chore: enable pyupgrade fixes (#1806)

# What does this PR do?

The goal of this PR is code base modernization.

Schema reflection code needed a minor adjustment to handle UnionTypes
and collections.abc.AsyncIterator. (Both are preferred for latest Python
releases.)

Note to reviewers: almost all changes here are automatically generated
by pyupgrade. Some additional unused imports were cleaned up. The only
change worth of note can be found under `docs/openapi_generator` and
`llama_stack/strong_typing/schema.py` where reflection code was updated
to deal with "newer" types.

Signed-off-by: Ihar Hrachyshka <ihar.hrachyshka@gmail.com>

llama_stack/providers/remote/vector_io/pgvector/__init__.py

@@ -4,14 +4,12 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-from typing import Dict
-
 from llama_stack.providers.datatypes import Api, ProviderSpec
 
 from .config import PGVectorVectorIOConfig
 
 
-async def get_adapter_impl(config: PGVectorVectorIOConfig, deps: Dict[Api, ProviderSpec]):
+async def get_adapter_impl(config: PGVectorVectorIOConfig, deps: dict[Api, ProviderSpec]):
     from .pgvector import PGVectorVectorIOAdapter
 
     impl = PGVectorVectorIOAdapter(config, deps[Api.inference])

llama_stack/providers/remote/vector_io/pgvector/config.py

@@ -4,7 +4,7 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-from typing import Any, Dict
+from typing import Any
 
 from pydantic import BaseModel, Field
 
@@ -28,5 +28,5 @@ class PGVectorVectorIOConfig(BaseModel):
         user: str = "${env.PGVECTOR_USER}",
         password: str = "${env.PGVECTOR_PASSWORD}",
         **kwargs: Any,
-    ) -> Dict[str, Any]:
+    ) -> dict[str, Any]:
         return {"host": host, "port": port, "db": db, "user": user, "password": password}

llama_stack/providers/remote/vector_io/pgvector/pgvector.py

@@ -5,7 +5,7 @@
 # the root directory of this source tree.
 
 import logging
-from typing import Any, Dict, List, Optional, Tuple
+from typing import Any
 
 import psycopg2
 from numpy.typing import NDArray
@@ -33,7 +33,7 @@ def check_extension_version(cur):
     return result[0] if result else None
 
 
-def upsert_models(conn, keys_models: List[Tuple[str, BaseModel]]):
+def upsert_models(conn, keys_models: list[tuple[str, BaseModel]]):
     with conn.cursor(cursor_factory=psycopg2.extras.DictCursor) as cur:
         query = sql.SQL(
             """
@@ -74,7 +74,7 @@ class PGVectorIndex(EmbeddingIndex):
             """
             )
 
-    async def add_chunks(self, chunks: List[Chunk], embeddings: NDArray):
+    async def add_chunks(self, chunks: list[Chunk], embeddings: NDArray):
         assert len(chunks) == len(embeddings), (
             f"Chunk length {len(chunks)} does not match embedding length {len(embeddings)}"
         )
@@ -180,8 +180,8 @@ class PGVectorVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate):
     async def insert_chunks(
         self,
         vector_db_id: str,
-        chunks: List[Chunk],
-        ttl_seconds: Optional[int] = None,
+        chunks: list[Chunk],
+        ttl_seconds: int | None = None,
     ) -> None:
         index = await self._get_and_cache_vector_db_index(vector_db_id)
         await index.insert_chunks(chunks)
@@ -190,7 +190,7 @@ class PGVectorVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate):
         self,
         vector_db_id: str,
         query: InterleavedContent,
-        params: Optional[Dict[str, Any]] = None,
+        params: dict[str, Any] | None = None,
     ) -> QueryChunksResponse:
         index = await self._get_and_cache_vector_db_index(vector_db_id)
         return await index.query_chunks(query, params)