Files
hao-ai-lab-FastVideo/v2/request/streams.py
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SolitaryThinker 4e331eb7ff [refactor] v2: use absolute imports (v2.*) everywhere instead of relative
Mechanical conversion of every relative import under v2/ to an absolute v2.* path
(from .x / ..x / ...x -> from v2.<pkg>.x) so imports are unambiguous, grep-able, and
stable when code is copied/moved between entrypoints (VideoGenerator, CLI, server).

Surgical prefix-only rewrite: only the 'from <dots><module>' prefix changed — import
names, parentheses, multi-line formatting, comments, and ordering are byte-for-byte
preserved (no collapsing, no reorder, no unrelated reformatting).

- 471 imports across 125 files; v2/tests/ was already absolute (untouched).
- Validated: all 125 files compile, every 'from v2.* import' target resolves to a real
  module/package, zero relative imports remain (full sweep), CPU mini suite green
  (202 passed, 2 skipped).
2026-07-04 17:15:34 +00:00

60 lines
2.1 KiB
Python

"""Streams + typed event taxonomy (design_v3 §12).
"A ``Stream`` is one ordered event channel for previews, media chunks, progress,
logs, finals." Event taxonomy: ``request.*``, ``session.*``, ``artifact.*``,
``media.{init,chunk,complete}``, ``trace.*``. A ``media.chunk`` must know its
stream, byte-range/buffer-ref, codec/container, timestamp range, and
preview-vs-final — invalid combinations are unrepresentable.
For v2 the Stream is a simple synchronous ordered channel (the core is
numpy/sync and CPU-testable); a GPU/server deployment swaps in an async channel
without changing the event types.
"""
from __future__ import annotations
from dataclasses import dataclass, field
from v2._types import TensorLike
@dataclass(frozen=True)
class OmniEvent:
type: str # e.g. "request.start", "media.chunk", "artifact.ready", "trace.step"
request_id: str
seq: int = 0
payload: dict[str, object] = field(default_factory=dict)
@dataclass(frozen=True)
class StreamChunk:
"""A media.chunk payload — invalid field combinations are unrepresentable."""
stream_id: str
modality: str # "video" | "audio" | "text"
seq: int
data: TensorLike = None # in-proc buffer (frames / samples / token ids)
codec: str = "raw" # raw | h264 | opus | ...
ts_start: float = 0.0 # presentation timestamp range (seconds)
ts_end: float = 0.0
preview: bool = False # preview vs final
final: bool = False # last chunk of the stream
class Stream:
"""Ordered event channel. Sync collector for tests; subscribe for streaming."""
def __init__(self, stream_id: str):
self.stream_id = stream_id
self.events: list[OmniEvent] = []
self._subscribers: list = []
def emit(self, event: OmniEvent) -> None:
self.events.append(event)
for cb in self._subscribers:
cb(event)
def subscribe(self, callback) -> None:
self._subscribers.append(callback)
def __iter__(self):
return iter(self.events)