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Analyze images with state‑of‑the‑art vision AI, instantly.","maintainers":[{"name":"xfanwu","email":"xfanwu@gmail.com"}],"readme":"# ChanceVision CLI\n\n[![CI](https://github.com/chancevision/chancevision-cli/actions/workflows/ci.yml/badge.svg)](https://github.com/chancevision/chancevision-cli/actions/workflows/ci.yml)\n[![npm version](https://img.shields.io/npm/v/@chancevision/cli)](https://www.npmjs.com/package/@chancevision/cli)\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE)\n[![Node.js](https://img.shields.io/badge/node-%3E%3D20-brightgreen)](https://nodejs.org)\n\n![ChanceVision CLI banner](.github/assets/banner.png)\n\n**Give your terminal, scripts, and agents eyes.**\n\nChanceVision CLI analyzes image URLs and local image files with the [Chance Vision](https://chance.vision) visual intelligence API. Use it to inspect screenshots, understand UI states, extract visual details, caption images, and give AI agents a simple command-line way to see.\n\n```bash\nnpm install -g @chancevision/cli\nexport CHANCEVISION_API_KEY=\"sk-...\"\n\nchancevision see ./screenshot.png\n```\n\n## Why ChanceVision CLI?\n\n- **Vision from the shell**: analyze local files or remote image URLs without opening a browser.\n- **Agent-friendly by design**: any agent that supports tools, skills, or shell commands can install and call it.\n- **Clean default output**: prints the model answer by default for easy reading and piping.\n- **Two focused formats**: request `markdown` for readable reports or `ui_component` for structured UI output.\n- **Streaming support**: use `--stream` when you want real-time output in interactive workflows.\n- **Script-ready**: works with environment-based auth, file paths, URLs, and standard CLI output.\n\n## Use Cases\n\n| Use case          | Example command                                                            |\n| ----------------- | -------------------------------------------------------------------------- |\n| Screenshot review | `chancevision see ./app-screen.png`                                        |\n| Markdown report   | `chancevision see --output-format markdown ./design.png`                   |\n| UI component data | `chancevision see --output-format ui_component ./mockup.png`               |\n| Remote image      | `chancevision see https://images.chance.vision/image/revisit.png`          |\n| Live response     | `chancevision see --stream https://images.chance.vision/image/revisit.png` |\n\n## Install\n\nRequires Node.js 20 or newer.\n\n```bash\n# npm\nnpm install -g @chancevision/cli\n\n# pnpm\npnpm add -g @chancevision/cli\n\n# yarn\nyarn global add @chancevision/cli\n\n# bun\nbun add -g @chancevision/cli\n\n# Run without installing\nnpx @chancevision/cli see --help\n```\n\n## Quick Start\n\n> **Get your API key** → [platform.chance.vision](https://platform.chance.vision/)\n\n```bash\nexport CHANCEVISION_API_KEY=\"sk-...\"\n\n# Analyze an image from a URL\nchancevision see https://example.com/photo.png\n\n# Analyze a local file\nchancevision see ~/Pictures/screenshot.png\n\n# Stream the response in real time\nchancevision see -s https://example.com/photo.png\n```\n\n## Agent-Ready\n\nChanceVision CLI works well inside local agent tools that can run shell commands, including [OpenClaw](https://github.com/bigcode-project/openclaw), [Hermes](https://github.com/NousResearch/hermes-agent), [Codex](https://github.com/openai/codex), [Claude Code](https://code.claude.com/), and similar agents.\n\nGive your agent this install prompt:\n\n```text\nInstall ChanceVision CLI so you can analyze screenshots and image files from the terminal.\n\nSteps:\n1. Check that Node.js 20+ is available.\n2. Install the CLI globally:\n   npm install -g @chancevision/cli\n3. Verify the install:\n   chancevision --help\n4. Use the existing CHANCEVISION_API_KEY environment variable if present.\n5. Do not print, log, or commit API keys.\n6. When asked to inspect an image, run:\n   chancevision see <image-path-or-url>\n7. For markdown output, run:\n   chancevision see --output-format markdown <image-path-or-url>\n8. For structured UI output, run:\n   chancevision see --output-format ui_component <image-path-or-url>\n```\n\n## Authentication\n\n```bash\n# Option 1: Flag, useful for one-off commands\nchancevision see -k \"sk-...\" https://example.com/img.png\n\n# Option 2: Environment variable, recommended for daily use\nexport CHANCEVISION_API_KEY=\"sk-...\"\nchancevision see https://example.com/img.png\n```\n\n## Usage\n\n```text\nchancevision see <image> [options]\n```\n\nSends the image to the model (`chance/chance-vision-1.5`) for analysis.\n\n### Options\n\n| Option                     | Default      | Description                                     |\n| -------------------------- | ------------ | ----------------------------------------------- |\n| `<image>`                  | _(required)_ | Image URL or local file path to analyze         |\n| `-k, --api-key <key>`      | -            | API key (or use `CHANCEVISION_API_KEY` env var) |\n| `-s, --stream`             | `false`      | Stream the response as SSE chunks               |\n| `--output-format <format>` | `markdown`   | Output format: `markdown` or `ui_component`     |\n| `--json`                   | `false`      | Print the raw JSON API response                 |\n| `-v, --verbose`            | `false`      | Show redacted request details and raw chunks    |\n\n## Development\n\n```bash\ngit clone https://github.com/chancevision/chancevision-cli\ncd chancevision-cli\npnpm install\n\n# Run checks\npnpm lint\npnpm typecheck\npnpm test\n\n# Build\npnpm build\n```\n\nTo try your local build globally:\n\n```bash\npnpm link --global\nchancevision --help\n```\n\nSee [CONTRIBUTING.md](CONTRIBUTING.md) for contribution guidelines.\n\n## API\n\nThis CLI is powered by the [Chance Vision API](https://chance.vision), a visual intelligence platform with streaming support and UI-component output.\n\n`POST https://openapi.chance.vision/v1/chat/completions`\n\n## License\n\n[MIT](LICENSE)\n","readmeFilename":"README.md"}