import json import rich from typing_extensions import Literal from anthropic import Anthropic, beta_tool client = Anthropic() @beta_tool def get_weather(location: str) -> str: """Lookup the weather for a given city in either celsius or fahrenheit Args: location: The city and state, e.g.

import json import rich from typing_extensions import Literal from anthropic import Anthropic, beta_tool client = Anthropic() @beta_tool def get_weather(location: str) -> str: """Lookup the weather for a given city in either celsius or fahrenheit Args: location: The city and state, e.g.

... The full API of this library can be found in api.md. import Anthropic from '@anthropic-ai/sdk'; const client = new Anthropic({ apiKey: process.env['ANTHROPIC_API_KEY'], // This is the default and can be omitted }); const message = await ...

from anthropic import Anthropic client = Anthropic() # Reads ANTHROPIC_API_KEY from environment message = client.messages.create( model="claude-sonnet-4-5", max_tokens=1024, messages=[{"role": "user", "content": "Hello, Claude"}] )

The Anthropic provider is available in the @ai-sdk/anthropic module. You can install it with ... If you need a customized setup, you can import createAnthropic from @ai-sdk/anthropic and create a provider instance with your settings:

Anthropic supports direct tool/function calling through the API. Using LlamaIndex, we can implement some core agentic tool calling patterns. ... from llama_index.core.tools import FunctionTool from llama_index.core.llms import ChatMessage from llama_index.llms.anthropic import Anthropic from datetime import datetime llm = Anthropic(model="claude-sonnet-4-0") def get_current_time() -> dict: """Get the current time""" return {"time": datetime.now().strftime("%Y-%m-%d %H:%M:%S")} # uses the tool name, any type annotations, and docstring to describe the tool tool = FunctionTool.from_defaults(fn=get_current_time)

Be aware that doing so may result in incorrect types and other unexpected or undefined behavior in the SDK. import Anthropic from '@anthropic-ai/sdk'; const client = new Anthropic(); const message = await client.messages.create( { max_tokens: ...

To use, you should have the anthropic python package installed, and the environment variable ANTHROPIC_API_KEY set with your API key, or pass it as a named parameter to the constructor. ... import anthropic from langchain_community.llms import Anthropic model = Anthropic(model="<model_name>", ...

You can install it with ... import { anthropic } from '@ai-sdk/anthropic'; import { generateText } from 'ai'; const { text } = await generateText({ model: anthropic('claude-3-haiku-20240307'), prompt: 'Write a vegetarian lasagna recipe for 4 ...

This page includes brief installation instructions and links to the open-source GitHub repositories for Anthropic’s Client SDKs.

export ANTHROPIC_BASE_URL=https://api.deepseek.com/anthropic export ANTHROPIC_API_KEY=${DEEPSEEK_API_KEY} Invoke the API · import anthropic client = anthropic.Anthropic() message = client.messages.create( model="deepseek-chat", max_tokens=1000, system="You are a helpful assistant.", messages=[ { "role": "user", "content": [ { "type": "text", "text": "Hi, how are you?"

Instructor makes it easy to analyse and extract semantic information from PDFs using Anthropic's Claude line of models. Let's see an example below with the sample PDF above where we'll load it in using our from_url method. Note that we support local files and base64 strings too with the from_path and the from_base64 class methods. from instructor.processing.multimodal import PDF from pydantic import BaseModel, Field import instructor from anthropic import Anthropic class Receipt(BaseModel): total: int items: list[str] client = instructor.from_provider("anthropic/claude-3-5-haiku-latest") url =

import Anthropic from "@anthropic-ai/sdk"; const baseURL = `https://gateway.ai.cloudflare.com/v1/{accountId}/{gatewayId}/anthropic`; const anthropic = new Anthropic({ baseURL, defaultHeaders: { Authorization: `Bearer {cf_api_token}`, }, }); ...

August 6, 2023 - Traceback (most recent call last): File "C:\metagpt\startup.py", line 7, in from metagpt.roles import Architect, Engineer, ProductManager, ProjectManager, QaEngineer File "C:\metagpt\metagpt\roles_init_.py", line 9, in from metagpt.roles.role import Role File "C:\metagpt\metagpt\roles\role.py", line 16, in from metagpt.actions import Action, ActionOutput File "C:\metagpt\metagpt\actions_init_.py", line 10, in from metagpt.actions.action import Action File "C:\metagpt\metagpt\actions\action.py", line 14, in from metagpt.llm import LLM File "C:\metagpt\metagpt\llm.py", line 9, in from metagpt.provider.anthropic_api import Claude2 as Claude File "C:\metagpt\metagpt\provider\anthropic_api.py", line 10, in from anthropic import Anthropic ImportError: cannot import name 'Anthropic' from 'anthropic' No one assigned ·

This page includes brief installation instructions and links to the open-source GitHub repositories for Anthropic's Client SDKs.

April 9, 2025 - pip install anthropic · import anthropic client = anthropic.Anthropic(api_key='your_api_key_here') npm install @anthropic-ai/sdk ·

const Anthropic = require('@anthropic-ai/sdk'); // Or using ES modules: // import Anthropic from '@anthropic-ai/sdk'; const anthropic = new Anthropic({ apiKey: 'your-api-key-here', // Replace with your actual API key });

March 5, 2024 - To start you need to import the packages we will need. Importing Anthropic is needed to talk to Claude or any of the models by Anthropic. Since we are using javascript we need to import dotenv to read our secret keys from the .env file.