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Introduces the unified NeMo inference server with a pluggable backend architecture. All backend-specific logic lives in backend modules, not the server. Backends declare their config via get_config_class() and can register additional routes via get_extra_routes(). - recipes/multimodal/server/unified_server.py: Generic FastAPI server with request batching and OpenAI-compatible /v1/chat/completions - recipes/multimodal/server/backends/base.py: Abstract InferenceBackend with get_config_class(), get_extra_routes() for future extensibility - recipes/multimodal/server/backends/__init__.py: Lazy-loading registry - nemo_skills/inference/server/serve_unified.py: CLI entrypoint with YAML config support and backward-compatible CLI args Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Replace ~20 hard-coded backend-specific CLI arguments with a generic parse_extra_args() that converts unknown flags to a config dict. This makes serve_unified.py truly backend-agnostic — new backends no longer need to edit the server entrypoint. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Implements MagpieTTSBackend with get_config_class() for the refactored unified server. Includes all bugfixes from the feature branch: - Checkpoint + hparams loading (alternative to .nemo) - Dummy wav for missing context audio - Decoder cache reset per request batch - HF resolve URL caching via huggingface_hub - KV cache disabled to avoid shape mismatches - Batch size configurable via config Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Summary
InferenceBackendinterfaceget_config_class()returningMagpieTTSConfigfor YAML-based configurationBugfixes included
.nemofilehuggingface_hubto avoid 429sDepends on
Files
recipes/multimodal/server/backends/magpie_tts_backend.py— full backend implementationTest plan
--backend magpie_tts --model /path --codec_model /path🤖 Generated with Claude Code