Genkit MCP
Official
by firebase
// Copyright 2024 Google LLC
// SPDX-License-Identifier: Apache-2.0
// [START main]
package main
import (
"context"
"errors"
"fmt"
"log"
// Import Genkit and the Google AI plugin
"github.com/firebase/genkit/go/ai"
"github.com/firebase/genkit/go/genkit"
"github.com/firebase/genkit/go/plugins/googleai"
)
func main() {
ctx := context.Background()
g, err := genkit.Init(ctx)
if err != nil {
log.Fatal(err)
}
// Initialize the Google AI plugin. When you pass nil for the
// Config parameter, the Google AI plugin will get the API key from the
// GOOGLE_GENAI_API_KEY environment variable, which is the recommended
// practice.
if err := googleai.Init(ctx, g, nil); err != nil {
log.Fatal(err)
}
// Define a simple flow that prompts an LLM to generate menu suggestions.
genkit.DefineFlow(g, "menuSuggestionFlow", func(ctx context.Context, input string) (string, error) {
// The Google AI API provides access to several generative models. Here,
// we specify gemini-1.5-flash.
m := googleai.Model(g, "gemini-1.5-flash")
if m == nil {
return "", errors.New("menuSuggestionFlow: failed to find model")
}
// Construct a request and send it to the model API (Google AI).
resp, err := genkit.Generate(ctx, g,
ai.WithModel(m),
ai.WithConfig(&ai.GenerationCommonConfig{Temperature: 1}),
ai.WithTextPrompt(fmt.Sprintf(`Suggest an item for the menu of a %s themed restaurant`, input)))
if err != nil {
return "", err
}
// Handle the response from the model API. In this sample, we just
// convert it to a string. but more complicated flows might coerce the
// response into structured output or chain the response into another
// LLM call.
text := resp.Text()
return text, nil
})
<-ctx.Done()
}
// [END main]