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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): | |
| # Beginn der Eingabeaufforderung mit dem Anfangs-Token | |
| 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]" | |
| # Hinzufügen der Historie der Interaktionen | |
| for user_prompt, bot_response in history: | |
| prompt += f"[INST] {user_prompt} [/INST]" | |
| prompt += f" {bot_response} </s> " # Beenden jeder Antwort mit End-of-Sentence-Token | |
| prompt += "<s>" # Beginn jeder neuen Aufforderung mit Start-of-Sentence-Token | |
| # Hinzufügen der aktuellen Benutzereingabe | |
| 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) |