Installation

Building From Package

Important

This part is in-the-works! For now, please refer to the Building From Source (with pip) section below.

Building From Source (with pip)

Make sure you have Python 3.12 and Poetry installed!

Clone this repository.

git clone https://github.com/couchbaselabs/agent-catalog

Installation using Makefile

To run the following make commands, you must have Anaconda and Make installed (make for MacOS, Windows, Ubuntu).

We recommend using Anaconda to create a virtual environment for your project to ensure no global dependencies interfere with the project.

Click here for Anaconda installation steps.

Once anaconda or any of its distribution is installed, run the following commands to create and activate a virtual environment using Anaconda and install Agentc. Replace agentcenv with any other suitable environment name.

You are now ready to explore Agentc!
Manual Installation

Alternatively, you can choose to manually install Agentc by first creating a virtual environment either using Anaconda or any other Python virtual environment manager.
```
conda create -n agentcenv python=3.12
conda activate agentcenv
```
Once environment is set up, execute the following command to install a local package with pip:
```
cd agent-catalog
# Install the agentc package.
pip install libs/agentc
```
If you are interested in developing with langchain, also install agentc_langchain by running the following:
```
cd libs/agentc
poetry build
```

Building From Source (with Poetry)

Make sure you have Python 3.12 and Poetry installed!

Clone this repository.

git clone https://github.com/couchbaselabs/agent-catalog

Within your own pyproject.toml file, add the following dependency to your project: The path should point to the location of the agentc package (and is relative to the pyproject.toml file itself).
```
[tool.poetry.dependencies]
agentc = { path = "agent-catalog/libs/agentc", develop = true }
```
Run the command poetry update to install the Agent Catalog package.
```
cd agent-catalog
poetry update
```
Install using Makefile

You can install Agentc without adding to your pyproject if you wish to explore first. Simply run the following make commands to create and activate a virtual environment and install the requirements.

To run the following make commands, you must have Anaconda and Make installed (make for MacOS, Windows, Ubuntu).

We recommend using Anaconda to create a virtual environment for your project to ensure no global dependencies interfere with the project.

Click here for Anaconda installation steps.

Once anaconda or any of its distribution is installed, run the following commands to create and activate a virtual environment using Anaconda and install Agentc.

Replace agentcenv with any other suitable environment name.
```
make dev-local-poetry env_name=agentcenv
conda activate agentcenv
```

Verifying Your Installation

If you’ve followed the steps above, you should now have the agentc command line tool. Run agentc --help to verify your installation (note that your first run will take a couple of seconds as some libraries like numpy need to be built, subsequent runs will be faster).

Usage: agentc [OPTIONS] COMMAND [ARGS]...

  The Couchbase Agent Catalog command line tool.

Options:
  -c, --catalog DIRECTORY         Directory of the local catalog files.  [default: .agent-catalog]
  -a, --activity DIRECTORY        Directory of the local activity files (runtime data).  [default: .agent-activity]
  -v, --verbose                   Flag to enable verbose output.  [default: 0; 0<=x<=2]
  -i, --interactive / -ni, --no-interactive
                                  Flag to enable interactive mode.  [default: i]
  --help                          Show this message and exit.

Commands:
  add      Interactively create a new tool or prompt and save it to the filesystem (output).
  clean    Delete all or specific (catalog and/or activity) agent related files / collections.
  env      Return all agentc related environment and configuration parameters as a JSON object.
  execute  Search and execute a specific tool.
  find     Find items from the catalog based on a natural language QUERY string or by name.
  index    Walk the source directory trees (SOURCE_DIRS) to index source files into the local catalog.
  ls       List all indexed tools and/or prompts in the catalog.
  publish  Upload the local catalog and/or logs to a Couchbase instance.
  status   Show the status of the local catalog.
  version  Show the current version of agentc.

  See: https://docs.couchbase.com or https://couchbaselabs.github.io/agent-catalog/index.html# for more information.

If you see the output above, you are all set! To build your first agent, head on over to the user guide page.