docs: fix index.rst for 0.4.0 #2263
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WalkthroughThe documentation introduction and structure were expanded and reorganized in Changes
Estimated code review effort🎯 1 (Trivial) | ⏱️ ~3 minutes Possibly related PRs
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Actionable comments posted: 0
🧹 Nitpick comments (4)
docs/index.rst (4)
20-23: Tone & conciseness: trim marketing language and drop the rhetorical questionThe two introductory paragraphs are clear but wordy and slightly marketing-oriented. A leaner, neutral style is easier to scan and better fits technical docs. Example rewrite:
-The NVIDIA Dynamo Platform is a high-performance, low-latency inference framework designed to serve generative AI and reasoning models—across any framework, architecture, or deployment scale. Built in Rust for performance and in Python for extensibility, Dynamo is fully open-source and driven by a transparent, OSS (Open Source Software) first development approach. - -Large language models are quickly outgrowing the memory and compute budget of any single GPU. Tensor-parallelism solves the capacity problem by spreading each layer across many GPUs—and sometimes many servers—but it creates a new one: how do you coordinate those shards, route requests, and share KV cache fast enough to feel like one accelerator? This orchestration gap is exactly what NVIDIA Dynamo is built to close. +NVIDIA Dynamo is a high-performance, low-latency inference platform for serving generative-AI and reasoning models at any scale. Written in Rust for speed and extended in Python for flexibility, Dynamo is developed in the open under the Apache-2.0 licence. + +Large language models exceed the capacity of a single GPU. Tensor parallelism distributes layers across multiple GPUs (or even servers) but introduces an orchestration challenge: coordinating shards and KV-cache quickly enough to behave like one accelerator. Dynamo closes this gap.Feel free to adjust wording, but consider avoiding rhetorical questions and redundant phrases like “OSS (Open Source Software) first.”
52-59: Minor wording & path consistency
- “GPU-unaware” is jargon; “GPU-agnostic” is clearer.
- Unlike other bullets,
vllm/READMEis referenced without.md. Sphinx resolves this only if the source suffix is registered; add the extension for portability.- Demonstrates the basic concepts of Dynamo by creating a simple GPU-unaware graph using Python bindings. + Demonstrates the basic concepts of Dynamo by creating a simple GPU-agnostic graph using the Python bindings. -.. grid-item-card:: :doc:`LLM Serving with vLLM <components/backends/vllm/README>` +.. grid-item-card:: :doc:`LLM Serving with vLLM <components/backends/vllm/README.md>`
60-65: Title length & duplicate “using”The card title is long and the description repeats “using” twice. Suggest shortening and removing redundancy:
-.. grid-item-card:: :doc:`Deploy DeepSeek R1 Disaggregated with WideEP using SGLang <components/backends/sglang/docs/dsr1-wideep-gb200.md>` +.. grid-item-card:: :doc:`DeepSeek R1 WideEP Deployment with SGLang <components/backends/sglang/docs/dsr1-wideep-gb200.md>` - Demonstrates disaggregated serving of DeepSeek R1 using Wide Expert Parallelism using SGLang. + Demonstrates disaggregated DeepSeek R1 serving with WideEP via SGLang.
104-108: Path extension inconsistencyMost toctree entries now include
.md; align this one for consistency:- Deploying Dynamo on Kubernetes <guides/dynamo_deploy/README.md> + Deploying Dynamo on Kubernetes <guides/dynamo_deploy/README.md>(If the
.mdsuffix is intentionally omitted elsewhere, feel free to ignore; just keep the convention consistent.)
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Learnt from: biswapanda
PR: ai-dynamo/dynamo#1412
File: lib/bindings/python/src/dynamo/runtime/logging.py:100-100
Timestamp: 2025-06-06T21:48:35.214Z
Learning: In the Dynamo codebase, BentoML has been completely removed from all executable code, with only documentation and attribution references remaining. The error_loggers configuration in lib/bindings/python/src/dynamo/runtime/logging.py should not include "bentoml" since those modules no longer exist.
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- GitHub Check: Build and Test - vllm
🔇 Additional comments (5)
docs/index.rst (5)
30-33: Links LGTMUpdated captions and ordering read well; targets resolve correctly.
40-42: Section title rename aligns with contentRenaming to “Dynamo Examples” improves clarity—no further action needed.
66-70: LGTMThe TensorRT-LLM example caption and summary look consistent.
117-118: LGTMMoving the Planner Benchmark into the visible Examples section is sensible.
124-125: API path visibility is helpfulSurfacing the NIXL Connect API in Reference improves discoverability—no issues spotted.
| |--------------------|--------------|-----------------------------------------------------------------------| | ||
| | **WideEP** | ✅ | | | ||
| | **DP Rank Routing**| ✅ | | | ||
| | **Attention DP** | ✅ | | |
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Let's be consistent with table across all 3 backends if possible
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great catch, thank you. will update all of them
rmccorm4
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rmccorm4
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Can you update this
dynamo/docs/architecture/dynamo_flow.md
Line 70 in d537378
NVIDIA Inference Xfer Library (NIXL) instead of NVIDIA Interchange Library?
ref: https://github.com/ai-dynamo/nixl
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