chore(deps): update astral-sh/setup-uv action to v10

[renovate]

This PR contains the following updates:

Package	Type	Update	Change
astral-sh/setup-uv	action	major	v9.0.0 → v10.0.1

---

Release Notes

astral-sh/setup-uv (astral-sh/setup-uv)

v10.0.1: 🌈 Tolerate transient manifest timeouts

Compare Source

Changes

Thank you @​arguile- for making this action more resilient.

🐛 Bug fixes

• Tolerate transient manifest timeouts @​arguile- (#​1016)

🧰 Maintenance

• chore: update known checksums for 0.12.4 @​github-actions[bot] (#​1017)

📚 Documentation

• docs: update version references to v10.0.0 @​github-actions[bot] (#​1014)

v10.0.0: 🌈 Disable automatic caching for sensitive events and new QOL features

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Changes

Another breaking release, directly after v9.0.0 but we think the added security justifies that.

Extra security by default

If you use the default enable-cache: auto this will now DISABLE THE CACHE to protect against cache poisoning for the following events:

• pull_request_target
• workflow_run
• release

You can read the full reasoning in #​984

version: latest-known

- name: Install the latest version of uv known to setup-uv
  uses: astral-sh/setup-uv@v10.0.0
  with:
    version: "latest-known"

This will now install the latest version with a checksum that is known by this action. The known uv checksums are automatically updated but will take a release of this action to take effect. You won't be always using the latest & greatest but you will have an extra level of security.

Read python version from .tool-versions

- name: Install uv based on the version defined in .tool-versions and also set python
  uses: astral-sh/setup-uv@v10.0.0
  with:
    version-file: "pyproject.toml"

Will now also set the python version if it is defined in .tool-versions. You can read the details in the docs

🚨 Breaking changes

• Disable automatic caching for sensitive events @​eifinger (#​992)

🐛 Bug fixes

• Reject paths in .tool-versions @​eifinger (#​1007)

🚀 Enhancements

• Read Python version from .tool-versions @​eifinger (#​996)
• Add latest-known version selector @​eifinger (#​993)

🧰 Maintenance

• Require pull requests for Dependabot rollups @​eifinger (#​1005)
• ci: pin Alpine container image @​eifinger (#​995)
• chore: update known checksums for 0.12.3 @​github-actions[bot] (#​991)
• chore: update known checksums for 0.12.2 @​github-actions[bot] (#​985)
• chore: update known checksums for 0.12.1 @​github-actions[bot] (#​982)
• chore: update known checksums for 0.12.0 @​github-actions[bot] (#​981)
• chore: update known checksums for 0.11.31/0.11.32 @​github-actions[bot] (#​972)

📚 Documentation

• docs: update version references to v9.0.0 @​github-actions[bot] (#​971)

⬆️ Dependency updates

• chore(deps): roll up Dependabot updates @​eifinger (#​1013)
• chore(deps): roll up Dependabot updates @​eifinger (#​1004)
• chore(deps): roll up Dependabot updates @​eifinger (#​994)
• chore(deps): bump zizmorcore/zizmor-action from 0.5.7 to 0.6.0 @​dependabot[bot] (#​976)
• chore(deps): bump actions/checkout from 7.0.0 to 7.0.1 @​dependabot[bot] (#​980)

---

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---

This PR was generated by Mend Renovate. View the repository job log.

[devin-ai-integration]

✅ Devin Review: No Issues Found

Devin Review analyzed this PR and found no bugs or issues to report.

[github-actions]

STT Test Results

Status: ✗ Some tests failed

Metric	Count
✓ Passed	19
✗ Failed	6
× Errors	0
→ Skipped	16
▣ Total	41
⏱ Duration	219.9s

Failed Tests

• tests.test_stt::test_stream[livekit.plugins.fireworksai]

  self = <livekit.plugins.fireworksai.stt.SpeechStream object at 0x7f75b7301a30>
  
      async def __anext__(self) -> SpeechEvent:
          try:
  >           val = await self._event_aiter.__anext__()
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  E           StopAsyncIteration
  
  livekit-agents/livekit/agents/stt/stt.py:598: StopAsyncIteration
  
  During handling of the above exception, another exception occurred:
  
  stt_factory = <function parameter_factory.<locals>.<lambda> at 0x7f75a87d5120>
  request = <FixtureRequest for <Coroutine test_stream[livekit.plugins.fireworksai]>>
  
      @pytest.mark.usefixtures("job_process")
      @pytest.mark.parametrize("stt_factory", STTs + STREAM_ONLY_STTs)
      async def test_stream(stt_factory: Callable[[], STT], request):
          sample_rate = SAMPLE_RATE
          plugin_id = request.node.callspec.id.split("-")[0]
          frames, transcript, _ = await make_test_speech(chunk_duration_ms=10, sample_rate=sample_rate)
    
          # TODO: differentiate missing key vs other errors
          try:
              stt_instance: STT = stt_factory()
          except ValueError as e:
              pytest.skip(f"{plugin_id}: {e}")
    
          async with stt_instance as stt:
              label = f"{stt.model}@{stt.provider}"
              if not stt.capabilities.streaming:
                  pytest.skip(f"{label} does not support streaming")
    
              for attempt in range(MAX_RETRIES):
                  try:
                      state = {"closing": False}
    
                      async def _stream_input(
                          frames: list[rtc.AudioFrame], stream: RecognizeStream, state: dict = state
                      ):
                          for frame in frames:
                              stream.push_frame(frame)
                              await asyncio.sleep(0.005)
    
                          stream.end_input()
                          state["closing"] = True
    
                      async def _stream_output(stream: RecognizeStream, state: dict = state):
  

• tests.test_stt::test_stream[livekit.plugins.nvidia]

  stt_factory = <function parameter_factory.<locals>.<lambda> at 0x7f815862a0c0>
  request = <FixtureRequest for <Coroutine test_stream[livekit.plugins.nvidia]>>
  
      @pytest.mark.usefixtures("job_process")
      @pytest.mark.parametrize("stt_factory", STTs + STREAM_ONLY_STTs)
      async def test_stream(stt_factory: Callable[[], STT], request):
          sample_rate = SAMPLE_RATE
          plugin_id = request.node.callspec.id.split("-")[0]
          frames, transcript, _ = await make_test_speech(chunk_duration_ms=10, sample_rate=sample_rate)
    
          # TODO: differentiate missing key vs other errors
          try:
              stt_instance: STT = stt_factory()
          except ValueError as e:
              pytest.skip(f"{plugin_id}: {e}")
    
          async with stt_instance as stt:
              label = f"{stt.model}@{stt.provider}"
              if not stt.capabilities.streaming:
                  pytest.skip(f"{label} does not support streaming")
    
              for attempt in range(MAX_RETRIES):
                  try:
                      state = {"closing": False}
    
                      async def _stream_input(
                          frames: list[rtc.AudioFrame], stream: RecognizeStream, state: dict = state
                      ):
                          for frame in frames:
                              stream.push_frame(frame)
                              await asyncio.sleep(0.005)
    
                          stream.end_input()
                          state["closing"] = True
    
                      async def _stream_output(stream: RecognizeStream, state: dict = state):
                          text = ""
                          # make sure the events are sent in the right order
                          recv_start, recv_end = False, True
                          start_time = time.time()
                          got_final_transcript = False
                          sos_count, final_count = 0, 0
    
                          async for event in stream:
                              if event.ty
  

• tests.test_stt::test_stream[livekit.plugins.assemblyai]

  stt_factory = <function parameter_factory.<locals>.<lambda> at 0x7f631194c4a0>
  request = <FixtureRequest for <Coroutine test_stream[livekit.plugins.assemblyai]>>
  
      @pytest.mark.usefixtures("job_process")
      @pytest.mark.parametrize("stt_factory", STTs + STREAM_ONLY_STTs)
      async def test_stream(stt_factory: Callable[[], STT], request):
          sample_rate = SAMPLE_RATE
          plugin_id = request.node.callspec.id.split("-")[0]
          frames, transcript, _ = await make_test_speech(chunk_duration_ms=10, sample_rate=sample_rate)
    
          # TODO: differentiate missing key vs other errors
          try:
              stt_instance: STT = stt_factory()
          except ValueError as e:
              pytest.skip(f"{plugin_id}: {e}")
    
          async with stt_instance as stt:
              label = f"{stt.model}@{stt.provider}"
              if not stt.capabilities.streaming:
                  pytest.skip(f"{label} does not support streaming")
    
              for attempt in range(MAX_RETRIES):
                  try:
                      state = {"closing": False}
    
                      async def _stream_input(
                          frames: list[rtc.AudioFrame], stream: RecognizeStream, state: dict = state
                      ):
                          for frame in frames:
                              stream.push_frame(frame)
                              await asyncio.sleep(0.005)
    
                          stream.end_input()
                          state["closing"] = True
    
                      async def _stream_output(stream: RecognizeStream, state: dict = state):
                          text = ""
                          # make sure the events are sent in the right order
                          recv_start, recv_end = False, True
                          start_time = time.time()
                          got_final_transcript = False
                          sos_count, final_count = 0, 0
    
                          async for event in stream:
                              if even
  

• tests.test_stt::test_stream[livekit.plugins.soniox]

  stt_factory = <function parameter_factory.<locals>.<lambda> at 0x7f75a87d5580>
  request = <FixtureRequest for <Coroutine test_stream[livekit.plugins.soniox]>>
  
      @pytest.mark.usefixtures("job_process")
      @pytest.mark.parametrize("stt_factory", STTs + STREAM_ONLY_STTs)
      async def test_stream(stt_factory: Callable[[], STT], request):
          sample_rate = SAMPLE_RATE
          plugin_id = request.node.callspec.id.split("-")[0]
          frames, transcript, _ = await make_test_speech(chunk_duration_ms=10, sample_rate=sample_rate)
    
          # TODO: differentiate missing key vs other errors
          try:
              stt_instance: STT = stt_factory()
          except ValueError as e:
              pytest.skip(f"{plugin_id}: {e}")
    
          async with stt_instance as stt:
              label = f"{stt.model}@{stt.provider}"
              if not stt.capabilities.streaming:
                  pytest.skip(f"{label} does not support streaming")
    
              for attempt in range(MAX_RETRIES):
                  try:
                      state = {"closing": False}
    
                      async def _stream_input(
                          frames: list[rtc.AudioFrame], stream: RecognizeStream, state: dict = state
                      ):
                          for frame in frames:
                              stream.push_frame(frame)
                              await asyncio.sleep(0.005)
    
                          stream.end_input()
                          state["closing"] = True
    
                      async def _stream_output(stream: RecognizeStream, state: dict = state):
                          text = ""
                          # make sure the events are sent in the right order
                          recv_start, recv_end = False, True
                          start_time = time.time()
                          got_final_transcript = False
                          sos_count, final_count = 0, 0
    
                          async for event in stream:
                              if event.ty
  

• tests.test_stt::test_stream[livekit.agents.inference]

  stt_factory = <function parameter_factory.<locals>.<lambda> at 0x7f815862a3e0>
  request = <FixtureRequest for <Coroutine test_stream[livekit.agents.inference]>>
  
      @pytest.mark.usefixtures("job_process")
      @pytest.mark.parametrize("stt_factory", STTs + STREAM_ONLY_STTs)
      async def test_stream(stt_factory: Callable[[], STT], request):
          sample_rate = SAMPLE_RATE
          plugin_id = request.node.callspec.id.split("-")[0]
          frames, transcript, _ = await make_test_speech(chunk_duration_ms=10, sample_rate=sample_rate)
    
          # TODO: differentiate missing key vs other errors
          try:
              stt_instance: STT = stt_factory()
          except ValueError as e:
              pytest.skip(f"{plugin_id}: {e}")
    
          async with stt_instance as stt:
              label = f"{stt.model}@{stt.provider}"
              if not stt.capabilities.streaming:
                  pytest.skip(f"{label} does not support streaming")
    
              for attempt in range(MAX_RETRIES):
                  try:
                      state = {"closing": False}
    
                      async def _stream_input(
                          frames: list[rtc.AudioFrame], stream: RecognizeStream, state: dict = state
                      ):
                          for frame in frames:
                              stream.push_frame(frame)
                              await asyncio.sleep(0.005)
    
                          stream.end_input()
                          state["closing"] = True
    
                      async def _stream_output(stream: RecognizeStream, state: dict = state):
                          text = ""
                          # make sure the events are sent in the right order
                          recv_start, recv_end = False, True
                          start_time = time.time()
                          got_final_transcript = False
                          sos_count, final_count = 0, 0
    
                          async for event in stream:
                              if event.
  

• tests.test_stt::test_stream[livekit.plugins.gradium.STT]

  self = <livekit.plugins.gradium.stt.SpeechStream object at 0x7f816719b8f0>
  
      async def _main_task(self) -> None:
          max_retries = self._conn_options.max_retry
          # we need to record last start time for each run/connection
          # so that returned transcripts can have linear timestamps
          last_start_time = time.time()
    
          while self._num_retries <= max_retries:
              try:
                  self._start_time_offset += time.time() - last_start_time
                  self._start_time = time.time()
                  last_start_time = time.time()
  >               return await self._run()
                         ^^^^^^^^^^^^^^^^^
  
  livekit-agents/livekit/agents/stt/stt.py:476: 
  _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
  
  self = <livekit.plugins.gradium.stt.SpeechStream object at 0x7f816719b8f0>
  
      async def _run(self) -> None:
          """
          Run a single websocket connection to Gradium and make sure to reconnect
          when something went wrong.
          """
    
          closing_ws = False
    
          async def send_task(ws: aiohttp.ClientWebSocketResponse) -> None:
              samples_per_buffer = 1920
    
              audio_bstream = utils.audio.AudioByteStream(
                  sample_rate=self._opts.sample_rate,
                  num_channels=1,
                  samples_per_channel=samples_per_buffer,
              )
    
              async for data in self._input_ch:
                  if isinstance(data, self._FlushSentinel):
                      frames = audio_bstream.flush()
                  else:
                      frames = audio_bstream.write(data.data.tobytes())
    
                  for frame in frames:
                      if len(frame.data) % 2 != 0:
                          logger.warning("Frame data size not aligned to int16 (multiple of 2)")
    
                      audio_data = base64.b64encode(frame.data.tobytes()).decode("utf-8")
                      audio_msg = {
                          "type": "a
  

Skipped Tests

Test	Reason
tests.test_stt::test_recognize[livekit.plugins.assemblyai]	universal-3-5-pro@AssemblyAI does not support batch recognition
tests.test_stt::test_recognize[livekit.plugins.speechmatics]	enhanced@Speechmatics does not support batch recognition
tests.test_stt::test_recognize[livekit.plugins.fireworksai]	unknown@FireworksAI does not support batch recognition
tests.test_stt::test_recognize[livekit.plugins.cartesia]	ink-2@Cartesia does not support batch recognition
tests.test_stt::test_recognize[livekit.plugins.soniox]	stt-rt-v5@Soniox does not support batch recognition
tests.test_stt::test_recognize[livekit.plugins.nvidia]	unknown@unknown does not support batch recognition
tests.test_stt::test_recognize[livekit.plugins.gradium.STT]	unknown@Gradium does not support batch recognition
tests.test_stt::test_recognize[livekit.agents.inference]	unknown@livekit does not support batch recognition
tests.test_stt::test_recognize[livekit.plugins.azure]	unknown@Azure STT does not support batch recognition
tests.test_stt::test_recognize[livekit.plugins.aws]	unknown@Amazon Transcribe does not support batch recognition
tests.test_stt::test_stream[livekit.plugins.elevenlabs]	scribe_v1@ElevenLabs does not support streaming
tests.test_stt::test_recognize[livekit.plugins.cartesia._legacy]	ink-whisper@Cartesia does not support batch recognition
tests.test_stt::test_recognize[livekit.plugins.deepgram.STTv2]	flux-general-en@Deepgram does not support batch recognition
tests.test_stt::test_stream[livekit.plugins.mistralai]	voxtral-mini-latest@MistralAI does not support streaming
tests.test_stt::test_stream[livekit.plugins.fal]	Wizper@Fal does not support streaming
tests.test_stt::test_stream[livekit.plugins.openai]	gpt-4o-mini-transcribe@api.openai.com does not support streaming

---

Triggered by workflow run #3753