Registry / llm-agents / llama-index-llms-anthropic

llama-index-llms-anthropic

library0.11.6pypypiunverified

The `llama-index-llms-anthropic` package provides an integration for using Anthropic's Claude models within the LlamaIndex framework. Anthropic is an AI research company focused on developing advanced language models, notably the Claude series, prioritizing safety and alignment. This integration allows LlamaIndex applications to leverage Anthropic's models for various LLM operations. The current version is `0.11.2`, and it follows LlamaIndex's rapid release cadence with frequent updates.

llm-agents ai-ml

pip install llama-index-llms-anthropic llama-index

package ↗homepage ↗

INSTALL

IMPORT

SIG · LLAMA-INDEX-LLMS-A

llama-index-llms-anthropic

llm-agentspythonv0.11.6

Install

26.6s avg

Import

7362ms

Disk

348MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.11.6 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.920 runs

installs and imports cleanly · install 0.0s · import 6.099s · 318.5MB

glibc

py 3.10–3.920 runs

installs and imports cleanly · install 26.6s · import 5.681s · 315MB

348MB installed

● package 348MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

Anthropic

✓ from llama_index.llms.anthropic import Anthropic

Settings

✓ from llama_index.core import Settings

✗ from llama_index.core.service_context import ServiceContext

ServiceContext was deprecated in LlamaIndex v0.11 and replaced by Settings.

ChatMessage

✓ from llama_index.core.llms import ChatMessage

✗ from llama_index.llms.anthropic import ChatMessage

ChatMessage is a core LlamaIndex object, not specific to the Anthropic integration.

This quickstart demonstrates how to initialize the Anthropic LLM, set the Anthropic API key from an environment variable, configure the LlamaIndex global tokenizer for accurate token counting, and make a basic text completion call using a Claude 3 Opus model.

import os from llama_index.llms.anthropic import Anthropic from llama_index.core import Settings os.environ["ANTHROPIC_API_KEY"] = os.environ.get("ANTHROPIC_API_KEY", "YOUR_ANTHROPIC_API_KEY") # Initialize the Anthropic LLM llm = Anthropic(model="claude-3-opus-20240229") # Set the tokenizer for accurate token counting (important for Anthropic models) Settings.tokenizer = llm.tokenizer # Make a completion call resp = llm.complete("What is the capital of France?") print(resp)

Debug

Known issues

breakingLlamaIndex Core v0.10/v0.11 introduced significant breaking changes. `ServiceContext` was completely removed in favor of `Settings`, and `LLMPredictor` was deprecated. Code written for older LlamaIndex versions (pre-0.10) relying on these abstractions will break.

fix

Migrate from `ServiceContext` to `Settings` (e.g., `from llama_index.core import Settings`). Update `LLMPredictor` usage to directly use `LLM` classes or other LlamaIndex components. Consult the LlamaIndex migration guides.

affects: LlamaIndex Core <0.10

gotchaEnsure your `ANTHROPIC_API_KEY` is correctly configured. The `Anthropic` class primarily looks for the `ANTHROPIC_API_KEY` environment variable. If it's not set or invalid, API calls will fail with authentication errors.

fix

Set the `ANTHROPIC_API_KEY` environment variable or pass the `api_key` argument explicitly during `Anthropic` class initialization: `llm = Anthropic(api_key="sk-...")`.

affects: All versions

gotchaFor accurate token counting with Anthropic models (especially newer Claude 3 models), it is crucial to explicitly set the LlamaIndex global tokenizer to the Anthropic tokenizer. The default LlamaIndex tokenizer (often `tiktoken`) will lead to incorrect token counts and can cause context overflow errors or unexpected behavior.

fix

After initializing your `Anthropic` LLM instance, assign its tokenizer to `Settings.tokenizer`: `Settings.tokenizer = llm.tokenizer`.

affects: All versions

gotchaDependency conflicts, especially with the underlying `anthropic` Python client library, can arise when combining `llama-index-llms-anthropic` with other `llama-index` integrations (e.g., `llama-index-multi-modal-llms-anthropic`). Older versions of certain integrations might have strict, incompatible `anthropic` client version requirements.

fix

Always check the specific version requirements of all `llama-index` packages and their dependencies. Consider upgrading all `llama-index-*` packages to their latest compatible versions or explicitly managing `anthropic` client versions to resolve conflicts.

affects: All versions, especially when combining with other `llama-index` integrations.

Upgrade

Version history

0.11.6latest on PyPI · released Jun 10, 2026

Audit

Dependencies

llama-index-corerequiredRequired for core LlamaIndex functionalities like Settings and ChatMessage objects.

anthropicrequiredThe underlying Python client library for interacting with Anthropic API.

pythonrequiredPython version compatibility.

Agent activity

19 hits · last 30 days

node

OpenAI (training)

Resources

packagehttps://pypi.org/project/llama-index-llms-anthropic/ ↗

homepagehttps://www.anthropic.com ↗