Adding embeddings results #47
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ganler
reviewed
Jun 12, 2024
repoqa/provider/embeddings/openai.py
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| from typing import List, Tuple | ||
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| from openai import Client | ||
| from sklearn.metrics.pairwise import cosine_similarity |
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sklearn is a bit huge. ideally we want some lighter dependencies (avoiding the risk of dep conflicts in the future) or just impl the function ourselves.
repoqa/search_needle_function.py
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| @@ -374,6 +385,8 @@ def evaluate_model( | |||
| eval_ignore_comments: bool = False, # ignore comments during score computation | |||
| trust_remote_code: bool = False, | |||
| attn_implementation=None, | |||
| is_embedding: bool = False, | |||
| embedding_context_chunk_size: int = 30 | |||
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is this # of chunks or # tokens for each chunk? better make it more explicit :)
also i think specifying the size /#token of each chunk might be more intuitive
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Currently it's lines of code per chunk, will change the variable name
…arn for cosine similarity
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