diff --git a/docs/my-website/blog/anthropic_advanced_features/index.md b/docs/my-website/blog/anthropic_opus_4_5_and_advanced_features/index.md similarity index 79% rename from docs/my-website/blog/anthropic_advanced_features/index.md rename to docs/my-website/blog/anthropic_opus_4_5_and_advanced_features/index.md index 71e5d9b192..0b0f4a5416 100644 --- a/docs/my-website/blog/anthropic_advanced_features/index.md +++ b/docs/my-website/blog/anthropic_opus_4_5_and_advanced_features/index.md @@ -1,7 +1,7 @@ --- slug: anthropic_advanced_features -title: "Advanced Anthropic Features in LiteLLM: Tool Search, Programmatic Tool Calling, Input Examples, and Effort Control" -date: 2025-01-25T10:00:00 +title: "Day 0 Support: Claude 4.5 Opus (+Advanced Features)" +date: 2025-11-25T10:00:00 authors: - name: Sameer Kankute title: SWE @ LiteLLM (LLM Translation) @@ -22,24 +22,205 @@ hide_table_of_contents: false import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; +This guide covers Anthropic's latest model (Claude Opus 4.5) and its advanced features now available in LiteLLM: Tool Search, Programmatic Tool Calling, Tool Input Examples, and the Effort Parameter. + +--- + +## Usage + + + + + +```python +import os +from litellm import completion + +# set env - [OPTIONAL] replace with your anthropic key +os.environ["ANTHROPIC_API_KEY"] = "your-api-key" + +messages = [{"role": "user", "content": "Hey! how's it going?"}] + +## OPENAI /chat/completions API format +response = completion(model="claude-opus-4-5-20251101", messages=messages) +print(response) + +``` + + + + +**1. Setup config.yaml** + +```yaml +model_list: + - model_name: claude-4 ### RECEIVED MODEL NAME ### + litellm_params: # all params accepted by litellm.completion() - https://docs.litellm.ai/docs/completion/input + model: claude-opus-4-5-20251101 ### MODEL NAME sent to `litellm.completion()` ### + api_key: "os.environ/ANTHROPIC_API_KEY" # does os.getenv("ANTHROPIC_API_KEY") +``` + +**2. Start the proxy** + +```bash +litellm --config /path/to/config.yaml +``` + +**3. Test it!** + + + +```bash +curl --location 'http://0.0.0.0:4000/chat/completions' \ +--header 'Content-Type: application/json' \ +--header 'Authorization: Bearer $LITELLM_KEY' \ +--data ' { + "model": "claude-4", + "messages": [ + { + "role": "user", + "content": "what llm are you" + } + ] + } +' +``` + + +```bash +curl --location 'http://0.0.0.0:4000/v1/messages' \ +--header 'Content-Type: application/json' \ +--header 'Authorization: Bearer $LITELLM_KEY' \ +--data ' { + "model": "claude-4", + "max_tokens": 1024, + "messages": [ + { + "role": "user", + "content": "what llm are you" + } + ] + } +' +``` + + + + + +## Usage - Bedrock + :::info -This guide covers Anthropic's latest advanced features now available in LiteLLM: Tool Search, Programmatic Tool Calling, Tool Input Examples, and the Effort Parameter. +LiteLLM uses the boto3 library to authenticate with Bedrock. + +For more ways to authenticate with Bedrock, see the [Bedrock documentation](../../docs/providers/bedrock#authentication). ::: -We're excited to announce support for Anthropic's latest advanced features in LiteLLM! These powerful capabilities enable you to build more efficient, scalable, and cost-effective AI applications with Claude. + + -## Table of Contents -1. [Tool Search](#tool-search) -2. [Programmatic Tool Calling](#programmatic-tool-calling) -3. [Tool Input Examples](#tool-input-examples) -4. [Effort Parameter: Control Token Usage](#effort-parameter) -5. [Cost Tracking: Monitor Tool Search Usage](#cost-tracking) -6. [Combining Features](#combining-features) +```python +import os +from litellm import completion + +os.environ["AWS_ACCESS_KEY_ID"] = "" +os.environ["AWS_SECRET_ACCESS_KEY"] = "" +os.environ["AWS_REGION_NAME"] = "" + +## OPENAI /chat/completions API format +response = completion( + model="bedrock/us.anthropic.claude-opus-4-5-20251101-v1:0", + messages=[{ "content": "Hello, how are you?","role": "user"}] +) +``` + + + + +**1. Setup config.yaml** + +```yaml +model_list: + - model_name: claude-4 ### RECEIVED MODEL NAME ### + litellm_params: # all params accepted by litellm.completion() - https://docs.litellm.ai/docs/completion/input + model: bedrock/us.anthropic.claude-opus-4-5-20251101-v1:0 ### MODEL NAME sent to `litellm.completion()` ### + aws_access_key_id: os.environ/AWS_ACCESS_KEY_ID + aws_secret_access_key: os.environ/AWS_SECRET_ACCESS_KEY + aws_region_name: os.environ/AWS_REGION_NAME +``` + +**2. Start the proxy** + +```bash +litellm --config /path/to/config.yaml +``` + +**3. Test it!** + + + +```bash +curl --location 'http://0.0.0.0:4000/chat/completions' \ +--header 'Content-Type: application/json' \ +--header 'Authorization: Bearer $LITELLM_KEY' \ +--data ' { + "model": "claude-4", + "messages": [ + { + "role": "user", + "content": "what llm are you" + } + ] + } +' +``` + + +```bash +curl --location 'http://0.0.0.0:4000/v1/messages' \ +--header 'Content-Type: application/json' \ +--header 'Authorization: Bearer $LITELLM_KEY' \ +--data ' { + "model": "claude-4", + "max_tokens": 1024, + "messages": [ + { + "role": "user", + "content": "what llm are you" + } + ] + } +' +``` + + +```bash +curl --location 'http://0.0.0.0:4000/bedrock/model/claude-4/invoke' \ +--header 'Content-Type: application/json' \ +--header 'Authorization: Bearer $LITELLM_KEY' \ +--data ' { + "max_tokens": 1024, + "messages": [{"role": "user", "content": "Hello, how are you?"}] + }' +``` + + +```bash +curl --location 'http://0.0.0.0:4000/bedrock/model/claude-4/converse' \ +--header 'Content-Type: application/json' \ +--header 'Authorization: Bearer $LITELLM_KEY' \ +--data ' { + "messages": [{"role": "user", "content": "Hello, how are you?"}] + }' +``` + + + + ---- ## Tool Search {#tool-search} diff --git a/docs/my-website/docs/providers/anthropic_tool_search.md b/docs/my-website/docs/providers/anthropic_tool_search.md index 3d61022b26..7b9e7cfaa7 100644 --- a/docs/my-website/docs/providers/anthropic_tool_search.md +++ b/docs/my-website/docs/providers/anthropic_tool_search.md @@ -380,7 +380,7 @@ If Claude references a tool that isn't in your deferred tools list, you'll get a **When traditional tool calling is better:** - Less than 10 tools total - All tools are frequently used -- Very small tool definitions (<100 tokens total) +- Very small tool definitions (\<100 tokens total) ## Limitations