readme, bugfixes, dedup

cogs/search_service_cog.py

@@ -140,6 +140,9 @@ class SearchService(discord.Cog, name="SearchService"):
         )
         urls = "\n".join(f"<{url}>" for url in urls)
 
+        # Deduplicate the urls
+        urls = "\n".join(dict.fromkeys(urls.split("\n")))
+
         if from_followup:
             original_link, followup_question = (
                 from_followup.original_link,

detailed_guides/AI-SEARCH.md

@@ -7,4 +7,6 @@ GOOGLE_SEARCH_ENGINE_ID="...."
   
 You first need to create a programmable search engine and get the search engine ID: https://developers.google.com/custom-search/docs/tutorial/creatingcse  
   
-Then you can get the API key, click the "Get a key" button on this page: https://developers.google.com/custom-search/v1/introduction  
+Then you can get the API key, click the "Get a key" button on this page: https://developers.google.com/custom-search/v1/introduction  
+
+You can limit the max price that is charged for a single search request by setting `MAX_SEARCH_PRICE` in your `.env` file.

detailed_guides/CUSTOM-INDEXES.md

@@ -16,4 +16,4 @@ You can also compose a singular index with itself with "Deep Compose", this will
 
 Doing a deep composition will also allow you to use the `child_branch_factor` parameter for `/index query`, increasing this past 1 will take a much longer time to query and will be much more expensive for large documents, so be wary.
 
-**When doing Deep Compositions, it's highly reccomended to keep the document size small, or only do deep compositions on single documents.** This is because a deep composition reorganizes the simple index into a tree structure and uses GPT3 to summarize different nodes of the tree, which will lead to high costs. For example, a deep composition of a 300 page lab manual and the contents of my personal website at https://kaveenk.com cost me $2 USD roughly.
+**When doing Deep Compositions, it's highly recommended to keep the document size small, or only do deep compositions on single documents.** This is because a deep composition reorganizes the simple index into a tree structure and uses GPT3 to summarize different nodes of the tree, which will lead to high costs. For example, a deep composition of a 300 page lab manual and the contents of my personal website at https://kaveenk.com cost me $2 USD roughly. To save on costs, you can limit the max price a deep composition can charge you by setting `MAX_DEEP_COMPOSE_PRICE` in your `.env` file.

models/index_model.py

@@ -596,7 +596,7 @@ class Index_handler:
                 )
 
             # Save the composed index
-            tree_index.save_to_disk(f"indexes/{user_id}/{name}.json")
+            tree_index.save_to_disk(f"indexes/{user_id}/{name}")
 
             self.index_storage[user_id].queryable_index = tree_index
         else:
@@ -624,7 +624,7 @@ class Index_handler:
                 name = f"composed_index_{date.today().month}_{date.today().day}.json"
 
             # Save the composed index
-            simple_index.save_to_disk(f"indexes/{user_id}/{name}.json")
+            simple_index.save_to_disk(f"indexes/{user_id}/{name}")
             self.index_storage[user_id].queryable_index = simple_index
 
     async def backup_discord(

sample.env

@@ -45,3 +45,9 @@ FORCE_ENGLISH = "False"
 
 # The welcome message to send it the welcome setting is set to true
 WELCOME_MESSAGE = "Hi There! Welcome to our Discord server. We hope you'll enjoy our server and we look forward to engaging with you!"  # This is a fallback message if gpt3 fails to generate a welcome message.
+
+# Max price to pay for a single search request
+MAX_SEARCH_PRICE = 1.00
+
+# Max price to pay for a deep composition
+MAX_DEEP_COMPOSE_PRICE = 3.00