Update README.md

README.md

@@ -117,7 +117,7 @@ curl -X POST http://127.0.0.1:8000/predict -H "Content-Type: application/json" -
 
 ### LLM serving
 LitServe isn’t *just* for LLMs like vLLM or Ollama; it serves any AI model with full control over internals ([learn more](https://lightning.ai/docs/litserve/features/serve-llms)).    
-For easy LLM serving, use [LitGPT](https://github.com/Lightning-AI/litgpt?tab=readme-ov-file#deploy-an-llm) (built on LitServe). 
+For easy LLM serving, integrate [vLLM with LitServe](https://lightning.ai/lightning-ai/studios/deploy-a-private-llama-3-2-rag-api), or use [LitGPT](https://github.com/Lightning-AI/litgpt?tab=readme-ov-file#deploy-an-llm) (built on LitServe). 
 
 ```
 litgpt serve microsoft/phi-2
@@ -146,7 +146,7 @@ Use LitServe to deploy any model or AI service: (Gen AI, classical ML, embedding
 <pre>
 <strong>Toy model:</strong>      <a target="_blank" href="#define-a-server">Hello world</a>
 <strong>LLMs:</strong>           <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-llama-3-2-vision-with-litserve">Llama 3.2</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/openai-fault-tolerant-proxy-server">LLM Proxy server</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-ai-agent-with-tool-use">Agent with tool use</a>
-<strong>RAG:</strong>            <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-a-private-llama-3-1-rag-api">RAG API (LlamaIndex)</a>
+<strong>RAG:</strong>            <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-a-private-llama-3-2-rag-api">vLLM RAG (Llama 3.2)</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-a-private-llama-3-1-rag-api">RAG API (LlamaIndex)</a>
 <strong>NLP:</strong>            <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-any-hugging-face-model-instantly">Hugging face</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-a-hugging-face-bert-model">BERT</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-text-embedding-api-with-litserve">Text embedding API</a>
 <strong>Multimodal:</strong>     <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-open-ai-clip-with-litserve">OpenAI Clip</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-a-multi-modal-llm-with-minicpm">MiniCPM</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-phi3-5-vision-api-with-litserve">Phi-3.5 Vision Instruct</a>, <a target="_blank" href="https://lightning.ai/bhimrajyadav/studios/deploy-and-chat-with-qwen2-vl-using-litserve">Qwen2-VL</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-a-multi-modal-llm-with-pixtral">Pixtral</a>
 <strong>Audio:</strong>          <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-open-ai-s-whisper-model">Whisper</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-an-music-generation-api-with-meta-s-audio-craft">AudioCraft</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-an-audio-generation-api">StableAudio</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-a-noise-cancellation-api-with-deepfilternet">Noise cancellation (DeepFilterNet)</a>
@@ -201,7 +201,7 @@ Reproduce the full benchmarks [here](https://lightning.ai/docs/litserve/home/ben
 
 These results are for image and text classification ML tasks. The performance relationships hold for other ML tasks (embedding, LLM serving, audio, segmentation, object detection, summarization etc...).   
 
-***💡 Note on LLM serving:*** For high-performance LLM serving (like Ollama/VLLM), use [LitGPT](https://github.com/Lightning-AI/litgpt?tab=readme-ov-file#deploy-an-llm) or build your custom VLLM-like server with LitServe. Optimizations like kv-caching, which can be done with LitServe, are needed to maximize LLM performance.
+***💡 Note on LLM serving:*** For high-performance LLM serving (like Ollama/VLLM), integrate [vLLM with LitServe](https://lightning.ai/lightning-ai/studios/deploy-a-private-llama-3-2-rag-api), or use [LitGPT](https://github.com/Lightning-AI/litgpt?tab=readme-ov-file#deploy-an-llm) or build your custom VLLM-like server with LitServe. Optimizations like kv-caching, which can be done with LitServe, are needed to maximize LLM performance.
 
 &nbsp;