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Feat elasticsearch japanese (#12194)
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api/core/rag/datasource/vdb/elasticsearch/elasticsearch_ja_vector.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,104 @@ | ||
| import json | ||
| import logging | ||
| from typing import Any, Optional | ||
|
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| from flask import current_app | ||
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| from core.rag.datasource.vdb.elasticsearch.elasticsearch_vector import ( | ||
| ElasticSearchConfig, | ||
| ElasticSearchVector, | ||
| ElasticSearchVectorFactory, | ||
| ) | ||
| from core.rag.datasource.vdb.field import Field | ||
| from core.rag.datasource.vdb.vector_type import VectorType | ||
| from core.rag.embedding.embedding_base import Embeddings | ||
| from extensions.ext_redis import redis_client | ||
| from models.dataset import Dataset | ||
|
|
||
| logger = logging.getLogger(__name__) | ||
|
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| class ElasticSearchJaVector(ElasticSearchVector): | ||
| def create_collection( | ||
| self, | ||
| embeddings: list[list[float]], | ||
| metadatas: Optional[list[dict[Any, Any]]] = None, | ||
| index_params: Optional[dict] = None, | ||
| ): | ||
| lock_name = f"vector_indexing_lock_{self._collection_name}" | ||
| with redis_client.lock(lock_name, timeout=20): | ||
| collection_exist_cache_key = f"vector_indexing_{self._collection_name}" | ||
| if redis_client.get(collection_exist_cache_key): | ||
| logger.info(f"Collection {self._collection_name} already exists.") | ||
| return | ||
|
|
||
| if not self._client.indices.exists(index=self._collection_name): | ||
| dim = len(embeddings[0]) | ||
| settings = { | ||
| "analysis": { | ||
| "analyzer": { | ||
| "ja_analyzer": { | ||
| "type": "custom", | ||
| "char_filter": [ | ||
| "icu_normalizer", | ||
| "kuromoji_iteration_mark", | ||
| ], | ||
| "tokenizer": "kuromoji_tokenizer", | ||
| "filter": [ | ||
| "kuromoji_baseform", | ||
| "kuromoji_part_of_speech", | ||
| "ja_stop", | ||
| "kuromoji_number", | ||
| "kuromoji_stemmer", | ||
| ], | ||
| } | ||
| } | ||
| } | ||
| } | ||
| mappings = { | ||
| "properties": { | ||
| Field.CONTENT_KEY.value: { | ||
| "type": "text", | ||
| "analyzer": "ja_analyzer", | ||
| "search_analyzer": "ja_analyzer", | ||
| }, | ||
| Field.VECTOR.value: { # Make sure the dimension is correct here | ||
| "type": "dense_vector", | ||
| "dims": dim, | ||
| "index": True, | ||
| "similarity": "cosine", | ||
| }, | ||
| Field.METADATA_KEY.value: { | ||
| "type": "object", | ||
| "properties": { | ||
| "doc_id": {"type": "keyword"} # Map doc_id to keyword type | ||
| }, | ||
| }, | ||
| } | ||
| } | ||
| self._client.indices.create(index=self._collection_name, settings=settings, mappings=mappings) | ||
|
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| redis_client.set(collection_exist_cache_key, 1, ex=3600) | ||
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| class ElasticSearchJaVectorFactory(ElasticSearchVectorFactory): | ||
| def init_vector(self, dataset: Dataset, attributes: list, embeddings: Embeddings) -> ElasticSearchJaVector: | ||
| if dataset.index_struct_dict: | ||
| class_prefix: str = dataset.index_struct_dict["vector_store"]["class_prefix"] | ||
| collection_name = class_prefix | ||
| else: | ||
| dataset_id = dataset.id | ||
| collection_name = Dataset.gen_collection_name_by_id(dataset_id) | ||
| dataset.index_struct = json.dumps(self.gen_index_struct_dict(VectorType.ELASTICSEARCH, collection_name)) | ||
|
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| config = current_app.config | ||
| return ElasticSearchJaVector( | ||
| index_name=collection_name, | ||
| config=ElasticSearchConfig( | ||
| host=config.get("ELASTICSEARCH_HOST", "localhost"), | ||
| port=config.get("ELASTICSEARCH_PORT", 9200), | ||
| username=config.get("ELASTICSEARCH_USERNAME", ""), | ||
| password=config.get("ELASTICSEARCH_PASSWORD", ""), | ||
| ), | ||
| attributes=[], | ||
| ) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,25 @@ | ||
| #!/bin/bash | ||
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| set -e | ||
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| if [ "${VECTOR_STORE}" = "elasticsearch-ja" ]; then | ||
| # Check if the ICU tokenizer plugin is installed | ||
| if ! /usr/share/elasticsearch/bin/elasticsearch-plugin list | grep -q analysis-icu; then | ||
| printf '%s\n' "Installing the ICU tokenizer plugin" | ||
| if ! /usr/share/elasticsearch/bin/elasticsearch-plugin install analysis-icu; then | ||
| printf '%s\n' "Failed to install the ICU tokenizer plugin" | ||
| exit 1 | ||
| fi | ||
| fi | ||
| # Check if the Japanese language analyzer plugin is installed | ||
| if ! /usr/share/elasticsearch/bin/elasticsearch-plugin list | grep -q analysis-kuromoji; then | ||
| printf '%s\n' "Installing the Japanese language analyzer plugin" | ||
| if ! /usr/share/elasticsearch/bin/elasticsearch-plugin install analysis-kuromoji; then | ||
| printf '%s\n' "Failed to install the Japanese language analyzer plugin" | ||
| exit 1 | ||
| fi | ||
| fi | ||
| fi | ||
|
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| # Run the original entrypoint script | ||
| exec /bin/tini -- /usr/local/bin/docker-entrypoint.sh |