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import gradio as gr
from huggingface_hub import InferenceClient
client = InferenceClient("mistralai/Mistral-7B-Instruct-v0.2")
def format_prompt(message, job_profession):
system_prompt = f"You are a People Generator. You generate People based on user input. Your responses should always be in the following format: You are (Name), (Age) years old from (Country), and an expert in the field of {job_profession}."
prompt = f"<s>[SYS] {system_prompt} [/SYS][INST] {message} [/INST]</s>"
return prompt
def generate(message, job_profession, temperature=0.9, max_new_tokens=8192, top_p=0.95, repetition_penalty=1.0):
# Parse the input to determine job profession based on the presence of a message.
actual_job = message if message else job_profession
temperature = float(temperature)
if temperature < 1e-2:
temperature = 1e-2
top_p = float(top_p)
generate_kwargs = {
"temperature": temperature,
"max_new_tokens": max_new_tokens,
"top_p": top_p,
"repetition_penalty": repetition_penalty,
"do_sample": True,
"seed": 42,
}
formatted_prompt = format_prompt("", actual_job) # message should be empty here if we're using job from input
stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
output = ""
for response in stream:
output += response.token.text
yield output
css = """
#mkd {
height: 500px;
overflow: auto;
border: 1px solid #ccc;
}
"""
with gr.Blocks(css=css) as demo:
with gr.Row():
with gr.Column(scale=2):
gr.HTML("<h1>Settings</h1>")
job_dropdown = gr.Dropdown(
label="Choose a job profession",
choices=["Relationship Expert", "Sales Manager", "Blue Team Hacker", "Senior Web Developer", "C++ Developer", "Article Author", "News Anchor", "Finance Advisor"],
value="Relationship Expert" # Initial value
)
with gr.Column(scale=3):
gr.HTML("<h1><center>GPT Prompt Generator<h1><center>")
message_input = gr.Textbox(label="Input your message (overrides job dropdown)", placeholder="Type a job profession here to override the dropdown...")
generate_button = gr.Button("Generate")
output_area = gr.Textbox(label="AI Response", interactive=False, lines=10)
generate_button.click(
fn=generate,
inputs=[message_input, job_dropdown],
outputs=output_area
)
demo.launch(debug=True)
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