Rename project to Saiki and unify CLI

saiki/importer.py

@@ -0,0 +1,112 @@
+"""Generate TTS audio and add sentence notes to Anki."""
+
+from __future__ import annotations
+
+import os
+import csv
+import shutil
+import subprocess
+import tempfile
+import time
+from dataclasses import dataclass
+from typing import Callable
+
+from .ankiconnect import anki_request
+from .config import Config
+
+
+@dataclass(frozen=True)
+class ImportResult:
+    processed: int
+    added: int
+    failed: int
+
+
+def parse_tags(value: str | None) -> list[str]:
+    tags = ["text-to-speech"]
+    if value:
+        tags.extend(tag.strip() for tag in value.split(",") if tag.strip())
+    else:
+        tags.append("AI-generated")
+    return tags
+
+
+def require_command(name: str) -> None:
+    if shutil.which(name) is None:
+        raise RuntimeError(f"Required command not found: {name}")
+
+
+def generate_tts(sentence: str, raw_output: str, lang_code: str, tld: str) -> None:
+    subprocess.run(["gtts-cli", sentence, "--lang", lang_code, "--tld", tld, "--output", raw_output], check=True)
+
+
+def speed_audio(raw_output: str, output_path: str, tempo: float) -> None:
+    subprocess.run(
+        ["ffmpeg", "-loglevel", "error", "-i", raw_output, "-filter:a", f"atempo={tempo}", "-y", output_path],
+        stdin=subprocess.DEVNULL,
+        check=True,
+    )
+
+
+def read_sentences(path: str) -> list[str]:
+    expanded = os.path.expanduser(path)
+    if expanded.lower().endswith((".tsv", ".csv")):
+        delimiter = "\t" if expanded.lower().endswith(".tsv") else ","
+        with open(expanded, "r", encoding="utf-8", newline="") as fh:
+            reader = csv.DictReader(fh, delimiter=delimiter)
+            if reader.fieldnames and "sentence" in reader.fieldnames:
+                return [row["sentence"].strip() for row in reader if row.get("sentence", "").strip()]
+        raise RuntimeError("TSV/CSV sentence imports must include a 'sentence' header.")
+
+    with open(expanded, "r", encoding="utf-8") as fh:
+        return [line.strip() for line in fh if line.strip()]
+
+
+def import_sentences(
+    config: Config,
+    lang: str,
+    sentence_file: str | None = None,
+    tags_value: str | None = None,
+    request: Callable = anki_request,
+) -> ImportResult:
+    require_command("gtts-cli")
+    require_command("ffmpeg")
+
+    language = config.language(lang)
+    decks = list(language.get("decks", []))
+    if not decks:
+        raise RuntimeError(f"No deck configured for language: {lang}")
+    deck = decks[0]
+
+    source = os.path.expanduser(sentence_file) if sentence_file else config.sentence_file_for(lang)
+    sentences = read_sentences(source)
+    tags = parse_tags(tags_value)
+    front_field = config.fields.get("front", "Front")
+    back_field = config.fields.get("back", "Back")
+    added = 0
+    failed = 0
+
+    with tempfile.TemporaryDirectory() as temp_dir:
+        for sentence in sentences:
+            basename = f"tts_{time.strftime('%Y%m%d_%H%M%S')}_{lang}_{os.getpid()}_{added + failed}"
+            raw_output = os.path.join(temp_dir, f"{basename}_original.mp3")
+            output_path = os.path.join(temp_dir, f"{basename}.mp3")
+            try:
+                generate_tts(sentence, raw_output, str(language["tts_code"]), str(language["tts_tld"]))
+                speed_audio(raw_output, output_path, float(language["tts_tempo"]))
+                request(
+                    "addNote",
+                    url=config.anki_connect_url,
+                    note={
+                        "deckName": deck,
+                        "modelName": config.note_model,
+                        "fields": {front_field: "", back_field: sentence},
+                        "options": {"allowDuplicate": False},
+                        "tags": tags,
+                        "audio": [{"path": output_path, "filename": f"{basename}.mp3", "fields": [front_field]}],
+                    },
+                )
+                added += 1
+            except Exception:
+                failed += 1
+    return ImportResult(processed=len(sentences), added=added, failed=failed)