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.env.example
.env.example
 
 
README.md
README.md
 
 
agent_runtime.py
agent_runtime.py
 
 
main.py
main.py
 
 
pyproject.toml
pyproject.toml
 
 

README.md

Business lookup with a Python agent

Stagehand is the SDK for browser agents.

This template uses LangChain Deep Agents for the reasoning loop and Stagehand V4 code mode for the browser. The agent opens San Francisco's official Open Data API, finds an exact DBA record, and returns a validated Pydantic object.

How it works

  • create_deep_agent owns planning, model calls, and structured output.
  • Stagehand code mode exposes one persistent Browserbase session through run, snapshot, and screenshot MCP tools.
  • Vercel AI Gateway supplies the bring-your-own agent model.
  • The Stagehand MCP server runs in an isolated uvx environment because the current Stagehand and Deep Agents clients require different websockets versions.
  • The template closes the MCP session and browser process automatically.

Quickstart

Requirements: Python 3.11–3.13 and uv.

cp .env.example .env
# Add BROWSERBASE_API_KEY and AI_GATEWAY_API_KEY to .env.
uv sync
uv run python main.py

The first run installs the Stagehand Deep Agents integration from stagehand/main in uvx; the integration pins its Stagehand server dependency to stagehand==4.0.0.

Expected outcome

The agent opens the official SF Open Data JSON endpoint and returns the exact Jalebi Street record, including its business account number, location ID, address, NAICS data when present, and the official source URL. The script exits nonzero if the returned DBA or evidence source does not match.

Configuration

  • BROWSERBASE_API_KEY: launches the Browserbase session.
  • AI_GATEWAY_API_KEY: authenticates the Deep Agents model through Vercel AI Gateway.
  • DEEPAGENTS_MODEL: optional model override; defaults to anthropic/claude-sonnet-4.6.
  • STAGEHAND_RUN_TIMEOUT_MS: optional browser-tool timeout; defaults to 120 seconds.

Resources