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⚡️ Speed up method VectorIndexAutoRetriever.agenerate_retrieval_spec by 684% #136

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⚡️ Speed up method VectorIndexAutoRetriever.agenerate_retrieval_spec by 684% #136

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12 changes: 7 additions & 5 deletions ...ex-core/llama_index/core/indices/vector_store/retrievers/auto_retriever/auto_retriever.py
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Original file line number Diff line number Diff line change
Expand Up @@ -120,13 +120,18 @@ def __init__(
raise ValueError("extra_filters cannot be OR condition")
self._extra_filters = extra_filters or MetadataFilters(filters=[])
self._kwargs = kwargs

super().__init__(
callback_manager=callback_manager,
object_map=object_map or self._index._object_map,
objects=objects,
verbose=verbose,
)

# Cache expensive serialization operations
self._info_str = self._vector_store_info.json(indent=4)
self._schema_str = VectorStoreQuerySpec.schema_json(indent=4)

def _get_prompts(self) -> PromptDictType:
"""Get prompts."""
return {
Expand Down Expand Up @@ -188,15 +193,12 @@ def generate_retrieval_spec(
async def agenerate_retrieval_spec(
self, query_bundle: QueryBundle, **kwargs: Any
) -> BaseModel:
# prepare input
info_str = self._vector_store_info.json(indent=4)
schema_str = VectorStoreQuerySpec.schema_json(indent=4)

# call LLM
output = await self._llm.apredict(
self._prompt,
schema_str=schema_str,
info_str=info_str,
schema_str=self._schema_str,
info_str=self._info_str,
query_str=query_bundle.query_str,
)

Expand Down