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# What does this PR do? Context: https://github.com/meta-llama/llama-stack/issues/2937 The API design is inspired by existing offerings, but not exactly the same: * `top_n` as the parameter to control number of results, instead of `top_k`, since `n` is conventional to control number * `truncation` bool instead of `max_token_per_doc`, since we should just handle the truncation automatically depending on model capability, instead of user setting the context length manually. * `data` field in the response, to be consistent with other OpenAI APIs (though they don't have a rerank API). Also, it is one less name to learn in the API. ## Test Plan Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com> |
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| .. | ||
| agents | ||
| batch_inference | ||
| batches | ||
| benchmarks | ||
| common | ||
| datasetio | ||
| datasets | ||
| eval | ||
| files | ||
| inference | ||
| inspect | ||
| models | ||
| post_training | ||
| providers | ||
| safety | ||
| scoring | ||
| scoring_functions | ||
| shields | ||
| synthetic_data_generation | ||
| telemetry | ||
| tools | ||
| vector_dbs | ||
| vector_io | ||
| __init__.py | ||
| datatypes.py | ||
| resource.py | ||
| version.py | ||