LiteLLM: One Unified API for All LLMs

& Announcing Developer Collaborations

LiteLLM - A unified API Endpoint

LiteLLM provides a single OpenAI-style endpoint to call any LLM API.

Supports streaming, tool calling, image inputs & custom endpoints.

Handles provider-specific formats (system prompts, context limits) while maintaining OpenAI syntax. Open source with enterprise backing.

Cheers, Ronan

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Developer Collaborations

Trelis offers enterprising developers the opportunity to collaborate on a product/video for the Trelis Youtube channel.

Here’s what you can expect:

• Recognition: Your contribution will be highlighted in the final video, drawing attention to your work.

• Payment: $500 upon completing the project and the video being published on time.

• Bonus: Possible additional payment if the product/video performs well (at Trelis' discretion).

• Ownership: All products and videos from this collaboration belong to Trelis.

• Project-Based: This is not an offer of employment. It’s a project-based collaboration.

• Pre-defined or Custom Projects: If selected for interview, you'll be offered a range of pre-defined projects to choose from OR the option to propose your own.

Trelis looks for applicants with creative, well-documented GitHub repositories and/or project portfolios.

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Unified API Access with LiteLLM: A Technical Overview

LiteLLM provides a single OpenAI-style endpoint to interact with multiple language model APIs, simplifying development and maintenance. Here's a detailed look at its key capabilities and implementation.

Core Features

• - **Unified API Format**: Converts all API calls to OpenAI-style syntax

• - **Wide Model Support**: Works with OpenAI, Anthropic, Google (Gemini), and custom endpoints

• - **Installation**: Simple pip install: `pip install litellm`

• - **API Key Management**: Requires standard provider keys (OpenAI, Anthropic, etc.)

Implementation Examples

Basic Usage

• - Uses standard OpenAI completion parameters

• - Requires provider prefix in model names (e.g., "openai/gpt-4o")

• - Supports common parameters like temperature, max_tokens

System Messages

• - Maintains OpenAI-style message format

• - Works across providers without syntax changes

Advanced Features

• - **Streaming**: Enabled via `stream=True` parameter

• - **Tool Calling**: Supports function calling across providers

• - **Long Context**: Handles provider-specific context limits appropriately

• - **Image Input**: Supports base64-encoded images or URLs

Custom Endpoint Integration

RunPod Setup

• - Uses port 8000 by default

• - Requires pod ID configuration

• - Supports models like LLAMA 3.1 8B with sglang

Local Deployment (LM Studio)

• - Runs on localhost:1234

• - Compatible with various open-source models

• - Recommend 8-bit quantized models for quality

Technical Benefits

• - Code reduction: ~3x less code compared to managing three separate APIs

• - Consistent error handling across providers

• - Simplified model switching

• - Standardized parameter passing

LiteLLM provides a robust solution for unified API access while maintaining provider-specific optimizations and capabilities.