test: type the eager_input_streaming test helpers and mark constants Final

tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_transformation.py

@@ -6372,18 +6372,19 @@ def test_response_format_tool_path_skips_forced_tool_choice_when_unsupported(loc
     assert "tool_choice" not in result
 
 
-def _eager_chat_tool(**extra):
+def _eager_chat_function(**extra: object) -> dict[str, object]:
     return {
-        "type": "function",
-        "function": {
-            "name": "write_file",
-            "description": "Write a file",
-            "parameters": {"type": "object", "properties": {"path": {"type": "string"}}, "required": ["path"]},
-        },
+        "name": "write_file",
+        "description": "Write a file",
+        "parameters": {"type": "object", "properties": {"path": {"type": "string"}}, "required": ["path"]},
         **extra,
     }
 
 
+def _eager_chat_tool(**extra: object) -> dict[str, object]:
+    return {"type": "function", "function": _eager_chat_function(), **extra}
+
+
 @pytest.mark.parametrize("flag", [True, False])
 def test_eager_input_streaming_passed_through_from_tool_top_level(flag):
     mapped_tool, _ = AnthropicConfig()._map_tool_helper(_eager_chat_tool(eager_input_streaming=flag))
@@ -6398,10 +6399,9 @@ def test_eager_input_streaming_passed_through_from_tool_top_level(flag):
 
 
 def test_eager_input_streaming_passed_through_from_function():
-    tool = _eager_chat_tool()
-    tool["function"]["eager_input_streaming"] = True
-
-    mapped_tool, _ = AnthropicConfig()._map_tool_helper(tool)
+    mapped_tool, _ = AnthropicConfig()._map_tool_helper(
+        {"type": "function", "function": _eager_chat_function(eager_input_streaming=True)}
+    )
 
     assert mapped_tool["eager_input_streaming"] is True
     assert "eager_input_streaming" not in mapped_tool["input_schema"]

tests/test_litellm/llms/bedrock/chat/invoke_transformations/test_bedrock_chat_invoke_transformations_anthropic_claude3_transformation.py

@@ -1,6 +1,7 @@
 import asyncio
 import json
 import uuid
+from typing import Final
 from unittest.mock import patch
 
 import httpx
@@ -861,14 +862,16 @@ def test_bedrock_chat_invoke_tool_search_beta_follows_model_map(
     assert result.get("anthropic_beta") == expected_betas
 
 
-FINE_GRAINED_TOOL_STREAMING_BETA = "fine-grained-tool-streaming-2025-05-14"
-EAGER_TOOL_SCHEMA = {"type": "object", "properties": {"path": {"type": "string"}}, "required": ["path"]}
+FINE_GRAINED_TOOL_STREAMING_BETA: Final = "fine-grained-tool-streaming-2025-05-14"
+EAGER_TOOL_SCHEMA: Final = {"type": "object", "properties": {"path": {"type": "string"}}, "required": ["path"]}
 
 
-def _chat_invoke_request_with_tools(tools, headers=None):
-    config = AmazonAnthropicClaudeConfig()
-    model = "us.anthropic.claude-sonnet-4-5-20250929-v1:0"
-    optional_params = config.map_openai_params(
+def _chat_invoke_request_with_tools(
+    tools: list[dict[str, object]], headers: dict[str, str] | None = None
+) -> dict[str, object]:
+    config: Final = AmazonAnthropicClaudeConfig()
+    model: Final = "us.anthropic.claude-sonnet-4-5-20250929-v1:0"
+    optional_params: Final = config.map_openai_params(
         non_default_params={"max_tokens": 64, "stream": True, "tools": tools},
         optional_params={},
         model=model,
@@ -883,7 +886,7 @@ def _chat_invoke_request_with_tools(tools, headers=None):
     )
 
 
-def _eager_openai_tool(name, **extra):
+def _eager_openai_tool(name: str, **extra: object) -> dict[str, object]:
     return {"type": "function", "function": {"name": name, "parameters": EAGER_TOOL_SCHEMA}, **extra}
 
 

tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py

@@ -4,6 +4,7 @@ import os
 import httpx
 import pytest
 
+from typing import Final
 from unittest.mock import MagicMock, patch
 
 import litellm
@@ -7402,23 +7403,25 @@ def test_transform_response_honors_json_mode_kwarg_when_optional_params_lack_it(
     assert json.loads(result.choices[0].message.content) == {"city": "Paris", "population": 2100000}
 
 
-FINE_GRAINED_TOOL_STREAMING_BETA = "fine-grained-tool-streaming-2025-05-14"
-EAGER_TOOL_SCHEMA = {"type": "object", "properties": {"path": {"type": "string"}}, "required": ["path"]}
+FINE_GRAINED_TOOL_STREAMING_BETA: Final = "fine-grained-tool-streaming-2025-05-14"
+EAGER_TOOL_SCHEMA: Final = {"type": "object", "properties": {"path": {"type": "string"}}, "required": ["path"]}
 
 
-def _eager_openai_tool(**extra):
+def _eager_openai_tool(**extra: object) -> dict[str, object]:
     return {"type": "function", "function": {"name": "write_file", "parameters": EAGER_TOOL_SCHEMA}, **extra}
 
 
-def _eager_openai_function_tool(**extra):
+def _eager_openai_function_tool(**extra: object) -> dict[str, object]:
     return {"type": "function", "function": {"name": "write_file", "parameters": EAGER_TOOL_SCHEMA, **extra}}
 
 
-def _eager_anthropic_tool(**extra):
+def _eager_anthropic_tool(**extra: object) -> dict[str, object]:
     return {"name": "write_file", "input_schema": EAGER_TOOL_SCHEMA, **extra}
 
 
-def _converse_request(model, tools, headers=None):
+def _converse_request(
+    model: str, tools: list[dict[str, object]], headers: dict[str, object] | None = None
+) -> dict[str, object]:
     return AmazonConverseConfig()._transform_request_helper(
         model=model,
         system_content_blocks=[],

tests/test_litellm/llms/bedrock/messages/invoke_transformations/test_anthropic_claude3_transformation.py

@@ -4,6 +4,7 @@ import json
 import os
 from datetime import datetime
 from types import SimpleNamespace
+from typing import Final
 from unittest.mock import Mock
 
 import pytest
@@ -3246,10 +3247,12 @@ def test_bedrock_messages_strips_effort_but_keeps_format_for_sonnet_4_5(local_mo
     assert result.get("output_config") == {"format": schema_format}
 
 
-FINE_GRAINED_TOOL_STREAMING_BETA = "fine-grained-tool-streaming-2025-05-14"
+FINE_GRAINED_TOOL_STREAMING_BETA: Final = "fine-grained-tool-streaming-2025-05-14"
 
 
-def _invoke_request_with_tools(tools, headers=None):
+def _invoke_request_with_tools(
+    tools: list[dict[str, object]], headers: dict[str, str] | None = None
+) -> dict[str, object]:
     from litellm.types.router import GenericLiteLLMParams
 
     return AmazonAnthropicClaudeMessagesConfig().transform_anthropic_messages_request(
@@ -3261,7 +3264,7 @@ def _invoke_request_with_tools(tools, headers=None):
     )
 
 
-def _eager_invoke_tool(name, eager_input_streaming):
+def _eager_invoke_tool(name: str, eager_input_streaming: bool) -> dict[str, object]:
     return {
         "name": name,
         "description": f"{name} tool",