vLLM /generate Endpoint Lacks Native Raw Multimodal Input Support for RL Workloads
Reinforcement learning frameworks need token-level inference calls that include raw multimodal data such as images and audio, but vLLM's /generate endpoint only accepts token IDs while multimodal support requires the higher-level chat completions path or an inefficient render-then-generate round trip. This forces RL callers to either serialize large media payloads over the wire or restructure their calling pattern around an API not designed for their token-first workflow.
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Problem descriptions, scores, analysis, and solution blueprints may be updated as new community data becomes available.