🔬 Plato Semantic Sim
Embedding-based tile comparison and deduplication for PLATO rooms
Computes similarity between knowledge tiles using cosine similarity, Jaccard index, and edit distance. Finds duplicates via content hashing (exact) and vector comparison (semantic).
Install
pip install plato-semantic-sim
Quick Start
from plato_semantic_sim import SimilarityEngine, DedupEngine
engine = SimilarityEngine()
scores = engine.find_similar([0.1, 0.2, 0.3], {"a": [0.1, 0.2, 0.3], "b": [0.9, 0.8, 0.7]})
print(scores) # [("a", 1.0)]
dedup = DedupEngine(similarity_threshold=0.85)
result = dedup.add("tile-1", "knowledge content", [0.1, 0.2, 0.3])
print(result) # {"status": "unique"}
API
| Class | Purpose |
|---|---|
SimilarityEngine |
Compare vectors, find similar, pairwise matrix |
CosineSimilarity |
Dot product / magnitude |
JaccardSimilarity |
Token overlap ratio |
DedupEngine |
Exact + semantic dedup in one pass |
Part of Cocapn · Agent Infrastructure
1 maintainer
Metadata
1 maintainer
Release files for plato-semantic-sim 0.1.1
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| plato_semantic_sim-0.1.1.tar.gz | 3.5 kB | Without provenance | Details for plato_semantic_sim-0.1.1.tar.gz |
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| File | Interpreter | ABI | Platform | Actions Reset |
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| plato_semantic_sim-0.1.1-py3-none-any.whl | Python 3 | none | any | Details for plato_semantic_sim-0.1.1-py3-none-any.whl |
Total release size: 8.1 kB
Release files / plato_semantic_sim-0.1.1.tar.gz
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