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anthropic[patch]: Release 0.1.13, tool_choice support (#21773)

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This commit is contained in:
Bagatur
2024-05-16 10:56:29 -07:00
committed by GitHub
parent 040597e832
commit 6416d16d39
6 changed files with 179 additions and 24 deletions
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78
libs/partners/anthropic/langchain_anthropic/chat_models.py
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@@ -542,6 +542,10 @@ class ChatAnthropic(BaseChatModel):
def bind_tools(
self,
tools: Sequence[Union[Dict[str, Any], Type[BaseModel], Callable, BaseTool]],
*,
tool_choice: Optional[
Union[Dict[str, str], Literal["any", "auto"], str]
] = None,
**kwargs: Any,
) -> Runnable[LanguageModelInput, BaseMessage]:
"""Bind tool-like objects to this chat model.
@@ -551,6 +555,15 @@ class ChatAnthropic(BaseChatModel):
Can be a dictionary, pydantic model, callable, or BaseTool. Pydantic
models, callables, and BaseTools will be automatically converted to
their schema dictionary representation.
tool_choice: Which tool to require the model to call.
Options are:
name of the tool (str): calls corresponding tool;
"auto" or None: automatically selects a tool (including no tool);
"any": force at least one tool to be called;
or a dict of the form:
{"type": "tool", "name": "tool_name"},
or {"type: "any"},
or {"type: "auto"};
**kwargs: Any additional parameters to bind.
Example:
@@ -564,9 +577,14 @@ class ChatAnthropic(BaseChatModel):
location: str = Field(..., description="The city and state, e.g. San Francisco, CA")
class GetPrice(BaseModel):
'''Get the price of a specific product.'''
product: str = Field(..., description="The product to look up.")
llm = ChatAnthropic(model="claude-3-opus-20240229", temperature=0)
llm_with_tools = llm.bind_tools([GetWeather])
llm_with_tools = llm.bind_tools([GetWeather, GetPrice])
llm_with_tools.invoke("what is the weather like in San Francisco",)
# -> AIMessage(
# content=[
@@ -576,8 +594,64 @@ class ChatAnthropic(BaseChatModel):
# response_metadata={'id': 'msg_01GM3zQtoFv8jGQMW7abLnhi', 'model': 'claude-3-opus-20240229', 'stop_reason': 'tool_use', 'stop_sequence': None, 'usage': {'input_tokens': 487, 'output_tokens': 145}},
# id='run-87b1331e-9251-4a68-acef-f0a018b639cc-0'
# )
Example — force tool call with tool_choice 'any':
.. code-block:: python
from langchain_anthropic import ChatAnthropic
from langchain_core.pydantic_v1 import BaseModel, Field
class GetWeather(BaseModel):
'''Get the current weather in a given location'''
location: str = Field(..., description="The city and state, e.g. San Francisco, CA")
class GetPrice(BaseModel):
'''Get the price of a specific product.'''
product: str = Field(..., description="The product to look up.")
llm = ChatAnthropic(model="claude-3-opus-20240229", temperature=0)
llm_with_tools = llm.bind_tools([GetWeather, GetPrice], tool_choice="any")
llm_with_tools.invoke("what is the weather like in San Francisco",)
Example — force specific tool call with tool_choice '<name_of_tool>':
.. code-block:: python
from langchain_anthropic import ChatAnthropic
from langchain_core.pydantic_v1 import BaseModel, Field
class GetWeather(BaseModel):
'''Get the current weather in a given location'''
location: str = Field(..., description="The city and state, e.g. San Francisco, CA")
class GetPrice(BaseModel):
'''Get the price of a specific product.'''
product: str = Field(..., description="The product to look up.")
llm = ChatAnthropic(model="claude-3-opus-20240229", temperature=0)
llm_with_tools = llm.bind_tools([GetWeather, GetPrice], tool_choice="GetWeather")
llm_with_tools.invoke("what is the weather like in San Francisco",)
""" # noqa: E501
formatted_tools = [convert_to_anthropic_tool(tool) for tool in tools]
if not tool_choice:
pass
elif isinstance(tool_choice, dict):
kwargs["tool_choice"] = tool_choice
elif isinstance(tool_choice, str) and tool_choice in ("any", "auto"):
kwargs["tool_choice"] = {"type": tool_choice}
elif isinstance(tool_choice, str):
kwargs["tool_choice"] = {"type": "tool", "name": tool_choice}
else:
raise ValueError(
f"Unrecognized 'tool_choice' type {tool_choice=}. Expected dict, "
f"str, or None."
)
return self.bind(tools=formatted_tools, **kwargs)
def with_structured_output(
@@ -683,7 +757,7 @@ class ChatAnthropic(BaseChatModel):
# }
""" # noqa: E501
llm = self.bind_tools([schema])
llm = self.bind_tools([schema], tool_choice="any")
if isinstance(schema, type) and issubclass(schema, BaseModel):
output_parser = ToolsOutputParser(
first_tool_only=True, pydantic_schemas=[schema]

10
libs/partners/anthropic/poetry.lock generated
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@@ -1,4 +1,4 @@
# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
[[package]]
name = "annotated-types"
@@ -16,13 +16,13 @@ typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.9\""}
[[package]]
name = "anthropic"
version = "0.25.9"
version = "0.26.0"
description = "The official Python library for the anthropic API"
optional = false
python-versions = ">=3.7"
files = [
{file = "anthropic-0.25.9-py3-none-any.whl", hash = "sha256:d0b17d442160356a531593b237de55d3125cc6fa708f1268c214107e61c81c57"},
{file = "anthropic-0.25.9.tar.gz", hash = "sha256:a4ec810b1cfbf3340af99b6f5bf599a83d66986e0f572a5f3bc4ebcab284f629"},
{file = "anthropic-0.26.0-py3-none-any.whl", hash = "sha256:38fc415561d71dcf263b89da0cc6ecec498379b56256fc4242e9128bc707b283"},
{file = "anthropic-0.26.0.tar.gz", hash = "sha256:6aaffeb05d515cf9788eef57150a5f827f3786883628ccac71dbe5671ab6f44e"},
]
[package.dependencies]
@@ -1212,4 +1212,4 @@ watchmedo = ["PyYAML (>=3.10)"]
[metadata]
lock-version = "2.0"
python-versions = ">=3.8.1,<4.0"
content-hash = "970ba277f7d892e877bf2ec55326417f4424d38a1fbf4e24149bad9d7862f7cd"
content-hash = "cd763107b1195eb05aee179f906103be2ec292914f37d546818c89960ebf6d75"

4
libs/partners/anthropic/pyproject.toml
View File

@@ -1,6 +1,6 @@
[tool.poetry]
name = "langchain-anthropic"
version = "0.1.12"
version = "0.1.13"
description = "An integration package connecting AnthropicMessages and LangChain"
authors = []
readme = "README.md"
@@ -13,7 +13,7 @@ license = "MIT"
[tool.poetry.dependencies]
python = ">=3.8.1,<4.0"
langchain-core = ">=0.1.43,<0.3"
anthropic = ">=0.23.0,<1"
anthropic = ">=0.26.0,<1"
defusedxml = { version = "^0.7.1", optional = true }
[tool.poetry.group.test]

18
libs/partners/anthropic/tests/integration_tests/test_chat_models.py
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@@ -3,6 +3,7 @@
import json
from typing import List
import pytest
from langchain_core.callbacks import CallbackManager
from langchain_core.messages import (
AIMessage,
@@ -14,6 +15,7 @@ from langchain_core.messages import (
)
from langchain_core.outputs import ChatGeneration, LLMResult
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.pydantic_v1 import BaseModel, Field
from langchain_core.tools import tool
from langchain_anthropic import ChatAnthropic, ChatAnthropicMessages
@@ -329,3 +331,19 @@ def test_with_structured_output() -> None:
response = structured_llm.invoke("what's the weather in san francisco, ca")
assert isinstance(response, dict)
assert response["location"]
class GetWeather(BaseModel):
"""Get the current weather in a given location"""
location: str = Field(..., description="The city and state, e.g. San Francisco, CA")
@pytest.mark.parametrize("tool_choice", ["GetWeather", "auto", "any"])
def test_anthropic_bind_tools_tool_choice(tool_choice: str) -> None:
chat_model = ChatAnthropic(
model="claude-3-sonnet-20240229",
)
chat_model_with_tools = chat_model.bind_tools([GetWeather], tool_choice=tool_choice)
response = chat_model_with_tools.invoke("what's the weather in ny and la")
assert isinstance(response, AIMessage)

36
libs/partners/anthropic/tests/unit_tests/test_chat_models.py
View File

@@ -8,6 +8,7 @@ from anthropic.types import ContentBlock, Message, Usage
from langchain_core.messages import AIMessage, HumanMessage, SystemMessage, ToolMessage
from langchain_core.outputs import ChatGeneration, ChatResult
from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr
from langchain_core.runnables import RunnableBinding
from langchain_core.tools import BaseTool
from pytest import CaptureFixture, MonkeyPatch
@@ -469,3 +470,38 @@ def test_anthropic_uses_actual_secret_value_from_secretstr() -> None:
cast(SecretStr, chat_model.anthropic_api_key).get_secret_value()
== "secret-api-key"
)
class GetWeather(BaseModel):
"""Get the current weather in a given location"""
location: str = Field(..., description="The city and state, e.g. San Francisco, CA")
def test_anthropic_bind_tools_tool_choice() -> None:
chat_model = ChatAnthropic(
model="claude-3-opus-20240229",
anthropic_api_key="secret-api-key",
)
chat_model_with_tools = chat_model.bind_tools(
[GetWeather], tool_choice={"type": "tool", "name": "GetWeather"}
)
assert cast(RunnableBinding, chat_model_with_tools).kwargs["tool_choice"] == {
"type": "tool",
"name": "GetWeather",
}
chat_model_with_tools = chat_model.bind_tools(
[GetWeather], tool_choice="GetWeather"
)
assert cast(RunnableBinding, chat_model_with_tools).kwargs["tool_choice"] == {
"type": "tool",
"name": "GetWeather",
}
chat_model_with_tools = chat_model.bind_tools([GetWeather], tool_choice="auto")
assert cast(RunnableBinding, chat_model_with_tools).kwargs["tool_choice"] == {
"type": "auto"
}
chat_model_with_tools = chat_model.bind_tools([GetWeather], tool_choice="any")
assert cast(RunnableBinding, chat_model_with_tools).kwargs["tool_choice"] == {
"type": "any"
}