Fix bug: Prevent multiple user creation with the same email

app.py

@@ -36,16 +36,23 @@ async def sign_up(email, username, password):
     res, _ = supabase.auth.sign_up(
         {"email": email, "password": password, "role": "user"}
     )
-    user_id = res[1].id
-    r_ = createUser(user_id=user_id, username=username)
-    print(r_)
-
-    response = {
-        "status": "success",
-        "code": 200,
-        "message": "Please check you email address for email verification",
-    }
 
+    user_id = res[1].id
+    r_ = createUser(user_id=user_id, username=username, email=email)
+    if r_.get('code') == 409:
+        return r_
+    elif r_.get('code') == 200:
+        response = {
+            "status": "success",
+            "code": 200,
+            "message": "Please check you email address for email verification",
+        }
+    else:
+        response = {
+            "status": "failed",
+            "code": 400,
+            "message": "Failed to sign up please try again later",
+        }
     return response
 
 
@@ -148,6 +155,8 @@ async def login_with_token(access_token: str, refresh_token: str):
         user_id_oauth = decoded_token.get("sub")
         try:
             user_id = supabase.table("ConversAI_UserInfo").select("*").filter("user_id", "eq", user_id_oauth).execute()
+            user_id = supabase.table("ConversAI_UserInfo").select("*").filter("email", "eq", user_id_oauth).execute()
+
             user_name = user_id.data[0]["username"]
 
         except:
@@ -171,8 +180,8 @@ async def login_with_token(access_token: str, refresh_token: str):
 
 
 @app.post("/user_name")
-async def user_name_(username: str, user_id: str):
-    r_ = createUser(user_id=user_id, username=username)
+async def user_name_(username: str, user_id: str, email: str):
+    r_ = createUser(user_id=user_id, username=username, email=email)
     return r_
 
 

functions.py

@@ -73,23 +73,32 @@ prompt = ChatPromptTemplate.from_template(prompt)
 chatHistoryStore = dict()
 
 
-def createUser(user_id: str, username: str) -> dict:
-    try:
-        userData = client.table("ConversAI_UserInfo").select("*").execute().data
-        if username not in [userData[x]["user_id"] for x in range(len(userData))]:
-            client.table("ConversAI_UserInfo").insert({"user_id": user_id, "username": username}).execute()
-            client.table("ConversAI_UserConfig").insert({"user_id": username}).execute()
+def createUser(user_id: str, username: str, email: str) -> dict:
+    userData = client.table("ConversAI_UserInfo").select("*").execute().data
+    if user_id not in [userData[x]["user_id"] for x in range(len(userData))]:
+        try:
+            client.table("ConversAI_UserInfo").insert(
+                {"user_id": user_id, "username": username, "email": email}).execute()
+
+            client.table("ConversAI_UserConfig").insert({"user_id": user_id}).execute()
 
-            return {
-                "output": "SUCCESS"
+            res = {
+                "code": 200,
+                "message": "User Setup Successful"
             }
-        else:
-            return {
-                "output": "USER ALREADY EXISTS"
+
+        except Exception as e:
+            res = {
+                "code": 409,
+                "message": "Email already exists",
             }
-    except Exception as e:
+
+        return res
+
+    else:
         return {
-            "error": e
+            "code": 409,
+            "message": "User already exists"
         }
 
 
@@ -182,10 +191,11 @@ def answerQuery(query: str, vectorstore: str, llmModel: str = "llama3-70b-8192")
         api_key=os.environ["QDRANT_API_KEY"],
         retrieval_mode=RetrievalMode.HYBRID
     )
-    retriever = vectorstore.as_retriever(search_type = "mmr", search_kwargs={"k": 4, "score_threshold": None})
+    retriever = vectorstore.as_retriever(search_type="mmr", search_kwargs={"k": 4, "score_threshold": None})
     baseChain = (
             {"context": RunnableLambda(lambda x: x["question"]) | retriever | RunnableLambda(format_docs),
-             "question": RunnableLambda(lambda x: x["question"]), "chatHistory": RunnableLambda(lambda x: x["chatHistory"])}
+             "question": RunnableLambda(lambda x: x["question"]),
+             "chatHistory": RunnableLambda(lambda x: x["chatHistory"])}
             | prompt
             | ChatGroq(model=llmModel, temperature=0.75, max_tokens=512)
             | StrOutputParser()
@@ -269,6 +279,7 @@ def getTextFromImagePDF(pdfBytes):
     def getText(image):
         global reader
         return "\n".join([text[1] for text in reader.readtext(np.array(image), paragraph=True)])
+
     allImages = convert_from_bytes(pdfBytes)
     texts = [getText(image) for image in allImages]
     return "\n\n\n".join(texts)