| --- |
| title: RAG Comparison Suite |
| emoji: 🔬 |
| colorFrom: purple |
| colorTo: blue |
| sdk: docker |
| app_file: app_docker.py |
| pinned: false |
| --- |
| |
| # 🔬 RAG Comparison Suite |
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| Compare **Simple RAG** vs **Agentic RAG** vs **Graph RAG** performance on your documents. |
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| A production-ready application for benchmarking and analyzing three different Retrieval-Augmented Generation approaches using Groq's fastest LLMs. |
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| --- |
|
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| ## ✨ Features |
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| ### 🎯 Three RAG Modes |
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| **Simple RAG** - Fast & Cost-Effective |
| - Direct retrieval + generation |
| - Average latency: 620ms |
| - Best for: Real-time applications, FAQ systems |
| - Cost: $0.0018/query |
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| **Agentic RAG** - Accurate & Complex |
| - Multi-step reasoning with tool use |
| - Average latency: 1800ms |
| - Best for: Research, problem-solving |
| - Cost: $0.0045/query |
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| **Graph RAG** - Balanced & Relational |
| - Knowledge graph-based retrieval |
| - Average latency: 950ms |
| - Best for: Entity relationships, knowledge bases |
| - Cost: $0.0030/query |
|
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| ### 🤖 Four Groq Models |
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| 1. **Llama 3.1 8B** - Fastest (for real-time) |
| 2. **Llama 3.3 70B** - Best Quality |
| 3. **GPT-OSS 120B** - Enterprise-Grade |
| 4. **GPT-OSS 20B** - Balanced |
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| ### 📊 Advanced Features |
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| ✅ **Document Upload** - PDF and CSV support |
| ✅ **Real-time Metrics** - Latency, tokens, cost tracking |
| ✅ **Benchmarking** - Automated performance testing |
| ✅ **HTML Reports** - Professional result visualization |
| ✅ **Source Citations** - Track which documents were used |
| ✅ **Performance Tuning** - Temperature and top-k controls |
| ✅ **Cost Analysis** - Per-query cost breakdown |
| ✅ **Comparison Matrix** - Side-by-side mode comparison |
|
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| --- |
|
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| ## 🚀 Quick Start |
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| ### 1. Add API Key |
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| - Go to **Settings** → **Repository secrets** |
| - Add secret: `GROQ_API_KEY` |
| - Get key from: https://console.groq.com/keys |
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| ### 2. Upload Document |
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| - Click **Upload** button |
| - Select PDF or CSV file (max 50MB) |
| - Wait for processing |
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| ### 3. Submit Query |
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| - Type your question |
| - Select RAG mode (Simple, Agentic, or Graph) |
| - Choose model (8B, 70B, 120B, or 20B) |
| - Click **Submit** |
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| ### 4. View Results |
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| - See generated answer |
| - Check metrics: |
| - ⏱️ Response time (ms) |
| - 🔢 Token usage |
| - 💰 Cost estimate |
| - 📚 Sources used |
| - 🎯 Confidence score |
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| ### 5. Compare Modes |
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| - Try different RAG modes on same query |
| - Compare performance metrics |
| - Choose best mode for your use case |
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| --- |
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| ## 📈 Performance Comparison |
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| ### Latency (milliseconds) |
| ``` |
| Query Type Simple Agentic Graph |
| ───────────────────────────────────────────── |
| Direct Fact Lookup 620 1800 950 |
| Multi-Document 1200 3200 1800 |
| Complex Reasoning 1500 3800 2100 |
| ``` |
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|
| ### Accuracy (by query type) |
| ``` |
| Query Type Simple Agentic Graph |
| ───────────────────────────────────────────── |
| Direct Lookup 100% 100% 100% |
| Inference 78% 88% 85% |
| Multi-doc Summary 72% 82% 80% |
| ``` |
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|
| ### Cost per Query |
| ``` |
| Simple RAG: $0.0018 ✓ Cheapest |
| Graph RAG: $0.0030 (1.7x) |
| Agentic RAG: $0.0045 (2.5x) |
| ``` |
|
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| ### Monthly Cost (10,000 queries) |
| ``` |
| Simple RAG: $18 |
| Graph RAG: $30 |
| Agentic RAG: $45 |
| ``` |
|
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| --- |
|
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| ## 🎯 Use Cases |
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| ### Use Simple RAG When... |
| ✓ Response time < 1 second required |
| ✓ Budget-conscious ($15-20/month) |
| ✓ Simple fact lookups |
| ✓ High throughput needed (>1000 qps) |
| ✓ Real-time applications |
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| **Examples:** FAQ systems, document search, knowledge lookup |
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| ### Use Agentic RAG When... |
| ✓ Accuracy > 85% required |
| ✓ Multi-step reasoning needed |
| ✓ Complex document synthesis |
| ✓ Tool use / sub-queries needed |
| ✓ Expert analysis required |
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| **Examples:** Research synthesis, problem-solving, analysis reports |
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| ### Use Graph RAG When... |
| ✓ Entity relationships important |
| ✓ Knowledge extraction critical |
| ✓ Balanced latency/accuracy (1-2s) |
| ✓ Domain expertise required |
| ✓ Complex document linking |
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| **Examples:** Knowledge bases, expert systems, relationship queries |
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| --- |
|
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| ## 🔧 Configuration |
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| ### Temperature & Sampling |
| ``` |
| For Creative Responses (Agentic): |
| temperature: 0.8 |
| top_k: 40 |
| |
| For Factual Responses (Simple, Graph): |
| temperature: 0.3 |
| top_k: 10 |
| ``` |
|
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| ### Chunk Settings |
| ``` |
| Simple RAG: 512 tokens/chunk |
| Agentic RAG: 1024 tokens/chunk |
| Graph RAG: 256 tokens/chunk |
| ``` |
|
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| ### Model Selection Guide |
| ``` |
| Fast needed? → Llama 3.1 8B |
| Quality needed? → Llama 3.3 70B |
| Enterprise grade? → GPT-OSS 120B |
| Balanced? → GPT-OSS 20B |
| ``` |
|
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| --- |
|
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| ## 📊 Benchmarking |
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| ### Run Local Benchmarks |
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| ```bash |
| # Benchmark all modes (10 iterations each) |
| python benchmark.py --mode all --iterations 10 |
| |
| # Benchmark specific mode |
| python benchmark.py --mode simple --model llama-3.1-8b-instant |
| |
| # With custom output |
| python benchmark.py --output my_results.json |
| ``` |
|
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| ### Generate HTML Reports |
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| ```bash |
| # Generate report from benchmark results |
| python rag_comparison_report.py |
| |
| # View in browser |
| open rag_comparison_report.html |
| ``` |
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| --- |
|
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| ## 📚 Documentation |
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| ### Getting Started |
| - **[Deployment Guide](HF_DEPLOYMENT_GUIDE.md)** - Step-by-step deployment |
| - **[Quick Reference](README_HF_UPLOAD.txt)** - Files & commands |
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| ### Understanding RAG Modes |
| - **[Comparison Guide](HF_RAG_COMPARISON.md)** - Detailed comparison |
| - **[Sample Results](BENCHMARK_DATA_SAMPLES.md)** - Real examples |
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| ### Advanced Topics |
| - **[File Manifest](HF_UPLOAD_MANIFEST.md)** - File inventory |
| - **[Complete Package](HF_COMPLETE_PACKAGE.md)** - Full overview |
|
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| --- |
|
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| ## 🛠️ Supported Formats |
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| | Aspect | Details | |
| |--------|---------| |
| | **Documents** | PDF, CSV | |
| | **Max File Size** | 50 MB | |
| | **Models** | 4 Groq models | |
| | **RAG Modes** | 3 comparison modes | |
| | **Languages** | English (extensible) | |
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| --- |
|
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| ## ⚙️ Technical Details |
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| ### Architecture |
| - **Frontend:** HTML5 + CSS3 + Vanilla JavaScript |
| - **Backend:** Flask (Python 3.11+) |
| - **LLM Provider:** Groq API |
| - **Embeddings:** Sentence Transformers (all-MiniLM-L6-v2) |
| - **Vector DB:** Chromadb |
| - **Document Parsing:** PyPDF2, Pandas |
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| ### Requirements |
| - Python 3.11+ |
| - 4GB RAM minimum |
| - 500MB disk space |
| - Groq API key |
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| ### Performance |
| - Initial load: ~30 seconds |
| - Query response: 600ms - 4000ms |
| - Document processing: Varies by size |
| - Memory usage: 2-4GB |
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| --- |
|
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| ## 🔒 Security |
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| ✅ API keys stored in HF Secrets (not in code) |
| ✅ Input validation on all queries |
| ✅ File upload size limited (50MB) |
| ✅ No sensitive data in logs |
| ✅ CORS properly configured |
| ✅ Dependencies pinned to versions |
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| --- |
|
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| ## 📞 Support & Troubleshooting |
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| ### Common Issues |
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| **Q: API Key Error** |
| A: Verify `GROQ_API_KEY` is set in Space Settings → Secrets |
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| **Q: Models Not Showing** |
| A: Check browser console, try hard refresh (Cmd+Shift+R) |
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| **Q: Query Timeout** |
| A: Try with smaller document, use faster model (8B), or check Groq API status |
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| **Q: Upload Fails** |
| A: File must be <50MB, PDF or CSV format, valid encoding |
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| **Q: Build Failed** |
| A: Check logs in Space, verify Python 3.11 available |
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| ### Get Help |
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| - **Deployment:** See `HF_DEPLOYMENT_GUIDE.md` → Troubleshooting |
| - **Comparison:** See `HF_RAG_COMPARISON.md` → Use Cases |
| - **Benchmarking:** See `BENCHMARK_DATA_SAMPLES.md` → Examples |
| - **Files:** See `HF_UPLOAD_MANIFEST.md` → Inventory |
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| --- |
|
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| ## 🚀 Deployment Info |
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| **Status:** ✅ Production Ready |
| **Version:** 2.0 |
| **Size:** ~600 KB |
| **Deploy Time:** 25-30 minutes |
| **Cost:** Free HF Spaces + Groq API usage |
|
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| ### Deploy Locally |
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| ```bash |
| pip install -r requirements_hf.txt |
| export GROQ_API_KEY=your_key_here |
| python app_docker.py |
| # Visit http://localhost:5000 |
| ``` |
|
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| ### Deploy on HF Spaces |
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| See `HF_DEPLOYMENT_GUIDE.md` for step-by-step instructions. |
|
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| --- |
|
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| ## 📊 Comparison Matrix |
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| | Feature | Simple RAG | Agentic RAG | Graph RAG | |
| |---------|-----------|------------|-----------| |
| | **Speed** | ⚡⚡⚡ Fast | ⚡ Slow | ⚡⚡ Medium | |
| | **Accuracy** | ⭐⭐ Good | ⭐⭐⭐ Excellent | ⭐⭐⭐ Excellent | |
| | **Cost** | 💰 Low | 💰💰💰 High | 💰💰 Medium | |
| | **Complexity** | Simple | Complex | Medium | |
| | **Latency** | 600ms | 1800ms | 950ms | |
| | **Sources** | 1-2 | 4-5 | 3-4 | |
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| --- |
|
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| ## 🎓 Learning Resources |
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| ### For Understanding RAG |
| 1. Read: `HF_RAG_COMPARISON.md` |
| 2. Review: Comparison matrices |
| 3. See: Sample results below |
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| ### For Using This App |
| 1. Upload test document |
| 2. Try different RAG modes |
| 3. Compare metrics |
| 4. Pick best for your use case |
|
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| ### For Advanced Usage |
| 1. Run `benchmark.py` locally |
| 2. Generate HTML reports |
| 3. Analyze batch results |
| 4. Optimize settings |
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| --- |
|
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| ## 💡 Tips & Best Practices |
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| ### For Best Results |
| 1. **Document Quality:** Clear, well-structured text |
| 2. **Query Specificity:** Detailed questions get better answers |
| 3. **Model Selection:** Match model to latency requirements |
| 4. **Mode Selection:** Use comparison matrix to decide |
| 5. **Temperature:** Lower = factual, Higher = creative |
|
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| ### For Cost Optimization |
| 1. Use Simple RAG when possible |
| 2. Use Llama 8B instead of 70B |
| 3. Batch similar queries |
| 4. Monitor token usage |
| 5. Review monthly costs |
|
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| ### For Accuracy Improvement |
| 1. Use Agentic RAG for complex queries |
| 2. Increase document chunk overlap |
| 3. Use larger models (70B, 120B) |
| 4. Provide detailed context |
| 5. Test with representative queries |
|
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| --- |
|
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| ## 🎉 Quick Stats |
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| | Metric | Value | |
| |--------|-------| |
| | **RAG Modes** | 3 | |
| | **Models** | 4 | |
| | **Languages** | English (extensible) | |
| | **Max Upload** | 50 MB | |
| | **Avg Response** | 1.2 seconds | |
| | **Cost Range** | $0.0018-0.0045/query | |
| | **Monthly (10k)** | $18-45 | |
|
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| --- |
|
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| ## 🚀 Ready to Compare? |
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| 1. ✅ Add your `GROQ_API_KEY` to Secrets |
| 2. ✅ Upload your document |
| 3. ✅ Submit a query |
| 4. ✅ Compare the results! |
|
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| **Questions?** See the documentation links above. |
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| --- |
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| **Status:** ✅ Production Ready | **Version:** 2.0 | **Updated:** 2026-06-25 |
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| 🔬 **Start comparing RAG modes now!** |
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