Built in
π CSV
Get Started
Components
- EmbedJs Components
- ποΈ Data sources
- ποΈ Vector databases
- π€ Large language models
- 𧩠Embedding models
- β‘ Stores
Integrations
Product
Built in
π CSV
You can load any csv file from your local file system or through a URL.
Headers are included for each line, so if you have an age
column, 18
will be added as age: 18
.
Install CSV addon
npm install @llm-tools/embedjs-loader-csv
Usage
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 { CsvLoader } from '@llm-tools/embedjs-loader-csv';
const app = await new RAGApplicationBuilder()
.setModel(SIMPLE_MODELS.OPENAI_GPT4_O)
.setEmbeddingModel(new OpenAiEmbeddings())
.setVectorDatabase(new HNSWDb())
.build();
app.addLoader(new CsvLoader({ filePathOrUrl: '/path/to/file.csv' }))
Load from URL
import { RAGApplicationBuilder } from '@llm-tools/embedjs';
import { OpenAiEmbeddings } from '@llm-tools/embedjs-openai';
import { HNSWDb } from '@llm-tools/embedjs-hnswlib';
import { CsvLoader } from '@llm-tools/embedjs-loader-csv';
const app = await new RAGApplicationBuilder()
.setModel(SIMPLE_MODELS.OPENAI_GPT4_O)
.setEmbeddingModel(new OpenAiEmbeddings())
.setVectorDatabase(new HNSWDb())
.build();
app.addLoader(new CsvLoader({ filePathOrUrl: 'https://people.sc.fsu.edu/~jburkardt/data/csv/airtravel.csv' }))