diff --git a/src/components/settings/slide.tsx b/src/components/settings/slide.tsx
index 9043e6e4..4509f4f6 100644
--- a/src/components/settings/slide.tsx
+++ b/src/components/settings/slide.tsx
@@ -1,6 +1,9 @@
import { useTranslation } from 'react-i18next'
import { useEffect, useState } from 'react'
-import settingsStore from '@/features/stores/settings'
+import settingsStore, {
+ multiModalAIServices,
+ multiModalAIServiceKey,
+} from '@/features/stores/settings'
import menuStore from '@/features/stores/menu'
import slideStore from '@/features/stores/slide'
import { TextButton } from '../textButton'
@@ -66,9 +69,9 @@ const Slide = () => {
{slideMode ? t('StatusOn') : t('StatusOff')}
@@ -92,9 +95,9 @@ const Slide = () => {
))}
- {selectAIService === 'openai' && (
-
- )}
+ {multiModalAIServices.includes(
+ selectAIService as multiModalAIServiceKey
+ ) && }
)}
diff --git a/src/components/settings/slideConvert.tsx b/src/components/settings/slideConvert.tsx
index a53e71eb..a7d58ff4 100644
--- a/src/components/settings/slideConvert.tsx
+++ b/src/components/settings/slideConvert.tsx
@@ -1,6 +1,9 @@
import React, { useState } from 'react'
import { useTranslation } from 'react-i18next'
-import settingsStore from '@/features/stores/settings'
+import settingsStore, {
+ multiModalAIServiceKey,
+ multiModalAIServices,
+} from '@/features/stores/settings'
import { TextButton } from '../textButton'
interface SlideConvertProps {
@@ -11,7 +14,9 @@ const SlideConvert: React.FC = ({ onFolderUpdate }) => {
const { t } = useTranslation()
const [file, setFile] = useState(null)
const [folderName, setFolderName] = useState('')
- const [apiKey] = useState(settingsStore.getState().openAiKey)
+ const aiService = settingsStore.getState()
+ .selectAIService as multiModalAIServiceKey
+
const [model, setModel] = useState('gpt-4o')
const [isLoading, setIsLoading] = useState(false)
const selectLanguage = settingsStore.getState().selectLanguage
@@ -27,6 +32,15 @@ const SlideConvert: React.FC = ({ onFolderUpdate }) => {
const handleFormSubmit = async (event: React.FormEvent) => {
event.preventDefault()
+
+ if (!multiModalAIServices.includes(aiService)) {
+ alert(t('InvalidAIService'))
+ return
+ }
+
+ const apiKeyName = `${aiService}Key` as const
+ const apiKey = settingsStore.getState()[apiKeyName]
+
if (!file || !folderName || !apiKey || !model) {
alert(t('PdfConvertSubmitError'))
return
@@ -37,6 +51,7 @@ const SlideConvert: React.FC = ({ onFolderUpdate }) => {
const formData = new FormData()
formData.append('file', file)
formData.append('folderName', folderName)
+ formData.append('aiService', aiService)
formData.append('apiKey', apiKey)
formData.append('model', model)
formData.append('selectLanguage', selectLanguage)
@@ -101,11 +116,50 @@ const SlideConvert: React.FC = ({ onFolderUpdate }) => {
onChange={(e) => setModel(e.target.value)}
className="text-ellipsis px-16 py-8 w-col-span-4 bg-surface1 hover:bg-surface1-hover rounded-8"
>
-
-
-
-
-
+ {aiService === 'openai' && (
+ <>
+
+
+
+
+
+
+ )}
+ {aiService === 'anthropic' && (
+ <>
+
+
+
+
+
+ )}
+ {aiService === 'google' && (
+ <>
+
+
+
+
+
+
+ )}
diff --git a/src/components/settings/youtube.tsx b/src/components/settings/youtube.tsx
index 2c130528..87b817f7 100644
--- a/src/components/settings/youtube.tsx
+++ b/src/components/settings/youtube.tsx
@@ -4,6 +4,7 @@ import homeStore from '@/features/stores/home'
import menuStore from '@/features/stores/menu'
import settingsStore from '@/features/stores/settings'
import { TextButton } from '../textButton'
+import { multiModalAIServices } from '@/features/stores/settings'
const YouTube = () => {
const youtubeApiKey = settingsStore((s) => s.youtubeApiKey)
@@ -98,8 +99,7 @@ const YouTube = () => {
})
}
disabled={
- (selectAIService !== 'openai' &&
- selectAIService !== 'anthropic') ||
+ !multiModalAIServices.includes(selectAIService as any) ||
slideMode ||
webSocketMode
}
diff --git a/src/features/chat/aiChatFactory.ts b/src/features/chat/aiChatFactory.ts
index 85382694..7bd4bc22 100644
--- a/src/features/chat/aiChatFactory.ts
+++ b/src/features/chat/aiChatFactory.ts
@@ -1,54 +1,41 @@
import { Message } from '@/features/messages/messages'
-import { AIService, AIServiceConfig } from '@/features/constants/settings'
-import { getAnthropicChatResponseStream } from './anthropicChat'
-import { getDifyChatResponseStream } from './difyChat'
-import { getGoogleChatResponseStream } from './googleChat'
-import { getGroqChatResponseStream } from './groqChat'
+import { AIService } from '@/features/constants/settings'
import { getLocalLLMChatResponseStream } from './localLLMChat'
-import { getOpenAIChatResponseStream } from './openAiChat'
+import { getDifyChatResponseStream } from './difyChat'
+import { getVercelAIChatResponseStream } from './vercelAIChat'
+import settingsStore from '@/features/stores/settings'
export async function getAIChatResponseStream(
service: AIService,
- messages: Message[],
- config: AIServiceConfig
+ messages: Message[]
): Promise | null> {
+ const ss = settingsStore.getState()
+
switch (service) {
case 'openai':
- return getOpenAIChatResponseStream(
- messages,
- config.openai.key,
- config.openai.model
- )
case 'anthropic':
- return getAnthropicChatResponseStream(
- messages,
- config.anthropic.key,
- config.anthropic.model
- )
case 'google':
- return getGoogleChatResponseStream(
+ case 'groq':
+ return getVercelAIChatResponseStream(
messages,
- config.google.key,
- config.google.model
+ ss[`${service}Key`] ||
+ process.env[`NEXT_PUBLIC_${service.toUpperCase()}_KEY`] ||
+ '',
+ service,
+ ss.selectAIModel
)
case 'localLlm':
return getLocalLLMChatResponseStream(
messages,
- config.localLlm.url,
- config.localLlm.model
- )
- case 'groq':
- return getGroqChatResponseStream(
- messages,
- config.groq.key,
- config.groq.model
+ ss.localLlmUrl || process.env.NEXT_PUBLIC_LOCAL_LLM_URL || '',
+ ss.selectAIModel || process.env.NEXT_PUBLIC_LOCAL_LLM_MODEL || ''
)
case 'dify':
return getDifyChatResponseStream(
messages,
- config.dify.key,
- config.dify.url,
- config.dify.conversationId
+ ss.difyKey || process.env.NEXT_PUBLIC_DIFY_KEY || '',
+ ss.difyUrl || process.env.NEXT_PUBLIC_DIFY_URL || '',
+ ss.difyConversationId
)
default:
throw new Error(`Unsupported AI service: ${service}`)
diff --git a/src/features/chat/anthropicChat.ts b/src/features/chat/anthropicChat.ts
deleted file mode 100644
index f0882151..00000000
--- a/src/features/chat/anthropicChat.ts
+++ /dev/null
@@ -1,81 +0,0 @@
-import { Message } from '../messages/messages'
-
-export async function getAnthropicChatResponse(
- messages: Message[],
- apiKey: string,
- model: string
-) {
- const response = await fetch('/api/anthropic', {
- method: 'POST',
- headers: {
- 'Content-Type': 'application/json',
- },
- body: JSON.stringify({ messages, apiKey, model }),
- })
-
- const data = await response.json()
- return { message: data.message[0].text }
-}
-
-export async function getAnthropicChatResponseStream(
- messages: Message[],
- apiKey: string,
- model: string
-) {
- const response = await fetch('/api/anthropic', {
- method: 'POST',
- headers: {
- 'Content-Type': 'application/json',
- },
- body: JSON.stringify({ messages, apiKey, model, stream: true }),
- })
-
- if (!response.ok) {
- throw new Error('Anthropic APIリクエストに失敗しました')
- }
-
- if (!response.body) {
- throw new Error('Anthropic APIレスポンスが空です')
- }
-
- const reader = response.body.getReader()
- const decoder = new TextDecoder('utf-8')
-
- return new ReadableStream({
- async start(controller) {
- while (true) {
- const { done, value } = await reader.read()
-
- if (done) {
- break
- }
-
- const chunk = decoder.decode(value)
- const lines = chunk.split('\n')
-
- for (const line of lines) {
- if (line.startsWith('data:')) {
- const data = line.substring(5).trim()
- if (data !== '[DONE]') {
- const event = JSON.parse(data)
- switch (event.type) {
- case 'content_block_delta':
- controller.enqueue(event.text)
- break
- case 'error':
- throw new Error(
- `Anthropic API error: ${JSON.stringify(event.error)}`
- )
- case 'message_stop':
- controller.close()
- return
- }
- }
- }
- }
- }
-
- controller.close()
- },
- })
-}
diff --git a/src/features/chat/googleChat.ts b/src/features/chat/googleChat.ts
deleted file mode 100644
index 5ec46341..00000000
--- a/src/features/chat/googleChat.ts
+++ /dev/null
@@ -1,164 +0,0 @@
-// import { Message } from "../messages/messages";
-
-// export async function getGoogleChatResponse(messages: Message[], apiKey: string, model: string) {
-// const response = await fetch("/api/google", {
-// method: "POST",
-// headers: {
-// "Content-Type": "application/json",
-// },
-// body: JSON.stringify({ messages, apiKey, model }),
-// });
-
-// const data = await response.json();
-// return data;
-// }
-
-// export async function getGoogleChatResponseStream(
-// messages: Message[],
-// apiKey: string,
-// model: string
-// ) {
-// const response = await fetch("/api/google", {
-// method: "POST",
-// headers: {
-// "Content-Type": "application/json",
-// },
-// body: JSON.stringify({ messages, apiKey, model, stream: true }),
-// });
-
-// if (!response.ok) {
-// throw new Error("Google Gemini APIリクエストに失敗しました");
-// }
-
-// if (response.body === null) {
-// throw new Error("Google Gemini APIリクエストに失敗しました");
-// }
-
-// const reader = response.body.getReader();
-// const decoder = new TextDecoder("utf-8");
-
-// return new ReadableStream({
-// async start(controller) {
-// while (true) {
-// const { done, value } = await reader.read();
-
-// if (done) {
-// break;
-// }
-
-// const chunk = decoder.decode(value);
-// // 各行を個別に処理
-// const lines = chunk.split('\n');
-// lines.forEach(line => {
-// if (line.startsWith('event: end')) {
-// controller.close(); // ストリームの終了を検出
-// return;
-// }
-// // 'data: ' プレフィックスを取り除く
-// const jsonStr = line.replace(/^data: /, '').trim();
-// if (jsonStr) {
-// try {
-// const json = JSON.parse(jsonStr);
-// if (json.text) {
-// controller.enqueue(json.text);
-// }
-// } catch (error) {
-// console.error("Failed to parse JSON:", error);
-// }
-// }
-// });
-// }
-
-// controller.close();
-// },
-// });
-// }
-
-import { GoogleGenerativeAI } from '@google/generative-ai'
-import { Message } from '../messages/messages'
-
-export async function getGoogleChatResponse(
- messages: Message[],
- apiKey: string,
- model: string
-) {
- const { history, systemMessage } = processMessages(messages)
-
- const genAI = new GoogleGenerativeAI(apiKey)
- const chatModel = genAI.getGenerativeModel({
- model: model,
- systemInstruction: systemMessage,
- })
-
- const chat = chatModel.startChat({ history })
- const lastMessage = messages[messages.length - 1].content
- const result = await chat.sendMessage(
- typeof lastMessage === 'string' ? lastMessage : lastMessage[0].text
- )
- const response = await result.response
- const text = response.text()
-
- return { text }
-}
-
-export async function getGoogleChatResponseStream(
- messages: Message[],
- apiKey: string,
- model: string
-) {
- const { history, systemMessage } = processMessages(messages)
-
- const genAI = new GoogleGenerativeAI(apiKey)
- const chatModel = genAI.getGenerativeModel({
- model: model,
- systemInstruction: systemMessage,
- })
-
- const chat = chatModel.startChat({ history })
- const lastMessage = messages[messages.length - 1].content
- const result = await chat.sendMessageStream(
- typeof lastMessage === 'string' ? lastMessage : lastMessage[0].text
- )
-
- const stream = new ReadableStream({
- async start(controller) {
- let text = ''
- for await (const chunk of result.stream) {
- const chunkText = chunk.text()
- text += chunkText
- controller.enqueue(chunkText)
- }
- controller.close()
- },
- })
-
- return stream
-}
-
-function processMessages(messages: Message[]) {
- let systemMessage = ''
- const history = messages
- .filter((message, index) => {
- if (message.role === 'system') {
- systemMessage =
- typeof message.content === 'string'
- ? message.content
- : message.content[0].text
- return false
- }
- return index === 0 ? message.role === 'user' : true
- })
- .map((message) => ({
- role: message.role === 'assistant' ? 'model' : message.role,
- parts: [
- {
- text:
- typeof message.content === 'string'
- ? message.content
- : message.content[0].text,
- },
- ],
- }))
-
- return { history, systemMessage }
-}
diff --git a/src/features/chat/groqChat.ts b/src/features/chat/groqChat.ts
deleted file mode 100644
index e7439593..00000000
--- a/src/features/chat/groqChat.ts
+++ /dev/null
@@ -1,85 +0,0 @@
-import { Message } from '../messages/messages'
-
-export async function getGroqChatResponse(
- messages: Message[],
- apiKey: string,
- model: string
-) {
- const response = await fetch('/api/groq', {
- method: 'POST',
- headers: {
- 'Content-Type': 'application/json',
- },
- body: JSON.stringify({ messages, apiKey, model }),
- })
-
- const data = await response.json()
- return data
-}
-
-export async function getGroqChatResponseStream(
- messages: Message[],
- apiKey: string,
- model: string
-) {
- const response = await fetch('/api/groq', {
- method: 'POST',
- headers: {
- 'Content-Type': 'application/json',
- },
- body: JSON.stringify({ messages, apiKey, model, stream: false }),
- })
-
- if (!response.ok) {
- throw new Error('Groq API request failed')
- }
-
- if (!response.body) {
- throw new Error('Groq API response is empty')
- }
-
- const reader = response.body.getReader()
- const decoder = new TextDecoder('utf-8')
-
- return new ReadableStream({
- async start(controller) {
- let buffer = ''
-
- while (true) {
- const { done, value } = await reader.read()
-
- if (done) {
- break
- }
-
- // const chunk = decoder.decode(value, { stream: true });
- // controller.enqueue(chunk);
-
- buffer += decoder.decode(value, { stream: true })
-
- // バッファを処理し、「{"message":」文字列を削除する
- buffer = buffer.replace(/{"message":\s*"/g, '')
-
- // バッファが完全なメッセージを含んでいる場合、それを送信する。
- if (buffer.includes('"}')) {
- const messages = buffer.split('"}')
-
- for (let i = 0; i < messages.length - 1; i++) {
- controller.enqueue(messages[i])
- }
-
- buffer = messages[messages.length - 1]
- }
- }
-
- console.log('buffer', buffer)
-
- // 残りのバッファを処理する。
- if (buffer.length > 0) {
- controller.enqueue(buffer)
- }
-
- controller.close()
- },
- })
-}
diff --git a/src/features/chat/handlers.ts b/src/features/chat/handlers.ts
index cb89e26a..1db47608 100644
--- a/src/features/chat/handlers.ts
+++ b/src/features/chat/handlers.ts
@@ -1,5 +1,5 @@
import { getAIChatResponseStream } from '@/features/chat/aiChatFactory'
-import { AIService, AIServiceConfig } from '@/features/constants/settings'
+import { AIService } from '@/features/constants/settings'
import { textsToScreenplay, Message } from '@/features/messages/messages'
import { speakCharacter } from '@/features/messages/speakCharacter'
import { judgeSlide } from '@/features/slide/slideAIHelpers'
@@ -143,39 +143,10 @@ export const processAIResponse = async (
const hs = homeStore.getState()
const currentSlideMessages: string[] = []
- const aiServiceConfig: AIServiceConfig = {
- openai: {
- key: ss.openAiKey || process.env.NEXT_PUBLIC_OPEN_AI_KEY || '',
- model: ss.selectAIModel,
- },
- anthropic: {
- key: ss.anthropicKey || process.env.NEXT_PUBLIC_ANTHROPIC_KEY || '',
- model: ss.selectAIModel,
- },
- google: {
- key: ss.googleKey || process.env.NEXT_PUBLIC_GOOGLE_KEY || '',
- model: ss.selectAIModel,
- },
- localLlm: {
- url: ss.localLlmUrl || process.env.NEXT_PUBLIC_LOCAL_LLM_URL || '',
- model: ss.selectAIModel || process.env.NEXT_PUBLIC_LOCAL_LLM_MODEL || '',
- },
- groq: {
- key: ss.groqKey || process.env.NEXT_PUBLIC_GROQ_KEY || '',
- model: ss.selectAIModel,
- },
- dify: {
- key: ss.difyKey || process.env.NEXT_PUBLIC_DIFY_KEY || '',
- url: ss.difyUrl || process.env.NEXT_PUBLIC_DIFY_URL || '',
- conversationId: ss.difyConversationId,
- },
- }
-
try {
stream = await getAIChatResponseStream(
ss.selectAIService as AIService,
- messages,
- aiServiceConfig
+ messages
)
} catch (e) {
console.error(e)
@@ -197,6 +168,8 @@ export const processAIResponse = async (
try {
while (true) {
const { done, value } = await reader.read()
+ console.log(done)
+ console.log(value)
if (done && receivedMessage.length === 0) break
if (value) receivedMessage += value
@@ -345,9 +318,9 @@ export const processAIResponse = async (
if (
typeof item.content != 'string' &&
item.content[0] &&
- item.content[1].image_url
+ item.content[1]
) {
- lastImageUrl = item.content[1].image_url.url
+ lastImageUrl = item.content[1].image
}
const lastItem = acc[acc.length - 1]
@@ -365,7 +338,7 @@ export const processAIResponse = async (
...item,
content: [
{ type: 'text', text: text.trim() },
- { type: 'image_url', image_url: { url: lastImageUrl } },
+ { type: 'image', image: lastImageUrl },
],
})
lastImageUrl = ''
@@ -430,7 +403,7 @@ export const handleSendChatFn =
// ChatVRM original mode
const emptyKeys = [
ss.selectAIService === 'openai' &&
- !ss.openAiKey &&
+ !ss.openaiKey &&
!process.env.NEXT_PUBLIC_OPEN_AI_KEY,
ss.selectAIService === 'anthropic' &&
@@ -500,13 +473,12 @@ export const handleSendChatFn =
...hs.chatLog,
{
role: 'user',
- content:
- hs.modalImage && ss.selectAIService === 'openai'
- ? [
- { type: 'text', text: newMessage },
- { type: 'image_url', image_url: { url: hs.modalImage } },
- ]
- : newMessage,
+ content: hs.modalImage
+ ? [
+ { type: 'text', text: newMessage },
+ { type: 'image', image: hs.modalImage },
+ ]
+ : newMessage,
},
]
if (hs.modalImage) {
@@ -515,14 +487,17 @@ export const handleSendChatFn =
homeStore.setState({ chatLog: messageLog })
// TODO: AIに送信するメッセージの加工、処理がひどいので要修正
- const processedMessageLog = messageLog.map((message) => ({
+ // 画像は直近のものしか送らない
+ const processedMessageLog = messageLog.map((message, index) => ({
role: ['assistant', 'user', 'system'].includes(message.role)
? message.role
: 'assistant',
content:
- typeof message.content === 'string' || ss.selectAIService === 'openai'
+ index === messageLog.length - 1
? message.content
- : message.content[0].text,
+ : Array.isArray(message.content)
+ ? message.content[0].text
+ : message.content,
}))
const messages: Message[] = [
diff --git a/src/features/chat/openAiChat.ts b/src/features/chat/openAiChat.ts
deleted file mode 100644
index 51cc9c4b..00000000
--- a/src/features/chat/openAiChat.ts
+++ /dev/null
@@ -1,95 +0,0 @@
-import { Message } from '../messages/messages'
-
-export async function getOpenAIChatResponse(
- messages: Message[],
- apiKey: string,
- model: string
-) {
- try {
- const response = await fetch('/api/openai', {
- method: 'POST',
- headers: {
- 'Content-Type': 'application/json',
- },
- body: JSON.stringify({ messages, apiKey, model }),
- })
-
- if (!response.ok) {
- throw new Error('Failed to fetch OpenAI API response')
- }
-
- const data = await response.json()
- return { message: data.message }
- } catch (error) {
- console.error('Error fetching OpenAI API response:', error)
- throw error
- }
-}
-
-export async function getOpenAIChatResponseStream(
- messages: Message[],
- apiKey: string,
- model: string
-) {
- try {
- const response = await fetch('/api/openai', {
- method: 'POST',
- headers: {
- 'Content-Type': 'application/json',
- },
- body: JSON.stringify({ messages, apiKey, model, stream: true }),
- })
-
- if (!response.ok) {
- throw new Error('OpenAI APIリクエストに失敗しました')
- }
-
- if (!response.body) {
- throw new Error('OpenAI APIレスポンスが空です')
- }
-
- const reader = response.body.getReader()
- const decoder = new TextDecoder('utf-8')
-
- return new ReadableStream({
- async start(controller) {
- while (true) {
- const { done, value } = await reader.read()
-
- if (done) {
- break
- }
-
- const chunk = decoder.decode(value)
- const lines = chunk.split('\n')
-
- for (const line of lines) {
- if (line.startsWith('data:')) {
- const data = line.substring(5).trim()
- if (data !== '[DONE]') {
- const event = JSON.parse(data)
- switch (event.type) {
- case 'content_block_delta':
- controller.enqueue(event.text)
- break
- case 'error':
- throw new Error(
- `OpenAI API error: ${JSON.stringify(event.error)}`
- )
- case 'message_stop':
- controller.close()
- return
- }
- }
- }
- }
- }
-
- controller.close()
- },
- })
- } catch (error) {
- console.error('Error fetching OpenAI API response stream:', error)
- throw error
- }
-}
diff --git a/src/features/chat/vercelAIChat.ts b/src/features/chat/vercelAIChat.ts
new file mode 100644
index 00000000..84005236
--- /dev/null
+++ b/src/features/chat/vercelAIChat.ts
@@ -0,0 +1,96 @@
+import { Message } from '../messages/messages'
+
+export async function getVercelAIChatResponse(
+ messages: Message[],
+ apiKey: string,
+ aiService: string,
+ model: string
+) {
+ try {
+ const response = await fetch('/api/aiChat', {
+ method: 'POST',
+ headers: {
+ 'Content-Type': 'application/json',
+ },
+ body: JSON.stringify({
+ messages,
+ apiKey,
+ aiService,
+ model,
+ stream: false,
+ }),
+ })
+
+ if (!response.ok) {
+ throw new Error(`API request to ${aiService} failed`)
+ }
+
+ if (!response.body) {
+ throw new Error(`API response from ${aiService} is empty`)
+ }
+
+ const data = await response.json()
+ return { message: data.message }
+ } catch (error) {
+ console.error(`Error fetching ${aiService} API response:`, error)
+ throw error
+ }
+}
+
+export async function getVercelAIChatResponseStream(
+ messages: Message[],
+ apiKey: string,
+ aiService: string,
+ model: string
+): Promise> {
+ const response = await fetch('/api/aiChat', {
+ method: 'POST',
+ headers: {
+ 'Content-Type': 'application/json',
+ },
+ body: JSON.stringify({
+ messages,
+ apiKey,
+ aiService,
+ model,
+ stream: true,
+ }),
+ })
+
+ if (!response.ok) {
+ throw new Error(`API request to ${aiService} failed`)
+ }
+
+ return new ReadableStream({
+ async start(controller) {
+ if (!response.body) {
+ throw new Error(`API response from ${aiService} is empty`)
+ }
+
+ const reader = response.body.getReader()
+ const decoder = new TextDecoder('utf-8')
+
+ try {
+ while (true) {
+ const { done, value } = await reader.read()
+ if (done) break
+
+ const chunk = decoder.decode(value)
+ const lines = chunk.split('\n')
+
+ for (const line of lines) {
+ if (line.startsWith('0:')) {
+ const content = line.substring(2).trim().replace(/^"|"$/g, '')
+ controller.enqueue(content)
+ }
+ }
+ }
+ } catch (error) {
+ controller.error(error)
+ } finally {
+ controller.close()
+ reader.releaseLock()
+ }
+ },
+ })
+}
diff --git a/src/features/messages/messages.ts b/src/features/messages/messages.ts
index 3e065f8a..bb39c37a 100644
--- a/src/features/messages/messages.ts
+++ b/src/features/messages/messages.ts
@@ -6,10 +6,7 @@ export type Message = {
role: string // "assistant" | "system" | "user";
content:
| string
- | [
- { type: string; text: string },
- { type: string; image_url: { url: string } },
- ] // マルチモーダル拡張
+ | [{ type: 'text'; text: string }, { type: 'image'; image: string }] // マルチモーダル拡張
}
const talkStyles = [
diff --git a/src/features/slide/slideAIHelpers.ts b/src/features/slide/slideAIHelpers.ts
index d22b1b0b..afc18627 100644
--- a/src/features/slide/slideAIHelpers.ts
+++ b/src/features/slide/slideAIHelpers.ts
@@ -1,7 +1,8 @@
-import { Message } from '@/features/messages/messages'
-import { getOpenAIChatResponse } from '@/features/chat/openAiChat'
-import { getAnthropicChatResponse } from '@/features/chat/anthropicChat'
-import settingsStore from '@/features/stores/settings'
+import { getVercelAIChatResponse } from '@/features/chat/vercelAIChat'
+import settingsStore, {
+ multiModalAIServiceKey,
+ multiModalAIServices,
+} from '@/features/stores/settings'
export const judgeSlide = async (
queryText: string,
@@ -9,6 +10,18 @@ export const judgeSlide = async (
supplement: string
): Promise => {
const ss = settingsStore.getState()
+ const aiService = ss.selectAIService as multiModalAIServiceKey
+
+ if (!multiModalAIServices.includes(aiService)) {
+ throw new Error('Invalid AI service')
+ }
+
+ const apiKeyName = `${aiService}Key` as const
+ const apiKey = ss[apiKeyName]
+
+ if (!apiKey) {
+ throw new Error('API key not found')
+ }
const systemMessage = `
You are an AI tasked with determining whether a user's comment is a question about a given script document and supplementary text, and if so, which page of the document is most relevant to the question. Follow these instructions carefully:
@@ -46,27 +59,14 @@ ${supplement}
Based on the user's comment and the content of both the script document and supplementary text, provide "only" your final answer in the specified JSON format.
`
- if (ss.selectAIService === 'openai') {
- const response = await getOpenAIChatResponse(
- [
- { role: 'system', content: systemMessage },
- { role: 'user', content: queryText },
- ],
- ss.openAiKey,
- ss.selectAIModel
- )
- return response.message
- } else if (ss.selectAIService === 'anthropic') {
- const response = await getAnthropicChatResponse(
- [
- { role: 'system', content: systemMessage },
- { role: 'user', content: queryText },
- ],
- ss.anthropicKey,
- ss.selectAIModel
- )
- return response.message
- } else {
- throw new Error('Unsupported AI service')
- }
+ const response = await getVercelAIChatResponse(
+ [
+ { role: 'system', content: systemMessage },
+ { role: 'user', content: queryText },
+ ],
+ aiService,
+ apiKey,
+ ss.selectAIModel
+ )
+ return response.message
}
diff --git a/src/features/stores/settings.ts b/src/features/stores/settings.ts
index 50a7a4b4..619e7c37 100644
--- a/src/features/stores/settings.ts
+++ b/src/features/stores/settings.ts
@@ -10,8 +10,15 @@ import {
VoiceLanguage,
} from '../constants/settings'
+export const multiModalAIServices = ['openai', 'anthropic', 'google'] as const
+export type multiModalAIServiceKey = (typeof multiModalAIServices)[number]
+
+type multiModalAPIKeys = {
+ [K in multiModalAIServiceKey as `${K}Key`]: string
+}
+
interface APIKeys {
- openAiKey: string
+ openaiKey: string
anthropicKey: string
googleKey: string
groqKey: string
@@ -71,6 +78,7 @@ interface General {
}
export type SettingsState = APIKeys &
+ multiModalAPIKeys &
ModelProvider &
Integrations &
Character &
@@ -80,7 +88,7 @@ const settingsStore = create()(
persist(
(set, get) => ({
// API Keys
- openAiKey: '',
+ openaiKey: '',
anthropicKey: '',
googleKey: '',
groqKey: '',
@@ -139,7 +147,7 @@ const settingsStore = create()(
{
name: 'aitube-kit-settings',
partialize: (state) => ({
- openAiKey: state.openAiKey,
+ openaiKey: state.openaiKey,
anthropicKey: state.anthropicKey,
googleKey: state.googleKey,
groqKey: state.groqKey,
diff --git a/src/features/youtube/conversationContinuityFunctions.ts b/src/features/youtube/conversationContinuityFunctions.ts
index b06fd792..01c83b23 100644
--- a/src/features/youtube/conversationContinuityFunctions.ts
+++ b/src/features/youtube/conversationContinuityFunctions.ts
@@ -1,26 +1,42 @@
import { Message } from '@/features/messages/messages'
-import { getOpenAIChatResponse } from '@/features/chat/openAiChat'
-import { getAnthropicChatResponse } from '@/features/chat/anthropicChat'
-
-const fetchAIResponse = async (
- queryMessages: any[],
- aiApiKey: string,
- selectAIService: string,
- selectAIModel: string
-): Promise => {
- if (selectAIService === 'openai') {
- return await getOpenAIChatResponse(queryMessages, aiApiKey, selectAIModel)
- } else if (selectAIService === 'anthropic') {
- return await getAnthropicChatResponse(
- queryMessages,
- aiApiKey,
- selectAIModel
- )
- } else {
- throw new Error('Unsupported AI service')
+import { getVercelAIChatResponse } from '@/features/chat/vercelAIChat'
+import settingsStore, {
+ multiModalAIServiceKey,
+ multiModalAIServices,
+} from '@/features/stores/settings'
+
+const getAIConfig = () => {
+ const ss = settingsStore.getState()
+ const aiService = ss.selectAIService as multiModalAIServiceKey
+
+ if (!multiModalAIServices.includes(aiService)) {
+ throw new Error('Invalid AI service')
+ }
+
+ const apiKeyName = `${aiService}Key` as const
+ const apiKey = ss[apiKeyName]
+
+ if (!apiKey) {
+ throw new Error('API key not found')
+ }
+
+ return {
+ aiApiKey: apiKey,
+ selectAIService: aiService,
+ selectAIModel: ss.selectAIModel,
}
}
+const fetchAIResponse = async (queryMessages: any[]): Promise => {
+ const { aiApiKey, selectAIService, selectAIModel } = getAIConfig()
+ return await getVercelAIChatResponse(
+ queryMessages,
+ aiApiKey,
+ selectAIService,
+ selectAIModel
+ )
+}
+
/**
* 共通のシステムメッセージをを返します。
*
@@ -112,16 +128,11 @@ const getLastMessages = (
*
* @param {Message[]} messages - メッセージの配列
* @param {any[]} youtubeComments - Youtubeのコメントの配列
- * @param {string} openAiKey - OpenAIのAPIキー
- * @param {string} selectAIModel - 使用するモデル
* @returns {Promise} - 最適なコメント
*/
export const getBestComment = async (
messages: Message[],
- youtubeComments: any[],
- aiApiKey: string,
- selectAIService: string,
- selectAIModel: string
+ youtubeComments: any[]
): Promise => {
console.log('getBestComment')
const lastTenMessages = getLastMessages(messages, 10)
@@ -159,12 +170,7 @@ ${lastTenMessages}
},
]
- const response = await fetchAIResponse(
- queryMessages,
- aiApiKey,
- selectAIService,
- selectAIModel
- )
+ const response = await fetchAIResponse(queryMessages)
return response.message
}
@@ -194,16 +200,9 @@ export const getMessagesForSleep = async (
* メッセージを受け取り、最新の4つのメッセージを使用して別の話題を取得します。
*
* @param {Message[]} messages - メッセージの配列
- * @param {string} openAiKey - OpenAIのAPIキー
- * @param {string} selectAIModel - 使用するモデル
* @returns {Promise} - 別の話題
*/
-export const getAnotherTopic = async (
- messages: Message[],
- aiApiKey: string,
- selectAIService: string,
- selectAIModel: string
-): Promise => {
+export const getAnotherTopic = async (messages: Message[]): Promise => {
console.log('getAnotherTopic')
const lastTenMessages = getLastMessages(messages, 10)
const queryMessages = [
@@ -223,12 +222,7 @@ export const getAnotherTopic = async (
...lastTenMessages,
]
- const response = await fetchAIResponse(
- queryMessages,
- aiApiKey,
- selectAIService,
- selectAIModel
- )
+ const response = await fetchAIResponse(queryMessages)
return response.message
}
@@ -260,15 +254,10 @@ export const getMessagesForNewTopic = async (
* メッセージを受け取り、次の発言者を判断します。
*
* @param {Message[]} messages - メッセージの配列
- * @param {string} openAiKey - OpenAIのAPIキー
- * @param {string} selectAIModel - 使用するモデル
* @returns {Promise} - 次の発言者
*/
export const checkIfResponseContinuationIsRequired = async (
- messages: Message[],
- aiApiKey: string,
- selectAIService: string,
- selectAIModel: string
+ messages: Message[]
): Promise => {
console.log('checkIfResponseContinuationIsRequired')
const lastTenMessages = getLastMessages(messages, 10)
@@ -277,7 +266,7 @@ export const checkIfResponseContinuationIsRequired = async (
}
const systemMessage = `与えられた会話文の文脈から、次にどの話者が発言すべきかを判断してください。
-最後の話者が話を続けるべきならば "true" を、逆に交代が必要な場合は "false" を返します。
+最後��話者が話を続けるべきならば "true" を、逆に交代が必要な場合は "false" を返します。
回答はJSON形式で、answerとreasonの2つのキーを持つオブジェクトとしてください。
## 例
@@ -342,12 +331,7 @@ B: 見てみたいな。送ってくれない？
// エラーが発生した場合はfalseを返す
let answer
try {
- const response = await fetchAIResponse(
- queryMessages,
- aiApiKey,
- selectAIService,
- selectAIModel
- )
+ const response = await fetchAIResponse(queryMessages)
console.log('response.message:', response.message)
const responseJson = JSON.parse(response.message)
answer = responseJson.answer
diff --git a/src/features/youtube/youtubeComments.ts b/src/features/youtube/youtubeComments.ts
index ccb69b08..05d55e9b 100644
--- a/src/features/youtube/youtubeComments.ts
+++ b/src/features/youtube/youtubeComments.ts
@@ -105,8 +105,6 @@ export const fetchAndProcessComments = async (
try {
const liveChatId = await getLiveChatId(ss.youtubeLiveId, ss.youtubeApiKey)
- const aiApiKey =
- ss.selectAIService === 'anthropic' ? ss.anthropicKey : ss.openAiKey
if (liveChatId) {
// 会話の継続が必要かどうかを確認
@@ -116,12 +114,7 @@ export const fetchAndProcessComments = async (
ss.conversationContinuityMode
) {
const isContinuationNeeded =
- await checkIfResponseContinuationIsRequired(
- hs.chatLog,
- aiApiKey,
- ss.selectAIService,
- ss.selectAIModel
- )
+ await checkIfResponseContinuationIsRequired(hs.chatLog)
if (isContinuationNeeded) {
const continuationMessage = await getMessagesForContinuation(
ss.systemPrompt,
@@ -153,17 +146,7 @@ export const fetchAndProcessComments = async (
settingsStore.setState({ youtubeSleepMode: false })
let selectedComment = ''
if (ss.conversationContinuityMode) {
- if (youtubeComments.length > 1) {
- selectedComment = await getBestComment(
- hs.chatLog,
- youtubeComments,
- aiApiKey,
- ss.selectAIService,
- ss.selectAIModel
- )
- } else {
- selectedComment = youtubeComments[0].userComment
- }
+ selectedComment = await getBestComment(hs.chatLog, youtubeComments)
} else {
selectedComment =
youtubeComments[Math.floor(Math.random() * youtubeComments.length)]
@@ -187,12 +170,7 @@ export const fetchAndProcessComments = async (
preProcessAIResponse(continuationMessage)
} else if (noCommentCount === 3) {
// 新しいトピックを生成
- const anotherTopic = await getAnotherTopic(
- hs.chatLog,
- aiApiKey,
- ss.selectAIService,
- ss.selectAIModel
- )
+ const anotherTopic = await getAnotherTopic(hs.chatLog)
console.log('anotherTopic:', anotherTopic)
const newTopicMessage = await getMessagesForNewTopic(
ss.systemPrompt,
diff --git a/src/pages/api/aiChat.ts b/src/pages/api/aiChat.ts
new file mode 100644
index 00000000..e52164eb
--- /dev/null
+++ b/src/pages/api/aiChat.ts
@@ -0,0 +1,120 @@
+import { createOpenAI } from '@ai-sdk/openai'
+import { createAnthropic } from '@ai-sdk/anthropic'
+import { createGoogleGenerativeAI } from '@ai-sdk/google'
+import { streamText, generateText } from 'ai'
+import { NextRequest } from 'next/server'
+
+type AIServiceKey = 'openai' | 'anthropic' | 'google' | 'groq'
+type AIServiceConfig = Record any>
+
+// Allow streaming responses up to 30 seconds
+export const maxDuration = 30
+
+export const config = {
+ runtime: 'edge',
+}
+
+export default async function handler(req: NextRequest) {
+ if (req.method !== 'POST') {
+ return new Response(JSON.stringify({ error: 'Method Not Allowed' }), {
+ status: 405,
+ headers: { 'Content-Type': 'application/json' },
+ })
+ }
+
+ const { messages, apiKey, aiService, model, stream } = await req.json()
+ const aiServiceConfig: AIServiceConfig = {
+ openai: () => createOpenAI({ apiKey }),
+ anthropic: () => createAnthropic({ apiKey }),
+ google: () => createGoogleGenerativeAI({ apiKey }),
+ groq: () =>
+ createOpenAI({ baseURL: 'https://api.groq.com/openai/v1', apiKey }),
+ }
+ const aiServiceInstance = aiServiceConfig[aiService as AIServiceKey]
+
+ if (!aiServiceInstance) {
+ return new Response(JSON.stringify({ error: 'Invalid AI service' }), {
+ status: 400,
+ headers: { 'Content-Type': 'application/json' },
+ })
+ }
+
+ const instance = aiServiceInstance()
+
+ const modifiedMessages = modifyMessages(aiService, messages)
+
+ if (stream) {
+ try {
+ const result = await streamText({
+ model: instance(model),
+ messages: modifiedMessages,
+ })
+
+ return result.toDataStreamResponse()
+ } catch (error) {
+ console.error('Error in OpenAI API call:', error)
+ return new Response(JSON.stringify({ error: 'Internal Server Error' }), {
+ status: 500,
+ headers: { 'Content-Type': 'application/json' },
+ })
+ }
+ } else {
+ const result = await generateText({
+ model: instance(model),
+ messages: modifiedMessages,
+ })
+ debugger
+ return result
+ }
+}
+
+function modifyMessages(aiService: string, messages: any[]) {
+ if (aiService === 'anthropic') {
+ return modifyAnthropicMessages(messages)
+ }
+ return messages
+}
+
+// Anthropicのメッセージを修正する
+function modifyAnthropicMessages(messages: any[]) {
+ const systemMessage = messages.find((message) => message.role === 'system')
+ let userMessages = messages
+ .filter((message) => message.role !== 'system')
+ .filter((message) => message.content !== '')
+
+ userMessages = consolidateMessages(userMessages)
+
+ while (userMessages.length > 0 && userMessages[0].role !== 'user') {
+ userMessages.shift()
+ }
+
+ return [systemMessage, ...userMessages]
+}
+
+// 同じroleのメッセージを結合する
+function consolidateMessages(messages: any[]) {
+ const consolidated: any[] = []
+ let lastRole: string | null = null
+ let combinedContent = ''
+
+ messages.forEach((message, index) => {
+ if (message.role === lastRole) {
+ combinedContent += '\n' + message.content
+ } else {
+ if (lastRole !== null) {
+ consolidated.push({ role: lastRole, content: combinedContent })
+ }
+ lastRole = message.role
+ combinedContent =
+ typeof message.content === 'string'
+ ? message.content
+ : message.content[0].text
+ }
+
+ if (index === messages.length - 1) {
+ consolidated.push({ role: lastRole, content: combinedContent })
+ }
+ })
+
+ return consolidated
+}
diff --git a/src/pages/api/chat.ts b/src/pages/api/chat.ts
deleted file mode 100644
index 0b72f406..00000000
--- a/src/pages/api/chat.ts
+++ /dev/null
@@ -1,38 +0,0 @@
-// import { Configuration, OpenAIApi } from "openai";
-
-// import type { NextApiRequest, NextApiResponse } from "next";
-
-// type Data = {
-// message: string;
-// };
-
-// export default async function handler(
-// req: NextApiRequest,
-// res: NextApiResponse
-// ) {
-// const apiKey = req.body.apiKey || process.env.OPEN_AI_KEY;
-
-// if (!apiKey) {
-// res
-// .status(400)
-// .json({ message: "APIキーが間違っているか、設定されていません。" });
-
-// return;
-// }
-
-// const configuration = new Configuration({
-// apiKey: apiKey,
-// });
-
-// const openai = new OpenAIApi(configuration);
-
-// const { data } = await openai.createChatCompletion({
-// model: "gpt-3.5-turbo",
-// messages: req.body.messages,
-// });
-
-// const [aiRes] = data.choices;
-// const message = aiRes.message?.content || "エラーが発生しました";
-
-// res.status(200).json({ message: message });
-// }
diff --git a/src/pages/api/convertSlide.ts b/src/pages/api/convertSlide.ts
index 2698e611..4b38271d 100644
--- a/src/pages/api/convertSlide.ts
+++ b/src/pages/api/convertSlide.ts
@@ -3,9 +3,17 @@ import formidable from 'formidable'
import fs from 'fs'
import path from 'path'
import { createCanvas } from 'canvas'
-import { OpenAI } from 'openai'
import * as pdfjsLib from 'pdfjs-dist/legacy/build/pdf.mjs'
+import { createOpenAI } from '@ai-sdk/openai'
+import { createAnthropic } from '@ai-sdk/anthropic'
+import { createGoogleGenerativeAI } from '@ai-sdk/google'
+import { generateObject } from 'ai'
+
+import { multiModalAIServiceKey } from '@/features/stores/settings'
+
+type AIServiceConfig = Record any>
+
export const config = {
api: {
bodyParser: false,
@@ -62,20 +70,40 @@ async function convertPdfToImages(pdfBuffer: Buffer): Promise {
return images
}
+interface SlideLineResponse {
+ line: string
+ notes: string
+ page?: number
+}
+
async function createSlideLine(
imageBase64: string,
apiKey: string,
+ aiService: string,
model: string,
selectLanguage: string,
previousResult: string | null
-) {
- const client = new OpenAI({ apiKey })
+): Promise {
const additionalPrompt = previousResult
? `Previous slide content: ${previousResult}`
: 'This is the first slide.'
- const response = await client.chat.completions.create({
- model: `${model}`,
+ const aiServiceConfig: AIServiceConfig = {
+ openai: () => createOpenAI({ apiKey }),
+ anthropic: () => createAnthropic({ apiKey }),
+ google: () => createGoogleGenerativeAI({ apiKey }),
+ }
+
+ const aiServiceInstance = aiServiceConfig[aiService as multiModalAIServiceKey]
+
+ if (!aiServiceInstance) {
+ throw new Error('Invalid AI service')
+ }
+
+ const instance = aiServiceInstance()
+
+ const response = await generateObject({
+ model: instance(model),
messages: [
{
role: 'system',
@@ -85,19 +113,21 @@ async function createSlideLine(
role: 'user',
content: [
{
- type: 'image_url',
- image_url: {
- url: `${imageBase64}`,
- },
+ type: 'text',
+ text: '',
+ },
+ {
+ type: 'image',
+ image: `${imageBase64}`,
},
],
},
],
- response_format: { type: 'json_object' },
+ output: 'no-schema',
+ mode: 'json',
})
- const result = JSON.parse(response.choices[0].message?.content || '{}')
- return result
+ return response.object as unknown as SlideLineResponse
}
async function handler(req: NextApiRequest, res: NextApiResponse) {
@@ -109,17 +139,17 @@ async function handler(req: NextApiRequest, res: NextApiResponse) {
return
}
+ const getField = (fieldName: string) => {
+ const field = fields[fieldName]
+ return Array.isArray(field) ? field[0] : field
+ }
+
const file = Array.isArray(files.file) ? files.file[0] : files.file
- const folderName = Array.isArray(fields.folderName)
- ? fields.folderName[0]
- : fields.folderName
- const apiKey = Array.isArray(fields.apiKey)
- ? fields.apiKey[0]
- : fields.apiKey
- const model = Array.isArray(fields.model) ? fields.model[0] : fields.model
- const selectLanguage = Array.isArray(fields.selectLanguage)
- ? fields.selectLanguage[0]
- : fields.selectLanguage
+ const folderName = getField('folderName')
+ const aiService = getField('aiService')
+ const apiKey = getField('apiKey')
+ const model = getField('model')
+ const selectLanguage = getField('selectLanguage')
if (!file) {
res.status(400).send('No file uploaded')
@@ -152,10 +182,11 @@ async function handler(req: NextApiRequest, res: NextApiResponse) {
for (let i = 0; i < images.length; i++) {
const imgBase64 = images[i]
- if (apiKey && model) {
+ if (aiService && apiKey && model) {
const slideLine = await createSlideLine(
imgBase64,
apiKey,
+ aiService,
model,
language,
previousResult
diff --git a/src/pages/api/google.ts b/src/pages/api/google.ts
deleted file mode 100644
index d0288141..00000000
--- a/src/pages/api/google.ts
+++ /dev/null
@@ -1,67 +0,0 @@
-// import { NextApiRequest, NextApiResponse } from "next";
-// import { GoogleGenerativeAI } from "@google/generative-ai";
-// import { Message } from "@/features/messages/messages";
-
-// export default async function handler(
-// req: NextApiRequest,
-// res: NextApiResponse
-// ) {
-// const { messages, apiKey, model, stream } = req.body;
-// const systemMessage = messages.find((message: any) => message.role === "system");
-// let userMessages = messages.filter((message: any) => message.role !== "system");
-
-// const genAI = new GoogleGenerativeAI(apiKey);
-// const geminiModel = genAI.getGenerativeModel({ model: "models/" + model, systemInstruction: systemMessage.content });
-
-// let filteredMessages = userMessages
-// .filter((message: Message) => message.content !== "")
-// .map((message: Message) => ({
-// role: message.role === "assistant" ? "model" : message.role,
-// parts: [{ text: message.content }],
-// }));
-
-// // 最初の要素の role が 'user' でなければ、その要素を除外
-// if (filteredMessages.length > 0 && filteredMessages[0].role !== 'user') {
-// filteredMessages = filteredMessages.slice(1);
-// }
-
-// const lastMessage = filteredMessages[filteredMessages.length - 1].parts[0].text;
-
-// if (stream) {
-// res.writeHead(200, {
-// "Content-Type": "text/event-stream",
-// "Cache-Control": "no-cache",
-// Connection: "keep-alive",
-// });
-
-// const chat = geminiModel.startChat({
-// history: filteredMessages,
-// generationConfig: {
-// maxOutputTokens: 200,
-// },
-// });
-
-// const result = await chat.sendMessageStream(lastMessage);
-
-// for await (const chunk of result.stream) {
-// const text = await chunk.text();
-// console.log(text);
-// res.write(`data: ${JSON.stringify({ text: text })}\n\n`);
-// }
-
-// res.write("event: end\n\n");
-// res.end();
-// } else {
-// const chat = await geminiModel.startChat({
-// history: filteredMessages,
-// generationConfig: {
-// maxOutputTokens: 200,
-// },
-// });
-
-// const result = await chat.sendMessage(lastMessage);
-// const response = await result.response;
-
-// res.status(200).json({ message: response.text() });
-// }
-// }
diff --git a/src/pages/api/groq.ts b/src/pages/api/groq.ts
deleted file mode 100644
index 25668202..00000000
--- a/src/pages/api/groq.ts
+++ /dev/null
@@ -1,130 +0,0 @@
-import { NextApiRequest, NextApiResponse } from 'next'
-import Groq from 'groq-sdk'
-import { Message } from '@/features/messages/messages'
-
-export default async function handler(
- req: NextApiRequest,
- res: NextApiResponse
-) {
- const { messages, apiKey, model, stream } = req.body
-
- console.log('Request body:', req.body)
-
- const client = new Groq({ apiKey })
-
- const systemMessage = messages.find(
- (message: any) => message.role === 'system'
- )
- let userMessages = messages.filter(
- (message: any) => message.role !== 'system'
- )
-
- userMessages = userMessages.filter(
- (message: Message) => message.content !== ''
- )
-
- const consolidatedMessages: Message[] = []
- let lastRole: string | null = null
- let combinedContent = ''
-
- userMessages.forEach((message: Message, index: number) => {
- if (message.role === lastRole) {
- combinedContent += '\n' + message.content
- } else {
- if (lastRole !== null) {
- consolidatedMessages.push({ role: lastRole, content: combinedContent })
- }
- lastRole = message.role
- combinedContent =
- typeof message.content === 'string'
- ? message.content
- : message.content[0].text
- }
-
- // 最後のメッセージの場合、現在の内容を追加
- if (index === userMessages.length - 1) {
- consolidatedMessages.push({ role: lastRole, content: combinedContent })
- }
- })
-
- userMessages = consolidatedMessages
-
- if (stream) {
- res.writeHead(200, {
- 'Content-Type': 'text/event-stream',
- 'Cache-Control': 'no-cache',
- Connection: 'keep-alive',
- })
-
- const stream = await client.chat.completions
- .create({
- messages: [
- { role: 'system', content: systemMessage?.content },
- ...userMessages,
- ],
- model: model,
- max_tokens: 200,
- stream: true,
- })
- .catch(async (err) => {
- if (err instanceof Groq.APIError) {
- res.write(
- `data: ${JSON.stringify({ type: 'error', error: err })}\n\n`
- )
- res.end()
- } else {
- throw err
- }
- })
-
- if (stream) {
- const reader = (
- stream as unknown as {
- getReader: () => ReadableStreamDefaultReader
- }
- ).getReader()
- const decoder = new TextDecoder('utf-8')
-
- while (true) {
- const { done, value } = await reader.read()
-
- if (done) {
- res.write(`data: ${JSON.stringify({ type: 'message_stop' })}\n\n`)
- res.end()
- break
- }
-
- const chunk = decoder.decode(value, { stream: true })
- console.log('chunk:', chunk)
- res.write(
- `data: ${JSON.stringify({ type: 'content_block_delta', text: chunk })}\n\n`
- )
- }
- }
- } else {
- const response = await client.chat.completions
- .create({
- messages: [
- { role: 'system', content: systemMessage?.content },
- ...userMessages,
- ],
- model: model,
- max_tokens: 200,
- })
- .catch(async (err) => {
- if (err instanceof Groq.APIError) {
- console.error('Groq API Error:', err)
- if (err.status) {
- res.status(err.status).json({ error: err })
- }
- } else {
- throw err
- }
- })
-
- if (response) {
- let messageContent = response.choices[0].message.content
- res.status(200).json({ message: messageContent })
- }
- }
-}
diff --git a/src/pages/api/openai.ts b/src/pages/api/openai.ts
deleted file mode 100644
index 8b58b4e2..00000000
--- a/src/pages/api/openai.ts
+++ /dev/null
@@ -1,47 +0,0 @@
-import { NextApiRequest, NextApiResponse } from 'next'
-import OpenAI from 'openai'
-import { Message } from '@/features/messages/messages'
-
-export default async function handler(
- req: NextApiRequest,
- res: NextApiResponse
-) {
- const { messages, apiKey, model, stream } = req.body
-
- const client = new OpenAI({ apiKey })
-
- if (stream) {
- res.writeHead(200, {
- 'Content-Type': 'text/event-stream',
- 'Cache-Control': 'no-cache',
- Connection: 'keep-alive',
- })
-
- const stream = await client.chat.completions.create({
- model: model,
- messages: messages,
- stream: true,
- max_tokens: 200,
- })
-
- for await (const chunk of stream) {
- const messagePiece = chunk.choices[0].delta.content
- if (messagePiece) {
- res.write(
- `data: ${JSON.stringify({ type: 'content_block_delta', text: messagePiece })}\n\n`
- )
- }
- }
-
- res.write(`data: ${JSON.stringify({ type: 'message_stop' })}\n\n`)
- res.end()
- } else {
- const response = await client.chat.completions.create({
- model: model,
- messages: messages,
- max_tokens: 200,
- })
-
- res.status(200).json({ message: response.choices[0].message.content })
- }
-}