Perplexity - Chroma — ContextQMD

Chroma provides a convenient wrapper around Perplexity's embedding API. This embedding function runs remotely on Perplexity's servers, and requires an API key. You can get an API key by signing up for an account at Perplexity.

This embedding function relies on the perplexityai python package, which you can install with pip install perplexityai.

python

import chromadb.utils.embedding_functions as embedding_functions

perplexity_ef = embedding_functions.PerplexityEmbeddingFunction(
    api_key="YOUR_API_KEY",
    model_name="pplx-embed-v1-4b"
)

perplexity_ef(input=["document1", "document2"])

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typescript

// npm install @chroma-core/perplexity

import { PerplexityEmbeddingFunction } from "@chroma-core/perplexity";

const embedder = new PerplexityEmbeddingFunction({
    apiKey: "YOUR_API_KEY",
    modelName: "pplx-embed-v1-4b",
});

// use directly
const embeddings = await embedder.generate(["document1", "document2"]);

// pass documents to query for .add and .query
const collection = await client.createCollection({
    name: "name",
    embeddingFunction: embedder,
});
const collectionGet = await client.getCollection({
    name: "name",
    embeddingFunction: embedder,
});

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Available Models

Perplexity offers two embedding models:

Model	Dimensions	Context Window	Price
`pplx-embed-v1-0.6b`	1024	32K tokens	$0.004/1M tokens
`pplx-embed-v1-4b`	2560	32K tokens	$0.03/1M tokens

Matryoshka Dimensions

Both models support Matryoshka Representation Learning, allowing you to reduce embedding dimensions while maintaining quality. This is useful for reducing storage costs and improving search speed.

python

# Reduce dimensions from 2560 to 512 for the 4b model
perplexity_ef = embedding_functions.PerplexityEmbeddingFunction(
    api_key="YOUR_API_KEY",
    model_name="pplx-embed-v1-4b",
    dimensions=512
)

embeddings = perplexity_ef(input=["document1", "document2"])
print(len(embeddings[0]))  # 512

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typescript

// Reduce dimensions from 2560 to 512 for the 4b model
const embedder = new PerplexityEmbeddingFunction({
    apiKey: "YOUR_API_KEY",
    modelName: "pplx-embed-v1-4b",
    dimensions: 512,
});

const embeddings = await embedder.generate(["document1", "document2"]);
console.log(embeddings[0].length);  // 512

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Supported dimension ranges:

pplx-embed-v1-0.6b: 128 to 1024
pplx-embed-v1-4b: 128 to 2560

For more details on Perplexity's embedding models, check the documentation.