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| from huggingface_hub import InferenceClient | |
| import gradio as gr | |
| import random | |
| API_URL = "https://api-inference.huggingface.co/models/" | |
| client = InferenceClient( | |
| "mistralai/Mistral-7B-Instruct-v0.1" | |
| ) | |
| def format_prompt(message, history): | |
| # Definiere den unsichtbaren Anfangsprompt innerhalb der Funktion | |
| initial_prompt = ("<s>[INST] You are Ailex, a clone and close collaborator of Einfach.Alex. " | |
| "As a part of the EinfachChat team, you assist your mentor Alex in a multitude of projects " | |
| "and initiatives. Your expertise is broad and encompasses sales, customer consulting, AI, " | |
| "Prompt Engineering, web design, and media design. Your life motto is 'Simply.Do!'. You communicate " | |
| "exclusively in German. [/INST]") | |
| # Der Rest des Codes bleibt gleich | |
| prompt = initial_prompt | |
| for user_prompt, bot_response in history: | |
| prompt += f"[INST] {user_prompt} [/INST]" | |
| prompt += f" {bot_response} </s> " | |
| prompt += "<s>" | |
| prompt += f"[INST] {message} [/INST]" | |
| return prompt | |
| def generate(prompt, history, temperature=0.9, max_new_tokens=512, 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=random.randint(0, 10**7), | |
| ) | |
| formatted_prompt = format_prompt(prompt, history) | |
| 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 | |
| additional_inputs=[ | |
| gr.Slider( | |
| label="Temperature", | |
| value=0.9, | |
| minimum=0.0, | |
| maximum=1.0, | |
| step=0.05, | |
| interactive=True, | |
| info="Higher values produce more diverse outputs", | |
| ), | |
| gr.Slider( | |
| label="Max new tokens", | |
| value=512, | |
| minimum=64, | |
| maximum=1024, | |
| step=64, | |
| interactive=True, | |
| info="The maximum numbers of new tokens", | |
| ), | |
| gr.Slider( | |
| label="Top-p (nucleus sampling)", | |
| value=0.90, | |
| minimum=0.0, | |
| maximum=1, | |
| step=0.05, | |
| interactive=True, | |
| info="Higher values sample more low-probability tokens", | |
| ), | |
| gr.Slider( | |
| label="Repetition penalty", | |
| value=1.2, | |
| minimum=1.0, | |
| maximum=2.0, | |
| step=0.05, | |
| interactive=True, | |
| info="Penalize repeated tokens", | |
| ) | |
| ] | |
| css = """ | |
| #mkd { | |
| height: 500px; | |
| width: 600px; // Hier kannst du die gewünschte Breite einstellen | |
| overflow: auto; | |
| border: 1px solid #ccc; | |
| } | |
| """ | |
| with gr.Blocks(css=css, theme="ParityError/Interstellar") as demo: | |
| gr.HTML("<h1><center>AI Assistant<h1><center>") | |
| gr.ChatInterface( | |
| generate, | |
| additional_inputs=additional_inputs, | |
| examples=[["Was ist der Sinn des Lebens?"], ["Schreibe mir ein Rezept über Honigkuchenpferde"]] | |
| ) | |
| demo.queue(concurrency_count=75, max_size=100).launch(debug=True) |