run-testsprite-backend
Run TestSprite Backend
Use TestSprite as an independent HTTP client against a publicly reachable deployment. Build executable Python tests from repository truth, run them through the TestSprite cloud, inspect immutable run evidence, fix the demonstrated layer, and repeat until a fresh run verifies the intended deployed revision.
This workflow is TypeScript-backend-first. For another stack, inspect and substitute that repository's route, schema, test, build, and deployment conventions; TestSprite still exercises the service over HTTP.
Value boundary
TestSprite is valuable here because it behaves like an independent deployed client: it can catch defects that native tests and same-process mocks miss, retain the exact request/response path, and challenge semantic contracts such as citations, streaming order, routing metadata, and typed failures.
It is not a deployment system, account/proxy provider, CAPTCHA solver, load tester, or autonomous repository maintainer. Its AI analysis proposes a cause and fix target; it does not prove either. A non-passing run can still be useful evidence when it correctly shows old production code, unavailable capacity, or an upstream gate.
| TestSprite can prove | It cannot prove by itself |
|---|---|
| What the public target returned to its HTTP client | That the target serves the commit in the checkout |
| Whether saved assertions held for one pinned run | That a suggested root cause is correct |
| Request, response, Data Flow, dependency, and artifact evidence | That an account, proxy, provider, or human challenge is healthy |
| A fresh external pass after deployment | Native unit correctness, load tolerance, or security completeness |