Add vision support to LlamaLanguageModel via mtmd - #213
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streamResponse consumed an inner AsyncThrowingStream whose builder ran the entire generation loop synchronously on the consuming task, so every snapshot buffered and arrived in one burst after generation finished. Yield snapshots directly from the generation loop on the streaming task, and check for task cancellation between tokens so an abandoned stream stops decoding promptly.
Image segments threw unsupportedFeature because the backend had no multimodal path, even though the prebuilt llama.cpp binaries ship the mtmd library and its helpers. Accept an mmprojPath at initialization and load the projector next to the model. When a projector is present, prompt formatting replaces each image segment with the mtmd media marker and collects payloads in order, then generation tokenizes the marker-annotated prompt with mtmd_tokenize and evaluates text and image chunks through mtmd_helper_eval_chunks before sampling continues from the resulting position. Both respond and streaming support images, and models without a projector keep rejecting image input. Adds live tests generating from an embedded test image through both paths.
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Image segments threw unsupportedFeature because the backend had no multimodal path, even though the prebuilt llama.cpp binaries ship the mtmd library. This accepts an mmprojPath at initialization, replaces image segments with the mtmd media marker during prompt formatting, and evaluates text and image chunks through mtmd_helper_eval_chunks before sampling continues. Both respond and streaming support images, and models without a projector keep rejecting image input. Stacks on #195; the squash-merge will sort out the shared commit.