Installation¶

Installing from PyPI¶

Note

This section is in the works! We recommend installing from our pre-built packages in the meantime.

Make sure you have python3.11 and sentence-transformers) installed!
Install agentc with pip.
```
$ pip install agentc
```
If you are interested in developing with LangChain or LangGraph, install the helper agentc_langchain package and/or agentc_langgraph packages as extras:
```
$ pip install agentc[langchain,langgraph]
```
Similarly, for LlamaIndex Developers:
```
$ pip install agentc[llamaindex]
```
Validate your installation by running agentc. If your installation was successful, you should see the following output:

Make sure you have python3.11 and sentence-transformers) installed!
Navigate to the releases page for Agent Catalog here and choose the latest version. Expand the "Assets" tab and download all *.whl files (e.g., agentc-0.2.0+g59944db-py3-none-any.whl) into your project location.

Install the agentc packages using the .whl file and pip. Note that order matters here!

$ pip install agentc_core-*.whl
$ pip install agentc_cli-*.whl
$ pip install agentc-*.whl

Make sure you have python3.11 and poetry installed!
Make sure you have make installed! For Mac-based installations, see here. For Windows-based installations, see here. For Ubuntu-based installations, see here.

Clone this repository.

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

Navigate to the agent-catalog directory and run make. This will a) create a new virtual environment using Poetry and b) install all required packages and CLI tools.
Activate your newly created virtual environment using the outputs of make activate or poetry env activate. If you do not want to copy-and-paste the output, you can run the command with eval:
```
$ eval $(poetry env activate)
```
If your environment has been successfully activated, you should see (Activated) after running poetry env list.
```
$ poetry env list
agent-catalog-UEfqTvAT-py3.13 (Activated)
```
Note

Note that you must activate your environment before running any agentc commands!
If you are interested in building a .whl file (for later use in .whl-based installation in other projects), run the following command:
```
$ ./scripts/pre-build.sh
$ ./scripts/build.sh
$ ./scripts/post-build.sh
```
Your .whl files will end up in the dist folder.

Make sure you have python3.11 and conda installed!
Create a new virtual environment with Anaconda and subsequently activate your environment. Again, you must activate your environment before running any agentc commands!
```
$ conda create -n my_agentc_env python=3.11
$ conda activate my_agentc_env
```
Add sentence-transformers to your new environment.
```
$ pip install sentence-transformers
```
Navigate to this directory and install Agent Catalog with pip:
```
$ cd agent-catalog

$ # Install the agentc package.
$ pip install libs/agentc
```
If you are interested in developing with LangChain or LangGraph, install the helper agentc_langchain package and/or agentc_langgraph package with the command(s) below:
```
$ pip install libs/agentc_integrations/langchain
$ pip install libs/agentc_integrations/langgraph
```
Similarly, for LlamaIndex Developers:
```
$ pip install libs/agentc_integrations/llamaindex
```