Hi! I'm Vivian, a member of the team at Replicate. I've created Daily Dose of News: an interactive news feed that renders AI-generated visualizations of today's top headlines. In this post, I'll show you how I used Replicate's API, Flask, and Vercel to create the app!

Daily Dose of News

To use Daily Dose of News, choose a category (business, health, sports, entertainment, etc...) and country (source of the article), then click anywhere to start loading up your news feed! A new article is loaded every 10 seconds by default.

To generate the visualizations, I use VQGAN-CLIP. VQGAN-CLIP is capable of producing high-quality images from complex text prompts without any training by using a unified vision and language encoder to guide image generations.

Getting set up

This Flask-based website uses Replicate's API for the model, News API for generating news headlines, and Vercel for deployment.

Using Flask

I use Flask as a web framework for the app, though you can use any web framework you like.

To use Flask, I import the Flask class and create an instance of the class:

from flask import (
    Flask,
    jsonify,
    render_template,
    send_from_directory,
    request,
)

app = Flask(__name__)

Then, I define various routes using the route decorator, including a prediction route:

@app.route("/api/predict", methods=["POST"])

Making predictions

To make predictions with Replicate's API, I first import the package in the main script app.py:

import replicate

As I mentioned, I use the VQGAN-CLIP model to generate the images. I fetched the latest version of VQGAN-CLIP as follows:

# Fetch model
model = replicate.models.get("mehdidc/feed_forward_vqgan_clip")

# Get model version
version = model.versions.get(
"28b5242dadb5503688e17738aaee48f5f7f5c0b6e56493d7cf55f74d02f144d8"
)

In static/index.js, I then make a POST request to /api/predict, which in turn creates a replicate.prediction object that feeds in the news headline as our text prompt, and outputs an AI-synthesized image.

prediction = replicate.predictions.create(
    version=version,
    input={
        "prompt":headline,
        "model": 'cc12m_32x1024_mlp_mixer_openclip_laion2b_ViTB32_256x256_v0.4.th',
        "prior": False,
        "grid": '1x1',
        "seed": random.randint(0, 2**15-1),
    },
)

Running the app locally

To run the app locally, I set up my local environment:

python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

As well as set up my API tokens as environment variables:

export REPLICATE_API_TOKEN=<my-replicate-api-token>
export NEWS_API_TOKEN=<my-news-api-token>

After, I run python app.py and open localhost:5000 to see the web app in action!

Deploying the app

I use Vercel to deploy my web app. To deploy your own app on Vercel like I did, you first need to create an account on Vercel.

To deploy onto Vercel, I created a vercel.json file to configure the root directory/main program script to app.py.

Then, I created "New Project" and configure from an existing Git repo/commit. I'm able to specify the API tokens as environment variables under "Project Settings".

Finally, I installed the Vercel CLI. From the command line, I ran vercel login followed by vercel --prod.

Create your own apps

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