Update app.py

app.py

@@ -112,7 +112,7 @@ def process_chunk(audio_chunk, preprocessed_data, args):
 
     first_coeff_path = preprocessed_data["first_coeff_path"]
     crop_pic_path = preprocessed_data["crop_pic_path"]
-    crop_info_path = r"C:\Users\fd01076\Downloads\preprocess_data\crop_info.json"
+    crop_info_path = "/home/user/app/preprocess_data/crop_info.json"
     with open(crop_info_path , "rb") as f:
             crop_info = json.load(f)
 
@@ -163,8 +163,8 @@ client = OpenAI(api_key="sk-proj-04146TPzEmvdV6DzSxsvNM7jxOnzys5TnB7iZB0tp59B-jM
 def openai_chat_avatar(text_prompt):
     response = client.chat.completions.create(
         model="gpt-4o-mini",
-        messages=[{"role": "system", "content": "Answer in English language always using the minimum words you can ever use."},
-            {"role": "user", "content": f"Hi! I need help with something. Can you assist me with the following: {text_prompt}"},
+        messages=[{"role": "system", "content": "Ensure answers are concise, human-like, and clear while maintaining quality. Use the fewest possible words, avoiding unnecessary articles, prepositions, and adjectives. Responses should be short but still address the question thoroughly without being verbose.Keep them to one sentence only"},
+            {"role": "user", "content": f"Hi! I need help with something. {text_prompt}"},
         ],
         max_tokens = len(text_prompt) + 300 # Use the length of the input text
         # temperature=0.3,
@@ -242,7 +242,7 @@ def run_preprocessing(args):
     global path_of_lm_croper, path_of_net_recon_model, dir_of_BFM_fitting
     first_frame_dir = os.path.join(args.result_dir, 'first_frame_dir')
     os.makedirs(first_frame_dir, exist_ok=True)
-    fixed_temp_dir = "C:/Users/fd01076/Downloads/preprocess_data/"
+    fixed_temp_dir = "/home/user/app/preprocess_data/"
     os.makedirs(fixed_temp_dir, exist_ok=True)
     preprocessed_data_path = os.path.join(fixed_temp_dir, "preprocessed_data.pkl")
 
@@ -264,7 +264,7 @@ def generate_video():
     try:
         if request.method == 'POST':
             # source_image = request.files['source_image']
-            image_path = 'C:/Users/fd01076/Downloads/marc_smile_image_videos/marc_smile_enhanced.png'
+            image_path = '/home/user/app/images/marc_smile_enhanced.jpg'
             source_image = Image.open(image_path)
             text_prompt = request.form['text_prompt']