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[AZ-178] Implement streaming video detection endpoint

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- Added `/detect/video` endpoint for true streaming video detection, allowing inference to start as upload bytes arrive.
- Introduced `run_detect_video_stream` method in the inference module to handle video processing from a file-like object.
- Updated media hashing to include a new function for computing hashes directly from files with minimal I/O.
- Enhanced documentation to reflect changes in video processing and API behavior.

Made-with: Cursor
This commit is contained in:
Oleksandr Bezdieniezhnykh
2026-04-01 03:11:43 +03:00
parent e65d8da6a3
commit be4cab4fcb
42 changed files with 2983 additions and 29 deletions
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.cursor/skills/test-spec/SKILL.md
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@@ -435,17 +435,20 @@ Write or update a **"Test Execution"** section in `TESTS_OUTPUT_DIR/environment.
3. Identify performance/load testing tools from dependencies (k6, locust, artillery, wrk, or built-in benchmarks)
4. Read `TESTS_OUTPUT_DIR/environment.md` for infrastructure requirements
#### Step 2 — Generate `scripts/run-tests.sh`
#### Step 2 — Generate test runner
Create `scripts/run-tests.sh` at the project root using `.cursor/skills/test-spec/templates/run-tests-script.md` as structural guidance. The script must:
**Docker is the default.** Only generate a local `scripts/run-tests.sh` if the Hardware-Dependency Assessment determined **local** or **both** execution (i.e., the project requires real hardware like GPU/CoreML/TPU/sensors). For all other projects, use `docker-compose.test.yml` — it provides reproducibility, isolation, and CI parity without a custom shell script.
**If local script is needed** — create `scripts/run-tests.sh` at the project root using `.cursor/skills/test-spec/templates/run-tests-script.md` as structural guidance. The script must:
1. Set `set -euo pipefail` and trap cleanup on EXIT
2. Optionally accept a `--unit-only` flag to skip blackbox tests
3. Run unit/blackbox tests using the detected test runner:
- **Local mode**: activate virtualenv (if present), run test runner directly on host
- **Docker mode**: spin up docker-compose environment, wait for health checks, run test suite, tear down
4. Print a summary of passed/failed/skipped tests
5. Exit 0 on all pass, exit 1 on any failure
2. **Install all project and test dependencies** (e.g. `pip install -q -r requirements.txt -r e2e/requirements.txt`, `dotnet restore`, `npm ci`). This prevents collection-time import errors on fresh environments.
3. Optionally accept a `--unit-only` flag to skip blackbox tests
4. Run unit/blackbox tests using the detected test runner (activate virtualenv if present, run test runner directly on host)
5. Print a summary of passed/failed/skipped tests
6. Exit 0 on all pass, exit 1 on any failure
**If Docker** — generate or update `docker-compose.test.yml` that builds the test image, installs all dependencies inside the container, runs the test suite, and exits with the test runner's exit code.
#### Step 3 — Generate `scripts/run-performance-tests.sh`