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Anthropic Plugin for Vision Agents

Anthropic Claude LLM integration for Vision Agents framework with support for streaming, function calling, and conversation memory.

It enables features such as:

  • Streaming responses with Claude models
  • Function calling capabilities for dynamic interactions
  • Automatic conversation history management

Installation

uv add "vision-agents[anthropic]"
# or directly
uv add vision-agents-plugins-anthropic

Usage

Standard LLM

This example shows how to use Claude with TTS and STT services for audio communication via anthropic.LLM() API.

The anthropic.LLM() class uses Anthropic's Messages API under the hood.

from vision_agents.core import User, Agent
from vision_agents.core.agents import AgentLauncher
from vision_agents.plugins import deepgram, getstream, cartesia, smart_turn, anthropic

agent = Agent(
    edge=getstream.Edge(),
    agent_user=User(name="Friendly AI"),
    instructions="Be nice to the user",
    llm=anthropic.LLM("claude-sonnet-4-6"),
    tts=cartesia.TTS(),
    stt=deepgram.STT(),
    turn_detection=smart_turn.TurnDetection(),
)

Function Calling

The LLM API supports function calling, allowing the assistant to invoke custom functions you define.

This enables dynamic interactions like:

  • Database queries
  • API calls to external services
  • File operations
  • Custom business logic
from vision_agents.plugins import anthropic

llm = anthropic.LLM("claude-sonnet-4-6")


@llm.register_function(
    name="get_weather",
    description="Get the current weather for a given city"
)
async def get_weather(city: str) -> dict:
    """Get weather information for a city."""
    return {
        "city": city,
        "temperature": 72,
        "condition": "Sunny"
    }
# The function will be automatically called when the model decides to use it

Requirements

  • Python 3.10+
  • GetStream account for video calls
  • Anthropic API key

Links

License

MIT

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