Update app.py
Browse files
app.py
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@@ -1,5 +1,71 @@
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import gradio as gr
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import json
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import os
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from openai import OpenAI
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@@ -58,4 +124,5 @@ interface = gr.Interface(
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description="Ingrese el texto para analizar y extraer informaci贸n en un formato JSON predefinido."
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)
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interface.launch()
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import gradio as gr
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import openai
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import os
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# Set the OpenAI API key
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openai.api_key = os.getenv("OPENAI_KEY") # Ensure this is set in the environment
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# Define the LLM function
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def generacion_llm(texto_input):
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# Define the system and user messages
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formato_json = '''
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{
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"reto": " ",
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"dudas": " ",
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"preguntas": " ",
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"expectativas": " "
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}
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'''
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mensaje_sistema = (
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"Eres un experto en identificar aspectos descriptivos de las razones "
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"por las cuales un usuario necesita asesor铆a para implementar retos "
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"que involucren inteligencia artificial de varios tipos."
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)
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mensaje_usuario = (
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f"Analizar el texto mostrado al final, buscando identificar los siguientes "
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f"extractos en el formato JSON: {formato_json}\n\nTexto a Analizar: {texto_input}"
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)
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# Call OpenAI API
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try:
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response = openai.ChatCompletion.create(
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model="gpt-3.5-turbo",
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messages=[
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{"role": "system", "content": mensaje_sistema},
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{"role": "user", "content": mensaje_usuario}
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],
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temperature=0.8,
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max_tokens=300,
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top_p=1,
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frequency_penalty=0,
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presence_penalty=0
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)
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# Extract the generated text from the response
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texto_respuesta = response["choices"][0]["message"]["content"]
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# Try parsing as JSON (if applicable)
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return texto_respuesta # Return plain text for now (replace with JSON if needed)
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except Exception as e:
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return f"Error: {e}"
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# Define Gradio app
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interface = gr.Interface(
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fn=generacion_llm,
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inputs=gr.Textbox(label="Ingrese su texto para analizar"),
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outputs=gr.Textbox(label="Resultado JSON"),
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title="Extractor de Texto a JSON",
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description="Ingrese el texto para analizar y extraer informaci贸n en un formato JSON predefinido."
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)
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interface.launch()
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'''
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import gradio as gr
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import json
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import os
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from openai import OpenAI
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description="Ingrese el texto para analizar y extraer informaci贸n en un formato JSON predefinido."
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)
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interface.launch()
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'''
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