Trainer_LLM/llm-api/exercise_router.py

# Test eines Kommentars, um die Funktion des gitea testen zu können

from fastapi import APIRouter, HTTPException, Query
from pydantic import BaseModel, Field
from typing import List, Optional, Dict, Any
from uuid import uuid4
from datetime import datetime, date
from clients import model, qdrant
from qdrant_client.models import PointStruct, VectorParams, Distance, PointIdsList
import os 

router = APIRouter()

# ---- Models ----
class Exercise(BaseModel):
    id: str = Field(default_factory=lambda: str(uuid4()))
    title: str
    summary: str
    short_description: str
    keywords: List[str] = []
    link: Optional[str] = None

    discipline: str
    group: Optional[str] = None
    age_group: str
    target_group: str
    min_participants: int
    duration_minutes: int

    capabilities: Dict[str, int] = {}
    category: str

    purpose: str
    execution: str
    notes: str
    preparation: str
    method: str
    equipment: List[str] = []

class PhaseExercise(BaseModel):
    exercise_id: str
    cond_load: Dict[str, Any] = {}
    coord_load: Dict[str, Any] = {}
    instructions: str

class PlanPhase(BaseModel):
    name: str
    duration_minutes: int
    method: str
    method_notes: str
    exercises: List[PhaseExercise]

class TrainingPlan(BaseModel):
    id: str = Field(default_factory=lambda: str(uuid4()))
    title: str
    short_description: str
    collection: str
    discipline: str
    group: Optional[str] = None
    dojo: str
    date: date
    plan_duration_weeks: int
    focus_areas: List[str] = []
    predecessor_plan_id: Optional[str] = None
    age_group: str
    created_at: datetime = Field(default_factory=datetime.utcnow)
    phases: List[PlanPhase]

class DeleteResponse(BaseModel):
    status: str
    count: int
    collection: str
    source: Optional[str] = None
    type: Optional[str] = None

# ---- CRUD Endpoints for Exercise ----
@router.post("/exercise", response_model=Exercise)
def create_exercise(ex: Exercise):
    # Ensure Exercise collection exists
    if not qdrant.collection_exists("exercises"):
        qdrant.recreate_collection(
            collection_name="exercises",
            vectors_config=VectorParams(
                size=model.get_sentence_embedding_dimension(),
                distance=Distance.COSINE
            )
        )
    vec = model.encode(f"{ex.title}. {ex.summary}").tolist()
    point = PointStruct(id=ex.id, vector=vec, payload=ex.dict())
    qdrant.upsert(collection_name="exercises", points=[point])
    return ex

@router.get("/exercise", response_model=List[Exercise])
def list_exercises(
    discipline: Optional[str] = Query(None),
    group: Optional[str] = Query(None),
    tags: Optional[str] = Query(None)
):
    filters = []
    if discipline:
        filters.append({"key": "discipline", "match": {"value": discipline}})
    if group:
        filters.append({"key": "group", "match": {"value": group}})
    if tags:
        for t in tags.split(","):
            filters.append({"key": "keywords", "match": {"value": t.strip()}})
    pts, _ = qdrant.scroll(
        collection_name="exercises",
        scroll_filter={"must": filters} if filters else None,
        limit=10000
    )
    return [Exercise(**pt.payload) for pt in pts]

# ---- CRUD Endpoints for TrainingPlan ----
@router.post("/plan", response_model=TrainingPlan)
def create_plan(plan: TrainingPlan):
    # Ensure TrainingPlan collection exists
    if not qdrant.collection_exists("training_plans"):
        qdrant.recreate_collection(
            collection_name="training_plans",
            vectors_config=VectorParams(
                size=model.get_sentence_embedding_dimension(),
                distance=Distance.COSINE
            )
        )
    vec = model.encode(f"{plan.title}. {plan.short_description}").tolist()
    point = PointStruct(id=plan.id, vector=vec, payload=plan.dict())
    qdrant.upsert(collection_name="training_plans", points=[point])
    return plan

@router.get("/plan", response_model=List[TrainingPlan])
def list_plans(
    collection: str = Query("training_plans"),
    discipline: Optional[str] = Query(None),
    group: Optional[str] = Query(None),
    dojo: Optional[str] = Query(None)
):
    if not qdrant.collection_exists(collection):
        return []
    pts, _ = qdrant.scroll(collection_name=collection, limit=10000)
    result = []
    for pt in pts:
        pl = TrainingPlan(**pt.payload)
        if discipline and pl.discipline != discipline:
            continue
        if group and pl.group != group:
            continue
        if dojo and pl.dojo != dojo:
            continue
        result.append(pl)
    return result

# ---- Delete Endpoints ----
@router.delete("/delete-source", response_model=DeleteResponse)
def delete_by_source(
    collection: str = Query(...),
    source: Optional[str] = Query(None),
    type: Optional[str] = Query(None)
):
    if not qdrant.collection_exists(collection):
        raise HTTPException(status_code=404, detail=f"Collection '{collection}' nicht gefunden.")
    filt = []
    if source:
        filt.append({"key": "source", "match": {"value": source}})
    if type:
        filt.append({"key": "type", "match": {"value": type}})
    if not filt:
        raise HTTPException(status_code=400, detail="Mindestens ein Filterparameter muss angegeben werden.")
    pts, _ = qdrant.scroll(collection_name=collection, scroll_filter={"must": filt}, limit=10000)
    ids = [str(p.id) for p in pts]
    if not ids:
        return DeleteResponse(status="🔍 Keine Einträge gefunden.", count=0, collection=collection)
    qdrant.delete(collection_name=collection, points_selector=PointIdsList(points=ids))
    return DeleteResponse(status="🗑️ gelöscht", count=len(ids), collection=collection)

@router.delete("/delete-collection", response_model=DeleteResponse)
def delete_collection(
    collection: str = Query(...)
):
    if not qdrant.collection_exists(collection):
        raise HTTPException(status_code=404, detail=f"Collection '{collection}' nicht gefunden.")
    qdrant.delete_collection(collection_name=collection)
    return DeleteResponse(status="🗑️ gelöscht", count=0, collection=collection)