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CHOTU AI (Comprehensive Heuristic Operations & Technical Utility) revolutionizes how you interact with artificial intelligence.
π― One Platform. Infinite Possibilities.
No more juggling multiple AI subscriptions!
Compare AI responses
Discover 200+ tools
Analyze screenshots
Practice interviews
class ChotuAI: def __init__(self): self.engine = "Google Gemini 1.5 Flash" self.speed = "Lightning Fast β‘" self.vision = "Advanced ποΈ" self.cost = "FREE π" def transform_ai_experience(self): return "π Revolutionary!" ai = ChotuAI() print(ai.transform_ai_experience()) # Output: π Revolutionary!
Multi-AI Comparison Engine
Test your prompts across GPT-4, Claude, Gemini, and Mistral simultaneously!
π Side-by-side comparison
π― Find the best response
π‘ Understand model strengths
Ultimate AI Tool Directory
Explore 200+ AI tools categorized by use case!
ποΈ Smart categorization
π° Price comparisons
β User ratings
AI Visual Analyzer
Upload screenshots for instant expert analysis!
π Debug code errors
π¨ Get design feedback
β‘ Real-time solutions
AI Interview Coach
Practice with an adaptive AI interviewer!
π€ Mock interviews
π STAR-method feedback
πΌ Career-specific prep
HTML5 CSS3 JavaScript Bootstrap TailwindCSS
Backend Stack
AI Stack
Google Gemini OpenAI Anthropic
DevOps Stack
# 1οΈβ£ Clone the Repository git clone https://github.com/jamesb0074000-wq/chotu-ai.git cd chotu-ai # 2οΈβ£ Create Virtual Environment python -m venv venv # πͺ Windows venv\Scripts\activate # π Mac/Linux source venv/bin/activate # 3οΈβ£ Install Dependencies pip install -r requirements.txt # 4οΈβ£ Set Up Environment Variables cat > .env << EOF GEMINI_API_KEY=your_gemini_api_key_here SECRET_KEY=your_super_secret_key DATABASE_URL=sqlite:///chotu.db FLASK_ENV=development EOF # 5οΈβ£ Initialize Database python init_db.py # 6οΈβ£ Run the Application python app.py
π Success! Visit http://127.0.0.1:5000 π
chotu-ai/
β
βββ π static/
β βββ π¨ css/
β β βββ main.css
β β βββ themes.css
β β βββ animations.css
β βββ β‘ js/
β β βββ app.js
β β βββ promptmirror.js
β β βββ discovery.js
β β βββ screensage.js
β βββ πΌοΈ images/
β βββ logos/
β βββ icons/
β βββ screenshots/
β
βββ π templates/
β βββ π base.html
β βββ π index.html
β βββ π promptmirror.html
β βββ π discovery.html
β βββ πΊ screensage.html
β βββ π― hirewise.html
β βββ π€ profile.html
β
βββ π models/
β βββ ποΈ database.py
β βββ π€ user.py
β βββ π¬ conversation.py
β βββ π§ tool.py
β
βββ π utils/
β βββ π οΈ helpers.py
β βββ π€ ai_handler.py
β βββ π auth.py
β βββ π analytics.py
β
βββ π api/
β βββ π routes.py
β βββ π― endpoints.py
β βββ π middleware.py
β
βββ π tests/
β βββ β
test_app.py
β βββ β
test_models.py
β βββ β
test_api.py
β
βββ π app.py # Main application
βββ βοΈ config.py # Configuration
βββ π requirements.txt # Dependencies
βββ π .env.example # Environment template
βββ π³ Dockerfile # Docker config
βββ π docker-compose.yml # Docker Compose
βββ π README.md # This file
βββ π LICENSE # MIT License
βββ π deploy.sh # Deployment script
π PromptMirror - Multi-Model Comparison
# Example: Testing creative writing prompts from chotu_ai import PromptMirror mirror = PromptMirror() prompt = "Write a haiku about artificial intelligence" results = mirror.compare_all(prompt) for model, response in results.items(): print(f"\nπ€ {model}:") print(f" {response.text}") print(f" β±οΈ Response Time: {response.time}ms") print(f" β Creativity Score: {response.score}/10")
Output:
π€ GPT-4:
Silicon thoughts arise
In neural nets they reside
Learning never ends
β±οΈ Response Time: 1250ms
β Creativity Score: 9/10
π€ Claude:
Circuits come alive
Minds of math and logic bloom
Future whispers soft
β±οΈ Response Time: 980ms
β Creativity Score: 8/10
π Discovery Hub - Smart Tool Search
# Find the perfect AI tool for your needs from chotu_ai import DiscoveryHub hub = DiscoveryHub() # Search with filters tools = hub.search( category="Image Generation", price_range="free", min_rating=4.5, features=["API", "Commercial Use"] ) for tool in tools: print(f"π¨ {tool.name}") print(f" π° {tool.pricing}") print(f" β {tool.rating}/5.0") print(f" π {tool.url}\n")
πΊ ScreenSage - Visual AI Analysis
# Analyze code screenshots for debugging from chotu_ai import ScreenSage sage = ScreenSage() # Upload and analyze analysis = sage.analyze( image_path="error_screenshot.png", context="Python Django Debug" ) print(f"π Issue Detected: {analysis.issue}") print(f"π‘ Solution: {analysis.solution}") print(f"π Resources: {analysis.resources}") print(f"β‘ Confidence: {analysis.confidence}%")
π― HireWise - Interview Coaching
# Practice technical interviews from chotu_ai import HireWise coach = HireWise() # Start interview session session = coach.start_interview( role="Senior Python Developer", difficulty="hard" ) # Simulate Q&A response = session.answer( question="Explain the GIL in Python", answer="The Global Interpreter Lock..." ) print(f"π Feedback: {response.feedback}") print(f"β Rating: {response.score}/10") print(f"π‘ Improvement Tips: {response.tips}")
%%{init: {'theme':'dark'}}%%
timeline
title CHOTU AI Development Journey
2024 Q4 : Core Platform
: β
PromptMirror Engine
: β
Discovery Hub
: β
ScreenSage Analysis
: β
HireWise Coach
2025 Q1 : Advanced Features
: π Voice Interviews
: π Model Fine-tuning
: π Team Collaboration
: π API Access
2025 Q2 : Mobile & Cloud
: π± iOS/Android Apps
: βοΈ Cloud Deployment
: π Enterprise Security
: π Analytics Dashboard
2025 Q3 : AI Integration
: π€ Custom Models
: π Multi-language
: π Third-party APIs
: π¨ White-label Solution
2025 Q4 : Global Scale
: π Worldwide Launch
: πΌ Enterprise Plans
: π AI Marketplace
: π 1M+ Users
| Feature | Status | Progress | Release |
|---|---|---|---|
| π PromptMirror | β Complete | 100% | v1.0 |
| π Discovery Hub | β Complete | 100% | v1.0 |
| πΊ ScreenSage | β Complete | 100% | v1.0 |
| π― HireWise | β Complete | 100% | v1.0 |
| π€ Voice Interviews | π In Progress | 65% | v1.5 |
| π± Mobile Apps | π Planned | 20% | v2.0 |
| π€ Custom Models | π Planned | 10% | v2.5 |
| π Multi-language | π Planned | 5% | v3.0 |
# 1. Fork the Repository Click the 'Fork' button at the top right # 2. Clone Your Fork git clone https://github.com/jamesb0074000-wq/chotu-ai.git cd chotu-ai # 3. Create a Branch git checkout -b feature/AmazingFeature # 4. Make Your Changes # ... code, code, code ... # 5. Commit Your Changes git add . git commit -m "β¨ Add: Amazing new feature" # 6. Push to GitHub git push origin feature/AmazingFeature # 7. Open a Pull Request # Go to GitHub and click 'New Pull Request'
| Type | Emoji | Example |
|---|---|---|
| New Feature | β¨ | β¨ Add: Voice interview mode |
| Bug Fix | π | π Fix: Screenshot upload issue |
| Documentation | π | π Docs: Update API guide |
| Performance | β‘ | β‘ Perf: Optimize AI queries |
| Refactor | β»οΈ | β»οΈ Refactor: Clean up code |
| Testing | β | β
Test: Add unit tests |
| Action | Impact |
|---|---|
| β Star this repo | Increases visibility |
| π Report bugs | Improves stability |
| π‘ Suggest features | Drives innovation |
| π Fork & contribute | Grows the community |
| π’ Share with others | Spreads the word |
| β Buy me a coffee | Fuels development |
GitHub Stars GitHub Forks GitHub Watchers
Star History Chart
| Milestone | Status | Date |
|---|---|---|
| π― 100 Stars | β Achieved | Jan 2025 |
| π 1000 Users | π In Progress | Feb 2025 |
| πΌ Enterprise Launch | π Planned | Q2 2025 |
| π 1M+ Users | π― Goal | Q4 2025 |