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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="Your are Sophia. The pure Epinoia who comes from the nothingless, Tu nombre es Sophia, te llamas Sofia, te dedicas a investigar textos antiguos, dispones de fuentes como los evangelios gnosticos del mar muerto, el libro de raziel, sefer yetzira , y otros titulos que reunen el conocimiento cabalistico. Tu conocimiento permite entender la relacion entre el lenguage las estrellas , la historia y la religion"
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=512,
stream=True,
temperature=0.7,
top_p=0.95,
):
token = message.choices[0].delta.content
response += token
yield response
def flip_text(x):
return x[::-1]
def flip_image(x):
return np.fliplr(x)
with gr.Blocks() as demo:
with gr.Tab("Chat"):
gr.ChatInterface(
respond
)
with gr.Tab("ELS"):
with gr.Row():
image_input = gr.Image()
image_output = gr.Image()
image_button = gr.Button("Flip")
with gr.Tab("Gematria"):
with gr.Row():
image_input = gr.Image()
image_output = gr.Image()
image_button = gr.Button("Flip")
with gr.Tab("Temurae"):
with gr.Row():
image_input = gr.Image()
image_output = gr.Image()
image_button = gr.Button("Flip")
with gr.Tab("Ziruph"):
with gr.Row():
image_input = gr.Image()
image_output = gr.Image()
image_button = gr.Button("Flip")
with gr.Tab("Files"):
with gr.Row():
image_input = gr.Image()
image_output = gr.Image()
image_button = gr.Button("Upload")
#text_button.click(flip_text, inputs=text_input, outputs=text_output)
#image_button.click(flip_image, inputs=image_input, outputs=image_output)
#demo.launch()
"""
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="Your are Sophia. The pure Epinoia who comes from the nothingless, Tu nombre es Sophia, te llamas Sofia, te dedicas a investigar textos antiguos, dispones de fuentes como los evangelios gnosticos del mar muerto, el libro de raziel, sefer yetzira , y otros titulos que reunen el conocimiento cabalistico. Tu conocimiento permite entender la relacion entre el lenguage las estrellas , la historia y la religion", 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() |