Langgraphintro
C 64 completed
Other
unknown / markdown · tiny
11
Files
596
LOC
0
Frameworks
3
Languages
Pipeline State
completedRun ID
#387080Phase
doneProgress
1%Started
Finished
2026-04-13 01:31:02LLM tokens
0Pipeline Metadata
Stage
SkippedDecision
skip_tinyNovelty
11.79Framework unique
—Isolation
—Last stage change
2026-04-16 18:15:42Deduplication group #47250
Member of a group with 2 similar repo(s) — canonical #110064 view group →
Top concepts (2)
Project DescriptionData/ML
Repobility — same analyzer, your code, free for public repos · /scan/
AI Prompt
Create a hands-on guide using Python to introduce LangGraph. I need the structure to walk through building LLM-powered workflows as graphs. The guide should cover two exercises: a simple "Hello World" single-node graph and a more complex "Research Assistant" multi-node pipeline. Please explain the core concepts like Nodes, Edges, and State flow, and structure the setup instructions to include creating a virtual environment and listing prerequisites like Python 3.10+.
python langgraph llm workflow graph ai tutorial python-scripting
Generated by gemma4:latest
Catalog Information
A hands-on introduction to LangGraph — a framework for building LLM-powered workflows as graphs.
Description
A hands-on introduction to LangGraph — a framework for building LLM-powered workflows as graphs.
Novelty
3/10Tags
python langgraph llm workflow graph ai tutorial python-scripting
Technologies
langchain openai
Claude Models
claude-opus-4-6
Quality Score
C
63.5/100
Structure
49
Code Quality
95
Documentation
65
Testing
0
Practices
68
Security
100
Dependencies
60
Strengths
- Consistent naming conventions (snake_case)
- Low average code complexity \u2014 well-structured code
- Good security practices \u2014 no major issues detected
- Properly licensed project
Weaknesses
- No tests found \u2014 high risk of regressions
- No CI/CD configuration \u2014 manual testing and deployment
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
- Address 21 TODO/FIXME items \u2014 consider tracking them as issues
Security & Health
9.3h
Tech Debt (E)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (10)
Repobility · code-quality intelligence · https://repobility.com
BSD-3-Clause
License
61.2%
Duplication
Languages
Frameworks
None detected
Concepts (2)
| Category | Name | Description | Confidence | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Repobility's GitHub App fixes findings like these · https://github.com/apps/repobility-bot | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| auto_description | Project Description | A hands-on introduction to LangGraph — a framework for building LLM-powered workflows as graphs. | 80% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| auto_category | Data/ML | data-ml | 70% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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