From e95a2615cc6c0fd6e54ab5fa4bfbceb71ccaa20e Mon Sep 17 00:00:00 2001 From: abhi1992002 Date: Sat, 17 Feb 2024 16:39:00 +0530 Subject: [PATCH] adding langchain output parser --- action/create-course.ts | 51 + action/create-image-query.ts | 32 + action/create-questions.ts | 59 + action/create-summary.ts | 33 + next.config.js | 3 + package-lock.json | 2630 ++++++++++++++++- package.json | 7 +- prisma/schema.prisma | 6 +- src/app/api/chapter/getInfo/route.ts | 52 +- src/app/api/course/createChapters/route.ts | 129 +- src/app/create/[courseId]/page.tsx | 3 +- src/app/create/page.tsx | 6 +- src/app/page.tsx | 3 - src/components/CreateCourseForm.tsx | 11 +- src/components/SubscriptionAction.tsx | 1 + src/components/ThemeToggle.tsx | 2 +- .../background/background.module.css | 11 - src/components/background/page.tsx | 13 - src/components/home/hero.tsx | 6 +- src/components/ui/navbar.tsx | 8 +- src/lib/gpt.ts | 149 - src/lib/youtube.ts | 61 +- src/validators/course.ts | 8 + 23 files changed, 2878 insertions(+), 406 deletions(-) create mode 100644 action/create-course.ts create mode 100644 action/create-image-query.ts create mode 100644 action/create-questions.ts create mode 100644 action/create-summary.ts delete mode 100644 src/components/background/background.module.css delete mode 100644 src/components/background/page.tsx delete mode 100644 src/lib/gpt.ts diff --git a/action/create-course.ts b/action/create-course.ts new file mode 100644 index 0000000..7cdb1c3 --- /dev/null +++ b/action/create-course.ts @@ -0,0 +1,51 @@ +"use server"; +import { OpenAI } from "@langchain/openai"; +import { RunnableSequence } from "@langchain/core/runnables"; +import { StructuredOutputParser } from "langchain/output_parsers"; +import { PromptTemplate } from "@langchain/core/prompts"; + +export const createCourse = async ({ + unit, + title, +}: { + unit: string; + title: string; +}) => { + try { + const parser = StructuredOutputParser.fromNamesAndDescriptions({ + chapter_title: "one chapter in the unit", + youtube_search_query: + "best youtube query for the chapter_title so he can confirm his concepts", + }); + + const chain = RunnableSequence.from([ + PromptTemplate.fromTemplate( + "Answer the users question as best as possible.\n{format_instructions}\n{question}" + ), + new OpenAI({ temperature: 0 }), + parser, + ]); + + const request1 = chain.invoke({ + question: `The title of course is ${title}, It has a unit named ${unit}. I want to create a chapter which tell about the basics of the unit , so name chapter accordingly`, + format_instructions: parser.getFormatInstructions(), + }); + + const request2 = chain.invoke({ + question: `The title of course is ${title}, It has a unit named ${unit}. I want to create a chapter which tell about the intermediate stuff of the unit , so name chapter accordingly`, + format_instructions: parser.getFormatInstructions(), + }); + + const request3 = chain.invoke({ + question: `The title of course is ${title}, It has a unit named ${unit}. I want to create a chapter which tell about the advance stuff of the unit , so name chapter accordingly`, + format_instructions: parser.getFormatInstructions(), + }); + + const courses = await Promise.all([request1, request2, request3]); + + return { success: "success", courses: courses }; + } catch (error) { + console.log(error); + return { error: error }; + } +}; diff --git a/action/create-image-query.ts b/action/create-image-query.ts new file mode 100644 index 0000000..14a85f8 --- /dev/null +++ b/action/create-image-query.ts @@ -0,0 +1,32 @@ +"use server"; +import { RunnableSequence } from "@langchain/core/runnables"; +import { StructuredOutputParser } from "langchain/output_parsers"; +import { PromptTemplate } from "@langchain/core/prompts"; +import { OpenAI } from "@langchain/openai"; + +export const createImageQuery = async ({ title }: { title: string }) => { + try { + const parser = StructuredOutputParser.fromNamesAndDescriptions({ + image_url: + "image url which suited my title and i can search it on unsplash", + }); + + const chain = RunnableSequence.from([ + PromptTemplate.fromTemplate( + "Answer the users question as best as possible.\n{format_instructions}\n{question}" + ), + new OpenAI({ temperature: 0 }), + parser, + ]); + + const request = await chain.invoke({ + question: `create image for the titlr : ${title}`, + format_instructions: parser.getFormatInstructions(), + }); + + return { success: "success", image: request }; + } catch (error) { + console.log(error); + return { error: error }; + } +}; diff --git a/action/create-questions.ts b/action/create-questions.ts new file mode 100644 index 0000000..137367f --- /dev/null +++ b/action/create-questions.ts @@ -0,0 +1,59 @@ +"use server"; +import { RunnableSequence } from "@langchain/core/runnables"; +import { StructuredOutputParser } from "langchain/output_parsers"; +import { PromptTemplate } from "@langchain/core/prompts"; +import { OpenAI } from "@langchain/openai"; + +export const createQuestion = async ({ + transcript, + segment, +}: { + transcript: string; + segment: "first" | "second" | "third" | "fourth"; +}) => { + try { + const parser = StructuredOutputParser.fromNamesAndDescriptions({ + question: + "relevant question for this chapter , create 4 option , out of which one is corrct and all other is wrong and put those into below keys ", + answer: "1st option , and this is right answer", + option1: "2nd option , and this option is wrong", + option2: "3rd option , and this option is wrong", + option3: "4th option , and this option is wrong", + }); + + const segmentLength = Math.floor(transcript.length / 4); + let segmentText = ""; + switch (segment) { + case "first": + segmentText = transcript.slice(0, segmentLength); + break; + case "second": + segmentText = transcript.slice(segmentLength, 2 * segmentLength); + break; + case "third": + segmentText = transcript.slice(2 * segmentLength, 3 * segmentLength); + break; + case "fourth": + segmentText = transcript.slice(3 * segmentLength); + break; + } + + const chain = RunnableSequence.from([ + PromptTemplate.fromTemplate( + "Answer the users question as best as possible.\n{format_instructions}\n{question}" + ), + new OpenAI({ temperature: 0, modelName: "gpt-3.5-turbo-1106" }), + parser, + ]); + + const request = await chain.invoke({ + question: `Create a question and answer object with 4 options out of which one is correct. The topic is based on the following content segment: ${segmentText}`, + format_instructions: parser.getFormatInstructions(), + }); + + return { success: "success", questions: request }; + } catch (error) { + console.log(error); + return { error: error }; + } +}; diff --git a/action/create-summary.ts b/action/create-summary.ts new file mode 100644 index 0000000..e84c34e --- /dev/null +++ b/action/create-summary.ts @@ -0,0 +1,33 @@ +"use server"; +import { RunnableSequence } from "@langchain/core/runnables"; +import { StructuredOutputParser } from "langchain/output_parsers"; +import { PromptTemplate } from "@langchain/core/prompts"; +import { OpenAI } from "@langchain/openai"; + +export const createSummary = async ({ transcript }: { transcript: string }) => { + try { + const parser = StructuredOutputParser.fromNamesAndDescriptions({ + summary: "a crisp summary of transcript that i will provide", + }); + + const chain = RunnableSequence.from([ + PromptTemplate.fromTemplate( + "Answer the users question as best as possible.\n{format_instructions}\n{question}" + ), + new OpenAI({ temperature: 0, modelName: "gpt-3.5-turbo-1106" }), + parser, + ]); + + const request = await chain.invoke({ + question: `Create summary of youtube transcript in less than 300 words. Do not talk of sponsor or anything unrealted to main topic , also do not introduce what the summary is about.\n${transcript}`, + format_instructions: parser.getFormatInstructions(), + }); + + console.log(request); + + return { success: "success", summary: request }; + } catch (error) { + console.log(error); + return { error: error }; + } +}; diff --git a/next.config.js b/next.config.js index 01a160e..56db9ac 100644 --- a/next.config.js +++ b/next.config.js @@ -13,6 +13,9 @@ const nextConfig = { typescript: { ignoreBuildErrors: true, }, + experimental: { + serverActions: true, + }, output: "standalone", }; diff --git a/package-lock.json b/package-lock.json index 8c2b46b..a108518 100644 --- a/package-lock.json +++ b/package-lock.json @@ -8,7 +8,9 @@ "name": "course", "version": "0.1.0", "dependencies": { + "@google/generative-ai": "^0.2.1", "@hookform/resolvers": "^3.3.1", + "@langchain/openai": "^0.0.14", "@next-auth/prisma-adapter": "^1.0.7", "@next/bundle-analyzer": "^13.5.4", "@nextui-org/react": "^2.1.13", @@ -27,18 +29,20 @@ "@types/node": "20.6.0", "@types/react": "18.2.21", "@types/react-dom": "18.2.7", + "ai": "^2.2.35", "autoprefixer": "10.4.15", "axios": "^1.5.0", "class-variance-authority": "^0.7.0", "clsx": "^2.0.0", "framer": "^2.4.1", "framer-motion": "^10.16.4", + "langchain": "^0.1.19", "lucide-react": "^0.274.0", "motion": "^10.16.2", "next": "13.4.19", "next-auth": "^4.23.1", "next-themes": "^0.2.1", - "openai": "^3.3.0", + "openai": "^4.28.0", "postcss": "8.4.29", "react": "18.2.0", "react-dom": "18.2.0", @@ -51,6 +55,7 @@ "tailwindcss": "3.3.3", "tailwindcss-animate": "^1.0.7", "typescript": "5.2.2", + "uuid": "^9.0.1", "youtube-transcript": "^1.0.6", "zod": "^3.22.2" }, @@ -69,6 +74,55 @@ "url": "https://github.com/sponsors/sindresorhus" } }, + "node_modules/@ampproject/remapping": { + "version": "2.2.1", + "resolved": "https://registry.npmjs.org/@ampproject/remapping/-/remapping-2.2.1.tgz", + "integrity": 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"sha512-iC+8Io04lddc+mVqQ9AZ7OQ2MrUKGN+oIQyq1vemgt46jwCwLfhq7/pwnBnNXXXZb8VTVLKwp9EDkx+ryxIWmg==" + }, + "zod-to-json-schema": { + "version": "3.22.4", + "resolved": "https://registry.npmjs.org/zod-to-json-schema/-/zod-to-json-schema-3.22.4.tgz", + "integrity": "sha512-2Ed5dJ+n/O3cU383xSY28cuVi0BCQhF8nYqWU5paEpl7fVdqdAmiLdqLyfblbNdfOFwFfi/mqU4O1pwc60iBhQ==", + "requires": {} } } } diff --git a/package.json b/package.json index 36a8a0a..1527469 100644 --- a/package.json +++ b/package.json @@ -9,7 +9,9 @@ "lint": "next lint" }, "dependencies": { + "@google/generative-ai": "^0.2.1", "@hookform/resolvers": "^3.3.1", + "@langchain/openai": "^0.0.14", "@next-auth/prisma-adapter": "^1.0.7", "@next/bundle-analyzer": "^13.5.4", "@nextui-org/react": "^2.1.13", @@ -28,18 +30,20 @@ "@types/node": "20.6.0", "@types/react": "18.2.21", "@types/react-dom": "18.2.7", + "ai": "^2.2.35", "autoprefixer": "10.4.15", "axios": "^1.5.0", "class-variance-authority": "^0.7.0", "clsx": "^2.0.0", "framer": "^2.4.1", "framer-motion": "^10.16.4", + "langchain": "^0.1.19", "lucide-react": "^0.274.0", "motion": "^10.16.2", "next": "13.4.19", "next-auth": "^4.23.1", "next-themes": "^0.2.1", - "openai": "^3.3.0", + "openai": "^4.28.0", "postcss": "8.4.29", "react": "18.2.0", "react-dom": "18.2.0", @@ -52,6 +56,7 @@ "tailwindcss": "3.3.3", "tailwindcss-animate": "^1.0.7", "typescript": "5.2.2", + "uuid": "^9.0.1", "youtube-transcript": "^1.0.6", "zod": "^3.22.2" }, diff --git a/prisma/schema.prisma b/prisma/schema.prisma index c2f749c..a215ed7 100644 --- a/prisma/schema.prisma +++ b/prisma/schema.prisma @@ -6,9 +6,9 @@ generator client { } datasource db { - provider = "mysql" - url = env("DATABASE_URL") - relationMode = "prisma" + provider = "postgresql" + url = env("DATABASE_URL") + directUrl = env("DIRECT_URL") } model Account { diff --git a/src/app/api/chapter/getInfo/route.ts b/src/app/api/chapter/getInfo/route.ts index d5dc97a..77a0349 100644 --- a/src/app/api/chapter/getInfo/route.ts +++ b/src/app/api/chapter/getInfo/route.ts @@ -1,14 +1,11 @@ // /api/chapter/getInfo import { prisma } from "@/lib/db"; -import { strict_output } from "@/lib/gpt"; -import { - getQuestionFromTranscript, - getTranscript, - searchYoutube, -} from "@/lib/youtube"; +import { getTranscript, searchYoutube } from "@/lib/youtube"; import { NextResponse } from "next/server"; import { z } from "zod"; +import { createSummary } from "../../../../../action/create-summary"; +import { createQuestion } from "../../../../../action/create-questions"; const bodyParser = z.object({ chapterId: z.string(), @@ -41,38 +38,33 @@ export async function POST(req: Request) { const videoId = await searchYoutube(chapter.youtubeSearchQuery); let transcript = await getTranscript(videoId); - const maxLength = 500; - transcript = transcript - .split(" ") - .slice(0, maxLength) - .join(" "); - const { summary }: { summary: string } = await strict_output( - "you are an AI capable of summarising a youtube transcript", - `summarize in 250 words or less and do not talk of sponsor or anything unrealted to main topic , also do not introduce what the summary is about.\n${transcript}`, - { - summary: "Summary of the transcript", - } - ); + const { summary } = await createSummary({ transcript }); - console.log(summary, "summary"); + const question1Promise = createQuestion({ transcript, segment: "first" }); + const question2Promise = createQuestion({ transcript, segment: "second" }); + const question3Promise = createQuestion({ transcript, segment: "third" }); + const question4Promise = createQuestion({ transcript, segment: "fourth" }); - const questions = await getQuestionFromTranscript(transcript, chapter.name); - - console.log(questions, "question"); + const questions = await Promise.all([ + question1Promise, + question2Promise, + question3Promise, + question4Promise, + ]); await prisma.question.createMany({ data: questions.map((question) => { const options = [ - question.answer, - question.option1, - question.option2, - question.option3, + question.questions?.answer, + question.questions?.option1, + question.questions?.option2, + question.questions?.option3, ]; options.sort(() => Math.random() - 0.5); return { - question: question.question, - answer: question.answer, + question: question.questions?.question!, + answer: question.questions?.answer!, options: JSON.stringify(options), chapterId, }; @@ -85,7 +77,7 @@ export async function POST(req: Request) { }, data: { videoId, - summary, + summary: summary?.summary, }, }); @@ -102,8 +94,6 @@ export async function POST(req: Request) { } ); } - - // console.log(error) return NextResponse.json( { success: false, diff --git a/src/app/api/course/createChapters/route.ts b/src/app/api/course/createChapters/route.ts index b6c205b..3b16cfc 100644 --- a/src/app/api/course/createChapters/route.ts +++ b/src/app/api/course/createChapters/route.ts @@ -1,13 +1,19 @@ // /api/couse/createChapters import { NextResponse } from "next/server"; -import { createChaptersSchema } from "@/validators/course"; +import { MutationTypeSchema, createChaptersSchema } from "@/validators/course"; import { ZodError } from "zod"; -import { strict_output } from "@/lib/gpt"; import { getUnsplashImage } from "@/lib/unsplash"; import { prisma } from "@/lib/db"; import { getAuthSession } from "@/lib/auth"; import { checkSubscription } from "@/lib/subscription"; +import { createCourse } from "../../../../../action/create-course"; +import { createImageQuery } from "../../../../../action/create-image-query"; + +type CourseType = { + chapter_title: string; + youtube_search_query: string; +}[]; export async function POST(req: Request) { try { @@ -23,88 +29,68 @@ export async function POST(req: Request) { const body = await req.json(); const { title, units } = createChaptersSchema.parse(body); - // we use title and units in openAI api to get below outputUnits - // sometime gpt gives invalid json , so it can break our code , so we hace strictJSON library , which can help us i checkingin json and when gpt send us wrong json , we send request again until we get the right json - // https://github.com/tanchongmin/strictjson/tree/main - type outputUnits = { - title: string; - chapters: { - youtube_search_query: string; - chapter_title: string; - }[]; - }[]; - - // we are using strict json gpt framework , we need give its input and it will generate my expected json for me - // go to gpt.ts to check all input functionality - const output_units: outputUnits = await strict_output( - "you are an ai capable of curating course content , coming up with relevant chapter titles, and finding relevant youtube videos for each chapter", - - // chat gpt will create 3 json for this - new Array(units.length).fill( - `its your job to create a course about ${title}. The user has requested to create chapters for each of the units. Then for each chapter, provide a detailed youtube search query that can be used to find informative educational video for each chapter. Each query should give a educational informative course in youtube` - ), - - // each json have this type of thing - { - // it means output object must have title with description - title: "title of the unit", - chapters: - "an array of chapters, each chapters should have a youtube search query and a chapter_title key in the json object", - } + const createCoursePromise = units.map((unit) => + createCourse({ unit: unit, title: title }) ); + type Chapter = { + [x: string]: string; + }; - console.log("creating title and units from chatGPT", output_units); - - // searching for photos of title of course - const imageSearchTerm = await strict_output( - "you are an ai capable of finding the most relevant image for a course", - `please provide a good image search term for the title of a course about ${title}.this search term will be fed into the unsplash api so make sure that this is a good search term that will return good results`, - { - image_search_term: "a good search term for the title of the course", - } - ); - - console.log("getting image_search_term from chatGPT", imageSearchTerm); - - // getting image from unspash using above search term - const course_image = await getUnsplashImage( - imageSearchTerm.image_search_term - ); + const { image } = await createImageQuery({ title }); - console.log( - "getting image using image_search_term from unsplash", - course_image - ); + const course_image = await getUnsplashImage(image?.image_url as string); const course = await prisma.course.create({ data: { name: title, - image: course_image, + image: course_image!, }, }); - console.log("adding course in database", course); - - for (const unit of output_units) { - const { title } = unit; + const response = await Promise.all(createCoursePromise); - const prismaUnit = await prisma.unit.create({ + units.forEach(async (unit, unitIndex) => { + const unitdb = await prisma.unit.create({ data: { - name: title, + name: unit, courseId: course.id, }, }); + console.log(response[unitIndex].courses?.[2]?.[0]); + await prisma.chapter.createMany({ - data: unit.chapters.map((chapter) => ({ - name: chapter.chapter_title, - youtubeSearchQuery: chapter.youtube_search_query, - unitId: prismaUnit.id, - })), + data: [ + { + name: + response[unitIndex].courses?.[0].chapter_title || + response[unitIndex].courses?.[0]?.[0]!, + youtubeSearchQuery: + response[unitIndex].courses?.[0].youtube_search_query || + response[unitIndex].courses?.[0]?.[1]!, + unitId: unitdb.id, + }, + { + name: + response[unitIndex].courses?.[1].chapter_title || + response[unitIndex].courses?.[1]?.[0]!, + youtubeSearchQuery: + response[unitIndex].courses?.[1].youtube_search_query || + response[unitIndex].courses?.[1]?.[1]!, + unitId: unitdb.id, + }, + { + name: + response[unitIndex].courses?.[2].chapter_title || + response[unitIndex].courses?.[2]?.[0]!, + youtubeSearchQuery: + response[unitIndex].courses?.[2].youtube_search_query || + response[unitIndex].courses?.[2]?.[1]!, + unitId: unitdb.id, + }, + ], }); - } - - console.log("adding units and title in database"); + }); await prisma.user.update({ where: { @@ -117,14 +103,17 @@ export async function POST(req: Request) { }, }); - console.log("updating credits of user"); - - return NextResponse.json({ course_id: course.id }); + return NextResponse.json({ + success: "Course created successfully", + courseId: course.id, + }); } catch (error) { if (error instanceof ZodError) { return new NextResponse("invalid body", { status: 400 }); } - return new NextResponse("Internal server error", { status: 500 }); + return new NextResponse("Getting some error, Please try again", { + status: 500, + }); } } diff --git a/src/app/create/[courseId]/page.tsx b/src/app/create/[courseId]/page.tsx index 3246c9a..822a6e2 100644 --- a/src/app/create/[courseId]/page.tsx +++ b/src/app/create/[courseId]/page.tsx @@ -3,7 +3,7 @@ import { getAuthSession } from "@/lib/auth"; import { prisma } from "@/lib/db"; import { Info } from "lucide-react"; import { redirect } from "next/navigation"; -import React, { useEffect, useState } from "react"; +import React from "react"; type CreateChaptersProps = { params: { @@ -39,7 +39,6 @@ const CreateChapters = async ({ return ( <> - {/* 
{JSON.stringify(course,null,2)}
*/}
Course Name diff --git a/src/app/create/page.tsx b/src/app/create/page.tsx index b5ef221..ae707ae 100644 --- a/src/app/create/page.tsx +++ b/src/app/create/page.tsx @@ -1,5 +1,4 @@ import { CreateCourseForm } from "@/components/CreateCourseForm"; -import Background from "@/components/background/page"; import { getAuthSession } from "@/lib/auth"; import { checkSubscription } from "@/lib/subscription"; @@ -19,7 +18,6 @@ const CreatePage = async ({}: CreatePageProps) => { return ( <> -

Create Course Using AI @@ -28,11 +26,11 @@ const CreatePage = async ({}: CreatePageProps) => {
- {/*
+
Enter in a course title , or what you want to larn about . Then enter a list of units, which are the specifics you want to learn. And our AI will generate a course for you -
*/} +
diff --git a/src/app/page.tsx b/src/app/page.tsx index 7cbd602..e58f3f4 100644 --- a/src/app/page.tsx +++ b/src/app/page.tsx @@ -1,5 +1,3 @@ -import Background from "@/components/background/page"; - import { HeroPage } from "@/components/home/hero"; import { MarqueeClient } from "@/components/home/marquee"; import { Footer } from "@/components/home/footer"; @@ -20,7 +18,6 @@ export default function Home() { return (
<> - diff --git a/src/components/CreateCourseForm.tsx b/src/components/CreateCourseForm.tsx index c1fcdfd..17538f9 100644 --- a/src/components/CreateCourseForm.tsx +++ b/src/components/CreateCourseForm.tsx @@ -1,6 +1,6 @@ "use client"; -import React from "react"; +import React, { useState } from "react"; import { z } from "zod"; import { createChaptersSchema } from "@/validators/course"; import { useForm } from "react-hook-form"; @@ -18,6 +18,8 @@ import { Form, FormControl, FormField, FormItem, FormLabel } from "./ui/form"; import SubscriptionAction from "./SubscriptionAction"; import { useRecoilState, useSetRecoilState } from "recoil"; import { loadingState } from "@/state/loading"; +import { v4 as uuidv4 } from "uuid"; +import { useChat } from "ai/react"; type CreateCourseFormProps = { isPro: boolean; @@ -67,15 +69,14 @@ export function CreateCourseForm({ isPro }: CreateCourseFormProps) { variant: "destructive", }); } - setLoading(true); - // whe we call createChapters => it hit the endpoint createChapters(data, { - onSuccess: ({ course_id }) => { + onSuccess: ({ courseId }) => { toast({ title: "success", description: "course creates successfully", }); - router.push(`/create/${course_id}`); + + router.push(`/create/${courseId}`); }, onError: (error) => { console.log(error); diff --git a/src/components/SubscriptionAction.tsx b/src/components/SubscriptionAction.tsx index 51a6452..d5bc792 100644 --- a/src/components/SubscriptionAction.tsx +++ b/src/components/SubscriptionAction.tsx @@ -28,6 +28,7 @@ function SubscriptionAction({}: SubscriptionActionProps) {
{data?.user.credits} / 10 Free Generation diff --git a/src/components/ThemeToggle.tsx b/src/components/ThemeToggle.tsx index 70f0c78..fdb3b9f 100644 --- a/src/components/ThemeToggle.tsx +++ b/src/components/ThemeToggle.tsx @@ -24,7 +24,7 @@ export function ThemeToggle({
-

Unlock the Future of Learning with AI-Powered Courses. Experience Personalized Learning like Never Before. Join us on a journey of diff --git a/src/components/ui/navbar.tsx b/src/components/ui/navbar.tsx index 3b4cb2d..8ed77f1 100644 --- a/src/components/ui/navbar.tsx +++ b/src/components/ui/navbar.tsx @@ -42,17 +42,19 @@ export function NavbarComponent({ session }: NavbarComponentProps) { {session?.user && ( <> - + Create-course - Settings + + Settings + )} - + Gallery diff --git a/src/lib/gpt.ts b/src/lib/gpt.ts deleted file mode 100644 index bb6effe..0000000 --- a/src/lib/gpt.ts +++ /dev/null @@ -1,149 +0,0 @@ -// gpt api with strict json -// we need to know how this works => firstly we need to tell what type of json we need , otherwise it requests again and again - -import { Configuration, OpenAIApi } from "openai"; - -const configuration = new Configuration({ - apiKey: process.env.OPENAI_API_KEY, -}); -const openai = new OpenAIApi(configuration); - -interface OutputFormat { - [key: string]: string | string[] | OutputFormat; -} - -export async function strict_output( - system_prompt: string, // to tell the role of ai - user_prompt: string | string[], // prompt => it can be multiple string - output_format: OutputFormat, // output json that you want - default_category: string = "", - output_value_only: boolean = false, - model: string = "gpt-3.5-turbo", - temperature: number = 1, - num_tries: number = 3, - verbose: boolean = false -) { - // if the user input is in a list, we also process the output as a list of json - const list_input: boolean = Array.isArray(user_prompt); - // if the output format contains dynamic elements of < or >, then add to the prompt to handle dynamic elements - const dynamic_elements: boolean = /<.*?>/.test(JSON.stringify(output_format)); - // if the output format contains list elements of [ or ], then we add to the prompt to handle lists - const list_output: boolean = /\[.*?\]/.test(JSON.stringify(output_format)); - - // start off with no error message - let error_msg: string = ""; - - for (let i = 0; i < num_tries; i++) { - let output_format_prompt: string = `\nYou are to output ${list_output && - "an array of objects in"} the following in json format: ${JSON.stringify( - output_format - )}. \nDo not put quotation marks or escape character \\ in the output fields.`; - - if (list_output) { - output_format_prompt += - "\nIf output field is a list, classify output into the best element of the list."; - } - - // if output_format contains dynamic elements, process it accordingly - if (dynamic_elements) { - output_format_prompt += - "\nAny text enclosed by < and > indicates you must generate content to replace it. Example input: Go to , Example output: Go to the garden\nAny output key containing < and > indicates you must generate the key name to replace it. Example input: {'': 'description of location'}, Example output: {school: a place for education}"; - } - - // if input is in a list format, ask it to generate json in a list - if (list_input) { - output_format_prompt += - "\nGenerate an array of json, one json for each input element."; - } - - // Use OpenAI to get a response - const response = await openai.createChatCompletion({ - temperature, - model, - messages: [ - { - role: "system", - content: system_prompt + output_format_prompt + error_msg, - }, - { role: "user", content: user_prompt.toString() }, - ], - }); - - let res: string = - response.data.choices[0].message?.content?.replace(/'/g, '"') ?? ""; - - // ensure that we don't replace away apostrophes in text - res = res.replace(/(\w)"(\w)/g, "$1'$2"); - - if (verbose) { - console.log( - "System prompt:", - system_prompt + output_format_prompt + error_msg - ); - console.log("\nUser prompt:", user_prompt); - console.log("\nGPT response:", res); - } - - // try-catch block to ensure output format is adhered to - try { - let output: any = JSON.parse(res); - - if (list_input) { - if (!Array.isArray(output)) { - throw new Error("Output format not in an array of json"); - } - } else { - output = [output]; - } - - // check for each element in the output_list, the format is correctly adhered to - for (let index = 0; index < output.length; index++) { - for (const key in output_format) { - // unable to ensure accuracy of dynamic output header, so skip it - if (/<.*?>/.test(key)) { - continue; - } - - // if output field missing, raise an error - if (!(key in output[index])) { - throw new Error(`${key} not in json output`); - } - - // check that one of the choices given for the list of words is an unknown - if (Array.isArray(output_format[key])) { - const choices = output_format[key] as string[]; - // ensure output is not a list - if (Array.isArray(output[index][key])) { - output[index][key] = output[index][key][0]; - } - // output the default category (if any) if GPT is unable to identify the category - if (!choices.includes(output[index][key]) && default_category) { - output[index][key] = default_category; - } - // if the output is a description format, get only the label - if (output[index][key].includes(":")) { - output[index][key] = output[index][key].split(":")[0]; - } - } - } - - // if we just want the values for the outputs - if (output_value_only) { - output[index] = Object.values(output[index]); - // just output without the list if there is only one element - if (output[index].length === 1) { - output[index] = output[index][0]; - } - } - } - - return list_input ? output : output[0]; - } catch (e) { - error_msg = `\n\nResult: ${res}\n\nError message: ${e}`; - console.log("An exception occurred:", e); - console.log("Current invalid json format ", res); - } - } - - return []; -} diff --git a/src/lib/youtube.ts b/src/lib/youtube.ts index 02a9c2a..fdb9810 100644 --- a/src/lib/youtube.ts +++ b/src/lib/youtube.ts @@ -1,10 +1,7 @@ import axios from "axios"; import { YoutubeTranscript } from "youtube-transcript"; -import { strict_output } from "./gpt"; export async function searchYoutube(searchQuery: string) { - // hello world => hello=world - searchQuery = encodeURIComponent(searchQuery); const { data } = await axios.get( @@ -21,8 +18,6 @@ export async function searchYoutube(searchQuery: string) { return null; } - console.log(data.items[0].id.videoId); - return data.items[0].id.videoId; } @@ -46,31 +41,31 @@ export async function getTranscript(videoId: string) { } } -export async function getQuestionFromTranscript( - transcript: string, - course_title: string -) { - type Question = { - question: string; - answer: string; - option1: string; - option2: string; - option3: string; - }[]; - console.log("question"); - const question: Question = await strict_output( - "you are an helpful AI thar is able to generate mcq question and answers, the length of each answer should not be more than 15 words", - new Array(5).fill( - `you are to generate a random hard mcq question about the ${course_title} with the context of the following transcript: ${transcript}` - ), - { - question: "question", - answer: "answer with max length of 15 words", - option1: "option2 with max length of 15 words", - option2: "option3 with max length of 15 words", - option3: "option4 with max length of 15 words", - } - ); - console.log(question, "question"); - return question; -} +// export async function getQuestionFromTranscript( +// transcript: string, +// course_title: string +// ) { +// type Question = { +// question: string; +// answer: string; +// option1: string; +// option2: string; +// option3: string; +// }[]; +// console.log("question"); +// const question: Question = await strict_output( +// "you are an helpful AI thar is able to generate mcq question and answers, the length of each answer should not be more than 15 words", +// new Array(5).fill( +// `you are to generate a random hard mcq question about the ${course_title} with the context of the following transcript: ${transcript}` +// ), +// { +// question: "question", +// answer: "answer with max length of 15 words", +// option1: "option2 with max length of 15 words", +// option2: "option3 with max length of 15 words", +// option3: "option4 with max length of 15 words", +// } +// ); +// console.log(question, "question"); +// return question; +// } diff --git a/src/validators/course.ts b/src/validators/course.ts index 95ac4f9..7e57310 100644 --- a/src/validators/course.ts +++ b/src/validators/course.ts @@ -7,3 +7,11 @@ export const createChaptersSchema = z.object({ .max(100), units: z.array(z.string()), }); +export const MutationTypeSchema = z.object({ + id: z.string(), + title: z + .string() + .min(3) + .max(100), + units: z.array(z.string()), +});