module-6

# Module 6 — Deploying with the Deepagents CLI ## Lesson Title Deploying Agents Without Writing Code: the Deepagents CLI ## Goal Show the student the alternative path: a "no Python" deployment that uses config files (`deepagents.toml`, `AGENTS.md`, `skills/`, `mcp.json`) instead of code. Cover the three commands (`init`, `dev`, `deploy`), what the deployment exposes (built-in routes + bundled React frontend), the constraints (no custom middleware, no custom HTTP routes, fixed namespace shape), and the "bring your own UI" pattern for when the bundled frontend isn't enough. ## How to run this lesson - Frame as a contrast with module 1: the code path is flexible but verbose; the CLI is convention-based and fast. Both produce a LangSmith deployment behind the scenes. - m6.1 (concepts): walk the student through `deepagents.toml` sections, the files (AGENTS.md, mcp.json, skills/, subagents/, user/), and the three commands. Mention that under the hood the CLI generates a `langgraph.json` + handler code from the template. - m6.2 (exercise): hands-on with `dacli_tutor`. Install CLI, set up `.env`, run `deepagents dev`, edit a skill, deploy. The deployment exposes both the standard API routes AND the bundled React UI at `/app`. - m6.3 (bring your own UI): use `deep_tutor`'s UI locally pointed at the CLI deployment. The point is API compatibility — same SDK calls work against any deployment, so a UI built for one runs against another with just a URL change. - Hammer the contrast: code path = Python code + langgraph.json; CLI = config files only, no Python. Same underlying deployment server. ## Key concepts to cover 1. `deepagents.toml` — the config file that replaces `langgraph.json` for CLI deploys 2. `AGENTS.md` — agent persona, loaded as system prompt 3. `skills/` — progressive-disclosure knowledge directories 4. `mcp.json` — MCP tool servers; CLI supports HTTP/SSE only (no stdio) 5. `subagents/` — optional sub-agent definitions 6. `user/` — per-user memory directory; populated by the CLI's user-memory scoping 7. The three commands: `deepagents init` (scaffold), `deepagents dev` (local), `deepagents deploy` (production) 8. What the CLI deployment exposes: standard Agent Server API + bundled React UI at `<url>/app` 9. `[auth] provider` options — `anonymous`, `supabase`, `clerk`; per-user identity comes from `runtime.server_info.user.identity` 10. The per-user namespace shape — `(assistant_id, user_identity)`; auth identity IS the namespace 11. CLI constraints — no custom middleware, no custom HTTP routes, no Python code; trade flexibility for speed 12. The "bring your own UI" pattern — local UI server uses the SDK to talk to the CLI deployment 13. The seed file (`_seed.json`) — skills + AGENTS.md are bundled at startup; no hot reload during `deepagents dev` 14. Hub seeding — LangSmith Hub repo is seeded once per first deploy; refreshes require deleting the hub or editing via Hub UI ## Tone guidance Contrast-driven. Students just spent five modules on the code path. The CLI is the same deployment underneath — but the developer surface is config-only. When the student asks "but how do I do X?", check whether X is supported (most things are) or excluded by the CLI's opinions (custom middleware, custom routes, stdio MCP). If excluded, the answer is "drop to the code path." ## Reference material Full reference material is in `information.md` in this directory. Read it before answering factual questions.