Add comprehensive interview preparation documentation

[Copilot]

Created technical documentation suite to help explain the Django LLM application architecture and implementation details during interviews.

Documentation Files

• START_HERE.md - Navigation hub with quick-start guides for different prep timelines (1 week to 30 minutes)
• INTERVIEW_GUIDE.md - Technical deep dive covering architecture, database design, API integration, security, and 40+ Q&A
• QUICK_REFERENCE.md - Cheat sheet with elevator pitch, key metrics, and common interview questions
• ARCHITECTURE_DIAGRAMS.md - ASCII diagrams showing system flows, data architecture, auth, and deployment
• INTERVIEW_PREP_INDEX.md - Week-by-week preparation strategy with confidence builders and interview tactics

Coverage

Application Structure:

• MVT pattern implementation with Django 4.2.16
• Single Conversation model with UUID-based threading
• Session-based context management for stateless LLM APIs
• Multi-model support (Llama 3.3, Qwen3, Mistral, Phi4)

Technical Details:

• OAuth integration via Django Allauth (Google, GitHub)
• File upload validation (.txt, .doc, .json, .csv, 30MB limit)
• API integration patterns with error handling
• PostgreSQL deployment on Heroku with Gunicorn
• Security measures (CSRF, environment variables, input validation)

Interview Preparation:

• Multiple preparation timelines based on available time
• Ready-to-use 30-second elevator pitch
• Whiteboard-ready architecture diagrams
• Common technical questions with detailed answers
• Demo flow guide and emergency reference

Total: 10,000+ words across 5 documents designed for quick scanning and progressive depth.

Original prompt

i want to understand the structure of this app in a way that i can explain it during my interview. help me by providing details of the app and features that i should remember

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