knowledge_base.py

import json
import os
from typing import List, Dict, Any, Optional, Generator
from dataclasses import dataclass
from enum import Enum
import hashlib
import logging
from datetime import datetime

import chromadb
from chromadb.config import Settings
from sentence_transformers import SentenceTransformer
from huggingface_hub import hf_hub_download

# Import the base LLM handler
from llm_handler import CybersecurityLLM

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)


# ================================================
# Security Knowledge Definitions
# ================================================

class SecurityTopic(Enum):
    PHISHING = "phishing"
    PASSWORDS = "passwords"
    MALWARE = "malware"
    SOCIAL_ENGINEERING = "social_engineering"
    DATA_PROTECTION = "data_protection"
    NETWORK_SECURITY = "network_security"
    INCIDENT_RESPONSE = "incident_response"
    PHYSICAL_SECURITY = "physical_security"
    MOBILE_SECURITY = "mobile_security"
    CLOUD_SECURITY = "cloud_security"
    COMPLIANCE = "compliance"
    EMAIL_SECURITY = "email_security"
    RANSOMWARE = "ransomware"
    ZERO_TRUST = "zero_trust"
    SUPPLY_CHAIN = "supply_chain"


@dataclass
class SecurityKnowledge:
    topic: SecurityTopic
    title: str
    content: str
    keywords: List[str]
    severity: str  # low, medium, high, critical
    last_updated: str = ""

    def to_dict(self) -> Dict[str, Any]:
        return {
            "topic": self.topic.value,
            "title": self.title,
            "content": self.content,
            "keywords": json.dumps(self.keywords),  # Serialize list to JSON string
            "severity": self.severity,
            "last_updated": self.last_updated or datetime.now().isoformat()
        }


# ================================================
# Main Knowledge Base Class
# ================================================

class CybersecurityKnowledgeBase:
    def __init__(self,
                 persist_directory: str = "./knowledge_db",
                 embedding_model: str = "all-MiniLM-L6-v2"):
        """
        Initialize knowledge base with vector database

        Args:
            persist_directory: Directory to persist ChromaDB
            embedding_model: Sentence transformer model for embeddings
        """

        logger.info(f"Initializing knowledge base at {persist_directory}")

        # Create directory if it doesn't exist
        os.makedirs(persist_directory, exist_ok=True)

        # Initialize ChromaDB with persistence
        self.client = chromadb.PersistentClient(
            path=persist_directory,
            settings=Settings(
                anonymized_telemetry=False,
                allow_reset=True
            )
        )

        # Create or get collection
        try:
            self.collection = self.client.get_collection("cybersecurity_knowledge")
            logger.info(f"Loaded existing collection with {self.collection.count()} documents")
        except:
            self.collection = self.client.create_collection(
                name="cybersecurity_knowledge",
                metadata={"description": "Cybersecurity best practices and knowledge"}
            )
            logger.info("Created new knowledge collection")

        # Initialize embedder
        logger.info(f"Loading embedding model: {embedding_model}")
        self.embedder = SentenceTransformer(embedding_model)

        # Load core knowledge if collection is empty
        if self.collection.count() == 0:
            logger.info("Loading core cybersecurity knowledge...")
            self._load_core_knowledge()

        # Track statistics
        self.stats = {
            "total_documents": self.collection.count(),
            "queries_processed": 0,
            "last_updated": datetime.now().isoformat()
        }

    def _load_core_knowledge(self):
        """Load comprehensive cybersecurity knowledge"""

        knowledge_items = [
            # Phishing and Email Security
            SecurityKnowledge(
                topic=SecurityTopic.PHISHING,
                title="Comprehensive Phishing Detection Guide",
                content="""
                IDENTIFYING PHISHING EMAILS - Complete Guide:

                Red Flags to Watch For:
                • Generic greetings: "Dear Customer" instead of your actual name
                • Urgency tactics: "Act now or your account will be closed!"
                • Grammar/spelling errors: Professional companies proofread their emails
                • Mismatched sender: Display name doesn't match email address
                • Suspicious links: Hover to see if URL matches claimed sender
                • Unexpected attachments: Especially .zip, .exe, .scr, .vbs files
                • Requests for sensitive info: Legitimate companies don't ask for passwords via email
                • Too good to be true: "You've won $1 million!"
                • Emotional manipulation: Fear, greed, curiosity, sympathy

                How to Verify Suspicious Emails:
                1. Check sender's email address carefully (not just display name)
                2. Hover over links WITHOUT clicking to preview destination
                3. Look for HTTPS and correct domain in links
                4. Contact company directly through official channels (not email links)
                5. Check for personalization - legitimate emails often include account numbers
                6. Verify with IT security team when in doubt

                What to Do If You Receive Phishing:
                1. Don't click links or download attachments
                2. Don't reply or provide any information
                3. Report to IT security immediately
                4. Forward to anti-phishing team if available
                5. Delete the email after reporting
                6. Warn colleagues if it's widespread

                If You Clicked a Phishing Link:
                1. Disconnect from network immediately
                2. Change passwords from a different device
                3. Report to IT security IMMEDIATELY
                4. Run antivirus scan
                5. Monitor accounts for suspicious activity
                6. Enable MFA on all accounts if not already done
                """,
                keywords=["phishing", "email", "scam", "suspicious", "link", "attachment", "spear phishing", "whaling",
                          "BEC"],
                severity="critical"
            ),

            # Password Security
            SecurityKnowledge(
                topic=SecurityTopic.PASSWORDS,
                title="Password Security Best Practices",
                content="""
                CREATING STRONG PASSWORDS:

                Requirements for Strong Passwords:
                • Minimum 12-16 characters (longer is better)
                • Mix of uppercase and lowercase letters
                • Include numbers and special characters (!@#$%^&*)
                • Avoid dictionary words and personal information
                • Unique for every account - never reuse passwords
                • Consider passphrases: 'Coffee@7Makes$Me!Happy2024'
                • Avoid patterns: Password1, Password2, etc.
                • Don't use keyboard patterns: qwerty, 123456

                Password Management Best Practices:
                • Use a reputable password manager (Bitwarden, 1Password, LastPass)
                • Enable two-factor authentication (2FA) everywhere possible
                • Use authenticator apps over SMS when possible
                • Never share passwords via email, chat, or phone
                • Change passwords immediately if breach suspected
                • Don't write passwords on sticky notes
                • Use different passwords for work and personal accounts
                • Consider using hardware keys for critical accounts

                Multi-Factor Authentication (MFA):
                • Something you know (password)
                • Something you have (phone, token)
                • Something you are (biometric)

                Password Manager Benefits:
                • Generate random, unique passwords
                • Securely store all passwords
                • Auto-fill credentials safely
                • Sync across devices
                • Alert you to breaches
                • Share passwords securely when needed

                Common Password Mistakes:
                • Using personal information (birthdate, pet names)
                • Reusing passwords across sites
                • Sharing passwords with others
                • Using simple substitutions (P@ssw0rd)
                • Not updating default passwords
                • Ignoring breach notifications
                """,
                keywords=["password", "authentication", "2FA", "MFA", "login", "credentials", "passphrase",
                          "password manager"],
                severity="critical"
            ),

            # Malware Prevention
            SecurityKnowledge(
                topic=SecurityTopic.MALWARE,
                title="Malware Prevention and Response",
                content="""
                MALWARE PREVENTION STRATEGIES:

                Prevention Best Practices:
                • Keep OS and all software updated with latest patches
                • Use reputable antivirus with real-time protection
                • Enable Windows Defender or equivalent
                • Download software only from official sources
                • Verify digital signatures on downloads
                • Scan USB drives before opening files
                • Disable macros in Office documents from unknown sources
                • Use application sandboxing when possible
                • Regular backups following 3-2-1 rule
                • Keep UAC (User Account Control) enabled

                Types of Malware:
                • Viruses: Self-replicating, attaches to files
                • Worms: Self-spreading through networks
                • Trojans: Disguised as legitimate software
                • Ransomware: Encrypts files for ransom
                • Spyware: Steals information secretly
                • Adware: Displays unwanted advertisements
                • Rootkits: Hides presence from system
                • Keyloggers: Records keystrokes
                • Cryptominers: Uses resources to mine cryptocurrency

                Warning Signs of Infection:
                • Computer running unusually slow
                • Frequent crashes or blue screens
                • Programs starting automatically
                • Browser homepage changed
                • New toolbars or extensions
                • Excessive pop-ups
                • Files encrypted with ransom note
                • Unusual network activity
                • Disabled security software
                • Missing or modified files

                If Infected - Immediate Steps:
                1. Disconnect from all networks (WiFi, Ethernet)
                2. Enter Safe Mode if possible
                3. Run full antivirus scan
                4. Use additional malware removal tools (Malwarebytes)
                5. Check for system restore points
                6. Contact IT security team immediately
                7. Change all passwords from clean device
                8. Monitor financial accounts
                9. Consider complete system reinstall for severe infections
                """,
                keywords=["malware", "virus", "ransomware", "trojan", "antivirus", "infection", "worm", "spyware"],
                severity="critical"
            ),

            # Social Engineering
            SecurityKnowledge(
                topic=SecurityTopic.SOCIAL_ENGINEERING,
                title="Social Engineering Defense Strategies",
                content="""
                DEFENDING AGAINST SOCIAL ENGINEERING:

                Common Social Engineering Tactics:
                • Pretexting: Creating fake scenarios to steal information
                • Baiting: Offering something enticing (USB drives, downloads)
                • Quid pro quo: Offering service for information
                • Tailgating: Following into secure areas
                • Vishing: Voice phishing via phone
                • Smishing: SMS/text message phishing
                • Watering hole: Compromising frequently visited websites
                • Dumpster diving: Searching trash for information
                • Shoulder surfing: Looking over shoulder for passwords

                Red Flags to Recognize:
                • Unsolicited contact asking for information
                • Urgency without verification
                • Requests to bypass normal procedures
                • Appeals to authority without proof
                • Offers that seem too good to be true
                • Requests for passwords or sensitive data
                • Emotional manipulation (fear, greed, sympathy)
                • Name dropping without context
                • Resistance to verification

                Defense Strategies:
                • Always verify identity before sharing information
                • Use callback numbers from official sources
                • Be suspicious of unsolicited contacts
                • Never give passwords over phone/email
                • Question unusual requests, even from "colleagues"
                • Report suspicious behavior immediately
                • Trust but verify - confirm through separate channel
                • Be aware of information you share publicly
                • Secure physical documents and screens
                • Educate family about work-related scams

                Verification Techniques:
                • Call back on known number
                • Check employee directory
                • Verify with manager
                • Ask for employee ID
                • Request email confirmation
                • Check digital signatures
                • Verify through IT security
                """,
                keywords=["social engineering", "pretexting", "vishing", "smishing", "manipulation", "tailgating",
                          "phishing"],
                severity="high"
            ),

            # Network Security
            SecurityKnowledge(
                topic=SecurityTopic.NETWORK_SECURITY,
                title="Network and WiFi Security Guide",
                content="""
                NETWORK SECURITY BEST PRACTICES:

                Home WiFi Security:
                • Change default router admin credentials immediately
                • Use WPA3 encryption (WPA2 minimum)
                • Create strong WiFi password (20+ characters)
                • Change default network name (SSID)
                • Disable WPS (WiFi Protected Setup)
                • Keep router firmware updated monthly
                • Use guest network for visitors and IoT devices
                • Disable remote management unless necessary
                • Turn off SSID broadcast if practical
                • Use MAC address filtering for added security
                • Position router centrally to minimize external signal
                • Regular reboot router (monthly)

                Public WiFi Safety:
                • Avoid accessing sensitive accounts
                • Always use VPN for all connections
                • Verify network name with venue staff
                • Turn off automatic WiFi connection
                • Forget network after use
                • Never accept certificate warnings
                • Disable file sharing
                • Use cellular data for sensitive tasks
                • Keep firewall enabled
                • Use HTTPS websites only

                VPN Best Practices:
                • Use company-approved VPN only
                • Connect before accessing any resources
                • Keep VPN client updated
                • Report connection issues immediately
                • Don't use free/public VPN services
                • Verify VPN is active before working

                Network Hygiene:
                • Regular network scans for unknown devices
                • Monitor bandwidth usage
                • Check for unauthorized access points
                • Secure all network equipment physically
                • Document network configuration
                • Regular security audits
                """,
                keywords=["wifi", "network", "router", "VPN", "encryption", "WPA3", "public wifi", "wireless"],
                severity="high"
            ),

            # Incident Response
            SecurityKnowledge(
                topic=SecurityTopic.INCIDENT_RESPONSE,
                title="Security Incident Response Procedures",
                content="""
                SECURITY INCIDENT RESPONSE GUIDE:

                IMMEDIATE RESPONSE STEPS:
                1. STOP - Don't try to fix it yourself
                2. DISCONNECT - Unplug network cable or disable WiFi
                3. DOCUMENT - Write down:
                   - What happened
                   - When it occurred
                   - What you were doing
                   - Error messages
                   - Unusual behavior observed
                4. REPORT - Contact IT security immediately
                5. PRESERVE - Don't delete anything, take screenshots
                6. WAIT - For IT security instructions

                Types of Incidents Requiring Immediate Reporting:
                • Clicked suspicious link or attachment
                • Entered credentials on suspicious site
                • Lost device with company data
                • Suspicious computer behavior
                • Unauthorized access attempts
                • Data breach or leak discovered
                • Ransomware infection
                • Physical security breach
                • Stolen credentials
                • Suspicious phone calls asking for info

                Information to Provide:
                • Your name and contact information
                • Time and date of incident
                • Affected systems/accounts
                • Description of what happened
                • Actions taken so far
                • Any error messages (exact wording)
                • Screenshots if possible
                • Anyone else who might be affected

                DO NOT:
                • Try to fix it yourself
                • Delete or modify evidence
                • Inform unauthorized people
                • Post about it on social media
                • Continue using affected systems
                • Pay ransoms

                Contact Information:
                IT Security Hotline: [Organization specific]
                Email: security@[organization]
                After hours: [Emergency contact]
                """,
                keywords=["incident", "breach", "response", "report", "emergency", "compromise", "security incident"],
                severity="critical"
            ),

            # Data Protection
            SecurityKnowledge(
                topic=SecurityTopic.DATA_PROTECTION,
                title="Data Protection and Privacy Guide",
                content="""
                DATA PROTECTION BEST PRACTICES:

                Data Classification:
                • Public: Can be freely shared
                • Internal: Within organization only
                • Confidential: Specific authorized individuals
                • Restricted: Highest sensitivity, strict controls

                Handling Sensitive Data:
                • Encrypt files before sharing externally
                • Use approved file sharing platforms only
                • Never use personal email for work data
                • Implement clean desk policy
                • Lock computer when stepping away (Win+L or Cmd+Ctrl+Q)
                • Use privacy screens in public spaces
                • Shred physical documents with sensitive info
                • Secure disposal of electronic media
                • Don't discuss sensitive info in public
                • Be aware of smart speakers/devices

                Encryption Best Practices:
                • Use full disk encryption (BitLocker, FileVault)
                • Encrypt removable media
                • Use encrypted communication channels
                • Encrypt email with sensitive data
                • Password protect sensitive documents
                • Use enterprise encryption tools
                • Store encryption keys securely

                Data Backup Practices:
                • Follow 3-2-1 rule:
                  - 3 copies of important data
                  - 2 different storage media
                  - 1 offsite backup
                • Test restore procedures regularly
                • Encrypt backup drives
                • Store backups securely
                • Automate where possible
                • Document what's backed up
                • Verify backup integrity

                Privacy Considerations:
                • Minimize data collection
                • Only share need-to-know basis
                • Regular data audits
                • Respect retention policies
                • Secure data destruction
                • GDPR/CCPA compliance
                """,
                keywords=["data", "encryption", "backup", "confidential", "sensitive", "GDPR", "privacy",
                          "classification"],
                severity="high"
            ),

            # Mobile Security
            SecurityKnowledge(
                topic=SecurityTopic.MOBILE_SECURITY,
                title="Mobile Device Security Guidelines",
                content="""
                MOBILE DEVICE SECURITY:

                Device Security Settings:
                • Enable screen lock (PIN, password, biometric)
                • Set auto-lock to 1-2 minutes
                • Keep OS and apps updated automatically
                • Download apps only from official stores
                • Review app permissions carefully
                • Enable remote wipe capability
                • Use Find My Device features
                • Encrypt device storage
                • Disable Bluetooth when not needed
                • Turn off WiFi auto-connect
                • Disable Siri/Assistant on lock screen

                BYOD (Bring Your Own Device) Security:
                • Separate work and personal data
                • Use MDM if required by company
                • Install company security apps
                • Follow company mobile policy
                • Report lost/stolen immediately
                • Don't jailbreak/root devices
                • Use company VPN for work
                • Regular security updates

                Mobile Threats:
                • Malicious apps
                • Unsecured WiFi
                • SMiShing (SMS phishing)
                • Bluetooth attacks
                • Physical theft
                • Shoulder surfing
                • Juice jacking (USB charging)
                • SIM swapping

                Safe Mobile Practices:
                • Avoid public WiFi for sensitive tasks
                • Use VPN when on public networks
                • Don't click links in text messages
                • Be cautious with QR codes
                • Use official app stores only
                • Keep personal info private
                • Regular app permission audits
                • Backup device regularly
                • Use mobile antivirus
                • Avoid charging at public USB ports
                """,
                keywords=["mobile", "smartphone", "tablet", "BYOD", "iOS", "Android", "app security", "MDM"],
                severity="medium"
            ),

            # Ransomware Specific
            SecurityKnowledge(
                topic=SecurityTopic.RANSOMWARE,
                title="Ransomware Prevention and Response",
                content="""
                RANSOMWARE PROTECTION GUIDE:

                Prevention Strategies:
                • Regular automated backups (tested restores)
                • Keep all software patched and updated
                • Email filtering and sandboxing
                • Disable macros by default
                • User training on phishing
                • Network segmentation
                • Principle of least privilege
                • Application whitelisting
                • Endpoint detection and response (EDR)

                If Ransomware Strikes:
                1. Immediately disconnect from network
                2. Power off if actively encrypting
                3. Report to IT security immediately
                4. Do NOT pay ransom
                5. Preserve evidence for investigation
                6. Check for decryption tools
                7. Restore from clean backups
                8. Rebuild affected systems
                9. Investigate root cause
                10. Implement lessons learned

                Warning Signs:
                • Files with strange extensions
                • Cannot open documents
                • Ransom notes in folders
                • Slow computer performance
                • Renamed files
                • Wallpaper changed to ransom message

                Recovery Planning:
                • Maintain offline backups
                • Test restore procedures
                • Document critical systems
                • Incident response plan
                • Communication plan
                • Legal/law enforcement contacts
                """,
                keywords=["ransomware", "encryption", "ransom", "backup", "recovery", "bitcoin", "crypto"],
                severity="critical"
            ),

            # Cloud Security
            SecurityKnowledge(
                topic=SecurityTopic.CLOUD_SECURITY,
                title="Cloud Services Security",
                content="""
                CLOUD SECURITY BEST PRACTICES:

                Account Security:
                • Use strong, unique passwords
                • Enable MFA on all cloud accounts
                • Regular access reviews
                • Monitor for unusual activity
                • Use SSO where available
                • Secure API keys and tokens

                Data Protection in Cloud:
                • Understand shared responsibility model
                • Encrypt data at rest and in transit
                • Use cloud provider encryption
                • Control data residency
                • Regular security audits
                • Implement DLP policies

                Safe Cloud Usage:
                • Only use approved cloud services
                • Read terms of service
                • Understand data ownership
                • Configure privacy settings
                • Regular permission reviews
                • Monitor shared links
                • Set expiration on shares
                • Audit access logs

                Common Cloud Risks:
                • Misconfigured storage buckets
                • Excessive permissions
                • Shadow IT
                • Account takeover
                • Data leakage
                • Compliance violations
                • Insider threats
                • API vulnerabilities
                """,
                keywords=["cloud", "SaaS", "AWS", "Azure", "Google Cloud", "OneDrive", "Dropbox", "Office 365"],
                severity="high"
            )
        ]

        # Add all knowledge items to vector database
        batch_size = 10
        for i in range(0, len(knowledge_items), batch_size):
            batch = knowledge_items[i:i + batch_size]

            embeddings = []
            documents = []
            metadatas = []
            ids = []

            for item in batch:
                # Generate embedding
                embedding = self.embedder.encode(item.content).tolist()
                embeddings.append(embedding)

                # Prepare document
                documents.append(item.content)

                # Prepare metadata
                metadatas.append(item.to_dict())

                # Generate unique ID
                doc_id = hashlib.md5(
                    f"{item.topic.value}_{item.title}_{len(item.content)}".encode()
                ).hexdigest()
                ids.append(doc_id)

            # Add batch to collection
            self.collection.add(
                embeddings=embeddings,
                documents=documents,
                metadatas=metadatas,
                ids=ids
            )

            logger.info(f"Added batch {i // batch_size + 1} of knowledge items")

        logger.info(f"Successfully loaded {len(knowledge_items)} knowledge items")

    def search(self,
               query: str,
               k: int = 3,
               filter_topic: Optional[str] = None,
               min_severity: Optional[str] = None) -> List[Dict[str, Any]]:
        """
        Search for relevant security information

        Args:
            query: User's question
            k: Number of results to return
            filter_topic: Optional topic filter
            min_severity: Minimum severity level filter

        Returns:
            List of relevant documents with metadata
        """

        self.stats["queries_processed"] += 1

        # Generate query embedding
        query_embedding = self.embedder.encode(query).tolist()

        # Build filter
        where_filter = {}
        if filter_topic:
            where_filter["topic"] = filter_topic
        if min_severity:
            severity_levels = ["low", "medium", "high", "critical"]
            min_index = severity_levels.index(min_severity)
            valid_severities = severity_levels[min_index:]
            where_filter["severity"] = {"$in": valid_severities}

        # Search with or without filter
        if where_filter:
            results = self.collection.query(
                query_embeddings=[query_embedding],
                n_results=k,
                where=where_filter
            )
        else:
            results = self.collection.query(
                query_embeddings=[query_embedding],
                n_results=k
            )

        # Format results
        formatted_results = []
        if results['documents'] and results['documents'][0]:
            for doc, metadata, distance in zip(
                    results['documents'][0],
                    results['metadatas'][0],
                    results['distances'][0]
            ):
                formatted_results.append({
                    'content': doc,
                    'topic': metadata.get('topic', 'unknown'),
                    'title': metadata.get('title', 'Untitled'),
                    'severity': metadata.get('severity', 'medium'),
                    'keywords': json.loads(metadata.get('keywords', '[]')),  # Deserialize JSON string back to list
                    'relevance_score': 1 - (distance / 2)  # Convert distance to similarity
                })

        return formatted_results

    def add_custom_knowledge(self,
                             content: str,
                             topic: str,
                             title: str,
                             keywords: List[str],
                             severity: str = "medium") -> bool:
        """
        Add custom security knowledge to the database

        Args:
            content: Knowledge content
            topic: Topic category
            title: Title of the knowledge
            keywords: Related keywords
            severity: Severity level

        Returns:
            Success status
        """

        try:
            # Generate embedding
            embedding = self.embedder.encode(content).tolist()

            # Generate unique ID
            doc_id = hashlib.md5(
                f"{topic}_{title}_{len(content)}_{datetime.now().isoformat()}".encode()
            ).hexdigest()

            # Add to collection
            self.collection.add(
                embeddings=[embedding],
                documents=[content],
                metadatas=[{
                    "topic": topic,
                    "title": title,
                    "keywords": json.dumps(keywords),  # Serialize list to JSON string
                    "severity": severity,
                    "last_updated": datetime.now().isoformat(),
                    "custom": True
                }],
                ids=[doc_id]
            )

            self.stats["total_documents"] = self.collection.count()
            logger.info(f"Added custom knowledge: {title}")
            return True

        except Exception as e:
            logger.error(f"Failed to add custom knowledge: {e}")
            return False

    def get_statistics(self) -> Dict[str, Any]:
        """Get knowledge base statistics"""

        self.stats["total_documents"] = self.collection.count()
        self.stats["last_accessed"] = datetime.now().isoformat()

        # Get topic distribution
        all_metadata = self.collection.get()['metadatas']
        topic_counts = {}
        severity_counts = {}

        for metadata in all_metadata:
            topic = metadata.get('topic', 'unknown')
            severity = metadata.get('severity', 'unknown')

            topic_counts[topic] = topic_counts.get(topic, 0) + 1
            severity_counts[severity] = severity_counts.get(severity, 0) + 1

        self.stats["topic_distribution"] = topic_counts
        self.stats["severity_distribution"] = severity_counts

        return self.stats

    def export_knowledge(self, output_file: str = "knowledge_export.json") -> bool:
        """Export all knowledge to JSON file"""

        try:
            all_data = self.collection.get()

            export_data = {
                "exported_at": datetime.now().isoformat(),
                "total_documents": len(all_data['ids']),
                "documents": []
            }

            for doc, metadata, doc_id in zip(
                    all_data['documents'],
                    all_data['metadatas'],
                    all_data['ids']
            ):
                export_data["documents"].append({
                    "id": doc_id,
                    "content": doc,
                    "metadata": metadata
                })

            with open(output_file, 'w') as f:
                json.dump(export_data, f, indent=2)

            logger.info(f"Exported knowledge to {output_file}")
            return True

        except Exception as e:
            logger.error(f"Failed to export knowledge: {e}")
            return False


# ================================================
# RAG-Enhanced LLM Class
# ================================================

class RAGCybersecurityLLM(CybersecurityLLM):
    def __init__(self,
                 repo_id: str = "daskalos-apps/phi4-cybersec-Q4_K_M",
                 filename: str = "phi4-mini-instruct-Q4_K_M.gguf",
                 local_dir: str = "./models",
                 knowledge_dir: str = "./knowledge_db",
                 force_download: bool = False):
        """
        Initialize LLM with RAG capabilities

        Args:
            repo_id: Hugging Face repository ID
            filename: Model filename
            local_dir: Local cache directory
            knowledge_dir: Knowledge base directory
            force_download: Force model re-download
        """

        # Initialize base LLM
        super().__init__(repo_id, filename, local_dir, force_download)

        # Initialize knowledge base
        logger.info("Initializing RAG knowledge base...")
        self.knowledge_base = CybersecurityKnowledgeBase(persist_directory=knowledge_dir)

        # Enhanced system prompt for RAG
        self.rag_prompt_template = """<|system|>
{system}

You have access to a comprehensive cybersecurity knowledge base. Use the provided context to give accurate, detailed answers. If the context doesn't contain relevant information, use your general knowledge but indicate when you're doing so.
<|end|>
<|user|>
Context from knowledge base:
{context}

User Question: {user}
<|end|>
<|assistant|>"""

    def generate_with_rag(self,
                          prompt: str,
                          max_tokens: int = 512,
                          use_rag: bool = True,
                          k_documents: int = 3,
                          min_relevance: float = 0.5) -> Dict[str, Any]:
        """
        Generate response with RAG enhancement

        Args:
            prompt: User's question
            max_tokens: Maximum response length
            use_rag: Whether to use RAG
            k_documents: Number of documents to retrieve
            min_relevance: Minimum relevance threshold

        Returns:
            Response with metadata and sources
        """

        context = None
        sources = []

        if use_rag:
            # Search knowledge base
            logger.info(f"Searching knowledge base for: {prompt[:50]}...")
            relevant_docs = self.knowledge_base.search(prompt, k=k_documents)

            # Filter by relevance
            relevant_docs = [
                doc for doc in relevant_docs
                if doc.get('relevance_score', 0) >= min_relevance
            ]

            if relevant_docs:
                # Build context from relevant documents
                context_parts = []
                for i, doc in enumerate(relevant_docs, 1):
                    context_parts.append(
                        f"[Source {i}: {doc['title']} - Severity: {doc['severity']}]\n"
                        f"{doc['content'][:1000]}..."  # Limit context length
                    )
                    sources.append({
                        "title": doc['title'],
                        "topic": doc['topic'],
                        "severity": doc['severity'],
                        "relevance": doc['relevance_score']
                    })

                context = "\n\n".join(context_parts)
                logger.info(f"Found {len(relevant_docs)} relevant documents")
            else:
                logger.info("No highly relevant documents found")

        # Generate response
        if context and use_rag:
            # Use RAG prompt template
            full_prompt = self.rag_prompt_template.format(
                system=self.system_prompt,
                context=context,
                user=prompt
            )
        else:
            # Use standard prompt template
            full_prompt = self.format_prompt(prompt)

        try:
            response = self.llm(
                full_prompt,
                max_tokens=max_tokens,
                temperature=0.7,
                top_p=0.95,
                top_k=40,
                repeat_penalty=1.1,
                stop=self.stop_tokens,
                echo=False
            )

            text = response['choices'][0]['text'].strip()

            return {
                "response": text,
                "tokens_used": response['usage']['total_tokens'],
                "model": self.model_info['repo_id'],
                "sources": sources,
                "rag_used": use_rag and bool(context)
            }

        except Exception as e:
            logger.error(f"Generation error: {e}")
            return {
                "response": "I apologize, but I encountered an error. Please try rephrasing your question.",
                "error": str(e),
                "sources": [],
                "rag_used": False
            }

    def generate_stream_with_rag(self,
                                 prompt: str,
                                 max_tokens: int = 512,
                                 use_rag: bool = True,
                                 k_documents: int = 3) -> Generator:
        """Stream response with RAG enhancement"""

        # Get context if using RAG
        context = None
        if use_rag:
            relevant_docs = self.knowledge_base.search(prompt, k=k_documents)
            if relevant_docs:
                context_parts = [f"{doc['title']}: {doc['content'][:500]}" for doc in relevant_docs]
                context = "\n\n".join(context_parts)

        # Generate prompt
        if context:
            full_prompt = self.rag_prompt_template.format(
                system=self.system_prompt,
                context=context,
                user=prompt
            )
        else:
            full_prompt = self.format_prompt(prompt)

        # Stream response
        stream = self.llm(
            full_prompt,
            max_tokens=max_tokens,
            temperature=0.7,
            top_p=0.95,
            top_k=40,
            repeat_penalty=1.1,
            stop=self.stop_tokens,
            echo=False,
            stream=True
        )

        for output in stream:
            token = output['choices'][0].get('text', '')
            if token:
                yield token

    def add_knowledge(self, content: str, topic: str, title: str, keywords: List[str]) -> bool:
        """Add new knowledge to the RAG system"""
        return self.knowledge_base.add_custom_knowledge(
            content=content,
            topic=topic,
            title=title,
            keywords=keywords
        )

    def get_knowledge_stats(self) -> Dict[str, Any]:
        """Get knowledge base statistics"""
        return self.knowledge_base.get_statistics()