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import os
import random
from huggingface_hub import InferenceClient
import gradio as gr
from utils import parse_action, parse_file_content, read_python_module_structure
from datetime import datetime
import agent
from models import models
import urllib.request
import uuid
base_url="https://johann22-chat-diffusion.hf.space/"
loaded_model=[]
for i,model in enumerate(models):
loaded_model.append(gr.load(f'models/{model}'))
print (loaded_model)
now = datetime.now()
date_time_str = now.strftime("%Y-%m-%d %H:%M:%S")
client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
#model = gr.load("models/stabilityai/sdxl-turbo")
history = []
def infer(txt):
return (model(txt))
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 run_gpt(in_prompt,history):
prompt=format_prompt(in_prompt,history)
seed = random.randint(1,1111111111111111)
print (seed)
generate_kwargs = dict(
temperature=1.0,
max_new_tokens=1048,
top_p=0.99,
repetition_penalty=1.0,
do_sample=True,
seed=seed,
)
content = agent.GENERATE_PROMPT + prompt
#print(content)
stream = client.text_generation(content, **generate_kwargs, stream=True, details=True, return_full_text=False)
resp = ""
for response in stream:
resp += response.token.text
return resp
def run(purpose,history,model_drop):
if history:
history=str(history).strip("[]")
if not history:
history = ""
out_prompt = run_gpt(purpose,history)
yield ("",[(purpose,out_prompt)],None)
model=loaded_model[int(model_drop)]
out_img=model(out_prompt)
print(out_img)
image=f'{base_url}file={out_img}'
uid = uuid.uuid4()
urllib.request.urlretrieve(image, f'{uid}.png')
return ("",[(purpose,out_prompt)],f'{uid}.png')
#return ("", [(purpose,history)])
################################################
with gr.Blocks() as iface:
gr.HTML("""<center><h1>Chat Diffusion</h1><br><h3>This chatbot will generate images</h3></center>""")
with gr.Row():
with gr.Column():
chatbot=gr.Chatbot()
msg = gr.Textbox()
model_drop=gr.Dropdown(label="Diffusion Models", type="index", choices=[m for m in models], value=models[0])
with gr.Row():
submit_b = gr.Button()
stop_b = gr.Button("Stop")
clear = gr.ClearButton([msg, chatbot])
sumbox=gr.Image(label="Image",type="filepath")
sub_b = submit_b.click(run, [msg,chatbot,model_drop],[msg,chatbot,sumbox])
sub_e = msg.submit(run, [msg, chatbot,model_drop], [msg, chatbot,sumbox])
stop_b.click(None,None,None, cancels=[sub_b,sub_e])
iface.launch()
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