Learn how to use the Call AI Model node to interact with various AI providers and models, with support for structured output.
Parameter | Description | Notes |
---|---|---|
Max Output Tokens | Maximum number of tokens in the model’s response | Higher values allow longer responses but increase costs. Each model has its own maximum limit. |
Temperature | Controls response randomness | Lower values (0.1-0.3): More focused, deterministic responses. Higher values (0.7-1.0): More creative, varied responses. Recommended: 0.1-0.3 for structured output. |
Top P (Nucleus Sampling) | Controls response diversity | Works alongside temperature. Lower values: More focused on likely tokens. Higher values: More diverse vocabulary. Not available in all models. |
Top K | Limits token selection to K most likely tokens | Helps prevent unlikely token selections. Only available in specific models (e.g., Google’s Gemini). |
Frequency Penalty | Reduces repetition based on token frequency | Higher values discourage repeating information. Useful for diverse content. Primarily in OpenAI models. |
Presence Penalty | Penalizes tokens that have appeared at all | Higher values encourage new topics. Helps prevent theme repetition. Primarily in OpenAI models. |
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