Added doxygen action and README, minor docstring fixes.

.github/workflows/doxygenate.yaml

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+on:
+  push:
+    branches:
+      - master
+
+name: Build documentation
+
+jobs:
+  doxygenator:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v4
+
+    - name: Add Pretty CSS
+      uses: wei/wget@v1
+      with:
+        args: -O docs/doxygen-awesome.css https://raw.githubusercontent.com/jothepro/doxygen-awesome-css/main/doxygen-awesome.css
+
+    - name: Add kmeans tagfile
+      uses: wei/wget@v1
+      with:
+        args: -O docs/knncolle.tag https://knncolle.github.io/knncolle/knncolle.tag
+
+    - name: Doxygen Action
+      uses: mattnotmitt/doxygen-action@v1
+      with:
+        working-directory: docs/
+    - name: GH Pages Deployment
+      uses: JamesIves/github-pages-deploy-action@v4
+      with:
+        branch: gh-pages # The branch the action should deploy to.
+        folder: docs/html
+        target-folder: docs/
+        clean: true # Automatically remove deleted files from the deploy branch

README.md

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+# knncolle bindings for Hnsw
+
+![Unit tests](https://github.com/knncolle/knncolle_hnsw/actions/workflows/run-tests.yaml/badge.svg)
+![Documentation](https://github.com/knncolle/knncolle_hnsw/actions/workflows/doxygenate.yaml/badge.svg)
+[![Codecov](https://codecov.io/gh/knncolle/knncolle_hnsw/branch/master/graph/badge.svg)](https://codecov.io/gh/knncolle/knncolle_hnsw)
+
+## Overview
+
+The **knncolle_hnsw** library provides [**knncolle**](https://github.com/knncolle/knncolle) bindings to 
+the [HNSW](https://github.com/nmslib/hnswlib) library for approximate nearest neighbors search.
+This allows users to use HNSW searches in any framework that accepts **knncolle** interfaces, sacrificing neighbor search accuracy for greater speed.
+For most applications involving large datasets, this is an acceptable trade-off.
+
+## Quick start
+
+Instances of the various `knncolle_hnsw::Hnsw*` classes can be used anywhere that accepts the corresponding **knncolle** interface.
+For example:
+
+```cpp
+#include "knncolle/knncolle_hnsw.hpp"
+
+// Wrap our data in a light SimpleMatrix.
+knncolle::SimpleMatrix<int, int, double> mat(ndim, nobs, matrix.data());
+
+// Build an Hnsw index. 
+knncolle_hnsw::HnswBuilder<> an_builder;
+auto an_index = an_builder.build_unique(mat);
+
+// Find 10 (approximate) nearest neighbors of every element.
+auto results = knncolle::find_nearest_neighbors(*an_index, 10); 
+```
+
+We could alternate between exact and approximate searches at run-time:
+
+```cpp
+std::unique_ptr<knncolle::Prebuilt<int, int, double> > ptr;
+if (use_exact) {
+    knncolle::KmknnBuilder<> kbuilder;
+    ptr = kbuilder.build_unique(mat);
+} else {
+    knncolle::HnswBuilder<> abuilder;
+    ptr = abuilder.build_unique(mat);
+}
+```
+
+We can also customize the construction of the `HnswBuilder` by passing in options:
+
+```cpp
+auto& an_opts = an_builder.get_options();
+an_opts.num_links = 100;
+an_opts.distance_options.create = [](int dim) -> 
+knncolle_hnsw::HnswBuilder<> an_builder2(an_opts);
+```
+
+Check out the [reference documentation](https://knncolle.github.io/knncolle_hnsw/) for more details.
+
+## Building projects 
+
+### CMake with `FetchContent`
+
+If you're using CMake, you just need to add something like this to your `CMakeLists.txt`:
+
+```cmake
+include(FetchContent)
+
+FetchContent_Declare(
+  knncolle
+  GIT_REPOSITORY https://github.com/knncolle/knncolle_hnsw
+  GIT_TAG master # or any version of interest
+)
+
+FetchContent_MakeAvailable(knncolle_hnsw)
+```
+
+Then you can link to **knncolle_hnsw** to make the headers available during compilation:
+
+```cmake
+# For executables:
+target_link_libraries(myexe knncolle::knncolle_hnsw)
+
+# For libaries
+target_link_libraries(mylib INTERFACE knncolle::knncolle_hnsw)
+```
+
+### CMake with `find_package()`
+
+```cmake
+find_package(knncolle_knncolle_hnsw CONFIG REQUIRED)
+target_link_libraries(mylib INTERFACE knncolle::knncolle_hnsw)
+```
+
+To install the library, use:
+
+```sh
+mkdir build && cd build
+cmake .. -DKNNCOLLE_HNSW_TESTS=OFF
+cmake --build . --target install
+```
+
+By default, this will use `FetchContent` to fetch all external dependencies.
+If you want to install them manually, use `-DKNNCOLLE_HNSW_FETCH_EXTERN=OFF`.
+See [`extern/CMakeLists.txt`](extern/CMakeLists.txt) to find compatible versions of each dependency.
+
+### Manual
+
+If you're not using CMake, the simple approach is to just copy the files in `include/` - either directly or with Git submodules - and include their path during compilation with, e.g., GCC's `-I`.
+This requires the external dependencies listed in [`extern/CMakeLists.txt`](extern/CMakeLists.txt), which also need to be made available during compilation.
+
+## Note on vectorization
+
+HNSW will attempt to perform manual vectorization based on SSE and/or AVX instructions.
+This may result in differences in the results across machines due to changes in numeric precision across architectures with varying support for SSE/AVX intrinsics.
+For the most part, such differences can be avoided by consistently compiling for the "near-lowest common denominator" (such as the typical `x86-64` default for GCC and Clang) 
+and ensuring that the more specific instruction subsets like SSE3 and AVX are not enabled (which are typically off by default anyway).
+Nonetheless, if reproducibility across architectures is important, it can be achieved at the cost of some speed by defining the `NO_MANUAL_VECTORIZATION` macro,
+which will instruct Hnsw to disable its vectorized optimizations.