Initial commit

2026-01-19 09:51:07 +08:00
commit 9ef82393be
174 changed files with 22285 additions and 0 deletions
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+"""
+Quality Manager Module
+
+Responsible for evaluating translation quality and deciding on re-translation.
+"""
+
+import json
+import random
+from typing import List, Dict, Any, Tuple
+from loguru import logger
+from .manifest_manager import ManifestItem
+from .llm_client import LLMClient
+
+class QualityManager:
+    def __init__(self, config: Dict, llm_client: LLMClient):
+        self.config = config
+        self.llm_client = llm_client
+        self.qc_config = config['translation'].get('quality_control', {})
+        self.pass_score = self.qc_config.get('pass_score', 7)
+        self.sample_size = self.qc_config.get('sample_size', 2)
+
+    async def evaluate_chunk(self, chunk: List[ManifestItem]) -> Tuple[bool, int, str]:
+        """
+        Evaluate a chunk of translations.
+        
+        Returns:
+            (passed: bool, average_score: int, reason: str)
+        """
+        if not self.qc_config.get('enabled', False):
+            return True, 10, "QC Disabled"
+
+        # 1. Sample items
+        # Filter for items that actually have content and translations
+        valid_items = [item for item in chunk if item.translation and len(item.clean_text) > 20]
+        
+        if not valid_items:
+            return True, 10, "No valid items to sample"
+            
+        sample_items = random.sample(valid_items, min(len(valid_items), self.sample_size))
+        
+        # 2. Build Prompt
+        prompt = self._build_evaluation_prompt(sample_items)
+        
+        # 3. Call LLM (Smart)
+        try:
+            response = await self.llm_client.raw_chat_completion(
+                system_prompt="You are a professional translation editor.",
+                user_prompt=prompt,
+                model_type="smart"
+            )
+            
+            # 4. Parse JSON
+            # Clean potential markdown
+            json_str = response.strip()
+            if "```json" in json_str:
+                json_str = json_str.split("```json")[1].split("```")[0].strip()
+            elif "```" in json_str:
+                json_str = json_str.split("```")[1].split("```")[0].strip()
+                
+            result = json.loads(json_str)
+            score = result.get('score', 0)
+            reason = result.get('reason', 'No reason provided')
+            
+            passed = score >= self.pass_score
+            return passed, score, reason
+            
+        except Exception as e:
+            logger.error(f"QC evaluation failed: {e}")
+            # If QC fails, we default to PASS to avoid blocking progress, but log it
+            return True, 0, f"QC Error: {e}"
+
+    def _build_evaluation_prompt(self, items: List[ManifestItem]) -> str:
+        content = ""
+        for i, item in enumerate(items, 1):
+            content += f"Item {i}:\nOriginal: {item.clean_text}\nTranslation: {item.translation}\n\n"
+            
+        return f"""Please evaluate the following translations (English to Chinese).
+Focus on accuracy, fluency, and terminology consistency.
+
+Items to evaluate:
+{content}
+
+Return a JSON object with:
+- \"score\": An integer from 1 to 10 (10 being perfect).
+- \"reason\": A brief explanation of the score.
+
+JSON Output:"""