landing_page/qdrant-landing/content/documentation/frameworks/langchain-go.md

title, weight

title	weight
Langchain Go	120

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.

import (
        "fmt"
        "log"

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

 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

• You can find usage examples of Langchain Go here.