Clean code

app.py

@@ -75,12 +75,11 @@ repo_name = gr.State()
 git_tickets = gr.State()
 git_titles = gr.State()
 git_ticket_choices = gr.State()
+vector_db_url = gr.State()
 git_tickets.value = []
 git_titles.value = []
 git_ticket_choices.value = []
 
-# repoName = "https://github.com/gradio-app/gradio.git"
-
 embeddings = OpenAIEmbeddings(disallowed_special=())
 
 def git_clone(repo_url):
@@ -179,6 +178,8 @@ def index_repo(textbox: str, dropdown: str) -> Response:
             stdout="",
         )
 
+    vector_db_url.value = dataset_path
+
     return {
         success_response: "SUCCESS",
         launch_product: gr.update(visible=True)
@@ -194,7 +195,7 @@ def answer_questions(question: str, github: str, **kwargs) -> Response:
     try:
         embeddings = OpenAIEmbeddings(disallowed_special=())
         pathName = github.split('/')[-1]
-        dataset_path = "hub://aiswaryas/" + pathName
+        dataset_path = vector_db_url.value
 
         print("before reading repo")
         db = DeepLake(dataset_path=dataset_path, read_only=True, embedding_function=embeddings)
@@ -321,7 +322,7 @@ def generateDocumentationPerFolder(dir, github):
     try:
         embeddings = OpenAIEmbeddings(disallowed_special=())
         pathName = github.split('/')[-1]
-        dataset_path = "hub://aiswaryas/" + pathName
+        dataset_path = vector_db_url.value
 
         db = DeepLake(dataset_path=dataset_path, read_only=True, embedding_function=embeddings)
 
@@ -371,7 +372,7 @@ def solveGithubIssue(ticket, history) -> Response:
     try:
         embeddings = OpenAIEmbeddings(disallowed_special=())
         pathName = github.split('/')[-1]
-        dataset_path = "hub://aiswaryas/" + pathName
+        dataset_path = vector_db_url.value
 
         db = DeepLake(dataset_path=dataset_path, read_only=True, embedding=embeddings)
 
@@ -423,7 +424,7 @@ def bot(history, **kwargs):
     try:
         embeddings = OpenAIEmbeddings(disallowed_special=())
         pathName = github.split('/')[-1]
-        dataset_path = "hub://aiswaryas/" + pathName
+        dataset_path = vector_db_url.value
 
         db = DeepLake(dataset_path=dataset_path, read_only=True, embedding_function=embeddings)
         retriever = db.as_retriever()