# Host ai workflow runner with FastAPI: streamed responses

Deploy an ai workflow runner built with FastAPI on Ample using the streaming response service 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 FastAPI: a Server-Sent Events endpoint read incrementally through the public HTTPS gateway: five one-second chunks arrived spread over time with the first within seconds (not buffered), a 70-second stream of 36 chunks completed past common 60-second idle timeouts, and a client that disconnected after two chunks was observed and recorded by the server (disconnected=true). Not separately tested: your event schema, reconnection strategy and any per-request duration ceiling beyond the 70 seconds measured; treat the ai workflow runner-specific behavior as your application code.

## Representative Queries
- Host ai workflow runner with FastAPI: streamed responses
- Where can I host AI workflow runner built with FastAPI?
- I need a tested end-to-end streaming transport, timeout behavior and client disconnect handling.

## Resource Requirements
- Compute
- 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 FastAPI 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
### 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.
### Implement the pattern on PostgreSQL
- The fixture's module implements streaming response service: a Server-Sent Events endpoint read incrementally through the public HTTPS gateway: five one-second chunks arrived spread over time with the first within seconds (not buffered), a 70-second stream of 36 chunks completed past common 60-second idle timeouts, and a client that disconnected after two chunks was observed and recorded by the server (disconnected=true). Copy the approach into your schema; keep migrations idempotent and run them with --release-command.
### 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.
- Command: ample deploy . --name  --public --start "python3 run.py"
### Verify
- Fetch the live URL and the pattern self-test route(s) (/p/streaming-response-service) from the example; then run your own checks. On failure read `ample logs  --kind build` then `--kind runtime`.
- Command: ample logs  --kind build

## Examples
### FastAPI pattern fixture
- Multi-pattern FastAPI app whose streaming response service module was checked live; the module is under tests/deploy-canaries/_pattern-modules.

## Success Checks
- **App responds on its public URL**  
  Path: `/`  
  Expect: `ample canary fastapi patterns`  
- **Streaming-response-service self-test**  
  Path: `/p/streaming-response-service`  
  Expect: `an SSE stream: data: id=, then chunk events one interval apart (read incrementally: first chunk within seconds, chunks spread over the interval), then data: done; /status?id= reports sent=N disconnected=true|false done=true|false`

## Limitations
- Verified on the python-3.12 template at s-1vcpu-1gb with the example fixture; other sizes, templates and FastAPI major versions are not verified.
- The ai workflow runner itself (your event schema, reconnection strategy and any per-request duration ceiling beyond the 70 seconds measured) is application code and was not separately tested; the pattern checks are what was verified.
- Region, compliance attestations and request-duration limits are unknown and not claimed.
- Apps auto-pause when idle and wake on the next request; always-on is an operator setting, not a plan feature.
- Managed PostgreSQL 16 only; extensions, connection limits and backup or restore procedures are not verified; apps and their databases are placed together.

## Cost Estimate
- Currency: USD  
- Monthly Amount: 10.0  
- Authoritative: true  
- Basis: size prices from pricing.toml (loaded by the API) at build revision 1ac5595375130d45290090e82ed0f554ccd45405-dirty
- Components:
  - Name: app server
    - Size: s-1vcpu-1gb
    - Quantity: 1.0
    - Monthly Amount: 5.0  
  - Name: 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.