fix(reader): prevent false phrasal verb detection for noun collocations and improve literary translation accuracy

app/ai.py

@@ -9,6 +9,36 @@ from app.database import get_db, get_cached_sentence_translation, save_sentence_
 logger = logging.getLogger(__name__)
 
 
+COMMON_STOPWORDS = {
+    "a", "an", "the", "in", "on", "at", "to", "for", "of", "with", "by", "from",
+    "up", "about", "into", "over", "after", "beneath", "under", "above", "is", "am",
+    "are", "was", "were", "be", "been", "being", "have", "has", "had", "do", "does",
+    "did", "and", "but", "if", "or", "because", "as", "until", "while", "this", "that",
+    "these", "those", "i", "you", "he", "she", "it", "we", "they", "them", "him", "her",
+    "us", "me", "my", "your", "his", "its", "our", "their", "not", "no", "nor", "can",
+    "could", "will", "would", "shall", "should", "may", "might", "must", "there", "here",
+    "when", "where", "why", "how", "all", "any", "both", "each", "few", "more", "most",
+    "other", "some", "such", "than", "too", "very", "so", "s", "t", "d", "ll", "ve", "m"
+}
+
+
+def clean_dict_translation(raw: str) -> str:
+    """Extracts first 1-2 clean Cyrillic meanings, stripping phonetic / Latin noise."""
+    if not raw:
+        return ""
+    clean = re.sub(r'/[^/]*$', '', raw)
+    parts = re.split(r'[,;]\s*', clean)
+    cyrillic_parts = []
+    for p in parts:
+        p_clean = re.sub(r"[a-zA-Záéíóúýšžčñ']+", '', p).strip()
+        p_clean = re.sub(r'\s+', ' ', p_clean).strip(' /\\,;-()[]')
+        if p_clean and re.search(r'[\u0400-\u04FF]', p_clean) and p_clean not in cyrillic_parts:
+            cyrillic_parts.append(p_clean)
+        if len(cyrillic_parts) >= 2:
+            break
+    return ", ".join(cyrillic_parts) if cyrillic_parts else raw[:50].strip()
+
+
 def get_dictionary_hint(term: str) -> str:
     """Retrieves verified offline dictionary translation hints for term."""
     clean = term.strip()
@@ -21,17 +51,80 @@ def get_dictionary_hint(term: str) -> str:
                 (clean,),
             ).fetchone()
             if row and row["translation"]:
-                return row["translation"].strip()
+                return clean_dict_translation(row["translation"])
     except Exception:
         pass
     return ""
 
 
+def get_sentence_dictionary_hints(sentence: str, target_word: str = "") -> str:
+    """Extracts verified offline dictionary translations for key words and phrases in sentence."""
+    if not sentence:
+        return ""
+    words = re.findall(r"\b[a-zA-Z\'-]+\b", sentence)
+    if not words:
+        return ""
+
+    candidates = set()
+    # Check 2-word contiguous phrases (collocations/idioms)
+    for i in range(len(words) - 1):
+        phrase = f"{words[i]} {words[i+1]}".lower()
+        candidates.add(phrase)
+
+    # Check content words
+    for w in words:
+        wl = w.lower()
+        if len(wl) > 2 and wl not in COMMON_STOPWORDS:
+            candidates.add(wl)
+
+    if not candidates:
+        return ""
+
+    hints = []
+    special_guidance = {
+        "owl": "owl — это сова/неясыть (ни в коем случае НЕ орёл!)",
+        "tawny owl": "tawny owl — это сова/неясыть (птица семейства совиных, ни в коем случае НЕ орёл!)",
+    }
+
+    try:
+        with get_db() as conn:
+            placeholders = ",".join(["?"] * len(candidates))
+            query = f"SELECT term, translation FROM offline_dictionary WHERE term IN ({placeholders}) COLLATE NOCASE"
+            rows = conn.execute(query, list(candidates)).fetchall()
+
+            matched_dict = {}
+            for r in rows:
+                term_lower = r["term"].lower()
+                clean_trans = clean_dict_translation(r["translation"])
+                if clean_trans:
+                    matched_dict[term_lower] = clean_trans
+
+            seen_terms = set()
+            for cand in sorted(matched_dict.keys(), key=lambda x: (0 if " " in x else 1, 0 if x == target_word.lower() else 1)):
+                if cand in seen_terms:
+                    continue
+                seen_terms.add(cand)
+                trans = matched_dict[cand]
+                guidance = special_guidance.get(cand, "")
+                if guidance:
+                    hints.append(f"- {cand}: {trans} (ВНИМАНИЕ: {guidance})")
+                else:
+                    hints.append(f"- {cand}: {trans}")
+
+                if len(hints) >= 8:
+                    break
+    except Exception as e:
+        logger.warning(f"Error extracting sentence dictionary hints: {e}")
+
+    return "\n".join(hints)
+
+
 def build_translation_prompt(
     sentence: str,
     target_word: str = "",
     context: str = "",
     dict_hint: str = "",
+    sentence_hints: str = "",
 ) -> str:
     clean_sentence = sentence.strip()
     clean_word = target_word.strip()
@@ -49,18 +142,24 @@ def build_translation_prompt(
             target_section += f'Возможные словарные значения: {dict_hint}\n'
         target_section += "\n"
 
+    hints_section = ""
+    if sentence_hints:
+        hints_section = f"Словарные подсказки по ключевым словам предложения:\n{sentence_hints}\n\n"
+
     return (
         "Ты — профессиональный литературный переводчик художественной и научно-популярной литературы на русский язык.\n"
         "Твоя задача — перевести указанное английское предложение на красивый, естественный, богатый и грамматически безупречный русский язык, идеально вписывающийся в повествование книги.\n\n"
         f"{context_section}"
         f'Предложение для перевода:\n"{clean_sentence}"\n\n'
         f"{target_section}"
+        f"{hints_section}"
         "Обязательные правила перевода:\n"
-        "1. ПОЛНОТА И СВЯЗНОСТЬ: Переводи абсолютно ВСЕ смысловые части и придаточные обороты без пропусков! Обращай особое внимание на бессоюзные определительные обороты (zero relative clauses, например: 'the book I read' -> 'книга, которую я читал', 'Tuesday our story starts' -> 'вторник, с которого начинается наша история'). Ничего не выбрасывай!\n"
+        "1. ПОЛНОТА И СВЯЗНОСТЬ: Переводи абсолютно ВСЕ смысловые части, обороты и определения без пропусков! Обращай особое внимание на цепочки прилагательных и определений (например: 'a large, tawny owl' -> 'крупная неясыть' или 'большая рыжевато-бурая сова' — ни в коем случае не пропускай 'large'!). Также переводи бессоюзные определительные обороты (zero relative clauses, например: 'Tuesday our story starts' -> 'вторник, с которого начинается наша история'). Ничего не выбрасывай!\n"
-        "2. БЕЗ ДОСЛОВНОГО КАЛЬКИРОВАНИЯ: Никаких топорных калек предлогов ('on Tuesday' -> 'во вторник', а не 'на вторнике'). Парные эпитеты ('dull, gray') переводи богатыми русскими синонимами ('пасмурный, серый'), не повторяя одно и то же слово.\n"
+        "2. БЕЗ ГАЛЛЮЦИНАЦИЙ И ТОЧНОСТЬ ЗНАЧЕНИЙ: Фауна, флора и объекты должны переводиться строго точно по смыслу и словарю (например: 'owl' — это сова/неясыть, ни в коем случае НЕ орёл!). Никаких смысловых подмен.\n"
-        "3. ИМЕНА И ТИТУЛЫ: Имена персонажей и фамилии передавай полностью на русском языке (кириллицей), без латинских букв (Mr. and Mrs. Dursley -> мистер и миссис Дурсли). Сохраняй титулы: Mr. -> мистер, Mrs. -> миссис, Dr. -> доктор, Prof. -> профессор.\n"
+        "3. БЕЗ ДОСЛОВНОГО КАЛЬКИРОВАНИЯ: Никаких топорных калек предлогов ('on Tuesday' -> 'во вторник', а не 'на вторнике'). Парные эпитеты ('dull, gray') переводи богатыми русскими синонимами ('пасмурный, серый'), не повторяя одно и то же слово.\n"
-        "4. РУССКИЙ СИНТАКСИС: Сохраняй естественный русский порядок слов (обстоятельства времени и места ставь перед сказуемым: 'вскоре по всей стране начнут происходить...').\n"
+        "4. ИМЕНА И ТИТУЛЫ: Имена персонажей и фамилии передавай полностью на русском языке (кириллицей), без латинских букв (Mr. and Mrs. Dursley -> мистер и миссис Дурсли). Сохраняй титулы: Mr. -> мистер, Mrs. -> миссис, Dr. -> доктор, Prof. -> профессор.\n"
-        f'5. В поле "word_meaning" укажи только точный перевод слова "{clean_word}" на русский язык в контексте этого предложения (выбрав лучший вариант из подсказок).\n\n'
+        "5. РУССКИЙ СИНТАКСИС: Сохраняй естественный русский порядок слов (обстоятельства времени и места ставь перед сказуемым: 'вскоре по всей стране начнут происходить...').\n"
+        f'6. В поле "word_meaning" укажи только точный перевод слова "{clean_word}" на русский язык в контексте этого предложения (выбрав лучший вариант из подсказок).\n\n'
         "Ответь ИСКЛЮЧИТЕЛЬНО в формате JSON:\n"
         "{\n"
         '  "sentence_ru": "полный качественный литературный перевод всего предложения без пропусков",\n'
@@ -113,8 +212,9 @@ async def translate_sentence_ai(
             "cached": True,
         }
 
-    # 2. Retrieve offline dictionary hint to steer LLM towards authentic meanings
+    # 2. Retrieve offline dictionary hints to steer LLM towards authentic meanings
     dict_hint = get_dictionary_hint(clean_word) if clean_word else ""
+    sentence_hints = get_sentence_dictionary_hints(clean_sentence, clean_word)
 
     # 3. Local AI Generation (Ollama)
     prompt = build_translation_prompt(
@@ -122,6 +222,7 @@ async def translate_sentence_ai(
         target_word=clean_word,
         context=clean_context,
         dict_hint=dict_hint,
+        sentence_hints=sentence_hints,
     )
 
     payload = {

app/phrasal.py

@@ -46,7 +46,14 @@ IRREGULARS = {
 
 PRONOUNS_AND_OBJECTS = {
     "it", "him", "her", "them", "us", "me", "you", "this", "that", "these", "those",
-    "things", "something", "everything", "anything", "all", "back", "away"
+    "things", "something", "everything", "anything", "all"
+}
+
+PHRASAL_PARTICLES = {
+    "about", "across", "ahead", "along", "apart", "around", "round", "aside",
+    "at", "away", "back", "by", "down", "for", "forth", "forward", "in",
+    "into", "off", "on", "onto", "out", "over", "past", "round", "through",
+    "to", "together", "under", "up", "upon", "with"
 }
 
 # Curated high-frequency English phrasal verbs (CEFR A2-B2) with clean translations
@@ -326,20 +333,26 @@ def detect_phrasal_verb(
                         }
                         break
 
-                    # Check offline dictionary
+                    # Check offline dictionary only for genuine phrasal verbs:
-                    row = execute_query(
+                    # 1. Candidate must end with a known particle (e.g. 'turn on', 'come up with')
-                        "SELECT term, translation FROM offline_dictionary WHERE term = ? COLLATE NOCASE",
+                    # 2. pos in offline_dictionary must explicitly be a verb / verb phrase
-                        (cand,),
+                    cand_words = cand.split()
-                    )
+                    if len(cand_words) >= 2 and cand_words[-1] in PHRASAL_PARTICLES:
-                    if row:
+                        row = execute_query(
-                        match_result = {
+                            "SELECT term, translation, pos FROM offline_dictionary WHERE term = ? COLLATE NOCASE",
-                            "term": row[0],
+                            (cand,),
-                            "raw": raw_match,
+                        )
-                            "translation": row[1],
+                        if row:
-                            "separable": False,
+                            pos_val = (row[2] or "").lower()
-                            "matched_words": tokens[start : start + span_len],
+                            if "verb" in pos_val:
-                        }
+                                match_result = {
-                        break
+                                    "term": row[0],
+                                    "raw": raw_match,
+                                    "translation": row[1],
+                                    "separable": False,
+                                    "matched_words": tokens[start : start + span_len],
+                                }
+                                break
                 if match_result:
                     break
             if match_result:
@@ -352,8 +365,10 @@ def detect_phrasal_verb(
             if lower_tokens[v_idx + 1] in PRONOUNS_AND_OBJECTS:
                 p_idx = v_idx + 2
                 if idx in (v_idx, p_idx):
-                    v_lemmas = lemmatize_word(lower_tokens[v_idx])
                     particle = lower_tokens[p_idx]
+                    if particle not in PHRASAL_PARTICLES:
+                        continue
+                    v_lemmas = lemmatize_word(lower_tokens[v_idx])
                     raw_match = " ".join(tokens[v_idx : p_idx + 1])
                     for v in v_lemmas:
                         cand = f"{v} {particle}"
@@ -367,18 +382,20 @@ def detect_phrasal_verb(
                             }
                             break
                         row = execute_query(
-                            "SELECT term, translation FROM offline_dictionary WHERE term = ? COLLATE NOCASE",
+                            "SELECT term, translation, pos FROM offline_dictionary WHERE term = ? COLLATE NOCASE",
                             (cand,),
                         )
                         if row:
-                            match_result = {
+                            pos_val = (row[2] or "").lower()
-                                "term": row[0],
+                            if "verb" in pos_val:
-                                "raw": raw_match,
+                                match_result = {
-                                "translation": row[1],
+                                    "term": row[0],
-                                "separable": True,
+                                    "raw": raw_match,
-                                "matched_words": [tokens[v_idx], tokens[p_idx]],
+                                    "translation": row[1],
-                            }
+                                    "separable": True,
-                            break
+                                    "matched_words": [tokens[v_idx], tokens[p_idx]],
+                                }
+                                break
                     if match_result:
                         break
         if match_result:

app/static/sw.js

@@ -1,7 +1,7 @@
 // Service Worker for Notes English PWA (Stage 2)
 // Strategy: Cache-first for static assets, Network-first for API calls.
 
-const CACHE_NAME = 'notes-v6.0';
+const CACHE_NAME = 'notes-v6.1';
 const OFFLINE_URL = '/';
 
 const PRECACHE_URLS = [

tests/test_api.py

@@ -1955,6 +1955,79 @@ def test_robust_sentence_split_and_ai_translation(monkeypatch):
     assert tr_data["target_word"] == "briefcase"
 
 
+def test_phrasal_verb_detection_no_false_positive_for_noun_phrase():
+    from app.phrasal import detect_phrasal_verb
+
+    # Seed temporary test dictionary with tawny owl
+    with get_db() as conn:
+        conn.execute(
+            "INSERT OR IGNORE INTO offline_dictionary (term, translation, phonetic, pos) VALUES (?, ?, '', ?)",
+            ("tawny owl", "неясыть, неясыть серая", "Noun"),
+        )
+        conn.execute(
+            "INSERT OR IGNORE INTO offline_dictionary (term, translation, phonetic, pos) VALUES (?, ?, '', ?)",
+            ("owl", "сыч, сова, филин", "Noun"),
+        )
+        conn.execute(
+            "INSERT OR IGNORE INTO offline_dictionary (term, translation, phonetic, pos) VALUES (?, ?, '', ?)",
+            ("tawny", "рыжевато-коричневый", "Adjective"),
+        )
+
+    sentence = "None of them noticed a large, tawny owl flutter past the window."
+    # tawny owl is a noun phrase (an animal species), NOT a phrasal verb!
+    assert detect_phrasal_verb(sentence, "owl") is None
+    assert detect_phrasal_verb(sentence, "tawny") is None
+    assert detect_phrasal_verb(sentence, "large") is None
+
+    # Genuine phrasal verbs must still be detected
+    s2 = "None of them noticed him take off his coat."
+    pv2 = detect_phrasal_verb(s2, "take")
+    assert pv2 is not None
+    assert pv2["term"] == "take off"
+
+    s3 = "He turned it off quietly."
+    pv3 = detect_phrasal_verb(s3, "turned")
+    assert pv3 is not None
+    assert pv3["term"] == "turn off"
+
+
+def test_sentence_dictionary_hints_and_fauna_precision():
+    from app.ai import get_sentence_dictionary_hints, build_translation_prompt
+
+    with get_db() as conn:
+        conn.execute(
+            "INSERT OR IGNORE INTO offline_dictionary (term, translation, phonetic, pos) VALUES (?, ?, '', ?)",
+            ("tawny owl", "неясыть, неясыть серая", "Noun"),
+        )
+        conn.execute(
+            "INSERT OR IGNORE INTO offline_dictionary (term, translation, phonetic, pos) VALUES (?, ?, '', ?)",
+            ("owl", "сыч, сова, филин", "Noun"),
+        )
+        conn.execute(
+            "INSERT OR IGNORE INTO offline_dictionary (term, translation, phonetic, pos) VALUES (?, ?, '', ?)",
+            ("large", "большой, крупный", "Adjective"),
+        )
+
+    sentence = "None of them noticed a large, tawny owl flutter past the window."
+    hints = get_sentence_dictionary_hints(sentence, "tawny")
+    assert "owl" in hints
+    assert "НЕ орёл" in hints
+    assert "large" in hints
+
+    prompt = build_translation_prompt(
+        sentence=sentence,
+        target_word="tawny",
+        context="",
+        dict_hint="рыжевато-коричневый",
+        sentence_hints=hints,
+    )
+    assert "Словарные подсказки по ключевым словам предложения" in prompt
+    assert "НЕ орёл" in prompt
+    assert "ПОЛНОТА И СВЯЗНОСТЬ" in prompt
+    assert "large" in prompt
+
+
+