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carlosdimare
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Create app.py
Browse files
app.py
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from flask import Flask, render_template, request
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from transformers import AutoTokenizer
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from transformers.adapters import AutoAdapterModel
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app = Flask(__name__)
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# Cargar el modelo y tokenizer
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model_name = "carlosdimare/clascon" # Nombre del modelo en Hugging Face
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoAdapterModel.from_pretrained(model_name)
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# Cargar el adapter preentrenado
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model.load_adapter(model_name, set_active=True)
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# Funci贸n para generar la respuesta
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def generar_respuesta(prompt):
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inputs = tokenizer(prompt, return_tensors="pt")
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outputs = model.generate(inputs["input_ids"], max_length=100, num_beams=5, no_repeat_ngram_size=2, early_stopping=True)
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return tokenizer.decode(outputs[0], skip_special_tokens=True)
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# Ruta principal para el formulario de chat
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@app.route("/", methods=["GET", "POST"])
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def index():
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response = None
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if request.method == "POST":
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prompt = request.form["prompt"]
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response = generar_respuesta(prompt)
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return render_template("index.html", response=response)
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# Ruta para manejar el chat
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@app.route("/chat", methods=["POST"])
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def chat():
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prompt = request.form["prompt"]
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response = generar_respuesta(prompt)
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return render_template("index.html", response=response)
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if __name__ == "__main__":
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app.run(debug=True)
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