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import gradio as gr
from huggingface_hub import InferenceClient
import csv
import json
def buscar_en_csv_y_generar_json(archivo_csv, valor_busqueda):
resultados = []
with open(archivo_csv, mode='r', encoding='utf-8') as file:
reader = csv.reader(file)
for fila in reader:
linea_completa = ','.join(fila)
if valor_busqueda in linea_completa:
resultados.append(fila)
if resultados:
return json.dumps(resultados, indent=4, ensure_ascii=False)
else:
return json.dumps({"mensaje": "No se encontraron coincidencias."}, indent=4, ensure_ascii=False)
"""
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
"""
css = "#component-2 {height: 350px}"
def search(term):
return buscar_en_csv_y_generar_json("proyectos_empresas.csv", term)
with gr.Blocks(title="SPAIN WIND ENERGY LOBBY",css=css) as app:
#with gr.Blocks(theme='gradio/soft') as demo:
#with gr.Blocks(title="Sophia, Torah Codes") as app:
#with gr.Row():
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)",
#),
],
)
with gr.Row():
to_convert = gr.Textbox(value="Forestalia",label="Search",scale=3)
search_els = gr.Button("Search",scale=1)
with gr.Row():
#els_results = gr.JSON(label="Results")
results = gr.JSON()
search_els.click(
search,
inputs=[to_convert,to_convert],
outputs= results
)
if __name__ == "__main__":
app.launch() |