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https://github.com/BerriAI/litellm.git
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fix(type_discipline): satisfy type discipline gate and ruff formatting
This commit is contained in:
Rahul Kumar
parent
065df9d7fb
commit
800b123a1b
3 changed files with 101 additions and 80 deletions
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@ -662,7 +662,9 @@ class AnthropicMessagesHandler(BaseTranslation):
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)
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if not scan_only_tool_results:
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retained_names: Final = frozenset(
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name for t in (data.get("tools") or []) for name in anthropic_tool_names(t)
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name
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for t in (data.get("tools") or ())
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for name in anthropic_tool_names(t) # comprehension-ok: flattens tool names across tools
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)
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self._strip_disallowed_tool_additions(data, retained_names)
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@ -940,55 +942,71 @@ class AnthropicMessagesHandler(BaseTranslation):
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"""Extract every tool name in an Anthropic messages request: tools[].name, plus
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tools[].function.name for OpenAI-format tools the bridge forwards verbatim,
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as well as mid-conversation tool additions in messages."""
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names = [name for tool in list_field(data, "tools") for name in anthropic_tool_names(tool)]
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messages = data.get("messages")
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if isinstance(messages, Sequence):
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for m in messages:
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if isinstance(m, Mapping):
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content = m.get("content")
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if isinstance(content, Sequence) and not isinstance(content, (str, bytes)):
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for block in content:
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if isinstance(block, Mapping) and block.get("type") == "tool_addition":
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tool = extract_tool_from_addition_block(block)
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if tool is not None:
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for name in anthropic_tool_names(tool):
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if name not in names:
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names.append(name)
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return names
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top_names: Final = [ # comprehension-ok: flattens tool names across tools
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name for tool in list_field(data, "tools") for name in anthropic_tool_names(tool)
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]
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messages: Final = data.get("messages")
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if not isinstance(messages, Sequence):
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return top_names
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extra_names: Final[list[str]] = [] # mutable-ok: accumulator
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for m in messages:
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if isinstance(m, Mapping):
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content: Final = m.get("content")
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if isinstance(content, Sequence) and not isinstance(content, (str, bytes)):
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for block in content:
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if isinstance(block, Mapping) and block.get("type") == "tool_addition":
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tool: Final = extract_tool_from_addition_block(block)
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if tool is not None:
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for name in anthropic_tool_names(tool):
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if name not in top_names and name not in extra_names:
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extra_names.append(name)
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return [*top_names, *extra_names]
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@classmethod
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def _strip_disallowed_tool_additions(cls, data: dict, retained_names: frozenset[str]) -> None:
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messages = data.get("messages")
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def _strip_disallowed_tool_additions(cls, data: Mapping[str, object], retained_names: frozenset[str]) -> None:
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messages: Final = data.get("messages")
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if not isinstance(messages, list):
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return
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cleaned_messages: list[object] = []
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cleaned_messages: Final[list[object]] = [] # mutable-ok: accumulator
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for m in messages:
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if not isinstance(m, dict):
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cleaned_messages.append(m)
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continue
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content = m.get("content")
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content: Final = m.get("content")
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if not isinstance(content, list):
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cleaned_messages.append(m)
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continue
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had_disallowed_addition = False
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remaining_blocks: list[object] = []
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for block in content:
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if isinstance(block, dict) and block.get("type") == "tool_addition":
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tool = extract_tool_from_addition_block(block)
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tool_names = anthropic_tool_names(tool) if tool else ()
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if tool_names and all(name in retained_names for name in tool_names):
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remaining_blocks.append(block)
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else:
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had_disallowed_addition = True
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else:
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remaining_blocks.append(block)
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had_disallowed_addition: Final = any(
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isinstance(block, dict)
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and block.get("type") == "tool_addition"
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and (
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not (tool := extract_tool_from_addition_block(block))
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or not (tool_names := anthropic_tool_names(tool))
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or not all(name in retained_names for name in tool_names)
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)
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for block in content
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)
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if not had_disallowed_addition:
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cleaned_messages.append(m)
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continue
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remaining_blocks: Final[list[object]] = [ # mutable-ok: accumulator
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block
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for block in content
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if not (
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isinstance(block, dict)
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and block.get("type") == "tool_addition"
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and (
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not (tool := extract_tool_from_addition_block(block))
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or not (tool_names := anthropic_tool_names(tool))
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or not all(name in retained_names for name in tool_names)
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)
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)
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]
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if remaining_blocks:
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new_m = dict(m)
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new_m: Final[dict[str, object]] = dict(m) # mutable-ok: message clone
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new_m["content"] = remaining_blocks
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cleaned_messages.append(new_m)
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elif not had_disallowed_addition:
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cleaned_messages.append(m)
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data["messages"] = cleaned_messages
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data["messages"] = cleaned_messages # rebind-ok: update request in place
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@classmethod
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def _extract_input_text_and_images(
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@ -1236,73 +1236,78 @@ class LiteLLMAnthropicMessagesAdapter:
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self,
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messages: Sequence[Mapping[str, object] | AllAnthropicPassThroughMessageValues],
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initial_tools: Sequence[AllAnthropicToolsValues] | None = None,
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) -> tuple[list[AllAnthropicToolsValues] | None, list[AllAnthropicPassThroughMessageValues]]:
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) -> tuple[tuple[AllAnthropicToolsValues, ...] | None, tuple[AllAnthropicPassThroughMessageValues, ...]]:
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"""
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Extract and apply mid-conversation tool changes (tool_addition, tool_removal)
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such as those sent by Claude Code under mid-conversation-tool-changes beta.
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Returns:
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Tuple of (active_tools, cleaned_messages)
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- active_tools: Updated tools list with additions applied and removals removed,
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- active_tools: Updated tools tuple with additions applied and removals removed,
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or None if no tools exist and none were added.
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- cleaned_messages: Messages list with tool_addition and tool_removal blocks stripped,
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- cleaned_messages: Messages tuple with tool_addition and tool_removal blocks stripped,
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and carrier messages left without content dropped.
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"""
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active_tools: list[AllAnthropicToolsValues] = list(initial_tools) if initial_tools else []
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had_tool_changes = False
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cleaned_messages: list[AllAnthropicPassThroughMessageValues] = []
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active_tools: tuple[AllAnthropicToolsValues, ...] = tuple(initial_tools or ()) # rebind-ok: tool updates
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had_tool_changes: bool = False # rebind-ok: state flag
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cleaned_messages: Final[list[AllAnthropicPassThroughMessageValues]] = [] # mutable-ok: accumulator
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for m in messages:
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if not isinstance(m, dict):
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cleaned_messages.append(m) # type: ignore[arg-type]
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if not isinstance(m, Mapping):
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cleaned_messages.append(m) # pyright: ignore[reportArgumentType] # non-mapping passthrough
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continue
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content = m.get("content")
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if not isinstance(content, list):
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cleaned_messages.append(cast(AllAnthropicPassThroughMessageValues, m))
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content: Final = m.get("content")
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if not isinstance(content, Sequence) or isinstance(content, (str, bytes)):
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msg_val: Final = cast(AllAnthropicPassThroughMessageValues, m) # cast-ok: msg
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cleaned_messages.append(msg_val)
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continue
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remaining_blocks: list[dict[str, Any]] = []
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remaining_blocks: Final[list[object]] = [] # mutable-ok: accumulator
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for block in content:
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if not isinstance(block, dict):
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if not isinstance(block, Mapping):
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remaining_blocks.append(block)
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continue
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btype = block.get("type")
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btype: Final = block.get("type")
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if btype == "tool_addition":
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had_tool_changes = True
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raw_tool = extract_tool_from_addition_block(block)
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if isinstance(raw_tool, dict) and raw_tool.get("name"):
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tool_name = str(raw_tool["name"])
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if not any(isinstance(t, dict) and t.get("name") == tool_name for t in active_tools):
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active_tools.append(cast(AllAnthropicToolsValues, raw_tool))
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raw_tool: Final = extract_tool_from_addition_block(block)
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if isinstance(raw_tool, Mapping) and raw_tool.get("name"):
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tool_name: Final = str(raw_tool["name"])
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if not any(isinstance(t, Mapping) and t.get("name") == tool_name for t in active_tools):
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added_tool: Final = cast(AllAnthropicToolsValues, dict(raw_tool)) # cast-ok: tool
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active_tools = (*active_tools, added_tool)
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elif btype == "tool_removal":
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had_tool_changes = True
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rem_name = (
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rem_name: Final = (
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block.get("tool_name")
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or block.get("name")
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or (block.get("tool", {}).get("name") if isinstance(block.get("tool"), dict) else None)
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or (block.get("tool", {}).get("name") if isinstance(block.get("tool"), Mapping) else None)
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or (block.get("tool") if isinstance(block.get("tool"), str) else None)
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)
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if rem_name:
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rem_name_str = str(rem_name)
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active_tools = [
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t for t in active_tools if not (isinstance(t, dict) and t.get("name") == rem_name_str)
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]
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rem_name_str: Final = str(rem_name)
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active_tools = tuple(
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t for t in active_tools if not (isinstance(t, Mapping) and t.get("name") == rem_name_str)
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)
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else:
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remaining_blocks.append(block)
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if remaining_blocks:
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new_m = dict(m)
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new_m: Final[dict[str, object]] = dict(m) # mutable-ok: message clone
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new_m["content"] = remaining_blocks
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cleaned_messages.append(cast(AllAnthropicPassThroughMessageValues, new_m))
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new_msg: Final = cast(AllAnthropicPassThroughMessageValues, new_m) # cast-ok: msg
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cleaned_messages.append(new_msg)
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elif not had_tool_changes:
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cleaned_messages.append(cast(AllAnthropicPassThroughMessageValues, m))
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clean_msg: Final = cast(AllAnthropicPassThroughMessageValues, m) # cast-ok: msg
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cleaned_messages.append(clean_msg)
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if not had_tool_changes and initial_tools is None:
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return None, cleaned_messages
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return None, tuple(cleaned_messages)
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return active_tools if active_tools else (
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[] if initial_tools is not None or had_tool_changes else None
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), cleaned_messages
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return (
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active_tools if active_tools else (() if initial_tools is not None or had_tool_changes else None),
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tuple(cleaned_messages),
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)
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def translate_anthropic_to_openai(
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self,
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@ -1320,8 +1325,6 @@ class LiteLLMAnthropicMessagesAdapter:
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- tool_name_mapping maps truncated tool names back to original names
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for tools that exceeded OpenAI's 64-char limit
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"""
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# Debug: Processing Anthropic message request
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new_messages: list[AllMessageValues] = []
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tool_name_mapping: dict[str, str] = {}
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## CONVERT ANTHROPIC MESSAGES TO OPENAI
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@ -1336,17 +1339,17 @@ class LiteLLMAnthropicMessagesAdapter:
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messages=messages_list,
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initial_tools=anthropic_message_request.get("tools"),
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)
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request_for_translation: Final[AnthropicMessagesRequest] = cast(
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request_for_translation: Final[AnthropicMessagesRequest] = cast( # cast-ok: anthropic request type
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AnthropicMessagesRequest, dict(anthropic_message_request)
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)
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if active_tools is not None:
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if active_tools:
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request_for_translation["tools"] = active_tools
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request_for_translation["tools"] = list(active_tools)
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else:
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request_for_translation.pop("tools", None)
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new_messages = self.translate_anthropic_messages_to_openai(
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messages=cleaned_messages,
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new_messages: Final = self.translate_anthropic_messages_to_openai(
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messages=list(cleaned_messages),
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model=request_for_translation.get("model"),
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custom_llm_provider=custom_llm_provider,
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preserve_midturn_system=preserve_midturn_system,
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@ -319,22 +319,22 @@ def anthropic_tool_name(tool: object) -> str | None:
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return names[0] if names else None
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def extract_tool_from_addition_block(block: object) -> dict[str, object] | None:
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def extract_tool_from_addition_block(block: object) -> Mapping[str, object] | None:
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"""Extract raw tool dict from an Anthropic tool_addition block."""
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if not isinstance(block, Mapping):
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return None
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tool_data = block.get("tool")
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if isinstance(tool_data, dict):
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tool_data: Final = block.get("tool")
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if isinstance(tool_data, Mapping):
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if (
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tool_data.get("type") == "tool_definition"
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and "definition" in tool_data
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and isinstance(tool_data["definition"], dict)
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and isinstance(tool_data["definition"], Mapping)
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):
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return tool_data["definition"]
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return tool_data
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if "definition" in block and isinstance(block["definition"], dict):
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if "definition" in block and isinstance(block["definition"], Mapping):
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return block["definition"]
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if isinstance(block.get("tool_definition"), dict):
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if isinstance(block.get("tool_definition"), Mapping):
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return block["tool_definition"]
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return None
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