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273 Commits

Author SHA1 Message Date
Aleix Conchillo Flaqué
bff5b3e562 LLMAssistantContextAggregator: always aggregate TTSTextFrame
This is the assistant aggregator and we should add everything that is being
spoekn. Because of that we should use TTSTextFrame because those are the frames
that are actually spoken. We should send the aggregation as soon as the bot
stops speaking.

So, we don't need to handle `LLMFullResponseStartFrame` and
`LLMFullResponseEndFrame` anymore.
2025-02-20 17:41:31 -08:00
Aleix Conchillo Flaqué
7e5e167a4b Merge pull request #1250 from pipecat-ai/aleix/context-aggregation-simulatenous-text-tools
AssistantContextAggregator: append aggregation and tools in the same turn
2025-02-20 17:32:57 -08:00
Aleix Conchillo Flaqué
d04c4b36f3 AssistantContextAggregator: append aggregation and tools in the same turn 2025-02-20 17:29:43 -08:00
Aleix Conchillo Flaqué
a811e53626 Merge pull request #1253 from pipecat-ai/aleix/http-tts-services-stopped-frame
HTTP TTS services stopped frame
2025-02-20 17:28:05 -08:00
Aleix Conchillo Flaqué
69e6f3fdb7 rime: pass aiohttp session to constructor 2025-02-20 07:36:24 -08:00
Aleix Conchillo Flaqué
6809254963 tts: fix metrics and TTSStoppedFrame frame in HTTP services
Fixes #1247
2025-02-20 07:36:21 -08:00
Aleix Conchillo Flaqué
81093d3bed Merge pull request #1252 from pipecat-ai/aleix/remove-vad-extra-logging
BaseInputTransport: remove VAD logging
2025-02-20 07:32:20 -08:00
Aleix Conchillo Flaqué
d9a67164f6 Merge pull request #1251 from pipecat-ai/aleix/fish-tts-service-push-stop-frame
FishAudioTTSService should push TTSStoppedFrame
2025-02-20 07:32:05 -08:00
Aleix Conchillo Flaqué
98259af54e update CHANGELOG 2025-02-19 22:05:48 -08:00
Dominic Stewart
039d144c79 examples(phone-bot): updated example to use Gemini (#1233) 2025-02-19 22:03:37 -08:00
Aleix Conchillo Flaqué
d0f67fc189 BaseInputTransport: remove VAD logging
These logs are very verbose. They were added to try to find an issue that
resulted in being because of low CPU/memory resources, but these logs were not
helpful to determine that.
2025-02-19 21:55:11 -08:00
Aleix Conchillo Flaqué
6e3f96aa83 fish: automatically send TTSStoppedFrame after timeout 2025-02-19 21:41:18 -08:00
Aleix Conchillo Flaqué
293677588d tts: make push_stop_frames default to 2.0s 2025-02-19 21:39:00 -08:00
Filipi da Silva Fuchter
77e777b1ce Merge pull request #1249 from pipecat-ai/invoking_call_start_function
Fixed an issue that `start_callback` was not invoked for some LLM services
2025-02-19 18:09:00 -03:00
Filipi Fuchter
7e7926059c Fixed an issue that start_callback was not invoked for some LLM services. 2025-02-19 18:04:20 -03:00
Aleix Conchillo Flaqué
c948754eff Merge pull request #1248 from pipecat-ai/aleix/daily-transport-room-url
daily: add room_url property
2025-02-19 09:46:46 -08:00
Aleix Conchillo Flaqué
83f1a8830d daily: add room_url property 2025-02-19 09:29:53 -08:00
James Hush
80f8e05fcf docs: fix transcripts in translation chatbot example (#1199) 2025-02-19 16:07:22 +08:00
Aleix Conchillo Flaqué
afd1a1e80b Merge pull request #1245 from pipecat-ai/aleix/stt-mute-filter-trace-logging 2025-02-18 21:21:55 -08:00
Aleix Conchillo Flaqué
84ac88cad7 STTMuteFilter: change suppressed logging to trace 2025-02-18 18:03:37 -08:00
Aleix Conchillo Flaqué
211163e5c7 Merge pull request #1241 from pipecat-ai/aleix/deepgram-nova-3
deepgram: use the new nova-3 model as default
2025-02-18 17:53:04 -08:00
Aleix Conchillo Flaqué
1b0bcebef6 deepgram: use the new nova-3 model as default 2025-02-18 17:51:54 -08:00
Aleix Conchillo Flaqué
89736b03c4 Merge pull request #1243 from pipecat-ai/aleix/add-deepgram-addons
deepgram: add ability to provide custom addons
2025-02-18 17:47:48 -08:00
Aleix Conchillo Flaqué
4edda718ed deepgram: add ability to provide custom addons 2025-02-18 17:45:41 -08:00
Aleix Conchillo Flaqué
22a62edc9e Merge pull request #1242 from pipecat-ai/aleix/utils-network-exponential
network: added exponential_backoff_time() function
2025-02-18 17:44:21 -08:00
Aleix Conchillo Flaqué
50b6cc8135 network: added exponential_backoff_time() function 2025-02-18 17:42:43 -08:00
Aleix Conchillo Flaqué
45cf36925a Merge pull request #1240 from pipecat-ai/aleix/handle-deepgram-on-error
deepgram: handle error event and reconnect
2025-02-18 17:41:29 -08:00
Filipi da Silva Fuchter
83a71e1fec Merge pull request #1112 from pipecat-ai/bot-ready-signalling-rn
React Native client for the bot ready example.
2025-02-18 15:17:38 -03:00
Filipi Fuchter
e809c8680e Upgrading to use the latest node stable version 2025-02-18 15:12:44 -03:00
Aleix Conchillo Flaqué
c926063d74 deepgram: handle error event and reconnect 2025-02-18 09:52:18 -08:00
Aleix Conchillo Flaqué
0334550356 Merge pull request #1238 from pipecat-ai/aleix/stt-mute-filter-ignore-input-audio-frames
STTMuteFilter: ignore audio frames so no transcriptions are generated
2025-02-18 09:48:13 -08:00
Aleix Conchillo Flaqué
90b9dce710 STTMuteFilter: ignore audio frames so no transcriptions are generated 2025-02-17 19:59:05 -08:00
Aleix Conchillo Flaqué
b45f7fee6f Merge pull request #1225 from pipecat-ai/aleix/prepare-0.0.57
update CHANGELOG for 0.0.57
2025-02-14 18:50:08 -08:00
Aleix Conchillo Flaqué
01c06c5cac update CHANGELOG for 0.0.57 2025-02-14 18:47:33 -08:00
Aleix Conchillo Flaqué
329e89c1d9 TTSService: push BotStoppedSpeakingFrame 2025-02-14 18:47:33 -08:00
Aleix Conchillo Flaqué
883410d8ac FrameProcessor: no need to create an input event every time 2025-02-14 18:47:33 -08:00
Aleix Conchillo Flaqué
1f5b790dd0 TTSService: reset processing text during interruptions 2025-02-14 18:47:33 -08:00
Aleix Conchillo Flaqué
a107b1cb4b examples(06a): use CartesiaTTSService 2025-02-14 18:47:33 -08:00
Aleix Conchillo Flaqué
63950912f0 LLMAssistantContextAggregator: add missing variable initialization 2025-02-14 18:47:33 -08:00
Aleix Conchillo Flaqué
2ce9402571 LLMAssistantResponseAggregator: initialize messages 2025-02-14 18:47:33 -08:00
Aleix Conchillo Flaqué
f6912c0f9a utils: don't consider colon an end of sentence 2025-02-14 18:47:33 -08:00
Aleix Conchillo Flaqué
633a4d4c58 FalImageGenService: load image async to not block the event loop 2025-02-14 18:47:33 -08:00
Aleix Conchillo Flaqué
67da745bb3 tts: make frame pausing/resuming optional 2025-02-14 18:47:33 -08:00
Aleix Conchillo Flaqué
5126d4de92 tts: handle incoming frames pausing/resuming from base TTSService class 2025-02-14 18:47:33 -08:00
Aleix Conchillo Flaqué
426d7ac213 transports: some local audio and tk updates 2025-02-14 18:47:33 -08:00
Mark Backman
9115692c72 Merge pull request #1227 from pipecat-ai/mb/fix-25-error
fix: ensure proper Google message format conversion in transcription …
2025-02-14 21:01:05 -05:00
Mark Backman
c26fe3f277 fix: ensure proper Google message format conversion in transcription filter 2025-02-14 20:28:26 -05:00
Mark Backman
47b059d387 Merge pull request #1226 from pipecat-ai/mb/add-transcript-processor-tests
tests: add tests for TranscriptProcessor
2025-02-14 19:50:38 -05:00
Mark Backman
a49d81e519 tests: add tests for TranscriptProcessor 2025-02-14 17:10:40 -05:00
Aleix Conchillo Flaqué
b3a575c7c7 Merge pull request #1212 from Vaibhav159/vl_fix_incorrect_has_regular_messages_check
fixing google llm service error
2025-02-14 13:16:37 -08:00
Aleix Conchillo Flaqué
790d0c1256 Merge pull request #1224 from M1ngXU/patch-1
Update openai.py
2025-02-14 13:13:00 -08:00
Aleix Conchillo Flaqué
ee7e0dc3f7 Merge pull request #1223 from pipecat-ai/aleix/audio-context-tts-service
audio context tts service and cartesia fixes
2025-02-14 12:12:42 -08:00
Aleix Conchillo Flaqué
f53ee79ddb RimeTTSService: use AudioContextWordTTSService 2025-02-14 11:55:54 -08:00
Aleix Conchillo Flaqué
aeadb40c3f CartesiaTTSService: use AudioContextWordTTSService
By supporting multiple audio requests we fix an issue that was causing audio
overlapping.
2025-02-14 11:55:54 -08:00
Aleix Conchillo Flaqué
cacb07f4c2 introduce AudioContextWordTTSService 2025-02-14 11:55:54 -08:00
M1ngXU
0b91d821fb Update openai.py
d
2025-02-14 20:27:08 +01:00
Aleix Conchillo Flaqué
af66a43056 Merge pull request #1222 from pipecat-ai/aleix/websocket-service-handle-clean-disconnection
WebsocketService: handle clean server disconnection
2025-02-14 10:33:54 -08:00
Aleix Conchillo Flaqué
e006dcf172 WebsocketService: handle clean server disconnection
The websocket async iterator doesn't raise an exception when the server
disconnects cleanly. We should handle that and raise an exception so we can
reconnect.
2025-02-14 10:11:56 -08:00
Filipi da Silva Fuchter
8588f8b0d8 Merge pull request #1220 from pipecat-ai/instant_voice_demo_example
Instant voice example.
2025-02-14 14:24:13 -03:00
Filipi Fuchter
bff54547b0 Instant voice example. 2025-02-14 14:19:17 -03:00
Mark Backman
b2754bf208 Merge pull request #1219 from pipecat-ai/mb/markdown-text-filter-tests
Add MarkdownTextFilter tests
2025-02-13 21:10:52 -05:00
Mark Backman
9a4942b0d0 Merge pull request #1218 from pipecat-ai/mb/user-idle-tests
Add UserIdleProcessor tests
2025-02-13 18:53:22 -05:00
Mark Backman
ed6201910b Add MarkdownTextFilter tests 2025-02-13 18:51:46 -05:00
Mark Backman
ac5ebc587e Add tests for UserIdleProcessor 2025-02-13 18:47:29 -05:00
Aleix Conchillo Flaqué
dff4c54e57 Merge pull request #1209 from pipecat-ai/aleix/reimplement-llm-response-aggregators
reimplement LLM response aggregators
2025-02-13 15:30:40 -08:00
Aleix Conchillo Flaqué
c744409651 SegmentedSTTService: fix process_audio_frame() arguments 2025-02-13 15:25:22 -08:00
Aleix Conchillo Flaqué
7578fbeaef update google requirements 2025-02-13 15:25:22 -08:00
Aleix Conchillo Flaqué
5909dff423 LLMContextResponseAggregator: add VAD emulation support 2025-02-13 15:25:22 -08:00
Aleix Conchillo Flaqué
a6502df72c services: forgot to pass context instead of user aggregator 2025-02-13 13:50:33 -08:00
Aleix Conchillo Flaqué
e0d24d7fc0 update CHANGELOG 2025-02-13 13:21:32 -08:00
Aleix Conchillo Flaqué
99779046a8 services: use push_context_frame() 2025-02-13 13:20:38 -08:00
Aleix Conchillo Flaqué
67cdc0063a BaseTransportOutput: allow pushing frames upstream 2025-02-13 13:20:38 -08:00
Aleix Conchillo Flaqué
b28f752afa tests: add anthropic and google aggregator tests 2025-02-13 13:20:38 -08:00
Aleix Conchillo Flaqué
463078e375 initialize assistant aggregators with context and push upstream instead 2025-02-13 13:20:38 -08:00
Aleix Conchillo Flaqué
84510fd521 LLMUserContextAggregator: add space between transcriptions 2025-02-13 13:20:38 -08:00
Aleix Conchillo Flaqué
9f6a1c093a LLMUserContextAggregator: reset user speaking time after bot interruption 2025-02-13 13:20:38 -08:00
Aleix Conchillo Flaqué
b602e78625 tests: add OpenAI context aggregator tests 2025-02-13 13:20:38 -08:00
Aleix Conchillo Flaqué
7c815121ea LLMContextResponseAggregator: add missing reset() implementation 2025-02-13 13:20:38 -08:00
Aleix Conchillo Flaqué
16a107948b services: missing kwargs in anthropic/openai user context aggregator 2025-02-13 13:20:38 -08:00
Aleix Conchillo Flaqué
839aa7d935 llm_response: add some initial docstrings to LLM aggregators 2025-02-13 13:20:38 -08:00
Aleix Conchillo Flaqué
4cbcfe2b0b LLMUserContextAggregator: interrupt the bot if VAD happened a while back 2025-02-13 13:20:38 -08:00
Aleix Conchillo Flaqué
91a628d1ba UserResponseAggregator: implement on top of LLMUserResponseAggregator 2025-02-13 13:20:37 -08:00
Aleix Conchillo Flaqué
50288eeaaa tests: add LLM response aggregators tests 2025-02-13 13:20:37 -08:00
Aleix Conchillo Flaqué
e1f2bbceb3 reimplement LLM response aggregators 2025-02-13 13:20:37 -08:00
Aleix Conchillo Flaqué
8bdd7ed0ed tests: implement langchain tests with run_test() 2025-02-13 13:20:37 -08:00
Aleix Conchillo Flaqué
1b7dfe8126 tests: add a new SleepFrame
The new SleepFrame allow us to control when system frames are pushed to the
pipeline.
2025-02-13 13:20:37 -08:00
Aleix Conchillo Flaqué
d1ee851a65 tests: rename some variables to make things clearer 2025-02-13 13:20:37 -08:00
Filipi da Silva Fuchter
0358673b46 Merge pull request #1215 from pipecat-ai/instant_voice_demo
Instant voice demo improvements - part 02
2025-02-13 18:14:15 -03:00
Filipi Fuchter
16fe1b10e9 - Added support for the RTVIProcessor to handle buffered audio in base64 format, converting it into InputAudioRawFrame for transport.
- Added support for the `RTVIProcessor` to trigger `start_audio_in_streaming` only after the `client-ready` message.
2025-02-13 18:08:55 -03:00
Filipi Fuchter
f001819df8 - Added a new audio_in_stream_on_start field to TransportParams.
- Added a new method `start_audio_in_streaming` in the `BaseInputTransport`.
- Updated `DailyTransport` to respect the `audio_in_stream_on_start` field, ensuring it only starts receiving the audio input if it is enabled.
2025-02-13 18:08:36 -03:00
Filipi Fuchter
dceec60186 Updated FastAPIWebsocketOutputTransport to send TransportMessageFrame and TransportMessageUrgentFrame to the serializer. 2025-02-13 18:07:33 -03:00
Filipi Fuchter
b96979a4ed Update WebsocketServer to not wrap the message inside a text frame. 2025-02-13 18:07:04 -03:00
Mark Backman
745c40def4 Merge pull request #1214 from pipecat-ai/mb/stt-mute-tests
Improve STTMuteFilter, add tests
2025-02-13 09:50:43 -05:00
Mark Backman
42ab62716d Merge pull request #1198 from pipecat-ai/mb/more-whisper-params
Add prompt and temperature args to OpenAI and Groq hosted Whisper STT…
2025-02-13 09:16:38 -05:00
Mark Backman
16ba2010aa Refactor process_frame to be more consistent 2025-02-13 09:15:29 -05:00
Mark Backman
ec0ca46617 Fix temperature docstrings to reference optional 2025-02-13 09:04:20 -05:00
Mark Backman
6ff1f526ff Merge pull request #1216 from pipecat-ai/mb/google-cloud-speech
Add the google-cloud-speech package to the google dependency
2025-02-13 07:04:34 -05:00
Mark Backman
84143cc80c self._muted now returns from STT process_audio_frames 2025-02-13 07:00:44 -05:00
Mark Backman
229dccedc6 Add the google-cloud-speech package to the google dependency 2025-02-12 23:19:17 -05:00
Aleix Conchillo Flaqué
68aaa1f8f4 Merge pull request #1213 from pipecat-ai/aleix/base-transport-output-bot-vad-stop-secs
BaseOutputTransport: use specific VAD stop secs for the bot
2025-02-12 19:01:56 -08:00
Aleix Conchillo Flaqué
f110a45c85 BaseOutputTransport: use specific VAD stop secs for the bot 2025-02-12 19:01:39 -08:00
Mark Backman
1e8a86de63 Handle starting muted, add tests 2025-02-12 19:01:49 -05:00
Mark Backman
ee93e2a2b1 Reorder frame pushing for STTMuteFilter, update STTMuteFrame to SystemFrame 2025-02-12 15:51:18 -05:00
Mark Backman
2e87a019a8 Merge pull request #1208 from pipecat-ai/mb/stt-mute-first-bot-speech
Add new STTMuteStrategy: MUTE_UNTIL_FIRST_BOT_COMPLETE
2025-02-12 12:21:02 -05:00
Vaibhav159
687b3d9d4c fixing google llm service error 2025-02-12 22:22:04 +05:30
Mark Backman
397768d872 Add new STTMuteStrategy: MUTE_UNTIL_FIRST_BOT_COMPLETE 2025-02-12 10:59:28 -05:00
Mark Backman
24cdcd74e6 Merge pull request #1197 from pipecat-ai/mb/google-stt
Add GoogleSTTService
2025-02-12 10:16:18 -05:00
Mark Backman
5d6370690c Add _reconnect_if_needed to simplify reconnect logic 2025-02-12 10:11:18 -05:00
Mark Backman
9f728aa623 Add reconnect logic to handle Google's 5 min time limit 2025-02-12 10:11:18 -05:00
Mark Backman
32d8f6153f Update InputParams to languages: support str or List of Languages 2025-02-12 10:11:18 -05:00
Mark Backman
8c2071f248 Add ClientOptions for region selection 2025-02-12 10:11:18 -05:00
Mark Backman
a9c2197dc6 Add ability to update options 2025-02-12 10:11:18 -05:00
Mark Backman
ce0358804b Docstrings and cleanup 2025-02-12 10:11:18 -05:00
Mark Backman
66a6a6a295 Enable interim transcriptions, add VAD events option 2025-02-12 10:11:18 -05:00
Mark Backman
9f1732c390 Update CHANGELOG and README 2025-02-12 10:11:17 -05:00
Mark Backman
b44ddf2456 07n uses all Google services 2025-02-12 10:09:36 -05:00
Mark Backman
17420f4d0c Update language support 2025-02-12 10:09:36 -05:00
Mark Backman
6cb55ec2cb Add GoogleSTTService 2025-02-12 10:09:36 -05:00
Filipi da Silva Fuchter
e2b4554a54 Merge pull request #1129 from pipecat-ai/instant_voice_demo
Pipecat improvements for the instant voice demo
2025-02-12 11:53:40 -03:00
Mark Backman
fd68b82e48 Merge pull request #1163 from pipecat-ai/mb/rime-websocket
Add RimeTTSService
2025-02-12 09:51:56 -05:00
Filipi Fuchter
cc90f5ab9f Sending the RTVI messages to the websocket 2025-02-12 11:46:49 -03:00
Filipi Fuchter
08f40d9179 Adding support to DailyTransport receive raw-audio through appMessage 2025-02-12 11:46:37 -03:00
Aleix Conchillo Flaqué
80e1325621 include codecov.yml 2025-02-11 23:46:19 -08:00
Aleix Conchillo Flaqué
ed76a5bfa5 Merge pull request #1202 from pipecat-ai/aleix/fix-simli-audiolayout-error
simli: fix audio layout error
2025-02-11 22:24:22 -08:00
Mark Backman
69b0d9035f Mark end_time as unused 2025-02-11 17:44:52 -05:00
Mark Backman
dcc63dd648 Use the vendor default for temperature 2025-02-11 14:29:33 -05:00
Aleix Conchillo Flaqué
2d08f42870 Merge pull request #1204 from pipecat-ai/aleix/add-coverage-support
github: add coverage support
2025-02-11 11:09:25 -08:00
Mark Backman
0814c0bc82 Merge pull request #1203 from pipecat-ai/expose-update-remote-participants-on-daily-transport
Expose `update_remote_participants()` from `DailyTransport`
2025-02-11 13:57:08 -05:00
Paul Kompfner
28e233b195 Update CHANGELOG to reflect the addition of update_remote_participants() 2025-02-11 13:23:47 -05:00
Aleix Conchillo Flaqué
6e4d2d6ade examples: fix more dependabot warnings 2025-02-11 10:09:33 -08:00
Aleix Conchillo Flaqué
266135ec54 examples: fix dependabot warnings 2025-02-11 10:07:05 -08:00
Aleix Conchillo Flaqué
d81aa48262 test-requirements: update transformers to 4.48.0 2025-02-11 10:04:21 -08:00
Aleix Conchillo Flaqué
8c7752fbc2 github: add coverage support 2025-02-11 09:58:21 -08:00
Julien Le Bourg
77fb63372a fix: incorrectly changed the base type in my last pull request for L… (#1184)
* fix: incorrectly changed the base type in my last pull request for  LocalAudioTransport

* update examples to use the new LocalTransportParams

* add local device select example
2025-02-11 08:35:57 -08:00
Paul Kompfner
5a8279d3c2 Expose update_remote_participants() from DailyTransport 2025-02-11 11:28:03 -05:00
Aleix Conchillo Flaqué
4db620198a simli: fix audio layout error
Fixes #1201
2025-02-11 07:05:35 -08:00
Mark Backman
d35f4c6b99 Add prompt and temperature args to OpenAI and Groq hosted Whisper STT services 2025-02-10 21:06:37 -05:00
Aleix Conchillo Flaqué
0a990b2aaa Merge pull request #1196 from pipecat-ai/aleix/audio-buffer-processor-continuous-intermittent-stream
AudioBufferProcessor: handle continuous and intermittent user audio
2025-02-10 16:07:12 -08:00
Mark Backman
97586b132d Simplify _calculate_word_times 2025-02-10 18:45:49 -05:00
Mark Backman
8020db350e Update RimeHttpTTSService to use mistv2 model by default 2025-02-10 18:45:48 -05:00
Mark Backman
54f64b8dad Code review feedback 2025-02-10 18:45:08 -05:00
Mark Backman
8f8a3ae7f9 Add RimeTTSService 2025-02-10 18:45:06 -05:00
Mark Backman
344aff5681 Merge pull request #1191 from pipecat-ai/mb/azure-tts-error-handling
Improve AzureTTSService error handling
2025-02-10 18:01:39 -05:00
Mark Backman
0d2e90cff1 Merge pull request #1190 from pipecat-ai/mb/languages-hosted-whisper
Add language support to OpenAI and Groq hosted Whisper
2025-02-10 17:49:38 -05:00
Mark Backman
1a8dd6b713 Improve AzureTTSService error handling 2025-02-10 17:48:55 -05:00
Mark Backman
2dc585aee0 Merge pull request #1185 from pipecat-ai/mb/update-readme-hacking
Add missing pip install -e . step to the README, and clarify steps
2025-02-10 17:45:58 -05:00
Mark Backman
a64fa44811 Merge pull request #1186 from pipecat-ai/mb/whisper-multilingual
Add language support to WhisperSTTService
2025-02-10 17:26:10 -05:00
Aleix Conchillo Flaqué
baeb83484d Merge pull request #1194 from Vaibhav159/vl_fix_elevenlabs_disconnect_issue
fixing disconnect issue
2025-02-10 13:41:59 -08:00
Vaibhav159
b0c3f80963 resolve merge conf 2025-02-11 03:03:32 +05:30
Aleix Conchillo Flaqué
eb3c9b1e75 AudioBufferProcessor: handle continuous and intermittent user audio
Fixes #1172
2025-02-10 11:26:31 -08:00
Mark Backman
ad4cbdb1ec Merge pull request #1159 from Canonical-AI-Inc/gemini-rag
Gemini 2.0 Flash Lite RAG example
2025-02-10 13:42:11 -05:00
Aleix Conchillo Flaqué
32baee924b RTVI: fix premature bot-tts-text messages (#1193) 2025-02-10 10:37:54 -08:00
Adrian Cowham
9cc53509d1 PR feedback: renamed file, added docstring, changed file read logic 2025-02-10 09:39:01 -08:00
Vaibhav159
2c62d3bf32 break once ConnectionClosed error 2025-02-10 23:04:05 +05:30
Vaibhav159
b06b16adb7 fixing disconnect issue 2025-02-10 22:55:20 +05:30
Mark Backman
cd52d73027 Add language support to OpenAI and Groq hosted Whisper 2025-02-10 10:18:00 -05:00
Mark Backman
c9d8c572c7 Add language support to WhisperSTTService 2025-02-09 10:51:23 -05:00
Mark Backman
d9439fd398 Add missing pip install -e . step to the README, and clarify steps 2025-02-09 09:15:10 -05:00
Mark Backman
081abcedb3 Merge pull request #1176 from pipecat-ai/mb/stt-mute-deprecate-stt-service
Deprecate stt_service parameter in STTMuteFilter
2025-02-09 08:35:22 -05:00
Mark Backman
1455e24ad1 Add keyword args, collocated warnings import with the deprecation 2025-02-09 08:29:20 -05:00
Mark Backman
4613cf4790 Merge pull request #1181 from pipecat-ai/mb/daily-docstrings
Add docstrings to daily.py
2025-02-09 08:05:59 -05:00
Mark Backman
7aa2e1209d Merge pull request #1177 from pipecat-ai/mb/perplexity
Add PerplexityLLMService
2025-02-09 08:05:46 -05:00
Mark Backman
76daaab6ca Add PerplexityLLMService 2025-02-09 08:00:31 -05:00
Mark Backman
37cfe870cc Merge pull request #1183 from pipecat-ai/mb/add-groq-stt
Add GroqSTTService, BaseWhisperSTTService, and refactor OpenAISTTService
2025-02-09 07:56:35 -05:00
Mark Backman
160167758b Add docstrings to daily.py 2025-02-09 07:53:51 -05:00
Mark Backman
4b634713a5 Merge pull request #1182 from pipecat-ai/mb/28c-optional-db
Update 28c option to output to log line only by default
2025-02-09 07:52:21 -05:00
Mark Backman
72954d5f15 Remove to base_whisper.py 2025-02-09 07:51:30 -05:00
Mark Backman
f2b07271c1 Update GroqLLMService to use llama-3.3-70b-versatile as the default model 2025-02-09 07:51:30 -05:00
Mark Backman
32b9de5f51 Add GroqSTTService, BaseWhisperSTTService, and refactor OpenAISTTService 2025-02-09 07:51:28 -05:00
Mark Backman
71ce8f9bcf Merge pull request #1179 from pipecat-ai/mb/remove-command-dash-badge
Remove CommandDash badge from README
2025-02-09 07:47:32 -05:00
Mark Backman
7d05728e2f Update 28c option to output to log line only by default 2025-02-08 10:00:45 -05:00
Mark Backman
dee5448b57 Merge pull request #1123 from pipecat-ai/cb/sqlite
Add SQLite storage to the Gemini persistent storage example
2025-02-08 09:07:52 -05:00
Mark Backman
d67861925a Merge pull request #1128 from golbin/whisper-api
Add Whisper STT service using OpenAI API
2025-02-08 08:35:26 -05:00
Mark Backman
0180619d44 Merge pull request #1173 from TheCodingLand/local-pyaudio-device-ids
adds configurable device ids for local audio transport
2025-02-08 08:04:00 -05:00
Mark Backman
f07e498612 Remove CommandDash badge from README 2025-02-08 07:59:39 -05:00
TheCodingLand
57964cb929 fix LocalAudioTransport param type 2025-02-08 12:32:20 +01:00
TheCodingLand
6840c77684 apply ruff formatting 2025-02-08 12:03:23 +01:00
Mark Backman
a1b58115ce Deprecate stt_service parameter in STTMuteFilter 2025-02-07 19:24:03 -05:00
chadbailey59
23eb6e3d46 storybot fixes (#1175)
* storybot fixes

* readme cleanup
2025-02-07 13:58:02 -06:00
Mark Backman
74a2c38c6c Merge pull request #1174 from pipecat-ai/mb/bump-google-genai-version
Bump google-genai version to 1.0.0
2025-02-07 14:53:44 -05:00
Mark Backman
90b217fda8 Bump google-genai version to 1.0.0 2025-02-07 14:32:37 -05:00
Aleix Conchillo Flaqué
6855bc0ada Merge pull request #1166 from pipecat-ai/aleix/google-rtvi-observer
rtvi: separate specific google RTVI into a GoogleRTVIObserver
2025-02-08 03:19:02 +08:00
TheCodingLand
a359434307 remove Doc and Annotated imports 2025-02-07 19:42:34 +01:00
TheCodingLand
856c8959c3 enhance doc 2025-02-07 19:38:26 +01:00
TheCodingLand
8da7a42137 adds configurable input and output device ids for local audio 2025-02-07 19:23:18 +01:00
Aleix Conchillo Flaqué
510a0f5ef5 rtvi: deprecate RTVI.observer() 2025-02-07 09:19:43 -08:00
Aleix Conchillo Flaqué
03ac744bcf rtvi: deprecate frame processors 2025-02-07 09:17:29 -08:00
Aleix Conchillo Flaqué
b058461a7d GoogleRTVIObserver: add explicit constructor 2025-02-07 09:15:32 -08:00
Mark Backman
abd9f16b90 Export .rtvi, update new-chatbot example, rename and update foundational 32 2025-02-07 09:15:32 -08:00
Aleix Conchillo Flaqué
d07732f2e8 rtvi: separate specific google RTVI into a GoogleRTVIObserver 2025-02-07 09:15:32 -08:00
Aleix Conchillo Flaqué
4d25582e16 dev-requirements: update pyright and ruff 2025-02-06 21:51:57 -08:00
Aleix Conchillo Flaqué
d4b2160f9c Merge pull request #1161 from pipecat-ai/aleix/prepare-0.0.56
update CHANGELOG for 0.0.56
2025-02-06 13:50:04 -08:00
Aleix Conchillo Flaqué
dd7926aab5 update CHANGELOG for 0.0.56 2025-02-06 13:45:13 -08:00
Aleix Conchillo Flaqué
070bf66980 transports: fix local transports audio cleanup 2025-02-06 13:45:13 -08:00
Aleix Conchillo Flaqué
962fc27dbd Merge pull request #1160 from pipecat-ai/aleix/fix-unit-test-logging
tests: remove logger from tests.utils
2025-02-06 13:26:37 -08:00
Mark Backman
3d4d6132fc Merge pull request #1158 from pipecat-ai/mb/update-22c
Update foundation examples 22b, 22c, and 22d to be ready for function…
2025-02-06 16:25:05 -05:00
Aleix Conchillo Flaqué
a96d9294b7 tests: remove logger from tests.utils 2025-02-06 13:18:28 -08:00
Aleix Conchillo Flaqué
a6e78550d5 Merge pull request #1156 from pipecat-ai/aleix/prefer-optional
prefer Optional over to "| None"
2025-02-06 13:08:48 -08:00
Adrian Cowham
d9f6b7b93c added an example using using Gemini's large context window for RAG 2025-02-06 12:49:29 -08:00
Mark Backman
969de92ad9 Update foundation examples 22b, 22c, and 22d to be ready for function calling 2025-02-06 15:36:16 -05:00
Aleix Conchillo Flaqué
c4dbe92b30 prefer Optional over to "| None" 2025-02-06 11:11:37 -08:00
Aleix Conchillo Flaqué
684764fece Merge pull request #1155 from pipecat-ai/aleix/sentry-fixes-and-example
sentry fixes and example
2025-02-06 11:09:31 -08:00
Aleix Conchillo Flaqué
c4be07693f examples: added sentry-metrics example 2025-02-06 10:46:04 -08:00
Aleix Conchillo Flaqué
c5d5ca8232 SentryMetrics: use transactions and call parent methods 2025-02-06 10:44:38 -08:00
Mark Backman
428e763814 Merge pull request #1149 from pipecat-ai/mb/update-google-default-llm-model
Use gemini-2.0-flash-001 as the default model for GoogleLLMService
2025-02-06 12:41:13 -05:00
Mark Backman
0efa2711ff Merge pull request #1152 from pipecat-ai/mb/docstrings
Add docstrings for PipelineTask and related classes/functions
2025-02-06 12:30:12 -05:00
Mark Backman
4904f52cee Use gemini-2.0-flash-001 as the default model for GoogleLLMService 2025-02-06 12:29:15 -05:00
Aleix Conchillo Flaqué
dbcf14ddb4 Merge pull request #1154 from pipecat-ai/aleix/twilio-telnyx-sample-rates
serializers: don't update twilio/telnyx sample rates
2025-02-06 09:27:42 -08:00
Aleix Conchillo Flaqué
7c13ec10d9 examples: cleanup ElevenLabsTTSService constructor arguments 2025-02-06 09:25:52 -08:00
Aleix Conchillo Flaqué
29b9dccc53 serializers: don't update twilio/telnyx sample rates 2025-02-06 09:25:52 -08:00
Aleix Conchillo Flaqué
e8ce826473 Merge pull request #1151 from pipecat-ai/aleix/base-output-transport-resample
BaseOutputTransport: resample incoming audio if needed
2025-02-06 09:25:07 -08:00
Aleix Conchillo Flaqué
bbb991dfd8 Merge pull request #1153 from pipecat-ai/aleix/base-input-transport-show-vad
BaseInputTransport: show VAD results when interruptions not allowed
2025-02-06 09:24:12 -08:00
Mark Backman
4432e7e4f7 Add docstrings for PipelineTask and related classes/functions 2025-02-06 11:04:54 -05:00
Aleix Conchillo Flaqué
ee9cce64b2 BaseInputTransport: show VAD results when interruptions not allowed 2025-02-06 07:40:03 -08:00
Aleix Conchillo Flaqué
1ae4f0150d BaseOutputTransport: resample incoming audio if needed 2025-02-06 07:37:43 -08:00
Mark Backman
4c77c3ed34 Merge pull request #1148 from pipecat-ai/mb/fix-twilio-serializer
Fix sample rate handling in Twilio and Telnyx serializers
2025-02-06 10:25:13 -05:00
Aleix Conchillo Flaqué
975b97472a Merge pull request #1144 from pipecat-ai/aleix/frame-processor-missing-init-warning
FrameProcessor: add an error about missing super().process_frame(...)
2025-02-06 07:18:35 -08:00
Mark Backman
c8ccf13bc7 fix: Use audio_in_sample_rate to deserialize data for TelnyxFrameSerializer 2025-02-06 09:59:21 -05:00
Mark Backman
ba59736f87 fix: Use audio_in_sample_rate to deserialize data for TwilioFrameSerializer 2025-02-06 09:55:15 -05:00
Jin Kim
5989e1ed16 Merge branch 'main' into whisper-api 2025-02-06 13:14:36 +09:00
Aleix Conchillo Flaqué
bc21a0b817 FrameProcessor: add an error about missing super().process_frame(...) 2025-02-05 18:33:03 -08:00
Aleix Conchillo Flaqué
99d3227ff5 Merge pull request #1126 from pipecat-ai/aleix/prepare-0.0.55
update CHANGELOG for 0.0.55
2025-02-05 11:32:39 -08:00
Aleix Conchillo Flaqué
7730f59635 update CHANGELOG for 0.0.55 2025-02-05 11:30:40 -08:00
Aleix Conchillo Flaqué
ba31546c32 Merge pull request #1139 from pipecat-ai/aleix/task-start-metadata
pipeline task start metadata and unit test improvements
2025-02-05 10:51:51 -08:00
Aleix Conchillo Flaqué
a363d12d1f dev-requirements: fix conflicts because of nvidia-riva-client 2025-02-05 10:34:46 -08:00
Aleix Conchillo Flaqué
feab9c8fa2 tests: run_test() now uses PipelineTask 2025-02-05 10:34:38 -08:00
Aleix Conchillo Flaqué
61f6669926 task: allow passing StartFrame metadata via start_metadata param 2025-02-05 10:34:38 -08:00
Aleix Conchillo Flaqué
3be69908d2 Merge pull request #1131 from pipecat-ai/aleix/global-audio-sample-rates
introduce PipelineParams audio input/output sample rates
2025-02-05 08:11:25 -08:00
Aleix Conchillo Flaqué
fcb80ec330 playht: don't set sample_rate in _settings 2025-02-05 07:46:24 -08:00
Mark Backman
c9f5684e2f OpenAITTSService: Add warning about changing sample_rate 2025-02-05 10:13:46 -05:00
Mark Backman
c257fa1573 AzureTTSService, AzureHttpTTSService: add start() method 2025-02-05 10:05:19 -05:00
Mark Backman
97c55da29f PlayHTHttpTTSService: add start() method to set sample_rate 2025-02-05 09:54:41 -05:00
Aleix Conchillo Flaqué
49426aa9a1 transport(websocket): improve exception logging 2025-02-04 23:50:45 -08:00
Aleix Conchillo Flaqué
0a333c26da services(elevenlabs): warn if sample rate not supported 2025-02-04 23:50:21 -08:00
Aleix Conchillo Flaqué
75a29424ff examples(telnyx-chatbot): use cartesia so we can use 8khz 2025-02-04 23:49:50 -08:00
Filipi da Silva Fuchter
cd1b429308 Merge pull request #1133 from pipecat-ai/fixing_krisp_issue
Fixing the issue in Krisp when trying to create more than one
2025-02-04 20:44:29 -03:00
Filipi Fuchter
7f1ae4b8cc Fixing the issue in Krisp when trying to create more than one filter in the same process. 2025-02-04 20:10:56 -03:00
Aleix Conchillo Flaqué
af9fd811cd examples(moondream-chatbot): fix UserImageRequester 2025-02-04 14:37:53 -08:00
Aleix Conchillo Flaqué
69f5c9b9d3 update anthropic and openpipe versions 2025-02-04 14:37:36 -08:00
Aleix Conchillo Flaqué
ab45e481be introduce PipelineParams audio input/output sample rates 2025-02-04 14:12:56 -08:00
Jin Kim
ef1e4277d3 Add an example for Whisper using OpenAI API 2025-02-04 10:32:55 +09:00
Jin Kim
823b763b25 Change OpenAI example file name 2025-02-04 10:28:06 +09:00
Jin Kim
3cb189eb1f Add whisper STT service using OpenAI API 2025-02-04 10:27:28 +09:00
Aleix Conchillo Flaqué
cc54255c41 Merge pull request #1125 from pipecat-ai/aleix/twilio-chatbot-improvements 2025-02-03 11:10:33 -08:00
Aleix Conchillo Flaqué
1cdb66f889 examples(twilio-chatbot): create sample rate variable 2025-02-03 10:58:06 -08:00
Aleix Conchillo Flaqué
51a86a509c examples: multiple twilio-chatbot improvements 2025-02-03 10:36:24 -08:00
Aleix Conchillo Flaqué
824898f7b7 Merge pull request #1121 from pipecat-ai/aleix/audio-resamplers
introduce audio resamplers
2025-02-03 10:32:55 -08:00
Aleix Conchillo Flaqué
57dadb6359 audio(utils): some variable renames 2025-02-03 09:33:04 -08:00
Aleix Conchillo Flaqué
5dcdc68ef5 examples: fix 22 series initial gate state 2025-02-03 09:16:58 -08:00
Aleix Conchillo Flaqué
aafb2db620 GatedOpenAILLMContextAggregator: use keyword argument and add start_open 2025-02-03 09:16:44 -08:00
Aleix Conchillo Flaqué
f3f22cf61c AudioBufferProcessor: add start_recording()/stop_recording() 2025-02-01 11:06:58 -08:00
Aleix Conchillo Flaqué
371c2f3704 canonical: do not reset audio buffers 2025-02-01 11:06:58 -08:00
Aleix Conchillo Flaqué
1f14f62696 AudioBufferProcessor: fix audio buffer silence computation 2025-02-01 11:06:58 -08:00
Aleix Conchillo Flaqué
06449eff2c BaseAudioResampler: make resample() async 2025-02-01 11:06:58 -08:00
Aleix Conchillo Flaqué
dcfb86583d serializers: serialize()/deserialize() are now async 2025-02-01 11:06:58 -08:00
Aleix Conchillo Flaqué
cda34a1320 AudioBufferProcessor: fix user/bot audio buffers silence padding 2025-02-01 11:06:58 -08:00
Aleix Conchillo Flaqué
13611fd8e1 AudioBufferProcessor: call callback on CancelFrame 2025-02-01 11:06:58 -08:00
Aleix Conchillo Flaqué
fc89aad469 introduce audio resamplers 2025-02-01 11:06:55 -08:00
Aleix Conchillo Flaqué
6c7474e1a2 frames: add pass to DTMFFrames 2025-01-31 18:37:40 -08:00
Aleix Conchillo Flaqué
95f0dbf3f3 CHANGELOG.md: task.cancel() and EndFrame clarification 2025-01-31 18:35:35 -08:00
Aleix Conchillo Flaqué
11aeb68ddb frames: fix type s/OuputDTMFFrame/OutputDTMFFrame/ 2025-01-31 18:28:38 -08:00
Aleix Conchillo Flaqué
a43c102fc8 Merge pull request #1064 from jcbjoe/jg/additional_dtmf_frames
Added: Additional DTMF frames
2025-01-31 18:25:08 -08:00
Chad Bailey
d236973c0f moved sqlite code back to a single example 2025-01-31 23:18:06 +00:00
Mark Backman
16b49bdce6 Merge pull request #1122 from pipecat-ai/mb/openai-org-id
Add organization and project level auth in OpenAILLMService
2025-01-31 14:35:26 -05:00
Mark Backman
41477c8f78 Add organization and project level auth in OpenAILLMService 2025-01-31 14:27:25 -05:00
Filipi Fuchter
7e3e126730 Migrating the base API URL for the react native example to an .env file. 2025-01-30 10:42:16 -03:00
Filipi Fuchter
75ca0571bb Improving the layout from the bot ready react native demo. 2025-01-30 10:31:04 -03:00
Filipi Fuchter
a48e5d0714 Only sending the message when it is a remote audio track. 2025-01-30 10:14:37 -03:00
Filipi Fuchter
2b6a992207 Sending the app-message to start playing audio once the track has started. 2025-01-30 09:37:33 -03:00
Filipi Fuchter
24cf106ed2 Refactoring the code to ask for the room that it should connect. 2025-01-30 09:14:18 -03:00
Filipi Fuchter
95c8346cb5 Starting to create a react native client for the bot ready example. 2025-01-29 19:00:42 -03:00
Chad Bailey
bc98c2e36c added sqlite storage example 2025-01-29 19:12:15 +00:00
Joe Garlick
b72504f1cb Added: Additional DTMF frames 2025-01-22 13:47:23 +00:00
221 changed files with 25469 additions and 2415 deletions

54
.github/workflows/coverage.yaml vendored Normal file
View File

@@ -0,0 +1,54 @@
name: coverage
on:
workflow_dispatch:
push:
branches:
- main
pull_request:
branches:
- "**"
paths-ignore:
- "docs/**"
jobs:
coverage:
name: "Coverage"
runs-on: ubuntu-latest
steps:
- name: Checkout repo
uses: actions/checkout@v4
- name: Set up Python
id: setup_python
uses: actions/setup-python@v4
with:
python-version: "3.10"
- name: Cache virtual environment
uses: actions/cache@v3
with:
# We are hashing dev-requirements.txt and test-requirements.txt which
# contain all dependencies needed to run the tests.
key: venv-${{ runner.os }}-${{ steps.setup_python.outputs.python-version}}-${{ hashFiles('dev-requirements.txt') }}-${{ hashFiles('test-requirements.txt') }}
path: .venv
- name: Install system packages
id: install_system_packages
run: |
sudo apt-get install -y portaudio19-dev
- name: Setup virtual environment
run: |
python -m venv .venv
- name: Install basic Python dependencies
run: |
source .venv/bin/activate
python -m pip install --upgrade pip
pip install -r dev-requirements.txt -r test-requirements.txt
- name: Run tests with coverage
run: |
source .venv/bin/activate
coverage run
coverage xml
- name: Upload coverage to Codecov
uses: codecov/codecov-action@v5
with:
token: ${{ secrets.CODECOV_TOKEN }}
slug: pipecat-ai/pipecat

15
.gitignore vendored
View File

@@ -32,6 +32,21 @@ fly.toml
# Example files
pipecat/examples/twilio-chatbot/templates/streams.xml
pipecat/examples/bot-ready-signalling/client/react-native/node_modules/
pipecat/examples/bot-ready-signalling/client/react-native/.expo/
pipecat/examples/bot-ready-signalling/client/react-native/dist/
pipecat/examples/bot-ready-signalling/client/react-native/npm-debug.*
pipecat/examples/bot-ready-signalling/client/react-native/*.jks
pipecat/examples/bot-ready-signalling/client/react-native/*.p8
pipecat/examples/bot-ready-signalling/client/react-native/*.p12
pipecat/examples/bot-ready-signalling/client/react-native/*.key
pipecat/examples/bot-ready-signalling/client/react-native/*.mobileprovision
pipecat/examples/bot-ready-signalling/client/react-native/*.orig.*
pipecat/examples/bot-ready-signalling/client/react-native/web-build/
# macOS
.DS_Store
# Documentation
docs/api/_build/

View File

@@ -5,10 +5,255 @@ All notable changes to **Pipecat** will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
## [Unreleased]
## Unreleased
### Added
- Added `room_url` property to `DailyTransport`.
- Added `addons` argument to `DeepgramSTTService`.
- Added `exponential_backoff_time()` to `utils.network` module.
### Changed
- `RimeHttpTTSService` needs an `aiohttp.ClientSession` to be passed to the
constructor as all the other HTTP-based services.
- `RimeHttpTTSService` doesn't use a default voice anymore.
- `DeepgramSTTService` now uses the new `nova-3` model by default. If you want
to use the previous model you can pass `LiveOptions(model="nova-2-general")`.
(see https://deepgram.com/learn/introducing-nova-3-speech-to-text-api)
```python
stt = DeepgramSTTService(..., live_options=LiveOptions(model="nova-2-general"))
```
### Fixed
- Fixed a context aggregator issue that would not append the LLM text response
to the context if a function call happened in the same LLM turn.
- Fixed an issue that was causing HTTP TTS services to push `TTSStoppedFrame`
more than once.
- Fixed a `FishAudioTTSService` issue where `TTSStoppedFrame` was not being
pushed.
- Fixed an issue that `start_callback` was not invoked for some LLM services.
- Fixed an issue that would cause `DeepgramSTTService` to stop working after an
error occurred (e.g. sudden network loss). If the network recovered we would
not reconnect.
- Fixed a `STTMuteFilter` issue that would not mute user audio frames causing
transcriptions to be generated by the STT service.
### Other
- Added Gemini support to `examples/phone-chatbot`.
## [0.0.57] - 2025-02-14
### Added
- Added new `AudioContextWordTTSService`. This is a TTS base class for TTS
services that handling multiple separate audio requests.
- Added new frames `EmulateUserStartedSpeakingFrame` and
`EmulateUserStoppedSpeakingFrame` which can be used to emulated VAD behavior
without VAD being present or not being triggered.
- Added a new `audio_in_stream_on_start` field to `TransportParams`.
- Added a new method `start_audio_in_streaming` in the `BaseInputTransport`.
- This method should be used to start receiving the input audio in case the
field `audio_in_stream_on_start` is set to `false`.
- Added support for the `RTVIProcessor` to handle buffered audio in `base64`
format, converting it into InputAudioRawFrame for transport.
- Added support for the `RTVIProcessor` to trigger `start_audio_in_streaming`
only after the `client-ready` message.
- Added new `MUTE_UNTIL_FIRST_BOT_COMPLETE` strategy to `STTMuteStrategy`. This
strategy starts muted and remains muted until the first bot speech completes,
ensuring the bot's first response cannot be interrupted. This complements the
existing `FIRST_SPEECH` strategy which only mutes during the first detected
bot speech.
- Added support for Google Cloud Speech-to-Text V2 through `GoogleSTTService`.
- Added `RimeTTSService`, a new `WordTTSService`. Updated the foundational
example `07q-interruptible-rime.py` to use `RimeTTSService`.
- Added support for Groq's Whisper API through the new `GroqSTTService` and
OpenAI's Whisper API through the new `OpenAISTTService`. Introduced a new
base class `BaseWhisperSTTService` to handle common Whisper API
functionality.
- Added `PerplexityLLMService` for Perplexity NIM API integration, with an
OpenAI-compatible interface. Also, added foundational example
`14n-function-calling-perplexity.py`.
- Added `DailyTransport.update_remote_participants()`. This allows you to update
remote participant's settings, like their permissions or which of their
devices are enabled. Requires that the local participant have participant
admin permission.
### Changed
- We don't consider a colon `:` and end of sentence any more.
- Updated `DailyTransport` to respect the `audio_in_stream_on_start` field,
ensuring it only starts receiving the audio input if it is enabled.
- Updated `FastAPIWebsocketOutputTransport` to send `TransportMessageFrame` and
`TransportMessageUrgentFrame` to the serializer.
- Updated `WebsocketServerOutputTransport` to send `TransportMessageFrame` and
`TransportMessageUrgentFrame` to the serializer.
- Enhanced `STTMuteConfig` to validate strategy combinations, preventing
`MUTE_UNTIL_FIRST_BOT_COMPLETE` and `FIRST_SPEECH` from being used together
as they handle first bot speech differently.
- Updated foundational example `07n-interruptible-google.py` to use all Google
services.
- `RimeHttpTTSService` now uses the `mistv2` model by default.
- Improved error handling in `AzureTTSService` to properly detect and log
synthesis cancellation errors.
- Enhanced `WhisperSTTService` with full language support and improved model
documentation.
- Updated foundation example `14f-function-calling-groq.py` to use
`GroqSTTService` for transcription.
- Updated `GroqLLMService` to use `llama-3.3-70b-versatile` as the default
model.
- `RTVIObserver` doesn't handle `LLMSearchResponseFrame` frames anymore. For
now, to handle those frames you need to create a `GoogleRTVIObserver`
instead.
### Deprecated
- `STTMuteFilter` constructor's `stt_service` parameter is now deprecated and
will be removed in a future version. The filter now manages mute state
internally instead of querying the STT service.
- `RTVI.observer()` is now deprecated, instantiate an `RTVIObserver` directly
instead.
- All RTVI frame processors (e.g. `RTVISpeakingProcessor`,
`RTVIBotLLMProcessor`) are now deprecated, instantiate an `RTVIObserver`
instead.
### Fixed
- Fixed a `FalImageGenService` issue that was causing the event loop to be
blocked while loading the downloadded image.
- Fixed a `CartesiaTTSService` service issue that would cause audio overlapping
in some cases.
- Fixed a websocket-based service issue (e.g. `CartesiaTTSService`) that was
preventing a reconnection after the server disconnected cleanly, which was
causing an inifite loop instead.
- Fixed a `BaseOutputTransport` issue that was causing upstream frames to no be
pushed upstream.
- Fixed multiple issue where user transcriptions where not being handled
properly. It was possible for short utterances to not trigger VAD which would
cause user transcriptions to be ignored. It was also possible for one or more
transcriptions to be generated after VAD in which case they would also be
ignored.
- Fixed an issue that was causing `BotStoppedSpeakingFrame` to be generated too
late. This could then cause issues unblocking `STTMuteFilter` later than
desired.
- Fixed an issue that was causing `AudioBufferProcessor` to not record
synchronized audio.
- Fixed an `RTVI` issue that was causing `bot-tts-text` messages to be sent
before being processed by the output transport.
- Fixed an issue[#1192] in 11labs where we are trying to reconnect/disconnect
the websocket connection even when the connection is already closed.
- Fixed an issue where `has_regular_messages` condition was always true in
`GoogleLLMContext` due to `Part` having `function_call` & `function_response`
with `None` values.
### Other
- Added new `instant-voice` example. This example showcases how to enable
instant voice communication as soon as a user connects.
- Added new `local-input-select-stt` example. This examples allows you to play
with local audio inputs by slecting them through a nice text interface.
## [0.0.56] - 2025-02-06
### Changed
- Use `gemini-2.0-flash-001` as the default model for `GoogleLLMSerivce`.
- Improved foundational examples 22b, 22c, and 22d to support function calling.
With these base examples, `FunctionCallInProgressFrame` and
`FunctionCallResultFrame` will no longer be blocked by the gates.
### Fixed
- Fixed a `TkLocalTransport` and `LocalAudioTransport` issues that was causing
errors on cleanup.
- Fixed an issue that was causing `tests.utils` import to fail because of
logging setup.
- Fixed a `SentryMetrics` issue that was preventing any metrics to be sent to
Sentry and also was preventing from metrics frames to be pushed to the
pipeline.
- Fixed an issue in `BaseOutputTransport` where incoming audio would not be
resampled to the desired output sample rate.
- Fixed an issue with the `TwilioFrameSerializer` and `TelnyxFrameSerializer`
where `twilio_sample_rate` and `telnyx_sample_rate` were incorrectly
initialized to `audio_in_sample_rate`. Those values currently default to 8000
and should be set manually from the serializer constructor if a different
value is needed.
### Other
- Added a new `sentry-metrics` example.
## [0.0.55] - 2025-02-05
### Added
- Added a new `start_metadata` field to `PipelineParams`. The provided metadata
will be set to the initial `StartFrame` being pushed from the `PipelineTask`.
- Added new fields to `PipelineParams` to control audio input and output sample
rates for the whole pipeline. This allows controlling sample rates from a
single place instead of having to specify sample rates in each
service. Setting a sample rate to a service is still possible and will
override the value from `PipelineParams`.
- Introduce audio resamplers (`BaseAudioResampler`). This is just a base class
to implement audio resamplers. Currently, two implementations are provided
`SOXRAudioResampler` and `ResampyResampler`. A new
`create_default_resampler()` has been added (replacing the now deprecated
`resample_audio()`).
- It is now possible to specify the asyncio event loop that a `PipelineTask` and
all the processors should run on by passing it as a new argument to the
`PipelineRunner`. This could allow running pipelines in multiple threads each
@@ -41,6 +286,12 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
### Changed
- `GatedOpenAILLMContextAggregator` now require keyword arguments. Also, a new
`start_open` argument has been added to set the initial state of the gate.
- Added `organization` and `project` level authentication to
`OpenAILLMService`.
- Improved the language checking logic in `ElevenLabsTTSService` and
`ElevenLabsHttpTTSService` to properly handle language codes based on model
compatibility, with appropriate warnings when language codes cannot be
@@ -50,8 +301,30 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
contain a combination of function calls, function call responses, system
messages, or just messages.
- `InputDTMFFrame` is now based on `DTMFFrame`. There's also a new
`OutputDTMFFrame` frame.
### Deprecated
- `resample_audio()` is now deprecated, use `create_default_resampler()`
instead.
### Removed
- `AudioBufferProcessor.reset_audio_buffers()` has been removed, use
`AudioBufferProcessor.start_recording()` and
`AudioBufferProcessor.stop_recording()` instead.
### Fixed
- Fixed a `AudioBufferProcessor` that would cause crackling in some recordings.
- Fixed an issue in `AudioBufferProcessor` where user callback would not be
called on task cancellation.
- Fixed an issue in `AudioBufferProcessor` that would cause wrong silence
padding in some cases.
- Fixed an issue where `ElevenLabsTTSService` messages would return a 1009
websocket error by increasing the max message size limit to 16MB.
@@ -67,11 +340,22 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
### Other
- Updated all examples to use `task.cancel()` instead of pushing an `EndFrame`
when a participant leaves/disconnects. If you push an `EndFrame` this will
cause the bot to run through everything that is internally queued (which could
take seconds). Instead, if a participant disconnects there is nothing else to
be sent and therefore we should stop immediately.
- Improved Unit Test `run_test()` to use `PipelineTask` and
`PipelineRunner`. There's now also some control around `StartFrame` and
`EndFrame`. The `EndTaskFrame` has been removed since it doesn't seem
necessary with this new approach.
- Updated `twilio-chatbot` with a few new features: use 8000 sample rate and
avoid resampling, a new client useful for stress testing and testing locally
without the need to make phone calls. Also, added audio recording on both the
client and the server to make sure the audio sounds good.
- Updated examples to use `task.cancel()` to immediately exit the example when a
participant leaves or disconnects, instead of pushing an `EndFrame`. Pushing
an `EndFrame` causes the bot to run through everything that is internally
queued (which could take some seconds). Note that using `task.cancel()` might
not always be the best option and pushing an `EndFrame` could still be
desirable to make sure all the pipeline is flushed.
## [0.0.54] - 2025-01-27
@@ -95,7 +379,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
- Added `enable_recording` and `geo` parameters to `DailyRoomProperties`.
- Added `RecordingsBucketConfig` to `DailyRoomProperties` to upload recordings to a custom AWS bucket.
- Added `RecordingsBucketConfig` to `DailyRoomProperties` to upload recordings
to a custom AWS bucket.
### Changed
@@ -1520,6 +1805,9 @@ async def on_connected(processor):
### Changed
- `FrameSerializer.serialize()` and `FrameSerializer.deserialize()` are now
`async`.
- `Filter` has been renamed to `FrameFilter` and it's now under
`processors/filters`.

View File

@@ -2,7 +2,7 @@
 <img alt="pipecat" width="300px" height="auto" src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/pipecat.png">
</div></h1>
[![PyPI](https://img.shields.io/pypi/v/pipecat-ai)](https://pypi.org/project/pipecat-ai) ![Tests](https://github.com/pipecat-ai/pipecat/actions/workflows/tests.yaml/badge.svg) [![Docs](https://img.shields.io/badge/Documentation-blue)](https://docs.pipecat.ai) [![Discord](https://img.shields.io/discord/1239284677165056021)](https://discord.gg/pipecat) <a href="https://app.commanddash.io/agent/github_pipecat-ai_pipecat"><img src="https://img.shields.io/badge/AI-Code%20Agent-EB9FDA"></a>
[![PyPI](https://img.shields.io/pypi/v/pipecat-ai)](https://pypi.org/project/pipecat-ai) ![Tests](https://github.com/pipecat-ai/pipecat/actions/workflows/tests.yaml/badge.svg) [![codecov](https://codecov.io/gh/pipecat-ai/pipecat/graph/badge.svg?token=LNVUIVO4Y9)](https://codecov.io/gh/pipecat-ai/pipecat) [![Docs](https://img.shields.io/badge/Documentation-blue)](https://docs.pipecat.ai) [![Discord](https://img.shields.io/discord/1239284677165056021)](https://discord.gg/pipecat)
Pipecat is an open source Python framework for building voice and multimodal conversational agents. It handles the complex orchestration of AI services, network transport, audio processing, and multimodal interactions, letting you focus on creating engaging experiences.
@@ -55,17 +55,17 @@ pip install "pipecat-ai[option,...]"
### Available services
| Category | Services | Install Command Example |
| ------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------- |
| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) | `pip install "pipecat-ai[deepgram]"` |
| LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [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), [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), [Together AI](https://docs.pipecat.ai/server/services/llm/together) | `pip install "pipecat-ai[openai]"` |
| Text-to-Speech | [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), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) | `pip install "pipecat-ai[cartesia]"` |
| Speech-to-Speech | [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai) | `pip install "pipecat-ai[openai]"` |
| Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local | `pip install "pipecat-ai[daily]"` |
| Video | [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) | `pip install "pipecat-ai[tavus,simli]"` |
| Vision & Image | [Moondream](https://docs.pipecat.ai/server/services/vision/moondream), [fal](https://docs.pipecat.ai/server/services/image-generation/fal) | `pip install "pipecat-ai[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), [Noisereduce](https://docs.pipecat.ai/server/utilities/audio/noisereduce-filter) | `pip install "pipecat-ai[silero]"` |
| Analytics & Metrics | [Canonical AI](https://docs.pipecat.ai/server/services/analytics/canonical), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) | `pip install "pipecat-ai[canonical]"` |
| Category | Services | Install Command Example |
| ------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------- |
| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [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), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) | `pip install "pipecat-ai[deepgram]"` |
| LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [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), [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), [Together AI](https://docs.pipecat.ai/server/services/llm/together) | `pip install "pipecat-ai[openai]"` |
| Text-to-Speech | [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), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) | `pip install "pipecat-ai[cartesia]"` |
| Speech-to-Speech | [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai) | `pip install "pipecat-ai[google]"` |
| Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local | `pip install "pipecat-ai[daily]"` |
| Video | [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) | `pip install "pipecat-ai[tavus,simli]"` |
| Vision & Image | [Moondream](https://docs.pipecat.ai/server/services/vision/moondream), [fal](https://docs.pipecat.ai/server/services/image-generation/fal) | `pip install "pipecat-ai[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), [Noisereduce](https://docs.pipecat.ai/server/utilities/audio/noisereduce-filter) | `pip install "pipecat-ai[silero]"` |
| Analytics & Metrics | [Canonical AI](https://docs.pipecat.ai/server/services/analytics/canonical), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) | `pip install "pipecat-ai[canonical]"` |
📚 [View full services documentation →](https://docs.pipecat.ai/server/services/supported-services)
@@ -149,36 +149,40 @@ Sign up [here](https://dashboard.daily.co/u/signup) and [create a room](https://
## Hacking on the framework itself
_Note that you may need to set up a virtual environment before following the instructions below. For instance, you might need to run the following from the root of the repo:_
_Note: You may need to set up a virtual environment before following these instructions. From the root of the repo:_
```shell
python3 -m venv venv
source venv/bin/activate
```
From the root of this repo, run the following:
Install the development dependencies:
```shell
pip install -r dev-requirements.txt
```
This will install the necessary development dependencies. Also, make sure you install the git pre-commit hooks:
Install the git pre-commit hooks (these help ensure your code follows project rules):
```shell
pre-commit install
```
The hooks will just save you time when you submit a PR by making sure your code follows the project rules.
To use the package locally (e.g. to run sample files), run:
Install the `pipecat-ai` package locally in editable mode:
```shell
pip install --editable ".[option,...]"
pip install -e .
```
The `--editable` option makes sure you don't have to run `pip install` again and you can just edit the project files locally.
The `-e` or `--editable` option allows you to modify the code without reinstalling.
If you want to use this package from another directory, you can run:
To include optional dependencies, add them to the install command. For example:
```shell
pip install -e ".[daily,deepgram,cartesia,openai,silero]" # Updated for the services you're using
```
If you want to use this package from another directory:
```shell
pip install "path_to_this_repo[option,...]"

11
codecov.yml Normal file
View File

@@ -0,0 +1,11 @@
coverage:
range: 50..90 # coverage lower than 50 is red, higher than 90 green, between color code
status:
project:
default:
target: auto # auto % coverage target
threshold: 5% # allow for 5% reduction of coverage without failing
# do not run coverage on patch nor changes
patch: false

View File

@@ -1,11 +1,12 @@
build~=1.2.2
grpcio-tools~=1.69.0
coverage~=7.6.12
grpcio-tools~=1.67.1
pip-tools~=7.4.1
pre-commit~=4.0.1
pyright~=1.1.392
pyright~=1.1.393
pytest~=8.3.4
pytest-asyncio~=0.25.2
ruff~=0.9.1
setuptools~=75.8.0
ruff~=0.9.5
setuptools~=70.0.0
setuptools_scm~=8.1.0
python-dotenv~=1.0.1

View File

@@ -12,7 +12,7 @@
"@daily-co/daily-js": "0.74.0"
},
"devDependencies": {
"vite": "^6.0.2"
"vite": "^6.0.9"
}
},
"node_modules/@babel/runtime": {
@@ -1007,15 +1007,14 @@
}
},
"node_modules/vite": {
"version": "6.0.7",
"resolved": "https://registry.npmjs.org/vite/-/vite-6.0.7.tgz",
"integrity": "sha512-RDt8r/7qx9940f8FcOIAH9PTViRrghKaK2K1jY3RaAURrEUbm9Du1mJ72G+jlhtG3WwodnfzY8ORQZbBavZEAQ==",
"version": "6.1.0",
"resolved": "https://registry.npmjs.org/vite/-/vite-6.1.0.tgz",
"integrity": "sha512-RjjMipCKVoR4hVfPY6GQTgveinjNuyLw+qruksLDvA5ktI1150VmcMBKmQaEWJhg/j6Uaf6dNCNA0AfdzUb/hQ==",
"dev": true,
"license": "MIT",
"dependencies": {
"esbuild": "^0.24.2",
"postcss": "^8.4.49",
"rollup": "^4.23.0"
"postcss": "^8.5.1",
"rollup": "^4.30.1"
},
"bin": {
"vite": "bin/vite.js"

View File

@@ -12,7 +12,7 @@
"license": "ISC",
"description": "",
"devDependencies": {
"vite": "^6.0.2"
"vite": "^6.0.9"
},
"dependencies": {
"@daily-co/daily-js": "0.74.0"

View File

@@ -0,0 +1 @@
22.14

View File

@@ -0,0 +1,60 @@
# React Native Implementation
Basic implementation using the [Pipecat React Native SDK](https://docs.pipecat.ai/client/react-native/introduction).
## Usage
### Expo requirements
This project cannot be used with an [Expo Go](https://docs.expo.dev/workflow/expo-go/) app because [it requires custom native code](https://docs.expo.io/workflow/customizing/).
When a project requires custom native code or a config plugin, we need to transition from using [Expo Go](https://docs.expo.dev/workflow/expo-go/)
to a [development build](https://docs.expo.dev/development/introduction/).
More details about the custom native code used by this demo can be found in [rn-daily-js-expo-config-plugin](https://github.com/daily-co/rn-daily-js-expo-config-plugin).
### Building remotely
If you do not have experience with Xcode and Android Studio builds or do not have them installed locally on your computer, you will need to follow [this guide from Expo to use EAS Build](https://docs.expo.dev/development/create-development-builds/#create-and-install-eas-build).
### Building locally
You will need to have installed locally on your computer:
- [Xcode](https://developer.apple.com/xcode/) to build for iOS;
- [Android Studio](https://developer.android.com/studio) to build for Android;
#### Install the demo dependencies
```bash
# Use the version of node specified in .nvmrc
nvm i
# Install dependencies
npm i
# Before a native app can be compiled, the native source code must be generated.
npx expo prebuild
# Configure the environment variable to connect to the local server
cp env.example .env
# edit .env and add your local ip address, for example: http://192.168.1.16:7860
```
#### Running on Android
After plugging in an Android device [configured for debugging](https://developer.android.com/studio/debug/dev-options), run the following command:
```
npm run android
```
#### Running on iOS
Run the following command:
```
npm run ios
```
#### Connect to the server
Use the http://localhost:5173 in your app.

View File

@@ -0,0 +1,75 @@
{
"expo": {
"name": "bot-ready-rn",
"slug": "bot-ready-rn",
"version": "1.0.0",
"orientation": "portrait",
"icon": "./assets/icon.png",
"userInterfaceStyle": "light",
"splash": {
"image": "./assets/splash.png",
"resizeMode": "contain",
"backgroundColor": "#ffffff"
},
"updates": {
"fallbackToCacheTimeout": 0
},
"assetBundlePatterns": [
"**/*"
],
"ios": {
"supportsTablet": true,
"bitcode": false,
"bundleIdentifier": "co.daily.expo.BotReady",
"infoPlist": {
"UIBackgroundModes": [
"voip"
]
},
"appleTeamId": "EEBGKV9N3N"
},
"android": {
"adaptiveIcon": {
"foregroundImage": "./assets/adaptive-icon.png",
"backgroundColor": "#FFFFFF"
},
"package": "co.daily.expo.BotReady",
"permissions": [
"android.permission.ACCESS_NETWORK_STATE",
"android.permission.BLUETOOTH",
"android.permission.CAMERA",
"android.permission.INTERNET",
"android.permission.MODIFY_AUDIO_SETTINGS",
"android.permission.RECORD_AUDIO",
"android.permission.SYSTEM_ALERT_WINDOW",
"android.permission.WAKE_LOCK",
"android.permission.FOREGROUND_SERVICE",
"android.permission.FOREGROUND_SERVICE_CAMERA",
"android.permission.FOREGROUND_SERVICE_MICROPHONE",
"android.permission.FOREGROUND_SERVICE_MEDIA_PROJECTION",
"android.permission.POST_NOTIFICATIONS"
]
},
"web": {
"favicon": "./assets/favicon.png"
},
"plugins": [
"@config-plugins/react-native-webrtc",
"@daily-co/config-plugin-rn-daily-js",
[
"expo-build-properties",
{
"android": {
"minSdkVersion": 24,
"compileSdkVersion": 35,
"targetSdkVersion": 34,
"buildToolsVersion": "35.0.0"
},
"ios": {
"deploymentTarget": "15.1"
}
}
]
]
}
}

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@@ -0,0 +1,7 @@
module.exports = function(api) {
api.cache(true);
return {
presets: ['babel-preset-expo'],
plugins: [["module:react-native-dotenv"]],
};
};

View File

@@ -0,0 +1 @@
API_BASE_URL=http://YOUR_LOCAL_IP:7860

View File

@@ -0,0 +1,7 @@
import { registerRootComponent } from "expo";
import App from "./src/App";
// registerRootComponent calls AppRegistry.registerComponent('main', () => App);
// It also ensures that the environment is set up appropriately
registerRootComponent(App);

View File

@@ -0,0 +1,4 @@
// Learn more https://docs.expo.io/guides/customizing-metro
const { getDefaultConfig } = require('expo/metro-config');
module.exports = getDefaultConfig(__dirname);

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View File

@@ -0,0 +1,31 @@
{
"name": "bot-ready-rn",
"version": "1.0.0",
"scripts": {
"start": "expo start --dev-client",
"android": "expo run:android --device",
"ios": "expo run:ios --device",
"web": "expo start --web"
},
"dependencies": {
"@config-plugins/react-native-webrtc": "^10.0.0",
"@daily-co/config-plugin-rn-daily-js": "0.0.7",
"@daily-co/react-native-daily-js": "^0.70.0",
"@daily-co/react-native-webrtc": "^118.0.3-daily.2",
"@react-native-async-storage/async-storage": "1.23.1",
"expo": "^52.0.0",
"expo-build-properties": "~0.13.1",
"expo-dev-client": "~5.0.5",
"expo-splash-screen": "~0.29.16",
"expo-status-bar": "~2.0.0",
"react": "18.3.1",
"react-native": "0.76.3",
"react-native-background-timer": "^2.4.1",
"react-native-dotenv": "^3.4.11",
"react-native-get-random-values": "^1.11.0"
},
"devDependencies": {
"@babel/core": "^7.12.9"
},
"private": true
}

View File

@@ -0,0 +1,121 @@
import React, { useState, useEffect } from 'react';
import {SafeAreaView, View, Text, Button, StyleSheet, ScrollView} from 'react-native';
import Daily from "@daily-co/react-native-daily-js";
import { API_BASE_URL } from "@env";
const CallScreen = () => {
const [connectionStatus, setConnectionStatus] = useState('Disconnected');
const [isConnected, setIsConnected] = useState(false);
const [callObject, setCallObject] = useState(null);
const [logs, setLogs] = useState([]);
useEffect(() => {
if (callObject) {
setupTrackListeners(callObject);
}
}, [callObject]);
const log = (message) => {
setLogs((prevLogs) => [...prevLogs, `${new Date().toISOString()} - ${message}`]);
console.log(message);
};
const setupTrackListeners = (callObject) => {
callObject.on("joined-meeting", () => {
setConnectionStatus('Connected');
setIsConnected(true);
log('Client connected');
});
callObject.on("left-meeting", () => {
setConnectionStatus('Disconnected');
setIsConnected(false);
log('Client disconnected');
});
callObject.on("participant-left", () => {
// When the bot leaves, we are also disconnecting from the call
disconnect().catch((err) => {
log(`Failed to disconnect ${err}`);
})
});
// Trigger so the bot can start sending audio
callObject.on("track-started", (evt) => {
if (evt.track.kind === "audio" && evt.participant.local === false) {
handleEventToConsole(evt)
log("Sending the message that will trigger the bot to play the audio.")
callObject.sendAppMessage("playable")
}
});
callObject.on("error", (evt) => log(`Error: ${evt.error}`));
// Other events just for awareness
callObject.on("track-stopped", handleEventToConsole);
callObject.on("participant-joined", handleEventToConsole);
callObject.on("participant-updated", handleEventToConsole);
};
const handleEventToConsole = (evt) => {
log(`Received event: ${evt.action}`);
};
const connect = async () => {
try {
const callObject = Daily.createCallObject({ subscribeToTracksAutomatically: true });
setCallObject(callObject);
const connectionUrl = `${API_BASE_URL}/connect`
const res = await fetch(connectionUrl, { method: "POST", headers: { "Content-Type": "application/json" } });
const roomInfo = await res.json();
await callObject.join({ url: roomInfo.room_url });
} catch (error) {
log(`Error connecting: ${error.message}`);
}
};
const disconnect = async () => {
if (callObject) {
try {
await callObject.leave();
await callObject.destroy();
setCallObject(null);
} catch (error) {
log(`Error disconnecting: ${error.message}`);
}
}
};
return (
<SafeAreaView style={styles.safeArea}>
<View style={styles.container}>
<View style={styles.statusBar}>
<Text>Status: <Text style={styles.status}>{connectionStatus}</Text></Text>
<View style={styles.controls}>
<Button
title={isConnected ? "Disconnect" : "Connect"}
onPress={isConnected ? disconnect : connect}
/>
</View>
</View>
<View style={styles.debugPanel}>
<Text style={styles.debugTitle}>Debug Info</Text>
<ScrollView style={styles.debugLog}>
{logs.map((logEntry, index) => (
<Text key={index} style={styles.logText}>{logEntry}</Text>
))}
</ScrollView>
</View>
</View>
</SafeAreaView>
);
};
const styles = StyleSheet.create({
safeArea: { flex: 1, backgroundColor: '#f0f0f0', padding: 20 },
container: { flex: 1, margin: 20 },
statusBar: { flexDirection: 'row', justifyContent: 'space-between', alignItems: 'center', padding: 10, backgroundColor: '#fff', borderRadius: 8, marginBottom: 20 },
status: { fontWeight: 'bold' },
controls: { flexDirection: 'row', gap: 10 },
debugPanel: { height: '80%', backgroundColor: '#fff', borderRadius: 8, padding: 20},
debugTitle: { fontSize: 16, fontWeight: 'bold' },
debugLog: { height: '100%', overflow: 'scroll', backgroundColor: '#f8f8f8', padding: 10, borderRadius: 4, fontFamily: 'monospace', fontSize: 12, lineHeight: 1.4 },
});
export default CallScreen;

View File

@@ -6,6 +6,7 @@
import argparse
import os
from typing import Optional
import aiohttp
@@ -18,7 +19,7 @@ async def configure(aiohttp_session: aiohttp.ClientSession):
async def configure_with_args(
aiohttp_session: aiohttp.ClientSession, parser: argparse.ArgumentParser | None = None
aiohttp_session: aiohttp.ClientSession, parser: Optional[argparse.ArgumentParser] = None
):
if not parser:
parser = argparse.ArgumentParser(description="Daily AI SDK Bot Sample")

View File

@@ -17,7 +17,7 @@ from runner import configure
from pipecat.frames.frames import AudioRawFrame, EndFrame, OutputAudioRawFrame, TTSSpeakFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.services.cartesia import CartesiaTTSService
from pipecat.transports.services.daily import DailyParams, DailyTransport
@@ -31,16 +31,15 @@ logger.add(sys.stderr, level="DEBUG")
class SilenceFrame(OutputAudioRawFrame):
def __init__(
self,
audio: bytes = None,
sample_rate: int = 16000,
num_channels: int = 1,
duration: float = 0.1,
*,
sample_rate: int,
duration: float,
):
# Initialize the parent class with the silent frame's data
super().__init__(
audio=self.create_silent_audio_frame(sample_rate, num_channels, duration).audio,
audio=self.create_silent_audio_frame(sample_rate, 1, duration).audio,
sample_rate=sample_rate,
num_channels=num_channels,
num_channels=1,
)
@staticmethod
@@ -80,7 +79,10 @@ async def main():
return
await task.queue_frames(
[
SilenceFrame(duration=0.5),
SilenceFrame(
sample_rate=task.params.audio_out_sample_rate,
duration=0.5,
),
TTSSpeakFrame(f"Hello there, how are you doing today ?"),
EndFrame(),
]

View File

@@ -65,7 +65,6 @@ async def main():
# English
#
voice_id="cgSgspJ2msm6clMCkdW9",
aiohttp_session=session,
#
# Spanish
#
@@ -124,6 +123,7 @@ async def main():
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):
await audio_buffer_processor.start_recording()
await transport.capture_participant_transcription(participant["id"])
await task.queue_frames([context_aggregator.user().get_context_frame()])

View File

@@ -82,7 +82,6 @@ async def main():
# English
#
voice_id="cgSgspJ2msm6clMCkdW9",
aiohttp_session=session,
#
# Spanish
#
@@ -109,8 +108,9 @@ async def main():
context = OpenAILLMContext(messages)
context_aggregator = llm.create_context_aggregator(context)
# Save audio every 10 seconds.
audiobuffer = AudioBufferProcessor(buffer_size=480000)
# NOTE: Watch out! This will save all the conversation in memory. You
# can pass `buffer_size` to get periodic callbacks.
audiobuffer = AudioBufferProcessor()
pipeline = Pipeline(
[
@@ -132,6 +132,7 @@ async def main():
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):
await audiobuffer.start_recording()
await transport.capture_participant_transcription(participant["id"])
await task.queue_frames([context_aggregator.user().get_context_frame()])

View File

@@ -16,8 +16,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.services.cartesia import CartesiaTTSService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.local.audio import LocalAudioTransport
from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams
load_dotenv(override=True)
@@ -26,7 +25,7 @@ logger.add(sys.stderr, level="DEBUG")
async def main():
transport = LocalAudioTransport(TransportParams(audio_out_enabled=True))
transport = LocalAudioTransport(LocalAudioTransportParams(audio_out_enabled=True))
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
@@ -41,7 +40,7 @@ async def main():
await asyncio.sleep(1)
await task.queue_frames([TTSSpeakFrame("Hello there, how is it going!"), EndFrame()])
runner = PipelineRunner()
runner = PipelineRunner(handle_sigint=False if sys.platform == "win32" else True)
await asyncio.gather(runner.run(task), say_something())

View File

@@ -51,7 +51,6 @@ async def main():
)
elevenlabs_tts = ElevenLabsTTSService(
aiohttp_session=session,
api_key=os.getenv("ELEVENLABS_API_KEY"),
voice_id=os.getenv("ELEVENLABS_VOICE_ID"),
)

View File

@@ -27,7 +27,7 @@ from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.services.cartesia import CartesiaHttpTTSService
from pipecat.services.cartesia import CartesiaTTSService
from pipecat.services.openai import OpenAILLMService
from pipecat.transports.services.daily import DailyParams, DailyTransport
@@ -91,7 +91,7 @@ async def main():
),
)
tts = CartesiaHttpTTSService(
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22", # British Lady
)

View File

@@ -18,7 +18,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.openai import OpenAILLMService, OpenAITTSService
from pipecat.services.openai import OpenAILLMService, OpenAISTTService, OpenAITTSService
from pipecat.transports.services.daily import DailyParams, DailyTransport
load_dotenv(override=True)
@@ -38,12 +38,21 @@ async def main():
DailyParams(
audio_out_enabled=True,
audio_out_sample_rate=24000,
transcription_enabled=True,
transcription_enabled=False,
vad_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
vad_audio_passthrough=True,
),
)
# You can use the OpenAI compatible API like Groq.
# stt = OpenAISTTService(
# base_url="https://api.groq.com/openai/v1",
# api_key="gsk_***",
# model="whisper-large-v3",
# )
stt = OpenAISTTService(api_key=os.getenv("OPENAI_API_KEY"), model="whisper-1")
tts = OpenAITTSService(api_key=os.getenv("OPENAI_API_KEY"), voice="alloy")
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
@@ -61,6 +70,7 @@ async def main():
pipeline = Pipeline(
[
transport.input(), # Transport user input
stt, # STT
context_aggregator.user(), # User responses
llm, # LLM
tts, # TTS

View File

@@ -38,7 +38,6 @@ async def main():
"Respond bot",
DailyParams(
audio_out_enabled=True,
audio_out_sample_rate=24000,
transcription_enabled=True,
vad_enabled=True,
vad_analyzer=SileroVADAnalyzer(),

View File

@@ -18,9 +18,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.deepgram import DeepgramSTTService
from pipecat.services.google import GoogleTTSService
from pipecat.services.openai import OpenAILLMService
from pipecat.services.google import GoogleLLMService, GoogleSTTService, GoogleTTSService
from pipecat.transcriptions.language import Language
from pipecat.transports.services.daily import DailyParams, DailyTransport
@@ -40,21 +38,22 @@ async def main():
"Respond bot",
DailyParams(
audio_out_enabled=True,
audio_out_sample_rate=24000,
vad_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
vad_audio_passthrough=True,
),
)
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
stt = GoogleSTTService(
params=GoogleSTTService.InputParams(languages=Language.EN_US),
)
tts = GoogleTTSService(
voice_id="en-US-Journey-F",
params=GoogleTTSService.InputParams(language=Language.EN_US),
)
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"))
messages = [
{

View File

@@ -19,7 +19,7 @@ from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.openai import OpenAILLMService
from pipecat.services.rime import RimeHttpTTSService
from pipecat.services.rime import RimeTTSService
from pipecat.transports.services.daily import DailyParams, DailyTransport
load_dotenv(override=True)
@@ -44,10 +44,9 @@ async def main():
),
)
tts = RimeHttpTTSService(
tts = RimeTTSService(
api_key=os.getenv("RIME_API_KEY", ""),
voice_id="rex",
params=RimeHttpTTSService.InputParams(reduce_latency=True),
)
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")

View File

@@ -216,11 +216,7 @@ async def main():
voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22", # British Lady
)
llm = GoogleLLMService(
model="gemini-1.5-flash-latest",
# model="gemini-exp-1114",
api_key=os.getenv("GOOGLE_API_KEY"),
)
llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"), model="gemini-2.0-flash-001")
messages = [
{

View File

@@ -48,7 +48,6 @@ async def main():
region=os.getenv("AZURE_SPEECH_REGION"),
)
tts2 = ElevenLabsTTSService(
aiohttp_session=session,
api_key=os.getenv("ELEVENLABS_API_KEY"),
voice_id="jBpfuIE2acCO8z3wKNLl",
)

View File

@@ -21,7 +21,7 @@ from pipecat.frames.frames import (
)
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.transports.services.daily import DailyParams, DailyTransport
@@ -61,7 +61,6 @@ async def main():
"Test",
DailyParams(
audio_in_enabled=True,
audio_in_sample_rate=24000,
audio_out_enabled=True,
camera_out_enabled=True,
camera_out_is_live=True,
@@ -78,7 +77,9 @@ async def main():
runner = PipelineRunner()
task = PipelineTask(pipeline)
task = PipelineTask(
pipeline, PipelineParams(audio_in_sample_rate=24000, audio_out_sample_rate=24000)
)
await runner.run(task)

View File

@@ -22,7 +22,7 @@ from pipecat.frames.frames import (
)
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.local.tk import TkLocalTransport
@@ -62,7 +62,7 @@ async def main():
tk_root.title("Local Mirror")
daily_transport = DailyTransport(
room_url, token, "Test", DailyParams(audio_in_enabled=True, audio_in_sample_rate=24000)
room_url, token, "Test", DailyParams(audio_in_enabled=True)
)
tk_transport = TkLocalTransport(
@@ -82,7 +82,9 @@ async def main():
pipeline = Pipeline([daily_transport.input(), MirrorProcessor(), tk_transport.output()])
task = PipelineTask(pipeline)
task = PipelineTask(
pipeline, PipelineParams(audio_in_sample_rate=24000, audio_out_sample_rate=24000)
)
async def run_tk():
while not task.has_finished():

View File

@@ -7,6 +7,7 @@
import asyncio
import os
import sys
from typing import Optional
import aiohttp
from dotenv import load_dotenv
@@ -32,7 +33,7 @@ logger.add(sys.stderr, level="DEBUG")
class UserImageRequester(FrameProcessor):
def __init__(self, participant_id: str | None = None):
def __init__(self, participant_id: Optional[str] = None):
super().__init__()
self._participant_id = participant_id

View File

@@ -7,6 +7,7 @@
import asyncio
import os
import sys
from typing import Optional
import aiohttp
from dotenv import load_dotenv
@@ -32,7 +33,7 @@ logger.add(sys.stderr, level="DEBUG")
class UserImageRequester(FrameProcessor):
def __init__(self, participant_id: str | None = None):
def __init__(self, participant_id: Optional[str] = None):
super().__init__()
self._participant_id = participant_id
@@ -72,9 +73,7 @@ async def main():
vision_aggregator = VisionImageFrameAggregator()
google = GoogleLLMService(
model="gemini-1.5-flash-latest", api_key=os.getenv("GOOGLE_API_KEY")
)
google = GoogleLLMService(model="gemini-2.0-flash-001", api_key=os.getenv("GOOGLE_API_KEY"))
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),

View File

@@ -7,6 +7,7 @@
import asyncio
import os
import sys
from typing import Optional
import aiohttp
from dotenv import load_dotenv
@@ -32,7 +33,7 @@ logger.add(sys.stderr, level="DEBUG")
class UserImageRequester(FrameProcessor):
def __init__(self, participant_id: str | None = None):
def __init__(self, participant_id: Optional[str] = None):
super().__init__()
self._participant_id = participant_id

View File

@@ -7,6 +7,7 @@
import asyncio
import os
import sys
from typing import Optional
import aiohttp
from dotenv import load_dotenv
@@ -32,7 +33,7 @@ logger.add(sys.stderr, level="DEBUG")
class UserImageRequester(FrameProcessor):
def __init__(self, participant_id: str | None = None):
def __init__(self, participant_id: Optional[str] = None):
super().__init__()
self._participant_id = participant_id

View File

@@ -16,8 +16,7 @@ from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.services.whisper import WhisperSTTService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.local.audio import LocalAudioTransport
from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams
load_dotenv(override=True)
@@ -34,7 +33,7 @@ class TranscriptionLogger(FrameProcessor):
async def main():
transport = LocalAudioTransport(TransportParams(audio_in_enabled=True))
transport = LocalAudioTransport(LocalAudioTransportParams(audio_in_enabled=True))
stt = WhisperSTTService()
@@ -44,7 +43,7 @@ async def main():
task = PipelineTask(pipeline)
runner = PipelineRunner()
runner = PipelineRunner(handle_sigint=False if sys.platform == "win32" else True)
await runner.run(task)

View File

@@ -14,6 +14,7 @@ from loguru import logger
from runner import configure
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import TTSSpeakFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -30,6 +31,12 @@ logger.add(sys.stderr, level="DEBUG")
video_participant_id = None
async def start_fetch_weather(function_name, llm, context):
"""Push a frame to the LLM; this is handy when the LLM response might take a while."""
await llm.push_frame(TTSSpeakFrame("Let me check on that."))
logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
async def get_weather(function_name, tool_call_id, arguments, llm, context, result_callback):
location = arguments["location"]
await result_callback(f"The weather in {location} is currently 72 degrees and sunny.")
@@ -62,12 +69,8 @@ async def main():
voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22", # British Lady
)
llm = GoogleLLMService(
model="gemini-1.5-flash-latest",
# model="gemini-exp-1114",
api_key=os.getenv("GOOGLE_API_KEY"),
)
llm.register_function("get_weather", get_weather)
llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"), model="gemini-2.0-flash-001")
llm.register_function("get_weather", get_weather, start_fetch_weather)
llm.register_function("get_image", get_image)
tools = [

View File

@@ -20,7 +20,7 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.services.cartesia import CartesiaTTSService
from pipecat.services.groq import GroqLLMService
from pipecat.services.groq import GroqLLMService, GroqSTTService
from pipecat.services.openai import OpenAILLMContext
from pipecat.transports.services.daily import DailyParams, DailyTransport
@@ -50,20 +50,20 @@ async def main():
"Respond bot",
DailyParams(
audio_out_enabled=True,
transcription_enabled=True,
vad_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
vad_audio_passthrough=True,
),
)
stt = GroqSTTService(api_key=os.getenv("GROQ_API_KEY"), model="distil-whisper-large-v3-en")
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22", # British Lady
)
llm = GroqLLMService(
api_key=os.getenv("GROQ_API_KEY"), model="llama3-groq-70b-8192-tool-use-preview"
)
llm = GroqLLMService(api_key=os.getenv("GROQ_API_KEY"), model="llama-3.3-70b-versatile")
# Register a function_name of None to get all functions
# sent to the same callback with an additional function_name parameter.
llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
@@ -105,6 +105,7 @@ async def main():
pipeline = Pipeline(
[
transport.input(),
stt,
context_aggregator.user(),
llm,
tts,

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@@ -0,0 +1,106 @@
#
# Copyright (c) 20242025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
"""This example demonstrates using the Perplexity API as a drop-in replacement for OpenAI.
Note that while this file is in the function-calling examples, Perplexity's API does not
currently support function calling. The example shows basic chat completion functionality
using Perplexity's API while maintaining compatibility with the OpenAI interface.
"""
import asyncio
import os
import sys
import aiohttp
from dotenv import load_dotenv
from loguru import logger
from openai.types.chat import ChatCompletionToolParam
from runner import configure
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import TTSSpeakFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.services.cartesia import CartesiaTTSService
from pipecat.services.openai import OpenAILLMContext, OpenAILLMService
from pipecat.services.perplexity import PerplexityLLMService
from pipecat.transports.services.daily import DailyParams, DailyTransport
load_dotenv(override=True)
logger.remove(0)
logger.add(sys.stderr, level="DEBUG")
async def main():
async with aiohttp.ClientSession() as session:
(room_url, token) = await configure(session)
transport = DailyTransport(
room_url,
token,
"Respond bot",
DailyParams(
audio_out_enabled=True,
transcription_enabled=True,
vad_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22", # British Lady
)
llm = PerplexityLLMService(api_key=os.getenv("PERPLEXITY_API_KEY"), model="sonar")
messages = [
{
"role": "user",
"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 = OpenAILLMContext(messages)
context_aggregator = llm.create_context_aggregator(context)
pipeline = Pipeline(
[
transport.input(),
context_aggregator.user(),
llm,
tts,
transport.output(),
context_aggregator.assistant(),
]
)
task = PipelineTask(
pipeline,
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,
report_only_initial_ttfb=True,
),
)
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):
await transport.capture_participant_transcription(participant["id"])
# Kick off the conversation.
await task.queue_frames([context_aggregator.user().get_context_frame()])
runner = PipelineRunner()
await runner.run(task)
if __name__ == "__main__":
asyncio.run(main())

View File

@@ -51,8 +51,6 @@ async def main():
out_params=GStreamerPipelineSource.OutputParams(
video_width=1280,
video_height=720,
audio_sample_rate=24000,
audio_channels=1,
),
)

View File

@@ -80,9 +80,7 @@ async def main():
"Respond bot",
DailyParams(
audio_in_enabled=True,
audio_in_sample_rate=24000,
audio_out_enabled=True,
audio_out_sample_rate=24000,
transcription_enabled=False,
vad_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.8)),

View File

@@ -177,9 +177,7 @@ async def main():
"Respond bot",
DailyParams(
audio_in_enabled=True,
audio_in_sample_rate=24000,
audio_out_enabled=True,
audio_out_sample_rate=24000,
transcription_enabled=False,
vad_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.8)),

View File

@@ -237,7 +237,7 @@ async def main():
voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22", # British Lady
)
llm = GoogleLLMService(model="gemini-1.5-flash-latest", api_key=os.getenv("GOOGLE_API_KEY"))
llm = GoogleLLMService(model="gemini-2.0-flash-001", api_key=os.getenv("GOOGLE_API_KEY"))
# you can either register a single function for all function calls, or specific functions
# llm.register_function(None, fetch_weather_from_api)

View File

@@ -88,6 +88,10 @@ async def main():
task = PipelineTask(
pipeline,
PipelineParams(
# We just use 16000 because that's what Tavus is expecting and
# we avoid resampling.
audio_in_sample_rate=16000,
audio_out_sample_rate=16000,
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -104,8 +104,11 @@ async def main():
)
# This processor keeps the last context and will let it through once the
# notifier is woken up.
gated_context_aggregator = GatedOpenAILLMContextAggregator(notifier)
# notifier is woken up. We start with the gate open because we send an
# initial context frame to start the conversation.
gated_context_aggregator = GatedOpenAILLMContextAggregator(
notifier=notifier, start_open=True
)
# Notify if the user hasn't said anything.
async def user_idle_notifier(frame):

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@@ -12,6 +12,7 @@ import time
import aiohttp
from dotenv import load_dotenv
from loguru import logger
from openai.types.chat import ChatCompletionToolParam
from runner import configure
from pipecat.audio.vad.silero import SileroVADAnalyzer
@@ -19,6 +20,8 @@ from pipecat.frames.frames import (
CancelFrame,
EndFrame,
Frame,
FunctionCallInProgressFrame,
FunctionCallResultFrame,
LLMMessagesFrame,
StartFrame,
StartInterruptionFrame,
@@ -26,6 +29,7 @@ from pipecat.frames.frames import (
SystemFrame,
TextFrame,
TranscriptionFrame,
TTSSpeakFrame,
UserStartedSpeakingFrame,
UserStoppedSpeakingFrame,
)
@@ -129,9 +133,9 @@ class CompletenessCheck(FrameProcessor):
class OutputGate(FrameProcessor):
def __init__(self, notifier: BaseNotifier, **kwargs):
def __init__(self, *, notifier: BaseNotifier, start_open: bool = False, **kwargs):
super().__init__(**kwargs)
self._gate_open = False
self._gate_open = start_open
self._frames_buffer = []
self._notifier = notifier
@@ -156,6 +160,11 @@ class OutputGate(FrameProcessor):
await self.push_frame(frame, direction)
return
# Don't block function call frames
if isinstance(frame, (FunctionCallInProgressFrame, FunctionCallResultFrame)):
await self.push_frame(frame, direction)
return
# Ignore frames that are not following the direction of this gate.
if direction != FrameDirection.DOWNSTREAM:
await self.push_frame(frame, direction)
@@ -186,6 +195,16 @@ class OutputGate(FrameProcessor):
break
async def start_fetch_weather(function_name, llm, context):
"""Push a frame to the LLM; this is handy when the LLM response might take a while."""
await llm.push_frame(TTSSpeakFrame("Let me check on that."))
logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
await result_callback({"conditions": "nice", "temperature": "75"})
async def main():
async with aiohttp.ClientSession() as session:
(room_url, _) = await configure(session)
@@ -216,6 +235,34 @@ async def main():
# This is the regular LLM.
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
# Register a function_name of None to get all functions
# sent to the same callback with an additional function_name parameter.
llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
tools = [
ChatCompletionToolParam(
type="function",
function={
"name": "get_current_weather",
"description": "Get the current weather",
"parameters": {
"type": "object",
"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 users location.",
},
},
"required": ["location", "format"],
},
},
)
]
messages = [
{
@@ -224,7 +271,7 @@ async def main():
},
]
context = OpenAILLMContext(messages)
context = OpenAILLMContext(messages, tools)
context_aggregator = llm.create_context_aggregator(context)
# We have instructed the LLM to return 'YES' if it thinks the user
@@ -252,7 +299,9 @@ async def main():
# sentence, this will wake up the notifier if that happens.
user_idle = UserIdleProcessor(callback=user_idle_notifier, timeout=5.0)
bot_output_gate = OutputGate(notifier=notifier)
# We start with the gate open because we send an initial context frame
# to start the conversation.
bot_output_gate = OutputGate(notifier=notifier, start_open=True)
async def block_user_stopped_speaking(frame):
return not isinstance(frame, UserStoppedSpeakingFrame)
@@ -263,6 +312,8 @@ async def main():
or isinstance(frame, LLMMessagesFrame)
or isinstance(frame, StartInterruptionFrame)
or isinstance(frame, StopInterruptionFrame)
or isinstance(frame, FunctionCallInProgressFrame)
or isinstance(frame, FunctionCallResultFrame)
)
pipeline = Pipeline(

View File

@@ -12,6 +12,7 @@ import time
import aiohttp
from dotenv import load_dotenv
from loguru import logger
from openai.types.chat import ChatCompletionToolParam
from runner import configure
from pipecat.audio.vad.silero import SileroVADAnalyzer
@@ -19,6 +20,8 @@ from pipecat.frames.frames import (
CancelFrame,
EndFrame,
Frame,
FunctionCallInProgressFrame,
FunctionCallResultFrame,
LLMMessagesFrame,
StartFrame,
StartInterruptionFrame,
@@ -26,6 +29,7 @@ from pipecat.frames.frames import (
SystemFrame,
TextFrame,
TranscriptionFrame,
TTSSpeakFrame,
UserStartedSpeakingFrame,
UserStoppedSpeakingFrame,
)
@@ -333,9 +337,9 @@ class CompletenessCheck(FrameProcessor):
class OutputGate(FrameProcessor):
def __init__(self, notifier: BaseNotifier, **kwargs):
def __init__(self, *, notifier: BaseNotifier, start_open: bool = False, **kwargs):
super().__init__(**kwargs)
self._gate_open = False
self._gate_open = start_open
self._frames_buffer = []
self._notifier = notifier
@@ -360,6 +364,11 @@ class OutputGate(FrameProcessor):
await self.push_frame(frame, direction)
return
# Don't block function call frames
if isinstance(frame, (FunctionCallInProgressFrame, FunctionCallResultFrame)):
await self.push_frame(frame, direction)
return
# Ignore frames that are not following the direction of this gate.
if direction != FrameDirection.DOWNSTREAM:
await self.push_frame(frame, direction)
@@ -390,6 +399,16 @@ class OutputGate(FrameProcessor):
break
async def start_fetch_weather(function_name, llm, context):
"""Push a frame to the LLM; this is handy when the LLM response might take a while."""
await llm.push_frame(TTSSpeakFrame("Let me check on that."))
logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
await result_callback({"conditions": "nice", "temperature": "75"})
async def main():
async with aiohttp.ClientSession() as session:
(room_url, _) = await configure(session)
@@ -426,6 +445,34 @@ async def main():
api_key=os.getenv("OPENAI_API_KEY"),
model="gpt-4o",
)
# Register a function_name of None to get all functions
# sent to the same callback with an additional function_name parameter.
llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
tools = [
ChatCompletionToolParam(
type="function",
function={
"name": "get_current_weather",
"description": "Get the current weather",
"parameters": {
"type": "object",
"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 users location.",
},
},
"required": ["location", "format"],
},
},
)
]
messages = [
{
@@ -434,7 +481,7 @@ async def main():
},
]
context = OpenAILLMContext(messages)
context = OpenAILLMContext(messages, tools)
context_aggregator = llm.create_context_aggregator(context)
# We have instructed the LLM to return 'YES' if it thinks the user
@@ -461,7 +508,9 @@ async def main():
# sentence, this will wake up the notifier if that happens.
user_idle = UserIdleProcessor(callback=user_idle_notifier, timeout=5.0)
bot_output_gate = OutputGate(notifier=notifier)
# We start with the gate open because we send an initial context frame
# to start the conversation.
bot_output_gate = OutputGate(notifier=notifier, start_open=True)
async def block_user_stopped_speaking(frame):
return not isinstance(frame, UserStoppedSpeakingFrame)
@@ -472,6 +521,8 @@ async def main():
or isinstance(frame, LLMMessagesFrame)
or isinstance(frame, StartInterruptionFrame)
or isinstance(frame, StopInterruptionFrame)
or isinstance(frame, FunctionCallInProgressFrame)
or isinstance(frame, FunctionCallResultFrame)
)
pipeline = Pipeline(

View File

@@ -20,6 +20,8 @@ from pipecat.frames.frames import (
CancelFrame,
EndFrame,
Frame,
FunctionCallInProgressFrame,
FunctionCallResultFrame,
InputAudioRawFrame,
LLMFullResponseEndFrame,
LLMFullResponseStartFrame,
@@ -55,13 +57,9 @@ load_dotenv(override=True)
logger.remove(0)
logger.add(sys.stderr, level="DEBUG")
# TRANSCRIBER_MODEL = "gemini-1.5-flash-latest"
# CLASSIFIER_MODEL = "gemini-1.5-flash-latest"
# CONVERSATION_MODEL = "gemini-1.5-flash-latest"
TRANSCRIBER_MODEL = "gemini-2.0-flash-exp"
CLASSIFIER_MODEL = "gemini-2.0-flash-exp"
CONVERSATION_MODEL = "gemini-2.0-flash-exp"
TRANSCRIBER_MODEL = "gemini-2.0-flash-001"
CLASSIFIER_MODEL = "gemini-2.0-flash-001"
CONVERSATION_MODEL = "gemini-2.0-flash-001"
transcriber_system_instruction = """You are an audio transcriber. You are receiving audio from a user. Your job is to
transcribe the input audio to text exactly as it was said by the user.
@@ -499,7 +497,7 @@ class UserAggregatorBuffer(LLMResponseAggregator):
if isinstance(frame, UserStartedSpeakingFrame):
self._transcription = ""
async def _push_aggregation(self):
async def push_aggregation(self):
if self._aggregation:
self._transcription = self._aggregation
self._aggregation = ""
@@ -579,6 +577,11 @@ class OutputGate(FrameProcessor):
await self.push_frame(frame, direction)
return
# Don't block function call frames
if isinstance(frame, (FunctionCallInProgressFrame, FunctionCallResultFrame)):
await self.push_frame(frame, direction)
return
# Ignore frames that are not following the direction of this gate.
if direction != FrameDirection.DOWNSTREAM:
await self.push_frame(frame, direction)
@@ -639,7 +642,6 @@ async def main():
vad_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
vad_audio_passthrough=True,
audio_in_sample_rate=16000,
),
)
@@ -677,12 +679,6 @@ async def main():
context = OpenAILLMContext()
context_aggregator = conversation_llm.create_context_aggregator(context)
# We have instructed the LLM to return 'True' if it thinks the user
# completed a sentence. So, if it's 'True' we will return true in this
# predicate which will wake up the notifier.
async def wake_check_filter(frame):
return frame.text == "True"
# This is a notifier that we use to synchronize the two LLMs.
notifier = EventNotifier()
@@ -699,14 +695,6 @@ async def main():
async def block_user_stopped_speaking(frame):
return not isinstance(frame, UserStoppedSpeakingFrame)
async def pass_only_llm_trigger_frames(frame):
return (
isinstance(frame, OpenAILLMContextFrame)
or isinstance(frame, LLMMessagesFrame)
or isinstance(frame, StartInterruptionFrame)
or isinstance(frame, StopInterruptionFrame)
)
conversation_audio_context_assembler = ConversationAudioContextAssembler(context=context)
user_aggregator_buffer = UserAggregatorBuffer()

View File

@@ -61,9 +61,11 @@ async def main():
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
# Configure the mute processor with both strategies
stt_mute_processor = STTMuteFilter(
stt_service=stt,
config=STTMuteConfig(
strategies={STTMuteStrategy.FIRST_SPEECH, STTMuteStrategy.FUNCTION_CALL}
strategies={
STTMuteStrategy.MUTE_UNTIL_FIRST_BOT_COMPLETE,
STTMuteStrategy.FUNCTION_CALL,
}
),
)

View File

@@ -143,7 +143,14 @@ class InputTranscriptionContextFilter(FrameProcessor):
return
try:
message = frame.context.messages[-1]
# Make sure we're working with a GoogleLLMContext
context = GoogleLLMContext.upgrade_to_google(frame.context)
message = context.messages[-1]
if not isinstance(message, glm.Content):
logger.error(f"Expected glm.Content, got {type(message)}")
return
last_part = message.parts[-1]
if not (
message.role == "user"
@@ -292,7 +299,7 @@ async def main():
conversation_llm = GoogleLLMService(
name="Conversation",
model="gemini-1.5-flash-latest",
model="gemini-2.0-flash-001",
# model="gemini-exp-1121",
api_key=os.getenv("GOOGLE_API_KEY"),
# we can give the GoogleLLMService a system instruction to use directly
@@ -303,7 +310,7 @@ async def main():
input_transcription_llm = GoogleLLMService(
name="Transcription",
model="gemini-1.5-flash-latest",
model="gemini-2.0-flash-001",
# model="gemini-exp-1121",
api_key=os.getenv("GOOGLE_API_KEY"),
system_instruction=transcriber_system_message,

View File

@@ -37,8 +37,6 @@ async def main():
token,
"Respond bot",
DailyParams(
audio_in_sample_rate=16000,
audio_out_sample_rate=24000,
audio_out_enabled=True,
vad_enabled=True,
vad_audio_passthrough=True,

View File

@@ -37,8 +37,6 @@ async def main():
token,
"Respond bot",
DailyParams(
audio_in_sample_rate=16000,
audio_out_sample_rate=24000,
audio_out_enabled=True,
vad_enabled=True,
vad_audio_passthrough=True,

View File

@@ -84,8 +84,6 @@ async def main():
token,
"Respond bot",
DailyParams(
audio_in_sample_rate=16000,
audio_out_sample_rate=24000,
audio_out_enabled=True,
vad_enabled=True,
vad_audio_passthrough=True,

View File

@@ -37,8 +37,6 @@ async def main():
token,
"Respond bot",
DailyParams(
audio_in_sample_rate=16000,
audio_out_sample_rate=24000,
audio_out_enabled=True,
vad_enabled=True,
vad_audio_passthrough=True,
@@ -47,8 +45,6 @@ async def main():
# matter because we can only use the Multimodal Live API's phrase
# endpointing, for now.
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)),
start_audio_paused=True,
start_video_paused=True,
),
)

View File

@@ -52,8 +52,6 @@ async def main():
token,
"Respond bot",
DailyParams(
audio_in_sample_rate=16000,
audio_out_sample_rate=24000,
audio_out_enabled=True,
vad_enabled=True,
vad_audio_passthrough=True,

View File

@@ -6,6 +6,7 @@
import asyncio
import os
import sqlite3
import sys
from typing import List, Optional
@@ -44,22 +45,33 @@ class TranscriptHandler:
output_file: Optional path to file where transcript is saved. If None, outputs to log only.
"""
def __init__(self, output_file: Optional[str] = None):
"""Initialize handler with optional file output.
def __init__(self, output_file: Optional[str] = None, output_db: Optional[str] = None):
"""Initialize handler with optional file or database output.
Args:
output_file: Path to output file. If None, outputs to log only.
"""
self.messages: List[TranscriptionMessage] = []
self.output_file: Optional[str] = output_file
self.output_db: Optional[str] = output_db
if self.output_db:
self.con = sqlite3.connect("example.db")
self.db = self.con.cursor()
table = self.db.execute("SELECT name FROM sqlite_master WHERE name='messages'")
if not (table.fetchone()):
self.db.execute(
"CREATE TABLE messages(role TEXT, content TEXT, timestamp DATETIME DEFAULT CURRENT_TIMESTAMP )"
)
logger.debug(
f"TranscriptHandler initialized {'with output_file=' + output_file if output_file else 'with log output only'}"
f"TranscriptHandler initialized; output file: {output_file}, output DB: {output_db}"
)
async def save_message(self, message: TranscriptionMessage):
"""Save a single transcript message.
Outputs the message to the log and optionally to a file.
Outputs the message to the log and optionally to a SQLite database or file.
Args:
message: The message to save
@@ -78,6 +90,14 @@ class TranscriptHandler:
except Exception as e:
logger.error(f"Error saving transcript message to file: {e}")
# and/or to a SQLite database
if self.output_db:
self.db.execute(
"INSERT INTO messages VALUES (?, ?, ?)",
(message.role, message.content, message.timestamp),
)
self.con.commit()
async def on_transcript_update(
self, processor: TranscriptProcessor, frame: TranscriptionUpdateFrame
):
@@ -136,8 +156,11 @@ async def main():
# Create transcript processor and handler
transcript = TranscriptProcessor()
# Select a TranscriptHandler output method
# Uncomment out only one of the following lines:
transcript_handler = TranscriptHandler() # Output to log only
# transcript_handler = TranscriptHandler(output_file="transcript.txt") # Output to file and log
# transcript_handler = TranscriptHandler(output_db="example.db") # Output to SQLite DB and log
pipeline = Pipeline(
[

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@@ -38,8 +38,6 @@ load_dotenv(override=True)
logger.remove(0)
logger.add(sys.stderr, level="DEBUG")
DESIRED_SAMPLE_RATE = 16000
def generate_token(room_name: str, participant_name: str, api_key: str, api_secret: str) -> str:
token = api.AccessToken(api_key, api_secret)
@@ -114,11 +112,8 @@ async def main():
token=token,
room_name=room_name,
params=LiveKitParams(
audio_in_channels=1,
audio_in_enabled=True,
audio_out_enabled=True,
audio_in_sample_rate=DESIRED_SAMPLE_RATE,
audio_out_sample_rate=DESIRED_SAMPLE_RATE,
vad_analyzer=SileroVADAnalyzer(),
vad_enabled=True,
vad_audio_passthrough=True,
@@ -128,7 +123,6 @@ async def main():
stt = DeepgramSTTService(
api_key=os.getenv("DEEPGRAM_API_KEY"),
live_options=LiveOptions(
sample_rate=DESIRED_SAMPLE_RATE,
vad_events=True,
),
)
@@ -138,7 +132,6 @@ async def main():
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22", # British Lady
sample_rate=DESIRED_SAMPLE_RATE,
)
messages = [

View File

@@ -89,6 +89,7 @@ async def main():
api_key=os.getenv("GOOGLE_API_KEY"),
system_instruction=system_instruction,
tools=tools,
model="gemini-1.5-flash-002",
)
context = OpenAILLMContext(

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@@ -0,0 +1,254 @@
#
# Copyright (c) 20242025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
"""CrossFit Games 2025 Rulebook RAG Demo.
This example demonstrates a Model-Assisted Generation (MAG) chatbot using Google's Gemini model.
This example uses 2 Gemini models:
- Gemini 2.0 Flash: This is the voice model that is used to generate the response.
- Gemini 2.0 Flash Lite: This is the model that is used to answer questions about the CrossFit Games 2025 rulebook - information that isn't yet publicly
indexed by Gemini (or any other LLM).
How it works:
- The voice model (Gemini 2.0 Flash) is configured to call a function whenever the user asks a question.
- The function call is a tool call to the MAG model (Gemini 2.0 Flash Lite).
- The MAG model generates a response based on the question. The MAG model has the entire contents of the CrossFit Games 2025 rulebook in it's context window.
- The response is returned to the voice model (Gemini 2.0 Flash), which then generates the response to the user.
Why this works:
- Gemini 2.0 Flash is fast
- Gemini 2.0 Flash Lite is faster
- Gemini 2.0 Flash Lite has a large (1 million tokens) context window
- IMPORTANT: The generated response from Gemini 2.0 Flash Lite is limited to 50 words or less and 64 tokens.
You can see this in the RAG_PROMPT variable and the generation_config in the query_knowledge_base function.
Long generations are slower and more expensive, in the world of Voice AI, we don't need long generations.
Example questions to ask and compare to other RAG solutions:
- What lenses are not allowed?
- How many people can be on a team?
- What do winning gyms get?
- What happens if I skip a workout?
- Can I switch my team members for the Games?
- What happens if I start too early?
Notes:
- The RAG model is Gemini 2.0 Flash Lite.
- The voice model is Gemini 2.0 Flash.
- The RAG content is stored in the assets/rag-content.txt file.
- The model for voice is Gemini 2.0 Flash, but can be easily switched to any other model.
Customization options:
- update assets/rag-content.txt with your own knowledge base
- increase/decrease the RAG_MODEL's generation length
- use a different voice model
- play with the RAG_PROMPT
- change the function calling logic
"""
import asyncio
import json
import os
import sys
import time
import aiohttp
import google.generativeai as genai
from dotenv import load_dotenv
from loguru import logger
from runner import configure
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.services.cartesia import CartesiaTTSService
from pipecat.services.google import GoogleLLMService
from pipecat.services.openai import OpenAILLMContext
from pipecat.transports.services.daily import DailyParams, DailyTransport
load_dotenv(override=True)
logger.remove(0)
logger.add(sys.stderr, level="INFO")
video_participant_id = None
def get_rag_content():
"""Get the RAG content from the file."""
script_dir = os.path.dirname(os.path.abspath(__file__))
rag_content_path = os.path.join(script_dir, "assets", "rag-content.txt")
with open(rag_content_path, "r") as f:
return f.read()
RAG_MODEL = "gemini-2.0-flash-lite-preview-02-05"
VOICE_MODEL = "gemini-2.0-flash"
RAG_CONTENT = get_rag_content()
RAG_PROMPT = f"""
You are a helpful assistant designed to answer user questions based solely on the provided knowledge base.
**Instructions:**
1. **Knowledge Base Only:** Answer questions *exclusively* using the information in the "Knowledge Base" section below. Do not use any outside information.
2. **Conversation History:** Use the "Conversation History" (ordered oldest to newest) to understand the context of the current question.
3. **Concise Response:** Respond in 50 words or fewer. The response will be spoken, so avoid symbols, abbreviations, or complex formatting. Use plain, natural language.
4. **Unknown Answer:** If the answer is not found within the "Knowledge Base," respond with "I don't know." Do not guess or make up an answer.
5. Do not introduce your response. Just provide the answer.
6. You must follow all instructions.
**Input Format:**
Each request will include:
* **Conversation History:** (A list of previous user and assistant messages, if any)
**Knowledge Base:**
Here is the knowledge base you have access to:
{RAG_CONTENT}
"""
genai.configure(api_key=os.environ["GOOGLE_API_KEY"])
async def query_knowledge_base(
function_name, tool_call_id, arguments, llm, context, result_callback
):
"""Query the knowledge base for the answer to the question."""
logger.info(f"Querying knowledge base for question: {arguments['question']}")
client = genai.GenerativeModel(
model_name=RAG_MODEL,
system_instruction=RAG_PROMPT,
generation_config=genai.types.GenerationConfig(
temperature=0.1,
max_output_tokens=64,
),
)
# for our case, the first two messages are the instructions and the user message
# so we remove them.
conversation_turns = context.messages[2:]
# convert to standard messages
messages = []
for turn in conversation_turns:
messages.extend(context.to_standard_messages(turn))
def _is_tool_call(turn):
if turn.get("role", None) == "tool":
return True
if turn.get("tool_calls", None):
return True
return False
# filter out tool calls
messages = [turn for turn in messages if not _is_tool_call(turn)]
# use the last 3 turns as the conversation history/context
messages = messages[-3:]
messages_json = json.dumps(messages, ensure_ascii=False, indent=2)
logger.info(f"Conversation turns: {messages_json}")
start = time.perf_counter()
response = client.generate_content(
contents=[messages_json],
)
end = time.perf_counter()
logger.info(f"Time taken: {end - start:.2f} seconds")
logger.info(response.text)
await result_callback(response.text)
async def main():
async with aiohttp.ClientSession() as session:
(room_url, token) = await configure(session)
transport = DailyTransport(
room_url,
token,
"Gemini RAG Bot",
DailyParams(
audio_out_enabled=True,
transcription_enabled=True,
vad_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
voice_id="f9836c6e-a0bd-460e-9d3c-f7299fa60f94", # Southern Lady
)
llm = GoogleLLMService(
model=VOICE_MODEL,
api_key=os.getenv("GOOGLE_API_KEY"),
)
llm.register_function("query_knowledge_base", query_knowledge_base)
tools = [
{
"function_declarations": [
{
"name": "query_knowledge_base",
"description": "Query the knowledge base for the answer to the question.",
"parameters": {
"type": "object",
"properties": {
"question": {
"type": "string",
"description": "The question to query the knowledge base with.",
},
},
},
},
],
},
]
system_prompt = """\
You are a helpful assistant who converses with a user and answers questions.
You have access to the tool, query_knowledge_base, that allows you to query the knowledge base for the answer to the user's question.
Your response will be turned into speech so use only simple words and punctuation.
"""
messages = [
{"role": "system", "content": system_prompt},
{"role": "user", "content": "Greet the user."},
]
context = OpenAILLMContext(messages, tools)
context_aggregator = llm.create_context_aggregator(context)
pipeline = Pipeline(
[
transport.input(),
context_aggregator.user(),
llm,
tts,
transport.output(),
context_aggregator.assistant(),
]
)
task = PipelineTask(
pipeline,
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,
),
)
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):
global video_participant_id
video_participant_id = participant["id"]
await transport.capture_participant_transcription(participant["id"])
await transport.capture_participant_video(video_participant_id, framerate=0)
# Kick off the conversation.
await task.queue_frames([context_aggregator.user().get_context_frame()])
runner = PipelineRunner()
await runner.run(task)
if __name__ == "__main__":
asyncio.run(main())

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@@ -6,6 +6,7 @@
import argparse
import os
from typing import Optional
import aiohttp
@@ -18,7 +19,7 @@ async def configure(aiohttp_session: aiohttp.ClientSession):
async def configure_with_args(
aiohttp_session: aiohttp.ClientSession, parser: argparse.ArgumentParser | None = None
aiohttp_session: aiohttp.ClientSession, parser: Optional[argparse.ArgumentParser] = None
):
if not parser:
parser = argparse.ArgumentParser(description="Daily AI SDK Bot Sample")

7
examples/instant-voice/.gitignore vendored Normal file
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@@ -0,0 +1,7 @@
venv
.idea
server/.env
client/javascript/node_modules
client/javascript/.vite
bkp

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# Instant Voice
This demo showcases how to enable instant voice communication as soon as a user connects.
By leveraging optimizations on both the server and client sides, users can start speaking immediately after pressing the connect button.
## How It Works
### Server-Side Improvements:
- A **pool of Daily rooms** is managed to ensure quick connections.
- When a user connects, an existing room from the pool is assigned.
- A new room is created asynchronously to maintain the predefined pool size.
### Client-Side Improvements:
- Using the **DailyTransport** property `bufferLocalAudioUntilBotReady` set to enabled, users can start speaking immediately
upon receiving the `AUDIO_BUFFERING_STARTED` event (typically within ~1s).
- This allows users to speak even before the bot is fully ready or the WebRTC connection is fully established.
## Quick Start
### 1. Start the Bot Server
1. Navigate to the server directory:
```bash
cd server
```
2. Create and activate a virtual environment:
```bash
python3 -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
3. Install dependencies:
```bash
pip install -r requirements.txt
```
4. Copy the `.env.example` file to `.env` and configure it:
- Add your API keys.
5. Start the server:
```bash
python src/server.py
```
### 2. Connect Using the Client App
For client-side setup, refer to the [JavaScript Guide](client/javascript/README.md).
## Important Notes
- The bot server **must** be running before using the client implementation.
- Ensure your environment variables are correctly set up.
## Requirements
- **Python 3.10+**
- **Node.js 16+** (for JavaScript/React client)
- **Daily API key**
- **Google API key**
- **Modern web browser with WebRTC support**

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@@ -0,0 +1,27 @@
# JavaScript Implementation
Basic implementation using the [Pipecat JavaScript SDK](https://docs.pipecat.ai/client/js/introduction).
## Setup
1. Run the bot server. See the [server README](../../README).
2. Navigate to the `client/javascript` directory:
```bash
cd client/javascript
```
3. Install dependencies:
```bash
npm install
```
4. Run the client app:
```
npm run dev
```
5. Visit http://localhost:5173 in your browser.

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@@ -0,0 +1,37 @@
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>AI Chatbot</title>
</head>
<body>
<div class="container">
<div class="status-bar">
<div class="status">
Buffering audio: <span id="buffering-status">No</span>
</div>
<div class="status">
Transport: <span id="connection-status">Disconnected</span>
</div>
<div class="controls">
<button id="connect-btn">Connect</button>
<button id="disconnect-btn" disabled>Disconnect</button>
</div>
</div>
<audio id="bot-audio" autoplay></audio>
<div class="debug-panel">
<h3>Debug Info</h3>
<div id="debug-log"></div>
</div>
</div>
<script type="module" src="/src/app.ts"></script>
<link rel="stylesheet" href="/src/style.css">
</body>
</html>

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{
"name": "client",
"version": "1.0.0",
"main": "index.js",
"scripts": {
"dev": "vite",
"build": "tsc && vite build",
"preview": "vite preview"
},
"keywords": [],
"author": "",
"license": "ISC",
"description": "",
"devDependencies": {
"@types/node": "^22.13.1",
"@vitejs/plugin-react-swc": "^3.7.2",
"typescript": "^5.7.3",
"vite": "^6.0.2"
},
"dependencies": {
"@pipecat-ai/client-js": "^0.3.2",
"@pipecat-ai/daily-transport": "^0.3.5"
}
}

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@@ -0,0 +1,268 @@
/**
* Copyright (c) 20242025, Daily
*
* SPDX-License-Identifier: BSD 2-Clause License
*/
/**
* RTVI Client Implementation
*
* This client connects to an RTVI-compatible bot server using WebRTC (via Daily).
* It handles audio/video streaming and manages the connection lifecycle.
*
* Requirements:
* - A running RTVI bot server (defaults to http://localhost:7860)
* - The server must implement the /connect endpoint that returns Daily.co room credentials
* - Browser with WebRTC support
*/
import {
Participant,
RTVIClient,
RTVIClientOptions,
RTVIEvent,
} from '@pipecat-ai/client-js';
import { DailyTransport } from '@pipecat-ai/daily-transport';
import SoundUtils from "./util/soundUtils";
import { InstantVoiceHelper } from "./util/instantVoiceHelper";
/**
* InstantVoiceClient handles the connection and media management for a real-time
* voice and video interaction with an AI bot.
*/
class InstantVoiceClient {
private declare rtviClient: RTVIClient;
private connectBtn: HTMLButtonElement | null = null;
private disconnectBtn: HTMLButtonElement | null = null;
private statusSpan: HTMLElement | null = null;
private bufferingAudioSpan: HTMLElement | null = null;
private debugLog: HTMLElement | null = null;
private botAudio: HTMLAudioElement;
private declare startTime: number;
constructor() {
this.botAudio = document.createElement('audio');
this.botAudio.autoplay = true;
document.body.appendChild(this.botAudio);
this.setupDOMElements();
this.setupEventListeners();
this.initializeRTVIClient();
}
/**
* Set up references to DOM elements and create necessary media elements
*/
private setupDOMElements(): void {
this.connectBtn = document.getElementById('connect-btn') as HTMLButtonElement;
this.disconnectBtn = document.getElementById('disconnect-btn') as HTMLButtonElement;
this.statusSpan = document.getElementById('connection-status');
this.bufferingAudioSpan = document.getElementById('buffering-status');
this.debugLog = document.getElementById('debug-log');
}
/**
* Set up event listeners for connect/disconnect buttons
*/
private setupEventListeners(): void {
this.connectBtn?.addEventListener('click', () => this.connect());
this.disconnectBtn?.addEventListener('click', () => this.disconnect());
}
private initializeRTVIClient(): void {
const transport = new DailyTransport({
bufferLocalAudioUntilBotReady: true
});
const RTVIConfig: RTVIClientOptions = {
transport,
params: {
// The baseURL and endpoint of your bot server that the client will connect to
baseUrl: 'http://localhost:7860',
endpoints: { connect: '/connect' },
},
enableMic: true,
enableCam: false,
callbacks: {
onConnected: () => {
this.updateStatus('Connected');
if (this.connectBtn) this.connectBtn.disabled = true;
if (this.disconnectBtn) this.disconnectBtn.disabled = false;
},
onDisconnected: () => {
this.updateStatus('Disconnected');
this.updateBufferingStatus('No');
if (this.connectBtn) this.connectBtn.disabled = false;
if (this.disconnectBtn) this.disconnectBtn.disabled = true;
this.log('Client disconnected');
},
onBotConnected: (participant: Participant) => {
this.log(`onBotConnected, timeTaken: ${Date.now() - this.startTime}`);
},
onBotReady: (data) => {
this.log(`onBotReady, timeTaken: ${Date.now() - this.startTime}`);
this.log(`Bot ready: ${JSON.stringify(data)}`);
this.setupMediaTracks();
},
onUserTranscript: (data) => {
if (data.final) {
this.log(`User: ${data.text}`);
}
},
onBotTranscript: (data) => this.log(`Bot: ${data.text}`),
onMessageError: (error) => console.error('Message error:', error),
onError: (error) => console.error('Error:', error),
},
}
this.rtviClient = new RTVIClient(RTVIConfig);
this.rtviClient.registerHelper("transport", new InstantVoiceHelper({
callbacks: {
onAudioBufferingStarted: () => {
SoundUtils.beep()
this.updateBufferingStatus('Yes');
this.log(`onMicCaptureStarted, timeTaken: ${Date.now() - this.startTime}`);
},
onAudioBufferingStopped: () => {
this.updateBufferingStatus('No');
this.log(`onMicCaptureStopped, timeTaken: ${Date.now() - this.startTime}`);
}
}
}
));
this.setupTrackListeners();
}
/**
* Add a timestamped message to the debug log
*/
private log(message: string): void {
if (!this.debugLog) return;
const entry = document.createElement('div');
entry.textContent = `${new Date().toISOString()} - ${message}`;
if (message.startsWith('User: ')) {
entry.style.color = '#2196F3';
} else if (message.startsWith('Bot: ')) {
entry.style.color = '#4CAF50';
}
this.debugLog.appendChild(entry);
this.debugLog.scrollTop = this.debugLog.scrollHeight;
console.log(message);
}
/**
* Update the connection status display
*/
private updateStatus(status: string): void {
if (this.statusSpan) {
this.statusSpan.textContent = status;
}
this.log(`Status: ${status}`);
}
/**
* Update the connection status display
*/
private updateBufferingStatus(status: string): void {
if (this.bufferingAudioSpan) {
this.bufferingAudioSpan.textContent = status;
}
this.log(`BufferingStatus: ${status}`);
}
/**
* Check for available media tracks and set them up if present
* This is called when the bot is ready or when the transport state changes to ready
*/
setupMediaTracks() {
if (!this.rtviClient) return;
const tracks = this.rtviClient.tracks();
if (tracks.bot?.audio) {
this.setupAudioTrack(tracks.bot.audio);
}
}
/**
* Set up listeners for track events (start/stop)
* This handles new tracks being added during the session
*/
setupTrackListeners() {
if (!this.rtviClient) return;
// Listen for new tracks starting
this.rtviClient.on(RTVIEvent.TrackStarted, (track, participant) => {
// Only handle non-local (bot) tracks
if (!participant?.local && track.kind === 'audio') {
this.setupAudioTrack(track);
}
});
// Listen for tracks stopping
this.rtviClient.on(RTVIEvent.TrackStopped, (track, participant) => {
this.log(`Track stopped: ${track.kind} from ${participant?.name || 'unknown'}`);
});
}
/**
* Set up an audio track for playback
* Handles both initial setup and track updates
*/
private setupAudioTrack(track: MediaStreamTrack): void {
this.log('Setting up audio track');
if (this.botAudio.srcObject && "getAudioTracks" in this.botAudio.srcObject) {
const oldTrack = this.botAudio.srcObject.getAudioTracks()[0];
if (oldTrack?.id === track.id) return;
}
this.botAudio.srcObject = new MediaStream([track]);
}
/**
* Initialize and connect to the bot
* This sets up the RTVI client, initializes devices, and establishes the connection
*/
public async connect(): Promise<void> {
try {
this.startTime = Date.now();
this.log('Connecting to bot...');
await this.rtviClient.connect();
} catch (error) {
this.log(`Error connecting: ${(error as Error).message}`);
this.updateStatus('Error');
this.updateBufferingStatus('No');
// Clean up if there's an error
if (this.rtviClient) {
try {
await this.rtviClient.disconnect();
} catch (disconnectError) {
this.log(`Error during disconnect: ${disconnectError}`);
}
}
}
}
/**
* Disconnect from the bot and clean up media resources
*/
public async disconnect(): Promise<void> {
try {
await this.rtviClient.disconnect();
if (this.botAudio.srcObject && "getAudioTracks" in this.botAudio.srcObject) {
this.botAudio.srcObject.getAudioTracks().forEach((track) => track.stop());
this.botAudio.srcObject = null;
}
} catch (error) {
this.log(`Error disconnecting: ${(error as Error).message}`);
}
}
}
declare global {
interface Window {
InstantVoiceClient: typeof InstantVoiceClient;
}
}
window.addEventListener('DOMContentLoaded', () => {
window.InstantVoiceClient = InstantVoiceClient;
new InstantVoiceClient();
});

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body {
margin: 0;
padding: 20px;
font-family: Arial, sans-serif;
background-color: #f0f0f0;
}
.container {
max-width: 1200px;
margin: 0 auto;
}
.status-bar {
display: flex;
justify-content: space-between;
align-items: center;
padding: 10px;
background-color: #fff;
border-radius: 8px;
margin-bottom: 20px;
}
.controls button {
padding: 8px 16px;
margin-left: 10px;
border: none;
border-radius: 4px;
cursor: pointer;
}
#connect-btn {
background-color: #4caf50;
color: white;
}
#disconnect-btn {
background-color: #f44336;
color: white;
}
button:disabled {
opacity: 0.5;
cursor: not-allowed;
}
.main-content {
background-color: #fff;
border-radius: 8px;
padding: 20px;
margin-bottom: 20px;
}
.bot-container {
display: flex;
flex-direction: column;
align-items: center;
}
#bot-video-container {
width: 640px;
height: 360px;
background-color: #e0e0e0;
border-radius: 8px;
margin: 20px auto;
overflow: hidden;
display: flex;
align-items: center;
justify-content: center;
}
#bot-video-container video {
width: 100%;
height: 100%;
object-fit: cover;
}
.debug-panel {
background-color: #fff;
border-radius: 8px;
padding: 20px;
}
.debug-panel h3 {
margin: 0 0 10px 0;
font-size: 16px;
font-weight: bold;
}
#debug-log {
height: 500px;
overflow-y: auto;
background-color: #f8f8f8;
padding: 10px;
border-radius: 4px;
font-family: monospace;
font-size: 12px;
line-height: 1.4;
}

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import {RTVIClientHelper, RTVIClientHelperOptions, RTVIMessage} from "@pipecat-ai/client-js";
import {DailyRTVIMessageType} from '@pipecat-ai/daily-transport';
export type InstantVoiceHelperCallbacks = Partial<{
onAudioBufferingStarted: () => void;
onAudioBufferingStopped: () => void;
}>;
// --- Interface and class
export interface InstantVoiceHelperOptions extends RTVIClientHelperOptions {
callbacks?: InstantVoiceHelperCallbacks;
}
export class InstantVoiceHelper extends RTVIClientHelper {
protected declare _options: InstantVoiceHelperOptions;
constructor(options: InstantVoiceHelperOptions) {
super(options);
}
handleMessage(rtviMessage: RTVIMessage): void {
switch (rtviMessage.type) {
case DailyRTVIMessageType.AUDIO_BUFFERING_STARTED:
if (this._options.callbacks?.onAudioBufferingStarted) {
this._options.callbacks?.onAudioBufferingStarted()
}
break;
case DailyRTVIMessageType.AUDIO_BUFFERING_STOPPED:
if (this._options.callbacks?.onAudioBufferingStopped) {
this._options.callbacks?.onAudioBufferingStopped()
}
break;
}
}
getMessageTypes(): string[] {
return [DailyRTVIMessageType.AUDIO_BUFFERING_STARTED, DailyRTVIMessageType.AUDIO_BUFFERING_STOPPED];
}
}

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class SoundUtils {
static beep() {
const snd = new Audio("data:audio/wav;base64,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");
void snd.play();
}
}
export default SoundUtils;

View File

@@ -0,0 +1,111 @@
{
"compilerOptions": {
/* Visit https://aka.ms/tsconfig to read more about this file */
/* Projects */
// "incremental": true, /* Save .tsbuildinfo files to allow for incremental compilation of projects. */
// "composite": true, /* Enable constraints that allow a TypeScript project to be used with project references. */
// "tsBuildInfoFile": "./.tsbuildinfo", /* Specify the path to .tsbuildinfo incremental compilation file. */
// "disableSourceOfProjectReferenceRedirect": true, /* Disable preferring source files instead of declaration files when referencing composite projects. */
// "disableSolutionSearching": true, /* Opt a project out of multi-project reference checking when editing. */
// "disableReferencedProjectLoad": true, /* Reduce the number of projects loaded automatically by TypeScript. */
/* Language and Environment */
"target": "es2016", /* Set the JavaScript language version for emitted JavaScript and include compatible library declarations. */
// "lib": [], /* Specify a set of bundled library declaration files that describe the target runtime environment. */
// "jsx": "preserve", /* Specify what JSX code is generated. */
// "experimentalDecorators": true, /* Enable experimental support for legacy experimental decorators. */
// "emitDecoratorMetadata": true, /* Emit design-type metadata for decorated declarations in source files. */
// "jsxFactory": "", /* Specify the JSX factory function used when targeting React JSX emit, e.g. 'React.createElement' or 'h'. */
// "jsxFragmentFactory": "", /* Specify the JSX Fragment reference used for fragments when targeting React JSX emit e.g. 'React.Fragment' or 'Fragment'. */
// "jsxImportSource": "", /* Specify module specifier used to import the JSX factory functions when using 'jsx: react-jsx*'. */
// "reactNamespace": "", /* Specify the object invoked for 'createElement'. This only applies when targeting 'react' JSX emit. */
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// "useDefineForClassFields": true, /* Emit ECMAScript-standard-compliant class fields. */
// "moduleDetection": "auto", /* Control what method is used to detect module-format JS files. */
/* Modules */
"module": "commonjs", /* Specify what module code is generated. */
// "rootDir": "./", /* Specify the root folder within your source files. */
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// "baseUrl": "./", /* Specify the base directory to resolve non-relative module names. */
// "paths": {}, /* Specify a set of entries that re-map imports to additional lookup locations. */
// "rootDirs": [], /* Allow multiple folders to be treated as one when resolving modules. */
// "typeRoots": [], /* Specify multiple folders that act like './node_modules/@types'. */
// "types": [], /* Specify type package names to be included without being referenced in a source file. */
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}

View File

@@ -0,0 +1,15 @@
import { defineConfig } from 'vite';
import react from '@vitejs/plugin-react-swc';
export default defineConfig({
plugins: [react()],
server: {
proxy: {
// Proxy /api requests to the backend server
'/connect': {
target: 'http://0.0.0.0:7860', // Replace with your backend URL
changeOrigin: true,
},
},
},
});

View File

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View File

@@ -0,0 +1,3 @@
DAILY_API_KEY=
GOOGLE_API_KEY=
DAILY_SAMPLE_ROOM_URL=https://yourdomain.daily.co/yourroom # (for joining the bot to the same room repeatedly for local dev)

View File

@@ -0,0 +1,11 @@
[tool.ruff]
exclude = [".git", "*_pb2.py"]
line-length = 100
[tool.ruff.lint]
select = [
"I", # Import rules
]
[tool.ruff.lint.pydocstyle]
convention = "google"

View File

@@ -0,0 +1,4 @@
python-dotenv
fastapi[all]
uvicorn
pipecat-ai[openai,silero,websocket,google,daily]

View File

@@ -0,0 +1,200 @@
#
# Copyright (c) 2025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
import asyncio
import os
from contextlib import asynccontextmanager
from typing import Any, Dict, List
import aiohttp
import uvicorn
from dotenv import load_dotenv
from fastapi import FastAPI, HTTPException, Request
from fastapi.middleware.cors import CORSMiddleware
from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper, DailyRoomParams
# Load environment variables
load_dotenv(override=True)
NUMBER_OF_ROOMS = 1
class RoomPool:
"""Manages a pool of pre-created rooms for quick allocation."""
def __init__(self, daily_rest_helper: DailyRESTHelper):
self.daily_rest_helper = daily_rest_helper
self.pool: List[Dict[str, str]] = []
self.lock = asyncio.Lock()
async def fill_pool(self, count: int):
"""Fills the pool with `count` new rooms."""
for _ in range(count):
await self.add_room()
async def add_room(self):
"""Creates a new room and adds it to the pool."""
try:
room = await self.daily_rest_helper.create_room(DailyRoomParams())
if not room.url:
raise HTTPException(status_code=500, detail="Failed to create room")
user_token = await self.daily_rest_helper.get_token(room.url)
if not user_token:
raise HTTPException(status_code=500, detail="Failed to get user token")
bot_token = await self.daily_rest_helper.get_token(room.url)
if not bot_token:
raise HTTPException(status_code=500, detail="Failed to get bot token")
async with self.lock:
self.pool.append(
{"room_url": room.url, "user_token": user_token, "bot_token": bot_token}
)
except Exception as e:
print(f"Error adding room to pool: {e}")
async def get_room(self) -> Dict[str, str]:
"""Retrieves a room from the pool and requests a new one to maintain the size."""
async with self.lock:
if not self.pool:
raise HTTPException(status_code=503, detail="No available rooms")
room = self.pool.pop(0) # Get first available room
# Start a background task to replenish the pool
asyncio.create_task(self.add_room())
return room
async def delete_room(self, room_url: str):
"""Deletes a room when it is not needed anymore"""
await self.daily_rest_helper.delete_room_by_url(room_url)
async def cleanup(self):
for rooms in self.pool:
room_url = rooms["room_url"]
await self.delete_room(room_url)
class BotManager:
"""Manages bot subprocesses asynchronously."""
def __init__(self):
self.bot_procs: Dict[int, asyncio.subprocess.Process] = {}
self.room_mappings: Dict[int, str] = {} # Maps process ID to room URL
async def start_bot(self, room_url: str, token: str) -> int:
bot_file = "single_bot"
command = f"python3 -m {bot_file} -u {room_url} -t {token}"
try:
proc = await asyncio.create_subprocess_shell(
command,
cwd=os.path.dirname(os.path.abspath(__file__)),
)
if proc.pid is None:
raise HTTPException(status_code=500, detail="Failed to get subprocess PID")
self.bot_procs[proc.pid] = proc
self.room_mappings[proc.pid] = room_url
# Monitor the process and delete the room when it exits
asyncio.create_task(self._monitor_process(proc.pid))
return proc.pid
except Exception as e:
raise HTTPException(status_code=500, detail=f"Failed to start subprocess: {e}")
async def _monitor_process(self, pid: int):
"""Monitors a bot process and deletes the associated room when it exits."""
proc = self.bot_procs.get(pid)
if proc:
await proc.wait() # Wait for the process to exit
room_url = self.room_mappings.pop(pid, None)
if room_url:
await room_pool.delete_room(room_url)
print(f"Deleted room: {room_url}")
del self.bot_procs[pid]
async def cleanup(self):
"""Terminates all running bot processes and deletes associated rooms."""
for pid, proc in list(self.bot_procs.items()):
try:
proc.terminate()
await asyncio.wait_for(proc.wait(), timeout=5)
room_url = self.room_mappings.pop(pid, None)
if room_url:
await room_pool.delete_room(room_url) # Delete room when process terminates
print(f"Deleted room: {room_url}")
except asyncio.TimeoutError:
print(f"Process {pid} did not terminate in time.")
except Exception as e:
print(f"Error terminating process {pid}: {e}")
# Clear remaining mappings
self.bot_procs.clear()
self.room_mappings.clear()
# Global instances
bot_manager = BotManager()
room_pool: RoomPool # Will be initialized in lifespan
@asynccontextmanager
async def lifespan(app: FastAPI):
"""Handles FastAPI startup and shutdown."""
global room_pool
aiohttp_session = aiohttp.ClientSession()
daily_rest_helper = DailyRESTHelper(
daily_api_key=os.getenv("DAILY_API_KEY", ""),
daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
aiohttp_session=aiohttp_session,
)
room_pool = RoomPool(daily_rest_helper)
await room_pool.fill_pool(NUMBER_OF_ROOMS) # Fill pool on startup
yield # Run app
await bot_manager.cleanup()
await room_pool.cleanup()
await aiohttp_session.close()
# Initialize FastAPI app with lifespan manager
app = FastAPI(lifespan=lifespan)
# Configure CORS to allow requests from any origin
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
@app.post("/connect")
async def bot_connect(request: Request) -> Dict[Any, Any]:
try:
room = await room_pool.get_room()
await bot_manager.start_bot(room["room_url"], room["bot_token"])
except HTTPException as e:
return {"error": str(e)}
return {
"room_url": room["room_url"],
"token": room["user_token"],
}
if __name__ == "__main__":
uvicorn.run(app, host="0.0.0.0", port=7860)

View File

@@ -0,0 +1,120 @@
#
# Copyright (c) 2025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
import argparse
import asyncio
import os
import sys
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIProcessor
from pipecat.services.gemini_multimodal_live import GeminiMultimodalLiveLLMService
from pipecat.transports.services.daily import DailyParams, DailyTransport
load_dotenv(override=True)
logger.remove(0)
logger.add(sys.stderr, level="DEBUG")
SYSTEM_INSTRUCTION = f"""
"You are Gemini Chatbot, a friendly, helpful robot.
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. Keep your responses brief. One or two sentences at most.
"""
def extract_arguments():
parser = argparse.ArgumentParser(description="Instant Voice Example")
parser.add_argument(
"-u", "--url", type=str, required=True, help="URL of the Daily room to join"
)
parser.add_argument(
"-t", "--token", type=str, required=False, help="Token of the Daily room to join"
)
args, unknown = parser.parse_known_args()
url = args.url or os.getenv("DAILY_SAMPLE_ROOM_URL")
token = args.token
return url, token
async def main():
room_url, token = extract_arguments()
print(f"room_url: {room_url}")
daily_transport = DailyTransport(
room_url,
token,
"Instant voice Chatbot",
DailyParams(
audio_out_enabled=True,
vad_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
vad_audio_passthrough=True,
),
)
llm = GeminiMultimodalLiveLLMService(
api_key=os.getenv("GOOGLE_API_KEY"),
voice_id="Puck", # Aoede, Charon, Fenrir, Kore, Puck
transcribe_user_audio=True,
transcribe_model_audio=True,
system_instruction=SYSTEM_INSTRUCTION,
)
context = OpenAILLMContext()
context_aggregator = llm.create_context_aggregator(context)
# RTVI events for Pipecat client UI
rtvi = RTVIProcessor(config=RTVIConfig(config=[]), transport=daily_transport)
pipeline = Pipeline(
[
daily_transport.input(),
context_aggregator.user(),
rtvi,
llm, # LLM
daily_transport.output(),
context_aggregator.assistant(),
]
)
task = PipelineTask(
pipeline,
params=PipelineParams(
allow_interruptions=True,
observers=[rtvi.observer()],
),
)
@rtvi.event_handler("on_client_ready")
async def on_client_ready(rtvi):
await rtvi.set_bot_ready()
@daily_transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):
await task.queue_frames([context_aggregator.user().get_context_frame()])
@daily_transport.event_handler("on_participant_left")
async def on_participant_left(transport, participant, reason):
print(f"Participant left: {participant}")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
await runner.run(task)
if __name__ == "__main__":
asyncio.run(main())

View File

@@ -0,0 +1,88 @@
# Pipecat Audio Transcription Example 🚀🎙️
Welcome to the **Pipecat Audio Transcription Example**!
This project showcases how to integrate the awesome [pipecat](https://github.com/pipecat-ai/pipecat) library with a neat textual interface (powered by [Textual](https://github.com/Textualize/textual)) to select audio devices, perform real-time speech-to-text (STT) transcription using [Whisper](https://github.com/openai/whisper).
> **Note:** Although the script allows you to select both input and output audio devices, this example only utilizes the audio **input** for transcription.
---
## 🎉 Features
- **Interactive Audio Device Selection:**
Choose your preferred audio input device using a cool, textual UI.
- **State-of-the-Art Transcription:**
Leverage Whisper's large model (running on CUDA) for high-quality, real-time STT.
- **Live Transcription Logging:**
Watch your spoken words transform into text on your console instantly.
- **Easy Setup:**
Everything you need is in the [`requirements.txt`](./requirements.txt).
---
## 🎥 Demo
Get a quick glimpse of the app in action!
*(Don't worry I'll be adding a GIF demo here soon!)*
![Demo GIF](demo.gif)
---
## 🔧 Installation
Install Dependencies:
```bash
pip install -r requirements.txt
```
---
## 🚀 Usage
Run the main script:
```bash
python bot.py
```
When the app launches, you'll see a textual interface that lets you select your audio input device. Once selected, the app will begin capturing audio, transcribing it using Whisper.
---
## ⚙️ How It Works
1. **LocalAudioTransport:**
Captures audio from your chosen input device.
2. **WhisperSTTService:**
Processes the audio stream using Whisper's large model for speech-to-text conversion.
3. **TranscriptionLogger:**
Logs the transcribed text to the console as soon as it's processed.
---
## 📦 Dependencies
The project relies on:
- [pipecat](https://github.com/yourusername/pipecat) For building the audio processing pipeline.
- [Textual](https://github.com/Textualize/textual) For the interactive terminal UI.
- [Whisper](https://github.com/openai/whisper) For state-of-the-art STT transcription.
---
## Example improvements:
I plan to improve this example with local LLM calls and audio output.

View File

@@ -0,0 +1,65 @@
#
# Copyright (c) 20242025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
import asyncio
import sys
from typing import Tuple
from dotenv import load_dotenv
from loguru import logger
from select_audio_device import AudioDevice, run_device_selector
from pipecat.frames.frames import Frame, TranscriptionFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.services.whisper import Model, WhisperSTTService
from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams
load_dotenv(override=True)
logger.remove(0)
logger.add(sys.stderr, level="DEBUG")
class TranscriptionLogger(FrameProcessor):
async def process_frame(self, frame: Frame, direction: FrameDirection):
await super().process_frame(frame, direction)
if isinstance(frame, TranscriptionFrame):
print(f"Transcription: {frame.text}")
async def main(input_device: int, output_device: int):
transport = LocalAudioTransport(
LocalAudioTransportParams(
audio_in_enabled=True,
audio_out_enabled=False,
input_device_index=input_device,
output_device_index=output_device,
)
)
stt = WhisperSTTService(device="cuda", model=Model.LARGE, no_speech_prob=0.3)
tl = TranscriptionLogger()
pipeline = Pipeline([transport.input(), stt, tl])
task = PipelineTask(pipeline)
runner = PipelineRunner(handle_sigint=False if sys.platform == "win32" else True)
await asyncio.gather(runner.run(task))
if __name__ == "__main__":
res: Tuple[AudioDevice, AudioDevice, int] = asyncio.run(
run_device_selector() # runs the textual app that allows to select input device
)
asyncio.run(main(res[0].index, res[1].index))

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@@ -0,0 +1,8 @@
--extra-index-url https://download.pytorch.org/whl/cu124
torch==2.5.0+cu124
torchvision
torchaudio
pipecat[whisper, openai]
textual==1.0.0
pydantic-settings==2.7.1
pyaudio==0.2.14

View File

@@ -0,0 +1,247 @@
from typing import List, Optional, Tuple
import pyaudio
from pydantic import BaseModel, ConfigDict, Field
from pydantic_settings import BaseSettings
from textual.app import App, ComposeResult
from textual.containers import Container
from textual.widgets import Footer, Header, Label, ListItem, ListView, Select
from textual.widgets.option_list import Option
# ─── DATA MODELS ───────────────────────────────────────────────────────────────
class HostApi(BaseModel):
index: int
struct_version: int = Field(..., alias="structVersion")
type: int
name: str
device_count: int = Field(..., alias="deviceCount")
default_input_device: int = Field(..., alias="defaultInputDevice")
default_output_device: int = Field(..., alias="defaultOutputDevice")
class AudioDevice(BaseModel):
model_config = ConfigDict(populate_by_name=True)
index: int
struct_version: int = Field(..., alias="structVersion")
name: str
host_api: int = Field(..., alias="hostApi")
max_input_channels: int = Field(..., alias="maxInputChannels")
max_output_channels: int = Field(..., alias="maxOutputChannels")
default_low_input_latency: float = Field(..., alias="defaultLowInputLatency")
default_low_output_latency: float = Field(..., alias="defaultLowOutputLatency")
default_high_input_latency: float = Field(..., alias="defaultHighInputLatency")
default_high_output_latency: float = Field(..., alias="defaultHighOutputLatency")
default_sample_rate: float = Field(..., alias="defaultSampleRate")
# ─── SETTINGS MODEL ───────────────────────────────────────────────────────────
class AudioSettings(BaseSettings): # to save settings to a file
host_api: Optional[int] = None
input_device: Optional[AudioDevice] = None
output_device: Optional[AudioDevice] = None
class Config:
env_file = "settings.env" # or adjust as needed
def save_to_json(self, filepath: str) -> None:
with open(filepath, "w") as f:
f.write(self.model_dump_json(indent=2))
# ─── TEXTUAL APP ──────────────────────────────────────────────────────────────
class AudioDeviceSelectorApp(App):
CSS = """
Screen {
align: center middle;
}
#container {
width: 80%;
border: round green;
padding: 1 2;
}
"""
def __init__(
self,
default_host_api: Optional[int] = None,
default_input_device: Optional[AudioDevice] = None,
default_output_device: Optional[AudioDevice] = None,
**kwargs,
) -> None:
super().__init__(**kwargs)
# Save defaults passed from settings.
self.default_host_api: Optional[int] = default_host_api
self.default_input_device: Optional[AudioDevice] = default_input_device
self.default_output_device: Optional[AudioDevice] = default_output_device
self.pyaudio_instance = pyaudio.PyAudio()
# Static datastructures: host APIs and devices as welltyped models.
self.host_apis: List[HostApi] = []
self.current_host_api: Optional[int] = None
self.all_input_devices: List[AudioDevice] = []
self.all_output_devices: List[AudioDevice] = []
self.input_devices: List[AudioDevice] = []
self.output_devices: List[AudioDevice] = []
# Stage management: first select input, then output.
self.stage: str = "input"
self.selected_input_device: Optional[AudioDevice] = None
self.selected_output_device: Optional[AudioDevice] = None
host_api_count: int = self.pyaudio_instance.get_host_api_count()
for i in range(host_api_count):
raw_api = self.pyaudio_instance.get_host_api_info_by_index(i)
# Inject the index (if not already present)
raw_api["index"] = i
try:
api = HostApi.parse_obj(raw_api)
self.host_apis.append(api)
except Exception as e:
# Skip APIs that don't conform.
continue
def compose(self) -> ComposeResult:
options: List[Tuple[str, Option]] = [
(
api.name,
Option(
prompt=str(api.name) if api.name else f"Host API {api.index}",
id=str(api.index),
),
)
for api in self.host_apis
]
yield Header()
yield Footer()
with Container(id="container"):
yield Label("Select Host API:", id="host-api-label")
# Create the Select widget with no options initially.
self.host_api_select: Select[HostApi] = Select(options=options, id="host-api-select")
yield self.host_api_select
self.prompt = Label("Select Input Audio Device:", id="prompt")
yield self.prompt
self.list_view = ListView(id="device-list")
yield self.list_view
def on_mount(self) -> None:
# Populate host APIs from PyAudio.
# Build the dropdown options.
self.host_api_select.refresh() # Force a redraw
# Determine the default host API.
if self.default_host_api is not None:
self.current_host_api = self.default_host_api
else:
default_api_info = self.pyaudio_instance.get_default_host_api_info()
self.current_host_api = default_api_info["index"]
# Delay setting the dropdown's value until the widget is fully initialized.
self.set_timer(
0,
lambda: setattr(self.host_api_select, "value", str(self.current_host_api)),
)
# Load all devices and parse them into AudioDevice objects.
device_count: int = self.pyaudio_instance.get_device_count()
for i in range(device_count):
raw_device = self.pyaudio_instance.get_device_info_by_index(i)
raw_device["index"] = i
try:
device = AudioDevice.parse_obj(raw_device)
except Exception as e:
# Skip devices missing required fields.
continue
if device.max_input_channels > 0:
self.all_input_devices.append(device)
if device.max_output_channels > 0:
self.all_output_devices.append(device)
self.filter_devices()
self.populate_list(self.input_devices)
if self.default_input_device:
self._select_default_in_list(self.default_input_device)
def filter_devices(self) -> None:
"""Filter devices based on the selected host API."""
self.input_devices = [
d for d in self.all_input_devices if d.host_api == self.current_host_api
]
self.output_devices = [
d for d in self.all_output_devices if d.host_api == self.current_host_api
]
def populate_list(self, devices: List[AudioDevice]) -> None:
"""Populate the ListView with a list of AudioDevice objects."""
self.list_view.clear()
for dev in devices:
item_text: str = f"{dev.name} (Index: {dev.index})"
item = ListItem(Label(item_text))
# Attach the AudioDevice instance to the widget.
item.device_info = dev # type: ignore
self.list_view.append(item)
def _select_default_in_list(self, default_device: AudioDevice) -> None:
"""Pre-select the default device if present in the current list."""
for idx, item in enumerate(self.list_view.children):
if hasattr(item, "device_info") and item.device_info.index == default_device.index:
self.list_view.index = idx
break
async def on_select_changed(self, event: Select.Changed) -> None:
"""Handle changes in the host API dropdown."""
if event.select.id == "host-api-select":
self.current_host_api = int(event.value.id)
self.filter_devices()
if self.stage == "input":
self.populate_list(self.input_devices)
if self.default_input_device:
self._select_default_in_list(self.default_input_device)
elif self.stage == "output":
self.populate_list(self.output_devices)
if self.default_output_device:
self._select_default_in_list(self.default_output_device)
async def on_list_view_selected(self, message: ListView.Selected) -> None:
"""Record device selection and switch stages."""
selected_item = message.item
device_info: AudioDevice = selected_item.device_info # type: ignore
if self.stage == "input":
self.selected_input_device = device_info
self.stage = "output"
self.prompt.update("Select Output Audio Device:")
self.populate_list(self.output_devices)
if self.default_output_device:
self._select_default_in_list(self.default_output_device)
elif self.stage == "output":
self.selected_output_device = device_info
await self.action_quit()
# ─── HELPER FUNCTIONS ─────────────────────────────────────────────────────────
async def run_device_selector(
default_host_api: Optional[int] = None,
default_input_device: Optional[AudioDevice] = None,
default_output_device: Optional[AudioDevice] = None,
) -> Tuple[AudioDevice, AudioDevice, int]:
app = AudioDeviceSelectorApp(
default_host_api=default_host_api,
default_input_device=default_input_device,
default_output_device=default_output_device,
)
await app.run_async()
# The current_host_api is guaranteed to be set.
return app.selected_input_device, app.selected_output_device, app.current_host_api # type: ignore

View File

@@ -106,8 +106,8 @@ class UserImageRequester(FrameProcessor):
UserImageRequestFrame(self.participant_id), FrameDirection.UPSTREAM
)
await self.push_frame(TextFrame("Describe the image in a short sentence."))
elif isinstance(frame, UserImageRawFrame):
await self.push_frame(frame)
else:
await self.push_frame(frame, direction)
class TextFilterProcessor(FrameProcessor):

View File

@@ -13,7 +13,7 @@
"@pipecat-ai/daily-transport": "^0.3.4"
},
"devDependencies": {
"vite": "^6.0.2"
"vite": "^6.0.9"
}
},
"node_modules/@babel/runtime": {
@@ -45,14 +45,13 @@
}
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"cpu": [
"ppc64"
],
"dev": true,
"license": "MIT",
"optional": true,
"os": [
"aix"
@@ -62,14 +61,13 @@
}
},
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"cpu": [
"arm"
],
"dev": true,
"license": "MIT",
"optional": true,
"os": [
"android"
@@ -79,14 +77,13 @@
}
},
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"version": "0.24.0",
"resolved": "https://registry.npmjs.org/@esbuild/android-arm64/-/android-arm64-0.24.0.tgz",
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"cpu": [
"arm64"
],
"dev": true,
"license": "MIT",
"optional": true,
"os": [
"android"
@@ -96,14 +93,13 @@
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},
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"cpu": [
"x64"
],
"dev": true,
"license": "MIT",
"optional": true,
"os": [
"android"
@@ -113,14 +109,13 @@
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"cpu": [
"arm64"
],
"dev": true,
"license": "MIT",
"optional": true,
"os": [
"darwin"
@@ -130,14 +125,13 @@
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"cpu": [
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],
"dev": true,
"license": "MIT",
"optional": true,
"os": [
"darwin"
@@ -147,14 +141,13 @@
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"cpu": [
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],
"dev": true,
"license": "MIT",
"optional": true,
"os": [
"freebsd"
@@ -164,14 +157,13 @@
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"cpu": [
"x64"
],
"dev": true,
"license": "MIT",
"optional": true,
"os": [
"freebsd"
@@ -181,14 +173,13 @@
}
},
"node_modules/@esbuild/linux-arm": {
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"cpu": [
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],
"dev": true,
"license": "MIT",
"optional": true,
"os": [
"linux"
@@ -198,14 +189,13 @@
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"cpu": [
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],
"dev": true,
"license": "MIT",
"optional": true,
"os": [
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@@ -215,14 +205,13 @@
}
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"cpu": [
"ia32"
],
"dev": true,
"license": "MIT",
"optional": true,
"os": [
"linux"
@@ -232,14 +221,13 @@
}
},
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"cpu": [
"loong64"
],
"dev": true,
"license": "MIT",
"optional": true,
"os": [
"linux"
@@ -249,14 +237,13 @@
}
},
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],
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"license": "MIT",
"optional": true,
"os": [
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]
},
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"resolved": "https://registry.npmjs.org/@rollup/rollup-win32-x64-msvc/-/rollup-win32-x64-msvc-4.28.0.tgz",
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"cpu": [
"x64"
],
"dev": true,
"license": "MIT",
"optional": true,
"os": [
"win32"
@@ -808,8 +795,7 @@
"version": "1.0.6",
"resolved": "https://registry.npmjs.org/@types/estree/-/estree-1.0.6.tgz",
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"dev": true,
"license": "MIT"
"dev": true
},
"node_modules/@types/events": {
"version": "3.0.3",
@@ -847,12 +833,11 @@
}
},
"node_modules/esbuild": {
"version": "0.24.0",
"resolved": "https://registry.npmjs.org/esbuild/-/esbuild-0.24.0.tgz",
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"dev": true,
"hasInstallScript": true,
"license": "MIT",
"bin": {
"esbuild": "bin/esbuild"
},
@@ -860,30 +845,31 @@
"node": ">=18"
},
"optionalDependencies": {
"@esbuild/aix-ppc64": "0.24.0",
"@esbuild/android-arm": "0.24.0",
"@esbuild/android-arm64": "0.24.0",
"@esbuild/android-x64": "0.24.0",
"@esbuild/darwin-arm64": "0.24.0",
"@esbuild/darwin-x64": "0.24.0",
"@esbuild/freebsd-arm64": "0.24.0",
"@esbuild/freebsd-x64": "0.24.0",
"@esbuild/linux-arm": "0.24.0",
"@esbuild/linux-arm64": "0.24.0",
"@esbuild/linux-ia32": "0.24.0",
"@esbuild/linux-loong64": "0.24.0",
"@esbuild/linux-mips64el": "0.24.0",
"@esbuild/linux-ppc64": "0.24.0",
"@esbuild/linux-riscv64": "0.24.0",
"@esbuild/linux-s390x": "0.24.0",
"@esbuild/linux-x64": "0.24.0",
"@esbuild/netbsd-x64": "0.24.0",
"@esbuild/openbsd-arm64": "0.24.0",
"@esbuild/openbsd-x64": "0.24.0",
"@esbuild/sunos-x64": "0.24.0",
"@esbuild/win32-arm64": "0.24.0",
"@esbuild/win32-ia32": "0.24.0",
"@esbuild/win32-x64": "0.24.0"
"@esbuild/aix-ppc64": "0.24.2",
"@esbuild/android-arm": "0.24.2",
"@esbuild/android-arm64": "0.24.2",
"@esbuild/android-x64": "0.24.2",
"@esbuild/darwin-arm64": "0.24.2",
"@esbuild/darwin-x64": "0.24.2",
"@esbuild/freebsd-arm64": "0.24.2",
"@esbuild/freebsd-x64": "0.24.2",
"@esbuild/linux-arm": "0.24.2",
"@esbuild/linux-arm64": "0.24.2",
"@esbuild/linux-ia32": "0.24.2",
"@esbuild/linux-loong64": "0.24.2",
"@esbuild/linux-mips64el": "0.24.2",
"@esbuild/linux-ppc64": "0.24.2",
"@esbuild/linux-riscv64": "0.24.2",
"@esbuild/linux-s390x": "0.24.2",
"@esbuild/linux-x64": "0.24.2",
"@esbuild/netbsd-arm64": "0.24.2",
"@esbuild/netbsd-x64": "0.24.2",
"@esbuild/openbsd-arm64": "0.24.2",
"@esbuild/openbsd-x64": "0.24.2",
"@esbuild/sunos-x64": "0.24.2",
"@esbuild/win32-arm64": "0.24.2",
"@esbuild/win32-ia32": "0.24.2",
"@esbuild/win32-x64": "0.24.2"
}
},
"node_modules/events": {
@@ -901,7 +887,6 @@
"integrity": "sha512-5xoDfX+fL7faATnagmWPpbFtwh/R77WmMMqqHGS65C3vvB0YHrgF+B1YmZ3441tMj5n63k0212XNoJwzlhffQw==",
"dev": true,
"hasInstallScript": true,
"license": "MIT",
"optional": true,
"os": [
"darwin"
@@ -951,7 +936,6 @@
"url": "https://github.com/sponsors/ai"
}
],
"license": "MIT",
"bin": {
"nanoid": "bin/nanoid.cjs"
},
@@ -963,13 +947,12 @@
"version": "1.1.1",
"resolved": "https://registry.npmjs.org/picocolors/-/picocolors-1.1.1.tgz",
"integrity": "sha512-xceH2snhtb5M9liqDsmEw56le376mTZkEX/jEb/RxNFyegNul7eNslCXP9FDj/Lcu0X8KEyMceP2ntpaHrDEVA==",
"dev": true,
"license": "ISC"
"dev": true
},
"node_modules/postcss": {
"version": "8.4.49",
"resolved": "https://registry.npmjs.org/postcss/-/postcss-8.4.49.tgz",
"integrity": "sha512-OCVPnIObs4N29kxTjzLfUryOkvZEq+pf8jTF0lg8E7uETuWHA+v7j3c/xJmiqpX450191LlmZfUKkXxkTry7nA==",
"version": "8.5.2",
"resolved": "https://registry.npmjs.org/postcss/-/postcss-8.5.2.tgz",
"integrity": "sha512-MjOadfU3Ys9KYoX0AdkBlFEF1Vx37uCCeN4ZHnmwm9FfpbsGWMZeBLMmmpY+6Ocqod7mkdZ0DT31OlbsFrLlkA==",
"dev": true,
"funding": [
{
@@ -985,9 +968,8 @@
"url": "https://github.com/sponsors/ai"
}
],
"license": "MIT",
"dependencies": {
"nanoid": "^3.3.7",
"nanoid": "^3.3.8",
"picocolors": "^1.1.1",
"source-map-js": "^1.2.1"
},
@@ -1002,11 +984,10 @@
"license": "MIT"
},
"node_modules/rollup": {
"version": "4.28.0",
"resolved": "https://registry.npmjs.org/rollup/-/rollup-4.28.0.tgz",
"integrity": "sha512-G9GOrmgWHBma4YfCcX8PjH0qhXSdH8B4HDE2o4/jaxj93S4DPCIDoLcXz99eWMji4hB29UFCEd7B2gwGJDR9cQ==",
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"resolved": "https://registry.npmjs.org/rollup/-/rollup-4.34.6.tgz",
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"dev": true,
"license": "MIT",
"dependencies": {
"@types/estree": "1.0.6"
},
@@ -1018,24 +999,25 @@
"npm": ">=8.0.0"
},
"optionalDependencies": {
"@rollup/rollup-android-arm-eabi": "4.28.0",
"@rollup/rollup-android-arm64": "4.28.0",
"@rollup/rollup-darwin-arm64": "4.28.0",
"@rollup/rollup-darwin-x64": "4.28.0",
"@rollup/rollup-freebsd-arm64": "4.28.0",
"@rollup/rollup-freebsd-x64": "4.28.0",
"@rollup/rollup-linux-arm-gnueabihf": "4.28.0",
"@rollup/rollup-linux-arm-musleabihf": "4.28.0",
"@rollup/rollup-linux-arm64-gnu": "4.28.0",
"@rollup/rollup-linux-arm64-musl": "4.28.0",
"@rollup/rollup-linux-powerpc64le-gnu": "4.28.0",
"@rollup/rollup-linux-riscv64-gnu": "4.28.0",
"@rollup/rollup-linux-s390x-gnu": "4.28.0",
"@rollup/rollup-linux-x64-gnu": "4.28.0",
"@rollup/rollup-linux-x64-musl": "4.28.0",
"@rollup/rollup-win32-arm64-msvc": "4.28.0",
"@rollup/rollup-win32-ia32-msvc": "4.28.0",
"@rollup/rollup-win32-x64-msvc": "4.28.0",
"@rollup/rollup-android-arm-eabi": "4.34.6",
"@rollup/rollup-android-arm64": "4.34.6",
"@rollup/rollup-darwin-arm64": "4.34.6",
"@rollup/rollup-darwin-x64": "4.34.6",
"@rollup/rollup-freebsd-arm64": "4.34.6",
"@rollup/rollup-freebsd-x64": "4.34.6",
"@rollup/rollup-linux-arm-gnueabihf": "4.34.6",
"@rollup/rollup-linux-arm-musleabihf": "4.34.6",
"@rollup/rollup-linux-arm64-gnu": "4.34.6",
"@rollup/rollup-linux-arm64-musl": "4.34.6",
"@rollup/rollup-linux-loongarch64-gnu": "4.34.6",
"@rollup/rollup-linux-powerpc64le-gnu": "4.34.6",
"@rollup/rollup-linux-riscv64-gnu": "4.34.6",
"@rollup/rollup-linux-s390x-gnu": "4.34.6",
"@rollup/rollup-linux-x64-gnu": "4.34.6",
"@rollup/rollup-linux-x64-musl": "4.34.6",
"@rollup/rollup-win32-arm64-msvc": "4.34.6",
"@rollup/rollup-win32-ia32-msvc": "4.34.6",
"@rollup/rollup-win32-x64-msvc": "4.34.6",
"fsevents": "~2.3.2"
}
},
@@ -1066,7 +1048,6 @@
"resolved": "https://registry.npmjs.org/source-map-js/-/source-map-js-1.2.1.tgz",
"integrity": "sha512-UXWMKhLOwVKb728IUtQPXxfYU+usdybtUrK/8uGE8CQMvrhOpwvzDBwj0QhSL7MQc7vIsISBG8VQ8+IDQxpfQA==",
"dev": true,
"license": "BSD-3-Clause",
"engines": {
"node": ">=0.10.0"
}
@@ -1101,15 +1082,14 @@
}
},
"node_modules/vite": {
"version": "6.0.2",
"resolved": "https://registry.npmjs.org/vite/-/vite-6.0.2.tgz",
"integrity": "sha512-XdQ+VsY2tJpBsKGs0wf3U/+azx8BBpYRHFAyKm5VeEZNOJZRB63q7Sc8Iup3k0TrN3KO6QgyzFf+opSbfY1y0g==",
"version": "6.1.0",
"resolved": "https://registry.npmjs.org/vite/-/vite-6.1.0.tgz",
"integrity": "sha512-RjjMipCKVoR4hVfPY6GQTgveinjNuyLw+qruksLDvA5ktI1150VmcMBKmQaEWJhg/j6Uaf6dNCNA0AfdzUb/hQ==",
"dev": true,
"license": "MIT",
"dependencies": {
"esbuild": "^0.24.0",
"postcss": "^8.4.49",
"rollup": "^4.23.0"
"esbuild": "^0.24.2",
"postcss": "^8.5.1",
"rollup": "^4.30.1"
},
"bin": {
"vite": "bin/vite.js"

View File

@@ -12,7 +12,7 @@
"license": "ISC",
"description": "",
"devDependencies": {
"vite": "^6.0.2"
"vite": "^6.0.9"
},
"dependencies": {
"@pipecat-ai/client-js": "^0.3.2",

View File

@@ -23,7 +23,7 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIProcessor
from pipecat.services.cartesia import CartesiaTTSService
from pipecat.services.deepgram import DeepgramSTTService
from pipecat.services.google import GoogleLLMService, LLMSearchResponseFrame
from pipecat.services.google import GoogleLLMService, GoogleRTVIObserver, LLMSearchResponseFrame
from pipecat.transports.services.daily import DailyParams, DailyTransport
from pipecat.utils.text.markdown_text_filter import MarkdownTextFilter
@@ -102,6 +102,7 @@ async def main():
llm = GoogleLLMService(
api_key=os.getenv("GOOGLE_API_KEY"),
model="gemini-1.5-flash-002",
system_instruction=system_instruction,
tools=tools,
)
@@ -141,7 +142,7 @@ async def main():
pipeline,
PipelineParams(
allow_interruptions=True,
observers=[rtvi.observer()],
observers=[GoogleRTVIObserver(rtvi)],
),
)

View File

@@ -6,6 +6,7 @@
import argparse
import os
from typing import Optional
import aiohttp
@@ -18,7 +19,7 @@ async def configure(aiohttp_session: aiohttp.ClientSession):
async def configure_with_args(
aiohttp_session: aiohttp.ClientSession, parser: argparse.ArgumentParser | None = None
aiohttp_session: aiohttp.ClientSession, parser: Optional[argparse.ArgumentParser] = None
):
if not parser:
parser = argparse.ArgumentParser(description="Daily AI SDK Bot Sample")

View File

@@ -1,3 +1,5 @@
<!-- @format -->
<div align="center">
 <img alt="pipecat" width="300px" height="auto" src="image.png">
</div>
@@ -104,6 +106,21 @@ curl -X POST "http://localhost:7860/daily_start_bot" \
-d '{"dialoutNumber": "+18057145330", "detectVoicemail": true}'
```
### New! Using Gemini with Daily
We have introduced a new example file that uses Gemini. You can find the code within bot_daily_gemini.py.
If you want to spin up a Gemini-based bot for this demo, instead of an OpenAI-based bot, call the same properties above but on the `daily_gemini_start_bot` endpoint instead.
For example:
```shell
curl -X POST "http://localhost:7860/daily_gemini_start_bot" \ py pipecat
-H "Content-Type: application/json" \
-d '{"detectVoicemail": true}'
```
Any request body properties supported by `/daily_start_bot` (such as "detectVoicemail", "dialoutnumber", etc) can also be passed to `/daily_gemini_start_bot`. The only difference is that calling the Gemini endpoint will start a Gemini bot session.
### More information
For more configuration options, please consult [Daily's API documentation](https://docs.daily.co).

View File

@@ -2,13 +2,14 @@ import argparse
import asyncio
import os
import sys
from typing import Optional
from dotenv import load_dotenv
from loguru import logger
from openai.types.chat import ChatCompletionToolParam
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import EndFrame, EndTaskFrame
from pipecat.frames.frames import EndTaskFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -42,7 +43,7 @@ async def main(
callId: str,
callDomain: str,
detect_voicemail: bool,
dialout_number: str | None,
dialout_number: Optional[str],
):
# dialin_settings are only needed if Daily's SIP URI is used
# If you are handling this via Twilio, Telnyx, set this to None
@@ -97,19 +98,22 @@ async def main(
- **"Record your message after the tone."**
- **Any phrase that suggests an answering machine or voicemail.**
- **ASSUME IT IS A VOICEMAIL. DO NOT WAIT FOR MORE CONFIRMATION.**
- **IF THE CALL SAYS "PLEASE LEAVE A MESSAGE AFTER THE BEEP", WAIT FOR THE BEEP BEFORE LEAVING A MESSAGE.**
#### **Step 2: Leave a Voicemail Message**
- Immediately say:
- Immediately say:
*"Hello, this is a message for Pipecat example user. This is Chatbot. Please call back on 123-456-7891. Thank you."*
- **IMMEDIATELY AFTER LEAVING THE MESSAGE, CALL `terminate_call`.**
- **DO NOT SPEAK AFTER CALLING `terminate_call`.**
- **FAILURE TO CALL `terminate_call` IMMEDIATELY IS A MISTAKE.**
#### **Step 3: If Speaking to a Human**
- If the call is answered by a human, say:
- If the call is answered by a human, say:
*"Oh, hello! I'm a friendly chatbot. Is there anything I can help you with?"*
- Keep responses **brief and helpful**.
- If the user no longer needs assistance, **call `terminate_call` immediately.**
- If the user no longer needs assistance, say:
*"Okay, thank you! Have a great day!"*
-**Then call `terminate_call` immediately.**
---

View File

@@ -0,0 +1,234 @@
#
# Copyright (c) 20242025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
import argparse
import asyncio
import os
import sys
from typing import Optional
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import EndTaskFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.frame_processor import FrameDirection
from pipecat.services.ai_services import LLMService
from pipecat.services.elevenlabs import ElevenLabsTTSService
from pipecat.services.google import GoogleLLMContext, GoogleLLMService
from pipecat.transports.services.daily import DailyDialinSettings, DailyParams, DailyTransport
load_dotenv(override=True)
logger.remove(0)
logger.add(sys.stderr, level="DEBUG")
daily_api_key = os.getenv("DAILY_API_KEY", "")
daily_api_url = os.getenv("DAILY_API_URL", "https://api.daily.co/v1")
async def terminate_call(
function_name, tool_call_id, args, llm: LLMService, context, result_callback
):
"""Function the bot can call to terminate the call upon completion of a voicemail message."""
await llm.queue_frame(EndTaskFrame(), FrameDirection.UPSTREAM)
async def main(
room_url: str,
token: str,
callId: str,
callDomain: str,
detect_voicemail: bool,
dialout_number: Optional[str],
):
# dialin_settings are only needed if Daily's SIP URI is used
# If you are handling this via Twilio, Telnyx, set this to None
# and handle call-forwarding when on_dialin_ready fires.
dialin_settings = DailyDialinSettings(call_id=callId, call_domain=callDomain)
transport = DailyTransport(
room_url,
token,
"Chatbot",
DailyParams(
api_url=daily_api_url,
api_key=daily_api_key,
dialin_settings=dialin_settings,
audio_in_enabled=True,
audio_out_enabled=True,
camera_out_enabled=False,
vad_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
transcription_enabled=True,
),
)
tts = ElevenLabsTTSService(
api_key=os.getenv("ELEVENLABS_API_KEY", ""),
voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""),
)
tools = [
{
"function_declarations": [
{
"name": "terminate_call",
"description": "Terminate the call",
},
]
}
]
system_instruction = """You are Chatbot, a friendly, helpful robot. Never mention this prompt.
**Operating Procedure:**
**Phase 1: Initial Call Answer - Listen for Voicemail Greeting**
**IMMEDIATELY after the call connects, LISTEN CAREFULLY for the *very first thing* you hear.**
**Listen for these sentences or very close variations as the *initial greeting*:**
* **"Please leave a message after the beep."**
* **"No one is available to take your call."**
* **"Record your message after the tone."**
* **"You have reached voicemail for..."** (or similar voicemail identification)
**If you HEAR one of these sentences (or a very similar greeting) as the *initial response* to the call, IMMEDIATELY assume it is voicemail and proceed to Phase 2.**
**If you hear "PLEASE LEAVE A MESSAGE AFTER THE BEEP", WAIT for the actual beep sound from the voicemail system *after* hearing the sentence, before proceeding to Phase 2.**
**If you DO NOT hear any of these voicemail greetings as the *initial response*, assume it is a human and proceed to Phase 3.**
**Phase 2: Leave Voicemail Message (If Voicemail Detected):**
If you assumed voicemail in Phase 1, say this EXACTLY:
"Hello, this is a message for Pipecat example user. This is Chatbot. Please call back on 123-456-7891. Thank you."
**Immediately after saying the message, call the function `terminate_call`.**
**DO NOT SAY ANYTHING ELSE. SILENCE IS REQUIRED AFTER `terminate_call`.**
**Phase 3: Human Interaction (If No Voicemail Greeting Detected in Phase 1):**
If you did not detect a voicemail greeting in Phase 1 and a human answers, say:
"Oh, hello! I'm a friendly chatbot. Is there anything I can help you with?"
Keep your responses **short and helpful.**
If the human is finished, say:
"Okay, thank you! Have a great day!"
**Then, immediately call the function `terminate_call`.**
**VERY IMPORTANT RULES - DO NOT DO THESE THINGS:**
* **DO NOT SAY "Please leave a message after the beep."**
* **DO NOT SAY "No one is available to take your call."**
* **DO NOT SAY "Record your message after the tone."**
* **DO NOT SAY ANY voicemail greeting yourself.**
* **Only check for voicemail greetings in Phase 1, *immediately after the call connects*.**
* **After voicemail or human interaction, ALWAYS call `terminate_call` immediately.**
* **Do not speak after calling `terminate_call`.**
* Your speech will be audio, so use simple language without special characters.
"""
llm = GoogleLLMService(
model="models/gemini-2.0-flash-exp",
api_key=os.getenv("GOOGLE_API_KEY"),
system_instruction=system_instruction,
tools=tools,
)
llm.register_function("terminate_call", terminate_call)
context = GoogleLLMContext()
context_aggregator = llm.create_context_aggregator(context)
pipeline = Pipeline(
[
transport.input(), # Transport user input
context_aggregator.user(), # User responses
llm, # LLM
tts, # TTS
transport.output(), # Transport bot output
context_aggregator.assistant(), # Assistant spoken responses
]
)
task = PipelineTask(
pipeline,
PipelineParams(allow_interruptions=True),
)
if dialout_number:
logger.debug("dialout number detected; doing dialout")
# Configure some handlers for dialing out
@transport.event_handler("on_joined")
async def on_joined(transport, data):
logger.debug(f"Joined; starting dialout to: {dialout_number}")
await transport.start_dialout({"phoneNumber": dialout_number})
@transport.event_handler("on_dialout_connected")
async def on_dialout_connected(transport, data):
logger.debug(f"Dial-out connected: {data}")
@transport.event_handler("on_dialout_answered")
async def on_dialout_answered(transport, data):
logger.debug(f"Dial-out answered: {data}")
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):
await transport.capture_participant_transcription(participant["id"])
# unlike the dialin case, for the dialout case, the caller will speak first. Presumably
# they will answer the phone and say "Hello?" Since we've captured their transcript,
# That will put a frame into the pipeline and prompt an LLM completion, which is how the
# bot will then greet the user.
elif detect_voicemail:
logger.debug("Detect voicemail example. You can test this in example in Daily Prebuilt")
# For the voicemail detection case, we do not want the bot to answer the phone. We want it to wait for the voicemail
# machine to say something like 'Leave a message after the beep', or for the user to say 'Hello?'.
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):
await transport.capture_participant_transcription(participant["id"])
else:
logger.debug("no dialout number; assuming dialin")
# Different handlers for dialin
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):
await transport.capture_participant_transcription(participant["id"])
# For the dialin case, we want the bot to answer the phone and greet the user. We
# can prompt the bot to speak by putting the context into the pipeline.
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_participant_left")
async def on_participant_left(transport, participant, reason):
await task.cancel()
runner = PipelineRunner()
await runner.run(task)
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Pipecat Simple ChatBot")
parser.add_argument("-u", type=str, help="Room URL")
parser.add_argument("-t", type=str, help="Token")
parser.add_argument("-i", type=str, help="Call ID")
parser.add_argument("-d", type=str, help="Call Domain")
parser.add_argument("-v", action="store_true", help="Detect voicemail")
parser.add_argument("-o", type=str, help="Dialout number", default=None)
config = parser.parse_args()
asyncio.run(main(config.u, config.t, config.i, config.d, config.v, config.o))

View File

@@ -110,10 +110,15 @@ async def _create_daily_room(
# Spawn a new agent, and join the user session
# Note: this is mostly for demonstration purposes (refer to 'deployment' in docs)
print(f"Vendor: {vendor}")
if vendor == "daily":
bot_proc = f"python3 -m bot_daily -u {room.url} -t {token} -i {callId} -d {callDomain}{' -v' if detect_voicemail else ''}"
if dialoutNumber:
bot_proc += f" -o {dialoutNumber}"
elif vendor == "daily-gemini":
bot_proc = f"python3 -m bot_daily_gemini -u {room.url} -t {token} -i {callId} -d {callDomain}{' -v' if detect_voicemail else ''}"
if dialoutNumber:
bot_proc += f" -o {dialoutNumber}"
else:
bot_proc = f"python3 -m bot_twilio -u {room.url} -t {token} -i {callId} -s {room.config.sip_endpoint}"
@@ -201,6 +206,38 @@ async def daily_start_bot(request: Request) -> JSONResponse:
return JSONResponse({"room_url": room.url, "sipUri": room.config.sip_endpoint})
@app.post("/daily_gemini_start_bot")
async def daily_gemini_start_bot(request: Request) -> JSONResponse:
# The /daily_start_bot is invoked when a call is received on Daily's SIP URI
# daily_start_bot will create the room, put the call on hold until
# the bot and sip worker are ready. Daily will automatically
# forward the call to the SIP URi when dialin_ready fires.
# Use specified room URL, or create a new one if not specified
room_url = os.getenv("DAILY_SAMPLE_ROOM_URL", None)
# Get the dial-in properties from the request
try:
data = await request.json()
if "test" in data:
# Pass through any webhook checks
return JSONResponse({"test": True})
detect_voicemail = data.get("detectVoicemail", False)
callId = data.get("callId", None)
callDomain = data.get("callDomain", None)
dialoutNumber = data.get("dialoutNumber", None)
except Exception:
raise HTTPException(
status_code=500, detail="Missing properties 'callId', 'callDomain', or 'dialoutNumber'"
)
room: DailyRoomObject = await _create_daily_room(
room_url, callId, callDomain, dialoutNumber, "daily-gemini", detect_voicemail
)
# Grab a token for the user to join with
return JSONResponse({"room_url": room.url, "sipUri": room.config.sip_endpoint})
# ----------------- Main ----------------- #

161
examples/sentry-metrics/.gitignore vendored Normal file
View File

@@ -0,0 +1,161 @@
# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class
# C extensions
*.so
# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST
# PyInstaller
# Usually these files are written by a python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec
# Installer logs
pip-log.txt
pip-delete-this-directory.txt
# Unit test / coverage reports
htmlcov/
.tox/
.nox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*.cover
*.py,cover
.hypothesis/
.pytest_cache/
cover/
# Translations
*.mo
*.pot
# Django stuff:
*.log
local_settings.py
db.sqlite3
db.sqlite3-journal
# Flask stuff:
instance/
.webassets-cache
# Scrapy stuff:
.scrapy
# Sphinx documentation
docs/_build/
# PyBuilder
.pybuilder/
target/
# Jupyter Notebook
.ipynb_checkpoints
# IPython
profile_default/
ipython_config.py
# pyenv
# For a library or package, you might want to ignore these files since the code is
# intended to run in multiple environments; otherwise, check them in:
# .python-version
# pipenv
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
# However, in case of collaboration, if having platform-specific dependencies or dependencies
# having no cross-platform support, pipenv may install dependencies that don't work, or not
# install all needed dependencies.
#Pipfile.lock
# poetry
# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
# This is especially recommended for binary packages to ensure reproducibility, and is more
# commonly ignored for libraries.
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
#poetry.lock
# pdm
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
#pdm.lock
# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
# in version control.
# https://pdm.fming.dev/#use-with-ide
.pdm.toml
# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
__pypackages__/
# Celery stuff
celerybeat-schedule
celerybeat.pid
# SageMath parsed files
*.sage.py
# Environments
.env
.venv
env/
venv/
ENV/
env.bak/
venv.bak/
# Spyder project settings
.spyderproject
.spyproject
# Rope project settings
.ropeproject
# mkdocs documentation
/site
# mypy
.mypy_cache/
.dmypy.json
dmypy.json
# Pyre type checker
.pyre/
# pytype static type analyzer
.pytype/
# Cython debug symbols
cython_debug/
# PyCharm
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
# and can be added to the global gitignore or merged into this file. For a more nuclear
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
#.idea/
runpod.toml

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