Add CPU LLM inference benchmark with vLLM

[valebes]

Summary

• Add 421.llm-inference, a CPU benchmark using vLLM 0.31.0 and SmolLM2-135M-Instruct LLM Model. Model preparation and upload use the SeBS storage; the function initializes the engine on its first invocation and reuses it for warm requests.

• Provide ARM64/x86_64 container builds targeting AWS Lambda, compatibility patches, regression and an example configuration. Measure model download, initialization and generation times, input/output token counts and total token throughput.

• Make the Lambda SDK read timeout configurable through deployment.aws.lambda-client-read-timeout, but retaining the 60s default. This benchmark uses 660 seconds to accommodate cold start in case of large models.

Validation

• Successfully validated through SeBS on AWS Lambda ARM.

Limitations

Lambda's restrictions on /dev/shm require UniProcExecutor compatibility patches.
On ARM64, restricted CPU metadata also requires topology, MIDR and L2-cache fallbacks.

Summary by CodeRabbit

• New Features
  • Added a CPU-based language model inference benchmark for AWS Lambda, supporting Python 3.12 and x64 or ARM64 container deployments.
  • The benchmark includes test, small, and large generation profiles and reports timing and token metrics.
  • Added a configurable AWS Lambda client read timeout, defaulting to 60 seconds, for synchronous invocations that may take longer than the default.
• Documentation
  • Added benchmark setup and usage guidance, including model configuration, and documented the Lambda read timeout setting and its behavior.

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📥 Commits

Reviewing files that changed from the base of the PR and between 25472a6 and 4148742.

📒 Files selected for processing: 1

• benchmarks/400.inference/421.llm-inference/README.md

🚧 Files skipped from review as they are similar to previous changes: 1

• benchmarks/400.inference/421.llm-inference/README.md

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📝 Walkthrough

Adds a Python 3.12 AWS benchmark for CPU-only vLLM inference. It stages and verifies model files, builds ARM64 and x64 container images, reuses the model and engine on warm invocations, and records inference measurements. AWS Lambda client read timeouts are configurable.

Changes: LLM Inference Benchmark

Layer / File(s)	Summary
Lambda client read timeout sebs/aws/config.py, sebs/aws/aws.py, configs/example.json, docs/platforms.md	AWSConfig accepts, validates, serializes, and exposes lambda_client_read_timeout. AWS Lambda client creation uses this value. The example and platform documentation describe the setting and its default.
Model manifest and benchmark input benchmarks/400.inference/421.llm-inference/config.json, aws.json, default-model.json, input.py	Adds benchmark settings and a pinned model manifest. Input generation verifies and uploads model files, selects a profile token limit, and returns model metadata. Output validation checks generated text, model ID, and token count.
CPU inference container build benchmarks/400.inference/421.llm-inference/python/Dockerfile, python/init.sh, python/requirements.txt, python/patches/*, pyproject.toml	Adds architecture-specific CPU dependency and vLLM build steps, applies vLLM and oneDNN patches, and packages the Lambda runtime. Package data now includes patch files.
Inference handler and benchmark registration benchmarks/400.inference/421.llm-inference/python/function.py, sebs/regression.py, docs/benchmarks.md, benchmarks/400.inference/421.llm-inference/README.md	The handler downloads and verifies model files, reuses a local model and warm engine, and returns generated text and timing and token measurements. Regression filtering limits the benchmark to supported AWS Python 3.12 container configurations. The benchmark documentation describes its configuration and measurements.

Priority: ➖ Normal

Estimated code review effort: 4 (Complex) | ~60 minutes

Change: Feature

Sequence Diagram(s)

sequenceDiagram
  participant BenchmarkInput
  participant SeBSStorage
  participant LambdaHandler
  participant vLLMEngine
  BenchmarkInput->>SeBSStorage: Upload model files under model ID
  LambdaHandler->>SeBSStorage: Download model files
  LambdaHandler->>LambdaHandler: Verify file sizes and SHA-256 digests
  LambdaHandler->>vLLMEngine: Generate chat completion
  vLLMEngine-->>LambdaHandler: Return generated text and token measurements

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Merge Risk: ⚪ Minimal · up to 41487

This incremental change only adds benchmark documentation and no actionable merge-blocking risk is evident from the supplied context.

Pre-merge checks: 5

Check name	Status	Explanation
Description Check		Check skipped - CodeRabbit’s high-level summary is enabled.
Title check		The title clearly and concisely describes the main change: adding a CPU LLM inference benchmark using vLLM.
Docstring Coverage		Docstring coverage is 100.00% which is sufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 16 functions across 6 files. (1 skipped: 1…
Linked Issues check		Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check		Check skipped because no linked issues were found for this pull request.

Full details: Docstring Coverage

Explanation

Docstring coverage is 100.00% which is sufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 16 functions across 6 files. (1 skipped: 1 unsupported.)

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Actionable comments posted: 1

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• 🪄 Fix comments: Fix CodeRabbit comments on this PR

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Inline comments:
Review comments at @benchmarks/400.inference/421.llm-inference/README.md:
- Line 5: Update the README’s Architecture statement to list both arm64 and x64,
while keeping the AWS container and Python 3.12 context; leave the
arm64-specific aws.json example unchanged.

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ℹ️ Review info

⚙️ Run configuration

• Configuration used: defaults
• Review profile: CHILL
• Plan: Advanced
• Run ID: a0d5e40b-8361-4b49-b488-a8aa5062f717

📥 Commits

Reviewing files that changed from the base of the PR and between adf2892 and 25472a6.

⛔ Files ignored due to path filters: 2

• benchmarks/400.inference/421.llm-inference/python/requirements.txt.arm64.lock is excluded by !**/*.lock
• benchmarks/400.inference/421.llm-inference/python/requirements.txt.x64.lock is excluded by !**/*.lock

📒 Files selected for processing: 20

• benchmarks/400.inference/421.llm-inference/README.md
• benchmarks/400.inference/421.llm-inference/aws.json
• benchmarks/400.inference/421.llm-inference/config.json
• benchmarks/400.inference/421.llm-inference/default-model.json
• benchmarks/400.inference/421.llm-inference/input.py
• benchmarks/400.inference/421.llm-inference/python/Dockerfile
• benchmarks/400.inference/421.llm-inference/python/function.py
• benchmarks/400.inference/421.llm-inference/python/init.sh
• benchmarks/400.inference/421.llm-inference/python/patches/onednn-arm64-midr.patch
• benchmarks/400.inference/421.llm-inference/python/patches/vllm-0.31.0-cpu-topology.patch
• benchmarks/400.inference/421.llm-inference/python/patches/vllm-0.31.0-l2-cache.patch
• benchmarks/400.inference/421.llm-inference/python/patches/vllm-0.31.0-uniproc.patch
• benchmarks/400.inference/421.llm-inference/python/requirements.txt
• configs/example.json
• docs/benchmarks.md
• docs/platforms.md
• pyproject.toml
• sebs/aws/aws.py
• sebs/aws/config.py
• sebs/regression.py

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