Agent Basics
Model Lifecycle Management
Model Library
The model library provides access to a large number of available models that you can leverage within your projects and Agents. This includes models from the leading providers and also includes Airia’s own fine tuned models.Adding a model
You can search, review costs, and prepare models for use in Airia agents. To add a model to a project:- Select the desired model
- Review the information
- Select Add
- Provide a friendly name to help you remember the model
- Select if you’ll use the Airia Universal Key or if you want to provide your own credentials for the model provider
- Select the scope for model accessibility
- Your model is now ready for use within Agents
Editing a model
You can revisit a model configuration at any time to edit the model display name, credential, prices(if using custom credential) and system prompt. Model configurations can be reviewed from either the Models page within a specific project or the Connected models page.Adding a custom model
You can add models that Airia has not published when you bring your own key. This allows you to leverage existing accounts with model providers for the endpoints supported by Airia. To add a custom model:- From any models page, select Custom Model.
- Provide a display name, and select the model provider.
- Add the model endpoint, and provide the model ID. Find supported provider endpoints below.
- To get the most of Airia’s consumption tracking, input the price charged by the provider for model usage.
- Select the input type, and provide a system prompt [Note: a system prompt is not required]
The model ID field expects the value used for API processing (e.g.,
claude-3-5-sonnet-latest), not the display name.Supported Endpoints
| Provider | Endpoint | Notes |
|---|---|---|
| AI21 | https://api.ai21.com/v1/chat/completions | |
| Alibaba | https://dashscope-intl.aliyuncs.com/compatible-mode/v1/ | Compatible with chat completions only |
| Anthropic | https://api.anthropic.com/v1/messages | |
| AWS Bedrock | https://console.aws.amazon.com | Compatible with conversational models only |
| Azure AI Studio | https://{{Model-Friendly-Name}}.{{Region}}.models.ai.azure.com/chat/completions | Model ID must also be set to the Model-Friendly-Name value |
| Azure (OpenAI) | https://{{deploymentId}}.openai.azure.com/openai/deployments/{{Model-Friendly-Name}}/chat/completions | Model ID must also be set to the Model-Friendly-Name value |
| Cohere | https://api.cohere.com/v1/chat | |
https://generativelanguage.googleapis.com/v1/models | Compatible with chat completions only | |
| Mistral | https://api.mistral.ai/v1/chat/completions | |
| OpenAI | https://api.openai.com/v1/chat/completionshttps://api.openai.com/v1/responses | |
| Ollama | http(s)://{{SomeIpOrName}}:11434/api/chat | |
| Perplexity | https://api.perplexity.ai/chat/completions | |
| Replicate | https://api.replicate.com/v1/models/{{Model-Name}}/predictions | |
| Together AI | https://api.together.xyz/v1/chat/completions | |
| xAI | https://api.x.ai/v1/ | Compatible with chat completions only |
| Custom | https://{{provider-domain}}/v1/ | Specify any OpenAI compliant provider domain. Compatible with chat completions only. |
Customizing an Agent model instance
Models can be configured in how they respond by setting several values in the sidebar when they are added to an Agent. These include- Temperature - to control the creativity of a model. Higher values generate more creative responses, and lower values are more deterministic.
- System Prompt - added to a model during initial configuration. This is for visibility only and cannot be changed within the Agent.
- Prompt - any secondary or additional system instructions to be included for the model request.
- Date and Time Context - provide context around the present day and time when sending messages to the model.
- Always include user input - ensures original user message is provided to model context when not directly connected to the step.