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The managed batch listing fetched one page of rows, derived has_more from that raw fetch, then dropped every row whose stored blob would not parse. last_id came from the survivors, so a page of corrupt or legacy rows came back as data [], last_id null, has_more true, and a client following last_id could not advance. The OpenAI SDK's auto-paginator, which cursors off the last item in data, stopped silently and returned a truncated list. Read chunks until page_size + 1 batches survive parsing and file-id resolution or the caller's rows run out, the way the managed file listing already does, so a page carries data and a usable cursor while parseable rows remain and has_more only says true when another one exists. The first chunk keeps the old page_size + 1 size so a healthy page still costs one query; a scan that has to continue widens to the file listing's continuation chunk and stops resolving rows once the page is full. |
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| .. | ||
| cloudformation_stack | ||
| dist | ||
| enterprise_hooks | ||
| enterprise_ui | ||
| litellm_enterprise | ||
| __init__.py | ||
| LICENSE.md | ||
| pyproject.toml | ||
| README.md | ||
LiteLLM Enterprise
Code in this folder is licensed under a commercial license. Please review the LICENSE file within the /enterprise folder
These features are covered under the LiteLLM Enterprise contract
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