├── .env.example
├── .eslintrc.json
├── .gitignore
├── .npmrc
├── .nvmrc
├── .prettierrc
├── README.md
├── README_ko.md
├── components
    ├── layout.tsx
    └── ui
    │   ├── LoadingDots.tsx
    │   ├── TextArea.tsx
    │   └── accordion.tsx
├── config
    └── chroma.ts
├── declarations
    └── pdf-parse.d.ts
├── docs
    └── .keep
├── faiss-store
    └── .keep
├── next.config.js
├── package-lock.json
├── package.json
├── pages
    ├── _app.tsx
    ├── _document.tsx
    ├── api
    │   └── chat.ts
    └── index.tsx
├── postcss.config.cjs
├── public
    ├── bot-image.png
    ├── favicon.ico
    └── usericon.png
├── scripts
    └── ingest-data.ts
├── styles
    ├── Home.module.css
    ├── base.css
    ├── chrome-bug.css
    └── loading-dots.module.css
├── tailwind.config.cjs
├── tsconfig.json
├── types
    └── chat.ts
├── utils
    ├── cn.ts
    ├── customPDFLoader.ts
    └── makechain.ts
└── visual-guide
    └── gpt-langchain-pdf.png


/.env.example:
--------------------------------------------------------------------------------
1 | OPENAI_API_KEY=
2 | OPENAI_CHAT_MODEL=gpt-3.5-turbo
3 | ANSWER_LANGUAGE=en-US
4 | 


--------------------------------------------------------------------------------
/.eslintrc.json:
--------------------------------------------------------------------------------
1 | {
2 |   "extends": "next/core-web-vitals"
3 | }
4 | 


--------------------------------------------------------------------------------
/.gitignore:
--------------------------------------------------------------------------------
 1 | # See https://help.github.com/articles/ignoring-files/ for more about ignoring files.
 2 | 
 3 | # dependencies
 4 | /node_modules
 5 | /.pnp
 6 | .pnp.js
 7 | 
 8 | # testing
 9 | /coverage
10 | 
11 | # next.js
12 | /.next/
13 | /out/
14 | 
15 | # production
16 | /build
17 | 
18 | # misc
19 | .DS_Store
20 | *.pem
21 | 
22 | # debug
23 | npm-debug.log*
24 | yarn-debug.log*
25 | yarn-error.log*
26 | .pnpm-debug.log*
27 | 
28 | # local env files
29 | .env*.local
30 | .env
31 | 
32 | # vercel
33 | .vercel
34 | 
35 | # typescript
36 | *.tsbuildinfo
37 | next-env.d.ts
38 | 
39 | #Notion_db
40 | /Notion_DB
41 | 
42 | #docs and store
43 | /docs/
44 | /faiss-store/


--------------------------------------------------------------------------------
/.npmrc:
--------------------------------------------------------------------------------
1 | engine-strict=true


--------------------------------------------------------------------------------
/.nvmrc:
--------------------------------------------------------------------------------
1 | 18
2 | 


--------------------------------------------------------------------------------
/.prettierrc:
--------------------------------------------------------------------------------
1 | {
2 |   "trailingComma": "all",
3 |   "singleQuote": true,
4 |   "printWidth": 80,
5 |   "tabWidth": 2
6 | }
7 | 


--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
 1 | # Create a ChatGPT Chatbot for Your CSV, TXT, PDF Files
 2 | 
 3 | [English](README.md) | [한국어](README_ko.md)
 4 | 
 5 | Use the new GPT-4 api to build a chatGPT chatbot for multiple Large PDF, CSV, TET files.
 6 | 
 7 | Tech stack used includes LangChain, Faiss, Typescript, Openai, and Next.js. LangChain is a framework that makes it easier to build scalable AI/LLM apps and chatbots. Faiss is a vectorstore for storing embeddings and your PDF in text to later retrieve similar docs.
 8 | 
 9 | [Tutorial video](https://www.youtube.com/watch?v=ih9PBGVVOO4)
10 | 
11 | [Join the discord if you have questions](https://discord.gg/E4Mc77qwjm)
12 | 
13 | The visual guide of this repo and tutorial is in the `visual guide` folder.
14 | 
15 | **If you run into errors, please review the troubleshooting section further down this page.**
16 | 
17 | Prelude: Please make sure you have already downloaded node on your system and the version is 18 or greater.
18 | 
19 | ## Development
20 | 
21 | 1. Install [Docker Desktop](https://www.docker.com/products/docker-desktop/) for your platform.
22 | 
23 | 2. Clone the repo or download the ZIP
24 | 
25 | ```
26 | git clone [github https url]
27 | ```
28 | 
29 | 3. Install packages
30 | 
31 | First run `npm install yarn -g` to install yarn globally (if you haven't already).
32 | 
33 | Then run:
34 | 
35 | ```
36 | yarn install
37 | ```
38 | 
39 | After installation, you should now see a `node_modules` folder.
40 | 
41 | 4. Set up your `.env` file
42 | 
43 | - Copy `.env.example` into `.env`
44 |   Your `.env` file should look like this:
45 | 
46 | ```
47 | OPENAI_API_KEY=
48 | OPENAI_CHAT_MODEL=
49 | ANSWER_LANGUAGE=
50 | ```
51 | 
52 | - Visit [openai](https://help.openai.com/en/articles/4936850-where-do-i-find-my-secret-api-key) to retrieve API keys and insert into your `.env` file.
53 | - If you want to use gpt-4, write gpt-4 in OPENAI_CHAT_MODEL. (default: gpt-3.5-turbo)
54 | - For ANSWER_LANGUAGE, enter the language you want ChatGPT to answer in. (default: English)
55 | 
56 | 5. In `utils/makechain.ts` chain change the `QA_PROMPT` for your own usecase. Change `modelName` in `new OpenAI` to `gpt-4`, if you have access to `gpt-4` api. Please verify outside this repo that you have access to `gpt-4` api, otherwise the application will not work.
57 | 
58 | ## Convert your PDF, CSV, TXT files to embeddings
59 | 
60 | **This repo can load multiple PDF files**
61 | 
62 | 1. Inside `docs` folder, add your pdf, csv, txt files or folders that contain files.
63 | 
64 | 2. Run the script `npm run ingest` to 'ingest' and embed your docs. If you run into errors troubleshoot below.
65 | 
66 | 3. Verify that the docstore.json and faiss.index files are successfully created in the `faiss-store` folder.
67 | 
68 | ## Run the app
69 | 
70 | Once you've verified that the embeddings and content have been successfully added to your faiss store, you can run the app `npm run dev` to launch the local dev environment, and then type a question in the chat interface.
71 | 
72 | ## Troubleshooting
73 | 
74 | In general, keep an eye out in the `issues` and `discussions` section of this repo for solutions.
75 | 
76 | **General errors**
77 | 
78 | - Make sure you're running the latest Node version. Run `node -v`
79 | - Try a different PDF or convert your PDF to text first. It's possible your PDF is corrupted, scanned, or requires OCR to convert to text.
80 | - `Console.log` the `env` variables and make sure they are exposed.
81 | - Make sure you're using the same versions of LangChain and Faiss as this repo.
82 | - Check that you've created an `.env` file that contains your valid (and working) API keys, environment and index name.
83 | - If you change `modelName` in `OpenAI`, make sure you have access to the api for the appropriate model.
84 | - Make sure you have enough OpenAI credits and a valid card on your billings account.
85 | - Check that you don't have multiple OPENAPI keys in your global environment. If you do, the local `env` file from the project will be overwritten by systems `env` variable.
86 | - Try to hard code your API keys into the `process.env` variables if there are still issues.
87 | 
88 | ## Credit
89 | 
90 | Frontend of this repo is inspired by [langchain-chat-nextjs](https://github.com/zahidkhawaja/langchain-chat-nextjs)
91 | 


--------------------------------------------------------------------------------
/README_ko.md:
--------------------------------------------------------------------------------
  1 | # CSV, TXT, PDF 파일을 위한 ChatGPT 챗봇 만들기
  2 | 
  3 | [English](README.md) | [한국어](README_ko.md)
  4 | 
  5 | OpenAI API를 사용하여 PDF, CSV, TET 파일에 대한 ChatGPT 챗봇을 구축할 수 있습니다.
  6 | 
  7 | 사용되는 기술 스택에는 LangChain, Faiss, Typescript, Openai 및 Next.js가 포함됩니다. LangChain은 확장 가능한 AI/LLM 앱과 챗봇을 쉽게 구축할 수 있는 프레임워크입니다. Faiss는 임베딩과 PDF를 텍스트에 저장하여 나중에 유사한 문서를 검색할 수 있는 벡터 저장소입니다.
  8 | 
  9 | [튜토리얼 동영상](https://www.youtube.com/watch?v=ih9PBGVVOO4)
 10 | 
 11 | [질문이 있는 경우 디스코드에 참여](https://discord.gg/E4Mc77qwjm)
 12 | 
 13 | 이 리포지토리와 튜토리얼의 비주얼 가이드는 `visual guide` 폴더에 있습니다.
 14 | 
 15 | **오류가 발생하면 이 페이지 아래쪽의 문제 해결 섹션을 참조하세요.**
 16 | 
 17 | 준비사항: 시스템에 [Node.JS](https://nodejs.org/ko)가 이미 다운로드되어 있고 Node.JS 버전이 18 이상인지 확인하세요.
 18 | 
 19 | ## 개발
 20 | 
 21 | 1. 리포지토리를 복제하거나,
 22 | 
 23 | ```
 24 | git clone https://github.com/anpigon/gpt4-pdf-chatbot-langchain-faiss.git
 25 | ```
 26 | 
 27 | 2. 또는 ZIP 파일을 다운로드 합니다.
 28 | 
 29 | <img src="https://i.imgur.com/rMThF2k.png" width="300"/>
 30 | 
 31 | 
 32 | 3. 패키지 설치
 33 | 
 34 | 다음 명령을 실행합니다:
 35 | 
 36 | ```
 37 | npm install
 38 | ```
 39 | 
 40 | 설치가 완료되면 이제 `node_modules` 폴더가 표시됩니다.
 41 | 
 42 | 4. `.env` 파일 설정
 43 | 
 44 | - `.env.example`를 `.env`에 복사합니다.
 45 |   `.env` 파일은 다음과 같아야 합니다:
 46 | 
 47 | ```
 48 | OPENAI_API_KEY=
 49 | OPENAI_CHAT_MODEL=
 50 | ANSWER_LANGUAGE=
 51 | ```
 52 | 
 53 | - `OPENAI_API_KEY`: API 키를 [openai](https://platform.openai.com/account/api-keys)에서 발급받고, 이를 .env 파일에 입력합니다.
 54 | - `OPENAI_CHAT_MODEL`: `gpt-4` 또는 `gpt-3.5-turbo`를 입력합니다. 
 55 | - `ANSWER_LANGUAGE`: ChatGPT가 응답할 언어를 입력합니다. 한국어로 응답을 받고 싶으면 **ko-KR**을 입력합니다.
 56 | 
 57 | 5. `utils/makechain.ts` 파일에서 자신의 입맛에 맞게 `QA_PROMPT` 프롬프트를 변경할 수 있습니다. 
 58 | 
 59 | ## PDF, CSV, TXT 파일을 임베딩으로 변환하세요.
 60 | 
 61 | **이 리포지토리는 여러 PDF, CSV, TXT 파일들을 로드할 수 있습니다**.
 62 | 
 63 | 1. `docs` 폴더에 PDF, CSV, TXT 파일 또는 파일이 들어있는 폴더를 추가합니다.
 64 | 
 65 | 2. `npm run ingest` 명령을 실행하여 문서를 'ingest'하고 문서를 임베드합니다. 오류가 발생하면 아래에서 문제를 해결하세요.
 66 | 
 67 | 3. `faiss-store` 폴더에 docstore.json 및 faiss.index 파일이 성공적으로 생성되었는지 확인합니다.
 68 | 
 69 | 4. ***주의***: `npm run ingest` 명령을 실행하면 기존 임베딩이 삭제되고 새로 생성됩니다.
 70 | 
 71 | ## 앱 실행하기
 72 | 
 73 | 임베딩과 콘텐츠가 faiss 스토어에 성공적으로 추가되었는지 확인한 후, `npm run dev` 명령을 실행하여 로컬 개발 환경을 시작합니다. 그런 다음, 채팅 인터페이스에 질문을 입력할 수 있습니다.
 74 | 
 75 | ## 문제 해결
 76 | 
 77 | 일반적으로 이 리포지토리의 `issues` 및 `discussions` 섹션에서 해결책을 찾아보세요.
 78 | 
 79 | **General errors**
 80 | 
 81 | - 최신 노드 버전을 실행하고 있는지 확인하세요. `node -v`를 실행하세요.
 82 | - 다른 PDF를 시도하거나 먼저 PDF를 텍스트로 변환하세요. PDF가 손상되었거나 스캔되었거나 텍스트로 변환하기 위해 OCR이 필요할 수 있습니다.
 83 | - `Console.log` 에서 `env` 변수를 확인하고 해당 변수가 노출되어 있는지 확인하세요.
 84 | - 이 리포지토리와 동일한 버전의 LangChain 및 Faiss를 사용하고 있는지 확인하세요.
 85 | - 유효한(그리고 작동하는) OpenAI API Key, 환경 및 인덱스 이름이 포함된 `.env` 파일을 생성했는지 확인합니다.
 86 | - `modelName` 을 변경하는 경우, 해당 모델의 API에 대한 액세스 권한이 있는지 확인하세요.
 87 | - 청구 계정에 충분한 OpenAI 크레딧과 유효한 카드가 있는지 확인하세요.
 88 | - 글로벌 환경에 여러 개의 OPENAPI 키가 없는지 확인하세요. 여러 개가 있는 경우 프로젝트의 로컬 `env` 파일을 시스템 `env` 변수로 덮어쓰게 됩니다.
 89 | - 여전히 문제가 있는 경우 API 키를 `process.env` 변수에 하드 코딩해 보세요.
 90 | 
 91 | ##### (추가) faiss에서 libomp 관련 오류가 발생할 경우, 다음과 같은 방법을 시도해 볼 수 있습니다.
 92 | "faiss-node"에서 "libomp" 관련 오류를 해결하려면 시스템에 "libomp" 라이브러리를 설치해 볼 수 있습니다. 이 라이브러리는 Faiss에 필요하며 우분투에서 다음 명령을 사용하여 설치할 수 있습니다:
 93 | 
 94 | ```sh
 95 | sudo apt-get install libomp-dev
 96 | ```
 97 | 
 98 | macOS에서는 Homebrew를 사용하여 설치할 수 있습니다:
 99 | ```sh
100 | brew install libomp
101 | ```
102 | 
103 | 윈도우에서는 다음 명령을 사용하여 설치할 수 있습니다:
104 | ```sh
105 | conda install libpython m2w64-toolchain -c msys2
106 | conda install faiss-cpu -c pytorch
107 | ```
108 | 
109 | 라이브러리를 설치한 후 코드를 다시 실행하여 오류가 지속되는지 확인합니다.
110 | 
111 | 
112 | ## 크레딧
113 | 이 리포지토리의 프론트엔드는 [langchain-chat-nextjs](https://github.com/zahidkhawaja/langchain-chat-nextjs)에서 영감을 얻었습니다.
114 | 


--------------------------------------------------------------------------------
/components/layout.tsx:
--------------------------------------------------------------------------------
 1 | interface LayoutProps {
 2 |   children?: React.ReactNode;
 3 | }
 4 | 
 5 | export default function Layout({ children }: LayoutProps) {
 6 |   return (
 7 |     <div className="mx-auto flex flex-col space-y-4">
 8 |       <header className="container sticky top-0 z-40 bg-white">
 9 |         <div className="h-16 border-b border-b-slate-200 py-4">
10 |           <nav className="ml-4 pl-6">
11 |             <a href="#" className="hover:text-slate-600 cursor-pointer">
12 |               Home
13 |             </a>
14 |           </nav>
15 |         </div>
16 |       </header>
17 |       <div>
18 |         <main className="flex w-full flex-1 flex-col overflow-hidden">
19 |           {children}
20 |         </main>
21 |       </div>
22 |     </div>
23 |   );
24 | }
25 | 


--------------------------------------------------------------------------------
/components/ui/LoadingDots.tsx:
--------------------------------------------------------------------------------
 1 | import styles from '@/styles/loading-dots.module.css';
 2 | 
 3 | const LoadingDots = ({
 4 |   color = '#000',
 5 |   style = 'small',
 6 | }: {
 7 |   color: string;
 8 |   style: string;
 9 | }) => {
10 |   return (
11 |     <span className={style == 'small' ? styles.loading2 : styles.loading}>
12 |       <span style={{ backgroundColor: color }} />
13 |       <span style={{ backgroundColor: color }} />
14 |       <span style={{ backgroundColor: color }} />
15 |     </span>
16 |   );
17 | };
18 | 
19 | export default LoadingDots;
20 | 
21 | LoadingDots.defaultProps = {
22 |   style: 'small',
23 | };
24 | 


--------------------------------------------------------------------------------
/components/ui/TextArea.tsx:
--------------------------------------------------------------------------------
 1 | import * as React from 'react';
 2 | import { cn } from '@/utils/cn';
 3 | 
 4 | export interface TextareaProps
 5 |   extends React.TextareaHTMLAttributes<HTMLTextAreaElement> {}
 6 | 
 7 | const Textarea = React.forwardRef<HTMLTextAreaElement, TextareaProps>(
 8 |   ({ className, ...props }, ref) => {
 9 |     return (
10 |       <textarea
11 |         className={cn(
12 |           'flex h-20 w-full rounded-md border border-slate-300 bg-transparent py-2 px-3 text-sm placeholder:text-slate-400 focus:outline-none focus:ring-2 focus:ring-slate-400 focus:ring-offset-2 disabled:cursor-not-allowed disabled:opacity-50 dark:border-slate-700 dark:text-slate-50 dark:focus:ring-slate-400 dark:focus:ring-offset-slate-900',
13 |           className,
14 |         )}
15 |         ref={ref}
16 |         {...props}
17 |       />
18 |     );
19 |   },
20 | );
21 | Textarea.displayName = 'Textarea';
22 | 
23 | export { Textarea };
24 | 


--------------------------------------------------------------------------------
/components/ui/accordion.tsx:
--------------------------------------------------------------------------------
 1 | import * as React from 'react';
 2 | import * as AccordionPrimitive from '@radix-ui/react-accordion';
 3 | import { ChevronDown } from 'lucide-react';
 4 | 
 5 | import { cn } from '@/utils/cn';
 6 | 
 7 | const Accordion = AccordionPrimitive.Root;
 8 | 
 9 | const AccordionItem = React.forwardRef<
10 |   React.ElementRef<typeof AccordionPrimitive.Item>,
11 |   React.ComponentPropsWithoutRef<typeof AccordionPrimitive.Item>
12 | >(({ className, ...props }, ref) => (
13 |   <AccordionPrimitive.Item
14 |     ref={ref}
15 |     className={cn(
16 |       'border-b border-b-slate-200 dark:border-b-slate-700',
17 |       className,
18 |     )}
19 |     {...props}
20 |   />
21 | ));
22 | AccordionItem.displayName = 'AccordionItem';
23 | 
24 | const AccordionTrigger = React.forwardRef<
25 |   React.ElementRef<typeof AccordionPrimitive.Trigger>,
26 |   React.ComponentPropsWithoutRef<typeof AccordionPrimitive.Trigger>
27 | >(({ className, children, ...props }, ref) => (
28 |   <AccordionPrimitive.Header className="flex">
29 |     <AccordionPrimitive.Trigger
30 |       ref={ref}
31 |       className={cn(
32 |         'flex flex-1 items-center justify-between py-4 font-medium transition-all hover:underline [&[data-state=open]>svg]:rotate-180',
33 |         className,
34 |       )}
35 |       {...props}
36 |     >
37 |       {children}
38 |       <ChevronDown className="h-4 w-4 transition-transform duration-200" />
39 |     </AccordionPrimitive.Trigger>
40 |   </AccordionPrimitive.Header>
41 | ));
42 | AccordionTrigger.displayName = AccordionPrimitive.Trigger.displayName;
43 | 
44 | const AccordionContent = React.forwardRef<
45 |   React.ElementRef<typeof AccordionPrimitive.Content>,
46 |   React.ComponentPropsWithoutRef<typeof AccordionPrimitive.Content>
47 | >(({ className, children, ...props }, ref) => (
48 |   <AccordionPrimitive.Content
49 |     ref={ref}
50 |     className={cn(
51 |       'data-[state=open]:animate-accordion-down data-[state=closed]:animate-accordion-up overflow-hidden text-sm transition-all',
52 |       className,
53 |     )}
54 |     {...props}
55 |   >
56 |     <div className="pt-0 pb-4">{children}</div>
57 |   </AccordionPrimitive.Content>
58 | ));
59 | AccordionContent.displayName = AccordionPrimitive.Content.displayName;
60 | 
61 | export { Accordion, AccordionItem, AccordionTrigger, AccordionContent };
62 | 


--------------------------------------------------------------------------------
/config/chroma.ts:
--------------------------------------------------------------------------------
 1 | /**
 2 |  * Change the namespace to the namespace on Pinecone you'd like to store your embeddings.
 3 |  */
 4 | 
 5 | if (!process.env.COLLECTION_NAME) {
 6 |   throw new Error('Missing collection name in .env file');
 7 | }
 8 | 
 9 | const COLLECTION_NAME = process.env.COLLECTION_NAME ?? '';
10 | 
11 | export { COLLECTION_NAME }


--------------------------------------------------------------------------------
/declarations/pdf-parse.d.ts:
--------------------------------------------------------------------------------
1 | declare module 'pdf-parse/lib/pdf-parse.js' {
2 |   import pdf from 'pdf-parse';
3 | 
4 |   export default pdf;
5 | }
6 | 


--------------------------------------------------------------------------------
/docs/.keep:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/anpigon/gpt4-pdf-chatbot-langchain-faiss/8294ffe186924b1d9050bd4fb3600433f92b882b/docs/.keep


--------------------------------------------------------------------------------
/faiss-store/.keep:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/anpigon/gpt4-pdf-chatbot-langchain-faiss/8294ffe186924b1d9050bd4fb3600433f92b882b/faiss-store/.keep


--------------------------------------------------------------------------------
/next.config.js:
--------------------------------------------------------------------------------
 1 | /** @type {import('next').NextConfig} */
 2 | const nextConfig = {
 3 |   reactStrictMode: true,
 4 |   swcMinify: true,
 5 |   webpack(config) {
 6 |     config.experiments = { ...config.experiments, topLevelAwait: true };
 7 |     return config;
 8 |   },
 9 | };
10 | 
11 | export default nextConfig;
12 | 


--------------------------------------------------------------------------------
/package-lock.json:
--------------------------------------------------------------------------------
   1 | {
   2 |   "name": "gpt4-langchain-pdf-chatbot",
   3 |   "version": "0.1.0",
   4 |   "lockfileVersion": 3,
   5 |   "requires": true,
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1409 |       "license": "MIT"
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4228 |       "dependencies": {
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4232 |         "node": ">=10"
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4235 |     "node_modules/node-abi/node_modules/semver": {
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4237 |       "license": "ISC",
4238 |       "dependencies": {
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4244 |       "engines": {
4245 |         "node": ">=10"
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4248 |     "node_modules/node-addon-api": {
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4250 |       "license": "MIT"
4251 |     },
4252 |     "node_modules/node-ensure": {
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4254 |       "license": "MIT"
4255 |     },
4256 |     "node_modules/node-fetch": {
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4259 |       "dependencies": {
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4264 |       },
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4274 |     "node_modules/node-releases": {
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4276 |       "dev": true,
4277 |       "license": "MIT"
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4279 |     "node_modules/normalize-path": {
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4282 |       "license": "MIT",
4283 |       "engines": {
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4287 |     "node_modules/normalize-range": {
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4289 |       "dev": true,
4290 |       "license": "MIT",
4291 |       "engines": {
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4295 |     "node_modules/num-sort": {
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4297 |       "license": "MIT",
4298 |       "engines": {
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4301 |       "funding": {
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4305 |     "node_modules/object-assign": {
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4307 |       "license": "MIT",
4308 |       "engines": {
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4312 |     "node_modules/object-hash": {
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4314 |       "license": "MIT",
4315 |       "engines": {
4316 |         "node": ">= 6"
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4319 |     "node_modules/object-inspect": {
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4321 |       "dev": true,
4322 |       "license": "MIT",
4323 |       "funding": {
4324 |         "url": "https://github.com/sponsors/ljharb"
4325 |       }
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4327 |     "node_modules/object-is": {
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4329 |       "dev": true,
4330 |       "license": "MIT",
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4338 |       "funding": {
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4342 |     "node_modules/object-keys": {
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4344 |       "dev": true,
4345 |       "license": "MIT",
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4367 |     "node_modules/object.entries": {
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4370 |       "license": "MIT",
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4382 |       "dev": true,
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4434 |       "license": "MIT",
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4450 |       "dependencies": {
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4457 |       "dev": true,
4458 |       "license": "MIT",
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4502 |       "funding": {
4503 |         "url": "https://github.com/sponsors/sindresorhus"
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4506 |     "node_modules/p-queue": {
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4508 |       "license": "MIT",
4509 |       "dependencies": {
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4544 |       "license": "MIT",
4545 |       "dependencies": {
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4555 |       "license": "MIT",
4556 |       "engines": {
4557 |         "node": ">=8"
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4562 |       "dev": true,
4563 |       "license": "MIT",
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4571 |       "license": "MIT",
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4579 |       "license": "MIT"
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4619 |     "node_modules/picocolors": {
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4637 |       "license": "MIT",
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4645 |       "license": "MIT",
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4805 |       "license": "MIT",
4806 |       "engines": {
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4845 |     "node_modules/pump": {
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4848 |       "dependencies": {
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6102 | }
6103 | 


--------------------------------------------------------------------------------
/package.json:
--------------------------------------------------------------------------------
 1 | {
 2 |   "name": "gpt4-langchain-pdf-chatbot",
 3 |   "version": "0.1.0",
 4 |   "private": true,
 5 |   "license": "MIT",
 6 |   "author": "Mayooear<twitter:@mayowaoshin>",
 7 |   "type": "module",
 8 |   "scripts": {
 9 |     "dev": "next dev",
10 |     "build": "next build",
11 |     "start": "next start",
12 |     "type-check": "tsc --noEmit",
13 |     "lint": "eslint --ignore-path .gitignore \"**/*.+(ts|js|tsx)\"",
14 |     "format": "prettier --ignore-path .gitignore \"**/*.+(ts|js|tsx)\" --write",
15 |     "ingest": "tsx -r dotenv/config scripts/ingest-data.ts"
16 |   },
17 |   "dependencies": {
18 |     "@microsoft/fetch-event-source": "^2.0.1",
19 |     "@radix-ui/react-accordion": "^1.1.1",
20 |     "clsx": "^1.2.1",
21 |     "d3-dsv": "2",
22 |     "dotenv": "^16.0.3",
23 |     "faiss-node": "^0.2.0",
24 |     "langchain": "0.0.84",
25 |     "lucide-react": "^0.125.0",
26 |     "next": "13.2.3",
27 |     "pdf-parse": "1.1.1",
28 |     "pickleparser": "^0.1.0",
29 |     "react": "18.2.0",
30 |     "react-dom": "18.2.0",
31 |     "react-markdown": "^8.0.5",
32 |     "tailwind-merge": "^1.10.0"
33 |   },
34 |   "devDependencies": {
35 |     "@types/node": "^18.14.6",
36 |     "@types/react": "^18.0.28",
37 |     "@types/react-dom": "^18.0.11",
38 |     "@typescript-eslint/parser": "^5.54.0",
39 |     "autoprefixer": "^10.4.13",
40 |     "eslint": "8.35.0",
41 |     "eslint-config-next": "13.2.3",
42 |     "postcss": "^8.4.21",
43 |     "prettier": "^2.8.4",
44 |     "tailwindcss": "^3.2.7",
45 |     "tsx": "^3.12.3",
46 |     "typescript": "^4.9.5"
47 |   },
48 |   "engines": {
49 |     "node": ">=18"
50 |   },
51 |   "keywords": [
52 |     "starter",
53 |     "gpt4",
54 |     "chroma",
55 |     "typescript",
56 |     "nextjs",
57 |     "langchain",
58 |     "law",
59 |     "legal",
60 |     "pdf",
61 |     "openai"
62 |   ]
63 | }
64 | 


--------------------------------------------------------------------------------
/pages/_app.tsx:
--------------------------------------------------------------------------------
 1 | import '@/styles/base.css';
 2 | import type { AppProps } from 'next/app';
 3 | import { Inter } from 'next/font/google';
 4 | 
 5 | const inter = Inter({
 6 |   variable: '--font-inter',
 7 |   subsets: ['latin'],
 8 | });
 9 | 
10 | function MyApp({ Component, pageProps }: AppProps) {
11 |   return (
12 |     <>
13 |       <main className={inter.variable}>
14 |         <Component {...pageProps} />
15 |       </main>
16 |     </>
17 |   );
18 | }
19 | 
20 | export default MyApp;
21 | 


--------------------------------------------------------------------------------
/pages/_document.tsx:
--------------------------------------------------------------------------------
 1 | import { Html, Head, Main, NextScript } from "next/document";
 2 | 
 3 | export default function Document() {
 4 |   return (
 5 |     <Html lang="en">
 6 |       <Head />
 7 |       <body>
 8 |         <Main />
 9 |         <NextScript />
10 |       </body>
11 |     </Html>
12 |   );
13 | }
14 | 


--------------------------------------------------------------------------------
/pages/api/chat.ts:
--------------------------------------------------------------------------------
 1 | import type { NextApiRequest, NextApiResponse } from 'next';
 2 | import { OpenAIEmbeddings } from 'langchain/embeddings/openai';
 3 | import { Chroma } from 'langchain/vectorstores/chroma';
 4 | import { makeChain } from '@/utils/makechain';
 5 | import { COLLECTION_NAME } from '@/config/chroma';
 6 | import { FaissStore } from 'langchain/vectorstores/faiss';
 7 | 
 8 | // Save the vector store to a directory
 9 | const directory = 'faiss-store';
10 | 
11 | export default async function handler(
12 |   req: NextApiRequest,
13 |   res: NextApiResponse,
14 | ) {
15 |   const { question, history } = req.body;
16 | 
17 |   console.log('question', question);
18 | 
19 |   //only accept post requests
20 |   if (req.method !== 'POST') {
21 |     res.status(405).json({ error: 'Method not allowed' });
22 |     return;
23 |   }
24 | 
25 |   if (!question) {
26 |     return res.status(400).json({ message: 'No question in the request' });
27 |   }
28 |   // OpenAI recommends replacing newlines with spaces for best results
29 |   const sanitizedQuestion = question.trim().replaceAll('\n', ' ');
30 | 
31 |   try {
32 | 
33 |     /* create vectorstore*/
34 |     /* const vectorStore = await Chroma.fromExistingCollection(
35 |       new OpenAIEmbeddings({}),
36 |       {
37 |         collectionName: COLLECTION_NAME,
38 |        },
39 |     ); */
40 |     const vectorStore = await FaissStore.load(
41 |       directory,
42 |       new OpenAIEmbeddings({}),
43 |     );
44 | 
45 |     //create chain
46 |     const chain = makeChain(vectorStore);
47 |     //Ask a question using chat history
48 |     const response = await chain.call({
49 |       question: sanitizedQuestion,
50 |       chat_history: history || [],
51 |     });
52 | 
53 |     console.log('response', response);
54 |     res.status(200).json(response);
55 |   } catch (error: any) {
56 |     console.log('error', error);
57 |     res.status(500).json({ error: error.message || 'Something went wrong' });
58 |   }
59 | }
60 | 


--------------------------------------------------------------------------------
/pages/index.tsx:
--------------------------------------------------------------------------------
  1 | import { useRef, useState, useEffect, Fragment } from 'react';
  2 | import Layout from '@/components/layout';
  3 | import styles from '@/styles/Home.module.css';
  4 | import { Message } from '@/types/chat';
  5 | import Image from 'next/image';
  6 | import ReactMarkdown from 'react-markdown';
  7 | import LoadingDots from '@/components/ui/LoadingDots';
  8 | import { Document } from 'langchain/document';
  9 | import {
 10 |   Accordion,
 11 |   AccordionContent,
 12 |   AccordionItem,
 13 |   AccordionTrigger,
 14 | } from '@/components/ui/accordion';
 15 | 
 16 | const BotAvatar: React.FC = () => {
 17 |   return (
 18 |     <Image
 19 |       src="/bot-image.png"
 20 |       alt="AI"
 21 |       width="40"
 22 |       height="40"
 23 |       className={styles.boticon}
 24 |       priority
 25 |     />
 26 |   );
 27 | };
 28 | 
 29 | const UserAvatar: React.FC = () => {
 30 |   return (
 31 |     <Image
 32 |       src="/usericon.png"
 33 |       alt="Me"
 34 |       width="30"
 35 |       height="30"
 36 |       className={styles.usericon}
 37 |       priority
 38 |     />
 39 |   );
 40 | };
 41 | 
 42 | export default function Home() {
 43 |   const [query, setQuery] = useState<string>('');
 44 |   const [loading, setLoading] = useState<boolean>(false);
 45 |   const [error, setError] = useState<string | null>(null);
 46 |   const [messageState, setMessageState] = useState<{
 47 |     messages: Message[];
 48 |     pending?: string;
 49 |     history: [string, string][];
 50 |     pendingSourceDocs?: Document[];
 51 |   }>({
 52 |     messages: [
 53 |       {
 54 |         message: 'Hi, what would you like to learn about this document?',
 55 |         type: 'apiMessage',
 56 |       },
 57 |     ],
 58 |     history: [],
 59 |   });
 60 | 
 61 |   const { messages, history } = messageState;
 62 | 
 63 |   const messageListRef = useRef<HTMLDivElement>(null);
 64 |   const textAreaRef = useRef<HTMLTextAreaElement>(null);
 65 | 
 66 |   useEffect(() => {
 67 |     textAreaRef.current?.focus();
 68 |   }, []);
 69 | 
 70 |   //handle form submission
 71 |   async function handleSubmit(e: any) {
 72 |     e.preventDefault();
 73 | 
 74 |     setError(null);
 75 | 
 76 |     if (!query) {
 77 |       alert('Please input a question');
 78 |       return;
 79 |     }
 80 | 
 81 |     const question = query.trim();
 82 | 
 83 |     setMessageState((state) => ({
 84 |       ...state,
 85 |       messages: [
 86 |         ...state.messages,
 87 |         {
 88 |           type: 'userMessage',
 89 |           message: question,
 90 |         },
 91 |       ],
 92 |     }));
 93 | 
 94 |     setLoading(true);
 95 |     setQuery('');
 96 | 
 97 |     try {
 98 |       const response = await fetch('/api/chat', {
 99 |         method: 'POST',
100 |         headers: {
101 |           'Content-Type': 'application/json',
102 |         },
103 |         body: JSON.stringify({
104 |           question,
105 |           history,
106 |         }),
107 |       });
108 |       const data = await response.json();
109 |       console.log('data', data);
110 | 
111 |       if (data.error) {
112 |         setError(data.error);
113 |       } else {
114 |         setMessageState((state) => ({
115 |           ...state,
116 |           messages: [
117 |             ...state.messages,
118 |             {
119 |               type: 'apiMessage',
120 |               message: data.text,
121 |               sourceDocs: data.sourceDocuments,
122 |             },
123 |           ],
124 |           history: [...state.history, [question, data.text]],
125 |         }));
126 |       }
127 |       console.log('messageState', messageState);
128 | 
129 |       setLoading(false);
130 | 
131 |       //scroll to bottom
132 |       messageListRef.current?.scrollTo(0, messageListRef.current.scrollHeight);
133 |     } catch (error) {
134 |       setLoading(false);
135 |       setError('An error occurred while fetching the data. Please try again.');
136 |       console.log('error', error);
137 |     }
138 |   }
139 | 
140 |   //prevent empty submissions
141 |   const handleEnter = (e: any) => {
142 |     if (e.key === 'Enter' && query) {
143 |       handleSubmit(e);
144 |     } else if (e.key == 'Enter') {
145 |       e.preventDefault();
146 |     }
147 |   };
148 | 
149 |   return (
150 |     <Layout>
151 |       <div className="mx-auto flex flex-col gap-4">
152 |         <h1 className="text-2xl font-bold leading-[1.1] tracking-tighter text-center">
153 |           Chat With Your Docs
154 |         </h1>
155 |         <main className={styles.main}>
156 |           <div className={styles.cloud}>
157 |             <div ref={messageListRef} className={styles.messagelist}>
158 |               {messages.map((message, index) => {
159 |                 let className;
160 |                 if (message.type === 'apiMessage') {
161 |                   className = styles.apimessage;
162 |                 } else {
163 |                   // The latest message sent by the user will be animated while waiting for a response
164 |                   className =
165 |                     loading && index === messages.length - 1
166 |                       ? styles.usermessagewaiting
167 |                       : styles.usermessage;
168 |                 }
169 |                 return (
170 |                   <Fragment key={`chatMessage-${index}`}>
171 |                     <div className={className}>
172 |                       {message.type === 'apiMessage' ? (
173 |                         <BotAvatar />
174 |                       ) : (
175 |                         <UserAvatar />
176 |                       )}
177 |                       <div className={styles.markdownanswer}>
178 |                         <ReactMarkdown linkTarget="_blank">
179 |                           {message.message}
180 |                         </ReactMarkdown>
181 |                       </div>
182 |                     </div>
183 |                     {message.sourceDocs && (
184 |                       <div className="p-5" key={`sourceDocsAccordion-${index}`}>
185 |                         <Accordion
186 |                           type="single"
187 |                           collapsible
188 |                           className="flex-col"
189 |                         >
190 |                           {message.sourceDocs.map((doc, index) => (
191 |                             <div key={`messageSourceDocs-${index}`}>
192 |                               <AccordionItem value={`item-${index}`}>
193 |                                 <AccordionTrigger>
194 |                                   <h3>Source {index + 1}</h3>
195 |                                 </AccordionTrigger>
196 |                                 <AccordionContent>
197 |                                   <ReactMarkdown linkTarget="_blank">
198 |                                     {doc.pageContent}
199 |                                   </ReactMarkdown>
200 |                                   <p className="mt-2">
201 |                                     <b>Source:</b> {doc.metadata.source}
202 |                                   </p>
203 |                                 </AccordionContent>
204 |                               </AccordionItem>
205 |                             </div>
206 |                           ))}
207 |                         </Accordion>
208 |                       </div>
209 |                     )}
210 |                   </Fragment>
211 |                 );
212 |               })}
213 |             </div>
214 |           </div>
215 |           <div className={styles.center}>
216 |             <div className={styles.cloudform}>
217 |               <form onSubmit={handleSubmit}>
218 |                 <textarea
219 |                   disabled={loading}
220 |                   onKeyDown={handleEnter}
221 |                   ref={textAreaRef}
222 |                   autoFocus={false}
223 |                   rows={1}
224 |                   maxLength={512}
225 |                   id="userInput"
226 |                   name="userInput"
227 |                   placeholder={
228 |                     loading
229 |                       ? 'Waiting for response...'
230 |                       : 'What is this legal case about?'
231 |                   }
232 |                   value={query}
233 |                   onChange={(e) => setQuery(e.target.value)}
234 |                   className={styles.textarea}
235 |                 />
236 |                 <button
237 |                   type="submit"
238 |                   disabled={loading}
239 |                   className={styles.generatebutton}
240 |                 >
241 |                   {loading ? (
242 |                     <div className={styles.loadingwheel}>
243 |                       <LoadingDots color="#000" />
244 |                     </div>
245 |                   ) : (
246 |                     // Send icon SVG in input field
247 |                     <svg
248 |                       viewBox="0 0 20 20"
249 |                       className={styles.svgicon}
250 |                       xmlns="http://www.w3.org/2000/svg"
251 |                     >
252 |                       <path d="M10.894 2.553a1 1 0 00-1.788 0l-7 14a1 1 0 001.169 1.409l5-1.429A1 1 0 009 15.571V11a1 1 0 112 0v4.571a1 1 0 00.725.962l5 1.428a1 1 0 001.17-1.408l-7-14z"></path>
253 |                     </svg>
254 |                   )}
255 |                 </button>
256 |               </form>
257 |             </div>
258 |           </div>
259 |           {error && (
260 |             <div className="border border-red-400 rounded-md p-4">
261 |               <p className="text-red-500">{error}</p>
262 |             </div>
263 |           )}
264 |         </main>
265 |       </div>
266 |       <footer className="m-auto p-4">
267 |         <a href="https://twitter.com/mayowaoshin">
268 |           Powered by LangChainAI and Faiss. Demo built by Mayo (Twitter:
269 |           @mayowaoshin).
270 |         </a>
271 |       </footer>
272 |     </Layout>
273 |   );
274 | }
275 | 


--------------------------------------------------------------------------------
/postcss.config.cjs:
--------------------------------------------------------------------------------
1 | module.exports = {
2 |   plugins: {
3 |     tailwindcss: {},
4 |     autoprefixer: {},
5 |   },
6 | };
7 | 


--------------------------------------------------------------------------------
/public/bot-image.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/anpigon/gpt4-pdf-chatbot-langchain-faiss/8294ffe186924b1d9050bd4fb3600433f92b882b/public/bot-image.png


--------------------------------------------------------------------------------
/public/favicon.ico:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/anpigon/gpt4-pdf-chatbot-langchain-faiss/8294ffe186924b1d9050bd4fb3600433f92b882b/public/favicon.ico


--------------------------------------------------------------------------------
/public/usericon.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/anpigon/gpt4-pdf-chatbot-langchain-faiss/8294ffe186924b1d9050bd4fb3600433f92b882b/public/usericon.png


--------------------------------------------------------------------------------
/scripts/ingest-data.ts:
--------------------------------------------------------------------------------
 1 | import { FaissStore } from 'langchain/vectorstores/faiss';
 2 | import { OpenAIEmbeddings } from 'langchain/embeddings/openai';
 3 | import { CSVLoader } from 'langchain/document_loaders/fs/csv';
 4 | import { TextLoader } from 'langchain/document_loaders/fs/text';
 5 | import { DirectoryLoader } from 'langchain/document_loaders/fs/directory';
 6 | import { CustomPDFLoader } from '@/utils/customPDFLoader';
 7 | 
 8 | /* Name of directory to retrieve your files from */
 9 | const filePath = 'docs';
10 | 
11 | // Save the vector store to a directory
12 | const indexFilePath = 'faiss-store';
13 | 
14 | export const run = async () => {
15 |   try {
16 |     /*load raw docs from the all files in the directory */
17 |     const directoryLoader = new DirectoryLoader(filePath, {
18 |       '.pdf': (path) => new CustomPDFLoader(path),
19 |       '.txt': (path) => new TextLoader(path),
20 |       '.csv': (path) => new CSVLoader(path),
21 |     });
22 | 
23 |     const rawDocs = await directoryLoader.load();
24 | 
25 |     const vectorStore = await FaissStore.fromDocuments(
26 |       rawDocs,
27 |       new OpenAIEmbeddings(),
28 |     );
29 | 
30 |     await vectorStore.save(indexFilePath);
31 |   } catch (error) {
32 |     console.log('error', error);
33 |     throw new Error('Failed to ingest your data');
34 |   }
35 | };
36 | 
37 | (async () => {
38 |   await run();
39 |   console.log('ingestion complete');
40 | })();
41 | 


--------------------------------------------------------------------------------
/styles/Home.module.css:
--------------------------------------------------------------------------------
  1 | .main {
  2 |   display: flex;
  3 |   flex-direction: column;
  4 |   justify-content: space-between;
  5 |   align-items: center;
  6 |   padding: 1rem;
  7 | }
  8 | 
  9 | .header {
 10 |   width: auto;
 11 | }
 12 | 
 13 | .header p {
 14 |   text-align: center;
 15 | }
 16 | 
 17 | .cloudform {
 18 |   position: relative;
 19 | }
 20 | 
 21 | .textarea {
 22 |   position: relative;
 23 |   resize: none;
 24 |   font-size: 1.1rem;
 25 |   padding: 1rem 2rem 1rem 2rem;
 26 |   width: 75vw;
 27 |   border-radius: 0.5rem;
 28 |   border: 1px solid #d9d9e3;
 29 |   background: #ffffff;
 30 |   color: #000;
 31 |   outline: none;
 32 | }
 33 | 
 34 | .textarea:disabled {
 35 |   opacity: 0.5;
 36 | }
 37 | 
 38 | .textarea:focus {
 39 |   outline: none;
 40 |   border-color: #6b7280;
 41 |   box-shadow: 0 0 0 3px rgba(156, 163, 175, 0.5);
 42 | }
 43 | 
 44 | .textarea::placeholder {
 45 |   color: #6b7280;
 46 | }
 47 | 
 48 | .generatebutton {
 49 |   position: absolute;
 50 |   top: 0.87rem;
 51 |   right: 1rem;
 52 |   color: rgb(165, 162, 162);
 53 |   background: none;
 54 |   padding: 0.3rem;
 55 |   border: none;
 56 |   display: flex;
 57 | }
 58 | 
 59 | .loadingwheel {
 60 |   position: absolute;
 61 |   top: 0.2rem;
 62 |   right: 0.25rem;
 63 | }
 64 | 
 65 | .svgicon {
 66 |   transform: rotate(90deg);
 67 |   width: 1.2em;
 68 |   height: 1.2em;
 69 |   fill: currentColor;
 70 | }
 71 | 
 72 | .generatebutton:hover {
 73 |   background: #e4575726;
 74 |   border-radius: 0.2rem;
 75 | }
 76 | 
 77 | .generatebutton:disabled {
 78 |   opacity: 0.9;
 79 |   cursor: not-allowed;
 80 |   background: none;
 81 | }
 82 | 
 83 | .messagelist {
 84 |   width: 100%;
 85 |   height: 100%;
 86 |   overflow-y: scroll;
 87 |   border-radius: 0.5rem;
 88 | }
 89 | 
 90 | .messagelistloading {
 91 |   display: flex;
 92 |   width: 100%;
 93 |   justify-content: center;
 94 |   margin-top: 1rem;
 95 | }
 96 | 
 97 | .usermessage {
 98 |   background: #ffffff;
 99 |   padding: 1.5rem;
100 |   color: #000;
101 | }
102 | 
103 | .usermessagewaiting {
104 |   padding: 1.5rem;
105 |   color: #000;
106 |   background: linear-gradient(to left, #07080938, #1a1c2024, #07080936);
107 |   background-size: 200% 200%;
108 |   background-position: -100% 0;
109 |   animation: loading-gradient 2s ease-in-out infinite;
110 |   animation-direction: alternate;
111 |   animation-name: loading-gradient;
112 | }
113 | 
114 | @keyframes loading-gradient {
115 |   0% {
116 |     background-position: -100% 0;
117 |   }
118 |   100% {
119 |     background-position: 100% 0;
120 |   }
121 | }
122 | 
123 | .apimessage {
124 |   background: #f9fafb;
125 |   padding: 1.5rem;
126 |   color: #000;
127 |   animation: fadein 0.5s;
128 | }
129 | 
130 | @keyframes fadein {
131 |   from {
132 |     opacity: 0;
133 |   }
134 |   to {
135 |     opacity: 1;
136 |   }
137 | }
138 | 
139 | .apimessage,
140 | .usermessage,
141 | .usermessagewaiting {
142 |   display: flex;
143 | }
144 | 
145 | .markdownanswer {
146 |   line-height: 1.75;
147 | }
148 | 
149 | .markdownanswer a:hover {
150 |   opacity: 0.8;
151 | }
152 | 
153 | .markdownanswer a {
154 |   color: #b13a3a;
155 |   font-weight: 500;
156 | }
157 | 
158 | .markdownanswer code {
159 |   color: #15cb19;
160 |   font-weight: 500;
161 |   white-space: pre-wrap !important;
162 | }
163 | 
164 | .markdownanswer ol,
165 | .markdownanswer ul {
166 |   margin: 1rem;
167 | }
168 | 
169 | .boticon,
170 | .usericon {
171 |   margin-right: 1rem;
172 |   border-radius: 0.1rem;
173 |   height: 100%;
174 | }
175 | 
176 | .markdownanswer h1,
177 | .markdownanswer h2,
178 | .markdownanswer h3 {
179 |   font-size: inherit;
180 | }
181 | 
182 | .center {
183 |   display: flex;
184 |   justify-content: center;
185 |   align-items: center;
186 |   position: relative;
187 |   padding: 1rem 0;
188 |   flex-direction: column;
189 | }
190 | 
191 | .cloud {
192 |   width: 75vw;
193 |   height: 65vh;
194 |   background: #ffffff;
195 |   border-radius: 0.5rem;
196 |   border: 1px solid #d9d9e3;
197 |   display: flex;
198 |   justify-content: center;
199 |   align-items: center;
200 | }
201 | 
202 | .pointsnormal {
203 |   width: 90%;
204 |   height: 90%;
205 | }
206 | 
207 | .pointsdim {
208 |   width: 90%;
209 |   height: 90%;
210 |   opacity: 0.25;
211 | }
212 | 
213 | .footer {
214 |   color: #5f6368;
215 |   font-size: 0.8rem;
216 |   margin: 1.5rem;
217 | }
218 | 
219 | .footer a {
220 |   font-weight: 500;
221 |   color: #7a7d81;
222 | }
223 | 
224 | .footer a:hover {
225 |   opacity: 0.8;
226 | }
227 | 
228 | /* Mobile optimization */
229 | @media (max-width: 600px) {
230 |   .main {
231 |     padding: 1rem;
232 |     max-height: 90vh;
233 |   }
234 | 
235 |   .cloud {
236 |     width: 22rem;
237 |     height: 28rem;
238 |   }
239 |   .textarea {
240 |     width: 22rem;
241 |   }
242 |   .topnav {
243 |     border: 1px solid black;
244 |     align-items: center;
245 |     padding: 0.85rem 0.75rem 0.85rem 0.75rem;
246 |   }
247 | 
248 |   .navlogo {
249 |     font-size: 1.25rem;
250 |     width: 20rem;
251 |   }
252 | 
253 |   .markdownanswer code {
254 |     white-space: pre-wrap !important;
255 |   }
256 | 
257 |   .footer {
258 |     font-size: 0.7rem;
259 |     width: 100%;
260 |     text-align: center;
261 |   }
262 | }
263 | 


--------------------------------------------------------------------------------
/styles/base.css:
--------------------------------------------------------------------------------
1 | @tailwind base;
2 | @tailwind components;
3 | @tailwind utilities;
4 | 


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/styles/chrome-bug.css:
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 1 | /**
 2 |  * Chrome has a bug with transitions on load since 2012!
 3 |  *
 4 |  * To prevent a "pop" of content, you have to disable all transitions until
 5 |  * the page is done loading.
 6 |  *
 7 |  * https://lab.laukstein.com/bug/input
 8 |  * https://twitter.com/timer150/status/1345217126680899584
 9 |  */
10 | body.loading * {
11 |   transition: none !important;
12 | }
13 | 


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/styles/loading-dots.module.css:
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 1 | .loading {
 2 |   display: inline-flex;
 3 |   align-items: center;
 4 | }
 5 | 
 6 | .loading .spacer {
 7 |   margin-right: 2px;
 8 | }
 9 | 
10 | .loading span {
11 |   animation-name: blink;
12 |   animation-duration: 1.4s;
13 |   animation-iteration-count: infinite;
14 |   animation-fill-mode: both;
15 |   width: 5px;
16 |   height: 5px;
17 |   border-radius: 50%;
18 |   display: inline-block;
19 |   margin: 0 1px;
20 | }
21 | 
22 | .loading span:nth-of-type(2) {
23 |   animation-delay: 0.2s;
24 | }
25 | 
26 | .loading span:nth-of-type(3) {
27 |   animation-delay: 0.4s;
28 | }
29 | 
30 | .loading2 {
31 |   display: inline-flex;
32 |   align-items: center;
33 | }
34 | 
35 | .loading2 .spacer {
36 |   margin-right: 2px;
37 | }
38 | 
39 | .loading2 span {
40 |   animation-name: blink;
41 |   animation-duration: 1.4s;
42 |   animation-iteration-count: infinite;
43 |   animation-fill-mode: both;
44 |   width: 4px;
45 |   height: 4px;
46 |   border-radius: 50%;
47 |   display: inline-block;
48 |   margin: 0 1px;
49 | }
50 | 
51 | .loading2 span:nth-of-type(2) {
52 |   animation-delay: 0.2s;
53 | }
54 | 
55 | .loading2 span:nth-of-type(3) {
56 |   animation-delay: 0.4s;
57 | }
58 | 
59 | @keyframes blink {
60 |   0% {
61 |     opacity: 0.2;
62 |   }
63 |   20% {
64 |     opacity: 1;
65 |   }
66 |   100% {
67 |     opacity: 0.2;
68 |   }
69 | }
70 | 


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/tailwind.config.cjs:
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 1 | /** @type {import('tailwindcss').Config} */
 2 | module.exports = {
 3 |   content: [
 4 |     './app/**/*.{js,ts,jsx,tsx}',
 5 |     './pages/**/*.{js,ts,jsx,tsx}',
 6 |     './components/**/*.{js,ts,jsx,tsx}',
 7 |   ],
 8 |   theme: {
 9 |     extend: {},
10 |   },
11 | };
12 | 


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/tsconfig.json:
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 1 | {
 2 |   "compilerOptions": {
 3 |     "target": "es2020",
 4 |     "lib": ["dom", "dom.iterable", "esnext"],
 5 |     "allowJs": true,
 6 |     "skipLibCheck": true,
 7 |     "strict": true,
 8 |     "forceConsistentCasingInFileNames": true,
 9 |     "noEmit": true,
10 |     "esModuleInterop": true,
11 |     "module": "esnext",
12 |     "moduleResolution": "node",
13 |     "resolveJsonModule": true,
14 |     "isolatedModules": true,
15 |     "jsx": "preserve",
16 |     "incremental": true,
17 |     "baseUrl": ".",
18 |     "plugins": [
19 |       {
20 |         "name": "next"
21 |       }
22 |     ],
23 |     "paths": {
24 |       "@/*": ["./*"]
25 |     }
26 |   },
27 |   "include": ["next-env.d.ts", "**/*.ts", "**/*.tsx", ".next/types/**/*.ts"],
28 |   "exclude": ["node_modules"]
29 | }
30 | 


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/types/chat.ts:
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1 | import { Document } from 'langchain/document';
2 | 
3 | export type Message = {
4 |   type: 'apiMessage' | 'userMessage';
5 |   message: string;
6 |   isStreaming?: boolean;
7 |   sourceDocs?: Document[];
8 | };
9 | 


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/utils/cn.ts:
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1 | import { ClassValue, clsx } from 'clsx';
2 | import { twMerge } from 'tailwind-merge';
3 | 
4 | export function cn(...inputs: ClassValue[]) {
5 |   return twMerge(clsx(inputs));
6 | }
7 | 


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/utils/customPDFLoader.ts:
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 1 | import { Document } from 'langchain/document';
 2 | import { readFile } from 'fs/promises';
 3 | import { BaseDocumentLoader } from 'langchain/document_loaders';
 4 | import { CharacterTextSplitter } from 'langchain/text_splitter';
 5 | 
 6 | export abstract class BufferLoader extends BaseDocumentLoader {
 7 |   constructor(public filePathOrBlob: string | Blob) {
 8 |     super();
 9 |   }
10 | 
11 |   protected abstract parse(
12 |     raw: Buffer,
13 |     metadata: Document['metadata'],
14 |   ): Promise<Document[]>;
15 | 
16 |   public async load(): Promise<Document[]> {
17 |     let buffer: Buffer;
18 |     let metadata: Record<string, string>;
19 |     if (typeof this.filePathOrBlob === 'string') {
20 |       buffer = await readFile(this.filePathOrBlob);
21 |       metadata = { source: this.filePathOrBlob };
22 |     } else {
23 |       buffer = await this.filePathOrBlob
24 |         .arrayBuffer()
25 |         .then((ab) => Buffer.from(ab));
26 |       metadata = { source: 'blob', blobType: this.filePathOrBlob.type };
27 |     }
28 |     return this.parse(buffer, metadata);
29 |   }
30 | }
31 | 
32 | export class CustomPDFLoader extends BufferLoader {
33 |   public async parse(
34 |     raw: Buffer,
35 |     metadata: Document['metadata'],
36 |   ): Promise<Document[]> {
37 |     const { pdf } = await PDFLoaderImports();
38 |     const parsed = await pdf(raw);
39 |     const splitter = new CharacterTextSplitter({
40 |       separator: '. ',
41 |       chunkSize: 1000,
42 |       chunkOverlap: 0,
43 |     });
44 |     const rawDocs = new Document({
45 |       pageContent: parsed.text,
46 |       metadata: {
47 |         ...metadata,
48 |         pdf_numpages: parsed.numpages,
49 |       },
50 |     });
51 |     return await splitter.splitDocuments([rawDocs]);
52 |   }
53 | }
54 | 
55 | async function PDFLoaderImports() {
56 |   try {
57 |     // the main entrypoint has some debug code that we don't want to import
58 |     const { default: pdf } = await import('pdf-parse/lib/pdf-parse.js');
59 |     return { pdf };
60 |   } catch (e) {
61 |     console.error(e);
62 |     throw new Error(
63 |       'Failed to load pdf-parse. Please install it with eg. `npm install pdf-parse`.',
64 |     );
65 |   }
66 | }
67 | 


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/utils/makechain.ts:
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 1 | import { ConversationalRetrievalQAChain } from 'langchain/chains';
 2 | import { VectorStore } from 'langchain/dist/vectorstores/base';
 3 | import { OpenAI } from 'langchain/llms/openai';
 4 | 
 5 | const ANSWER_LANGUAGE = process.env.ANSWER_LANGUAGE || 'English';
 6 | const OPENAI_CHAT_MODEL = process.env.OPENAI_CHAT_MODEL || 'gpt-3.5-turbo';
 7 | 
 8 | const CONDENSE_PROMPT = `Given the following conversation and a follow up question, rephrase the follow up question to be a standalone question.
 9 | 
10 | Chat History:
11 | {chat_history}
12 | Follow Up Input: {question}
13 | Standalone question:`;
14 | 
15 | const QA_PROMPT = `You are a helpful AI assistant. Use the following pieces of context to answer the question at the end.
16 | If you don't know the answer, just say you don't know. DO NOT try to make up an answer.
17 | If the question is not related to the context, politely respond that you are tuned to only answer questions that are related to the context.
18 | 
19 | {context}
20 | 
21 | Question: {question}
22 | Helpful answer in markdown(Please answer in ${ANSWER_LANGUAGE}):`;
23 | 
24 | export const makeChain = (vectorstore: VectorStore) => {
25 |   const model = new OpenAI({
26 |     temperature: 0, // increase temepreature to get more creative answers
27 |     modelName: OPENAI_CHAT_MODEL, //change this to gpt-4 if you have access
28 |   });
29 |   const chain = ConversationalRetrievalQAChain.fromLLM(
30 |     model,
31 |     vectorstore.asRetriever(5),
32 |     {
33 |       qaTemplate: QA_PROMPT,
34 |       questionGeneratorTemplate: CONDENSE_PROMPT,
35 |       returnSourceDocuments: true, //The number of source documents returned is 4 by default
36 |     },
37 |   );
38 |   return chain;
39 | };
40 | 


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/visual-guide/gpt-langchain-pdf.png:
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https://raw.githubusercontent.com/anpigon/gpt4-pdf-chatbot-langchain-faiss/8294ffe186924b1d9050bd4fb3600433f92b882b/visual-guide/gpt-langchain-pdf.png


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