Google Gemini + LangChain

from langchain_google_genai import ChatGoogleGenerativeAI

Basic Gemini with LangChain

llm = ChatGoogleGenerativeAI(model="gemini-pro", temperature=0.7)
result = llm.invoke("Write a meal plan for today")
print(result.content)

for chunk in llm.stream("Write a meal plan for today"):
print(chunk.content)
print("---")

Basic Multi Chain

from langchain.prompts import ChatPromptTemplate
from langchain.schema.output_parser import StrOutputParser

prompt = ChatPromptTemplate.from_template(
"tell me about {topic}"
)
output_parser = StrOutputParser()
chain = prompt | llm | output_parser
print(chain.invoke({"topic": "Artificial Intelligence"}))

Multi Modal

import requests
from langchain_core.messages import HumanMessage

llm = ChatGoogleGenerativeAI(model="gemini-pro-vision", temperature=0.7)
image_url = "https://raw.githubusercontent.com/langchain-ai/langchain/master/docs/static/img/agents_vs_chains.png"
content = requests.get(image_url).content

message = HumanMessage(content=[{"type": "text", "text": "What's in this image and who lives there?"},
{"type": "image_url", "image_url": image_url}])
print(llm.invoke([message]).content)