LangChain (Gemini)

For authentication and model list, see Gemini Overview.

This page is a framework integration guide. For the raw HTTP endpoint reference, see Generate Content.

Installation

pip install langchain-google-genai

Code Examples

Python
Node.js

import os
from langchain_google_genai import ChatGoogleGenerativeAI

llm = ChatGoogleGenerativeAI(
  model='gemini-3-flash-preview',
  google_api_key=os.getenv('PIPELLM_API_KEY'),
  transport='rest',
  client_options={'api_endpoint': 'https://api.pipellm.ai'}
)

response = llm.invoke([
  ('user', 'Why is the sky blue?')
])

print(response.content)

import { ChatGoogleGenerativeAI } from '@langchain/google-genai';

const llm = new ChatGoogleGenerativeAI({
  model: 'gemini-3-flash-preview',
  apiKey: process.env.PIPELLM_API_KEY,
  baseUrl: 'https://api.pipellm.ai'
});

const response = await llm.invoke([
  { role: 'user', content: 'Why is the sky blue?' }
]);

console.log(response.content);

Streaming

import os
from langchain_google_genai import ChatGoogleGenerativeAI

llm = ChatGoogleGenerativeAI(
  model='gemini-3-flash-preview',
  google_api_key=os.getenv('PIPELLM_API_KEY'),
  transport='rest',
  client_options={'api_endpoint': 'https://api.pipellm.ai'},
  streaming=True
)

for chunk in llm.stream('Tell me a story'):
  print(chunk.content, end='', flush=True)

Gemini Overview

Headers, models, and native routes

Generate Content

Raw endpoint reference for POST /v1beta/models/{model}:generateContent

Developer Tools Overview

More tools and framework integrations on PipeLLM

LangChain (Anthropic)

Overview

Coding Assistants

Frameworks

Installation

Code Examples

Streaming

Gemini Overview

Generate Content

Developer Tools Overview

​Installation

​Code Examples

​Streaming

​Related Docs

Gemini Overview

Generate Content

Developer Tools Overview

Installation

Code Examples

Streaming

Related Docs