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| # modules/chatbot/chatbot/chat_process.py | |
| import anthropic | |
| import logging | |
| from typing import Dict, Generator | |
| logger = logging.getLogger(__name__) | |
| class ChatProcessor: | |
| def __init__(self): | |
| self.client = anthropic.Anthropic(api_key=os.environ["ANTHROPIC_API_KEY"]) | |
| self.conversation_history = [] | |
| def process_chat_input(self, message: str, lang_code: str) -> Generator[str, None, None]: | |
| """ | |
| Procesa el input del chat y genera respuestas por chunks | |
| """ | |
| try: | |
| # Agregar mensaje a la historia | |
| self.conversation_history.append(f"Human: {message}") | |
| # Generar respuesta | |
| response = self.client.completions.create( | |
| model="claude-3-opus-20240229", | |
| prompt=f"{message}\n\nAssistant:", | |
| max_tokens_to_sample=300, | |
| temperature=0.7, | |
| stream=True # Habilitar streaming | |
| ) | |
| # Retornar chunks de la respuesta | |
| full_response = "" | |
| for chunk in response: | |
| if chunk.completion: | |
| yield chunk.completion | |
| full_response += chunk.completion | |
| # Guardar respuesta completa en la historia | |
| self.conversation_history.append(f"Assistant: {full_response}") | |
| except Exception as e: | |
| logger.error(f"Error en process_chat_input: {str(e)}") | |
| yield f"Error: {str(e)}" |