diff --git a/ai_functions.py b/ai_functions.py
index 21f33f5..39fd294 100644
--- a/ai_functions.py
+++ b/ai_functions.py
@@ -41,8 +41,6 @@ try:
 except ImportError:  # pragma: no cover - optional at runtime
     anthropic = None
 
-# this do per user
-VECTOR_STORE_ID = -1
 
 
 # *=========================================== AI provider abstraction
@@ -410,58 +408,6 @@ async def openai_call(messages, model, temperature=0.2):
         )
 
 
-def create_vector_store():
-    # Create a vector store caled "Financial Statements"
-    return OPENAICLIENT.beta.vector_stores.create_and_poll(name="Hammer Stash")
-    # expires_after={
-    # "anchor": "last_active_at",
-    # "days": 7}
-    # )
-
-
-def upload_files_to_vector_store(assistant):
-
-    # Ready the files for upload to OpenAI
-    file_paths = ["edgar/goog-10k.pdf", "edgar/brka-10k.txt"]
-    file_streams = [open(path, "rb") for path in file_paths]
-
-    # file = client.beta.vector_stores.files.create_and_poll(
-    # vector_store_id="vs_abc123",
-    # file_id="file-abc123"
-    # )
-    # batch = client.beta.vector_stores.file_batches.create_and_poll(
-    # vector_store_id="vs_abc123",
-    # file_ids=['file_1', 'file_2', 'file_3', 'file_4', 'file_5']
-    # )
-
-    # Use the upload and poll SDK helper to upload the files, add them to the vector store,
-    # and poll the status of the file batch for completion.
-    file_batch = OPENAICLIENT.beta.vector_stores.file_batches.upload_and_poll(
-        vector_store_id=VECTOR_STORE_ID, files=file_streams
-    )
-
-    # You can print the status and the file counts of the batch to see the result of this operation.
-    print(file_batch.status)
-    print(file_batch.file_counts)
-    assistant = OPENAICLIENT.beta.assistants.update(
-        assistant_id=assistant.id,
-        tool_resources={"file_search": {"vector_store_ids": [VECTOR_STORE_ID]}},
-    )
-
-
-def delete_files_from_vector_store(assistant, file_id):
-    result = OPENAICLIENT.beta.vector_stores.file_batches.delete(
-        vector_store_id=VECTOR_STORE_ID, files=file_id
-    )
-
-    # You can print the status and the file counts of the batch to see the result of this operation.
-    print(result)
-    assistant = OPENAICLIENT.beta.assistants.update(
-        assistant_id=assistant.id,
-        tool_resources={"file_search": {"vector_store_ids": [VECTOR_STORE_ID]}},
-    )
-
-
 def num_tokens_from_string(message, model):
     """
     The function takes a string message and a model as input and returns the number of tokens in the