AI: delete the dead OpenAI vector-store / file_search code

file_search was confirmed unused, and these four functions were its only
implementation: create_vector_store, upload_files_to_vector_store,
add_files_to_vector_store and delete_files_from_vector_store, plus the
VECTOR_STORE_ID constant they were the only readers of.

Nothing called any of them - verified before removing - so they could not
crash anything, but they were the last references to beta.vector_stores and
beta.assistants: a sunset API that already took the whole AI cog down once
when a startup path touched it. Wiring them back up would have hit the same
404. Removing them means no path in this module can reach that API again.

54 lines gone, no behaviour change. Suite: 82 unit + 71 integration green.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

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