Update app.py
Browse files
app.py
CHANGED
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import gradio as gr
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from
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from ddgs import DDGS
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import re
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class
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def __init__(self):
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print("
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# Используем
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self.model =
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"text-generation",
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model="microsoft/DialoGPT-medium", # Более качественная чем small
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max_length=300,
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temperature=0.3, # Меньше креативности, больше фактов
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do_sample=True
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)
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#
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self.
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print("Improved AI Agent ready!")
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def search_web(self, query):
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"""Поиск в интернете через DuckDuckGo"""
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try:
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results = list(self.ddgs.text(query, max_results=3))
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if results:
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# Собираем информацию из нескольких результатов
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combined_info = []
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for result in results[:2]: # Берем первые 2 результата
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text = result.get('body', '')
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if text and len(text) > 10: # Фильтруем слишком короткие
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combined_info.append(text[:200]) # Ограничиваем длину
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if combined_info:
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return " | ".join(combined_info)
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return None
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except Exception as e:
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print(f"Search error: {e}")
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return None
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def is_factual_question(self, question):
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"""Определяем, является ли вопрос фактологическим"""
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question_lower = question.lower()
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def chat(self, message, history):
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try:
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#
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search_result = self.search_web(message)
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if search_result:
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# Промпт с найденной информацией
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prompt = f"""Based on this information: {search_result}
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Question: {message}
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Provide a concise and accurate answer:"""
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else:
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# Если поиск не сработал, используем общий промпт
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prompt = f"""Answer this question accurately: {message}
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If you don't know the exact answer, say so."""
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else:
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# Для не-фактологических вопросов используем обычный чат
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prompt = f"User: {message}\nAssistant:"
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# Генерируем ответ
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response = self.model(
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prompt,
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max_length=400,
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num_return_sequences=1,
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temperature=0.3, # Низкая температура для фактов
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do_sample=True,
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pad_token_id=50256,
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repetition_penalty=1.3
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)
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# Извлекаем ответ
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full_text = response[0]['generated_text']
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answer = full_text.split("Assistant:")[-1].strip()
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else:
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answer = full_text.replace(prompt, "").strip()
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clean_answer = self.clean_response(answer)
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# Если ответ явно неправильный, даем запасной ответ
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if self.is_wrong_answer(clean_answer, message):
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clean_answer = "I'm not sure about that. Let me search for more information."
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search_fallback = self.search_web(message)
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if search_fallback:
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clean_answer = f"Based on what I found: {search_fallback[:300]}..."
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print(f"Assistant: {clean_answer[:100]}...")
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return clean_answer
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except Exception as e:
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print(f"Error: {e}")
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return
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def
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"""
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if 'capital' in question_lower:
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# Проверяем, содержит ли ответ название города
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if not any(indicator in answer_lower for indicator in ['city', 'capital', 'is']):
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return True
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# Если ответ содержит "ambassador" или подобное для вопроса о столице - это ошибка
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if 'ambassador' in answer_lower:
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return True
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return False
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def clean_response(self, text):
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"""Очистка ответа"""
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# Убираем технические части
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text = re.sub(r'Based on this information:.*?Provide a concise answer:', '', text, flags=re.DOTALL)
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text = re.sub(r'Question:.*?Answer:', '', text, flags=re.DOTALL)
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# Берем первую релевантную часть
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sentences = text.split('.')
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clean_sentences = []
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for sentence in sentences:
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sentence = sentence.strip()
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if sentence and len(sentence) > 5:
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clean_sentences.append(sentence)
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if len(clean_sentences) >= 2: # Ограничиваем 2 предложениями
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break
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# Создаем агента
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# Создаем интерфейс
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with gr.Blocks() as
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gr.Markdown("#
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gr.Markdown("I can
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chatbot = gr.Chatbot(
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height=400,
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show_copy_button=True
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)
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msg = gr.Textbox(
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label="Your question",
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placeholder="Ask me
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lines=2
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)
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clear = gr.Button("Clear Chat")
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def respond(message, chat_history):
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return "", chat_history
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msg.submit(respond, [msg, chatbot], [msg, chatbot])
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if __name__ == "__main__":
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print("Starting
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import gradio as gr
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from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel
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class SimpleAIAgent:
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def __init__(self):
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print("Initializing AI Agent...")
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# Используем языковую модель от Hugging Face
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self.model = HfApiModel("Qwen/Qwen2.5-Coder-32B-Instruct")
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# Инструмент для поиска в интернете
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self.search_tool = DuckDuckGoSearchTool()
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# Создаем агента который может искать в интернете
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self.agent = CodeAgent(
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tools=[self.search_tool],
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model=self.model,
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max_steps=4
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)
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print("AI Agent ready!")
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def chat(self, message, history):
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"""
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Основная функция для общения с агентом
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"""
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print(f"User asked: {message}")
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# Создаем инструкцию для агента
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prompt = f"""
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The user asked: {message}
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Please provide a helpful and accurate answer.
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If you need current information, use the search tool to find it online.
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Keep your response clear and conversational.
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"""
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try:
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# Получаем ответ от агента
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response = self.agent.run(prompt)
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# Очищаем ответ от технических деталей
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clean_response = self.clean_answer(response)
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print(f"Agent replied: {clean_response[:100]}...")
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return clean_response
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except Exception as e:
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error_msg = f"Sorry, I encountered an error: {str(e)}"
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print(f"Error: {e}")
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return error_msg
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def clean_answer(self, answer):
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"""
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Убираем техническую информацию из ответа агента
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"""
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lines = answer.split('\n')
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clean_lines = []
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for line in lines:
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# Пропускаем строки про инструменты и процесс поиска
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lower_line = line.lower()
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if any(word in lower_line for word in ['tool:', 'searching', 'step', 'using tool']):
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continue
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# Пропускаем пустые строки в начале
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if line.strip():
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clean_lines.append(line)
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# Собираем обратно в текст
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result = '\n'.join(clean_lines).strip()
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# Если ответ слишком длинный, обрезаем
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if len(result) > 1500:
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result = result[:1497] + "..."
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return result if result else "I couldn't find a good answer to that question."
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# Создаем экземпляр агента
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ai_agent = SimpleAIAgent()
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# Создаем интерфейс чата
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with gr.Blocks(title="My AI Assistant") as chat_interface:
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gr.Markdown("# My AI Assistant")
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gr.Markdown("Ask me anything! I can search the internet for current information.")
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# Создаем чат-интерфейс
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chatbot = gr.Chatbot(height=400)
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msg = gr.Textbox(
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label="Your question",
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placeholder="Ask me anything...",
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lines=2
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clear_btn = gr.Button("Clear Chat")
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def respond(message, chat_history):
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# Получаем ответ от агента
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bot_response = ai_agent.chat(message, chat_history)
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# Добавляем в историю чата
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chat_history.append((message, bot_response))
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return "", chat_history
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# Обработчики событий
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msg.submit(respond, [msg, chatbot], [msg, chatbot])
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clear_btn.click(lambda: None, None, chatbot, queue=False)
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# Запускаем приложение
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if __name__ == "__main__":
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print("Starting AI Chat Assistant...")
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chat_interface.launch(share=True)
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