#!/usr/bin/env python
# coding: utf-8
import base64
from io import BytesIO
import requests
import streamlit as st
from PIL import Image
class ServiceError(Exception):
def __init__(self, status_code):
self.status_code = status_code
def get_images_from_backend(prompt, backend_url):
r = requests.post(backend_url, json={"prompt": prompt})
if r.status_code == 200:
images = r.json()["images"]
images = [Image.open(BytesIO(base64.b64decode(img))) for img in images]
return images
else:
raise ServiceError(r.status_code)
st.sidebar.markdown(
"""
""",
unsafe_allow_html=True,
)
st.sidebar.markdown(
"""
___
DALL·E mini is an AI model that generates images from any prompt you give!
Created by Boris Dayma et al. 2021
GitHub | Project Report
""",
unsafe_allow_html=True,
)
st.header("DALL·E mini")
st.subheader("Generate images from text")
prompt = st.text_input("What do you want to see?")
DEBUG = False
if prompt != "":
container = st.empty()
container.markdown(
f"""
Generating predictions for:
{prompt}
Predictions may take up to 40s under high load. Please stand by.
""",
unsafe_allow_html=True,
)
try:
backend_url = st.secrets["BACKEND_SERVER"]
print(f"Getting selections: {prompt}")
selected = get_images_from_backend(prompt, backend_url)
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")
except ServiceError as error:
container.text(f"Service unavailable, status: {error.status_code}")
except KeyError:
if DEBUG:
container.markdown(
"""
**Error: BACKEND_SERVER unset**
Please, create a file called `.streamlit/secrets.toml` inside the app's folder and include a line to configure the server URL:
```
BACKEND_SERVER=""
```
"""
)
else:
container.markdown(
"Error -5, please try again or [report it](mailto:pcuenca-dalle@guenever.net)."
)