What Is LiteLLM

LiteLLM is an open-source LLM gateway and proxy that allows developers to access multiple AI models through a single unified API.

Instead of writing different integrations for every AI provider, LiteLLM lets you call them all using one OpenAI-compatible interface.

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Simple Definition

LiteLLM = A universal adapter for AI models.

It sits between your application and different AI providers and routes requests to them.

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Why LiteLLM Exists

Different AI providers use different APIs:

Provider	API Style
OpenAI	OpenAI API
Anthropic	Different API
Google Gemini	Different API
Cohere	Different API
Azure OpenAI	Slightly different

Without LiteLLM, developers must write separate code for each provider.

With LiteLLM, you call:

/v1/chat/completions

and LiteLLM routes the request to any model.

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What LiteLLM Can Do

1️⃣ Unified API for 100+ Models

You can call models from:

• OpenAI
• Anthropic
• Google Gemini
• Mistral
• Cohere
• Azure OpenAI
• Local models (Ollama, vLLM)

All through the same API format.

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2️⃣ LLM Gateway / Proxy

LiteLLM can run as a central AI gateway for your organization.

Example architecture:

Application
      │
      ▼
   LiteLLM
      │
 ┌────┼───────────────┐
 ▼    ▼               ▼
OpenAI  Anthropic   Local LLM

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3️⃣ Model Routing

You can configure rules like:

• Use GPT-4 for complex tasks
• Use Mistral for cheaper requests
• Use local model for internal data

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4️⃣ Cost Tracking

LiteLLM provides:

• per-user cost tracking
• token usage tracking
• API key quotas

This is useful for AI SaaS platforms.

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5️⃣ Rate Limiting

You can set limits like:

User A → 10k tokens/day
User B → 100 requests/hour

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6️⃣ Fallback Models

If one model fails, LiteLLM automatically switches.

Example:

Try GPT-4
   ↓
If fail → Claude
   ↓
If fail → Mistral

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Why Companies Use LiteLLM

It helps companies build AI platforms without vendor lock-in.

Benefits:

• multi-model support
• cost control
• unified API
• reliability
• easy switching of models

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Example API Call

Your app calls LiteLLM like OpenAI:

response = client.chat.completions.create(
    model="gpt-4",
    messages=[{"role": "user", "content": "Hello"}]
)

LiteLLM decides which provider to send it to.

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Example Real Architecture

Many AI platforms run something like this:

Frontend Apps
      │
      ▼
   API Gateway
      │
      ▼
    LiteLLM
      │
 ┌────┼───────────────┐
 ▼    ▼               ▼
OpenAI  Claude     Local Models

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In Our Case

• It act as your central LLM gateway
• support multiple model providers
• track usage and billing
• expose OpenAI compatible APIs to developers

So AgentNXXT platform can support 100+ AI models without rewriting code.

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