feat: generate for 0.2

package.json

@@ -15,7 +15,8 @@
     "release:patch:all": "npm run release:python patch && npm run release:ts patch",
     "release:minor:all": "npm run release:python minor && npm run release:ts minor",
     "release:major:all": "npm run release:python major && npm run release:ts major",
-    "download-spec":  "curl -fs -o ./vectorize_api.json http://localhost:3000/api/openapi"
+    "download-spec":  "curl -fs -o ./vectorize_api.json https://platform.vectorize.io/api/openapi",
+    "download-spec:dev":  "curl -fs -o ./vectorize_api.json http://localhost:3000/api/openapi"
   },
   "author": "",
   "license": "ISC",

src/python/vectorize_client/__init__.py

@@ -41,6 +41,7 @@
 from vectorize_client.models.ai_platform_type import AIPlatformType
 from vectorize_client.models.add_user_from_source_connector_response import AddUserFromSourceConnectorResponse
 from vectorize_client.models.add_user_to_source_connector_request import AddUserToSourceConnectorRequest
+from vectorize_client.models.add_user_to_source_connector_request_selected_files_value import AddUserToSourceConnectorRequestSelectedFilesValue
 from vectorize_client.models.create_ai_platform_connector import CreateAIPlatformConnector
 from vectorize_client.models.create_ai_platform_connector_response import CreateAIPlatformConnectorResponse
 from vectorize_client.models.create_destination_connector import CreateDestinationConnector
@@ -76,6 +77,8 @@
 from vectorize_client.models.get_pipelines_response import GetPipelinesResponse
 from vectorize_client.models.get_source_connectors200_response import GetSourceConnectors200Response
 from vectorize_client.models.get_upload_files_response import GetUploadFilesResponse
+from vectorize_client.models.metadata_extraction_strategy import MetadataExtractionStrategy
+from vectorize_client.models.metadata_extraction_strategy_schema import MetadataExtractionStrategySchema
 from vectorize_client.models.n8_n_config import N8NConfig
 from vectorize_client.models.pipeline_configuration_schema import PipelineConfigurationSchema
 from vectorize_client.models.pipeline_events import PipelineEvents

src/python/vectorize_client/models/__init__.py

@@ -20,6 +20,7 @@
 from vectorize_client.models.ai_platform_type import AIPlatformType
 from vectorize_client.models.add_user_from_source_connector_response import AddUserFromSourceConnectorResponse
 from vectorize_client.models.add_user_to_source_connector_request import AddUserToSourceConnectorRequest
+from vectorize_client.models.add_user_to_source_connector_request_selected_files_value import AddUserToSourceConnectorRequestSelectedFilesValue
 from vectorize_client.models.create_ai_platform_connector import CreateAIPlatformConnector
 from vectorize_client.models.create_ai_platform_connector_response import CreateAIPlatformConnectorResponse
 from vectorize_client.models.create_destination_connector import CreateDestinationConnector
@@ -55,6 +56,8 @@
 from vectorize_client.models.get_pipelines_response import GetPipelinesResponse
 from vectorize_client.models.get_source_connectors200_response import GetSourceConnectors200Response
 from vectorize_client.models.get_upload_files_response import GetUploadFilesResponse
+from vectorize_client.models.metadata_extraction_strategy import MetadataExtractionStrategy
+from vectorize_client.models.metadata_extraction_strategy_schema import MetadataExtractionStrategySchema
 from vectorize_client.models.n8_n_config import N8NConfig
 from vectorize_client.models.pipeline_configuration_schema import PipelineConfigurationSchema
 from vectorize_client.models.pipeline_events import PipelineEvents

src/python/vectorize_client/models/add_user_to_source_connector_request.py

@@ -18,7 +18,8 @@
 import json
 
 from pydantic import BaseModel, ConfigDict, Field, StrictStr
-from typing import Any, ClassVar, Dict, List, Optional
+from typing import Any, ClassVar, Dict, List
+from vectorize_client.models.add_user_to_source_connector_request_selected_files_value import AddUserToSourceConnectorRequestSelectedFilesValue
 from typing import Optional, Set
 from typing_extensions import Self
 
@@ -27,9 +28,9 @@ class AddUserToSourceConnectorRequest(BaseModel):
     AddUserToSourceConnectorRequest
     """ # noqa: E501
     user_id: StrictStr = Field(alias="userId")
-    file_ids: Optional[List[StrictStr]] = Field(default=None, alias="fileIds")
+    selected_files: Dict[str, AddUserToSourceConnectorRequestSelectedFilesValue] = Field(alias="selectedFiles")
     refresh_token: StrictStr = Field(alias="refreshToken")
-    __properties: ClassVar[List[str]] = ["userId", "fileIds", "refreshToken"]
+    __properties: ClassVar[List[str]] = ["userId", "selectedFiles", "refreshToken"]
 
     model_config = ConfigDict(
         populate_by_name=True,
@@ -70,6 +71,13 @@ def to_dict(self) -> Dict[str, Any]:
             exclude=excluded_fields,
             exclude_none=True,
         )
+        # override the default output from pydantic by calling `to_dict()` of each value in selected_files (dict)
+        _field_dict = {}
+        if self.selected_files:
+            for _key_selected_files in self.selected_files:
+                if self.selected_files[_key_selected_files]:
+                    _field_dict[_key_selected_files] = self.selected_files[_key_selected_files].to_dict()
+            _dict['selectedFiles'] = _field_dict
         return _dict
 
     @classmethod
@@ -83,7 +91,12 @@ def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
 
         _obj = cls.model_validate({
             "userId": obj.get("userId"),
-            "fileIds": obj.get("fileIds"),
+            "selectedFiles": dict(
+                (_k, AddUserToSourceConnectorRequestSelectedFilesValue.from_dict(_v))
+                for _k, _v in obj["selectedFiles"].items()
+            )
+            if obj.get("selectedFiles") is not None
+            else None,
             "refreshToken": obj.get("refreshToken")
         })
         return _obj

src/python/vectorize_client/models/add_user_to_source_connector_request_selected_files_value.py

@@ -0,0 +1,89 @@
+# coding: utf-8
+
+"""
+    Vectorize API (Beta)
+
+    API for Vectorize services
+
+    The version of the OpenAPI document: 0.0.1
+    Generated by OpenAPI Generator (https://openapi-generator.tech)
+
+    Do not edit the class manually.
+"""  # noqa: E501
+
+
+from __future__ import annotations
+import pprint
+import re  # noqa: F401
+import json
+
+from pydantic import BaseModel, ConfigDict, Field, StrictStr
+from typing import Any, ClassVar, Dict, List
+from typing import Optional, Set
+from typing_extensions import Self
+
+class AddUserToSourceConnectorRequestSelectedFilesValue(BaseModel):
+    """
+    AddUserToSourceConnectorRequestSelectedFilesValue
+    """ # noqa: E501
+    name: StrictStr
+    mime_type: StrictStr = Field(alias="mimeType")
+    __properties: ClassVar[List[str]] = ["name", "mimeType"]
+
+    model_config = ConfigDict(
+        populate_by_name=True,
+        validate_assignment=True,
+        protected_namespaces=(),
+    )
+
+
+    def to_str(self) -> str:
+        """Returns the string representation of the model using alias"""
+        return pprint.pformat(self.model_dump(by_alias=True))
+
+    def to_json(self) -> str:
+        """Returns the JSON representation of the model using alias"""
+        # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
+        return json.dumps(self.to_dict())
+
+    @classmethod
+    def from_json(cls, json_str: str) -> Optional[Self]:
+        """Create an instance of AddUserToSourceConnectorRequestSelectedFilesValue from a JSON string"""
+        return cls.from_dict(json.loads(json_str))
+
+    def to_dict(self) -> Dict[str, Any]:
+        """Return the dictionary representation of the model using alias.
+
+        This has the following differences from calling pydantic's
+        `self.model_dump(by_alias=True)`:
+
+        * `None` is only added to the output dict for nullable fields that
+          were set at model initialization. Other fields with value `None`
+          are ignored.
+        """
+        excluded_fields: Set[str] = set([
+        ])
+
+        _dict = self.model_dump(
+            by_alias=True,
+            exclude=excluded_fields,
+            exclude_none=True,
+        )
+        return _dict
+
+    @classmethod
+    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
+        """Create an instance of AddUserToSourceConnectorRequestSelectedFilesValue from a dict"""
+        if obj is None:
+            return None
+
+        if not isinstance(obj, dict):
+            return cls.model_validate(obj)
+
+        _obj = cls.model_validate({
+            "name": obj.get("name"),
+            "mimeType": obj.get("mimeType")
+        })
+        return _obj
+
+

src/python/vectorize_client/models/destination_connector_type.py

@@ -34,6 +34,7 @@ class DestinationConnectorType(str, Enum):
     MILVUS = 'MILVUS'
     POSTGRESQL = 'POSTGRESQL'
     QDRANT = 'QDRANT'
+    SUPABASE = 'SUPABASE'
     WEAVIATE = 'WEAVIATE'
     AZUREAISEARCH = 'AZUREAISEARCH'
     VECTORIZE = 'VECTORIZE'

src/python/vectorize_client/models/extraction_result.py

@@ -17,7 +17,7 @@
 import re  # noqa: F401
 import json
 
-from pydantic import BaseModel, ConfigDict, StrictBool, StrictStr
+from pydantic import BaseModel, ConfigDict, Field, StrictBool, StrictStr
 from typing import Any, ClassVar, Dict, List, Optional
 from typing import Optional, Set
 from typing_extensions import Self
@@ -29,8 +29,12 @@ class ExtractionResult(BaseModel):
     success: StrictBool
     chunks: Optional[List[StrictStr]] = None
     text: Optional[StrictStr] = None
+    metadata: Optional[StrictStr] = None
+    metadata_schema: Optional[StrictStr] = Field(default=None, alias="metadataSchema")
+    chunks_metadata: Optional[List[StrictStr]] = Field(default=None, alias="chunksMetadata")
+    chunks_schema: Optional[List[StrictStr]] = Field(default=None, alias="chunksSchema")
     error: Optional[StrictStr] = None
-    __properties: ClassVar[List[str]] = ["success", "chunks", "text", "error"]
+    __properties: ClassVar[List[str]] = ["success", "chunks", "text", "metadata", "metadataSchema", "chunksMetadata", "chunksSchema", "error"]
 
     model_config = ConfigDict(
         populate_by_name=True,
@@ -86,6 +90,10 @@ def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
             "success": obj.get("success"),
             "chunks": obj.get("chunks"),
             "text": obj.get("text"),
+            "metadata": obj.get("metadata"),
+            "metadataSchema": obj.get("metadataSchema"),
+            "chunksMetadata": obj.get("chunksMetadata"),
+            "chunksSchema": obj.get("chunksSchema"),
             "error": obj.get("error")
         })
         return _obj

src/python/vectorize_client/models/metadata_extraction_strategy.py

@@ -0,0 +1,97 @@
+# coding: utf-8
+
+"""
+    Vectorize API (Beta)
+
+    API for Vectorize services
+
+    The version of the OpenAPI document: 0.0.1
+    Generated by OpenAPI Generator (https://openapi-generator.tech)
+
+    Do not edit the class manually.
+"""  # noqa: E501
+
+
+from __future__ import annotations
+import pprint
+import re  # noqa: F401
+import json
+
+from pydantic import BaseModel, ConfigDict, Field, StrictBool
+from typing import Any, ClassVar, Dict, List, Optional
+from vectorize_client.models.metadata_extraction_strategy_schema import MetadataExtractionStrategySchema
+from typing import Optional, Set
+from typing_extensions import Self
+
+class MetadataExtractionStrategy(BaseModel):
+    """
+    MetadataExtractionStrategy
+    """ # noqa: E501
+    schemas: Optional[List[MetadataExtractionStrategySchema]] = None
+    infer_schema: Optional[StrictBool] = Field(default=None, alias="inferSchema")
+    __properties: ClassVar[List[str]] = ["schemas", "inferSchema"]
+
+    model_config = ConfigDict(
+        populate_by_name=True,
+        validate_assignment=True,
+        protected_namespaces=(),
+    )
+
+
+    def to_str(self) -> str:
+        """Returns the string representation of the model using alias"""
+        return pprint.pformat(self.model_dump(by_alias=True))
+
+    def to_json(self) -> str:
+        """Returns the JSON representation of the model using alias"""
+        # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
+        return json.dumps(self.to_dict())
+
+    @classmethod
+    def from_json(cls, json_str: str) -> Optional[Self]:
+        """Create an instance of MetadataExtractionStrategy from a JSON string"""
+        return cls.from_dict(json.loads(json_str))
+
+    def to_dict(self) -> Dict[str, Any]:
+        """Return the dictionary representation of the model using alias.
+
+        This has the following differences from calling pydantic's
+        `self.model_dump(by_alias=True)`:
+
+        * `None` is only added to the output dict for nullable fields that
+          were set at model initialization. Other fields with value `None`
+          are ignored.
+        """
+        excluded_fields: Set[str] = set([
+        ])
+
+        _dict = self.model_dump(
+            by_alias=True,
+            exclude=excluded_fields,
+            exclude_none=True,
+        )
+        # override the default output from pydantic by calling `to_dict()` of each item in schemas (list)
+        _items = []
+        if self.schemas:
+            for _item_schemas in self.schemas:
+                if _item_schemas:
+                    _items.append(_item_schemas.to_dict())
+            _dict['schemas'] = _items
+        return _dict
+
+    @classmethod
+    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
+        """Create an instance of MetadataExtractionStrategy from a dict"""
+        if obj is None:
+            return None
+
+        if not isinstance(obj, dict):
+            return cls.model_validate(obj)
+
+        _obj = cls.model_validate({
+            "schemas": [MetadataExtractionStrategySchema.from_dict(_item) for _item in obj["schemas"]] if obj.get("schemas") is not None else None,
+            "inferSchema": obj.get("inferSchema")
+        })
+        return _obj
+
+