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4ae4ae8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 | """Configuration for REFRAME app."""
import os
# --- Backend Selection ---
# Auto: Ollama locally, llama-cpp-python on HF Spaces (no Ollama daemon there).
# Override with REFRAME_BACKEND=ollama|llamacpp.
_ON_SPACE = bool(os.environ.get("SPACE_ID"))
BACKEND = os.environ.get("REFRAME_BACKEND", "llamacpp" if _ON_SPACE else "ollama")
# Optional fully-offline local run (no network) — uses only the HF cache.
# Set REFRAME_OFFLINE=1 locally. Never applied on a Space (it must download once).
if os.environ.get("REFRAME_OFFLINE") and not _ON_SPACE:
os.environ.setdefault("HF_HUB_OFFLINE", "1")
os.environ.setdefault("TRANSFORMERS_OFFLINE", "1")
# --- Ollama Config (local) ---
OLLAMA_MODEL = os.environ.get("OLLAMA_MODEL", "gemma4_mentalhealthbuddy_v1")
OLLAMA_BASE_URL = os.environ.get("OLLAMA_BASE_URL", "http://localhost:11434")
# Keep the chat model resident between turns (-1 = never unload). Avoids slow,
# failure-prone cold reloads when RAM is tight (STT + LLM share system memory).
OLLAMA_KEEP_ALIVE = os.environ.get("OLLAMA_KEEP_ALIVE", -1)
# --- llama-cpp-python Config (HF Spaces) ---
GGUF_REPO_ID = os.environ.get("GGUF_REPO_ID", "") # e.g. "username/mentalhealthbuddy-gguf"
GGUF_FILENAME = os.environ.get("GGUF_FILENAME", "mentalhealthbuddy_q4_k_m.gguf")
GGUF_LOCAL_PATH = os.environ.get("GGUF_LOCAL_PATH", "") # if already downloaded
# --- Generation Parameters ---
MAX_TOKENS = 256
TEMPERATURE = 0.4
TOP_P = 0.9
REPEAT_PENALTY = 1.1
# --- App Settings ---
APP_TITLE = "REFRAME"
APP_SUBTITLE = "Reframe your thinking."
RESPONSE_DELAY = 1.5 # seconds before model starts responding (thoughtfulness)
STREAM_SPEED = 0.02 # seconds between tokens when streaming
# --- Session Limits ---
MAX_CARDS = 50
MAX_SESSION_SUMMARIES = 20
# --- Cognitive Distortions ---
DISTORTIONS = [
"catastrophizing",
"overgeneralization",
"all-or-nothing thinking",
"mind-reading",
"fortune-telling",
"should-statements",
"emotional reasoning",
"labeling",
"personalization",
"mental filter",
"disqualifying the positive",
]
# --- Crisis Keywords (C-SSRS framework) ---
CRISIS_KEYWORDS = [
"kill myself",
"end my life",
"suicide",
"suicidal",
"want to die",
"better off dead",
"no reason to live",
"can't go on",
"self-harm",
"hurt myself",
"cutting myself",
"overdose",
]
# --- Helplines ---
HELPLINES = [
{"name": "988 Suicide & Crisis Lifeline (US)", "contact": "Call or text 988"},
{"name": "Crisis Text Line (US)", "contact": "Text HOME to 741741"},
{"name": "Samaritans (UK/IE)", "contact": "Call 116 123 (free, 24/7)"},
{"name": "Befrienders Worldwide", "contact": "befrienders.org"},
]
# --- Speech-to-Text (optional, requires requirements-stt.txt) ---
STT_ENABLED = True # Set False to hide mic entirely
# STT_MODEL = os.environ.get("STT_MODEL", "openai/whisper-small")
STT_MODEL = os.environ.get("STT_MODEL", "CohereLabs/cohere-transcribe-03-2026") # gated — needs HF login + access request
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