patch for pormpter folder saving

app.py

@@ -2,6 +2,7 @@ import streamlit as st
 from topics import TopicModelling
 import mdforest
 import utils
+import os
 
 st.title("Drop the first document")
 file1 = st.file_uploader("Upload a file", type=["md", "txt"], key="first")
@@ -14,6 +15,9 @@ results = {}
 embedder = utils.load_model()
 nlp = utils.load_nlp()
 
+if not os.path.exists("./prompter/"):
+    os.mkdir("./prompter/")
+
 if file1 is not None and file2 is not None:
     
     input_text1 = file1.read().decode("utf-8")

utils.py

@@ -133,8 +133,8 @@ def generate_insights(topics:dict, name1:str, name2:str, text1:str, text2:str, c
 		# print(cluster_id, " ", sentences)
 		final_prompt = PROMPT.replace("{{sentences}}", "\n".join(sentences))
 	
-		with open(f"prompter/insights_{cluster_id}.prompt", "w") as f:
-			f.write(final_prompt)
+		# with open(f"prompter/insights_{cluster_id}.prompt", "w") as f:
+		# 	f.write(final_prompt)
      
 		# Generate insights for each cluster
 		response = openai.Completion.create(
@@ -157,8 +157,8 @@ def generate_insights(topics:dict, name1:str, name2:str, text1:str, text2:str, c
 		# print(description)
 		# final_insights.append({"name": name_of_insight, "description": description})
 		
-		with open(f"prompter/insights_{cluster_id}.prompt", "a") as f:
-			f.write(text)
+		# with open(f"prompter/insights_{cluster_id}.prompt", "a") as f:
+		# 	f.write(text)
    
 		final_insights.append(text)
 	return final_insights