Update app.py

app.py

@@ -1,45 +1,63 @@
+import os
 import gradio as gr
 import requests
-import os
 
-# Получаем переменные окружения
+# Загружаем токен и имя модели из secrets
 API_TOKEN = os.getenv("HF_API_TOKEN")
 MODEL_NAME = os.getenv("MODEL_NAME", "google/flan-t5-small")
 API_URL = f"https://api-inference.huggingface.co/models/{MODEL_NAME}"
-
 headers = {"Authorization": f"Bearer {API_TOKEN}"}
 
+
 def query_huggingface(prompt):
+    if not API_TOKEN:
+        return "❌ Токен HF_API_TOKEN не задан! Добавь его в Secrets."
+    
     payload = {"inputs": prompt}
-    response = requests.post(API_URL, headers=headers, json=payload)
+
+    try:
+        response = requests.post(API_URL, headers=headers, json=payload)
+    except Exception as e:
+        return f"🚫 Ошибка подключения: {str(e)}"
+
+    if response.status_code != 200:
+        return f"❌ Ошибка API: {response.status_code}\n{response.text}"
 
     try:
         result = response.json()
-        if isinstance(result, list) and "generated_text" in result[0]:
-            return result[0]["generated_text"]
-        elif isinstance(result, dict) and "generated_text" in result:
-            return result["generated_text"]
-        else:
-            return f"⚠️ Ответ не распознан: {result}"
     except Exception as e:
-        return f"❌ Ошибка: {str(e)}"
+        return f"❌ Ошибка парсинга ответа: {str(e)}\nОтвет: {response.text}"
+
+    # Разбор разных форматов
+    if isinstance(result, list) and "generated_text" in result[0]:
+        return result[0]["generated_text"]
+    elif isinstance(result, dict) and "generated_text" in result:
+        return result["generated_text"]
+    elif isinstance(result, dict) and "error" in result:
+        return f"⚠️ Ошибка модели: {result['error']}"
+    else:
+        return f"⚠️ Неожиданный формат ответа: {result}"
+
 
 def chat(user_input, history):
     history = history or []
     prompt = f"Q: {user_input}\nA:"
-    output = query_huggingface(prompt)
-    history.append((user_input, output))
+    response = query_huggingface(prompt)
+    history.append((user_input, response))
     return history, history
 
+
+# UI через Gradio Blocks
 with gr.Blocks() as demo:
-    gr.Markdown("## 🤖 Чат с моделью Hugging Face")
-    chatbot = gr.Chatbot()
-    msg = gr.Textbox(placeholder="Введите сообщение и нажмите Enter...")
-    clear = gr.Button("Очистить")
+    gr.Markdown("## 🤖 FlareGPT — чат с моделью Hugging Face")
+
+    chatbot = gr.Chatbot(height=400)
+    message = gr.Textbox(placeholder="Введите сообщение и нажмите Enter...")
+    clear = gr.Button("🧹 Очистить")
 
     state = gr.State([])
 
-    msg.submit(chat, [msg, state], [chatbot, state])
+    message.submit(chat, [message, state], [chatbot, state])
     clear.click(lambda: ([], []), None, [chatbot, state])
 
 demo.launch()