kitchen_sink.go•5.35 kB
// Copyright 2025 Google LLC
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package main
import (
"context"
"fmt"
"log"
"net/http"
"github.com/firebase/genkit/go/ai"
"github.com/firebase/genkit/go/genkit"
"github.com/firebase/genkit/go/plugins/firebase"
"github.com/firebase/genkit/go/plugins/googlegenai"
"github.com/firebase/genkit/go/plugins/server"
"google.golang.org/genai"
)
type SearchInput struct {
Query string `json:"query" description:"The search query or topic to search for"`
}
type SearchResult struct {
Title string `json:"title"`
Content string `json:"content"`
}
func main() {
ctx := context.Background()
// Initialize Firebase telemetry
firebase.EnableFirebaseTelemetry(&firebase.FirebaseTelemetryOptions{
ForceDevExport: true, // Force telemetry export in development
})
// Initialize Genkit with plugins
g := genkit.Init(ctx, genkit.WithPlugins(
&googlegenai.GoogleAI{},
))
// Define a tool for web search simulation - using struct input for model compatibility
searchTool := genkit.DefineTool(g, "webSearch",
"Search the web for information about a topic",
func(ctx *ai.ToolContext, input SearchInput) (*SearchResult, error) {
// Simulate search with some realistic results
return &SearchResult{
Title: fmt.Sprintf("Search results for: %s", input.Query),
Content: fmt.Sprintf("Here are the top results about %s with detailed information and recent updates.", input.Query),
}, nil
},
)
// Flow 1: Text with Tools
genkit.DefineFlow(g, "textFlow", func(ctx context.Context, topic string) (string, error) {
if topic == "" {
topic = "artificial intelligence"
}
searchResp, err := genkit.Generate(ctx, g,
ai.WithModelName("googleai/gemini-2.5-flash"),
ai.WithTools(searchTool),
ai.WithConfig(&genai.GenerateContentConfig{
Temperature: genai.Ptr[float32](0.7),
}),
ai.WithPrompt("Research information about %s. Use the webSearch tool to find relevant details.", topic))
if err != nil {
return "", fmt.Errorf("research failed: %w", err)
}
return searchResp.Text(), nil
})
// Flow 2: Image Analysis
type ImageRequest struct {
ImageURL string `json:"imageUrl"`
Prompt string `json:"prompt,omitempty"`
}
genkit.DefineFlow(g, "imageFlow", func(ctx context.Context, req ImageRequest) (string, error) {
prompt := req.Prompt
if prompt == "" {
prompt = "Describe what you see in this image"
}
resp, err := genkit.Generate(ctx, g,
ai.WithModelName("googleai/gemini-2.5-flash"),
ai.WithMessages(
ai.NewUserMessage(
ai.NewTextPart(prompt),
ai.NewMediaPart("", req.ImageURL),
),
),
ai.WithConfig(&genai.GenerateContentConfig{
Temperature: genai.Ptr[float32](0.7),
}))
if err != nil {
return "", fmt.Errorf("image analysis failed: %w", err)
}
return resp.Text(), nil
})
// Flow 3: Batch processing flow
genkit.DefineFlow(g, "batchFlow", func(ctx context.Context, topics []string) (map[string]string, error) {
results := make(map[string]string)
for _, topic := range topics {
resp, err := genkit.Generate(ctx, g,
ai.WithModelName("googleai/gemini-2.5-flash"),
ai.WithConfig(&genai.GenerateContentConfig{
Temperature: genai.Ptr[float32](0.8),
}),
ai.WithPrompt("Generate a brief, interesting fact about %s", topic))
if err != nil {
results[topic] = fmt.Sprintf("Error: %v", err)
} else {
results[topic] = resp.Text()
}
}
return results, nil
})
// Start the server
fmt.Println("Kitchen Sink Telemetry Demo")
fmt.Println("Firebase telemetry with various scenarios:")
fmt.Println(" • Tool calls and function execution")
fmt.Println(" • Multi-step RAG operations")
fmt.Println(" • Batch processing flows")
fmt.Println("")
fmt.Println("Server: http://localhost:3400")
fmt.Println("")
fmt.Println("Test endpoints:")
fmt.Println()
fmt.Println("Text + Tools:")
fmt.Println(`curl -X POST http://localhost:3400/textFlow -H 'Content-Type: application/json' -d '{"data": "machine learning"}'`)
fmt.Println()
fmt.Println("Image Analysis:")
fmt.Println(`curl -X POST http://localhost:3400/imageFlow -H 'Content-Type: application/json' -d '{"data": {"imageUrl": "https://www.google.com/images/branding/googlelogo/2x/googlelogo_color_272x92dp.png", "prompt": "What logo is this?"}}'`)
fmt.Println()
fmt.Println("Batch Processing:")
fmt.Println(`curl -X POST http://localhost:3400/batchFlow -H 'Content-Type: application/json' -d '{"data": ["AI", "robotics", "quantum"]}'`)
mux := http.NewServeMux()
for _, flow := range genkit.ListFlows(g) {
fmt.Printf("Registered flow: %s\n", flow.Name())
mux.HandleFunc("POST /"+flow.Name(), genkit.Handler(flow))
}
fmt.Println("\nAll telemetry modules active - check Google Cloud Console!")
log.Fatal(server.Start(ctx, "127.0.0.1:3400", mux))
}