[https://nvbugs/6215684][fix] Fix invalid links in deployment guide

docs/source/deployment-guide/deployment-guide-for-deepseek-r1-on-trtllm.md

@@ -58,7 +58,7 @@ Note:
 * The command also maps port `8000` from the container to your host so you can access the LLM API endpoint from your host
 * See the <https://catalog.ngc.nvidia.com/orgs/nvidia/teams/tensorrt-llm/containers/release/tags> for all the available containers. The containers published in the main branch weekly have `rcN` suffix, while the monthly release with QA tests has no `rcN` suffix. Use the `rc` release to get the latest model and feature support.
 
-If you want to use latest main branch, you can choose to build from source to install TensorRT LLM, the steps refer to [https://nvidia.github.io/TensorRT-LLM/latest/installation/build-from-source-linux.html](https://nvidia.github.io/TensorRT-LLM/latest/installation/build-from-source-linux.html)
+If you want to use latest main branch, you can choose to build from source to install TensorRT LLM, the steps refer to [https://nvidia.github.io/TensorRT-LLM/latest/installation/build-from-source.html](https://nvidia.github.io/TensorRT-LLM/latest/installation/build-from-source.html)
 
 ### Recommended Performance Settings
 

docs/source/deployment-guide/deployment-guide-for-glm-5-on-trtllm.md

@@ -63,7 +63,7 @@ Note:
 * The command maps port `8000` from the container to your host so you can access the LLM API endpoint from your host.
 * See <https://catalog.ngc.nvidia.com/orgs/nvidia/teams/tensorrt-llm/containers/release/tags> for all available containers. Containers published in the main branch weekly have an `rcN` suffix, while the monthly release with QA tests has no `rcN` suffix. Use the `rc` release to get the latest model and feature support.
 
-If you want to use the latest main branch, you can build from source: [https://nvidia.github.io/TensorRT-LLM/latest/installation/build-from-source-linux.html](https://nvidia.github.io/TensorRT-LLM/latest/installation/build-from-source-linux.html)
+If you want to use the latest main branch, you can build from source: [https://nvidia.github.io/TensorRT-LLM/latest/installation/build-from-source.html](https://nvidia.github.io/TensorRT-LLM/latest/installation/build-from-source.html)
 
 > **All commands below should be run inside the Docker container.**
 

docs/source/deployment-guide/deployment-guide-for-gpt-oss-on-trtllm.md

@@ -54,7 +54,7 @@ Note:
 * The command also maps port `8000` from the container to your host so you can access the LLM API endpoint from your host
 * See the <https://catalog.ngc.nvidia.com/orgs/nvidia/teams/tensorrt-llm/containers/release/tags> for all the available containers. The containers published in the main branch weekly have `rcN` suffix, while the monthly release with QA tests has no `rcN` suffix. Use the `rc` release to get the latest model and feature support.
 
-If you want to use latest main branch, you can choose to build from source to install TensorRT-LLM, the steps refer to <https://nvidia.github.io/TensorRT-LLM/latest/installation/build-from-source-linux.html>.
+If you want to use latest main branch, you can choose to build from source to install TensorRT-LLM, the steps refer to <https://nvidia.github.io/TensorRT-LLM/latest/installation/build-from-source.html>.
 
 ### Recommended Performance Settings
 

docs/source/deployment-guide/deployment-guide-for-llama3.3-70b-on-trtllm.md

@@ -50,7 +50,7 @@ Note:
 * The command also maps port **8000** from the container to your host so you can access the LLM API endpoint from your host
 * See the [https://catalog.ngc.nvidia.com/orgs/nvidia/teams/tensorrt-llm/containers/release/tags](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/tensorrt-llm/containers/release/tags) for all the available containers. The containers published in the main branch weekly have “rcN” suffix, while the monthly release with QA tests has no “rcN” suffix. Use the rc release to get the latest model and feature support.
 
-If you want to use latest main branch, you can choose to build from source to install TensorRT LLM, the steps refer to [https://nvidia.github.io/TensorRT-LLM/latest/installation/build-from-source-linux.html](https://nvidia.github.io/TensorRT-LLM/latest/installation/build-from-source-linux.html)
+If you want to use latest main branch, you can choose to build from source to install TensorRT LLM, the steps refer to [https://nvidia.github.io/TensorRT-LLM/latest/installation/build-from-source.html](https://nvidia.github.io/TensorRT-LLM/latest/installation/build-from-source.html)
 
 ### Recommended Performance Settings
 

docs/source/deployment-guide/deployment-guide-for-llama4-scout-on-trtllm.md

@@ -49,7 +49,7 @@ Note:
 * The command also maps port `8000` from the container to your host so you can access the LLM API endpoint from your host
 * See the <https://catalog.ngc.nvidia.com/orgs/nvidia/teams/tensorrt-llm/containers/release/tags> for all the available containers. The containers published in the main branch weekly have `rcN` suffix, while the monthly release with QA tests has no `rcN` suffix. Use the `rc` release to get the latest model and feature support.
 
-If you want to use latest main branch, you can choose to build from source to install TensorRT LLM, the steps refer to [https://nvidia.github.io/TensorRT-LLM/latest/installation/build-from-source-linux.html](https://nvidia.github.io/TensorRT-LLM/latest/installation/build-from-source-linux.html)
+If you want to use latest main branch, you can choose to build from source to install TensorRT LLM, the steps refer to [https://nvidia.github.io/TensorRT-LLM/latest/installation/build-from-source.html](https://nvidia.github.io/TensorRT-LLM/latest/installation/build-from-source.html)
 
 ### Recommended Performance Settings
 

docs/source/deployment-guide/deployment-guide-for-nemotron-3-super-on-trtllm.md

@@ -53,7 +53,7 @@ Note:
 * The command also maps port `8000` from the container to your host so you can access the LLM API endpoint from your host.
 * See the <https://catalog.ngc.nvidia.com/orgs/nvidia/teams/tensorrt-llm/containers/release/tags> for all the available containers. The containers published in the main branch weekly have `rcN` suffix, while the monthly release with QA tests has no `rcN` suffix. Use the `rc` release to get the latest model and feature support.
 
-If you want to use latest main branch, you can choose to build from source to install TensorRT LLM, the steps refer to [https://nvidia.github.io/TensorRT-LLM/latest/installation/build-from-source-linux.html](https://nvidia.github.io/TensorRT-LLM/latest/installation/build-from-source-linux.html)
+If you want to use latest main branch, you can choose to build from source to install TensorRT LLM, the steps refer to [https://nvidia.github.io/TensorRT-LLM/latest/installation/build-from-source.html](https://nvidia.github.io/TensorRT-LLM/latest/installation/build-from-source.html)
 
 ### Recommended Performance Settings
 

tests/integration/test_lists/waives.txt

@@ -348,7 +348,6 @@ stress_test/stress_test.py::test_run_stress_test[DeepSeek-V3_tp8-stress_time_360
 stress_test/stress_test.py::test_run_stress_test[DeepSeek-V3_tp8-stress_time_3600s_timeout_10800s-MAX_UTILIZATION-pytorch-stress-test-with-accuracy] SKIP (https://nvbugs/6143599)
 stress_test/stress_test.py::test_run_stress_test[llama-v3-8b-instruct-hf_tp1-stress_time_300s_timeout_450s-GUARANTEED_NO_EVICT-pytorch-stress-test] SKIP (https://nvbugs/6215678)
 stress_test/stress_test.py::test_run_stress_test[llama-v3-8b-instruct-hf_tp1-stress_time_300s_timeout_450s-MAX_UTILIZATION-pytorch-stress-test] SKIP (https://nvbugs/6215678)
-test_doc.py::test_url_validity SKIP (https://nvbugs/6215684)
 test_e2e.py::test_draft_token_tree_quickstart_advanced_eagle3[Llama-3.1-8b-Instruct-llama-3.1-model/Llama-3.1-8B-Instruct-EAGLE3-LLaMA3.1-Instruct-8B] SKIP (https://nvbugs/5989907)
 test_e2e.py::test_draft_token_tree_quickstart_advanced_eagle3_depth_1_tree[Llama-3.1-8b-Instruct-llama-3.1-model/Llama-3.1-8B-Instruct-EAGLE3-LLaMA3.1-Instruct-8B] SKIP (https://nvbugs/5989907)
 test_e2e.py::test_multi_nodes_eval[DeepSeek-R1/DeepSeek-R1-0528-FP4-tp16-mmlu] SKIP (https://nvbugs/6114608)