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loztcontrol
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0311faf
Upload 3 files
Browse files#first version. Be patient
- README.md +15 -5
- app.py +63 -0
- requirements.txt +3 -0
README.md
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---
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title:
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emoji:
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colorFrom:
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sdk: gradio
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sdk_version: 4.44.0
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app_file: app.py
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pinned: false
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license: mit
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---
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-
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title: Chat-with-OpenAI-o1
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emoji: 🚀
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colorFrom: red
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colorTo: indigo
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sdk: gradio
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sdk_version: 4.44.0
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app_file: app.py
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pinned: false
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license: mit
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duplicated_from: ysharma/ChatGPT4
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disable_embedding: true
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datasets:
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- allenai/WildChat-1M
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- allenai/WildChat-1M-Full
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- allenai/WildChat
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models:
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- allenai/WildLlama-7b-user-assistant
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- allenai/WildLlama-7b-assistant-only
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---
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- https://arxiv.org/abs/2405.01470
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- https://arxiv.org/abs/2409.03753
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app.py
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import gradio as gr
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import os
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import requests
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import random
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# Variables de entorno necesarias
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API_URL = os.getenv("API_URL")
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OPENAI_API_KEYS = os.getenv("OPENAI_API_KEYS", "").split(',')
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NUM_THREADS = int(os.getenv("NUM_THREADS", "1"))
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# Verifica que las variables de entorno necesarias estén definidas
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if not API_URL or not OPENAI_API_KEYS:
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raise ValueError("API_URL y OPENAI_API_KEYS deben estar definidas en el entorno.")
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# Función para manejar errores
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def exception_handler(exception_type, exception, traceback):
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print(f"{exception_type.__name__}: {exception}")
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sys.excepthook = exception_handler
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sys.tracebacklimit = 0
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# Función que procesa bloques de código en Markdown para ser renderizado en HTML
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def parse_codeblock(text):
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lines = text.split("\n")
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for i, line in enumerate(lines):
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if "```" in line:
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if line != "```":
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lines[i] = f'<pre><code class="{lines[i][3:]}">'
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else:
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lines[i] = '</code></pre>'
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else:
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if i > 0:
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lines[i] = "<br/>" + line.replace("<", "<").replace(">", ">")
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return "\n".join(lines)
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# Función principal que interactúa con el modelo o API externa
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def query_api(input_text):
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headers = {"Authorization": f"Bearer {random.choice(OPENAI_API_KEYS)}"}
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payload = {"input": input_text}
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try:
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response = requests.post(API_URL, json=payload, headers=headers)
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if response.status_code == 200:
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return response.json().get("output", "No response from API.")
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else:
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return f"Error: {response.status_code} - {response.text}"
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except Exception as e:
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return f"Excepción en la consulta: {str(e)}"
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# Interfaz de Gradio
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def app_function(input_text):
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# Llamada a la función que consulta la API
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result = query_api(input_text)
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return result
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# Definir la interfaz de Gradio
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interface = gr.Interface(fn=app_function, inputs="text", outputs="text",
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title="Consulta a la API",
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description="Introduce un texto para consultar la API.")
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# Ejecutar la interfaz en Hugging Face
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if __name__ == "__main__":
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interface.launch()
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requirements.txt
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gradio
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requests
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