# Dick Show Index - Configuration Template
# Copy to config.py and customize

import os

# ============================================================================
# Base Paths
# ============================================================================
BASE_DIR = os.path.dirname(os.path.abspath(__file__))

# Data directories
AUDIO_DIR = os.path.join(BASE_DIR, "audio")
TRANSCRIPT_DIR = os.path.join(BASE_DIR, "transcripts")
DATA_DIR = os.path.join(BASE_DIR, "data")
DB_PATH = os.path.join(DATA_DIR, "index.db")
EPISODES_JSONL = os.path.join(DATA_DIR, "episodes.jsonl")

# RSS Feed
FEED_URL = "https://thedickshow.com/feed/podcast/"

# ============================================================================
# Whisper Settings
# ============================================================================
# Model: tiny, base, small, medium, large-v3
# smaller = faster, less accurate
WHISPER_MODEL = os.environ.get("DS_MODEL", "small")

# Device: cpu, cuda
DEVICE = os.environ.get("DS_DEVICE", "cpu")

# Compute type: int8, float16, float32
# int8 = fastest, lowest memory (CPU)
# float16 = GPU with tensor cores
COMPUTE_TYPE = os.environ.get("DS_COMPUTE", "int8")

# Language
LANGUAGE = "en"

# VAD filter removes silence/music - big speed win
VAD_FILTER = True

# Beam size (1 = greedy, 5 = better accuracy, slower)
BEAM_SIZE = 1

# Word timestamps (slower, more detailed)
WORD_TIMESTAMPS = False

# Condition on previous text (can propagate errors on long audio)
CONDITION_ON_PREVIOUS_TEXT = False

# ============================================================================
# Audio Processing
# ============================================================================
TARGET_RATE = 16000  # Whisper expects 16kHz

# HTTP settings
DOWNLOAD_TIMEOUT = (15, 120)  # (connect, read) seconds
CHUNK_SIZE = 1 << 20  # 1 MiB
MAX_FEED_RETRIES = 3

# Disk policy: delete MP3 after transcription (saves ~75GB for full backlog)
KEEP_AUDIO = os.environ.get("DS_KEEP_AUDIO", "0") == "1"

# ============================================================================
# Analysis (opencode/LLM)
# ============================================================================
# Path to opencode binary
OPENCODE = os.environ.get("OPENCODE_BIN", os.path.expanduser(r"~\.opencode\bin\opencode.exe"))

# Model for analysis (see: opencode models)
OPENCODE_MODEL = os.environ.get("OPENCODE_ANALYZE_MODEL", "opencode/nemotron-3-ultra-free")

# Timeout for analysis (seconds)
OPENCODE_TIMEOUT = int(os.environ.get("DS_ANALYZE_TIMEOUT", "600"))

# Pause between analysis calls (seconds) - be nice to the provider
ANALYSIS_PAUSE = int(os.environ.get("DS_ANALYZE_PAUSE", "45"))

# ============================================================================
# Memory / Rate Limit Guards
# ============================================================================
# Minimum free RAM before pausing transcription (bytes)
MIN_FREE_RAM = int(os.environ.get("DS_MIN_FREE_RAM", str(1024 * 1024 * 1024)))  # 1 GB

# Cooldown after rate limit hit (seconds)
RATE_COOLDOWN_SECONDS = int(os.environ.get("DS_RATE_COOLDOWN", "900"))  # 15 min

# ============================================================================
# HTTP / Feed
# ============================================================================
DOWNLOAD_TIMEOUT = (15, 120)  # (connect, read)
CHUNK_SIZE = 1 << 20  # 1 MiB
MAX_FEED_RETRIES = 3

# Ensure directories exist
os.makedirs(AUDIO_DIR, exist_ok=True)
os.makedirs(TRANSCRIPT_DIR, exist_ok=True)
os.makedirs(os.path.join(os.path.dirname(__file__), "data"), exist_ok=True)

# ============================================================================
# Analysis Timeout (seconds)
# ============================================================================
ANALYSIS_TIMEOUT = int(os.environ.get("DS_ANALYZE_TIMEOUT", "600"))

# Analysis pause between calls
ANALYSIS_PAUSE = int(os.environ.get("DS_ANALYZE_PAUSE", "45"))

# Minimum free RAM (bytes)
MIN_FREE_RAM = int(os.environ.get("DS_MIN_FREE_RAM", str(1024 * 1024 * 1024)))

# Rate cooldown seconds
RATE_COOLDOWN_SECONDS = int(os.environ.get("DS_RATE_COOLDOWN", "900"))

# ============================================================================
# Directory Setup (auto-create)
# ============================================================================
for d in [AUDIO_DIR, TRANSCRIPT_DIR, os.path.join(os.path.dirname(__file__), "data")]:
    os.makedirs(d, exist_ok=True)