Next.js marketplace website · FastAPI · PostgreSQL
Polka marketplace
A storefront needs both a catalog and an answer to “what do you have under 3,000”. Here a phrase becomes filters, and a price in the answer is taken from the product stored in the database. The order is saved in PostgreSQL and opens in the account by phone.
Scenario: Polka marketplace from Kazan — fictional: six workshops, one hundred home goods, a warehouse in the same city.
Open the demo
Type “lamp under 3000” or ask the consultant “I want an elephant” — there isn’t one in the catalog, and it says so. Place an order and sign in to the account with the code 4237: the order comes from the database. The order and a question to a seller appear in the owner dashboard.
Leads from the demo website are visible only to you, in the “Owner dashboard”: the server validates the form and stores nothing.
What the demo shows
How to try it
Search in words
On the first screen type “lamp under 3000” or open “linen throw”. Above the grid the catalog says how the request was read.
Ask the consultant
The “Ask Polka” button is at the bottom left. Ask “I want an elephant”, then “how much is delivery”.
Look at similar items
Open a product and the “Similar” block. Two items in the catalog have “Add to cart” closed: they are out of stock.
Place an order
On the Delivery page choose a point in Kazan — it is filled into the cart and delivery becomes free. By courier, a product under 5,000 ₽ costs 390 ₽. The order number looks like ПК-0001.
Open the route
On “Where is the order” enter the number. Stages follow the checkout time: accepted, packed, on the way, then a point or a courier. No warehouse is connected.
Open the account
Sign in as Anna, code 4237. The overview shows the order from the database. From there you can repeat the order, leave a return request, and open saves, viewed items and addresses.
No paid neural networks
There are no paid neural network requests: a phrase is parsed by rules on the server — category, colour, “under” and “from” with a price, word forms such as “linen”. The consultant names only products that passed that filter, and their price from the database. In a production version a language model follows the same scheme, with the catalog, stock and delivery given to it as tools — it won’t invent a product or quote someone else’s price. The workshops, goods and demo orders are fictional.
The demo runs without OpenAI, YandexGPT or GigaChat API keys. Wherever a production system calls a model, there’s a local stub with the same interface — so the demo is free, always available and never makes things up.
What a production project adds
- Catalog, stock and prices from the sellers’ inventory or a PIM, the order in an OMS. Payment via acquiring and SBP (Russia’s Faster Payments System), a receipt under 54-FZ
- Points and tracking via a CDEK or other carrier API: a tariff, a point map and shipment statuses. Here the stages are counted from the order time
- Search and the consultant — a language model (YandexGPT or GigaChat) with the catalog, stock and delivery rules as tools
- The account — by phone and a code, or SMS sign-in. Saves and the cart can live on the server, not only in the browser
- Requests from the account and questions to a seller go to a CRM, and the seller gets a notification
Stack
- All demos by stack:
- Next.js
- TypeScript
- Python
- Next.js 16
- React 19
- TypeScript
- Tailwind CSS 4
- FastAPI
- PostgreSQL
Want the same for your business?
Tell me about your task — I’ll tell you what from the demo fits, how long it will take and what I’ll need from you.
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