delete async function because its confusing

src/chatbot_csv.py

@@ -13,8 +13,7 @@ def init():
     load_dotenv()
     st.set_page_config(layout="wide", page_icon="💬", page_title="ChatBot-CSV")
 
-
-async def main():
+def main():
 
     init()
     layout, sidebar, utils = Layout(), Sidebar(), Utilities()
@@ -34,7 +33,7 @@ async def main():
 
 
             try:
-                chatbot = await utils.setup_chatbot(
+                chatbot = utils.setup_chatbot(
                     uploaded_file, st.session_state["model"], st.session_state["temperature"]
                 )
                 st.session_state["chatbot"] = chatbot
@@ -51,7 +50,7 @@ async def main():
 
                         if is_ready:
                             history.append("user", user_input)
-                            output = await st.session_state["chatbot"].conversational_chat(user_input)
+                            output = st.session_state["chatbot"].conversational_chat(user_input)
                             history.append("assistant", output)
 
                     history.generate_messages(response_container)
@@ -66,6 +65,4 @@ async def main():
     sidebar.about()
 
 if __name__ == "__main__":
-    if "page" not in st.session_state:
-        st.session_state.page = "main"
-    asyncio.run(main())
+    main()

src/csv_agent.py

@@ -13,7 +13,5 @@ def extra_chatbot_page():
         if agent :
             st.write(agent.run(query))
 
-if __name__ == "__main__":
-    extra_chatbot_page()
 
 

src/modules/chatbot.py

@@ -29,7 +29,7 @@ class Chatbot:
         self.temperature = temperature
         self.vectors = vectors
 
-    async def conversational_chat(self, query):
+    def conversational_chat(self, query):
         """
         Starts a conversational chat with a model via Langchain
         """

src/modules/embedder.py

@@ -18,7 +18,7 @@ class Embedder:
         if not os.path.exists(self.PATH):
             os.mkdir(self.PATH)
 
-    async def storeDocEmbeds(self, file, filename):
+    def storeDocEmbeds(self, file, filename):
         """
         Stores document embeddings using Langchain and FAISS
         """
@@ -42,14 +42,14 @@ class Embedder:
         with open(f"{self.PATH}/{filename}.pkl", "wb") as f:
             pickle.dump(vectors, f)
 
-    async def getDocEmbeds(self, file, filename):
+    def getDocEmbeds(self, file, filename):
         """
         Retrieves document embeddings
         """
         # Check if embeddings vectors have already been stored in a pickle file
         if not os.path.isfile(f"{self.PATH}/{filename}.pkl"):
             # If not, store the vectors using the storeDocEmbeds function
-            await self.storeDocEmbeds(file, filename)
+            self.storeDocEmbeds(file, filename)
 
         # Load the vectors from the pickle file
         with open(f"{self.PATH}/{filename}.pkl", "rb") as f:

src/modules/utils.py

@@ -48,7 +48,7 @@ class Utilities:
         return uploaded_file
 
     @staticmethod
-    async def setup_chatbot(uploaded_file, model, temperature):
+    def setup_chatbot(uploaded_file, model, temperature):
         """
         Sets up the chatbot with the uploaded file, model, and temperature
         """
@@ -56,7 +56,7 @@ class Utilities:
         with st.spinner("Processing..."):
             uploaded_file.seek(0)
             file = uploaded_file.read()
-            vectors = await embeds.getDocEmbeds(file, uploaded_file.name)
+            vectors = embeds.getDocEmbeds(file, uploaded_file.name)
             chatbot = Chatbot(model, temperature, vectors)
         st.session_state["ready"] = True
         return chatbot