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For authentication and model list, see Anthropic Overview.
This page is a framework integration guide. For the raw HTTP endpoint reference, see Messages.

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Installation

pip install langchain-anthropic

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Code Examples

import os
from langchain_anthropic import ChatAnthropic

llm = ChatAnthropic(
  model='claude-sonnet-4-5-20250929',
  anthropic_api_key=os.getenv('PIPELLM_API_KEY'),
  anthropic_api_url='https://api.pipellm.ai'
)

response = llm.invoke([
  ('user', 'Why is the sky blue?')
])

print(response.content)

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Streaming

import os
from langchain_anthropic import ChatAnthropic

llm = ChatAnthropic(
  model='claude-sonnet-4-5-20250929',
  anthropic_api_key=os.getenv('PIPELLM_API_KEY'),
  anthropic_api_url='https://api.pipellm.ai',
  streaming=True
)

for chunk in llm.stream('Tell me a story'):
  print(chunk.content, end='', flush=True)

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Function Calling

import os
from langchain_anthropic import ChatAnthropic
from langchain_core.tools import tool

@tool
def get_weather(location: str) -> str:
  """Get the weather for a location."""
  return f"Weather in {location}: 22°C, Sunny"

llm = ChatAnthropic(
  model='claude-sonnet-4-5-20250929',
  anthropic_api_key=os.getenv('PIPELLM_API_KEY'),
  anthropic_api_url='https://api.pipellm.ai'
)

llm_with_tools = llm.bind_tools([get_weather])
response = llm_with_tools.invoke("What's the weather in Tokyo?")

print(response.tool_calls)

Anthropic Overview

Headers, models, and native routes

Messages

Raw endpoint reference for POST /v1/messages

Developer Tools Overview

More tools and framework integrations on PipeLLM