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11697f85c5
Embedding models are tiny and can be pulled on-demand. Let's do that so the user doesn't have to do "yet another thing" to get themselves set up. Thanks @hardikjshah for the suggestion. Also fixed a build dependency miss (TODO: distro_codegen needs to actually check that the build template contains all providers mentioned for the run.yaml file) ## Test Plan First run `ollama rm all-minilm:latest`. Run `llama stack build --template ollama && llama stack run ollama --env INFERENCE_MODEL=llama3.2:3b-instruct-fp16`. See that it outputs a "Pulling embedding model `all-minilm:latest`" output and the stack starts up correctly. Verify that `ollama list` shows the model is correctly downloaded. |
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| .. | ||
| bedrock | ||
| cerebras | ||
| dell | ||
| experimental-post-training | ||
| fireworks | ||
| hf-endpoint | ||
| hf-serverless | ||
| meta-reference-gpu | ||
| meta-reference-quantized-gpu | ||
| nvidia | ||
| ollama | ||
| passthrough | ||
| remote-vllm | ||
| sambanova | ||
| tgi | ||
| together | ||
| vllm-gpu | ||
| __init__.py | ||
| template.py | ||