Delete app.py

import gradio as gr
import requests, os

# URL del modelo de corrección gramátical
API_URL = "/static-proxy?url=https%3A%2F%2Fapi-inference.huggingface.co%2Fmodels%2Fistartt%2FGrammarErrorCorrectorV2%26quot%3B%3Cbr%2F%3Eheaders = {"Authorization": f"Bearer {os.getenv('HF_TOKEN')}"}

def chat_es(texto):
"""Envía el texto a Hugging Face y devuelve la corrección."""
respuesta = requests.post(API_URL, headers=headers, json={"inputs": texto})
data = respuesta.json()
if isinstance(data, list) and data:
return data[0].get("generated_text", texto)
return "❌ Error al procesar. Intenta de nuevo."

iface = gr.Interface(
fn=chat_es,
inputs=gr.Textbox(lines=4, placeholder="Escribe tu frase en español aquí…"),
outputs=gr.Textbox(label="Corrección"),
title="Chat de práctica A2–B1",
description="Recibe correcciones automáticas de tus frases en español.",
allow_flagging="never"
)

if __name__ == "__main__":
iface.launch(server_name="0.0.0.0", server_port=7860)

app.py

@@ -1,64 +0,0 @@
-import gradio as gr
-from huggingface_hub import InferenceClient
-
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
-
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
-
-
-if __name__ == "__main__":
-    demo.launch()