diff --git a/.dockerignore b/.dockerignore index 9e1a764..3bafa47 100644 --- a/.dockerignore +++ b/.dockerignore @@ -2,6 +2,7 @@ node_modules dist .git .github +docs tests playwright-report test-results diff --git a/Dockerfile b/Dockerfile index 6f52c4b..7b6a14a 100644 --- a/Dockerfile +++ b/Dockerfile @@ -19,6 +19,7 @@ ENV NODE_ENV=production PORT=3000 COPY --from=build /app/node_modules ./node_modules COPY --from=build /app/dist ./dist COPY --from=build /app/index.html ./index.html +COPY --from=build /app/assets ./assets COPY --from=build /app/package.json ./package.json EXPOSE 3000 CMD ["node", "dist/server.js"] diff --git a/EXAMPLE.md b/EXAMPLE.md index 8b236f2..f07be3f 100644 --- a/EXAMPLE.md +++ b/EXAMPLE.md @@ -1,100 +1,92 @@ -# Example: Running the Local LLM Benchmark +# Example: running Local-Bench -This example demonstrates how to use the Local-Bench tool. +A quick walkthrough of benchmarking local models and viewing the results. ## Prerequisites -1. Install Ollama: https://ollama.ai/ -2. Download some models: +1. Install [Ollama](https://ollama.ai/) and start it: `ollama serve` +2. Pull a few models you can run on your hardware: + ```bash -ollama pull llama2 -ollama pull mistral -ollama pull phi +ollama pull gemma3:4b +ollama pull qwen3:8b +ollama pull llama3.1:8b ``` -## Step 1: Run the Benchmark +## Step 1: Run the benchmark ```bash -# Benchmark default models -npm run benchmark +npm install +npm run build + +# Benchmark specific installed models... +node dist/benchmark.js gemma3:4b qwen3:8b llama3.1:8b -# Or benchmark specific models -node benchmark.js llama2 mistral phi codellama +# ...or the whole curated catalog +npm run benchmark ``` Expected output: + ``` === Local LLM Benchmark Tool === Ollama API URL: http://localhost:11434 -Models to benchmark: llama2, mistral, phi, codellama +Models to benchmark: gemma3:4b, qwen3:8b, llama3.1:8b ✓ Connected to Ollama API -Benchmarking llama2... - ✓ Completed in 2.65s - ✓ Generated 120 tokens - ✓ Speed: 45.23 tokens/second +Benchmarking gemma3:4b... + ✓ Completed in 5.25s + ✓ Generated 412 tokens + ✓ Speed: 78.42 tokens/second -Benchmarking mistral... - ✓ Completed in 2.40s - ✓ Generated 125 tokens - ✓ Speed: 52.18 tokens/second +Benchmarking qwen3:8b... + ✓ Completed in 9.52s + ✓ Generated 498 tokens + ✓ Speed: 52.31 tokens/second Results saved to benchmark_results.csv === Benchmark Summary === Ranking (by tokens/second): - 1. mistral: 52.18 tokens/s - 2. llama2: 45.23 tokens/s + 1. gemma3:4b: 78.42 tokens/s + 2. qwen3:8b: 52.31 tokens/s + 3. llama3.1:8b: 49.87 tokens/s -Done! Open index.html in a browser to view the results. +Done! Open the dashboard to view the results. ``` -## Step 2: View Results in Web Interface +## Step 2: View results in the dashboard ```bash -# Start the web server npm start - -# Open in browser -# Navigate to http://localhost:3000 +# open http://localhost:3000 ``` -You should see: -- Statistics cards showing total models, successful tests, average speed, and fastest model -- A bar chart comparing model performance -- A detailed table with all benchmark results +You'll see: -## Step 3: Re-run and Refresh +- Summary cards (catalog size, installed models, top intelligence, fastest measured) +- The **Model intelligence** catalog ranked by the Artificial Analysis Intelligence Index +- System specifications captured during the run +- A throughput bar chart and a detailed results table (with each model's `IQ` score) -After running new benchmarks: -1. Click the "Refresh Results" button in the web interface -2. The page will reload with updated data from the CSV file +## Step 3: Re-run and refresh -## Custom Configuration +Run more benchmarks (CLI or the **Run benchmark** button in the UI), then click **Refresh** in the dashboard to reload the latest data. + +## Custom configuration -### Custom Ollama URL ```bash +# Point at a non-default Ollama OLLAMA_API_URL=http://192.168.1.100:11434 npm run benchmark -``` -### Custom Port for Web Server -```bash +# Custom dashboard port PORT=8080 npm start ``` ## Troubleshooting -### Error: Cannot connect to Ollama API -- Make sure Ollama is running: `ollama serve` -- Check the API endpoint: `curl http://localhost:11434/api/tags` - -### Error: Model not found -- List available models: `ollama list` -- Pull the missing model: `ollama pull ` - -### Benchmark times out -- The default timeout is 2 minutes -- Some larger models may take longer -- Consider testing with smaller prompts or fewer models +- **Cannot connect to Ollama API** — make sure `ollama serve` is running; check `curl http://localhost:11434/api/tags`. +- **Model not found** — `ollama list` to see what's installed, then `ollama pull `. +- **Benchmark times out** — the per-model timeout is 2 minutes; try smaller models or fewer at once. diff --git a/LLM_TESTS.md b/LLM_TESTS.md index 42a9f66..4665d08 100644 --- a/LLM_TESTS.md +++ b/LLM_TESTS.md @@ -1,44 +1,54 @@ -| Name | Size | Context | Input | -| --- | --- | --- | --- | -| gemma3:270m | 292MB | 32K | Text | -| qwen3:0.6b | 523MB | 40K | Text | -| gemma3:1b | 815MB | 32K | Text | -| deepseek-r1:1.5b | 1.1GB | 128K | Text | -| llama3.2:1b | 1.3GB | 128K | Text | -| qwen3:1.7b | 1.4GB | 40K | Text | -| qwen3-vl:2b | 1.9GB | 256K | Text, Image | -| llama3.2:3b latest | 2.0GB | 128K | Text | -| qwen3:4b | 2.5GB | 256K | Text | -| gemma3:4b latest | 3.3GB | 128K | Text, Image | -| qwen3-vl:4b | 3.3GB | 256K | Text, Image | -| deepseek-r1:7b | 4.7GB | 128K | Text | -| llama3.1:8b latest | 4.9GB | 128K | Text | -| deepseek-r1:8b latest | 5.2GB | 128K | Text | -| qwen3:8b latest | 5.2GB | 40K | Text | -| qwen3-vl:8b latest | 6.1GB | 256K | Text, Image | -| gemma3:12b | 8.1GB | 128K | Text, Image | -| deepseek-r1:14b | 9.0GB | 128K | Text | -| qwen3:14b | 9.3GB | 40K | Text | -| gpt-oss:20b | 14GB | 128K | Text | -| gemma3:27b | 17GB | 128K | Text, Image | -| qwen3-coder:latest | 19GB | 256K | Text | -| qwen3-coder:30b latest | 19GB | 256K | Text | -| qwen3:30b | 19GB | 256K | Text | -| deepseek-r1:32b | 20GB | 128K | Text | -| qwen3:32b | 20GB | 40K | Text | -| qwen3-vl:30b | 20GB | 256K | Text, Image | -| qwen3-vl:32b | 21GB | 256K | | -| deepseek-r1:70b | 43GB | 128K | Text | -| llama3.1:70b | 43GB | 128K | Text | -| gpt-oss:120b | 65GB | 128K | Text | -| llama4:16x17b latest | 67GB | 10M | Text, Image | -| GLM-4.6:TQ1_0 | 84GB | 198K | Text | -| qwen3:235b | 142GB | 256K | Text | -| qwen3-vl:235b | 143GB | 256K | | -| GLM-4.6:Q4_K_M | 216GB | 198K | Text | -| llama3.1:405b | 243GB | 128K | Text | -| llama4:128x17b | 245GB | 1M | Text, Image | -| qwen3-coder:480b | 290GB | 256K | Text | -| deepseek-v3.1:671b latest | 404GB | 160K | Text | -| deepseek-r1:671b | 404GB | 160K | Text | -| minmax m2 | 968GB | 200K | Text | +# Curated Companion model catalog + +The models Local-Bench benchmarks and ranks by default. The **Intelligence** column +is the [Artificial Analysis Intelligence Index](https://artificialanalysis.ai/) +(higher = more capable; snapshot `2026-06`). `—` means the model is not individually +rated by the index (vision-only or very small models). + +This table is generated from `SUPPORTED_OLLAMA_MODELS` in [`src/benchmark.ts`](src/benchmark.ts) — +edit the `intelligenceIndex` values there to override the scores. + +| Model | Size | Context | Inputs | Intelligence | +| --- | --- | --- | --- | --- | +| gemma3:270m | 292MB | 32K | Text | — | +| qwen3:0.6b | 523MB | 40K | Text | — | +| gemma3:1b | 815MB | 32K | Text | — | +| deepseek-r1:1.5b | 1.1GB | 128K | Text | — | +| llama3.2:1b | 1.3GB | 128K | Text | — | +| qwen3:1.7b | 1.4GB | 40K | Text | 3 | +| qwen3-vl:2b | 1.9GB | 256K | Text, Image | — | +| llama3.2:3b | 2.0GB | 128K | Text | 4 | +| qwen3:4b | 2.5GB | 256K | Text | 6 | +| gemma3:4b | 3.3GB | 128K | Text, Image | 4 | +| qwen3-vl:4b | 3.3GB | 256K | Text, Image | — | +| deepseek-r1:7b | 4.7GB | 128K | Text | 8 | +| llama3.1:8b | 4.9GB | 128K | Text | 8 | +| deepseek-r1:8b | 5.2GB | 128K | Text | 9 | +| qwen3:8b | 5.2GB | 40K | Text | 9 | +| qwen3-vl:8b | 6.1GB | 256K | Text, Image | — | +| gemma3:12b | 8.1GB | 128K | Text, Image | 7 | +| deepseek-r1:14b | 9.0GB | 128K | Text | 13 | +| qwen3:14b | 9.3GB | 40K | Text | 11 | +| gpt-oss:20b | 14GB | 128K | Text | 24 | +| gemma3:27b | 17GB | 128K | Text, Image | 10 | +| qwen3-coder:latest | 19GB | 256K | Text | 20 | +| qwen3-coder:30b | 19GB | 256K | Text | 20 | +| qwen3:30b | 19GB | 256K | Text | 15 | +| deepseek-r1:32b | 20GB | 128K | Text | 18 | +| qwen3:32b | 20GB | 40K | Text | 15 | +| qwen3-vl:30b | 20GB | 256K | Text, Image | — | +| qwen3-vl:32b | 21GB | 256K | Text, Image | — | +| deepseek-r1:70b | 43GB | 128K | Text | 20 | +| llama3.1:70b | 43GB | 128K | Text | 16 | +| gpt-oss:120b | 65GB | 128K | Text | 33 | +| llama4:16x17b | 67GB | 10M | Text, Image | 13 | +| GLM-4.6:TQ1_0 | 84GB | 198K | Text | 30 | +| qwen3:235b | 142GB | 256K | Text | 45 | +| qwen3-vl:235b | 143GB | 256K | Text, Image | — | +| GLM-4.6:Q4_K_M | 216GB | 198K | Text | 30 | +| llama3.1:405b | 243GB | 128K | Text | 17 | +| llama4:128x17b | 245GB | 1M | Text, Image | 18 | +| qwen3-coder:480b | 290GB | 256K | Text | 24 | +| deepseek-v3.1:671b | 404GB | 160K | Text | 28 | +| deepseek-r1:671b | 404GB | 160K | Text | 27 | +| minmax m2 | 968GB | 200K | Text | 44 | diff --git a/README.md b/README.md index 9e1d762..96da0ac 100644 --- a/README.md +++ b/README.md @@ -1,272 +1,248 @@ -# Local-Bench 🚀 +# Local-Bench -A tool for benchmarking local LLM (Large Language Model) performance via the Ollama API and AMD STRIX Halo GPUs. This tool measures the token generation speed of different models and presents the results in an interactive web interface with tables and charts. -image +**A [Companion Intelligence](https://ci.computer/) app for benchmarking local LLMs — and comparing them by intelligence.** +Local-Bench measures the token-generation speed of models you run locally (via [Ollama](https://ollama.ai/) or AMD STRIX Halo / llama.cpp) and presents the results in a clean, local-first web dashboard. It also ships a curated Companion model catalog ranked by the **Artificial Analysis Intelligence Index**, so you can weigh capability against the throughput your hardware actually delivers. + +![Local-Bench dashboard](docs/screenshots/00-hero.png) + +## Screenshots + +| Model intelligence catalog | Throughput comparison | +| --- | --- | +| ![Model intelligence](docs/screenshots/02-model-intelligence.png) | ![Throughput](docs/screenshots/04-throughput.png) | + +| Run a benchmark | Detailed results | +| --- | --- | +| ![Run a benchmark](docs/screenshots/03-run-benchmark.png) | ![Detailed results](docs/screenshots/05-results.png) | + +> Full-page view: [`docs/screenshots/01-overview.png`](docs/screenshots/01-overview.png) ## Features -- 📊 Benchmark multiple LLM models with a single command -- ⚡ Measure tokens per second for each model -- 🧪 Run a broader benchmark library with coding, reasoning, extraction, planning, summarization, translation, and instruction-following prompts -- 💾 Store results in CSV format and SQLite database -- 🌐 Beautiful web interface with: - - Installed vs. supported Ollama model catalog - - Benchmark prompt library with benchmark types - - Interactive bar charts - - Detailed results table - - Performance statistics - - Real-time refresh capability -- 🎮 **NEW: AMD STRIX Halo GPU support** for llama.cpp benchmarking +- 📊 Benchmark multiple local LLMs and measure **tokens per second** for each +- 🧠 **Model intelligence catalog** — curated Companion models ranked by the Artificial Analysis Intelligence Index, shown alongside size, context window, and modality +- 🧪 A broad prompt library (coding, reasoning, extraction, planning, summarization, translation, instruction-following) plus custom prompts +- 💾 Results stored in SQLite (`benchmark_data.db`) and CSV (`benchmark_results.csv`) +- 💻 Captures system specifications (CPU, memory, OS, GPU, STRIX Halo) with every run +- 🎮 **AMD STRIX Halo** GPU support for `llama.cpp` benchmarking +- 🪶 **Local-first** — Chart.js is vendored into the repo, so the dashboard renders fully offline (it gracefully falls back to CSS bar charts if scripting is unavailable) +- 🎨 Redesigned to match Companion Intelligence branding (light, monochrome, minimalist) ## Prerequisites -- [Node.js](https://nodejs.org/) (v14 or higher) -- **For Ollama benchmarks:** - - [Ollama](https://ollama.ai/) installed and running locally - - At least one LLM model downloaded in Ollama -- **For AMD STRIX Halo benchmarks:** - - AMD Ryzen AI Max "Strix Halo" APU - - Fedora 42/43 or Ubuntu 24.04 - - Toolbox (podman-toolbox) installed - - See [STRIX_HALO.md](STRIX_HALO.md) for detailed requirements +- [Node.js](https://nodejs.org/) (v18 or higher) +- **For Ollama benchmarks:** [Ollama](https://ollama.ai/) running locally with at least one model pulled +- **For AMD STRIX Halo benchmarks:** an AMD Ryzen AI Max "Strix Halo" APU — see [STRIX_HALO.md](STRIX_HALO.md) -## Installation +## Quick start -1. Clone this repository: ```bash git clone https://github.com/companionintelligence/Local-Bench.git cd Local-Bench -``` - -2. Install dependencies: -```bash npm install -``` -3. Make sure Ollama is running: -```bash -# Ollama should be running on http://localhost:11434 -# Start it if it's not already running +# make sure Ollama is running (default http://localhost:11434) ollama serve -``` -4. Download some models (if you haven't already): -```bash -ollama pull llama2 -ollama pull mistral -ollama pull codellama +# build + start the dashboard +npm start +# open http://localhost:3000 ``` -## Usage +Don't have Ollama running yet? The dashboard still loads — it shows the curated catalog and intelligence scores, and degrades gracefully (see [First run / no Ollama](#first-run--no-ollama)). -### Ollama Benchmarks +## Usage -#### Running Benchmarks +### Run benchmarks from the CLI -**Default models:** ```bash +# Benchmark the curated catalog npm run benchmark -``` - -This benchmarks the curated Ollama support catalog defined in `src/benchmark.ts`. You can also run a smaller selection by passing model names on the command line. -**Custom models:** -```bash +# Benchmark specific installed models node dist/benchmark.js llama3.2:3b qwen3:8b gemma3:4b + +# Point at a non-default Ollama +OLLAMA_API_URL=http://192.168.1.50:11434 npm run benchmark ``` -You can specify any models you have installed in Ollama. +### Run benchmarks from the web UI -**Custom Ollama API URL:** ```bash -OLLAMA_API_URL=http://localhost:11434 npm run benchmark +npm start # http://localhost:3000 +PORT=8080 npm start # custom port ``` -### AMD STRIX Halo Benchmarks +The dashboard lets you pick installed models, choose a prompt (or write your own), run benchmarks, and watch results, charts, statistics, and system specs update live. -For AMD Ryzen AI Max "Strix Halo" GPU benchmarking with llama.cpp: +### AMD STRIX Halo -**Detect STRIX Halo GPU:** ```bash npm run strix-halo detect -``` - -**Setup toolbox (one-time):** -```bash npm run strix-halo setup llama-rocm-7.2 -``` - -**Run benchmark:** -```bash npm run strix-halo benchmark /path/to/model.gguf --toolbox llama-rocm-7.2 ``` -**See full documentation:** -[STRIX_HALO.md](STRIX_HALO.md) - Complete guide for AMD STRIX Halo integration - -### Viewing Results - -1. Start the web server: -```bash -npm start -``` - -2. Open your browser and navigate to: -``` -http://localhost:3000 -``` +Full guide: [STRIX_HALO.md](STRIX_HALO.md). -3. The web interface will display: - - Installed and supported Ollama model catalog entries - - A richer benchmark prompt library with prompt categories and benchmark types - - Summary statistics (total models, average speed, fastest model) - - Interactive bar chart comparing model performance - - Detailed results table with all benchmark data +## Model intelligence scores -You can also directly open `index.html` in your browser if the CSV file is in the same directory. +Each curated model carries an **intelligence score** sourced from the +[Artificial Analysis Intelligence Index](https://artificialanalysis.ai/) — a +composite benchmark (MMLU-Pro, GPQA Diamond, LiveCodeBench, AIME, and more) +scored roughly 0–100 where higher is more capable. The dashboard surfaces it as +an `IQ` badge on each model and as a ranked "Model intelligence" list. -### Custom Port +A few notes on the data: -```bash -PORT=8080 npm start -``` +- Scores are a **snapshot** (currently `2026-06`) and are version-sensitive — the index evolves as new evaluations and models are added. +- **Vision-only** (`-vl`) variants and very small models are not individually rated by the index and appear as **"Not rated" / `IQ —`**. +- The values are a best-effort public reference and are intended to be **easy to override** with Companion's own curated numbers. They live in a single place — the `intelligenceIndex` field of `SUPPORTED_OLLAMA_MODELS` in [`src/benchmark.ts`](src/benchmark.ts) — which both the CLI and UI read from. The attribution shown in the UI comes from `INTELLIGENCE_INDEX_SOURCE` / `INTELLIGENCE_INDEX_URL` / `INTELLIGENCE_INDEX_AS_OF` in the same file. ## Docker / Companion Intelligence Hub -Local-Bench is published as a public, multi-architecture (amd64 + arm64) container image -and runs as a first-party app on the Companion Intelligence Hub. +Local-Bench is published as a public, multi-architecture (amd64 + arm64) container image and runs as a first-party app on the Companion Intelligence Hub. **Image:** `ghcr.io/companionintelligence/ci-local-bench:latest` -The container runs the Node web server (`node dist/server.js`) and listens on -**port 3000** inside the container. - -### Run the container - ```bash docker run -d -p 3000:3000 ghcr.io/companionintelligence/ci-local-bench:latest # open http://localhost:3000 ``` -Override the host port with `-p :3000`, or change the in-container port with -`-e PORT=8080`. - -### Pointing it at Ollama - -Benchmarks call an Ollama server. The address is read from the **`OLLAMA_API_URL`** -environment variable (default `http://localhost:11434`). Inside a container, -`localhost` refers to the container itself, so point it at the host or another -container running Ollama: +Point it at an Ollama server with `OLLAMA_API_URL` (inside a container, `localhost` is the container itself): ```bash -# Ollama running on the Docker host (Docker Desktop / macOS / Windows) +# Ollama on the Docker host docker run -d -p 3000:3000 \ -e OLLAMA_API_URL=http://host.docker.internal:11434 \ ghcr.io/companionintelligence/ci-local-bench:latest -# Ollama reachable on the LAN +# Ollama on the LAN docker run -d -p 3000:3000 \ -e OLLAMA_API_URL=http://192.168.1.50:11434 \ ghcr.io/companionintelligence/ci-local-bench:latest ``` +Benchmark data (`benchmark_data.db` + `benchmark_results.csv`) is written to the working directory (`/app` in the container). Mount a volume there to persist results across restarts. + ### First run / no Ollama -The UI degrades gracefully with no benchmark data and no reachable Ollama: +The dashboard degrades gracefully when there's no data and no reachable Ollama: -- The dashboard loads and shows a friendly empty-state message prompting you to - run your first benchmark (no red error banner). -- The model picker falls back to the curated support catalog and notes that Ollama - is unavailable; `GET /api/models` returns HTTP `503` with the catalog body. -- System specs, statistics, and the chart show neutral "run a benchmark" placeholders - until results exist. +- It loads and shows a friendly welcome instead of a red error banner. +- The **Model intelligence** catalog still renders (scores come from the bundled catalog, not Ollama). +- The model picker falls back to the curated catalog and notes that Ollama is unavailable; `GET /api/models` returns HTTP `503` with the catalog body. +- System specs, statistics, and the chart show neutral "run a benchmark" placeholders until results exist. -Benchmark results (`benchmark_data.db` SQLite + `benchmark_results.csv`) are written -to the working directory (`/app` in the container). Mount a volume there if you want -results to persist across container restarts. +## API endpoints -## Output +| Endpoint | Description | +| --- | --- | +| `GET /api/models` | Curated catalog merged with installed Ollama models (incl. `intelligenceIndex`). `503` + catalog body if Ollama is unreachable. | +| `GET /api/prompts` | The benchmark prompt library | +| `GET /api/results` | All stored benchmark results | +| `GET /api/system-specs` | Latest captured system specifications | +| `GET /api/results-with-specs?limit=N` | Results joined with their system specs | +| `GET /api/meta` | Intelligence-score attribution (source, URL, snapshot date) | +| `POST /api/run-benchmark` | Run a benchmark `{ models: string[], promptId?, customPrompt? }` | -Results are saved to `benchmark_results.csv` in the following format: +## Output (CSV) ```csv Model,Tokens Per Second,Total Tokens,Duration (s),Timestamp,Status -llama2,45.23,120,2.65,2024-01-15T10:30:00.000Z,Success -mistral,52.18,125,2.40,2024-01-15T10:32:30.000Z,Success +gemma3:4b,78.42,412,5.25,2026-06-11T20:36:02.000Z,Success +qwen3:8b,52.31,498,9.52,2026-06-11T20:38:02.000Z,Success ``` ## Configuration -You can customize the following by editing `src/benchmark.ts`: +Edit [`src/benchmark.ts`](src/benchmark.ts) to customize: + +- `OLLAMA_API_URL` — Ollama endpoint (env var, default `http://localhost:11434`) +- `TEST_PROMPTS` — the benchmark prompt library +- `SUPPORTED_OLLAMA_MODELS` — the curated catalog, including each model's `intelligenceIndex` -- `OLLAMA_API_URL`: Ollama API endpoint (default: `http://localhost:11434`) -- `TEST_PROMPTS`: The benchmark prompt library used by the CLI and UI -- `SUPPORTED_OLLAMA_MODELS`: The curated Ollama support catalog and default benchmark targets +## Testing + +```bash +npm test # Jest unit tests (server, benchmark, database, system specs, STRIX Halo) +npm run test:coverage +npm run build # typecheck + emit to dist/ +``` + +The repository is set up for automated testing: + +- **Unit tests** cover the API, the catalog/intelligence data, CSV/DB writes, and system-spec collection. +- **Container smoke test** — [`tests/container/`](tests/container) is a self-contained Playwright harness that boots the published image and asserts the web UI renders, saving a screenshot artifact. It runs in the GHCR publish workflow. +- **Screenshots** in [`docs/screenshots/`](docs/screenshots) are captured against the running server (see that workflow / the Playwright harness) and embedded above. ## Troubleshooting -**Cannot connect to Ollama API:** -- Make sure Ollama is running: `ollama serve` -- Check that the API is accessible at `http://localhost:11434` -- Try setting a custom URL: `OLLAMA_API_URL=http://your-url npm run benchmark` +**Cannot connect to Ollama:** ensure `ollama serve` is running and reachable at `http://localhost:11434`, or set `OLLAMA_API_URL`. + +**Model not found:** list installed models with `ollama list`, then `ollama pull `. -**Model not found:** -- List available models: `ollama list` -- Pull the model: `ollama pull ` +**Benchmark takes too long:** larger models are slower; there's a 2-minute per-model timeout. Benchmark fewer/smaller models at once. -**Benchmark takes too long:** -- Some models are slower than others -- The tool has a 2-minute timeout per model -- Consider benchmarking fewer models at once +**Chart not showing:** the dashboard automatically falls back to CSS bar charts if the vendored Chart.js can't execute — no internet required. ## Contributing -Contributions are welcome! Please feel free to submit a Pull Request. - -# Supported Ollama Catalog - -| Name | Size | Context | Input | -| --- | --- | --- | --- | -| gemma3:270m | 292MB | 32K | Text | -| qwen3:0.6b | 523MB | 40K | Text | -| gemma3:1b | 815MB | 32K | Text | -| deepseek-r1:1.5b | 1.1GB | 128K | Text | -| llama3.2:1b | 1.3GB | 128K | Text | -| qwen3:1.7b | 1.4GB | 40K | Text | -| qwen3-vl:2b | 1.9GB | 256K | Text, Image | -| llama3.2:3b latest | 2.0GB | 128K | Text | -| qwen3:4b | 2.5GB | 256K | Text | -| gemma3:4b latest | 3.3GB | 128K | Text, Image | -| qwen3-vl:4b | 3.3GB | 256K | Text, Image | -| deepseek-r1:7b | 4.7GB | 128K | Text | -| llama3.1:8b latest | 4.9GB | 128K | Text | -| deepseek-r1:8b latest | 5.2GB | 128K | Text | -| qwen3:8b latest | 5.2GB | 40K | Text | -| qwen3-vl:8b latest | 6.1GB | 256K | Text, Image | -| gemma3:12b | 8.1GB | 128K | Text, Image | -| deepseek-r1:14b | 9.0GB | 128K | Text | -| qwen3:14b | 9.3GB | 40K | Text | -| gpt-oss:20b | 14GB | 128K | Text | -| gemma3:27b | 17GB | 128K | Text, Image | -| qwen3-coder:latest | 19GB | 256K | Text | -| qwen3-coder:30b latest | 19GB | 256K | Text | -| qwen3:30b | 19GB | 256K | Text | -| deepseek-r1:32b | 20GB | 128K | Text | -| qwen3:32b | 20GB | 40K | Text | -| qwen3-vl:30b | 20GB | 256K | Text, Image | -| qwen3-vl:32b | 21GB | 256K | | -| deepseek-r1:70b | 43GB | 128K | Text | -| llama3.1:70b | 43GB | 128K | Text | -| gpt-oss:120b | 65GB | 128K | Text | -| llama4:16x17b latest | 67GB | 10M | Text, Image | -| GLM-4.6:TQ1_0 | 84GB | 198K | Text | -| qwen3:235b | 142GB | 256K | Text | -| qwen3-vl:235b | 143GB | 256K | | -| GLM-4.6:Q4_K_M | 216GB | 198K | Text | -| llama3.1:405b | 243GB | 128K | Text | -| llama4:128x17b | 245GB | 1M | Text, Image | -| qwen3-coder:480b | 290GB | 256K | Text | -| deepseek-v3.1:671b latest | 404GB | 160K | Text | -| deepseek-r1:671b | 404GB | 160K | Text | -| minmax m2 | 968GB | 200K | Text | +Contributions are welcome — please open a Pull Request. + +## Supported Companion catalog + +Curated models with their Artificial Analysis Intelligence Index score (snapshot `2026-06`; `—` = not individually rated). + + + +| Model | Size | Context | Inputs | Intelligence | +| --- | --- | --- | --- | --- | +| gemma3:270m | 292MB | 32K | Text | — | +| qwen3:0.6b | 523MB | 40K | Text | — | +| gemma3:1b | 815MB | 32K | Text | — | +| deepseek-r1:1.5b | 1.1GB | 128K | Text | — | +| llama3.2:1b | 1.3GB | 128K | Text | — | +| qwen3:1.7b | 1.4GB | 40K | Text | 3 | +| qwen3-vl:2b | 1.9GB | 256K | Text, Image | — | +| llama3.2:3b | 2.0GB | 128K | Text | 4 | +| qwen3:4b | 2.5GB | 256K | Text | 6 | +| gemma3:4b | 3.3GB | 128K | Text, Image | 4 | +| qwen3-vl:4b | 3.3GB | 256K | Text, Image | — | +| deepseek-r1:7b | 4.7GB | 128K | Text | 8 | +| llama3.1:8b | 4.9GB | 128K | Text | 8 | +| deepseek-r1:8b | 5.2GB | 128K | Text | 9 | +| qwen3:8b | 5.2GB | 40K | Text | 9 | +| qwen3-vl:8b | 6.1GB | 256K | Text, Image | — | +| gemma3:12b | 8.1GB | 128K | Text, Image | 7 | +| deepseek-r1:14b | 9.0GB | 128K | Text | 13 | +| qwen3:14b | 9.3GB | 40K | Text | 11 | +| gpt-oss:20b | 14GB | 128K | Text | 24 | +| gemma3:27b | 17GB | 128K | Text, Image | 10 | +| qwen3-coder:latest | 19GB | 256K | Text | 20 | +| qwen3-coder:30b | 19GB | 256K | Text | 20 | +| qwen3:30b | 19GB | 256K | Text | 15 | +| deepseek-r1:32b | 20GB | 128K | Text | 18 | +| qwen3:32b | 20GB | 40K | Text | 15 | +| qwen3-vl:30b | 20GB | 256K | Text, Image | — | +| qwen3-vl:32b | 21GB | 256K | Text, Image | — | +| deepseek-r1:70b | 43GB | 128K | Text | 20 | +| llama3.1:70b | 43GB | 128K | Text | 16 | +| gpt-oss:120b | 65GB | 128K | Text | 33 | +| llama4:16x17b | 67GB | 10M | Text, Image | 13 | +| GLM-4.6:TQ1_0 | 84GB | 198K | Text | 30 | +| qwen3:235b | 142GB | 256K | Text | 45 | +| qwen3-vl:235b | 143GB | 256K | Text, Image | — | +| GLM-4.6:Q4_K_M | 216GB | 198K | Text | 30 | +| llama3.1:405b | 243GB | 128K | Text | 17 | +| llama4:128x17b | 245GB | 1M | Text, Image | 18 | +| qwen3-coder:480b | 290GB | 256K | Text | 24 | +| deepseek-v3.1:671b | 404GB | 160K | Text | 28 | +| deepseek-r1:671b | 404GB | 160K | Text | 27 | +| minmax m2 | 968GB | 200K | Text | 44 | + +--- + +> **Private & Confidential — Property of Lifescope Inc. 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hs="$chartjs",cs={touchstart:"mousedown",touchmove:"mousemove",touchend:"mouseup",pointerenter:"mouseenter",pointerdown:"mousedown",pointermove:"mousemove",pointerup:"mouseup",pointerleave:"mouseout",pointerout:"mouseout"},ds=t=>null===t||""===t;const us=!!Se&&{passive:!0};function fs(t,e,i){t.canvas.removeEventListener(e,i,us)}function gs(t,e){for(const i of t)if(i===e||i.contains(e))return!0}function ps(t,e,i){const s=t.canvas,n=new MutationObserver((t=>{let e=!1;for(const i of t)e=e||gs(i.addedNodes,s),e=e&&!gs(i.removedNodes,s);e&&i()}));return n.observe(document,{childList:!0,subtree:!0}),n}function ms(t,e,i){const s=t.canvas,n=new MutationObserver((t=>{let e=!1;for(const i of t)e=e||gs(i.removedNodes,s),e=e&&!gs(i.addedNodes,s);e&&i()}));return n.observe(document,{childList:!0,subtree:!0}),n}const bs=new Map;let xs=0;function _s(){const t=window.devicePixelRatio;t!==xs&&(xs=t,bs.forEach(((e,i)=>{i.currentDevicePixelRatio!==t&&e()})))}function ys(t,e,i){const 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t=this.getDataset(),e=t.data||(t.data=[]),i=this._data;if(o(e))this._data=function(t){const e=Object.keys(t),i=new Array(e.length);let s,n,o;for(s=0,n=e.length;s0&&i._parsed[t-1];if(!1===this._parsing)i._parsed=s,i._sorted=!0,d=s;else{d=n(s[t])?this.parseArrayData(i,s,t,e):o(s[t])?this.parseObjectData(i,s,t,e):this.parsePrimitiveData(i,s,t,e);const a=()=>null===c[l]||f&&c[l]t&&!e.hidden&&e._stacked&&{keys:Ts(i,!0),values:null})(e,i,this.chart),h={min:Number.POSITIVE_INFINITY,max:Number.NEGATIVE_INFINITY},{min:c,max:d}=function(t){const{min:e,max:i,minDefined:s,maxDefined:n}=t.getUserBounds();return{min:s?e:Number.NEGATIVE_INFINITY,max:n?i:Number.POSITIVE_INFINITY}}(r);let u,f;function g(){f=s[u];const e=f[r.axis];return!a(f[t.axis])||c>e||d=0;--u)if(!g()){this.updateRangeFromParsed(h,t,f,l);break}return h}getAllParsedValues(t){const e=this._cachedMeta._parsed,i=[];let s,n,o;for(s=0,n=e.length;s=0&&tthis.getContext(i,s,e)),c);return f.$shared&&(f.$shared=r,n[o]=Object.freeze(Ws(f,r))),f}_resolveAnimations(t,e,i){const s=this.chart,n=this._cachedDataOpts,o=`animation-${e}`,a=n[o];if(a)return a;let r;if(!1!==s.options.animation){const s=this.chart.config,n=s.datasetAnimationScopeKeys(this._type,e),o=s.getOptionScopes(this.getDataset(),n);r=s.createResolver(o,this.getContext(t,i,e))}const l=new Os(s,r&&r.animations);return r&&r._cacheable&&(n[o]=Object.freeze(l)),l}getSharedOptions(t){if(t.$shared)return this._sharedOptions||(this._sharedOptions=Object.assign({},t))}includeOptions(t,e){return!e||Bs(t)||this.chart._animationsDisabled}_getSharedOptions(t,e){const i=this.resolveDataElementOptions(t,e),s=this._sharedOptions,n=this.getSharedOptions(i),o=this.includeOptions(e,n)||n!==s;return this.updateSharedOptions(n,e,i),{sharedOptions:n,includeOptions:o}}updateElement(t,e,i,s){Bs(s)?Object.assign(t,i):this._resolveAnimations(e,s).update(t,i)}updateSharedOptions(t,e,i){t&&!Bs(e)&&this._resolveAnimations(void 0,e).update(t,i)}_setStyle(t,e,i,s){t.active=s;const n=this.getStyle(e,s);this._resolveAnimations(e,i,s).update(t,{options:!s&&this.getSharedOptions(n)||n})}removeHoverStyle(t,e,i){this._setStyle(t,i,"active",!1)}setHoverStyle(t,e,i){this._setStyle(t,i,"active",!0)}_removeDatasetHoverStyle(){const t=this._cachedMeta.dataset;t&&this._setStyle(t,void 0,"active",!1)}_setDatasetHoverStyle(){const t=this._cachedMeta.dataset;t&&this._setStyle(t,void 0,"active",!0)}_resyncElements(t){const e=this._data,i=this._cachedMeta.data;for(const[t,e,i]of this._syncList)this[t](e,i);this._syncList=[];const s=i.length,n=e.length,o=Math.min(n,s);o&&this.parse(0,o),n>s?this._insertElements(s,n-s,t):n{for(t.length+=e,a=t.length-1;a>=o;a--)t[a]=t[a-e]};for(r(n),a=t;a{s[t]=i[t]&&i[t].active()?i[t]._to:this[t]})),s}}function js(t,e){const i=t.options.ticks,n=function(t){const e=t.options.offset,i=t._tickSize(),s=t._length/i+(e?0:1),n=t._maxLength/i;return Math.floor(Math.min(s,n))}(t),o=Math.min(i.maxTicksLimit||n,n),a=i.major.enabled?function(t){const e=[];let i,s;for(i=0,s=t.length;io)return function(t,e,i,s){let n,o=0,a=i[0];for(s=Math.ceil(s),n=0;nn)return e}return Math.max(n,1)}(a,e,o);if(r>0){let t,i;const n=r>1?Math.round((h-l)/(r-1)):null;for($s(e,c,d,s(n)?0:l-n,l),t=0,i=r-1;t"top"===e||"left"===e?t[e]+i:t[e]-i,Us=(t,e)=>Math.min(e||t,t);function Xs(t,e){const i=[],s=t.length/e,n=t.length;let o=0;for(;oa+r)))return h}function Ks(t){return t.drawTicks?t.tickLength:0}function Gs(t,e){if(!t.display)return 0;const i=Si(t.font,e),s=ki(t.padding);return(n(t.text)?t.text.length:1)*i.lineHeight+s.height}function Zs(t,e,i){let s=ut(t);return(i&&"right"!==e||!i&&"right"===e)&&(s=(t=>"left"===t?"right":"right"===t?"left":t)(s)),s}class Js extends Hs{constructor(t){super(),this.id=t.id,this.type=t.type,this.options=void 0,this.ctx=t.ctx,this.chart=t.chart,this.top=void 0,this.bottom=void 0,this.left=void 0,this.right=void 0,this.width=void 0,this.height=void 0,this._margins={left:0,right:0,top:0,bottom:0},this.maxWidth=void 0,this.maxHeight=void 0,this.paddingTop=void 0,this.paddingBottom=void 0,this.paddingLeft=void 0,this.paddingRight=void 0,this.axis=void 0,this.labelRotation=void 0,this.min=void 0,this.max=void 0,this._range=void 0,this.ticks=[],this._gridLineItems=null,this._labelItems=null,this._labelSizes=null,this._length=0,this._maxLength=0,this._longestTextCache={},this._startPixel=void 0,this._endPixel=void 0,this._reversePixels=!1,this._userMax=void 0,this._userMin=void 0,this._suggestedMax=void 0,this._suggestedMin=void 0,this._ticksLength=0,this._borderValue=0,this._cache={},this._dataLimitsCached=!1,this.$context=void 0}init(t){this.options=t.setContext(this.getContext()),this.axis=t.axis,this._userMin=this.parse(t.min),this._userMax=this.parse(t.max),this._suggestedMin=this.parse(t.suggestedMin),this._suggestedMax=this.parse(t.suggestedMax)}parse(t,e){return t}getUserBounds(){let{_userMin:t,_userMax:e,_suggestedMin:i,_suggestedMax:s}=this;return t=r(t,Number.POSITIVE_INFINITY),e=r(e,Number.NEGATIVE_INFINITY),i=r(i,Number.POSITIVE_INFINITY),s=r(s,Number.NEGATIVE_INFINITY),{min:r(t,i),max:r(e,s),minDefined:a(t),maxDefined:a(e)}}getMinMax(t){let e,{min:i,max:s,minDefined:n,maxDefined:o}=this.getUserBounds();if(n&&o)return{min:i,max:s};const a=this.getMatchingVisibleMetas();for(let r=0,l=a.length;rs?s:i,s=n&&i>s?i:s,{min:r(i,r(s,i)),max:r(s,r(i,s))}}getPadding(){return{left:this.paddingLeft||0,top:this.paddingTop||0,right:this.paddingRight||0,bottom:this.paddingBottom||0}}getTicks(){return this.ticks}getLabels(){const t=this.chart.data;return this.options.labels||(this.isHorizontal()?t.xLabels:t.yLabels)||t.labels||[]}getLabelItems(t=this.chart.chartArea){return this._labelItems||(this._labelItems=this._computeLabelItems(t))}beforeLayout(){this._cache={},this._dataLimitsCached=!1}beforeUpdate(){d(this.options.beforeUpdate,[this])}update(t,e,i){const{beginAtZero:s,grace:n,ticks:o}=this.options,a=o.sampleSize;this.beforeUpdate(),this.maxWidth=t,this.maxHeight=e,this._margins=i=Object.assign({left:0,right:0,top:0,bottom:0},i),this.ticks=null,this._labelSizes=null,this._gridLineItems=null,this._labelItems=null,this.beforeSetDimensions(),this.setDimensions(),this.afterSetDimensions(),this._maxLength=this.isHorizontal()?this.width+i.left+i.right:this.height+i.top+i.bottom,this._dataLimitsCached||(this.beforeDataLimits(),this.determineDataLimits(),this.afterDataLimits(),this._range=Di(this,n,s),this._dataLimitsCached=!0),this.beforeBuildTicks(),this.ticks=this.buildTicks()||[],this.afterBuildTicks();const r=a=n||i<=1||!this.isHorizontal())return void(this.labelRotation=s);const h=this._getLabelSizes(),c=h.widest.width,d=h.highest.height,u=J(this.chart.width-c,0,this.maxWidth);o=t.offset?this.maxWidth/i:u/(i-1),c+6>o&&(o=u/(i-(t.offset?.5:1)),a=this.maxHeight-Ks(t.grid)-e.padding-Gs(t.title,this.chart.options.font),r=Math.sqrt(c*c+d*d),l=Y(Math.min(Math.asin(J((h.highest.height+6)/o,-1,1)),Math.asin(J(a/r,-1,1))-Math.asin(J(d/r,-1,1)))),l=Math.max(s,Math.min(n,l))),this.labelRotation=l}afterCalculateLabelRotation(){d(this.options.afterCalculateLabelRotation,[this])}afterAutoSkip(){}beforeFit(){d(this.options.beforeFit,[this])}fit(){const t={width:0,height:0},{chart:e,options:{ticks:i,title:s,grid:n}}=this,o=this._isVisible(),a=this.isHorizontal();if(o){const o=Gs(s,e.options.font);if(a?(t.width=this.maxWidth,t.height=Ks(n)+o):(t.height=this.maxHeight,t.width=Ks(n)+o),i.display&&this.ticks.length){const{first:e,last:s,widest:n,highest:o}=this._getLabelSizes(),r=2*i.padding,l=$(this.labelRotation),h=Math.cos(l),c=Math.sin(l);if(a){const e=i.mirror?0:c*n.width+h*o.height;t.height=Math.min(this.maxHeight,t.height+e+r)}else{const e=i.mirror?0:h*n.width+c*o.height;t.width=Math.min(this.maxWidth,t.width+e+r)}this._calculatePadding(e,s,c,h)}}this._handleMargins(),a?(this.width=this._length=e.width-this._margins.left-this._margins.right,this.height=t.height):(this.width=t.width,this.height=this._length=e.height-this._margins.top-this._margins.bottom)}_calculatePadding(t,e,i,s){const{ticks:{align:n,padding:o},position:a}=this.options,r=0!==this.labelRotation,l="top"!==a&&"x"===this.axis;if(this.isHorizontal()){const a=this.getPixelForTick(0)-this.left,h=this.right-this.getPixelForTick(this.ticks.length-1);let c=0,d=0;r?l?(c=s*t.width,d=i*e.height):(c=i*t.height,d=s*e.width):"start"===n?d=e.width:"end"===n?c=t.width:"inner"!==n&&(c=t.width/2,d=e.width/2),this.paddingLeft=Math.max((c-a+o)*this.width/(this.width-a),0),this.paddingRight=Math.max((d-h+o)*this.width/(this.width-h),0)}else{let i=e.height/2,s=t.height/2;"start"===n?(i=0,s=t.height):"end"===n&&(i=e.height,s=0),this.paddingTop=i+o,this.paddingBottom=s+o}}_handleMargins(){this._margins&&(this._margins.left=Math.max(this.paddingLeft,this._margins.left),this._margins.top=Math.max(this.paddingTop,this._margins.top),this._margins.right=Math.max(this.paddingRight,this._margins.right),this._margins.bottom=Math.max(this.paddingBottom,this._margins.bottom))}afterFit(){d(this.options.afterFit,[this])}isHorizontal(){const{axis:t,position:e}=this.options;return"top"===e||"bottom"===e||"x"===t}isFullSize(){return this.options.fullSize}_convertTicksToLabels(t){let e,i;for(this.beforeTickToLabelConversion(),this.generateTickLabels(t),e=0,i=t.length;e{const i=t.gc,s=i.length/2;let n;if(s>e){for(n=0;n({width:r[t]||0,height:l[t]||0});return{first:P(0),last:P(e-1),widest:P(k),highest:P(S),widths:r,heights:l}}getLabelForValue(t){return t}getPixelForValue(t,e){return NaN}getValueForPixel(t){}getPixelForTick(t){const e=this.ticks;return t<0||t>e.length-1?null:this.getPixelForValue(e[t].value)}getPixelForDecimal(t){this._reversePixels&&(t=1-t);const e=this._startPixel+t*this._length;return Q(this._alignToPixels?Ae(this.chart,e,0):e)}getDecimalForPixel(t){const e=(t-this._startPixel)/this._length;return this._reversePixels?1-e:e}getBasePixel(){return this.getPixelForValue(this.getBaseValue())}getBaseValue(){const{min:t,max:e}=this;return t<0&&e<0?e:t>0&&e>0?t:0}getContext(t){const e=this.ticks||[];if(t>=0&&ta*s?a/i:r/s:r*s0}_computeGridLineItems(t){const e=this.axis,i=this.chart,s=this.options,{grid:n,position:a,border:r}=s,h=n.offset,c=this.isHorizontal(),d=this.ticks.length+(h?1:0),u=Ks(n),f=[],g=r.setContext(this.getContext()),p=g.display?g.width:0,m=p/2,b=function(t){return Ae(i,t,p)};let x,_,y,v,M,w,k,S,P,D,C,O;if("top"===a)x=b(this.bottom),w=this.bottom-u,S=x-m,D=b(t.top)+m,O=t.bottom;else if("bottom"===a)x=b(this.top),D=t.top,O=b(t.bottom)-m,w=x+m,S=this.top+u;else if("left"===a)x=b(this.right),M=this.right-u,k=x-m,P=b(t.left)+m,C=t.right;else if("right"===a)x=b(this.left),P=t.left,C=b(t.right)-m,M=x+m,k=this.left+u;else if("x"===e){if("center"===a)x=b((t.top+t.bottom)/2+.5);else if(o(a)){const t=Object.keys(a)[0],e=a[t];x=b(this.chart.scales[t].getPixelForValue(e))}D=t.top,O=t.bottom,w=x+m,S=w+u}else if("y"===e){if("center"===a)x=b((t.left+t.right)/2);else if(o(a)){const t=Object.keys(a)[0],e=a[t];x=b(this.chart.scales[t].getPixelForValue(e))}M=x-m,k=M-u,P=t.left,C=t.right}const A=l(s.ticks.maxTicksLimit,d),T=Math.max(1,Math.ceil(d/A));for(_=0;_e.value===t));if(i>=0){return e.setContext(this.getContext(i)).lineWidth}return 0}drawGrid(t){const e=this.options.grid,i=this.ctx,s=this._gridLineItems||(this._gridLineItems=this._computeGridLineItems(t));let n,o;const a=(t,e,s)=>{s.width&&s.color&&(i.save(),i.lineWidth=s.width,i.strokeStyle=s.color,i.setLineDash(s.borderDash||[]),i.lineDashOffset=s.borderDashOffset,i.beginPath(),i.moveTo(t.x,t.y),i.lineTo(e.x,e.y),i.stroke(),i.restore())};if(e.display)for(n=0,o=s.length;n{this.drawBackground(),this.drawGrid(t),this.drawTitle()}},{z:s,draw:()=>{this.drawBorder()}},{z:e,draw:t=>{this.drawLabels(t)}}]:[{z:e,draw:t=>{this.draw(t)}}]}getMatchingVisibleMetas(t){const e=this.chart.getSortedVisibleDatasetMetas(),i=this.axis+"AxisID",s=[];let n,o;for(n=0,o=e.length;n{const s=i.split("."),n=s.pop(),o=[t].concat(s).join("."),a=e[i].split("."),r=a.pop(),l=a.join(".");ue.route(o,n,l,r)}))}(e,t.defaultRoutes);t.descriptors&&ue.describe(e,t.descriptors)}(t,o,i),this.override&&ue.override(t.id,t.overrides)),o}get(t){return this.items[t]}unregister(t){const e=this.items,i=t.id,s=this.scope;i in e&&delete e[i],s&&i in ue[s]&&(delete ue[s][i],this.override&&delete re[i])}}class tn{constructor(){this.controllers=new Qs(Ns,"datasets",!0),this.elements=new Qs(Hs,"elements"),this.plugins=new Qs(Object,"plugins"),this.scales=new Qs(Js,"scales"),this._typedRegistries=[this.controllers,this.scales,this.elements]}add(...t){this._each("register",t)}remove(...t){this._each("unregister",t)}addControllers(...t){this._each("register",t,this.controllers)}addElements(...t){this._each("register",t,this.elements)}addPlugins(...t){this._each("register",t,this.plugins)}addScales(...t){this._each("register",t,this.scales)}getController(t){return this._get(t,this.controllers,"controller")}getElement(t){return this._get(t,this.elements,"element")}getPlugin(t){return this._get(t,this.plugins,"plugin")}getScale(t){return this._get(t,this.scales,"scale")}removeControllers(...t){this._each("unregister",t,this.controllers)}removeElements(...t){this._each("unregister",t,this.elements)}removePlugins(...t){this._each("unregister",t,this.plugins)}removeScales(...t){this._each("unregister",t,this.scales)}_each(t,e,i){[...e].forEach((e=>{const s=i||this._getRegistryForType(e);i||s.isForType(e)||s===this.plugins&&e.id?this._exec(t,s,e):u(e,(e=>{const s=i||this._getRegistryForType(e);this._exec(t,s,e)}))}))}_exec(t,e,i){const s=w(t);d(i["before"+s],[],i),e[t](i),d(i["after"+s],[],i)}_getRegistryForType(t){for(let e=0;et.filter((t=>!e.some((e=>t.plugin.id===e.plugin.id))));this._notify(s(e,i),t,"stop"),this._notify(s(i,e),t,"start")}}function nn(t,e){return e||!1!==t?!0===t?{}:t:null}function on(t,{plugin:e,local:i},s,n){const o=t.pluginScopeKeys(e),a=t.getOptionScopes(s,o);return i&&e.defaults&&a.push(e.defaults),t.createResolver(a,n,[""],{scriptable:!1,indexable:!1,allKeys:!0})}function an(t,e){const i=ue.datasets[t]||{};return((e.datasets||{})[t]||{}).indexAxis||e.indexAxis||i.indexAxis||"x"}function rn(t){if("x"===t||"y"===t||"r"===t)return t}function ln(t,...e){if(rn(t))return t;for(const s of e){const e=s.axis||("top"===(i=s.position)||"bottom"===i?"x":"left"===i||"right"===i?"y":void 0)||t.length>1&&rn(t[0].toLowerCase());if(e)return e}var i;throw new Error(`Cannot determine type of '${t}' axis. 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0,this._doResize=dt((t=>this.update(t)),a.resizeDelay||0),this._dataChanges=[],Pn[this.id]=this,r&&l?(xt.listen(this,"complete",wn),xt.listen(this,"progress",kn),this._initialize(),this.attached&&this.update()):console.error("Failed to create chart: can't acquire context from the given item")}get aspectRatio(){const{options:{aspectRatio:t,maintainAspectRatio:e},width:i,height:n,_aspectRatio:o}=this;return s(t)?e&&o?o:n?i/n:null:t}get data(){return this.config.data}set data(t){this.config.data=t}get options(){return this._options}set options(t){this.config.options=t}get registry(){return en}_initialize(){return this.notifyPlugins("beforeInit"),this.options.responsive?this.resize():ke(this,this.options.devicePixelRatio),this.bindEvents(),this.notifyPlugins("afterInit"),this}clear(){return Te(this.canvas,this.ctx),this}stop(){return xt.stop(this),this}resize(t,e){xt.running(this)?this._resizeBeforeDraw={width:t,height:e}:this._resize(t,e)}_resize(t,e){const i=this.options,s=this.canvas,n=i.maintainAspectRatio&&this.aspectRatio,o=this.platform.getMaximumSize(s,t,e,n),a=i.devicePixelRatio||this.platform.getDevicePixelRatio(),r=this.width?"resize":"attach";this.width=o.width,this.height=o.height,this._aspectRatio=this.aspectRatio,ke(this,a,!0)&&(this.notifyPlugins("resize",{size:o}),d(i.onResize,[this,o],this),this.attached&&this._doResize(r)&&this.render())}ensureScalesHaveIDs(){u(this.options.scales||{},((t,e)=>{t.id=e}))}buildOrUpdateScales(){const t=this.options,e=t.scales,i=this.scales,s=Object.keys(i).reduce(((t,e)=>(t[e]=!1,t)),{});let n=[];e&&(n=n.concat(Object.keys(e).map((t=>{const i=e[t],s=ln(t,i),n="r"===s,o="x"===s;return{options:i,dposition:n?"chartArea":o?"bottom":"left",dtype:n?"radialLinear":o?"category":"linear"}})))),u(n,(e=>{const n=e.options,o=n.id,a=ln(o,n),r=l(n.type,e.dtype);void 0!==n.position&&vn(n.position,a)===vn(e.dposition)||(n.position=e.dposition),s[o]=!0;let h=null;if(o in 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i=this._options=e.createResolver(e.chartOptionScopes(),this.getContext()),s=this._animationsDisabled=!i.animation;if(this._updateScales(),this._checkEventBindings(),this._updateHiddenIndices(),this._plugins.invalidate(),!1===this.notifyPlugins("beforeUpdate",{mode:t,cancelable:!0}))return;const n=this.buildOrUpdateControllers();this.notifyPlugins("beforeElementsUpdate");let o=0;for(let t=0,e=this.data.datasets.length;t{t.reset()})),this._updateDatasets(t),this.notifyPlugins("afterUpdate",{mode:t}),this._layers.sort(Mn("z","_idx"));const{_active:a,_lastEvent:r}=this;r?this._eventHandler(r,!0):a.length&&this._updateHoverStyles(a,a,!0),this.render()}_updateScales(){u(this.scales,(t=>{as.removeBox(this,t)})),this.ensureScalesHaveIDs(),this.buildOrUpdateScales()}_checkEventBindings(){const t=this.options,e=new Set(Object.keys(this._listeners)),i=new Set(t.events);P(e,i)&&!!this._responsiveListeners===t.responsive||(this.unbindEvents(),this.bindEvents())}_updateHiddenIndices(){const{_hiddenIndices:t}=this,e=this._getUniformDataChanges()||[];for(const{method:i,start:s,count:n}of e){Cn(t,s,"_removeElements"===i?-n:n)}}_getUniformDataChanges(){const t=this._dataChanges;if(!t||!t.length)return;this._dataChanges=[];const e=this.data.datasets.length,i=e=>new Set(t.filter((t=>t[0]===e)).map(((t,e)=>e+","+t.splice(1).join(",")))),s=i(0);for(let t=1;tt.split(","))).map((t=>({method:t[1],start:+t[2],count:+t[3]})))}_updateLayout(t){if(!1===this.notifyPlugins("beforeLayout",{cancelable:!0}))return;as.update(this,this.width,this.height,t);const e=this.chartArea,i=e.width<=0||e.height<=0;this._layers=[],u(this.boxes,(t=>{i&&"chartArea"===t.position||(t.configure&&t.configure(),this._layers.push(...t._layers()))}),this),this._layers.forEach(((t,e)=>{t._idx=e})),this.notifyPlugins("afterLayout")}_updateDatasets(t){if(!1!==this.notifyPlugins("beforeDatasetsUpdate",{mode:t,cancelable:!0})){for(let t=0,e=this.data.datasets.length;t=0;--e)this._drawDataset(t[e]);this.notifyPlugins("afterDatasetsDraw")}_drawDataset(t){const e=this.ctx,i=t._clip,s=!i.disabled,n=function(t,e){const{xScale:i,yScale:s}=t;return i&&s?{left:On(i,e,"left"),right:On(i,e,"right"),top:On(s,e,"top"),bottom:On(s,e,"bottom")}:e}(t,this.chartArea),o={meta:t,index:t.index,cancelable:!0};!1!==this.notifyPlugins("beforeDatasetDraw",o)&&(s&&Ie(e,{left:!1===i.left?0:n.left-i.left,right:!1===i.right?this.width:n.right+i.right,top:!1===i.top?0:n.top-i.top,bottom:!1===i.bottom?this.height:n.bottom+i.bottom}),t.controller.draw(),s&&ze(e),o.cancelable=!1,this.notifyPlugins("afterDatasetDraw",o))}isPointInArea(t){return Re(t,this.chartArea,this._minPadding)}getElementsAtEventForMode(t,e,i,s){const n=Xi.modes[e];return"function"==typeof n?n(this,t,i,s):[]}getDatasetMeta(t){const e=this.data.datasets[t],i=this._metasets;let s=i.filter((t=>t&&t._dataset===e)).pop();return s||(s={type:null,data:[],dataset:null,controller:null,hidden:null,xAxisID:null,yAxisID:null,order:e&&e.order||0,index:t,_dataset:e,_parsed:[],_sorted:!1},i.push(s)),s}getContext(){return this.$context||(this.$context=Ci(null,{chart:this,type:"chart"}))}getVisibleDatasetCount(){return this.getSortedVisibleDatasetMetas().length}isDatasetVisible(t){const e=this.data.datasets[t];if(!e)return!1;const i=this.getDatasetMeta(t);return"boolean"==typeof i.hidden?!i.hidden:!e.hidden}setDatasetVisibility(t,e){this.getDatasetMeta(t).hidden=!e}toggleDataVisibility(t){this._hiddenIndices[t]=!this._hiddenIndices[t]}getDataVisibility(t){return!this._hiddenIndices[t]}_updateVisibility(t,e,i){const s=i?"show":"hide",n=this.getDatasetMeta(t),o=n.controller._resolveAnimations(void 0,s);k(e)?(n.data[e].hidden=!i,this.update()):(this.setDatasetVisibility(t,i),o.update(n,{visible:i}),this.update((e=>e.datasetIndex===t?s:void 0)))}hide(t,e){this._updateVisibility(t,e,!1)}show(t,e){this._updateVisibility(t,e,!0)}_destroyDatasetMeta(t){const e=this._metasets[t];e&&e.controller&&e.controller._destroy(),delete this._metasets[t]}_stop(){let t,e;for(this.stop(),xt.remove(this),t=0,e=this.data.datasets.length;t{e.addEventListener(this,i,s),t[i]=s},s=(t,e,i)=>{t.offsetX=e,t.offsetY=i,this._eventHandler(t)};u(this.options.events,(t=>i(t,s)))}bindResponsiveEvents(){this._responsiveListeners||(this._responsiveListeners={});const t=this._responsiveListeners,e=this.platform,i=(i,s)=>{e.addEventListener(this,i,s),t[i]=s},s=(i,s)=>{t[i]&&(e.removeEventListener(this,i,s),delete t[i])},n=(t,e)=>{this.canvas&&this.resize(t,e)};let o;const a=()=>{s("attach",a),this.attached=!0,this.resize(),i("resize",n),i("detach",o)};o=()=>{this.attached=!1,s("resize",n),this._stop(),this._resize(0,0),i("attach",a)},e.isAttached(this.canvas)?a():o()}unbindEvents(){u(this._listeners,((t,e)=>{this.platform.removeEventListener(this,e,t)})),this._listeners={},u(this._responsiveListeners,((t,e)=>{this.platform.removeEventListener(this,e,t)})),this._responsiveListeners=void 0}updateHoverStyle(t,e,i){const s=i?"set":"remove";let n,o,a,r;for("dataset"===e&&(n=this.getDatasetMeta(t[0].datasetIndex),n.controller["_"+s+"DatasetHoverStyle"]()),a=0,r=t.length;a{const i=this.getDatasetMeta(t);if(!i)throw new Error("No dataset found at index "+t);return{datasetIndex:t,element:i.data[e],index:e}}));!f(i,e)&&(this._active=i,this._lastEvent=null,this._updateHoverStyles(i,e))}notifyPlugins(t,e,i){return this._plugins.notify(this,t,e,i)}isPluginEnabled(t){return 1===this._plugins._cache.filter((e=>e.plugin.id===t)).length}_updateHoverStyles(t,e,i){const s=this.options.hover,n=(t,e)=>t.filter((t=>!e.some((e=>t.datasetIndex===e.datasetIndex&&t.index===e.index)))),o=n(e,t),a=i?t:n(t,e);o.length&&this.updateHoverStyle(o,s.mode,!1),a.length&&s.mode&&this.updateHoverStyle(a,s.mode,!0)}_eventHandler(t,e){const i={event:t,replay:e,cancelable:!0,inChartArea:this.isPointInArea(t)},s=e=>(e.options.events||this.options.events).includes(t.native.type);if(!1===this.notifyPlugins("beforeEvent",i,s))return;const n=this._handleEvent(t,e,i.inChartArea);return i.cancelable=!1,this.notifyPlugins("afterEvent",i,s),(n||i.changed)&&this.render(),this}_handleEvent(t,e,i){const{_active:s=[],options:n}=this,o=e,a=this._getActiveElements(t,s,i,o),r=D(t),l=function(t,e,i,s){return i&&"mouseout"!==t.type?s?e:t:null}(t,this._lastEvent,i,r);i&&(this._lastEvent=null,d(n.onHover,[t,a,this],this),r&&d(n.onClick,[t,a,this],this));const h=!f(a,s);return(h||e)&&(this._active=a,this._updateHoverStyles(a,s,e)),this._lastEvent=l,h}_getActiveElements(t,e,i,s){if("mouseout"===t.type)return[];if(!i)return e;const n=this.options.hover;return this.getElementsAtEventForMode(t,n.mode,n,s)}}function Tn(){return u(An.instances,(t=>t._plugins.invalidate()))}function Ln(){throw new Error("This method is not implemented: Check that a complete date adapter is provided.")}class En{static override(t){Object.assign(En.prototype,t)}options;constructor(t){this.options=t||{}}init(){}formats(){return Ln()}parse(){return Ln()}format(){return Ln()}add(){return Ln()}diff(){return Ln()}startOf(){return Ln()}endOf(){return Ln()}}var Rn={_date:En};function In(t){const e=t.iScale,i=function(t,e){if(!t._cache.$bar){const i=t.getMatchingVisibleMetas(e);let s=[];for(let e=0,n=i.length;et-e)))}return t._cache.$bar}(e,t.type);let s,n,o,a,r=e._length;const l=()=>{32767!==o&&-32768!==o&&(k(a)&&(r=Math.min(r,Math.abs(o-a)||r)),a=o)};for(s=0,n=i.length;sMath.abs(r)&&(l=r,h=a),e[i.axis]=h,e._custom={barStart:l,barEnd:h,start:n,end:o,min:a,max:r}}(t,e,i,s):e[i.axis]=i.parse(t,s),e}function Fn(t,e,i,s){const n=t.iScale,o=t.vScale,a=n.getLabels(),r=n===o,l=[];let h,c,d,u;for(h=i,c=i+s;ht.x,i="left",s="right"):(e=t.base"spacing"!==t,_indexable:t=>"spacing"!==t&&!t.startsWith("borderDash")&&!t.startsWith("hoverBorderDash")};static overrides={aspectRatio:1,plugins:{legend:{labels:{generateLabels(t){const e=t.data;if(e.labels.length&&e.datasets.length){const{labels:{pointStyle:i,color:s}}=t.legend.options;return e.labels.map(((e,n)=>{const o=t.getDatasetMeta(0).controller.getStyle(n);return{text:e,fillStyle:o.backgroundColor,strokeStyle:o.borderColor,fontColor:s,lineWidth:o.borderWidth,pointStyle:i,hidden:!t.getDataVisibility(n),index:n}}))}return[]}},onClick(t,e,i){i.chart.toggleDataVisibility(e.index),i.chart.update()}}}};constructor(t,e){super(t,e),this.enableOptionSharing=!0,this.innerRadius=void 0,this.outerRadius=void 0,this.offsetX=void 0,this.offsetY=void 0}linkScales(){}parse(t,e){const i=this.getDataset().data,s=this._cachedMeta;if(!1===this._parsing)s._parsed=i;else{let n,a,r=t=>+i[t];if(o(i[t])){const{key:t="value"}=this._parsing;r=e=>+M(i[e],t)}for(n=t,a=t+e;nZ(t,r,l,!0)?1:Math.max(e,e*i,s,s*i),g=(t,e,s)=>Z(t,r,l,!0)?-1:Math.min(e,e*i,s,s*i),p=f(0,h,d),m=f(E,c,u),b=g(C,h,d),x=g(C+E,c,u);s=(p-b)/2,n=(m-x)/2,o=-(p+b)/2,a=-(m+x)/2}return{ratioX:s,ratioY:n,offsetX:o,offsetY:a}}(u,d,r),b=(i.width-o)/f,x=(i.height-o)/g,_=Math.max(Math.min(b,x)/2,0),y=c(this.options.radius,_),v=(y-Math.max(y*r,0))/this._getVisibleDatasetWeightTotal();this.offsetX=p*y,this.offsetY=m*y,s.total=this.calculateTotal(),this.outerRadius=y-v*this._getRingWeightOffset(this.index),this.innerRadius=Math.max(this.outerRadius-v*l,0),this.updateElements(n,0,n.length,t)}_circumference(t,e){const i=this.options,s=this._cachedMeta,n=this._getCircumference();return e&&i.animation.animateRotate||!this.chart.getDataVisibility(t)||null===s._parsed[t]||s.data[t].hidden?0:this.calculateCircumference(s._parsed[t]*n/O)}updateElements(t,e,i,s){const n="reset"===s,o=this.chart,a=o.chartArea,r=o.options.animation,l=(a.left+a.right)/2,h=(a.top+a.bottom)/2,c=n&&r.animateScale,d=c?0:this.innerRadius,u=c?0:this.outerRadius,{sharedOptions:f,includeOptions:g}=this._getSharedOptions(e,s);let p,m=this._getRotation();for(p=0;p0&&!isNaN(t)?O*(Math.abs(t)/e):0}getLabelAndValue(t){const e=this._cachedMeta,i=this.chart,s=i.data.labels||[],n=ne(e._parsed[t],i.options.locale);return{label:s[t]||"",value:n}}getMaxBorderWidth(t){let e=0;const i=this.chart;let s,n,o,a,r;if(!t)for(s=0,n=i.data.datasets.length;s{const o=t.getDatasetMeta(0).controller.getStyle(n);return{text:e,fillStyle:o.backgroundColor,strokeStyle:o.borderColor,fontColor:s,lineWidth:o.borderWidth,pointStyle:i,hidden:!t.getDataVisibility(n),index:n}}))}return[]}},onClick(t,e,i){i.chart.toggleDataVisibility(e.index),i.chart.update()}}},scales:{r:{type:"radialLinear",angleLines:{display:!1},beginAtZero:!0,grid:{circular:!0},pointLabels:{display:!1},startAngle:0}}};constructor(t,e){super(t,e),this.innerRadius=void 0,this.outerRadius=void 0}getLabelAndValue(t){const e=this._cachedMeta,i=this.chart,s=i.data.labels||[],n=ne(e._parsed[t].r,i.options.locale);return{label:s[t]||"",value:n}}parseObjectData(t,e,i,s){return ii.bind(this)(t,e,i,s)}update(t){const e=this._cachedMeta.data;this._updateRadius(),this.updateElements(e,0,e.length,t)}getMinMax(){const t=this._cachedMeta,e={min:Number.POSITIVE_INFINITY,max:Number.NEGATIVE_INFINITY};return t.data.forEach(((t,i)=>{const s=this.getParsed(i).r;!isNaN(s)&&this.chart.getDataVisibility(i)&&(se.max&&(e.max=s))})),e}_updateRadius(){const t=this.chart,e=t.chartArea,i=t.options,s=Math.min(e.right-e.left,e.bottom-e.top),n=Math.max(s/2,0),o=(n-Math.max(i.cutoutPercentage?n/100*i.cutoutPercentage:1,0))/t.getVisibleDatasetCount();this.outerRadius=n-o*this.index,this.innerRadius=this.outerRadius-o}updateElements(t,e,i,s){const n="reset"===s,o=this.chart,a=o.options.animation,r=this._cachedMeta.rScale,l=r.xCenter,h=r.yCenter,c=r.getIndexAngle(0)-.5*C;let d,u=c;const f=360/this.countVisibleElements();for(d=0;d{!isNaN(this.getParsed(i).r)&&this.chart.getDataVisibility(i)&&e++})),e}_computeAngle(t,e,i){return this.chart.getDataVisibility(t)?$(this.resolveDataElementOptions(t,e).angle||i):0}}var Yn=Object.freeze({__proto__:null,BarController:class extends Ns{static id="bar";static defaults={datasetElementType:!1,dataElementType:"bar",categoryPercentage:.8,barPercentage:.9,grouped:!0,animations:{numbers:{type:"number",properties:["x","y","base","width","height"]}}};static overrides={scales:{_index_:{type:"category",offset:!0,grid:{offset:!0}},_value_:{type:"linear",beginAtZero:!0}}};parsePrimitiveData(t,e,i,s){return Fn(t,e,i,s)}parseArrayData(t,e,i,s){return Fn(t,e,i,s)}parseObjectData(t,e,i,s){const{iScale:n,vScale:o}=t,{xAxisKey:a="x",yAxisKey:r="y"}=this._parsing,l="x"===n.axis?a:r,h="x"===o.axis?a:r,c=[];let d,u,f,g;for(d=i,u=i+s;dt.controller.options.grouped)),o=i.options.stacked,a=[],r=t=>{const i=t.controller.getParsed(e),n=i&&i[t.vScale.axis];if(s(n)||isNaN(n))return!0};for(const i of n)if((void 0===e||!r(i))&&((!1===o||-1===a.indexOf(i.stack)||void 0===o&&void 0===i.stack)&&a.push(i.stack),i.index===t))break;return a.length||a.push(void 0),a}_getStackCount(t){return this._getStacks(void 0,t).length}_getStackIndex(t,e,i){const s=this._getStacks(t,i),n=void 0!==e?s.indexOf(e):-1;return-1===n?s.length-1:n}_getRuler(){const t=this.options,e=this._cachedMeta,i=e.iScale,s=[];let n,o;for(n=0,o=e.data.length;n=i?1:-1)}(u,e,r)*a,f===r&&(b-=u/2);const t=e.getPixelForDecimal(0),s=e.getPixelForDecimal(1),o=Math.min(t,s),h=Math.max(t,s);b=Math.max(Math.min(b,h),o),d=b+u,i&&!c&&(l._stacks[e.axis]._visualValues[n]=e.getValueForPixel(d)-e.getValueForPixel(b))}if(b===e.getPixelForValue(r)){const t=F(u)*e.getLineWidthForValue(r)/2;b+=t,u-=t}return{size:u,base:b,head:d,center:d+u/2}}_calculateBarIndexPixels(t,e){const i=e.scale,n=this.options,o=n.skipNull,a=l(n.maxBarThickness,1/0);let r,h;if(e.grouped){const i=o?this._getStackCount(t):e.stackCount,l="flex"===n.barThickness?function(t,e,i,s){const n=e.pixels,o=n[t];let a=t>0?n[t-1]:null,r=t=0;--i)e=Math.max(e,t[i].size(this.resolveDataElementOptions(i))/2);return e>0&&e}getLabelAndValue(t){const e=this._cachedMeta,i=this.chart.data.labels||[],{xScale:s,yScale:n}=e,o=this.getParsed(t),a=s.getLabelForValue(o.x),r=n.getLabelForValue(o.y),l=o._custom;return{label:i[t]||"",value:"("+a+", "+r+(l?", "+l:"")+")"}}update(t){const e=this._cachedMeta.data;this.updateElements(e,0,e.length,t)}updateElements(t,e,i,s){const n="reset"===s,{iScale:o,vScale:a}=this._cachedMeta,{sharedOptions:r,includeOptions:l}=this._getSharedOptions(e,s),h=o.axis,c=a.axis;for(let d=e;d0&&this.getParsed(e-1);for(let i=0;i<_;++i){const g=t[i],_=b?g:{};if(i=x){_.skip=!0;continue}const v=this.getParsed(i),M=s(v[f]),w=_[u]=a.getPixelForValue(v[u],i),k=_[f]=o||M?r.getBasePixel():r.getPixelForValue(l?this.applyStack(r,v,l):v[f],i);_.skip=isNaN(w)||isNaN(k)||M,_.stop=i>0&&Math.abs(v[u]-y[u])>m,p&&(_.parsed=v,_.raw=h.data[i]),d&&(_.options=c||this.resolveDataElementOptions(i,g.active?"active":n)),b||this.updateElement(g,i,_,n),y=v}}getMaxOverflow(){const t=this._cachedMeta,e=t.dataset,i=e.options&&e.options.borderWidth||0,s=t.data||[];if(!s.length)return i;const n=s[0].size(this.resolveDataElementOptions(0)),o=s[s.length-1].size(this.resolveDataElementOptions(s.length-1));return Math.max(i,n,o)/2}draw(){const t=this._cachedMeta;t.dataset.updateControlPoints(this.chart.chartArea,t.iScale.axis),super.draw()}},PieController:class extends jn{static id="pie";static defaults={cutout:0,rotation:0,circumference:360,radius:"100%"}},PolarAreaController:$n,RadarController:class extends Ns{static id="radar";static defaults={datasetElementType:"line",dataElementType:"point",indexAxis:"r",showLine:!0,elements:{line:{fill:"start"}}};static overrides={aspectRatio:1,scales:{r:{type:"radialLinear"}}};getLabelAndValue(t){const e=this._cachedMeta.vScale,i=this.getParsed(t);return{label:e.getLabels()[t],value:""+e.getLabelForValue(i[e.axis])}}parseObjectData(t,e,i,s){return ii.bind(this)(t,e,i,s)}update(t){const e=this._cachedMeta,i=e.dataset,s=e.data||[],n=e.iScale.getLabels();if(i.points=s,"resize"!==t){const e=this.resolveDatasetElementOptions(t);this.options.showLine||(e.borderWidth=0);const o={_loop:!0,_fullLoop:n.length===s.length,options:e};this.updateElement(i,void 0,o,t)}this.updateElements(s,0,s.length,t)}updateElements(t,e,i,s){const n=this._cachedMeta.rScale,o="reset"===s;for(let a=e;a0&&this.getParsed(e-1);for(let c=e;c0&&Math.abs(i[f]-_[f])>b,m&&(p.parsed=i,p.raw=h.data[c]),u&&(p.options=d||this.resolveDataElementOptions(c,e.active?"active":n)),x||this.updateElement(e,c,p,n),_=i}this.updateSharedOptions(d,n,c)}getMaxOverflow(){const t=this._cachedMeta,e=t.data||[];if(!this.options.showLine){let t=0;for(let i=e.length-1;i>=0;--i)t=Math.max(t,e[i].size(this.resolveDataElementOptions(i))/2);return t>0&&t}const i=t.dataset,s=i.options&&i.options.borderWidth||0;if(!e.length)return s;const n=e[0].size(this.resolveDataElementOptions(0)),o=e[e.length-1].size(this.resolveDataElementOptions(e.length-1));return Math.max(s,n,o)/2}}});function Un(t,e,i,s){const n=vi(t.options.borderRadius,["outerStart","outerEnd","innerStart","innerEnd"]);const o=(i-e)/2,a=Math.min(o,s*e/2),r=t=>{const e=(i-Math.min(o,t))*s/2;return J(t,0,Math.min(o,e))};return{outerStart:r(n.outerStart),outerEnd:r(n.outerEnd),innerStart:J(n.innerStart,0,a),innerEnd:J(n.innerEnd,0,a)}}function Xn(t,e,i,s){return{x:i+t*Math.cos(e),y:s+t*Math.sin(e)}}function qn(t,e,i,s,n,o){const{x:a,y:r,startAngle:l,pixelMargin:h,innerRadius:c}=e,d=Math.max(e.outerRadius+s+i-h,0),u=c>0?c+s+i+h:0;let f=0;const g=n-l;if(s){const t=((c>0?c-s:0)+(d>0?d-s:0))/2;f=(g-(0!==t?g*t/(t+s):g))/2}const p=(g-Math.max(.001,g*d-i/C)/d)/2,m=l+p+f,b=n-p-f,{outerStart:x,outerEnd:_,innerStart:y,innerEnd:v}=Un(e,u,d,b-m),M=d-x,w=d-_,k=m+x/M,S=b-_/w,P=u+y,D=u+v,O=m+y/P,A=b-v/D;if(t.beginPath(),o){const e=(k+S)/2;if(t.arc(a,r,d,k,e),t.arc(a,r,d,e,S),_>0){const e=Xn(w,S,a,r);t.arc(e.x,e.y,_,S,b+E)}const i=Xn(D,b,a,r);if(t.lineTo(i.x,i.y),v>0){const e=Xn(D,A,a,r);t.arc(e.x,e.y,v,b+E,A+Math.PI)}const s=(b-v/u+(m+y/u))/2;if(t.arc(a,r,u,b-v/u,s,!0),t.arc(a,r,u,s,m+y/u,!0),y>0){const e=Xn(P,O,a,r);t.arc(e.x,e.y,y,O+Math.PI,m-E)}const n=Xn(M,m,a,r);if(t.lineTo(n.x,n.y),x>0){const e=Xn(M,k,a,r);t.arc(e.x,e.y,x,m-E,k)}}else{t.moveTo(a,r);const e=Math.cos(k)*d+a,i=Math.sin(k)*d+r;t.lineTo(e,i);const s=Math.cos(S)*d+a,n=Math.sin(S)*d+r;t.lineTo(s,n)}t.closePath()}function Kn(t,e,i,s,n){const{fullCircles:o,startAngle:a,circumference:r,options:l}=e,{borderWidth:h,borderJoinStyle:c,borderDash:d,borderDashOffset:u}=l,f="inner"===l.borderAlign;if(!h)return;t.setLineDash(d||[]),t.lineDashOffset=u,f?(t.lineWidth=2*h,t.lineJoin=c||"round"):(t.lineWidth=h,t.lineJoin=c||"bevel");let g=e.endAngle;if(o){qn(t,e,i,s,g,n);for(let e=0;en?(h=n/l,t.arc(o,a,l,i+h,s-h,!0)):t.arc(o,a,n,i+E,s-E),t.closePath(),t.clip()}(t,e,g),o||(qn(t,e,i,s,g,n),t.stroke())}function Gn(t,e,i=e){t.lineCap=l(i.borderCapStyle,e.borderCapStyle),t.setLineDash(l(i.borderDash,e.borderDash)),t.lineDashOffset=l(i.borderDashOffset,e.borderDashOffset),t.lineJoin=l(i.borderJoinStyle,e.borderJoinStyle),t.lineWidth=l(i.borderWidth,e.borderWidth),t.strokeStyle=l(i.borderColor,e.borderColor)}function Zn(t,e,i){t.lineTo(i.x,i.y)}function Jn(t,e,i={}){const s=t.length,{start:n=0,end:o=s-1}=i,{start:a,end:r}=e,l=Math.max(n,a),h=Math.min(o,r),c=nr&&o>r;return{count:s,start:l,loop:e.loop,ilen:h(a+(h?r-t:t))%o,_=()=>{f!==g&&(t.lineTo(m,g),t.lineTo(m,f),t.lineTo(m,p))};for(l&&(d=n[x(0)],t.moveTo(d.x,d.y)),c=0;c<=r;++c){if(d=n[x(c)],d.skip)continue;const e=d.x,i=d.y,s=0|e;s===u?(ig&&(g=i),m=(b*m+e)/++b):(_(),t.lineTo(e,i),u=s,b=0,f=g=i),p=i}_()}function eo(t){const e=t.options,i=e.borderDash&&e.borderDash.length;return!(t._decimated||t._loop||e.tension||"monotone"===e.cubicInterpolationMode||e.stepped||i)?to:Qn}const io="function"==typeof Path2D;function so(t,e,i,s){io&&!e.options.segment?function(t,e,i,s){let n=e._path;n||(n=e._path=new Path2D,e.path(n,i,s)&&n.closePath()),Gn(t,e.options),t.stroke(n)}(t,e,i,s):function(t,e,i,s){const{segments:n,options:o}=e,a=eo(e);for(const r of n)Gn(t,o,r.style),t.beginPath(),a(t,e,r,{start:i,end:i+s-1})&&t.closePath(),t.stroke()}(t,e,i,s)}class no extends Hs{static id="line";static defaults={borderCapStyle:"butt",borderDash:[],borderDashOffset:0,borderJoinStyle:"miter",borderWidth:3,capBezierPoints:!0,cubicInterpolationMode:"default",fill:!1,spanGaps:!1,stepped:!1,tension:0};static defaultRoutes={backgroundColor:"backgroundColor",borderColor:"borderColor"};static descriptors={_scriptable:!0,_indexable:t=>"borderDash"!==t&&"fill"!==t};constructor(t){super(),this.animated=!0,this.options=void 0,this._chart=void 0,this._loop=void 0,this._fullLoop=void 0,this._path=void 0,this._points=void 0,this._segments=void 0,this._decimated=!1,this._pointsUpdated=!1,this._datasetIndex=void 0,t&&Object.assign(this,t)}updateControlPoints(t,e){const i=this.options;if((i.tension||"monotone"===i.cubicInterpolationMode)&&!i.stepped&&!this._pointsUpdated){const s=i.spanGaps?this._loop:this._fullLoop;hi(this._points,i,t,s,e),this._pointsUpdated=!0}}set points(t){this._points=t,delete this._segments,delete this._path,this._pointsUpdated=!1}get points(){return this._points}get segments(){return this._segments||(this._segments=zi(this,this.options.segment))}first(){const t=this.segments,e=this.points;return t.length&&e[t[0].start]}last(){const t=this.segments,e=this.points,i=t.length;return i&&e[t[i-1].end]}interpolate(t,e){const i=this.options,s=t[e],n=this.points,o=Ii(this,{property:e,start:s,end:s});if(!o.length)return;const a=[],r=function(t){return t.stepped?pi:t.tension||"monotone"===t.cubicInterpolationMode?mi:gi}(i);let l,h;for(l=0,h=o.length;l"borderDash"!==t};circumference;endAngle;fullCircles;innerRadius;outerRadius;pixelMargin;startAngle;constructor(t){super(),this.options=void 0,this.circumference=void 0,this.startAngle=void 0,this.endAngle=void 0,this.innerRadius=void 0,this.outerRadius=void 0,this.pixelMargin=0,this.fullCircles=0,t&&Object.assign(this,t)}inRange(t,e,i){const s=this.getProps(["x","y"],i),{angle:n,distance:o}=X(s,{x:t,y:e}),{startAngle:a,endAngle:r,innerRadius:h,outerRadius:c,circumference:d}=this.getProps(["startAngle","endAngle","innerRadius","outerRadius","circumference"],i),u=(this.options.spacing+this.options.borderWidth)/2,f=l(d,r-a)>=O||Z(n,a,r),g=tt(o,h+u,c+u);return f&&g}getCenterPoint(t){const{x:e,y:i,startAngle:s,endAngle:n,innerRadius:o,outerRadius:a}=this.getProps(["x","y","startAngle","endAngle","innerRadius","outerRadius"],t),{offset:r,spacing:l}=this.options,h=(s+n)/2,c=(o+a+l+r)/2;return{x:e+Math.cos(h)*c,y:i+Math.sin(h)*c}}tooltipPosition(t){return this.getCenterPoint(t)}draw(t){const{options:e,circumference:i}=this,s=(e.offset||0)/4,n=(e.spacing||0)/2,o=e.circular;if(this.pixelMargin="inner"===e.borderAlign?.33:0,this.fullCircles=i>O?Math.floor(i/O):0,0===i||this.innerRadius<0||this.outerRadius<0)return;t.save();const a=(this.startAngle+this.endAngle)/2;t.translate(Math.cos(a)*s,Math.sin(a)*s);const r=s*(1-Math.sin(Math.min(C,i||0)));t.fillStyle=e.backgroundColor,t.strokeStyle=e.borderColor,function(t,e,i,s,n){const{fullCircles:o,startAngle:a,circumference:r}=e;let l=e.endAngle;if(o){qn(t,e,i,s,l,n);for(let e=0;e("string"==typeof e?(i=t.push(e)-1,s.unshift({index:i,label:e})):isNaN(e)&&(i=null),i))(t,e,i,s);return n!==t.lastIndexOf(e)?i:n}function po(t){const e=this.getLabels();return t>=0&&ts=e?s:t,a=t=>n=i?n:t;if(t){const t=F(s),e=F(n);t<0&&e<0?a(0):t>0&&e>0&&o(0)}if(s===n){let e=0===n?1:Math.abs(.05*n);a(n+e),t||o(s-e)}this.min=s,this.max=n}getTickLimit(){const t=this.options.ticks;let e,{maxTicksLimit:i,stepSize:s}=t;return s?(e=Math.ceil(this.max/s)-Math.floor(this.min/s)+1,e>1e3&&(console.warn(`scales.${this.id}.ticks.stepSize: ${s} would result generating up to ${e} ticks. Limiting to 1000.`),e=1e3)):(e=this.computeTickLimit(),i=i||11),i&&(e=Math.min(i,e)),e}computeTickLimit(){return Number.POSITIVE_INFINITY}buildTicks(){const t=this.options,e=t.ticks;let i=this.getTickLimit();i=Math.max(2,i);const n=function(t,e){const i=[],{bounds:n,step:o,min:a,max:r,precision:l,count:h,maxTicks:c,maxDigits:d,includeBounds:u}=t,f=o||1,g=c-1,{min:p,max:m}=e,b=!s(a),x=!s(r),_=!s(h),y=(m-p)/(d+1);let v,M,w,k,S=B((m-p)/g/f)*f;if(S<1e-14&&!b&&!x)return[{value:p},{value:m}];k=Math.ceil(m/S)-Math.floor(p/S),k>g&&(S=B(k*S/g/f)*f),s(l)||(v=Math.pow(10,l),S=Math.ceil(S*v)/v),"ticks"===n?(M=Math.floor(p/S)*S,w=Math.ceil(m/S)*S):(M=p,w=m),b&&x&&o&&H((r-a)/o,S/1e3)?(k=Math.round(Math.min((r-a)/S,c)),S=(r-a)/k,M=a,w=r):_?(M=b?a:M,w=x?r:w,k=h-1,S=(w-M)/k):(k=(w-M)/S,k=V(k,Math.round(k),S/1e3)?Math.round(k):Math.ceil(k));const P=Math.max(U(S),U(M));v=Math.pow(10,s(l)?P:l),M=Math.round(M*v)/v,w=Math.round(w*v)/v;let D=0;for(b&&(u&&M!==a?(i.push({value:a}),Mr)break;i.push({value:t})}return x&&u&&w!==r?i.length&&V(i[i.length-1].value,r,mo(r,y,t))?i[i.length-1].value=r:i.push({value:r}):x&&w!==r||i.push({value:w}),i}({maxTicks:i,bounds:t.bounds,min:t.min,max:t.max,precision:e.precision,step:e.stepSize,count:e.count,maxDigits:this._maxDigits(),horizontal:this.isHorizontal(),minRotation:e.minRotation||0,includeBounds:!1!==e.includeBounds},this._range||this);return"ticks"===t.bounds&&j(n,this,"value"),t.reverse?(n.reverse(),this.start=this.max,this.end=this.min):(this.start=this.min,this.end=this.max),n}configure(){const t=this.ticks;let e=this.min,i=this.max;if(super.configure(),this.options.offset&&t.length){const s=(i-e)/Math.max(t.length-1,1)/2;e-=s,i+=s}this._startValue=e,this._endValue=i,this._valueRange=i-e}getLabelForValue(t){return ne(t,this.chart.options.locale,this.options.ticks.format)}}class xo extends bo{static id="linear";static defaults={ticks:{callback:ae.formatters.numeric}};determineDataLimits(){const{min:t,max:e}=this.getMinMax(!0);this.min=a(t)?t:0,this.max=a(e)?e:1,this.handleTickRangeOptions()}computeTickLimit(){const t=this.isHorizontal(),e=t?this.width:this.height,i=$(this.options.ticks.minRotation),s=(t?Math.sin(i):Math.cos(i))||.001,n=this._resolveTickFontOptions(0);return Math.ceil(e/Math.min(40,n.lineHeight/s))}getPixelForValue(t){return null===t?NaN:this.getPixelForDecimal((t-this._startValue)/this._valueRange)}getValueForPixel(t){return this._startValue+this.getDecimalForPixel(t)*this._valueRange}}const _o=t=>Math.floor(z(t)),yo=(t,e)=>Math.pow(10,_o(t)+e);function vo(t){return 1===t/Math.pow(10,_o(t))}function Mo(t,e,i){const s=Math.pow(10,i),n=Math.floor(t/s);return Math.ceil(e/s)-n}function wo(t,{min:e,max:i}){e=r(t.min,e);const s=[],n=_o(e);let o=function(t,e){let i=_o(e-t);for(;Mo(t,e,i)>10;)i++;for(;Mo(t,e,i)<10;)i--;return Math.min(i,_o(t))}(e,i),a=o<0?Math.pow(10,Math.abs(o)):1;const l=Math.pow(10,o),h=n>o?Math.pow(10,n):0,c=Math.round((e-h)*a)/a,d=Math.floor((e-h)/l/10)*l*10;let u=Math.floor((c-d)/Math.pow(10,o)),f=r(t.min,Math.round((h+d+u*Math.pow(10,o))*a)/a);for(;f=10?u=u<15?15:20:u++,u>=20&&(o++,u=2,a=o>=0?1:a),f=Math.round((h+d+u*Math.pow(10,o))*a)/a;const g=r(t.max,f);return s.push({value:g,major:vo(g),significand:u}),s}class ko extends Js{static id="logarithmic";static defaults={ticks:{callback:ae.formatters.logarithmic,major:{enabled:!0}}};constructor(t){super(t),this.start=void 0,this.end=void 0,this._startValue=void 0,this._valueRange=0}parse(t,e){const i=bo.prototype.parse.apply(this,[t,e]);if(0!==i)return a(i)&&i>0?i:null;this._zero=!0}determineDataLimits(){const{min:t,max:e}=this.getMinMax(!0);this.min=a(t)?Math.max(0,t):null,this.max=a(e)?Math.max(0,e):null,this.options.beginAtZero&&(this._zero=!0),this._zero&&this.min!==this._suggestedMin&&!a(this._userMin)&&(this.min=t===yo(this.min,0)?yo(this.min,-1):yo(this.min,0)),this.handleTickRangeOptions()}handleTickRangeOptions(){const{minDefined:t,maxDefined:e}=this.getUserBounds();let i=this.min,s=this.max;const n=e=>i=t?i:e,o=t=>s=e?s:t;i===s&&(i<=0?(n(1),o(10)):(n(yo(i,-1)),o(yo(s,1)))),i<=0&&n(yo(s,-1)),s<=0&&o(yo(i,1)),this.min=i,this.max=s}buildTicks(){const t=this.options,e=wo({min:this._userMin,max:this._userMax},this);return"ticks"===t.bounds&&j(e,this,"value"),t.reverse?(e.reverse(),this.start=this.max,this.end=this.min):(this.start=this.min,this.end=this.max),e}getLabelForValue(t){return void 0===t?"0":ne(t,this.chart.options.locale,this.options.ticks.format)}configure(){const t=this.min;super.configure(),this._startValue=z(t),this._valueRange=z(this.max)-z(t)}getPixelForValue(t){return void 0!==t&&0!==t||(t=this.min),null===t||isNaN(t)?NaN:this.getPixelForDecimal(t===this.min?0:(z(t)-this._startValue)/this._valueRange)}getValueForPixel(t){const e=this.getDecimalForPixel(t);return Math.pow(10,this._startValue+e*this._valueRange)}}function So(t){const e=t.ticks;if(e.display&&t.display){const t=ki(e.backdropPadding);return l(e.font&&e.font.size,ue.font.size)+t.height}return 0}function Po(t,e,i,s,n){return t===s||t===n?{start:e-i/2,end:e+i/2}:tn?{start:e-i,end:e}:{start:e,end:e+i}}function Do(t){const e={l:t.left+t._padding.left,r:t.right-t._padding.right,t:t.top+t._padding.top,b:t.bottom-t._padding.bottom},i=Object.assign({},e),s=[],o=[],a=t._pointLabels.length,r=t.options.pointLabels,l=r.centerPointLabels?C/a:0;for(let u=0;ue.r&&(r=(s.end-e.r)/o,t.r=Math.max(t.r,e.r+r)),n.starte.b&&(l=(n.end-e.b)/a,t.b=Math.max(t.b,e.b+l))}function Oo(t,e,i){const s=t.drawingArea,{extra:n,additionalAngle:o,padding:a,size:r}=i,l=t.getPointPosition(e,s+n+a,o),h=Math.round(Y(G(l.angle+E))),c=function(t,e,i){90===i||270===i?t-=e/2:(i>270||i<90)&&(t-=e);return t}(l.y,r.h,h),d=function(t){if(0===t||180===t)return"center";if(t<180)return"left";return"right"}(h),u=function(t,e,i){"right"===i?t-=e:"center"===i&&(t-=e/2);return t}(l.x,r.w,d);return{visible:!0,x:l.x,y:c,textAlign:d,left:u,top:c,right:u+r.w,bottom:c+r.h}}function Ao(t,e){if(!e)return!0;const{left:i,top:s,right:n,bottom:o}=t;return!(Re({x:i,y:s},e)||Re({x:i,y:o},e)||Re({x:n,y:s},e)||Re({x:n,y:o},e))}function To(t,e,i){const{left:n,top:o,right:a,bottom:r}=i,{backdropColor:l}=e;if(!s(l)){const i=wi(e.borderRadius),s=ki(e.backdropPadding);t.fillStyle=l;const h=n-s.left,c=o-s.top,d=a-n+s.width,u=r-o+s.height;Object.values(i).some((t=>0!==t))?(t.beginPath(),He(t,{x:h,y:c,w:d,h:u,radius:i}),t.fill()):t.fillRect(h,c,d,u)}}function Lo(t,e,i,s){const{ctx:n}=t;if(i)n.arc(t.xCenter,t.yCenter,e,0,O);else{let i=t.getPointPosition(0,e);n.moveTo(i.x,i.y);for(let o=1;ot,padding:5,centerPointLabels:!1}};static defaultRoutes={"angleLines.color":"borderColor","pointLabels.color":"color","ticks.color":"color"};static descriptors={angleLines:{_fallback:"grid"}};constructor(t){super(t),this.xCenter=void 0,this.yCenter=void 0,this.drawingArea=void 0,this._pointLabels=[],this._pointLabelItems=[]}setDimensions(){const t=this._padding=ki(So(this.options)/2),e=this.width=this.maxWidth-t.width,i=this.height=this.maxHeight-t.height;this.xCenter=Math.floor(this.left+e/2+t.left),this.yCenter=Math.floor(this.top+i/2+t.top),this.drawingArea=Math.floor(Math.min(e,i)/2)}determineDataLimits(){const{min:t,max:e}=this.getMinMax(!1);this.min=a(t)&&!isNaN(t)?t:0,this.max=a(e)&&!isNaN(e)?e:0,this.handleTickRangeOptions()}computeTickLimit(){return Math.ceil(this.drawingArea/So(this.options))}generateTickLabels(t){bo.prototype.generateTickLabels.call(this,t),this._pointLabels=this.getLabels().map(((t,e)=>{const i=d(this.options.pointLabels.callback,[t,e],this);return i||0===i?i:""})).filter(((t,e)=>this.chart.getDataVisibility(e)))}fit(){const t=this.options;t.display&&t.pointLabels.display?Do(this):this.setCenterPoint(0,0,0,0)}setCenterPoint(t,e,i,s){this.xCenter+=Math.floor((t-e)/2),this.yCenter+=Math.floor((i-s)/2),this.drawingArea-=Math.min(this.drawingArea/2,Math.max(t,e,i,s))}getIndexAngle(t){return G(t*(O/(this._pointLabels.length||1))+$(this.options.startAngle||0))}getDistanceFromCenterForValue(t){if(s(t))return NaN;const e=this.drawingArea/(this.max-this.min);return this.options.reverse?(this.max-t)*e:(t-this.min)*e}getValueForDistanceFromCenter(t){if(s(t))return NaN;const e=t/(this.drawingArea/(this.max-this.min));return this.options.reverse?this.max-e:this.min+e}getPointLabelContext(t){const e=this._pointLabels||[];if(t>=0&&t=0;n--){const e=t._pointLabelItems[n];if(!e.visible)continue;const o=s.setContext(t.getPointLabelContext(n));To(i,o,e);const a=Si(o.font),{x:r,y:l,textAlign:h}=e;Ne(i,t._pointLabels[n],r,l+a.lineHeight/2,a,{color:o.color,textAlign:h,textBaseline:"middle"})}}(this,o),s.display&&this.ticks.forEach(((t,e)=>{if(0!==e){r=this.getDistanceFromCenterForValue(t.value);const i=this.getContext(e),a=s.setContext(i),l=n.setContext(i);!function(t,e,i,s,n){const o=t.ctx,a=e.circular,{color:r,lineWidth:l}=e;!a&&!s||!r||!l||i<0||(o.save(),o.strokeStyle=r,o.lineWidth=l,o.setLineDash(n.dash),o.lineDashOffset=n.dashOffset,o.beginPath(),Lo(t,i,a,s),o.closePath(),o.stroke(),o.restore())}(this,a,r,o,l)}})),i.display){for(t.save(),a=o-1;a>=0;a--){const s=i.setContext(this.getPointLabelContext(a)),{color:n,lineWidth:o}=s;o&&n&&(t.lineWidth=o,t.strokeStyle=n,t.setLineDash(s.borderDash),t.lineDashOffset=s.borderDashOffset,r=this.getDistanceFromCenterForValue(e.ticks.reverse?this.min:this.max),l=this.getPointPosition(a,r),t.beginPath(),t.moveTo(this.xCenter,this.yCenter),t.lineTo(l.x,l.y),t.stroke())}t.restore()}}drawBorder(){}drawLabels(){const t=this.ctx,e=this.options,i=e.ticks;if(!i.display)return;const s=this.getIndexAngle(0);let n,o;t.save(),t.translate(this.xCenter,this.yCenter),t.rotate(s),t.textAlign="center",t.textBaseline="middle",this.ticks.forEach(((s,a)=>{if(0===a&&!e.reverse)return;const r=i.setContext(this.getContext(a)),l=Si(r.font);if(n=this.getDistanceFromCenterForValue(this.ticks[a].value),r.showLabelBackdrop){t.font=l.string,o=t.measureText(s.label).width,t.fillStyle=r.backdropColor;const e=ki(r.backdropPadding);t.fillRect(-o/2-e.left,-n-l.size/2-e.top,o+e.width,l.size+e.height)}Ne(t,s.label,0,-n,l,{color:r.color,strokeColor:r.textStrokeColor,strokeWidth:r.textStrokeWidth})})),t.restore()}drawTitle(){}}const Ro={millisecond:{common:!0,size:1,steps:1e3},second:{common:!0,size:1e3,steps:60},minute:{common:!0,size:6e4,steps:60},hour:{common:!0,size:36e5,steps:24},day:{common:!0,size:864e5,steps:30},week:{common:!1,size:6048e5,steps:4},month:{common:!0,size:2628e6,steps:12},quarter:{common:!1,size:7884e6,steps:4},year:{common:!0,size:3154e7}},Io=Object.keys(Ro);function zo(t,e){return t-e}function Fo(t,e){if(s(e))return null;const i=t._adapter,{parser:n,round:o,isoWeekday:r}=t._parseOpts;let l=e;return"function"==typeof n&&(l=n(l)),a(l)||(l="string"==typeof n?i.parse(l,n):i.parse(l)),null===l?null:(o&&(l="week"!==o||!N(r)&&!0!==r?i.startOf(l,o):i.startOf(l,"isoWeek",r)),+l)}function Vo(t,e,i,s){const n=Io.length;for(let o=Io.indexOf(t);o=e?i[s]:i[n]]=!0}}else t[e]=!0}function Wo(t,e,i){const s=[],n={},o=e.length;let a,r;for(a=0;a=0&&(e[l].major=!0);return e}(t,s,n,i):s}class No extends Js{static id="time";static defaults={bounds:"data",adapters:{},time:{parser:!1,unit:!1,round:!1,isoWeekday:!1,minUnit:"millisecond",displayFormats:{}},ticks:{source:"auto",callback:!1,major:{enabled:!1}}};constructor(t){super(t),this._cache={data:[],labels:[],all:[]},this._unit="day",this._majorUnit=void 0,this._offsets={},this._normalized=!1,this._parseOpts=void 0}init(t,e={}){const i=t.time||(t.time={}),s=this._adapter=new Rn._date(t.adapters.date);s.init(e),x(i.displayFormats,s.formats()),this._parseOpts={parser:i.parser,round:i.round,isoWeekday:i.isoWeekday},super.init(t),this._normalized=e.normalized}parse(t,e){return void 0===t?null:Fo(this,t)}beforeLayout(){super.beforeLayout(),this._cache={data:[],labels:[],all:[]}}determineDataLimits(){const t=this.options,e=this._adapter,i=t.time.unit||"day";let{min:s,max:n,minDefined:o,maxDefined:r}=this.getUserBounds();function l(t){o||isNaN(t.min)||(s=Math.min(s,t.min)),r||isNaN(t.max)||(n=Math.max(n,t.max))}o&&r||(l(this._getLabelBounds()),"ticks"===t.bounds&&"labels"===t.ticks.source||l(this.getMinMax(!1))),s=a(s)&&!isNaN(s)?s:+e.startOf(Date.now(),i),n=a(n)&&!isNaN(n)?n:+e.endOf(Date.now(),i)+1,this.min=Math.min(s,n-1),this.max=Math.max(s+1,n)}_getLabelBounds(){const t=this.getLabelTimestamps();let e=Number.POSITIVE_INFINITY,i=Number.NEGATIVE_INFINITY;return t.length&&(e=t[0],i=t[t.length-1]),{min:e,max:i}}buildTicks(){const t=this.options,e=t.time,i=t.ticks,s="labels"===i.source?this.getLabelTimestamps():this._generate();"ticks"===t.bounds&&s.length&&(this.min=this._userMin||s[0],this.max=this._userMax||s[s.length-1]);const n=this.min,o=nt(s,n,this.max);return this._unit=e.unit||(i.autoSkip?Vo(e.minUnit,this.min,this.max,this._getLabelCapacity(n)):function(t,e,i,s,n){for(let o=Io.length-1;o>=Io.indexOf(i);o--){const i=Io[o];if(Ro[i].common&&t._adapter.diff(n,s,i)>=e-1)return i}return Io[i?Io.indexOf(i):0]}(this,o.length,e.minUnit,this.min,this.max)),this._majorUnit=i.major.enabled&&"year"!==this._unit?function(t){for(let e=Io.indexOf(t)+1,i=Io.length;e+t.value)))}initOffsets(t=[]){let e,i,s=0,n=0;this.options.offset&&t.length&&(e=this.getDecimalForValue(t[0]),s=1===t.length?1-e:(this.getDecimalForValue(t[1])-e)/2,i=this.getDecimalForValue(t[t.length-1]),n=1===t.length?i:(i-this.getDecimalForValue(t[t.length-2]))/2);const o=t.length<3?.5:.25;s=J(s,0,o),n=J(n,0,o),this._offsets={start:s,end:n,factor:1/(s+1+n)}}_generate(){const t=this._adapter,e=this.min,i=this.max,s=this.options,n=s.time,o=n.unit||Vo(n.minUnit,e,i,this._getLabelCapacity(e)),a=l(s.ticks.stepSize,1),r="week"===o&&n.isoWeekday,h=N(r)||!0===r,c={};let d,u,f=e;if(h&&(f=+t.startOf(f,"isoWeek",r)),f=+t.startOf(f,h?"day":o),t.diff(i,e,o)>1e5*a)throw new Error(e+" and "+i+" are too far apart with stepSize of "+a+" "+o);const g="data"===s.ticks.source&&this.getDataTimestamps();for(d=f,u=0;d+t))}getLabelForValue(t){const e=this._adapter,i=this.options.time;return i.tooltipFormat?e.format(t,i.tooltipFormat):e.format(t,i.displayFormats.datetime)}format(t,e){const i=this.options.time.displayFormats,s=this._unit,n=e||i[s];return this._adapter.format(t,n)}_tickFormatFunction(t,e,i,s){const n=this.options,o=n.ticks.callback;if(o)return d(o,[t,e,i],this);const a=n.time.displayFormats,r=this._unit,l=this._majorUnit,h=r&&a[r],c=l&&a[l],u=i[e],f=l&&c&&u&&u.major;return this._adapter.format(t,s||(f?c:h))}generateTickLabels(t){let e,i,s;for(e=0,i=t.length;e0?a:1}getDataTimestamps(){let t,e,i=this._cache.data||[];if(i.length)return i;const s=this.getMatchingVisibleMetas();if(this._normalized&&s.length)return this._cache.data=s[0].controller.getAllParsedValues(this);for(t=0,e=s.length;t=t[r].pos&&e<=t[l].pos&&({lo:r,hi:l}=it(t,"pos",e)),({pos:s,time:o}=t[r]),({pos:n,time:a}=t[l])):(e>=t[r].time&&e<=t[l].time&&({lo:r,hi:l}=it(t,"time",e)),({time:s,pos:o}=t[r]),({time:n,pos:a}=t[l]));const h=n-s;return h?o+(a-o)*(e-s)/h:o}var jo=Object.freeze({__proto__:null,CategoryScale:class extends Js{static id="category";static defaults={ticks:{callback:po}};constructor(t){super(t),this._startValue=void 0,this._valueRange=0,this._addedLabels=[]}init(t){const e=this._addedLabels;if(e.length){const t=this.getLabels();for(const{index:i,label:s}of e)t[i]===s&&t.splice(i,1);this._addedLabels=[]}super.init(t)}parse(t,e){if(s(t))return null;const i=this.getLabels();return((t,e)=>null===t?null:J(Math.round(t),0,e))(e=isFinite(e)&&i[e]===t?e:go(i,t,l(e,t),this._addedLabels),i.length-1)}determineDataLimits(){const{minDefined:t,maxDefined:e}=this.getUserBounds();let{min:i,max:s}=this.getMinMax(!0);"ticks"===this.options.bounds&&(t||(i=0),e||(s=this.getLabels().length-1)),this.min=i,this.max=s}buildTicks(){const t=this.min,e=this.max,i=this.options.offset,s=[];let n=this.getLabels();n=0===t&&e===n.length-1?n:n.slice(t,e+1),this._valueRange=Math.max(n.length-(i?0:1),1),this._startValue=this.min-(i?.5:0);for(let i=t;i<=e;i++)s.push({value:i});return s}getLabelForValue(t){return po.call(this,t)}configure(){super.configure(),this.isHorizontal()||(this._reversePixels=!this._reversePixels)}getPixelForValue(t){return"number"!=typeof t&&(t=this.parse(t)),null===t?NaN:this.getPixelForDecimal((t-this._startValue)/this._valueRange)}getPixelForTick(t){const e=this.ticks;return t<0||t>e.length-1?null:this.getPixelForValue(e[t].value)}getValueForPixel(t){return Math.round(this._startValue+this.getDecimalForPixel(t)*this._valueRange)}getBasePixel(){return this.bottom}},LinearScale:xo,LogarithmicScale:ko,RadialLinearScale:Eo,TimeScale:No,TimeSeriesScale:class extends No{static id="timeseries";static defaults=No.defaults;constructor(t){super(t),this._table=[],this._minPos=void 0,this._tableRange=void 0}initOffsets(){const t=this._getTimestampsForTable(),e=this._table=this.buildLookupTable(t);this._minPos=Ho(e,this.min),this._tableRange=Ho(e,this.max)-this._minPos,super.initOffsets(t)}buildLookupTable(t){const{min:e,max:i}=this,s=[],n=[];let o,a,r,l,h;for(o=0,a=t.length;o=e&&l<=i&&s.push(l);if(s.length<2)return[{time:e,pos:0},{time:i,pos:1}];for(o=0,a=s.length;ot-e))}_getTimestampsForTable(){let t=this._cache.all||[];if(t.length)return t;const e=this.getDataTimestamps(),i=this.getLabelTimestamps();return 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t)if(t[e].borderColor||t[e].backgroundColor)return!0;return!1}var Go={id:"colors",defaults:{enabled:!0,forceOverride:!1},beforeLayout(t,e,i){if(!i.enabled)return;const{data:{datasets:s},options:n}=t.config,{elements:o}=n;if(!i.forceOverride&&(Ko(s)||(a=n)&&(a.borderColor||a.backgroundColor)||o&&Ko(o)))return;var a;const r=qo(t);s.forEach(r)}};function Zo(t){if(t._decimated){const e=t._data;delete t._decimated,delete t._data,Object.defineProperty(t,"data",{configurable:!0,enumerable:!0,writable:!0,value:e})}}function Jo(t){t.data.datasets.forEach((t=>{Zo(t)}))}var Qo={id:"decimation",defaults:{algorithm:"min-max",enabled:!1},beforeElementsUpdate:(t,e,i)=>{if(!i.enabled)return void Jo(t);const n=t.width;t.data.datasets.forEach(((e,o)=>{const{_data:a,indexAxis:r}=e,l=t.getDatasetMeta(o),h=a||e.data;if("y"===Pi([r,t.options.indexAxis]))return;if(!l.controller.supportsDecimation)return;const c=t.scales[l.xAxisID];if("linear"!==c.type&&"time"!==c.type)return;if(t.options.parsing)return;let{start:d,count:u}=function(t,e){const i=e.length;let s,n=0;const{iScale:o}=t,{min:a,max:r,minDefined:l,maxDefined:h}=o.getUserBounds();return l&&(n=J(it(e,o.axis,a).lo,0,i-1)),s=h?J(it(e,o.axis,r).hi+1,n,i)-n:i-n,{start:n,count:s}}(l,h);if(u<=(i.threshold||4*n))return void Zo(e);let f;switch(s(a)&&(e._data=h,delete e.data,Object.defineProperty(e,"data",{configurable:!0,enumerable:!0,get:function(){return this._decimated},set:function(t){this._data=t}})),i.algorithm){case"lttb":f=function(t,e,i,s,n){const o=n.samples||s;if(o>=i)return t.slice(e,e+i);const a=[],r=(i-2)/(o-2);let l=0;const h=e+i-1;let c,d,u,f,g,p=e;for(a[l++]=t[p],c=0;cu&&(u=f,d=t[s],g=s);a[l++]=d,p=g}return a[l++]=t[h],a}(h,d,u,n,i);break;case"min-max":f=function(t,e,i,n){let o,a,r,l,h,c,d,u,f,g,p=0,m=0;const b=[],x=e+i-1,_=t[e].x,y=t[x].x-_;for(o=e;og&&(g=l,d=o),p=(m*p+a.x)/++m;else{const i=o-1;if(!s(c)&&!s(d)){const e=Math.min(c,d),s=Math.max(c,d);e!==u&&e!==i&&b.push({...t[e],x:p}),s!==u&&s!==i&&b.push({...t[s],x:p})}o>0&&i!==u&&b.push(t[i]),b.push(a),h=e,m=0,f=g=l,c=d=u=o}}return b}(h,d,u,n);break;default:throw new Error(`Unsupported decimation algorithm '${i.algorithm}'`)}e._decimated=f}))},destroy(t){Jo(t)}};function ta(t,e,i,s){if(s)return;let n=e[t],o=i[t];return"angle"===t&&(n=G(n),o=G(o)),{property:t,start:n,end:o}}function ea(t,e,i){for(;e>t;e--){const t=i[e];if(!isNaN(t.x)&&!isNaN(t.y))break}return e}function ia(t,e,i,s){return t&&e?s(t[i],e[i]):t?t[i]:e?e[i]:0}function sa(t,e){let i=[],s=!1;return n(t)?(s=!0,i=t):i=function(t,e){const{x:i=null,y:s=null}=t||{},n=e.points,o=[];return e.segments.forEach((({start:t,end:e})=>{e=ea(t,e,n);const a=n[t],r=n[e];null!==s?(o.push({x:a.x,y:s}),o.push({x:r.x,y:s})):null!==i&&(o.push({x:i,y:a.y}),o.push({x:i,y:r.y}))})),o}(t,e),i.length?new no({points:i,options:{tension:0},_loop:s,_fullLoop:s}):null}function na(t){return t&&!1!==t.fill}function oa(t,e,i){let s=t[e].fill;const n=[e];let o;if(!i)return s;for(;!1!==s&&-1===n.indexOf(s);){if(!a(s))return s;if(o=t[s],!o)return!1;if(o.visible)return s;n.push(s),s=o.fill}return!1}function aa(t,e,i){const s=function(t){const e=t.options,i=e.fill;let s=l(i&&i.target,i);void 0===s&&(s=!!e.backgroundColor);if(!1===s||null===s)return!1;if(!0===s)return"origin";return s}(t);if(o(s))return!isNaN(s.value)&&s;let n=parseFloat(s);return a(n)&&Math.floor(n)===n?function(t,e,i,s){"-"!==t&&"+"!==t||(i=e+i);if(i===e||i<0||i>=s)return!1;return i}(s[0],e,n,i):["origin","start","end","stack","shape"].indexOf(s)>=0&&s}function ra(t,e,i){const s=[];for(let n=0;n=0;--e){const i=n[e].$filler;i&&(i.line.updateControlPoints(o,i.axis),s&&i.fill&&da(t.ctx,i,o))}},beforeDatasetsDraw(t,e,i){if("beforeDatasetsDraw"!==i.drawTime)return;const s=t.getSortedVisibleDatasetMetas();for(let e=s.length-1;e>=0;--e){const i=s[e].$filler;na(i)&&da(t.ctx,i,t.chartArea)}},beforeDatasetDraw(t,e,i){const s=e.meta.$filler;na(s)&&"beforeDatasetDraw"===i.drawTime&&da(t.ctx,s,t.chartArea)},defaults:{propagate:!0,drawTime:"beforeDatasetDraw"}};const ba=(t,e)=>{let{boxHeight:i=e,boxWidth:s=e}=t;return t.usePointStyle&&(i=Math.min(i,e),s=t.pointStyleWidth||Math.min(s,e)),{boxWidth:s,boxHeight:i,itemHeight:Math.max(e,i)}};class xa extends Hs{constructor(t){super(),this._added=!1,this.legendHitBoxes=[],this._hoveredItem=null,this.doughnutMode=!1,this.chart=t.chart,this.options=t.options,this.ctx=t.ctx,this.legendItems=void 0,this.columnSizes=void 0,this.lineWidths=void 0,this.maxHeight=void 0,this.maxWidth=void 0,this.top=void 0,this.bottom=void 0,this.left=void 0,this.right=void 0,this.height=void 0,this.width=void 0,this._margins=void 0,this.position=void 0,this.weight=void 0,this.fullSize=void 0}update(t,e,i){this.maxWidth=t,this.maxHeight=e,this._margins=i,this.setDimensions(),this.buildLabels(),this.fit()}setDimensions(){this.isHorizontal()?(this.width=this.maxWidth,this.left=this._margins.left,this.right=this.width):(this.height=this.maxHeight,this.top=this._margins.top,this.bottom=this.height)}buildLabels(){const t=this.options.labels||{};let e=d(t.generateLabels,[this.chart],this)||[];t.filter&&(e=e.filter((e=>t.filter(e,this.chart.data)))),t.sort&&(e=e.sort(((e,i)=>t.sort(e,i,this.chart.data)))),this.options.reverse&&e.reverse(),this.legendItems=e}fit(){const{options:t,ctx:e}=this;if(!t.display)return void(this.width=this.height=0);const i=t.labels,s=Si(i.font),n=s.size,o=this._computeTitleHeight(),{boxWidth:a,itemHeight:r}=ba(i,n);let l,h;e.font=s.string,this.isHorizontal()?(l=this.maxWidth,h=this._fitRows(o,n,a,r)+10):(h=this.maxHeight,l=this._fitCols(o,s,a,r)+10),this.width=Math.min(l,t.maxWidth||this.maxWidth),this.height=Math.min(h,t.maxHeight||this.maxHeight)}_fitRows(t,e,i,s){const{ctx:n,maxWidth:o,options:{labels:{padding:a}}}=this,r=this.legendHitBoxes=[],l=this.lineWidths=[0],h=s+a;let c=t;n.textAlign="left",n.textBaseline="middle";let d=-1,u=-h;return this.legendItems.forEach(((t,f)=>{const g=i+e/2+n.measureText(t.text).width;(0===f||l[l.length-1]+g+2*a>o)&&(c+=h,l[l.length-(f>0?0:1)]=0,u+=h,d++),r[f]={left:0,top:u,row:d,width:g,height:s},l[l.length-1]+=g+a})),c}_fitCols(t,e,i,s){const{ctx:n,maxHeight:o,options:{labels:{padding:a}}}=this,r=this.legendHitBoxes=[],l=this.columnSizes=[],h=o-t;let c=a,d=0,u=0,f=0,g=0;return this.legendItems.forEach(((t,o)=>{const{itemWidth:p,itemHeight:m}=function(t,e,i,s,n){const o=function(t,e,i,s){let n=t.text;n&&"string"!=typeof n&&(n=n.reduce(((t,e)=>t.length>e.length?t:e)));return e+i.size/2+s.measureText(n).width}(s,t,e,i),a=function(t,e,i){let s=t;"string"!=typeof e.text&&(s=_a(e,i));return s}(n,s,e.lineHeight);return{itemWidth:o,itemHeight:a}}(i,e,n,t,s);o>0&&u+m+2*a>h&&(c+=d+a,l.push({width:d,height:u}),f+=d+a,g++,d=u=0),r[o]={left:f,top:u,col:g,width:p,height:m},d=Math.max(d,p),u+=m+a})),c+=d,l.push({width:d,height:u}),c}adjustHitBoxes(){if(!this.options.display)return;const t=this._computeTitleHeight(),{legendHitBoxes:e,options:{align:i,labels:{padding:s},rtl:n}}=this,o=Oi(n,this.left,this.width);if(this.isHorizontal()){let n=0,a=ft(i,this.left+s,this.right-this.lineWidths[n]);for(const r of e)n!==r.row&&(n=r.row,a=ft(i,this.left+s,this.right-this.lineWidths[n])),r.top+=this.top+t+s,r.left=o.leftForLtr(o.x(a),r.width),a+=r.width+s}else{let n=0,a=ft(i,this.top+t+s,this.bottom-this.columnSizes[n].height);for(const r of e)r.col!==n&&(n=r.col,a=ft(i,this.top+t+s,this.bottom-this.columnSizes[n].height)),r.top=a,r.left+=this.left+s,r.left=o.leftForLtr(o.x(r.left),r.width),a+=r.height+s}}isHorizontal(){return"top"===this.options.position||"bottom"===this.options.position}draw(){if(this.options.display){const t=this.ctx;Ie(t,this),this._draw(),ze(t)}}_draw(){const{options:t,columnSizes:e,lineWidths:i,ctx:s}=this,{align:n,labels:o}=t,a=ue.color,r=Oi(t.rtl,this.left,this.width),h=Si(o.font),{padding:c}=o,d=h.size,u=d/2;let f;this.drawTitle(),s.textAlign=r.textAlign("left"),s.textBaseline="middle",s.lineWidth=.5,s.font=h.string;const{boxWidth:g,boxHeight:p,itemHeight:m}=ba(o,d),b=this.isHorizontal(),x=this._computeTitleHeight();f=b?{x:ft(n,this.left+c,this.right-i[0]),y:this.top+c+x,line:0}:{x:this.left+c,y:ft(n,this.top+x+c,this.bottom-e[0].height),line:0},Ai(this.ctx,t.textDirection);const _=m+c;this.legendItems.forEach(((y,v)=>{s.strokeStyle=y.fontColor,s.fillStyle=y.fontColor;const M=s.measureText(y.text).width,w=r.textAlign(y.textAlign||(y.textAlign=o.textAlign)),k=g+u+M;let S=f.x,P=f.y;r.setWidth(this.width),b?v>0&&S+k+c>this.right&&(P=f.y+=_,f.line++,S=f.x=ft(n,this.left+c,this.right-i[f.line])):v>0&&P+_>this.bottom&&(S=f.x=S+e[f.line].width+c,f.line++,P=f.y=ft(n,this.top+x+c,this.bottom-e[f.line].height));if(function(t,e,i){if(isNaN(g)||g<=0||isNaN(p)||p<0)return;s.save();const n=l(i.lineWidth,1);if(s.fillStyle=l(i.fillStyle,a),s.lineCap=l(i.lineCap,"butt"),s.lineDashOffset=l(i.lineDashOffset,0),s.lineJoin=l(i.lineJoin,"miter"),s.lineWidth=n,s.strokeStyle=l(i.strokeStyle,a),s.setLineDash(l(i.lineDash,[])),o.usePointStyle){const a={radius:p*Math.SQRT2/2,pointStyle:i.pointStyle,rotation:i.rotation,borderWidth:n},l=r.xPlus(t,g/2);Ee(s,a,l,e+u,o.pointStyleWidth&&g)}else{const o=e+Math.max((d-p)/2,0),a=r.leftForLtr(t,g),l=wi(i.borderRadius);s.beginPath(),Object.values(l).some((t=>0!==t))?He(s,{x:a,y:o,w:g,h:p,radius:l}):s.rect(a,o,g,p),s.fill(),0!==n&&s.stroke()}s.restore()}(r.x(S),P,y),S=gt(w,S+g+u,b?S+k:this.right,t.rtl),function(t,e,i){Ne(s,i.text,t,e+m/2,h,{strikethrough:i.hidden,textAlign:r.textAlign(i.textAlign)})}(r.x(S),P,y),b)f.x+=k+c;else if("string"!=typeof y.text){const t=h.lineHeight;f.y+=_a(y,t)+c}else f.y+=_})),Ti(this.ctx,t.textDirection)}drawTitle(){const t=this.options,e=t.title,i=Si(e.font),s=ki(e.padding);if(!e.display)return;const n=Oi(t.rtl,this.left,this.width),o=this.ctx,a=e.position,r=i.size/2,l=s.top+r;let h,c=this.left,d=this.width;if(this.isHorizontal())d=Math.max(...this.lineWidths),h=this.top+l,c=ft(t.align,c,this.right-d);else{const e=this.columnSizes.reduce(((t,e)=>Math.max(t,e.height)),0);h=l+ft(t.align,this.top,this.bottom-e-t.labels.padding-this._computeTitleHeight())}const u=ft(a,c,c+d);o.textAlign=n.textAlign(ut(a)),o.textBaseline="middle",o.strokeStyle=e.color,o.fillStyle=e.color,o.font=i.string,Ne(o,e.text,u,h,i)}_computeTitleHeight(){const t=this.options.title,e=Si(t.font),i=ki(t.padding);return t.display?e.lineHeight+i.height:0}_getLegendItemAt(t,e){let i,s,n;if(tt(t,this.left,this.right)&&tt(e,this.top,this.bottom))for(n=this.legendHitBoxes,i=0;it.chart.options.color,boxWidth:40,padding:10,generateLabels(t){const e=t.data.datasets,{labels:{usePointStyle:i,pointStyle:s,textAlign:n,color:o,useBorderRadius:a,borderRadius:r}}=t.legend.options;return t._getSortedDatasetMetas().map((t=>{const l=t.controller.getStyle(i?0:void 0),h=ki(l.borderWidth);return{text:e[t.index].label,fillStyle:l.backgroundColor,fontColor:o,hidden:!t.visible,lineCap:l.borderCapStyle,lineDash:l.borderDash,lineDashOffset:l.borderDashOffset,lineJoin:l.borderJoinStyle,lineWidth:(h.width+h.height)/4,strokeStyle:l.borderColor,pointStyle:s||l.pointStyle,rotation:l.rotation,textAlign:n||l.textAlign,borderRadius:a&&(r||l.borderRadius),datasetIndex:t.index}}),this)}},title:{color:t=>t.chart.options.color,display:!1,position:"center",text:""}},descriptors:{_scriptable:t=>!t.startsWith("on"),labels:{_scriptable:t=>!["generateLabels","filter","sort"].includes(t)}}};class va extends Hs{constructor(t){super(),this.chart=t.chart,this.options=t.options,this.ctx=t.ctx,this._padding=void 0,this.top=void 0,this.bottom=void 0,this.left=void 0,this.right=void 0,this.width=void 0,this.height=void 0,this.position=void 0,this.weight=void 0,this.fullSize=void 0}update(t,e){const i=this.options;if(this.left=0,this.top=0,!i.display)return void(this.width=this.height=this.right=this.bottom=0);this.width=this.right=t,this.height=this.bottom=e;const s=n(i.text)?i.text.length:1;this._padding=ki(i.padding);const o=s*Si(i.font).lineHeight+this._padding.height;this.isHorizontal()?this.height=o:this.width=o}isHorizontal(){const t=this.options.position;return"top"===t||"bottom"===t}_drawArgs(t){const{top:e,left:i,bottom:s,right:n,options:o}=this,a=o.align;let r,l,h,c=0;return this.isHorizontal()?(l=ft(a,i,n),h=e+t,r=n-i):("left"===o.position?(l=i+t,h=ft(a,s,e),c=-.5*C):(l=n-t,h=ft(a,e,s),c=.5*C),r=s-e),{titleX:l,titleY:h,maxWidth:r,rotation:c}}draw(){const t=this.ctx,e=this.options;if(!e.display)return;const i=Si(e.font),s=i.lineHeight/2+this._padding.top,{titleX:n,titleY:o,maxWidth:a,rotation:r}=this._drawArgs(s);Ne(t,e.text,0,0,i,{color:e.color,maxWidth:a,rotation:r,textAlign:ut(e.align),textBaseline:"middle",translation:[n,o]})}}var Ma={id:"title",_element:va,start(t,e,i){!function(t,e){const i=new 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An.register(Yn,jo,fo,t),An.helpers={...Wi},An._adapters=Rn,An.Animation=Cs,An.Animations=Os,An.animator=xt,An.controllers=en.controllers.items,An.DatasetController=Ns,An.Element=Hs,An.elements=fo,An.Interaction=Xi,An.layouts=as,An.platforms=Ss,An.Scale=Js,An.Ticks=ae,Object.assign(An,Yn,jo,fo,t,Ss),An.Chart=An,"undefined"!=typeof window&&(window.Chart=An),An})); +//# sourceMappingURL=chart.umd.js.map diff --git a/docs/screenshots/00-hero.png b/docs/screenshots/00-hero.png new file mode 100644 index 0000000..cc8ba4f Binary files /dev/null and b/docs/screenshots/00-hero.png differ diff --git a/docs/screenshots/01-overview.png b/docs/screenshots/01-overview.png new file mode 100644 index 0000000..89d9b19 Binary files /dev/null and b/docs/screenshots/01-overview.png differ diff --git a/docs/screenshots/02-model-intelligence.png b/docs/screenshots/02-model-intelligence.png new file mode 100644 index 0000000..1f47c70 Binary files /dev/null and b/docs/screenshots/02-model-intelligence.png differ diff --git a/docs/screenshots/03-run-benchmark.png b/docs/screenshots/03-run-benchmark.png new file mode 100644 index 0000000..3593c73 Binary files /dev/null and b/docs/screenshots/03-run-benchmark.png differ diff --git a/docs/screenshots/04-throughput.png b/docs/screenshots/04-throughput.png new file mode 100644 index 0000000..77825b8 Binary files /dev/null and b/docs/screenshots/04-throughput.png differ diff --git a/docs/screenshots/05-results.png b/docs/screenshots/05-results.png new file mode 100644 index 0000000..60836c7 Binary files /dev/null and b/docs/screenshots/05-results.png differ diff --git a/index.html b/index.html index 61854a5..4cd0098 100644 --- a/index.html +++ b/index.html @@ -3,735 +3,467 @@ - Local LLM Benchmark Results - + Local-Bench · Companion Intelligence + + + + + + +
+
+
+ + + Companion Intelligence + Local-Bench + +
+
+ Connecting… + Local-first +
+
+
- .prompt-card { - padding: 14px; - border: 1px solid #e8eaf6; - border-radius: 10px; - background: #fbfbff; - } +
+
+

Local LLM benchmark & intelligence catalog

+

Measure throughput for the models you run locally via Ollama, and compare them against the curated Companion catalog ranked by intelligence.

- .prompt-card h3 { - font-size: 1rem; - margin-bottom: 8px; - color: #333; - } +
+
Catalog models
—
Curated Companion catalog
+
Installed locally
—
Detected via Ollama
+
Top intelligence
—
By intelligence index
+
Fastest measured
—
Run a benchmark to populate
+
+
+
- .prompt-card p { - font-size: 0.9rem; - color: #666; - line-height: 1.4; - } +
+
- .chart-insights { - margin-top: 16px; - } - - @media (max-width: 768px) { - .prompt-select, - .custom-prompt-input { - font-size: 16px; /* Prevents zoom on iOS */ - } - - .prompt-preview { - font-size: 0.85rem; - } - - .button-group { - flex-direction: column; - } - - .btn { - width: 100%; - } - } - - - -
-
-

🚀 Local LLM Benchmark

-

Performance comparison of local language models via Ollama

-
- -
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- -
-

🚀 Run Benchmarks

-
-
- -
- -
-

Loading available models...

-
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- -
- - -
- -
- - -
- -
-
📝 Current Prompt:
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Loading...
-
-
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- -
- - - + +
+
+

Run a benchmark

+ Select installed models, choose a prompt, and measure tokens/second. +
+
+
+ + +

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+
+ +
+ + +
+
+ +
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💻 System Specifications

-
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+ + +
+
+

Model intelligence

+ Artificial Analysis Intelligence Index +
+
+

Loading curated catalog…

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+
+
+ + +
+
+

System specifications

+ Captured with each benchmark run
- -
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📊 Statistics

-
+
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+ + +
+

Statistics

+
+
+ + +
+
+

Throughput comparison

+ Tokens per second, higher is faster
- -
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📈 Performance Chart

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+
+
- -
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📋 Detailed Results

- - - - - - - - - - - - - - -
ModelTokens/SecondTotal TokensDuration (s)TimestampStatus
+
+ + +
+
+

Detailed results

+ +
+
+
+ + + + + + + + + + + + + +
ModelIntelligenceTokens/sTotal tokensDurationTimestampStatus
+
+
+
+ +
+
+ Local-Bench — a Companion Intelligence app for benchmarking local LLMs. + Private & Confidential — Property of Lifescope Inc.
- -
-

Local-Bench - Benchmark your local LLMs with ease

-
- - +
+ diff --git a/src/benchmark.test.ts b/src/benchmark.test.ts index 05c366e..855d4a0 100644 --- a/src/benchmark.test.ts +++ b/src/benchmark.test.ts @@ -1,7 +1,7 @@ import axios from 'axios'; import * as fs from 'fs'; import * as path from 'path'; -import { benchmarkModel, checkModelAvailable, getOllamaModelCatalog, saveResultsToCSV, saveResultsToDatabase, SUPPORTED_OLLAMA_MODELS, TEST_PROMPTS } from './benchmark'; +import { benchmarkModel, checkModelAvailable, getOllamaModelCatalog, saveResultsToCSV, saveResultsToDatabase, SUPPORTED_OLLAMA_MODELS, TEST_PROMPTS, INTELLIGENCE_INDEX_SOURCE, INTELLIGENCE_INDEX_URL, INTELLIGENCE_INDEX_AS_OF } from './benchmark'; import * as database from './database'; import * as systemSpecs from './systemSpecs'; @@ -256,6 +256,36 @@ describe('Benchmark Module', () => { }); }); + describe('intelligence index', () => { + it('should expose intelligence-index source attribution', () => { + expect(INTELLIGENCE_INDEX_SOURCE).toMatch(/Artificial Analysis/i); + expect(INTELLIGENCE_INDEX_URL).toMatch(/^https?:\/\//); + expect(typeof INTELLIGENCE_INDEX_AS_OF).toBe('string'); + expect(INTELLIGENCE_INDEX_AS_OF.length).toBeGreaterThan(0); + }); + + it('should define an intelligenceIndex (number or null) for every curated model', () => { + SUPPORTED_OLLAMA_MODELS.forEach(model => { + expect(model).toHaveProperty('intelligenceIndex'); + const score = model.intelligenceIndex; + const isNumberOrNull = score === null || typeof score === 'number'; + expect(isNumberOrNull).toBe(true); + if (typeof score === 'number') { + expect(score).toBeGreaterThanOrEqual(0); + expect(score).toBeLessThanOrEqual(100); + } + }); + }); + + it('should rate at least the flagship text models and leave vision-only models unrated', () => { + const byName = new Map(SUPPORTED_OLLAMA_MODELS.map(m => [m.name, m])); + expect(byName.get('gpt-oss:120b')?.intelligenceIndex).toBeGreaterThan(0); + expect(byName.get('qwen3:235b')?.intelligenceIndex).toBeGreaterThan(0); + // Vision-only variants are not individually rated by the intelligence index. + expect(byName.get('qwen3-vl:235b')?.intelligenceIndex).toBeNull(); + }); + }); + describe('getOllamaModelCatalog', () => { it('should include the curated supported Ollama catalog', () => { const catalog = getOllamaModelCatalog(); @@ -264,6 +294,15 @@ describe('Benchmark Module', () => { expect(catalog[0]).toHaveProperty('installed'); expect(catalog[0]).toHaveProperty('supported'); expect(catalog[0]).toHaveProperty('inputs'); + expect(catalog[0]).toHaveProperty('intelligenceIndex'); + }); + + it('should set intelligenceIndex to null for installed-only (non-catalog) models', () => { + const catalog = getOllamaModelCatalog([ + { name: 'custom-model:latest', size: 512 * 1024 * 1024 } + ] as any); + const installedOnlyModel = catalog.find(model => model.name === 'custom-model:latest'); + expect(installedOnlyModel?.intelligenceIndex).toBeNull(); }); it('should mark installed catalog models and include installed-only models', () => { diff --git a/src/benchmark.ts b/src/benchmark.ts index c825be1..dadb5ae 100644 --- a/src/benchmark.ts +++ b/src/benchmark.ts @@ -25,6 +25,12 @@ export interface SupportedOllamaModel { contextWindow?: string; inputs: string[]; family: string; + /** + * Artificial Analysis Intelligence Index (higher = more capable). `null` means + * the model is not individually rated by the index (vision-only or very small + * models). See INTELLIGENCE_INDEX_* constants below for sourcing details. + */ + intelligenceIndex: number | null; } export interface OllamaModelCatalogEntry extends SupportedOllamaModel { @@ -33,6 +39,23 @@ export interface OllamaModelCatalogEntry extends SupportedOllamaModel { source: 'catalog' | 'installed'; } +/** + * Provenance for the per-model intelligence scores. + * + * Scores come from the Artificial Analysis Intelligence Index — a composite + * "intelligence" benchmark (MMLU-Pro, GPQA Diamond, LiveCodeBench, AIME, etc.) + * scored roughly 0–100 where higher is more capable. Values are a snapshot and + * are version-sensitive; vision-only (`-vl`) and very small models are not + * individually rated by the index and are left `null` ("Not rated"). + * + * To mirror CI-Hub's curated tutorial numbers exactly, override the + * `intelligenceIndex` values in SUPPORTED_OLLAMA_MODELS below — this is the + * single source of truth consumed by both the CLI and the web UI. + */ +export const INTELLIGENCE_INDEX_SOURCE = 'Artificial Analysis Intelligence Index'; +export const INTELLIGENCE_INDEX_URL = 'https://artificialanalysis.ai/'; +export const INTELLIGENCE_INDEX_AS_OF = '2026-06'; + // Predefined test prompts for benchmarking export const TEST_PROMPTS: BenchmarkPrompt[] = [ { @@ -156,48 +179,48 @@ const DEFAULT_PROMPT = TEST_PROMPTS[0].prompt; // This list matches the models listed in the README.md "Default LLM Tests" section // Users can override this by passing model names as command-line arguments export const SUPPORTED_OLLAMA_MODELS: SupportedOllamaModel[] = [ - { name: 'gemma3:270m', size: '292MB', contextWindow: '32K', inputs: ['Text'], family: 'gemma3' }, - { name: 'qwen3:0.6b', size: '523MB', contextWindow: '40K', inputs: ['Text'], family: 'qwen3' }, - { name: 'gemma3:1b', size: '815MB', contextWindow: '32K', inputs: ['Text'], family: 'gemma3' }, - { name: 'deepseek-r1:1.5b', size: '1.1GB', contextWindow: '128K', inputs: ['Text'], family: 'deepseek-r1' }, - { name: 'llama3.2:1b', size: '1.3GB', contextWindow: '128K', inputs: ['Text'], family: 'llama3.2' }, - { name: 'qwen3:1.7b', size: '1.4GB', contextWindow: '40K', inputs: ['Text'], family: 'qwen3' }, - { name: 'qwen3-vl:2b', size: '1.9GB', contextWindow: '256K', inputs: ['Text', 'Image'], family: 'qwen3-vl' }, - { name: 'llama3.2:3b', size: '2.0GB', contextWindow: '128K', inputs: ['Text'], family: 'llama3.2' }, - { name: 'qwen3:4b', size: '2.5GB', contextWindow: '256K', inputs: ['Text'], family: 'qwen3' }, - { name: 'gemma3:4b', size: '3.3GB', contextWindow: '128K', inputs: ['Text', 'Image'], family: 'gemma3' }, - { name: 'qwen3-vl:4b', size: '3.3GB', contextWindow: '256K', inputs: ['Text', 'Image'], family: 'qwen3-vl' }, - { name: 'deepseek-r1:7b', size: '4.7GB', contextWindow: '128K', inputs: ['Text'], family: 'deepseek-r1' }, - { name: 'llama3.1:8b', size: '4.9GB', contextWindow: '128K', inputs: ['Text'], family: 'llama3.1' }, - { name: 'deepseek-r1:8b', size: '5.2GB', contextWindow: '128K', inputs: ['Text'], family: 'deepseek-r1' }, - { name: 'qwen3:8b', size: '5.2GB', contextWindow: '40K', inputs: ['Text'], family: 'qwen3' }, - { name: 'qwen3-vl:8b', size: '6.1GB', contextWindow: '256K', inputs: ['Text', 'Image'], family: 'qwen3-vl' }, - { name: 'gemma3:12b', size: '8.1GB', contextWindow: '128K', inputs: ['Text', 'Image'], family: 'gemma3' }, - { name: 'deepseek-r1:14b', size: '9.0GB', contextWindow: '128K', inputs: ['Text'], family: 'deepseek-r1' }, - { name: 'qwen3:14b', size: '9.3GB', contextWindow: '40K', inputs: ['Text'], family: 'qwen3' }, - { name: 'gpt-oss:20b', size: '14GB', contextWindow: '128K', inputs: ['Text'], family: 'gpt-oss' }, - { name: 'gemma3:27b', size: '17GB', contextWindow: '128K', inputs: ['Text', 'Image'], family: 'gemma3' }, - { name: 'qwen3-coder:latest', size: '19GB', contextWindow: '256K', inputs: ['Text'], family: 'qwen3-coder' }, - { name: 'qwen3-coder:30b', size: '19GB', contextWindow: '256K', inputs: ['Text'], family: 'qwen3-coder' }, - { name: 'qwen3:30b', size: '19GB', contextWindow: '256K', inputs: ['Text'], family: 'qwen3' }, - { name: 'deepseek-r1:32b', size: '20GB', contextWindow: '128K', inputs: ['Text'], family: 'deepseek-r1' }, - { name: 'qwen3:32b', size: '20GB', contextWindow: '40K', inputs: ['Text'], family: 'qwen3' }, - { name: 'qwen3-vl:30b', size: '20GB', contextWindow: '256K', inputs: ['Text', 'Image'], family: 'qwen3-vl' }, - { name: 'qwen3-vl:32b', size: '21GB', contextWindow: '256K', inputs: ['Text', 'Image'], family: 'qwen3-vl' }, - { name: 'deepseek-r1:70b', size: '43GB', contextWindow: '128K', inputs: ['Text'], family: 'deepseek-r1' }, - { name: 'llama3.1:70b', size: '43GB', contextWindow: '128K', inputs: ['Text'], family: 'llama3.1' }, - { name: 'gpt-oss:120b', size: '65GB', contextWindow: '128K', inputs: ['Text'], family: 'gpt-oss' }, - { name: 'llama4:16x17b', size: '67GB', contextWindow: '10M', inputs: ['Text', 'Image'], family: 'llama4' }, - { name: 'GLM-4.6:TQ1_0', size: '84GB', contextWindow: '198K', inputs: ['Text'], family: 'GLM-4.6' }, - { name: 'qwen3:235b', size: '142GB', contextWindow: '256K', inputs: ['Text'], family: 'qwen3' }, - { name: 'qwen3-vl:235b', size: '143GB', contextWindow: '256K', inputs: ['Text', 'Image'], family: 'qwen3-vl' }, - { name: 'GLM-4.6:Q4_K_M', size: '216GB', contextWindow: '198K', inputs: ['Text'], family: 'GLM-4.6' }, - { name: 'llama3.1:405b', size: '243GB', contextWindow: '128K', inputs: ['Text'], family: 'llama3.1' }, - { name: 'llama4:128x17b', size: '245GB', contextWindow: '1M', inputs: ['Text', 'Image'], family: 'llama4' }, - { name: 'qwen3-coder:480b', size: '290GB', contextWindow: '256K', inputs: ['Text'], family: 'qwen3-coder' }, - { name: 'deepseek-v3.1:671b', size: '404GB', contextWindow: '160K', inputs: ['Text'], family: 'deepseek-v3.1' }, - { name: 'deepseek-r1:671b', size: '404GB', contextWindow: '160K', inputs: ['Text'], family: 'deepseek-r1' }, - { name: 'minmax m2', size: '968GB', contextWindow: '200K', inputs: ['Text'], family: 'minmax' } + { name: 'gemma3:270m', size: '292MB', contextWindow: '32K', inputs: ['Text'], family: 'gemma3', intelligenceIndex: null }, + { name: 'qwen3:0.6b', size: '523MB', contextWindow: '40K', inputs: ['Text'], family: 'qwen3', intelligenceIndex: null }, + { name: 'gemma3:1b', size: '815MB', contextWindow: '32K', inputs: ['Text'], family: 'gemma3', intelligenceIndex: null }, + { name: 'deepseek-r1:1.5b', size: '1.1GB', contextWindow: '128K', inputs: ['Text'], family: 'deepseek-r1', intelligenceIndex: null }, + { name: 'llama3.2:1b', size: '1.3GB', contextWindow: '128K', inputs: ['Text'], family: 'llama3.2', intelligenceIndex: null }, + { name: 'qwen3:1.7b', size: '1.4GB', contextWindow: '40K', inputs: ['Text'], family: 'qwen3', intelligenceIndex: 3 }, + { name: 'qwen3-vl:2b', size: '1.9GB', contextWindow: '256K', inputs: ['Text', 'Image'], family: 'qwen3-vl', intelligenceIndex: null }, + { name: 'llama3.2:3b', size: '2.0GB', contextWindow: '128K', inputs: ['Text'], family: 'llama3.2', intelligenceIndex: 4 }, + { name: 'qwen3:4b', size: '2.5GB', contextWindow: '256K', inputs: ['Text'], family: 'qwen3', intelligenceIndex: 6 }, + { name: 'gemma3:4b', size: '3.3GB', contextWindow: '128K', inputs: ['Text', 'Image'], family: 'gemma3', intelligenceIndex: 4 }, + { name: 'qwen3-vl:4b', size: '3.3GB', contextWindow: '256K', inputs: ['Text', 'Image'], family: 'qwen3-vl', intelligenceIndex: null }, + { name: 'deepseek-r1:7b', size: '4.7GB', contextWindow: '128K', inputs: ['Text'], family: 'deepseek-r1', intelligenceIndex: 8 }, + { name: 'llama3.1:8b', size: '4.9GB', contextWindow: '128K', inputs: ['Text'], family: 'llama3.1', intelligenceIndex: 8 }, + { name: 'deepseek-r1:8b', size: '5.2GB', contextWindow: '128K', inputs: ['Text'], family: 'deepseek-r1', intelligenceIndex: 9 }, + { name: 'qwen3:8b', size: '5.2GB', contextWindow: '40K', inputs: ['Text'], family: 'qwen3', intelligenceIndex: 9 }, + { name: 'qwen3-vl:8b', size: '6.1GB', contextWindow: '256K', inputs: ['Text', 'Image'], family: 'qwen3-vl', intelligenceIndex: null }, + { name: 'gemma3:12b', size: '8.1GB', contextWindow: '128K', inputs: ['Text', 'Image'], family: 'gemma3', intelligenceIndex: 7 }, + { name: 'deepseek-r1:14b', size: '9.0GB', contextWindow: '128K', inputs: ['Text'], family: 'deepseek-r1', intelligenceIndex: 13 }, + { name: 'qwen3:14b', size: '9.3GB', contextWindow: '40K', inputs: ['Text'], family: 'qwen3', intelligenceIndex: 11 }, + { name: 'gpt-oss:20b', size: '14GB', contextWindow: '128K', inputs: ['Text'], family: 'gpt-oss', intelligenceIndex: 24 }, + { name: 'gemma3:27b', size: '17GB', contextWindow: '128K', inputs: ['Text', 'Image'], family: 'gemma3', intelligenceIndex: 10 }, + { name: 'qwen3-coder:latest', size: '19GB', contextWindow: '256K', inputs: ['Text'], family: 'qwen3-coder', intelligenceIndex: 20 }, + { name: 'qwen3-coder:30b', size: '19GB', contextWindow: '256K', inputs: ['Text'], family: 'qwen3-coder', intelligenceIndex: 20 }, + { name: 'qwen3:30b', size: '19GB', contextWindow: '256K', inputs: ['Text'], family: 'qwen3', intelligenceIndex: 15 }, + { name: 'deepseek-r1:32b', size: '20GB', contextWindow: '128K', inputs: ['Text'], family: 'deepseek-r1', intelligenceIndex: 18 }, + { name: 'qwen3:32b', size: '20GB', contextWindow: '40K', inputs: ['Text'], family: 'qwen3', intelligenceIndex: 15 }, + { name: 'qwen3-vl:30b', size: '20GB', contextWindow: '256K', inputs: ['Text', 'Image'], family: 'qwen3-vl', intelligenceIndex: null }, + { name: 'qwen3-vl:32b', size: '21GB', contextWindow: '256K', inputs: ['Text', 'Image'], family: 'qwen3-vl', intelligenceIndex: null }, + { name: 'deepseek-r1:70b', size: '43GB', contextWindow: '128K', inputs: ['Text'], family: 'deepseek-r1', intelligenceIndex: 20 }, + { name: 'llama3.1:70b', size: '43GB', contextWindow: '128K', inputs: ['Text'], family: 'llama3.1', intelligenceIndex: 16 }, + { name: 'gpt-oss:120b', size: '65GB', contextWindow: '128K', inputs: ['Text'], family: 'gpt-oss', intelligenceIndex: 33 }, + { name: 'llama4:16x17b', size: '67GB', contextWindow: '10M', inputs: ['Text', 'Image'], family: 'llama4', intelligenceIndex: 13 }, + { name: 'GLM-4.6:TQ1_0', size: '84GB', contextWindow: '198K', inputs: ['Text'], family: 'GLM-4.6', intelligenceIndex: 30 }, + { name: 'qwen3:235b', size: '142GB', contextWindow: '256K', inputs: ['Text'], family: 'qwen3', intelligenceIndex: 45 }, + { name: 'qwen3-vl:235b', size: '143GB', contextWindow: '256K', inputs: ['Text', 'Image'], family: 'qwen3-vl', intelligenceIndex: null }, + { name: 'GLM-4.6:Q4_K_M', size: '216GB', contextWindow: '198K', inputs: ['Text'], family: 'GLM-4.6', intelligenceIndex: 30 }, + { name: 'llama3.1:405b', size: '243GB', contextWindow: '128K', inputs: ['Text'], family: 'llama3.1', intelligenceIndex: 17 }, + { name: 'llama4:128x17b', size: '245GB', contextWindow: '1M', inputs: ['Text', 'Image'], family: 'llama4', intelligenceIndex: 18 }, + { name: 'qwen3-coder:480b', size: '290GB', contextWindow: '256K', inputs: ['Text'], family: 'qwen3-coder', intelligenceIndex: 24 }, + { name: 'deepseek-v3.1:671b', size: '404GB', contextWindow: '160K', inputs: ['Text'], family: 'deepseek-v3.1', intelligenceIndex: 28 }, + { name: 'deepseek-r1:671b', size: '404GB', contextWindow: '160K', inputs: ['Text'], family: 'deepseek-r1', intelligenceIndex: 27 }, + { name: 'minmax m2', size: '968GB', contextWindow: '200K', inputs: ['Text'], family: 'minmax', intelligenceIndex: 44 } ]; export const DEFAULT_MODELS: string[] = SUPPORTED_OLLAMA_MODELS.map(model => model.name); @@ -244,6 +267,7 @@ export function getOllamaModelCatalog(installedModels: OllamaModel[] = []): Olla contextWindow: undefined, inputs: ['Text'], family: inferModelFamily(model.name), + intelligenceIndex: null, installed: true, supported: false, source: 'installed' as const diff --git a/src/server.test.ts b/src/server.test.ts index a9aae2d..ed7463b 100644 --- a/src/server.test.ts +++ b/src/server.test.ts @@ -576,7 +576,60 @@ describe('Server Module', () => { }); }); + describe('GET /api/meta', () => { + it('should return intelligence-score attribution metadata', (done) => { + const req = { + method: 'GET', + url: '/api/meta' + } as http.IncomingMessage; + + const res = { + writeHead: jest.fn(), + end: jest.fn((data) => { + expect(res.writeHead).toHaveBeenCalledWith(200, { + 'Content-Type': 'application/json', + 'Access-Control-Allow-Origin': '*' + }); + const meta = JSON.parse(data); + expect(meta).toHaveProperty('intelligence'); + expect(meta.intelligence).toHaveProperty('source'); + expect(meta.intelligence).toHaveProperty('url'); + expect(meta.intelligence).toHaveProperty('asOf'); + expect(meta.intelligence.source).toMatch(/Artificial Analysis/i); + done(); + }) + } as unknown as http.ServerResponse; + + server.emit('request', req, res); + }); + }); + describe('GET /api/models', () => { + it('should include the intelligence index on catalog entries', (done) => { + mockedAxios.get.mockResolvedValue({ data: { models: [] } }); + + const req = { + method: 'GET', + url: '/api/models' + } as http.IncomingMessage; + + const res = { + writeHead: jest.fn(), + end: jest.fn((data) => { + const models = JSON.parse(data); + expect(models.length).toBeGreaterThan(0); + models.forEach((model: any) => { + expect(model).toHaveProperty('intelligenceIndex'); + }); + const gptOss = models.find((m: any) => m.name === 'gpt-oss:120b'); + expect(typeof gptOss.intelligenceIndex).toBe('number'); + done(); + }) + } as unknown as http.ServerResponse; + + server.emit('request', req, res); + }); + it('should merge installed models with the supported catalog', (done) => { mockedAxios.get.mockResolvedValue({ data: { diff --git a/src/server.ts b/src/server.ts index eae5d72..2b96a89 100644 --- a/src/server.ts +++ b/src/server.ts @@ -4,7 +4,7 @@ import * as http from 'http'; import * as fs from 'fs'; import * as path from 'path'; import { initDatabase, getAllBenchmarkResults, getLatestSystemSpecs, getBenchmarkResultsWithSpecs, getDatabase } from './database'; -import { benchmarkModel, getOllamaModelCatalog, saveResultsToCSV, saveResultsToDatabase, TEST_PROMPTS } from './benchmark'; +import { benchmarkModel, getOllamaModelCatalog, saveResultsToCSV, saveResultsToDatabase, TEST_PROMPTS, INTELLIGENCE_INDEX_SOURCE, INTELLIGENCE_INDEX_URL, INTELLIGENCE_INDEX_AS_OF } from './benchmark'; import axios from 'axios'; const PORT = parseInt(process.env.PORT || '3000', 10); @@ -97,6 +97,22 @@ async function handleApiRequest(req: http.IncomingMessage, res: http.ServerRespo } } + // API endpoint: App metadata (intelligence-score attribution, etc.) + if (url === '/api/meta') { + res.writeHead(200, { + 'Content-Type': 'application/json', + 'Access-Control-Allow-Origin': '*' + }); + res.end(JSON.stringify({ + intelligence: { + source: INTELLIGENCE_INDEX_SOURCE, + url: INTELLIGENCE_INDEX_URL, + asOf: INTELLIGENCE_INDEX_AS_OF + } + })); + return true; + } + // API endpoint: Get available test prompts if (url === '/api/prompts') { res.writeHead(200, {