Gemini

出た直後の情報はっつけ

公式、利用例 notebooks

画像に関するベスト プラクティス

がある、テキストの前に画像を置く / 複数置く場合はインデックスつける等

モデル情報

en のほう見るべき

pro は json schema 指定できるようになっていた

Colab でちょっと試す時のコピペ用

code:colab.py

import google

google.colab.auth.authenticate_user()

import vertexai

from vertexai.generative_models import (

GenerationConfig,

GenerativeModel,

)

project = "pokutuna-playground"

location = "us-central1"

vertexai.init(project=project, location=location)

model_id = "gemini-1.5-pro-001" # or "gemini-1.5-flash-001"

model = GenerativeModel(

model_id,

)

generation_config = GenerationConfig(

candidate_count=1,

# ...

)

res = model.generate_content(

generation_config=generation_config,

)

print(res.text)

token 数見る

とある電子書籍1冊入れるとして

code:count_tokens.py

from pprint import pprint

import vertexai

from vertexai.generative_models import (

GenerativeModel,

)

project = "pokutuna-playground"

location = "asia-northeast1"

vertexai.init(project=project, location=location)

model_id = "gemini-1.5-pro-preview-0409"

model = GenerativeModel(model_id)

pprint(f"chars: {len(content)}")

# => chars: 240926

pprint(f"tokens: {model.count_tokens(content)}")

# => tokens: total_tokens: 117983\ntotal_billable_characters: 232291\n

node で readline 使いつつチャット

code:chat.ts

import { VertexAI } from "@google-cloud/vertexai";

import * as readline from "readline";

const project = "pokutuna-playground";

const location = "us-central1";

const model = "gemini-1.5-pro-preview-0409";

const vertexAI = new VertexAI({ project, location });

const genModel = vertexAI.getGenerativeModel({ model });

const chat = genModel.startChat();

const rl = readline.createInterface({

input: process.stdin,

output: process.stdout,

});

async function* userMessageGenerator(rl: readline.Interface): AsyncGenerator<string> {

while (true) {

const input = await new Promise<string>((resolve) => {

rl.question("> ", (input) => resolve(input));

});

if (/^\s*$/.test(input)) break;

yield input;

}

}

for await (const input of userMessageGenerator(rl)) {

const res = await chat.sendMessageStream(input);

for await (const item of res.stream) {

}

}

rl.close();