Text Resolver ≥0.1.0¶
The text resolver generates a semantic embedding from free-form text using a GGUF language model via llama.cpp. This is useful for fields such as descriptions, titles, or any natural language content.
How It Works¶
When an aspect using the text resolver is first created, Aspected loads the specified GGUF model from disk. The input text is tokenised and passed through the model to produce a dense embedding vector. The model is shared across all aspects that reference the same model file.
The output is a many-dimensional vector, scaled by an optional multiplier.
Settings¶
| Setting | Type | Default | Description |
|---|---|---|---|
model |
string | nomic-embed-text-v1.5.f16.gguf |
Filename of the GGUF model to use (must exist in the models directory). |
Embedding Size¶
The number of dimensions is determined by the model. For example:
| Model | Dimensions |
|---|---|
nomic-embed-text-v1.5.f16.gguf |
768 |
Qwen3-Embedding-0.6B-f16.gguf |
1024 |
Downloading Models¶
Aspected does not ship with embedding models included. You must download GGUF model files from Hugging Face and make them available to the server.
To download the default models, run:
mkdir -p models
wget -O models/nomic-embed-text-v1.5.f16.gguf \
https://huggingface.co/nomic-ai/nomic-embed-text-v1.5-GGUF/resolve/main/nomic-embed-text-v1.5.f16.gguf
wget -O models/Qwen3-Embedding-0.6B-f16.gguf \
https://huggingface.co/Qwen/Qwen3-Embedding-0.6B-GGUF/resolve/main/Qwen3-Embedding-0.6B-f16.gguf
This downloads two models into the models/ directory:
| Model | Source |
|---|---|
nomic-embed-text-v1.5.f16.gguf |
nomic-ai/nomic-embed-text-v1.5-GGUF |
Qwen3-Embedding-0.6B-f16.gguf |
Qwen/Qwen3-Embedding-0.6B-GGUF |
You can also download any other GGUF embedding model and place it in the models directory. The model must support generating embeddings (encoder-only or decoder-only with embedding support); encoder-decoder models are not supported.
Making Models Available in Docker¶
When running Aspected via Docker, mount the models directory into the container:
The default models path inside the container is ./models. You can change this with the llama.modelsPath
configuration option (see Configuration).
Using a Custom Model¶
To use a different GGUF model, download it and reference it by filename in the aspect settings:
{
"name": "description",
"type": "text",
"path": "$.description",
"settings": {
"model": "my-custom-model.gguf"
}
}
Make sure the model file is present in the configured models directory before creating the index.