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main.go
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package main
import (
"fmt"
"log"
"os"
"github.com/joho/godotenv"
"github.com/parakeet-nest/parakeet/completion"
"github.com/parakeet-nest/parakeet/embeddings"
"github.com/parakeet-nest/parakeet/llm"
)
func main() {
err := godotenv.Load()
if err != nil {
log.Fatalln("😡:", err)
}
url := "http://localhost:11434/v1"
embeddingsModel := "mxbai-embed-large"
model := "qwen2.5:14b"
elasticStore := embeddings.ElasticsearchStore{}
err = elasticStore.Initialize(
[]string{
os.Getenv("ELASTICSEARCH_URL"),
},
os.Getenv("ELASTICSEARCH_USER"),
os.Getenv("ELASTICSEARCH_PASSWORD"),
nil,
"mxbai-golang-index",
)
if err != nil {
log.Fatalln("😡:", err)
}
userContent := `Summarize what's new with benchmarks in 3 bullet points. Be succinct`
// Create an embedding from the question
embeddingFromQuestion, err := embeddings.CreateEmbeddingWithOpenAI(
url,
llm.OpenAIQuery4Embedding{
Model: embeddingsModel,
Input: userContent,
},
"question",
)
if err != nil {
log.Fatalln("😡:", err)
}
fmt.Println("🔎 searching for similarity...")
similarities, err := elasticStore.SearchTopNSimilarities(embeddingFromQuestion, 5)
for _, similarity := range similarities {
fmt.Println("📝 doc:", similarity.Id, "score:", similarity.Score)
}
if err != nil {
log.Fatalln("😡:", err)
}
documentsContent := embeddings.GenerateContentFromSimilarities(similarities)
fmt.Println("Context is now: ", documentsContent)
systemContent := `You are a Golang expert.
Using only the below provided context, answer the user's question
to the best of your ability using only the resources provided.
`
queryChat := llm.OpenAIQuery{
Model: model,
Messages: []llm.Message{
{Role: "system", Content: systemContent},
{Role: "system", Content: documentsContent},
{Role: "user", Content: userContent},
},
}
fmt.Println()
fmt.Println("🤖 answer:")
// Answer the question
_, err = completion.ChatWithOpenAIStream(url, queryChat,
func(answer llm.OpenAIAnswer) error {
fmt.Print(answer.Choices[0].Delta.Content)
return nil
})
if err != nil {
log.Fatal("😡:", err)
}
fmt.Println()
}