💡 WRAP-UP

Built a complete RAG system with:
✅ Optimized retrieval (k=3, 86.67% precision)
✅ Evaluated prompts (8.0/10 quality)
✅ Real-time monitoring (7 charts)
✅ Full Docker deployment
✅ Hallucination prevention

#LLMZOOMCAMP #BuildInPublic

🔄 REPRODUCIBILITY

Everything needed to run this:
📦 requirements.txt with pinned versions
🐳 Docker Compose for one-command deploy
📚 Complete documentation
🎯 Sample data included

Clone, configure API key, run. That's it!

#LLMZOOMCAMP

⏱️ PERFORMANCE NUMBERS

• Retrieval: < 1 second
• Processing: 1,400 chunks/min
• Batch size: 5,000 docs
• Dataset: 10+ technical books (15,354 chunks)

Fast enough for real-time queries!

#LLMZOOMCAMP #Performance

📥 SMART INGESTION

Auto-detects existing vector DB or creates new one
Handles PDFs + TXT files
Batch processing for large collections
Graceful error handling

Set it and forget it!

#LLMZOOMCAMP #DataEngineering

📈 EVALUATION FRAMEWORK

Retrieval: Precision + keyword relevance
LLM: Quality scoring (accuracy, depth, honesty)

Ran ~50 test queries across both evaluations.

Measure everything. Improve what matters.

#LLMZOOMCAMP #MLOps

🛡️ PREVENTING HALLUCINATIONS

Tested with out-of-scope questions.

System correctly says "I cannot tell you based on the provided context" instead of making things up.

Honesty > Confidence

#LLMZOOMCAMP #AIEthics

🎨 USER EXPERIENCE

Two-tab Streamlit interface:
1. Q&A System with source previews
2. Analytics Dashboard

Auto-initialization on startup = zero-config for users

Good UX = better adoption!

#LLMZOOMCAMP #UX

SCALING CHALLENGES

Hit API limits at 15,000+ document chunks!

Solution: Batch processing (5000 chunks/batch)
Result: ~1,400 chunks/min processing speed

Always plan for scale from day one.

#LLMZOOMCAMP #Scaling

🐳 FULL CONTAINERIZATION

Docker Compose with:
• Named volumes for persistence
• Health checks
• Resource limits (2 CPU, 4GB RAM)
• Non-root user for security
• Auto-restart policies

One command deploy!

#LLMZOOMCAMP #DevOps #Docker

📊 MONITORING MATTERS

Built an integrated dashboard with 7 real-time charts:
- Feedback distribution
- Response times
- Query volume
- Activity patterns

User feedback: 👍/👎 buttons after every answer

#LLMZOOMCAMP #DataViz

🤖 PROMPT ENGINEERING

Tested 4 prompt templates on quality:
• Expert Technical: 8.0/10 ⭐
• Detailed Context: 7.9/10
• Structured: 7.0/10
• Concise: 6.2/10

Comprehensive wins over brevity for technical Q&A!

#LLMZOOMCAMP #PromptEngineering

🔍 RETRIEVAL OPTIMIZATION

Evaluated 4 different approaches:
• Semantic (k=3): 86.67% precision ✅
• Semantic (k=5): 84.00%
• Semantic (k=10): 84.00%
• MMR (k=5): 84.00%

Less is more! k=3 won with best relevance.

#LLMZOOMCAMP #MachineLearning

🛠️ TECH STACK

• LLM: Google Gemini 2.5 Pro
• Embeddings: text-embedding-004
• Vector DB: ChromaDB
• Framework: LangChain
• UI: Streamlit
• Container: Docker

All production-ready with monitoring!

#LLMZOOMCAMP #TechStack