chore: import upstream snapshot with attribution

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+# Examples
+
+vLLM's examples are organized into the following categories:
+
+- **[`basic/`](../../examples/basic)** – Minimal examples for offline inference and online serving.
+- **[`generate/`](../../examples/generate)** – Text generation examples, including multimodal models.
+- **[`pooling/`](../../examples/pooling)** – Examples for embedding, classification, scoring, reward, etc.
+- **[`speech_to_text/`](../../examples/speech_to_text)** – Speech transcription, translation and real-time audio examples.
+- **[`features/`](../../examples/features)** – Demonstrations of individual vLLM features: automatic prefix caching, speculative decoding, LoRA, structured outputs, prompt embedding, pause/resume, batch invariance, KV events, data parallelism, and more.
+- **[`reasoning/`](../../examples/reasoning)** – Examples for reasoning with vLLM.
+- **[`tool_calling/`](../../examples/tool_calling)** – Examples for function/tool calling with vLLM.
+- **[`applications/`](../../examples/applications)** – Application examples such as simpler api server, chatbots and RAG (Retrieval-Augmented Generation).
+- **[`rl/`](../../examples/rl)** – Reinforcement learning examples.
+- **[`deployment/`](../../examples/deployment)** – Examples for deploying vLLM in production.
+- **[`ray_serving/`](../../examples/ray_serving)** – Scalable serving using Ray.
+- **[`disaggregated/`](../../examples/disaggregated)** – Examples for Disaggregated P/D (Prefill/Decoding) inference, including various kv cache connectors (LMCache, Mooncake, FlexKV, P2P NCCL) and failure recovery.
+- **[`scale_out/`](../../examples/scale_out)** – Examples for Token In <> Token Out API Server.
+- **[`observability/`](../../examples/observability)** – Metrics, logging, tracing (OpenTelemetry), and dashboards (Grafana, Perses).