81 lines
1.7 KiB
Markdown
81 lines
1.7 KiB
Markdown
# FastVideo Performance Dashboard
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Local FastAPI + React dashboard for records stored in the Hugging Face
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performance tracking dataset.
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## Data Source
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The dashboard reads the same normalized JSON records used by
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`fastvideo/tests/performance/compare_baseline.py`.
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Defaults:
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- `HF_REPO_ID=FastVideo/performance-tracking`
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- `PERFORMANCE_TRACKING_ROOT=/tmp/fastvideo-perf-dashboard`
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- `PERF_MAX_REGRESSION=0.05`
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Set one of `HF_API_KEY`, `HUGGINGFACE_HUB_TOKEN`, or `HF_TOKEN` if the
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configured dataset repo requires authenticated access:
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```bash
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export HF_TOKEN=hf_...
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```
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If Hugging Face returns `401 Unauthorized`, confirm that `HF_REPO_ID` points to
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the dataset repo you expect and that your token has access to it.
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## Development
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Run the API:
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```bash
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python -m fastvideo.performance_dashboard --host 127.0.0.1 --port 8000 --reload
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```
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Run the React dev server:
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```bash
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cd performance_dashboard/frontend
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npm install
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npm run dev
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```
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Open `http://127.0.0.1:5173`. Vite proxies `/api/*` to the FastAPI server on
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port 8000.
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## Single-Port Mode For ngrok
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Build the frontend:
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```bash
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cd performance_dashboard/frontend
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npm install
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npm run build
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```
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Serve API and built frontend from one FastAPI process:
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```bash
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python -m fastvideo.performance_dashboard --host 0.0.0.0 --port 8000
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```
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Expose it:
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```bash
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ngrok http 8000
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```
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The ngrok URL will serve the dashboard UI and all `/api/performance/*`
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endpoints from the same local port.
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## API
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- `GET /api/performance/health`
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- `POST /api/performance/refresh`
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- `GET /api/performance/summary?days=90`
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- `GET /api/performance/trends?days=90`
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- `GET /api/performance/records?days=90`
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The current v1 grouping key is `(model_id, gpu_type)`. Baselines are computed
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from the latest five previous successful records in each group.
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