com.alibaba.dashscope.aigc.conversation.ConversationParam Maven / Gradle / Ivy
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// Copyright (c) Alibaba, Inc. and its affiliates.
package com.alibaba.dashscope.aigc.conversation;
import static com.alibaba.dashscope.utils.ApiKeywords.*;
import com.alibaba.dashscope.aigc.generation.GenerationParamBase;
import com.alibaba.dashscope.common.Message;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.InputRequiredException;
import com.alibaba.dashscope.utils.JsonUtils;
import com.google.gson.JsonArray;
import com.google.gson.JsonObject;
import com.google.gson.annotations.SerializedName;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import lombok.Builder;
import lombok.Builder.Default;
import lombok.Data;
import lombok.EqualsAndHashCode;
import lombok.Singular;
import lombok.experimental.SuperBuilder;
import lombok.extern.slf4j.Slf4j;
@Slf4j
@EqualsAndHashCode(callSuper = true)
@Data
@SuperBuilder
public class ConversationParam extends GenerationParamBase {
public static class ResultFormat {
public static String TEXT = "text";
public static String MESSAGE = "message";
}
private List messages;
/* @deprecated use maxTokens instead */
@Deprecated private Integer maxLength;
/* A sampling strategy, called nucleus
sampling, where the model considers the results of the
tokens with top_p probability mass. So 0.1 means only
the tokens comprising the top 10% probability mass are
considered */
private Double topP;
/* A sampling strategy, the k largest elements of the
given mass are considered */
private Integer topK;
/* Whether to enable web search(quark).
Currently works best only on the first round of conversation.
Default to False */
@Builder.Default private Boolean enableSearch = false;
/*
* When generating, the seed of the random number is used to control the randomness of the model generation.
* If you use the same seed, each run will generate the same results;
* you can use the same seed when you need to reproduce the model's generated results.
* The seed parameter supports unsigned 64-bit integer types. Default value 1234
*/
private Integer seed;
/** The output format, text or message, default message. */
@SerializedName("result_format")
@Default
private String resultFormat = ResultFormat.TEXT;
/**
* Used to control the degree of randomness and diversity. Specifically, the temperature value
* controls the degree to which the probability distribution of each candidate word is smoothed
* when generating text. A higher temperature value will reduce the peak value of the probability
* distribution, allowing more low-probability words to be selected, and the generated results
* will be more diverse; while a lower temperature value will enhance the peak value of the
* probability distribution, making it easier for high-probability words to be selected, the
* generated results are more deterministic, range(0, 2) for [qwen-turbo,qwen-plus].
*/
private Float temperature;
/**
* Used to control the streaming output mode. If true, the subsequent output will include the
* previously input content by default. Otherwise, the subsequent output will not include the
* previously output content. Default: false eg(false):
*
*
* I
* I like
* I like apple
* true:
* I
* like
* apple
*
*/
@Builder.Default private Boolean incrementalOutput = false;
/*
* Maximum tokens to generate.
*/
private Integer maxTokens;
/*
* repetition penalty
*/
private Float repetitionPenalty;
/*
* stopString and token are mutually exclusive.
*/
@Singular("stopString")
private List stopStrings;
@Singular private List> stopTokens;
@Override
public JsonObject getInput() {
JsonObject jsonObject = new JsonObject();
JsonArray requestMessages = new JsonArray();
if (getMessages() != null && !getMessages().isEmpty()) {
requestMessages.addAll(JsonUtils.toJsonArray(getMessages()));
if (getPrompt() != null) {
Message msg = Message.builder().role(Role.USER.getValue()).content(getPrompt()).build();
requestMessages.add(JsonUtils.toJsonElement(msg));
}
jsonObject.add(MESSAGES, requestMessages);
} else if (getHistory() != null && !getHistory().isEmpty()) {
JsonArray ar = JsonUtils.toJsonElement(getHistory()).getAsJsonArray();
jsonObject.add(HISTORY, ar);
if (getPrompt() != null) {
jsonObject.addProperty(PROMPT, getPrompt());
}
} else {
if (getPrompt() != null) {
jsonObject.addProperty(PROMPT, getPrompt());
}
}
return jsonObject;
}
@Override
public Map getParameters() {
Map params = new HashMap<>();
if (maxLength != null) {
params.put("max_length", maxLength);
}
if (topP != null) {
params.put("top_p", topP);
}
if (topK != null) {
params.put("top_k", topK);
}
if (enableSearch) {
params.put("enable_search", enableSearch);
}
// Server default is text.
if (ResultFormat.MESSAGE.equals(getResultFormat())) {
params.put("result_format", getResultFormat());
}
if (seed != null) {
params.put("seed", seed);
}
if (temperature != null) {
params.put("temperature", temperature);
}
// default false
if (incrementalOutput) {
params.put("incremental_output", incrementalOutput);
}
if (repetitionPenalty != null) {
params.put(REPETITION_PENALTY, repetitionPenalty);
}
if (maxTokens != null) {
params.put(MAX_TOKENS, maxTokens);
}
if (stopStrings != null && !stopStrings.isEmpty()) {
params.put(STOP, stopStrings);
} else if (stopTokens != null && !stopTokens.isEmpty()) {
params.put(STOP, stopTokens);
}
params.putAll(parameters);
return params;
}
@Override
public void validate() throws InputRequiredException {
if (getModel().equals(Conversation.Models.QWEN_PLUG_V1)) {
log.warn(
"Model: {} is deprecated, use: {} instead!", getModel(), Conversation.Models.QWEN_PLUS);
}
if (getModel().equals(Conversation.Models.QWEN_V1)) {
log.warn(
"Model: {} is deprecated, use: {} instead!", getModel(), Conversation.Models.QWEN_TURBO);
}
if (getPrompt() == null
&& (getHistory() == null || getHistory().isEmpty())
&& (getMessages() == null || getMessages().isEmpty())) {
throw new InputRequiredException("history and prompt must not all null");
}
}
}