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https://github.com/hwchase17/langchain
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anthropic[patch]: release 0.1.9, use tool calls if content is empty (#20535)
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parent
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commit
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@ -10,6 +10,7 @@ from typing import (
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Dict,
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Dict,
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Iterator,
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Iterator,
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List,
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List,
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Literal,
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Mapping,
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Mapping,
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Optional,
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Optional,
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Sequence,
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Sequence,
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@ -38,6 +39,7 @@ from langchain_core.messages import (
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BaseMessage,
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BaseMessage,
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HumanMessage,
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HumanMessage,
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SystemMessage,
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SystemMessage,
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ToolCall,
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ToolMessage,
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ToolMessage,
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)
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)
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from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
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from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
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@ -156,7 +158,7 @@ def _format_messages(messages: List[BaseMessage]) -> Tuple[Optional[str], List[D
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continue
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continue
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role = _message_type_lookups[message.type]
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role = _message_type_lookups[message.type]
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content: Union[str, List[Dict]]
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content: Union[str, List]
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if not isinstance(message.content, str):
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if not isinstance(message.content, str):
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# parse as dict
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# parse as dict
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@ -195,6 +197,20 @@ def _format_messages(messages: List[BaseMessage]) -> Tuple[Optional[str], List[D
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raise ValueError(
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raise ValueError(
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f"Content items must be str or dict, instead was: {type(item)}"
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f"Content items must be str or dict, instead was: {type(item)}"
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)
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)
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elif (
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isinstance(message, AIMessage)
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and not isinstance(message.content, list)
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and message.tool_calls
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):
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content = (
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[]
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if not message.content
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else [{"type": "text", "text": message.content}]
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)
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# Note: Anthropic can't have invalid tool calls as presently defined,
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# since the model already returns dicts args not JSON strings, and invalid
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# tool calls are those with invalid JSON for args.
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content += _lc_tool_calls_to_anthropic_tool_use_blocks(message.tool_calls)
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else:
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else:
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content = message.content
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content = message.content
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@ -677,6 +693,29 @@ def _tools_in_params(params: dict) -> bool:
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)
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)
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class _AnthropicToolUse(TypedDict):
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type: Literal["tool_use"]
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name: str
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input: dict
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id: str
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def _lc_tool_calls_to_anthropic_tool_use_blocks(
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tool_calls: List[ToolCall],
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) -> List[_AnthropicToolUse]:
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blocks = []
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for tool_call in tool_calls:
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blocks.append(
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_AnthropicToolUse(
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type="tool_use",
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name=tool_call["name"],
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input=tool_call["args"],
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id=cast(str, tool_call["id"]),
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)
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)
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return blocks
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@deprecated(since="0.1.0", removal="0.2.0", alternative="ChatAnthropic")
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@deprecated(since="0.1.0", removal="0.2.0", alternative="ChatAnthropic")
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class ChatAnthropicMessages(ChatAnthropic):
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class ChatAnthropicMessages(ChatAnthropic):
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pass
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pass
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@ -1,6 +1,6 @@
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[tool.poetry]
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[tool.poetry]
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name = "langchain-anthropic"
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name = "langchain-anthropic"
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version = "0.1.8"
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version = "0.1.9"
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description = "An integration package connecting AnthropicMessages and LangChain"
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description = "An integration package connecting AnthropicMessages and LangChain"
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authors = []
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authors = []
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readme = "README.md"
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readme = "README.md"
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@ -11,7 +11,11 @@ from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr
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from langchain_core.tools import BaseTool
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from langchain_core.tools import BaseTool
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from langchain_anthropic import ChatAnthropic
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from langchain_anthropic import ChatAnthropic
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from langchain_anthropic.chat_models import _merge_messages, convert_to_anthropic_tool
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from langchain_anthropic.chat_models import (
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_format_messages,
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_merge_messages,
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convert_to_anthropic_tool,
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)
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os.environ["ANTHROPIC_API_KEY"] = "foo"
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os.environ["ANTHROPIC_API_KEY"] = "foo"
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@ -268,3 +272,131 @@ def test_convert_to_anthropic_tool(
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for fn in (pydantic, function, dummy_tool, json_schema, expected, openai_function):
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for fn in (pydantic, function, dummy_tool, json_schema, expected, openai_function):
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actual = convert_to_anthropic_tool(fn) # type: ignore
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actual = convert_to_anthropic_tool(fn) # type: ignore
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assert actual == expected
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assert actual == expected
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def test__format_messages_with_tool_calls() -> None:
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system = SystemMessage("fuzz")
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human = HumanMessage("foo")
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ai = AIMessage(
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"",
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tool_calls=[{"name": "bar", "id": "1", "args": {"baz": "buzz"}}],
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)
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tool = ToolMessage(
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"blurb",
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tool_call_id="1",
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)
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messages = [system, human, ai, tool]
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expected = (
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"fuzz",
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[
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{"role": "user", "content": "foo"},
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{
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"role": "assistant",
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"content": [
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{
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"type": "tool_use",
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"name": "bar",
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"id": "1",
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"input": {"baz": "buzz"},
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}
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],
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},
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{
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"role": "user",
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"content": [
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{"type": "tool_result", "content": "blurb", "tool_use_id": "1"}
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],
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},
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],
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)
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actual = _format_messages(messages)
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assert expected == actual
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def test__format_messages_with_str_content_and_tool_calls() -> None:
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system = SystemMessage("fuzz")
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human = HumanMessage("foo")
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# If content and tool_calls are specified and content is a string, then both are
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# included with content first.
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ai = AIMessage(
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"thought",
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tool_calls=[{"name": "bar", "id": "1", "args": {"baz": "buzz"}}],
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)
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tool = ToolMessage(
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"blurb",
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tool_call_id="1",
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)
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messages = [system, human, ai, tool]
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expected = (
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"fuzz",
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[
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{"role": "user", "content": "foo"},
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{
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"role": "assistant",
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"content": [
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{
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"type": "text",
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"text": "thought",
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},
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{
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"type": "tool_use",
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"name": "bar",
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"id": "1",
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"input": {"baz": "buzz"},
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},
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],
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},
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{
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"role": "user",
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"content": [
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{"type": "tool_result", "content": "blurb", "tool_use_id": "1"}
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],
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},
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],
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)
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actual = _format_messages(messages)
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assert expected == actual
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def test__format_messages_with_list_content_and_tool_calls() -> None:
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system = SystemMessage("fuzz")
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human = HumanMessage("foo")
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# If content and tool_calls are specified and content is a list, then content is
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# preferred.
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ai = AIMessage(
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[
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{
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"type": "text",
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"text": "thought",
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}
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],
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tool_calls=[{"name": "bar", "id": "1", "args": {"baz": "buzz"}}],
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)
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tool = ToolMessage(
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"blurb",
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tool_call_id="1",
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)
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messages = [system, human, ai, tool]
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expected = (
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"fuzz",
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[
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{"role": "user", "content": "foo"},
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{
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"role": "assistant",
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"content": [
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{
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"type": "text",
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"text": "thought",
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}
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],
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},
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{
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"role": "user",
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"content": [
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{"type": "tool_result", "content": "blurb", "tool_use_id": "1"}
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],
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},
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],
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)
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actual = _format_messages(messages)
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assert expected == actual
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