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Parent(s):
4e33a18
Create gen.py
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gen.py
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1 |
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import torch
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from transformers import pipeline
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import sys
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import sys
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# Cargar el pipeline de generación de texto
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pipe = pipeline("text-generation", model="HuggingFaceH4/zephyr-7b-beta", torch_dtype=torch.bfloat16, device_map="auto")
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# Definir el prompt para generar un JSON con eventos anidados
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prompt = (
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"Genera un JSON que describa una serie de eventos consecutivos en un formato similar al siguiente:\n\n"
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"{\n"
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" \"events\": {\n"
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" \"event\": {\n"
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" \"event_number\": 1,\n"
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" \"name\": \"conflict_start\",\n"
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" \"description\": \"Tensions escalate between Iran and Israel\",\n"
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" \"probability\": 70,\n"
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" \"duration_days\": 30,\n"
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" \"subevents\": {\n"
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" \"event\": {\n"
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" \"event_number\": 2,\n"
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" \"name\": \"diplomatic_failure\",\n"
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" \"description\": \"Diplomatic negotiations fail\",\n"
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" \"probability\": 60,\n"
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" \"duration_days\": 15,\n"
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" \"subevents\": {\n"
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" \"event\": {\n"
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" \"event_number\": 3,\n"
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" \"name\": \"military_clash\",\n"
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" \"description\": \"Initial military clash at the border\",\n"
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" \"probability\": 50,\n"
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" \"duration_days\": 10,\n"
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" \"subevents\": {\n"
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" \"event\": [\n"
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" {\n"
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" \"event_number\": 4,\n"
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" \"name\": \"escalation\",\n"
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" \"description\": \"Conflict escalates into full-scale war\",\n"
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" \"probability\": 40,\n"
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" \"duration_days\": 180,\n"
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" \"subevents\": {\n"
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" \"event\": [\n"
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" {\n"
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" \"event_number\": 5,\n"
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" \"name\": \"regional_involvement\",\n"
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" \"description\": \"Other Middle Eastern countries get involved\",\n"
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" \"probability\": 30,\n"
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" \"duration_days\": 365,\n"
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" \"subevents\": {\n"
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" \"event\": [\n"
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" {\n"
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" \"event_number\": 6,\n"
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" \"name\": \"ceasefire\",\n"
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" \"description\": \"International powers broker a ceasefire\",\n"
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" \"probability\": 20,\n"
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" \"duration_days\": 30\n"
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" },\n"
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" {\n"
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" \"event_number\": 7,\n"
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" \"name\": \"prolonged_conflict\",\n"
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" \"description\": \"Conflict continues for over a year\",\n"
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" \"probability\": 50,\n"
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" \"duration_days\": 365\n"
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" }\n"
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" ]\n"
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" }\n"
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" },\n"
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" {\n"
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" \"event_number\": 8,\n"
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" \"name\": \"international_intervention\",\n"
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" \"description\": \"UN or other international organizations intervene\",\n"
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" \"probability\": 25,\n"
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" \"duration_days\": 60\n"
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" }\n"
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" ]\n"
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" }\n"
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" },\n"
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" {\n"
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" \"event_number\": 9,\n"
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" \"name\": \"containment\",\n"
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" \"description\": \"Conflict is contained and doesn't escalate\",\n"
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" \"probability\": 30,\n"
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" \"duration_days\": 90\n"
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" }\n"
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" ]\n"
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" }\n"
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" },\n"
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" \"event\": {\n"
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" \"event_number\": 10,\n"
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" \"name\": \"sanctions\",\n"
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" \"description\": \"Increased sanctions on Iran\",\n"
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" \"probability\": 70,\n"
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" \"duration_days\": 180,\n"
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" \"subevents\": {\n"
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" \"event\": [\n"
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" {\n"
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" \"event_number\": 11,\n"
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" \"name\": \"iran_retaliates\",\n"
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" \"description\": \"Iran retaliates with cyberattacks\",\n"
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" \"probability\": 40,\n"
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" \"duration_days\": 60\n"
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" },\n"
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" {\n"
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" \"event_number\": 12,\n"
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" \"name\": \"israel_response\",\n"
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" \"description\": \"Israel responds with targeted airstrikes\",\n"
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" \"probability\": 50,\n"
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" \"duration_days\": 60\n"
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" }\n"
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" ]\n"
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" }\n"
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" }\n"
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" }\n"
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" },\n"
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" \"event\": {\n"
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" \"event_number\": 13,\n"
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" \"name\": \"diplomatic_success\",\n"
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" \"description\": \"Successful diplomatic negotiations\",\n"
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" \"probability\": 40,\n"
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" \"duration_days\": 30,\n"
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" \"subevents\": {\n"
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" \"event\": [\n"
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" {\n"
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" \"event_number\": 14,\n"
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" \"name\": \"peace_agreement\",\n"
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" \"description\": \"Iran and Israel sign a peace agreement\",\n"
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" \"probability\": 20,\n"
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" \"duration_days\": 60\n"
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" },\n"
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" {\n"
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" \"event_number\": 15,\n"
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" \"name\": \"temporary_truce\",\n"
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" \"description\": \"A temporary truce is established\",\n"
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" \"probability\": 30,\n"
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" \"duration_days\": 30\n"
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" }\n"
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" ]\n"
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" }\n"
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" }\n"
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" }\n"
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" }\n"
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" }\n"
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"}\n\n"
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"Ahora, genera un JSON similar con eventos anidados, pero cambia los detalles y números para hacer que sea con el input que viene a continuacion, respondiendo solo el JSON: "
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)
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def generate():
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# Generar el texto usando el modelo
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outputs = pipe(prompt+" "+sys.argv[1], max_new_tokens=1024, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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# Imprimir la salida generada
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print(outputs[0]["generated_text"])
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return outputs[0]["generated_text"]
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