Vector stores cannot be used outside of Assistants.
You can set the chunk size and overlap yourself when creating. You can set the number of chunk results to return, default 20.
Then it not really RAG, it is a search function. The search is a 256 dimension 3-large embeddings search with the query the AI wrote. There is no similarity threshold, just max chunk count.
Typical search return is larger than the AI can return. You can ask a typical question, or ask for a specific search query sent to myfiles_browser, and then ask for a short report from which you can infer where in the documents the results came from.
This may be more obfuscated if you didn’t provide plain text, like the OpenAI API yaml specification of 1MB in this case, where I asked how to make speech. The actual assistant may be less helpful in dumping out the knowledge without some prompt engineering.