You can load any pdf file from your local file system or through a URL.

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Install PDF addon

npm install @llm-tools/embedjs-loader-pdf

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Usage

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Load from a local file

import { RAGApplicationBuilder } from '@llm-tools/embedjs';
import { OpenAiEmbeddings } from '@llm-tools/embedjs-openai';
import { HNSWDb } from '@llm-tools/embedjs-hnswlib';
import { PdfLoader } from '@llm-tools/embedjs-loader-pdf';

const app = await new RAGApplicationBuilder()
.setModel(SIMPLE_MODELS.OPENAI_GPT4_O)
.setEmbeddingModel(new OpenAiEmbeddings())
.setVectorDatabase(new HNSWDb())
.build();

app.addLoader(new PdfLoader({ filePathOrUrl: '/path/to/file.pdf' }))

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Load from URL

import { RAGApplicationBuilder } from '@llm-tools/embedjs';
import { OpenAiEmbeddings } from '@llm-tools/embedjs-openai';
import { HNSWDb } from '@llm-tools/embedjs-hnswlib';
import { PdfLoader } from '@llm-tools/embedjs-loader-pdf';

const app = await new RAGApplicationBuilder()
.setModel(SIMPLE_MODELS.OPENAI_GPT4_O)
.setEmbeddingModel(new OpenAiEmbeddings())
.setVectorDatabase(new HNSWDb())
.build();

await app.addLoader(new PdfLoader({ filePathOrUrl: 'https://arxiv.org/pdf/1706.03762.pdf' }))
await app.query("What is the paper 'attention is all you need' about?");
Note that we do not support password protected pdf files.