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from huggingface_hub import InferenceClient
import gradio as gr
import random
client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
from prompts import GAME_MASTER, COMPRESS_HISTORY
def format_prompt(message, history):
prompt=""
'''
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
temperature=0.9
top_p=0.95
repetition_penalty=1.0
def compress_history(history):
formatted_prompt=f"{COMPRESS_HISTORY.format(history=history)}"
generate_kwargs = dict(
temperature=temperature,
max_new_tokens=1024,
top_p=top_p,
repetition_penalty=repetition_penalty,
do_sample=True,
seed=random.randint(1,99999999999)
#seed=42,
)
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
return output
MAX_HISTORY=100
def generate(prompt, history,max_new_tokens):
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(1,99999999999)
#seed=42,
)
cnt=0
for ea in history:
print (ea)
for l in ea:
print (l)
cnt+=len(l.split("\n"))
print(f'cnt:: {cnt}')
if cnt > MAX_HISTORY:
history = compress_history(str(history), temperature, max_new_tokens, top_p, repetition_penalty)
formatted_prompt = format_prompt(f"{GAME_MASTER.format(history=history)}, {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 "",[(prompt,output)]
lines = output.strip().strip("\n").split("\n")
#history=""
for i,line in enumerate(lines):
if line.startswith("1. "):
print(line)
if line.startswith("2. "):
print(line)
if line.startswith("3. "):
print(line)
if line.startswith("4. "):
print(line)
if line.startswith("5. "):
print(line)
return "",[(prompt,output)]
additional_inputs=[
gr.Textbox(
label="System Prompt",
max_lines=1,
interactive=True,
),
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=1048,
minimum=0,
maximum=1048*10,
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",
)
]
def clear_fn():
return None,None
with gr.Blocks() as app:
gr.HTML("""<center><h1>Mixtral 8x7B RPG</h1><h3>Role Playing Game Master</h3>""")
chatbot = gr.Chatbot(label="Mixtral 8x7B Chatbot",show_copy_button=True)
with gr.Row():
with gr.Column(scale=3):
prompt=gr.Textbox(label = "Prompt")
with gr.Column(scale=1):
button=gr.Button()
#models_dd=gr.Dropdown(choices=[m for m in return_list],interactive=True)
with gr.Row():
stop_button=gr.Button("Stop")
clear_btn = gr.Button("Clear")
with gr.Row():
tokens=additional_inputs[2]
json_out=gr.JSON()
e_box=gr.Textbox()
#text=gr.JSON()
#inp_query.change(search_models,inp_query,models_dd)
#test_b=test_btn.click(itt,url,e_box)
clear_btn.click(clear_fn,None,[prompt,chatbot])
go=button.click(generate,[prompt,chatbot,tokens],[prompt,chatbot])
stop_button.click(None,None,None,cancels=[go])
app.launch(show_api=False)
'''
examples=[["Start the Game", None, None, None, None, None, ],
["Start a Game based in the year 1322", None, None, None, None, None,],
]
gr.ChatInterface(
fn=generate,
chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"),
additional_inputs=additional_inputs,
title="Mixtral RPG Game Master",
examples=examples,
concurrency_limit=20,
).launch(share=True,show_api=True)
'''
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