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from huggingface_hub import InferenceClient
import gradio as gr
import random
import prompts
client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
def format_prompt(message, history):
prompt = "<s>"
for user_prompt, bot_response in history:
prompt += f"[INST] {user_prompt} [/INST]"
prompt += f" {bot_response}</s> "
prompt += f"[INST] {message} [/INST]"
return prompt
def generate(prompt, history, max_new_tokens, seed):
print(seed)
system_prompt = prompts.ARTICLE_WRITER.format(history=history)
generate_kwargs = dict(
temperature=0.9,
max_new_tokens=max_new_tokens,
top_p=0.95,
repetition_penalty=1.0,
do_sample=True,
seed=seed,
)
formatted_prompt = format_prompt(f"{system_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
additional_inputs = [
gr.Slider(
label="Max new tokens",
value=4096,
minimum=10,
maximum=1048*10,
step=64,
interactive=True,
info="The maximum numbers of words the chatbot will return",
),
gr.Slider(
label="Seed",
value=random.randint(1,9999999999999999),
minimum=0,
maximum=9999999999999999,
step=64,
interactive=True,
info="Each seed produces a different output to a single prompt",
),
]
examples = [
["Write a 1000-word article about the benefits of a healthy lifestyle."],
["Compose a 2000-word essay on the impact of technology on modern society."],
["Generate a 1500-word article discussing the importance of environmental conservation."],
["Create a 3000-word piece exploring the role of art in shaping cultural identity."],
]
gr.ChatInterface(
fn=generate,
chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"),
title="Article Writer",
additional_inputs=additional_inputs,
examples=examples,
concurrency_limit=20,
).launch(show_api=False) |