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Add pipeline engine and remove legacy compatibility paths

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This commit is contained in:
Thales Maciel 2026-02-25 22:40:03 -03:00
parent 3bc473262d
commit e221d49020
18 changed files with 1523 additions and 399 deletions
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88
README.md
View file

@ -80,8 +80,7 @@ Create `~/.config/aman/config.json` (or let `aman` create it automatically on fi
{ "from": "docker", "to": "Docker" }
],
"terms": ["Systemd", "Kubernetes"]
},
"domain_inference": { "enabled": true }
}
}
```
@ -92,6 +91,9 @@ Hotkey notes:
- Use one key plus optional modifiers (for example `Cmd+m`, `Super+m`, `Ctrl+space`).
- `Super` and `Cmd` are equivalent aliases for the same modifier.
- Invalid hotkey syntax in config prevents startup/reload.
- When `~/.config/aman/pipelines.py` exists, hotkeys come from `HOTKEY_PIPELINES`.
- `daemon.hotkey` is used as the fallback/default hotkey only when no pipelines file is present.
AI cleanup is always enabled and uses the locked local Llama-3.2-3B GGUF model
downloaded to `~/.cache/aman/models/` during daemon initialization.
@ -107,11 +109,6 @@ Vocabulary correction:
- Wildcards are intentionally rejected (`*`, `?`, `[`, `]`, `{`, `}`) to avoid ambiguous rules.
- Rules are deduplicated case-insensitively; conflicting replacements are rejected.
Domain inference:
- Domain context is advisory only and is used to improve cleanup prompts.
- When confidence is low, it falls back to `general` context.
STT hinting:
- Vocabulary is passed to Whisper as `hotwords`/`initial_prompt` only when those
@ -134,6 +131,12 @@ systemctl --user enable --now aman
- Press it again to stop and run STT.
- Press `Esc` while recording to cancel without processing.
- Transcript contents are logged only when `-v/--verbose` is used.
- Config changes are hot-reloaded automatically (polled every 1 second).
- `~/.config/aman/pipelines.py` changes are hot-reloaded automatically (polled every 1 second).
- Send `SIGHUP` to force an immediate reload of config and pipelines:
`systemctl --user kill -s HUP aman` (or send `HUP` to the process directly).
- Reloads are applied when the daemon is idle; invalid updates are rejected and the last valid config stays active.
- Reload success/failure is logged, and desktop notifications are shown when available.
Wayland note:
@ -149,6 +152,77 @@ AI processing:
- Local llama.cpp model only (no remote provider configuration).
## Pipelines API
`aman` is split into:
- shell daemon: hotkeys, recording/cancel, and desktop injection
- pipeline engine: `lib.transcribe(...)` and `lib.llm(...)`
- pipeline implementation: Python callables mapped per hotkey
Pipeline file path:
- `~/.config/aman/pipelines.py`
- You can start from [`pipelines.example.py`](./pipelines.example.py).
- If `pipelines.py` is missing, `aman` uses a built-in reference pipeline bound to `daemon.hotkey`.
- If `pipelines.py` exists but is invalid, startup fails fast.
- Pipelines are hot-reloaded automatically when the module file changes.
- Send `SIGHUP` to force an immediate reload of both config and pipelines.
Expected module exports:
```python
HOTKEY_PIPELINES = {
"Super+m": my_pipeline,
"Super+Shift+m": caps_pipeline,
}
PIPELINE_OPTIONS = {
"Super+Shift+m": {"failure_policy": "strict"}, # optional
}
```
Pipeline callable signature:
```python
def my_pipeline(audio, lib) -> str:
text = lib.transcribe(audio)
context = lib.llm(
system_prompt="context system prompt",
user_prompt=f"Transcript: {text}",
)
out = lib.llm(
system_prompt="amanuensis prompt",
user_prompt=f"context={context}\ntext={text}",
)
return out
```
`lib` API:
- `lib.transcribe(audio, hints=None, whisper_opts=None) -> str`
- `lib.llm(system_prompt=..., user_prompt=..., llm_opts=None) -> str`
Failure policy options:
- `best_effort` (default): pipeline errors return empty output
- `strict`: pipeline errors abort the current run
Validation:
- `HOTKEY_PIPELINES` must be a non-empty dictionary.
- Every hotkey key must be a non-empty string.
- Every pipeline value must be callable.
- `PIPELINE_OPTIONS` must be a dictionary when provided.
Reference behavior:
- The built-in fallback pipeline (used when `pipelines.py` is missing) uses `lib.llm(...)` twice:
- first to infer context
- second to run the amanuensis rewrite
- The second pass requests JSON output and expects `{"cleaned_text": "..."}`.
- Deterministic dictionary replacements are then applied as part of that reference implementation.
Control:
```bash

50
pipelines.example.py Normal file
View file

@ -0,0 +1,50 @@
import json
CONTEXT_PROMPT = (
"Return a concise plain-text context hint (max 12 words) "
"for the transcript domain and style."
)
AMANUENSIS_PROMPT = (
"Rewrite the transcript into clean prose without changing intent. "
"Return only the final text."
)
def default_pipeline(audio, lib) -> str:
text = lib.transcribe(audio)
if not text:
return ""
context = lib.llm(
system_prompt=CONTEXT_PROMPT,
user_prompt=json.dumps({"transcript": text}, ensure_ascii=False),
llm_opts={"temperature": 0.0},
).strip()
output = lib.llm(
system_prompt=AMANUENSIS_PROMPT,
user_prompt=json.dumps(
{"transcript": text, "context": context},
ensure_ascii=False,
),
llm_opts={"temperature": 0.0},
)
return output.strip()
def caps_pipeline(audio, lib) -> str:
return lib.transcribe(audio).upper()
HOTKEY_PIPELINES = {
"Super+m": default_pipeline,
"Super+Shift+m": caps_pipeline,
}
PIPELINE_OPTIONS = {
"Super+m": {"failure_policy": "best_effort"},
"Super+Shift+m": {"failure_policy": "strict"},
}

39
src/aiprocess.py
View file

@ -76,18 +76,41 @@ class LlamaProcessor:
if cleaned_dictionary:
request_payload["dictionary"] = cleaned_dictionary
content = self.chat(
system_prompt=SYSTEM_PROMPT,
user_prompt=json.dumps(request_payload, ensure_ascii=False),
llm_opts={"temperature": 0.0, "response_format": {"type": "json_object"}},
)
return _extract_cleaned_text_from_raw(content)
def chat(
self,
*,
system_prompt: str,
user_prompt: str,
llm_opts: dict[str, Any] | None = None,
) -> str:
opts = dict(llm_opts or {})
temperature = float(opts.pop("temperature", 0.0))
response_format = opts.pop("response_format", None)
if opts:
unknown = ", ".join(sorted(opts.keys()))
raise ValueError(f"unsupported llm options: {unknown}")
kwargs: dict[str, Any] = {
"messages": [
{"role": "system", "content": SYSTEM_PROMPT},
{"role": "user", "content": json.dumps(request_payload, ensure_ascii=False)},
{"role": "system", "content": system_prompt},
{"role": "user", "content": user_prompt},
],
"temperature": 0.0,
"temperature": temperature,
}
if _supports_response_format(self.client.create_chat_completion):
kwargs["response_format"] = {"type": "json_object"}
if response_format is not None and _supports_response_format(
self.client.create_chat_completion
):
kwargs["response_format"] = response_format
response = self.client.create_chat_completion(**kwargs)
return _extract_cleaned_text(response)
return _extract_chat_text(response)
def ensure_model():
@ -148,6 +171,10 @@ def _extract_chat_text(payload: Any) -> str:
def _extract_cleaned_text(payload: Any) -> str:
raw = _extract_chat_text(payload)
return _extract_cleaned_text_from_raw(raw)
def _extract_cleaned_text_from_raw(raw: str) -> str:
try:
parsed = json.loads(raw)
except json.JSONDecodeError as exc:

678
src/aman.py
View file

@ -3,6 +3,7 @@ from __future__ import annotations
import argparse
import errno
import hashlib
import inspect
import json
import logging
@ -12,12 +13,21 @@ import sys
import threading
import time
from pathlib import Path
from typing import Any
from typing import Any, Callable
from aiprocess import LlamaProcessor
from aiprocess import LlamaProcessor, SYSTEM_PROMPT
from config import Config, load, redacted_dict
from constants import RECORD_TIMEOUT_SEC, STT_LANGUAGE
from constants import (
CONFIG_RELOAD_POLL_INTERVAL_SEC,
DEFAULT_CONFIG_PATH,
RECORD_TIMEOUT_SEC,
STT_LANGUAGE,
)
from desktop import get_desktop_adapter
from engine import Engine, PipelineBinding, PipelineLib, PipelineOptions
from notify import DesktopNotifier
from pipelines_runtime import DEFAULT_PIPELINES_PATH, fingerprint as pipelines_fingerprint
from pipelines_runtime import load_bindings
from recorder import start_recording as start_audio_recording
from recorder import stop_recording as stop_audio_recording
from vocabulary import VocabularyEngine
@ -55,6 +65,52 @@ def _compute_type(device: str) -> str:
return "int8"
def _replacement_view(cfg: Config) -> list[tuple[str, str]]:
return [(item.source, item.target) for item in cfg.vocabulary.replacements]
def _config_fields_changed(current: Config, candidate: Config) -> list[str]:
changed: list[str] = []
if current.daemon.hotkey != candidate.daemon.hotkey:
changed.append("daemon.hotkey")
if current.recording.input != candidate.recording.input:
changed.append("recording.input")
if current.stt.model != candidate.stt.model:
changed.append("stt.model")
if current.stt.device != candidate.stt.device:
changed.append("stt.device")
if current.injection.backend != candidate.injection.backend:
changed.append("injection.backend")
if (
current.injection.remove_transcription_from_clipboard
!= candidate.injection.remove_transcription_from_clipboard
):
changed.append("injection.remove_transcription_from_clipboard")
if _replacement_view(current) != _replacement_view(candidate):
changed.append("vocabulary.replacements")
if current.vocabulary.terms != candidate.vocabulary.terms:
changed.append("vocabulary.terms")
return changed
CONTEXT_SYSTEM_PROMPT = (
"You infer concise writing context from transcript text.\n"
"Return a short plain-text hint (max 12 words) that describes the likely domain and style.\n"
"Do not add punctuation, quotes, XML tags, or markdown."
)
def _extract_cleaned_text_from_llm_raw(raw: str) -> str:
parsed = json.loads(raw)
if isinstance(parsed, str):
return parsed
if isinstance(parsed, dict):
cleaned_text = parsed.get("cleaned_text")
if isinstance(cleaned_text, str):
return cleaned_text
raise RuntimeError("unexpected ai output format: missing cleaned_text")
class Daemon:
def __init__(self, cfg: Config, desktop, *, verbose: bool = False):
self.cfg = cfg
@ -66,17 +122,34 @@ class Daemon:
self.stream = None
self.record = None
self.timer: threading.Timer | None = None
self.model = _build_whisper_model(
cfg.stt.model,
cfg.stt.device,
)
self._config_apply_in_progress = False
self._active_hotkey: str | None = None
self._pending_worker_hotkey: str | None = None
self._pipeline_bindings: dict[str, PipelineBinding] = {}
self.model = _build_whisper_model(cfg.stt.model, cfg.stt.device)
logging.info("initializing ai processor")
self.ai_processor = LlamaProcessor(verbose=self.verbose)
logging.info("ai processor ready")
self.log_transcript = verbose
self.vocabulary = VocabularyEngine(cfg.vocabulary, cfg.domain_inference)
self.vocabulary = VocabularyEngine(cfg.vocabulary)
self._stt_hint_kwargs_cache: dict[str, Any] | None = None
self.lib = PipelineLib(
transcribe_fn=self._transcribe_with_options,
llm_fn=self._llm_with_options,
)
self.engine = Engine(self.lib)
self.set_pipeline_bindings(
{
cfg.daemon.hotkey: PipelineBinding(
hotkey=cfg.daemon.hotkey,
handler=self.build_reference_pipeline(),
options=PipelineOptions(failure_policy="best_effort"),
)
}
)
def set_state(self, state: str):
with self.lock:
prev = self.state
@ -93,16 +166,74 @@ class Daemon:
def request_shutdown(self):
self._shutdown_requested.set()
def toggle(self):
def current_hotkeys(self) -> list[str]:
with self.lock:
return list(self._pipeline_bindings.keys())
def set_pipeline_bindings(self, bindings: dict[str, PipelineBinding]) -> None:
if not bindings:
raise ValueError("at least one pipeline binding is required")
with self.lock:
self._pipeline_bindings = dict(bindings)
if self._active_hotkey and self._active_hotkey not in self._pipeline_bindings:
self._active_hotkey = None
def build_hotkey_callbacks(
self,
hotkeys: list[str],
*,
dry_run: bool,
) -> dict[str, Callable[[], None]]:
callbacks: dict[str, Callable[[], None]] = {}
for hotkey in hotkeys:
if dry_run:
callbacks[hotkey] = (lambda hk=hotkey: logging.info("hotkey pressed: %s (dry-run)", hk))
else:
callbacks[hotkey] = (lambda hk=hotkey: self.handle_hotkey(hk))
return callbacks
def apply_pipeline_bindings(
self,
bindings: dict[str, PipelineBinding],
callbacks: dict[str, Callable[[], None]],
) -> tuple[str, str]:
with self.lock:
if self._shutdown_requested.is_set():
return "deferred", "shutdown in progress"
if self._config_apply_in_progress:
return "deferred", "reload in progress"
if self.state != State.IDLE:
return "deferred", f"daemon is busy ({self.state})"
self._config_apply_in_progress = True
try:
self.desktop.set_hotkeys(callbacks)
with self.lock:
if self._shutdown_requested.is_set():
return "deferred", "shutdown in progress"
if self.state != State.IDLE:
return "deferred", f"daemon is busy ({self.state})"
self._pipeline_bindings = dict(bindings)
return "applied", ""
except Exception as exc:
return "error", str(exc)
finally:
with self.lock:
self._config_apply_in_progress = False
def handle_hotkey(self, hotkey: str):
should_stop = False
with self.lock:
if self._shutdown_requested.is_set():
logging.info("shutdown in progress, trigger ignored")
return
if self._config_apply_in_progress:
logging.info("reload in progress, trigger ignored")
return
if self.state == State.IDLE:
self._active_hotkey = hotkey
self._start_recording_locked()
return
if self.state == State.RECORDING:
if self.state == State.RECORDING and self._active_hotkey == hotkey:
should_stop = True
else:
logging.info("busy (%s), trigger ignored", self.state)
@ -113,6 +244,9 @@ class Daemon:
if self.state != State.IDLE:
logging.info("busy (%s), trigger ignored", self.state)
return
if self._config_apply_in_progress:
logging.info("reload in progress, trigger ignored")
return
try:
stream, record = start_audio_recording(self.cfg.recording.input)
except Exception as exc:
@ -133,10 +267,17 @@ class Daemon:
def _timeout_stop(self):
self.stop_recording(trigger="timeout")
def _start_stop_worker(self, stream: Any, record: Any, trigger: str, process_audio: bool):
def _start_stop_worker(
self,
stream: Any,
record: Any,
trigger: str,
process_audio: bool,
):
active_hotkey = self._pending_worker_hotkey or self.cfg.daemon.hotkey
threading.Thread(
target=self._stop_and_process,
args=(stream, record, trigger, process_audio),
args=(stream, record, trigger, process_audio, active_hotkey),
daemon=True,
).start()
@ -145,6 +286,8 @@ class Daemon:
return None
stream = self.stream
record = self.record
active_hotkey = self._active_hotkey or self.cfg.daemon.hotkey
self._active_hotkey = None
self.stream = None
self.record = None
if self.timer:
@ -158,9 +301,17 @@ class Daemon:
logging.warning("recording resources are unavailable during stop")
self.state = State.IDLE
return None
return stream, record
return stream, record, active_hotkey
def _stop_and_process(self, stream: Any, record: Any, trigger: str, process_audio: bool):
def _stop_and_process(
self,
stream: Any,
record: Any,
trigger: str,
process_audio: bool,
active_hotkey: str | None = None,
):
hotkey = active_hotkey or self.cfg.daemon.hotkey
logging.info("stopping recording (%s)", trigger)
try:
audio = stop_audio_recording(stream, record)
@ -179,44 +330,17 @@ class Daemon:
return
try:
self.set_state(State.STT)
logging.info("stt started")
text = self._transcribe(audio)
logging.info("pipeline started (%s)", hotkey)
text = self._run_pipeline(audio, hotkey).strip()
except Exception as exc:
logging.error("stt failed: %s", exc)
logging.error("pipeline failed: %s", exc)
self.set_state(State.IDLE)
return
text = (text or "").strip()
if not text:
self.set_state(State.IDLE)
return
if self.log_transcript:
logging.debug("stt: %s", text)
else:
logging.info("stt produced %d chars", len(text))
domain = self.vocabulary.infer_domain(text)
if not self._shutdown_requested.is_set():
self.set_state(State.PROCESSING)
logging.info("ai processing started")
try:
processor = self._get_ai_processor()
ai_text = processor.process(
text,
lang=STT_LANGUAGE,
dictionary_context=self.vocabulary.build_ai_dictionary_context(),
domain_name=domain.name,
domain_confidence=domain.confidence,
)
if ai_text and ai_text.strip():
text = ai_text.strip()
except Exception as exc:
logging.error("ai process failed: %s", exc)
text = self.vocabulary.apply_deterministic_replacements(text).strip()
if self.log_transcript:
logging.debug("processed: %s", text)
else:
@ -242,13 +366,23 @@ class Daemon:
finally:
self.set_state(State.IDLE)
def _run_pipeline(self, audio: Any, hotkey: str) -> str:
with self.lock:
binding = self._pipeline_bindings.get(hotkey)
if binding is None and self._pipeline_bindings:
binding = next(iter(self._pipeline_bindings.values()))
if binding is None:
return ""
return self.engine.run(binding, audio)
def stop_recording(self, *, trigger: str = "user", process_audio: bool = True):
payload = None
with self.lock:
payload = self._begin_stop_locked()
if payload is None:
return
stream, record = payload
stream, record, active_hotkey = payload
self._pending_worker_hotkey = active_hotkey
self._start_stop_worker(stream, record, trigger, process_audio)
def cancel_recording(self):
@ -270,40 +404,129 @@ class Daemon:
time.sleep(0.05)
return self.get_state() == State.IDLE
def build_reference_pipeline(self) -> Callable[[Any, PipelineLib], str]:
def _reference_pipeline(audio: Any, lib: PipelineLib) -> str:
text = (lib.transcribe(audio) or "").strip()
if not text:
return ""
dictionary_context = self.vocabulary.build_ai_dictionary_context()
context_prompt = {
"transcript": text,
"dictionary": dictionary_context,
}
context = (
lib.llm(
system_prompt=CONTEXT_SYSTEM_PROMPT,
user_prompt=json.dumps(context_prompt, ensure_ascii=False),
llm_opts={"temperature": 0.0},
)
.strip()
)
payload: dict[str, Any] = {
"language": STT_LANGUAGE,
"transcript": text,
"context": context,
}
if dictionary_context:
payload["dictionary"] = dictionary_context
ai_raw = lib.llm(
system_prompt=SYSTEM_PROMPT,
user_prompt=json.dumps(payload, ensure_ascii=False),
llm_opts={"temperature": 0.0, "response_format": {"type": "json_object"}},
)
cleaned_text = _extract_cleaned_text_from_llm_raw(ai_raw)
return self.vocabulary.apply_deterministic_replacements(cleaned_text).strip()
return _reference_pipeline
def _transcribe(self, audio) -> str:
return self._transcribe_with_options(audio)
def _transcribe_with_options(
self,
audio: Any,
*,
hints: list[str] | None = None,
whisper_opts: dict[str, Any] | None = None,
) -> str:
kwargs: dict[str, Any] = {
"language": STT_LANGUAGE,
"vad_filter": True,
}
kwargs.update(self._stt_hint_kwargs())
kwargs.update(self._stt_hint_kwargs(hints=hints))
if whisper_opts:
kwargs.update(whisper_opts)
segments, _info = self.model.transcribe(audio, **kwargs)
parts = []
for seg in segments:
text = (seg.text or "").strip()
if text:
parts.append(text)
return " ".join(parts).strip()
out = " ".join(parts).strip()
if self.log_transcript:
logging.debug("stt: %s", out)
else:
logging.info("stt produced %d chars", len(out))
return out
def _llm_with_options(
self,
*,
system_prompt: str,
user_prompt: str,
llm_opts: dict[str, Any] | None = None,
) -> str:
if self.get_state() != State.PROCESSING:
self.set_state(State.PROCESSING)
logging.info("llm processing started")
processor = self._get_ai_processor()
return processor.chat(
system_prompt=system_prompt,
user_prompt=user_prompt,
llm_opts=llm_opts,
)
def _get_ai_processor(self) -> LlamaProcessor:
if self.ai_processor is None:
raise RuntimeError("ai processor is not initialized")
return self.ai_processor
def _stt_hint_kwargs(self) -> dict[str, Any]:
if self._stt_hint_kwargs_cache is not None:
def _stt_hint_kwargs(self, *, hints: list[str] | None = None) -> dict[str, Any]:
if not hints and self._stt_hint_kwargs_cache is not None:
return self._stt_hint_kwargs_cache
hotwords, initial_prompt = self.vocabulary.build_stt_hints()
extra_hints = [item.strip() for item in (hints or []) if isinstance(item, str) and item.strip()]
if extra_hints:
words = [item.strip() for item in hotwords.split(",") if item.strip()]
words.extend(extra_hints)
deduped: list[str] = []
seen: set[str] = set()
for item in words:
key = item.casefold()
if key in seen:
continue
seen.add(key)
deduped.append(item)
merged = ", ".join(deduped)
hotwords = merged[:1024]
if hotwords:
initial_prompt = f"Preferred vocabulary: {hotwords}"[:600]
if not hotwords and not initial_prompt:
self._stt_hint_kwargs_cache = {}
return self._stt_hint_kwargs_cache
if not hints:
self._stt_hint_kwargs_cache = {}
return self._stt_hint_kwargs_cache
return {}
try:
signature = inspect.signature(self.model.transcribe)
except (TypeError, ValueError):
logging.debug("stt signature inspection failed; skipping hints")
self._stt_hint_kwargs_cache = {}
return self._stt_hint_kwargs_cache
if not hints:
self._stt_hint_kwargs_cache = {}
return self._stt_hint_kwargs_cache
return {}
params = signature.parameters
kwargs: dict[str, Any] = {}
@ -313,8 +536,288 @@ class Daemon:
kwargs["initial_prompt"] = initial_prompt
if not kwargs:
logging.debug("stt hint arguments are not supported by this whisper runtime")
self._stt_hint_kwargs_cache = kwargs
return self._stt_hint_kwargs_cache
if not hints:
self._stt_hint_kwargs_cache = kwargs
return self._stt_hint_kwargs_cache
return kwargs
def try_apply_config(self, candidate: Config) -> tuple[str, list[str], str]:
with self.lock:
if self._shutdown_requested.is_set():
return "deferred", [], "shutdown in progress"
if self._config_apply_in_progress:
return "deferred", [], "config reload already in progress"
if self.state != State.IDLE:
return "deferred", [], f"daemon is busy ({self.state})"
self._config_apply_in_progress = True
current_cfg = self.cfg
try:
changed = _config_fields_changed(current_cfg, candidate)
if not changed:
return "applied", [], ""
next_model = None
if (
current_cfg.stt.model != candidate.stt.model
or current_cfg.stt.device != candidate.stt.device
):
try:
next_model = _build_whisper_model(candidate.stt.model, candidate.stt.device)
except Exception as exc:
return "error", [], f"stt model reload failed: {exc}"
try:
next_vocab = VocabularyEngine(candidate.vocabulary)
except Exception as exc:
return "error", [], f"vocabulary reload failed: {exc}"
with self.lock:
if self._shutdown_requested.is_set():
return "deferred", [], "shutdown in progress"
if self.state != State.IDLE:
return "deferred", [], f"daemon is busy ({self.state})"
self.cfg = candidate
if next_model is not None:
self.model = next_model
self.vocabulary = next_vocab
self._stt_hint_kwargs_cache = None
return "applied", changed, ""
finally:
with self.lock:
self._config_apply_in_progress = False
class ConfigReloader:
def __init__(
self,
*,
daemon: Daemon,
config_path: Path,
notifier: DesktopNotifier | None = None,
poll_interval_sec: float = CONFIG_RELOAD_POLL_INTERVAL_SEC,
):
self.daemon = daemon
self.config_path = config_path
self.notifier = notifier
self.poll_interval_sec = poll_interval_sec
self._stop_event = threading.Event()
self._request_lock = threading.Lock()
self._pending_reload_reason = ""
self._pending_force = False
self._last_seen_fingerprint = self._fingerprint()
self._thread: threading.Thread | None = None
def start(self) -> None:
if self._thread is not None:
return
self._thread = threading.Thread(target=self._run, daemon=True, name="config-reloader")
self._thread.start()
def stop(self, timeout: float = 2.0) -> None:
self._stop_event.set()
if self._thread is not None:
self._thread.join(timeout=timeout)
self._thread = None
def request_reload(self, reason: str, *, force: bool = False) -> None:
with self._request_lock:
if self._pending_reload_reason:
self._pending_reload_reason = f"{self._pending_reload_reason}; {reason}"
else:
self._pending_reload_reason = reason
self._pending_force = self._pending_force or force
logging.debug("config reload requested: %s (force=%s)", reason, force)
def tick(self) -> None:
self._detect_file_change()
self._apply_if_pending()
def _run(self) -> None:
while not self._stop_event.wait(self.poll_interval_sec):
self.tick()
def _detect_file_change(self) -> None:
fingerprint = self._fingerprint()
if fingerprint == self._last_seen_fingerprint:
return
self._last_seen_fingerprint = fingerprint
self.request_reload("file change detected", force=False)
def _apply_if_pending(self) -> None:
with self._request_lock:
reason = self._pending_reload_reason
force_reload = self._pending_force
if not reason:
return
if self.daemon.get_state() != State.IDLE:
logging.debug("config reload deferred; daemon state=%s", self.daemon.get_state())
return
try:
candidate = load(str(self.config_path))
except Exception as exc:
self._clear_pending()
msg = f"config reload failed ({reason}): {exc}"
logging.error(msg)
self._notify("Config Reload Failed", str(exc), error=True)
return
status, changed, error = self.daemon.try_apply_config(candidate)
if status == "deferred":
logging.debug("config reload deferred during apply: %s", error)
return
self._clear_pending()
if status == "error":
msg = f"config reload failed ({reason}): {error}"
logging.error(msg)
self._notify("Config Reload Failed", error, error=True)
return
if changed:
msg = ", ".join(changed)
logging.info("config reloaded (%s): %s", reason, msg)
self._notify("Config Reloaded", f"Applied: {msg}", error=False)
return
if force_reload:
logging.info("config reloaded (%s): no effective changes", reason)
self._notify("Config Reloaded", "No effective changes", error=False)
def _clear_pending(self) -> None:
with self._request_lock:
self._pending_reload_reason = ""
self._pending_force = False
def _fingerprint(self) -> str | None:
try:
data = self.config_path.read_bytes()
return hashlib.sha256(data).hexdigest()
except FileNotFoundError:
return None
except OSError as exc:
logging.warning("config fingerprint failed (%s): %s", self.config_path, exc)
return None
def _notify(self, title: str, body: str, *, error: bool) -> None:
if self.notifier is None:
return
sent = self.notifier.send(title, body, error=error)
if not sent:
logging.debug("desktop notifications unavailable: %s", title)
class PipelineReloader:
def __init__(
self,
*,
daemon: Daemon,
pipelines_path: Path,
notifier: DesktopNotifier | None = None,
dry_run: bool = False,
poll_interval_sec: float = CONFIG_RELOAD_POLL_INTERVAL_SEC,
):
self.daemon = daemon
self.pipelines_path = pipelines_path
self.notifier = notifier
self.dry_run = dry_run
self.poll_interval_sec = poll_interval_sec
self._stop_event = threading.Event()
self._request_lock = threading.Lock()
self._pending_reload_reason = ""
self._pending_force = False
self._last_seen_fingerprint = pipelines_fingerprint(self.pipelines_path)
self._thread: threading.Thread | None = None
def start(self) -> None:
if self._thread is not None:
return
self._thread = threading.Thread(target=self._run, daemon=True, name="pipeline-reloader")
self._thread.start()
def stop(self, timeout: float = 2.0) -> None:
self._stop_event.set()
if self._thread is not None:
self._thread.join(timeout=timeout)
self._thread = None
def request_reload(self, reason: str, *, force: bool = False) -> None:
with self._request_lock:
if self._pending_reload_reason:
self._pending_reload_reason = f"{self._pending_reload_reason}; {reason}"
else:
self._pending_reload_reason = reason
self._pending_force = self._pending_force or force
logging.debug("pipeline reload requested: %s (force=%s)", reason, force)
def tick(self) -> None:
self._detect_file_change()
self._apply_if_pending()
def _run(self) -> None:
while not self._stop_event.wait(self.poll_interval_sec):
self.tick()
def _detect_file_change(self) -> None:
fingerprint = pipelines_fingerprint(self.pipelines_path)
if fingerprint == self._last_seen_fingerprint:
return
self._last_seen_fingerprint = fingerprint
self.request_reload("file change detected", force=False)
def _apply_if_pending(self) -> None:
with self._request_lock:
reason = self._pending_reload_reason
force_reload = self._pending_force
if not reason:
return
if self.daemon.get_state() != State.IDLE:
logging.debug("pipeline reload deferred; daemon state=%s", self.daemon.get_state())
return
try:
bindings = load_bindings(
path=self.pipelines_path,
default_hotkey=self.daemon.cfg.daemon.hotkey,
default_handler_factory=self.daemon.build_reference_pipeline,
)
callbacks = self.daemon.build_hotkey_callbacks(
list(bindings.keys()),
dry_run=self.dry_run,
)
except Exception as exc:
self._clear_pending()
logging.error("pipeline reload failed (%s): %s", reason, exc)
self._notify("Pipelines Reload Failed", str(exc), error=True)
return
status, error = self.daemon.apply_pipeline_bindings(bindings, callbacks)
if status == "deferred":
logging.debug("pipeline reload deferred during apply: %s", error)
return
self._clear_pending()
if status == "error":
logging.error("pipeline reload failed (%s): %s", reason, error)
self._notify("Pipelines Reload Failed", error, error=True)
return
hotkeys = ", ".join(sorted(bindings.keys()))
logging.info("pipelines reloaded (%s): %s", reason, hotkeys)
self._notify("Pipelines Reloaded", f"Hotkeys: {hotkeys}", error=False)
if force_reload and not bindings:
logging.info("pipelines reloaded (%s): no hotkeys", reason)
def _clear_pending(self) -> None:
with self._request_lock:
self._pending_reload_reason = ""
self._pending_force = False
def _notify(self, title: str, body: str, *, error: bool) -> None:
if self.notifier is None:
return
sent = self.notifier.send(title, body, error=error)
if not sent:
logging.debug("desktop notifications unavailable: %s", title)
def _read_lock_pid(lock_file) -> str:
@ -366,19 +869,49 @@ def main():
level=logging.DEBUG if args.verbose else logging.INFO,
format="aman: %(asctime)s %(levelname)s %(message)s",
)
cfg = load(args.config)
config_path = Path(args.config) if args.config else DEFAULT_CONFIG_PATH
cfg = load(str(config_path))
_LOCK_HANDLE = _lock_single_instance()
logging.info("hotkey: %s", cfg.daemon.hotkey)
logging.info(
"config (%s):\n%s",
args.config or str(Path.home() / ".config" / "aman" / "config.json"),
str(config_path),
json.dumps(redacted_dict(cfg), indent=2),
)
config_reloader = None
pipeline_reloader = None
try:
desktop = get_desktop_adapter()
daemon = Daemon(cfg, desktop, verbose=args.verbose)
notifier = DesktopNotifier(app_name="aman")
config_reloader = ConfigReloader(
daemon=daemon,
config_path=config_path,
notifier=notifier,
poll_interval_sec=CONFIG_RELOAD_POLL_INTERVAL_SEC,
)
pipelines_path = DEFAULT_PIPELINES_PATH
initial_bindings = load_bindings(
path=pipelines_path,
default_hotkey=cfg.daemon.hotkey,
default_handler_factory=daemon.build_reference_pipeline,
)
initial_callbacks = daemon.build_hotkey_callbacks(
list(initial_bindings.keys()),
dry_run=args.dry_run,
)
status, error = daemon.apply_pipeline_bindings(initial_bindings, initial_callbacks)
if status != "applied":
raise RuntimeError(f"pipeline setup failed: {error}")
pipeline_reloader = PipelineReloader(
daemon=daemon,
pipelines_path=pipelines_path,
notifier=notifier,
dry_run=args.dry_run,
poll_interval_sec=CONFIG_RELOAD_POLL_INTERVAL_SEC,
)
except Exception as exc:
logging.error("startup failed: %s", exc)
raise SystemExit(1)
@ -390,6 +923,10 @@ def main():
return
shutdown_once.set()
logging.info("%s, shutting down", reason)
if config_reloader is not None:
config_reloader.stop(timeout=2.0)
if pipeline_reloader is not None:
pipeline_reloader.stop(timeout=2.0)
if not daemon.shutdown(timeout=5.0):
logging.warning("timed out waiting for idle state during shutdown")
desktop.request_quit()
@ -397,15 +934,30 @@ def main():
def handle_signal(_sig, _frame):
threading.Thread(target=shutdown, args=("signal received",), daemon=True).start()
def handle_reload_signal(_sig, _frame):
if shutdown_once.is_set():
return
if config_reloader is not None:
threading.Thread(
target=lambda: config_reloader.request_reload("signal SIGHUP", force=True),
daemon=True,
).start()
if pipeline_reloader is not None:
threading.Thread(
target=lambda: pipeline_reloader.request_reload("signal SIGHUP", force=True),
daemon=True,
).start()
signal.signal(signal.SIGINT, handle_signal)
signal.signal(signal.SIGTERM, handle_signal)
signal.signal(signal.SIGHUP, handle_reload_signal)
try:
desktop.start_hotkey_listener(
cfg.daemon.hotkey,
lambda: logging.info("hotkey pressed (dry-run)") if args.dry_run else daemon.toggle(),
)
desktop.start_cancel_listener(lambda: daemon.cancel_recording())
if config_reloader is not None:
config_reloader.start()
if pipeline_reloader is not None:
pipeline_reloader.start()
except Exception as exc:
logging.error("hotkey setup failed: %s", exc)
raise SystemExit(1)
@ -413,6 +965,10 @@ def main():
try:
desktop.run_tray(daemon.get_state, lambda: shutdown("quit requested"))
finally:
if config_reloader is not None:
config_reloader.stop(timeout=2.0)
if pipeline_reloader is not None:
pipeline_reloader.stop(timeout=2.0)
daemon.shutdown(timeout=1.0)

41
src/config.py
View file

@ -51,11 +51,6 @@ class VocabularyConfig:
terms: list[str] = field(default_factory=list)
@dataclass
class DomainInferenceConfig:
enabled: bool = True
@dataclass
class Config:
daemon: DaemonConfig = field(default_factory=DaemonConfig)
@ -63,7 +58,6 @@ class Config:
stt: SttConfig = field(default_factory=SttConfig)
injection: InjectionConfig = field(default_factory=InjectionConfig)
vocabulary: VocabularyConfig = field(default_factory=VocabularyConfig)
domain_inference: DomainInferenceConfig = field(default_factory=DomainInferenceConfig)
def load(path: str | None) -> Config:
@ -124,20 +118,8 @@ def validate(cfg: Config) -> None:
cfg.vocabulary.replacements = _validate_replacements(cfg.vocabulary.replacements)
cfg.vocabulary.terms = _validate_terms(cfg.vocabulary.terms)
if not isinstance(cfg.domain_inference.enabled, bool):
raise ValueError("domain_inference.enabled must be boolean")
def _from_dict(data: dict[str, Any], cfg: Config) -> Config:
if "logging" in data:
raise ValueError("logging section is no longer supported; use -v/--verbose")
if "log_transcript" in data:
raise ValueError("log_transcript is no longer supported; use -v/--verbose")
if "ai" in data:
raise ValueError("ai section is no longer supported")
if "ai_enabled" in data:
raise ValueError("ai_enabled is no longer supported")
has_sections = any(
key in data
for key in (
@ -146,7 +128,6 @@ def _from_dict(data: dict[str, Any], cfg: Config) -> Config:
"stt",
"injection",
"vocabulary",
"domain_inference",
)
)
if has_sections:
@ -155,7 +136,6 @@ def _from_dict(data: dict[str, Any], cfg: Config) -> Config:
stt = _ensure_dict(data.get("stt"), "stt")
injection = _ensure_dict(data.get("injection"), "injection")
vocabulary = _ensure_dict(data.get("vocabulary"), "vocabulary")
domain_inference = _ensure_dict(data.get("domain_inference"), "domain_inference")
if "hotkey" in daemon:
cfg.daemon.hotkey = _as_nonempty_str(daemon["hotkey"], "daemon.hotkey")
@ -176,28 +156,7 @@ def _from_dict(data: dict[str, Any], cfg: Config) -> Config:
cfg.vocabulary.replacements = _as_replacements(vocabulary["replacements"])
if "terms" in vocabulary:
cfg.vocabulary.terms = _as_terms(vocabulary["terms"])
if "max_rules" in vocabulary:
raise ValueError("vocabulary.max_rules is no longer supported")
if "max_terms" in vocabulary:
raise ValueError("vocabulary.max_terms is no longer supported")
if "enabled" in domain_inference:
cfg.domain_inference.enabled = _as_bool(
domain_inference["enabled"], "domain_inference.enabled"
)
if "mode" in domain_inference:
raise ValueError("domain_inference.mode is no longer supported")
return cfg
if "hotkey" in data:
cfg.daemon.hotkey = _as_nonempty_str(data["hotkey"], "hotkey")
if "input" in data:
cfg.recording.input = _as_recording_input(data["input"])
if "whisper_model" in data:
cfg.stt.model = _as_nonempty_str(data["whisper_model"], "whisper_model")
if "whisper_device" in data:
cfg.stt.device = _as_nonempty_str(data["whisper_device"], "whisper_device")
if "injection_backend" in data:
cfg.injection.backend = _as_nonempty_str(data["injection_backend"], "injection_backend")
return cfg

1
src/constants.py
View file

@ -2,6 +2,7 @@ from pathlib import Path
DEFAULT_CONFIG_PATH = Path.home() / ".config" / "aman" / "config.json"
CONFIG_RELOAD_POLL_INTERVAL_SEC = 1.0
RECORD_TIMEOUT_SEC = 300
STT_LANGUAGE = "en"
TRAY_UPDATE_MS = 250

2
src/desktop.py
View file

@ -5,7 +5,7 @@ from typing import Callable, Protocol
class DesktopAdapter(Protocol):
def start_hotkey_listener(self, hotkey: str, callback: Callable[[], None]) -> None:
def set_hotkeys(self, bindings: dict[str, Callable[[], None]]) -> None:
raise NotImplementedError
def start_cancel_listener(self, callback: Callable[[], None]) -> None:

2
src/desktop_wayland.py
View file

@ -4,7 +4,7 @@ from typing import Callable
class WaylandAdapter:
def start_hotkey_listener(self, _hotkey: str, _callback: Callable[[], None]) -> None:
def set_hotkeys(self, _bindings: dict[str, Callable[[], None]]) -> None:
raise SystemExit("Wayland hotkeys are not supported yet.")
def start_cancel_listener(self, _callback: Callable[[], None]) -> None:

107
src/desktop_x11.py
View file

@ -4,7 +4,7 @@ import logging
import threading
import time
import warnings
from typing import Callable, Iterable
from typing import Any, Callable, Iterable
import gi
from Xlib import X, XK, display
@ -43,6 +43,8 @@ class X11Adapter:
self.indicator = None
self.status_icon = None
self.menu = None
self._hotkey_listener_lock = threading.Lock()
self._hotkey_listeners: dict[str, dict[str, Any]] = {}
if AppIndicator3 is not None:
self.indicator = AppIndicator3.Indicator.new(
"aman",
@ -65,15 +67,29 @@ class X11Adapter:
if self.menu:
self.menu.popup(None, None, None, None, 0, _time)
def start_hotkey_listener(self, hotkey: str, callback: Callable[[], None]) -> None:
mods, keysym = self._parse_hotkey(hotkey)
self._validate_hotkey_registration(mods, keysym)
thread = threading.Thread(target=self._listen, args=(mods, keysym, callback), daemon=True)
thread.start()
def set_hotkeys(self, bindings: dict[str, Callable[[], None]]) -> None:
if not isinstance(bindings, dict):
raise ValueError("bindings must be a dictionary")
next_listeners: dict[str, dict[str, Any]] = {}
try:
for hotkey, callback in bindings.items():
if not callable(callback):
raise ValueError(f"callback for hotkey {hotkey} must be callable")
next_listeners[hotkey] = self._spawn_hotkey_listener(hotkey, callback)
except Exception:
for listener in next_listeners.values():
self._stop_hotkey_listener(listener)
raise
with self._hotkey_listener_lock:
previous = self._hotkey_listeners
self._hotkey_listeners = next_listeners
for listener in previous.values():
self._stop_hotkey_listener(listener)
def start_cancel_listener(self, callback: Callable[[], None]) -> None:
mods, keysym = self._parse_hotkey("Escape")
thread = threading.Thread(target=self._listen, args=(mods, keysym, callback), daemon=True)
thread = threading.Thread(target=self._listen, args=(mods, keysym, callback, threading.Event()), daemon=True)
thread.start()
def inject_text(
@ -127,7 +143,14 @@ class X11Adapter:
finally:
self.request_quit()
def _listen(self, mods: int, keysym: int, callback: Callable[[], None]) -> None:
def _listen(
self,
mods: int,
keysym: int,
callback: Callable[[], None],
stop_event: threading.Event,
listener_meta: dict[str, Any] | None = None,
) -> None:
disp = None
root = None
keycode = None
@ -135,14 +158,26 @@ class X11Adapter:
disp = display.Display()
root = disp.screen().root
keycode = self._grab_hotkey(disp, root, mods, keysym)
while True:
if listener_meta is not None:
listener_meta["display"] = disp
listener_meta["root"] = root
listener_meta["keycode"] = keycode
listener_meta["ready"].set()
while not stop_event.is_set():
if disp.pending_events() == 0:
time.sleep(0.05)
continue
ev = disp.next_event()
if ev.type == X.KeyPress and ev.detail == keycode:
state = ev.state & ~(X.LockMask | X.Mod2Mask)
if state == mods:
callback()
except Exception as exc:
logging.error("hotkey listener stopped: %s", exc)
if listener_meta is not None:
listener_meta["error"] = exc
listener_meta["ready"].set()
if not stop_event.is_set():
logging.error("hotkey listener stopped: %s", exc)
finally:
if root is not None and keycode is not None and disp is not None:
try:
@ -150,6 +185,13 @@ class X11Adapter:
disp.sync()
except Exception:
pass
if disp is not None:
try:
disp.close()
except Exception:
pass
if listener_meta is not None:
listener_meta["ready"].set()
def _parse_hotkey(self, hotkey: str):
mods = 0
@ -185,6 +227,51 @@ class X11Adapter:
except Exception:
pass
def _spawn_hotkey_listener(self, hotkey: str, callback: Callable[[], None]) -> dict[str, Any]:
mods, keysym = self._parse_hotkey(hotkey)
self._validate_hotkey_registration(mods, keysym)
stop_event = threading.Event()
listener_meta: dict[str, Any] = {
"hotkey": hotkey,
"mods": mods,
"keysym": keysym,
"stop_event": stop_event,
"display": None,
"root": None,
"keycode": None,
"error": None,
"ready": threading.Event(),
}
thread = threading.Thread(
target=self._listen,
args=(mods, keysym, callback, stop_event, listener_meta),
daemon=True,
)
listener_meta["thread"] = thread
thread.start()
if not listener_meta["ready"].wait(timeout=2.0):
stop_event.set()
raise RuntimeError("hotkey listener setup timed out")
if listener_meta["error"] is not None:
stop_event.set()
raise listener_meta["error"]
if listener_meta["keycode"] is None:
stop_event.set()
raise RuntimeError("hotkey listener failed to initialize")
return listener_meta
def _stop_hotkey_listener(self, listener: dict[str, Any]) -> None:
listener["stop_event"].set()
disp = listener.get("display")
if disp is not None:
try:
disp.close()
except Exception:
pass
thread = listener.get("thread")
if thread is not None:
thread.join(timeout=1.0)
def _grab_hotkey(self, disp, root, mods, keysym):
keycode = disp.keysym_to_keycode(keysym)
if keycode == 0:

86
src/engine.py Normal file
View file

@ -0,0 +1,86 @@
from __future__ import annotations
import logging
from dataclasses import dataclass
from typing import Any, Callable
ALLOWED_FAILURE_POLICIES = {"best_effort", "strict"}
@dataclass(frozen=True)
class PipelineOptions:
failure_policy: str = "best_effort"
def __post_init__(self):
policy = (self.failure_policy or "").strip().lower()
if policy not in ALLOWED_FAILURE_POLICIES:
allowed = ", ".join(sorted(ALLOWED_FAILURE_POLICIES))
raise ValueError(f"failure_policy must be one of: {allowed}")
object.__setattr__(self, "failure_policy", policy)
@dataclass(frozen=True)
class PipelineBinding:
hotkey: str
handler: Callable[[Any, "PipelineLib"], str]
options: PipelineOptions
class PipelineLib:
def __init__(
self,
*,
transcribe_fn: Callable[[Any], str],
llm_fn: Callable[..., str],
):
self._transcribe_fn = transcribe_fn
self._llm_fn = llm_fn
def transcribe(
self,
audio: Any,
*,
hints: list[str] | None = None,
whisper_opts: dict[str, Any] | None = None,
) -> str:
return self._transcribe_fn(
audio,
hints=hints,
whisper_opts=whisper_opts,
)
def llm(
self,
*,
system_prompt: str,
user_prompt: str,
llm_opts: dict[str, Any] | None = None,
) -> str:
return self._llm_fn(
system_prompt=system_prompt,
user_prompt=user_prompt,
llm_opts=llm_opts,
)
class Engine:
def __init__(self, lib: PipelineLib):
self.lib = lib
def run(self, binding: PipelineBinding, audio: Any) -> str:
try:
output = binding.handler(audio, self.lib)
except Exception as exc:
if binding.options.failure_policy == "strict":
raise
logging.error("pipeline failed for hotkey %s: %s", binding.hotkey, exc)
return ""
if output is None:
return ""
if not isinstance(output, str):
raise RuntimeError(
f"pipeline for hotkey {binding.hotkey} returned non-string output"
)
return output

40
src/notify.py Normal file
View file

@ -0,0 +1,40 @@
from __future__ import annotations
class DesktopNotifier:
def __init__(self, app_name: str = "aman"):
self._app_name = app_name
self._notify = None
self._ready = False
self._attempted = False
def send(self, title: str, body: str, *, error: bool = False) -> bool:
_ = error
notify = self._ensure_backend()
if notify is None:
return False
try:
notification = notify.Notification.new(title, body, None)
notification.show()
return True
except Exception:
return False
def _ensure_backend(self):
if self._attempted:
return self._notify if self._ready else None
self._attempted = True
try:
import gi
gi.require_version("Notify", "0.7")
from gi.repository import Notify # type: ignore[import-not-found]
if Notify.init(self._app_name):
self._notify = Notify
self._ready = True
except Exception:
self._notify = None
self._ready = False
return self._notify if self._ready else None

97
src/pipelines_runtime.py Normal file
View file

@ -0,0 +1,97 @@
from __future__ import annotations
import hashlib
import importlib.util
from pathlib import Path
from types import ModuleType
from typing import Any, Callable
from engine import PipelineBinding, PipelineOptions
DEFAULT_PIPELINES_PATH = Path.home() / ".config" / "aman" / "pipelines.py"
def fingerprint(path: Path) -> str | None:
try:
data = path.read_bytes()
except FileNotFoundError:
return None
return hashlib.sha256(data).hexdigest()
def load_bindings(
*,
path: Path,
default_hotkey: str,
default_handler_factory: Callable[[], Callable[[Any, Any], str]],
) -> dict[str, PipelineBinding]:
if not path.exists():
handler = default_handler_factory()
options = PipelineOptions(failure_policy="best_effort")
return {
default_hotkey: PipelineBinding(
hotkey=default_hotkey,
handler=handler,
options=options,
)
}
module = _load_module(path)
return _bindings_from_module(module)
def _load_module(path: Path) -> ModuleType:
module_name = f"aman_user_pipelines_{hash(path.resolve())}"
spec = importlib.util.spec_from_file_location(module_name, str(path))
if spec is None or spec.loader is None:
raise ValueError(f"unable to load pipelines module: {path}")
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
return module
def _bindings_from_module(module: ModuleType) -> dict[str, PipelineBinding]:
raw_pipelines = getattr(module, "HOTKEY_PIPELINES", None)
if not isinstance(raw_pipelines, dict):
raise ValueError("HOTKEY_PIPELINES must be a dictionary")
if not raw_pipelines:
raise ValueError("HOTKEY_PIPELINES cannot be empty")
raw_options = getattr(module, "PIPELINE_OPTIONS", {})
if raw_options is None:
raw_options = {}
if not isinstance(raw_options, dict):
raise ValueError("PIPELINE_OPTIONS must be a dictionary when provided")
bindings: dict[str, PipelineBinding] = {}
for key, handler in raw_pipelines.items():
hotkey = _validate_hotkey(key)
if not callable(handler):
raise ValueError(f"HOTKEY_PIPELINES[{hotkey}] must be callable")
option_data = raw_options.get(hotkey, {})
options = _parse_options(hotkey, option_data)
bindings[hotkey] = PipelineBinding(
hotkey=hotkey,
handler=handler,
options=options,
)
return bindings
def _validate_hotkey(value: Any) -> str:
if not isinstance(value, str):
raise ValueError("pipeline hotkey keys must be strings")
hotkey = value.strip()
if not hotkey:
raise ValueError("pipeline hotkey keys cannot be empty")
return hotkey
def _parse_options(hotkey: str, value: Any) -> PipelineOptions:
if value is None:
return PipelineOptions()
if not isinstance(value, dict):
raise ValueError(f"PIPELINE_OPTIONS[{hotkey}] must be an object")
failure_policy = value.get("failure_policy", "best_effort")
return PipelineOptions(failure_policy=failure_policy)

161
src/vocabulary.py
View file

@ -4,101 +4,7 @@ import re
from dataclasses import dataclass
from typing import Iterable
from config import DomainInferenceConfig, VocabularyConfig
DOMAIN_GENERAL = "general"
DOMAIN_PERSONAL_NAMES = "personal_names"
DOMAIN_SOFTWARE_DEV = "software_dev"
DOMAIN_OPS_INFRA = "ops_infra"
DOMAIN_BUSINESS = "business"
DOMAIN_MEDICAL_LEGAL = "medical_legal"
DOMAIN_ORDER = (
DOMAIN_PERSONAL_NAMES,
DOMAIN_SOFTWARE_DEV,
DOMAIN_OPS_INFRA,
DOMAIN_BUSINESS,
DOMAIN_MEDICAL_LEGAL,
)
DOMAIN_KEYWORDS = {
DOMAIN_SOFTWARE_DEV: {
"api",
"bug",
"code",
"commit",
"docker",
"function",
"git",
"github",
"javascript",
"python",
"refactor",
"repository",
"typescript",
"unit",
"test",
},
DOMAIN_OPS_INFRA: {
"cluster",
"container",
"deploy",
"deployment",
"incident",
"kubernetes",
"monitoring",
"nginx",
"pod",
"prod",
"service",
"systemd",
"terraform",
},
DOMAIN_BUSINESS: {
"budget",
"client",
"deadline",
"finance",
"invoice",
"meeting",
"milestone",
"project",
"quarter",
"roadmap",
"sales",
"stakeholder",
},
DOMAIN_MEDICAL_LEGAL: {
"agreement",
"case",
"claim",
"compliance",
"contract",
"diagnosis",
"liability",
"patient",
"prescription",
"regulation",
"symptom",
"treatment",
},
}
DOMAIN_PHRASES = {
DOMAIN_SOFTWARE_DEV: ("pull request", "code review", "integration test"),
DOMAIN_OPS_INFRA: ("on call", "service restart", "roll back"),
DOMAIN_BUSINESS: ("follow up", "action items", "meeting notes"),
DOMAIN_MEDICAL_LEGAL: ("terms and conditions", "medical record", "legal review"),
}
GREETING_TOKENS = {"hello", "hi", "hey", "good morning", "good afternoon", "good evening"}
@dataclass(frozen=True)
class DomainResult:
name: str
confidence: float
from config import VocabularyConfig
@dataclass(frozen=True)
@ -108,10 +14,9 @@ class _ReplacementView:
class VocabularyEngine:
def __init__(self, vocab_cfg: VocabularyConfig, domain_cfg: DomainInferenceConfig):
def __init__(self, vocab_cfg: VocabularyConfig):
self._replacements = [_ReplacementView(r.source, r.target) for r in vocab_cfg.replacements]
self._terms = list(vocab_cfg.terms)
self._domain_enabled = bool(domain_cfg.enabled)
self._replacement_map = {
_normalize_key(rule.source): rule.target for rule in self._replacements
@ -161,55 +66,6 @@ class VocabularyEngine:
used += addition
return "\n".join(out)
def infer_domain(self, text: str) -> DomainResult:
if not self._domain_enabled:
return DomainResult(name=DOMAIN_GENERAL, confidence=0.0)
normalized = text.casefold()
tokens = re.findall(r"[a-z0-9+#./_-]+", normalized)
if not tokens:
return DomainResult(name=DOMAIN_GENERAL, confidence=0.0)
scores = {domain: 0 for domain in DOMAIN_ORDER}
for token in tokens:
for domain, keywords in DOMAIN_KEYWORDS.items():
if token in keywords:
scores[domain] += 2
for domain, phrases in DOMAIN_PHRASES.items():
for phrase in phrases:
if phrase in normalized:
scores[domain] += 2
if any(token in GREETING_TOKENS for token in tokens):
scores[DOMAIN_PERSONAL_NAMES] += 1
# Boost domains from configured dictionary terms and replacement targets.
dictionary_tokens = self._dictionary_tokens()
for token in dictionary_tokens:
for domain, keywords in DOMAIN_KEYWORDS.items():
if token in keywords and token in tokens:
scores[domain] += 1
top_domain = DOMAIN_GENERAL
top_score = 0
total_score = 0
for domain in DOMAIN_ORDER:
score = scores[domain]
total_score += score
if score > top_score:
top_score = score
top_domain = domain
if top_score < 2 or total_score == 0:
return DomainResult(name=DOMAIN_GENERAL, confidence=0.0)
confidence = top_score / total_score
if confidence < 0.45:
return DomainResult(name=DOMAIN_GENERAL, confidence=0.0)
return DomainResult(name=top_domain, confidence=round(confidence, 2))
def _build_stt_hotwords(self, *, limit: int, char_budget: int) -> str:
items = _dedupe_preserve_order(
[rule.target for rule in self._replacements] + self._terms
@ -236,19 +92,6 @@ class VocabularyEngine:
return ""
return prefix + hotwords
def _dictionary_tokens(self) -> set[str]:
values: list[str] = []
for rule in self._replacements:
values.append(rule.source)
values.append(rule.target)
values.extend(self._terms)
tokens: set[str] = set()
for value in values:
for token in re.findall(r"[a-z0-9+#./_-]+", value.casefold()):
tokens.add(token)
return tokens
def _build_replacement_pattern(sources: Iterable[str]) -> re.Pattern[str] | None:
unique_sources = _dedupe_preserve_order(list(sources))

209
tests/test_aman.py
View file

@ -1,3 +1,4 @@
import json
import os
import sys
import tempfile
@ -11,14 +12,25 @@ if str(SRC) not in sys.path:
sys.path.insert(0, str(SRC))
import aman
from config import Config, VocabularyReplacement
from config import Config, VocabularyReplacement, redacted_dict
from engine import PipelineBinding, PipelineOptions
class FakeDesktop:
def __init__(self):
self.inject_calls = []
self.hotkey_updates = []
self.hotkeys = {}
self.cancel_callback = None
self.quit_calls = 0
def set_hotkeys(self, bindings):
self.hotkeys = dict(bindings)
self.hotkey_updates.append(tuple(sorted(bindings.keys())))
def start_cancel_listener(self, callback):
self.cancel_callback = callback
def inject_text(
self,
text: str,
@ -76,12 +88,30 @@ class FakeAIProcessor:
def process(self, text, lang="en", **_kwargs):
return text
def chat(self, *, system_prompt, user_prompt, llm_opts=None):
_ = system_prompt
opts = llm_opts or {}
if "response_format" in opts:
payload = json.loads(user_prompt)
transcript = payload.get("transcript", "")
return json.dumps({"cleaned_text": transcript})
return "general"
class FakeAudio:
def __init__(self, size: int):
self.size = size
class FakeNotifier:
def __init__(self):
self.events = []
def send(self, title, body, *, error=False):
self.events.append((title, body, error))
return True
class DaemonTests(unittest.TestCase):
def _config(self) -> Config:
cfg = Config()
@ -103,19 +133,23 @@ class DaemonTests(unittest.TestCase):
@patch("aman.stop_audio_recording", return_value=FakeAudio(8))
@patch("aman.start_audio_recording", return_value=(object(), object()))
def test_toggle_start_stop_injects_text(self, _start_mock, _stop_mock):
def test_hotkey_start_stop_injects_text(self, _start_mock, _stop_mock):
desktop = FakeDesktop()
daemon = self._build_daemon(desktop, FakeModel(), verbose=False)
daemon._start_stop_worker = (
lambda stream, record, trigger, process_audio: daemon._stop_and_process(
stream, record, trigger, process_audio
stream,
record,
trigger,
process_audio,
daemon._pending_worker_hotkey,
)
)
daemon.toggle()
daemon.handle_hotkey(daemon.cfg.daemon.hotkey)
self.assertEqual(daemon.get_state(), aman.State.RECORDING)
daemon.toggle()
daemon.handle_hotkey(daemon.cfg.daemon.hotkey)
self.assertEqual(daemon.get_state(), aman.State.IDLE)
self.assertEqual(desktop.inject_calls, [("hello world", "clipboard", False)])
@ -131,7 +165,7 @@ class DaemonTests(unittest.TestCase):
)
)
daemon.toggle()
daemon.handle_hotkey(daemon.cfg.daemon.hotkey)
self.assertEqual(daemon.get_state(), aman.State.RECORDING)
self.assertTrue(daemon.shutdown(timeout=0.2))
@ -153,8 +187,8 @@ class DaemonTests(unittest.TestCase):
)
)
daemon.toggle()
daemon.toggle()
daemon.handle_hotkey(daemon.cfg.daemon.hotkey)
daemon.handle_hotkey(daemon.cfg.daemon.hotkey)
self.assertEqual(desktop.inject_calls, [("good morning Marta", "clipboard", False)])
@ -223,8 +257,8 @@ class DaemonTests(unittest.TestCase):
)
)
daemon.toggle()
daemon.toggle()
daemon.handle_hotkey(daemon.cfg.daemon.hotkey)
daemon.handle_hotkey(daemon.cfg.daemon.hotkey)
self.assertEqual(desktop.inject_calls, [("hello world", "clipboard", True)])
@ -239,6 +273,161 @@ class DaemonTests(unittest.TestCase):
any("DEBUG:root:state: idle -> recording" in line for line in logs.output)
)
def test_hotkey_dispatches_to_matching_pipeline(self):
desktop = FakeDesktop()
daemon = self._build_daemon(desktop, FakeModel(), verbose=False)
daemon.set_pipeline_bindings(
{
"Super+m": PipelineBinding(
hotkey="Super+m",
handler=lambda _audio, _lib: "default",
options=PipelineOptions(failure_policy="best_effort"),
),
"Super+Shift+m": PipelineBinding(
hotkey="Super+Shift+m",
handler=lambda _audio, _lib: "caps",
options=PipelineOptions(failure_policy="best_effort"),
),
}
)
out = daemon._run_pipeline(object(), "Super+Shift+m")
self.assertEqual(out, "caps")
def test_try_apply_config_applies_new_runtime_settings(self):
desktop = FakeDesktop()
cfg = self._config()
daemon = self._build_daemon(desktop, FakeModel(), cfg=cfg, verbose=False)
daemon._stt_hint_kwargs_cache = {"hotwords": "old"}
candidate = Config()
candidate.injection.backend = "injection"
candidate.vocabulary.replacements = [
VocabularyReplacement(source="Martha", target="Marta"),
]
status, changed, error = daemon.try_apply_config(candidate)
self.assertEqual(status, "applied")
self.assertEqual(error, "")
self.assertIn("injection.backend", changed)
self.assertIn("vocabulary.replacements", changed)
self.assertEqual(daemon.cfg.injection.backend, "injection")
self.assertEqual(
daemon.vocabulary.apply_deterministic_replacements("Martha"),
"Marta",
)
self.assertIsNone(daemon._stt_hint_kwargs_cache)
def test_try_apply_config_reloads_stt_model(self):
desktop = FakeDesktop()
cfg = self._config()
daemon = self._build_daemon(desktop, FakeModel(), cfg=cfg, verbose=False)
candidate = Config()
candidate.stt.model = "small"
next_model = FakeModel(text="from-new-model")
with patch("aman._build_whisper_model", return_value=next_model):
status, changed, error = daemon.try_apply_config(candidate)
self.assertEqual(status, "applied")
self.assertEqual(error, "")
self.assertIn("stt.model", changed)
self.assertIs(daemon.model, next_model)
def test_try_apply_config_is_deferred_while_busy(self):
desktop = FakeDesktop()
daemon = self._build_daemon(desktop, FakeModel(), verbose=False)
daemon.set_state(aman.State.RECORDING)
status, changed, error = daemon.try_apply_config(Config())
self.assertEqual(status, "deferred")
self.assertEqual(changed, [])
self.assertIn("busy", error)
class ConfigReloaderTests(unittest.TestCase):
def _write_config(self, path: Path, cfg: Config):
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(json.dumps(redacted_dict(cfg)), encoding="utf-8")
def _daemon_for_path(self, path: Path) -> tuple[aman.Daemon, FakeDesktop]:
cfg = Config()
self._write_config(path, cfg)
desktop = FakeDesktop()
with patch("aman._build_whisper_model", return_value=FakeModel()), patch(
"aman.LlamaProcessor", return_value=FakeAIProcessor()
):
daemon = aman.Daemon(cfg, desktop, verbose=False)
return daemon, desktop
def test_reloader_applies_changed_config(self):
with tempfile.TemporaryDirectory() as td:
path = Path(td) / "config.json"
daemon, _desktop = self._daemon_for_path(path)
notifier = FakeNotifier()
reloader = aman.ConfigReloader(
daemon=daemon,
config_path=path,
notifier=notifier,
poll_interval_sec=0.01,
)
updated = Config()
updated.injection.backend = "injection"
self._write_config(path, updated)
reloader.tick()
self.assertEqual(daemon.cfg.injection.backend, "injection")
self.assertTrue(any(evt[0] == "Config Reloaded" and not evt[2] for evt in notifier.events))
def test_reloader_keeps_last_good_config_when_invalid(self):
with tempfile.TemporaryDirectory() as td:
path = Path(td) / "config.json"
daemon, _desktop = self._daemon_for_path(path)
notifier = FakeNotifier()
reloader = aman.ConfigReloader(
daemon=daemon,
config_path=path,
notifier=notifier,
poll_interval_sec=0.01,
)
path.write_text('{"injection":{"backend":"invalid"}}', encoding="utf-8")
reloader.tick()
self.assertEqual(daemon.cfg.injection.backend, "clipboard")
fail_events = [evt for evt in notifier.events if evt[0] == "Config Reload Failed"]
self.assertEqual(len(fail_events), 1)
reloader.tick()
fail_events = [evt for evt in notifier.events if evt[0] == "Config Reload Failed"]
self.assertEqual(len(fail_events), 1)
def test_reloader_defers_apply_until_idle(self):
with tempfile.TemporaryDirectory() as td:
path = Path(td) / "config.json"
daemon, _desktop = self._daemon_for_path(path)
notifier = FakeNotifier()
reloader = aman.ConfigReloader(
daemon=daemon,
config_path=path,
notifier=notifier,
poll_interval_sec=0.01,
)
updated = Config()
updated.injection.backend = "injection"
self._write_config(path, updated)
daemon.set_state(aman.State.RECORDING)
reloader.tick()
self.assertEqual(daemon.cfg.injection.backend, "clipboard")
daemon.set_state(aman.State.IDLE)
reloader.tick()
self.assertEqual(daemon.cfg.injection.backend, "injection")
class LockTests(unittest.TestCase):
def test_lock_rejects_second_instance(self):

89
tests/test_config.py
View file

@ -26,7 +26,6 @@ class ConfigTests(unittest.TestCase):
self.assertFalse(cfg.injection.remove_transcription_from_clipboard)
self.assertEqual(cfg.vocabulary.replacements, [])
self.assertEqual(cfg.vocabulary.terms, [])
self.assertTrue(cfg.domain_inference.enabled)
self.assertTrue(missing.exists())
written = json.loads(missing.read_text(encoding="utf-8"))
@ -48,7 +47,6 @@ class ConfigTests(unittest.TestCase):
],
"terms": ["Systemd", "Kubernetes"],
},
"domain_inference": {"enabled": True},
}
with tempfile.TemporaryDirectory() as td:
path = Path(td) / "config.json"
@ -66,7 +64,6 @@ class ConfigTests(unittest.TestCase):
self.assertEqual(cfg.vocabulary.replacements[0].source, "Martha")
self.assertEqual(cfg.vocabulary.replacements[0].target, "Marta")
self.assertEqual(cfg.vocabulary.terms, ["Systemd", "Kubernetes"])
self.assertTrue(cfg.domain_inference.enabled)
def test_super_modifier_hotkey_is_valid(self):
payload = {"daemon": {"hotkey": "Super+m"}}
@ -98,28 +95,6 @@ class ConfigTests(unittest.TestCase):
):
load(str(path))
def test_loads_legacy_keys(self):
payload = {
"hotkey": "Alt+m",
"input": "Mic",
"whisper_model": "tiny",
"whisper_device": "cpu",
"injection_backend": "clipboard",
}
with tempfile.TemporaryDirectory() as td:
path = Path(td) / "config.json"
path.write_text(json.dumps(payload), encoding="utf-8")
cfg = load(str(path))
self.assertEqual(cfg.daemon.hotkey, "Alt+m")
self.assertEqual(cfg.recording.input, "Mic")
self.assertEqual(cfg.stt.model, "tiny")
self.assertEqual(cfg.stt.device, "cpu")
self.assertEqual(cfg.injection.backend, "clipboard")
self.assertFalse(cfg.injection.remove_transcription_from_clipboard)
self.assertEqual(cfg.vocabulary.replacements, [])
def test_invalid_injection_backend_raises(self):
payload = {"injection": {"backend": "invalid"}}
with tempfile.TemporaryDirectory() as td:
@ -138,41 +113,20 @@ class ConfigTests(unittest.TestCase):
with self.assertRaisesRegex(ValueError, "injection.remove_transcription_from_clipboard"):
load(str(path))
def test_removed_ai_section_raises(self):
payload = {"ai": {"enabled": True}}
def test_unknown_top_level_fields_are_ignored(self):
payload = {
"custom_a": {"enabled": True},
"custom_b": {"nested": "value"},
"custom_c": 123,
}
with tempfile.TemporaryDirectory() as td:
path = Path(td) / "config.json"
path.write_text(json.dumps(payload), encoding="utf-8")
with self.assertRaisesRegex(ValueError, "ai section is no longer supported"):
load(str(path))
cfg = load(str(path))
def test_removed_legacy_ai_enabled_raises(self):
payload = {"ai_enabled": True}
with tempfile.TemporaryDirectory() as td:
path = Path(td) / "config.json"
path.write_text(json.dumps(payload), encoding="utf-8")
with self.assertRaisesRegex(ValueError, "ai_enabled is no longer supported"):
load(str(path))
def test_removed_logging_section_raises(self):
payload = {"logging": {"log_transcript": True}}
with tempfile.TemporaryDirectory() as td:
path = Path(td) / "config.json"
path.write_text(json.dumps(payload), encoding="utf-8")
with self.assertRaisesRegex(ValueError, "no longer supported"):
load(str(path))
def test_removed_legacy_log_transcript_raises(self):
payload = {"log_transcript": True}
with tempfile.TemporaryDirectory() as td:
path = Path(td) / "config.json"
path.write_text(json.dumps(payload), encoding="utf-8")
with self.assertRaisesRegex(ValueError, "no longer supported"):
load(str(path))
self.assertEqual(cfg.daemon.hotkey, "Cmd+m")
self.assertEqual(cfg.injection.backend, "clipboard")
def test_conflicting_replacements_raise(self):
payload = {
@ -224,32 +178,15 @@ class ConfigTests(unittest.TestCase):
with self.assertRaisesRegex(ValueError, "wildcard"):
load(str(path))
def test_removed_domain_mode_raises(self):
payload = {"domain_inference": {"mode": "heuristic"}}
def test_unknown_vocabulary_fields_are_ignored(self):
payload = {"vocabulary": {"custom_limit": 100, "custom_extra": 200, "terms": ["Docker"]}}
with tempfile.TemporaryDirectory() as td:
path = Path(td) / "config.json"
path.write_text(json.dumps(payload), encoding="utf-8")
with self.assertRaisesRegex(ValueError, "domain_inference.mode is no longer supported"):
load(str(path))
cfg = load(str(path))
def test_removed_vocabulary_max_rules_raises(self):
payload = {"vocabulary": {"max_rules": 100}}
with tempfile.TemporaryDirectory() as td:
path = Path(td) / "config.json"
path.write_text(json.dumps(payload), encoding="utf-8")
with self.assertRaisesRegex(ValueError, "vocabulary.max_rules is no longer supported"):
load(str(path))
def test_removed_vocabulary_max_terms_raises(self):
payload = {"vocabulary": {"max_terms": 100}}
with tempfile.TemporaryDirectory() as td:
path = Path(td) / "config.json"
path.write_text(json.dumps(payload), encoding="utf-8")
with self.assertRaisesRegex(ValueError, "vocabulary.max_terms is no longer supported"):
load(str(path))
self.assertEqual(cfg.vocabulary.terms, ["Docker"])
if __name__ == "__main__":

92
tests/test_engine.py Normal file
View file

@ -0,0 +1,92 @@
import sys
import unittest
from pathlib import Path
ROOT = Path(__file__).resolve().parents[1]
SRC = ROOT / "src"
if str(SRC) not in sys.path:
sys.path.insert(0, str(SRC))
from engine import Engine, PipelineBinding, PipelineLib, PipelineOptions
class EngineTests(unittest.TestCase):
def test_best_effort_pipeline_failure_returns_empty_string(self):
lib = PipelineLib(
transcribe_fn=lambda *_args, **_kwargs: "text",
llm_fn=lambda **_kwargs: "result",
)
engine = Engine(lib)
def failing_pipeline(_audio, _lib):
raise RuntimeError("boom")
binding = PipelineBinding(
hotkey="Cmd+m",
handler=failing_pipeline,
options=PipelineOptions(failure_policy="best_effort"),
)
out = engine.run(binding, object())
self.assertEqual(out, "")
def test_strict_pipeline_failure_raises(self):
lib = PipelineLib(
transcribe_fn=lambda *_args, **_kwargs: "text",
llm_fn=lambda **_kwargs: "result",
)
engine = Engine(lib)
def failing_pipeline(_audio, _lib):
raise RuntimeError("boom")
binding = PipelineBinding(
hotkey="Cmd+m",
handler=failing_pipeline,
options=PipelineOptions(failure_policy="strict"),
)
with self.assertRaisesRegex(RuntimeError, "boom"):
engine.run(binding, object())
def test_pipeline_lib_forwards_arguments(self):
seen = {}
def transcribe_fn(audio, *, hints=None, whisper_opts=None):
seen["audio"] = audio
seen["hints"] = hints
seen["whisper_opts"] = whisper_opts
return "hello"
def llm_fn(*, system_prompt, user_prompt, llm_opts=None):
seen["system_prompt"] = system_prompt
seen["user_prompt"] = user_prompt
seen["llm_opts"] = llm_opts
return "world"
lib = PipelineLib(
transcribe_fn=transcribe_fn,
llm_fn=llm_fn,
)
audio = object()
self.assertEqual(
lib.transcribe(audio, hints=["Docker"], whisper_opts={"vad_filter": True}),
"hello",
)
self.assertEqual(
lib.llm(
system_prompt="sys",
user_prompt="user",
llm_opts={"temperature": 0.2},
),
"world",
)
self.assertIs(seen["audio"], audio)
self.assertEqual(seen["hints"], ["Docker"])
self.assertEqual(seen["whisper_opts"], {"vad_filter": True})
self.assertEqual(seen["system_prompt"], "sys")
self.assertEqual(seen["user_prompt"], "user")
self.assertEqual(seen["llm_opts"], {"temperature": 0.2})
if __name__ == "__main__":
unittest.main()

109
tests/test_pipelines_runtime.py Normal file
View file

@ -0,0 +1,109 @@
import tempfile
import textwrap
import sys
import unittest
from pathlib import Path
ROOT = Path(__file__).resolve().parents[1]
SRC = ROOT / "src"
if str(SRC) not in sys.path:
sys.path.insert(0, str(SRC))
from pipelines_runtime import fingerprint, load_bindings
class PipelinesRuntimeTests(unittest.TestCase):
def test_missing_file_uses_default_binding(self):
with tempfile.TemporaryDirectory() as td:
path = Path(td) / "pipelines.py"
called = {"count": 0}
def factory():
called["count"] += 1
def handler(_audio, _lib):
return "ok"
return handler
bindings = load_bindings(
path=path,
default_hotkey="Cmd+m",
default_handler_factory=factory,
)
self.assertEqual(list(bindings.keys()), ["Cmd+m"])
self.assertEqual(called["count"], 1)
def test_loads_module_bindings_and_options(self):
with tempfile.TemporaryDirectory() as td:
path = Path(td) / "pipelines.py"
path.write_text(
textwrap.dedent(
"""
def p1(audio, lib):
return "one"
def p2(audio, lib):
return "two"
HOTKEY_PIPELINES = {
"Cmd+m": p1,
"Ctrl+space": p2,
}
PIPELINE_OPTIONS = {
"Ctrl+space": {"failure_policy": "strict"},
}
"""
),
encoding="utf-8",
)
bindings = load_bindings(
path=path,
default_hotkey="Cmd+m",
default_handler_factory=lambda: (lambda _audio, _lib: "default"),
)
self.assertEqual(sorted(bindings.keys()), ["Cmd+m", "Ctrl+space"])
self.assertEqual(bindings["Cmd+m"].options.failure_policy, "best_effort")
self.assertEqual(bindings["Ctrl+space"].options.failure_policy, "strict")
def test_invalid_options_fail(self):
with tempfile.TemporaryDirectory() as td:
path = Path(td) / "pipelines.py"
path.write_text(
textwrap.dedent(
"""
def p(audio, lib):
return "ok"
HOTKEY_PIPELINES = {"Cmd+m": p}
PIPELINE_OPTIONS = {"Cmd+m": {"failure_policy": "invalid"}}
"""
),
encoding="utf-8",
)
with self.assertRaisesRegex(ValueError, "failure_policy"):
load_bindings(
path=path,
default_hotkey="Cmd+m",
default_handler_factory=lambda: (lambda _audio, _lib: "default"),
)
def test_fingerprint_changes_with_content(self):
with tempfile.TemporaryDirectory() as td:
path = Path(td) / "pipelines.py"
self.assertIsNone(fingerprint(path))
path.write_text("HOTKEY_PIPELINES = {}", encoding="utf-8")
first = fingerprint(path)
path.write_text("HOTKEY_PIPELINES = {'Cmd+m': lambda a, l: ''}", encoding="utf-8")
second = fingerprint(path)
self.assertIsNotNone(first)
self.assertIsNotNone(second)
self.assertNotEqual(first, second)
if __name__ == "__main__":
unittest.main()

31
tests/test_vocabulary.py
View file

@ -7,18 +7,17 @@ SRC = ROOT / "src"
if str(SRC) not in sys.path:
sys.path.insert(0, str(SRC))
from config import DomainInferenceConfig, VocabularyConfig, VocabularyReplacement
from vocabulary import DOMAIN_GENERAL, VocabularyEngine
from config import VocabularyConfig, VocabularyReplacement
from vocabulary import VocabularyEngine
class VocabularyEngineTests(unittest.TestCase):
def _engine(self, replacements=None, terms=None, domain_enabled=True):
def _engine(self, replacements=None, terms=None):
vocab = VocabularyConfig(
replacements=replacements or [],
terms=terms or [],
)
domain = DomainInferenceConfig(enabled=domain_enabled)
return VocabularyEngine(vocab, domain)
return VocabularyEngine(vocab)
def test_boundary_aware_replacement(self):
engine = self._engine(
@ -50,27 +49,5 @@ class VocabularyEngineTests(unittest.TestCase):
self.assertLessEqual(len(hotwords), 1024)
self.assertLessEqual(len(prompt), 600)
def test_domain_inference_general_fallback(self):
engine = self._engine()
result = engine.infer_domain("please call me later")
self.assertEqual(result.name, DOMAIN_GENERAL)
self.assertEqual(result.confidence, 0.0)
def test_domain_inference_for_technical_text(self):
engine = self._engine(terms=["Docker", "Systemd"])
result = engine.infer_domain("restart Docker and systemd service on prod")
self.assertNotEqual(result.name, DOMAIN_GENERAL)
self.assertGreater(result.confidence, 0.0)
def test_domain_inference_can_be_disabled(self):
engine = self._engine(domain_enabled=False)
result = engine.infer_domain("please restart docker")
self.assertEqual(result.name, DOMAIN_GENERAL)
self.assertEqual(result.confidence, 0.0)
if __name__ == "__main__":
unittest.main()