import os
from pathlib import Path
from dotenv import load_dotenv

ROOT = Path(__file__).resolve().parents[1]
load_dotenv(ROOT / ".env", override=False)

for _flag in ("LANGSMITH_TRACING", "LANGCHAIN_TRACING_V2", "LANGCHAIN_TRACING"):
    os.environ[_flag] = "false"
GEMINI_MODEL = os.getenv("GEMINI_MODEL", "gemini-3.5-flash-lite").strip() or "gemini-3.5-flash-lite"
GEMINI_TIMEOUT = float(os.getenv("LEXQUERY_GEMINI_TIMEOUT", "120"))
OCR_MAX_TOKENS = 32768
MAX_PDF_BYTES = 40 * 1024**2
MAX_PDF_PAGES = 100
FULL_CONTEXT_CHAR_LIMIT = 160000
SARVAM_REPO = "mradermacher/sarvam-translate-GGUF"
SARVAM_FILE = "sarvam-translate.Q4_K_M.gguf"
EMBEDDING_MODEL = "sentence-transformers/all-MiniLM-L6-v2"
THREADS = int(os.getenv("LEXQUERY_THREADS", str(min(8, max(1, (os.cpu_count() or 4) // 2)))))
CONTEXT = 8192
LANGUAGES = ["English", "Assamese", "Bengali", "Bodo", "Dogri", "Gujarati", "Hindi",
             "Kannada", "Kashmiri", "Konkani", "Maithili", "Malayalam", "Manipuri",
             "Marathi", "Nepali", "Odia", "Punjabi", "Sanskrit", "Santali", "Sindhi",
             "Tamil", "Telugu", "Urdu"]
FIELD_NAMES = ["case_number", "court", "parties", "judges", "order_date", "outcome"]