Stirling-PDF/scripts/translations/auto_translate.py
stirlingbot[bot] d5509ec517
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Signed-off-by: stirlingbot[bot] <stirlingbot[bot]@users.noreply.github.com>
2025-12-18 15:52:00 +00:00

385 lines
12 KiB
Python

#!/usr/bin/env python3
"""
Automated Translation Pipeline
Extracts, translates, merges, and beautifies translations for a language.
TOML format only.
"""
import json
import sys
import argparse
import os
import subprocess
from pathlib import Path
import time
import tomllib
def run_command(cmd, description=""):
"""Run a shell command and return success status."""
if description:
print(f"\n{'=' * 60}")
print(f"Step: {description}")
print(f"{'=' * 60}")
result = subprocess.run(cmd, shell=True, capture_output=True, text=True)
if result.stdout:
print(result.stdout)
if result.stderr:
print(result.stderr, file=sys.stderr)
return result.returncode == 0
def find_translation_file(lang_dir):
"""Find translation file in language directory."""
toml_file = lang_dir / "translation.toml"
if toml_file.exists():
return toml_file
return None
def load_translation_file(file_path):
"""Load TOML translation file."""
with open(file_path, "rb") as f:
return tomllib.load(f)
def extract_untranslated(language_code, batch_size=500, include_existing=False):
"""Extract untranslated entries and split into batches."""
mode = (
"all untranslated (including existing)" if include_existing else "new (missing)"
)
print(f"\n🔍 Extracting {mode} entries for {language_code}...")
# Load files
golden_path = find_translation_file(Path("frontend/public/locales/en-GB"))
lang_path = find_translation_file(Path(f"frontend/public/locales/{language_code}"))
if not golden_path:
print("Error: Golden truth file not found in frontend/public/locales/en-GB")
return None
if not lang_path:
print(
f"Error: Language file not found in frontend/public/locales/{language_code}"
)
return None
def flatten_dict(d, parent_key="", separator="."):
items = []
for k, v in d.items():
new_key = f"{parent_key}{separator}{k}" if parent_key else k
if isinstance(v, dict):
items.extend(flatten_dict(v, new_key, separator).items())
else:
items.append((new_key, str(v)))
return dict(items)
golden = load_translation_file(golden_path)
lang_data = load_translation_file(lang_path)
if not golden or not lang_data:
print("Error: Failed to load translation files")
return None
golden_flat = flatten_dict(golden)
lang_flat = flatten_dict(lang_data)
# Find untranslated
untranslated = {}
for key, value in golden_flat.items():
if include_existing:
# Include missing keys, keys with English values, and [UNTRANSLATED] keys
if (
key not in lang_flat
or lang_flat.get(key) == value
or (
isinstance(lang_flat.get(key), str)
and lang_flat.get(key).startswith("[UNTRANSLATED]")
)
):
untranslated[key] = value
else:
# Only include missing keys (not in target file at all)
if key not in lang_flat:
untranslated[key] = value
total = len(untranslated)
print(f"Found {total} {mode} entries")
if total == 0:
print("✓ Language is already complete!")
return []
# Split into batches
entries = list(untranslated.items())
num_batches = (total + batch_size - 1) // batch_size
batch_files = []
lang_code_safe = language_code.replace("-", "_")
for i in range(num_batches):
start = i * batch_size
end = min((i + 1) * batch_size, total)
batch = dict(entries[start:end])
filename = f"{lang_code_safe}_batch_{i + 1}_of_{num_batches}.json"
with open(filename, "w", encoding="utf-8") as f:
json.dump(batch, f, ensure_ascii=False, separators=(",", ":"))
batch_files.append(filename)
print(f" Created {filename} with {len(batch)} entries")
return batch_files
def translate_batches(batch_files, language_code, api_key, timeout=600):
"""Translate all batch files using GPT-5."""
if not batch_files:
return []
print(f"\n🤖 Translating {len(batch_files)} batches using GPT-5...")
print(f"Timeout: {timeout}s ({timeout // 60} minutes) per batch")
translated_files = []
for i, batch_file in enumerate(batch_files, 1):
print(f"\n[{i}/{len(batch_files)}] Translating {batch_file}...")
# Always pass API key since it's required
cmd = f'python3 scripts/translations/batch_translator.py "{batch_file}" --language {language_code} --api-key "{api_key}"'
# Run with timeout
result = subprocess.run(
cmd, shell=True, capture_output=True, text=True, timeout=timeout
)
if result.stdout:
print(result.stdout)
if result.stderr:
print(result.stderr, file=sys.stderr)
if result.returncode != 0:
print(f"✗ Failed to translate {batch_file}")
return None
translated_file = batch_file.replace(".json", "_translated.json")
translated_files.append(translated_file)
# Small delay between batches
if i < len(batch_files):
time.sleep(1)
print(f"\n✓ All {len(batch_files)} batches translated successfully")
return translated_files
def merge_translations(translated_files, language_code):
"""Merge all translated batch files."""
if not translated_files:
return None
print(f"\n🔗 Merging {len(translated_files)} translated batches...")
merged = {}
for filename in translated_files:
if not Path(filename).exists():
print(f"Error: Translated file not found: {filename}")
return None
with open(filename, "r", encoding="utf-8") as f:
merged.update(json.load(f))
lang_code_safe = language_code.replace("-", "_")
merged_file = f"{lang_code_safe}_merged.json"
with open(merged_file, "w", encoding="utf-8") as f:
json.dump(merged, f, ensure_ascii=False, separators=(",", ":"))
print(f"✓ Merged {len(merged)} translations into {merged_file}")
return merged_file
def apply_translations(merged_file, language_code):
"""Apply merged translations to the language file."""
print(f"\n📝 Applying translations to {language_code}...")
cmd = f"python3 scripts/translations/translation_merger.py {language_code} apply-translations --translations-file {merged_file}"
if not run_command(cmd):
print("✗ Failed to apply translations")
return False
print("✓ Translations applied successfully")
return True
def beautify_translations(language_code):
"""Beautify translation file to match en-GB structure."""
print(f"\n✨ Beautifying {language_code} translation file...")
cmd = f"python3 scripts/translations/toml_beautifier.py --language {language_code}"
if not run_command(cmd):
print("✗ Failed to beautify translations")
return False
print("✓ Translation file beautified")
return True
def cleanup_temp_files(language_code):
"""Remove temporary batch files."""
print("\n🧹 Cleaning up temporary files...")
lang_code_safe = language_code.replace("-", "_")
patterns = [f"{lang_code_safe}_batch_*.json", f"{lang_code_safe}_merged.json"]
import glob
removed = 0
for pattern in patterns:
for file in glob.glob(pattern):
Path(file).unlink()
removed += 1
print(f"✓ Removed {removed} temporary files")
def verify_completion(language_code):
"""Check final completion percentage."""
print("\n📊 Verifying completion...")
cmd = f"python3 scripts/translations/translation_analyzer.py --language {language_code} --summary"
run_command(cmd)
def main():
parser = argparse.ArgumentParser(
description="Automated translation pipeline for Stirling PDF",
formatter_class=argparse.RawDescriptionHelpFormatter,
epilog="""
Note: This script works with TOML translation files.
Examples:
# Translate Spanish with API key in environment
export OPENAI_API_KEY=your_key_here
python3 scripts/translations/auto_translate.py es-ES
# Translate German with inline API key
python3 scripts/translations/auto_translate.py de-DE --api-key YOUR_KEY
# Translate Italian with custom batch size
python3 scripts/translations/auto_translate.py it-IT --batch-size 600
# Skip cleanup (keep temporary files for inspection)
python3 scripts/translations/auto_translate.py fr-FR --no-cleanup
""",
)
parser.add_argument("language", help="Language code (e.g., es-ES, de-DE, zh-CN)")
parser.add_argument(
"--api-key", help="OpenAI API key (or set OPENAI_API_KEY env var)"
)
parser.add_argument(
"--batch-size", type=int, default=500, help="Entries per batch (default: 500)"
)
parser.add_argument(
"--no-cleanup", action="store_true", help="Keep temporary batch files"
)
parser.add_argument(
"--skip-verification", action="store_true", help="Skip final completion check"
)
parser.add_argument(
"--timeout",
type=int,
default=600,
help="Timeout per batch in seconds (default: 600 = 10 minutes)",
)
parser.add_argument(
"--include-existing",
action="store_true",
help="Also retranslate existing keys that match English (default: only translate missing keys)",
)
args = parser.parse_args()
# Verify API key
api_key = args.api_key or os.environ.get("OPENAI_API_KEY")
if not api_key:
print(
"Error: OpenAI API key required. Provide via --api-key or OPENAI_API_KEY environment variable"
)
sys.exit(1)
print("=" * 60)
print("Automated Translation Pipeline")
print(f"Language: {args.language}")
print(f"Batch Size: {args.batch_size} entries")
print("=" * 60)
start_time = time.time()
try:
# Step 1: Extract and split
batch_files = extract_untranslated(
args.language, args.batch_size, args.include_existing
)
if batch_files is None:
sys.exit(1)
if len(batch_files) == 0:
print("\n✓ Nothing to translate!")
sys.exit(0)
# Step 2: Translate all batches
translated_files = translate_batches(
batch_files, args.language, api_key, args.timeout
)
if translated_files is None:
sys.exit(1)
# Step 3: Merge translations
merged_file = merge_translations(translated_files, args.language)
if merged_file is None:
sys.exit(1)
# Step 4: Apply translations
if not apply_translations(merged_file, args.language):
sys.exit(1)
# Step 5: Beautify
if not beautify_translations(args.language):
sys.exit(1)
# Step 6: Cleanup
if not args.no_cleanup:
cleanup_temp_files(args.language)
# Step 7: Verify
if not args.skip_verification:
verify_completion(args.language)
elapsed = time.time() - start_time
print("\n" + "=" * 60)
print("✅ Translation pipeline completed successfully!")
print(f"Time elapsed: {elapsed:.1f} seconds")
print("=" * 60)
except KeyboardInterrupt:
print("\n\n⚠ Translation interrupted by user")
sys.exit(1)
except Exception as e:
print(f"\n\n✗ Error: {e}")
import traceback
traceback.print_exc()
sys.exit(1)
if __name__ == "__main__":
main()