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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) |