diff --git a/pilot/configs/model_config.py b/pilot/configs/model_config.py
index 1238d1bcb..675c51b66 100644
--- a/pilot/configs/model_config.py
+++ b/pilot/configs/model_config.py
@@ -4,34 +4,34 @@
 import torch
 import os
 
-root_path = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-model_path = os.path.join(root_path, "models")
-vector_storepath = os.path.join(root_path, "vector_store")
-LOGDIR = os.path.join(root_path, "logs")
+ROOT_PATH = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+MODEL_PATH = os.path.join(ROOT_PATH, "models")
+VECTORE_PATH = os.path.join(ROOT_PATH, "vector_store")
+LOGDIR = os.path.join(ROOT_PATH, "logs")
 
 
 DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
-llm_model_config = {
-    "flan-t5-base": os.path.join(model_path, "flan-t5-base"),
-    "vicuna-13b": os.path.join(model_path, "vicuna-13b"),
-    "sentence-transforms": os.path.join(model_path, "all-MiniLM-L6-v2")
+LLM_MODEL_CONFIG = {
+    "flan-t5-base": os.path.join(MODEL_PATH, "flan-t5-base"),
+    "vicuna-13b": os.path.join(MODEL_PATH, "vicuna-13b"),
+    "sentence-transforms": os.path.join(MODEL_PATH, "all-MiniLM-L6-v2")
 }
 
 
 LLM_MODEL = "vicuna-13b"
 LIMIT_MODEL_CONCURRENCY = 5
 MAX_POSITION_EMBEDDINGS = 2048
-vicuna_model_server = "http://192.168.31.114:8000"
+VICUNA_MODEL_SERVER = "http://192.168.31.114:8000"
 
 
 # Load model config
-isload_8bit = True
-isdebug = False
+ISLOAD_8BIT = True
+ISDEBUG = False
 
 
 DB_SETTINGS = {
     "user": "root",
-    "password": "********",
+    "password": "aa123456",
     "host": "localhost",
     "port": 3306
 }
\ No newline at end of file
diff --git a/pilot/model/vicuna_llm.py b/pilot/model/vicuna_llm.py
index 26673344f..eba2834ae 100644
--- a/pilot/model/vicuna_llm.py
+++ b/pilot/model/vicuna_llm.py
@@ -25,7 +25,7 @@ class VicunaRequestLLM(LLM):
             "stop": stop
         }
         response = requests.post(
-            url=urljoin(vicuna_model_server, self.vicuna_generate_path),
+            url=urljoin(VICUNA_MODEL_SERVER, self.vicuna_generate_path),
             data=json.dumps(params),
         )
         response.raise_for_status()
@@ -55,7 +55,7 @@ class VicunaEmbeddingLLM(BaseModel, Embeddings):
         print("Sending prompt ", p)
 
         response = requests.post(
-            url=urljoin(vicuna_model_server, self.vicuna_embedding_path),
+            url=urljoin(VICUNA_MODEL_SERVER, self.vicuna_embedding_path),
             json={
                 "prompt": p
             }
diff --git a/pilot/server/webserver.py b/pilot/server/webserver.py
index c13a5331f..4468082d8 100644
--- a/pilot/server/webserver.py
+++ b/pilot/server/webserver.py
@@ -14,7 +14,7 @@ from pilot.configs.model_config import DB_SETTINGS
 from pilot.connections.mysql_conn import MySQLOperator
 
 
-from pilot.configs.model_config import LOGDIR, vicuna_model_server, LLM_MODEL
+from pilot.configs.model_config import LOGDIR, VICUNA_MODEL_SERVER, LLM_MODEL
 
 from pilot.conversation import (
     default_conversation,
@@ -181,7 +181,7 @@ def http_bot(state, db_selector, temperature, max_new_tokens, request: gr.Reques
 
     try:
         # Stream output
-        response = requests.post(urljoin(vicuna_model_server, "generate_stream"),
+        response = requests.post(urljoin(VICUNA_MODEL_SERVER, "generate_stream"),
             headers=headers, json=payload, stream=True, timeout=20)
         for chunk in response.iter_lines(decode_unicode=False, delimiter=b"\0"):
             if chunk: