diff --git a/backend/innercontext/api/products.py b/backend/innercontext/api/products.py index f8f3c77..25a1c82 100644 --- a/backend/innercontext/api/products.py +++ b/backend/innercontext/api/products.py @@ -1,16 +1,12 @@ -import json from datetime import date from typing import Optional from uuid import UUID, uuid4 -from fastapi import APIRouter, Depends, HTTPException, Query -from google.genai import types as genai_types -from pydantic import ValidationError +from fastapi import APIRouter, Depends, Query from sqlmodel import Session, SQLModel, select from db import get_session from innercontext.api.utils import get_or_404 -from innercontext.llm import get_gemini_client from innercontext.models import ( Product, ProductBase, @@ -99,50 +95,6 @@ class ProductUpdate(SQLModel): personal_repurchase_intent: Optional[bool] = None -class ProductParseRequest(SQLModel): - text: str - - -class ProductParseResponse(SQLModel): - name: Optional[str] = None - brand: Optional[str] = None - line_name: Optional[str] = None - sku: Optional[str] = None - url: Optional[str] = None - barcode: Optional[str] = None - category: Optional[ProductCategory] = None - recommended_time: Optional[DayTime] = None - texture: Optional[TextureType] = None - absorption_speed: Optional[AbsorptionSpeed] = None - leave_on: Optional[bool] = None - price_tier: Optional[PriceTier] = None - size_ml: Optional[float] = None - full_weight_g: Optional[float] = None - empty_weight_g: Optional[float] = None - pao_months: Optional[int] = None - inci: Optional[list[str]] = None - actives: Optional[list[ActiveIngredient]] = None - recommended_for: Optional[list[SkinType]] = None - targets: Optional[list[SkinConcern]] = None - contraindications: Optional[list[str]] = None - usage_notes: Optional[str] = None - fragrance_free: Optional[bool] = None - essential_oils_free: Optional[bool] = None - alcohol_denat_free: Optional[bool] = None - pregnancy_safe: Optional[bool] = None - product_effect_profile: Optional[ProductEffectProfile] = None - ph_min: Optional[float] = None - ph_max: Optional[float] = None - incompatible_with: Optional[list[ProductInteraction]] = None - synergizes_with: Optional[list[str]] = None - context_rules: Optional[ProductContext] = None - min_interval_hours: Optional[int] = None - max_frequency_per_week: Optional[int] = None - is_medication: Optional[bool] = None - is_tool: Optional[bool] = None - needle_length_mm: Optional[float] = None - - class InventoryCreate(SQLModel): is_opened: bool = False opened_at: Optional[date] = None @@ -216,160 +168,6 @@ def create_product(data: ProductCreate, session: Session = Depends(get_session)) return product -def _product_parse_system_prompt() -> str: - return """\ -You are a skincare and cosmetics product data extraction expert. \ -Given raw text (product page copy, ingredient list, label scan, etc.), \ -extract structured product data and return it as a single JSON object. - -RULES: -- Return ONLY raw JSON — no markdown code fences, no explanation, no preamble. -- Omit any field you cannot confidently determine from the text. Do not guess. -- All enum values must exactly match the allowed strings listed below. -- For INCI lists: return each ingredient as a separate string in the array, \ -preserving standard INCI names exactly as they appear. -- For actives: extract name, concentration (numeric, 0–100), functions \ -(use the allowed strings), and strength/irritation level if inferable. -- For effect_profile scores (0–5 int): ALWAYS return the full product_effect_profile \ -object with all 13 fields. Infer each score from ingredient activity and product claims. \ -Use 0 only when you truly have no basis for an estimate. -- For pH: extract from explicit mention (e.g. "pH 5.5", "pH range 4.0–5.0"). \ -Do not infer from ingredients alone. -- For context_rules: infer from usage instructions and ingredient interactions \ -(e.g. "do not use with AHAs" → safe_after_acids: false). -- fragrance_free / essential_oils_free / alcohol_denat_free: infer from INCI \ -or explicit claims. Fragrance = "Parfum" or "Fragrance" in INCI → fragrance_free: false. -- For leave_on: true = leave-on treatment, false = rinse-off (cleanser, mask to rinse). -- recommended_time: "am" if contains SPF or vitamin C; "pm" if retinoid/retinol; \ -"both" otherwise (when unclear, use "both"). - -ENUM ALLOWED VALUES (use ONLY these exact strings): - -category: "cleanser" | "toner" | "essence" | "serum" | "moisturizer" | "spf" | \ -"mask" | "exfoliant" | "hair_treatment" | "tool" | "spot_treatment" | "oil" - -recommended_time: "am" | "pm" | "both" - -texture: "watery" | "gel" | "emulsion" | "cream" | "oil" | "balm" | "foam" | "fluid" - -absorption_speed: "very_fast" | "fast" | "moderate" | "slow" | "very_slow" - -price_tier: "budget" | "mid" | "premium" | "luxury" - -recommended_for (array, pick applicable): -"dry" | "oily" | "combination" | "sensitive" | "normal" | "acne_prone" - -targets (array, pick applicable): -"acne" | "rosacea" | "hyperpigmentation" | "aging" | "dehydration" | "redness" | \ -"damaged_barrier" | "pore_visibility" | "uneven_texture" | "hair_growth" | "sebum_excess" - -actives[].functions (array, pick applicable): -"humectant" | "emollient" | "occlusive" | "exfoliant_aha" | "exfoliant_bha" | \ -"exfoliant_pha" | "retinoid" | "antioxidant" | "soothing" | "barrier_support" | \ -"brightening" | "anti_acne" | "ceramide" | "niacinamide" | "sunscreen" | "peptide" | \ -"hair_growth_stimulant" | "prebiotic" | "vitamin_c" - -actives[].strength_level: 1 (low) | 2 (medium) | 3 (high) -actives[].irritation_potential: 1 (low) | 2 (medium) | 3 (high) - -incompatible_with[].scope: "same_step" | "same_day" | "same_period" - -OUTPUT SCHEMA (all fields optional — omit what you cannot determine): -{ - "name": string, - "brand": string, - "line_name": string, - "sku": string, - "url": string, - "barcode": string, - "category": string, - "recommended_time": string, - "texture": string, - "absorption_speed": string, - "leave_on": boolean, - "price_tier": string, - "size_ml": number, - "full_weight_g": number, - "empty_weight_g": number, - "pao_months": integer, - "inci": [string, ...], - "actives": [ - { - "name": string, - "percent": number, - "functions": [string, ...], - "strength_level": 1|2|3, - "irritation_potential": 1|2|3 - } - ], - "recommended_for": [string, ...], - "targets": [string, ...], - "contraindications": [string, ...], - "usage_notes": string, - "fragrance_free": boolean, - "essential_oils_free": boolean, - "alcohol_denat_free": boolean, - "pregnancy_safe": boolean, - "product_effect_profile": { - "hydration_immediate": integer (0-5), - "hydration_long_term": integer (0-5), - "barrier_repair_strength": integer (0-5), - "soothing_strength": integer (0-5), - "exfoliation_strength": integer (0-5), - "retinoid_strength": integer (0-5), - "irritation_risk": integer (0-5), - "comedogenic_risk": integer (0-5), - "barrier_disruption_risk": integer (0-5), - "dryness_risk": integer (0-5), - "brightening_strength": integer (0-5), - "anti_acne_strength": integer (0-5), - "anti_aging_strength": integer (0-5) - }, - "ph_min": number, - "ph_max": number, - "incompatible_with": [ - {"target": string, "scope": string, "reason": string} - ], - "synergizes_with": [string, ...], - "context_rules": { - "safe_after_shaving": boolean, - "safe_after_acids": boolean, - "safe_after_retinoids": boolean, - "safe_with_compromised_barrier": boolean, - "low_uv_only": boolean - }, - "min_interval_hours": integer, - "max_frequency_per_week": integer, - "is_medication": boolean, - "is_tool": boolean, - "needle_length_mm": number -} -""" - - -@router.post("/parse-text", response_model=ProductParseResponse) -def parse_product_text(data: ProductParseRequest) -> ProductParseResponse: - client, model = get_gemini_client() - response = client.models.generate_content( - model=model, - contents=f"Extract product data from this text:\n\n{data.text}", - config=genai_types.GenerateContentConfig( - system_instruction=_product_parse_system_prompt(), - response_mime_type="application/json", - max_output_tokens=4096, - temperature=0.0, - ), - ) - try: - parsed = json.loads(response.text) - except (json.JSONDecodeError, Exception) as e: - raise HTTPException(status_code=502, detail=f"LLM returned invalid JSON: {e}") - try: - return ProductParseResponse.model_validate(parsed) - except ValidationError as e: - raise HTTPException(status_code=422, detail=e.errors()) - - @router.get("/{product_id}", response_model=ProductWithInventory) def get_product(product_id: UUID, session: Session = Depends(get_session)): product = get_or_404(session, Product, product_id) diff --git a/backend/innercontext/api/skincare.py b/backend/innercontext/api/skincare.py index 8e2cf9c..0bed948 100644 --- a/backend/innercontext/api/skincare.py +++ b/backend/innercontext/api/skincare.py @@ -1,16 +1,12 @@ -import json from datetime import date from typing import Optional from uuid import UUID, uuid4 -from fastapi import APIRouter, Depends, File, HTTPException, UploadFile -from google.genai import types as genai_types -from pydantic import ValidationError +from fastapi import APIRouter, Depends from sqlmodel import Session, SQLModel, select from db import get_session from innercontext.api.utils import get_or_404 -from innercontext.llm import get_gemini_client from innercontext.models import ( SkinConditionSnapshot, SkinConditionSnapshotBase, @@ -20,7 +16,7 @@ from innercontext.models.enums import ( BarrierState, OverallSkinState, SkinConcern, - SkinTexture, + SkinTrend, SkinType, ) @@ -39,8 +35,8 @@ class SnapshotCreate(SkinConditionSnapshotBase): class SnapshotUpdate(SQLModel): snapshot_date: Optional[date] = None overall_state: Optional[OverallSkinState] = None + trend: Optional[SkinTrend] = None skin_type: Optional[SkinType] = None - texture: Optional[SkinTexture] = None hydration_level: Optional[int] = None sebum_tzone: Optional[int] = None @@ -55,117 +51,11 @@ class SnapshotUpdate(SQLModel): notes: Optional[str] = None -class SkinPhotoAnalysisResponse(SQLModel): - overall_state: Optional[OverallSkinState] = None - skin_type: Optional[SkinType] = None - texture: Optional[SkinTexture] = None - hydration_level: Optional[int] = None - sebum_tzone: Optional[int] = None - sebum_cheeks: Optional[int] = None - sensitivity_level: Optional[int] = None - barrier_state: Optional[BarrierState] = None - active_concerns: Optional[list[SkinConcern]] = None - risks: Optional[list[str]] = None - priorities: Optional[list[str]] = None - notes: Optional[str] = None - - -# --------------------------------------------------------------------------- -# Helpers -# --------------------------------------------------------------------------- - - -def _skin_photo_system_prompt() -> str: - return """\ -You are a dermatology-trained skin assessment AI. Analyze the provided photo(s) of a person's -skin and return a structured JSON assessment. - -RULES: -- Return ONLY raw JSON — no markdown fences, no explanation. -- Omit any field you cannot confidently determine from the photos. Do not guess. -- All enum values must exactly match the allowed strings listed below. -- Numeric metrics use a 1–5 scale (1 = minimal, 5 = maximal). -- risks and priorities: short English phrases, max 10 words each. -- notes: 2–4 sentence paragraph describing key observations. - -ENUM VALUES: -overall_state: "excellent" | "good" | "fair" | "poor" -skin_type: "dry" | "oily" | "combination" | "sensitive" | "normal" | "acne_prone" -texture: "smooth" | "rough" | "flaky" | "bumpy" -barrier_state: "intact" | "mildly_compromised" | "compromised" -active_concerns: "acne" | "rosacea" | "hyperpigmentation" | "aging" | "dehydration" | - "redness" | "damaged_barrier" | "pore_visibility" | "uneven_texture" | "sebum_excess" - -METRICS (int 1–5, omit if not assessable): -hydration_level: 1=very dehydrated/dull → 5=plump/luminous -sebum_tzone: 1=very dry T-zone → 5=very oily T-zone -sebum_cheeks: 1=very dry cheeks → 5=very oily cheeks -sensitivity_level: 1=no visible signs → 5=severe redness/reactivity - -OUTPUT (all fields optional): -{"overall_state":…, "skin_type":…, "texture":…, "hydration_level":…, - "sebum_tzone":…, "sebum_cheeks":…, "sensitivity_level":…, - "barrier_state":…, "active_concerns":[…], "risks":[…], "priorities":[…], "notes":…} -""" - - # --------------------------------------------------------------------------- # Routes # --------------------------------------------------------------------------- -MAX_IMAGE_BYTES = 5 * 1024 * 1024 # 5 MB - - -@router.post("/analyze-photos", response_model=SkinPhotoAnalysisResponse) -async def analyze_skin_photos( - photos: list[UploadFile] = File(...), -) -> SkinPhotoAnalysisResponse: - if not (1 <= len(photos) <= 3): - raise HTTPException(status_code=422, detail="Send between 1 and 3 photos.") - - client, model = get_gemini_client() - - allowed = {"image/jpeg", "image/png", "image/webp"} - parts: list[genai_types.Part] = [] - for photo in photos: - if photo.content_type not in allowed: - raise HTTPException(status_code=422, detail=f"Unsupported type: {photo.content_type}") - data = await photo.read() - if len(data) > MAX_IMAGE_BYTES: - raise HTTPException(status_code=413, detail=f"{photo.filename} exceeds 5 MB.") - parts.append(genai_types.Part.from_bytes(data=data, mime_type=photo.content_type)) - parts.append( - genai_types.Part.from_text( - text="Analyze the skin condition visible in the above photo(s) and return the JSON assessment." - ) - ) - - try: - response = client.models.generate_content( - model=model, - contents=parts, - config=genai_types.GenerateContentConfig( - system_instruction=_skin_photo_system_prompt(), - response_mime_type="application/json", - max_output_tokens=2048, - temperature=0.0, - ), - ) - except Exception as e: - raise HTTPException(status_code=502, detail=f"Gemini API error: {e}") - - try: - parsed = json.loads(response.text) - except json.JSONDecodeError as e: - raise HTTPException(status_code=502, detail=f"LLM returned invalid JSON: {e}") - - try: - return SkinPhotoAnalysisResponse.model_validate(parsed) - except ValidationError as e: - raise HTTPException(status_code=422, detail=e.errors()) - - @router.get("", response_model=list[SkinConditionSnapshotPublic]) def list_snapshots( from_date: Optional[date] = None, diff --git a/backend/innercontext/llm.py b/backend/innercontext/llm.py deleted file mode 100644 index 428b744..0000000 --- a/backend/innercontext/llm.py +++ /dev/null @@ -1,21 +0,0 @@ -"""Shared helpers for Gemini API access.""" - -import os - -from fastapi import HTTPException -from google import genai - - -_DEFAULT_MODEL = "gemini-flash-latest" - - -def get_gemini_client() -> tuple[genai.Client, str]: - """Return an authenticated Gemini client and the configured model name. - - Raises HTTP 503 if GEMINI_API_KEY is not set. - """ - api_key = os.environ.get("GEMINI_API_KEY") - if not api_key: - raise HTTPException(status_code=503, detail="GEMINI_API_KEY not configured") - model = os.environ.get("GEMINI_MODEL", _DEFAULT_MODEL) - return genai.Client(api_key=api_key), model diff --git a/backend/innercontext/mcp_server.py b/backend/innercontext/mcp_server.py deleted file mode 100644 index 618f267..0000000 --- a/backend/innercontext/mcp_server.py +++ /dev/null @@ -1,438 +0,0 @@ -from __future__ import annotations - -from datetime import date, timedelta -from typing import Optional -from uuid import UUID - -from fastmcp import FastMCP -from sqlmodel import Session, col, select - -from db import engine -from innercontext.models import ( - GroomingSchedule, - LabResult, - MedicationEntry, - MedicationUsage, - Product, - ProductInventory, - Routine, - RoutineStep, - SkinConditionSnapshot, -) - -mcp = FastMCP("innercontext") - - -# ── Products ────────────────────────────────────────────────────────────────── - - -@mcp.tool() -def get_products( - category: Optional[str] = None, - is_medication: bool = False, - is_tool: bool = False, -) -> list[dict]: - """List products. By default returns skincare products (excludes medications and tools). - Pass is_medication=True or is_tool=True to retrieve those categories instead.""" - with Session(engine) as session: - stmt = select(Product) - if category is not None: - stmt = stmt.where(Product.category == category) - stmt = stmt.where(Product.is_medication == is_medication) - stmt = stmt.where(Product.is_tool == is_tool) - products = session.exec(stmt).all() - return [p.to_llm_context() for p in products] - - -@mcp.tool() -def get_product(product_id: str) -> dict: - """Get full context for a single product (UUID) including all inventory entries.""" - with Session(engine) as session: - product = session.get(Product, UUID(product_id)) - if product is None: - return {"error": f"Product {product_id} not found"} - ctx = product.to_llm_context() - entries = session.exec( - select(ProductInventory).where(ProductInventory.product_id == product.id) - ).all() - ctx["inventory"] = [ - { - "id": str(inv.id), - "is_opened": inv.is_opened, - "opened_at": inv.opened_at.isoformat() if inv.opened_at else None, - "finished_at": inv.finished_at.isoformat() if inv.finished_at else None, - "expiry_date": inv.expiry_date.isoformat() if inv.expiry_date else None, - "current_weight_g": inv.current_weight_g, - } - for inv in entries - ] - return ctx - - -# ── Inventory ───────────────────────────────────────────────────────────────── - - -@mcp.tool() -def get_open_inventory() -> list[dict]: - """Return all currently open packages (is_opened=True, finished_at=None) - with product name, opening date, weight, and expiry date.""" - with Session(engine) as session: - stmt = ( - select(ProductInventory, Product) - .join(Product, ProductInventory.product_id == Product.id) - .where(ProductInventory.is_opened == True) # noqa: E712 - .where(ProductInventory.finished_at == None) # noqa: E711 - ) - rows = session.exec(stmt).all() - return [ - { - "inventory_id": str(inv.id), - "product_id": str(product.id), - "product_name": product.name, - "brand": product.brand, - "opened_at": inv.opened_at.isoformat() if inv.opened_at else None, - "current_weight_g": inv.current_weight_g, - "expiry_date": inv.expiry_date.isoformat() if inv.expiry_date else None, - } - for inv, product in rows - ] - - -# ── Routines ────────────────────────────────────────────────────────────────── - - -@mcp.tool() -def get_recent_routines(days: int = 14) -> list[dict]: - """Get skincare routines from the last N days, newest first. - Each routine includes its ordered steps with product name or action.""" - with Session(engine) as session: - cutoff = date.today() - timedelta(days=days) - routines = session.exec( - select(Routine) - .where(Routine.routine_date >= cutoff) - .order_by(col(Routine.routine_date).desc()) - ).all() - - result = [] - for routine in routines: - steps = session.exec( - select(RoutineStep) - .where(RoutineStep.routine_id == routine.id) - .order_by(RoutineStep.order_index) - ).all() - - steps_data = [] - for step in steps: - step_dict: dict = {"order": step.order_index} - if step.product_id: - product = session.get(Product, step.product_id) - if product: - step_dict["product"] = product.name - step_dict["product_id"] = str(product.id) - if step.action_type: - step_dict["action"] = ( - step.action_type.value - if hasattr(step.action_type, "value") - else str(step.action_type) - ) - if step.action_notes: - step_dict["notes"] = step.action_notes - if step.dose: - step_dict["dose"] = step.dose - if step.region: - step_dict["region"] = step.region - steps_data.append(step_dict) - - result.append( - { - "id": str(routine.id), - "date": routine.routine_date.isoformat(), - "part_of_day": ( - routine.part_of_day.value - if hasattr(routine.part_of_day, "value") - else str(routine.part_of_day) - ), - "notes": routine.notes, - "steps": steps_data, - } - ) - - return result - - -# ── Skin snapshots ──────────────────────────────────────────────────────────── - - -def _snapshot_to_dict(s: SkinConditionSnapshot, *, full: bool) -> dict: - def ev(v: object) -> object: - return v.value if v is not None and hasattr(v, "value") else v - - d: dict = { - "id": str(s.id), - "date": s.snapshot_date.isoformat(), - "overall_state": ev(s.overall_state), - "hydration_level": s.hydration_level, - "sensitivity_level": s.sensitivity_level, - "barrier_state": ev(s.barrier_state), - "active_concerns": [ev(c) for c in (s.active_concerns or [])], - } - if full: - d.update( - { - "skin_type": ev(s.skin_type), - "texture": ev(s.texture), - "sebum_tzone": s.sebum_tzone, - "sebum_cheeks": s.sebum_cheeks, - "risks": s.risks or [], - "priorities": s.priorities or [], - "notes": s.notes, - } - ) - return d - - -@mcp.tool() -def get_latest_skin_snapshot() -> dict | None: - """Get the most recent skin condition snapshot with all metrics.""" - with Session(engine) as session: - snapshot = session.exec( - select(SkinConditionSnapshot).order_by( - col(SkinConditionSnapshot.snapshot_date).desc() - ) - ).first() - if snapshot is None: - return None - return _snapshot_to_dict(snapshot, full=True) - - -@mcp.tool() -def get_skin_history(weeks: int = 8) -> list[dict]: - """Get skin condition snapshots from the last N weeks with key metrics.""" - with Session(engine) as session: - cutoff = date.today() - timedelta(weeks=weeks) - snapshots = session.exec( - select(SkinConditionSnapshot) - .where(SkinConditionSnapshot.snapshot_date >= cutoff) - .order_by(col(SkinConditionSnapshot.snapshot_date).desc()) - ).all() - return [_snapshot_to_dict(s, full=False) for s in snapshots] - - -@mcp.tool() -def get_skin_snapshot_dates() -> list[str]: - """List all dates (YYYY-MM-DD) for which skin snapshots exist, newest first.""" - with Session(engine) as session: - snapshots = session.exec( - select(SkinConditionSnapshot).order_by( - col(SkinConditionSnapshot.snapshot_date).desc() - ) - ).all() - return [s.snapshot_date.isoformat() for s in snapshots] - - -@mcp.tool() -def get_skin_snapshot(snapshot_date: str) -> dict | None: - """Get the full skin condition snapshot for a specific date (YYYY-MM-DD).""" - with Session(engine) as session: - target = date.fromisoformat(snapshot_date) - snapshot = session.exec( - select(SkinConditionSnapshot).where( - SkinConditionSnapshot.snapshot_date == target - ) - ).first() - if snapshot is None: - return None - return _snapshot_to_dict(snapshot, full=True) - - -# ── Health / medications ─────────────────────────────────────────────────────── - - -@mcp.tool() -def get_medications() -> list[dict]: - """Get all medication entries with their currently active usage records - (valid_to IS NULL or >= today).""" - with Session(engine) as session: - medications = session.exec(select(MedicationEntry)).all() - today = date.today() - result = [] - for med in medications: - usages = session.exec( - select(MedicationUsage) - .where(MedicationUsage.medication_record_id == med.record_id) - .where( - (MedicationUsage.valid_to == None) # noqa: E711 - | (col(MedicationUsage.valid_to) >= today) - ) - ).all() - result.append( - { - "id": str(med.record_id), - "product_name": med.product_name, - "kind": ( - med.kind.value if hasattr(med.kind, "value") else str(med.kind) - ), - "active_substance": med.active_substance, - "formulation": med.formulation, - "route": med.route, - "notes": med.notes, - "active_usages": [ - { - "id": str(u.record_id), - "dose": ( - f"{u.dose_value} {u.dose_unit}" - if u.dose_value is not None and u.dose_unit - else None - ), - "frequency": u.frequency, - "schedule_text": u.schedule_text, - "as_needed": u.as_needed, - "valid_from": u.valid_from.isoformat() - if u.valid_from - else None, - "valid_to": u.valid_to.isoformat() if u.valid_to else None, - } - for u in usages - ], - } - ) - return result - - -# ── Expiring inventory ──────────────────────────────────────────────────────── - - -@mcp.tool() -def get_expiring_inventory(days: int = 30) -> list[dict]: - """List open packages whose expiry date falls within the next N days. - Sorted by days remaining (soonest first).""" - with Session(engine) as session: - cutoff = date.today() + timedelta(days=days) - stmt = ( - select(ProductInventory, Product) - .join(Product, ProductInventory.product_id == Product.id) - .where(ProductInventory.is_opened == True) # noqa: E712 - .where(ProductInventory.finished_at == None) # noqa: E711 - .where(ProductInventory.expiry_date != None) # noqa: E711 - .where(col(ProductInventory.expiry_date) <= cutoff) - ) - rows = session.exec(stmt).all() - today = date.today() - result = [ - { - "product_name": product.name, - "brand": product.brand, - "expiry_date": inv.expiry_date.isoformat() if inv.expiry_date else None, - "days_remaining": (inv.expiry_date - today).days - if inv.expiry_date - else None, - "current_weight_g": inv.current_weight_g, - } - for inv, product in rows - ] - return sorted(result, key=lambda x: x["days_remaining"] or 0) - - -# ── Grooming schedule ───────────────────────────────────────────────────────── - - -@mcp.tool() -def get_grooming_schedule() -> list[dict]: - """Get the full grooming schedule sorted by day of week (0=Monday, 6=Sunday).""" - with Session(engine) as session: - entries = session.exec( - select(GroomingSchedule).order_by(GroomingSchedule.day_of_week) - ).all() - return [ - { - "id": str(e.id), - "day_of_week": e.day_of_week, - "action": ( - e.action.value if hasattr(e.action, "value") else str(e.action) - ), - "notes": e.notes, - } - for e in entries - ] - - -# ── Lab results ─────────────────────────────────────────────────────────────── - - -def _lab_result_to_dict(r: LabResult) -> dict: - return { - "id": str(r.record_id), - "collected_at": r.collected_at.isoformat(), - "test_code": r.test_code, - "test_name_loinc": r.test_name_loinc, - "test_name_original": r.test_name_original, - "value_num": r.value_num, - "value_text": r.value_text, - "value_bool": r.value_bool, - "unit": r.unit_ucum or r.unit_original, - "ref_low": r.ref_low, - "ref_high": r.ref_high, - "ref_text": r.ref_text, - "flag": r.flag.value if r.flag and hasattr(r.flag, "value") else r.flag, - "lab": r.lab, - "notes": r.notes, - } - - -@mcp.tool() -def get_recent_lab_results(limit: int = 30) -> list[dict]: - """Get the most recent lab results sorted by collection date descending.""" - with Session(engine) as session: - results = session.exec( - select(LabResult) - .order_by(col(LabResult.collected_at).desc()) - .limit(limit) - ).all() - return [_lab_result_to_dict(r) for r in results] - - -@mcp.tool() -def get_available_lab_tests() -> list[dict]: - """List all distinct lab tests ever performed, grouped by LOINC test_code. - Returns test_code, LOINC name, original lab names, result count, and last collection date.""" - with Session(engine) as session: - results = session.exec(select(LabResult)).all() - tests: dict[str, dict] = {} - for r in results: - code = r.test_code - if code not in tests: - tests[code] = { - "test_code": code, - "test_name_loinc": r.test_name_loinc, - "test_names_original": set(), - "count": 0, - "last_collected_at": r.collected_at, - } - tests[code]["count"] += 1 - if r.test_name_original: - tests[code]["test_names_original"].add(r.test_name_original) - if r.collected_at > tests[code]["last_collected_at"]: - tests[code]["last_collected_at"] = r.collected_at - - return [ - { - "test_code": v["test_code"], - "test_name_loinc": v["test_name_loinc"], - "test_names_original": sorted(v["test_names_original"]), - "count": v["count"], - "last_collected_at": v["last_collected_at"].isoformat(), - } - for v in sorted(tests.values(), key=lambda x: x["test_code"]) - ] - - -@mcp.tool() -def get_lab_results_for_test(test_code: str) -> list[dict]: - """Get the full chronological history of results for a specific LOINC test code.""" - with Session(engine) as session: - results = session.exec( - select(LabResult) - .where(LabResult.test_code == test_code) - .order_by(col(LabResult.collected_at).asc()) - ).all() - return [_lab_result_to_dict(r) for r in results] diff --git a/backend/innercontext/models/__init__.py b/backend/innercontext/models/__init__.py index 1ffe287..50b164a 100644 --- a/backend/innercontext/models/__init__.py +++ b/backend/innercontext/models/__init__.py @@ -15,7 +15,7 @@ from .enums import ( ResultFlag, RoutineRole, SkinConcern, - SkinTexture, + SkinTrend, SkinType, StrengthLevel, TextureType, @@ -59,7 +59,7 @@ __all__ = [ "ResultFlag", "RoutineRole", "SkinConcern", - "SkinTexture", + "SkinTrend", "SkinType", "StrengthLevel", "TextureType", diff --git a/backend/innercontext/models/enums.py b/backend/innercontext/models/enums.py index e610a03..1441bf5 100644 --- a/backend/innercontext/models/enums.py +++ b/backend/innercontext/models/enums.py @@ -186,11 +186,11 @@ class OverallSkinState(str, Enum): POOR = "poor" -class SkinTexture(str, Enum): - SMOOTH = "smooth" - ROUGH = "rough" - FLAKY = "flaky" - BUMPY = "bumpy" +class SkinTrend(str, Enum): + IMPROVING = "improving" + STABLE = "stable" + WORSENING = "worsening" + FLUCTUATING = "fluctuating" class BarrierState(str, Enum): diff --git a/backend/innercontext/models/skincare.py b/backend/innercontext/models/skincare.py index 9eed99c..de5eebf 100644 --- a/backend/innercontext/models/skincare.py +++ b/backend/innercontext/models/skincare.py @@ -9,7 +9,7 @@ from sqlmodel import Field, SQLModel from .base import utc_now from .domain import Domain -from .enums import BarrierState, OverallSkinState, SkinConcern, SkinTexture, SkinType +from .enums import BarrierState, OverallSkinState, SkinConcern, SkinTrend, SkinType # --------------------------------------------------------------------------- # Base model (pure Python types, no sa_column, no id/created_at) @@ -20,8 +20,8 @@ class SkinConditionSnapshotBase(SQLModel): snapshot_date: date overall_state: OverallSkinState | None = None + trend: SkinTrend | None = None skin_type: SkinType | None = None - texture: SkinTexture | None = None # Metryki wizualne (1 = minimalne, 5 = maksymalne nasilenie) hydration_level: int | None = Field(default=None, ge=1, le=5) diff --git a/backend/main.py b/backend/main.py index 93c035a..d996bd7 100644 --- a/backend/main.py +++ b/backend/main.py @@ -6,19 +6,9 @@ load_dotenv() # load .env before db.py reads DATABASE_URL from fastapi import FastAPI # noqa: E402 from fastapi.middleware.cors import CORSMiddleware # noqa: E402 -from fastmcp.utilities.lifespan import combine_lifespans # noqa: E402 from db import create_db_and_tables # noqa: E402 -from innercontext.api import ( # noqa: E402 - health, - inventory, - products, - routines, - skincare, -) -from innercontext.mcp_server import mcp # noqa: E402 - -mcp_app = mcp.http_app(path="/mcp") +from innercontext.api import health, inventory, products, routines, skincare # noqa: E402 @asynccontextmanager @@ -27,11 +17,7 @@ async def lifespan(app: FastAPI): yield -app = FastAPI( - title="innercontext API", - lifespan=combine_lifespans(lifespan, mcp_app.lifespan), - redirect_slashes=False, -) +app = FastAPI(title="innercontext API", lifespan=lifespan, redirect_slashes=False) app.add_middleware( CORSMiddleware, # ty: ignore[invalid-argument-type] @@ -47,9 +33,6 @@ app.include_router(routines.router, prefix="/routines", tags=["routines"]) app.include_router(skincare.router, prefix="/skincare", tags=["skincare"]) -app.mount("/mcp", mcp_app) - - @app.get("/health-check") def health_check(): return {"status": "ok"} diff --git a/backend/pyproject.toml b/backend/pyproject.toml index 1dbbe7d..9f6edfd 100644 --- a/backend/pyproject.toml +++ b/backend/pyproject.toml @@ -6,11 +6,8 @@ readme = "README.md" requires-python = ">=3.12" dependencies = [ "fastapi>=0.132.0", - "fastmcp>=2.0", - "google-genai>=1.65.0", "psycopg>=3.3.3", "python-dotenv>=1.2.1", - "python-multipart>=0.0.22", "sqlmodel>=0.0.37", "uvicorn[standard]>=0.34.0", ] diff --git a/backend/tests/conftest.py b/backend/tests/conftest.py index 2cc5b80..7085b78 100644 --- a/backend/tests/conftest.py +++ b/backend/tests/conftest.py @@ -1,5 +1,4 @@ import os -from contextlib import asynccontextmanager # Must be set before importing db (which calls create_engine at module level) os.environ.setdefault("DATABASE_URL", "sqlite://") @@ -14,18 +13,6 @@ from db import get_session from main import app -@asynccontextmanager -async def _db_only_lifespan(a): - """Lifespan without the MCP server for test isolation. - - StreamableHTTPSessionManager.run() can only be called once per instance, - which conflicts with the per-test TestClient lifecycle. We replace the - combined (db + MCP) lifespan with one that only does DB setup. - """ - db_module.create_db_and_tables() - yield - - @pytest.fixture() def session(monkeypatch): """Per-test fresh SQLite in-memory database with full isolation.""" @@ -45,11 +32,8 @@ def session(monkeypatch): @pytest.fixture() -def client(session, monkeypatch): +def client(session): """TestClient using the per-test session for every request.""" - # Replace combined (db+MCP) lifespan with DB-only to avoid the - # StreamableHTTPSessionManager single-run limitation. - monkeypatch.setattr(app.router, "lifespan_context", _db_only_lifespan) def _override(): yield session diff --git a/backend/tests/test_skincare.py b/backend/tests/test_skincare.py index 5bf9db5..db5f63a 100644 --- a/backend/tests/test_skincare.py +++ b/backend/tests/test_skincare.py @@ -16,8 +16,8 @@ def test_create_snapshot_full(client): json={ "snapshot_date": "2026-02-20", "overall_state": "good", + "trend": "improving", "skin_type": "combination", - 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category?: string; recommended_time?: string; texture?: string; absorption_speed?: string; - leave_on?: boolean; price_tier?: string; - size_ml?: number; full_weight_g?: number; empty_weight_g?: number; pao_months?: number; - inci?: string[]; actives?: ActiveIngredient[]; - recommended_for?: string[]; targets?: string[]; - contraindications?: string[]; usage_notes?: string; - fragrance_free?: boolean; essential_oils_free?: boolean; - alcohol_denat_free?: boolean; pregnancy_safe?: boolean; - product_effect_profile?: ProductEffectProfile; - ph_min?: number; ph_max?: number; - incompatible_with?: ProductInteraction[]; synergizes_with?: string[]; - context_rules?: ProductContext; - min_interval_hours?: number; max_frequency_per_week?: number; - is_medication?: boolean; is_tool?: boolean; needle_length_mm?: number; -} - -export const parseProductText = (text: string): Promise => - api.post('/products/parse-text', { text }); - // ─── Routines ──────────────────────────────────────────────────────────────── export interface RoutineListParams { @@ -218,29 +193,3 @@ export const updateSkinSnapshot = ( body: Record ): Promise => api.patch(`/skincare/${id}`, body); export const deleteSkinSnapshot = (id: string): Promise => api.del(`/skincare/${id}`); - -export interface SkinPhotoAnalysisResponse { - overall_state?: string; - texture?: string; - skin_type?: string; - hydration_level?: number; - sebum_tzone?: number; - sebum_cheeks?: number; - sensitivity_level?: number; - barrier_state?: string; - active_concerns?: string[]; - risks?: string[]; - priorities?: string[]; - notes?: string; -} - -export async function analyzeSkinPhotos(files: File[]): Promise { - const body = new FormData(); - for (const file of files) body.append('photos', file); - const res = await fetch(`${PUBLIC_API_BASE}/skincare/analyze-photos`, { method: 'POST', body }); - if (!res.ok) { - const detail = await res.json().catch(() => ({ detail: res.statusText })); - throw new Error(detail?.detail ?? res.statusText); - } - return res.json(); -} diff --git a/frontend/src/lib/components/ProductForm.svelte b/frontend/src/lib/components/ProductForm.svelte index 700ceb1..2967b50 100644 --- a/frontend/src/lib/components/ProductForm.svelte +++ b/frontend/src/lib/components/ProductForm.svelte @@ -7,7 +7,6 @@ import { Label } from '$lib/components/ui/label'; import { Select, SelectContent, SelectItem, SelectTrigger } from '$lib/components/ui/select'; import { Card, CardContent, CardHeader, CardTitle } from '$lib/components/ui/card'; - import { parseProductText, type ProductParseResponse } from '$lib/api'; let { product }: { product?: Product } = $props(); @@ -59,118 +58,6 @@ { key: 'anti_aging_strength', label: 'Anti-aging' } ] as const; - // ── Controlled text/number inputs ──────────────────────────────────────── - - let name = $state(untrack(() => product?.name ?? '')); - let brand = $state(untrack(() => product?.brand ?? '')); - let lineName = $state(untrack(() => product?.line_name ?? '')); - let url = $state(untrack(() => product?.url ?? '')); - let sku = $state(untrack(() => product?.sku ?? '')); - let barcode = $state(untrack(() => product?.barcode ?? '')); - let sizeMl = $state(untrack(() => (product?.size_ml != null ? String(product.size_ml) : ''))); - let fullWeightG = $state(untrack(() => (product?.full_weight_g != null ? String(product.full_weight_g) : ''))); - let emptyWeightG = $state(untrack(() => (product?.empty_weight_g != null ? String(product.empty_weight_g) : ''))); - let paoMonths = $state(untrack(() => (product?.pao_months != null ? String(product.pao_months) : ''))); - let phMin = $state(untrack(() => (product?.ph_min != null ? String(product.ph_min) : ''))); - let phMax = $state(untrack(() => (product?.ph_max != null ? String(product.ph_max) : ''))); - let minIntervalHours = $state(untrack(() => (product?.min_interval_hours != null ? String(product.min_interval_hours) : ''))); - let maxFrequencyPerWeek = $state(untrack(() => (product?.max_frequency_per_week != null ? String(product.max_frequency_per_week) : ''))); - let needleLengthMm = $state(untrack(() => (product?.needle_length_mm != null ? String(product.needle_length_mm) : ''))); - let usageNotes = $state(untrack(() => product?.usage_notes ?? '')); - let inciText = $state(untrack(() => product?.inci?.join('\n') ?? '')); - let contraindicationsText = $state(untrack(() => product?.contraindications?.join('\n') ?? '')); - let synergizesWithText = $state(untrack(() => product?.synergizes_with?.join('\n') ?? '')); - - let recommendedFor = $state(untrack(() => [...(product?.recommended_for ?? [])])); - let targetConcerns = $state(untrack(() => [...(product?.targets ?? [])])); - let isMedication = $state(untrack(() => product?.is_medication ?? false)); - let isTool = $state(untrack(() => product?.is_tool ?? false)); - - // ── AI pre-fill state ───────────────────────────────────────────────────── - - let aiPanelOpen = $state(false); - let aiText = $state(''); - let aiLoading = $state(false); - let aiError = $state(''); - - async function parseWithAi() { - if (!aiText.trim()) return; - aiLoading = true; - aiError = ''; - try { - const r = await parseProductText(aiText); - applyAiResult(r); - aiPanelOpen = false; - } catch (e) { - aiError = (e as Error).message; - } finally { - aiLoading = false; - } - } - - function applyAiResult(r: ProductParseResponse) { - if (r.name) name = r.name; - if (r.brand) brand = r.brand; - if (r.line_name) lineName = r.line_name; - if (r.url) url = r.url; - if (r.sku) sku = r.sku; - if (r.barcode) barcode = r.barcode; - if (r.usage_notes) usageNotes = r.usage_notes; - if (r.category) category = r.category; - if (r.recommended_time) recommendedTime = r.recommended_time; - if (r.texture) texture = r.texture; - if (r.absorption_speed) absorptionSpeed = r.absorption_speed; - if (r.price_tier) priceTier = r.price_tier; - if (r.leave_on != null) leaveOn = String(r.leave_on); - if (r.size_ml != null) sizeMl = String(r.size_ml); - if (r.full_weight_g != null) fullWeightG = String(r.full_weight_g); - if (r.empty_weight_g != null) emptyWeightG = String(r.empty_weight_g); - if (r.pao_months != null) paoMonths = String(r.pao_months); - if (r.ph_min != null) phMin = String(r.ph_min); - if (r.ph_max != null) phMax = String(r.ph_max); - if (r.min_interval_hours != null) minIntervalHours = String(r.min_interval_hours); - if (r.max_frequency_per_week != null) maxFrequencyPerWeek = String(r.max_frequency_per_week); - if (r.needle_length_mm != null) needleLengthMm = String(r.needle_length_mm); - if (r.fragrance_free != null) fragranceFree = String(r.fragrance_free); - if (r.essential_oils_free != null) essentialOilsFree = String(r.essential_oils_free); - if (r.alcohol_denat_free != null) alcoholDenatFree = String(r.alcohol_denat_free); - if (r.pregnancy_safe != null) pregnancySafe = String(r.pregnancy_safe); - if (r.recommended_for?.length) recommendedFor = [...r.recommended_for]; - if (r.targets?.length) targetConcerns = [...r.targets]; - if (r.is_medication != null) isMedication = r.is_medication; - if (r.is_tool != null) isTool = r.is_tool; - if (r.inci?.length) inciText = r.inci.join('\n'); - if (r.contraindications?.length) contraindicationsText = r.contraindications.join('\n'); - if (r.synergizes_with?.length) synergizesWithText = r.synergizes_with.join('\n'); - if (r.actives?.length) { - actives = r.actives.map((a) => ({ - name: a.name, - percent: a.percent != null ? String(a.percent) : '', - functions: [...(a.functions ?? [])] as IngredientFunction[], - strength_level: a.strength_level != null ? String(a.strength_level) : '', - irritation_potential: a.irritation_potential != null ? String(a.irritation_potential) : '' - })); - } - if (r.incompatible_with?.length) { - incompatibleWith = r.incompatible_with.map((i) => ({ - target: i.target, - scope: i.scope, - reason: i.reason ?? '' - })); - } - if (r.product_effect_profile) { - effectValues = { ...effectValues, ...r.product_effect_profile }; - } - if (r.context_rules) { - const cr = r.context_rules; - if (cr.safe_after_shaving != null) ctxAfterShaving = String(cr.safe_after_shaving); - if (cr.safe_after_acids != null) ctxAfterAcids = String(cr.safe_after_acids); - if (cr.safe_after_retinoids != null) ctxAfterRetinoids = String(cr.safe_after_retinoids); - if (cr.safe_with_compromised_barrier != null) ctxCompromisedBarrier = String(cr.safe_with_compromised_barrier); - if (cr.low_uv_only != null) ctxLowUvOnly = String(cr.low_uv_only); - } - } - // ── Select reactive state ───────────────────────────────────────────────── let category = $state(untrack(() => product?.category ?? '')); @@ -323,35 +210,6 @@ 'h-9 w-full rounded-md border border-input bg-background px-3 py-1 text-sm focus:outline-none focus:ring-2 focus:ring-ring'; - - - - - - {#if aiPanelOpen} - -

- Wklej opis produktu ze strony, listę składników lub inny tekst. - AI uzupełni dostępne pola — możesz je przejrzeć i poprawić przed zapisem. -

- - {#if aiError} -

{aiError}

- {/if} - - - {/if} - - Basic info @@ -359,31 +217,31 @@
- +
- +
- +
- +
- +
- +
@@ -476,13 +334,7 @@ type="checkbox" name="recommended_for" value={st} - checked={recommendedFor.includes(st)} - onchange={() => { - if (recommendedFor.includes(st)) - recommendedFor = recommendedFor.filter((s) => s !== st); - else - recommendedFor = [...recommendedFor, st]; - }} + checked={product?.recommended_for?.includes(st as never) ?? false} class="rounded border-input" /> {lbl(st)} @@ -500,13 +352,7 @@ type="checkbox" name="targets" value={sc} - checked={targetConcerns.includes(sc)} - onchange={() => { - if (targetConcerns.includes(sc)) - targetConcerns = targetConcerns.filter((s) => s !== sc); - else - targetConcerns = [...targetConcerns, sc]; - }} + checked={product?.targets?.includes(sc as never) ?? false} class="rounded border-input" /> {lbl(sc)} @@ -523,8 +369,7 @@ rows="2" placeholder="e.g. active rosacea flares" class={textareaClass} - bind:value={contraindicationsText} - > + >{product?.contraindications?.join('\n') ?? ''} @@ -541,8 +386,7 @@ rows="5" placeholder="Aqua Glycerin Niacinamide" class={textareaClass} - bind:value={inciText} - > + >{product?.inci?.join('\n') ?? ''}
@@ -664,8 +508,7 @@ rows="3" placeholder="Ceramides Niacinamide Retinoids" class={textareaClass} - bind:value={synergizesWithText} - > + >{product?.synergizes_with?.join('\n') ?? ''}
@@ -819,33 +662,83 @@
- +
- +
- +
- +
- +
- +
@@ -857,8 +750,7 @@ rows="2" placeholder="e.g. Apply to damp skin, avoid eye area" class={textareaClass} - bind:value={usageNotes} - > + >{product?.usage_notes ?? ''} @@ -938,31 +830,46 @@
- +
- +
+ {#if s.trend} +

Trend: {s.trend}

+ {/if} {#if s.active_concerns.length}
- {#each s.active_concerns as concern (concern)} + {#each s.active_concerns as concern} {concern.replace(/_/g, ' ')} {/each}
@@ -64,7 +67,7 @@ {#if data.recentRoutines.length}