Hi, everyone!
I’m having trouble creating a vector store using the OpenAI REST API. According to the documentation, the /v1/files
endpoint only accepts .jsonl
files for upload, especially when working with fine-tuning. However, when I try to create a vector store using the /v1/vector_stores
endpoint, I get an error if I include .jsonl
files, stating that this format is not supported for retrieval.
Here’s the error response:
{
"error": {
"message": "Files with extensions [.jsonl] are not supported for retrieval. See https://platform.openai.com/docs/assistants/tools/file-search#supported-files",
"type": "invalid_request_error",
"param": "file_ids",
"code": "unsupported_file"
}
}
In the documentation, examples using the Python SDK suggest that it’s possible to use formats like PDF and TXT to create a vector store. Here’s a snippet of the provided example:
python
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# Python SDK Example
vector_store = client.beta.vector_stores.create(name="Financial Statements")
file_paths = ["edgar/goog-10k.pdf", "edgar/brka-10k.txt"]
file_streams = [open(path, "rb") for path in file_paths]
file_batch = client.beta.vector_stores.file_batches.upload_and_poll(
vector_store_id=vector_store.id, files=file_streams
)
I’d like to know how to achieve this same process using the REST API (without relying on the SDK).
- What is the correct way to create a vector store with supported file formats like PDF, CSV, or TXT?
- Is there a specific endpoint or configuration required to make this work?
Thank you in advance for your help!