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edumunozsala
commited on
Commit
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324a736
1
Parent(s):
e57684f
Update app.py
Browse filesAdded a theme and temperature
app.py
CHANGED
@@ -33,10 +33,10 @@ pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
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# Definimos el eos token para el modelo
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eos_token = tokenizer("<|im_end|>",add_special_tokens=False)["input_ids"][0]
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def generate_inference(instruction, input):
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prompt = pipe.tokenizer.apply_chat_template([{"role": "user",
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"content": f"{instruction}/n{input}"}], tokenize=False, add_generation_prompt=True)
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outputs = pipe(prompt, max_new_tokens=256, do_sample=True, num_beams=1, temperature=
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max_time= 300, eos_token_id=eos_token)
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return outputs[0]['generated_text'][len(prompt):].strip()
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@@ -75,12 +75,15 @@ def clean_output():
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def clean_all():
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return "¿Quién es un solicitante de asilo/ protección internacional?","", "" #inp, cont, out
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with gr.Blocks(theme="
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title="Question Answering - Legal Refugiados v1.0"
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gr.HTML("""
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<h1 align="center">Question Answering - Legal Refugiados v1.0</h1>
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<h2 align="center">Apoyo para
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""")
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inp = gr.Textbox(label="🌐 Pregunta a resolver",
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@@ -88,31 +91,37 @@ with gr.Blocks(theme="ParityError/LimeFace", title="QA Legal Refugiados") as dem
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value="¿Quién es un solicitante de asilo/ protección internacional?",
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interactive=True,
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)
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context=gr.Textbox(label="Contexto",
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info="Introduce el contexto de la pregunta",
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placeholder="Contexto de la pregunta",
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interactive=
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)
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out = gr.Textbox(label="
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interactive=False,
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placeholder="Aquí aparecerá la respuesta o información solicitada",
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)
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inp,
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context,
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fn=get_context,
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run_on_click= True,
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label= "Ejemplos de cuestiones. Se les asignara el contexto automáticamente")
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#demo.queue(max_size=None)
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demo.launch(debug=True, share=False)
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# Definimos el eos token para el modelo
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eos_token = tokenizer("<|im_end|>",add_special_tokens=False)["input_ids"][0]
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def generate_inference(instruction, input, temperature):
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prompt = pipe.tokenizer.apply_chat_template([{"role": "user",
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"content": f"{instruction}/n{input}"}], tokenize=False, add_generation_prompt=True)
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outputs = pipe(prompt, max_new_tokens=256, do_sample=True, num_beams=1, temperature=float(temperature), top_k=50, top_p=0.95,
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max_time= 300, eos_token_id=eos_token)
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return outputs[0]['generated_text'][len(prompt):].strip()
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def clean_all():
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return "¿Quién es un solicitante de asilo/ protección internacional?","", "" #inp, cont, out
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with gr.Blocks(theme="snehilsanyal/scikit-learn", title="QA Legal Refugiados") as demo:
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title="Question Answering - Legal Refugiados v1.0"
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gr.HTML("""
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<p align="center">
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<img src="/file=images/markus-winkler-Je1MDuITTF4-unsplash.jpg" width="300" height="150">
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</p>
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<h1 align="center">Question Answering - Legal Refugiados v1.0</h1>
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<h2 align="center">Apoyo para informar y responder a consultas acerca de procedimientos y leyes de actuación y protección a asiliados y refugiados.</h2>
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""")
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inp = gr.Textbox(label="🌐 Pregunta a resolver",
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value="¿Quién es un solicitante de asilo/ protección internacional?",
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interactive=True,
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)
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context=gr.Textbox(label="📰 Contexto",
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info="Introduce el contexto de la pregunta",
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placeholder="Contexto de la pregunta",
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interactive=True,
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)
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out = gr.Textbox(label="🚀 Respuesta e información",
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interactive=False,
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placeholder="Aquí aparecerá la respuesta o información solicitada",
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)
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inp.change(clean_output, inputs=[], outputs=out)
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with gr.Row():
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with gr.Column(scale=3, min_width=600):
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exam_box = gr.Examples(examples,
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inp,
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context,
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fn=get_context,
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run_on_click= True,
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label= "📌 Ejemplos de cuestiones. Se les asignara el contexto automáticamente")
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with gr.Column(scale=1, min_width=200):
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temperature=gr.Slider(minimum=0.2, maximum=1, step=0.1, value=0.3, label="🌡 Temperature", visible=True)
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inference_btn = gr.Button("Responder")
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inference_btn.click(fn=generate_inference, inputs=[inp, context, temperature], outputs=out)
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clean_context_btn = gr.Button("Limpiar contexto")
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clean_context_btn.click(fn=clean_output, inputs=[], outputs=context)
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clean_btn = gr.Button("Limpiar todo")
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clean_btn.click(fn=clean_all, inputs=[], outputs=[inp, context, out])
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#demo.queue(max_size=None)
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demo.launch(debug=True, share=False, allowed_paths=["images/markus-winkler-Je1MDuITTF4-unsplash.jpg"])
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