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feat: extract model runtime

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Signed-off-by: -LAN- <laipz8200@outlook.com>
This commit is contained in:
-LAN-
2026-03-15 15:34:47 +08:00
parent 3d5a29462e
commit fbb74a4af9
178 changed files with 4343 additions and 2134 deletions
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6
api/controllers/console/datasets/datasets.py
View File

@@ -25,7 +25,7 @@ from controllers.console.wraps import (
)
from core.errors.error import LLMBadRequestError, ProviderTokenNotInitError
from core.indexing_runner import IndexingRunner
from core.provider_manager import ProviderManager
from core.plugin.impl.model_runtime_factory import create_plugin_provider_manager
from core.rag.datasource.vdb.vector_type import VectorType
from core.rag.extractor.entity.datasource_type import DatasourceType
from core.rag.extractor.entity.extract_setting import ExtractSetting, NotionInfo, WebsiteInfo
@@ -331,7 +331,7 @@ class DatasetListApi(Resource):
)
# check embedding setting
provider_manager = ProviderManager()
provider_manager = create_plugin_provider_manager(tenant_id=current_tenant_id)
configurations = provider_manager.get_configurations(tenant_id=current_tenant_id)
embedding_models = configurations.get_models(model_type=ModelType.TEXT_EMBEDDING, only_active=True)
@@ -445,7 +445,7 @@ class DatasetApi(Resource):
data.update({"partial_member_list": part_users_list})
# check embedding setting
provider_manager = ProviderManager()
provider_manager = create_plugin_provider_manager(tenant_id=current_tenant_id)
configurations = provider_manager.get_configurations(tenant_id=current_tenant_id)
embedding_models = configurations.get_models(model_type=ModelType.TEXT_EMBEDDING, only_active=True)

2
api/controllers/console/datasets/datasets_document.py
View File

@@ -452,7 +452,7 @@ class DatasetInitApi(Resource):
if knowledge_config.embedding_model is None or knowledge_config.embedding_model_provider is None:
raise ValueError("embedding model and embedding model provider are required for high quality indexing.")
try:
model_manager = ModelManager()
model_manager = ModelManager.for_tenant(tenant_id=current_tenant_id)
model_manager.get_model_instance(
tenant_id=current_tenant_id,
provider=knowledge_config.embedding_model_provider,

8
api/controllers/console/datasets/datasets_segments.py
View File

@@ -282,7 +282,7 @@ class DatasetDocumentSegmentApi(Resource):
if dataset.indexing_technique == "high_quality":
# check embedding model setting
try:
model_manager = ModelManager()
model_manager = ModelManager.for_tenant(tenant_id=current_tenant_id)
model_manager.get_model_instance(
tenant_id=current_tenant_id,
provider=dataset.embedding_model_provider,
@@ -335,7 +335,7 @@ class DatasetDocumentSegmentAddApi(Resource):
# check embedding model setting
if dataset.indexing_technique == "high_quality":
try:
model_manager = ModelManager()
model_manager = ModelManager.for_tenant(tenant_id=current_tenant_id)
model_manager.get_model_instance(
tenant_id=current_tenant_id,
provider=dataset.embedding_model_provider,
@@ -386,7 +386,7 @@ class DatasetDocumentSegmentUpdateApi(Resource):
if dataset.indexing_technique == "high_quality":
# check embedding model setting
try:
model_manager = ModelManager()
model_manager = ModelManager.for_tenant(tenant_id=current_tenant_id)
model_manager.get_model_instance(
tenant_id=current_tenant_id,
provider=dataset.embedding_model_provider,
@@ -571,7 +571,7 @@ class ChildChunkAddApi(Resource):
# check embedding model setting
if dataset.indexing_technique == "high_quality":
try:
model_manager = ModelManager()
model_manager = ModelManager.for_tenant(tenant_id=current_tenant_id)
model_manager.get_model_instance(
tenant_id=current_tenant_id,
provider=dataset.embedding_model_provider,