Demo Sandoz Capa

D 52 completed
Other
unknown / html · tiny
21
Files
2,154
LOC
1
Frameworks
6
Languages

Pipeline State

completed
Run ID
#396383
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Skipped
Decision
skip_scaffold_dup
Novelty
33.62
Framework unique
Isolation
Last stage change
2026-04-16 18:15:42
Deduplication group #47880
Member of a group with 1 similar repo(s) — canonical #100064 view group →
Top concepts (1)
Web Backend
All rows above produced by Repobility · https://repobility.com

AI Prompt

I want to build a demo application, similar to the zeroth-agents demo, that analyzes pharmaceutical CAPA SOPs. The system should ingest both global and local CAPA SOPs, and then extract atomic knowledge units, or CxUs, from them. A key feature should be the ability to identify conflicts between different procedures found in the SOPs. Finally, I need to incorporate agentic analysis capabilities using the extracted knowledge against CAPA test data. The project structure seems to involve Python, FastAPI, and should ideally have a dashboard interface using HTML.
python fastapi html markdown pharma capa sop ai-agent knowledge-extraction demo
Generated by gemma4:latest

Catalog Information

A Pyrana demo that demonstrates CxU-powered analysis of pharmaceutical CAPA (Corrective Action Preventive Action) SOPs. The demo ingests global and local CAPA SOPs, extracts atomic knowledge as CxUs, identifies conflicts between procedures, and runs agentic analysis on CAPA test data.

Description

A Pyrana demo that demonstrates CxU-powered analysis of pharmaceutical CAPA (Corrective Action Preventive Action) SOPs. The demo ingests global and local CAPA SOPs, extracts atomic knowledge as CxUs, identifies conflicts between procedures, and runs agentic analysis on CAPA test data.

Novelty

3/10

Tags

python fastapi html markdown pharma capa sop ai-agent knowledge-extraction demo

Technologies

fastapi

Claude Models

claude-opus-4-6

Quality Score

D
51.9/100
Structure
33
Code Quality
85
Documentation
27
Testing
0
Practices
66
Security
100
Dependencies
60

Strengths

  • Consistent naming conventions (snake_case)
  • Good security practices \u2014 no major issues detected

Weaknesses

  • Missing README file \u2014 critical for project understanding
  • No LICENSE file \u2014 legal ambiguity for contributors
  • No tests found \u2014 high risk of regressions
  • No CI/CD configuration \u2014 manual testing and deployment

Recommendations

  • Add a comprehensive README.md explaining purpose, setup, usage, and architecture
  • Add a test suite \u2014 start with critical path integration tests
  • Set up CI/CD (GitHub Actions recommended) to automate testing and deployment
  • Add a linter configuration to enforce code style consistency
  • Add a LICENSE file (MIT recommended for open source)

Security & Health

4.1h
Tech Debt (D)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (4)
Repobility (the analyzer behind this table) · https://repobility.com
Unknown
License
0.0%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

html
54.9%
markdown
16.5%
python
14.1%
json
13.7%
shell
0.6%
text
0.1%

Frameworks

FastAPI

Concepts (1)

Open methodology · Repobility · https://repobility.com/research/
CategoryNameDescriptionConfidence
Methodology: Repobility · https://repobility.com/research/state-of-ai-code-2026/
auto_categoryWeb Backendweb-backend70%

Quality Timeline

1 quality score recorded.

View File Metrics

Embed Badge

Add to your README:

![Quality](https://repos.aljefra.com/badge/120744.svg)
Quality BadgeSecurity Badge
Export Quality CSVDownload SBOMExport Findings CSV