Hybrid Search #653
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Hybrid Search #653
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yuhongsun96
commented
Oct 30, 2023
| @@ -615,7 +612,7 @@ def keyword_retrieval( | |||
| "query": final_query, | |||
| "input.query(decay_factor)": str(DOC_TIME_DECAY * decay_multiplier), | |||
| "hits": num_to_retrieve, | |||
| "num_to_rerank": 10 * num_to_retrieve, | |||
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This was never doing anything :/
yuhongsun96
commented
Oct 30, 2023
| @@ -640,7 +637,6 @@ def semantic_retrieval( | |||
| # needed for highlighting while the N-gram highlighting is broken / | |||
| # not working as desired | |||
| + f'or ({{defaultIndex: "{CONTENT_SUMMARY}"}}userInput(@query)))' | |||
| + _build_vespa_limit(num_to_retrieve) | |||
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As far as testing shows, adding it to yql vs parameters is the same, feels easier/cleaner to just have it in the params
yuhongsun96
commented
Oct 30, 2023
| ) | ||
|
|
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| params: dict[str, str | int] = { | ||
| "yql": yql, | ||
| "query": query, | ||
| "hits": num_to_retrieve, | ||
| "num_to_rerank": 10 * num_to_retrieve, | ||
| "offset": 0, |
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Set all these as 0 just so we remember later how to do it if we decide to introduce pagination
yuhongsun96
commented
Oct 30, 2023
| @@ -21,7 +21,9 @@ | |||
| DOC_EMBEDDING_DIM = 384 | |||
| # Model should be chosen with 512 context size, ideally don't change this | |||
| DOC_EMBEDDING_CONTEXT_SIZE = 512 | |||
| NORMALIZE_EMBEDDINGS = (os.environ.get("SKIP_RERANKING") or "False").lower() == "true" | |||
Weves
approved these changes
Oct 30, 2023
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