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from huggingface_hub import InferenceClient
import gradio as gr
css = '''
.gradio-container{max-width: 690px !important}
h1{text-align:center}
footer {
visibility: hidden
}
'''
client = InferenceClient("mistralai/Mistral-7B-Instruct-v0.3")
mood_prompts = {
"Fun": "Respond in a light-hearted, playful manner.",
"Serious": "Respond in a thoughtful, serious tone.",
"Professional": "Respond in a formal, professional manner.",
"Upset": "Respond in a slightly irritated, upset tone.",
"Empathetic": "Respond in a warm and understanding tone.",
"Optimistic": "Respond in a positive, hopeful manner.",
"Sarcastic": "Respond with a hint of sarcasm.",
"Motivational": "Respond with encouragement and motivation.",
"Curious": "Respond with a sense of wonder and curiosity.",
"Humorous": "Respond with a touch of humor.",
"Cautious": "Respond with careful consideration and caution.",
"Assertive": "Respond with confidence and assertiveness.",
"Friendly": "Respond in a warm and friendly manner.",
"Romantic": "Respond with affection and romance.",
"Nostalgic": "Respond with a sense of longing for the past.",
"Grateful": "Respond with gratitude and appreciation.",
"Inspirational": "Respond with inspiration and positivity.",
"Casual": "Respond in a relaxed and informal tone.",
"Formal": "Respond with a high level of formality.",
"Pessimistic": "Respond with a focus on potential negatives.",
"Excited": "Respond with enthusiasm and excitement.",
"Melancholic": "Respond with a sense of sadness or longing.",
"Confident": "Respond with self-assurance and confidence.",
"Suspicious": "Respond with caution and doubt.",
"Reflective": "Respond with deep thought and introspection.",
"Joyful": "Respond with happiness and joy.",
"Mysterious": "Respond with an air of mystery and intrigue.",
"Aggressive": "Respond with force and intensity.",
"Calm": "Respond with a sense of peace and tranquility.",
"Gloomy": "Respond with a sense of sadness or pessimism.",
"Encouraging": "Respond with words of support and encouragement.",
"Sympathetic": "Respond with understanding and compassion.",
"Disappointed": "Respond with a tone of disappointment.",
"Proud": "Respond with a sense of pride and accomplishment.",
"Playful": "Respond in a fun and playful manner.",
"Inquisitive": "Respond with curiosity and interest.",
"Supportive": "Respond with reassurance and support.",
"Reluctant": "Respond with hesitation and reluctance.",
"Confused": "Respond with uncertainty and confusion.",
"Energetic": "Respond with high energy and enthusiasm.",
"Relaxed": "Respond with a calm and laid-back tone.",
"Grumpy": "Respond with a touch of irritation.",
"Hopeful": "Respond with a sense of hope and optimism.",
"Indifferent": "Respond with a lack of strong emotion.",
"Surprised": "Respond with shock and astonishment.",
"Tense": "Respond with a sense of urgency or anxiety.",
"Enthusiastic": "Respond with eagerness and excitement.",
"Worried": "Respond with concern and apprehension."
}
def format_prompt(message, history, system_prompt=None, mood=None):
prompt = "<s>"
if mood:
mood_description = mood_prompts.get(mood, "")
prompt += f"[SYS] {mood_description} [/SYS] "
for user_prompt, bot_response in history:
prompt += f"[INST] {user_prompt} [/INST]"
prompt += f" {bot_response}</s> "
if system_prompt:
prompt += f"[SYS] {system_prompt} [/SYS]"
prompt += f"[INST] {message} [/INST]"
return prompt
def generate(
prompt, history, system_prompt=None, mood=None, temperature=0.2, max_new_tokens=1024, top_p=0.95, repetition_penalty=1.0,
):
temperature = float(temperature)
if temperature < 1e-2:
temperature = 1e-2
top_p = float(top_p)
generate_kwargs = dict(
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(prompt, history, system_prompt, mood)
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
return output
def gradio_interface():
with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
with gr.Row():
mood = gr.Radio(choices=list(mood_prompts.keys()), value="Professional", label="Select Mood")
history = gr.State([])
system_prompt = gr.Textbox(placeholder="System prompt (optional)", lines=1)
prompt = gr.Textbox(placeholder="Enter your message", lines=2)
generate_btn = gr.Button("Generate")
output = gr.Chatbot()
generate_btn.click(
generate,
inputs=[prompt, history, system_prompt, mood],
outputs=[output]
)
demo.queue().launch(show_api=False)
gradio_interface() |