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import os
import requests
import json
from io import BytesIO
from flask import Flask, jsonify, render_template, request, send_file
from modules.inference import infer_t5
from modules.dataset import query_emotion
# https://huggingface.co/settings/tokens
# https://huggingface.co/spaces/{username}/{space}/settings
API_TOKEN = os.getenv("BIG_GAN_TOKEN")
app = Flask(__name__)
@app.route("/")
def index():
return render_template("index.html")
@app.route("/infer_biggan")
def biggan():
input = request.args.get("input")
output = requests.request(
"POST",
"https://api-inference.huggingface.co/models/osanseviero/BigGAN-deep-128",
headers={"Authorization": f"Bearer {API_TOKEN}"},
data=json.dumps(input),
)
return send_file(BytesIO(output.content), mimetype="image/png")
@app.route("/infer_t5")
def t5():
input = request.args.get("input")
output = infer_t5(input)
return jsonify({"output": output})
@app.route("/query_emotion")
def emotion():
start = request.args.get("start")
end = request.args.get("end")
print(start)
print(end)
output = query_emotion(int(start), int(end))
return jsonify({"output": output})
if __name__ == "__main__":
app.run(host="0.0.0.0", port=7860)
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