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Make getting deduped search results configurable via Search API
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parent
b6cdc5c7cb
commit
672f61529e
2 changed files with 14 additions and 7 deletions
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@ -60,6 +60,7 @@ def search(
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t: Optional[SearchType] = None,
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r: Optional[bool] = False,
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score_threshold: Optional[float | None] = None,
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dedupe: Optional[bool] = True,
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):
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results: List[SearchResponse] = []
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if q is None or q == "":
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@ -72,7 +73,7 @@ def search(
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score_threshold = score_threshold if score_threshold is not None else -math.inf
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# return cached results, if available
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query_cache_key = f"{user_query}-{n}-{t}-{r}-{score_threshold}"
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query_cache_key = f"{user_query}-{n}-{t}-{r}-{score_threshold}-{dedupe}"
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if query_cache_key in state.query_cache:
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logger.debug(f"Return response from query cache")
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return state.query_cache[query_cache_key]
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@ -81,7 +82,7 @@ def search(
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# query org-mode notes
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with timer("Query took", logger):
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hits, entries = text_search.query(
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user_query, state.model.orgmode_search, rank_results=r, score_threshold=score_threshold
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user_query, state.model.orgmode_search, rank_results=r, score_threshold=score_threshold, dedupe=dedupe
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)
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# collate and return results
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@ -92,7 +93,7 @@ def search(
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# query markdown files
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with timer("Query took", logger):
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hits, entries = text_search.query(
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user_query, state.model.markdown_search, rank_results=r, score_threshold=score_threshold
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user_query, state.model.markdown_search, rank_results=r, score_threshold=score_threshold, dedupe=dedupe
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)
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# collate and return results
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@ -103,7 +104,7 @@ def search(
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# query transactions
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with timer("Query took", logger):
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hits, entries = text_search.query(
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user_query, state.model.ledger_search, rank_results=r, score_threshold=score_threshold
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user_query, state.model.ledger_search, rank_results=r, score_threshold=score_threshold, dedupe=dedupe
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)
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# collate and return results
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@ -114,7 +115,7 @@ def search(
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# query music library
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with timer("Query took", logger):
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hits, entries = text_search.query(
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user_query, state.model.music_search, rank_results=r, score_threshold=score_threshold
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user_query, state.model.music_search, rank_results=r, score_threshold=score_threshold, dedupe=dedupe
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)
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# collate and return results
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@ -148,6 +149,7 @@ def search(
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state.model.plugin_search.get(t.value) or next(iter(state.model.plugin_search.values())),
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rank_results=r,
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score_threshold=score_threshold,
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dedupe=dedupe,
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)
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# collate and return results
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@ -101,7 +101,11 @@ def compute_embeddings(
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def query(
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raw_query: str, model: TextSearchModel, rank_results: bool = False, score_threshold: float = -math.inf
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raw_query: str,
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model: TextSearchModel,
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rank_results: bool = False,
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score_threshold: float = -math.inf,
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dedupe: bool = True,
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) -> Tuple[List[dict], List[Entry]]:
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"Search for entries that answer the query"
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query, entries, corpus_embeddings = raw_query, model.entries, model.corpus_embeddings
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@ -139,7 +143,8 @@ def query(
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hits = sort_results(rank_results, hits)
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# Deduplicate entries by raw entry text before showing to users
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hits = deduplicate_results(entries, hits)
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if dedupe:
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hits = deduplicate_results(entries, hits)
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return hits, entries
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