#!/usr/bin/env python

from os import getenv
from dotenv import load_dotenv
from autotagger import Autotagger
from base64 import b64encode
from flask import Flask, request, render_template, jsonify
from fastai.vision.core import PILImage

load_dotenv()
model_path = getenv("MODEL_PATH", "models/model.pth")
autotagger = Autotagger(model_path)

app = Flask(__name__)
app.config["JSON_SORT_KEYS"] = False
app.config["JSON_PRETTYPRINT_REGULAR"] = True

@app.route("/", methods=["GET"])
def index():
    return render_template("index.html")

@app.route("/evaluate", methods=["POST"])
def evaluate():
    files = request.files.getlist("file")
    images = [PILImage.create(file) for file in files]
    threshold = float(request.form.get("threshold", 0.1))
    output = request.form.get("format", "html")
    limit = int(request.form.get("limit", 50))

    predictions = autotagger.predict(images, threshold=threshold, limit=limit)

    if output == "html":
        for file in files:
            file.seek(0)

        base64data = [b64encode(file.read()).decode() for file in files]
        return render_template("evaluate.html", predictions=zip(base64data, predictions))
    elif output == "json":
        predictions = [{ "filename": file.filename, "tags": tags } for file, tags in zip(files, predictions)]
        return jsonify(predictions)
    else:
        return 400

if __name__ == "__main__":
    app.run(host="0.0.0.0")