fix(client): remove invalid min_items=1 on str __root__ fields (#813)

QueryItem and SearchQueryItem declare `__root__: Annotated[str, Field(..., min_items=1)]`.
`min_items` applies to list/sequence length; on a str field, pydantic v1 compat
raises ValueError at class-definition time:

  ValueError: On field '__root__' the following field constraints are set but not enforced: min_items

This breaks any consumer that imports llmengine.data_types.gen.openai under
pydantic v2 with v1 compat (e.g. egp-api-backend).

Drop the meaningless constraint. Bump to 0.0.0.beta47.

Note: gen/openai.py is generated from the OpenAPI schema via
datamodel-code-generator. Follow-up needed to fix the source schema so this
doesn't regress on next regen.

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

Author: scale-ballen

clients/python/llmengine/data_types/gen/openai.py

@@ -6875,7 +6875,7 @@ class VectorStoreObject(BaseModel):
 
 
 class QueryItem(BaseModel):
-    __root__: Annotated[str, Field(description="A list of queries to search for.", min_items=1)]
+    __root__: Annotated[str, Field(description="A list of queries to search for.")]
 
 
 class RankingOptions(BaseModel):
@@ -6937,7 +6937,7 @@ class Config:
 
 
 class SearchQueryItem(BaseModel):
-    __root__: Annotated[str, Field(description="The query used for this search.", min_items=1)]
+    __root__: Annotated[str, Field(description="The query used for this search.")]
 
 
 class VectorStoreSearchResultsPage(BaseModel):

clients/python/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "scale-llm-engine"
-version = "0.0.0.beta46"
+version = "0.0.0.beta47"
 description = "Scale LLM Engine Python client"
 license = "Apache-2.0"
 authors = ["Phil Chen <phil.chen@scale.com>"]