[None][chore] Use a cached model path for Ray integration test

[achartier]

Summary by CodeRabbit

• New Features
  • Added Ray orchestrator support for LLM inference, enabling distributed model execution.
  • Extended command-line interface to accept model selection arguments.

Description

Avoid pulling TinyLlama from HF as it can hit HTTP error 429 (Too Many Requests for url)

Test Coverage

tests/integration/defs/examples/test_ray.py

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[achartier]

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[coderabbitai]

📝 Walkthrough

Walkthrough

The changes add CLI argument parsing for model selection to the Ray orchestrator example script and introduce a new orchestrator_type parameter to LLM initialization. The test is updated to provide the model path and corresponding flag when invoking the example script.

Changes

Cohort / File(s)	Summary
Ray orchestrator example examples/ray_orchestrator/llm_inference_async_ray.py, requirements.txt, pyproject.toml	Added argparse to parse --model CLI argument; wired model argument into LLM initialization; extended LLM constructor call to include orchestrator_type="ray" parameter; retained KV cache configuration with tensor parallelism option commented out
Ray example test tests/integration/defs/examples/test_ray.py	Updated test_llm_inference_async_ray to supply model path via llm_models_root() (pointing to TinyLlama-1.1B-Chat-v1.0) and pass --model flag to script invocation

Estimated code review effort

🎯 2 (Simple) | ⏱️ ~12 minutes

Pre-merge checks and finishing touches

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 0.00% which is insufficient. The required threshold is 80.00%.	You can run @coderabbitai generate docstrings to improve docstring coverage.

✅ Passed checks (2 passed)

Check name	Status	Explanation
Title Check	✅ Passed	The PR title "[None][chore] Use a cached model path for Ray integration test" is directly related to the main objective of the changeset, which is to avoid pulling the TinyLlama model from Hugging Face to prevent HTTP 429 errors. The title clearly describes the primary change—using a cached model path instead of downloading from HF—though it focuses more on the test aspect than mentioning the supporting script modifications that add --model argument handling. The title is concise, specific, and scannable, making it clear to a teammate reviewing the history what this change addresses.
Description Check	✅ Passed	The PR description adequately follows the repository template structure with properly formatted sections. It includes a concise Description section explaining the issue (HTTP 429 errors from Hugging Face) and the rationale for the change, a Test Coverage section identifying the affected test file (tests/integration/defs/examples/test_ray.py), and a completed PR Checklist confirming review of coding guidelines, tests, and other relevant items. While the description is relatively brief, it covers all critical template sections and provides sufficient context about what the PR accomplishes and why.

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📥 Commits

Reviewing files that changed from the base of the PR and between 02081e2 and 601d1ea.

📒 Files selected for processing (2)

• examples/ray_orchestrator/llm_inference_async_ray.py (1 hunks)
• tests/integration/defs/examples/test_ray.py (1 hunks)

🧰 Additional context used

📓 Path-based instructions (3)

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Files:

• tests/integration/defs/examples/test_ray.py
• examples/ray_orchestrator/llm_inference_async_ray.py

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Files:

• tests/integration/defs/examples/test_ray.py
• examples/ray_orchestrator/llm_inference_async_ray.py

**/*.{cpp,cxx,cc,h,hpp,hh,hxx,cu,cuh,py}

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Files:

• tests/integration/defs/examples/test_ray.py
• examples/ray_orchestrator/llm_inference_async_ray.py

🧬 Code graph analysis (2)

tests/integration/defs/examples/test_ray.py (3)

tests/unittest/_torch/executor/test_overlap_scheduler.py (1)

• model_path (20-21)

tests/integration/defs/conftest.py (1)

• llm_models_root (80-94)

tests/integration/defs/common.py (1)

• venv_check_call (34-40)

examples/ray_orchestrator/llm_inference_async_ray.py (2)

tensorrt_llm/llmapi/llm.py (1)

• LLM (1084-1100)

examples/ray_orchestrator/llm_inference_distributed_ray.py (1)

• main (7-37)

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• GitHub Check: Pre-commit Check

🔇 Additional comments (3)

tests/integration/defs/examples/test_ray.py (1)

17-18: LGTM! Cached model path correctly prevents HuggingFace downloads.

The changes successfully address the PR objective by passing a cached model path to avoid HTTP 429 errors. The use of llm_models_root() ensures proper path resolution with fallback handling.

examples/ray_orchestrator/llm_inference_async_ray.py (2)

10-19: Verify the default model choice.

The argparse implementation is correct, but the default model still points to HuggingFace. When this script is run standalone without the --model argument, it will attempt to download from HuggingFace and could still encounter HTTP 429 errors.

Is this intentional to maintain standalone usability, or should the default also point to a cached path? If you'd like to fully prevent HuggingFace downloads, consider whether the default should be updated or if documentation should clarify that the --model flag is required in rate-limited environments.

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27-27: LGTM! Model parameter correctly wired from CLI argument.

The change properly enables the script to accept a model path from the command line, allowing the test to pass in a cached path.

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[tensorrt-cicd]

PR_Github #22471 [ run ] triggered by Bot. Commit: 601d1ea

[tensorrt-cicd]

PR_Github #22471 [ run ] completed with state SUCCESS. Commit: 601d1ea
/LLM/main/L0_MergeRequest_PR pipeline #16936 completed with status: 'FAILURE'