Spaces:
Sleeping
Sleeping
Commit ·
7e40c1d
1
Parent(s): d6d3678
feat: Implement API key authentication, owner bypass, and rate limiting for the Gradio interface.
Browse files
README.md
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@@ -56,8 +56,25 @@ Esta aplicación está lista para usar. Solo escribe tu texto en inglés y obté
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python app.py
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```
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Visita `http://127.0.0.1:7860` en tu navegador.
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## 📁 Estructura del Proyecto
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- `app.py`: Interfaz de usuario con Gradio
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python app.py
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```
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Visita `http://127.0.0.1:7860` en tu navegador.
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### ⚡️ Setup Ultrarrápido con uv
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Si prefieres usar [uv](https://github.com/astral-sh/uv) para una gestión de dependencias mucho más rápida:
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1. **Instalar uv** (si no lo tienes):
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```bash
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curl -LsSf https://astral.sh/uv/install.sh | sh
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```
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2. **Inicializar y ejecutar**:
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```bash
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uv venv
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uv pip install -r requirements.txt
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uv run app.py
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```
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## 📁 Estructura del Proyecto
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- `app.py`: Interfaz de usuario con Gradio
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app.py
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import gradio as gr
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import pandas as pd
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from core import analyze_text
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"""
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Wrapper function for Gradio interface.
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"""
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# Process errors for DataFrame
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errors_list = result.get("errors", [])
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result.get("general_feedback", "")
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)
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copy_table_btn = gr.Button("📋 Copiar Tabla", size="sm")
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copy_table_output = gr.Textbox(visible=False)
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outputs=[polished_text, spanish_translation, error_table, feedback_msg]
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#
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demo.launch(theme=gr.themes.Soft())
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import gradio as gr
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import pandas as pd
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import os
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import secrets
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import time
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from collections import defaultdict
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from dotenv import load_dotenv
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from core import analyze_text
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# Cargar variables de entorno desde .env
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load_dotenv()
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# DEBUG: Verificar carga de variables
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print("=" * 50)
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print("DEBUG - Variables de entorno cargadas:")
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print(f"GROQ_API_KEY existe: {bool(os.environ.get('GROQ_API_KEY'))}")
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print(f"pass_owner value: '{os.environ.get('pass_owner')}'")
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print("=" * 50)
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# Rate limiting (almacenado en memoria del servidor)
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login_attempts = defaultdict(list)
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MAX_ATTEMPTS = 5
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LOCKOUT_TIME = 300 # 5 minutos
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def interface_fn(input_text, api_key):
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"""
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Wrapper function for Gradio interface.
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"""
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# Si es el token del owner, usar la key del entorno
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if api_key == "owner_authenticated":
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actual_key = os.environ.get("GROQ_API_KEY")
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if not actual_key:
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return ("", "", pd.DataFrame(), "⚠️ Error de configuración del servidor")
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else:
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actual_key = api_key
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result = analyze_text(input_text, actual_key)
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# Process errors for DataFrame
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errors_list = result.get("errors", [])
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result.get("general_feedback", "")
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)
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def verify_key(key, request: gr.Request):
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"""
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Verifies the input key and implements the owner bypass.
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SECURE VERSION for Hugging Face Spaces.
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"""
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# Rate limiting por IP
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client_ip = request.client.host if request else "unknown"
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now = time.time()
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# Limpiar intentos antiguos
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login_attempts[client_ip] = [t for t in login_attempts[client_ip] if now - t < LOCKOUT_TIME]
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if len(login_attempts[client_ip]) >= MAX_ATTEMPTS:
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return None, gr.update(visible=True), gr.update(visible=False), "⚠️ Demasiados intentos. Espera 5 minutos."
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key = key.strip()
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# Check for bypass con comparación de tiempo constante
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if key.startswith("pass"):
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pass_owner = os.environ.get("pass_owner")
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if pass_owner:
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expected = "pass" + pass_owner
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# Usar secrets.compare_digest para evitar timing attacks
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if len(key) == len(expected) and secrets.compare_digest(key, expected):
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# ✅ NO retornar la API key real
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# Usar un token de sesión en su lugar
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session_token = "owner_authenticated"
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login_attempts[client_ip] = [] # Reset intentos
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return session_token, gr.update(visible=False), gr.update(visible=True), ""
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else:
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login_attempts[client_ip].append(now)
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return None, gr.update(visible=True), gr.update(visible=False), "⚠️ Credenciales incorrectas."
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# Validar formato de API key de usuario (Groq keys empiezan con gsk_)
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if key and key.startswith("gsk_") and len(key) > 30:
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login_attempts[client_ip] = []
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return key, gr.update(visible=False), gr.update(visible=True), ""
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login_attempts[client_ip].append(now)
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return None, gr.update(visible=True), gr.update(visible=False), "⚠️ API Key inválida."
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with gr.Blocks(title="Assistant Inglés L2") as demo:
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# State to store the authenticated API key
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api_key_state = gr.State()
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# --- Login View ---
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with gr.Column(visible=True) as login_view:
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gr.Markdown(
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"""
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# 🔐 Configuración
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Para usar el Asistente, por favor ingresa tu **Groq API Key**.
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*(Si eres el administrador, usa tu frase de paso)*
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"""
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)
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api_key_input = gr.Textbox(
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label="Groq API Key (o frase de administrador)",
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type="password",
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placeholder="gsk_... o pass...",
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lines=1
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)
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login_btn = gr.Button("Ingresar", variant="primary")
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login_msg = gr.Markdown("")
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# --- Main View ---
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with gr.Column(visible=False) as main_view:
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gr.Markdown(
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"""
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# 🇬🇧 Asistente Inteligente de Escritura Inglés (L2)
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Escribe en inglés y recibe correcciones, traducción y explicaciones al instante.
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"""
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)
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with gr.Row():
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with gr.Column(scale=1):
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input_box = gr.Textbox(
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label="Tu texto en inglés",
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placeholder="Escribe aquí... (ej. She dont like play football)",
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lines=10
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)
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submit_btn = gr.Button("Analizar y Corregir", variant="primary")
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with gr.Column(scale=1):
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with gr.Row():
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polished_text = gr.Textbox(label="Texto Pulido", interactive=False, lines=8, scale=4)
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copy_polished_btn = gr.Button("📋", scale=1, size="sm")
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with gr.Row():
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spanish_translation = gr.Textbox(label="Verificación de Significado (ES)", interactive=False, lines=8, scale=4)
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copy_translation_btn = gr.Button("📋", scale=1, size="sm")
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feedback_msg = gr.Label(label="Feedback General")
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with gr.Row():
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with gr.Column():
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error_table = gr.Dataframe(
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headers=["Original", "Corrección", "Explicación", "Tipo"],
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label="Detalle de Errores",
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interactive=False,
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wrap=True
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)
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copy_table_btn = gr.Button("📋 Copiar Tabla", size="sm")
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copy_table_output = gr.Textbox(visible=False)
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submit_btn.click(
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fn=interface_fn,
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inputs=[input_box, api_key_state],
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outputs=[polished_text, spanish_translation, error_table, feedback_msg]
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)
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# Copy button functionality
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copy_polished_btn.click(lambda x: x, inputs=[polished_text], outputs=[polished_text], js="(x) => {navigator.clipboard.writeText(x); return x;}")
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copy_translation_btn.click(lambda x: x, inputs=[spanish_translation], outputs=[spanish_translation], js="(x) => {navigator.clipboard.writeText(x); return x;}")
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def format_table_for_copy(df):
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if df is None or len(df) == 0:
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return ""
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lines = []
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for _, row in df.iterrows():
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lines.append(f"Original: {row['Original']}\nCorrección: {row['Corrección']}\nExplicación: {row['Explicación']}\nTipo: {row['Tipo']}\n")
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return "\n".join(lines)
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copy_table_btn.click(
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fn=format_table_for_copy,
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inputs=[error_table],
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outputs=[copy_table_output],
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js="(df) => {const text = df; navigator.clipboard.writeText(text); return text;}"
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)
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# --- Event Wiring ---
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login_btn.click(
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fn=verify_key,
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inputs=[api_key_input],
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outputs=[api_key_state, login_view, main_view, login_msg]
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)
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# Allow Enter key to submit on login
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api_key_input.submit(
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fn=verify_key,
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inputs=[api_key_input],
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outputs=[api_key_state, login_view, main_view, login_msg]
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)
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if __name__ == "__main__":
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demo.launch(theme=gr.themes.Soft())
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core.py
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# Initialize Groq client
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# Security Note: API Key is loaded from environment variable GROQ_API_KEY
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# In Hugging Face Spaces, this will be loaded from Repository Secrets
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client = Groq(
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MODEL_NAME = "llama-3.3-70b-versatile"
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Do not include any text outside the JSON object.
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"""
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def analyze_text(input_text: str) -> dict:
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"""
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Analyzes the input English text using Groq API and returns a structured response.
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Args:
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input_text (str): The English text to analyze.
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Returns:
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dict: The structured analysis result.
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"general_feedback": "Por favor, ingresa un texto para analizar."
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}
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try:
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completion = client.chat.completions.create(
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model=MODEL_NAME,
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messages=[
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# Initialize Groq client
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# Security Note: API Key is loaded from environment variable GROQ_API_KEY
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# In Hugging Face Spaces, this will be loaded from Repository Secrets
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# client = Groq(
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# api_key=os.environ.get("GROQ_API_KEY"),
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# )
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MODEL_NAME = "llama-3.3-70b-versatile"
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Do not include any text outside the JSON object.
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"""
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def analyze_text(input_text: str, api_key: str) -> dict:
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"""
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Analyzes the input English text using Groq API and returns a structured response.
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Args:
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input_text (str): The English text to analyze.
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api_key (str): The Groq API key to use.
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Returns:
|
| 57 |
dict: The structured analysis result.
|
|
|
|
| 64 |
"general_feedback": "Por favor, ingresa un texto para analizar."
|
| 65 |
}
|
| 66 |
|
| 67 |
+
if not api_key:
|
| 68 |
+
return {
|
| 69 |
+
"corrected_text": input_text,
|
| 70 |
+
"spanish_translation": "Error de configuración",
|
| 71 |
+
"errors": [],
|
| 72 |
+
"general_feedback": "No se proporcionó una API Key válida."
|
| 73 |
+
}
|
| 74 |
+
|
| 75 |
try:
|
| 76 |
+
client = Groq(api_key=api_key)
|
| 77 |
+
|
| 78 |
completion = client.chat.completions.create(
|
| 79 |
model=MODEL_NAME,
|
| 80 |
messages=[
|
requirements.txt
CHANGED
|
@@ -1,3 +1,4 @@
|
|
| 1 |
gradio>=4.0.0
|
| 2 |
groq>=0.4.0
|
| 3 |
pandas>=2.0.0
|
|
|
|
|
|
| 1 |
gradio>=4.0.0
|
| 2 |
groq>=0.4.0
|
| 3 |
pandas>=2.0.0
|
| 4 |
+
python-dotenv>=1.0.0
|