TAMR+ Lite
Trust-Augmented Multi-phase Retrieval — Open-Core Edition
The open-source core of the TAMR+ framework, providing EU AI Act-compliant scoring, gap attribution, and retrieval primitives for building trustworthy AI applications.
Three-Stage Architecture
- Document Manifest Selector — 5-signal deterministic pre-filtering (zero LLM calls)
- Multi-Phase Retrieval — Vector ANN, KG alignment, causal density, diversity selection
- TRACE Scoring — 5-dimension formula-based scoring with gap attribution
Installation
pip install tamr-plus-lite
Quick Start
from tamr_plus_lite import build_trace_scores, compute_gap_attribution
# Score a response
score = build_trace_scores(
source_count=5,
total_claims=10,
cited_claims=8,
evidence_strength=0.8,
)
print(f"TRACE Score: {score.overall:.0%}")
print(score.explanation)
# Explain gaps
gap = compute_gap_attribution(
trace_score=score.overall,
source_count=5,
total_claims=10,
cited_claims=8,
)
print(gap.explanation)
for component in gap.components:
print(f" {component.friendly_name}: {component.value:.1%} — {component.action}")
Modules
| Module | Description |
|---|---|
tamr_plus_lite.scoring |
TRACE 5-dimension scoring engine |
tamr_plus_lite.gap |
Gap attribution ("Why not 100%?") |
tamr_plus_lite.manifest |
Document manifest selector (Stage 1) |
tamr_plus_lite.classifier |
Zero-LLM query classifier |
tamr_plus_lite.interfaces |
Abstract interfaces for pluggable backends |
tamr_plus_lite.extraction |
KG extraction prompt + utilities |
tamr_plus_lite.chunking |
Text chunking + JSON repair |
tamr_plus_lite.profiles |
Domain scoring profiles |
EU AI Act Compliance
All scoring is formula-based (not ML) for full transparency:
- Art. 13: Every parameter is explicit and auditable
- Art. 14: Every score decomposes into human-readable factors
- Art. 15: Deterministic formulas guarantee reproducibility
TRACE Dimensions
| Dimension | Weight | What It Measures |
|---|---|---|
| T — Transparency | 25% | Source attribution and model identification |
| R — Reasoning | 20% | Evidence basis and cross-document connections |
| A — Auditability | 20% | Audit trail completeness |
| C — Compliance | 20% | Regulatory framework alignment |
| E — Explainability | 15% | Response structure quality |
Gap Attribution Taxonomy
| Code | Friendly Name | Description |
|---|---|---|
| SCG | Document Coverage | How much is backed by uploaded documents |
| PKC | AI Knowledge Used | Reliance on AI training data |
| DLT | Specialized Vocabulary | Domain terminology precision |
| ADG | Citation Coverage | Citation completeness |
| FSC | System Limitation | Irreducible 3% structural ceiling |
Full TAMR+
This is the open-core edition. The full TAMR+ SDK includes:
- Premium 7-phase retrieval pipeline (HDI, governance, compliance certificates)
- Gamified insights engine
- Production domain profiles with calibrated weights
Contact: harish.kumar@quantamixsolutions.com
License
Apache-2.0 — Quantamix Solutions B.V.
Patent Notice
TAMR+ Lite implements methods covered by European Patent Applications EP26162901.8 and EP26166054.2, owned by Quantamix Solutions B.V.
Licensed under Apache 2.0 with express patent grant (Section 3). Reimplementation of the patented methods outside this software requires a separate patent license. See LICENSE for details.
Metadata
Release files for tamr-plus-lite 0.1.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| tamr_plus_lite-0.1.1.tar.gz | 21.0 kB | Without provenance | Details for tamr_plus_lite-0.1.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| tamr_plus_lite-0.1.1-py3-none-any.whl | Python 3 | none | any | Details for tamr_plus_lite-0.1.1-py3-none-any.whl |
Total release size: 44.7 kB
Release files / tamr_plus_lite-0.1.1.tar.gz
| Download URL | tamr_plus_lite-0.1.1.tar.gz |
|---|---|
| Size | 21.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
664244e726d3effe11dc1493565ee0b0d700741d419605a8d894254213cba63e
|
|
BLAKE2b-256 checksum How to use checksums |
cb013abbb3d1884cef6a0fa000573b19296259f6b230c2f31ef7ef2e9b2e70ca
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.10.11
|
Release files / tamr_plus_lite-0.1.1-py3-none-any.whl
| Download URL | tamr_plus_lite-0.1.1-py3-none-any.whl |
|---|---|
| Size | 23.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
a3e49cf76915fa4682c333518d01ec338361d8f79732a42dff5d1d01ea58efa5
|
|
BLAKE2b-256 checksum How to use checksums |
0f03f950465aeb13ba2a1caf90bb14fbc3d0ed548b760e5027d9c277af6ff023
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.10.11
|
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