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@@ -6,11 +6,12 @@ from flask import Flask, current_app
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from core.rag.data_post_processor.data_post_processor import DataPostProcessor
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from core.rag.data_post_processor.data_post_processor import DataPostProcessor
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from core.rag.datasource.keyword.keyword_factory import Keyword
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from core.rag.datasource.keyword.keyword_factory import Keyword
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from core.rag.datasource.vdb.vector_factory import Vector
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from core.rag.datasource.vdb.vector_factory import Vector
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+from core.rag.retrieval.retrival_methods import RetrievalMethod
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from extensions.ext_database import db
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from extensions.ext_database import db
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from models.dataset import Dataset
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from models.dataset import Dataset
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default_retrieval_model = {
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default_retrieval_model = {
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- 'search_method': 'semantic_search',
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+ 'search_method': RetrievalMethod.SEMANTIC_SEARCH,
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'reranking_enable': False,
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'reranking_enable': False,
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'reranking_model': {
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'reranking_model': {
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'reranking_provider_name': '',
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'reranking_provider_name': '',
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@@ -47,7 +48,7 @@ class RetrievalService:
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threads.append(keyword_thread)
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threads.append(keyword_thread)
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keyword_thread.start()
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keyword_thread.start()
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# retrieval_model source with semantic
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# retrieval_model source with semantic
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- if retrival_method == 'semantic_search' or retrival_method == 'hybrid_search':
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+ if RetrievalMethod.is_support_semantic_search(retrival_method):
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embedding_thread = threading.Thread(target=RetrievalService.embedding_search, kwargs={
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embedding_thread = threading.Thread(target=RetrievalService.embedding_search, kwargs={
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'flask_app': current_app._get_current_object(),
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'flask_app': current_app._get_current_object(),
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'dataset_id': dataset_id,
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'dataset_id': dataset_id,
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@@ -63,7 +64,7 @@ class RetrievalService:
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embedding_thread.start()
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embedding_thread.start()
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# retrieval source with full text
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# retrieval source with full text
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- if retrival_method == 'full_text_search' or retrival_method == 'hybrid_search':
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+ if RetrievalMethod.is_support_fulltext_search(retrival_method):
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full_text_index_thread = threading.Thread(target=RetrievalService.full_text_index_search, kwargs={
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full_text_index_thread = threading.Thread(target=RetrievalService.full_text_index_search, kwargs={
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'flask_app': current_app._get_current_object(),
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'flask_app': current_app._get_current_object(),
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'dataset_id': dataset_id,
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'dataset_id': dataset_id,
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@@ -85,7 +86,7 @@ class RetrievalService:
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exception_message = ';\n'.join(exceptions)
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exception_message = ';\n'.join(exceptions)
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raise Exception(exception_message)
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raise Exception(exception_message)
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- if retrival_method == 'hybrid_search':
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+ if retrival_method == RetrievalMethod.HYBRID_SEARCH:
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data_post_processor = DataPostProcessor(str(dataset.tenant_id), reranking_model, False)
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data_post_processor = DataPostProcessor(str(dataset.tenant_id), reranking_model, False)
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all_documents = data_post_processor.invoke(
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all_documents = data_post_processor.invoke(
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query=query,
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query=query,
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@@ -141,7 +142,7 @@ class RetrievalService:
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)
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)
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if documents:
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if documents:
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- if reranking_model and retrival_method == 'semantic_search':
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+ if reranking_model and retrival_method == RetrievalMethod.SEMANTIC_SEARCH:
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data_post_processor = DataPostProcessor(str(dataset.tenant_id), reranking_model, False)
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data_post_processor = DataPostProcessor(str(dataset.tenant_id), reranking_model, False)
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all_documents.extend(data_post_processor.invoke(
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all_documents.extend(data_post_processor.invoke(
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query=query,
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query=query,
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@@ -173,7 +174,7 @@ class RetrievalService:
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top_k=top_k
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top_k=top_k
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)
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)
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if documents:
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if documents:
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- if reranking_model and retrival_method == 'full_text_search':
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+ if reranking_model and retrival_method == RetrievalMethod.FULL_TEXT_SEARCH:
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data_post_processor = DataPostProcessor(str(dataset.tenant_id), reranking_model, False)
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data_post_processor = DataPostProcessor(str(dataset.tenant_id), reranking_model, False)
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all_documents.extend(data_post_processor.invoke(
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all_documents.extend(data_post_processor.invoke(
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query=query,
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query=query,
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