Update app.py

app.py

@@ -13,23 +13,25 @@ root_path = os.path.abspath(current_file_path)
 class RepoSearch:
     def __init__(self):
 
-        # db_path = os.path.join(root_path, "database", "faiss_index")
-        
+        db_path = os.path.join(root_path, "database", "faiss_index")
+        print(db_path)
         # db_path = root_path
-        # embeddings = OpenAIEmbeddings(api_key="sk-Mo5K9m2hKXjV1DeGeBAIzXLZFxxiOTvSwUoemKmfMXdmE9Bs", 
-        #                       base_url="https://api.wlai.vip/v1",
-        #                       model="text-embedding-3-small")
+        embeddings = OpenAIEmbeddings(api_key="sk-Mo5K9m2hKXjV1DeGeBAIzXLZFxxiOTvSwUoemKmfMXdmE9Bs", 
+                              base_url="https://api.wlai.vip/v1",
+                              model="text-embedding-3-small")
+        print("embeddings already")
         
-        # assert os.path.exists(db_path), f"Database not found: {db_path}"
-        # self.vector_db = FAISS.load_local(db_path, embeddings, 
-        #                                   allow_dangerous_deserialization=True)
-        pass
+        assert os.path.exists(db_path), f"Database not found: {db_path}"
+        self.vector_db = FAISS.load_local(db_path, embeddings, 
+                                          allow_dangerous_deserialization=True)
+        print("vector_db already")
+        # pass
         
     def search(self, query, k=10):
         '''
             name + description + html_url + topics
         '''
-        return "sss"
+        # return "sss"
         results = self.vector_db.similarity_search(query + " technology", k=k)
 
         simple_str = ""