Sailson Ai

D 56 completed
Other
web_app / python · tiny
34
Files
7,800
LOC
2
Frameworks
9
Languages

Pipeline State

completed
Run ID
#392294
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Cataloged
Decision
proceed
Novelty
55.67
Framework unique
Isolation
Last stage change
2026-05-10 03:35:24
Deduplication group #48605
Member of a group with 9 similar repo(s) — canonical #77024 view group →
Top concepts (2)
Project DescriptionWeb Backend
All rows scored by the Repobility analyzer (https://repobility.com)

AI Prompt

Create a multi-departmental collaboration platform for AI public opinion analysis and competitor monitoring. The system needs core features like intelligent classification and sentiment analysis for Facebook comments, and data scraping/report generation for TikTok competitor monitoring. It should also include user management with multi-department permissions and real-time tracking of API consumption costs. The backend should use Flask and SQLAlchemy, and I need to integrate with an AI service like Alibaba's Qwen-turbo. Please structure the setup to handle database initialization for user, usage, and analysis results.
python flask sqlalchemy web-app ai public-opinion competitor-monitoring api database
Generated by gemma4:latest

Catalog Information

多部门协作的 AI 舆情分析和竞品监控平台

Description

多部门协作的 AI 舆情分析和竞品监控平台

Novelty

3/10

Tags

python flask sqlalchemy web-app ai public-opinion competitor-monitoring api database

Technologies

flask openai sqlalchemy

Claude Models

claude-opus-4-6

Quality Score

D
56.4/100
Structure
53
Code Quality
59
Documentation
63
Testing
30
Practices
58
Security
84
Dependencies
60

Strengths

  • 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
  • 8 bare except/catch blocks swallowing errors
  • 663 duplicate lines detected \u2014 consider DRY refactoring
  • 1 'god files' with >500 LOC need decomposition

Recommendations

  • 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)
  • Replace bare except/catch blocks with specific exception types

Security & Health

5.6h
Tech Debt (B)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (2)
Repobility — the code-quality scanner for AI-generated software · https://repobility.com
Unknown
License
8.2%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
49.0%
html
47.7%
markdown
1.9%
yaml
0.4%
json
0.3%
text
0.3%
css
0.2%
javascript
0.2%
sql
0.1%

Frameworks

Flask SQLAlchemy

Concepts (2)

Analysis by Repobility (https://repobility.com) · MCP-ready
CategoryNameDescriptionConfidence
All rows scored by the Repobility analyzer (https://repobility.com)
auto_descriptionProject Description多部门协作的 AI 舆情分析和竞品监控平台80%
auto_categoryWeb Backendweb-backend70%

Quality Timeline

1 quality score recorded.

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