langchain/libs/partners/anthropic
enfeng b20c2640da
anthropic[patch]: update base_url of anthropic (#18634)
A small change ~

- [ ] **update base_url**: "package: langchain_anthropic"

---------

Co-authored-by: yangenfeng <yangenfeng@xiaoniangao.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
2024-03-20 21:04:55 -07:00
..
langchain_anthropic anthropic[patch]: update base_url of anthropic (#18634) 2024-03-20 21:04:55 -07:00
scripts infra: add print rule to ruff (#16221) 2024-02-09 16:13:30 -08:00
tests anthropic[patch]: integration test update (#18823) 2024-03-08 13:47:31 -08:00
.gitignore
LICENSE
Makefile anthropic[patch]: de-beta anthropic messages, release 0.0.2 (#17540) 2024-02-14 10:31:45 -08:00
poetry.lock anthropic[minor]: add tool calling (#18554) 2024-03-05 08:30:16 -08:00
pyproject.toml anthropic[patch]: release 0.1.4 (#18822) 2024-03-08 21:34:47 +00:00
README.md anthropic[minor]: add tool calling (#18554) 2024-03-05 08:30:16 -08:00

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: ")