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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,180 @@ | ||
| import { StreamingTextResponse, LangChainStream } from "ai"; | ||
| import { eq } from "drizzle-orm"; | ||
| import { db } from "@/lib/db"; | ||
| import { chats } from "@/lib/db/schema"; | ||
| import { CHAT_COMPLETION_CONTENT, ChatEntry, ChatLog } from "@/lib/types"; | ||
| import { systemPrompt } from "@/utils/prompts"; | ||
| import { | ||
| chooseModel, | ||
| jsonToLangchain, | ||
| generateTitle, | ||
| // azureOpenAiChatModel, | ||
| // OPEN_AI_MODELS, | ||
| openAIChatModel, | ||
| } from "@/utils/apiHelper"; | ||
| import { Calculator } from "langchain/tools/calculator"; | ||
| import { NextResponse } from "next/server"; | ||
| import { SerpAPI } from "langchain/tools"; | ||
| import { initializeAgentExecutorWithOptions } from "langchain/agents"; | ||
| import { BufferMemory, ChatMessageHistory } from "langchain/memory"; | ||
| const apiKey = | ||
| "1d72abd1addcda2e0cba4c2fa96279ca11af10b43a4c6e21d41ade61cccd0156"; | ||
|
|
||
| export const revalidate = 0; // disable cache | ||
|
|
||
| export async function POST( | ||
| request: Request, | ||
| params: { params: { chatid: string } }, | ||
| ) { | ||
| const body = await request.json(); | ||
|
|
||
| const _chat = body.messages; | ||
| const isFast = body.isFast || true; | ||
| let orgId = ""; | ||
| orgId = body.orgId; | ||
|
|
||
| let id = params.params.chatid as any; | ||
| // exceptional case | ||
| if (_chat.length === 0) { | ||
| console.error( | ||
| "somehow got the length 0, this shouldn't happen if validating messages length before calling the api", | ||
| ); | ||
| return; | ||
| } | ||
| const msgs = jsonToLangchain(_chat, systemPrompt); | ||
| console.log("msgs", msgs[0]); | ||
|
|
||
| const { error, model } = chooseModel(isFast, msgs, systemPrompt); | ||
|
|
||
| if (error) { | ||
| const msg = { | ||
| content: CHAT_COMPLETION_CONTENT, | ||
| role: "assistant", | ||
| }; | ||
| _chat.push(msg); // pushing the final message to identify that the chat is completed | ||
| await db | ||
| .update(chats) | ||
| .set({ | ||
| messages: JSON.stringify({ log: _chat }), | ||
| updatedAt: new Date(), | ||
| }) | ||
| .where(eq(chats.id, Number(id))) | ||
| .run(); | ||
| return NextResponse.json( | ||
| { ...msg }, | ||
| { | ||
| status: 400, | ||
| }, | ||
| ); | ||
| } | ||
|
|
||
| const { stream, handlers } = LangChainStream({ | ||
| onCompletion: async (fullResponse: string) => { | ||
| const latestReponse = { role: "assistant", content: fullResponse }; | ||
| if (orgId !== "") { | ||
| // it means it is the first message in a specific chat id | ||
| // Handling organization chat inputs | ||
| if (_chat.length === 1) { | ||
| console.log("got in 1 length case"); | ||
| _chat.push(latestReponse); | ||
| const title = await generateTitle(_chat as ChatEntry[]); | ||
| // popping up because inserted the prompt for generating the title so removing the title prompt | ||
| _chat.pop(); | ||
| console.log("generated title", title); | ||
| await db | ||
| .update(chats) | ||
| .set({ | ||
| messages: JSON.stringify({ log: _chat } as ChatLog), | ||
| title: title, | ||
| }) | ||
| .where(eq(chats.id, Number(id))) | ||
| .run(); | ||
| } else { | ||
| _chat.push(latestReponse); | ||
| await db | ||
| .update(chats) | ||
| .set({ | ||
| messages: JSON.stringify({ log: _chat }), | ||
| updatedAt: new Date(), | ||
| }) | ||
| .where(eq(chats.id, Number(id))) | ||
| .run(); | ||
| } | ||
| } | ||
| // handling user's personal chat | ||
| // else { | ||
| // // it means it is the first message in a specific chat id | ||
| // if (_chat.length === 1) { | ||
| // _chat.push(latestReponse); | ||
| // await db.insert(chats).values({ | ||
| // user_id: String(userId), | ||
| // messages: JSON.stringify({ log: _chat } as ChatLog), | ||
| // }); | ||
| // } else { | ||
| // _chat.push(latestReponse); | ||
| // await db | ||
| // .update(chats) | ||
| // .set({ messages: JSON.stringify({ log: _chat }) }) | ||
| // .where(eq(chats.id, Number(id))); | ||
| // } | ||
| // } | ||
| }, | ||
| onFinal(completion) { | ||
| console.log( | ||
| "this is the data on the completion of function call", | ||
| completion, | ||
| ); | ||
| }, | ||
| onToken(token) { | ||
| console.log("this is onToken", token); | ||
| }, | ||
| onStart() { | ||
| console.log("this is on start"); | ||
| }, | ||
| }); | ||
|
|
||
| // const azure_chat_model = azureOpenAiChatModel( | ||
| // OPEN_AI_MODELS.gptTurbo16k, | ||
| // true, | ||
| // handlers, | ||
| // ); // here it is type unsafe | ||
| const tools = [ | ||
| new SerpAPI( | ||
| apiKey, | ||
| // { | ||
| // location: "Austin,Texas,United States", | ||
| // hl: "en", | ||
| // gl: "us", | ||
| // } | ||
| ), | ||
| new Calculator(), | ||
| ]; | ||
| const openai_chat_model = openAIChatModel(model, false); | ||
| const memory = new BufferMemory({ memoryKey: "chat_history" }); | ||
| const executor = await initializeAgentExecutorWithOptions( | ||
| tools, | ||
| openai_chat_model, | ||
| { | ||
| // agentType: "chat-conversational-react-description", | ||
| agentType: "openai-functions", | ||
| memory: new BufferMemory({ | ||
| memoryKey: "chat_history", | ||
| chatHistory: new ChatMessageHistory(msgs), | ||
| returnMessages: true, | ||
| outputKey: "output", | ||
| }), | ||
| returnIntermediateSteps: true, | ||
| // verbose: true, | ||
| }, | ||
| ); | ||
|
|
||
| // const modelWithFallback = openai_chat_model.withFallbacks({ | ||
| // fallbacks: [azure_chat_model], | ||
| // }); | ||
| // modelWithFallback.invoke(msgs); | ||
| // openai_chat_model.call(msgs, { tools : [new SerpAPI(apiKey), new Calculator()] }); | ||
| const data = await executor.call({ input: msgs[msgs.length - 1].content }); | ||
| console.log("this is data", data); | ||
| console.info("info", openai_chat_model.lc_kwargs); | ||
| return new Response(JSON.stringify(data)); | ||
| } |
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