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# # backend/src/api/routes/visual.py
# import json
# import asyncio
# from fastapi import (
# APIRouter,
# Depends,
# UploadFile,
# File,
# HTTPException,
# BackgroundTasks
# )
# from sqlalchemy.ext.asyncio import AsyncSession
# from sqlalchemy.future import select
# from qdrant_client import QdrantClient
# from qdrant_client.http import models
# # =========================
# # Auth & DB Imports
# # =========================
# from backend.src.api.routes.deps import get_current_user
# from backend.src.db.session import get_db, AsyncSessionLocal
# from backend.src.models.user import User
# from backend.src.models.integration import UserIntegration
# from backend.src.models.ingestion import IngestionJob, JobStatus
# # =========================
# # Visual Services
# # =========================
# from backend.src.services.visual.engine import get_image_embedding
# from backend.src.services.visual.agent import run_visual_sync
# router = APIRouter()
# # ======================================================
# # 1. VISUAL SYNC (BACKGROUND)
# # ======================================================
# @router.post("/visual/sync")
# async def trigger_visual_sync(
# background_tasks: BackgroundTasks,
# db: AsyncSession = Depends(get_db),
# current_user: User = Depends(get_current_user)
# ):
# try:
# job = IngestionJob(
# session_id=f"visual_sync_{current_user.id}",
# ingestion_type="visual_sync",
# source_name="Store Integration (Visual)",
# status=JobStatus.PENDING,
# total_items=0,
# items_processed=0
# )
# db.add(job)
# await db.commit()
# await db.refresh(job)
# background_tasks.add_task(
# run_visual_sync,
# str(current_user.id),
# job.id,
# AsyncSessionLocal
# )
# return {
# "status": "processing",
# "message": "Visual Sync started successfully.",
# "job_id": job.id
# }
# except Exception as e:
# print(f"β Visual Sync Failed: {e}")
# raise HTTPException(status_code=500, detail=str(e))
# # ======================================================
# # 2. VISUAL SEARCH (QDRANT 1.16.1 β DEDUPLICATED)
# # ======================================================
# @router.post("/visual/search")
# async def search_visual_products(
# file: UploadFile = File(...),
# db: AsyncSession = Depends(get_db),
# current_user: User = Depends(get_current_user)
# ):
# """
# Image β Embedding β Qdrant query_points β Unique Results
# """
# # ----------------------------------
# # 1. Load Qdrant Integration
# # ----------------------------------
# stmt = select(UserIntegration).where(
# UserIntegration.user_id == str(current_user.id),
# UserIntegration.provider == "qdrant",
# UserIntegration.is_active == True
# )
# result = await db.execute(stmt)
# integration = result.scalars().first()
# if not integration:
# raise HTTPException(
# status_code=400,
# detail="Qdrant integration not found."
# )
# try:
# creds = json.loads(integration.credentials)
# qdrant_url = creds["url"]
# qdrant_key = creds["api_key"]
# collection_name = "visual_search_products"
# except Exception:
# raise HTTPException(
# status_code=500,
# detail="Invalid Qdrant credentials format."
# )
# # ----------------------------------
# # 2. Image β Vector
# # ----------------------------------
# try:
# image_bytes = await file.read()
# vector = get_image_embedding(image_bytes)
# if not vector:
# raise ValueError("Empty embedding returned")
# except Exception as e:
# raise HTTPException(
# status_code=400,
# detail=f"Image processing failed: {e}"
# )
# # ----------------------------------
# # 3. Qdrant Search (query_points)
# # ----------------------------------
# try:
# def run_search():
# client = QdrantClient(
# url=qdrant_url,
# api_key=qdrant_key
# )
# # NOTE: Limit increased to 25 to ensure we have enough results
# # after removing duplicates (variants with same image).
# return client.query_points(
# collection_name=collection_name,
# query=vector,
# limit=25,
# with_payload=True,
# query_filter=models.Filter(
# must=[
# models.FieldCondition(
# key="user_id",
# match=models.MatchValue(
# value=str(current_user.id)
# )
# )
# ]
# )
# )
# # Execute search in thread
# search_response = await asyncio.to_thread(run_search)
# # Get points from response object
# hits = search_response.points
# # ----------------------------------
# # 4. Format & Remove Duplicates
# # ----------------------------------
# results = []
# seen_products = set() # To track unique product IDs
# for hit in hits:
# if hit.score < 0.50:
# continue
# payload = hit.payload or {}
# product_id = payload.get("product_id")
# # β
DUPLICATE CHECK:
# # Agar ye product ID pehle aa chuka hai (higher score ke sath),
# # toh is wale ko skip karo.
# if product_id in seen_products:
# continue
# seen_products.add(product_id)
# results.append({
# "product_id": product_id,
# "slug": payload.get("slug"),
# "image_path": payload.get("image_url"),
# "similarity": hit.score
# })
# # Optional: Limit final output to top 10 unique products
# if len(results) >= 10:
# break
# return {"results": results}
# except Exception as e:
# print(f"β Visual Search Failed: {e}")
# msg = str(e)
# if "dimension" in msg.lower():
# msg = "Vector dimension mismatch. Please re-run Visual Sync."
# if "not found" in msg.lower():
# msg = "Visual search collection not found. Run Sync first."
# raise HTTPException(status_code=500, detail=msg)
import json
import asyncio
from fastapi import (
APIRouter,
Depends,
UploadFile,
File,
HTTPException,
BackgroundTasks,
Request, # <--- NEW: Request object for headers/origin check
status
)
from sqlalchemy.ext.asyncio import AsyncSession
from sqlalchemy.future import select
from qdrant_client import QdrantClient
from qdrant_client.http import models
# =========================
# Auth & DB Imports
# =========================
# π Change: Humne naya auth method import kiya
from backend.src.api.routes.deps import get_current_user, get_current_user_by_api_key
from backend.src.db.session import get_db, AsyncSessionLocal
from backend.src.models.user import User
from backend.src.models.integration import UserIntegration
from backend.src.models.ingestion import IngestionJob, JobStatus
# =========================
# Visual Services
# =========================
from backend.src.services.visual.engine import get_image_embedding
from backend.src.services.visual.agent import run_visual_sync
router = APIRouter()
# ======================================================
# HELPER: DOMAIN LOCK SECURITY π
# ======================================================
def check_domain_authorization(user: User, request: Request):
"""
Check if the request is coming from an allowed domain.
Logic copied from chat.py for consistency.
"""
# 1. Browser headers check karein
client_origin = request.headers.get("origin") or request.headers.get("referer") or ""
# 2. Agar user ne "*" set kiya hai, to sab allow hai
if user.allowed_domains == "*":
return True
# 3. Allowed domains ki list banao
allowed = [d.strip() for d in user.allowed_domains.split(",")]
# 4. Check karo ke origin match karta hai ya nahi
is_authorized = any(domain in client_origin for domain in allowed)
if not is_authorized:
print(f"π« [Visual Security] Blocked unauthorized domain: {client_origin}")
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail="Domain not authorized to use this API."
)
# ======================================================
# 1. VISUAL SYNC (Dashboard Only - Uses JWT)
# ======================================================
@router.post("/visual/sync")
async def trigger_visual_sync(
background_tasks: BackgroundTasks,
db: AsyncSession = Depends(get_db),
# NOTE: Sync humesha Dashboard se hota hai, isliye JWT (get_current_user) rakha hai.
current_user: User = Depends(get_current_user)
):
try:
job = IngestionJob(
session_id=f"visual_sync_{current_user.id}",
ingestion_type="visual_sync",
source_name="Store Integration (Visual)",
status=JobStatus.PENDING,
total_items=0,
items_processed=0
)
db.add(job)
await db.commit()
await db.refresh(job)
background_tasks.add_task(
run_visual_sync,
str(current_user.id),
job.id,
AsyncSessionLocal
)
return {
"status": "processing",
"message": "Visual Sync started successfully.",
"job_id": job.id
}
except Exception as e:
print(f"β Visual Sync Failed: {e}")
raise HTTPException(status_code=500, detail=str(e))
# ======================================================
# 2. VISUAL SEARCH (Public Widget - Uses API Key + Domain Lock)
# ======================================================
@router.post("/visual/search")
async def search_visual_products(
request: Request, # <--- Browser Request Access
file: UploadFile = File(...),
db: AsyncSession = Depends(get_db),
# π₯ CHANGE: Ab ye API Key se authenticate hoga (Widget Friendly)
current_user: User = Depends(get_current_user_by_api_key)
):
"""
Image β Embedding β Qdrant query_points β Unique Results
Secured by API Key & Domain Lock.
"""
# π 1. Domain Security Check
check_domain_authorization(current_user, request)
# ----------------------------------
# 2. Load Qdrant Integration
# ----------------------------------
stmt = select(UserIntegration).where(
UserIntegration.user_id == str(current_user.id),
UserIntegration.provider == "qdrant",
UserIntegration.is_active == True
)
result = await db.execute(stmt)
integration = result.scalars().first()
if not integration:
raise HTTPException(
status_code=400,
detail="Qdrant integration not found."
)
try:
creds = json.loads(integration.credentials)
qdrant_url = creds["url"]
qdrant_key = creds["api_key"]
# π₯ CHANGE: Look for 'visual_collection_name' specifically
# This prevents conflict with Chat's 'collection_name'
collection_name = creds.get("visual_collection_name", "visual_search_products")
except Exception:
raise HTTPException(
status_code=500,
detail="Invalid Qdrant credentials format."
)
# ----------------------------------
# 3. Image β Vector
# ----------------------------------
try:
image_bytes = await file.read()
vector = get_image_embedding(image_bytes)
if not vector:
raise ValueError("Empty embedding returned")
except Exception as e:
raise HTTPException(
status_code=400,
detail=f"Image processing failed: {e}"
)
# ----------------------------------
# 4. Qdrant Search (query_points)
# ----------------------------------
try:
def run_search():
client = QdrantClient(
url=qdrant_url,
api_key=qdrant_key
)
# Limit 25 taake duplicates hatane ke baad bhi kafi results bachein
return client.query_points(
collection_name=collection_name,
query=vector,
limit=25,
with_payload=True,
query_filter=models.Filter(
must=[
models.FieldCondition(
key="user_id",
match=models.MatchValue(
value=str(current_user.id)
)
)
]
)
)
# Execute search in thread
search_response = await asyncio.to_thread(run_search)
# Get points from response object
hits = search_response.points
# ----------------------------------
# 5. Format & Remove Duplicates
# ----------------------------------
results = []
seen_products = set() # To track unique product IDs
for hit in hits:
if hit.score < 0.50:
continue
payload = hit.payload or {}
product_id = payload.get("product_id")
# β
DUPLICATE CHECK
if product_id in seen_products:
continue
seen_products.add(product_id)
results.append({
"product_id": product_id,
"slug": payload.get("slug"),
"image_path": payload.get("image_url"),
"similarity": hit.score
})
# Optional: Limit final output to top 10 unique products
if len(results) >= 10:
break
return {"results": results}
except Exception as e:
print(f"β Visual Search Failed: {e}")
msg = str(e)
if "dimension" in msg.lower():
msg = "Vector dimension mismatch. Please re-run Visual Sync."
if "not found" in msg.lower():
msg = "Visual search collection not found. Run Sync first."
raise HTTPException(status_code=500, detail=msg) |