anthropic[patch]: release 0.1.9, use tool calls if content is empty (#20535)

pull/20537/head
Bagatur 6 months ago committed by GitHub
parent 6adca37eb7
commit 96d8769eae
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194

@ -10,6 +10,7 @@ from typing import (
Dict,
Iterator,
List,
Literal,
Mapping,
Optional,
Sequence,
@ -38,6 +39,7 @@ from langchain_core.messages import (
BaseMessage,
HumanMessage,
SystemMessage,
ToolCall,
ToolMessage,
)
from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
@ -156,7 +158,7 @@ def _format_messages(messages: List[BaseMessage]) -> Tuple[Optional[str], List[D
continue
role = _message_type_lookups[message.type]
content: Union[str, List[Dict]]
content: Union[str, List]
if not isinstance(message.content, str):
# parse as dict
@ -195,6 +197,20 @@ def _format_messages(messages: List[BaseMessage]) -> Tuple[Optional[str], List[D
raise ValueError(
f"Content items must be str or dict, instead was: {type(item)}"
)
elif (
isinstance(message, AIMessage)
and not isinstance(message.content, list)
and message.tool_calls
):
content = (
[]
if not message.content
else [{"type": "text", "text": message.content}]
)
# Note: Anthropic can't have invalid tool calls as presently defined,
# since the model already returns dicts args not JSON strings, and invalid
# tool calls are those with invalid JSON for args.
content += _lc_tool_calls_to_anthropic_tool_use_blocks(message.tool_calls)
else:
content = message.content
@ -677,6 +693,29 @@ def _tools_in_params(params: dict) -> bool:
)
class _AnthropicToolUse(TypedDict):
type: Literal["tool_use"]
name: str
input: dict
id: str
def _lc_tool_calls_to_anthropic_tool_use_blocks(
tool_calls: List[ToolCall],
) -> List[_AnthropicToolUse]:
blocks = []
for tool_call in tool_calls:
blocks.append(
_AnthropicToolUse(
type="tool_use",
name=tool_call["name"],
input=tool_call["args"],
id=cast(str, tool_call["id"]),
)
)
return blocks
@deprecated(since="0.1.0", removal="0.2.0", alternative="ChatAnthropic")
class ChatAnthropicMessages(ChatAnthropic):
pass

@ -1,6 +1,6 @@
[tool.poetry]
name = "langchain-anthropic"
version = "0.1.8"
version = "0.1.9"
description = "An integration package connecting AnthropicMessages and LangChain"
authors = []
readme = "README.md"

@ -11,7 +11,11 @@ from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr
from langchain_core.tools import BaseTool
from langchain_anthropic import ChatAnthropic
from langchain_anthropic.chat_models import _merge_messages, convert_to_anthropic_tool
from langchain_anthropic.chat_models import (
_format_messages,
_merge_messages,
convert_to_anthropic_tool,
)
os.environ["ANTHROPIC_API_KEY"] = "foo"
@ -268,3 +272,131 @@ def test_convert_to_anthropic_tool(
for fn in (pydantic, function, dummy_tool, json_schema, expected, openai_function):
actual = convert_to_anthropic_tool(fn) # type: ignore
assert actual == expected
def test__format_messages_with_tool_calls() -> None:
system = SystemMessage("fuzz")
human = HumanMessage("foo")
ai = AIMessage(
"",
tool_calls=[{"name": "bar", "id": "1", "args": {"baz": "buzz"}}],
)
tool = ToolMessage(
"blurb",
tool_call_id="1",
)
messages = [system, human, ai, tool]
expected = (
"fuzz",
[
{"role": "user", "content": "foo"},
{
"role": "assistant",
"content": [
{
"type": "tool_use",
"name": "bar",
"id": "1",
"input": {"baz": "buzz"},
}
],
},
{
"role": "user",
"content": [
{"type": "tool_result", "content": "blurb", "tool_use_id": "1"}
],
},
],
)
actual = _format_messages(messages)
assert expected == actual
def test__format_messages_with_str_content_and_tool_calls() -> None:
system = SystemMessage("fuzz")
human = HumanMessage("foo")
# If content and tool_calls are specified and content is a string, then both are
# included with content first.
ai = AIMessage(
"thought",
tool_calls=[{"name": "bar", "id": "1", "args": {"baz": "buzz"}}],
)
tool = ToolMessage(
"blurb",
tool_call_id="1",
)
messages = [system, human, ai, tool]
expected = (
"fuzz",
[
{"role": "user", "content": "foo"},
{
"role": "assistant",
"content": [
{
"type": "text",
"text": "thought",
},
{
"type": "tool_use",
"name": "bar",
"id": "1",
"input": {"baz": "buzz"},
},
],
},
{
"role": "user",
"content": [
{"type": "tool_result", "content": "blurb", "tool_use_id": "1"}
],
},
],
)
actual = _format_messages(messages)
assert expected == actual
def test__format_messages_with_list_content_and_tool_calls() -> None:
system = SystemMessage("fuzz")
human = HumanMessage("foo")
# If content and tool_calls are specified and content is a list, then content is
# preferred.
ai = AIMessage(
[
{
"type": "text",
"text": "thought",
}
],
tool_calls=[{"name": "bar", "id": "1", "args": {"baz": "buzz"}}],
)
tool = ToolMessage(
"blurb",
tool_call_id="1",
)
messages = [system, human, ai, tool]
expected = (
"fuzz",
[
{"role": "user", "content": "foo"},
{
"role": "assistant",
"content": [
{
"type": "text",
"text": "thought",
}
],
},
{
"role": "user",
"content": [
{"type": "tool_result", "content": "blurb", "tool_use_id": "1"}
],
},
],
)
actual = _format_messages(messages)
assert expected == actual

Loading…
Cancel
Save