app.py

import base64
import os
import time
from io import BytesIO
from multiprocessing import Process

import streamlit as st
from PIL import Image

import requests


def start_server():
    os.system("uvicorn server:app --port 8080 --host 0.0.0.0 --workers 2")


def load_models():
    if not is_port_in_use(8080):
        with st.spinner(text="Loading models, please wait..."):
            proc = Process(target=start_server, args=(), daemon=True)
            proc.start()
            while not is_port_in_use(8080):
                time.sleep(1)
            st.success("Model server started.")
    else:
        st.success("Model server already running...")
    st.session_state["models_loaded"] = True


def is_port_in_use(port):
    import socket

    with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
        return s.connect_ex(("0.0.0.0", port)) == 0


def generate(prompt):
    correct_request = f"http://0.0.0.0:8080/correct?prompt={prompt}"
    response = requests.get(correct_request)
    images = response.json()["images"]
    images = [Image.open(BytesIO(base64.b64decode(img))) for img in images]
    return images


if "models_loaded" not in st.session_state:
    st.session_state["models_loaded"] = False


st.header("minDALL-E")
st.subheader("Generate images from text")

if not st.session_state["models_loaded"]:
    load_models()

prompt = st.text_input("What do you want to see?")

DEBUG = False
if prompt != "":
    container = st.empty()
    container.markdown(
        f"""
        <style> p {{ margin:0 }} div {{ margin:0 }} </style>
        <div data-stale="false" class="element-container css-1e5imcs e1tzin5v1">
        <div class="stAlert">
        <div role="alert" data-baseweb="notification" class="st-ae st-af st-ag st-ah st-ai st-aj st-ak st-g3 st-am st-b8 st-ao st-ap st-aq st-ar st-as st-at st-au st-av st-aw st-ax st-ay st-az st-b9 st-b1 st-b2 st-b3 st-b4 st-b5 st-b6">
        <div class="st-b7">
        <div class="css-whx05o e13vu3m50">
        <div data-testid="stMarkdownContainer" class="css-1ekf893 e16nr0p30">
                <img src="https://raw.githubusercontent.com/borisdayma/dalle-mini/main/app/streamlit/img/loading.gif" width="30"/>
                Generating predictions for: <b>{prompt}</b>
        </div>
        </div>
        </div>
        </div>
        </div>
        </div>
        <small><i>Predictions may take up to 40s under high load. Please stand by.</i></small>
    """,
        unsafe_allow_html=True,
    )

    print(f"Getting selections: {prompt}")
    selected = generate(prompt)

    margin = 0.1  # for better position of zoom in arrow
    n_columns = 3
    cols = st.columns([1] + [margin, 1] * (n_columns - 1))
    for i, img in enumerate(selected):
        cols[(i % n_columns) * 2].image(img)
    container.markdown(f"**{prompt}**")

    st.button("Again!", key="again_button")