forked from phoenix-oss/llama-stack-mirror
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>
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319 changed files with 2843 additions and 3033 deletions
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@ -4,7 +4,7 @@
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from typing import Any, Dict, Optional
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from typing import Any
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from pydantic import BaseModel
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@ -12,10 +12,10 @@ from pydantic import BaseModel
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class WolframAlphaToolConfig(BaseModel):
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"""Configuration for WolframAlpha Tool Runtime"""
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api_key: Optional[str] = None
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api_key: str | None = None
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@classmethod
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def sample_run_config(cls, __distro_dir__: str, **kwargs: Any) -> Dict[str, Any]:
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def sample_run_config(cls, __distro_dir__: str, **kwargs: Any) -> dict[str, Any]:
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return {
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"api_key": "${env.WOLFRAM_ALPHA_API_KEY:}",
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}
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# the root directory of this source tree.
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import json
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from typing import Any, Dict, Optional
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from typing import Any
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import httpx
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@ -50,7 +50,7 @@ class WolframAlphaToolRuntimeImpl(ToolsProtocolPrivate, ToolRuntime, NeedsReques
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return provider_data.wolfram_alpha_api_key
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async def list_runtime_tools(
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self, tool_group_id: Optional[str] = None, mcp_endpoint: Optional[URL] = None
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self, tool_group_id: str | None = None, mcp_endpoint: URL | None = None
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) -> ListToolDefsResponse:
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return ListToolDefsResponse(
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data=[
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@ -68,7 +68,7 @@ class WolframAlphaToolRuntimeImpl(ToolsProtocolPrivate, ToolRuntime, NeedsReques
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]
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)
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async def invoke_tool(self, tool_name: str, kwargs: Dict[str, Any]) -> ToolInvocationResult:
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async def invoke_tool(self, tool_name: str, kwargs: dict[str, Any]) -> ToolInvocationResult:
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api_key = self._get_api_key()
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params = {
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"input": kwargs["query"],
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