Popular AI gateway startup LiteLLM ditches controversial startup Delve

Introduction

In this tutorial, you'll learn how to set up and use LiteLLM, an open-source AI gateway that helps developers integrate and manage multiple AI models. This tutorial is perfect for beginners who want to understand how AI gateways work and how to use them to connect to various AI services. LiteLLM acts as a middle layer between your applications and AI providers, making it easier to switch between different AI services and manage costs.

Prerequisites

Before starting this tutorial, you'll need:

• A computer with internet access
• Python 3.7 or higher installed
• Basic understanding of command line interface
• Access to an AI provider account (like OpenAI, Anthropic, or Hugging Face)

Step-by-step Instructions

Step 1: Install Python and Set Up Your Environment

First, ensure you have Python installed on your system. Open your terminal or command prompt and run:

python --version

If Python isn't installed, download and install it from python.org. For this tutorial, we'll use Python 3.8 or higher.

Step 2: Create a New Project Directory

Create a new folder for our LiteLLM project and navigate into it:

mkdir litellm-project
 cd litellm-project

This keeps our files organized and makes it easier to manage dependencies.

Step 3: Install LiteLLM

Install LiteLLM using pip, Python's package installer:

pip install litellm

This command downloads and installs the LiteLLM package, which includes all necessary components to work with AI gateways.

Step 4: Get Your AI Provider API Keys

Before using LiteLLM, you need API keys from AI providers. For this tutorial, we'll use OpenAI:

1. Visit OpenAI's platform
2. Create an account if you don't have one
3. Navigate to the API section
4. Generate a new API key
5. Copy the key for later use

Why this step matters: LiteLLM needs these keys to authenticate with AI services and make requests on your behalf.

Step 5: Create Your First LiteLLM Configuration File

Create a new file called config.yaml in your project directory:

touch config.yaml

Open the file in a text editor and add the following configuration:

model_list:
  - model_name: gpt-3.5-turbo
    litellm_params:
      model: openai/gpt-3.5-turbo
      api_key: sk-...your-openai-key-here...
      api_base: https://api.openai.com/v1

  - model_name: claude-2
    litellm_params:
      model: anthropic/claude-2
      api_key: sk-...your-anthropic-key-here...
      api_base: https://api.anthropic.com/v1

Why this step matters: This configuration file tells LiteLLM which AI models to use and how to connect to them using your API keys.

Step 6: Create a Simple Python Script to Test LiteLLM

Create a file called test_litellm.py:

touch test_litellm.py

Add this code to the file:

import litellm

# Set your API keys (in practice, use environment variables)
import os
os.environ["OPENAI_API_KEY"] = "sk-...your-openai-key-here..."
os.environ["ANTHROPIC_API_KEY"] = "sk-...your-anthropic-key-here..."

# Test calling different models
response1 = litellm.completion(
    model="gpt-3.5-turbo",
    messages=[{"role": "user", "content": "Hello, how are you?"}]
)

print("GPT-3.5 Response:")
print(response1.choices[0].message.content)

response2 = litellm.completion(
    model="claude-2",
    messages=[{"role": "user", "content": "Hello, how are you?"}]
)

print("\nClaude Response:")
print(response2.choices[0].message.content)

Why this step matters: This script demonstrates how LiteLLM can call different AI models through a unified interface, making it easier to switch between providers.

Step 7: Run Your Test Script

Execute your script using Python:

python test_litellm.py

You should see responses from both AI models. If you encounter errors, double-check your API keys and ensure you have internet connectivity.

Step 8: Understanding the Benefits of Using LiteLLM

LiteLLM provides several advantages:

• Unified Interface: Call different AI models with the same function syntax
• Cost Management: Track and control costs across different providers
• Easy Switching: Switch between providers without changing your application code
• Rate Limiting: Handle rate limits automatically

Summary

In this tutorial, you've learned how to set up and use LiteLLM, an AI gateway that helps manage multiple AI providers. You installed LiteLLM, configured it with API keys, and tested it by calling different AI models. LiteLLM simplifies working with AI by providing a consistent interface, making it easier to switch between different AI services and manage costs. This is especially important in the current AI landscape, where security and reliability are paramount considerations.

Remember that while LiteLLM is a powerful tool, always keep your API keys secure and consider using environment variables for sensitive information rather than hardcoding them in your scripts.