fi.evolver.ai.spring.skill.mock.LlmSkill Maven / Gradle / Ivy

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package fi.evolver.ai.spring.skill.mock;

import java.util.Objects;

import fi.evolver.ai.spring.Model;
import fi.evolver.ai.spring.chat.ChatApi;
import fi.evolver.ai.spring.chat.ChatResponse;
import fi.evolver.ai.spring.chat.prompt.ChatPrompt;
import fi.evolver.ai.spring.chat.prompt.ChatPrompt.Builder;
import fi.evolver.ai.spring.chat.prompt.Message;
import fi.evolver.ai.spring.json.JsonSpec;
import fi.evolver.ai.spring.skill.Skill;
import fi.evolver.ai.spring.skill.SkillException;
import io.swagger.v3.core.util.Json;

public class LlmSkill extends Skill {
	private final JsonSpec spec;
	private final ChatApi chatApi;
	private final Model model;
	private final String systemPrompt;


	public LlmSkill(Class parameterType, Class resultType, ChatApi chatApi, Model model, String systemPrompt) {
		super(parameterType, resultType);
		this.spec = JsonSpec.of(resultType);
		this.chatApi = Objects.requireNonNull(chatApi);
		this.model = Objects.requireNonNull(model);
		this.systemPrompt = Objects.requireNonNull(systemPrompt);
	}


	@Override
	public R apply(T parameters) throws SkillException {
		Builder builder = ChatPrompt.builder(model)
				.setResponseFormat(spec)
				.add(Message.system(systemPrompt))
				.add(Message.user(Json.pretty(parameters)));

		ChatResponse response = chatApi.send(builder.build());
		String data = response.getTextContent().orElseThrow(() -> new SkillException("No content from LLM"));
		return spec.parse(data);
	}

}