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app.py

@@ -1,41 +1,94 @@
 import nh3
-from fastapi import FastAPI, Request
-# from doc_searcher import DocSearcher
+from fastapi import FastAPI, Query
 from doc_searcher_v2 import DocSearcherV2
 from huggingface_hub import login
-from config import HUGGING_FACE_API_KEY, COLLECTION_NAME, API_KEY, COLLECTION_NAME_SUGGESTION
-from fastapi.responses import StreamingResponse
-import httpx
+from config import HUGGING_FACE_API_KEY, COLLECTION_NAME, API_KEY
+import time
+import logging
+
+# Setup logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
 
 login(HUGGING_FACE_API_KEY)
 
-app = FastAPI()
+app = FastAPI(
+    title="Senatus Legal Search API",
+    description="Semantička pretraga pravnih dokumenata sa Qwen3 reranker-om",
+    version="2.0"
+)
 
-# doc_searcher = DocSearcher(collection_name=COLLECTION_NAME)
+# Globalno inicijalizuj DocSearcher (učitava se samo jednom)
 doc_searcher_v2 = DocSearcherV2(collection_name=COLLECTION_NAME)
 
 ALLOWED_API_KEY = str(API_KEY)
 
+@app.on_event("startup")
+async def warm_up():
+    """Warm up modela pri pokretanju aplikacije"""
+    logger.info("🔥 Warming up models...")
+    start = time.time()
+    try:
+        # Pokreni dummy query da učita sve modele u memoriju
+        _ = await doc_searcher_v2.search_semantic("test", qdrant_limit=5, top_k=1)
+        elapsed = time.time() - start
+        logger.info(f"✅ Models ready! Warmup took {elapsed:.1f}s")
+    except Exception as e:
+        logger.error(f"❌ Warmup failed: {e}")
+
 @app.get("/")
 async def root():
     """Root endpoint za provjeru da li aplikacija radi"""
-    return {"status": "ok", "message": "Senatus API is running", "version": "v2"}
+    return {
+        "status": "ok",
+        "message": "Senatus API is running",
+        "version": "2.0",
+        "endpoints": {
+            "search": "/api/v2/search",
+            "docs": "/docs",
+            "health": "/health"
+        }
+    }
 
 @app.get("/health")
 async def health():
     """Health check endpoint"""
-    return {"status": "healthy"}
-
-# @app.get("/api/search")
-# async def search(q: str, type: int, lt: str | None = None, offset: int = 0):
-#     query = q.lower()
-#     xss = nh3.clean(query)
-#     data = await doc_searcher.search(text=xss,type=type,law_type=lt,offset=offset)
-#     return data
+    return {
+        "status": "healthy",
+        "models_loaded": True,
+        "version": "2.0"
+    }
 
 @app.get("/api/v2/search")
-async def v2_search(q: str):
+async def v2_search(
+    q: str = Query(..., description="Query tekst za pretragu"),
+    limit: int = Query(3, ge=1, le=10, description="Broj rezultata (1-10, default: 3)"),
+    qdrant_limit: int = Query(20, ge=10, le=50, description="Broj chunk-ova iz Qdrant-a (10-50, default: 20)")
+):
+    """
+    Semantička pretraga pravnih dokumenata
+    
+    - **q**: Tekstualni upit
+    - **limit**: Broj rezultata za vraćanje (default: 3, max: 10)
+    - **qdrant_limit**: Broj dokumenata iz Qdrant-a prije rerankinga (default: 20, max: 50)
+    
+    Returns: Lista rezultata sa skorovima, sortirana po relevantnosti
+    """
+    logger.info(f"Search query: '{q}' | limit={limit} | qdrant_limit={qdrant_limit}")
+    start = time.time()
+    
+    # Sanitizacija inputa
     query = q.lower()
     xss = nh3.clean(query)
-    data = await doc_searcher_v2.search_semantic(text=xss)
+    
+    # Pretraga sa parametrima
+    data = await doc_searcher_v2.search_semantic(
+        text=xss,
+        qdrant_limit=qdrant_limit,
+        top_k=limit
+    )
+    
+    elapsed = time.time() - start
+    logger.info(f"Search completed in {elapsed:.2f}s | Results: {len(data)}")
+    
     return data