mirror of
https://github.com/langbot-app/LangBot.git
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RockChinQ
135 lines
3.6 KiB
Markdown
135 lines
3.6 KiB
Markdown
# LangBot PyPI Package Installation
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## Quick Start with uvx
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The easiest way to run LangBot is using `uvx` (recommended for quick testing):
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```bash
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uvx langbot
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```
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This will automatically download and run the latest version of LangBot.
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SeekDB support is optional and is not installed by the command above. If you
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want to use the SeekDB vector database or the built-in SeekDB embedding model,
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run LangBot with the `seekdb` extra:
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```bash
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uvx --from 'langbot[seekdb]@latest' langbot
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```
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The extra includes native dependencies whose supported operating systems may
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be narrower than LangBot's. In particular, the current Apple Silicon wheels
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require macOS 15 or later. The default Chroma backend does not have this
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requirement.
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## Install with pip/uv
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You can also install LangBot as a regular Python package:
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```bash
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# Using pip
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pip install langbot
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# Using uv
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uv pip install langbot
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# Include optional SeekDB support
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pip install 'langbot[seekdb]'
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# or: uv pip install 'langbot[seekdb]'
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```
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Then run it:
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```bash
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langbot
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```
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Or using Python module syntax:
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```bash
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python -m langbot
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```
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## Installation with Frontend
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When published to PyPI, the LangBot package includes the pre-built frontend files. You don't need to build the frontend separately.
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## Data Directory
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When running LangBot as a package, it will create a `data/` directory in your current working directory to store configuration, logs, and other runtime data. You can run LangBot from any directory, and it will set up its data directory there.
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## Command Line Options
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LangBot supports the following command line options:
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- `--standalone-runtime`: Use standalone plugin runtime
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- `--debug`: Enable debug mode
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Example:
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```bash
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langbot --debug
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```
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## Comparison with Other Installation Methods
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### PyPI Package (uvx/pip)
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- **Pros**: Easy to install and update, no need to clone repository or build frontend
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- **Cons**: Less flexible for development/customization
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### Docker
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- **Pros**: Isolated environment, easy deployment
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- **Cons**: Requires Docker
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### Manual Source Installation
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- **Pros**: Full control, easy to customize and develop
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- **Cons**: Requires building frontend, managing dependencies manually
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## Development
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If you want to contribute or customize LangBot, you should still use the manual installation method by cloning the repository:
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```bash
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git clone https://github.com/langbot-app/LangBot
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cd LangBot
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uv sync
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cd web
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npm install
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npm run build
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cd ..
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uv run main.py
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```
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## Updating
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To update to the latest version:
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```bash
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# With pip
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pip install --upgrade langbot
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# With uv
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uv pip install --upgrade langbot
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# With uvx (automatically uses latest)
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uvx langbot
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```
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## System Requirements
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- Python 3.11 or higher (lower than Python 4)
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- Operating System: Linux, macOS, or Windows
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## Differences from Source Installation
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When running LangBot from the PyPI package (via uvx or pip), there are a few behavioral differences compared to running from source:
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1. **Version Check**: The package version does not prompt for user input when the Python version is incompatible. It simply prints an error message and exits. This makes it compatible with non-interactive environments like containers and CI/CD.
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2. **Working Directory**: The package version does not require being run from the LangBot project root. You can run `langbot` from any directory, and it will create a `data/` directory in your current working directory.
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3. **Frontend Files**: The frontend is pre-built and included in the package, so you don't need to run `npm build` separately.
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These differences are intentional to make the package more user-friendly and suitable for various deployment scenarios.
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