As the underlying intelligent engine of an agent, an AI large language model (LLM) must be bound to the agent during runtime. The model is responsible for core capabilities, such as natural language understanding, logical reasoning, SQL statement generation, and report generation. Through the Model module, LLMs available for agents to invoke within the platform can be configured and managed in a unified way.
Choose Management Backend > Model, click the Add Model button in the upper right corner, and enter the basic information of the model in the model adding pop-up box.
Item
Description
API Invocation Protocol
Select the API invocation protocol that the model to be added complies with.
Currently, the following two protocols are supported:
OpenAI Compatibility Protocol
Azure Compatibility Protocol
API Key
Enter the API key provided by the model's official provider for identity authentication.
Enter the API URL of the model service.
Model Name
Enter the official model name provided by the model service provider.
You can click Get Model Name to pull the name automatically.
Taking how to add the deepseek-v3 model as an example, the following figure shows the effect.
After setting the above items, click Test Connection to check whether the API connection is normal. After the test is passed, click Save to complete the model adding.
The model list displays all added LLMs and supports the following operations on existing models:
Search: Quickly locate the target model by model name through the top search box.
Test Connection: Hover your cursor over the target model, click ... on the right, and select Test Connection from the drop-down list to check whether the model's API connection is normal. If so, the agent can be invoked normally.
Delete: Hover your cursor over the target model, click ... on the right, and select Delete from the drop-down list to delete this model that is no longer in use.
(1) Disclaimer: FanRuan only provides recommended LLMs and connection methods for reference and takes no liability for any issues with the LLMs themselves.
(2) A model deleted cannot be restored. Check whether the model is referenced by an agent before the deletion.
(3) The API key and endpoint are sensitive information and should be kept properly to avoid leakage.
(4) Ensure that the network environment can access the API URL of the corresponding model. Otherwise, the connection test will fail.
(5) The model name must be exactly the same as the one provided by the service provider. Otherwise, the agent invocation will be abnormal.