File size: 4,235 Bytes
585cfd5 6f805e9 585cfd5 6f805e9 585cfd5 | 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 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 | """
config.py — Central configuration for the Personal Document Intel & Archiver
All paths, model settings, and user-configurable patient info live here.
"""
import json
import os
from pathlib import Path
BASE_DIR = Path(__file__).parent
# ── Directory layout ────────────────────────────────────────────────────────
DATA_DIR = BASE_DIR / "data"
DOCUMENTS_DIR = DATA_DIR / "documents"
CACHE_DIR = BASE_DIR / "cache"
MODELS_DIR = BASE_DIR / "models"
ASSETS_DIR = BASE_DIR / "assets"
# ── Model settings ──────────────────────────────────────────────────────────
MODEL_PATH = MODELS_DIR / "qwen2.5-3b-instruct-q4_k_m.gguf"
EMBEDDING_MODEL = "all-MiniLM-L6-v2"
CHUNK_SIZE = 500
CHUNK_OVERLAP = 50
TOP_K_RETRIEVAL = 3
TEMPERATURE = 0.1
MAX_TOKENS = 512
CONTEXT_SIZE = 4096
# ── LM Studio endpoint ────────────────────────────────────────────────────────
LM_STUDIO_URL = "http://192.168.1.160:1234/v1/completions"
# ── FAISS / chunk cache ─────────────────────────────────────────────────────
FAISS_INDEX_PATH = CACHE_DIR / "index.faiss"
CHUNKS_JSON_PATH = CACHE_DIR / "chunks.json"
# ── Data store paths ────────────────────────────────────────────────────────
MEDICATIONS_JSON = DATA_DIR / "medications.json"
APPOINTMENTS_JSON = DATA_DIR / "appointments.json"
FOOD_CHART_JSON = DATA_DIR / "food_chart.json"
PATIENT_CONFIG_JSON = DATA_DIR / "patient_config.json"
# ── Patient info defaults (overridden by PATIENT_CONFIG_JSON at runtime) ────
_PATIENT_DEFAULTS = {
"patient_name": "",
"patient_dob": "",
"insurance_info": "",
"model_path": str(MODEL_PATH),
"welcome_dismissed": False,
"active_profile_id": "",
}
def _ensure_dirs():
"""Create all required directories if they don't exist."""
for d in [DATA_DIR, DOCUMENTS_DIR, CACHE_DIR, MODELS_DIR, ASSETS_DIR]:
d.mkdir(parents=True, exist_ok=True)
def _ensure_model():
"""
Stub: previously auto-downloaded a local GGUF for llama-cpp-python.
Now we use the Hugging Face Inference API (hosted Qwen 2.5 7B), which
needs no local model file. Kept as a no-op for backwards compatibility
with any callers that still expect this function to exist.
"""
return
def load_patient_config() -> dict:
"""Load patient config from disk, falling back to defaults."""
_ensure_dirs()
if PATIENT_CONFIG_JSON.exists():
try:
with open(PATIENT_CONFIG_JSON, "r", encoding="utf-8") as f:
data = json.load(f)
# Merge so any new keys from defaults are present
merged = {**_PATIENT_DEFAULTS, **data}
return merged
except Exception:
pass
return dict(_PATIENT_DEFAULTS)
def save_patient_config(cfg: dict):
"""Persist patient config to disk."""
_ensure_dirs()
with open(PATIENT_CONFIG_JSON, "w", encoding="utf-8") as f:
json.dump(cfg, f, indent=2)
def get_model_path() -> Path:
"""Return the active model path (from saved config or default)."""
cfg = load_patient_config()
return Path(cfg.get("model_path", str(MODEL_PATH)))
def load_active_profile_id() -> str:
"""Return persisted active care profile id, or empty string."""
return (load_patient_config().get("active_profile_id") or "").strip()
def save_active_profile_id(profile_id: str | None):
"""Persist the active care profile id (empty string clears the session)."""
cfg = load_patient_config()
cfg["active_profile_id"] = profile_id or ""
save_patient_config(cfg)
# Ensure directories exist when module is first imported
_ensure_dirs()
_ensure_model()
|