Update app.py

app.py

@@ -1,60 +1,12 @@
-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")
+from flask import Flask, render_template
 
 app = Flask(__name__)
 
+@app.route('/')
+def display_info():
+    with open('info.txt', 'r') as file:
+        info = file.read().replace('\n', '<br>')
+    return render_template('index.html', info=info)
 
-@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__":
+if __name__ == '__main__':
     app.run(host="0.0.0.0", port=7860)