dguiducci
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DeepInfra's chat API is plain OpenAI-compatible (api.deepinfra.com/v1/openai)
and its GET /models returns the OpenAI data envelope, but the declared
engine could not describe it: metadata sits under dotted paths
(metadata.context_length, metadata.pricing.*), capabilities ride a
metadata.tags string array, and the catalog mixes in tts/stt/embed/image
models with no way to keep only chat ones.
Three generic extensions to the declared engine close that, usable by any
future provider entry:
- map field names accept dotted paths (metadata.pricing.input_tokens)
- map.tags + map.capability_tags enable a capability when the model's
tags array contains a value (a vision one also sets the vision flag)
- models.filter { field, contains } keeps only listed models whose
string-array field holds the value (endpoint listings only)
The deepinfra entry filters on the chat tag, maps context/pricing/vision/
reasoning from the live catalog, and wires the flat reasoning_effort knob
(disabled remaps to none) for models tagged reasoning_effort.