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import gradio as gr
from huggingface_hub import InferenceClient
# HF Inference Endpoints parameter
endpoint_url = "https://rrxlgzql27e1l4x1.us-east-1.aws.endpoints.huggingface.cloud"
hf_token = "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"
# Streaming Client
client = InferenceClient(endpoint_url, token=hf_token)
# generation parameter
gen_kwargs = dict(
max_new_tokens=512,
temperature=0.5,
repetition_penalty=1.02,
)
with gr.Blocks(title="Kind Words - Gradio") as demo:
gr.Markdown(
"""
# Kind Words - Gradio
Please fill in the details below to create kind words
""")
with gr.Group():
name_box = gr.Textbox(label="Name", value="Emily")
situation_box = gr.Textbox(label="Situation", value="Writing a scientific blog post about using AI to protect deep-sea coral reefs")
behavior_box = gr.Textbox(label="Behavior", value="Emily interacted professionally and efficiently, was open to making modifications based on feedback and worked proficiently with the time constraints of others")
impact_box = gr.Textbox(label="Impact", value="A professional and engaging science blog post was created that communicated our science well")
with gr.Row():
perspective_dropdown = gr.Dropdown(["First Person", "Third Person"], label="Perspective", value="Third Person")
length_dropdown = gr.Dropdown(["Short", "Medium", "Long"], label="Output length", value="Medium")
praise_dropdown = gr.Dropdown(["Minimal", "Modest", "High"], label="Praise level", value="Modest")
submit_btn = gr.Button("Submit")
error_box = gr.Textbox(label="Error", visible=False)
with gr.Column() as output_col:
output_box = gr.Textbox(label="Output")
def submit(name, situation, behavior, impact, perspective, length, praise):
if len(name) == 0:
return {error_box: gr.update(value="Enter name", visible=True)}
elif len(situation) == 0:
return {error_box: gr.update(value="Enter a description of the situation", visible=True)}
elif len(behavior) == 0:
return {error_box: gr.update(value="Enter a description of the behavior", visible=True)}
elif len(impact) == 0:
return {error_box: gr.update(value="Enter a description of the impact", visible=True)}
if length == "Short":
output_length = "a short paragraph"
elif length == "Long":
output_length = "several paragraphs"
else:
output_length = "a couple of paragraphs"
if praise == "High":
praise = "lots of"
prompt = f"""The situation was: {situation}. The behavior was: {behavior}. The impact was: {impact}. Write {output_length} in a {perspective.lower()} perspective about {name}, providing positive feedback with {praise.lower()} praise."""
response = client.text_generation(prompt, stream=False, details=False, **gen_kwargs)
return {
output_box: response.strip(),
}
submit_btn.click(
submit,
[name_box, situation_box, behavior_box, impact_box, perspective_dropdown, length_dropdown, praise_dropdown],
output_box,
)
demo.launch()
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