Add link checker for doc build and test

build.sh

@@ -358,5 +358,5 @@ if buildAll || hasArg docs; then
 
     cd "${REPODIR}"/docs/cuopt
     make clean
-    make html
+    make html linkcheck
 fi

docs/cuopt/Makefile

@@ -23,12 +23,22 @@ SPHINXPROJ    = cuOpt
 SOURCEDIR     = source
 BUILDDIR      = build
 
-# Put it first so that "make" without argument is like "make help".
+# Default target: build documentation and run link check
+all: html linkcheck
+
+# Build HTML documentation
+html:
+	@$(SPHINXBUILD) -M html "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
+
+# Check all external links in the documentation
+linkcheck:
+	@$(SPHINXBUILD) -M linkcheck "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
+
+# Show help
 help:
 	@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
 
-
-.PHONY: help clean Makefile
+.PHONY: all html linkcheck help clean Makefile
 
 clean:
 	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

docs/cuopt/source/conf.py

@@ -325,6 +325,27 @@ def setup(app):
 }
 html_search = True
 
+# Link checker settings
+linkcheck_retries = 3
+linkcheck_timeout = 30
+linkcheck_workers = 5
+linkcheck_rate_limit_timeout = 60
+
+# GitHub and GitLab link checker exceptions
+linkcheck_ignore = [
+    # GitHub (Rate Limited)
+    r'https://github\.com/.*',
+    r'https://api\.github\.com/.*',
+    r'https://raw\.githubusercontent\.com/.*',
+    r'https://gist\.github\.com/.*',
+
+    # GitLab (Rate Limited)
+    r'https://gitlab\.com/.*',
+    r'https://api\.gitlab\.com/.*',
+    r'https://gitlab\.org/.*',
+    r'https://api\.gitlab\.org/.*',
+]
+
 def setup(app):
     from sphinx.application import Sphinx
     from typing import Any, List

docs/cuopt/source/cuopt-c/lp-milp/lp-example.rst

@@ -5,7 +5,7 @@ LP C API Examples
 Example With Data
 -----------------
 
-This example demonstrates how to use the LP solver in C. More details on the API can be found in `C API <lp-milp-c-api.html>`_.
+This example demonstrates how to use the LP solver in C. More details on the API can be found in :doc:`C API <lp-milp-c-api>`.
 
 Copy the code below into a file called ``lp_example.c``:
 

docs/cuopt/source/cuopt-c/lp-milp/lp-milp-c-api.rst

@@ -48,15 +48,15 @@ Certain constants are needed to define an optimization problem. These constants
 Objective Sense Constants
 -------------------------
 
-These constants are used to define the objective sense in the `cuOptCreateProblem <lp-milp-c-api.html#c.cuOptCreateProblem>`_ and `cuOptCreateRangedProblem <lp-milp-c-api.html#c.cuOptCreateRangedProblem>`_ functions.
+These constants are used to define the objective sense in the :c:func:`cuOptCreateProblem` and :c:func:`cuOptCreateRangedProblem` functions.
 
 .. doxygendefine:: CUOPT_MINIMIZE
 .. doxygendefine:: CUOPT_MAXIMIZE
 
 Constraint Sense Constants
 --------------------------
 
-These constants are used to define the constraint sense in the `cuOptCreateProblem <lp-milp-c-api.html#c.cuOptCreateProblem>`_ and `cuOptCreateRangedProblem <lp-milp-c-api.html#c.cuOptCreateRangedProblem>`_ functions.
+These constants are used to define the constraint sense in the :c:func:`cuOptCreateProblem` and :c:func:`cuOptCreateRangedProblem` functions.
 
 .. doxygendefine:: CUOPT_LESS_THAN
 .. doxygendefine:: CUOPT_GREATER_THAN
@@ -65,15 +65,15 @@ These constants are used to define the constraint sense in the `cuOptCreateProbl
 Variable Type Constants
 -----------------------
 
-These constants are used to define the the variable type in the `cuOptCreateProblem <lp-milp-c-api.html#c.cuOptCreateProblem>`_ and `cuOptCreateRangedProblem <lp-milp-c-api.html#c.cuOptCreateRangedProblem>`_ functions.
+These constants are used to define the the variable type in the :c:func:`cuOptCreateProblem` and :c:func:`cuOptCreateRangedProblem` functions.
 
 .. doxygendefine:: CUOPT_CONTINUOUS
 .. doxygendefine:: CUOPT_INTEGER
 
 Infinity Constant
 -----------------
 
-This constant may be used to represent infinity in the `cuOptCreateProblem <lp-milp-c-api.html#c.cuOptCreateProblem>`_ and `cuOptCreateRangedProblem <lp-milp-c-api.html#c.cuOptCreateRangedProblem>`_ functions.
+This constant may be used to represent infinity in the :c:func:`cuOptCreateProblem` and :c:func:`cuOptCreateRangedProblem` functions.
 
 .. doxygendefine:: CUOPT_INFINITY
 
@@ -118,7 +118,7 @@ When you are done with a solve you should destroy a `cuOptSolverSettings` object
 
 Setting Parameters
 ------------------
-The following functions are used to set and get parameters. You can find more details on the available parameters in the `LP/MILP settings <../../lp-milp-settings.html>`_ section.
+The following functions are used to set and get parameters. You can find more details on the available parameters in the :doc:`LP/MILP settings <../../lp-milp-settings>` section.
 
 .. doxygenfunction:: cuOptSetParameter
 .. doxygenfunction:: cuOptGetParameter
@@ -127,11 +127,12 @@ The following functions are used to set and get parameters. You can find more de
 .. doxygenfunction:: cuOptSetFloatParameter
 .. doxygenfunction:: cuOptGetFloatParameter
 
+.. _parameter-constants:
 
 Parameter Constants
 -------------------
 
-These constants are used as the parameter name in the `cuOptSetParameter <lp-milp-c-api.html#c.cuOptSetParameter>`_ , `cuOptGetParameter <lp-milp-c-api.html#c.cuOptGetParameter>`_ and similar functions. More details on the parameters can be found in the `LP/MILP settings <../../lp-milp-settings.html>`_ section.
+These constants are used as parameter names in the :c:func:`cuOptSetParameter`, :c:func:`cuOptGetParameter`, and similar functions. For more details on the available parameters, see the :doc:`LP/MILP settings <../../lp-milp-settings>` section.
 
 .. LP/MIP parameter string constants
 .. doxygendefine:: CUOPT_ABSOLUTE_DUAL_TOLERANCE
@@ -161,20 +162,24 @@ These constants are used as the parameter name in the `cuOptSetParameter <lp-mil
 .. doxygendefine:: CUOPT_NUM_CPU_THREADS
 .. doxygendefine:: CUOPT_USER_PROBLEM_FILE
 
+.. _pdlp-solver-mode-constants:
+
 PDLP Solver Mode Constants
 --------------------------
 
-These constants are used to configure `CUOPT_PDLP_SOLVER_MODE` via `cuOptSetIntegerParameter <lp-milp-c-api.html#c.cuOptSetIntegerParameter>`_.
+These constants are used to configure `CUOPT_PDLP_SOLVER_MODE` via :c:func:`cuOptSetIntegerParameter`.
 
 .. doxygendefine:: CUOPT_PDLP_SOLVER_MODE_STABLE1
 .. doxygendefine:: CUOPT_PDLP_SOLVER_MODE_STABLE2
 .. doxygendefine:: CUOPT_PDLP_SOLVER_MODE_METHODICAL1
 .. doxygendefine:: CUOPT_PDLP_SOLVER_MODE_FAST1
 
+.. _method-constants:
+
 Method Constants
 ----------------
 
-These constants are used to configure `CUOPT_METHOD` via `cuOptSetIntegerParameter <lp-milp-c-api.html#c.cuOptSetIntegerParameter>`_.
+These constants are used to configure `CUOPT_METHOD` via :c:func:`cuOptSetIntegerParameter`.
 
 .. doxygendefine:: CUOPT_METHOD_CONCURRENT
 .. doxygendefine:: CUOPT_METHOD_PDLP
@@ -214,7 +219,7 @@ When you are finished with a `cuOptSolution` object you should destory it with
 Termination Status Constants
 ----------------------------
 
-These constants define the termination status received from the `cuOptGetTerminationStatus <lp-milp-c-api.html#c.cuOptGetTerminationStatus>`_ function.
+These constants define the termination status received from the :c:func:`cuOptGetTerminationStatus` function.
 
 .. LP/MIP termination status constants
 .. doxygendefine:: CUOPT_TERIMINATION_STATUS_NO_TERMINATION

docs/cuopt/source/cuopt-c/lp-milp/milp-examples.rst

@@ -5,7 +5,7 @@ MILP C API Examples
 Example With Data
 -----------------
 
-This example demonstrates how to use the MILP solver in C. More details on the API can be found in `C API <lp-milp-c-api.html>`_.
+This example demonstrates how to use the MILP solver in C. More details on the API can be found in :doc:`C API <lp-milp-c-api>`.
 
 Copy the code below into a file called ``milp_example.c``:
 

docs/cuopt/source/cuopt-cli/quick-start.rst

@@ -2,7 +2,7 @@
 Quickstart Guide
 =================
 
-cuopt_cli is built as part of the libcuopt package and you can follow these `instructions <../cuopt-c/quick-start.html>`_ to install it.
+cuopt_cli is built as part of the libcuopt package and you can follow these :doc:`../cuopt-c/quick-start` to install it.
 
 To see all available options and their descriptions:
 
@@ -17,4 +17,4 @@ This will display the complete list of command-line arguments and their usage:
     :language: shell
     :linenos:
 
-Please refer to `parameter settings <../lp-milp-settings.html>`_ for more details on default values and other options.
+Please refer to :doc:`../lp-milp-settings` for more details on default values and other options.

docs/cuopt/source/cuopt-python/quick-start.rst

@@ -24,7 +24,7 @@ For CUDA 12.x:
 Conda
 -----
 
-NVIDIA cuOpt can be installed with Conda (via `miniforge <https://github.com/conda-forge/miniforge>`_ from the ``nvidia`` channel:
+NVIDIA cuOpt can be installed with Conda (via `miniforge <https://github.com/conda-forge/miniforge>`_) from the ``nvidia`` channel:
 
 .. code-block:: bash
 
@@ -41,16 +41,19 @@ NVIDIA cuOpt is also available as a container from Docker Hub:
 
 .. code-block:: bash
 
-    docker pull nvidia/cuopt:latest-cuda12.8-py312
+    docker pull nvidia/cuopt:latest-cuda12.8-py3.12
 
 .. note::
-   The ``latest`` tag is the latest stable release of cuOpt. If you want to use a specific version, you can use the ``<version>-cuda12.8-py312`` tag. For example, to use cuOpt 25.5.0, you can use the ``25.5.0-cuda12.8-py312`` tag. Please refer to `cuOpt dockerhub page <https://hub.docker.com/r/nvidia/cuopt>`_ for the list of available tags.
+   The ``latest`` tag is the latest stable release of cuOpt. If you want to use a specific version, you can use the ``<version>-cuda12.8-py3.12`` tag. For example, to use cuOpt 25.5.0, you can use the ``25.5.0-cuda12.8-py3.12`` tag. Please refer to `cuOpt dockerhub page <https://hub.docker.com/r/nvidia/cuopt>`_ for the list of available tags.
+
+.. note::
+   The nightly version of cuOpt is available as ``[VERSION]a-cuda12.8-py3.12`` tag. For example, to use cuOpt 25.8.0a, you can use the ``25.8.0a-cuda12.8-py3.12`` tag.
 
 The container includes both the Python API and self-hosted server components. To run the container:
 
 .. code-block:: bash
 
-    docker run --gpus all -it --rm nvidia/cuopt:latest-cuda12.8-py312
+    docker run --gpus all -it --rm nvidia/cuopt:latest-cuda12.8-py3.12 /bin/bash
 
 This will start an interactive session with cuOpt pre-installed and ready to use.
 

docs/cuopt/source/cuopt-server/client-api/sh-cli-build.rst

@@ -73,9 +73,9 @@ Success Response:
    {"reqId":"1df28c33-8b8c-4bb7-9ff9-1e19929094c6"}
 
 
-When sending files to the server, the server must be configured with appropriate data and result directories to temporarily store these files. These directories can be set using the ``-d`` and ``-r`` options when starting the server. Please refer to the `Server CLI documentation <../server-api/server-cli.html>`_ for more details on configuring these directories.
+When sending files to the server, the server must be configured with appropriate data and result directories to temporarily store these files. These directories can be set using the ``-d`` and ``-r`` options when starting the server. Please refer to the :doc:`Server CLI documentation <../server-api/server-cli>` for more details on configuring these directories.
 
-``JSON_DATA`` should follow the `spec <../../open-api.html#operation/postrequest_cuopt_request_post>`_ described for cuOpt input.
+``JSON_DATA`` should follow the :doc:`spec under "POST /cuopt/request" schema <../../open-api>` described for cuOpt input.
 
 Polling for Request Status:
 ---------------------------
@@ -92,7 +92,7 @@ Users can poll the request id for status with the help of ``/cuopt/request/{requ
 
 In case the solver has completed the job, the response will be "completed".
 
-Please refer to the `Solver status in spec <../../open-api.html#operation/getrequest_cuopt_request__id__get>`_ for more details on responses.
+Please refer to the :doc:`Solver status in spec using "GET /cuopt/request/{request-id}" <../../open-api>` for more details on responses.
 
 
 cuOpt Result Retrieval
@@ -106,7 +106,7 @@ Once you have received successful response from solver with status "completed",
    curl --location "http://$ip:$port/cuopt/solution/{request-id}"
 
 
-This would fetch the result in JSON format. Please refer to the `Response structure in spec <../../open-api.html#operation/getrequest_cuopt_solution__id__get>`_ for more details on responses.
+This would fetch the result in JSON format. Please refer to the :doc:`Response structure in spec using "GET /cuopt/solution/{request-id}" <../../open-api>` for more details on responses.
 
 
 .. important::

docs/cuopt/source/cuopt-server/csp-guides/csp-aws.rst

@@ -46,10 +46,10 @@ Step 1: Create an AWS VM with NVAIE Image
 Step 2: Activate NVAIE Subscription
 ------------------------------------
 
-Once connected to the VM, generate an identity token. Activate your NVIDIA AI Enterprise subscription using that identity token on NGC. Follow the instructions `here <https://docs.nvidia.com/ai-enterprise/deployment-guide-cloud/0.1.0/azure-ai-enterprise-vmi.html#accessing-the-nc-on-ngc>`__.
+Once connected to the VM, generate an identity token. Activate your NVIDIA AI Enterprise subscription using that identity token on NGC. Follow the instructions `here <https://docs.nvidia.com/ai-enterprise/deployment/cloud/latest/azure-ai-enterprise-vmi.html#accessing-the-ngc-catalog-on-ngc>`__.
 
 Step 3: Run cuOpt
 ------------------
 
-To run cuOpt, you will need to log in to the NVIDIA Container Registry, pull the cuOpt container, and then run it. To test that it is successfully running, you can run a sample cuOpt request. This process is the same for deploying cuOpt on your own infrastructure. Refer to  `Self-Hosted Service Quickstart Guide </cuopt-server/quick-start.html#container-from-nvidia-ngc>`__.
+To run cuOpt, you will need to log in to the NVIDIA Container Registry, pull the cuOpt container, and then run it. To test that it is successfully running, you can run a sample cuOpt request. This process is the same for deploying cuOpt on your own infrastructure. Refer to  :ref:`Self-Hosted Service Quickstart Guide <container-from-nvidia-ngc>`.
 

docs/cuopt/source/cuopt-server/csp-guides/csp-azure.rst

@@ -56,12 +56,12 @@ Step 1: Create an Azure VM with NVAIE Image
 Step 2: Activate NVAIE Subscription
 ------------------------------------
 
-Once connected to the VM, generate an identity token. Activate your NVIDIA AI Enterprise subscription using that identity token on NGC. Follow the instructions `here <https://docs.nvidia.com/ai-enterprise/deployment-guide-cloud/0.1.0/azure-ai-enterprise-vmi.html#accessing-the-nc-on-ngc>`__.
+Once connected to the VM, generate an identity token. Activate your NVIDIA AI Enterprise subscription using that identity token on NGC. Follow the instructions `here <https://docs.nvidia.com/ai-enterprise/deployment/cloud/latest/azure-ai-enterprise-vmi.html#accessing-the-ngc-catalog-on-ngc>`__.
 
 Step 3: Run cuOpt
 ------------------
 
-To run cuOpt, you will need to log in to the NVIDIA Container Registry, pull the cuOpt container, and then run it. To test that it is successfully running, you can run a sample cuOpt request. This process is the same for deploying cuOpt on your own infrastructure. Refer `Self-Hosted Service Quickstart Guide </cuopt-server/quick-start.html#container-from-nvidia-ngc>`__.
+To run cuOpt, you will need to log in to the NVIDIA Container Registry, pull the cuOpt container, and then run it. To test that it is successfully running, you can run a sample cuOpt request. This process is the same for deploying cuOpt on your own infrastructure. Refer :ref:`Self-Hosted Service Quickstart Guide <container-from-nvidia-ngc>`.
 
 
 Step 4: Mapping Visualization with Azure

docs/cuopt/source/cuopt-server/examples/lp-examples.rst

@@ -4,7 +4,7 @@ LP Python Examples
 
 The following example showcases how to use the ``CuOptServiceSelfHostClient`` to solve a simple LP problem in normal mode and batch mode (where multiple problems are solved at once).
 
-The OpenAPI specification for the server is available in `open-api spec <../../open-api.html>`_. The example data is structured as per the OpenAPI specification for the server, please refer `LPData <../../open-api.html#/default/postrequest_cuopt_request_post>`_ under schema section. LP and MILP share same spec.
+The OpenAPI specification for the server is available in :doc:`open-api spec <../../open-api>`. The example data is structured as per the OpenAPI specification for the server, please refer :doc:`LPData under "POST /cuopt/request" <../../open-api>` under schema section. LP and MILP share same spec.
 
 If you want to run server locally, please run the following command in a terminal or tmux session so you can test examples in another terminal.
 
@@ -15,6 +15,8 @@ If you want to run server locally, please run the following command in a termina
     export port=5000
     python -m cuopt_server.cuopt_service --ip $ip --port $port
 
+.. _generic-example-with-normal-and-batch-mode:
+
 Genric Example With Normal Mode and Batch Mode
 ------------------------------------------------
 
@@ -225,6 +227,8 @@ Batch mode response:
 .. note::
     Warm start is only applicable to LP and not for MILP.
 
+.. _warm-start:
+
 Warm Start
 ----------
 
@@ -428,7 +432,7 @@ The response is:
 Generate Datamodel from MPS Parser
 ----------------------------------
 
-Use a datamodel generated from mps file as input; this yields a solution object in response. For more details please refer to `LP/MILP parameters <../../lp-milp-settings.html>`_.
+Use a datamodel generated from mps file as input; this yields a solution object in response. For more details please refer to :doc:`LP/MILP parameters <../../lp-milp-settings>`.
 
 .. code-block:: python
     :linenos:
@@ -560,13 +564,13 @@ The response would be as follows:
 
 Example with DataModel is available in the `Examples Notebooks Repository <https://github.com/NVIDIA/cuopt-examples>`_.
 
-The ``data`` argument to ``get_LP_solve`` may be a dictionary of the format shown in `LP Open-API spec <../../open-api.html#operation/postrequest_cuopt_request_post>`_. More details on the response can be found under the responses schema `request and solution API spec <../../open-api.html#/default/getrequest_cuopt_request__id__get>`_.
+The ``data`` argument to ``get_LP_solve`` may be a dictionary of the format shown in :doc:`LP Open-API spec <../../open-api>`. More details on the response can be found under the responses schema :doc:`"get /cuopt/request" and "get /cuopt/solution" API spec <../../open-api>`.
 
 
 Aborting a Running Job in Thin Client
 -------------------------------------
 
-Please refer to the `MILP Example on Aborting a Running Job in Thin Client <milp-examples.html#aborting-a-running-job-in-thin-client>`_ for more details.
+Please refer to the :ref:`aborting-thin-client` in the MILP Example for more details.
 
 
 =================================================
@@ -709,7 +713,7 @@ In the case of batch mode, you can send a bunch of ``mps`` files at once, and ac
 Aborting a Running Job In CLI
 -----------------------------
 
-Please refer to the `MILP Example <milp-examples.html#aborting-a-running-job-in-cli>`_ for more details.
+Please refer to the :ref:`aborting-cli` in the MILP Example for more details.
 
 .. note::
    Please use solver settings while using .mps files.