selfhostyourtech/reflector
2
0
Fork 0
mirror of https://github.com/Monadical-SAS/reflector.git synced 2026-02-04 09:56:47 +00:00
Code Issues Packages Projects Releases Wiki Activity

feat: modal padding (#837)

Browse Source 
* Add Modal backend for audio padding

- Create reflector_padding.py Modal deployment (CPU-based)
- Add PaddingWorkflow with conditional Modal/local backend
- Update deploy-all.sh to include padding deployment

---------

Co-authored-by: Igor Loskutov <igor.loskutoff@gmail.com>
This commit is contained in:
Igor Monadical
2026-01-30 13:11:51 -05:00
committed by GitHub
parent 2ca624f052
commit 7fde64e252
11 changed files with 625 additions and 82 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
server/pyproject.toml
View File

@@ -8,7 +8,7 @@ readme = "README.md"
dependencies = [
"aiohttp>=3.9.0",
"aiohttp-cors>=0.7.0",
"av>=10.0.0",
"av>=15.0.0",
"requests>=2.31.0",
"aiortc>=1.5.0",
"sortedcontainers>=2.4.0",

2
server/reflector/hatchet/constants.py
View File

@@ -37,5 +37,5 @@ LLM_RATE_LIMIT_PER_SECOND = 10
TIMEOUT_SHORT = 60 # Quick operations: API calls, DB updates
TIMEOUT_MEDIUM = 120 # Single LLM calls, waveform generation
TIMEOUT_LONG = 180 # Action items (larger context LLM)
TIMEOUT_AUDIO = 300 # Audio processing: padding, mixdown
TIMEOUT_AUDIO = 720 # Audio processing: padding, mixdown
TIMEOUT_HEAVY = 600 # Transcription, fan-out LLM tasks

165
server/reflector/hatchet/workflows/padding_workflow.py Normal file
View File

@@ -0,0 +1,165 @@
"""
Hatchet child workflow: PaddingWorkflow
Handles individual audio track padding via Modal.com backend.
"""
from datetime import timedelta
import av
from hatchet_sdk import Context
from pydantic import BaseModel
from reflector.hatchet.client import HatchetClientManager
from reflector.hatchet.constants import TIMEOUT_AUDIO
from reflector.hatchet.workflows.models import PadTrackResult
from reflector.logger import logger
from reflector.utils.audio_constants import PRESIGNED_URL_EXPIRATION_SECONDS
from reflector.utils.audio_padding import extract_stream_start_time_from_container
class PaddingInput(BaseModel):
"""Input for individual track padding."""
track_index: int
s3_key: str
bucket_name: str
transcript_id: str
hatchet = HatchetClientManager.get_client()
padding_workflow = hatchet.workflow(
name="PaddingWorkflow", input_validator=PaddingInput
)
@padding_workflow.task(execution_timeout=timedelta(seconds=TIMEOUT_AUDIO), retries=3)
async def pad_track(input: PaddingInput, ctx: Context) -> PadTrackResult:
"""Pad audio track with silence based on WebM container start_time."""
ctx.log(f"pad_track: track {input.track_index}, s3_key={input.s3_key}")
logger.info(
"[Hatchet] pad_track",
track_index=input.track_index,
s3_key=input.s3_key,
transcript_id=input.transcript_id,
)
try:
# Create fresh storage instance to avoid aioboto3 fork issues
from reflector.settings import settings # noqa: PLC0415
from reflector.storage.storage_aws import AwsStorage # noqa: PLC0415
storage = AwsStorage(
aws_bucket_name=settings.TRANSCRIPT_STORAGE_AWS_BUCKET_NAME,
aws_region=settings.TRANSCRIPT_STORAGE_AWS_REGION,
aws_access_key_id=settings.TRANSCRIPT_STORAGE_AWS_ACCESS_KEY_ID,
aws_secret_access_key=settings.TRANSCRIPT_STORAGE_AWS_SECRET_ACCESS_KEY,
)
source_url = await storage.get_file_url(
input.s3_key,
operation="get_object",
expires_in=PRESIGNED_URL_EXPIRATION_SECONDS,
bucket=input.bucket_name,
)
# Extract start_time to determine if padding needed
with av.open(source_url) as in_container:
if in_container.duration:
try:
duration = timedelta(seconds=in_container.duration // 1_000_000)
ctx.log(
f"pad_track: track {input.track_index}, duration={duration}"
)
except (ValueError, TypeError, OverflowError) as e:
ctx.log(
f"pad_track: track {input.track_index}, duration error: {str(e)}"
)
start_time_seconds = extract_stream_start_time_from_container(
in_container, input.track_index, logger=logger
)
if start_time_seconds <= 0:
logger.info(
f"Track {input.track_index} requires no padding",
track_index=input.track_index,
)
return PadTrackResult(
padded_key=input.s3_key,
bucket_name=input.bucket_name,
size=0,
track_index=input.track_index,
)
storage_path = f"file_pipeline_hatchet/{input.transcript_id}/tracks/padded_{input.track_index}.webm"
# Presign PUT URL for output (Modal will upload directly)
output_url = await storage.get_file_url(
storage_path,
operation="put_object",
expires_in=PRESIGNED_URL_EXPIRATION_SECONDS,
)
import httpx # noqa: PLC0415
from reflector.processors.audio_padding_modal import ( # noqa: PLC0415
AudioPaddingModalProcessor,
)
try:
processor = AudioPaddingModalProcessor()
result = await processor.pad_track(
track_url=source_url,
output_url=output_url,
start_time_seconds=start_time_seconds,
track_index=input.track_index,
)
file_size = result.size
ctx.log(f"pad_track: Modal returned size={file_size}")
except httpx.HTTPStatusError as e:
error_detail = e.response.text if hasattr(e.response, "text") else str(e)
logger.error(
"[Hatchet] Modal padding HTTP error",
transcript_id=input.transcript_id,
track_index=input.track_index,
status_code=e.response.status_code if hasattr(e, "response") else None,
error=error_detail,
exc_info=True,
)
raise Exception(
f"Modal padding failed: HTTP {e.response.status_code}"
) from e
except httpx.TimeoutException as e:
logger.error(
"[Hatchet] Modal padding timeout",
transcript_id=input.transcript_id,
track_index=input.track_index,
error=str(e),
exc_info=True,
)
raise Exception("Modal padding timeout") from e
logger.info(
"[Hatchet] pad_track complete",
track_index=input.track_index,
padded_key=storage_path,
)
return PadTrackResult(
padded_key=storage_path,
bucket_name=None, # None = use default transcript storage bucket
size=file_size,
track_index=input.track_index,
)
except Exception as e:
logger.error(
"[Hatchet] pad_track failed",
transcript_id=input.transcript_id,
track_index=input.track_index,
error=str(e),
exc_info=True,
)
raise

86
server/reflector/hatchet/workflows/track_processing.py
View File

@@ -14,9 +14,7 @@ Hatchet workers run in forked processes; fresh imports per task ensure
storage/DB connections are not shared across forks.
"""
import tempfile
from datetime import timedelta
from pathlib import Path
import av
from hatchet_sdk import Context
@@ -27,10 +25,7 @@ from reflector.hatchet.constants import TIMEOUT_AUDIO, TIMEOUT_HEAVY
from reflector.hatchet.workflows.models import PadTrackResult, TranscribeTrackResult
from reflector.logger import logger
from reflector.utils.audio_constants import PRESIGNED_URL_EXPIRATION_SECONDS
from reflector.utils.audio_padding import (
apply_audio_padding_to_file,
extract_stream_start_time_from_container,
)
from reflector.utils.audio_padding import extract_stream_start_time_from_container
class TrackInput(BaseModel):
@@ -83,63 +78,44 @@ async def pad_track(input: TrackInput, ctx: Context) -> PadTrackResult:
)
with av.open(source_url) as in_container:
if in_container.duration:
try:
duration = timedelta(seconds=in_container.duration // 1_000_000)
ctx.log(
f"pad_track: track {input.track_index}, duration={duration}"
)
except Exception:
ctx.log(f"pad_track: track {input.track_index}, duration=ERROR")
start_time_seconds = extract_stream_start_time_from_container(
in_container, input.track_index, logger=logger
)
# If no padding needed, return original S3 key
if start_time_seconds <= 0:
logger.info(
f"Track {input.track_index} requires no padding",
track_index=input.track_index,
)
return PadTrackResult(
padded_key=input.s3_key,
bucket_name=input.bucket_name,
size=0,
track_index=input.track_index,
)
# If no padding needed, return original S3 key
if start_time_seconds <= 0:
logger.info(
f"Track {input.track_index} requires no padding",
track_index=input.track_index,
)
return PadTrackResult(
padded_key=input.s3_key,
bucket_name=input.bucket_name,
size=0,
track_index=input.track_index,
)
with tempfile.NamedTemporaryFile(suffix=".webm", delete=False) as temp_file:
temp_path = temp_file.name
storage_path = f"file_pipeline_hatchet/{input.transcript_id}/tracks/padded_{input.track_index}.webm"
try:
apply_audio_padding_to_file(
in_container,
temp_path,
start_time_seconds,
input.track_index,
logger=logger,
)
# Presign PUT URL for output (Modal uploads directly)
output_url = await storage.get_file_url(
storage_path,
operation="put_object",
expires_in=PRESIGNED_URL_EXPIRATION_SECONDS,
)
file_size = Path(temp_path).stat().st_size
storage_path = f"file_pipeline_hatchet/{input.transcript_id}/tracks/padded_{input.track_index}.webm"
from reflector.processors.audio_padding_modal import ( # noqa: PLC0415
AudioPaddingModalProcessor,
)
logger.info(
f"About to upload padded track",
key=storage_path,
size=file_size,
)
with open(temp_path, "rb") as padded_file:
await storage.put_file(storage_path, padded_file)
logger.info(
f"Uploaded padded track to S3",
key=storage_path,
size=file_size,
)
finally:
Path(temp_path).unlink(missing_ok=True)
processor = AudioPaddingModalProcessor()
result = await processor.pad_track(
track_url=source_url,
output_url=output_url,
start_time_seconds=start_time_seconds,
track_index=input.track_index,
)
file_size = result.size
ctx.log(f"pad_track complete: track {input.track_index} -> {storage_path}")
logger.info(

112
server/reflector/processors/audio_padding_modal.py Normal file
View File

@@ -0,0 +1,112 @@
"""
Modal.com backend for audio padding.
"""
import asyncio
import os
import httpx
from pydantic import BaseModel
from reflector.logger import logger
class PaddingResponse(BaseModel):
size: int
cancelled: bool = False
class AudioPaddingModalProcessor:
"""Audio padding processor using Modal.com CPU backend via HTTP."""
def __init__(
self, padding_url: str | None = None, modal_api_key: str | None = None
):
self.padding_url = padding_url or os.getenv("PADDING_URL")
if not self.padding_url:
raise ValueError(
"PADDING_URL required to use AudioPaddingModalProcessor. "
"Set PADDING_URL environment variable or pass padding_url parameter."
)
self.modal_api_key = modal_api_key or os.getenv("MODAL_API_KEY")
async def pad_track(
self,
track_url: str,
output_url: str,
start_time_seconds: float,
track_index: int,
) -> PaddingResponse:
"""Pad audio track with silence via Modal backend.
Args:
track_url: Presigned GET URL for source audio track
output_url: Presigned PUT URL for output WebM
start_time_seconds: Amount of silence to prepend
track_index: Track index for logging
"""
if not track_url:
raise ValueError("track_url cannot be empty")
if start_time_seconds <= 0:
raise ValueError(
f"start_time_seconds must be positive, got {start_time_seconds}"
)
log = logger.bind(track_index=track_index, padding_seconds=start_time_seconds)
log.info("Sending Modal padding HTTP request")
url = f"{self.padding_url}/pad"
headers = {}
if self.modal_api_key:
headers["Authorization"] = f"Bearer {self.modal_api_key}"
try:
async with httpx.AsyncClient() as client:
response = await client.post(
url,
headers=headers,
json={
"track_url": track_url,
"output_url": output_url,
"start_time_seconds": start_time_seconds,
"track_index": track_index,
},
follow_redirects=True,
)
if response.status_code != 200:
error_body = response.text
log.error(
"Modal padding API error",
status_code=response.status_code,
error_body=error_body,
)
response.raise_for_status()
result = response.json()
# Check if work was cancelled
if result.get("cancelled"):
log.warning("Modal padding was cancelled by disconnect detection")
raise asyncio.CancelledError(
"Padding cancelled due to client disconnect"
)
log.info("Modal padding complete", size=result["size"])
return PaddingResponse(**result)
except asyncio.CancelledError:
log.warning(
"Modal padding cancelled (Hatchet timeout, disconnect detected on Modal side)"
)
raise
except httpx.TimeoutException as e:
log.error("Modal padding timeout", error=str(e), exc_info=True)
raise Exception(f"Modal padding timeout: {e}") from e
except httpx.HTTPStatusError as e:
log.error("Modal padding HTTP error", error=str(e), exc_info=True)
raise Exception(f"Modal padding HTTP error: {e}") from e
except Exception as e:
log.error("Modal padding unexpected error", error=str(e), exc_info=True)
raise

4
server/reflector/settings.py
View File

@@ -98,6 +98,10 @@ class Settings(BaseSettings):
# Diarization: local pyannote.audio
DIARIZATION_PYANNOTE_AUTH_TOKEN: str | None = None
# Audio Padding (Modal.com backend)
PADDING_URL: str | None = None
PADDING_MODAL_API_KEY: str | None = None
# Sentry
SENTRY_DSN: str | None = None

2
server/reflector/utils/audio_constants.py
View File

@@ -5,7 +5,9 @@ Used by both Hatchet workflows and Celery pipelines for consistent audio encodin
"""
# Opus codec settings
# ref B0F71CE8-FC59-4AA5-8414-DAFB836DB711
OPUS_STANDARD_SAMPLE_RATE = 48000
# ref B0F71CE8-FC59-4AA5-8414-DAFB836DB711
OPUS_DEFAULT_BIT_RATE = 128000 # 128kbps for good speech quality
# S3 presigned URL expiration

45
server/uv.lock generated
View File

@@ -159,21 +159,20 @@ wheels = [
[[package]]
name = "aiortc"
version = "1.13.0"
version = "1.14.0"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "aioice" },
{ name = "av" },
{ name = "cffi" },
{ name = "cryptography" },
{ name = "google-crc32c" },
{ name = "pyee" },
{ name = "pylibsrtp" },
{ name = "pyopenssl" },
]
sdist = { url = "https://files.pythonhosted.org/packages/62/03/bc947d74c548e0c17cf94e5d5bdacaed0ee9e5b2bb7b8b8cf1ac7a7c01ec/aiortc-1.13.0.tar.gz", hash = "sha256:5d209975c22d0910fb5a0f0e2caa828f2da966c53580f7c7170ac3a16a871620", size = 1179894 }
sdist = { url = "https://files.pythonhosted.org/packages/51/9c/4e027bfe0195de0442da301e2389329496745d40ae44d2d7c4571c4290ce/aiortc-1.14.0.tar.gz", hash = "sha256:adc8a67ace10a085721e588e06a00358ed8eaf5f6b62f0a95358ff45628dd762", size = 1180864 }
wheels = [
{ url = "https://files.pythonhosted.org/packages/87/29/765633cab5f1888890f5f172d1d53009b9b14e079cdfa01a62d9896a9ea9/aiortc-1.13.0-py3-none-any.whl", hash = "sha256:9ccccec98796f6a96bd1c3dd437a06da7e0f57521c96bd56e4b965a91b03a0a0", size = 92910 },
{ url = "https://files.pythonhosted.org/packages/57/ab/31646a49209568cde3b97eeade0d28bb78b400e6645c56422c101df68932/aiortc-1.14.0-py3-none-any.whl", hash = "sha256:4b244d7e482f4e1f67e685b3468269628eca1ec91fa5b329ab517738cfca086e", size = 93183 },
]
[[package]]
@@ -327,28 +326,24 @@ wheels = [
[[package]]
name = "av"
version = "14.4.0"
version = "16.1.0"
source = { registry = "https://pypi.org/simple" }
sdist = { url = "https://files.pythonhosted.org/packages/86/f6/0b473dab52dfdea05f28f3578b1c56b6c796ce85e76951bab7c4e38d5a74/av-14.4.0.tar.gz", hash = "sha256:3ecbf803a7fdf67229c0edada0830d6bfaea4d10bfb24f0c3f4e607cd1064b42", size = 3892203 }
sdist = { url = "https://files.pythonhosted.org/packages/78/cd/3a83ffbc3cc25b39721d174487fb0d51a76582f4a1703f98e46170ce83d4/av-16.1.0.tar.gz", hash = "sha256:a094b4fd87a3721dacf02794d3d2c82b8d712c85b9534437e82a8a978c175ffd", size = 4285203 }
wheels = [
{ url = "https://files.pythonhosted.org/packages/18/8a/d57418b686ffd05fabd5a0a9cfa97e63b38c35d7101af00e87c51c8cc43c/av-14.4.0-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:5b21d5586a88b9fce0ab78e26bd1c38f8642f8e2aad5b35e619f4d202217c701", size = 19965048 },
{ url = "https://files.pythonhosted.org/packages/f5/aa/3f878b0301efe587e9b07bb773dd6b47ef44ca09a3cffb4af50c08a170f3/av-14.4.0-cp311-cp311-macosx_12_0_x86_64.whl", hash = "sha256:cf8762d90b0f94a20c9f6e25a94f1757db5a256707964dfd0b1d4403e7a16835", size = 23750064 },
{ url = "https://files.pythonhosted.org/packages/9a/b4/6fe94a31f9ed3a927daa72df67c7151968587106f30f9f8fcd792b186633/av-14.4.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c0ac9f08920c7bbe0795319689d901e27cb3d7870b9a0acae3f26fc9daa801a6", size = 33648775 },
{ url = "https://files.pythonhosted.org/packages/6c/f3/7f3130753521d779450c935aec3f4beefc8d4645471159f27b54e896470c/av-14.4.0-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a56d9ad2afdb638ec0404e962dc570960aae7e08ae331ad7ff70fbe99a6cf40e", size = 32216915 },
{ url = "https://files.pythonhosted.org/packages/f8/9a/8ffabfcafb42154b4b3a67d63f9b69e68fa8c34cb39ddd5cb813dd049ed4/av-14.4.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6bed513cbcb3437d0ae47743edc1f5b4a113c0b66cdd4e1aafc533abf5b2fbf2", size = 35287279 },
{ url = "https://files.pythonhosted.org/packages/ad/11/7023ba0a2ca94a57aedf3114ab8cfcecb0819b50c30982a4c5be4d31df41/av-14.4.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:d030c2d3647931e53d51f2f6e0fcf465263e7acf9ec6e4faa8dbfc77975318c3", size = 36294683 },
{ url = "https://files.pythonhosted.org/packages/3d/fa/b8ac9636bd5034e2b899354468bef9f4dadb067420a16d8a493a514b7817/av-14.4.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:1cc21582a4f606271d8c2036ec7a6247df0831050306c55cf8a905701d0f0474", size = 34552391 },
{ url = "https://files.pythonhosted.org/packages/fb/29/0db48079c207d1cba7a2783896db5aec3816e17de55942262c244dffbc0f/av-14.4.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:ce7c9cd452153d36f1b1478f904ed5f9ab191d76db873bdd3a597193290805d4", size = 37265250 },
{ url = "https://files.pythonhosted.org/packages/1c/55/715858c3feb7efa4d667ce83a829c8e6ee3862e297fb2b568da3f968639d/av-14.4.0-cp311-cp311-win_amd64.whl", hash = "sha256:fd261e31cc6b43ca722f80656c39934199d8f2eb391e0147e704b6226acebc29", size = 27925845 },
{ url = "https://files.pythonhosted.org/packages/a6/75/b8641653780336c90ba89e5352cac0afa6256a86a150c7703c0b38851c6d/av-14.4.0-cp312-cp312-macosx_12_0_arm64.whl", hash = "sha256:a53e682b239dd23b4e3bc9568cfb1168fc629ab01925fdb2e7556eb426339e94", size = 19954125 },
{ url = "https://files.pythonhosted.org/packages/99/e6/37fe6fa5853a48d54d749526365780a63a4bc530be6abf2115e3a21e292a/av-14.4.0-cp312-cp312-macosx_12_0_x86_64.whl", hash = "sha256:5aa0b901751a32703fa938d2155d56ce3faf3630e4a48d238b35d2f7e49e5395", size = 23751479 },
{ url = "https://files.pythonhosted.org/packages/f7/75/9a5f0e6bda5f513b62bafd1cff2b495441a8b07ab7fb7b8e62f0c0d1683f/av-14.4.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a3b316fed3597675fe2aacfed34e25fc9d5bb0196dc8c0b014ae5ed4adda48de", size = 33801401 },
{ url = "https://files.pythonhosted.org/packages/6a/c9/e4df32a2ad1cb7f3a112d0ed610c5e43c89da80b63c60d60e3dc23793ec0/av-14.4.0-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a587b5c5014c3c0e16143a0f8d99874e46b5d0c50db6111aa0b54206b5687c81", size = 32364330 },
{ url = "https://files.pythonhosted.org/packages/ca/f0/64e7444a41817fde49a07d0239c033f7e9280bec4a4bb4784f5c79af95e6/av-14.4.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:10d53f75e8ac1ec8877a551c0db32a83c0aaeae719d05285281eaaba211bbc30", size = 35519508 },
{ url = "https://files.pythonhosted.org/packages/c2/a8/a370099daa9033a3b6f9b9bd815304b3d8396907a14d09845f27467ba138/av-14.4.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:c8558cfde79dd8fc92d97c70e0f0fa8c94c7a66f68ae73afdf58598f0fe5e10d", size = 36448593 },
{ url = "https://files.pythonhosted.org/packages/27/bb/edb6ceff8fa7259cb6330c51dbfbc98dd1912bd6eb5f7bc05a4bb14a9d6e/av-14.4.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:455b6410dea0ab2d30234ffb28df7d62ca3cdf10708528e247bec3a4cdcced09", size = 34701485 },
{ url = "https://files.pythonhosted.org/packages/a7/8a/957da1f581aa1faa9a5dfa8b47ca955edb47f2b76b949950933b457bfa1d/av-14.4.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:1661efbe9d975f927b8512d654704223d936f39016fad2ddab00aee7c40f412c", size = 37521981 },
{ url = "https://files.pythonhosted.org/packages/28/76/3f1cf0568592f100fd68eb40ed8c491ce95ca3c1378cc2d4c1f6d1bd295d/av-14.4.0-cp312-cp312-win_amd64.whl", hash = "sha256:fbbeef1f421a3461086853d6464ad5526b56ffe8ccb0ab3fd0a1f121dfbf26ad", size = 27925944 },
{ url = "https://files.pythonhosted.org/packages/48/d0/b71b65d1b36520dcb8291a2307d98b7fc12329a45614a303ff92ada4d723/av-16.1.0-cp311-cp311-macosx_11_0_x86_64.whl", hash = "sha256:e88ad64ee9d2b9c4c5d891f16c22ae78e725188b8926eb88187538d9dd0b232f", size = 26927747 },
{ url = "https://files.pythonhosted.org/packages/2f/79/720a5a6ccdee06eafa211b945b0a450e3a0b8fc3d12922f0f3c454d870d2/av-16.1.0-cp311-cp311-macosx_14_0_arm64.whl", hash = "sha256:cb296073fa6935724de72593800ba86ae49ed48af03960a4aee34f8a611f442b", size = 21492232 },
{ url = "https://files.pythonhosted.org/packages/8e/4f/a1ba8d922f2f6d1a3d52419463ef26dd6c4d43ee364164a71b424b5ae204/av-16.1.0-cp311-cp311-manylinux_2_28_aarch64.whl", hash = "sha256:720edd4d25aa73723c1532bb0597806d7b9af5ee34fc02358782c358cfe2f879", size = 39291737 },
{ url = "https://files.pythonhosted.org/packages/1a/31/fc62b9fe8738d2693e18d99f040b219e26e8df894c10d065f27c6b4f07e3/av-16.1.0-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:c7f2bc703d0df260a1fdf4de4253c7f5500ca9fc57772ea241b0cb241bcf972e", size = 40846822 },
{ url = "https://files.pythonhosted.org/packages/53/10/ab446583dbce730000e8e6beec6ec3c2753e628c7f78f334a35cad0317f4/av-16.1.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:d69c393809babada7d54964d56099e4b30a3e1f8b5736ca5e27bd7be0e0f3c83", size = 40675604 },
{ url = "https://files.pythonhosted.org/packages/31/d7/1003be685277005f6d63fd9e64904ee222fe1f7a0ea70af313468bb597db/av-16.1.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:441892be28582356d53f282873c5a951592daaf71642c7f20165e3ddcb0b4c63", size = 42015955 },
{ url = "https://files.pythonhosted.org/packages/2f/4a/fa2a38ee9306bf4579f556f94ecbc757520652eb91294d2a99c7cf7623b9/av-16.1.0-cp311-cp311-win_amd64.whl", hash = "sha256:273a3e32de64819e4a1cd96341824299fe06f70c46f2288b5dc4173944f0fd62", size = 31750339 },
{ url = "https://files.pythonhosted.org/packages/9c/84/2535f55edcd426cebec02eb37b811b1b0c163f26b8d3f53b059e2ec32665/av-16.1.0-cp312-cp312-macosx_11_0_x86_64.whl", hash = "sha256:640f57b93f927fba8689f6966c956737ee95388a91bd0b8c8b5e0481f73513d6", size = 26945785 },
{ url = "https://files.pythonhosted.org/packages/b6/17/ffb940c9e490bf42e86db4db1ff426ee1559cd355a69609ec1efe4d3a9eb/av-16.1.0-cp312-cp312-macosx_14_0_arm64.whl", hash = "sha256:ae3fb658eec00852ebd7412fdc141f17f3ddce8afee2d2e1cf366263ad2a3b35", size = 21481147 },
{ url = "https://files.pythonhosted.org/packages/15/c1/e0d58003d2d83c3921887d5c8c9b8f5f7de9b58dc2194356a2656a45cfdc/av-16.1.0-cp312-cp312-manylinux_2_28_aarch64.whl", hash = "sha256:27ee558d9c02a142eebcbe55578a6d817fedfde42ff5676275504e16d07a7f86", size = 39517197 },
{ url = "https://files.pythonhosted.org/packages/32/77/787797b43475d1b90626af76f80bfb0c12cfec5e11eafcfc4151b8c80218/av-16.1.0-cp312-cp312-manylinux_2_28_x86_64.whl", hash = "sha256:7ae547f6d5fa31763f73900d43901e8c5fa6367bb9a9840978d57b5a7ae14ed2", size = 41174337 },
{ url = "https://files.pythonhosted.org/packages/8e/ac/d90df7f1e3b97fc5554cf45076df5045f1e0a6adf13899e10121229b826c/av-16.1.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:8cf065f9d438e1921dc31fc7aa045790b58aee71736897866420d80b5450f62a", size = 40817720 },
{ url = "https://files.pythonhosted.org/packages/80/6f/13c3a35f9dbcebafd03fe0c4cbd075d71ac8968ec849a3cfce406c35a9d2/av-16.1.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:a345877a9d3cc0f08e2bc4ec163ee83176864b92587afb9d08dff50f37a9a829", size = 42267396 },
{ url = "https://files.pythonhosted.org/packages/c8/b9/275df9607f7fb44317ccb1d4be74827185c0d410f52b6e2cd770fe209118/av-16.1.0-cp312-cp312-win_amd64.whl", hash = "sha256:f49243b1d27c91cd8c66fdba90a674e344eb8eb917264f36117bf2b6879118fd", size = 31752045 },
]
[[package]]
@@ -3267,7 +3262,7 @@ requires-dist = [
{ name = "aiohttp-cors", specifier = ">=0.7.0" },
{ name = "aiortc", specifier = ">=1.5.0" },
{ name = "alembic", specifier = ">=1.11.3" },
{ name = "av", specifier = ">=10.0.0" },
{ name = "av", specifier = ">=15.0.0" },
{ name = "celery", specifier = ">=5.3.4" },
{ name = "databases", extras = ["aiosqlite", "asyncpg"], specifier = ">=0.7.0" },
{ name = "fastapi", extras = ["standard"], specifier = ">=0.100.1" },