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import os |
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import anthropic |
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import streamlit as st |
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class ClaudeAPIChat: |
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def __init__(self): |
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api_key = os.environ.get("ANTHROPIC_API_KEY") |
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if not api_key: |
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raise ValueError("No se encontr贸 la clave API de Anthropic. Aseg煤rate de configurarla en las variables de entorno.") |
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self.client = anthropic.Anthropic(api_key=api_key) |
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self.conversation_history = [] |
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def generate_response(self, prompt, lang_code): |
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self.conversation_history.append(f"Human: {prompt}") |
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full_message = "\n".join(self.conversation_history) |
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try: |
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response = self.client.completions.create( |
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model="claude-2", |
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prompt=f"{full_message}\n\nAssistant:", |
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max_tokens_to_sample=300, |
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temperature=0.7, |
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stop_sequences=["Human:"] |
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) |
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claude_response = response.completion.strip() |
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self.conversation_history.append(f"Assistant: {claude_response}") |
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if len(self.conversation_history) > 10: |
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self.conversation_history = self.conversation_history[-10:] |
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return claude_response |
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except anthropic.APIError as e: |
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st.error(f"Error al llamar a la API de Claude: {str(e)}") |
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return "Lo siento, hubo un error al procesar tu solicitud." |
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def initialize_chatbot(): |
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return ClaudeAPIChat() |
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def get_chatbot_response(chatbot, prompt, lang_code): |
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if 'api_calls' not in st.session_state: |
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st.session_state.api_calls = 0 |
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if st.session_state.api_calls >= 50: |
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return "Lo siento, has alcanzado el l铆mite de consultas para esta sesi贸n." |
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st.session_state.api_calls += 1 |
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return chatbot.generate_response(prompt, lang_code) |