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backend/core/models.py

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+from django.db import models
+from django.contrib.postgres.search import SearchVectorField
+from django.contrib.postgres.indexes import GinIndex
+from django.utils import timezone
+import uuid
+
+
+def legal_document_upload_path(instance, filename):
+    base = "legal_uploads"
+    code = (instance.code or uuid.uuid4().hex).replace("/", "_")
+    return f"{base}/{code}/{filename}"
+
+
+def legal_document_image_upload_path(instance, filename):
+    base = "legal_images"
+    code = (instance.document.code if instance.document else uuid.uuid4().hex).replace("/", "_")
+    timestamp = timezone.now().strftime("%Y%m%d%H%M%S")
+    return f"{base}/{code}/{timestamp}_{filename}"
+
+class Procedure(models.Model):
+    title = models.CharField(max_length=500)
+    domain = models.CharField(max_length=100, db_index=True)  # ANTT/Cư trú/PCCC/GT
+    level = models.CharField(max_length=50, blank=True)  # Tỉnh/Huyện/Xã
+    conditions = models.TextField(blank=True)
+    dossier = models.TextField(blank=True)
+    fee = models.CharField(max_length=200, blank=True)
+    duration = models.CharField(max_length=200, blank=True)
+    authority = models.CharField(max_length=300, blank=True)
+    source_url = models.URLField(max_length=1000, blank=True)
+    updated_at = models.DateTimeField(auto_now=True)
+    tsv_body = SearchVectorField(null=True, editable=False)
+    embedding = models.BinaryField(null=True, blank=True, editable=False)
+    
+    class Meta:
+        indexes = [
+            GinIndex(fields=["tsv_body"], name="procedure_tsv_idx"),
+        ]
+    
+    def search_vector(self) -> str:
+        """Create searchable text vector for this procedure."""
+        fields = [self.title, self.domain, self.level, self.conditions, self.dossier]
+        return " ".join(str(f) for f in fields if f)
+
+class Fine(models.Model):
+    code = models.CharField(max_length=50, unique=True)
+    name = models.CharField(max_length=500)
+    article = models.CharField(max_length=100, blank=True)
+    decree = models.CharField(max_length=100, blank=True)
+    min_fine = models.DecimalField(max_digits=12, decimal_places=0, null=True, blank=True)
+    max_fine = models.DecimalField(max_digits=12, decimal_places=0, null=True, blank=True)
+    license_points = models.CharField(max_length=50, blank=True)
+    remedial = models.TextField(blank=True)
+    source_url = models.URLField(max_length=1000, blank=True)
+    tsv_body = SearchVectorField(null=True, editable=False)
+    embedding = models.BinaryField(null=True, blank=True, editable=False)
+    
+    class Meta:
+        indexes = [
+            GinIndex(fields=["tsv_body"], name="fine_tsv_idx"),
+        ]
+    
+    def search_vector(self) -> str:
+        """Create searchable text vector for this fine."""
+        fields = [self.name, self.code, self.article, self.decree, self.remedial]
+        return " ".join(str(f) for f in fields if f)
+
+class Office(models.Model):
+    unit_name = models.CharField(max_length=300)
+    address = models.CharField(max_length=500, blank=True)
+    district = models.CharField(max_length=100, blank=True, db_index=True)
+    working_hours = models.CharField(max_length=200, blank=True)
+    phone = models.CharField(max_length=100, blank=True)
+    email = models.EmailField(blank=True)
+    latitude = models.FloatField(null=True, blank=True)
+    longitude = models.FloatField(null=True, blank=True)
+    service_scope = models.CharField(max_length=300, blank=True)
+    tsv_body = SearchVectorField(null=True, editable=False)
+    embedding = models.BinaryField(null=True, blank=True, editable=False)
+    
+    class Meta:
+        indexes = [
+            GinIndex(fields=["tsv_body"], name="office_tsv_idx"),
+        ]
+    
+    def search_vector(self) -> str:
+        """Create searchable text vector for this office."""
+        fields = [self.unit_name, self.address, self.district, self.service_scope]
+        return " ".join(str(f) for f in fields if f)
+
+class Advisory(models.Model):
+    title = models.CharField(max_length=500)
+    summary = models.TextField()
+    source_url = models.URLField(max_length=1000, blank=True)
+    published_at = models.DateField(null=True, blank=True)
+    tsv_body = SearchVectorField(null=True, editable=False)
+    embedding = models.BinaryField(null=True, blank=True, editable=False)
+    
+    class Meta:
+        indexes = [
+            GinIndex(fields=["tsv_body"], name="advisory_tsv_idx"),
+        ]
+    
+    def search_vector(self) -> str:
+        """Create searchable text vector for this advisory."""
+        fields = [self.title, self.summary]
+        return " ".join(str(f) for f in fields if f)
+
+
+class LegalDocument(models.Model):
+    """Metadata + raw text for authoritative legal documents."""
+
+    DOCUMENT_TYPES = [
+        ("decision", "Decision"),
+        ("circular", "Circular"),
+        ("guideline", "Guideline"),
+        ("plan", "Plan"),
+        ("other", "Other"),
+    ]
+
+    code = models.CharField(max_length=100, unique=True)
+    title = models.CharField(max_length=500)
+    doc_type = models.CharField(max_length=30, choices=DOCUMENT_TYPES, default="other")
+    summary = models.TextField(blank=True)
+    issued_by = models.CharField(max_length=200, blank=True)
+    issued_at = models.DateField(null=True, blank=True)
+    source_file = models.CharField(max_length=500, blank=True)
+    uploaded_file = models.FileField(upload_to=legal_document_upload_path, null=True, blank=True)
+    original_filename = models.CharField(max_length=255, blank=True)
+    mime_type = models.CharField(max_length=120, blank=True)
+    file_size = models.BigIntegerField(null=True, blank=True)
+    file_checksum = models.CharField(max_length=128, blank=True)
+    content_checksum = models.CharField(max_length=128, blank=True)
+    source_url = models.URLField(max_length=1000, blank=True)
+    page_count = models.IntegerField(null=True, blank=True)
+    raw_text = models.TextField()
+    raw_text_ocr = models.TextField(blank=True)
+    metadata = models.JSONField(default=dict, blank=True)
+    created_at = models.DateTimeField(auto_now_add=True)
+    updated_at = models.DateTimeField(auto_now=True)
+    tsv_body = SearchVectorField(null=True, editable=False)
+
+    class Meta:
+        indexes = [
+            GinIndex(fields=["tsv_body"], name="legal_document_tsv_idx"),
+            models.Index(fields=["doc_type"]),
+            models.Index(fields=["issued_at"]),
+        ]
+        ordering = ["title"]
+
+    def search_vector(self) -> str:
+        """Return concatenated searchable text."""
+        fields = [
+            self.title,
+            self.code,
+            self.summary,
+            self.issued_by,
+            self.raw_text,
+        ]
+        return " ".join(str(f) for f in fields if f)
+
+
+class LegalSection(models.Model):
+    """Structured snippet (chapter/section/article) for each legal document."""
+
+    LEVEL_CHOICES = [
+        ("chapter", "Chapter"),
+        ("section", "Section"),
+        ("article", "Article"),
+        ("clause", "Clause"),
+        ("note", "Note"),
+        ("other", "Other"),
+    ]
+
+    document = models.ForeignKey(
+        LegalDocument,
+        on_delete=models.CASCADE,
+        related_name="sections",
+    )
+    section_code = models.CharField(max_length=120)
+    section_title = models.CharField(max_length=500, blank=True)
+    level = models.CharField(max_length=30, choices=LEVEL_CHOICES, default="other")
+    order = models.PositiveIntegerField(default=0, db_index=True)
+    page_start = models.IntegerField(null=True, blank=True)
+    page_end = models.IntegerField(null=True, blank=True)
+    content = models.TextField()
+    excerpt = models.TextField(blank=True)
+    metadata = models.JSONField(default=dict, blank=True)
+    is_ocr = models.BooleanField(default=False)
+    tsv_body = SearchVectorField(null=True, editable=False)
+    embedding = models.BinaryField(null=True, blank=True, editable=False)
+
+    class Meta:
+        indexes = [
+            GinIndex(fields=["tsv_body"], name="legal_section_tsv_idx"),
+            models.Index(fields=["document", "order"]),
+            models.Index(fields=["level"]),
+        ]
+        ordering = ["document", "order"]
+        unique_together = ("document", "section_code", "order")
+
+    def search_vector(self) -> str:
+        fields = [
+            self.section_title,
+            self.section_code,
+            self.content,
+            self.excerpt,
+        ]
+        return " ".join(str(f) for f in fields if f)
+
+
+class Synonym(models.Model):
+    keyword = models.CharField(max_length=120, unique=True)
+    alias = models.CharField(max_length=120)
+
+
+class LegalDocumentImage(models.Model):
+    """Metadata for images extracted from uploaded legal documents."""
+
+    document = models.ForeignKey(
+        LegalDocument,
+        on_delete=models.CASCADE,
+        related_name="images",
+    )
+    image = models.ImageField(upload_to=legal_document_image_upload_path)
+    page_number = models.IntegerField(null=True, blank=True)
+    description = models.CharField(max_length=255, blank=True)
+    width = models.IntegerField(null=True, blank=True)
+    height = models.IntegerField(null=True, blank=True)
+    checksum = models.CharField(max_length=128, blank=True)
+    created_at = models.DateTimeField(auto_now_add=True)
+
+    class Meta:
+        indexes = [
+            models.Index(fields=["document", "page_number"]),
+            models.Index(fields=["checksum"]),
+        ]
+
+    def __str__(self) -> str:
+        return f"Image {self.id} of {self.document.code}"
+
+
+class IngestionJob(models.Model):
+    """Background ingestion task information."""
+
+    STATUS_PENDING = "pending"
+    STATUS_RUNNING = "running"
+    STATUS_COMPLETED = "completed"
+    STATUS_FAILED = "failed"
+
+    STATUS_CHOICES = [
+        (STATUS_PENDING, "Pending"),
+        (STATUS_RUNNING, "Running"),
+        (STATUS_COMPLETED, "Completed"),
+        (STATUS_FAILED, "Failed"),
+    ]
+
+    id = models.UUIDField(primary_key=True, default=uuid.uuid4, editable=False)
+    code = models.CharField(max_length=128)
+    filename = models.CharField(max_length=255)
+    document = models.ForeignKey(
+        LegalDocument,
+        related_name="ingestion_jobs",
+        on_delete=models.SET_NULL,
+        null=True,
+        blank=True,
+    )
+    metadata = models.JSONField(default=dict, blank=True)
+    stats = models.JSONField(default=dict, blank=True)
+    status = models.CharField(max_length=20, choices=STATUS_CHOICES, default=STATUS_PENDING)
+    error_message = models.TextField(blank=True)
+    storage_path = models.CharField(max_length=512, blank=True)
+    progress = models.PositiveIntegerField(default=0)
+    created_at = models.DateTimeField(auto_now_add=True)
+    updated_at = models.DateTimeField(auto_now=True)
+    started_at = models.DateTimeField(null=True, blank=True)
+    finished_at = models.DateTimeField(null=True, blank=True)
+
+    class Meta:
+        ordering = ("-created_at",)
+
+    def __str__(self) -> str:  # pragma: no cover - trivial
+        return f"IngestionJob({self.code}, {self.status})"
+
+class AuditLog(models.Model):
+    created_at = models.DateTimeField(auto_now_add=True)
+    ip = models.GenericIPAddressField(null=True, blank=True)
+    user_agent = models.CharField(max_length=300, blank=True)
+    path = models.CharField(max_length=300)
+    query = models.CharField(max_length=500, blank=True)
+    status = models.IntegerField(default=200)
+    intent = models.CharField(max_length=50, blank=True)
+    confidence = models.FloatField(null=True, blank=True)
+    latency_ms = models.FloatField(null=True, blank=True)
+
+
+class MLMetrics(models.Model):
+    date = models.DateField(unique=True)
+    total_requests = models.IntegerField(default=0)
+    intent_accuracy = models.FloatField(null=True, blank=True)
+    average_latency_ms = models.FloatField(null=True, blank=True)
+    error_rate = models.FloatField(null=True, blank=True)
+    intent_breakdown = models.JSONField(default=dict, blank=True)
+    generated_at = models.DateTimeField(auto_now_add=True)
+    
+    class Meta:
+        ordering = ["-date"]
+        verbose_name = "ML Metrics"
+        verbose_name_plural = "ML Metrics"
+
+
+class ConversationSession(models.Model):
+    """Model to store conversation sessions for context management."""
+    session_id = models.UUIDField(default=uuid.uuid4, unique=True, editable=False)
+    user_id = models.CharField(max_length=100, null=True, blank=True, db_index=True)
+    created_at = models.DateTimeField(auto_now_add=True)
+    updated_at = models.DateTimeField(auto_now=True)
+    metadata = models.JSONField(default=dict, blank=True)
+    
+    class Meta:
+        ordering = ["-updated_at"]
+        verbose_name = "Conversation Session"
+        verbose_name_plural = "Conversation Sessions"
+        indexes = [
+            models.Index(fields=["session_id"]),
+            models.Index(fields=["user_id", "-updated_at"]),
+        ]
+    
+    def __str__(self):
+        return f"Session {self.session_id}"
+
+
+class ConversationMessage(models.Model):
+    """Model to store individual messages in a conversation session."""
+    ROLE_CHOICES = [
+        ("user", "User"),
+        ("bot", "Bot"),
+    ]
+    
+    session = models.ForeignKey(
+        ConversationSession,
+        on_delete=models.CASCADE,
+        related_name="messages"
+    )
+    role = models.CharField(max_length=10, choices=ROLE_CHOICES)
+    content = models.TextField()
+    intent = models.CharField(max_length=50, blank=True, null=True)
+    entities = models.JSONField(default=dict, blank=True)
+    timestamp = models.DateTimeField(auto_now_add=True)
+    metadata = models.JSONField(default=dict, blank=True)
+    
+    class Meta:
+        ordering = ["timestamp"]
+        verbose_name = "Conversation Message"
+        verbose_name_plural = "Conversation Messages"
+        indexes = [
+            models.Index(fields=["session", "timestamp"]),
+            models.Index(fields=["session", "role", "timestamp"]),
+        ]
+    
+    def __str__(self):
+        return f"{self.role}: {self.content[:50]}..."
+