"examples/vscode:/vscode.git/clone" did not exist on "08fd28978c1480e5ec07f4dc82d9befa24908230"
- 06 May, 2025 2 commits
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hhzhang16 authored
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Graham King authored
Adding this to a Python script makes it register on the network so that `dynamo-run` can discover it and send it requests: ``` from dynamo.llm import register_llm MODEL = "Qwen/Qwen2.5-0.5B-Instruct" await register_llm(endpoint, MODEL, 3) ``` Full vllm example, with pre-processing in dynamo: - `dynamo-run in=text out=dyn://dynamo.backend.generate` - `cd lib/bindings/python/examples/hello_world` - `python server_vllm.py` This builds on top of the work to move pre-processor to ingress side. It means we can decouple Rust and Python using NATS as the bus. The `register_llm` call does this: - Download the model from HF if necessary - Load the model deployment card from the HF folder or extract from GGUF - Push the tokenizer config etc into NATS object store so ingress can access it from a different machine - Publish the model deployment card to ETCD
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- 05 May, 2025 6 commits
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julienmancuso authored
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Hongkuan Zhou authored
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richardhuo-nv authored
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julienmancuso authored
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Harrison Saturley-Hall authored
Signed-off-by:
Harrison Saturley-Hall <454891+saturley-hall@users.noreply.github.com> Co-authored-by:
Anant Sharma <anants@nvidia.com>
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Hongkuan Zhou authored
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- 02 May, 2025 3 commits
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Tanmay Verma authored
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Ryan McCormick authored
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Kris Hung authored
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- 01 May, 2025 7 commits
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hhzhang16 authored
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Graham King authored
Part of https://github.com/ai-dynamo/dynamo/issues/743
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Biswa Panda authored
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Abrar Shivani authored
The build script currently fails on macOS due to an incompatible Bash version. This PR adds a version check to ensure the correct Bash version is being used before proceeding. Closes GitHub issue: https://github.com/ai-dynamo/dynamo/issues/318
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Abrar Shivani authored
Allow `hf://` prefix on command line. Closes GitHub issue: https://github.com/ai-dynamo/dynamo/issues/829
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Yan Ru Pei authored
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Ziqi Fan authored
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- 30 Apr, 2025 5 commits
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Biswa Panda authored
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ishandhanani authored
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Yan Ru Pei authored
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hhzhang16 authored
Signed-off-by:
hhzhang16 <54051230+hhzhang16@users.noreply.github.com> Co-authored-by:
mohammedabdulwahhab <furkhan324@berkeley.edu>
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julienmancuso authored
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- 29 Apr, 2025 13 commits
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mohammedabdulwahhab authored
Signed-off-by:
mohammedabdulwahhab <furkhan324@berkeley.edu> Co-authored-by:
hhzhang16 <54051230+hhzhang16@users.noreply.github.com>
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julienmancuso authored
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wxsm authored
Signed-off-by:
wxsm <wxsms@foxmail.com> Co-authored-by:
ptarasiewiczNV <104908264+ptarasiewiczNV@users.noreply.github.com>
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Abrar Shivani authored
Adds support for specifying default request parameters through a json template file that can be applied across all inference requests. This enables consistent parameter settings while still allowing per-request overrides. Changes: - Add --request-template CLI flag to specify template file path - Integrate template support in HTTP, batch and text input modes - Template values can be overridden by individual request parameters - Example template.json: ``` { "model": "Qwen2.5-3B-Instruct", "temperature": 0.7, "max_completion_tokens": 4096 } ``` -
Graham King authored
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Hongkuan Zhou authored
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Biswa Panda authored
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Graham King authored
In a distributed system we don't know if the remote workers need pre-processing done ingress-side or not. Previously Client required us to decide this before discovering the remote endpoints, which was fine because pre-processing was worker-side. As part of moving pre-processing back to ingress-side we need to split this into two steps: - Client discovers the endpoints, and (later PR) will fetch their Model Deployment Card. - PushRouter will use the Model Deployment Card to decide if they need pre-processing or not, which affects the types of the generic parameters. Part of #743
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Anant Sharma authored
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Neelay Shah authored
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nnshah1 authored
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Ziqi Fan authored
refactor: change trtllm example kv routing use python bindings | deal with trtllm partial blocks | trtllm event change (#866)
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- 28 Apr, 2025 4 commits
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richardhuo-nv authored
We were observing a 40% performance drop compared with trtllm serve when benchmarking with isl=1000 and osl=200 at a concurrency level > 128. The number of the tokenization worker is the bottleneck. After bumping the tokenization processors number to 5, dynamo's benchmarking perf could match the trtllm serve's perf.
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Graham King authored
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Biswa Panda authored
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ishandhanani authored
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