recommendation

.env

@@ -1,2 +0,0 @@
-BASE_URL = "http://127.0.0.1:7860"
-OPENAI_API_KEY = "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"

.gitignore

@@ -2,4 +2,5 @@ models
 __pycache__
 Acne_Classifyer_N_Resnet.h5
 haarcascade_eye.xml
-shape_predictor_68_face_landmarks.dat
+shape_predictor_68_face_landmarks.dat
+.env

main.py

@@ -4,6 +4,7 @@ from io import BytesIO
 import PIL 
 import numpy as np
 import os
+import json
 
 BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
 
@@ -40,14 +41,13 @@ def sentence_builder(age, sex, skin_type, allergies, diet, file):
 
     try:
         response = index.recommendation(data)
-        data = response.json()
-        content = data['choices'][0]['message']['content']
+        content = response['choices'][0]['message']['content']
         return content, output1, output2, output3, output4
     except: 
         return "No recommendation found", output1, output2, output3, output4
 
 with gr.Blocks() as demo:
-    gr.Markdown("Flip text or image files using this demo.")
+    gr.Markdown("Flip text or image files using this    demo.")
     with gr.Row():
         with gr.Column():
             age = gr.Number(value=20, label="Age")
@@ -67,6 +67,7 @@ with gr.Blocks() as demo:
             fh = gr.Label(num_top_classes=3, label="Fore Head|Acne Level")
             lc = gr.Label(num_top_classes=3, label="Left Cheek|Acne Level")
             rc = gr.Label(num_top_classes=3, label="Right Cheek|Acne Level")
+      
         with gr.Tab("Recommendation:Treatment Plan"):
             html_output = gr.HTML('Recommendation will be shown here')