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# SGLang Provider Shape
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Last updated: dev@e57f60b | 2026-07-20
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## Scope
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Canonical provider ID `sglang`; OpenAI Chat/Responses plus native generation;
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Cookbook launch behavior in `routes/cookbook_routes.py` and serving UI modules.
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There is no dedicated SGLang canonical reader on current `dev`.
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## Metadata Shapes
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Preferred native `GET /model_info` (legacy `/get_model_info`) returns:
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- `model_path` and `tokenizer_path`;
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- `is_generation`;
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- `has_image_understanding` and `has_audio_understanding`;
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- `model_type`, `architectures`, `weight_version`;
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- `preferred_sampling_params`.
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These are provider observations for a future dedicated reader. Current generic
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normalization does not map `is_generation`, modality booleans, sampling keys,
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or `max_model_len`.
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`GET /v1/models` returns served IDs with `owned_by: sglang`, `root`, and
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`max_model_len`; it supplies identity/context but not parser capability.
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## Runtime Capability
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Tools and reasoning depend on explicit `--tool-call-parser` and
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`--reasoning-parser`; multimodality and context can also be launch-configured.
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Cookbook recipes for Qwen, DeepSeek, GLM, Kimi, MiniMax, StepFun, and other
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families are deployment observations, not universal model-name rules. Persist
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the selected parser/config as endpoint evidence before canonical promotion.
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## Fallback And Safety
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Current reader detection identifies port 30000 as SGLang, or accepts an
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explicit endpoint kind, then dispatches to the generic identity-only reader.
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It does not infer SGLang from `/model_info` payload shape. Avoid normal
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discovery through the broad admin `/server_info` dump.
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## Current Gaps
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- Endpoint records do not yet store parser/task configuration canonically.
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- Non-generation task classification needs explicit serving metadata.
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- No dedicated reader maps SGLang metadata today.
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