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import gradio as gr
from huggingface_hub import InferenceClient
import random
models=[
"google/gemma-7b",
"google/gemma-7b-it",
"google/gemma-2b",
"google/gemma-2b-it"
]
clients=[
InferenceClient(models[0]),
InferenceClient(models[1]),
InferenceClient(models[2]),
InferenceClient(models[3]),
]
def format_prompt(message, history):
prompt = "<s>"
if history:
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 chat_inf(system_prompt,prompt,history,client_choice):
#token max=8192
client=clients[int(client_choice)-1]
if not history:
history = []
hist_len=0
if history:
hist_len=len(history)
print(hist_len)
seed = random.randint(1,1111111111111111)
generate_kwargs = dict(
temperature=0.9,
max_new_tokens=6000,
top_p=0.95,
repetition_penalty=1.0,
do_sample=True,
seed=seed,
)
formatted_prompt=prompt
#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 [(prompt,output)]
history.append((prompt,output))
yield history
with gr.Blocks() as app:
with gr.Group():
chat_b = gr.Chatbot()
with gr.Row():
with gr.Column(scale=3):
inp = gr.Textbox(label="Prompt")
sys_inp = gr.Textbox(label="System Prompt (optional)")
btn = gr.Button("Chat")
with gr.Column(scale=1):
with gr.Group():
stop_btn=gr.Button("Stop")
clear_btn=gr.Button("Clear")
client_choice=gr.Dropdown(label="Models",type='index',choices=[c for c in models],value=models[0],interactive=True)
go=btn.click(chat_inf,[sys_inp,inp,chat_b,client_choice],chat_b)
stop_btn.click(None,None,None,cancels=go)
app.launch()
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