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import gradio as gr
from huggingface_hub import InferenceClient
from datasets import load_dataset
import pandas as pd
df = None
def load_new_dataset():
global df
gr.Info(message="Loading dataset...")
# https://huggingface.co/datasets/fka/awesome-chatgpt-prompts
ds = pd.read_csv("hf://datasets/fka/awesome-chatgpt-prompts/prompts.csv")
df = pd.DataFrame(ds)
def run_query(input: str):
try:
df_results = df[df['act'].str.contains(input, case=False, na=False)]
logging_message = f"Results for '{input}' found."
except Exception as e:
raise gr.Error(f"Error running query: {e}")
return df_results, logging_message
#----------------------
with gr.Blocks() as demo:
text_input = gr.Textbox(visible=True, label="Enter value to generate a prompt for an 'actor' (for instance, developer):")
btn_run = gr.Button(visible=True, value="Search")
results_output = gr.Dataframe(label="Results", visible=True, wrap=True)
logging_output = gr.Label(visible="True", value="")
btn_run.click(
fn=run_query, # Call the run_query function and update the label
inputs=text_input,
outputs=[results_output, logging_output] # Update both the DataFrame and the label
)
#----------------------
if __name__ == "__main__":
load_new_dataset()
demo.launch()
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