This method returns text generated by an LLM based on the provided system and user prompts, as well as any other optional paramaters that have been set.

The request argument for this method should be a dictionary with the following structure:

This method returns a dictionary with the following structure:

Sets a fixed seed for the random number generator, allowing reproducible responses in cases where the same input parameters are used across multiple requests. By setting the same seed value, you can obtain identical results for debugging, testing, or evaluation purposes. The value of Seed should be an integer. Non-integral values will be truncated. Default is 0.

The system prompt provides context to the model about its role, tone, or behavior during the conversation. This parameter can guide the model on how to respond, setting expectations like "You are an assistant" or "Use a formal tone."

Controls the "creativity" or randomness of the model's responses. Values closer to 1 increase randomness, while values closer to 0 make the responses more focused and deterministic. Values outside the accepted range will be clamped to the range of [0.4, 1.0]. Default is 0.7.

Helps the model narrow or expand the range of possible words to sample from while generating the next token. This setting narrows the token choices to only contain words that together make up a certain percentage of total likelihood (for example, 90%). A lower TopP means the model sticks to closer and more predictable choices, while a higher TopP opens the door to more diverse and creative responses. Values outside the accepted range will be clamped to the range of [0.5, 1.0]. Default is 0.9.