Aumai Linguaforge

B+ 90 completed
Library
cli / python · tiny
23
Files
1,362
LOC
1
Frameworks
4
Languages

Pipeline State

completed
Run ID
#304016
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Skipped
Decision
skip_scaffold_dup
Novelty
31.54
Framework unique
Isolation
Last stage change
2026-04-16 18:15:42
Deduplication group #47941
Member of a group with 1 similar repo(s) — canonical #9446 view group →
Top concepts (4)
Project DescriptiontestingTestingTesting
Generated by Repobility's multi-pass static-analysis pipeline (https://repobility.com)

AI Prompt

Create a command-line NLP toolkit, similar to AumAI Linguaforge, specifically designed to support multiple Indic languages. I need the structure to be robust, including sections for documentation, examples, and clear contribution guidelines. Since this is a CLI tool, please ensure the project setup is ready for testing using pytest and that it uses Python as the primary language.
python cli nlp indic-languages toolkit pytest command-line
Generated by gemma4:latest

Catalog Information

The AUMAI LinguaForge project is a multi-language NLP toolkit focused on supporting Indic languages.

Description

AUMAI LinguaForge is a comprehensive Natural Language Processing (NLP) toolkit designed to support multiple languages, with a special emphasis on Indic languages. This toolkit aims to provide a robust set of tools for various NLP tasks, including text processing, tokenization, and more. With its focus on Indic languages, it seeks to bridge the gap in NLP resources available for these languages.

الوصف

يعد AUMAI LinguaForge مجموعة أدوات معالجة اللغة الطبيعية (NLP) الشاملة التي تهدف إلى دعم اللغات المتعددة، مع التركيز خاصةً على اللغات الهندية. هذه المجموعة من الأدوات تسعى إلى تقديم مجموعة متنوعة من الأدوات لتنفيذ مهام NLP المختلفة، بما في ذلك معالجة النصوص وتحليلها.

Novelty

5/10

Tags

natural-language-processing indic-languages text-processing tokenization language-support

Technologies

click pydantic

Claude Models

claude-opus-4.6

Quality Score

B+
89.9/100
Structure
93
Code Quality
100
Documentation
85
Testing
85
Practices
72
Security
100
Dependencies
80

Strengths

  • CI/CD pipeline configured (github_actions)
  • Good test coverage (50% test-to-source ratio)
  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)
  • Good security practices \u2014 no major issues detected
  • Properly licensed project

Security & Health

4.1h
Tech Debt (D)
Medium
DORA Rating
A
OWASP (100%)
Citation: Repobility (2026). State of AI-Generated Code. https://repobility.com/research/
PASS
Quality Gate
A
Risk (7)
Apache-2.0
License
3.8%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
79.5%
markdown
10.1%
yaml
5.9%
toml
4.5%

Frameworks

pytest

Symbols

variable22
method9
class8
function7
constant5

Concepts (4)

All metrics by Repobility · https://repobility.com
CategoryNameDescriptionConfidence
Repobility · code-quality intelligence · https://repobility.com
auto_descriptionProject Description> Multi-language NLP toolkit with Indic language focus80%
arch_layertestingDetected testing layer70%
auto_categoryTestingtesting70%
business_logicTestingDetected from 3 related files50%

Quality Timeline

1 quality score recorded.

View File Metrics
Source: Repobility analyzer · https://repobility.com

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BinComp Dependency Hardening

All packages →
2 of this repo's dependencies have been scanned for binary hardening. Grade reflects RELRO / stack canary / FORTIFY / PIE coverage.
Nclick8.3.2 · 0 gadgets · risk 0.0Npydantic2.12.5 · 0 gadgets · risk 0.0