feat(macos): add Canvas A2UI renderer

vendor/a2ui/specification/0.8/eval/README.md

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+# Genkit Eval Framework for UI generation
+
+This is for evaluating A2UI (v0.8) against various LLMs.
+
+## Setup
+
+To use the models, you need to set the following environment variables with your API keys:
+
+- `GEMINI_API_KEY`
+- `OPENAI_API_KEY`
+- `ANTHROPIC_API_KEY`
+
+You can set these in a `.env` file in the root of the project, or in your shell's configuration file (e.g., `.bashrc`, `.zshrc`).
+
+You also need to install dependencies before running:
+
+```bash
+pnpm install
+```
+
+## Running all evals (warning: can use *lots* of model quota)
+
+To run the flow, use the following command:
+
+```bash
+pnpm run evalAll
+```
+
+## Running a Single Test
+
+You can run the script for a single model and data point by using the `--model` and `--prompt` command-line flags. This is useful for quick tests and debugging.
+
+### Syntax
+
+```bash
+pnpm run eval -- --model='<model_name>' --prompt=<prompt_name>
+```
+
+### Example
+
+To run the test with the `gpt-5-mini (reasoning: minimal)` model and the `generateDogUIs` prompt, use the following command:
+
+```bash
+pnpm run eval -- --model='gpt-5-mini (reasoning: minimal)' --prompt=generateDogUIs
+```
+
+## Controlling Output
+
+By default, the script only prints the summary table and any errors that occur during generation. To see the full JSON output for each successful generation, use the `--verbose` flag.
+
+To keep the input and output for each run in separate files, specify the `--keep=<output_dir>` flag, which will create a directory hierarchy with the input and output for each LLM call in separate files.
+
+### Example
+
+```bash
+pnpm run evalAll -- --verbose
+```
+
+```bash
+pnpm run evalAll -- --keep=output
+```