Model connection
The Model connection dropdown lists all connections registered in Settings → Model Connections. Select the one this agent should use — credentials are inherited from the connection; you do not re-enter API keys here. Each option shows the connection name, type, and model ID (e.g., GPT-4o Production — OpenAI withgpt-4o below).
Different agents in the same workspace can use different connections. Common patterns:
- Use a powerful model (e.g., Claude Sonnet, GPT-4o) for complex reasoning agents
- Use a fast, cheap model (e.g., Groq Llama, Claude Haiku) for simple classification or routing agents
- Use a custom endpoint for local development and testing
Model parameters
Model parameters are optional key-value pairs passed to the LLM at inference time. They let you tune the model’s behavior per-agent without changing the connection itself. Common parameters:| Parameter | Type | Description |
|---|---|---|
temperature | float (0.0–2.0) | Creativity vs. determinism. 0 = highly deterministic, 1+ = more creative |
max_tokens | integer | Maximum number of tokens in the response |
top_p | float (0.0–1.0) | Nucleus sampling. Alternative to temperature for controlling randomness |
top_k | integer | Limits sampling to the top K most likely tokens |
frequency_penalty | float | Reduces repetition of frequently used words |
presence_penalty | float | Encourages the model to introduce new topics |
Supported parameters vary by connection type. Unsupported parameters are silently ignored by the runtime. Refer to your provider’s API documentation for the full list.
Next steps
With a model connection selected, your agent is ready to run. From here you can optionally add:MCP Tools
Connect external tools and APIs.
Knowledge Base
Add document retrieval for RAG-based answers.