docs: Added technical video

.github/workflows/docker.yml

@@ -0,0 +1,76 @@
+name: Docker CI
+
+on:
+  push:
+    branches: [ main, master ]
+  pull_request:
+    branches: [ main, master ]
+
+env:
+  REGISTRY: ghcr.io
+  IMAGE_NAME_WEB: ghcr.io/${{ github.repository }}/web
+  IMAGE_NAME_WORKER: ghcr.io/${{ github.repository }}/worker
+
+jobs:
+  build-and-push:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      packages: write
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - name: Log in to GHCR
+        if: github.event_name == 'push'
+        uses: docker/login-action@v3
+        with:
+          registry: ${{ env.REGISTRY }}
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Extract metadata (tags, labels) for Web
+        id: meta-web
+        uses: docker/metadata-action@v5
+        with:
+          images: ${{ env.IMAGE_NAME_WEB }}
+          tags: |
+            type=ref,event=branch
+            type=ref,event=pr
+            type=sha,format=short
+            latest
+
+      - name: Build and Push Web Image
+        uses: docker/build-push-action@v6
+        with:
+          context: .
+          push: ${{ github.event_name == 'push' }}
+          tags: ${{ steps.meta-web.outputs.tags }}
+          labels: ${{ steps.meta-web.outputs.labels }}
+          cache-from: type=gha
+          cache-to: type=gha,mode=max
+
+      - name: Extract metadata (tags, labels) for Worker
+        id: meta-worker
+        uses: docker/metadata-action@v5
+        with:
+          images: ${{ env.IMAGE_NAME_WORKER }}
+          tags: |
+            type=ref,event=branch
+            type=ref,event=pr
+            type=sha,format=short
+            latest
+
+      - name: Build and Push Worker Image
+        uses: docker/build-push-action@v6
+        with:
+          context: .
+          push: ${{ github.event_name == 'push' }}
+          tags: ${{ steps.meta-worker.outputs.tags }}
+          labels: ${{ steps.meta-worker.outputs.labels }}
+          cache-from: type=gha
+          cache-to: type=gha,mode=max

.github/workflows/security.yml

@@ -0,0 +1,57 @@
+name: Security Scanning
+
+on:
+  push:
+    branches: [ main, master ]
+  pull_request:
+    branches: [ main, master ]
+
+jobs:
+  bandit:
+    name: Run Bandit (SAST)
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v5
+        with:
+          enable-cache: true
+          python-version: "3.14"
+
+      - name: Run Bandit
+        run: uvx bandit -r app/ -ll -ii
+
+  pip-audit:
+    name: Dependency Audit
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v5
+        with:
+          enable-cache: true
+          python-version: "3.14"
+
+      - name: Compile requirements
+        run: uv pip compile pyproject.toml -o requirements.txt
+
+      - name: Run pip-audit
+        run: uvx pip-audit -r requirements.txt
+
+  gitleaks:
+    name: Secret Scanning
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: Run Gitleaks
+        uses: gitleaks/gitleaks-action@v2
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/tests.yml

@@ -0,0 +1,60 @@
+name: Run Tests
+
+on:
+  push:
+    branches: [ main, master ]
+  pull_request:
+    branches: [ main, master ]
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+
+    services:
+      postgres:
+        image: postgres:16-alpine
+        env:
+          POSTGRES_USER: postgres
+          POSTGRES_PASSWORD: postgres
+          POSTGRES_DB: alemno_test_db
+        ports:
+          - 5432:5432
+        options: >-
+          --health-cmd pg_isready
+          --health-interval 10s
+          --health-timeout 5s
+          --health-retries 5
+
+      redis:
+        image: redis:7-alpine
+        ports:
+          - 6379:6379
+        options: >-
+          --health-cmd "redis-cli ping"
+          --health-interval 10s
+          --health-timeout 5s
+          --health-retries 5
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v5
+        with:
+          enable-cache: true
+          python-version: "3.14"
+
+      - name: Run Tests with Coverage
+        env:
+          DATABASE_URL: postgresql+asyncpg://postgres:postgres@localhost:5432/alemno_test_db
+          REDIS_URL: redis://localhost:6379/0
+          TESTING: "True"
+        run: |
+          uv run pytest --cov=app --cov-report=xml --cov-report=term-missing -v
+
+      - name: Upload Coverage Report
+        uses: actions/upload-artifact@v4
+        with:
+          name: code-coverage-report
+          path: coverage.xml

README.md

@@ -1 +1,194 @@
-# Alemno Payments
+# Alemeno Payments
+
+[![Python Version](https://img.shields.io/badge/python-3.14-blue?style=flat-square&logo=python)](file:///home/sortedcord/Projects/alemno_payments/pyproject.toml)
+[![FastAPI](https://img.shields.io/badge/FastAPI-0.139-009688?style=flat-square&logo=fastapi)](file:///home/sortedcord/Projects/alemno_payments/app/app.py)
+[![Test CI Status](https://github.com/sortedcord/alemno-payments/actions/workflows/tests.yml/badge.svg)](https://github.com/sortedcord/alemno-payments/actions/workflows/tests.yml)
+[![Lint CI Status](https://github.com/sortedcord/alemno-payments/actions/workflows/lint.yml/badge.svg)](https://github.com/sortedcord/alemno-payments/actions/workflows/lint.yml)
+[![Docker CI Status](https://github.com/sortedcord/alemno-payments/actions/workflows/docker.yml/badge.svg)](https://github.com/sortedcord/alemno-payments/actions/workflows/docker.yml)
+[![Security CI Status](https://github.com/sortedcord/alemno-payments/actions/workflows/security.yml/badge.svg)](https://github.com/sortedcord/alemno-payments/actions/workflows/security.yml)
+
+An asynchronous transactional data cleaning, validation, and LLM powered categorization pipeline.
+
+## Features
+
+- Reads multi format dates and handles missing transaction IDs by auto generating unique fallbacks, and parses messy amounts with currency signs and commas cleanly.
+- Offloads validation, spend conversion, and analysis to a Celery background worker backed by Redis.
+- Integrates with the Google GenAI SDK (`gemini-2.5-flash-lite` 75% cheaper than `gemini-3.5-flash-lite with no tangible decrease in performance) using structured output schemas to categorize transaction records into database- defined custom categories.
+- Uses Redis caching with a 24-hour TTL to store live exchange rates, falling back to a hardcoded rate of `93.0` if offline.
+- Statistical Anomaly Detection:
+  - Flags transactions exceeding 3 times the account's median spend as statistical outliers.
+  - Flags domestic transactions in USD currency.
+  - Flags high value transactions and transactions with fraud indicative keywords.
+
+[![High Level Overview](./docs/assets/Overview.svg)](https://drive.google.com/file/d/1yk0-pXClrOp0ccTiaO7tbXPHZg4EH1eE/view?usp=sharing)
+
+[Technical Video](https://www.youtube.com/watch?v=Xjfyf1ct-0U)
+
+_Click on the image to view the [Draw.io](https://drive.google.com/file/d/1yk0-pXClrOp0ccTiaO7tbXPHZg4EH1eE/view?usp=sharing) file_
+
+## Self Hosting & Deployment
+
+We publish production-ready images to **GitHub Container Registry (GHCR)**. You can pull them directly or run them via Docker Compose.
+
+Create a `docker-compose.yml` file to host the entire stack (or just clone the repo and directly run `docker compose up -d` :
+
+```yaml
+version: "3.8"
+
+services:
+  db:
+    image: postgres:16-alpine
+    container_name: alemno_db
+    ports:
+      - "5432:5432"
+    environment:
+      POSTGRES_USER: postgres
+      POSTGRES_PASSWORD: postgres
+      POSTGRES_DB: alemno_payments
+    volumes:
+      - postgres_data:/var/lib/postgresql/data
+    healthcheck:
+      test: ["CMD-SHELL", "pg_isready -U postgres -d alemno_payments"]
+      interval: 5s
+      timeout: 5s
+      retries: 5
+
+  redis:
+    image: redis:7-alpine
+    container_name: alemno_redis
+    ports:
+      - "6379:6379"
+
+  web:
+    image: ghcr.io/sortedcord/alemno-payments/web:latest
+    container_name: alemno_web
+    ports:
+      - "3000:3000"
+    environment:
+      - POSTGRES_HOST=db
+      - POSTGRES_PORT=5432
+      - POSTGRES_USER=postgres
+      - POSTGRES_PASSWORD=postgres
+      - POSTGRES_DB=alemno_payments
+      - REDIS_HOST=redis
+      - REDIS_PORT=6379
+      - REDIS_DB=0
+      - GEMINI_API_KEY=your-gemini-api-key
+    depends_on:
+      db:
+        condition: service_healthy
+      redis:
+        condition: service_started
+
+  worker:
+    image: ghcr.io/sortedcord/alemno-payments/worker:latest
+    container_name: alemno_worker
+    environment:
+      - POSTGRES_HOST=db
+      - POSTGRES_PORT=5432
+      - POSTGRES_USER=postgres
+      - POSTGRES_PASSWORD=postgres
+      - POSTGRES_DB=alemno_payments
+      - REDIS_HOST=redis
+      - REDIS_PORT=6379
+      - REDIS_DB=0
+      - GEMINI_API_KEY=your-gemini-api-key
+    depends_on:
+      db:
+        condition: service_healthy
+      redis:
+        condition: service_started
+
+volumes:
+  postgres_data:
+```
+
+Launch the stack:
+
+```bash
+docker compose up -d
+```
+
+## Testing the API with curl
+
+All API endpoints are prefixed with `/api/v1`. Below are copy-pasteable `curl` commands using the sample [transactions.csv](file:///home/sortedcord/Projects/alemno_payments/transactions.csv) dataset.
+
+### 1. Upload CSV Transaction Data
+
+Submit a CSV file for asynchronous processing.
+
+```bash
+curl -X POST -F "file=@transactions.csv" http://localhost:3000/api/v1/jobs/upload
+```
+
+_Response Example:_
+
+```json
+{
+  "filename": "transactions.csv",
+  "id": "c0249af1-c52d-4d49-9305-3d1a10f29e03",
+  "status": "pending",
+  "row_count_raw": null,
+  "row_count_clean": null,
+  "created_at": "2026-07-03T06:29:13.123456Z",
+  "completed_at": null,
+  "error_message": null
+}
+```
+
+### 2. Check Job Status
+
+Check the status of a job using the job ID returned by the upload endpoint.
+
+```bash
+curl http://localhost:3000/api/v1/jobs/c0249af1-c52d-4d49-9305-3d1a10f29e03/status
+```
+
+_Response Example (while processing):_
+
+```json
+{
+  "id": "c0249af1-c52d-4d49-9305-3d1a10f29e03",
+  "status": "processing",
+  "summary": null
+}
+```
+
+### 3. Get Full Job Results
+
+Retrieve the high-level summary along with all categorized and parsed transactions once the job is completed.
+
+```bash
+curl http://localhost:3000/api/v1/jobs/c0249af1-c52d-4d49-9305-3d1a10f29e03/results
+```
+
+### 4. List All Jobs
+
+List all historical processing jobs. You can optionally filter by status (e.g. `pending`, `processing`, `completed`, `failed`).
+
+```bash
+# List all jobs
+curl http://localhost:3000/api/v1/jobs
+
+# List completed jobs only
+curl "http://localhost:3000/api/v1/jobs?status=completed"
+```
+
+### 5. List Categories
+
+List all available transaction categories sorted alphabetically.
+
+```bash
+curl http://localhost:3000/api/v1/categories
+```
+
+### 6. Create Custom Category
+
+Add a new custom category. Newly uploaded transactions will dynamically map to this category during classification if identified by the LLM.
+
+```bash
+curl -X POST \
+  -H "Content-Type: application/json" \
+  -d '{"name": "Subscription"}' \
+  http://localhost:3000/api/v1/categories
+```

app/api/v1/categories.py

@@ -0,0 +1,35 @@
+from typing import List
+from fastapi import APIRouter, Depends, HTTPException, status
+from app.core.dependencies import get_category_service
+from app.core.exceptions import CategoryAlreadyExistsException
+from app.schemas.category import CategoryCreate, CategoryResponse
+from app.services.category_service import CategoryService
+
+router = APIRouter(prefix="/categories", tags=["categories"])
+
+
+@router.get("", response_model=List[CategoryResponse])
+async def list_categories(
+    service: CategoryService = Depends(get_category_service),
+):
+    """
+    Returns the list of all available categories ordered alphabetically.
+    """
+    return await service.list_categories()
+
+
+@router.post("", response_model=CategoryResponse, status_code=status.HTTP_201_CREATED)
+async def create_category(
+    category_in: CategoryCreate,
+    service: CategoryService = Depends(get_category_service),
+):
+    """
+    Creates a new custom category. The name must be unique.
+    """
+    try:
+        return await service.create_category(name=category_in.name)
+    except CategoryAlreadyExistsException as e:
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail=str(e),
+        )

app/clients/exchange_rate_client.py

@@ -4,6 +4,9 @@ from app.core.config import settings
 from app.core.logging import logger
 
 
+from app.core.observability import time_it
+
+
 class ExchangeRateClient:
     def __init__(self):
         self.default_rate = 93.0
@@ -20,6 +23,7 @@ class ExchangeRateClient:
             logger.warning(f"Could not connect to Redis for exchange rate caching: {e}")
             self.redis_client = None
 
+    @time_it("Get USD to INR Exchange Rate")
     async def get_usd_to_inr_rate(self) -> float:
         """
         Retrieves the USD to INR conversion rate.

app/core/dependencies.py

@@ -3,6 +3,7 @@ from sqlalchemy.ext.asyncio import AsyncSession
 from app.db.session import get_db
 from app.repositories.job_repository import JobRepository
 from app.services.job_service import JobService
+from app.services.category_service import CategoryService
 
 
 def get_job_repository(db: AsyncSession = Depends(get_db)) -> JobRepository:
@@ -13,3 +14,8 @@ def get_job_repository(db: AsyncSession = Depends(get_db)) -> JobRepository:
 def get_job_service(repo: JobRepository = Depends(get_job_repository)) -> JobService:
     """Dependency to retrieve JobService"""
     return JobService(repo)
+
+
+def get_category_service(db: AsyncSession = Depends(get_db)) -> CategoryService:
+    """Dependency to retrieve CategoryService"""
+    return CategoryService(db)

app/core/exceptions.py

@@ -18,3 +18,11 @@ class InvalidCSVException(AlemnoException):
     def __init__(self, detail: str):
         self.detail = detail
         super().__init__(detail)
+
+
+class CategoryAlreadyExistsException(AlemnoException):
+    """Raised when a category already exists"""
+
+    def __init__(self, name: str):
+        self.name = name
+        super().__init__(f"Category '{name}' already exists.")

app/core/observability.py

@@ -0,0 +1,59 @@
+import functools
+import inspect
+import time
+from contextlib import contextmanager
+from typing import Optional
+from app.core.logging import logger
+
+
+@contextmanager
+def benchmark(name: str):
+    """
+    Context manager to benchmark a block of code.
+    Example:
+        with benchmark("Database save"):
+            await repo.save(data)
+    """
+    start_time = time.perf_counter()
+    try:
+        yield
+    finally:
+        elapsed = time.perf_counter() - start_time
+        logger.info(f"[BENCHMARK] {name} completed in {elapsed:.4f} seconds")
+
+
+def time_it(name: Optional[str] = None):
+    """
+    Decorator to benchmark synchronous or asynchronous functions.
+    Example:
+        @time_it("Retrieve exchange rate")
+        async def get_rate():
+            ...
+    """
+
+    def decorator(func):
+        label = name or func.__name__
+
+        @functools.wraps(func)
+        async def async_wrapper(*args, **kwargs):
+            start = time.perf_counter()
+            try:
+                return await func(*args, **kwargs)
+            finally:
+                elapsed = time.perf_counter() - start
+                logger.info(f"[BENCHMARK] {label} completed in {elapsed:.4f} seconds")
+
+        @functools.wraps(func)
+        def sync_wrapper(*args, **kwargs):
+            start = time.perf_counter()
+            try:
+                return func(*args, **kwargs)
+            finally:
+                elapsed = time.perf_counter() - start
+                logger.info(f"[BENCHMARK] {label} completed in {elapsed:.4f} seconds")
+
+        if inspect.iscoroutinefunction(func):
+            return async_wrapper
+        return sync_wrapper
+
+    return decorator

app/db/models/__init__.py

@@ -2,5 +2,6 @@ from app.db.base import Base
 from app.db.models.job import Job
 from app.db.models.transaction import Transaction
 from app.db.models.job_summary import JobSummary
+from app.db.models.category import Category
 
-__all__ = ["Base", "Job", "Transaction", "JobSummary"]
+__all__ = ["Base", "Job", "Transaction", "JobSummary", "Category"]

app/db/models/category.py

@@ -0,0 +1,10 @@
+from sqlalchemy import Integer, String
+from sqlalchemy.orm import Mapped, mapped_column
+from app.db.base import Base
+
+
+class Category(Base):
+    __tablename__ = "categories"
+
+    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
+    name: Mapped[str] = mapped_column(String(100), unique=True, nullable=False)

app/main.py

@@ -2,6 +2,7 @@ from contextlib import asynccontextmanager
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 from app.api.v1.jobs import router as jobs_router
+from app.api.v1.categories import router as categories_router
 from app.core.config import settings
 from app.db.base import Base
 from app.db.session import engine
@@ -12,6 +13,28 @@ async def lifespan(app: FastAPI):
     # Startup: Create tables if they don't exist
     async with engine.begin() as conn:
         await conn.run_sync(Base.metadata.create_all)
+
+    # Seed default categories if empty
+    from app.db.session import AsyncSessionLocal
+    from app.db.models.category import Category
+    from sqlalchemy import select
+
+    async with AsyncSessionLocal() as session:
+        result = await session.execute(select(Category))
+        if not result.scalars().first():
+            defaults = [
+                Category(name="Food"),
+                Category(name="Shopping"),
+                Category(name="Travel"),
+                Category(name="Transport"),
+                Category(name="Utilities"),
+                Category(name="Cash Withdrawal"),
+                Category(name="Entertainment"),
+                Category(name="Other"),
+            ]
+            session.add_all(defaults)
+            await session.commit()
+
     yield
     # Shutdown: Clean up pool
     await engine.dispose()
@@ -32,8 +55,9 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
-# Include API Router
+# Include API Routers
 app.include_router(jobs_router, prefix=settings.API_V1_STR)
+app.include_router(categories_router, prefix=settings.API_V1_STR)
 
 
 # Root healthcheck endpoint

app/repositories/category_repository.py

@@ -0,0 +1,28 @@
+from typing import List, Optional
+from sqlalchemy import select
+from sqlalchemy.ext.asyncio import AsyncSession
+from app.db.models.category import Category
+
+
+class CategoryRepository:
+    def __init__(self, db: AsyncSession):
+        self.db = db
+
+    async def list_all(self) -> List[Category]:
+        """List all category records ordered alphabetically by name"""
+        query = select(Category).order_by(Category.name.asc())
+        result = await self.db.execute(query)
+        return list(result.scalars().all())
+
+    async def create(self, name: str) -> Category:
+        """Create a new category record"""
+        category = Category(name=name)
+        self.db.add(category)
+        await self.db.flush()
+        return category
+
+    async def get_by_name(self, name: str) -> Optional[Category]:
+        """Fetch a category record by name (case-insensitive)"""
+        query = select(Category).where(Category.name.ilike(name))
+        result = await self.db.execute(query)
+        return result.scalar_one_or_none()

app/schemas/category.py

@@ -0,0 +1,17 @@
+from pydantic import BaseModel, Field, ConfigDict
+
+
+class CategoryBase(BaseModel):
+    name: str = Field(
+        ..., description="Unique category name", min_length=1, max_length=100
+    )
+
+
+class CategoryCreate(CategoryBase):
+    pass
+
+
+class CategoryResponse(CategoryBase):
+    id: int
+
+    model_config = ConfigDict(from_attributes=True)

app/services/category_service.py

@@ -0,0 +1,26 @@
+from typing import List
+from sqlalchemy.ext.asyncio import AsyncSession
+from app.repositories.category_repository import CategoryRepository
+from app.db.models.category import Category
+from app.core.exceptions import CategoryAlreadyExistsException
+
+
+class CategoryService:
+    def __init__(self, db: AsyncSession):
+        self.db = db
+        self.repo = CategoryRepository(db)
+
+    async def list_categories(self) -> List[Category]:
+        """Returns all categories alphabetical list"""
+        return await self.repo.list_all()
+
+    async def create_category(self, name: str) -> Category:
+        """Creates a new category, validating uniqueness first"""
+        name_clean = name.strip()
+        existing = await self.repo.get_by_name(name_clean)
+        if existing:
+            raise CategoryAlreadyExistsException(name_clean)
+
+        category = await self.repo.create(name_clean)
+        await self.db.commit()
+        return category

app/services/job_service.py

@@ -6,10 +6,14 @@ from app.utils.csv_parser import parse_and_validate_csv
 from app.worker import process_transaction_job
 
 
+from app.core.observability import time_it
+
+
 class JobService:
     def __init__(self, repo: JobRepository):
         self.repo = repo
 
+    @time_it("Upload CSV Service")
     async def upload_csv(self, filename: str, content: bytes) -> Job:
         parsed_transactions = parse_and_validate_csv(content)
 
@@ -19,17 +23,20 @@ class JobService:
 
         return job
 
+    @time_it("Get Job Status Service")
     async def get_job_status(self, job_id: str) -> Job:
         job = await self.repo.get_by_id(job_id)
         if not job:
             raise JobNotFoundException(job_id)
         return job
 
+    @time_it("Get Job Results Service")
     async def get_job_results(self, job_id: str) -> Job:
         job = await self.repo.get_by_id(job_id)
         if not job:
             raise JobNotFoundException(job_id)
         return job
 
+    @time_it("List Jobs Service")
     async def list_jobs(self, status: Optional[str] = None) -> List[Job]:
         return await self.repo.list_all(status=status)

app/utils/csv_parser.py

@@ -4,9 +4,12 @@ from datetime import datetime
 from typing import Any, Dict, List
 from app.core.exceptions import InvalidCSVException
 
+from app.core.observability import time_it
+
 REQUIRED_COLUMNS = {"txn_id", "date", "merchant", "amount"}
 
 
+@time_it("Parse and Validate CSV")
 def parse_and_validate_csv(content: bytes) -> List[Dict[str, Any]]:
     """
     Parses CSV content from bytes, validates headers, and checks field types.
@@ -83,6 +86,7 @@ def parse_and_validate_csv(content: bytes) -> List[Dict[str, Any]]:
         # Auto-generate txn_id if missing or empty
         if not txn_id or not txn_id.strip():
             import uuid
+
             txn_id = f"GEN_{uuid.uuid4().hex[:8].upper()}"
         else:
             txn_id = txn_id.strip()

app/worker.py

@@ -3,10 +3,10 @@ import json
 import os
 import statistics
 from datetime import datetime, date
-from typing import Any, Dict, List
+from typing import Any, Dict, List, Optional
 from sqlalchemy import select
 from celery import Celery
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, Field, AliasChoices
 from google import genai
 from app.core.config import settings
 from app.core.logging import logger
@@ -15,16 +15,38 @@ from app.repositories.job_repository import JobRepository
 from app.db.models.transaction import Transaction
 from app.db.models.job_summary import JobSummary
 from app.clients.exchange_rate_client import ExchangeRateClient
+from app.core.observability import time_it, benchmark
 
 exchange_rate_client = ExchangeRateClient()
 
 
+def clean_json_response(text: str) -> str:
+    """Extracts the first JSON object or array from the text, handling markdown fences and conversational prefix/suffix."""
+    text = text.strip()
+    start_idx = -1
+    for i, char in enumerate(text):
+        if char in ("{", "["):
+            start_idx = i
+            break
+
+    end_idx = -1
+    for i in range(len(text) - 1, -1, -1):
+        if text[i] in ("}", "]"):
+            end_idx = i
+            break
+
+    if start_idx != -1 and end_idx != -1 and end_idx > start_idx:
+        return text[start_idx : end_idx + 1]
+
+    return text
+
+
 class TransactionClassification(BaseModel):
     txn_id: str = Field(
         description="The unique transaction ID (txn_id) from the input."
     )
     category: str = Field(
-        description="Assigned category, must be one of: Food, Shopping, Travel, Transport, Utilities, Cash Withdrawal, Entertainment, or Other."
+        description="Assigned category matching one of the allowed categories list."
     )
 
 
@@ -32,9 +54,11 @@ class BatchClassificationResponse(BaseModel):
     classifications: List[TransactionClassification]
 
 
+@time_it("LLM Batch Classification Request")
 async def classify_transactions_batch(
     client: genai.Client,
     batch_txns: List[Dict[str, Any]],
+    allowed_categories: List[str],
 ) -> Dict[str, Dict[str, Any]]:
     """
     Calls the Gemini model to classify a batch of transactions.
@@ -55,8 +79,7 @@ async def classify_transactions_batch(
 
     input_prompt = (
         "Classify the following financial transactions. For each transaction, match its txn_id "
-        "and assign one of the allowed categories: Food, Shopping, Travel, Transport, Utilities, "
-        "Cash Withdrawal, Entertainment, or Other based on the merchant name and details:\n\n"
+        f"and assign one of the allowed categories: {', '.join(allowed_categories)} based on the merchant name and details:\n\n"
         f"{json.dumps(prompt_data, indent=2)}"
     )
 
@@ -70,7 +93,7 @@ async def classify_transactions_batch(
             interaction = await loop.run_in_executor(
                 None,
                 lambda: client.interactions.create(
-                    model="gemini-3.5-flash",
+                    model="gemini-2.5-flash-lite",
                     input=input_prompt,
                     response_format={
                         "type": "text",
@@ -80,9 +103,8 @@ async def classify_transactions_batch(
                 ),
             )
 
-            resp_obj = BatchClassificationResponse.model_validate_json(
-                interaction.output_text
-            )
+            clean_text = clean_json_response(interaction.output_text)
+            resp_obj = BatchClassificationResponse.model_validate_json(clean_text)
 
             results = {}
             for item in resp_obj.classifications:
@@ -113,6 +135,95 @@ async def classify_transactions_batch(
     return results
 
 
+class JobNarrativeSummary(BaseModel):
+    total_spend_by_currency: Dict[str, float] = Field(
+        validation_alias=AliasChoices(
+            "total_spend_by_currency", "spend_by_currency", "total_spend"
+        ),
+        description="Total spend grouped by original currency",
+    )
+    top_3_merchants: Dict[str, float] = Field(
+        validation_alias=AliasChoices("top_3_merchants", "top_merchants", "top_3"),
+        description="Top 3 merchants by spend volume (value in USD equivalent)",
+    )
+    anomaly_count: int = Field(
+        validation_alias=AliasChoices(
+            "anomaly_count", "total_anomalies", "anomalies", "anomaly_transactions"
+        ),
+        description="Total number of anomaly transactions flagged in the dataset",
+    )
+    spending_narrative: str = Field(
+        validation_alias=AliasChoices("spending_narrative", "narrative", "summary"),
+        description="A cohesive 2-3 sentence spending narrative",
+    )
+    risk_level: str = Field(
+        validation_alias=AliasChoices("risk_level", "overall_risk_level", "risk"),
+        description="Overall risk level: Low, Medium, or High",
+    )
+
+
+@time_it("LLM Job Narrative Summary Request")
+async def generate_job_summary_llm(
+    client: genai.Client,
+    db_transactions: List[Transaction],
+) -> Optional[JobNarrativeSummary]:
+    """
+    Calls the Gemini model to produce a structured JSON summary:
+    total spend by currency, top 3 merchants, anomaly count, a 2-3 sentence spending narrative, and a risk level.
+    """
+    # Build a simplified list of transactions for context
+    tx_data = [
+        {
+            "merchant": t.merchant,
+            "amount": t.amount,
+            "currency": t.currency,
+            "category": t.category,
+            "is_anomaly": t.is_anomaly,
+            "anomaly_reason": t.anomaly_reason,
+        }
+        for t in db_transactions
+    ]
+
+    input_prompt = (
+        "Analyze the following list of processed financial transactions and generate a structured JSON summary. "
+        "The returned JSON MUST contain exactly the following keys:\n"
+        '  - "total_spend_by_currency": dictionary mapping currency symbol/code to total amount spent (e.g. {"USD": 150.0, "INR": 25000.0})\n'
+        '  - "top_3_merchants": dictionary mapping the top 3 merchants by spend to their total spend value in USD equivalent (assuming 83 INR per USD for conversion)\n'
+        '  - "anomaly_count": integer showing the total count of flagged anomaly transactions (is_anomaly=True)\n'
+        '  - "spending_narrative": string containing a cohesive 2-3 sentence narrative summarizing key spending insights and largest merchants\n'
+        '  - "risk_level": string showing the overall risk level of the job: "Low", "Medium", or "High" (pick one based on the nature of anomalies)\n\n'
+        f"{json.dumps(tx_data, indent=2)}"
+    )
+
+    for attempt in range(1, 4):
+        try:
+            logger.info(
+                f"Calling LLM to generate job narrative summary (Attempt {attempt})..."
+            )
+            loop = asyncio.get_running_loop()
+            interaction = await loop.run_in_executor(
+                None,
+                lambda: client.interactions.create(
+                    model="gemini-2.5-flash-lite",
+                    input=input_prompt,
+                    response_format={
+                        "type": "text",
+                        "mime_type": "application/json",
+                        "schema": JobNarrativeSummary.model_json_schema(),
+                    },
+                ),
+            )
+            clean_text = clean_json_response(interaction.output_text)
+            resp_obj = JobNarrativeSummary.model_validate_json(clean_text)
+            return resp_obj
+        except Exception as e:
+            logger.warning(f"Failed to generate LLM summary (Attempt {attempt}): {e}")
+            if attempt == 3:
+                break
+            await asyncio.sleep(2)
+    return None
+
+
 # Define Celery app
 celery_app = Celery(
     "alemno_worker",
@@ -145,19 +256,26 @@ def process_transaction_job(job_id: str, transactions: List[Dict[str, Any]]):
     return run_async(_process_job_async(job_id, transactions))
 
 
+@time_it("Process Job Background Task")
 async def _process_job_async(job_id: str, transactions: List[Dict[str, Any]]):
-    async with AsyncSessionLocal() as db:
-        repo = JobRepository(db)
-        job = await repo.get_by_id(job_id)
-        if not job:
-            logger.error(f"Job with ID {job_id} not found in database.")
-            return
+    from app.db.session import engine
+
+    with benchmark("Dispose Engine"):
+        await engine.dispose()
+
+    async with AsyncSessionLocal() as db:
+        with benchmark("Initial Job Setup"):
+            repo = JobRepository(db)
+            job = await repo.get_by_id(job_id)
+            if not job:
+                logger.error(f"Job with ID {job_id} not found in database.")
+                return
 
-        try:
             # Update status to processing
             await repo.update(job, status="processing")
             await db.commit()
 
+        try:
             db_transactions = []
             total_spend_inr = 0.0
             total_spend_usd = 0.0
@@ -166,43 +284,44 @@ async def _process_job_async(job_id: str, transactions: List[Dict[str, Any]]):
 
             USD_TO_INR = await exchange_rate_client.get_usd_to_inr_rate()
 
-            # 1. Fetch existing transaction amounts and currencies for all accounts in this job to calculate median
-            account_ids = {
-                t.get("account_id") for t in transactions if t.get("account_id")
-            }
-            existing_amounts_inr = {}
-            if account_ids:
-                stmt = select(
-                    Transaction.account_id, Transaction.amount, Transaction.currency
-                ).where(Transaction.account_id.in_(account_ids))
-                res = await db.execute(stmt)
-                for acc_id, amt, curr in res.all():
-                    if acc_id not in existing_amounts_inr:
-                        existing_amounts_inr[acc_id] = []
-                    # Standardize to INR for median calculation
-                    amt_inr = amt * USD_TO_INR if curr.upper() == "USD" else amt
-                    existing_amounts_inr[acc_id].append(amt_inr)
+            with benchmark("Compute Account History Medians"):
+                # 1. Fetch existing transaction amounts and currencies for all accounts in this job to calculate median
+                account_ids = {
+                    t.get("account_id") for t in transactions if t.get("account_id")
+                }
+                existing_amounts_inr = {}
+                if account_ids:
+                    stmt = select(
+                        Transaction.account_id, Transaction.amount, Transaction.currency
+                    ).where(Transaction.account_id.in_(account_ids))
+                    res = await db.execute(stmt)
+                    for acc_id, amt, curr in res.all():
+                        if acc_id not in existing_amounts_inr:
+                            existing_amounts_inr[acc_id] = []
+                        # Standardize to INR for median calculation
+                        amt_inr = amt * USD_TO_INR if curr.upper() == "USD" else amt
+                        existing_amounts_inr[acc_id].append(amt_inr)
 
-            # Group incoming transaction amounts standardized to INR
-            incoming_amounts_inr = {}
-            for t in transactions:
-                acc_id = t.get("account_id")
-                if acc_id:
-                    if acc_id not in incoming_amounts_inr:
-                        incoming_amounts_inr[acc_id] = []
-                    amt = float(t["amount"])
-                    curr = t.get("currency", "INR").strip().upper()
-                    amt_inr = amt * USD_TO_INR if curr == "USD" else amt
-                    incoming_amounts_inr[acc_id].append(amt_inr)
+                # Group incoming transaction amounts standardized to INR
+                incoming_amounts_inr = {}
+                for t in transactions:
+                    acc_id = t.get("account_id")
+                    if acc_id:
+                        if acc_id not in incoming_amounts_inr:
+                            incoming_amounts_inr[acc_id] = []
+                        amt = float(t["amount"])
+                        curr = t.get("currency", "INR").strip().upper()
+                        amt_inr = amt * USD_TO_INR if curr == "USD" else amt
+                        incoming_amounts_inr[acc_id].append(amt_inr)
 
-            # Precalculate median of (existing + incoming) transactions in INR
-            account_medians_inr = {}
-            for acc_id in account_ids:
-                all_amts = existing_amounts_inr.get(
-                    acc_id, []
-                ) + incoming_amounts_inr.get(acc_id, [])
-                if all_amts:
-                    account_medians_inr[acc_id] = statistics.median(all_amts)
+                # Precalculate median of (existing + incoming) transactions in INR
+                account_medians_inr = {}
+                for acc_id in account_ids:
+                    all_amts = existing_amounts_inr.get(
+                        acc_id, []
+                    ) + incoming_amounts_inr.get(acc_id, [])
+                    if all_amts:
+                        account_medians_inr[acc_id] = statistics.median(all_amts)
 
             # 2. Call LLM to classify transactions without a category
             # Find all uncategorized incoming transactions
@@ -215,20 +334,62 @@ async def _process_job_async(job_id: str, transactions: List[Dict[str, Any]]):
             llm_results = {}
             api_key = settings.GEMINI_API_KEY or os.environ.get("GEMINI_API_KEY")
             if uncategorized_txns:
+                # Load allowed categories from the database categories table
+                from app.db.models.category import Category
+
+                try:
+                    res_cats = await db.execute(select(Category.name))
+                    allowed_categories = [r[0] for r in res_cats.all()]
+                except Exception as db_err:
+                    logger.warning(f"Could not load categories from database: {db_err}")
+                    allowed_categories = []
+
+                if not allowed_categories:
+                    allowed_categories = [
+                        "Food",
+                        "Shopping",
+                        "Travel",
+                        "Transport",
+                        "Utilities",
+                        "Cash Withdrawal",
+                        "Entertainment",
+                        "Other",
+                    ]
+
                 if api_key:
                     logger.info(
                         f"Found {len(uncategorized_txns)} uncategorized transactions. Initializing GenAI client..."
                     )
                     try:
                         client = genai.Client(api_key=api_key)
-                        # Batch transactions in chunks of 50
+                        # Split into batches of 50 and fire all concurrently
                         batch_size = 50
-                        for i in range(0, len(uncategorized_txns), batch_size):
-                            batch = uncategorized_txns[i : i + batch_size]
-                            batch_results = await classify_transactions_batch(
-                                client, batch
+                        batches = [
+                            uncategorized_txns[i : i + batch_size]
+                            for i in range(0, len(uncategorized_txns), batch_size)
+                        ]
+                        logger.info(
+                            f"Dispatching {len(batches)} classification batch(es) concurrently..."
+                        )
+                        with benchmark(
+                            "LLM Concurrent Batch Classification (all batches)"
+                        ):
+                            batch_results_list = await asyncio.gather(
+                                *[
+                                    classify_transactions_batch(
+                                        client, batch, allowed_categories
+                                    )
+                                    for batch in batches
+                                ],
+                                return_exceptions=True,
                             )
-                            llm_results.update(batch_results)
+                        for batch_result in batch_results_list:
+                            if isinstance(batch_result, Exception):
+                                logger.error(
+                                    f"A classification batch failed: {batch_result}"
+                                )
+                            else:
+                                llm_results.update(batch_result)
                     except Exception as e:
                         logger.error(
                             f"Failed to initialize GenAI Client or classify: {e}"
@@ -247,58 +408,92 @@ async def _process_job_async(job_id: str, transactions: List[Dict[str, Any]]):
                     # Mock categorization mapping based on merchant name keywords
                     for t in uncategorized_txns:
                         merchant_lower = t["merchant"].lower()
-                        cat = "Other"
-                        if any(
-                            kw in merchant_lower
-                            for kw in ["swiggy", "zomato", "restaurant", "cafe", "food"]
+                        cat = (
+                            "Other"
+                            if "Other" in allowed_categories
+                            else (
+                                allowed_categories[0] if allowed_categories else "Other"
+                            )
+                        )
+                        if (
+                            any(
+                                kw in merchant_lower
+                                for kw in [
+                                    "swiggy",
+                                    "zomato",
+                                    "restaurant",
+                                    "cafe",
+                                    "food",
+                                ]
+                            )
+                            and "Food" in allowed_categories
                         ):
                             cat = "Food"
-                        elif any(
-                            kw in merchant_lower
-                            for kw in ["ola", "uber", "taxi", "metro", "train"]
+                        elif (
+                            any(
+                                kw in merchant_lower
+                                for kw in ["ola", "uber", "taxi", "metro", "train"]
+                            )
+                            and "Transport" in allowed_categories
                         ):
                             cat = "Transport"
-                        elif any(
-                            kw in merchant_lower
-                            for kw in [
-                                "amazon",
-                                "flipkart",
-                                "shopping",
-                                "store",
-                                "supermarket",
-                            ]
+                        elif (
+                            any(
+                                kw in merchant_lower
+                                for kw in [
+                                    "amazon",
+                                    "flipkart",
+                                    "shopping",
+                                    "store",
+                                    "supermarket",
+                                ]
+                            )
+                            and "Shopping" in allowed_categories
                         ):
                             cat = "Shopping"
-                        elif any(
-                            kw in merchant_lower
-                            for kw in ["air", "flight", "hotel", "travel", "irctc"]
+                        elif (
+                            any(
+                                kw in merchant_lower
+                                for kw in ["air", "flight", "hotel", "travel", "irctc"]
+                            )
+                            and "Travel" in allowed_categories
                         ):
                             cat = "Travel"
-                        elif any(
-                            kw in merchant_lower
-                            for kw in [
-                                "electric",
-                                "power",
-                                "water",
-                                "bill",
-                                "utility",
-                                "utilities",
-                            ]
+                        elif (
+                            any(
+                                kw in merchant_lower
+                                for kw in [
+                                    "electric",
+                                    "power",
+                                    "water",
+                                    "bill",
+                                    "utility",
+                                    "utilities",
+                                ]
+                            )
+                            and "Utilities" in allowed_categories
                         ):
                             cat = "Utilities"
-                        elif any(
-                            kw in merchant_lower for kw in ["atm", "cash", "withdrawal"]
+                        elif (
+                            any(
+                                kw in merchant_lower
+                                for kw in ["atm", "cash", "withdrawal"]
+                            )
+                            and "Cash Withdrawal" in allowed_categories
                         ):
                             cat = "Cash Withdrawal"
-                        elif any(
-                            kw in merchant_lower
-                            for kw in [
-                                "netflix",
-                                "spotify",
-                                "movie",
-                                "show",
-                                "entertainment",
-                            ]
+                        elif (
+                            any(
+                                kw in merchant_lower
+                                for kw in [
+                                    "netflix",
+                                    "spotify",
+                                    "movie",
+                                    "show",
+                                    "entertainment",
+                                ]
+                            )
+                            and "Entertainment" in allowed_categories
                         ):
                             cat = "Entertainment"
 
@@ -412,55 +607,84 @@ async def _process_job_async(job_id: str, transactions: List[Dict[str, Any]]):
                 )
                 db_transactions.append(db_txn)
 
-            await repo.add_transactions(db_transactions)
+            with benchmark("Save Cleaned Transactions to DB"):
+                await repo.add_transactions(db_transactions)
 
-            top_merchant = (
-                max(merchant_spends, key=merchant_spends.get)
-                if merchant_spends
-                else "None"
-            )
-            risk_level = "Low"
-            if anomaly_count > 2:
-                risk_level = "High"
-            elif anomaly_count > 0:
-                risk_level = "Medium"
+            # Generate narrative and risk summary using LLM if api_key is available
+            llm_summary = None
+            if api_key:
+                try:
+                    client = genai.Client(api_key=api_key)
+                    llm_summary = await generate_job_summary_llm(
+                        client, db_transactions
+                    )
+                except Exception as e:
+                    logger.error(f"Error in LLM summary generation: {e}")
 
-            narrative = (
-                f"Successfully parsed and clean-processed {len(transactions)} transaction records. "
-                f"Total spend is INR {total_spend_inr:,.2f} (${total_spend_usd:,.2f} USD). "
-                f"Top merchant by spend volume is '{top_merchant}' with total of ${merchant_spends.get(top_merchant, 0):,.2f} USD. "
-                f"Scan flagged {anomaly_count} potential anomalies, resulting in a overall risk level of '{risk_level}'."
-            )
+            if llm_summary:
+                # Normalize risk level value to match capitalized Low/Medium/High in our DB
+                risk_level_str = llm_summary.risk_level.strip().lower()
+                if risk_level_str == "high":
+                    risk_level = "High"
+                elif risk_level_str == "medium":
+                    risk_level = "Medium"
+                else:
+                    risk_level = "Low"
 
-            # Build top merchants dict sorted by spend limit (keep top 5)
-            sorted_merchants = sorted(
-                merchant_spends.items(), key=lambda x: x[1], reverse=True
-            )[:5]
-            top_merchants_json = {
-                merchant: round(spend, 2) for merchant, spend in sorted_merchants
-            }
+                narrative = llm_summary.spending_narrative.strip()
+                top_merchants_json = {
+                    merchant: round(spend, 2)
+                    for merchant, spend in llm_summary.top_3_merchants.items()
+                }
+                anomaly_count = llm_summary.anomaly_count
+            else:
+                top_merchant = (
+                    max(merchant_spends, key=merchant_spends.get)
+                    if merchant_spends
+                    else "None"
+                )
+                risk_level = "Low"
+                if anomaly_count > 2:
+                    risk_level = "High"
+                elif anomaly_count > 0:
+                    risk_level = "Medium"
+
+                narrative = (
+                    f"Successfully parsed and clean-processed {len(transactions)} transaction records. "
+                    f"Total spend is INR {total_spend_inr:,.2f} (${total_spend_usd:,.2f} USD). "
+                    f"Top merchant by spend volume is '{top_merchant}' with total of ${merchant_spends.get(top_merchant, 0):,.2f} USD. "
+                    f"Scan flagged {anomaly_count} potential anomalies, resulting in a overall risk level of '{risk_level}'."
+                )
+
+                sorted_merchants = sorted(
+                    merchant_spends.items(), key=lambda x: x[1], reverse=True
+                )[:3]
+                top_merchants_json = {
+                    merchant: round(spend, 2) for merchant, spend in sorted_merchants
+                }
 
             # Create job summary
-            summary = JobSummary(
-                job_id=job_id,
-                total_spend_inr=round(total_spend_inr, 2),
-                total_spend_usd=round(total_spend_usd, 2),
-                top_merchants=top_merchants_json,
-                anomaly_count=anomaly_count,
-                narrative=narrative,
-                risk_level=risk_level,
-            )
-            await repo.add_summary(summary)
+            with benchmark("Save Summary and Complete Job"):
+                summary = JobSummary(
+                    job_id=job_id,
+                    total_spend_inr=round(total_spend_inr, 2),
+                    total_spend_usd=round(total_spend_usd, 2),
+                    top_merchants=top_merchants_json,
+                    anomaly_count=anomaly_count,
+                    narrative=narrative,
+                    risk_level=risk_level,
+                )
+                await repo.add_summary(summary)
 
-            # Update job state
-            await repo.update(
-                job,
-                status="completed",
-                row_count_raw=len(transactions),
-                row_count_clean=len(db_transactions),
-                completed_at=datetime.utcnow(),
-            )
-            await db.commit()
+                # Update job state
+                await repo.update(
+                    job,
+                    status="completed",
+                    row_count_raw=len(transactions),
+                    row_count_clean=len(db_transactions),
+                    completed_at=datetime.utcnow(),
+                )
+                await db.commit()
             logger.info(f"Job {job_id} processing completed successfully.")
 
         except Exception as e:

coverage.xml

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+					</lines>
+				</class>
+				<class name="job_summary.py" filename="db/models/job_summary.py" complexity="0" line-rate="1" branch-rate="0">
+					<methods/>
+					<lines>
+						<line number="1" hits="1"/>
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+				</class>
+				<class name="transaction.py" filename="db/models/transaction.py" complexity="0" line-rate="1" branch-rate="0">
+					<methods/>
+					<lines>
+						<line number="1" hits="1"/>
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+						<line number="39" hits="1"/>
+						<line number="40" hits="1"/>
+						<line number="43" hits="1"/>
+					</lines>
+				</class>
+			</classes>
+		</package>
+		<package name="repositories" line-rate="0.4262" branch-rate="0" complexity="0">
+			<classes>
+				<class name="__init__.py" filename="repositories/__init__.py" complexity="0" line-rate="1" branch-rate="0">
+					<methods/>
+					<lines>
+						<line number="1" hits="1"/>
+						<line number="3" hits="1"/>
+					</lines>
+				</class>
+				<class name="category_repository.py" filename="repositories/category_repository.py" complexity="0" line-rate="0.45" branch-rate="0">
+					<methods/>
+					<lines>
+						<line number="1" hits="1"/>
+						<line number="2" hits="1"/>
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+						<line number="24" hits="1"/>
+						<line number="26" hits="0"/>
+						<line number="27" hits="0"/>
+						<line number="28" hits="0"/>
+					</lines>
+				</class>
+				<class name="job_repository.py" filename="repositories/job_repository.py" complexity="0" line-rate="0.3846" branch-rate="0">
+					<methods/>
+					<lines>
+						<line number="1" hits="1"/>
+						<line number="2" hits="1"/>
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+						<line number="53" hits="1"/>
+						<line number="55" hits="0"/>
+						<line number="56" hits="0"/>
+						<line number="57" hits="0"/>
+					</lines>
+				</class>
+			</classes>
+		</package>
+		<package name="schemas" line-rate="1" branch-rate="0" complexity="0">
+			<classes>
+				<class name="__init__.py" filename="schemas/__init__.py" complexity="0" line-rate="1" branch-rate="0">
+					<methods/>
+					<lines>
+						<line number="1" hits="1"/>
+						<line number="10" hits="1"/>
+					</lines>
+				</class>
+				<class name="category.py" filename="schemas/category.py" complexity="0" line-rate="1" branch-rate="0">
+					<methods/>
+					<lines>
+						<line number="1" hits="1"/>
+						<line number="4" hits="1"/>
+						<line number="5" hits="1"/>
+						<line number="10" hits="1"/>
+						<line number="11" hits="1"/>
+						<line number="14" hits="1"/>
+						<line number="17" hits="1"/>
+					</lines>
+				</class>
+				<class name="job.py" filename="schemas/job.py" complexity="0" line-rate="1" branch-rate="0">
+					<methods/>
+					<lines>
+						<line number="1" hits="1"/>
+						<line number="2" hits="1"/>
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+						<line number="68" hits="1"/>
+						<line number="72" hits="1"/>
+						<line number="73" hits="1"/>
+					</lines>
+				</class>
+			</classes>
+		</package>
+		<package name="services" line-rate="0.4894" branch-rate="0" complexity="0">
+			<classes>
+				<class name="__init__.py" filename="services/__init__.py" complexity="0" line-rate="1" branch-rate="0">
+					<methods/>
+					<lines>
+						<line number="1" hits="1"/>
+						<line number="3" hits="1"/>
+					</lines>
+				</class>
+				<class name="category_service.py" filename="services/category_service.py" complexity="0" line-rate="0.4737" branch-rate="0">
+					<methods/>
+					<lines>
+						<line number="1" hits="1"/>
+						<line number="2" hits="1"/>
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+						<line number="24" hits="0"/>
+						<line number="25" hits="0"/>
+						<line number="26" hits="0"/>
+					</lines>
+				</class>
+				<class name="job_service.py" filename="services/job_service.py" complexity="0" line-rate="0.4615" branch-rate="0">
+					<methods/>
+					<lines>
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+						<line number="31" hits="0"/>
+						<line number="32" hits="0"/>
+						<line number="34" hits="1"/>
+						<line number="35" hits="0"/>
+					</lines>
+				</class>
+			</classes>
+		</package>
+		<package name="utils" line-rate="0.8857" branch-rate="0" complexity="0">
+			<classes>
+				<class name="csv_parser.py" filename="utils/csv_parser.py" complexity="0" line-rate="0.8857" branch-rate="0">
+					<methods/>
+					<lines>
+						<line number="1" hits="1"/>
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+						<line number="109" hits="1"/>
+						<line number="111" hits="1"/>
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+						<line number="116" hits="1"/>
+						<line number="128" hits="1"/>
+						<line number="129" hits="0"/>
+						<line number="131" hits="1"/>
+					</lines>
+				</class>
+			</classes>
+		</package>
+	</packages>
+</coverage>

pyproject.toml

@@ -27,4 +27,5 @@ asyncio_mode = "auto"
 [dependency-groups]
 dev = [
     "ruff>=0.15.20",
+    "pytest-cov>=6.0.0",
 ]

tests/api/test_categories_api.py

@@ -0,0 +1,32 @@
+import pytest
+from httpx import AsyncClient
+
+pytestmark = pytest.mark.asyncio
+
+
+async def test_get_categories_seeded_defaults(client: AsyncClient):
+    # Retrieve categories and verify the default list is present (since lifespan seeds them)
+    response = await client.get("/api/v1/categories")
+    assert response.status_code == 200
+    categories = response.json()
+    assert len(categories) >= 8
+
+    names = [c["name"] for c in categories]
+    assert "Food" in names
+    assert "Shopping" in names
+    assert "Travel" in names
+    assert "Other" in names
+
+
+async def test_create_and_duplicate_category(client: AsyncClient):
+    # 1. Create a new category
+    response = await client.post("/api/v1/categories", json={"name": "Medical"})
+    assert response.status_code == 201
+    data = response.json()
+    assert "id" in data
+    assert data["name"] == "Medical"
+
+    # 2. Try creating the same category (duplicate, case-insensitive check)
+    dup_response = await client.post("/api/v1/categories", json={"name": "medical"})
+    assert dup_response.status_code == 400
+    assert "already exists" in dup_response.json()["detail"]

tests/conftest.py

@@ -46,6 +46,24 @@ def initialize_test_db():
             await conn.run_sync(Base.metadata.drop_all)
             await conn.run_sync(Base.metadata.create_all)
 
+        # Seed categories in test DB
+        from sqlalchemy.ext.asyncio import AsyncSession
+        from app.db.models.category import Category
+
+        async with AsyncSession(test_engine) as session:
+            defaults = [
+                Category(name="Food"),
+                Category(name="Shopping"),
+                Category(name="Travel"),
+                Category(name="Transport"),
+                Category(name="Utilities"),
+                Category(name="Cash Withdrawal"),
+                Category(name="Entertainment"),
+                Category(name="Other"),
+            ]
+            session.add_all(defaults)
+            await session.commit()
+
     async def teardown_db():
         async with test_engine.begin() as conn:
             await conn.run_sync(Base.metadata.drop_all)

tests/services/test_benchmarker.py

@@ -0,0 +1,53 @@
+import pytest
+import asyncio
+from app.core.observability import benchmark, time_it
+
+
+def test_benchmark_context_manager(caplog):
+    import logging
+
+    with caplog.at_level(logging.INFO):
+        with benchmark("Test Task"):
+            # simulate work
+            pass
+
+    assert any(
+        "[BENCHMARK] Test Task completed in" in record.message
+        for record in caplog.records
+    )
+
+
+def test_time_it_decorator_sync(caplog):
+    import logging
+
+    @time_it("Sync Helper")
+    def my_sync_fn(x, y):
+        return x + y
+
+    with caplog.at_level(logging.INFO):
+        res = my_sync_fn(10, 20)
+
+    assert res == 30
+    assert any(
+        "[BENCHMARK] Sync Helper completed in" in record.message
+        for record in caplog.records
+    )
+
+
+@pytest.mark.asyncio
+async def test_time_it_decorator_async(caplog):
+    import logging
+
+    @time_it("Async Helper")
+    async def my_async_fn():
+        await asyncio.sleep(0.01)
+        return "done"
+
+    with caplog.at_level(logging.INFO):
+        res = await my_async_fn()
+
+    assert res == "done"
+    assert any(
+        "[BENCHMARK] Async Helper completed in" in record.message
+        for record in caplog.records
+    )

tests/services/test_llm_classification.py

@@ -18,7 +18,9 @@ async def test_classify_transactions_batch_retry_success():
         {"txn_id": "TX2", "merchant": "Amazon", "amount": 1200.0},
     ]
 
-    results = await classify_transactions_batch(mock_client, batch_txns)
+    results = await classify_transactions_batch(
+        mock_client, batch_txns, ["Food", "Shopping", "Other"]
+    )
     assert len(results) == 2
     assert results["TX1"]["category"] == "Food"
     assert results["TX1"]["failed"] is False
@@ -37,7 +39,9 @@ async def test_classify_transactions_batch_retry_failure():
 
     # Patch sleep to make retry test run instantly
     with patch("asyncio.sleep", return_value=None):
-        results = await classify_transactions_batch(mock_client, batch_txns)
+        results = await classify_transactions_batch(
+            mock_client, batch_txns, ["Food", "Shopping", "Other"]
+        )
 
     assert len(results) == 1
     assert results["TX1"]["category"] == "Other"

tests/services/test_llm_summary.py

@@ -0,0 +1,77 @@
+import pytest
+from app.worker import generate_job_summary_llm, clean_json_response
+from app.db.models.transaction import Transaction
+from google import genai
+from unittest.mock import MagicMock, patch
+
+
+def test_clean_json_response_markdown():
+    # Test stripping markdown code fences
+    dirty_json = '```json\n{"key": "value"}\n```'
+    assert clean_json_response(dirty_json) == '{"key": "value"}'
+
+    # Test stripping markdown code fences with conversational prefix
+    dirty_conversational = (
+        'Here is the data:\n```\n{"key": "value"}\n```\nHope it helps.'
+    )
+    assert clean_json_response(dirty_conversational) == '{"key": "value"}'
+
+
+@pytest.mark.asyncio
+async def test_generate_job_summary_llm_success():
+    # 1. Setup mock transactions
+    t1 = Transaction(
+        merchant="Zomato",
+        amount=100.0,
+        currency="USD",
+        category="Food",
+        is_anomaly=False,
+    )
+    t2 = Transaction(
+        merchant="Ola",
+        amount=2500.0,
+        currency="INR",
+        category="Transport",
+        is_anomaly=True,
+        anomaly_reason="Outlier",
+    )
+    tx_list = [t1, t2]
+
+    # 2. Mock client and return json
+    mock_client = MagicMock(spec=genai.Client)
+    mock_interaction = MagicMock()
+    mock_interaction.output_text = """
+    ```json
+    {
+      "total_spend_by_currency": {"USD": 100.0, "INR": 2500.0},
+      "top_3_merchants": {"Ola": 30.12, "Zomato": 100.0},
+      "anomaly_count": 1,
+      "spending_narrative": "Cohesive two sentence summary of spendings. Mostly food and transit.",
+      "risk_level": "Medium"
+    }
+    ```
+    """
+    mock_client.interactions.create.return_value = mock_interaction
+
+    # 3. Call and assert
+    result = await generate_job_summary_llm(mock_client, tx_list)
+    assert result is not None
+    assert result.anomaly_count == 1
+    assert result.risk_level == "Medium"
+    assert result.total_spend_by_currency["USD"] == 100.0
+    assert result.total_spend_by_currency["INR"] == 2500.0
+    assert "Ola" in result.top_3_merchants
+
+
+@pytest.mark.asyncio
+async def test_generate_job_summary_llm_retry_failure():
+    mock_client = MagicMock(spec=genai.Client)
+    mock_client.interactions.create.side_effect = Exception("API Key Expired")
+
+    tx_list = [Transaction(merchant="Test", amount=1.0, currency="USD")]
+
+    # Patch sleep to execute instantly
+    with patch("asyncio.sleep", return_value=None):
+        result = await generate_job_summary_llm(mock_client, tx_list)
+
+    assert result is None

transactions.csv

@@ -0,0 +1,96 @@
+txn_id,date,merchant,amount,currency,status,category,account_id,notes
+TXN1065,04-09-2024,Flipkart,10882.55,INR,SUCCESS,Shopping,ACC003,Refund expected
+TXN1054,2024/02/05,Swiggy,$11325.79,INR,success,Food,ACC004,
+TXN1021,17-02-2024,Zomato,2536.35,USD,SUCCESS,Food,ACC001,Verified
+TXN1045,07-05-2024,Amazon,6874.1,INR,failed,Shopping,ACC004,SUSPICIOUS
+TXN1076,14-08-2024,Flipkart,2763.26,INR,SUCCESS,Shopping,ACC004,Duplicate?
+TXN1029,19-05-2024,Flipkart,9092.21,INR,FAILED,Shopping,ACC003,
+TXN1004,04-07-2024,Jio Recharge,2924.71,INR,SUCCESS,Utilities,ACC001,Verified
+TXN1002,2024/01/04,HDFC ATM,10487.18,INR,FAILED,Cash Withdrawal,ACC004,
+TXN1000,23-11-2024,Dentist Appointment Fee,423.91,INR,failed,,ACC004,
+TXN1073,16-05-2024,HDFC ATM,1117.58,INR,failed,Cash Withdrawal,ACC004,
+TXN1019,26-11-2024,Amazon,956.16,INR,success,Shopping,ACC004,Refund expected
+TXN1006,24-03-2024,IRCTC,5722.86,INR,FAILED,Travel,ACC001,Refund expected
+TXN1014,2024/09/05,Amazon,14670.87,INR,failed,Shopping,ACC005,
+TXN1009,11-03-2024,MakeMyTrip,7428.06,USD,success,Travel,ACC004,SUSPICIOUS
+TXN1066,2024/06/03,Swiggy,10634.88,INR,FAILED,Food,ACC002,
+TXN1071,09-10-2024,Amazon,2390.16,INR,SUCCESS,Shopping,ACC003,
+TXN1044,16-03-2024,Swiggy,13395.26,INR,success,Food,ACC005,Verified
+TXN1047,2024/09/23,IRCTC,9419.89,INR,FAILED,Travel,ACC005,
+TXN1068,03-02-2024,Ola,7401.61,inr,failed,Transport,ACC001,Refund expected
+TXN1077,23-02-2024,HDFC ATM,4980.56,INR,failed,,ACC001,Duplicate?
+TXN1060,22-05-2024,IRCTC,3695.76,INR,SUCCESS,Travel,ACC003,Refund expected
+TXN1009,11-03-2024,MakeMyTrip,7428.06,USD,success,Travel,ACC004,SUSPICIOUS
+TXN1033,13-10-2024,Ola,14608.86,inr,success,Transport,ACC002,Verified
+TXN1059,29-11-2024,Flipkart,9257.89,INR,failed,Shopping,ACC002,
+TXN1034,19-06-2024,Ola,12043.42,inr,SUCCESS,Transport,ACC001,
+TXN1062,27-07-2024,IRCTC,8349.88,INR,PENDING,Travel,ACC001,Duplicate?
+TXN1042,20-09-2024,Jio Recharge,5061.06,INR,success,Utilities,ACC002,
+TXN1023,2024/10/23,MakeMyTrip,961.32,USD,failed,Travel,ACC005,
+TXN1011,16-05-2024,BookMyShow,1717.7,INR,FAILED,Entertainment,ACC002,SUSPICIOUS
+,25-06-2024,Jio Recharge,4004.59,INR,PENDING,,ACC003,
+TXN1020,22-05-2024,IRCTC,3784.61,INR,failed,,ACC005,
+TXN1064,20-08-2024,Flipkart,4634.01,INR,failed,Shopping,ACC002,Refund expected
+TXN1025,02-08-2024,Jio Recharge,8500.14,INR,FAILED,Utilities,ACC004,Refund expected
+TXN1069,01-08-2024,Jio Recharge,8962.1,INR,PENDING,Utilities,ACC005,Verified
+TXN1024,05-02-2024,Jio Recharge,1066.01,INR,failed,Utilities,ACC005,
+TXN1005,21-11-2024,BookMyShow,2481.68,INR,SUCCESS,Entertainment,ACC002,SUSPICIOUS
+TXN1018,30-08-2024,Ola,2896.63,inr,PENDING,Transport,ACC001,
+TXN1032,06-03-2024,Swiggy,4658.46,INR,FAILED,Food,ACC002,
+TXN1028,30-11-2024,MakeMyTrip,166.96,USD,success,Travel,ACC001,
+TXN1070,13-11-2024,Swiggy,9163.98,INR,success,Food,ACC001,Refund expected
+TXN1043,31-08-2024,Jio Recharge,12753.58,INR,success,Utilities,ACC004,Verified
+TXN1079,12-09-2024,IRCTC,11411.86,INR,PENDING,Travel,ACC004,
+TXN1008,25-11-2024,IRCTC,2185.93,INR,failed,Travel,ACC005,Verified
+TXN1035,12-04-2024,IRCTC,5277.39,INR,success,Travel,ACC003,
+TXN1072,06-02-2024,Zomato,13862.47,USD,success,Food,ACC005,Refund expected
+TXN1039,15-11-2024,BookMyShow,9967.64,INR,PENDING,Entertainment,ACC003,SUSPICIOUS
+TXN1079,12-09-2024,IRCTC,11411.86,INR,PENDING,Travel,ACC004,
+TXN1038,07-04-2024,Flipkart,713.58,INR,success,Shopping,ACC001,
+TXN1026,2024/06/02,IRCTC,4776.85,INR,failed,Travel,ACC001,SUSPICIOUS
+TXN1040,03-08-2024,Ola,10175.9,inr,failed,Transport,ACC003,Duplicate?
+TXN1058,2024/06/23,Swiggy,12751.16,INR,PENDING,Food,ACC004,Refund expected
+,2024/04/21,Zomato,7605.06,USD,failed,Food,ACC004,SUSPICIOUS
+TXN1022,20-08-2024,Flipkart,6373.96,INR,PENDING,Shopping,ACC003,Refund expected
+TXN1075,16-02-2024,Zomato,14430.57,USD,FAILED,Food,ACC002,Verified
+TXN1012,2024/11/16,Flipkart,12632.96,INR,success,Shopping,ACC005,
+TXN1074,04-06-2024,Ola,14143.01,inr,SUCCESS,Transport,ACC003,SUSPICIOUS
+TXN1063,20-12-2024,Zomato,4627.78,USD,PENDING,Food,ACC005,Duplicate?
+TXN1013,07-09-2024,Swiggy,1722.42,INR,success,,ACC005,
+TXN1057,03-06-2024,Jio Recharge,$12092.64,INR,failed,Utilities,ACC003,
+TXN1010,14-07-2024,Jio Recharge,14942.01,INR,SUCCESS,Utilities,ACC001,
+TXN1046,15-09-2024,Ola,12467.01,inr,PENDING,Transport,ACC002,
+TXN1017,17-01-2024,BookMyShow,1109.32,INR,success,Entertainment,ACC005,SUSPICIOUS
+TXN1050,02-08-2024,MakeMyTrip,11225.36,USD,success,Travel,ACC004,
+TXN1078,2024/02/29,Ola,12980.41,inr,PENDING,Transport,ACC002,SUSPICIOUS
+TXN1041,23-10-2024,Jio Recharge,9837.85,INR,PENDING,Utilities,ACC002,
+TXN1035,12-04-2024,IRCTC,5277.39,INR,success,Travel,ACC003,
+TXN1037,15-05-2024,Swiggy,1670.62,INR,failed,Food,ACC001,Verified
+TXN2003,2024-07-15,IRCTC,193647.29,INR,SUCCESS,,ACC002,
+TXN1048,2024/04/28,Ola,10424.55,inr,failed,Transport,ACC001,Refund expected
+TXN1016,25-04-2024,Amazon,5104.38,INR,SUCCESS,Shopping,ACC001,Refund expected
+TXN1053,13-07-2024,Flipkart,11292.55,INR,SUCCESS,Shopping,ACC001,Duplicate?
+TXN1033,13-10-2024,Ola,14608.86,inr,success,Transport,ACC002,Verified
+TXN1031,14-10-2024,Swiggy,1722.51,INR,SUCCESS,Food,ACC005,SUSPICIOUS
+TXN1000_DUP,23-11-2024,Amazon,423.91,INR,failed,,ACC004,
+TXN2002,2024-07-15,Ola,91185.1,INR,SUCCESS,,ACC001,
+TXN1055,2024/04/21,IRCTC,10507.0,INR,SUCCESS,Travel,ACC002,Duplicate?
+TXN1036,22-05-2024,BookMyShow,9640.15,INR,SUCCESS,Entertainment,ACC003,Refund expected
+TXN2001,2024-07-15,Flipkart,146100.68,INR,SUCCESS,,ACC005,
+,20-11-2024,Ola,12448.75,inr,FAILED,Transport,ACC004,SUSPICIOUS
+TXN1007,10-06-2024,Ola,4052.73,inr,FAILED,Transport,ACC004,Verified
+TXN1015,18-04-2024,MakeMyTrip,11341.21,USD,FAILED,Travel,ACC005,Verified
+TXN2004,2024-07-15,IRCTC,191918.37,INR,SUCCESS,,ACC003,
+TXN1067,08-09-2024,Amazon,13097.16,INR,success,Shopping,ACC003,
+TXN1020,22-05-2024,IRCTC,3784.61,INR,failed,,ACC005,
+TXN1042,20-09-2024,Jio Recharge,5061.06,INR,success,Utilities,ACC002,
+TXN1016,25-04-2024,Amazon,5104.38,INR,SUCCESS,Shopping,ACC001,Refund expected
+TXN1061,30-06-2024,Flipkart,5138.07,INR,SUCCESS,Shopping,ACC002,
+,18-07-2024,Jio Recharge,14193.63,INR,PENDING,,ACC003,Duplicate?
+TXN1027,15-05-2024,HDFC ATM,14002.23,INR,success,Cash Withdrawal,ACC005,
+TXN1051,08-12-2024,Ola,10876.51,inr,failed,,ACC004,SUSPICIOUS
+TXN1052,14-01-2024,Amazon,9659.11,INR,PENDING,Shopping,ACC004,Duplicate?
+TXN1044,16-03-2024,Swiggy,13395.26,INR,success,Food,ACC005,Verified
+TXN1029,19-05-2024,Flipkart,9092.21,INR,FAILED,Shopping,ACC003,
+TXN2000,2024-07-15,Jio Recharge,175917.65,INR,SUCCESS,,ACC002,
+TXN1056,14-01-2024,Flipkart,8658.16,INR,success,,ACC002,

uv.lock

@@ -24,6 +24,7 @@ dependencies = [
 
 [package.dev-dependencies]
 dev = [
+    { name = "pytest-cov" },
     { name = "ruff" },
 ]
 
@@ -45,7 +46,10 @@ requires-dist = [
 ]
 
 [package.metadata.requires-dev]
-dev = [{ name = "ruff", specifier = ">=0.15.20" }]
+dev = [
+    { name = "pytest-cov", specifier = ">=6.0.0" },
+    { name = "ruff", specifier = ">=0.15.20" },
+]
 
 [[package]]
 name = "amqp"
@@ -283,6 +287,45 @@ wheels = [
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 ]
 
+[[package]]
+name = "coverage"
+version = "7.15.0"
+source = { registry = "https://pypi.org/simple" }
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+wheels = [
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+    { url = "https://files.pythonhosted.org/packages/09/37/f718613d83b274880382f6b67e78f3802549ae39b0b3e65ae5b5974df56e/coverage-7.15.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:7d2008989ef8fe54188d3f3bfa2e3099b025af11e90a6a1b9e7dc433d04263d8", size = 221239, upload-time = "2026-07-02T13:09:53.138Z" },
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