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refactor: Update CLI mode documentation with commands and interactive features (#8303)
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Bashwara Undupitiya
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# CLI Mode
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OpenHands can be run in an interactive CLI mode, which allows users to start an interactive session via the command line.
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CLI mode provides a powerful interactive Command-Line Interface (CLI) that lets you engage with OpenHands directly from your terminal.
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This mode is different from the [headless mode](headless-mode), which is non-interactive and better for scripting.
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## With Python
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## Getting Started
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To start an interactive OpenHands session via the command line:
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### Prerequisites
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- Ensure you have followed the [Development setup instructions](https://github.com/All-Hands-AI/OpenHands/blob/main/Development.md).
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- You will need your LLM model name and API key.
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1. Ensure you have followed the [Development setup instructions](https://github.com/All-Hands-AI/OpenHands/blob/main/Development.md).
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2. Run the following command:
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### Running with Python
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To launch an interactive OpenHands conversation from the command line:
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```bash
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poetry run python -m openhands.core.cli
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poetry run python -m openhands.cli.main
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```
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This command will start an interactive session where you can input tasks and receive responses from OpenHands.
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This command opens an interactive prompt where you can type tasks or commands and get responses from OpenHands.
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You'll need to be sure to set your model, API key, and other settings via environment variables
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[or the `config.toml` file](https://github.com/All-Hands-AI/OpenHands/blob/main/config.template.toml).
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You can set your model, API key, and other preferences using environment variables or with the [`config.toml`](https://github.com/All-Hands-AI/OpenHands/blob/main/config.template.toml) file.
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## With Docker
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### Running with Docker
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To use OpenHands CLI mode with Docker:
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To run OpenHands in CLI mode with Docker:
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1. Set the following environment variables in your terminal:
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- `SANDBOX_VOLUMES` to specify the directory you want OpenHands to access (Ex: `export SANDBOX_VOLUMES=$(pwd)/workspace:/workspace:rw`).
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- The agent works in `/workspace` by default, so mount your project directory there if you want the agent to modify files.
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- For read-only data, use a different mount path (Ex: `export SANDBOX_VOLUMES=$(pwd)/workspace:/workspace:rw,/path/to/large/dataset:/data:ro`).
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- `LLM_MODEL` — the LLM model to use (e.g. `export LLM_MODEL="anthropic/claude-3-5-sonnet-20241022"`)
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- `LLM_API_KEY` — your API key (e.g. `export LLM_API_KEY="sk_test_12345"`)
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1. Set the following environmental variables in your terminal:
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- `SANDBOX_VOLUMES` to specify the directory you want OpenHands to access (Ex: `export SANDBOX_VOLUMES=$(pwd)/workspace:/workspace:rw`).
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- The agent works in `/workspace` by default, so mount your project directory there if you want the agent to modify files.
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- For read-only data, use a different mount path (Ex: `export SANDBOX_VOLUMES=$(pwd)/workspace:/workspace:rw,/path/to/large/dataset:/data:ro`).
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- `LLM_MODEL` to the model to use (Ex: `export LLM_MODEL="anthropic/claude-3-5-sonnet-20241022"`).
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- `LLM_API_KEY` to the API key (Ex: `export LLM_API_KEY="sk_test_12345"`).
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2. Run the following Docker command:
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2. Run the following command:
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```bash
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docker run -it \
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@@ -47,10 +46,73 @@ docker run -it \
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--add-host host.docker.internal:host-gateway \
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--name openhands-app-$(date +%Y%m%d%H%M%S) \
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docker.all-hands.dev/all-hands-ai/openhands:0.37 \
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python -m openhands.core.cli
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python -m openhands.cli.main
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```
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This command will start an interactive session in Docker where you can input tasks and receive responses from OpenHands.
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This launches the CLI in Docker, allowing you to interact with OpenHands as described above.
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The `-e SANDBOX_USER_ID=$(id -u)` is passed to the Docker command to ensure the sandbox user matches the host user’s
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permissions. This prevents the agent from creating root-owned files in the mounted workspace.
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The `-e SANDBOX_USER_ID=$(id -u)` ensures files created by the agent in your workspace have the correct permissions.
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---
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## Interactive CLI Overview
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### What is CLI Mode?
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CLI mode enables real-time interaction with OpenHands agents. You can type natural language tasks, use interactive commands, and receive instant feedback—all inside your terminal.
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### Starting a Conversation
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When you start the CLI, you'll see a welcome message and a prompt (`>`). Enter your first task or type a command to begin your conversation.
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### Entering Tasks
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Type your request (for example, "Refactor the utils.py file to improve readability") and press Enter. The agent will process your input and reply.
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---
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## Available Commands
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You can use the following commands whenever the prompt (`>`) is displayed:
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| Command | Description |
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|--------------|----------------------------------------------------------------|
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| `/help` | Show all available interactive commands and their descriptions |
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| `/exit` | Exit the application |
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| `/init` | Initialize a new repository for agent exploration |
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| `/status` | Show conversation details and usage metrics |
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| `/new` | Start a new conversation |
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| `/settings` | View and modify current LLM/agent settings |
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| `/resume` | Resume the agent if paused |
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---
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## Settings and Configuration
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You can update your model, API key, agent, and other preferences interactively using the `/settings` command. Just follow the prompts:
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- **Basic settings**: Choose a model/provider and enter your API key.
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- **Advanced settings**: Set custom endpoints, enable or disable confirmation mode, and configure memory condensation.
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Settings can also be managed via the `config.toml` file.
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---
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## Repository Initialization
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The `/init` command helps the agent understand your project by creating a `.openhands/microagents/repo.md` file with project details and structure. Use this when onboarding the agent to a new codebase.
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---
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## Agent Pause/Resume Feature
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You can pause the agent while it is running by pressing `Ctrl-P`. To continue the conversation after pausing, simply type `/resume` at the prompt.
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---
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## Tips and Troubleshooting
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- Use `/help` at any time to see the list of available commands.
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- If you encounter permission issues, make sure your workspace directory is trusted and all required environment variables are set correctly.
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- For advanced LLM configuration, use the advanced options in `/settings`.
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- When confirmation mode is enabled, the CLI will prompt before sensitive operations. You can type `a` or `always` at the first confirmation prompt to automatically confirm subsequent actions for the current conversation.
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- If you want to start over, use `/new` to begin a fresh conversation without restarting the CLI.
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---
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