config.py

from __future__ import annotations

import os
from dataclasses import dataclass
from pathlib import Path


BASE_DIR = Path(__file__).resolve().parent
DATA_DIR = BASE_DIR / "data"
LOCAL_LOG_DIR = BASE_DIR / "logs"


@dataclass(frozen=True)
class Settings:
    app_name: str = os.getenv("APP_NAME", "Trading Game Study AI")
    app_version: str = os.getenv("APP_VERSION", "2.0.0")
    port: int = int(os.getenv("PORT", "7860"))

    embedding_model: str = os.getenv(
        "EMBEDDING_MODEL",
        "sentence-transformers/all-MiniLM-L6-v2",
    )
    cross_encoder_model: str = os.getenv(
        "CROSS_ENCODER_MODEL",
        "cross-encoder/ms-marco-MiniLM-L-6-v2",
    )
    generator_model: str = os.getenv(
        "GENERATOR_MODEL",
        "google/flan-t5-small",
    )
    generator_task: str = os.getenv(
        "GENERATOR_TASK",
        "text2text-generation",
    )
    generator_max_new_tokens: int = int(os.getenv("GENERATOR_MAX_NEW_TOKENS", "220"))
    generator_temperature: float = float(os.getenv("GENERATOR_TEMPERATURE", "0.6"))
    generator_top_p: float = float(os.getenv("GENERATOR_TOP_P", "0.9"))
    generator_do_sample: bool = os.getenv("GENERATOR_DO_SAMPLE", "1") == "1"

    local_chunks_path: str = os.getenv(
        "LOCAL_CHUNKS_PATH",
        str(DATA_DIR / "gmat_hf_chunks.jsonl"),
    )
    question_seed_path: str = os.getenv(
        "QUESTION_SEED_PATH",
        str(DATA_DIR / "gmat_question_seed.jsonl"),
    )
    topic_index_path: str = os.getenv(
        "TOPIC_INDEX_PATH",
        str(DATA_DIR / "gmat_topic_index.json"),
    )
    dataset_repo_id: str = os.getenv("DATASET_REPO_ID", "j-js/gmat-quant-corpus")
    dataset_split: str = os.getenv("DATASET_SPLIT", "train")
    retrieval_k: int = int(os.getenv("RETRIEVAL_K", "8"))
    rerank_k: int = int(os.getenv("RERANK_K", "4"))
    max_chunks_to_show: int = int(os.getenv("MAX_CHUNKS_TO_SHOW", "3"))
    max_reply_chars: int = int(os.getenv("MAX_REPLY_CHARS", "1600"))
    enable_remote_dataset_fallback: bool = os.getenv("ENABLE_REMOTE_DATASET_FALLBACK", "1") == "1"

    local_log_dir: str = os.getenv("LOCAL_LOG_DIR", str(LOCAL_LOG_DIR))
    ingest_api_key: str = os.getenv("INGEST_API_KEY", "")
    research_api_key: str = os.getenv("RESEARCH_API_KEY", "")
    hf_token: str = os.getenv("HF_TOKEN", "")
    log_dataset_repo_id: str = os.getenv("LOG_DATASET_REPO_ID", "")
    log_dataset_private: bool = os.getenv("LOG_DATASET_PRIVATE", "1") == "1"
    push_logs_to_hub: bool = os.getenv("PUSH_LOGS_TO_HUB", "0") == "1"


settings = Settings()