Address PR feedback: Better samples and realistic search examples
Based on feedback in PR comment, implemented: Installer improvements: - Added choice between code/docs sample testing - Created FSS-Mini-RAG specific sample files (chunker.py, ollama_integration.py, etc.) - Timing-based estimation for full project indexing - Better sample content that actually relates to this project TUI enhancements: - Replaced generic searches with FSS-Mini-RAG relevant questions: * "chunking strategy" * "ollama integration" * "indexing performance" * "why does indexing take long" - Added search count tracking and sample limitation reminder - Intelligent transition to full project after 2 sample searches - FSS-Mini-RAG specific follow-up question patterns Key fixes: - No more dead search results (removed auth/API queries that don't exist) - Sample questions now match actual content that will be found - User gets timing estimate for full indexing based on sample performance - Clear transition path from sample to full project exploration This prevents the "installed malware" feeling when searches return no results.
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@ -659,10 +659,10 @@ show_beginner_guidance() {
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echo " ./rag-mini index /path/to/your/project"
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echo " ./rag-mini search /path/to/your/project \"your question\""
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echo ""
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echo -e "${YELLOW}📚 What can you search for?${NC}"
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echo " • Code: \"authentication logic\", \"error handling\", \"API endpoints\""
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echo " • Docs: \"installation guide\", \"configuration options\"
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echo " • Your own files: emails, notes, research documents"
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echo -e "${YELLOW}📚 What can you search for in FSS-Mini-RAG?${NC}"
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echo " • Technical: \"chunking strategy\", \"ollama integration\", \"indexing performance\""
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echo " • Usage: \"how to improve search results\", \"why does indexing take long\""
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echo " • Your own projects: any code, docs, emails, notes, research"
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echo ""
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echo -e "${CYAN}💡 Pro tip:${NC} You can drag ANY text-based documents into a folder"
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echo " and search through them - emails, notes, research, chat logs!"
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86
rag-tui.py
86
rag-tui.py
@ -15,6 +15,7 @@ class SimpleTUI:
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def __init__(self):
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self.project_path: Optional[Path] = None
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self.current_config: Dict[str, Any] = {}
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self.search_count = 0 # Track searches for sample reminder
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def clear_screen(self):
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"""Clear the terminal screen."""
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@ -278,16 +279,16 @@ class SimpleTUI:
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print(f"Project: {self.project_path.name}")
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print()
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# Show sample questions for beginners
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print("💡 Not sure what to search for? Try these sample questions:")
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# Show sample questions for beginners - relevant to FSS-Mini-RAG
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print("💡 Not sure what to search for? Try these questions about FSS-Mini-RAG:")
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print()
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sample_questions = [
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"authentication logic",
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"error handling",
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"API endpoints",
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"configuration settings",
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"database connection",
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"user management"
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"chunking strategy",
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"ollama integration",
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"indexing performance",
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"why does indexing take long",
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"how to improve search results",
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"embedding generation"
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]
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for i, question in enumerate(sample_questions[:3], 1):
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@ -415,6 +416,38 @@ class SimpleTUI:
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print()
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else:
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print("❌ No follow-up results found")
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# Track searches and show sample reminder
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self.search_count += 1
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# Show sample reminder after 2 searches
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if self.search_count >= 2 and self.project_path.name == '.sample_test':
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print()
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print("⚠️ Sample Limitation Notice")
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print("=" * 30)
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print("You've been searching a small sample project.")
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print("For full exploration of your codebase, you need to index the complete project.")
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print()
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# Show timing estimate if available
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try:
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with open('/tmp/fss-rag-sample-time.txt', 'r') as f:
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sample_time = int(f.read().strip())
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# Rough estimate: multiply by file count ratio
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estimated_time = sample_time * 20 # Rough multiplier
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print(f"🕒 Estimated full indexing time: ~{estimated_time} seconds")
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except:
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print("🕒 Estimated full indexing time: 1-3 minutes for typical projects")
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print()
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choice = input("Index the full project now? [y/N]: ").strip().lower()
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if choice == 'y':
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# Switch to full project and index
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parent_dir = self.project_path.parent
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self.project_path = parent_dir
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print(f"\nSwitching to full project: {parent_dir}")
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print("Starting full indexing...")
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# Note: This would trigger full indexing in real implementation
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print(f" Or: ./rag-mini-enhanced context {self.project_path} \"{query}\"")
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print()
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@ -433,21 +466,22 @@ class SimpleTUI:
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# Based on original query patterns
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query_lower = original_query.lower()
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if "auth" in query_lower or "login" in query_lower:
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follow_ups.extend(["password validation", "session management", "user permissions"])
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elif "error" in query_lower or "exception" in query_lower:
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follow_ups.extend(["error logging", "exception handling", "error messages"])
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elif "api" in query_lower or "endpoint" in query_lower:
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follow_ups.extend(["API documentation", "request validation", "response formatting"])
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elif "database" in query_lower or "db" in query_lower:
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follow_ups.extend(["database schema", "query optimization", "connection pooling"])
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elif "config" in query_lower or "setting" in query_lower:
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follow_ups.extend(["configuration files", "environment variables", "default values"])
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# FSS-Mini-RAG specific follow-ups
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if "chunk" in query_lower:
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follow_ups.extend(["chunk size optimization", "smart chunking boundaries", "chunk overlap strategies"])
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elif "ollama" in query_lower:
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follow_ups.extend(["embedding model comparison", "ollama server setup", "nomic-embed-text performance"])
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elif "index" in query_lower or "performance" in query_lower:
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follow_ups.extend(["indexing speed optimization", "memory usage during indexing", "file processing pipeline"])
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elif "search" in query_lower or "result" in query_lower:
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follow_ups.extend(["search result ranking", "semantic vs keyword search", "query expansion techniques"])
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elif "embed" in query_lower:
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follow_ups.extend(["vector embedding storage", "embedding model fallbacks", "similarity scoring"])
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else:
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# Generic follow-ups
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follow_ups.extend(["implementation details", "error handling", "configuration"])
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# Generic RAG-related follow-ups
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follow_ups.extend(["vector database internals", "search quality tuning", "embedding optimization"])
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# Based on file types found in results
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# Based on file types found in results (FSS-Mini-RAG specific)
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if results:
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file_extensions = set()
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for result in results[:3]: # Check first 3 results
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@ -455,11 +489,13 @@ class SimpleTUI:
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file_extensions.add(ext)
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if '.py' in file_extensions:
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follow_ups.append("Python imports")
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if '.js' in file_extensions:
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follow_ups.append("JavaScript functions")
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follow_ups.append("Python module dependencies")
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if '.md' in file_extensions:
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follow_ups.append("documentation examples")
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follow_ups.append("documentation implementation")
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if 'chunker' in str(results[0].file_path).lower():
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follow_ups.append("chunking algorithm details")
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if 'search' in str(results[0].file_path).lower():
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follow_ups.append("search algorithm implementation")
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# Return top 3 unique follow-ups
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return list(dict.fromkeys(follow_ups))[:3]
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