VXDF Python Library
VXDF (Vector eXchange Data Format) is an AI-native container for text, metadata and vector embeddings—portable, indexable and compressed. If you do RAG, semantic search or compliance audits, VXDF gives you one file, one command.
Quick-start
pip install vxdf[zstd] # installs optional Zstandard support
python - << 'PY'
from vxdf import VXDFWriter, VXDFReader
# create a small file
data = [
{"id": "1", "text": "hello", "vector": [0.1, 0.2]},
{"id": "2", "text": "world", "vector": [0.3, 0.4]},
]
with VXDFWriter("demo.vxdf", embedding_dim=2, compression="zstd") as w:
for chunk in data:
w.add_chunk(chunk)
# read it back
a = VXDFReader("demo.vxdf")
print(a.get_chunk("2"))
PY
Command-line
vxdf pack data.jsonl data.vxdf --compression zstd # create
vxdf info data.vxdf # header & stats
vxdf list data.vxdf | head # ids
vxdf get data.vxdf some-id > doc.json # extract
# Pipe stdin to stdout (auto-detects model, disables banner/progress)
cat report.txt | vxdf convert - - > report.vxdf
Colab / Notebook
LangChain integration (preview)
from langchain_community.vectorstores import VXDF
vs = VXDF.from_vxdf("demo.vxdf")
See examples/langchain_integration.py for a minimal adapter.
Authentication
VXDF commands that interact with cloud services need credentials.
OpenAI embeddings
The client looks for an API key in this order (first match wins):
--openai-keyCLI flag (e.g.vxdf convert my.pdf out.vxdf --model openai --openai-key sk-...)OPENAI_API_KEYenvironment variable.~/.vxdf/config.tomlunder the[openai]table:
[openai]
api_key = "sk-..."
AWS (S3 URLs)
Uses the standard AWS credential chain provided by boto3 – environment variables (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY), the AWS CLI config, or an attached IAM role. Run aws configure if unsure.
GCP (gs:// URLs)
Relies on Application Default Credentials. Run gcloud auth application-default login or set the GOOGLE_APPLICATION_CREDENTIALS environment variable pointing at a JSON key file.
If credentials are missing VXDF exits early with a clear message and a hint on how to configure them.
Shell completion
Install extra dependencies and activate once:
pip install vxdf[completion]
activate-global-python-argcomplete --user # bash/zsh/fish supported
Re-open your terminal and enjoy TAB-completion for vxdf sub-commands and options.
VXDF is BSD-3-licensed. Contributions welcome!
Metadata
Release files for vxdf 0.1.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| vxdf-0.1.3.tar.gz | 35.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| vxdf-0.1.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 68.8 kB
Release files / vxdf-0.1.3.tar.gz
| Download URL | vxdf-0.1.3.tar.gz |
|---|---|
| Size | 35.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/6.1.0 CPython/3.9.6
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Release files / vxdf-0.1.3-py3-none-any.whl
| Download URL | vxdf-0.1.3-py3-none-any.whl |
|---|---|
| Size | 33.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.9.6
|