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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 | |
| import chat_models | |
| loaded_model=[] | |
| chat_model=[] | |
| for i,model in enumerate(models): | |
| loaded_model.append(gr.load(f'models/{model}')) | |
| print (loaded_model) | |
| for i,model_c in enumerate(chat_models.models): | |
| chat_model.append(model_c) | |
| print (chat_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,model_drop): | |
| client = InferenceClient(chat_models.models[int(model_drop)]) | |
| 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,chat_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,model_drop) | |
| #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) | |
| ################################################ | |
| style=""" | |
| .top_head{ | |
| background: no-repeat; | |
| background-image: url(https://huggingface.co/spaces/johann22/chat-diffusion/resolve/main/image.png); | |
| background-position-y: bottom; | |
| height: 180px; | |
| background-position-x: center; | |
| } | |
| .top_h1{ | |
| color: white!important; | |
| -webkit-text-stroke-width: medium; | |
| } | |
| """ | |
| with gr.Blocks(css=style) as iface: | |
| gr.HTML("""<div class="top_head"><center><br><h1 class="top_h1">Mixtral Chat Diffusion</h1><br><h3 class="top_h1">This chatbot will generate images</h3></center></div?""") | |
| #chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"), | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| 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]) | |
| chat_model_drop=gr.Dropdown(label="Chatbot Models", type="index", choices=[m for m in chat_models.models], value=chat_models.models[0]) | |
| with gr.Group(): | |
| with gr.Row(): | |
| submit_b = gr.Button() | |
| stop_b = gr.Button("Stop") | |
| clear = gr.ClearButton([msg, chatbot]) | |
| with gr.Column(scale=2): | |
| sumbox=gr.Image(label="Image") | |
| sub_b = submit_b.click(run, [msg,chatbot,model_drop,chat_model_drop],[chatbot,sumbox]) | |
| sub_e = msg.submit(run, [msg, chatbot,model_drop,chat_model_drop], [chatbot,sumbox]) | |
| stop_b.click(None,None,None, cancels=[sub_b,sub_e]) | |
| iface.launch() | |