### Host AI Chat Application with Starlette: Postgres-Backed State

#### Summary
Deploy an AI chat application built with Starlette on Ample using the durable job state pattern. Compute runs the app in an isolated microVM behind a public HTTPS URL, a managed PostgreSQL 16 database is auto-provisioned and injected as DATABASE_URL. Verified on Starlette: a jobs table with a state and attempts counter, processing inside a row-locked transaction, and a second run that is a no-op (job=done attempts=1 idempotent=true). Not separately tested: your job types, payload schema and retry policy; treat the AI chat application-specific behavior as your application code.

#### Representative Queries
- Host AI chat application with Starlette: Postgres-backed state
- Where can I host AI chat application built with Starlette?
- I need a durable state schema and retry/recovery semantics implemented by application code.

#### Resource Requirements
- **primitive:** compute
- **primitive:** postgres

#### Infrastructure Requirements
- **Compute**:  Apps run in isolated x86_64 Firecracker microVMs that auto-pause when idle and wake on request; sizes are the priced VM sizes.
- **Postgres**: Managed PostgreSQL 16 runs in its own microVM and is auto-provisioned when an app needs a database and no DATABASE_URL is supplied.

#### Prerequisites
- A Starlette project that builds and starts with the documented commands (pip install into .ample/python from requirements.txt, then uvicorn from run.py reading PORT on the python-3.12 template).
- A PostgreSQL driver reading DATABASE_URL at runtime (auto-provisioned when omitted, or supplied with --env).
- An Ample account token with servers:write, databases:read.

#### Workflow Steps
1. **Build and start**: pip install into .ample/python from requirements.txt, then uvicorn from run.py reading PORT on the python-3.12 template. The server must bind 0.0.0.0 on PORT.
2. **Implement the pattern on PostgreSQL**: The fixture's module implements durable job state: a jobs table with a state and attempts counter, processing inside a row-locked transaction, and a second run that is a no-op (job=done attempts=1 idempotent=true). Copy the approach into your schema; keep migrations idempotent and run them with --release-command.
3. **Deploy**: Run the synchronous deploy once and read the result (exit 0 live, 1 failed, 2 blocked). Re-running with no change is a no-op.
   ```bash
   ample deploy . --name --public --start "python3 run.py"
   ```
4. **Verify**: Fetch the live URL and the pattern self-test route(s) (/p/durable-job-state) from the example; then run your own checks. On failure read `ample logs --kind build` then `--kind runtime`.
   ```bash
   ample logs --kind build
   ```

#### Limitations
- Verified on the python-3.12 template at s-1vcpu-1gb with the example fixture; other sizes, templates and Starlette major versions are not verified.
- The AI chat application itself (your job types, payload schema and retry policy) is application code and was not separately tested; the pattern checks are what was verified.

#### Cost Estimate
- **Currency**: USD
- **Monthly Amount**: 10.0
- **Basis**: size prices from pricing.toml (loaded by the API) at build revision 1ac5595375130d45290090e82ed0f554ccd45405-dirty
  - **App server**: size s-1vcpu-1gb, quantity 1.0, monthly amount 5.0
  - **Managed PostgreSQL database**: size s-1vcpu-1gb, quantity 1.0, monthly amount 5.0
- **Note**: Always-on monthly price of the tested sizes; apps and databases auto-pause when idle. Buckets are allocation-priced per quota and not included.

#### Examples
- **Starlette pattern fixture**: Multi-pattern Starlette app whose durable job state module was checked live; the module is under tests/deploy-canaries/_pattern-modules.
  - **Source Ref**: tests/deploy-canaries/starlette-patterns

#### Success Checks
- **App responds on its public URL**: `http_get` path: /, expect: ample canary starlette patterns.
- **Durable-job-state self-test**: `http_get` path: /p/durable-job-state, expect: job=done attempts=1 idempotent=true.