Update app.py

app.py

@@ -16,7 +16,7 @@ os.environ["OPENAI_API_KEY"] = os.environ['SECRET_CODE']
 DATASET_REPO_URL = "https://huggingface.co/datasets/peterpull/MediatorBot"
 DATA_FILENAME = "data.txt"
 INDEX_FILENAME = "index.json"
-DATA_FILE = os.path.join("data", DATA_FILENAME)
+DATA_FILEP = os.path.join("data", DATA_FILENAME)
 INDEX_FILE = os.path.join("data", INDEX_FILENAME)
 
 # we need a write access token.
@@ -50,17 +50,9 @@ def store_message(chatinput: str, chatresponse: str):
             file.write(f"{datetime.now()},{chatinput},{chatresponse}\n")
             print(f"Wrote to datafile: {datetime.now()},{chatinput},{chatresponse}\n")
 
-        # Push back to hub every 10th time the function is called
-    if store_message.count_calls % 10 == 0:
-        print("Pushing back to Hugging Face model hub")
-        # Call the push_to_hub() function to push the changes to the hub
-        push_to_hub(commit_message="Added new chat data")
-    store_message.count_calls += 1
     
     return generate_text()
 
-store_message.count_calls = 1  #initiases the count at one. We want to count how many messages stored before pushing back to repo.
-
 #gets the index file which is the context data
 def get_index(index_file_path):
     if os.path.exists(index_file_path):
@@ -72,7 +64,7 @@ def get_index(index_file_path):
         sys.exit()
 
 index = get_index(INDEX_FILE)
-
+        
 # passes the prompt to the chatbot
 def chatbot(input_text, mentioned_person='Mediator John Haynes', confidence_threshold=0.5):
     prompt = f"You are {mentioned_person}. Answer this: {input_text}. Only reply from the contextual data, or say you don't know. At the end of your answer ask an insightful question."