- overlay: show × button in busy state (transcribing/rewriting), not only while recording — updates hit-region, draw call, and label layout - daemon: cancel_dictation() now handles _busy via threading.Event (_abort_event); _process() clears the event at start, checks after STT returns and after LLM rewrite completes, skipping delivery if set - llm: chat() and _read_stream() accept abort_event; streaming loop breaks immediately when the event is set so cancellation is near-instant Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
137 lines
4.8 KiB
Python
137 lines
4.8 KiB
Python
"""LLM engine abstraction for the rewrite step.
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Engines are user-managed presets pointing at any OpenAI-compatible chat endpoint
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(OpenAI, vLLM, llama-swap, Ollama /v1, LM Studio, Groq, OpenRouter, …). Provides
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reachability status (online/offline) and a chat-completion call. Uses only the
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standard library so the daemon needs no extra deps.
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"""
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from __future__ import annotations
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import json
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import os
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import urllib.error
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import urllib.request
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from dataclasses import dataclass
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from typing import Callable
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from .stt import reachable
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@dataclass
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class LLMEngine:
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name: str
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url: str = "https://api.openai.com/v1" # base URL (incl. /v1)
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model: str = "gpt-4o-mini"
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api_key_env: str = "OPENAI_API_KEY"
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temperature: float = 0.3
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type: str = "cloud" # "local" | "cloud" (label/category)
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@property
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def api_key(self) -> str | None:
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return os.environ.get(self.api_key_env) if self.api_key_env else None
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class LLMError(RuntimeError):
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pass
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def status(engine: LLMEngine, timeout: float = 2.0) -> bool:
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"""Reachable if the endpoint host:port accepts a TCP connection."""
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return reachable(engine.url, timeout)
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def chat(
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engine: LLMEngine,
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system_prompt: str,
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user_text: str,
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*,
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model: str | None = None,
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temperature: float | None = None,
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timeout: int = 45,
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on_token: Callable[[str], None] | None = None,
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abort_event=None,
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) -> str:
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"""Run a chat completion and return the full text.
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When ``on_token`` is given, the request is streamed and each content delta is
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handed to the callback as it arrives (so a UI can show the model writing in
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real time). The callback is best-effort — it never affects the return value,
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which is always the complete, stripped response.
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"""
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stream = on_token is not None
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api_key = engine.api_key
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body_obj = {
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"model": model or engine.model,
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"temperature": engine.temperature if temperature is None else temperature,
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"messages": [
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": user_text},
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],
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}
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if stream:
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body_obj["stream"] = True
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payload = json.dumps(body_obj).encode("utf-8")
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headers = {"Content-Type": "application/json"}
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if api_key:
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headers["Authorization"] = f"Bearer {api_key}"
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req = urllib.request.Request(
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engine.url.rstrip("/") + "/chat/completions", data=payload, headers=headers, method="POST"
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)
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try:
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with urllib.request.urlopen(req, timeout=timeout) as resp:
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if stream:
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content = _read_stream(resp, on_token, abort_event)
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else:
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body = json.loads(resp.read().decode("utf-8"))
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content = body["choices"][0]["message"]["content"]
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except urllib.error.HTTPError as exc:
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detail = exc.read().decode("utf-8", "replace")[:300]
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raise LLMError(f"HTTP {exc.code}: {detail}") from exc
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except urllib.error.URLError as exc:
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raise LLMError(f"Connection failed: {exc.reason}") from exc
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except (KeyError, IndexError, TypeError) as exc:
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raise LLMError(f"Unexpected response: {exc}") from exc
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except (TimeoutError, OSError) as exc:
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# socket.timeout (subclass of OSError / TimeoutError) fires when the server
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# stops sending data mid-stream. Not wrapped in URLError — must be caught
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# separately or it would propagate uncaught and kill the background thread.
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raise LLMError(f"Request timed out or connection lost: {exc}") from exc
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except Exception as exc: # noqa: BLE001
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raise LLMError(f"Unexpected error: {exc}") from exc
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content = (content or "").strip()
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if not content:
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raise LLMError("Empty response from model.")
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return content
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def _read_stream(resp, on_token: Callable[[str], None], abort_event=None) -> str:
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"""Parse an OpenAI-style SSE stream, returning the accumulated content and
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feeding each delta to ``on_token``. Tolerant of keep-alive blanks and the
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trailing ``[DONE]`` sentinel."""
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parts: list[str] = []
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for raw in resp:
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if abort_event and abort_event.is_set():
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break
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line = raw.decode("utf-8", "replace").strip()
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if not line or not line.startswith("data:"):
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continue
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data = line[len("data:"):].strip()
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if data == "[DONE]":
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break
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try:
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obj = json.loads(data)
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delta = obj["choices"][0]["delta"].get("content")
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except (ValueError, KeyError, IndexError, TypeError):
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continue
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if delta:
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parts.append(delta)
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try:
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on_token(delta)
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except Exception: # noqa: BLE001 - UI hiccups must not break delivery
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pass
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return "".join(parts)
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