mirror of
https://github.com/tencentmusic/supersonic.git
synced 2025-12-10 19:51:00 +00:00
(improvement)(common) Fix the issue with querying large models using the GLM interface. (#1226)
This commit is contained in:
lexluo09
@@ -0,0 +1,264 @@
|
||||
package dev.langchain4j.model.openai;
|
||||
|
||||
import dev.ai4j.openai4j.OpenAiClient;
|
||||
import dev.ai4j.openai4j.OpenAiHttpException;
|
||||
import dev.ai4j.openai4j.chat.ChatCompletionRequest;
|
||||
import dev.ai4j.openai4j.chat.ChatCompletionResponse;
|
||||
import dev.langchain4j.agent.tool.ToolSpecification;
|
||||
import dev.langchain4j.data.message.AiMessage;
|
||||
import dev.langchain4j.data.message.ChatMessage;
|
||||
import dev.langchain4j.model.Tokenizer;
|
||||
import dev.langchain4j.model.chat.ChatLanguageModel;
|
||||
import dev.langchain4j.model.chat.TokenCountEstimator;
|
||||
import dev.langchain4j.model.chat.listener.ChatLanguageModelRequest;
|
||||
import dev.langchain4j.model.chat.listener.ChatLanguageModelResponse;
|
||||
import dev.langchain4j.model.listener.ModelListener;
|
||||
import dev.langchain4j.model.openai.spi.OpenAiChatModelBuilderFactory;
|
||||
import dev.langchain4j.model.output.Response;
|
||||
import lombok.Builder;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
|
||||
import java.net.Proxy;
|
||||
import java.time.Duration;
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
|
||||
import static dev.langchain4j.internal.RetryUtils.withRetry;
|
||||
import static dev.langchain4j.internal.Utils.getOrDefault;
|
||||
import static dev.langchain4j.model.openai.InternalOpenAiHelper.DEFAULT_USER_AGENT;
|
||||
import static dev.langchain4j.model.openai.InternalOpenAiHelper.OPENAI_DEMO_API_KEY;
|
||||
import static dev.langchain4j.model.openai.InternalOpenAiHelper.OPENAI_DEMO_URL;
|
||||
import static dev.langchain4j.model.openai.InternalOpenAiHelper.OPENAI_URL;
|
||||
import static dev.langchain4j.model.openai.InternalOpenAiHelper.aiMessageFrom;
|
||||
import static dev.langchain4j.model.openai.InternalOpenAiHelper.createModelListenerRequest;
|
||||
import static dev.langchain4j.model.openai.InternalOpenAiHelper.createModelListenerResponse;
|
||||
import static dev.langchain4j.model.openai.InternalOpenAiHelper.finishReasonFrom;
|
||||
import static dev.langchain4j.model.openai.InternalOpenAiHelper.toOpenAiMessages;
|
||||
import static dev.langchain4j.model.openai.InternalOpenAiHelper.toTools;
|
||||
import static dev.langchain4j.model.openai.InternalOpenAiHelper.tokenUsageFrom;
|
||||
import static dev.langchain4j.model.openai.OpenAiModelName.GPT_3_5_TURBO;
|
||||
import static dev.langchain4j.spi.ServiceHelper.loadFactories;
|
||||
import static java.time.Duration.ofSeconds;
|
||||
import static java.util.Collections.emptyList;
|
||||
import static java.util.Collections.singletonList;
|
||||
|
||||
/**
|
||||
* Represents an OpenAI language model with a chat completion interface, such as gpt-3.5-turbo and gpt-4.
|
||||
* You can find description of parameters <a href="https://platform.openai.com/docs/api-reference/chat/create">here</a>.
|
||||
*/
|
||||
@Slf4j
|
||||
public class OpenAiChatModel implements ChatLanguageModel, TokenCountEstimator {
|
||||
|
||||
public static final String ZHIPU = "bigmodel";
|
||||
private final OpenAiClient client;
|
||||
private final String baseUrl;
|
||||
private final String modelName;
|
||||
private final Double temperature;
|
||||
private final Double topP;
|
||||
private final List<String> stop;
|
||||
private final Integer maxTokens;
|
||||
private final Double presencePenalty;
|
||||
private final Double frequencyPenalty;
|
||||
private final Map<String, Integer> logitBias;
|
||||
private final String responseFormat;
|
||||
private final Integer seed;
|
||||
private final String user;
|
||||
private final Integer maxRetries;
|
||||
private final Tokenizer tokenizer;
|
||||
|
||||
private final List<ModelListener<ChatLanguageModelRequest, ChatLanguageModelResponse>> listeners;
|
||||
|
||||
@Builder
|
||||
public OpenAiChatModel(String baseUrl,
|
||||
String apiKey,
|
||||
String organizationId,
|
||||
String modelName,
|
||||
Double temperature,
|
||||
Double topP,
|
||||
List<String> stop,
|
||||
Integer maxTokens,
|
||||
Double presencePenalty,
|
||||
Double frequencyPenalty,
|
||||
Map<String, Integer> logitBias,
|
||||
String responseFormat,
|
||||
Integer seed,
|
||||
String user,
|
||||
Duration timeout,
|
||||
Integer maxRetries,
|
||||
Proxy proxy,
|
||||
Boolean logRequests,
|
||||
Boolean logResponses,
|
||||
Tokenizer tokenizer,
|
||||
Map<String, String> customHeaders,
|
||||
List<ModelListener<ChatLanguageModelRequest, ChatLanguageModelResponse>> listeners) {
|
||||
|
||||
baseUrl = getOrDefault(baseUrl, OPENAI_URL);
|
||||
if (OPENAI_DEMO_API_KEY.equals(apiKey)) {
|
||||
baseUrl = OPENAI_DEMO_URL;
|
||||
}
|
||||
this.baseUrl = baseUrl;
|
||||
|
||||
timeout = getOrDefault(timeout, ofSeconds(60));
|
||||
|
||||
this.client = OpenAiClient.builder()
|
||||
.openAiApiKey(apiKey)
|
||||
.baseUrl(baseUrl)
|
||||
.organizationId(organizationId)
|
||||
.callTimeout(timeout)
|
||||
.connectTimeout(timeout)
|
||||
.readTimeout(timeout)
|
||||
.writeTimeout(timeout)
|
||||
.proxy(proxy)
|
||||
.logRequests(logRequests)
|
||||
.logResponses(logResponses)
|
||||
.userAgent(DEFAULT_USER_AGENT)
|
||||
.customHeaders(customHeaders)
|
||||
.build();
|
||||
this.modelName = getOrDefault(modelName, GPT_3_5_TURBO);
|
||||
this.temperature = getOrDefault(temperature, 0.7);
|
||||
this.topP = topP;
|
||||
this.stop = stop;
|
||||
this.maxTokens = maxTokens;
|
||||
this.presencePenalty = presencePenalty;
|
||||
this.frequencyPenalty = frequencyPenalty;
|
||||
this.logitBias = logitBias;
|
||||
this.responseFormat = responseFormat;
|
||||
this.seed = seed;
|
||||
this.user = user;
|
||||
this.maxRetries = getOrDefault(maxRetries, 3);
|
||||
this.tokenizer = getOrDefault(tokenizer, OpenAiTokenizer::new);
|
||||
this.listeners = listeners == null ? emptyList() : new ArrayList<>(listeners);
|
||||
}
|
||||
|
||||
public String modelName() {
|
||||
return modelName;
|
||||
}
|
||||
|
||||
@Override
|
||||
public Response<AiMessage> generate(List<ChatMessage> messages) {
|
||||
return generate(messages, null, null);
|
||||
}
|
||||
|
||||
@Override
|
||||
public Response<AiMessage> generate(List<ChatMessage> messages, List<ToolSpecification> toolSpecifications) {
|
||||
return generate(messages, toolSpecifications, null);
|
||||
}
|
||||
|
||||
@Override
|
||||
public Response<AiMessage> generate(List<ChatMessage> messages, ToolSpecification toolSpecification) {
|
||||
return generate(messages, singletonList(toolSpecification), toolSpecification);
|
||||
}
|
||||
|
||||
private Response<AiMessage> generate(List<ChatMessage> messages,
|
||||
List<ToolSpecification> toolSpecifications,
|
||||
ToolSpecification toolThatMustBeExecuted
|
||||
) {
|
||||
ChatCompletionRequest.Builder requestBuilder = ChatCompletionRequest.builder()
|
||||
.model(modelName)
|
||||
.messages(toOpenAiMessages(messages))
|
||||
.topP(topP)
|
||||
.stop(stop)
|
||||
.maxTokens(maxTokens)
|
||||
.presencePenalty(presencePenalty)
|
||||
.frequencyPenalty(frequencyPenalty)
|
||||
.logitBias(logitBias)
|
||||
.responseFormat(responseFormat)
|
||||
.seed(seed)
|
||||
.user(user);
|
||||
if (!(baseUrl.contains(ZHIPU))) {
|
||||
requestBuilder.temperature(temperature);
|
||||
}
|
||||
|
||||
if (toolSpecifications != null && !toolSpecifications.isEmpty()) {
|
||||
requestBuilder.tools(toTools(toolSpecifications));
|
||||
}
|
||||
if (toolThatMustBeExecuted != null) {
|
||||
requestBuilder.toolChoice(toolThatMustBeExecuted.name());
|
||||
}
|
||||
|
||||
ChatCompletionRequest request = requestBuilder.build();
|
||||
|
||||
ChatLanguageModelRequest modelListenerRequest =
|
||||
createModelListenerRequest(request, messages, toolSpecifications);
|
||||
listeners.forEach(listener -> {
|
||||
try {
|
||||
listener.onRequest(modelListenerRequest);
|
||||
} catch (Exception e) {
|
||||
log.warn("Exception while calling model listener", e);
|
||||
}
|
||||
});
|
||||
|
||||
try {
|
||||
ChatCompletionResponse chatCompletionResponse =
|
||||
withRetry(() -> client.chatCompletion(request).execute(), maxRetries);
|
||||
|
||||
Response<AiMessage> response = Response.from(
|
||||
aiMessageFrom(chatCompletionResponse),
|
||||
tokenUsageFrom(chatCompletionResponse.usage()),
|
||||
finishReasonFrom(chatCompletionResponse.choices().get(0).finishReason())
|
||||
);
|
||||
|
||||
ChatLanguageModelResponse modelListenerResponse = createModelListenerResponse(
|
||||
chatCompletionResponse.id(),
|
||||
chatCompletionResponse.model(),
|
||||
response
|
||||
);
|
||||
listeners.forEach(listener -> {
|
||||
try {
|
||||
listener.onResponse(modelListenerResponse, modelListenerRequest);
|
||||
} catch (Exception e) {
|
||||
log.warn("Exception while calling model listener", e);
|
||||
}
|
||||
});
|
||||
|
||||
return response;
|
||||
} catch (RuntimeException e) {
|
||||
|
||||
Throwable error;
|
||||
if (e.getCause() instanceof OpenAiHttpException) {
|
||||
error = e.getCause();
|
||||
} else {
|
||||
error = e;
|
||||
}
|
||||
|
||||
listeners.forEach(listener -> {
|
||||
try {
|
||||
listener.onError(error, null, modelListenerRequest);
|
||||
} catch (Exception e2) {
|
||||
log.warn("Exception while calling model listener", e2);
|
||||
}
|
||||
});
|
||||
throw e;
|
||||
}
|
||||
}
|
||||
|
||||
@Override
|
||||
public int estimateTokenCount(List<ChatMessage> messages) {
|
||||
return tokenizer.estimateTokenCountInMessages(messages);
|
||||
}
|
||||
|
||||
public static OpenAiChatModel withApiKey(String apiKey) {
|
||||
return builder().apiKey(apiKey).build();
|
||||
}
|
||||
|
||||
public static OpenAiChatModelBuilder builder() {
|
||||
for (OpenAiChatModelBuilderFactory factory : loadFactories(OpenAiChatModelBuilderFactory.class)) {
|
||||
return factory.get();
|
||||
}
|
||||
return new OpenAiChatModelBuilder();
|
||||
}
|
||||
|
||||
public static class OpenAiChatModelBuilder {
|
||||
|
||||
public OpenAiChatModelBuilder() {
|
||||
// This is public so it can be extended
|
||||
// By default with Lombok it becomes package private
|
||||
}
|
||||
|
||||
public OpenAiChatModelBuilder modelName(String modelName) {
|
||||
this.modelName = modelName;
|
||||
return this;
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,114 @@
|
||||
package dev.langchain4j.model.zhipu;
|
||||
|
||||
import dev.ai4j.openai4j.chat.ChatCompletionModel;
|
||||
import dev.langchain4j.agent.tool.ToolSpecification;
|
||||
import dev.langchain4j.data.message.AiMessage;
|
||||
import dev.langchain4j.data.message.ChatMessage;
|
||||
import dev.langchain4j.model.chat.ChatLanguageModel;
|
||||
import dev.langchain4j.model.output.Response;
|
||||
import dev.langchain4j.model.zhipu.chat.ChatCompletionRequest;
|
||||
import dev.langchain4j.model.zhipu.chat.ChatCompletionResponse;
|
||||
import dev.langchain4j.model.zhipu.spi.ZhipuAiChatModelBuilderFactory;
|
||||
import lombok.Builder;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
import static dev.langchain4j.internal.RetryUtils.withRetry;
|
||||
import static dev.langchain4j.internal.Utils.getOrDefault;
|
||||
import static dev.langchain4j.internal.Utils.isNullOrEmpty;
|
||||
import static dev.langchain4j.internal.ValidationUtils.ensureNotEmpty;
|
||||
import static dev.langchain4j.model.zhipu.DefaultZhipuAiHelper.aiMessageFrom;
|
||||
import static dev.langchain4j.model.zhipu.DefaultZhipuAiHelper.finishReasonFrom;
|
||||
import static dev.langchain4j.model.zhipu.DefaultZhipuAiHelper.toTools;
|
||||
import static dev.langchain4j.model.zhipu.DefaultZhipuAiHelper.toZhipuAiMessages;
|
||||
import static dev.langchain4j.model.zhipu.DefaultZhipuAiHelper.tokenUsageFrom;
|
||||
import static dev.langchain4j.model.zhipu.chat.ToolChoiceMode.AUTO;
|
||||
import static dev.langchain4j.spi.ServiceHelper.loadFactories;
|
||||
import static java.util.Collections.singletonList;
|
||||
|
||||
/**
|
||||
* Represents an ZhipuAi language model with a chat completion interface, such as glm-3-turbo and glm-4.
|
||||
* You can find description of parameters <a href="https://open.bigmodel.cn/dev/api">here</a>.
|
||||
*/
|
||||
public class ZhipuAiChatModel implements ChatLanguageModel {
|
||||
|
||||
private final String baseUrl;
|
||||
private final Double temperature;
|
||||
private final Double topP;
|
||||
private final String model;
|
||||
private final Integer maxRetries;
|
||||
private final Integer maxToken;
|
||||
private final ZhipuAiClient client;
|
||||
|
||||
@Builder
|
||||
public ZhipuAiChatModel(
|
||||
String baseUrl,
|
||||
String apiKey,
|
||||
Double temperature,
|
||||
Double topP,
|
||||
String model,
|
||||
Integer maxRetries,
|
||||
Integer maxToken,
|
||||
Boolean logRequests,
|
||||
Boolean logResponses
|
||||
) {
|
||||
this.baseUrl = getOrDefault(baseUrl, "https://open.bigmodel.cn/");
|
||||
this.temperature = getOrDefault(temperature, 0.7);
|
||||
this.topP = topP;
|
||||
this.model = getOrDefault(model, ChatCompletionModel.GPT_4.toString());
|
||||
this.maxRetries = getOrDefault(maxRetries, 3);
|
||||
this.maxToken = getOrDefault(maxToken, 512);
|
||||
this.client = ZhipuAiClient.builder()
|
||||
.baseUrl(this.baseUrl)
|
||||
.apiKey(apiKey)
|
||||
.logRequests(getOrDefault(logRequests, false))
|
||||
.logResponses(getOrDefault(logResponses, false))
|
||||
.build();
|
||||
}
|
||||
|
||||
public static ZhipuAiChatModelBuilder builder() {
|
||||
for (ZhipuAiChatModelBuilderFactory factories : loadFactories(ZhipuAiChatModelBuilderFactory.class)) {
|
||||
return factories.get();
|
||||
}
|
||||
return new ZhipuAiChatModelBuilder();
|
||||
}
|
||||
|
||||
@Override
|
||||
public Response<AiMessage> generate(List<ChatMessage> messages) {
|
||||
return generate(messages, (ToolSpecification) null);
|
||||
}
|
||||
|
||||
@Override
|
||||
public Response<AiMessage> generate(List<ChatMessage> messages, List<ToolSpecification> toolSpecifications) {
|
||||
ensureNotEmpty(messages, "messages");
|
||||
|
||||
ChatCompletionRequest.Builder requestBuilder = ChatCompletionRequest.builder()
|
||||
.model(this.model)
|
||||
.maxTokens(maxToken)
|
||||
.stream(false)
|
||||
.topP(topP)
|
||||
.toolChoice(AUTO)
|
||||
.messages(toZhipuAiMessages(messages));
|
||||
|
||||
if (!isNullOrEmpty(toolSpecifications)) {
|
||||
requestBuilder.tools(toTools(toolSpecifications));
|
||||
}
|
||||
|
||||
ChatCompletionResponse response = withRetry(() -> client.chatCompletion(requestBuilder.build()), maxRetries);
|
||||
return Response.from(
|
||||
aiMessageFrom(response),
|
||||
tokenUsageFrom(response.getUsage()),
|
||||
finishReasonFrom(response.getChoices().get(0).getFinishReason())
|
||||
);
|
||||
}
|
||||
|
||||
@Override
|
||||
public Response<AiMessage> generate(List<ChatMessage> messages, ToolSpecification toolSpecification) {
|
||||
return generate(messages, toolSpecification != null ? singletonList(toolSpecification) : null);
|
||||
}
|
||||
|
||||
public static class ZhipuAiChatModelBuilder {
|
||||
public ZhipuAiChatModelBuilder() {
|
||||
}
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user