Add Word Count stats block above tabs (General Stats)

app.py

@@ -27,12 +27,25 @@ async def read_root(request: Request):
 
 @app.post("/analyze", response_model=AnalysisResponse)
 async def analyze_text(request: AnalysisRequest):
+    # 1. Считаем слова (Word Count)
+    wc_target = logic.count_words(request.target_text, request.language)
+    wc_competitors = [logic.count_words(t, request.language) for t in request.competitors]
+    wc_avg = sum(wc_competitors) / len(wc_competitors) if wc_competitors else 0
+    
+    word_counts_data = {
+        "target": wc_target,
+        "competitors": wc_competitors,
+        "avg": round(wc_avg)
+    }
+
+    # 2. N-gram stats
     ngram_stats_result = logic.calculate_ngram_stats(
         request.target_text, 
         request.competitors, 
         request.language
     )
     
+    # 3. BM25
     key_phrases, key_words_unigrams = logic.parse_keywords(request.keywords, request.language)
     
     bm25_recs = logic.calculate_bm25_recommendations(
@@ -42,6 +55,7 @@ async def analyze_text(request: AnalysisRequest):
         request.language
     )
     
+    # 4. BERT
     bert_results = logic.perform_bert_analysis(
         request.target_text,
         request.competitors,
@@ -52,7 +66,8 @@ async def analyze_text(request: AnalysisRequest):
     return AnalysisResponse(
         ngram_stats=ngram_stats_result,
         bm25_recommendations=bm25_recs,
-        bert_analysis=bert_results
+        bert_analysis=bert_results,
+        word_counts=word_counts_data
     )
 
 # Hugging Face Spaces использует порт 7860

logic.py

@@ -172,6 +172,23 @@ def generate_ngrams_safe(text: str, lang: str, n: int) -> List[str]:
             
     return all_ngrams
 
+# --- WORD COUNT ---
+
+def count_words(text: str, lang: str) -> int:
+    """
+    Считает количество слов (токенов), исключая пунктуацию и пробелы.
+    """
+    if not text.strip():
+        return 0
+    
+    doc = get_doc(text, lang)
+    
+    count = 0
+    for t in doc:
+        if not t.is_punct and not t.is_space and not t.pos_ == "SYM":
+            count += 1
+    return count
+
 # --- ANALYTICS (N-grams & BM25) ---
 
 def calculate_ngram_stats(target_text: str, competitor_texts: List[str], lang: str) -> Dict:

models.py

@@ -1,5 +1,4 @@
 from pydantic import BaseModel
-from typing import List, Optional
 from typing import List, Dict, Optional, Any
 
 
@@ -16,4 +15,5 @@ class AnalysisRequest(BaseModel):
 class AnalysisResponse(BaseModel):
     ngram_stats: dict               # Статистика униграм/биграм
     bm25_recommendations: List[dict] # Рекомендации "добавить/убрать"
-    bert_analysis: Dict[str, Any]   # Векторный анализ
+    bert_analysis: Dict[str, Any]   # Векторный анализ
+    word_counts: Dict[str, Any]     # {'target': 500, 'competitors': [600, 450], 'avg': 525}

templates/index.html

@@ -76,6 +76,11 @@
 
         <!-- ПРАВАЯ КОЛОНКА: РЕЗУЛЬТАТЫ -->
         <div class="col-md-7">
+
+            <!-- Блок общей статистики (Word Count) -->
+            <div id="generalStats" class="mb-4">
+                <!-- Сюда JS вставит карточки -->
+            </div>
             
             <!-- Табы -->
             <ul class="nav nav-tabs mb-3" id="resultsTab" role="tablist">
@@ -217,6 +222,47 @@
     }
 
     function renderResults(data) {
+        // 0. General Stats Render (Word Count)
+        const statsContainer = document.getElementById('generalStats');
+        statsContainer.innerHTML = '';
+        
+        if (data.word_counts) {
+            const myWords = data.word_counts.target;
+            const avgWords = data.word_counts.avg;
+            
+            let compsHtml = '';
+            data.word_counts.competitors.forEach((count, idx) => {
+                compsHtml += `<div class="px-2 border-end"><small class="text-muted d-block">K${idx+1}</small><strong>${count}</strong></div>`;
+            });
+
+            const html = `
+            <div class="card border-0 shadow-sm">
+                <div class="card-body py-2 d-flex align-items-center justify-content-between">
+                    
+                    <!-- Мой результат -->
+                    <div class="d-flex align-items-center">
+                        <div class="me-3">
+                            <small class="text-muted d-block">Мой текст</small>
+                            <span class="h4 mb-0 fw-bold ${myWords < avgWords ? 'text-danger' : 'text-success'}">${myWords}</span> <small class="text-muted">слов</small>
+                        </div>
+                    </div>
+
+                    <!-- Сравнение -->
+                    <div class="d-flex text-center">
+                        <div class="px-3">
+                            <small class="text-muted d-block">Среднее (Конкуренты)</small>
+                            <span class="h5 mb-0 fw-bold">${avgWords}</span>
+                        </div>
+                        <div class="d-flex align-items-center border-start ps-2">
+                             ${compsHtml}
+                        </div>
+                    </div>
+
+                </div>
+            </div>`;
+            statsContainer.innerHTML = html;
+        }
+
         // 1. BERT Render (ИСПРАВЛЕННЫЙ ПОД НОВУЮ СТРУКТУРУ)
         const bertContainer = document.getElementById('bertResultsContainer');
         bertContainer.innerHTML = '';