import gradio as gr from openai import OpenAI import os css = ''' .gradio-container{max-width: 1000px !important} h1{text-align:center} footer { visibility: hidden } ''' ACCESS_TOKEN = os.getenv("HF_TOKEN") client = OpenAI( base_url="https://api-inference.huggingface.co/v1/", api_key=ACCESS_TOKEN, ) # Mood prompts dictionary 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 respond( message, history: list[tuple[str, str]], system_message, max_tokens, temperature, top_p, mood ): # Update system message with mood prompt mood_prompt = mood_prompts.get(mood, "") full_system_message = f"{system_message} {mood_prompt}".strip() messages = [{"role": "system", "content": full_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.completions.create( model="meta-llama/Meta-Llama-3.1-8B-Instruct", max_tokens=max_tokens, stream=True, temperature=temperature, top_p=top_p, messages=messages, ): token = message.choices[0].delta.content response += token yield response demo = gr.ChatInterface( respond, additional_inputs=[ gr.Textbox(value="", label="System message", visible=False), gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens", visible=False), gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature", visible=False), gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-P", visible=False), gr.Dropdown(choices=list(mood_prompts.keys()), label="Mood", value="Casual"), ], title="MOOD SWINGS😉", description="Chat Response Mood Types in Additional Inputs🧠", css=css, theme="allenai/gradio-theme", ) if __name__ == "__main__": demo.launch()