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1538ee17f9
Last week Anthropic released version 0.39.0 of its python sdk, which enabled support for Python 3.13. This release deleted a legacy `client.count_tokens` method, which we currently access during init of the `Anthropic` LLM. Anthropic has replaced this functionality with the [client.beta.messages.count_tokens() API](https://github.com/anthropics/anthropic-sdk-python/pull/726). To enable support for `anthropic >= 0.39.0` and Python 3.13, here we drop support for the legacy token counting method, and add support for the new method via `ChatAnthropic.get_num_tokens_from_messages`. To fully support the token counting API, we update the signature of `get_num_tokens_from_message` to accept tools everywhere. --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
langchain-anthropic
This package contains the LangChain integration for Anthropic's generative models.
Installation
pip install -U langchain-anthropic
Chat Models
Anthropic recommends using their chat models over text completions.
You can see their recommended models here.
To use, you should have an Anthropic API key configured. Initialize the model as:
from langchain_anthropic import ChatAnthropic
from langchain_core.messages import AIMessage, HumanMessage
model = ChatAnthropic(model="claude-3-opus-20240229", temperature=0, max_tokens=1024)
Define the input message
message = HumanMessage(content="What is the capital of France?")
Generate a response using the model
response = model.invoke([message])
For a more detailed walkthrough see here.
LLMs (Legacy)
You can use the Claude 2 models for text completions.
from langchain_anthropic import AnthropicLLM
model = AnthropicLLM(model="claude-2.1", temperature=0, max_tokens=1024)
response = model.invoke("The best restaurant in San Francisco is: ")