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StreamLM\n\n[![Downloads](https://static.pepy.tech/badge/streamlm)](https://pepy.tech/project/streamlm)\n[![PyPI version](https://badge.fury.io/py/streamlm.svg)](https://badge.fury.io/py/streamlm)\n[![GitHub Release](https://img.shields.io/github/v/release/jeffmylife/streamlm)](https://github.com/jeffmylife/streamlm/releases)\n[![Build Status](https://github.com/jeffmylife/streamlm/workflows/Test/badge.svg)](https://github.com/jeffmylife/streamlm/actions)\n[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)\n\nA command-line interface for interacting with various Large Language Models with beautiful markdown-formatted responses.\n\n## Installation\n\n### uv (recommended)\n\n```bash\nuv tool install streamlm\n```\n\n### PyPI\n```bash\npip install streamlm\n```\n\n### Homebrew (macOS/Linux)\n```bash\nbrew install jeffmylife/streamlm/streamlm\n```\n\n## Usage\n\nAfter installation, you can use the `lm` command:\n\n```bash\nlm explain quantum computing\nlm -m gpt-4o \"write a Python function\"\nlm -m claude-3-5-sonnet \"analyze this data\"\n```\n\n### Raw Markdown Output\n\nStreamLM includes beautiful built-in markdown formatting, but you can also output raw markdown for piping to other tools:\n\n```bash\n# Output raw markdown without Rich formatting\nlm --md \"explain machine learning\" \u003e output.md\n\n# Pipe to your favorite markdown formatter (like glow)\nlm --md \"write a Python tutorial\" | glow\n\n# Use with other markdown tools\nlm --raw \"create documentation\" | pandoc -f markdown -t html\n```\n\n### Supported Models\n\nStreamLM provides access to various Large Language Models including:\n\n- **OpenAI**: GPT-4o, o1, o3-mini, GPT-4o-mini\n- **Anthropic**: Claude-3-7-sonnet, Claude-3-5-sonnet, Claude-3-5-haiku\n- **Google**: Gemini-2.5-flash, Gemini-2.5-pro, Gemini-2.0-flash-thinking\n- **DeepSeek**: DeepSeek-R1, DeepSeek-V3\n- **xAI**: Grok-4, Grok-3-beta, Grok-3-mini-beta\n- **Local models**: Via Ollama (Llama3.3, Qwen2.5, DeepSeek-Coder, etc.)\n\n### Options\n\n- `--model` / `-m`: Choose the LLM model\n- `--image` / `-i`: Include image files for vision models\n- `--context` / `-c`: Add context from a file\n- `--max-tokens` / `-t`: Set maximum response length\n- `--temperature` / `-temp`: Control response creativity (0.0-1.0)\n- `--think`: Show reasoning process (for reasoning models)\n- `--debug` / `-d`: Enable debug mode\n- `--raw` / `--md`: Output raw markdown without Rich formatting\n\n## Features\n\n- 🎨 Beautiful markdown-formatted responses\n- 🖼️ Image input support for compatible models\n- 📁 Context file support\n- 🧠 Reasoning model support (DeepSeek, OpenAI o1, etc.)\n- 🔧 Extensive model support across providers\n- ⚡ Fast and lightweight\n- 🛠️ Easy configuration\n\n## Links\n\n- [PyPI Package](https://pypi.org/project/streamlm/)\n- [Homebrew Tap](https://github.com/jeffmylife/homebrew-streamlm)\n- [Issues](https://github.com/jeffmylife/streamlm/issues)\n\n## License\n\nMIT License - see [LICENSE](LICENSE) file for details.\n\n## Development\n\n```bash\n# Make your changes\nuv version --bump patch\ngit add .\ngit commit -m \"feat: your changes\"\ngit push\n\n# Create GitHub release (this triggers everything automatically)\ngh release create v0.1.4 --generate-notes\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjeffmylife%2Fstreamlm","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjeffmylife%2Fstreamlm","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjeffmylife%2Fstreamlm/lists"}