Lyzr ADK Overview

Get started with the Lyzr Agent Development Kit (ADK) for building AI agents

The Lyzr ADK (Agent Development Kit) is a Python library for building, deploying, and managing AI agents. It provides a simple, intuitive interface to create agents with features like RAG, memory, tools, and responsible AI guardrails.

Installation

Install the ADK using pip:

pip install lyzr-adk

Quick Start

from lyzr import Studio

# Initialize the SDK
studio = Studio(api_key="your-api-key")

# Create an agent
agent = studio.create_agent(
    name="My Assistant",
    provider="gpt-4o",
    role="Helpful assistant",
    goal="Help users with their questions",
    instructions="Be concise and accurate"
)

# Run the agent
response = agent.run("What is machine learning?")
print(response.response)

Authentication

The ADK requires an API key for authentication.

Getting Your API Key

1. Sign in to Lyzr Studio
2. Go to your Account page
3. Copy your API key

Keep your API key secure. Never commit it to version control or share it publicly.

Providing the API Key

You can provide the API key in three ways:

Direct Parameter

studio = Studio(api_key="your-api-key")

Environment Variable

export LYZR_API_KEY="your-api-key"

studio = Studio()  # Reads from LYZR_API_KEY

.env File

Create a .env file in your project root:

LYZR_API_KEY=your-api-key

studio = Studio()  # Auto-loads from .env

Key Concepts

Studio

The Studio class is the main entry point. It manages connections and provides methods to create and manage all resources.

from lyzr import Studio

studio = Studio(api_key="your-api-key")

Agents

Agents are AI-powered entities that can understand and respond to messages. Each agent has a provider (LLM), role, goal, and instructions.

agent = studio.create_agent(
    name="Support Bot",
    provider="gpt-4o",
    role="Customer support agent",
    goal="Resolve customer issues",
    instructions="Be empathetic and solution-oriented"
)

response = agent.run("I need help with my order")

Knowledge Bases

Knowledge bases enable RAG (Retrieval Augmented Generation) by storing and querying documents.

kb = studio.create_knowledge_base(
    name="Product Docs",
    vector_store="qdrant",
    embedding_model="text-embedding-3-large"
)

kb.add_pdf("manual.pdf")
kb.add_website("https://docs.example.com", max_pages=50)

Memory

Memory allows agents to maintain conversation context across sessions.

agent = studio.create_agent(
    name="Assistant",
    provider="gpt-4o",
    memory=30  # Keep last 30 messages
)

Tools

Tools let agents execute Python functions to perform actions.

def get_weather(city: str) -> str:
    """Get current weather for a city"""
    return f"Weather in {city}: 72°F, Sunny"

agent.add_tool(get_weather)

Contexts

Contexts provide background information to agents as key-value pairs.

context = studio.create_context(
    name="company_info",
    value="Acme Corp - Founded 2020, 50k customers"
)

agent = studio.create_agent(..., contexts=[context])

RAI Guardrails

Responsible AI policies provide safety features like toxicity detection, PII handling, and content filtering.

from lyzr import PIIType, PIIAction

policy = studio.create_rai_policy(
    name="SafePolicy",
    description="Content safety guardrails",
    toxicity_threshold=0.3,
    pii_detection={PIIType.CREDIT_CARD: PIIAction.BLOCK}
)

agent = studio.create_agent(..., rai_policy=policy)

Supported Providers

The ADK supports multiple LLM providers:

Provider	Models
OpenAI	gpt-4o, gpt-4o-mini, gpt-5, o3, o4-mini
Anthropic	claude-sonnet-4.5, claude-opus-4.5, claude-3.7
Google	gemini-2.0-flash, gemini-2.5-pro, gemini-3.0-pro
Groq	llama-3.3-70b, llama-4-maverick
Perplexity	sonar, sonar-pro
AWS Bedrock	nova-pro, claude-3.7-sonnet

Context Manager

The ADK supports context manager pattern for automatic cleanup:

with Studio(api_key="your-api-key") as studio:
    agent = studio.create_agent(...)
    response = agent.run("Hello")
# Connection automatically closed

Next Steps

Studio

Learn about the Studio class and initialization options

Agents

Create and manage AI agents

Knowledge Bases

Build RAG-powered agents with document retrieval

Providers

See all supported LLM providers and models