Quickstart

Get a running Lyzr agent in under 5 minutes.

Get a running agent in under 5 minutes using the method that fits your workflow.

Before you begin

• A Lyzr Studio account. Sign up at studio.lyzr.ai via Google, GitHub, or email.
• For Option C or D: an API key from Account > API Keys in Agent Studio.

Option A: Agent Studio (no code)

1. Sign in at studio.lyzr.ai.
2. On the home screen, describe what you want to build in plain English. The conversational builder asks follow-up questions and configures the agent for you. Alternatively, select Agents in the sidebar, then New Agent to use the manual builder.
3. Give your agent a name, select an LLM (GPT-4o Mini is a good starting point for cost), and write a role, goal, and instructions.
4. Optionally enable Knowledge Base and upload a PDF or enter a URL.
5. Select Test to open the chat interface. Send a message to verify the agent responds correctly.
6. Select Deploy and choose visibility: Private, Public, or Organization.

Your agent now has a live REST endpoint. Find it in Agent > API tab.

Option B: Architect (natural language)

Architect builds a full-stack agentic application from a plain-English description. Use it when you want a working product with a UI, not just an API endpoint.

1. Go to architect.new.
2. Type your prompt and hit enter. Architect will ask follow-up questions to confirm requirements, then generate the full application for you:

Build a Q&A agent that ingests my company documents, PDFs, and wiki pages,
then answers employee questions accurately with source references.

3. Architect configures the Knowledge Base, sets up the agent, and generates a frontend UI automatically.
4. Review the generated application in the preview, then deploy with one click.

Your application is live with a hosted URL, a multi-agent backend, and source-referenced answers out of the box.

Option C: ADK (Python)

pip install lyzr-adk

from lyzr_adk import Studio

studio = Studio(api_key="<YOUR_API_KEY>")  # get key from Agent Studio > Account

agent = studio.create_agent(
    name="Support Bot",
    provider="gpt-4o-mini",
    role="Customer support agent",
    goal="Resolve customer inquiries about billing and account issues",
    instructions="Be concise. Always ask for the account ID before looking up details."
)

response = agent.run("My invoice shows the wrong amount")
print(response.response)

Option D: REST API

# Create an agent
curl -X POST https://agent-prod.studio.lyzr.ai/v3/agent \
  -H "x-api-key: <YOUR_API_KEY>" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Support Bot",
    "provider": "gpt-4o-mini",
    "role": "Customer support agent",
    "goal": "Resolve customer inquiries",
    "instructions": "Be concise and ask for account ID first"
  }'

# Chat with the agent
curl -X POST https://agent-prod.studio.lyzr.ai/v3/agent/{agent_id}/chat \
  -H "x-api-key: <YOUR_API_KEY>" \
  -H "Content-Type: application/json" \
  -d '{"message": "My invoice shows the wrong amount", "session_id": "user-123"}'

What’s next

• Add a Knowledge Base to ground your agent in your documents.
• Connect Tools to let your agent take actions on external systems.
• Set up Responsible AI guardrails before going to production.
• Evaluate your agent with automated test cases.