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https://github.com/meilisearch/MeiliSearch
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Create a new _vector extractor
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Cargo.lock
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1
Cargo.lock
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@ -2683,6 +2683,7 @@ dependencies = [
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"bimap",
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"bimap",
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"bincode",
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"bincode",
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"bstr",
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"bstr",
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"bytemuck",
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"byteorder",
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"byteorder",
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"charabia",
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"charabia",
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"concat-arrays",
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"concat-arrays",
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@ -15,6 +15,7 @@ license.workspace = true
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bimap = { version = "0.6.3", features = ["serde"] }
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bimap = { version = "0.6.3", features = ["serde"] }
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bincode = "1.3.3"
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bincode = "1.3.3"
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bstr = "1.4.0"
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bstr = "1.4.0"
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bytemuck = "1.13.1"
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byteorder = "1.4.3"
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byteorder = "1.4.3"
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charabia = { version = "0.7.2", default-features = false }
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charabia = { version = "0.7.2", default-features = false }
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concat-arrays = "0.1.2"
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concat-arrays = "0.1.2"
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@ -0,0 +1,40 @@
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use std::fs::File;
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use std::io;
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use bytemuck::cast_slice;
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use serde_json::from_slice;
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use super::helpers::{create_writer, writer_into_reader, GrenadParameters};
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use crate::{FieldId, InternalError, Result};
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/// Extracts the embedding vector contained in each document under the `_vector` field.
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///
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/// Returns the generated grenad reader containing the docid as key associated to the Vec<f32>
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#[logging_timer::time]
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pub fn extract_vector_points<R: io::Read + io::Seek>(
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obkv_documents: grenad::Reader<R>,
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indexer: GrenadParameters,
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vector_fid: FieldId,
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) -> Result<grenad::Reader<File>> {
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let mut writer = create_writer(
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indexer.chunk_compression_type,
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indexer.chunk_compression_level,
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tempfile::tempfile()?,
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);
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let mut cursor = obkv_documents.into_cursor()?;
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while let Some((docid_bytes, value)) = cursor.move_on_next()? {
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let obkv = obkv::KvReader::new(value);
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// first we get the _vector field
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if let Some(vector) = obkv.get(vector_fid) {
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// try to extract the vector
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let vector: Vec<f32> = from_slice(vector).map_err(InternalError::SerdeJson).unwrap();
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let bytes = cast_slice(&vector);
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writer.insert(docid_bytes, bytes)?;
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}
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// else => the _vector object was `null`, there is nothing to do
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}
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writer_into_reader(writer)
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}
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@ -4,6 +4,7 @@ mod extract_facet_string_docids;
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mod extract_fid_docid_facet_values;
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mod extract_fid_docid_facet_values;
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mod extract_fid_word_count_docids;
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mod extract_fid_word_count_docids;
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mod extract_geo_points;
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mod extract_geo_points;
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mod extract_vector_points;
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mod extract_word_docids;
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mod extract_word_docids;
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mod extract_word_fid_docids;
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mod extract_word_fid_docids;
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mod extract_word_pair_proximity_docids;
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mod extract_word_pair_proximity_docids;
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@ -22,6 +23,7 @@ use self::extract_facet_string_docids::extract_facet_string_docids;
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use self::extract_fid_docid_facet_values::{extract_fid_docid_facet_values, ExtractedFacetValues};
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use self::extract_fid_docid_facet_values::{extract_fid_docid_facet_values, ExtractedFacetValues};
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use self::extract_fid_word_count_docids::extract_fid_word_count_docids;
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use self::extract_fid_word_count_docids::extract_fid_word_count_docids;
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use self::extract_geo_points::extract_geo_points;
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use self::extract_geo_points::extract_geo_points;
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use self::extract_vector_points::extract_vector_points;
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use self::extract_word_docids::extract_word_docids;
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use self::extract_word_docids::extract_word_docids;
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use self::extract_word_fid_docids::extract_word_fid_docids;
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use self::extract_word_fid_docids::extract_word_fid_docids;
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use self::extract_word_pair_proximity_docids::extract_word_pair_proximity_docids;
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use self::extract_word_pair_proximity_docids::extract_word_pair_proximity_docids;
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