Files
watch_sceen_ai/wsai/pipeline.py
claude-owner 4eeddc4b1f feat: scaffold watch-screen AI pipeline (mock-runnable skeleton)
Modular async pipeline: FrameSource->Vision->context and STT/text->Brain->TTS.
All stages are Protocols; mock backends run end-to-end with no deps/keys.
Real backends included: mss screen capture, Claude vision+brain (guarded imports).
2026-08-09 02:16:14 +09:00

115 lines
3.6 KiB
Python

"""Orchestrator: wires the perception loop and the conversation loop together."""
from __future__ import annotations
import asyncio
import logging
from .interfaces import (
Brain,
FrameSource,
Reply,
SpeechToText,
TextChannel,
TextToSpeech,
Utterance,
VisionBackend,
)
from .state import SharedScreenContext
log = logging.getLogger("wsai.pipeline")
class Pipeline:
"""Runs two concurrent loops:
* perception: FrameSource -> VisionBackend -> SharedScreenContext
* conversation: (SpeechToText | TextChannel) -> Brain -> (TextToSpeech | TextChannel)
Either input/output half can be None, so you can run text-only, voice-only,
or a headless "just watch" configuration.
"""
def __init__(
self,
*,
source: FrameSource,
vision: VisionBackend,
brain: Brain,
stt: SpeechToText | None = None,
tts: TextToSpeech | None = None,
text_channel: TextChannel | None = None,
history_turns: int = 12,
) -> None:
self.source = source
self.vision = vision
self.brain = brain
self.stt = stt
self.tts = tts
self.text_channel = text_channel
self.context = SharedScreenContext()
self._history: list[tuple[str, str]] = []
self._history_turns = history_turns
# -- perception -------------------------------------------------------- #
async def _perceive(self) -> None:
async for frame in self.source.frames():
try:
obs = await self.vision.describe(frame)
except Exception: # a single bad frame must not kill the loop
log.exception("vision.describe failed")
continue
await self.context.update(obs)
log.debug("screen: %s", obs.text[:120])
# -- conversation ------------------------------------------------------ #
async def _handle(self, utt: Utterance) -> None:
screen = await self.context.latest()
reply = await self.brain.respond(utt.text, screen, self._history)
self._remember(utt.text, reply.text)
await self._emit(reply)
def _remember(self, user: str, ai: str) -> None:
self._history.append((user, ai))
if len(self._history) > self._history_turns:
self._history = self._history[-self._history_turns :]
async def _emit(self, reply: Reply) -> None:
tasks = []
if self.tts is not None:
tasks.append(self.tts.speak(reply))
if self.text_channel is not None:
tasks.append(self.text_channel.send(reply))
if not tasks:
log.info("AI: %s", reply.text)
else:
await asyncio.gather(*tasks)
async def _listen_voice(self) -> None:
if self.stt is None:
return
async for utt in self.stt.utterances():
await self._handle(utt)
async def _listen_text(self) -> None:
if self.text_channel is None:
return
async for utt in self.text_channel.messages():
await self._handle(utt)
# -- lifecycle --------------------------------------------------------- #
async def run(self) -> None:
loops = [self._perceive(), self._listen_voice(), self._listen_text()]
try:
await asyncio.gather(*loops)
finally:
await self.aclose()
async def aclose(self) -> None:
for closer in (self.source, self.stt, self.text_channel):
if closer is not None:
try:
await closer.aclose()
except Exception:
log.exception("error closing %s", closer)