config.py

from dotenv import load_dotenv
load_dotenv()

import os
import logging
from pathlib import Path
from typing import Dict, List, Optional
from pydantic import BaseModel, Field

# Logging configuration
logging.basicConfig(
    level=logging.INFO,
    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
    handlers=[
        logging.FileHandler("dissistant.log"),
        logging.StreamHandler()
    ]
)

# Base directory
BASE_DIR = Path(__file__).resolve().parent

class Settings(BaseModel):
    """Application settings"""
    # Application settings
    app_name: str = "Graduate Center Dissertation Compliance Assistant"
    description: str = "A tool to check dissertations and theses for compliance with Graduate Center formatting and citation rules."
    version: str = "0.1.0"
    debug: bool = os.getenv("DEBUG", "False").lower() == "true"  # Default to False if not set

    # Paths
    rules_dir: Path = BASE_DIR / "rules"
    formatting_rules_path: Path = rules_dir / "formatting_rules.md"
    citation_rules_path: Path = rules_dir / "citation_rules.md"
    metadata_rules_path: Path = rules_dir / "metadata_rules.md"
    
    # LLM settings
    llm_provider: str = os.getenv("LLM_PROVIDER", "openrouter").lower()  # 'local', 'openai', or 'openrouter'
    llm_model_name: str = os.getenv("LLM_MODEL_NAME", "google/gemini-2.5-pro")
    llm_base_url: str = os.getenv("LLM_API_BASE", "https://openrouter.ai/api/v1")
    llm_api_key: str = os.getenv("LLM_API_KEY", "lm-studio")  # Default for local LM Studio
    
    # OpenAI specific settings
    openai_api_key: Optional[str] = os.getenv("OPENAI_API_KEY")
    openai_model: str = os.getenv("OPENAI_MODEL", "gpt-4")

    # OpenRouter specific settings
    openrouter_api_key: Optional[str] = os.getenv("OPENROUTER_API_KEY")
    
    # Document processing settings
    max_file_size_mb: int = 50  # Maximum file size in MB
    supported_file_types: List[str] = ["pdf", "docx"]
    
    # Citation styles
    citation_styles: List[str] = ["APA", "MLA", "Chicago", "Custom"]
    default_citation_style: str = "APA"
    
    # Department-specific settings
    departments: List[str] = [
        "General",
        "English",
        "History",
        "Psychology",
        "Computer Science",
        "Other"
    ]

    # LLM prompt templates
    formatting_analysis_template: str = """
    You are an expert in academic document formatting. Analyze the following document excerpt for compliance with the institutional formatting rules.
    
    FORMATTING RULES:
    {formatting_rules}
    
    DOCUMENT METADATA:
    {document_metadata}
    
    DOCUMENT EXCERPT:
    {document_excerpt}
    
    Identify any formatting issues in the document. For each issue, provide:
    1. A description of the issue
    2. The location in the document
    3. The specific rule that is violated
    4. A suggestion for how to fix the issue
    5. The severity of the issue (critical, warning, or info)
    
    Format your response as a JSON array of issues, with each issue having the following fields:
    - "message": A clear description of the issue
    - "location": Where in the document the issue occurs
    - "rule": The specific rule that is violated
    - "suggestion": How to fix the issue
    - "severity": The severity level (critical, warning, or info)
    
    If no issues are found, return an empty array.
    """
    
    citation_analysis_template: str = """
    You are an expert in academic citation styles. Analyze the following document excerpt for compliance with the specified citation style.
    
    CITATION STYLE: {citation_style}
    
    CITATION STYLE GUIDELINES:
    {citation_guidelines}
    
    DOCUMENT EXCERPT:
    {document_excerpt}
    
    Identify any citation issues in the document. For each issue, provide:
    1. A description of the issue
    2. The problematic citation
    3. The page or location where it appears
    4. A suggestion for how to fix the issue
    5. The severity of the issue (critical, warning, or info)
    
    Format your response as a JSON array of issues, with each issue having the following fields:
    - "message": A clear description of the issue
    - "citation": The problematic citation
    - "page": The page or location where it appears
    - "suggestion": How to fix the issue
    - "severity": The severity level (critical, warning, or info)
    
    If no issues are found, return an empty array.
    """
    
    metadata_analysis_template: str = """
    You are an expert in academic document structure. Analyze the following document front matter for compliance with the institutional metadata requirements.
    
    METADATA REQUIREMENTS:
    {metadata_requirements}
    
    DOCUMENT FRONT MATTER:
    {front_matter}
    
    Identify any metadata or front matter issues in the document. For each issue, provide:
    1. A description of the issue
    2. The specific element that is problematic
    3. A suggestion for how to fix the issue
    4. The severity of the issue (critical, warning, or info)
    
    Format your response as a JSON array of issues, with each issue having the following fields:
    - "message": A clear description of the issue
    - "element": The specific element that is problematic
    - "suggestion": How to fix the issue
    - "severity": The severity level (critical, warning, or info)
    
    If no issues are found, return an empty array.
    """
    
    overall_analysis_template: str = """
    You are an expert in academic document formatting and citation. Review the following analysis results and provide an overall assessment of the document's compliance with institutional requirements.
    
    FORMATTING ISSUES:
    {formatting_issues}
    
    CITATION ISSUES:
    {citation_issues}
    
    METADATA ISSUES:
    {metadata_issues}
    
    Provide:
    1. An overall assessment of the document's compliance
    2. A list of key recommendations for improving the document
    
    Format your response as a JSON object with the following fields:
    - "overall_assessment": A paragraph summarizing the document's compliance status
    - "recommendations": An array of specific recommendations for improving the document
    
    Be constructive and helpful in your assessment and recommendations.
    """

# Instantiate settings
settings = Settings()

if __name__ == "__main__":
    # Print out the settings for verification if run directly
    print("Application Settings:")
    for field_name, value in settings.model_dump().items():
        if not isinstance(value, str) or len(value) < 100:  # Skip printing long strings like templates
            print(f"  {field_name}: {value}")