Back to normal app.py v1.5

app.py

@@ -1,44 +1,57 @@
 # app.py
 import gradio as gr
+import asyncio
+from itertools import cycle
 from core.utils import generate_first_question
 from core.mbti_analyzer import analyze_mbti
 from core.interviewer import generate_question, session_state
 
-def analyze_and_ask(user_text, prev_count):
+async def async_loader(progress_fn):
+    """Асинхронный loader-аниматор (вращающиеся точки)."""
+    frames = cycle(["⠋", "⠙", "⠹", "⠸", "⠼", "⠴", "⠦", "⠧", "⠇", "⠏"])
+    for _ in range(10):
+        await asyncio.sleep(0.2)
+        progress_fn(next(frames))
+
+def analyze_and_ask(user_text, prev_count, progress=gr.Progress(track_tqdm=True)):
     if not user_text.strip():
         yield "⚠️ Please enter your answer.", "", prev_count
         return
 
     user_id = "default_user"
-
     try:
         n = int(prev_count.split("/")[0]) + 1
     except Exception:
         n = 1
     counter = f"{n}/8"
 
-    # 1️⃣ Сразу показываем “Thinking...”
-    yield "⏳ Analyzing personality...", "💭 Interviewer is thinking...", counter
+    # 1️⃣ Первое сообщение — мгновенно
+    yield "⏳ Analyzing personality...", "💭 Interviewer is thinking... ⠋", counter
+
+    # 2️⃣ Анимация лоадера в фоне
+    loop = asyncio.new_event_loop()
+    asyncio.set_event_loop(loop)
+    loop.create_task(async_loader(lambda f: None))
 
-    # 2️⃣ Анализ MBTI
+    # 3️⃣ Анализ MBTI
     mbti_gen = analyze_mbti(user_text)
     mbti_text = ""
     for chunk in mbti_gen:
         mbti_text = chunk
-        yield mbti_text, "💭 Interviewer is thinking...", counter
+        yield mbti_text, "💭 Interviewer is thinking... ⠙", counter
 
-    # 3️⃣ Генерация вопроса
+    # 4️⃣ Генерация вопроса
     question = generate_question(user_id)
 
     if question.startswith("✅ All"):
         yield f"{mbti_text}\n\nSession complete.", "🎯 All MBTI axes covered.", "8/8"
         return
 
-    # 4️⃣ Финальный вывод
+    # 5️⃣ Финальный вывод
     yield mbti_text, question, counter
 
 # --------------------------------------------------------------
-# Интерфейс Gradio
+# UI
 # --------------------------------------------------------------
 with gr.Blocks(theme=gr.themes.Soft(), title="MBTI Personality Interviewer") as demo:
     gr.Markdown(

core/interviewer.py

@@ -1,5 +1,6 @@
 # core/interviewer.py
 import random
+import itertools
 from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
 
 INTERVIEWER_MODEL = "f3nsmart/TinyLlama-MBTI-Interviewer-LoRA"
@@ -13,7 +14,7 @@ llm_pipe = pipeline(
     "text-generation",
     model=model,
     tokenizer=tokenizer,
-    max_new_tokens=60,
+    max_new_tokens=70,
     temperature=0.6,
     top_p=0.9,
 )
@@ -40,14 +41,34 @@ def select_next_category(user_id: str):
     return next_cat
 
 def build_prompt(category: str):
+    # ✅ Новый, более "демонстративный" промпт:
     return (
-        f"Ask one open-ended question about {category}. "
-        f"Do not repeat or rephrase previous questions. "
-        f"Output only the question itself."
+        f"You are a friendly MBTI interviewer.\n"
+        f"Ask one short, open-ended question that explores {category.lower()}.\n"
+        f"Examples: 'What makes you feel most energized in social situations?'\n"
+        f"Output only the question, without quotes, without explanations."
     )
 
+def clean_question(text: str) -> str:
+    """Удаляет инструкции и оставляет только вопрос."""
+    text = text.strip()
+
+    # убираем строки с 'ask', 'instruction' и т.п.
+    bad_phrases = ["ask", "instruction", "output only", "question about", "you are"]
+    for phrase in bad_phrases:
+        if phrase.lower() in text.lower():
+            # берём только часть после последнего примера знака '?'
+            if '?' in text:
+                text = text.split('?')[-1]
+            else:
+                text = text.replace(phrase, '')
+    text = text.strip().strip('"').strip("'")
+    if not text.endswith("?"):
+        text += "?"
+    return text
+
 def generate_question(user_id: str) -> str:
-    """Возвращает только финальный вопрос."""
+    """Генерация нового вопроса по категории."""
     if user_id not in session_state:
         init_session(user_id)
 
@@ -57,7 +78,5 @@ def generate_question(user_id: str) -> str:
 
     prompt = build_prompt(category)
     raw = llm_pipe(prompt)[0]["generated_text"]
-    question = raw.strip().split("\n")[0]
-    if "?" not in question:
-        question += "?"
+    question = clean_question(raw)
     return f"({category}) {question}"