Transform AI-generated content into natural, human-like writing with our advanced text humanization tool. This project addresses the growing need for AI-generated content that feels authentic and human-written.
mindmap
root((AI Text<br>Humanization))
Problem
AI-generated text detection
Unnatural patterns
Lack of human touch
Repetitive structures
Solution
Advanced NLP processing
LLM integration
Humanization metrics
Multiple tone support
Benefits
Authentic content
Better engagement
Reduced detection
Natural flow
graph TD
A[AI Text Humanizer] --> B[Text Processing]
A --> C[Content Generation]
A --> D[Analysis & Metrics]
B --> B1[Text Input]
B --> B2[Pattern Analysis]
B --> B3[Humanization]
C --> C1[Topic Input]
C --> C2[Tone Selection]
C --> C3[Length Control]
D --> D1[Humanization Score]
D --> D2[Reading Time]
D --> D3[Style Analysis]
flowchart TD
subgraph Frontend
A[Streamlit UI] --> B[User Input]
B --> C[Display Results]
end
subgraph Backend
D[Text Humanizer] --> E[LLM Integration]
E --> F[Text Processing]
F --> G[Metrics Engine]
end
subgraph DataFlow
H[Input Text] --> I[Processing Pipeline]
I --> J[Output Text]
J --> K[Analysis Results]
end
Frontend --> Backend
Backend --> DataFlow
sequenceDiagram
participant User
participant UI as Streamlit UI
participant TH as Text Humanizer
participant LLM as Language Model
participant ME as Metrics Engine
User->>UI: Input Text/Topic
UI->>TH: Process Request
alt Text Humanization
TH->>TH: Pre-process Text
TH->>LLM: Request Humanization
LLM-->>TH: Return Enhanced Text
else Content Generation
TH->>LLM: Generate Content
LLM-->>TH: Return Generated Text
end
TH->>ME: Calculate Metrics
ME-->>TH: Return Analysis
TH-->>UI: Display Results
UI-->>User: Show Humanized Text
flowchart LR
subgraph InputProcessing
A[Raw Text] --> B[Text Cleaning]
B --> C[Pattern Analysis]
end
subgraph Humanization
C --> D[Style Detection]
D --> E[LLM Processing]
E --> F[Text Enhancement]
end
subgraph QualityControl
F --> G[Grammar Check]
G --> H[Flow Analysis]
H --> I[Final Review]
end
subgraph Output
I --> J[Humanized Text]
I --> K[Metrics]
I --> L[Analysis Report]
end
graph TD
A[Humanization Score] --> B[Overall Score]
A --> C[Component Scores]
B --> D[Final Percentage]
C --> E[Sentence Variety]
C --> F[Personal Voice]
C --> G[Natural Flow]
E --> H[Variety Score]
F --> I[Voice Score]
G --> J[Flow Score]
flowchart TD
subgraph TextAnalysis
A[Input Text] --> B[Tokenization]
B --> C[Pattern Detection]
C --> D[Style Analysis]
end
subgraph Scoring
D --> E[Calculate Metrics]
E --> F[Generate Scores]
F --> G[Create Report]
end
subgraph Output
G --> H[Humanization Score]
G --> I[Detailed Analysis]
G --> J[Improvement Suggestions]
end
graph LR
A[AI Text Humanizer] --> B[Frontend]
A --> C[Backend]
A --> D[AI/ML]
B --> B1[Streamlit]
B --> B2[HTML/CSS]
C --> C1[Python]
D --> D1[LLM]
D --> D2[NLP Pipeline]
- Clone the repository:
git clone https://github.com/srikrishnavansi/Humanize.git
cd humanizer- Create and activate a virtual environment:
python -m venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate- Install dependencies:
pip install -r requirements.txtgraph TD
A[Start App] --> B[Choose Mode]
B --> C[Text Humanization]
B --> D[Content Generation]
C --> E[Input Text]
E --> F[Process]
F --> G[View Results]
D --> H[Set Parameters]
H --> I[Generate]
I --> J[View Results]
mindmap
root((Advanced<br>Features))
Text Processing
Multiple Languages
Style Adaptation
Tone Matching
Content Generation
Topic Research
Length Control
Style Variation
Analysis
Detailed Metrics
Pattern Detection
Improvement Suggestions
sequenceDiagram
participant User
participant System
participant LLM
participant Analyzer
User->>System: Input Text
System->>Analyzer: Analyze Patterns
Analyzer->>System: Return Analysis
System->>LLM: Request Humanization
LLM->>System: Return Enhanced Text
System->>Analyzer: Calculate Metrics
Analyzer->>System: Return Scores
System->>User: Display Results
sequenceDiagram
participant User
participant System
participant LLM
participant Validator
User->>System: Input Topic
System->>LLM: Generate Content
LLM->>System: Return Content
System->>Validator: Validate Quality
Validator->>System: Return Validation
System->>User: Display Results
graph TD
A[Performance Metrics] --> B[Processing Time]
A --> C[Quality Scores]
A --> D[User Feedback]
B --> B1[Text Analysis]
B --> B2[Generation Time]
C --> C1[Humanization Score]
C --> C2[Naturalness]
D --> D1[User Ratings]
D --> D2[Improvement Rate]
mindmap
root((Future<br>Enhancements))
Features
Multi-language Support
Advanced Style Transfer
Custom Tone Training
Performance
Faster Processing
Better Accuracy
Enhanced Metrics
Integration
API Support
Plugin System
Cloud Deployment
graph TD
A[Ethical Use] --> B[Academic Integrity]
A --> C[Content Authenticity]
A --> D[User Responsibility]
B --> B1[No Plagiarism]
B --> B2[Proper Attribution]
C --> C1[Transparent Usage]
C --> C2[Quality Standards]
D --> D1[Ethical Guidelines]
D --> D2[Best Practices]
This tool is designed for ethical use only. Please use responsibly and avoid any form of academic dishonesty.