langdb-adk 0.1.9

Google ADK model implementation for LangDB's LLM API.

LangDB LLM for Google ADK

A Google ADK (Agent Development Kit) model implementation for LangDB's LLM API. This package provides seamless integration of LangDB's LLM capabilities into the Google ADK framework.

Features

• Native integration with Google ADK's BaseLlm interface
• Support for both streaming and non-streaming completions
• Built-in function calling support
• Integration with MCP (Model Control Protocol) servers
• Asynchronous API compatible with ADK's execution model
• Automatic handling of tool execution and responses

Installation

pip install -e .

Usage with Google ADK

Basic Usage

import os
import asyncio
from google.adk import Agent
from langdb_adk import LangDBLlm
from google.adk.runners import InMemoryRunner

async def main():
    # Initialize the LangDB LLM with your credentials
    llm = LangDBLlm(
        model="anthropic/claude-sonnet-4",
        api_key=os.getenv("LANGDB_API_KEY"),
        project_id=os.getenv("LANGDB_PROJECT_ID")
    )
    
    # Create an ADK agent with the LangDB LLM
    agent = Agent(llm=llm)
    
    # Create a runner to execute the agent
    runner = InMemoryRunner()
    
    # Run the agent with a prompt
    response = await runner.run(agent, "Hello, how are you?")
    print(response.text)

if __name__ == "__main__":
    asyncio.run(main())

With MCP Servers

# Configure MCP servers for LangDB
mcp_servers = [
    {
        "server_url": "server_url",
        "type": "sse",
        "name": "search",
        "description": "Web search capabilities via DuckDuckGo"
    }
]

async def main():
    # Initialize the LangDB LLM with MCP servers
    llm = LangDBLlm(
        model="anthropic/claude-sonnet-4",
        api_key=os.getenv("LANGDB_API_KEY"),
        project_id=os.getenv("LANGDB_PROJECT_ID"),
        mcp_servers=mcp_servers
    )
    
    # Create an ADK agent with the LangDB LLM
    agent = Agent(llm=llm)
    
    # Create a runner to execute the agent
    runner = InMemoryRunner()
    
    # Run the agent with a prompt that can use MCP tools
    response = await runner.run(agent, "Search for the latest news about AI")
    print(response.text)

Configuration

Environment Variables

• LANGDB_API_KEY: Your LangDB API key (required)
• LANGDB_PROJECT_ID: Your LangDB project ID (required)

LangDBLlm Parameters

• model: The name of the model to use (e.g., "anthropic/claude-sonnet-4")
• api_key: Your LangDB API key
• project_id: Your LangDB project ID
• extra_headers: Additional headers to include in requests
• mcp_servers: List of MCP server configurations for extended capabilities

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Acknowledgements

• Google ADK Team for the Agent Development Kit