Shared knowledge atlas built on PTEX nonce-addressed textures
Project description
Amni-Prism
Shared knowledge atlas built on PTEX nonce-addressed textures. Every fact gets a unique GF(17) nonce — contribute knowledge, it deduplicates automatically, and the atlas grows.
Install
pip install -e .
Quick Start
import prism
# Contribute knowledge
prism.contribute_text('./codex', 'The speed of light is 299792458 m/s', domain='physics')
# Query it back
result = prism.query_text('./codex', 'The speed of light is 299792458 m/s')
# Search by keyword
hits = prism.search_keyword('./codex', 'speed of light')
CLI
# Contribute text
prism contribute "The speed of light is 299792458 m/s" -d physics
# Search
prism search "speed of light"
# Small model proposes a fact
prism propose "Water boils at 100C at sea level" -d physics --confidence 0.8
# Large model verifies pending proposals
prism pending
prism verify
# Scrape text for facts
prism scrape --file article.txt --source "https://en.wikipedia.org/wiki/Light"
# Stats
prism stats
How It Works
- GF(17) Nonces — Every word/line/block gets a unique nonce in GF(17) finite field space. Same content = same nonce = automatic dedup.
- PTEX Storage — Knowledge stored as nonce-addressed texture maps. Vocab in NLX format, hierarchical tiers in HNA format.
- Content-Hash Dedup — SHA-256 content hashing ensures no duplicates across contributors.
- Two-Tier Verification — Small models propose (~50 tokens), large models verify (~20 tokens). ~70 tokens per verified fact.
- NDJSON Manifests — Append-only JSON-lines manifests are git-merge-friendly. No merge conflicts.
Contributing
# Fork, clone, then:
pip install -e .
prism contribute "Your knowledge here" -d general
# Or pipe from stdin:
cat facts.txt | prism contribute -d science
Domains
25 built-in domains: code, math, science, history, language, music, art, philosophy, psychology, economics, politics, law, medicine, engineering, technology, education, sports, entertainment, food, travel, nature, religion, mythology, literature, general.
License
MIT
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file amni_prism-0.1.0.tar.gz.
File metadata
- Download URL: amni_prism-0.1.0.tar.gz
- Upload date:
- Size: 21.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.10
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f6a62b50f659b735d32841db3f3f45989febda781566763f662fb8d72ad43c45
|
|
| MD5 |
e0bd893a2fe938f2aec344c787bb9005
|
|
| BLAKE2b-256 |
6cd3222a9153a1104b882d87408e342fed5fd77305ccdd0eb3388558d0ae8078
|
File details
Details for the file amni_prism-0.1.0-py3-none-any.whl.
File metadata
- Download URL: amni_prism-0.1.0-py3-none-any.whl
- Upload date:
- Size: 20.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.10
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
a22fd162189be4e134dde0e9a00292dbb0664bbda1de83aa11865753115c7b0e
|
|
| MD5 |
0f17bf4eb1bc88fec741a7abdad18383
|
|
| BLAKE2b-256 |
3acd3c1025857e1f8afb7c696f050942093b8efa3080d517d1efb913a9848581
|