025-07-27T13:04:26.824Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/53/58/e863e10d08361e694935c815b73faad7e1ab03f99ae154d86c4e2f331896/pybase64-1.4.2-cp313-cp313t-musllinux_1_2_ppc64le.whl", hash = "sha256:312f2aa4cf5d199a97fbcaee75d2e59ebbaafcd091993eb373b43683498cdacb", size = 62453, upload-time = "2025-07-27T13:04:28.562Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/95/f0/c392c4ac8ccb7a34b28377c21faa2395313e3c676d76c382642e19a20703/pybase64-1.4.2-cp313-cp313t-musllinux_1_2_riscv64.whl", hash = "sha256:ad59362fc267bf15498a318c9e076686e4beeb0dfe09b457fabbc2b32468b97a", size = 58103, upload-time = "2025-07-27T13:04:29.996Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/32/30/00ab21316e7df8f526aa3e3dc06f74de6711d51c65b020575d0105a025b2/pybase64-1.4.2-cp313-cp313t-musllinux_1_2_s390x.whl", hash = "sha256:01593bd064e7dcd6c86d04e94e44acfe364049500c20ac68ca1e708fbb2ca970", size = 60779, upload-time = "2025-07-27T13:04:31.549Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/a6/65/114ca81839b1805ce4a2b7d58bc16e95634734a2059991f6382fc71caf3e/pybase64-1.4.2-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:5b81547ad8ea271c79fdf10da89a1e9313cb15edcba2a17adf8871735e9c02a0", size = 74684, upload-time = "2025-07-27T13:04:32.976Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/54/8f/aa9d445b9bb693b8f6bb1456bd6d8576d79b7a63bf6c69af3a539235b15f/pybase64-1.4.2-cp313-cp313t-win32.whl", hash = "sha256:7edbe70b5654545a37e6e6b02de738303b1bbdfcde67f6cfec374cfb5cc4099e", size = 33961, upload-time = "2025-07-27T13:04:34.806Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/0e/e5/da37cfb173c646fd4fc7c6aae2bc41d40de2ee49529854af8f4e6f498b45/pybase64-1.4.2-cp313-cp313t-win_amd64.whl", hash = "sha256:385690addf87c25d6366fab5d8ff512eed8a7ecb18da9e8152af1c789162f208", size = 36199, upload-time = "2025-07-27T13:04:36.223Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/66/3e/1eb68fb7d00f2cec8bd9838e2a30d183d6724ae06e745fd6e65216f170ff/pybase64-1.4.2-cp313-cp313t-win_arm64.whl", hash = "sha256:c2070d0aa88580f57fe15ca88b09f162e604d19282915a95a3795b5d3c1c05b5", size = 31221, upload-time = "2025-07-27T13:04:37.704Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/99/bf/00a87d951473ce96c8c08af22b6983e681bfabdb78dd2dcf7ee58eac0932/pybase64-1.4.2-cp314-cp314-ios_13_0_arm64_iphoneos.whl", hash = "sha256:4157ad277a32cf4f02a975dffc62a3c67d73dfa4609b2c1978ef47e722b18b8e", size = 30924, upload-time = "2025-07-27T13:04:39.189Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/ae/43/dee58c9d60e60e6fb32dc6da722d84592e22f13c277297eb4ce6baf99a99/pybase64-1.4.2-cp314-cp314-ios_13_0_arm64_iphonesimulator.whl", hash = "sha256:e113267dc349cf624eb4f4fbf53fd77835e1aa048ac6877399af426aab435757", size = 31390, upload-time = "2025-07-27T13:04:40.995Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/e1/11/b28906fc2e330b8b1ab4bc845a7bef808b8506734e90ed79c6062b095112/pybase64-1.4.2-cp314-cp314-ios_13_0_x86_64_iphonesimulator.whl", hash = "sha256:cea5aaf218fd9c5c23afacfe86fd4464dfedc1a0316dd3b5b4075b068cc67df0", size = 38212, upload-time = "2025-07-27T13:04:42.729Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/24/9e/868d1e104413d14b19feaf934fc7fad4ef5b18946385f8bb79684af40f24/pybase64-1.4.2-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:41213497abbd770435c7a9c8123fb02b93709ac4cf60155cd5aefc5f3042b600", size = 38303, upload-time = "2025-07-27T13:04:44.095Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/a3/73/f7eac96ca505df0600280d6bfc671a9e2e2f947c2b04b12a70e36412f7eb/pybase64-1.4.2-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:c8b522df7ee00f2ac1993ccd5e1f6608ae7482de3907668c2ff96a83ef213925", size = 31669, upload-time = "2025-07-27T13:04:45.845Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/c6/43/8e18bea4fd455100112d6a73a83702843f067ef9b9272485b6bdfd9ed2f0/pybase64-1.4.2-cp314-cp314-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:06725022e540c5b098b978a0418ca979773e2cbdbb76f10bd97536f2ad1c5b49", size = 68452, upload-time = "2025-07-27T13:04:47.788Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/e4/2e/851eb51284b97354ee5dfa1309624ab90920696e91a33cd85b13d20cc5c1/pybase64-1.4.2-cp314-cp314-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:a3e54dcf0d0305ec88473c9d0009f698cabf86f88a8a10090efeff2879c421bb", size = 71674, upload-time = "2025-07-27T13:04:49.294Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/57/0d/5cf1e5dc64aec8db43e8dee4e4046856d639a72bcb0fb3e716be42ced5f1/pybase64-1.4.2-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:67675cee727a60dc91173d2790206f01aa3c7b3fbccfa84fd5c1e3d883fe6caa", size = 60027, upload-time = "2025-07-27T13:04:50.769Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/a4/8e/3479266bc0e65f6cc48b3938d4a83bff045330649869d950a378f2ddece0/pybase64-1.4.2-cp314-cp314-manylinux2014_armv7l.manylinux_2_17_armv7l.whl", hash = "sha256:753da25d4fd20be7bda2746f545935773beea12d5cb5ec56ec2d2960796477b1", size = 56461, upload-time = "2025-07-27T13:04:52.37Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/20/b6/f2b6cf59106dd78bae8717302be5b814cec33293504ad409a2eb752ad60c/pybase64-1.4.2-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:a78c768ce4ca550885246d14babdb8923e0f4a848dfaaeb63c38fc99e7ea4052", size = 59446, upload-time = "2025-07-27T13:04:53.967Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/16/70/3417797dfccdfdd0a54e4ad17c15b0624f0fc2d6a362210f229f5c4e8fd0/pybase64-1.4.2-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:51b17f36d890c92f0618fb1c8db2ccc25e6ed07afa505bab616396fc9b0b0492", size = 60350, upload-time = "2025-07-27T13:04:55.881Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/a0/c6/6e4269dd98d150ae95d321b311a345eae0f7fd459d97901b4a586d7513bb/pybase64-1.4.2-cp314-cp314-manylinux_2_31_riscv64.whl", hash = "sha256:f92218d667049ab4f65d54fa043a88ffdb2f07fff1f868789ef705a5221de7ec", size = 54989, upload-time = "2025-07-27T13:04:57.436Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/f9/e8/18c1b0c255f964fafd0412b0d5a163aad588aeccb8f84b9bf9c8611d80f6/pybase64-1.4.2-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:3547b3d1499919a06491b3f879a19fbe206af2bd1a424ecbb4e601eb2bd11fea", size = 58724, upload-time = "2025-07-27T13:04:59.406Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/b1/ad/ddfbd2125fc20b94865fb232b2e9105376fa16eee492e4b7786d42a86cbf/pybase64-1.4.2-cp314-cp314-musllinux_1_2_armv7l.whl", hash = "sha256:958af7b0e09ddeb13e8c2330767c47b556b1ade19c35370f6451d139cde9f2a9", size = 52285, upload-time = "2025-07-27T13:05:01.198Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/b6/4c/b9d4ec9224add33c84b925a03d1a53cd4106efb449ea8e0ae7795fed7bf7/pybase64-1.4.2-cp314-cp314-musllinux_1_2_i686.whl", hash = "sha256:4facc57f6671e2229a385a97a618273e7be36a9ea0a9d1c1b9347f14d19ceba8", size = 69036, upload-time = "2025-07-27T13:05:03.109Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/92/38/7b96794da77bed3d9b4fea40f14ae563648fba83a696e7602fabe60c0eb7/pybase64-1.4.2-cp314-cp314-musllinux_1_2_ppc64le.whl", hash = "sha256:a32fc57d05d73a7c9b0ca95e9e265e21cf734195dc6873829a890058c35f5cfd", size = 57938, upload-time = "2025-07-27T13:05:04.744Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/eb/c5/ae8bbce3c322d1b074e79f51f5df95961fe90cb8748df66c6bc97616e974/pybase64-1.4.2-cp314-cp314-musllinux_1_2_riscv64.whl", hash = "sha256:3dc853243c81ce89cc7318e6946f860df28ddb7cd2a0648b981652d9ad09ee5a", size = 54474, upload-time = "2025-07-27T13:05:06.662Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/15/9a/c09887c4bb1b43c03fc352e2671ef20c6686c6942a99106a45270ee5b840/pybase64-1.4.2-cp314-cp314-musllinux_1_2_s390x.whl", hash = "sha256:0e6d863a86b3e7bc6ac9bd659bebda4501b9da842521111b0b0e54eb51295df5", size = 56533, upload-time = "2025-07-27T13:05:08.368Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/4f/0f/d5114d63d35d085639606a880cb06e2322841cd4b213adfc14d545c1186f/pybase64-1.4.2-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:6579475140ff2067903725d8aca47f5747bcb211597a1edd60b58f6d90ada2bd", size = 71030, upload-time = "2025-07-27T13:05:10.3Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/40/0e/fe6f1ed22ea52eb99f490a8441815ba21de288f4351aeef4968d71d20d2d/pybase64-1.4.2-cp314-cp314-win32.whl", hash = "sha256:373897f728d7b4f241a1f803ac732c27b6945d26d86b2741ad9b75c802e4e378", size = 34174, upload-time = "2025-07-27T13:05:12.254Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/71/46/0e15bea52ffc63e8ae7935e945accbaf635e0aefa26d3e31fdf9bc9dcd01/pybase64-1.4.2-cp314-cp314-win_amd64.whl", hash = "sha256:1afe3361344617d298c1d08bc657ef56d0f702d6b72cb65d968b2771017935aa", size = 36308, upload-time = "2025-07-27T13:05:13.898Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/4f/dc/55849fee2577bda77c1e078da04cc9237e8e474a8c8308deb702a26f2511/pybase64-1.4.2-cp314-cp314-win_arm64.whl", hash = "sha256:f131c9360babe522f3d90f34da3f827cba80318125cf18d66f2ee27e3730e8c4", size = 31341, upload-time = "2025-07-27T13:05:15.553Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/39/44/c69d088e28b25e70ac742b6789cde038473815b2a69345c4bae82d5e244d/pybase64-1.4.2-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:2583ac304131c1bd6e3120b0179333610f18816000db77c0a2dd6da1364722a8", size = 38678, upload-time = "2025-07-27T13:05:17.544Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/00/93/2860ec067497b9cbb06242f96d44caebbd9eed32174e4eb8c1ffef760f94/pybase64-1.4.2-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:75a8116be4ea4cdd30a5c4f1a6f3b038e0d457eb03c8a2685d8ce2aa00ef8f92", size = 32066, upload-time = "2025-07-27T13:05:19.18Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/d3/55/1e96249a38759332e8a01b31c370d88c60ceaf44692eb6ba4f0f451ee496/pybase64-1.4.2-cp314-cp314t-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:217ea776a098d7c08668e5526b9764f5048bbfd28cac86834217ddfe76a4e3c4", size = 72465, upload-time = "2025-07-27T13:05:20.866Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/6d/ab/0f468605b899f3e35dbb7423fba3ff98aeed1ec16abb02428468494a58f4/pybase64-1.4.2-cp314-cp314t-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:4ec14683e343c95b14248cdfdfa78c052582be7a3865fd570aa7cffa5ab5cf37", size = 75693, upload-time = "2025-07-27T13:05:22.896Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/91/d1/9980a0159b699e2489baba05b71b7c953b29249118ba06fdbb3e9ea1b9b5/pybase64-1.4.2-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:480ecf21e1e956c5a10d3cf7b3b7e75bce3f9328cf08c101e4aab1925d879f34", size = 65577, upload-time = "2025-07-27T13:05:25Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/16/86/b27e7b95f9863d245c0179a7245582eda3d262669d8f822777364d8fd7d5/pybase64-1.4.2-cp314-cp314t-manylinux2014_armv7l.manylinux_2_17_armv7l.whl", hash = "sha256:1fe1ebdc55e9447142e2f6658944aadfb5a4fbf03dbd509be34182585515ecc1", size = 60662, upload-time = "2025-07-27T13:05:27.138Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/28/87/a7f0dde0abc26bfbee761f1d3558eb4b139f33ddd9fe1f6825ffa7daa22d/pybase64-1.4.2-cp314-cp314t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:c793a2b06753accdaf5e1a8bbe5d800aab2406919e5008174f989a1ca0081411", size = 64179, upload-time = "2025-07-27T13:05:28.996Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/1e/88/5d6fa1c60e1363b4cac4c396978f39e9df4689e75225d7d9c0a5998e3a14/pybase64-1.4.2-cp314-cp314t-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:6acae6e1d1f7ebe40165f08076c7a73692b2bf9046fefe673f350536e007f556", size = 64968, upload-time = "2025-07-27T13:05:30.818Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/20/6e/2ed585af5b2211040445d9849326dd2445320c9316268794f5453cfbaf30/pybase64-1.4.2-cp314-cp314t-manylinux_2_31_riscv64.whl", hash = "sha256:88b91cd0949358aadcea75f8de5afbcf3c8c5fb9ec82325bd24285b7119cf56e", size = 58738, upload-time = "2025-07-27T13:05:32.629Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/ce/94/e2960b56322eabb3fbf303fc5a72e6444594c1b90035f3975c6fe666db5c/pybase64-1.4.2-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:53316587e1b1f47a11a5ff068d3cbd4a3911c291f2aec14882734973684871b2", size = 63802, upload-time = "2025-07-27T13:05:34.687Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/95/47/312139d764c223f534f751528ce3802887c279125eac64f71cd3b4e05abc/pybase64-1.4.2-cp314-cp314t-musllinux_1_2_armv7l.whl", hash = "sha256:caa7f20f43d00602cf9043b5ba758d54f5c41707d3709b2a5fac17361579c53c", size = 56341, upload-time = "2025-07-27T13:05:36.554Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/3f/d7/aec9a6ed53b128dac32f8768b646ca5730c88eef80934054d7fa7d02f3ef/pybase64-1.4.2-cp314-cp314t-musllinux_1_2_i686.whl", hash = "sha256:2d93817e24fdd79c534ed97705df855af6f1d2535ceb8dfa80da9de75482a8d7", size = 72838, upload-time = "2025-07-27T13:05:38.459Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/e3/a8/6ccc54c5f1f7c3450ad7c56da10c0f131d85ebe069ea6952b5b42f2e92d9/pybase64-1.4.2-cp314-cp314t-musllinux_1_2_ppc64le.whl", hash = "sha256:63cd769b51474d8d08f7f2ce73b30380d9b4078ec92ea6b348ea20ed1e1af88a", size = 62633, upload-time = "2025-07-27T13:05:40.624Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/34/22/2b9d89f8ff6f2a01d6d6a88664b20a4817049cfc3f2c62caca040706660c/pybase64-1.4.2-cp314-cp314t-musllinux_1_2_riscv64.whl", hash = "sha256:cd07e6a9993c392ec8eb03912a43c6a6b21b2deb79ee0d606700fe276e9a576f", size = 58282, upload-time = "2025-07-27T13:05:42.565Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/b2/14/dbf6266177532a6a11804ac080ebffcee272f491b92820c39886ee20f201/pybase64-1.4.2-cp314-cp314t-musllinux_1_2_s390x.whl", hash = "sha256:6a8944e8194adff4668350504bc6b7dbde2dab9244c88d99c491657d145b5af5", size = 60948, upload-time = "2025-07-27T13:05:44.48Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/fd/7a/b2ae9046a66dd5746cd72836a41386517b1680bea5ce02f2b4f1c9ebc688/pybase64-1.4.2-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:04ab398ec4b6a212af57f6a21a6336d5a1d754ff4ccb215951366ab9080481b2", size = 74854, upload-time = "2025-07-27T13:05:46.416Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/ef/7e/9856f6d6c38a7b730e001123d2d9fa816b8b1a45f0cdee1d509d5947b047/pybase64-1.4.2-cp314-cp314t-win32.whl", hash = "sha256:3b9201ecdcb1c3e23be4caebd6393a4e6615bd0722528f5413b58e22e3792dd3", size = 34490, upload-time = "2025-07-27T13:05:48.304Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/c7/38/8523a9dc1ec8704dedbe5ccc95192ae9a7585f7eec85cc62946fe3cacd32/pybase64-1.4.2-cp314-cp314t-win_amd64.whl", hash = "sha256:36e9b0cad8197136d73904ef5a71d843381d063fd528c5ab203fc4990264f682", size = 36680, upload-time = "2025-07-27T13:05:50.264Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/3c/52/5600104ef7b85f89fb8ec54f73504ead3f6f0294027e08d281f3cafb5c1a/pybase64-1.4.2-cp314-cp314t-win_arm64.whl", hash = "sha256:f25140496b02db0e7401567cd869fb13b4c8118bf5c2428592ec339987146d8b", size = 31600, upload-time = "2025-07-27T13:05:52.24Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/32/34/b67371f4fcedd5e2def29b1cf92a4311a72f590c04850f370c75297b48ce/pybase64-1.4.2-graalpy311-graalpy242_311_native-macosx_10_9_x86_64.whl", hash = "sha256:b4eed40a5f1627ee65613a6ac834a33f8ba24066656f569c852f98eb16f6ab5d", size = 38667, upload-time = "2025-07-27T13:07:25.315Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/aa/3e/e57fe09ed1c7e740d21c37023c5f7c8963b4c36380f41d10261cc76f93b4/pybase64-1.4.2-graalpy311-graalpy242_311_native-macosx_11_0_arm64.whl", hash = "sha256:57885fa521e9add235af4db13e9e048d3a2934cd27d7c5efac1925e1b4d6538d", size = 32094, upload-time = "2025-07-27T13:07:28.235Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/51/34/f40d3262c3953814b9bcdcf858436bd5bc1133a698be4bcc7ed2a8c0730d/pybase64-1.4.2-graalpy311-graalpy242_311_native-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:eef9255d926c64e2fca021d3aee98023bacb98e1518e5986d6aab04102411b04", size = 43212, upload-time = "2025-07-27T13:07:31.327Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/8c/2a/5e05d25718cb8ffd68bd46553ddfd2b660893d937feda1716b8a3b21fb38/pybase64-1.4.2-graalpy311-graalpy242_311_native-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:89614ea2d2329b6708746c540e0f14d692125df99fb1203ff0de948d9e68dfc9", size = 35789, upload-time = "2025-07-27T13:07:34.026Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/d5/9d/f56c3ee6e94faaae2896ecaf666428330cb24096abf7d2427371bb2b403a/pybase64-1.4.2-graalpy311-graalpy242_311_native-win_amd64.whl", hash = "sha256:e401cecd2d7ddcd558768b2140fd4430746be4d17fb14c99eec9e40789df136d", size = 35861, upload-time = "2025-07-27T13:07:37.099Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/fb/04/bfe2bd0d76385750f3541724b4abfe4ea111b3cc01ff7e83f410054adc30/pybase64-1.4.2-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:4b29c93414ba965777643a9d98443f08f76ac04519ad717aa859113695372a07", size = 38226, upload-time = "2025-07-27T13:07:40.121Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/22/13/c717855760b78ded1a9d308984c7e3e99fcf79c6cac5a231ed8c1238218f/pybase64-1.4.2-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:5e0c3353c0bf099c5c3f8f750202c486abee8f23a566b49e9e7b1222fbf5f259", size = 31524, upload-time = "2025-07-27T13:07:43.946Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/cf/da/2b7e69abfc62abe4d54b10d1e09ec78021a6b9b2d7e6e7b632243a19433e/pybase64-1.4.2-pp310-pypy310_pp73-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:4f98c5c6152d3c01d933fcde04322cd9ddcf65b5346034aac69a04c1a7cbb012", size = 40667, upload-time = "2025-07-27T13:07:46.715Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/f1/11/ba738655fb3ba85c7a0605eddd2709fef606e654840c72ee5c5ff7ab29bf/pybase64-1.4.2-pp310-pypy310_pp73-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:9096a4977b7aff7ef250f759fb6a4b6b7b6199d99c84070c7fc862dd3b208b34", size = 41290, upload-time = "2025-07-27T13:07:49.534Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/5d/38/2d5502fcaf712297b95c1b6ca924656dd7d17501fd7f9c9e0b3bbf8892ef/pybase64-1.4.2-pp310-pypy310_pp73-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:49d8597e2872966399410502310b1e2a5b7e8d8ba96766ee1fe242e00bd80775", size = 35438, upload-time = "2025-07-27T13:07:52.327Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/b6/db/e03b8b6daa60a3fbef21741403e0cf18b2aff3beebdf6e3596bb9bab16c7/pybase64-1.4.2-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:2ef16366565389a287df82659e055e88bdb6c36e46a3394950903e0a9cb2e5bf", size = 36121, upload-time = "2025-07-27T13:07:55.54Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/0e/bf/5ebaa2d9ddb5fc506633bc8b820fc27e64da964937fb30929c0367c47d00/pybase64-1.4.2-pp311-pypy311_pp73-macosx_10_15_x86_64.whl", hash = "sha256:0a5393be20b0705870f5a8969749af84d734c077de80dd7e9f5424a247afa85e", size = 38162, upload-time = "2025-07-27T13:07:58.364Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/25/41/795c5fd6e5571bb675bf9add8a048166dddf8951c2a903fea8557743886b/pybase64-1.4.2-pp311-pypy311_pp73-macosx_11_0_arm64.whl", hash = "sha256:448f0259a2f1a17eb086f70fe2ad9b556edba1fc5bc4e62ce6966179368ee9f8", size = 31452, upload-time = "2025-07-27T13:08:01.259Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/aa/dd/c819003b59b2832256b72ad23cbeadbd95d083ef0318d07149a58b7a88af/pybase64-1.4.2-pp311-pypy311_pp73-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:1159e70cba8e76c3d8f334bd1f8fd52a1bb7384f4c3533831b23ab2df84a6ef3", size = 40668, upload-time = "2025-07-27T13:08:04.176Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/0e/c5/38c6aba28678c4a4db49312a6b8171b93a0ffe9f21362cf4c0f325caa850/pybase64-1.4.2-pp311-pypy311_pp73-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:7d943bc5dad8388971494554b97f22ae06a46cc7779ad0de3d4bfdf7d0bbea30", size = 41281, upload-time = "2025-07-27T13:08:07.395Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/e5/23/5927bd9e59714e4e8cefd1d21ccd7216048bb1c6c3e7104b1b200afdc63d/pybase64-1.4.2-pp311-pypy311_pp73-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:10b99182c561d86422c5de4265fd1f8f172fb38efaed9d72c71fb31e279a7f94", size = 35433, upload-time = "2025-07-27T13:08:10.551Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/01/0f/fab7ed5bf4926523c3b39f7621cea3e0da43f539fbc2270e042f1afccb79/pybase64-1.4.2-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:bb082c1114f046e59fcbc4f2be13edc93b36d7b54b58605820605be948f8fdf6", size = 36131, upload-time = "2025-07-27T13:08:13.777Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "pycairo"
|
||||
version = "1.28.0"
|
||||
@@ -6483,16 +6560,16 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "smithy-aws-core"
|
||||
version = "0.1.1"
|
||||
version = "0.1.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "aws-sdk-signers", marker = "python_full_version >= '3.12'" },
|
||||
{ name = "smithy-core", marker = "python_full_version >= '3.12'" },
|
||||
{ name = "smithy-http", marker = "python_full_version >= '3.12'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/56/d3/f847e0fd36b95aa36ce3a4c9ce1a08e16b2aa9a56b71714045c9c924e282/smithy_aws_core-0.1.1.tar.gz", hash = "sha256:78dfd7040fc2bc72b6af293096642fc9a7bfd2db28ddbdf7c4110535eab9d662", size = 11196, upload-time = "2025-10-21T20:21:18.648Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/ec/e8/8cef48be92ed09a112c54747a4515313ba96e767e7e0118a769aeb147e07/smithy_aws_core-0.1.0.tar.gz", hash = "sha256:5f197b69ad1380e9118e1e3c9032e0e305525ef56fb4fc97dea6414281065526", size = 11135, upload-time = "2025-09-29T19:37:13.072Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/d0/04/87cb06f0f6d664b5cffdef6d4042dd52c11c138436084d30ffdaa3543031/smithy_aws_core-0.1.1-py3-none-any.whl", hash = "sha256:0d1634f276c2999dc2a04fafef63b9d28309de50d939d1d49df952773a7063c4", size = 18963, upload-time = "2025-10-21T20:21:17.692Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/46/7e/6d05275646bc2cdf7b0749e9bd54958a4e808aafeee4d8ff2fdaa8233dc2/smithy_aws_core-0.1.0-py3-none-any.whl", hash = "sha256:a8cda4011562f45f1fc5957c3a981b6016d736178450e5f2a1586937632af487", size = 18959, upload-time = "2025-09-29T19:37:12.041Z" },
|
||||
]
|
||||
|
||||
[package.optional-dependencies]
|
||||
@@ -6526,14 +6603,14 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "smithy-http"
|
||||
version = "0.2.0"
|
||||
version = "0.1.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "smithy-core", marker = "python_full_version >= '3.12'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/3c/1c/44e99a7dfb8c39bf0c3d998accdf4573a7a3488863b90f21af260cec2d45/smithy_http-0.2.0.tar.gz", hash = "sha256:2382562fa9af326be455f14b18615f16ffe9db756e51b2a4ca0d23e1b881cff8", size = 26729, upload-time = "2025-10-21T20:21:06.146Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/4e/62/5ba46c7432fbb0852acf8340402879ba53bb4c009b875e1b5b2e9df844ff/smithy_http-0.1.0.tar.gz", hash = "sha256:ed44552531f594e31101f7186c7b01b508ecd38a860b45390a1cce7da700df4b", size = 28269, upload-time = "2025-09-29T19:37:18.629Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/d4/e2/d475fad81ac74ec0e145cb6d72afe5ecde4e2358bd632c2fd5d3f4bc87dc/smithy_http-0.2.0-py3-none-any.whl", hash = "sha256:49ee2402d7737798d70f99f491fbfb2a5767283ae562e21b6f86e3fd14f3e3e0", size = 37328, upload-time = "2025-10-21T20:21:05.362Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/5b/23/d18076ea45b3000c5e9eb8ebd75a4ea1b65b5c59e5c2080a119e2679dfba/smithy_http-0.1.0-py3-none-any.whl", hash = "sha256:7657aaf4b9e025cb9d317406f417b49cf19fba9d1b2ab4f5e6d9dc5a2dd7cdba", size = 38995, upload-time = "2025-09-29T19:37:17.506Z" },
|
||||
]
|
||||
|
||||
[package.optional-dependencies]
|
||||
@@ -6619,14 +6696,14 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "speechmatics-rt"
|
||||
version = "0.5.0"
|
||||
version = "0.4.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "websockets" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/57/26/10359e1f16c2aa6a198eb11a9056f4a86a8bb8d4e610bbbe4a118b227b59/speechmatics_rt-0.5.0.tar.gz", hash = "sha256:ca974a186a012f946fd997deeaf3bf1c4f203f6d6e05a866172d27709183afc8", size = 26832, upload-time = "2025-10-15T15:54:25.695Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/17/2e/d694390d58b9b6807280441d1275856f5a316c3e8a815c2037502636bbea/speechmatics_rt-0.4.2.tar.gz", hash = "sha256:c0f7ed34442b0f505a12d1b19c8cc8dc2cc0b1a423aeb5669ca0738fc5e59f0d", size = 26142, upload-time = "2025-09-30T10:50:36.804Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/47/2e/9931ebe9360e9d385c68826b33137c2c9a4cfa361cd929d1ac6e72ebfe53/speechmatics_rt-0.5.0-py3-none-any.whl", hash = "sha256:58151488f891fa00cf7054f0cfab1b1eb94b55c3441be587f7941c726caef991", size = 32850, upload-time = "2025-10-15T15:54:24.5Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/9a/c7/2cd551c71e14256ca463f31feec17f466b57c2730d636e20803e7a541104/speechmatics_rt-0.4.2-py3-none-any.whl", hash = "sha256:70b91ff750e2f7516eaf1839d39f7a8ac65ff6665638b837cf67bab9cc9967bc", size = 32131, upload-time = "2025-09-30T10:50:35.656Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -7451,7 +7528,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "vllm"
|
||||
version = "0.9.1"
|
||||
version = "0.9.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "aiohttp" },
|
||||
@@ -7475,10 +7552,6 @@ dependencies = [
|
||||
{ name = "numpy" },
|
||||
{ name = "openai" },
|
||||
{ name = "opencv-python-headless" },
|
||||
{ name = "opentelemetry-api" },
|
||||
{ name = "opentelemetry-exporter-otlp" },
|
||||
{ name = "opentelemetry-sdk" },
|
||||
{ name = "opentelemetry-semantic-conventions-ai" },
|
||||
{ name = "outlines" },
|
||||
{ name = "partial-json-parser" },
|
||||
{ name = "pillow" },
|
||||
@@ -7487,6 +7560,7 @@ dependencies = [
|
||||
{ name = "protobuf" },
|
||||
{ name = "psutil" },
|
||||
{ name = "py-cpuinfo" },
|
||||
{ name = "pybase64" },
|
||||
{ name = "pydantic" },
|
||||
{ name = "python-json-logger" },
|
||||
{ name = "pyyaml" },
|
||||
@@ -7509,11 +7583,11 @@ dependencies = [
|
||||
{ name = "typing-extensions" },
|
||||
{ name = "watchfiles" },
|
||||
{ name = "xformers", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "xgrammar", marker = "platform_machine == 'aarch64' or platform_machine == 'x86_64'" },
|
||||
{ name = "xgrammar", marker = "platform_machine == 'aarch64' or platform_machine == 'arm64' or platform_machine == 'x86_64'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/c5/5b/5f42b41d045c01821be62162fc6b1cfb14db1674027c7b623adb3a66dccf/vllm-0.9.1.tar.gz", hash = "sha256:c5ad11603f49a1fad05c88debabb8b839780403ce1b51751ec4da4e8a838082c", size = 8670972, upload-time = "2025-06-10T21:46:12.114Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/35/89/2fbf95d398b5751b44c7256bd80e57c589142f1bfcc15f5dc76438b8853a/vllm-0.9.2.tar.gz", hash = "sha256:6b0d855ea8ba18d76364c9b82ea94bfcaa9c9e724055438b5733e4716ed104e1", size = 8997087, upload-time = "2025-07-08T04:49:01.722Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/b5/56/ffcf6215a571cf9aa58ded06a9640bff21b4918e27344677cd33290ab9da/vllm-0.9.1-cp38-abi3-manylinux1_x86_64.whl", hash = "sha256:28b99e8df39c7aaeda04f7e5353b18564a1a9d1c579691945523fc4777a1a8c8", size = 394637693, upload-time = "2025-06-10T21:46:01.784Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/f4/72/c14ff1acac64294f45782769b9c8144a1c3e8d4f2228d4648197511b015a/vllm-0.9.2-cp38-abi3-manylinux1_x86_64.whl", hash = "sha256:f3c5da29a286f4933b480a5b4749fab226564f35c96928eeef547f88d385cd34", size = 383350132, upload-time = "2025-07-08T04:48:54.133Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -7823,6 +7897,7 @@ name = "xgrammar"
|
||||
version = "0.1.19"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "mlx-lm", marker = "platform_machine == 'arm64' and sys_platform == 'darwin'" },
|
||||
{ name = "ninja" },
|
||||
{ name = "pydantic" },
|
||||
{ name = "sentencepiece" },
|
||||
|
||||
Reference in New Issue
Block a user