BobAi
4166d0a362
🎯 Complete transformation from 5.9GB bloated system to 70MB optimized solution ✨ Key Features: - Hybrid embedding system (Ollama + ML fallback + hash backup) - Intelligent chunking with language-aware parsing - Semantic + BM25 hybrid search with rich context - Zero-config portable design with graceful degradation - Beautiful TUI for beginners + powerful CLI for experts - Comprehensive documentation with 8+ Mermaid diagrams - Professional animated demo (183KB optimized GIF) 🏗️ Architecture Highlights: - LanceDB vector storage with streaming indexing - Smart file tracking (size/mtime) to avoid expensive rehashing - Progressive chunking: Markdown headers → Python functions → fixed-size - Quality filtering: 200+ chars, 20+ words, 30% alphanumeric content - Concurrent batch processing with error recovery 📦 Package Contents: - Core engine: claude_rag/ (11 modules, 2,847 lines) - Entry points: rag-mini (unified), rag-tui (beginner interface) - Documentation: README + 6 guides with visual diagrams - Assets: 3D icon, optimized demo GIF, recording tools - Tests: 8 comprehensive integration and validation tests - Examples: Usage patterns, config templates, dependency analysis 🎥 Demo System: - Scripted demonstration showing 12 files → 58 chunks indexing - Semantic search with multi-line result previews - Complete workflow from TUI startup to CLI mastery - Professional recording pipeline with asciinema + GIF conversion 🛡️ Security & Quality: - Complete .gitignore with personal data protection - Dependency optimization (removed python-dotenv) - Code quality validation and educational test suite - Agent-reviewed architecture and documentation Ready for production use - copy folder, run ./rag-mini, start searching\!
234 lines
8.7 KiB
Python
Executable File
234 lines
8.7 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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Create an animated demo script that simulates the FSS-Mini-RAG TUI experience.
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This script generates a realistic but controlled demonstration for GIF recording.
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"""
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import time
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import sys
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import os
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from typing import List
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class DemoSimulator:
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def __init__(self):
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self.width = 80
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self.height = 24
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def clear_screen(self):
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"""Clear the terminal screen."""
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print("\033[H\033[2J", end="")
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def type_text(self, text: str, delay: float = 0.03):
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"""Simulate typing text character by character."""
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for char in text:
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print(char, end="", flush=True)
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time.sleep(delay)
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print()
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def pause(self, duration: float):
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"""Pause for the specified duration."""
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time.sleep(duration)
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def show_header(self):
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"""Display the TUI header."""
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print("╔════════════════════════════════════════════════════╗")
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print("║ FSS-Mini-RAG TUI ║")
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print("║ Semantic Code Search Interface ║")
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print("╚════════════════════════════════════════════════════╝")
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print()
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def show_menu(self):
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"""Display the main menu."""
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print("🎯 Main Menu")
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print("============")
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print()
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print("1. Select project directory")
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print("2. Index project for search")
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print("3. Search project")
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print("4. View status")
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print("5. Configuration")
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print("6. CLI command reference")
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print("7. Exit")
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print()
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print("💡 All these actions can be done via CLI commands")
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print(" You'll see the commands as you use this interface!")
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print()
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def simulate_project_selection(self):
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"""Simulate selecting a project directory."""
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print("Select option (number): ", end="", flush=True)
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self.type_text("1", delay=0.15)
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self.pause(0.5)
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print()
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print("📁 Select Project Directory")
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print("===========================")
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print()
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print("Project path: ", end="", flush=True)
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self.type_text("./demo-project", delay=0.08)
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self.pause(0.8)
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print()
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print("✅ Selected: ./demo-project")
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print()
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print("💡 CLI equivalent: rag-mini index ./demo-project")
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self.pause(1.5)
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def simulate_indexing(self):
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"""Simulate the indexing process."""
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self.clear_screen()
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self.show_header()
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print("🚀 Indexing demo-project")
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print("========================")
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print()
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print("Found 12 files to index")
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print()
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# Simulate progress bar
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print(" Indexing files... ", end="")
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progress_chars = "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━"
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for i, char in enumerate(progress_chars):
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print(char, end="", flush=True)
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time.sleep(0.03) # Slightly faster
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if i % 8 == 0:
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percentage = int((i / len(progress_chars)) * 100)
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print(f" {percentage}%", end="\r")
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print(" Indexing files... " + progress_chars[:i+1], end="")
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print(" 100%")
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print()
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print(" Added 58 chunks to database")
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print()
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print("Indexing Complete!")
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print("Files indexed: 12")
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print("Chunks created: 58")
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print("Time taken: 2.8 seconds")
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print("Speed: 4.3 files/second")
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print("✅ Indexed 12 files in 2.8s")
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print(" Created 58 chunks")
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print(" Speed: 4.3 files/sec")
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print()
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print("💡 CLI equivalent: rag-mini index ./demo-project")
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self.pause(2.0)
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def simulate_search(self):
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"""Simulate searching the indexed project."""
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self.clear_screen()
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self.show_header()
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print("🔍 Search Project")
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print("=================")
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print()
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print("Search query: ", end="", flush=True)
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self.type_text('"user authentication"', delay=0.08)
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self.pause(0.8)
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print()
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print("🔍 Searching \"user authentication\" in demo-project")
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self.pause(0.5)
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print("✅ Found 8 results:")
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print()
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# Show search results with multi-line previews
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results = [
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{
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"file": "auth/manager.py",
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"function": "AuthManager.login()",
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"preview": "Authenticate user and create session.\nValidates credentials against database and\nreturns session token on success.",
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"score": "0.94"
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},
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{
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"file": "auth/validators.py",
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"function": "validate_password()",
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"preview": "Validate user password against stored hash.\nSupports bcrypt, scrypt, and argon2 hashing.\nIncludes timing attack protection.",
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"score": "0.91"
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},
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{
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"file": "middleware/auth.py",
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"function": "require_authentication()",
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"preview": "Authentication middleware decorator.\nChecks session tokens and JWT validity.\nRedirects to login on authentication failure.",
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"score": "0.88"
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},
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{
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"file": "api/endpoints.py",
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"function": "login_endpoint()",
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"preview": "Handle user login API requests.\nAccepts JSON credentials, validates input,\nand returns authentication tokens.",
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"score": "0.85"
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},
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{
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"file": "models/user.py",
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"function": "User.authenticate()",
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"preview": "User model authentication method.\nQueries database for user credentials\nand handles account status checks.",
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"score": "0.82"
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}
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]
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for i, result in enumerate(results, 1):
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print(f"📄 Result {i} (Score: {result['score']})")
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print(f" File: {result['file']}")
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print(f" Function: {result['function']}")
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preview_lines = result['preview'].split('\n')
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for j, line in enumerate(preview_lines):
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if j == 0:
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print(f" Preview: {line}")
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else:
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print(f" {line}")
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print()
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self.pause(0.6)
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print("💡 CLI equivalent: rag-mini search ./demo-project \"user authentication\"")
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self.pause(2.5)
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def simulate_cli_reference(self):
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"""Show CLI command reference."""
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self.clear_screen()
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self.show_header()
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print("🖥️ CLI Command Reference")
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print("=========================")
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print()
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print("What you just did in the TUI:")
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print()
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print("1️⃣ Select & Index Project:")
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print(" rag-mini index ./demo-project")
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print(" # Indexed 12 files → 58 semantic chunks")
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print()
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print("2️⃣ Search Project:")
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print(' rag-mini search ./demo-project "user authentication"')
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print(" # Found 8 relevant matches with context")
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print()
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print("3️⃣ Check Status:")
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print(" rag-mini status ./demo-project")
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print()
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print("🚀 You can now use these commands directly!")
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print(" No TUI required for power users.")
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print()
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print("💡 Try semantic queries like:")
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print(' • "error handling" • "database queries"')
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print(' • "API validation" • "configuration management"')
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self.pause(3.0)
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def run_demo(self):
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"""Run the complete demo simulation."""
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print("🎬 Starting FSS-Mini-RAG Demo...")
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self.pause(1.0)
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# Clear and show TUI startup
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self.clear_screen()
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self.show_header()
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self.show_menu()
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self.pause(1.5)
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# Simulate workflow
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self.simulate_project_selection()
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self.simulate_indexing()
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self.simulate_search()
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self.simulate_cli_reference()
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# Final message
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self.clear_screen()
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print("🎉 Demo Complete!")
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print()
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print("FSS-Mini-RAG: Semantic code search that actually works")
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print("Copy the folder, run ./rag-mini, and start searching!")
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print()
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print("Ready to try it yourself? 🚀")
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if __name__ == "__main__":
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demo = DemoSimulator()
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demo.run_demo() |