LangChainでGeminiを使用する

import vertexai
from langchain_google_vertexai import ChatVertexAI

vertexai.init(
    project="xxx",
    location="asia-northeast1"
)

llm = ChatVertexAI(
    model="gemini-1.5-flash-002",
    temperature=0,
    max_tokens=None,
    max_retries=6,
    stop=None,
)

messages = [
    (
        "system",
        "You are a helpful assistant that translates English to French. Translate the user sentence.",
    ),
    ("human", "I love programming."),
]
ai_msg = llm.invoke(messages)
print(ai_msg.content)

gcloud auth application-default login

import vertexai
from langchain_google_vertexai import ChatVertexAI
from langchain_core.prompts import ChatPromptTemplate

prompt = ChatPromptTemplate.from_messages(
    [
        (
            "system",
            "You are a helpful assistant that translates {input_language} to {output_language}.",
        ),
        ("human", "{input}"),
    ]
)

chain = prompt | llm
chain.invoke(
    {
        "input_language": "English",
        "output_language": "Japanese",
        "input": "I love programming.",
    }
).content

from langchain_core.messages import HumanMessage
import base64
import httpx

image_url = "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
image_data = base64.b64encode(httpx.get(image_url).content).decode("utf-8")

message = HumanMessage(
    content=[
        {"type": "text", "text": "describe the weather in this image"},
        {
            "type": "image_url",
            "image_url": {"url": f"data:image/jpeg;base64,{image_data}"},
        },
    ],
)
# llmはsample1で定義したgeminiモデル
response = llm.invoke([message])
print(response.content)

message = HumanMessage(
    content=[
        {"type": "text", "text": "describe the weather in this image"},
        {"type": "image_url", "image_url": {"url": image_url}},
    ],
)
response = llm.invoke([message])
print(response.content)