Content
# Strands CLI
> When terminal meets intelligence: AI at your fingertips.
A minimalist Strands Agents-powered CLI assistant for your terminal. Strands brings the power of Claude 3.7 Sonnet to your command line with advanced tool integration and knowledge base capabilities.
## Quick Start
```bash
# Install
pipx install strands-agents-builder
# Run interactive mode
strands
# One-off query
strands "What's the capital of France?"
# Pipe content
cat document.txt | strands "Summarize this"
# Use with knowledge base
strands --kb YOUR_KB_ID "Tell me about our project"
```
## Features
- 💬 Interactive command-line interface with rich output
- 🔍 One-off queries via arguments or pipes
- 🛠️ Powerful integrated tools (12+ tools including shell, editor, HTTP, Python)
- 🧠 Knowledge base integration for memory and context
- 🎮 Customizable system prompt
- 🪄 Nested agent capabilities with tool delegation
- 🔧 Dynamic tool loading for extending functionality
- 🖥️ Environment variable management and customization
## Integrated Tools
Strands comes with a comprehensive set of built-in tools:
- **shell**: Run command-line operations with interactive support
- **editor**: View and edit files with syntax highlighting
- **http_request**: Make API calls with authentication support
- **python_repl**: Execute Python code interactively
- **calculator**: Perform mathematical operations powered by SymPy
- **retrieve**: Query knowledge bases for relevant information
- **store_in_kb**: Save content to knowledge bases for future reference
- **load_tool**: Dynamically load additional tools at runtime
- **environment**: Manage environment variables
- **strands**: Create nested agent instances with specialized capabilities
- **dialog**: Create interactive dialog interfaces
- **use_aws**: Make AWS API calls through boto3
## Knowledge Base Integration
Strands can leverage Amazon Bedrock Knowledge Bases to retrieve information and remember conversations.
```bash
# Specify knowledge base via command line
strands --kb YOUR_KB_ID "What does our API do?"
# Or set a default knowledge base via environment variable
export STRANDS_KNOWLEDGE_BASE_ID="YOUR_KB_ID"
strands "What were our key decisions last week?"
```
Features:
- 🔄 Automatic retrieval of relevant information before answering queries
- 💾 Conversation storage for building persistent memory
- 📝 Every exchange is stored with proper formatting for future reference
- 🔍 Contextual awareness across multiple conversations
## Nested Agent Capabilities
Use the `strands` tool to create specialized sub-agents with their own tools and system prompts:
```python
# Basic usage
agent.tool.strand(query="List files in the current directory")
# With specific tools
agent.tool.strand(
query="Analyze this Python code",
tool_names=["python_repl", "editor"],
system_prompt="You are an expert Python developer specializing in code optimization."
)
```
## Custom Model Provider
You can configure strands to use a different model provider with specific settings by passing in the following arguments:
```bash
strands --model-provider <NAME> --model-config <JSON|FILE>
```
As an example, if you wanted to use the packaged Ollama provider with a specific model id, you would run:
```bash
strands --model-provider ollama --model-config '{"model_id": <ID>}'
```
Strands is packaged with the following providers:
| Name | Config |
| ---- | ------ |
| `bedrock` | [reference](<LINK>) |
| `ollama` | [reference](<LINK>) |
If you have implemented a custom model provider ([instructions](<LINK>)) and would like to use it with strands, create a python module under the directory "$CWD/.models" and expose an `instance` function that returns an instance of your provider. As an example, assume you have:
```bash
$ cat ./.models/custom_model.py
from mymodels import CustomModel
def instance(**config):
return CustomModel(**config)
```
You can then use it with strands by running:
```bash
$ strands --model-provider custom_model --model-config <JSON|FILE>
```
## Custom Systm Prompts
```bash
# Via environment variable
export STRANDS_SYSTEM_PROMPT="You are a Python expert."
# Or local file
echo "You are a security expert." > .prompt
```
## Contributing
```bash
git clone https://github.com/strands-agents/agent-builder.git ~/.agent-builder
cd ~/.agent-builder
python3 -m venv venv && source venv/bin/activate
pip3 install -e .
pip3 install -e ".[test]"
# Run tests
hatch run test # Run all tests with verbose coverage output
hatch run test -k test_pattern # Run specific tests matching a pattern
```
Testing is managed through hatch scripting in pyproject.toml.
## Exit
Type `exit`, `quit`, or press `Ctrl+C`/`Ctrl+D`
