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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
from PIL import Image
import agent
from models import models
import urllib.request
import uuid
import requests
import io
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")
history = []
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):
print(f'history :: {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):
print (history)
task=None
#if history:
# history=str(history).strip("[]")
#if not history:
# history = ""
#action_name, action_input = parse_action(line)
out_prompt = run_gpt(purpose,history)
#yield ([(purpose,out_prompt)],None)
history.append((purpose,out_prompt))
yield (history,None)
#out_img = infer(out_prompt)
model=loaded_model[int(model_drop)]
out_img=model(out_prompt)
print(out_img)
url=f'https://johann22-chat-diffusion.hf.space/file={out_img}'
print(url)
uid = uuid.uuid4()
#urllib.request.urlretrieve(image, 'tmp.png')
#out=Image.open('tmp.png')
r = requests.get(url, stream=True)
if r.status_code == 200:
out = Image.open(io.BytesIO(r.content))
#yield ([(purpose,out_prompt)],out)
yield (history,out)
else:
yield ([(purpose,"an Error occured")],None)
################################################
with gr.Blocks() as iface:
gr.HTML("""<center><h1>Mixtral Chat Diffusion</h1><br><h3>This chatbot will generate images</h3></center>""")
#chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"),
with gr.Row():
with gr.Column():
chatbot=gr.Chatbot(show_copy_button=True, layout='panel')
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")
sub_b = submit_b.click(run, [msg,chatbot,model_drop],[chatbot,sumbox])
sub_e = msg.submit(run, [msg, chatbot,model_drop], [chatbot,sumbox])
stop_b.click(None,None,None, cancels=[sub_b,sub_e])
iface.launch()
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