Package io.quarkiverse.langchain4j.ollama.runtime.config

Interface EmbeddingModelConfig

public interface EmbeddingModelConfig

Method Summary

Modifier and Type	Method	Description
Optional<Boolean>	logRequests()	Whether embedding model requests should be logged
Optional<Boolean>	logResponses()	Whether embedding model responses should be logged
Integer	numPredict()	Maximum number of tokens to predict when generating text
Optional<List<String>>	stop()	Sets the stop sequences to use.
Double	temperature()	The temperature of the model.
Integer	topK()	Reduces the probability of generating nonsense.
Double	topP()	Works together with top-k.

Method Details

temperature

@WithDefault("0.8")
Double temperature()

The temperature of the model. Increasing the temperature will make the model answer with more variability. A lower temperature will make the model answer more conservatively.

numPredict

@WithDefault("128")
Integer numPredict()

Maximum number of tokens to predict when generating text

stop

Optional<List<String>> stop()

Sets the stop sequences to use. When this pattern is encountered the LLM will stop generating text and return

topP

@WithDefault("0.9")
Double topP()

Works together with top-k. A higher value (e.g., 0.95) will lead to more diverse text, while a lower value (e.g., 0.5) will generate more focused and conservative text

topK

@WithDefault("40")
Integer topK()

Reduces the probability of generating nonsense. A higher value (e.g. 100) will give more diverse answers, while a lower value (e.g. 10) will be more conservative

logRequests

@ConfigDocDefault("false")
@WithDefault("${quarkus.langchain4j.ollama.log-requests}")
Optional<Boolean> logRequests()

Whether embedding model requests should be logged

logResponses

@ConfigDocDefault("false")
@WithDefault("${quarkus.langchain4j.ollama.log-responses}")
Optional<Boolean> logResponses()

Whether embedding model responses should be logged