Spaces:
Sleeping
Sleeping
| 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"), | |
| ], | |
| css=css, | |
| theme="allenai/gradio-theme", | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() |