from pydantic import BaseModel, Field
from typing import Dict, List, Optional, Any
from datetime import datetime
from enum import Enum
# =============================================================================
# Enums
# =============================================================================
class DocumentType(Enum):
"""Document type"""
REFERENCE = "reference"
GUIDE = "guide"
API = "api"
EXAMPLE = "example"
OVERVIEW = "overview"
CONFIG = "configuration"
TROUBLESHOOTING = "troubleshooting"
CHANGELOG = "changelog"
class ComplexityLevel(Enum):
"""Complexity level"""
BEGINNER = "beginner"
INTERMEDIATE = "intermediate"
ADVANCED = "advanced"
# =============================================================================
# Data Models
# =============================================================================
class DocumentMetadata(BaseModel):
"""Enhanced metadata extracted from a document"""
# Basic extracted metadata
title: str
headings: List[str]
code_blocks: List[Dict[str, str]]
frontmatter: Dict[str, Any]
primary_language: Optional[str] = None
# LLM-enhanced metadata
doc_type: Optional[DocumentType] = DocumentType.GUIDE
key_concepts: List[str] = Field(default_factory=list)
learning_objectives: List[str] = Field(default_factory=list)
semantic_summary: Optional[str] = None
class DocumentNode(BaseModel):
"""Represents a single documentation file"""
id: str
path: str # relative path from repo root
filename: str
content: str
metadata: DocumentMetadata
parent_path: Optional[str] = None
children_paths: List[str] = Field(default_factory=list)
# Enhanced relationships
related_documents: List[str] = Field(default_factory=list)
prerequisite_documents: List[str] = Field(default_factory=list)
follow_up_documents: List[str] = Field(default_factory=list)
class DocumentTree(BaseModel):
"""Complete documentation tree structure"""
repo_url: str
repo_name: str
root_path: str
nodes: Dict[str, DocumentNode] = Field(..., description="Path to node mapping")
tree_structure: Dict[str, List[str]] = Field(..., description="Folder to list of files/folders mapping")
cross_references: Dict[str, List[str]] = Field(..., description="File to list of referenced files mapping")
last_updated: datetime = Field(default_factory=datetime.now)
# Enhanced tree-level metadata
document_categories: Dict[str, List[str]] = Field(default_factory=dict) # Changed from DocumentType keys
complexity_distribution: Dict[str, int] = Field(default_factory=dict) # Changed from ComplexityLevel keys
learning_paths: List[List[str]] = Field(default_factory=list)
class AssessmentPoint(BaseModel):
"""Simple assessment point within a learning module"""
assessment_id: str
title: str
concepts_to_assess: List[str]
class LearningModule(BaseModel):
"""A group of related documents forming a learning unit"""
module_id: str
title: str
theme: str # Core concept/technology focus
description: str
documents: List[str] # Ordered list of document paths
learning_objectives: List[str]
assessment: AssessmentPoint
class GroupedLearningPath(BaseModel):
"""Learning path with organized modules"""
pathway_id: str
title: str
description: str
target_complexity: ComplexityLevel
modules: List[LearningModule]
welcome_message: str
class ModuleContent(BaseModel):
"""Generated content for a single module - all 5 components"""
module_id: str
title: str = Field(..., description="The title of the learning module.")
description: str = Field(..., description="A detailed description of the module's content and goals.")
learning_objectives: List[str] = Field(default_factory=list, description="List of learning objectives for the module.")
introduction: str # Module introduction content (markdown)
main_content: str # Synthesized main content from source documents (markdown)
conclusion: str # Module conclusion content (markdown)
assessment: str # Assessment questions with answers (markdown)
summary: str # Module summary/wrap-up (markdown)
class GeneratedCourse(BaseModel):
"""Complete generated course"""
course_id: str
title: str
description: str
welcome_message: str # Course introduction
modules: List[ModuleContent]
course_conclusion: str # Final wrap-up
