diff --git a/pyproject.toml b/pyproject.toml index 4483896..4775b0e 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -10,6 +10,12 @@ dependencies = [ "typer>=0.20.0", "pyyaml>=6.0.2", "python-frontmatter>=1.1.0", + "transformers>=4.46.3", + "torch>=2.5.1", + "sentencepiece>=0.2.0", + "sacremoses>=0.1.1", + "fast-langdetect>=1.0.0", + "fasttext>=0.9.3", ] [project.scripts] diff --git a/src/scribae/main.py b/src/scribae/main.py index 0390f52..10927ae 100644 --- a/src/scribae/main.py +++ b/src/scribae/main.py @@ -2,15 +2,15 @@ import typer -from . import brief from .brief_cli import brief_command from .idea_cli import idea_command from .meta_cli import meta_command +from .translate_cli import translate_command from .write_cli import write_command app = typer.Typer(help="Scribae CLI — generate writing briefs from local notes.") -__all__ = ["app", "main", "brief"] +__all__ = ["app", "main"] @app.callback(invoke_without_command=True) @@ -20,6 +20,7 @@ def app_callback() -> None: app.command("brief", help="Create a structured creative brief from a Markdown note.")(brief_command) app.command("write", help="Generate article body from a note + SeoBrief.")(write_command) app.command("meta", help="Generate final article metadata/frontmatter.")(meta_command) +app.command("translate", help="Translate Markdown locally (MT + post-edit).")(translate_command) app.command("idea", help="Brainstorm content ideas from a Markdown note.")(idea_command) diff --git a/src/scribae/translate/__init__.py b/src/scribae/translate/__init__.py new file mode 100644 index 0000000..c889c5e --- /dev/null +++ b/src/scribae/translate/__init__.py @@ -0,0 +1,20 @@ +from .markdown_segmenter import MarkdownSegmenter, ProtectedText, TextBlock +from .model_registry import ModelRegistry, ModelSpec, RouteStep +from .mt import MTTranslator +from .pipeline import ToneProfile, TranslationConfig, TranslationPipeline +from .postedit import LLMPostEditor, PostEditValidationError + +__all__ = [ + "MarkdownSegmenter", + "ProtectedText", + "TextBlock", + "ModelRegistry", + "ModelSpec", + "RouteStep", + "MTTranslator", + "ToneProfile", + "TranslationConfig", + "TranslationPipeline", + "LLMPostEditor", + "PostEditValidationError", +] diff --git a/src/scribae/translate/markdown_segmenter.py b/src/scribae/translate/markdown_segmenter.py new file mode 100644 index 0000000..a82f46f --- /dev/null +++ b/src/scribae/translate/markdown_segmenter.py @@ -0,0 +1,148 @@ +from __future__ import annotations + +import re +from dataclasses import dataclass, field +from typing import Any + + +@dataclass +class TextBlock: + """Structured unit of markdown content.""" + + kind: str + text: str + meta: dict[str, Any] = field(default_factory=dict) + + +@dataclass +class ProtectedText: + """Text with protected spans swapped for sentinel tokens.""" + + text: str + placeholders: dict[str, str] + + def restore(self, translated: str) -> str: + restored = translated + for token, original in self.placeholders.items(): + restored = restored.replace(token, original) + return restored + + +class MarkdownSegmenter: + """Lightweight markdown segmenter with protection helpers.""" + + DEFAULT_PATTERNS = [ + r"`[^`]+`", # inline code + r"\{[^{}]+\}", # placeholders + r"\{\{[^{}]+\}\}", + r":[a-z0-9_-]+:", + r"https?://[^\s\]]+", + ] + + def __init__(self, protected_patterns: list[str] | None = None) -> None: + self.protected_patterns = self.DEFAULT_PATTERNS + (protected_patterns or []) + + def segment(self, text: str) -> list[TextBlock]: + """Split markdown text into blocks while preserving structure.""" + remaining = text + blocks: list[TextBlock] = [] + frontmatter_match = re.match(r"^---\n(.+?)\n---\n?", remaining, flags=re.DOTALL) + if frontmatter_match: + fm_text = frontmatter_match.group(0) + fm_body = frontmatter_match.group(1) + blocks.append(TextBlock(kind="frontmatter", text=fm_text, meta={"body": fm_body})) + remaining = remaining[len(fm_text) :] + + blocks.extend(self._segment_body(remaining)) + return blocks + + def _segment_body(self, text: str) -> list[TextBlock]: + lines = text.splitlines() + blocks: list[TextBlock] = [] + buffer: list[str] = [] + current_kind = "paragraph" + in_code = False + fence = "" + + def _flush() -> None: + nonlocal buffer, current_kind + if buffer: + blocks.append(TextBlock(kind=current_kind, text="\n".join(buffer))) + buffer = [] + current_kind = "paragraph" + + for line in lines: + fence_match = re.match(r"^(```|~~~)", line) + if fence_match: + marker = fence_match.group(1) + if in_code and marker == fence: + buffer.append(line) + _flush() + in_code = False + fence = "" + continue + if in_code: + buffer.append(line) + continue + _flush() + in_code = True + fence = marker + current_kind = "code_block" + buffer.append(line) + continue + + if in_code: + buffer.append(line) + continue + + if line.startswith("#"): + _flush() + level = len(line) - len(line.lstrip("#")) + heading_text = line.lstrip("#").strip() + blocks.append(TextBlock(kind="heading", text=line, meta={"level": level, "title": heading_text})) + continue + + if re.match(r"^(\s*[-*+]|[0-9]+\.)\s+", line): + if current_kind not in {"list_item"}: + _flush() + current_kind = "list_item" + blocks.append(TextBlock(kind="list_item", text=line, meta={"marker": line.split()[0]})) + current_kind = "paragraph" + continue + + if line.strip() == "": + _flush() + blocks.append(TextBlock(kind="blank", text="")) + continue + + buffer.append(line) + + _flush() + return blocks + + def reconstruct(self, blocks: list[TextBlock]) -> str: + parts = [block.text for block in blocks] + return "\n".join(parts).rstrip("\n") + + def protect_text(self, text: str, extra_patterns: list[str] | None = None) -> ProtectedText: + """Return text where protected spans are replaced with sentinels.""" + patterns = self.protected_patterns + (extra_patterns or []) + placeholders: dict[str, str] = {} + pattern = re.compile("|".join(f"({p})" for p in patterns), flags=re.IGNORECASE) + + def _replace(match: re.Match[str]) -> str: + token = f"<<>>" + placeholders[token] = match.group(0) + return token + + replaced = pattern.sub(_replace, text) + return ProtectedText(text=replaced, placeholders=placeholders) + + def extract_links(self, text: str) -> list[str]: + return re.findall(r"https?://[^\s\])>]+", text) + + def extract_numbers(self, text: str) -> list[str]: + return re.findall(r"\d+(?:[.,:/-]\d+)*", text) + + +__all__ = ["MarkdownSegmenter", "ProtectedText", "TextBlock"] diff --git a/src/scribae/translate/model_registry.py b/src/scribae/translate/model_registry.py new file mode 100644 index 0000000..dfd1b92 --- /dev/null +++ b/src/scribae/translate/model_registry.py @@ -0,0 +1,128 @@ +from __future__ import annotations + +from collections.abc import Iterable, Sequence +from dataclasses import dataclass +from typing import Literal + +Backend = Literal["marian", "nllb"] + + +@dataclass(frozen=True) +class ModelSpec: + """Translation model metadata.""" + + model_id: str + src_lang: str + tgt_lang: str + backend: Backend + disabled: bool = False + + +@dataclass(frozen=True) +class RouteStep: + """Resolved translation step and model.""" + + src_lang: str + tgt_lang: str + model: ModelSpec + + +class ModelRegistry: + """Registry for deterministic routing between language pairs.""" + + def __init__( + self, + specs: Iterable[ModelSpec] | None = None, + *, + nllb_model_id: str | None = None, + ) -> None: + self._specs: list[ModelSpec] = list(specs) if specs else _default_specs() + self._nllb_model_id = nllb_model_id or "facebook/nllb-200-distilled-600M" + + def normalize_lang(self, lang: str) -> str: + return lang.lower() + + def find_direct(self, src_lang: str, tgt_lang: str) -> ModelSpec | None: + src = self.normalize_lang(src_lang) + tgt = self.normalize_lang(tgt_lang) + for spec in self._specs: + if spec.disabled: + continue + if self.normalize_lang(spec.src_lang) == src and self.normalize_lang(spec.tgt_lang) == tgt: + return spec + return None + + def nllb_spec(self) -> ModelSpec: + return ModelSpec( + model_id=self._nllb_model_id, + src_lang="multi", + tgt_lang="multi", + backend="nllb", + ) + + def supported_pairs(self) -> set[tuple[str, str]]: + return {(self.normalize_lang(spec.src_lang), self.normalize_lang(spec.tgt_lang)) for spec in self._specs} + + def route( + self, + src_lang: str, + tgt_lang: str, + *, + allow_pivot: bool = True, + backend: str = "marian_then_nllb", + ) -> list[RouteStep]: + """Return deterministic route for a language pair.""" + src = self.normalize_lang(src_lang) + tgt = self.normalize_lang(tgt_lang) + + direct = self.find_direct(src, tgt) + if direct: + return [RouteStep(src_lang=src, tgt_lang=tgt, model=direct)] + + pivot_steps = self._pivot_route(src, tgt, allow_pivot=allow_pivot) + if pivot_steps: + return pivot_steps + + if "nllb" in backend: + nllb = self.nllb_spec() + return [RouteStep(src_lang=src, tgt_lang=tgt, model=nllb)] + + raise ValueError(f"No route found for {src}->{tgt}") + + def _pivot_route(self, src_lang: str, tgt_lang: str, *, allow_pivot: bool) -> list[RouteStep] | None: + if not allow_pivot: + return None + if src_lang == "en" or tgt_lang == "en": + return None + first = self.find_direct(src_lang, "en") + second = self.find_direct("en", tgt_lang) + if first and second: + return [ + RouteStep(src_lang=src_lang, tgt_lang="en", model=first), + RouteStep(src_lang="en", tgt_lang=tgt_lang, model=second), + ] + return None + + +def _default_specs() -> list[ModelSpec]: + """Default MarianMT pairs for Scribae.""" + pairs: Sequence[tuple[str, str, str]] = ( + ("en", "de", "Helsinki-NLP/opus-mt-en-de"), + ("de", "en", "Helsinki-NLP/opus-mt-de-en"), + ("en", "es", "Helsinki-NLP/opus-mt-en-es"), + ("es", "en", "Helsinki-NLP/opus-mt-es-en"), + ("en", "fr", "Helsinki-NLP/opus-mt-en-fr"), + ("fr", "en", "Helsinki-NLP/opus-mt-fr-en"), + ("en", "it", "Helsinki-NLP/opus-mt-en-it"), + ("it", "en", "Helsinki-NLP/opus-mt-it-en"), + ("en", "pt", "Helsinki-NLP/opus-mt-en-pt"), + ("pt", "en", "Helsinki-NLP/opus-mt-pt-en"), + ("de", "es", "Helsinki-NLP/opus-mt-de-es"), + ("de", "fr", "Helsinki-NLP/opus-mt-de-fr"), + ("de", "it", "Helsinki-NLP/opus-mt-de-it"), + ("de", "pt", "Helsinki-NLP/opus-mt-de-pt"), + ) + return [ModelSpec(model_id=model_id, src_lang=src, tgt_lang=tgt, backend="marian") for src, tgt, model_id in pairs] + + +__all__ = ["ModelRegistry", "ModelSpec", "RouteStep"] diff --git a/src/scribae/translate/mt.py b/src/scribae/translate/mt.py new file mode 100644 index 0000000..5aa6bb4 --- /dev/null +++ b/src/scribae/translate/mt.py @@ -0,0 +1,98 @@ +from __future__ import annotations + +from typing import TYPE_CHECKING, Any + +from .model_registry import ModelRegistry, RouteStep + +if TYPE_CHECKING: + from transformers import Pipeline + + +class MTTranslator: + """Offline machine translation wrapper around Transformers pipelines.""" + + def __init__(self, registry: ModelRegistry, device: str | None = None) -> None: + self.registry = registry + self.device = device + self._pipelines: dict[str, Pipeline] = {} + + def translate_block( + self, + text: str, + src_lang: str, + tgt_lang: str, + *, + allow_pivot: bool = True, + backend: str = "marian_then_nllb", + ) -> str: + result = self.translate_blocks([text], src_lang, tgt_lang, allow_pivot=allow_pivot, backend=backend) + return result[0] + + def translate_blocks( + self, + texts: list[str], + src_lang: str, + tgt_lang: str, + *, + allow_pivot: bool = True, + backend: str = "marian_then_nllb", + ) -> list[str]: + if not texts: + return [] + steps = self.registry.route(src_lang, tgt_lang, allow_pivot=allow_pivot, backend=backend) + current: list[str] = texts + for step in steps: + current = self._run_step_batch(step, current) + return current + + def _pipeline_for(self, model_id: str) -> Pipeline: + # Import transformers lazily so CLI startup stays fast when the translation command isn't invoked. + from transformers import pipeline + + if model_id not in self._pipelines: + if self.device is None or self.device == "auto": + import torch + + device = 0 if torch.cuda.is_available() else -1 + self._pipelines[model_id] = pipeline("translation", model=model_id, device=device) + else: + self._pipelines[model_id] = pipeline( + "translation", model=model_id, device=self.device + ) + return self._pipelines[model_id] + + def _run_step(self, step: RouteStep, text: str) -> str: + translator = self._pipeline_for(step.model.model_id) + result: list[dict[str, Any]] | str = translator( + text, + src_lang=step.src_lang if step.model.backend == "nllb" else None, + tgt_lang=step.tgt_lang if step.model.backend == "nllb" else None, + ) + return self._extract_translation(result)[0] + + def _run_step_batch(self, step: RouteStep, texts: list[str]) -> list[str]: + translator = self._pipeline_for(step.model.model_id) + result: list[dict[str, Any]] = translator( + texts, + src_lang=step.src_lang if step.model.backend == "nllb" else None, + tgt_lang=step.tgt_lang if step.model.backend == "nllb" else None, + ) + return self._extract_translation(result) + + def _extract_translation(self, result: list[dict[str, Any]] | str) -> list[str]: + if isinstance(result, str): + return [result] + if not isinstance(result, list): + raise RuntimeError("Translation pipeline returned unexpected output shape") + if not result: + raise RuntimeError("Translation pipeline returned no output") + translations: list[str] = [] + for item in result: + translated = item.get("translation_text") or item.get("generated_text") + if not translated: + raise RuntimeError("Translation pipeline returned no translation_text") + translations.append(str(translated)) + return translations + + +__all__ = ["MTTranslator"] diff --git a/src/scribae/translate/pipeline.py b/src/scribae/translate/pipeline.py new file mode 100644 index 0000000..8675a96 --- /dev/null +++ b/src/scribae/translate/pipeline.py @@ -0,0 +1,378 @@ +from __future__ import annotations + +from collections.abc import Callable +from dataclasses import dataclass, field +from typing import Any + +from .markdown_segmenter import MarkdownSegmenter, ProtectedText, TextBlock +from .model_registry import ModelRegistry +from .mt import MTTranslator +from .postedit import LLMPostEditor, PostEditAborted, PostEditValidationError + +DebugCallback = Callable[[dict[str, Any]], None] | None +Reporter = Callable[[str], None] | None + + +@dataclass +class ToneProfile: + register: str = "neutral" + audience: str = "general" + + +@dataclass +class TranslationConfig: + source_lang: str + target_lang: str + tone: ToneProfile + glossary: dict[str, str] = field(default_factory=dict) + protected_patterns: list[str] = field(default_factory=list) + allow_pivot_via_en: bool = True + mt_backend: str = "marian_then_nllb" + postedit_enabled: bool = True + + +class TranslationPipeline: + """Coordinate markdown-safe translation across MT + LLM stages.""" + + def __init__( + self, + registry: ModelRegistry, + mt: MTTranslator, + postedit: LLMPostEditor, + *, + segmenter: MarkdownSegmenter | None = None, + debug_callback: DebugCallback = None, + reporter: Reporter = None, + ) -> None: + self.registry = registry + self.mt = mt + self.postedit = postedit + self.segmenter = segmenter or MarkdownSegmenter() + self.debug_callback = debug_callback + self.reporter = reporter + + def _report(self, message: str) -> None: + """Send a progress message to the reporter if configured.""" + if self.reporter: + self.reporter(message) + + def _report_block( + self, + block_index: int, + message: str, + *, + total_blocks: int | None = None, + block_kind: str | None = None, + ) -> None: + count = f"{block_index + 1}" + if total_blocks is not None: + count = f"{count}/{total_blocks}" + prefix = f"Block {count}" + if block_kind: + prefix = f"{prefix} ({block_kind})" + self._report(f"{prefix}: {message}") + + def translate(self, text: str, cfg: TranslationConfig) -> str: + self._report(f"Starting translation: {cfg.source_lang} -> {cfg.target_lang}") + self._report("Segmenting markdown into blocks...") + blocks = self.segmenter.segment(text) + self._report(f"Found {len(blocks)} blocks to process") + translated_blocks = self.translate_blocks(blocks, cfg) + self._report("Reconstructing translated document...") + result = self.segmenter.reconstruct(translated_blocks) + self._report("Translation complete") + return result + + def translate_blocks(self, blocks: list[TextBlock], cfg: TranslationConfig) -> list[TextBlock]: + translated: list[TextBlock] = [block for block in blocks] + total_blocks = len(blocks) + translatable: list[tuple[int, TextBlock, ProtectedText]] = [] + for idx, block in enumerate(blocks): + if block.kind in {"code_block", "frontmatter", "blank"}: + self._report_block( + idx, + "Skipping non-translatable block", + total_blocks=total_blocks, + block_kind=block.kind, + ) + continue + self._report_block( + idx, + "Translating...", + total_blocks=total_blocks, + block_kind=block.kind, + ) + self._report_block( + idx, + "Protecting patterns and placeholders...", + total_blocks=total_blocks, + block_kind=block.kind, + ) + protected = self.segmenter.protect_text(block.text, cfg.protected_patterns) + translatable.append((idx, block, protected)) + + if translatable: + texts = [item[2].text for item in translatable] + self._report(f"Running machine translation batch ({cfg.mt_backend}) for {len(texts)} blocks...") + mt_outputs = self.mt.translate_blocks( + texts, + cfg.source_lang, + cfg.target_lang, + allow_pivot=cfg.allow_pivot_via_en, + backend=cfg.mt_backend, + ) + if len(mt_outputs) != len(translatable): + raise ValueError("MT batch output count does not match input blocks") + + for (idx, block, protected), mt_output in zip(translatable, mt_outputs, strict=False): + updated_text = self._translate_block( + block, + cfg, + block_index=idx, + total_blocks=total_blocks, + protected=protected, + mt_output=mt_output, + ) + translated[idx] = TextBlock(kind=block.kind, text=updated_text, meta=block.meta) + if len(translated) != len(blocks): + raise ValueError("Block structure changed during translation") + return translated + + def _translate_block( + self, + block: TextBlock, + cfg: TranslationConfig, + *, + block_index: int, + total_blocks: int | None = None, + protected: ProtectedText | None = None, + mt_output: str | None = None, + ) -> str: + if protected is None: + self._report_block( + block_index, + "Protecting patterns and placeholders...", + total_blocks=total_blocks, + block_kind=block.kind, + ) + protected = self.segmenter.protect_text(block.text, cfg.protected_patterns) + + if mt_output is None: + self._report_block( + block_index, + f"Running machine translation ({cfg.mt_backend})...", + total_blocks=total_blocks, + block_kind=block.kind, + ) + mt_output = self.mt.translate_block( + protected.text, + cfg.source_lang, + cfg.target_lang, + allow_pivot=cfg.allow_pivot_via_en, + backend=cfg.mt_backend, + ) + else: + self._report_block( + block_index, + "Using batched machine translation output", + total_blocks=total_blocks, + block_kind=block.kind, + ) + + mt_restored = protected.restore(mt_output) + self._report_block( + block_index, + "Validating MT output...", + total_blocks=total_blocks, + block_kind=block.kind, + ) + mt_valid = self._validate_stage( + block.text, + mt_output, + mt_restored, + protected, + stage="mt", + block_index=block_index, + ) + if not mt_valid: + self._report_block( + block_index, + "MT validation failed, retrying with expanded patterns...", + total_blocks=total_blocks, + block_kind=block.kind, + ) + expanded_patterns = cfg.protected_patterns + [r"\d+(?:[.,:/-]\d+)*"] + protected = self.segmenter.protect_text(block.text, expanded_patterns) + mt_output = self.mt.translate_block( + protected.text, + cfg.source_lang, + cfg.target_lang, + allow_pivot=cfg.allow_pivot_via_en, + backend=cfg.mt_backend, + ) + mt_restored = protected.restore(mt_output) + self._validate_stage( + block.text, + mt_output, + mt_restored, + protected, + stage="mt_retry", + block_index=block_index, + ) + + candidate_tokens = mt_output + if cfg.postedit_enabled: + candidate_tokens = self._run_postedit( + source_text=block.text, + mt_draft=mt_output, + cfg=cfg, + protected=protected, + block_index=block_index, + block_kind=block.kind, + total_blocks=total_blocks, + ) + + final_text = protected.restore(candidate_tokens) + self._report_block( + block_index, + "Validating final output...", + total_blocks=total_blocks, + block_kind=block.kind, + ) + postedit_ok = self._validate_stage( + block.text, candidate_tokens, final_text, protected, stage="postedit", block_index=block_index + ) + if not postedit_ok: + self._report_block( + block_index, + "Validation failed, falling back to MT output", + total_blocks=total_blocks, + block_kind=block.kind, + ) + return mt_restored + self._report_block( + block_index, + "Block translation complete", + total_blocks=total_blocks, + block_kind=block.kind, + ) + return final_text + + def _run_postedit( + self, + source_text: str, + mt_draft: str, + cfg: TranslationConfig, + protected: ProtectedText, + *, + block_index: int, + block_kind: str, + total_blocks: int | None = None, + ) -> str: + self._report_block( + block_index, + "Running LLM post-edit (non-strict mode)...", + total_blocks=total_blocks, + block_kind=block_kind, + ) + try: + edited = self.postedit.post_edit(source_text, mt_draft, cfg, protected, strict=False) + self._report_block( + block_index, + "Post-edit completed successfully", + total_blocks=total_blocks, + block_kind=block_kind, + ) + return edited + except PostEditAborted as exc: + reason = getattr(exc, "reason", str(exc)) + self._report_block( + block_index, + f"Post-edit skipped: {reason}", + total_blocks=total_blocks, + block_kind=block_kind, + ) + self._debug( + stage="postedit_aborted", + block_index=block_index, + message=str(reason), + ) + return mt_draft + except PostEditValidationError: + self._report_block( + block_index, + "Non-strict post-edit failed, retrying in strict mode...", + total_blocks=total_blocks, + block_kind=block_kind, + ) + + try: + edited = self.postedit.post_edit(source_text, mt_draft, cfg, protected, strict=True) + self._report_block( + block_index, + "Strict post-edit completed successfully", + total_blocks=total_blocks, + block_kind=block_kind, + ) + return edited + except PostEditAborted as exc: + reason = getattr(exc, "reason", str(exc)) + self._report_block( + block_index, + f"Post-edit unavailable: {reason}", + total_blocks=total_blocks, + block_kind=block_kind, + ) + self._debug( + stage="postedit_aborted", + block_index=block_index, + message=str(reason), + ) + return mt_draft + except PostEditValidationError: + self._report_block( + block_index, + "Post-edit failed twice, falling back to MT draft", + total_blocks=total_blocks, + block_kind=block_kind, + ) + self._debug( + stage="postedit_fallback", + block_index=block_index, + message="Post-edit failed twice, falling back to MT draft.", + ) + return mt_draft + + def _validate_stage( + self, + source_text: str, + candidate_with_tokens: str, + restored: str, + protected: ProtectedText, + *, + stage: str, + block_index: int, + ) -> bool: + placeholders_ok = all(token in candidate_with_tokens for token in protected.placeholders) + numbers_ok = self._numbers_match(source_text, restored) + urls_ok = self._links_match(source_text, restored) + + report = { + "stage": stage, + "block_index": block_index, + "placeholders_ok": placeholders_ok, + "numbers_ok": numbers_ok, + "urls_ok": urls_ok, + } + self._debug(**report, restored=restored, candidate=candidate_with_tokens) + return placeholders_ok and numbers_ok and urls_ok + + def _numbers_match(self, source_text: str, translated: str) -> bool: + return sorted(self.segmenter.extract_numbers(source_text)) == sorted(self.segmenter.extract_numbers(translated)) + + def _links_match(self, source_text: str, translated: str) -> bool: + return sorted(self.segmenter.extract_links(source_text)) == sorted(self.segmenter.extract_links(translated)) + + def _debug(self, **payload: Any) -> None: + if self.debug_callback: + self.debug_callback(payload) diff --git a/src/scribae/translate/postedit.py b/src/scribae/translate/postedit.py new file mode 100644 index 0000000..b90e038 --- /dev/null +++ b/src/scribae/translate/postedit.py @@ -0,0 +1,457 @@ +from __future__ import annotations + +import asyncio +import importlib +import os +from collections.abc import Callable, Iterable +from dataclasses import dataclass +from typing import TYPE_CHECKING, Any, Literal, cast + +from pydantic_ai import Agent, NativeOutput, UnexpectedModelBehavior +from pydantic_ai.settings import ModelSettings + +from scribae.llm import LLM_OUTPUT_RETRIES, OpenAISettings, make_model + +from .markdown_segmenter import ProtectedText + +if TYPE_CHECKING: + from .pipeline import TranslationConfig + + +class PostEditValidationError(ValueError): + """Raised when a post-edit output violates constraints.""" + + +class PostEditAborted(PostEditValidationError): + """Raised when post-editing cannot proceed (e.g., prompt too large or timed out).""" + + def __init__(self, reason: str) -> None: + super().__init__(reason) + self.reason = reason + + +@dataclass(frozen=True) +class PostEditResult: + text: str + validated: bool + + +class LLMPostEditor: + """Post-edit pass to improve tone and idioms while preserving structure.""" + + def __init__( + self, + agent: Agent[None, str] | None = None, + *, + model_name: str = "mistral-nemo", + temperature: float = 0.2, + create_agent: bool = True, + max_chars: int | None = 4_000, + timeout_seconds: float | None = 60.0, + language_detector: Callable[[str], str] | None = None, + ) -> None: + self.agent: Agent[None, str] | None = None + self.max_chars = max_chars + self.timeout_seconds = timeout_seconds + self._language_detector = language_detector + if agent is not None: + self.agent = agent + elif create_agent: + self.agent = self._create_agent(model_name, temperature=temperature) + + def post_edit( + self, + source_text: str, + mt_draft: str, + cfg: TranslationConfig, + protected: ProtectedText, + *, + strict: bool = False, + ) -> str: + """Run the LLM pass and return only the translation string.""" + if self.agent is None: + enforced = self._apply_glossary(mt_draft, cfg.glossary) + self._validate_output(enforced, protected.placeholders.keys(), cfg.glossary) + return enforced + + trimmed_source, trimmed_mt = self._trim_inputs(source_text, mt_draft) + prompt = self._build_prompt(trimmed_source, trimmed_mt, cfg, protected.placeholders.keys(), strict=strict) + if self.max_chars is not None and len(prompt) > self.max_chars: + raise PostEditAborted( + f"post-edit prompt length {len(prompt)} exceeds limit of {self.max_chars} characters" + ) + try: + result = self._invoke(prompt, protected.placeholders.keys(), mt_draft, expected_lang=cfg.target_lang) + except PostEditAborted: + raise + except UnexpectedModelBehavior as exc: + raise PostEditValidationError("LLM output failed validation") from exc + + # Restore Markdown structure that may have been corrupted by the LLM + result = self._restore_markdown_structure(mt_draft, result) + + enforced = self._apply_glossary(result, cfg.glossary) + self._validate_output(enforced, protected.placeholders.keys(), cfg.glossary) + return enforced + + def _invoke(self, prompt: str, placeholders: Iterable[str], mt_draft: str, *, expected_lang: str) -> str: + agent = self.agent + if agent is None: + return prompt + + output_validator = self._build_output_validator(placeholders, mt_draft, expected_lang) + + async def _call() -> str: + run_coro = agent.run( + prompt, + output_type=NativeOutput(output_validator, name="translation", strict=True), + ) + try: + run = ( + await asyncio.wait_for(run_coro, timeout=self.timeout_seconds) + if self.timeout_seconds + else await run_coro + ) + except TimeoutError as exc: + timeout = f"{self.timeout_seconds:.0f}s" if self.timeout_seconds else "configured timeout" + raise PostEditAborted(f"post-edit call exceeded {timeout}") from exc + output = getattr(run, "output", None) + if isinstance(output, str): + return output + if output is None: + raise UnexpectedModelBehavior("missing output from LLM") + return str(output) + + return asyncio.run(_call()) + + def _build_output_validator( + self, + placeholders: Iterable[str], + mt_draft: str, + expected_lang: str, + ) -> Callable[[str], str]: + placeholder_list = list(placeholders) + mt_lines = mt_draft.splitlines() + + def _validator(text: str) -> str: + missing = [token for token in placeholder_list if token not in text] + if missing: + raise UnexpectedModelBehavior(f"missing placeholders: {', '.join(missing)}") + + if not mt_lines: + return text + + candidate_lines = text.splitlines() + drift_ratio = abs(len(mt_lines) - len(candidate_lines)) / len(mt_lines) + if drift_ratio > 0.5: + raise UnexpectedModelBehavior( + f"post-edit line count drifted by {drift_ratio:.2f} (MT lines={len(mt_lines)}, " + f"post-edit={len(candidate_lines)})" + ) + + markers_missing: list[str] = [] + for mt_line, candidate_line in zip(mt_lines, candidate_lines, strict=False): + marker = self._leading_markdown_marker(mt_line) + if marker and not candidate_line.startswith(marker): + markers_missing.append(marker.strip()) + + if markers_missing: + unique_markers = sorted(set(markers_missing)) + raise UnexpectedModelBehavior( + "post-edit removed required Markdown prefixes: " + ", ".join(unique_markers) + ) + + detected_lang = self._detect_language(text) + if not self._lang_matches(detected_lang, expected_lang): + raise UnexpectedModelBehavior( + f"post-edit output language '{detected_lang}' does not match expected '{expected_lang}'" + ) + + return text + + return _validator + + def _lang_matches(self, detected: str, expected: str) -> bool: + return self._normalize_lang(detected) == self._normalize_lang(expected) + + def _normalize_lang(self, lang: str) -> str: + return lang.split("-")[0].strip().lower() + + def _detect_language(self, text: str) -> str: + detector = self._get_language_detector() + sample = text[:5_000] + try: + return detector(sample) + except FileNotFoundError as exc: + raise PostEditAborted(f"Language model missing for detection: {exc}") from exc + except Exception as exc: + raise PostEditAborted(f"Language detection failed: {exc}") from exc + + def _get_language_detector(self) -> Callable[[str], str]: + if self._language_detector is None: + try: + self._language_detector = self._create_language_detector() + except Exception as exc: # pragma: no cover - defensive: handled in _detect_language + raise PostEditAborted(f"Language detection unavailable: {exc}") from exc + return self._language_detector + + def _create_language_detector(self) -> Callable[[str], str]: + fast_langdetect = importlib.import_module("fast_langdetect") + config_kwargs: dict[str, Any] = {} + env_model_path = os.getenv("FASTTEXT_LID_MODEL") + if env_model_path: + config_kwargs["custom_model_path"] = env_model_path + + config = fast_langdetect.LangDetectConfig(**config_kwargs) if config_kwargs else None + detector = fast_langdetect.LangDetector(config) if config else fast_langdetect.LangDetector() + + def _detect(text: str) -> str: + results = self._detect_labels(detector, text, model="auto", k=1, threshold=0.0) + if not results: + raise UnexpectedModelBehavior("language detector returned no labels") + lang = results[0].get("lang") + if not isinstance(lang, str) or not lang: + raise UnexpectedModelBehavior("language detector returned invalid language label") + return self._normalize_lang(lang) + + return _detect + + def _detect_labels( + self, + detector: Any, + text: str, + *, + model: Literal["lite", "full", "auto"], + k: int, + threshold: float, + ) -> list[dict[str, object]]: + try: + return cast(list[dict[str, object]], detector.detect(text, model=model, k=k, threshold=threshold)) + except ValueError as exc: + message = str(exc) + copy_error = "Unable to avoid copy while creating an array as requested" + if copy_error not in message: + raise + return self._detect_with_fasttext_copy_fix(detector, text, model=model, k=k, threshold=threshold) + + def _detect_with_fasttext_copy_fix( + self, + detector: Any, + text: str, + *, + model: Literal["lite", "full", "auto"], + k: int, + threshold: float, + ) -> list[dict[str, object]]: + if model not in {"lite", "full", "auto"}: + raise UnexpectedModelBehavior(f"Invalid language detection model '{model}'") + + if model == "lite": + ft_model = detector._get_model(low_memory=True, fallback_on_memory_error=False) + elif model == "full": + ft_model = detector._get_model(low_memory=False, fallback_on_memory_error=False) + else: + ft_model = detector._get_model(low_memory=False, fallback_on_memory_error=True) + + processed = detector._preprocess_text(text) + normalized = detector._normalize_text(processed, detector.config.normalize_input) + if "\n" in normalized: + raise UnexpectedModelBehavior("language detection input contains newline characters") + + raw_predictor = getattr(ft_model, "f", None) + if raw_predictor is None or not hasattr(raw_predictor, "predict"): + raise UnexpectedModelBehavior("fasttext model missing raw predictor for copy-safe language detection") + + predictions = cast(list[tuple[float, str]], raw_predictor.predict(f"{normalized}\n", k, threshold, "strict")) + if not predictions: + return [] + + scored = [(str(label).replace("__label__", ""), min(float(score), 1.0)) for score, label in predictions] + scored.sort(key=lambda item: item[1], reverse=True) + return [{"lang": label, "score": score} for label, score in scored] + + def _leading_markdown_marker(self, line: str) -> str: + """Return the Markdown prefix (blockquote, list, heading) if present.""" + import re + + patterns = [ + r"^((?:>\s*)+)", # blockquotes with nesting + r"^(\s*(?:[-*+]|\d+\.)\s+)", # list markers + r"^(#+\s+)", # headings + ] + for pattern in patterns: + match = re.match(pattern, line) + if match: + return match.group(1) + return "" + + def _build_prompt( + self, + source_text: str, + mt_draft: str, + cfg: TranslationConfig, + placeholders: Iterable[str], + *, + strict: bool, + ) -> str: + placeholder_text = ", ".join(placeholders) or "none" + constraints = [ + "Preserve meaning exactly; do not add or remove claims or reorder sentences.", + f"Output must stay in the target language ({cfg.target_lang}); no code-switching.", + "Maintain IDENTICAL line count and Markdown structure to the MT draft.", + "Blockquotes MUST retain the '> ' prefix on each line (including nested '> > ').", + "List markers (-, *, +, 1., 2., etc.) MUST stay unchanged at the start of lines.", + "Headings (##, ###, etc.) MUST remain at their exact level.", + "Bold (**text**) and italic (*text*) markers MUST be preserved exactly.", + "Empty lines and spacing MUST match the MT draft structure exactly.", + f"Do not alter protected tokens (placeholders): {placeholder_text}.", + "Preserve URLs, IDs, file names, and numeric values.", + "Apply glossary substitutions exactly; do not paraphrase glossary targets.", + "Make only minimal edits needed for fluency and idioms.", + ] + if strict: + constraints.append("If uncertain or constraints conflict, return the MT draft verbatim.") + + glossary_lines = [f"- {src} -> {tgt}" for src, tgt in cfg.glossary.items()] + glossary_section = ( + "\n".join(glossary_lines) if glossary_lines else "none (use KEEP to leave the source term as-is)" + ) + + self_checks = [ + "- Placeholders are unchanged and all present.", + "- Glossary targets are applied (KEEP terms remain in source form).", + "- Line count and Markdown prefixes (quotes, lists, headings) match the MT draft.", + f"- Output language matches target '{cfg.target_lang}'.", + ] + + tone = cfg.tone + return ( + "You are a post-editor improving a machine translation with minimal edits.\n" + f"Source language: {cfg.source_lang}; Target language: {cfg.target_lang}.\n" + f"Tone: register={tone.register}, audience={tone.audience}.\n" + "[CONSTRAINTS]\n" + + "\n".join(f"- {line}" for line in constraints) + + "\n[GLOSSARY]\n" + f"{glossary_section}\n" + "[INPUT] SOURCE TEXT:\n" + f"{source_text}\n\n" + "[INPUT] MT DRAFT:\n" + f"{mt_draft}\n\n" + "[SELF-CHECK BEFORE ANSWERING]\n" + + "\n".join(self_checks) + + "\nReturn only the corrected translation in the target language." + ) + + def _restore_markdown_structure(self, mt_draft: str, edited: str) -> str: + """Restore Markdown structure (blockquotes, list markers) if stripped by LLM. + + Compares line-by-line between the MT draft and edited output, restoring + blockquote prefixes and list markers if they were stripped. + + Args: + mt_draft: The original MT draft with correct Markdown structure. + edited: The LLM-edited output that may have lost Markdown formatting. + + Returns: + The edited text with Markdown structure restored from mt_draft. + """ + import re + + mt_lines = mt_draft.splitlines() + edited_lines = edited.splitlines() + + # Skip restoration if line counts differ significantly (>33% difference) + if len(mt_lines) == 0: + return edited + line_diff_ratio = abs(len(mt_lines) - len(edited_lines)) / len(mt_lines) + if line_diff_ratio > 0.33: + return edited + + # Patterns for Markdown prefixes we want to restore + # Blockquote pattern: one or more '>' possibly with spaces + blockquote_pattern = re.compile(r'^((?:>\s*)+)') + # List marker pattern: optional whitespace + marker + space + # Supports: -, *, +, and numbered lists like 1., 2., 10. + list_marker_pattern = re.compile(r'^(\s*(?:[-*+]|\d+\.)\s+)') + + restored_lines = [] + for i, edited_line in enumerate(edited_lines): + if i >= len(mt_lines): + # More edited lines than MT lines - keep as-is + restored_lines.append(edited_line) + continue + + mt_line = mt_lines[i] + restored_line = edited_line + + # Check for blockquote prefix in MT draft + mt_blockquote = blockquote_pattern.match(mt_line) + edited_blockquote = blockquote_pattern.match(edited_line) + + if mt_blockquote and not edited_blockquote: + # MT has blockquote prefix but edited doesn't - restore it + prefix = mt_blockquote.group(1) + restored_line = prefix + edited_line + + # Check for list marker in MT draft (only if not a blockquote line) + if not mt_blockquote: + mt_list = list_marker_pattern.match(mt_line) + edited_list = list_marker_pattern.match(edited_line) + + if mt_list and not edited_list: + # MT has list marker but edited doesn't - restore it + prefix = mt_list.group(1) + restored_line = prefix + edited_line + + restored_lines.append(restored_line) + + return '\n'.join(restored_lines) + + def _apply_glossary(self, text: str, glossary: dict[str, str]) -> str: + translation = text + for src_term, tgt_term in glossary.items(): + source = str(src_term) + target = str(tgt_term) + if target.upper() == "KEEP": + continue + if target not in translation: + translation = translation.replace(source, target) + return translation + + def _validate_output(self, text: str, placeholders: Iterable[str], glossary: dict[str, str]) -> None: + for token in placeholders: + if token not in text: + raise PostEditValidationError(f"Protected token missing: {token}") + for src_term, tgt_term in glossary.items(): + source = str(src_term) + target = str(tgt_term) + if target.upper() == "KEEP": + if source not in text: + raise PostEditValidationError(f"Term marked KEEP missing: {source}") + elif target not in text: + raise PostEditValidationError(f"Glossary target not enforced: {target}") + + def _create_agent(self, model_name: str, *, temperature: float) -> Agent[None, str] | None: + settings = OpenAISettings.from_env() + settings.configure_environment() + model_settings = ModelSettings(temperature=temperature) + model = make_model(model_name, model_settings=model_settings, settings=settings) + return Agent[None, str]( + model=model, + output_type=NativeOutput(str, name="translation", strict=True), + instructions="You post-edit machine translations.", + output_retries=LLM_OUTPUT_RETRIES, + ) + + def _trim_inputs(self, source_text: str, mt_draft: str) -> tuple[str, str]: + """Trim inputs to reduce prompt size when a max_chars budget is set.""" + if self.max_chars is None: + return source_text, mt_draft + budget = int(self.max_chars * 0.4) + budget = max(budget, 1) + trimmed_source = source_text[:budget] + trimmed_mt = mt_draft[:budget] + return trimmed_source, trimmed_mt + + +__all__ = ["LLMPostEditor", "PostEditAborted", "PostEditValidationError", "PostEditResult"] diff --git a/src/scribae/translate_cli.py b/src/scribae/translate_cli.py new file mode 100644 index 0000000..499fb87 --- /dev/null +++ b/src/scribae/translate_cli.py @@ -0,0 +1,207 @@ +from __future__ import annotations + +import json +from dataclasses import asdict +from pathlib import Path +from typing import Any + +import typer +import yaml + +from scribae.project import load_project +from scribae.translate import ( + LLMPostEditor, + MarkdownSegmenter, + ModelRegistry, + MTTranslator, + ToneProfile, + TranslationConfig, + TranslationPipeline, +) + +translate_app = typer.Typer() + + +def _load_glossary(path: Path | None) -> dict[str, str]: + if path is None: + return {} + data = yaml.safe_load(path.read_text(encoding="utf-8")) or {} + if not isinstance(data, dict): + raise typer.BadParameter("Glossary file must contain a mapping of source->target") + return {str(k): str(v) for k, v in data.items()} + + +def _debug_path(base: Path) -> Path: + return base.with_suffix(base.suffix + ".debug.json") + + +@translate_app.command() +def translate( + src: str | None = typer.Option( # noqa: B008 + None, + "--src", + help="Source language code, e.g. en. Required unless provided via --project.", + ), + tgt: str = typer.Option( # noqa: B008 + ..., + "--tgt", + help="Target language code, e.g. de.", + ), + input_path: Path = typer.Option( # noqa: B008 + ..., + "--in", + exists=True, + readable=True, + dir_okay=False, + help="Input markdown.", + ), + output_path: Path | None = typer.Option( # noqa: B008 + None, + "--out", + dir_okay=False, + help="Output path (stdout if omitted).", + ), + glossary: Path | None = typer.Option( # noqa: B008 + None, + "--glossary", + help="YAML glossary mapping source->target terms.", + ), + tone: str | None = typer.Option( # noqa: B008 + None, + "--tone", + help=( + "Tone register: neutral, formal, academic. If omitted, uses project.tone when --project is set, " + "otherwise neutral." + ), + ), + audience: str | None = typer.Option( # noqa: B008 + None, + "--audience", + help=( + "Target audience description. If omitted, uses project.audience when --project is set, " + "otherwise educated general." + ), + ), + project: str | None = typer.Option( # noqa: B008 + None, + "--project", + "-p", + help="Project name used to load projects/.yaml for translation defaults.", + ), + postedit: bool = typer.Option( # noqa: B008 + True, + "--postedit/--no-postedit", + help="Enable post-edit LLM pass.", + ), + allow_pivot: bool = typer.Option( # noqa: B008 + True, + "--allow-pivot/--no-allow-pivot", + help="Allow pivot via English.", + ), + debug: bool = typer.Option( # noqa: B008 + False, + "--debug", + help="Write debug artifacts alongside output.", + ), + protect: list[str] = typer.Option( # noqa: B008 + [], + "--protect", + help="Additional regex patterns to protect.", + ), + postedit_model: str = typer.Option( # noqa: B008 + "mistral-nemo", + "--postedit-model", + help="Model name for post-edit LLM pass.", + ), + postedit_max_chars: int | None = typer.Option( # noqa: B008 + 4_000, + "--postedit-max-chars", + help="Maximum characters allowed in post-edit prompt (None disables limit).", + ), + postedit_temperature: float = typer.Option( # noqa: B008 + 0.2, + "--postedit-temperature", + help="Temperature for post-edit LLM pass.", + ), + device: str = typer.Option( # noqa: B008 + "auto", + "--device", + "-d", + help="Device for translation models: auto, cpu, cuda, or GPU index (e.g., 0).", + ), + verbose: bool = typer.Option( # noqa: B008 + False, + "--verbose", + "-v", + help="Print progress information to stderr.", + ), +) -> None: + """Translate a Markdown file using offline MT + local post-edit.""" + reporter = (lambda msg: typer.secho(msg, err=True)) if verbose else None + + project_cfg = None + if project: + try: + project_cfg = load_project(project) + except (FileNotFoundError, ValueError, OSError) as exc: + typer.secho(str(exc), err=True, fg=typer.colors.RED) + raise typer.Exit(5) from exc + resolved_src = src or (project_cfg["language"] if project_cfg else None) + if not resolved_src: + raise typer.BadParameter("--src is required unless --project provides a language") + resolved_tone = tone or (project_cfg["tone"] if project_cfg else "neutral") + resolved_audience = audience or (project_cfg["audience"] if project_cfg else "educated general") + + text = input_path.read_text(encoding="utf-8") + glossary_map = _load_glossary(glossary) + tone_profile = ToneProfile(register=resolved_tone, audience=resolved_audience) + + cfg = TranslationConfig( + source_lang=resolved_src, + target_lang=tgt, + tone=tone_profile, + glossary=glossary_map, + protected_patterns=protect, + allow_pivot_via_en=allow_pivot, + postedit_enabled=postedit, + ) + + registry = ModelRegistry() + mt = MTTranslator(registry, device=device) + posteditor = LLMPostEditor( + model_name=postedit_model, + temperature=postedit_temperature, + create_agent=postedit, + max_chars=postedit_max_chars, + ) + debug_records: list[dict[str, Any]] = [] + segmenter = MarkdownSegmenter(protected_patterns=protect) + pipeline = TranslationPipeline( + registry=registry, + mt=mt, + postedit=posteditor, + segmenter=segmenter, + debug_callback=debug_records.append if debug else None, + reporter=reporter, + ) + + translated = pipeline.translate(text, cfg) + if output_path: + output_path.write_text(translated, encoding="utf-8") + typer.echo(f"Wrote translation to {output_path}") + else: + typer.echo(translated) + + if debug: + debug_payload = { + "blocks": [asdict(block) for block in segmenter.segment(text)], + "stages": debug_records, + } + debug_path = _debug_path(output_path or input_path) + debug_path.write_text(json.dumps(debug_payload, indent=2), encoding="utf-8") + typer.echo(f"Wrote debug report to {debug_path}") + + +translate_command = translate + +__all__ = ["translate_command", "translate_app"] diff --git a/tests/unit/main_test.py b/tests/unit/main_test.py index bf13206..edbbcfc 100644 --- a/tests/unit/main_test.py +++ b/tests/unit/main_test.py @@ -65,7 +65,7 @@ def test_brief_requires_output_choice(note_file: Path) -> None: def test_brief_prints_json(monkeypatch: pytest.MonkeyPatch, note_file: Path, fake: Faker) -> None: brief_obj = _fake_brief(fake) - monkeypatch.setattr("scribae.main.brief.generate_brief", lambda *_, **__: brief_obj) + monkeypatch.setattr("scribae.brief.generate_brief", lambda *_, **__: brief_obj) result = runner.invoke( app, @@ -85,7 +85,7 @@ def test_brief_prints_json(monkeypatch: pytest.MonkeyPatch, note_file: Path, fak def test_brief_writes_to_file(monkeypatch: pytest.MonkeyPatch, note_file: Path, tmp_path: Path, fake: Faker) -> None: brief_obj = _fake_brief(fake) - monkeypatch.setattr("scribae.main.brief.generate_brief", lambda *_, **__: brief_obj) + monkeypatch.setattr("scribae.brief.generate_brief", lambda *_, **__: brief_obj) output_path = tmp_path / "brief.json" result = runner.invoke( @@ -115,7 +115,7 @@ def test_brief_dry_run_prints_prompt(monkeypatch: pytest.MonkeyPatch, note_file: def _should_not_run(*_: object, **__: object) -> None: raise AssertionError("generate_brief should not run during dry run") - monkeypatch.setattr("scribae.main.brief.generate_brief", _should_not_run) + monkeypatch.setattr("scribae.brief.generate_brief", _should_not_run) result = runner.invoke( app, @@ -140,8 +140,8 @@ def test_brief_save_prompt_creates_files( note_body: str, ) -> None: brief_obj = _fake_brief(fake) - monkeypatch.setattr("scribae.main.brief.generate_brief", lambda *_, **__: brief_obj) - monkeypatch.setattr("scribae.main.brief._current_timestamp", lambda: "20240101-120000") + monkeypatch.setattr("scribae.brief.generate_brief", lambda *_, **__: brief_obj) + monkeypatch.setattr("scribae.brief._current_timestamp", lambda: "20240101-120000") prompt_dir = tmp_path / "prompts" diff --git a/tests/unit/test_postedit.py b/tests/unit/test_postedit.py new file mode 100644 index 0000000..2b6669c --- /dev/null +++ b/tests/unit/test_postedit.py @@ -0,0 +1,335 @@ +"""Tests for LLMPostEditor Markdown structure preservation.""" + +from __future__ import annotations + +import asyncio +from pathlib import Path +from typing import Any, cast + +import pytest +from pydantic_ai import Agent, UnexpectedModelBehavior + +from scribae.translate.markdown_segmenter import ProtectedText +from scribae.translate.pipeline import ToneProfile, TranslationConfig +from scribae.translate.postedit import LLMPostEditor, PostEditAborted + + +class TestRestoreMarkdownStructure: + """Tests for the _restore_markdown_structure method.""" + + def setup_method(self) -> None: + """Create a post-editor instance for testing.""" + self.posteditor = LLMPostEditor(create_agent=False) + + def test_blockquotes_preserved(self) -> None: + """Blockquote prefixes are restored when stripped by LLM.""" + mt_draft = "> This is a quote\n> Second line of quote" + edited = "This is a quote\nSecond line of quote" + + result = self.posteditor._restore_markdown_structure(mt_draft, edited) + + assert result == "> This is a quote\n> Second line of quote" + + def test_nested_blockquotes_preserved(self) -> None: + """Nested blockquote prefixes are restored correctly.""" + mt_draft = "> Outer quote\n> > Nested quote\n> > > Deeply nested" + edited = "Outer quote\nNested quote\nDeeply nested" + + result = self.posteditor._restore_markdown_structure(mt_draft, edited) + + assert "> Outer quote" in result + assert "> > Nested quote" in result + assert "> > > Deeply nested" in result + + def test_bullet_list_preserved(self) -> None: + """Bullet list markers (-, *, +) are restored when stripped.""" + mt_draft = "- Item one\n- Item two\n- Item three" + edited = "Item one\nItem two\nItem three" + + result = self.posteditor._restore_markdown_structure(mt_draft, edited) + + assert result == "- Item one\n- Item two\n- Item three" + + def test_asterisk_list_preserved(self) -> None: + """Asterisk list markers are restored when stripped.""" + mt_draft = "* First\n* Second" + edited = "First\nSecond" + + result = self.posteditor._restore_markdown_structure(mt_draft, edited) + + assert result == "* First\n* Second" + + def test_plus_list_preserved(self) -> None: + """Plus list markers are restored when stripped.""" + mt_draft = "+ Alpha\n+ Beta" + edited = "Alpha\nBeta" + + result = self.posteditor._restore_markdown_structure(mt_draft, edited) + + assert result == "+ Alpha\n+ Beta" + + def test_numbered_list_preserved(self) -> None: + """Numbered list markers are restored when stripped.""" + mt_draft = "1. First item\n2. Second item\n10. Tenth item" + edited = "First item\nSecond item\nTenth item" + + result = self.posteditor._restore_markdown_structure(mt_draft, edited) + + assert result == "1. First item\n2. Second item\n10. Tenth item" + + def test_mixed_markdown_preserved(self) -> None: + """Mixed Markdown content (blockquotes + lists + text) is preserved.""" + mt_draft = "# Heading\n\n> A blockquote\n\n- List item\n\n**Bold text**" + edited = "# Heading\n\nA blockquote\n\nList item\n\n**Bold text**" + + result = self.posteditor._restore_markdown_structure(mt_draft, edited) + + assert "> A blockquote" in result + assert "- List item" in result + assert "**Bold text**" in result + + def test_indented_list_preserved(self) -> None: + """Indented list markers are restored correctly.""" + mt_draft = "- Parent\n - Child\n - Grandchild" + edited = "Parent\nChild\nGrandchild" + + result = self.posteditor._restore_markdown_structure(mt_draft, edited) + + assert "- Parent" in result + assert " - Child" in result + assert " - Grandchild" in result + + def test_no_restoration_when_line_counts_differ_significantly(self) -> None: + """Restoration is skipped when line counts differ by more than 33%.""" + mt_draft = "Line 1\nLine 2\nLine 3" + # Edited has 5 lines vs 3 lines in MT (>33% difference) + edited = "Line 1\nLine 2\nLine 3\nLine 4\nLine 5" + + result = self.posteditor._restore_markdown_structure(mt_draft, edited) + + # Should return edited unchanged + assert result == edited + + def test_no_restoration_when_fewer_lines_significantly(self) -> None: + """Restoration is skipped when edited has significantly fewer lines.""" + mt_draft = "Line 1\nLine 2\nLine 3\nLine 4\nLine 5\nLine 6" + # Edited has 3 lines vs 6 lines in MT (50% difference) + edited = "Line 1\nLine 2\nLine 3" + + result = self.posteditor._restore_markdown_structure(mt_draft, edited) + + # Should return edited unchanged + assert result == edited + + def test_empty_mt_draft_returns_edited(self) -> None: + """Empty MT draft returns edited text unchanged.""" + mt_draft = "" + edited = "Some edited text" + + result = self.posteditor._restore_markdown_structure(mt_draft, edited) + + assert result == edited + + def test_preserves_existing_markdown_in_edited(self) -> None: + """Does not double-add prefixes if edited already has them.""" + mt_draft = "> Quote line\n- List item" + edited = "> Quote line\n- List item" + + result = self.posteditor._restore_markdown_structure(mt_draft, edited) + + assert result == "> Quote line\n- List item" + + def test_extra_edited_lines_kept_as_is(self) -> None: + """Extra lines in edited (within threshold) are kept unchanged.""" + mt_draft = "> Line 1\n> Line 2\n> Line 3\n> Line 4" + # 5 lines vs 4 lines is 25% difference, within 33% threshold + edited = "Line 1\nLine 2\nLine 3\nLine 4\nExtra line" + + result = self.posteditor._restore_markdown_structure(mt_draft, edited) + + lines = result.splitlines() + assert lines[0] == "> Line 1" + assert lines[1] == "> Line 2" + assert lines[2] == "> Line 3" + assert lines[3] == "> Line 4" + assert lines[4] == "Extra line" + + def test_blockquote_with_list_inside(self) -> None: + """Blockquotes containing lists are handled (blockquote takes precedence).""" + mt_draft = "> - List in quote" + edited = "- List in quote" + + result = self.posteditor._restore_markdown_structure(mt_draft, edited) + + # The blockquote prefix should be restored + assert result == "> - List in quote" + + +class TestPostEditGuards: + def setup_method(self) -> None: + self.cfg = TranslationConfig(source_lang="en", target_lang="de", tone=ToneProfile()) + + def test_prompt_too_long_aborts_postedit(self) -> None: + class DummyAgent: + async def run(self, prompt: str, **_: object) -> object: # pragma: no cover - should be skipped by guard + return type("Run", (), {"output": "ok"})() + + posteditor = LLMPostEditor(agent=cast(Agent[None, str], DummyAgent()), max_chars=10, timeout_seconds=1) + + with pytest.raises(PostEditAborted): + posteditor.post_edit("source", "mt draft", self.cfg, ProtectedText("mt draft", {})) + + def test_timeout_aborts_postedit(self) -> None: + class SlowAgent: + async def run(self, prompt: str, **_: object) -> object: + await asyncio.sleep(0.05) + return type("Run", (), {"output": "ok"})() + + posteditor = LLMPostEditor(agent=cast(Agent[None, str], SlowAgent()), timeout_seconds=0.01, max_chars=1_000_000) + + with pytest.raises(PostEditAborted): + posteditor.post_edit("source", "mt draft", self.cfg, ProtectedText("mt draft", {})) + + def test_inputs_trimmed_to_budget(self) -> None: + recorded: dict[str, str] = {} + + class RecordingAgent: + async def run(self, prompt: str, **_: object) -> object: + recorded["prompt"] = prompt + return type("Run", (), {"output": "ok"})() + + posteditor = LLMPostEditor( + agent=cast(Agent[None, str], RecordingAgent()), + max_chars=10_000, + timeout_seconds=1, + ) + long_source = "X" * 6_000 + long_mt = "Y" * 6_000 + + posteditor.post_edit(long_source, long_mt, self.cfg, ProtectedText(long_mt, {})) + + prompt = recorded["prompt"] + assert "X" * 4_501 not in prompt + assert "Y" * 4_501 not in prompt + + +class TestPostEditOutputValidator: + def setup_method(self) -> None: + self.posteditor = LLMPostEditor(create_agent=False, language_detector=lambda _text: "de") + + def test_rejects_missing_placeholder(self) -> None: + validator = self.posteditor._build_output_validator(["__P1__"], mt_draft="> Quote", expected_lang="de") + + with pytest.raises(UnexpectedModelBehavior): + validator("> Quote without token") + + def test_rejects_large_line_drift(self) -> None: + validator = self.posteditor._build_output_validator([], mt_draft="Line 1\nLine 2\nLine 3", expected_lang="de") + + with pytest.raises(UnexpectedModelBehavior): + validator("Only one line") + + def test_rejects_removed_markdown_markers(self) -> None: + mt_draft = "> Quoted line\n- list item" + validator = self.posteditor._build_output_validator([], mt_draft=mt_draft, expected_lang="de") + + with pytest.raises(UnexpectedModelBehavior): + validator("Quoted line\nlist item") + + def test_accepts_valid_output(self) -> None: + mt_draft = "> Quoted line\n- list item" + validator = self.posteditor._build_output_validator(["__P1__"], mt_draft=mt_draft, expected_lang="de") + + result = validator("> Quoted line with __P1__\n- list item") + + assert result.startswith("> Quoted line with __P1__") + + def test_rejects_unexpected_language(self) -> None: + posteditor = LLMPostEditor(create_agent=False, language_detector=lambda _text: "fr") + validator = posteditor._build_output_validator([], mt_draft="Text", expected_lang="de") + + with pytest.raises(UnexpectedModelBehavior): + validator("Bonjour tout le monde") + + def test_language_detection_uses_fast_langdetect(self, tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None: + model_path = tmp_path / "lid.176.bin" + posteditor = LLMPostEditor(create_agent=False, language_detector=None) + monkeypatch.setenv("FASTTEXT_LID_MODEL", str(model_path)) + + captured: dict[str, Any] = {} + + class FakeConfig: + def __init__(self, **kwargs: object) -> None: + captured["config_kwargs"] = kwargs + + class FakeDetector: + def __init__(self, config: FakeConfig | None = None) -> None: + captured["config"] = config + + def detect( + self, + text: str, + model: str = "auto", + k: int = 1, + threshold: float = 0.0, + ) -> list[dict[str, object]]: + captured["detect_args"] = (text, model, k, threshold) + return [{"lang": "DE", "score": 0.9}] + + class FakeModule: + LangDetectConfig = FakeConfig + LangDetector = FakeDetector + + fake_module = FakeModule() + monkeypatch.setattr("scribae.translate.postedit.importlib.import_module", lambda name: fake_module) + + detector = posteditor._create_language_detector() + lang = detector("Hallo Welt") + + assert lang == "de" + assert captured["config_kwargs"] == {"custom_model_path": str(model_path)} + assert captured["detect_args"][1:] == ("auto", 1, 0.0) + + def test_language_detection_falls_back_on_numpy_copy_error(self) -> None: + posteditor = LLMPostEditor(create_agent=False, language_detector=None) + + class FakeDetector: + config = type("Config", (), {"normalize_input": True})() + + def __init__(self) -> None: + self.called = {"detect": 0, "predict": 0} + + def detect( + self, text: str, model: str = "auto", k: int = 1, threshold: float = 0.0 + ) -> list[dict[str, object]]: + self.called["detect"] += 1 + raise ValueError("Unable to avoid copy while creating an array as requested.") + + def _get_model(self, low_memory: bool, fallback_on_memory_error: bool) -> Any: + self.called["predict"] += 1 + + class RawPredictor: + def __init__(self) -> None: + class F: + def predict( + self_inner, text: str, k: int, threshold: float, mode: str + ) -> list[tuple[float, str]]: + return [(0.9, "__label__EN")] + + self.f = F() + + return RawPredictor() + + def _preprocess_text(self, text: str) -> str: + return text + + def _normalize_text(self, text: str, normalize_input: bool) -> str: + return text + + detector = FakeDetector() + results = posteditor._detect_labels(detector, "Hello", model="auto", k=1, threshold=0.0) + + assert results[0]["lang"] == "EN" + assert results[0]["score"] == 0.9 + assert detector.called["detect"] == 1 + assert detector.called["predict"] == 1 diff --git a/tests/unit/translate_cli_test.py b/tests/unit/translate_cli_test.py new file mode 100644 index 0000000..e9f09a3 --- /dev/null +++ b/tests/unit/translate_cli_test.py @@ -0,0 +1,179 @@ +from __future__ import annotations + +import re +from pathlib import Path +from typing import Any, cast + +import pytest +from typer.testing import CliRunner + +from scribae import project as project_module +from scribae.main import app +from scribae.translate import TranslationConfig + +runner = CliRunner() + + +@pytest.fixture() +def input_markdown(tmp_path: Path) -> Path: + path = tmp_path / "note.md" + path.write_text("Hello world", encoding="utf-8") + return path + + +@pytest.fixture(autouse=True) +def stub_translation_components(monkeypatch: pytest.MonkeyPatch) -> dict[str, Any]: + calls: dict[str, Any] = {} + + class DummyRegistry: + def __init__(self, *args: object, **kwargs: object) -> None: + self.args = args + self.kwargs = kwargs + + class DummyTranslator: + def __init__(self, registry: DummyRegistry, device: str | None = None) -> None: + self.registry = registry + self.device = device + + class DummyPostEditor: + def __init__(self, *args: object, **kwargs: object) -> None: + self.args = args + self.kwargs = kwargs + + class DummySegmenter: + def __init__(self, protected_patterns: list[str] | None = None) -> None: + self.protected_patterns = protected_patterns or [] + + class DummyPipeline: + def __init__( + self, + *, + registry: DummyRegistry, + mt: DummyTranslator, + postedit: DummyPostEditor, + segmenter: DummySegmenter, + debug_callback: object = None, + reporter: object = None, + ) -> None: + self.registry = registry + self.mt = mt + self.postedit = postedit + self.segmenter = segmenter + self.debug_callback = debug_callback + self.reporter = reporter + + def translate(self, text: str, cfg: Any) -> str: + calls["text"] = text + calls["cfg"] = cfg + return f"translated:{getattr(cfg, 'source_lang', '?')}->{getattr(cfg, 'target_lang', '?')}" + + monkeypatch.setattr("scribae.translate_cli.ModelRegistry", DummyRegistry) + monkeypatch.setattr("scribae.translate_cli.MTTranslator", DummyTranslator) + monkeypatch.setattr("scribae.translate_cli.LLMPostEditor", DummyPostEditor) + monkeypatch.setattr("scribae.translate_cli.MarkdownSegmenter", DummySegmenter) + monkeypatch.setattr("scribae.translate_cli.TranslationPipeline", DummyPipeline) + + return calls + + +def _patch_loader(monkeypatch: pytest.MonkeyPatch, projects_dir: Path) -> None: + loader = project_module.load_project + monkeypatch.setattr( + "scribae.translate_cli.load_project", lambda name: loader(name, base_dir=projects_dir) + ) + + +def test_translate_requires_src_without_project( + stub_translation_components: dict[str, Any], + input_markdown: Path, +) -> None: + result = runner.invoke( + app, + [ + "translate", + "--tgt", + "de", + "--in", + str(input_markdown), + ], + ) + + assert result.exit_code != 0 + # Rich/Click may add ANSI color codes; strip them before assertion + ansi_stripped = re.sub(r"\x1b\[[0-9;]*m", "", result.stderr) + assert "--src is required unless --project provides a language" in ansi_stripped + + +def test_translate_uses_project_defaults( + monkeypatch: pytest.MonkeyPatch, + stub_translation_components: dict[str, Any], + tmp_path: Path, + input_markdown: Path, +) -> None: + projects_dir = tmp_path / "projects" + projects_dir.mkdir() + (projects_dir / "demo.yaml").write_text( + "language: fr\n" "tone: academic\n" "audience: researchers\n", + encoding="utf-8", + ) + _patch_loader(monkeypatch, projects_dir) + + result = runner.invoke( + app, + [ + "translate", + "--project", + "demo", + "--tgt", + "de", + "--in", + str(input_markdown), + ], + ) + + assert result.exit_code == 0 + cfg = cast(TranslationConfig, stub_translation_components["cfg"]) + assert cfg.source_lang == "fr" + assert cfg.tone.register == "academic" + assert cfg.tone.audience == "researchers" + assert "translated:fr->de" in result.stdout + + +def test_translate_flags_override_project_defaults( + monkeypatch: pytest.MonkeyPatch, + stub_translation_components: dict[str, Any], + tmp_path: Path, + input_markdown: Path, +) -> None: + projects_dir = tmp_path / "projects" + projects_dir.mkdir() + (projects_dir / "demo.yaml").write_text( + "language: fr\n" "tone: academic\n" "audience: researchers\n", + encoding="utf-8", + ) + _patch_loader(monkeypatch, projects_dir) + + result = runner.invoke( + app, + [ + "translate", + "--project", + "demo", + "--src", + "en", + "--tone", + "casual", + "--audience", + "gamers", + "--tgt", + "de", + "--in", + str(input_markdown), + ], + ) + + assert result.exit_code == 0 + cfg = cast(TranslationConfig, stub_translation_components["cfg"]) + assert cfg.source_lang == "en" + assert cfg.tone.register == "casual" + assert cfg.tone.audience == "gamers" diff --git a/tests/unit/translate_pipeline_test.py b/tests/unit/translate_pipeline_test.py new file mode 100644 index 0000000..c56a779 --- /dev/null +++ b/tests/unit/translate_pipeline_test.py @@ -0,0 +1,229 @@ +from __future__ import annotations + +from typing import cast + +from transformers import Pipeline + +from scribae.translate.markdown_segmenter import MarkdownSegmenter, ProtectedText +from scribae.translate.model_registry import ModelRegistry, ModelSpec +from scribae.translate.mt import MTTranslator +from scribae.translate.pipeline import ToneProfile, TranslationConfig, TranslationPipeline +from scribae.translate.postedit import LLMPostEditor, PostEditAborted, PostEditValidationError + + +class StubMT(MTTranslator): + def __init__(self, registry: ModelRegistry) -> None: + super().__init__(registry=registry) + + def translate_block( + self, + text: str, + src_lang: str, + tgt_lang: str, + *, + allow_pivot: bool = True, + backend: str = "marian_then_nllb", + ) -> str: + return text.replace("Hello", "Hallo").replace("product", "Produkt") + + def translate_blocks( + self, + texts: list[str], + src_lang: str, + tgt_lang: str, + *, + allow_pivot: bool = True, + backend: str = "marian_then_nllb", + ) -> list[str]: + return [self.translate_block(t, src_lang, tgt_lang, allow_pivot=allow_pivot, backend=backend) for t in texts] + + +def test_pipeline_preserves_code_links_and_placeholders() -> None: + registry = ModelRegistry(specs=[]) + mt = StubMT(registry) + posteditor = LLMPostEditor(create_agent=False) + segmenter = MarkdownSegmenter() + pipeline = TranslationPipeline(registry=registry, mt=mt, postedit=posteditor, segmenter=segmenter) + + text = "Hello `code` world [link](https://example.com) and {placeholder}\n\n```\nHello code\n```" + cfg = TranslationConfig(source_lang="en", target_lang="de", tone=ToneProfile()) + + result = pipeline.translate(text, cfg) + + assert "`code`" in result + assert "https://example.com" in result + assert "{placeholder}" in result + assert "Hallo" in result.splitlines()[0] + assert "Hello code" in result.splitlines()[-2] + + +def test_routing_direct_pivot_and_fallback() -> None: + registry = ModelRegistry() + direct_route = registry.route("en", "de") + assert len(direct_route) == 1 + assert direct_route[0].model.backend == "marian" + + custom_registry = ModelRegistry( + specs=[ + ModelSpec(model_id="mt-de-en", src_lang="de", tgt_lang="en", backend="marian"), + ModelSpec(model_id="mt-en-it", src_lang="en", tgt_lang="it", backend="marian"), + ] + ) + pivot_route = custom_registry.route("de", "it", allow_pivot=True) + assert [step.model.model_id for step in pivot_route] == ["mt-de-en", "mt-en-it"] + + fallback_route = custom_registry.route("de", "fr", allow_pivot=False) + assert len(fallback_route) == 1 + assert fallback_route[0].model.backend == "nllb" + + +def test_postedit_enforces_glossary_keep_and_target() -> None: + posteditor = LLMPostEditor(create_agent=False) + segmenter = MarkdownSegmenter() + protected = segmenter.protect_text("SaaS keeps product", []) + cfg = TranslationConfig( + source_lang="en", + target_lang="de", + tone=ToneProfile(), + glossary={"SaaS": "KEEP", "product": "Produkt"}, + ) + + result = posteditor.post_edit("SaaS keeps product", protected.text, cfg, protected) + + assert "SaaS" in result + assert "Produkt" in result + + +def test_postedit_fallback_returns_mt_draft_when_validation_fails() -> None: + class AlwaysFailPost(LLMPostEditor): + def __init__(self) -> None: + super().__init__(create_agent=False) + + def post_edit( + self, + source_text: str, + mt_draft: str, + cfg: TranslationConfig, + protected: ProtectedText, + *, + strict: bool = False, + ) -> str: + raise PostEditValidationError("fail") + + class EchoMT(MTTranslator): + def __init__(self, registry: ModelRegistry) -> None: + super().__init__(registry=registry) + + def translate_block( + self, + text: str, + src_lang: str, + tgt_lang: str, + *, + allow_pivot: bool = True, + backend: str = "marian_then_nllb", + ) -> str: + return text + " ::mt" + + def translate_blocks( + self, + texts: list[str], + src_lang: str, + tgt_lang: str, + *, + allow_pivot: bool = True, + backend: str = "marian_then_nllb", + ) -> list[str]: + return [ + self.translate_block(t, src_lang, tgt_lang, allow_pivot=allow_pivot, backend=backend) for t in texts + ] + + registry = ModelRegistry(specs=[]) + mt = EchoMT(registry) + posteditor = AlwaysFailPost() + pipeline = TranslationPipeline(registry=registry, mt=mt, postedit=posteditor, segmenter=MarkdownSegmenter()) + cfg = TranslationConfig(source_lang="en", target_lang="de", tone=ToneProfile()) + + result = pipeline.translate("Simple text", cfg) + assert result.endswith("::mt") + + +def test_postedit_abort_skips_strict_retry() -> None: + class AbortPostEditor(LLMPostEditor): + def __init__(self) -> None: + super().__init__(create_agent=False) + self.calls = 0 + + def post_edit( + self, + source_text: str, + mt_draft: str, + cfg: TranslationConfig, + protected: ProtectedText, + *, + strict: bool = False, + ) -> str: + self.calls += 1 + raise PostEditAborted("prompt too large") + + class EchoMT(MTTranslator): + def __init__(self, registry: ModelRegistry) -> None: + super().__init__(registry=registry) + + def translate_block( + self, + text: str, + src_lang: str, + tgt_lang: str, + *, + allow_pivot: bool = True, + backend: str = "marian_then_nllb", + ) -> str: + return text + " ::mt" + + def translate_blocks( + self, + texts: list[str], + src_lang: str, + tgt_lang: str, + *, + allow_pivot: bool = True, + backend: str = "marian_then_nllb", + ) -> list[str]: + return [ + self.translate_block(t, src_lang, tgt_lang, allow_pivot=allow_pivot, backend=backend) for t in texts + ] + + registry = ModelRegistry(specs=[]) + mt = EchoMT(registry) + posteditor = AbortPostEditor() + pipeline = TranslationPipeline(registry=registry, mt=mt, postedit=posteditor, segmenter=MarkdownSegmenter()) + cfg = TranslationConfig(source_lang="en", target_lang="de", tone=ToneProfile()) + + result = pipeline.translate("Simple text", cfg) + + assert result.endswith("::mt") + assert posteditor.calls == 1 + + +def test_mt_translator_batches_and_preserves_order() -> None: + calls: list[list[str] | str] = [] + + class RecordingMT(MTTranslator): + def _pipeline_for(self, model_id: str) -> Pipeline: + def translator(texts: list[str] | str, **_: object) -> list[dict[str, str]]: + calls.append(texts) + if isinstance(texts, list): + return [{"translation_text": t.upper()} for t in texts] + return [{"translation_text": str(texts).upper()}] + + return cast(Pipeline, translator) + + registry = ModelRegistry(specs=[ModelSpec(model_id="mt-en-de", src_lang="en", tgt_lang="de", backend="marian")]) + mt = RecordingMT(registry=registry) + + outputs = mt.translate_blocks(["a", "b"], "en", "de") + + assert outputs == ["A", "B"] + assert len(calls) == 1 + assert calls[0] == ["a", "b"] diff --git a/uv.lock b/uv.lock index ca7ba82..e942442 100644 --- 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