https://raw.githubusercontent.com/OrcVole/vllm-cloudron/main/CloudronVersions.json
Description
`0.28.0
vLLM is a high-throughput inference server for large language models with the most widely
supported OpenAI-compatible API of the self-hosted options. This package runs it as a
Cloudron app: one install serves one model at https://<location>/v1, protected by a
generated API key, with weights cached locally and every OpenAI-style client able to connect
unchanged.
This is CPU inference (amd64). It will not match GPU speed and it is not meant to: it gives integrations, automations and privacy-sensitive workloads a fully self-hosted OpenAI endpoint on the server you already run. Pair it with a chat frontend, an AI gateway, embeddings and a vector store to complete a private AI stack on Cloudron.
Unofficial community package. Not affiliated with the vLLM project or Cloudron.
Recent Changes
Update vLLM 0.27.1 -> 0.28.0
Security: fixes prevent denial of service via forged audio sample rates and oversized image inputs, unauthenticated access to API endpoints, arbitrary code execution from untrusted model repositories, and resource exhaustion from unbounded generation requests
Breaking: bitsandbytes quantization moved to an out-of-tree plugin; Transformers dependency bumped to 5.15.0; removed flags
calculate_kv_scalesandoverride_attention_dtype;reasoning_contentno longer included in output; MoE legacy code paths removed;cache_saltnow required to be non-emptyBehaviour changes:
max_num_batched_tokensdefault raised to 16384; prefix caching now enabled by default for Mamba models; Blackwell CUDA graph capture default raised to 1024; KV offload tiering metrics renamed from block to chunkPackaging: pin moved; /dev/shm detection in start.sh unchanged and still required
