diff --git a/src/blackbox/chroma_query.py b/src/blackbox/chroma_query.py
index c936bf3..449b317 100755
--- a/src/blackbox/chroma_query.py
+++ b/src/blackbox/chroma_query.py
@@ -22,11 +22,12 @@ class ChromaQuery(Blackbox):
     def __init__(self, *args, **kwargs) -> None:
         # config = read_yaml(args[0])
         # load chromadb and embedding model
-        self.embedding_model_1 = embedding_functions.SentenceTransformerEmbeddingFunction(model_name="/home/gpu/Workspace/Models/BAAI/bge-large-zh-v1.5", device = "cuda:0")
-        self.embedding_model_2 = embedding_functions.SentenceTransformerEmbeddingFunction(model_name="/home/gpu/Workspace/Models/BAAI/bge-small-en-v1.5", device = "cuda:0")
-        self.client_1 = chromadb.HttpClient(host='10.6.81.119', port=7000)
+        self.embedding_model_1 = embedding_functions.SentenceTransformerEmbeddingFunction(model_name="/home/administrator/Workspace/Models/BAAI/bge-large-zh-v1.5", device = "cuda:0")
+        self.embedding_model_2 = embedding_functions.SentenceTransformerEmbeddingFunction(model_name="/home/administrator/Workspace/Models/BAAI/bge-small-en-v1.5", device = "cuda:0")
+        self.embedding_model_3 = embedding_functions.SentenceTransformerEmbeddingFunction(model_name="/home/administrator/Workspace/Models/BAAI/bge-m3", device = "cuda:0")
+        self.client_1 = chromadb.HttpClient(host='172.16.4.7', port=7000)
         # self.client_2 = chromadb.HttpClient(host='10.6.82.192', port=8000)
-        self.reranker_model_1 = CrossEncoder("/home/gpu/Workspace/Models/BAAI/bge-reranker-v2-m3", max_length=512, device = "cuda")
+        self.reranker_model_1 = CrossEncoder("/home/administrator/Workspace/Models/BAAI/bge-reranker-v2-m3", max_length=512, device = "cuda")
 
     def __call__(self, *args, **kwargs):
         return self.processing(*args, **kwargs)
@@ -56,10 +57,10 @@ class ChromaQuery(Blackbox):
             return JSONResponse(content={"error": "question is required"}, status_code=status.HTTP_400_BAD_REQUEST)
 
         if chroma_embedding_model is None or chroma_embedding_model.isspace() or chroma_embedding_model == "":
-            chroma_embedding_model = "/home/gpu/Workspace/Models/BAAI/bge-large-zh-v1.5"
+            chroma_embedding_model = "/home/administrator/Workspace/Models/BAAI/bge-large-zh-v1.5"
 
         if chroma_host is None or chroma_host.isspace() or chroma_host == "":
-            chroma_host = "10.6.81.119"
+            chroma_host = "172.16.4.7"
         
         if chroma_port is None or chroma_port.isspace() or chroma_port == "":
             chroma_port = "7000"
@@ -71,7 +72,7 @@ class ChromaQuery(Blackbox):
             chroma_n_results = 10
 
         # load client and embedding model from init
-        if re.search(r"10.6.81.119", chroma_host) and re.search(r"7000", chroma_port):
+        if re.search(r"172.16.4.7", chroma_host) and re.search(r"7000", chroma_port):
             client = self.client_1
         else:
             try:
@@ -79,10 +80,12 @@ class ChromaQuery(Blackbox):
             except:
                 return JSONResponse(content={"error": "chroma client not found"}, status_code=status.HTTP_400_BAD_REQUEST)
 
-        if re.search(r"/home/gpu/Workspace/Models/BAAI/bge-large-zh-v1.5", chroma_embedding_model):
+        if re.search(r"/home/administrator/Workspace/Models/BAAI/bge-large-zh-v1.5", chroma_embedding_model):
             embedding_model = self.embedding_model_1
-        elif re.search(r"/home/gpu/Workspace/Models/BAAI/bge-small-en-v1.5", chroma_embedding_model):
+        elif re.search(r"/home/administrator/Workspace/Models/BAAI/bge-small-en-v1.5", chroma_embedding_model):
             embedding_model = self.embedding_model_2
+        elif re.search(r"/home/administrator/Workspace/Models/BAAI/bge-m3", chroma_embedding_model):
+            embedding_model = self.embedding_model_3
         else:
             try:
                 embedding_model = embedding_functions.SentenceTransformerEmbeddingFunction(model_name=chroma_embedding_model, device = "cuda:0")
@@ -120,8 +123,8 @@ class ChromaQuery(Blackbox):
         final_result =  str(results["documents"])
 
         if chroma_reranker_model:
-            if re.search(r"/home/gpu/Workspace/Models/BAAI/bge-reranker-v2-m3", chroma_embedding_model):
-                reranker_model = self.chroma_reranker_model_1
+            if re.search(r"/home/administrator/Workspace/Models/BAAI/bge-reranker-v2-m3", chroma_reranker_model):
+                reranker_model = self.reranker_model_1
             else:
                 try:
                     reranker_model = CrossEncoder(chroma_reranker_model, max_length=512, device = "cuda")