⚡ Building applications with LLMs through composability in Go ⚡
GoLC is an innovative project heavily inspired by the LangChain project, aimed at building applications with Large Language Models (LLMs) by leveraging the concept of composability. It provides a framework that enables developers to create and integrate LLM-based applications seamlessly. Through the principles of composability, GoLC allows for the modular construction of LLM-based components, offering flexibility and extensibility to develop powerful language processing applications. By leveraging the capabilities of LLMs and embracing composability, GoLC brings new opportunities to the Golang ecosystem for the development of natural language processing applications.
go get github.com/hupe1980/golc
package main
import (
"context"
"fmt"
"log"
"os"
"github.com/hupe1980/golc"
"github.com/hupe1980/golc/chain"
"github.com/hupe1980/golc/model/llm"
"github.com/hupe1980/golc/schema"
)
func main() {
openai, err := llm.NewOpenAI(os.Getenv("OPENAI_API_KEY"))
if err != nil {
log.Fatal(err)
}
conversationChain, err := chain.NewConversation(openai)
if err != nil {
log.Fatal(err)
}
ctx := context.Background()
result1, err := golc.SimpleCall(ctx, conversationChain, "What year was Einstein born?")
if err != nil {
log.Fatal(err)
}
fmt.Println(result1)
result2, err := golc.SimpleCall(ctx, conversationChain, "Multiply the year by 3.")
if err != nil {
log.Fatal(err)
}
fmt.Println(result2)
}Output:
Einstein was born in 1879.
1879 multiplied by 3 equals 5637.
For more example usage, see _examples.