The CheshireCat plugin for regolo.ai represents a powerful integration that allows you to leverage regolo.ai’s artificial intelligence models directly within the CheshireCat environment.
Let’s see how to install and configure it correctly.
Plugin Installation
To start using the plugin, follow these simple steps:
- Make sure CheshireCat is properly installed and configured on your system. If you haven’t done this yet, you can follow the official installation guide available here.
- Access the “Plugins” section of CheshireCat.
- Search for “regolo” in the search field.
- Click the “Install” button to install the plugin.
Plugin Configuration
1. Inserting the API Key
The first thing to do after installation is to authenticate the plugin with your regolo.ai API key:
- Go to the “Plugins” section of CheshireCat
- Click on the Options icon next to the regolo.ai plugin
- Enter your API key in the designated field
- Important: Click the “Save” button to save the settings
2. LLM Model Configuration
To configure the language model you want to use:
- Navigate to the “Settings” section of CheshireCat
- Select “Large Language Model”
- From the dropdown menu, choose “Regolo LLM”
- Select the desired LLM model from those available in the list
3. Embedder Configuration
To configure the embedding model:
- In the same “Settings” section of CheshireCat
- Go to the “Embedder” section
- Select “Regolo embedder models” from the menu
- Choose your preferred embedding model from those available
Useful Tips
If you don’t see some models that are listed on the regolo.ai website, verify that your API key was generated with access to the models you need. If not, you can generate a new key by accessing the regolo.ai dashboard.
Troubleshooting
If you encounter problems using the plugin, here are some solutions:
- Incorrect API key: Re-enter the key in the Options section of the plugin
- Errors after updating the plugin: Try reinstalling the plugin. If problems persist, restart the Docker container (remember to back up your data first)
What You Can Do with CheshireCat and regolo.ai
Once configured, the plugin will allow you to fully leverage CheshireCat’s capabilities, including:
- Advanced conversations via WebSocket and customizable REST API
- Built-in RAG (Retrieval Augmented Generation) with Qdrant
- Extensibility through plugins
- Event callbacks, function calling, and conversational forms
- Intuitive admin panel
- Support for any language model via langchain
- Multi-user functionality with granular permissions
The integration with regolo.ai allows you to select specific models for both conversations and embeddings, thus optimizing performance based on your needs.
Do you have questions about using this plugin? Feel free to comment on this post or join our active Discord community for support!