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com.microsoft.semantickernel.aiservices.openai.chatcompletion.OpenAIChatCompletion Maven / Gradle / Ivy
// Copyright (c) Microsoft. All rights reserved.
package com.microsoft.semantickernel.aiservices.openai.chatcompletion;
import com.azure.ai.openai.OpenAIAsyncClient;
import com.azure.ai.openai.models.ChatChoice;
import com.azure.ai.openai.models.ChatCompletions;
import com.azure.ai.openai.models.ChatCompletionsFunctionToolCall;
import com.azure.ai.openai.models.ChatCompletionsFunctionToolDefinition;
import com.azure.ai.openai.models.ChatCompletionsJsonResponseFormat;
import com.azure.ai.openai.models.ChatCompletionsOptions;
import com.azure.ai.openai.models.ChatCompletionsTextResponseFormat;
import com.azure.ai.openai.models.ChatCompletionsToolCall;
import com.azure.ai.openai.models.ChatCompletionsToolDefinition;
import com.azure.ai.openai.models.ChatRequestAssistantMessage;
import com.azure.ai.openai.models.ChatRequestMessage;
import com.azure.ai.openai.models.ChatRequestSystemMessage;
import com.azure.ai.openai.models.ChatRequestToolMessage;
import com.azure.ai.openai.models.ChatRequestUserMessage;
import com.azure.ai.openai.models.ChatResponseMessage;
import com.azure.ai.openai.models.FunctionCall;
import com.azure.core.util.BinaryData;
import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.JsonNode;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.fasterxml.jackson.databind.node.ContainerNode;
import com.microsoft.semantickernel.Kernel;
import com.microsoft.semantickernel.aiservices.openai.OpenAiService;
import com.microsoft.semantickernel.aiservices.openai.implementation.OpenAIRequestSettings;
import com.microsoft.semantickernel.contextvariables.ContextVariable;
import com.microsoft.semantickernel.contextvariables.ContextVariableTypes;
import com.microsoft.semantickernel.exceptions.AIException;
import com.microsoft.semantickernel.exceptions.AIException.ErrorCodes;
import com.microsoft.semantickernel.exceptions.SKException;
import com.microsoft.semantickernel.hooks.KernelHookEvent;
import com.microsoft.semantickernel.hooks.KernelHooks;
import com.microsoft.semantickernel.hooks.PostChatCompletionEvent;
import com.microsoft.semantickernel.hooks.PreChatCompletionEvent;
import com.microsoft.semantickernel.hooks.PreToolCallEvent;
import com.microsoft.semantickernel.implementation.CollectionUtil;
import com.microsoft.semantickernel.orchestration.FunctionResult;
import com.microsoft.semantickernel.orchestration.FunctionResultMetadata;
import com.microsoft.semantickernel.orchestration.InvocationContext;
import com.microsoft.semantickernel.orchestration.InvocationReturnMode;
import com.microsoft.semantickernel.orchestration.PromptExecutionSettings;
import com.microsoft.semantickernel.orchestration.ToolCallBehavior;
import com.microsoft.semantickernel.semanticfunctions.KernelFunction;
import com.microsoft.semantickernel.semanticfunctions.KernelFunctionArguments;
import com.microsoft.semantickernel.services.chatcompletion.AuthorRole;
import com.microsoft.semantickernel.services.chatcompletion.ChatCompletionService;
import com.microsoft.semantickernel.services.chatcompletion.ChatHistory;
import com.microsoft.semantickernel.services.chatcompletion.ChatMessageContent;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collections;
import java.util.List;
import java.util.Map;
import java.util.Objects;
import java.util.stream.Collectors;
import java.util.stream.Stream;
import javax.annotation.CheckReturnValue;
import javax.annotation.Nullable;
import org.apache.commons.text.StringEscapeUtils;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import reactor.core.publisher.Flux;
import reactor.core.publisher.Mono;
/**
* OpenAI chat completion service.
*/
public class OpenAIChatCompletion extends OpenAiService implements ChatCompletionService {
private static final Logger LOGGER = LoggerFactory.getLogger(OpenAIChatCompletion.class);
protected OpenAIChatCompletion(
OpenAIAsyncClient client,
String deploymentName,
String modelId,
@Nullable String serviceId) {
super(client, serviceId, modelId, deploymentName);
}
/**
* Create a new instance of {@link OpenAIChatCompletion.Builder}.
*
* @return a new instance of {@link OpenAIChatCompletion.Builder}
*/
public static OpenAIChatCompletion.Builder builder() {
return new OpenAIChatCompletion.Builder();
}
@Override
public Mono>> getChatMessageContentsAsync(
ChatHistory chatHistory,
@Nullable Kernel kernel,
@Nullable InvocationContext invocationContext) {
List chatRequestMessages = getChatRequestMessages(chatHistory);
ChatMessages messages = new ChatMessages(chatRequestMessages);
return internalChatMessageContentsAsync(
messages,
kernel,
invocationContext)
.map(history -> {
ChatHistory chatHistoryResult;
if (invocationContext != null
&& invocationContext.returnMode() == InvocationReturnMode.FULL_HISTORY) {
chatHistoryResult = new ChatHistory(chatHistory.getMessages());
} else {
chatHistoryResult = new ChatHistory();
}
chatHistoryResult.addAll(
new ChatHistory(toOpenAIChatMessageContent(history.newMessages)));
chatHistoryResult.addAll(new ChatHistory(history.newChatMessageContent));
if (invocationContext != null
&& invocationContext.returnMode() == InvocationReturnMode.LAST_MESSAGE_ONLY) {
chatHistoryResult = new ChatHistory(
Collections.singletonList(
CollectionUtil.getLastOrNull(chatHistory.getMessages())));
}
return chatHistoryResult.getMessages();
});
}
@Override
public Mono>> getChatMessageContentsAsync(
String prompt,
@Nullable Kernel kernel,
@Nullable InvocationContext invocationContext) {
ParsedPrompt parsedPrompt = XMLPromptParser.parse(prompt);
ChatMessages messages = new ChatMessages(parsedPrompt.getChatRequestMessages());
return internalChatMessageContentsAsync(
messages,
kernel,
invocationContext)
.map(m -> {
ChatHistory result = new ChatHistory(toOpenAIChatMessageContent(m.allMessages));
result.addAll(new ChatHistory(m.newChatMessageContent));
if (invocationContext != null
&& invocationContext.returnMode() == InvocationReturnMode.LAST_MESSAGE_ONLY) {
result = new ChatHistory(
Collections.singletonList(
CollectionUtil.getLastOrNull(result.getMessages())));
}
return result.getMessages();
});
}
// Holds messages temporarily as we build up our result
private static class ChatMessages {
private final List newMessages;
private final List allMessages;
private final List newChatMessageContent;
public ChatMessages(List allMessages) {
this.allMessages = Collections.unmodifiableList(allMessages);
this.newMessages = Collections.unmodifiableList(new ArrayList<>());
this.newChatMessageContent = Collections.unmodifiableList(new ArrayList<>());
}
private ChatMessages(
List allMessages,
List newMessages,
List newChatMessageContent) {
this.allMessages = Collections.unmodifiableList(allMessages);
this.newMessages = Collections.unmodifiableList(newMessages);
this.newChatMessageContent = Collections.unmodifiableList(newChatMessageContent);
}
@CheckReturnValue
public ChatMessages addAll(List requestMessage) {
List tmpAllMessages = new ArrayList<>(allMessages);
List tmpNewMessages = new ArrayList<>(newMessages);
tmpAllMessages.addAll(requestMessage);
tmpNewMessages.addAll(requestMessage);
return new ChatMessages(
tmpAllMessages,
tmpNewMessages,
newChatMessageContent);
}
@CheckReturnValue
public ChatMessages add(ChatRequestMessage requestMessage) {
return addAll(Arrays.asList(requestMessage));
}
@CheckReturnValue
public ChatMessages addChatMessage(List chatMessageContent) {
ArrayList tmpChatMessageContent = new ArrayList<>(
newChatMessageContent);
tmpChatMessageContent.addAll(chatMessageContent);
return new ChatMessages(
allMessages,
newMessages,
tmpChatMessageContent);
}
}
private Mono internalChatMessageContentsAsync(
ChatMessages messages,
@Nullable Kernel kernel,
@Nullable InvocationContext invocationContext) {
List functions = new ArrayList<>();
if (kernel != null) {
kernel.getPlugins()
.forEach(plugin -> plugin.getFunctions().forEach((name, function) -> functions
.add(OpenAIFunction.build(function.getMetadata(), plugin.getName()))));
}
// Create copy to avoid reactor exceptions when updating request messages internally
return internalChatMessageContentsAsync(
messages,
kernel,
functions,
invocationContext,
Math.min(MAXIMUM_INFLIGHT_AUTO_INVOKES,
invocationContext != null && invocationContext.getToolCallBehavior() != null
? invocationContext.getToolCallBehavior().getMaximumAutoInvokeAttempts()
: 0));
}
private Mono internalChatMessageContentsAsync(
ChatMessages messages,
@Nullable Kernel kernel,
List functions,
@Nullable InvocationContext invocationContext,
int autoInvokeAttempts) {
ChatCompletionsOptions options = executeHook(
invocationContext,
new PreChatCompletionEvent(
getCompletionsOptions(
this,
messages.allMessages,
functions,
invocationContext)))
.getOptions();
return getClient()
.getChatCompletionsWithResponse(getDeploymentName(), options,
OpenAIRequestSettings.getRequestOptions())
.flatMap(completionsResult -> {
if (completionsResult.getStatusCode() >= 400) {
return Mono.error(new AIException(ErrorCodes.SERVICE_ERROR,
"Request failed: " + completionsResult.getStatusCode()));
}
return Mono.just(completionsResult.getValue());
})
.flatMap(completions -> {
List responseMessages = completions
.getChoices()
.stream()
.map(ChatChoice::getMessage)
.filter(Objects::nonNull)
.collect(Collectors.toList());
// execute post chat completion hook
executeHook(invocationContext, new PostChatCompletionEvent(completions));
// Just return the result:
// If we don't want to attempt to invoke any functions
// Or if we are auto-invoking, but we somehow end up with other than 1 choice even though only 1 was requested
if (autoInvokeAttempts == 0 || responseMessages.size() != 1) {
return getChatMessageContentsAsync(completions)
.flatMap(m -> {
return Mono.just(messages.addChatMessage(m));
});
}
// Or if there are no tool calls to be done
ChatResponseMessage response = responseMessages.get(0);
List toolCalls = response.getToolCalls();
if (toolCalls == null || toolCalls.isEmpty()) {
return getChatMessageContentsAsync(completions)
.flatMap(m -> {
return Mono.just(messages.addChatMessage(m));
});
}
ChatRequestAssistantMessage requestMessage = new ChatRequestAssistantMessage(
response.getContent());
requestMessage.setToolCalls(toolCalls);
// Add the original assistant message to the chat options; this is required for the service
// to understand the tool call responses
ChatMessages messagesWithToolCall = messages.add(requestMessage);
return Flux
.fromIterable(toolCalls)
.reduce(
Mono.just(messagesWithToolCall),
(requestMessages, toolCall) -> {
if (toolCall instanceof ChatCompletionsFunctionToolCall) {
return performToolCall(kernel, invocationContext, requestMessages,
toolCall);
}
return requestMessages;
})
.flatMap(it -> it)
.flatMap(msgs -> {
return internalChatMessageContentsAsync(msgs, kernel, functions,
invocationContext, autoInvokeAttempts - 1);
})
.onErrorResume(e -> {
LOGGER.warn("Tool invocation attempt failed: ", e);
// If FunctionInvocationError occurred and there are still attempts left, retry, else exit
if (autoInvokeAttempts > 0) {
ChatMessages currentMessages = messages;
if (e instanceof FunctionInvocationError) {
currentMessages = currentMessages.addAll(
((FunctionInvocationError) e).getMessages());
}
return internalChatMessageContentsAsync(
currentMessages,
kernel,
functions,
invocationContext,
autoInvokeAttempts - 1);
} else {
return Mono.error(e);
}
});
});
}
private Mono performToolCall(
@Nullable Kernel kernel,
@Nullable InvocationContext invocationContext,
Mono requestMessages,
ChatCompletionsToolCall toolCall) {
return requestMessages
.flatMap(messages -> {
try {
// OpenAI only supports function tool call at the moment
ChatCompletionsFunctionToolCall functionToolCall = (ChatCompletionsFunctionToolCall) toolCall;
if (kernel == null) {
return Mono.error(new SKException(
"A tool call was requested, but no kernel was provided to the invocation, this is a unsupported configuration"));
}
ContextVariableTypes contextVariableTypes = invocationContext == null
? new ContextVariableTypes()
: invocationContext.getContextVariableTypes();
return invokeFunctionTool(
kernel,
invocationContext,
functionToolCall,
contextVariableTypes)
.map(functionResult -> {
// Add chat request tool message to the chat options
ChatRequestMessage requestToolMessage = new ChatRequestToolMessage(
functionResult.getResult(),
functionToolCall.getId());
return messages.add(requestToolMessage);
})
.switchIfEmpty(Mono.fromSupplier(
() -> {
ChatRequestMessage requestToolMessage = new ChatRequestToolMessage(
"Completed successfully with no return value",
functionToolCall.getId());
return messages.add(requestToolMessage);
}))
.onErrorResume(e -> emitError(toolCall, messages, e));
} catch (Exception e) {
return emitError(toolCall, messages, e);
}
});
}
private Mono emitError(
ChatCompletionsToolCall toolCall,
ChatMessages msgs,
Throwable e) {
msgs = msgs.add(new ChatRequestToolMessage(
"Call failed: " + e.getMessage(),
toolCall.getId()));
return Mono.error(new FunctionInvocationError(e, msgs.allMessages));
}
/**
* Exception to be thrown when a function invocation fails.
*/
private static class FunctionInvocationError extends SKException {
private final List messages;
public FunctionInvocationError(Throwable e, List msgs) {
super(e.getMessage(), e);
this.messages = msgs;
}
public List getMessages() {
return messages;
}
}
@SuppressWarnings("StringSplitter")
private Mono> invokeFunctionTool(
Kernel kernel,
@Nullable InvocationContext invocationContext,
ChatCompletionsFunctionToolCall toolCall,
ContextVariableTypes contextVariableTypes) {
try {
OpenAIFunctionToolCall openAIFunctionToolCall = extractOpenAIFunctionToolCall(toolCall);
String pluginName = openAIFunctionToolCall.getPluginName();
if (pluginName == null || pluginName.isEmpty()) {
return Mono.error(
new SKException("Plugin name is required for function tool call"));
}
KernelFunction function = kernel.getFunction(
pluginName,
openAIFunctionToolCall.getFunctionName());
PreToolCallEvent hookResult = executeHook(invocationContext, new PreToolCallEvent(
openAIFunctionToolCall.getFunctionName(),
openAIFunctionToolCall.getArguments(),
function,
contextVariableTypes));
function = hookResult.getFunction();
KernelFunctionArguments arguments = hookResult.getArguments();
return function
.invokeAsync(kernel)
.withArguments(arguments)
.withResultType(contextVariableTypes.getVariableTypeForClass(String.class));
} catch (JsonProcessingException e) {
return Mono.error(new SKException("Failed to parse tool arguments"));
}
}
private static T executeHook(
@Nullable InvocationContext invocationContext,
T event) {
KernelHooks kernelHooks = invocationContext != null
&& invocationContext.getKernelHooks() != null
? invocationContext.getKernelHooks()
: new KernelHooks();
return kernelHooks.executeHooks(event);
}
@SuppressWarnings("StringSplitter")
private OpenAIFunctionToolCall extractOpenAIFunctionToolCall(
ChatCompletionsFunctionToolCall toolCall) throws JsonProcessingException {
// Split the full name of a function into plugin and function name
String name = toolCall.getFunction().getName();
String[] parts = name.split(OpenAIFunction.getNameSeparator());
String pluginName = parts.length > 1 ? parts[0] : "";
String fnName = parts.length > 1 ? parts[1] : parts[0];
KernelFunctionArguments arguments = KernelFunctionArguments.builder().build();
ObjectMapper mapper = new ObjectMapper();
JsonNode jsonToolCallArguments = mapper.readTree(toolCall.getFunction().getArguments());
jsonToolCallArguments.fields().forEachRemaining(
entry -> {
if (entry.getValue() instanceof ContainerNode) {
arguments.put(entry.getKey(),
ContextVariable.of(entry.getValue().toPrettyString()));
} else {
arguments.put(entry.getKey(),
ContextVariable.of(entry.getValue().asText()));
}
});
return new OpenAIFunctionToolCall(
toolCall.getId(),
pluginName,
fnName,
arguments);
}
private Mono> getChatMessageContentsAsync(
ChatCompletions completions) {
FunctionResultMetadata completionMetadata = FunctionResultMetadata.build(
completions.getId(),
completions.getUsage(),
completions.getCreatedAt());
List responseMessages = completions
.getChoices()
.stream()
.map(ChatChoice::getMessage)
.filter(Objects::nonNull)
.collect(Collectors.toList());
return Flux.fromIterable(responseMessages)
.map(response -> new OpenAIChatMessageContent(
AuthorRole.ASSISTANT,
response.getContent(),
this.getModelId(),
null,
null,
completionMetadata,
formOpenAiToolCalls(response)))
.collectList();
}
private List> toOpenAIChatMessageContent(
List requestMessages) {
return requestMessages
.stream()
.map(message -> {
if (message instanceof ChatRequestUserMessage) {
return new OpenAIChatMessageContent<>(
AuthorRole.USER,
((ChatRequestUserMessage) message).getContent().toString(),
null,
null,
null,
null,
null);
} else if (message instanceof ChatRequestSystemMessage) {
return new OpenAIChatMessageContent<>(
AuthorRole.SYSTEM,
((ChatRequestSystemMessage) message).getContent(),
null,
null,
null,
null,
null);
} else if (message instanceof ChatRequestAssistantMessage) {
List calls = getToolCalls(
((ChatRequestAssistantMessage) message).getToolCalls());
return new OpenAIChatMessageContent<>(
AuthorRole.ASSISTANT,
((ChatRequestAssistantMessage) message).getContent(),
null,
null,
null,
null,
calls);
} else if (message instanceof ChatRequestToolMessage) {
return new OpenAIChatMessageContent<>(
AuthorRole.TOOL,
((ChatRequestToolMessage) message).getContent(),
null,
null,
null,
FunctionResultMetadata.build(
((ChatRequestToolMessage) message).getToolCallId(),
null,
null),
null);
}
throw new SKException(
"Unknown message type: " + message.getClass().getSimpleName());
})
.collect(Collectors.toList());
}
@Nullable
private List getToolCalls(
@Nullable List toolCalls) {
if (toolCalls == null || toolCalls.isEmpty()) {
return null;
}
return toolCalls
.stream()
.map(call -> {
if (call instanceof ChatCompletionsFunctionToolCall) {
try {
return extractOpenAIFunctionToolCall(
(ChatCompletionsFunctionToolCall) call);
} catch (JsonProcessingException e) {
throw new SKException("Failed to parse tool arguments", e);
}
} else {
return new OpenAIFunctionToolCall(
call.getId(),
null,
null,
null);
}
})
.collect(Collectors.toList());
}
@Nullable
private List formOpenAiToolCalls(
ChatResponseMessage response) {
if (response.getToolCalls() == null || response.getToolCalls().isEmpty()) {
return null;
}
return response
.getToolCalls()
.stream()
.map(call -> {
if (call instanceof ChatCompletionsFunctionToolCall) {
try {
return extractOpenAIFunctionToolCall(
(ChatCompletionsFunctionToolCall) call);
} catch (JsonProcessingException e) {
throw new SKException("Failed to parse tool arguments", e);
}
} else {
return null;
}
})
.filter(Objects::nonNull)
.collect(Collectors.toList());
}
private static ChatCompletionsOptions getCompletionsOptions(
ChatCompletionService chatCompletionService,
List chatRequestMessages,
@Nullable List functions,
@Nullable InvocationContext invocationContext) {
chatRequestMessages = chatRequestMessages
.stream()
.map(XMLPromptParser::unescapeRequest)
.collect(Collectors.toList());
ChatCompletionsOptions options = new ChatCompletionsOptions(chatRequestMessages)
.setModel(chatCompletionService.getModelId());
if (invocationContext != null && invocationContext.getToolCallBehavior() != null) {
configureToolCallBehaviorOptions(
options,
invocationContext.getToolCallBehavior(),
functions,
chatRequestMessages);
}
PromptExecutionSettings promptExecutionSettings = invocationContext != null
? invocationContext.getPromptExecutionSettings()
: null;
if (promptExecutionSettings == null) {
return options;
}
if (promptExecutionSettings.getResultsPerPrompt() < 1
|| promptExecutionSettings.getResultsPerPrompt() > MAX_RESULTS_PER_PROMPT) {
throw new AIException(AIException.ErrorCodes.INVALID_REQUEST,
String.format("Results per prompt must be in range between 1 and %d, inclusive.",
MAX_RESULTS_PER_PROMPT));
}
Map logit = null;
if (promptExecutionSettings.getTokenSelectionBiases() != null) {
logit = promptExecutionSettings
.getTokenSelectionBiases()
.entrySet()
.stream()
.collect(Collectors.toMap(
entry -> entry.getKey().toString(),
Map.Entry::getValue));
}
options
.setTemperature(promptExecutionSettings.getTemperature())
.setTopP(promptExecutionSettings.getTopP())
.setPresencePenalty(promptExecutionSettings.getPresencePenalty())
.setFrequencyPenalty(promptExecutionSettings.getFrequencyPenalty())
.setPresencePenalty(promptExecutionSettings.getPresencePenalty())
.setMaxTokens(promptExecutionSettings.getMaxTokens())
.setN(promptExecutionSettings.getResultsPerPrompt())
// Azure OpenAI WithData API does not allow to send empty array of stop sequences
// Gives back "Validation error at #/stop/str: Input should be a valid string\nValidation error at #/stop/list[str]: List should have at least 1 item after validation, not 0"
.setStop(promptExecutionSettings.getStopSequences() == null
|| promptExecutionSettings.getStopSequences().isEmpty() ? null
: promptExecutionSettings.getStopSequences())
.setUser(promptExecutionSettings.getUser())
.setLogitBias(logit);
if (promptExecutionSettings.getResponseFormat() != null) {
switch (promptExecutionSettings.getResponseFormat()) {
case JSON_OBJECT:
options.setResponseFormat(new ChatCompletionsJsonResponseFormat());
break;
case TEXT:
options.setResponseFormat(new ChatCompletionsTextResponseFormat());
break;
default:
throw new SKException(
"Unknown response format: " + promptExecutionSettings.getResponseFormat());
}
}
return options;
}
private static void configureToolCallBehaviorOptions(
ChatCompletionsOptions options,
@Nullable ToolCallBehavior toolCallBehavior,
@Nullable List functions,
List chatRequestMessages) {
if (toolCallBehavior == null) {
return;
}
if (functions == null || functions.isEmpty()) {
return;
}
// If a specific function is required to be called
if (toolCallBehavior instanceof ToolCallBehavior.RequiredKernelFunction) {
KernelFunction toolChoice = ((ToolCallBehavior.RequiredKernelFunction) toolCallBehavior)
.getRequiredFunction();
String toolChoiceName = String.format("%s%s%s",
toolChoice.getPluginName(),
OpenAIFunction.getNameSeparator(),
toolChoice.getName());
// If required tool call has already been called dont ask for it again
boolean hasBeenExecuted = hasToolCallBeenExecuted(chatRequestMessages, toolChoiceName);
if (hasBeenExecuted) {
return;
}
List toolDefinitions = new ArrayList<>();
toolDefinitions.add(new ChatCompletionsFunctionToolDefinition(
OpenAIFunction.toFunctionDefinition(
toolChoice.getMetadata(),
toolChoice.getPluginName())));
options.setTools(toolDefinitions);
try {
String json = String.format(
"{\"type\":\"function\",\"function\":{\"name\":\"%s\"}}", toolChoiceName);
options.setToolChoice(BinaryData.fromObject(new ObjectMapper().readTree(json)));
} catch (JsonProcessingException e) {
throw new RuntimeException(e);
}
return;
}
// If a set of functions are enabled to be called
ToolCallBehavior.AllowedKernelFunctions enabledKernelFunctions = (ToolCallBehavior.AllowedKernelFunctions) toolCallBehavior;
List toolDefinitions = functions.stream()
.filter(function -> {
// check if all kernel functions are enabled
if (enabledKernelFunctions.isAllKernelFunctionsAllowed()) {
return true;
}
// otherwise, check for the specific function
return enabledKernelFunctions.isFunctionAllowed(function.getPluginName(),
function.getName());
})
.map(OpenAIFunction::getFunctionDefinition)
.map(ChatCompletionsFunctionToolDefinition::new)
.collect(Collectors.toList());
if (toolDefinitions.isEmpty()) {
return;
}
options.setTools(toolDefinitions);
options.setToolChoice(BinaryData.fromString("auto"));
}
private static boolean hasToolCallBeenExecuted(List chatRequestMessages,
String toolChoiceName) {
return chatRequestMessages
.stream()
.flatMap(message -> {
// Extract tool calls
if (message instanceof ChatRequestAssistantMessage) {
return ((ChatRequestAssistantMessage) message).getToolCalls().stream();
}
return Stream.empty();
})
.filter(toolCall -> {
// Filter if tool call has correct name
if (toolCall instanceof ChatCompletionsFunctionToolCall) {
return ((ChatCompletionsFunctionToolCall) toolCall).getFunction().getName()
.equals(toolChoiceName);
}
return false;
})
.allMatch(toolcall -> {
String id = toolcall.getId();
// True if tool call id has a response message
return chatRequestMessages
.stream()
.filter(
chatRequestMessage -> chatRequestMessage instanceof ChatRequestToolMessage)
.anyMatch(
chatRequestMessage -> ((ChatRequestToolMessage) chatRequestMessage)
.getToolCallId()
.equals(id));
});
}
private static List getChatRequestMessages(
List messages) {
if (messages == null || messages.isEmpty()) {
return new ArrayList<>();
}
return messages.stream()
.map(OpenAIChatCompletion::getChatRequestMessage)
.collect(Collectors.toList());
}
private static List getChatRequestMessages(ChatHistory chatHistory) {
return getChatRequestMessages(chatHistory.getMessages());
}
private static ChatRequestMessage getChatRequestMessage(
ChatMessageContent message) {
AuthorRole authorRole = message.getAuthorRole();
String content = message.getContent();
switch (authorRole) {
case ASSISTANT:
return formAssistantMessage(message, content);
case SYSTEM:
return new ChatRequestSystemMessage(content);
case USER:
return new ChatRequestUserMessage(content);
case TOOL:
String id = null;
if (message.getMetadata() != null) {
id = message.getMetadata().getId();
}
if (id == null) {
throw new SKException(
"Require to create a tool call message, but not tool call id is available");
}
return new ChatRequestToolMessage(content, id);
default:
LOGGER.debug("Unexpected author role: {}", authorRole);
throw new SKException("Unexpected author role: " + authorRole);
}
}
private static ChatRequestAssistantMessage formAssistantMessage(
ChatMessageContent message,
@Nullable String content) {
// TODO: handle tools other than function calls
ChatRequestAssistantMessage asstMessage = new ChatRequestAssistantMessage(content);
List toolCalls = null;
if (message instanceof OpenAIChatMessageContent) {
toolCalls = ((OpenAIChatMessageContent) message).getToolCall();
}
if (toolCalls != null) {
asstMessage.setToolCalls(
toolCalls.stream()
.map(toolCall -> {
KernelFunctionArguments arguments = toolCall.getArguments();
String args = arguments != null && !arguments.isEmpty()
? arguments.entrySet().stream()
.map(entry -> String.format("\"%s\": \"%s\"",
StringEscapeUtils.escapeJson(entry.getKey()),
StringEscapeUtils.escapeJson(
entry.getValue().toPromptString())))
.collect(Collectors.joining("{", "}", ","))
: "{}";
String prefix = "";
if (toolCall.getPluginName() == null) {
prefix = toolCall.getPluginName() + OpenAIFunction.getNameSeparator();
}
String name = prefix + toolCall.getFunctionName();
FunctionCall fnCall = new FunctionCall(name, args);
return new ChatCompletionsFunctionToolCall(toolCall.getId(),
fnCall);
})
.collect(Collectors.toList()));
}
return asstMessage;
}
static ChatRequestMessage getChatRequestMessage(
AuthorRole authorRole,
String content) {
switch (authorRole) {
case ASSISTANT:
return new ChatRequestAssistantMessage(content);
case SYSTEM:
return new ChatRequestSystemMessage(content);
case USER:
return new ChatRequestUserMessage(content);
case TOOL:
return new ChatRequestToolMessage(content, null);
default:
LOGGER.debug("Unexpected author role: " + authorRole);
throw new SKException("Unexpected author role: " + authorRole);
}
}
/**
* Builder for creating a new instance of {@link OpenAIChatCompletion}.
*/
public static class Builder extends ChatCompletionService.Builder {
@Override
public OpenAIChatCompletion build() {
if (this.client == null) {
throw new AIException(AIException.ErrorCodes.INVALID_REQUEST,
"OpenAI client must be provided");
}
if (this.modelId == null || modelId.isEmpty()) {
throw new AIException(AIException.ErrorCodes.INVALID_REQUEST,
"OpenAI model id must be provided");
}
if (deploymentName == null) {
LOGGER.debug("Deployment name is not provided, using model id as deployment name");
deploymentName = modelId;
}
return new OpenAIChatCompletion(client, deploymentName, modelId, serviceId);
}
}
}
