[None][Doc]Added info about AGIV in readme

[ncomly-nvidia]

Add quick note on AGIV work starting & point to sidebranch on main readme

Summary by CodeRabbit

Release Notes

• Documentation
  • Updated README to announce ongoing development of Image & Video Diffusion models functionality.

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📝 Walkthrough

Walkthrough

The README.md file is updated with a new information_source line announcing ongoing work on Image & Video Diffusion models, referencing the visual_gen feature branch. This is a documentation-only addition with no code or functional changes.

Changes

Cohort / File(s)	Summary
Documentation README.md	Adds information_source entry announcing Image & Video Diffusion model development with link to visual_gen feature branch (+2 lines)

Estimated code review effort

🎯 1 (Trivial) | ⏱️ ~2 minutes

🚥 Pre-merge checks | ✅ 2 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Description check	⚠️ Warning	The description is minimal and does not follow the repository's required PR template structure, missing required sections like ticket reference, type designation, test coverage, and checklist confirmation.	Follow the repository template: include ticket/issue reference with type (e.g., [None][doc]), add Test Coverage section, and confirm the PR Checklist items before submission.

✅ Passed checks (2 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title 'Added info about AGIV in readme' is directly related to the changeset, which adds information about AGIV work to the README file.
Docstring Coverage	✅ Passed	No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check.

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📜 Recent review details

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📥 Commits

Reviewing files that changed from the base of the PR and between c99faae and 1ff7061.

📒 Files selected for processing (1)

• README.md

🧰 Additional context used

📓 Path-based instructions (1)

**/*.{md,rst}

📄 CodeRabbit inference engine (CODING_GUIDELINES.md)

When documenting CLI commands for TensorRT-LLM tools like trtllm-serve, trtllm-bench, or trtllm-eval, prefer using --config over --extra_llm_api_options for specifying configuration files

Files:

• README.md

🧠 Learnings (10)

📚 Learning: 2025-08-27T14:23:55.566Z

Learnt from: ixlmar
Repo: NVIDIA/TensorRT-LLM PR: 7294
File: tensorrt_llm/_torch/modules/rms_norm.py:17-17
Timestamp: 2025-08-27T14:23:55.566Z
Learning: The TensorRT-LLM project requires Python 3.10+ as evidenced by the use of TypeAlias from typing module, match/case statements, and union type | syntax throughout the codebase, despite some documentation still mentioning Python 3.8+.

Applied to files:

• README.md

📚 Learning: 2025-08-06T13:58:07.506Z

Learnt from: galagam
Repo: NVIDIA/TensorRT-LLM PR: 6487
File: tests/unittest/_torch/auto_deploy/unit/singlegpu/test_ad_trtllm_bench.py:1-12
Timestamp: 2025-08-06T13:58:07.506Z
Learning: In TensorRT-LLM, test files (files under tests/ directories) do not require NVIDIA copyright headers, unlike production source code files. Test files typically start directly with imports, docstrings, or code.

Applied to files:

• README.md

📚 Learning: 2025-08-01T15:14:45.673Z

Learnt from: yibinl-nvidia
Repo: NVIDIA/TensorRT-LLM PR: 6506
File: examples/models/core/mixtral/requirements.txt:3-3
Timestamp: 2025-08-01T15:14:45.673Z
Learning: In TensorRT-LLM, examples directory can have different dependency versions than the root requirements.txt file. Version conflicts between root and examples dependencies are acceptable because examples are designed to be standalone and self-contained.

Applied to files:

• README.md

📚 Learning: 2025-07-28T17:06:08.621Z

Learnt from: moraxu
Repo: NVIDIA/TensorRT-LLM PR: 6303
File: tests/integration/test_lists/qa/examples_test_list.txt:494-494
Timestamp: 2025-07-28T17:06:08.621Z
Learning: In TensorRT-LLM testing, it's common to have both CLI flow tests (test_cli_flow.py) and PyTorch API tests (test_llm_api_pytorch.py) for the same model. These serve different purposes: CLI flow tests validate the traditional command-line workflow, while PyTorch API tests validate the newer LLM API backend. Both are legitimate and should coexist.

Applied to files:

• README.md

📚 Learning: 2026-01-06T03:07:15.754Z

Learnt from: CR
Repo: NVIDIA/TensorRT-LLM PR: 0
File: CODING_GUIDELINES.md:0-0
Timestamp: 2026-01-06T03:07:15.754Z
Learning: Applies to **/*.py : The code developed for TensorRT-LLM should conform to Python 3.8+

Applied to files:

• README.md

📚 Learning: 2025-09-09T09:40:45.658Z

Learnt from: fredricz-20070104
Repo: NVIDIA/TensorRT-LLM PR: 7645
File: tests/integration/test_lists/qa/llm_function_core.txt:648-648
Timestamp: 2025-09-09T09:40:45.658Z
Learning: In TensorRT-LLM test lists, it's common and intentional for the same test to appear in multiple test list files when they serve different purposes (e.g., llm_function_core.txt for comprehensive core functionality testing and llm_function_core_sanity.txt for quick sanity checks). This duplication allows tests to be run in different testing contexts.

Applied to files:

• README.md

📚 Learning: 2025-10-17T13:21:31.724Z

Learnt from: ixlmar
Repo: NVIDIA/TensorRT-LLM PR: 8398
File: tensorrt_llm/_torch/pyexecutor/sampling_utils.py:237-272
Timestamp: 2025-10-17T13:21:31.724Z
Learning: The setup.py file in TensorRT-LLM explicitly requires Python 3.10+ via `python_requires=">=3.10, <4"`, making match/case statements and other Python 3.10+ features appropriate throughout the codebase.

Applied to files:

• README.md

📚 Learning: 2025-08-21T00:16:56.457Z

Learnt from: farshadghodsian
Repo: NVIDIA/TensorRT-LLM PR: 7101
File: docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md:36-36
Timestamp: 2025-08-21T00:16:56.457Z
Learning: TensorRT-LLM container release tags in documentation should only reference published NGC container images. The README badge version may be ahead of the actual published container versions.

Applied to files:

• README.md

📚 Learning: 2025-08-14T15:38:01.771Z

Learnt from: MatthiasKohl
Repo: NVIDIA/TensorRT-LLM PR: 6904
File: cpp/tensorrt_llm/pybind/thop/bindings.cpp:55-57
Timestamp: 2025-08-14T15:38:01.771Z
Learning: In TensorRT-LLM Python bindings, tensor parameter collections like mla_tensor_params and spec_decoding_tensor_params are kept as required parameters without defaults to maintain API consistency, even when it might affect backward compatibility.

Applied to files:

• README.md

📚 Learning: 2025-08-11T20:09:24.389Z

Learnt from: achartier
Repo: NVIDIA/TensorRT-LLM PR: 6763
File: tests/integration/defs/triton_server/conftest.py:16-22
Timestamp: 2025-08-11T20:09:24.389Z
Learning: In the TensorRT-LLM test infrastructure, the team prefers simple, direct solutions (like hard-coding directory traversal counts) over more complex but robust approaches when dealing with stable directory structures. They accept the maintenance cost of updating tests if the layout changes.

Applied to files:

• README.md

⏰ Context from checks skipped due to timeout of 90000ms. You can increase the timeout in your CodeRabbit configuration to a maximum of 15 minutes (900000ms). (1)

• GitHub Check: Pre-commit Check

🔇 Additional comments (1)

README.md (1)

8-9: The link and path are valid. The feat/visual_gen branch exists and the path tensorrt_llm/visual_gen is correctly specified in the GitHub URL. The announcement is accurate and properly formatted.

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