New Indexer Database Architecture

TON CoreVerified, @toncore

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New Indexer Database Architecture The database has been divided into three tiers: Hot — transactions from the last week; Cold — the complete transaction history; Key-Value — states, BOCs, and metadata. This makes processing queries to recent data, which account for most of the load, 2–4× faster. The architecture is already used in toncenter.com/api/v3 and will later be available as a standalone build. API V2 Hardware Update The API V2 server infrastructure for direct requests to liteservers has been upgraded. New Features — A new API for nominator pools. — A new API for validation cycles, including elections and complaints. — Support for new DeDust V2 actions. — Fixes and Improvements. NFT Content Filtering As network fees have decreased, the risk of spam and inappropriate content being distributed through NFTs has increased. Toncenter has implemented a manual blacklist for individual NFTs and collections and is developing an automated LLM-based analyzer. Inappropriate pics will be displayed in a blurred form.

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    LLM-based content moderation in Toncenter API Toncenter API now automatically filters inappropriate token images (NFTs and Jettons) using an LLM-based moderation system. Following the reduction in TON transaction fees, spam and inappropriate content distributed as NFTs have become more noticeable on the network. Building on its existing manual moderation tools, Toncenter has introduced an LLM-based image analyzer. Images flagged as inappropriate are now served by the API in blurred form. No changes are required for services already using Toncenter API. Guidelines for Services Toncenter API v3 metadata includes the following fields to help services handle potentially unsafe or malicious tokens: - is_nsfw — marks tokens that have been identified as unsafe or potentially unsafe; - is_scam — marks tokens associated with scams or spam; - extra._image_big, extra._image_medium, and extra._image_small — contain links to processed token images. Images are resized to standard presets and automatically blurred when a token is marked as unsafe. To better protect users, we recommend using an opt-in approach when displaying tokens in wallets, explorers, and other services. By default, show only well-known or trusted tokens and their images. Other tokens and their images should be displayed only after the user explicitly chooses to enable them. Please note: LLM-based filtering provides an additional layer of protection, but no automated filtering system can guarantee 100% accuracy. Both false negatives and false positives may occur.

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