Ujeebu Langchain Py
C+ 74 completed
Other
unknown / python · tiny
32
Files
4,525
LOC
1
Frameworks
5
Languages
Pipeline State
completedRun ID
#389514Phase
doneProgress
1%Started
Finished
2026-04-13 01:31:02LLM tokens
0Pipeline Metadata
Stage
SkippedDecision
skip_scaffold_dupNovelty
29.20Framework unique
—Isolation
—Last stage change
2026-04-16 18:15:42Deduplication group #47518
Member of a group with 1 similar repo(s) — canonical #113957 view group →
Top concepts (2)
Project DescriptionTesting
Repobility · open methodology · https://repobility.com/research/
AI Prompt
Create a Python integration for LangChain that uses the Ujeebu Extract API. I need this to help extract clean, structured content from news articles and blog posts for use with LLMs. The tool should allow loading articles as LangChain Documents, and also function as an Agent Tool. Please ensure it can extract rich metadata like author, publication date, title, and images. It would be great if it supports an optional fast extraction mode and uses full type hints for type safety.
python langchain llm api content-extraction agent document-loader structured-data
Generated by gemma4:latest
Catalog Information
Official LangChain integration for Ujeebu Extract API - Extract clean, structured content from news articles and blog posts for use with Large Language Models (LLMs) and AI applications.
Description
Official LangChain integration for Ujeebu Extract API - Extract clean, structured content from news articles and blog posts for use with Large Language Models (LLMs) and AI applications.
Novelty
3/10Tags
python langchain llm api content-extraction agent document-loader structured-data
Technologies
langchain pydantic
Claude Models
claude-opus-4-6
Quality Score
C+
73.9/100
Structure
84
Code Quality
65
Documentation
65
Testing
85
Practices
63
Security
90
Dependencies
60
Strengths
- CI/CD pipeline configured (github_actions)
- Good test coverage (82% test-to-source ratio)
- Code linting configured (flake8, ruff (possible))
- Consistent naming conventions (snake_case)
- Good security practices \u2014 no major issues detected
- Properly licensed project
Weaknesses
- 1 bare except/catch blocks swallowing errors
- Potential hardcoded secrets in 1 files
- 352 duplicate lines detected \u2014 consider DRY refactoring
Recommendations
- Replace bare except/catch blocks with specific exception types
- Move hardcoded secrets to environment variables or a secrets manager
Security & Health
4.1h
Tech Debt (C)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (2)
Repobility — same analyzer, your code, free for public repos · /scan/
MIT
License
12.8%
Duplication
Languages
Frameworks
pytest
Concepts (2)
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| auto_category | Testing | testing | 70% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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