Deep Agents Python quickstart

create_deep_agent

Local setup constraints

1. Ask which provider/model to use. Showcase that Deep Agents are model-agnostic. Suggested prompt:

   Which model should this agent use? Pass a

   provider:model

   string — e.g.

   openai:gpt-5.5

   ,

   anthropic:claude-sonnet-5

   ,

   google_genai:gemini-3.5-flash

   . Default if you're unsure:

   anthropic:claude-sonnet-5

   .
   We'll use that provider's built-in web search (no separate search API key).

2. Create a new directory (e.g.

   deep-agent/

   ) and do all work there — do not pollute the open project.
3. Do not use Tavily (or any second search vendor). Replace the quickstart's

   internet_search

   / Tavily tool with the chosen provider's built-in web search. Look up the current tool shape on that provider's LangChain chat docs (examples as of writing — re-check if needed):

   Provider	Built-in search tool
   Anthropic	{"type": "web_search_20260209", "name": "web_search", "max_uses": 5}
   OpenAI	{"type": "web_search"}
   Google	{"google_search": {}}

   Prefer Anthropic / OpenAI / Google so provider search is available. Only secret: that provider's API key in

   .env

   (gitignored). Skip LangSmith tracing unless they ask.
4. Install

   deepagents

   (+

   python-dotenv

   ) and the provider package for their model — not

   tavily-python

   .
5. Run the research example, show output, then stop. Point to

   deep-agents-core

   / customization / Managed Deep Agents for next steps.