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Langchain Go

Langchain Go is a framework for developing data-aware applications powered by language models in Go.

You can use Qdrant as a vector store in Langchain Go.

Setup

Install the langchain-go project dependency

go get -u github.com/tmc/langchaingo

Usage

Before you use the following code sample, customize the following values for your configuration:

  • YOUR_QDRANT_REST_URL: If you’ve set up Qdrant using the Quick Start guide, set this value to http://localhost:6333.
  • YOUR_COLLECTION_NAME: Use our Collections guide to create or list collections.
package main

import (
	"log"
	"net/url"

	"github.com/tmc/langchaingo/embeddings"
	"github.com/tmc/langchaingo/llms/openai"
	"github.com/tmc/langchaingo/vectorstores/qdrant"
)

func main() {
	llm, err := openai.New()
	if err != nil {
		log.Fatal(err)
	}

	e, err := embeddings.NewEmbedder(llm)
	if err != nil {
		log.Fatal(err)
	}

	url, err := url.Parse("YOUR_QDRANT_REST_URL")
	if err != nil {
		log.Fatal(err)
	}

	store, err := qdrant.New(
		qdrant.WithURL(*url),
		qdrant.WithCollectionName("YOUR_COLLECTION_NAME"),
		qdrant.WithEmbedder(e),
	)
	if err != nil {
		log.Fatal(err)
	}
}

Further Reading

Langchain Go