dtlvnative

Provides pre-built native dependencies for Datalevin database. This is done by packaging the compiled native libraries and JavaCPP JNI library files in the platform specific JAR files.

In addition to JavaCPP's JNI library, these native libraries are included:

• dlmdb a fork of LMDB key value storage library.
• usearch a vector indexing and similarity search library that is exposed directly for callers.
• llama.cpp built as a minimal CPU-only GGUF embedding runtime and exposed directly for callers.
• dtlv wraps DLMDB. It implements Datalevin iterators, counters and samplers.

The following platforms are currently supported:

• macosx-arm64
• freebsd-x86_64
• linux-arm64
• linux-x86_64
• windows-x86_64

The name of the released JAR is org.clojars.huahaiy/dtlvnative-PLATFORM, where PLATFORM is one of the above.

Vector support using usearch on Windows is experimental.

llama.cpp embedding

dtlvnative includes a reduced llama.cpp build for embeddings only. It keeps the CPU backend enabled, uses OpenMP, and strips chat, generation, and other non-embedding model/runtime code from the packaged static library.

The upstream src/llama.cpp submodule stays clean in git. The reduction is applied by the parent build scripts with script/patches/llama-embed-only.patch.

The exposed native/JavaCPP embedding API is:

Function	Description
dtlv_llama_embedder_create	Load a GGUF model and create an embedder
dtlv_llama_embedder_n_embd	Return the embedding dimension
dtlv_llama_embedder_n_ctx	Return the context size (max tokens)
dtlv_llama_token_count	Count tokens for a string without allocating
dtlv_llama_tokenize	Tokenize a string into a caller-owned int[] buffer
dtlv_llama_detokenize	Convert tokens back to a UTF-8 string
dtlv_llama_embed	Compute an embedding for a single string
dtlv_llama_embed_batch	Compute embeddings for multiple strings in one call
dtlv_llama_embedder_destroy	Free the embedder

The model must be a GGUF embedding model. The current smoke test uses multilingual-e5-small-Q8_0.gguf.

dtlv_llama_embedder_create takes model_path, n_ctx, n_batch, n_threads, and normalize. Pass 0 for n_ctx and n_batch to use model defaults. A non-zero normalize returns L2-normalized embeddings.

Single embedding

DTLV.dtlv_llama_embedder embedder = new DTLV.dtlv_llama_embedder();
int rc = DTLV.dtlv_llama_embedder_create(
        embedder,
        "multilingual-e5-small-Q8_0.gguf",
        0, 0, 4, 1);

int nEmbd = DTLV.dtlv_llama_embedder_n_embd(embedder);
float[] output = new float[nEmbd];
rc = DTLV.dtlv_llama_embed(embedder, "query: hello world", output, nEmbd);

DTLV.dtlv_llama_embedder_destroy(embedder);

Token counting and tokenization

// check token count before embedding
int nTokens = DTLV.dtlv_llama_token_count(embedder, text);
int maxTokens = DTLV.dtlv_llama_embedder_n_ctx(embedder);

// tokenize, truncate, detokenize
int[] tokens = new int[maxTokens];
int actual = DTLV.dtlv_llama_tokenize(embedder, text, tokens, maxTokens);
if (actual > maxTokens) {
    // truncate to fit
    actual = maxTokens;
}
byte[] buf = new byte[text.length() * 4];
int len = DTLV.dtlv_llama_detokenize(embedder, tokens, actual, buf, buf.length);
String truncated = new String(buf, 0, len, StandardCharsets.UTF_8);

Batch embedding

PointerPointer texts = new PointerPointer("query: hello", "query: world");
int nTexts = 2;
float[] output = new float[nTexts * nEmbd];
rc = DTLV.dtlv_llama_embed_batch(embedder, texts, nTexts, output, output.length);
// output[0..nEmbd-1] = embedding for "query: hello"
// output[nEmbd..2*nEmbd-1] = embedding for "query: world"

The Java test in src/java/datalevin/dtlvnative/Test.java will use target/embedding-models/multilingual-e5-small-Q8_0.gguf if present, fall back to a repository-root copy if present, and otherwise download the model from Hugging Face before running the embedding smoke test.

Additional dependencies

Right now, the included shared libraries depend on some system libraries.

• libc
• libmvec
• libomp or libgomp

We bundle libomp in the Jar. However, on systems that the bundled library is not working, or libc is not available, you will have to install them yourself. For example, on Ubuntu/Debian, apt install libgomp1, or apt install gcc-12 g++-12; on MacOS, brew install libomp libllvm

License

Copyright © 2021-2026 Huahai Yang

This program and the accompanying materials are made available under the terms of the Eclipse Public License 2.0 which is available at http://www.eclipse.org/legal/epl-2.0.

This Source Code may also be made available under the following Secondary Licenses when the conditions for such availability set forth in the Eclipse Public License, v. 2.0 are satisfied: GNU General Public License as published by the Free Software Foundation, either version 2 of the License, or (at your option) any later version, with the GNU Classpath Exception which is available at https://www.gnu.org/software/classpath/license.html.