统计 Gemini 词元

此代码示例演示了如何使用 Vertex AI Generative Models API 统计提示中的词元数，并使用 Gemini 模型生成内容。

深入探索

如需查看包含此代码示例的详细文档，请参阅以下内容：

代码示例

Go

在尝试此示例之前，请按照《Vertex AI 快速入门：使用客户端库》中的 Go 设置说明执行操作。 如需了解详情，请参阅 Vertex AI Go API 参考文档。

如需向 Vertex AI 进行身份验证，请设置应用默认凭据。 如需了解详情，请参阅为本地开发环境设置身份验证。 

import (
	"context"
	"fmt"
	"io"
	"mime"
	"path/filepath"

	"cloud.google.com/go/vertexai/genai"
)

// countTokensMultimodal finds the number of tokens for a multimodal prompt (video+text), and writes to w. Then,
// it calls the model with the multimodal prompt and writes token counts from the response metadata to w.
//
// video is a Google Cloud Storage path starting with "gs://"
func countTokensMultimodal(w io.Writer, projectID, location, modelName string) error {
	// location := "us-central1"
	// modelName := "gemini-1.5-flash-001"
	prompt := "Provide a description of the video."
	video := "gs://cloud-samples-data/generative-ai/video/pixel8.mp4"

	ctx := context.Background()

	client, err := genai.NewClient(ctx, projectID, location)
	if err != nil {
		return fmt.Errorf("unable to create client: %w", err)
	}
	defer client.Close()

	model := client.GenerativeModel(modelName)

	part1 := genai.Text(prompt)

	// Given a video file URL, prepare video file as genai.Part
	part2 := genai.FileData{
		MIMEType: mime.TypeByExtension(filepath.Ext(video)),
		FileURI:  video,
	}

	// Finds the total number of tokens for the 2 parts (text, video) of the multimodal prompt,
	// before actually calling the model for inference.
	resp, err := model.CountTokens(ctx, part1, part2)
	if err != nil {
		return err
	}

	fmt.Fprintf(w, "Number of tokens for the multimodal video prompt: %d\n", resp.TotalTokens)

	res, err := model.GenerateContent(ctx, part1, part2)
	if err != nil {
		return fmt.Errorf("unable to generate contents: %w", err)
	}

	// The token counts are also provided in the model response metadata, after inference.
	fmt.Fprintln(w, "\nModel response")
	md := res.UsageMetadata
	fmt.Fprintf(w, "Prompt Token Count: %d\n", md.PromptTokenCount)
	fmt.Fprintf(w, "Candidates Token Count: %d\n", md.CandidatesTokenCount)
	fmt.Fprintf(w, "Total Token Count: %d\n", md.TotalTokenCount)

	return nil
}

Python

在尝试此示例之前，请按照《Vertex AI 快速入门：使用客户端库》中的 Python 设置说明执行操作。 如需了解详情，请参阅 Vertex AI Python API 参考文档。

如需向 Vertex AI 进行身份验证，请设置应用默认凭据。 如需了解详情，请参阅为本地开发环境设置身份验证。 

import vertexai
from vertexai.generative_models import GenerativeModel, Part

# TODO(developer): Update and un-comment below lines
# project_id = "PROJECT_ID"

vertexai.init(project=project_id, location="us-central1")

model = GenerativeModel(model_name="gemini-1.5-flash-001")

contents = [
    Part.from_uri(
        "gs://cloud-samples-data/generative-ai/video/pixel8.mp4",
        mime_type="video/mp4",
    ),
    "Provide a description of the video.",
]

# Prompt tokens count
response = model.count_tokens(contents)
print(f"Prompt Token Count: {response.total_tokens}")
print(f"Prompt Character Count: {response.total_billable_characters}")

# Send text to Gemini
response = model.generate_content(contents)
usage_metadata = response.usage_metadata

# Response tokens count
print(f"Prompt Token Count: {usage_metadata.prompt_token_count}")
print(f"Candidates Token Count: {usage_metadata.candidates_token_count}")
print(f"Total Token Count: {usage_metadata.total_token_count}")

后续步骤

如需搜索和过滤其他 Google Cloud 产品的代码示例，请参阅 Google Cloud 示例浏览器。