try

.idea/workspace.xml

@@ -63,7 +63,7 @@
       <recent name="D:\Development_Web\FullStackVercel\backend\src" />
     </key>
   </component>
-  <component name="RunManager" selected="Python.hf2">
+  <component name="RunManager" selected="Python.hf">
     <configuration name="cth" type="PythonConfigurationType" factoryName="Python" temporary="true" nameIsGenerated="true">
       <module name="backend" />
       <option name="ENV_FILES" value="" />
@@ -132,8 +132,8 @@
     </configuration>
     <recent_temporary>
       <list>
-        <item itemvalue="Python.hf2" />
         <item itemvalue="Python.hf" />
+        <item itemvalue="Python.hf2" />
         <item itemvalue="Python.cth" />
       </list>
     </recent_temporary>

src/hf.py

@@ -4,7 +4,7 @@ from transformers import BertTokenizer, BertForSequenceClassification,TextClassi
 # Load tokenizer and model from the fine-tuned directory
 model_path = './intent_classification/TinyBERT_106_V2'  # can try other checkpoints
 
-tokenizer = BertTokenizer.from_pretrained('KhairulAmirinUM/Advisor_AI_BERT')
+tokenizer = BertTokenizer.from_pretrained(model_path)
 # model = BertForSequenceClassification.from_pretrained(model_path)
 model = AutoModelForSequenceClassification.from_pretrained(model_path, local_files_only=True)
 print(os.path.exists(model_path))
@@ -35,4 +35,8 @@ def generate_response(user_query):
     return topic_label, score
 
 
-print(generate_response("Procedure to withdraw"))
+def get_dir():
+    return os.getcwd()
+
+print(generate_response("Procedure to withdraw"))
+get_dir()

src/main.py

@@ -1,7 +1,9 @@
+import os
+
 import uvicorn
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
-from src.hf import generate_response
+from src.hf import generate_response, get_dir
 
 
 app = FastAPI()
@@ -19,19 +21,24 @@ app.add_middleware(
 
 @app.get("/")
 async def root():
-    return {"message": "Hello World"}
+    current_dir = os.getcwd()
+    return {"message": "Hello World", "dir": current_dir}
 
 @app.get("/book")
 async def root():
     return {"book_name": "Hikayat Naga Terbang"}
 
-@app.post('/classify')
-async def classify_text(question:str):
-    answer = generate_response(question)
-    topic_label, score = answer
-
-    return {"label": topic_label}
-
+# @app.post('/classify')
+# async def classify_text(question:str):
+#     answer = generate_response(question)
+#     topic_label, score = answer
+#
+#     return {"label": topic_label}
+@app.get('/hf-dir')
+def get_hf_dir():
+    return {
+        "hf_dir": get_dir()
+    }
 
 if __name__ == '__main__':
     uvicorn.run("main:app", host="127.0.0.1", port=8000, reload=True)