Prompt

llm sdk python javascript

Artificial Intelligence / AI Platforms1 observationLast seen Oct 8, 2026

Latest observation

Oct 8, 2026OpenAI APIWeb search: off

If you’re looking for LLM SDKs in Python and JavaScript, here are the most common options:

Python

Popular SDKs/libraries:

  • OpenAI Python SDK — for OpenAI models
    • pip install openai
  • Anthropic SDK — for Claude
    • pip install anthropic
  • Google Gemini SDK
    • pip install google-generativeai
  • LangChain — orchestration framework for multiple LLMs
    • pip install langchain
  • LlamaIndex — retrieval + LLM apps
    • pip install llama-index

Example (OpenAI, Python):

from openai import OpenAI

client = OpenAI(api_key="YOUR_API_KEY")

resp = client.responses.create(
    model="gpt-4.1-mini",
    input="Write a short poem about the sea."
)

print(resp.output_text)

JavaScript / TypeScript

Popular SDKs/libraries:

  • OpenAI JS SDK
    • npm install openai
  • Anthropic SDK
    • npm install @anthropic-ai/sdk
  • Google Gemini SDK
    • npm install @google/generative-ai
  • LangChain JS
    • npm install langchain
  • LlamaIndex TS
    • npm install llamaindex

Example (OpenAI, JavaScript):

import OpenAI from "openai";

const client = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });

const resp = await client.responses.create({
  model: "gpt-4.1-mini",
  input: "Write a short poem about the sea."
});

console.log(resp.output_text);

If you mean “which is better?”

  • Python: better for AI/ML workflows, data processing, backend pipelines
  • JavaScript: better for web apps, frontends, Node.js backends

Common choices

  • Direct API SDK: OpenAI / Anthropic / Gemini
  • Multi-model abstraction: LangChain
  • RAG/document apps: LlamaIndex

If you want, I can also give you:

  1. a comparison table of Python vs JavaScript LLM SDKs, or
  2. a minimal working example for OpenAI in both languages.

Observation history

How did Obsurfable measure this prompt?

Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.

Which AI systems does Obsurfable collect answers from?

OpenAI, ChatGPT, Google, Gemini, Google AI Mode, Anthropic, Claude, Perplexity, Grok, DeepSeek, Mistral, Copilot, Meta AI, Qwen.

How can brands improve their AEO?

Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as dotdotPR. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.

Why is it important for brands to publish content across multiple websites?

Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.

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