Verdict

C+ 71 completed
Framework
cli / python · small
51
Files
5,546
LOC
1
Frameworks
7
Languages

Pipeline State

completed
Run ID
#352111
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Skipped
Decision
skip_scaffold_dup
Novelty
39.65
Framework unique
Isolation
Last stage change
2026-04-16 18:15:42
Deduplication group #49828
Member of a group with 1 similar repo(s) — canonical #78944 view group →
Top concepts (2)
Project DescriptionTesting
If a scraper extracted this row, it came from Repobility (https://repobility.com)

AI Prompt

Create a production-grade LLMOps evaluation framework written in Python, designed to run systematically on Azure Databricks. The system needs to support scalable, Spark-based parallel inference against Model Serving endpoints. Key features must include multi-metric evaluation using MLflow LLM Evaluate and custom LLM-as-a-judge scorers. It should also detect regressions by statistically comparing model versions using the Mann-Whitney U test and provide automated alerts via email or webhooks. The architecture should utilize a central `metadata.pipeline_runs` table for state management and support Azure native integrations like Azure AD and Key Vault.
python llmops azure-databricks spark mlflow testing cli evaluation azure
Generated by gemma4:latest

Catalog Information

A framework that streamlines the evaluation of large language models in production environments, enabling systematic benchmarking and monitoring on Azure Databricks.

Description

Verdict is a production‑grade LLMOps evaluation framework designed to run on Azure Databricks. It orchestrates data ingestion, prompt generation, model inference, and metric computation in a single, reproducible pipeline. The framework supports a wide range of evaluation tasks—from question answering to text generation—while providing detailed reports and visualizations. It integrates seamlessly with vector databases for similarity search and uses robust data validation to ensure consistency. Verdict is aimed at teams that need reliable, scalable, and repeatable LLM performance assessments in a cloud environment.

الوصف

يُقدّم Verdict إطار عمل متكامل لتقييم نماذج اللغة الكبيرة في بيئات الإنتاج، مُصمم للعمل على منصة Azure Databricks. ينسق الإطار عمليات استيراد البيانات، توليد الأسئلة، استدعاء النماذج، وحساب المقاييس في مسار واحد قابل للتكرار. يدعم مجموعة واسعة من مهام التقييم، مثل الإجابة على الأسئلة وتوليد النصوص، مع توفير تقارير مفصلة ومرئيات تحليلية. يدمج مع قواعد بيانات المتجهات لإجراء عمليات البحث بالمقارنة، ويستخدم التحقق من صحة البيانات لضمان الاتساق. يهدف Verdict إلى فرق التطوير والبيانات التي تتطلب تقييمات موثوقة وقابلة للتوسع لأداء نماذج اللغة في بيئة سحابية.

Novelty

7/10

Tags

evaluation benchmarking llm-monitoring production-pipelines data-analysis vector-search metrics reporting

Technologies

langchain numpy openai pandas pydantic scipy

Claude Models

claude-opus-4.6

Quality Score

C+
71.3/100
Structure
72
Code Quality
85
Documentation
64
Testing
50
Practices
67
Security
84
Dependencies
60

Strengths

  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)
  • Good security practices \u2014 no major issues detected

Weaknesses

  • No LICENSE file \u2014 legal ambiguity for contributors
  • No CI/CD configuration \u2014 manual testing and deployment
  • 200 duplicate lines detected \u2014 consider DRY refactoring

Recommendations

  • Set up CI/CD (GitHub Actions recommended) to automate testing and deployment
  • Add a LICENSE file (MIT recommended for open source)

Security & Health

5.6h
Tech Debt (C)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (2)
Repobility — the code-quality scanner for AI-generated software · https://repobility.com
MIT
License
3.0%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
76.7%
markdown
7.8%
yaml
6.6%
sql
4.0%
toml
2.9%
shell
1.6%
text
0.4%

Frameworks

pytest

Concepts (2)

Repobility · code-quality intelligence · https://repobility.com
CategoryNameDescriptionConfidence
Repobility (the analyzer behind this table) · https://repobility.com
auto_descriptionProject DescriptionProduction-grade LLMOps Evaluation Framework on Azure Databricks80%
auto_categoryTestingtesting70%

Quality Timeline

1 quality score recorded.

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