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llm-interface
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A simple, unified interface for integrating and interacting with multiple Large Language Model (LLM) APIs, including OpenAI, Anthropic, Google Gemini, Groq, and LlamaCPP.
The LLM Interface project is a versatile and comprehensive wrapper designed to interact with multiple Large Language Model (LLM) APIs. It simplifies integrating various LLM providers, including OpenAI, AI21 Studio, Anthropic, Cohere, Google Gemini, Goose AI, Groq, Hugging Face, Mistral AI, Perplexity, Reka AI, and LLaMA.cpp, into your applications. This project aims to provide a simplified and unified interface for sending messages and receiving responses from different LLM services, making it easier for developers to work with multiple LLMs without worrying about the specific intricacies of each API.
v0.0.11
v0.0.10
json_object
mode now guarantees the return a valid JSON object or null.v0.0.9
The project relies on several npm packages and APIs. Here are the primary dependencies:
axios
: For making HTTP requests (used for various HTTP AI APIs).@anthropic-ai/sdk
: SDK for interacting with the Anthropic API.@google/generative-ai
: SDK for interacting with the Google Gemini API.groq-sdk
: SDK for interacting with the Groq API.openai
: SDK for interacting with the OpenAI API.dotenv
: For managing environment variables. Used by test cases.flat-cache
: For caching API responses to improve performance and reduce redundant requests.jest
: For running test cases.To install the llm-interface
package, you can use npm:
npm install llm-interface
Import llm-interface
using:
const LLMInterface = require("llm-interface");
or
import LLMInterface from "llm-interface";
then call the handler you want to use:
const openai = new LLMInterface.openai(process.env.OPENAI_API_KEY);
const message = {
model: "gpt-3.5-turbo",
messages: [
{ role: "system", content: "You are a helpful assistant." },
{ role: "user", content: "Explain the importance of low latency LLMs." },
],
};
openai
.sendMessage(message, { max_tokens: 150 })
.then((response) => {
console.log(response);
})
.catch((error) => {
console.error(error);
});
or if you want to keep things simple you can use:
const openai = new LLMInterface.openai(process.env.OPENAI_API_KEY);
openai
.sendMessage("Explain the importance of low latency LLMs.")
.then((response) => {
console.log(response);
})
.catch((error) => {
console.error(error);
});
If you need API Keys, use this starting point. Additional usage examples and an API reference are available. You may also wish to review the test cases for further examples.
The project includes tests for each LLM handler. To run the tests, use the following command:
npm test
Contributions to this project are welcome. Please fork the repository and submit a pull request with your changes or improvements.
This project is licensed under the MIT License - see the LICENSE file for details.
FAQs
A simple, unified NPM-based interface for interacting with multiple Large Language Model (LLM) APIs, including OpenAI, AI21 Studio, Anthropic, Cloudflare AI, Cohere, Fireworks AI, Google Gemini, Goose AI, Groq, Hugging Face, Mistral AI, Perplexity, Reka A
The npm package llm-interface receives a total of 71 weekly downloads. As such, llm-interface popularity was classified as not popular.
We found that llm-interface demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 0 open source maintainers collaborating on the project.
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