RAG Technique Uses Live News APIs to Reduce Chatbot Hallucinations on Current Events

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Large language models frequently produce outdated or fabricated answers about recent events because their training data has a fixed cutoff date. A retrieval-augmented generation (RAG) approach addresses this by fetching live news articles at query time and injecting them into the model's prompt as context. NewsAgent Data offers an API that delivers pre-classified, real-time news articles enriched with urgency scores, political lean, topic tags, and event cluster IDs. The service aggregates roughly 3,000 public Telegram channels alongside RSS feeds, with deepest coverage in English and Russian, and offers a free tier of 100 requests per day. Developers can integrate it directly into chatbots or AI agents via a REST API or an MCP server, though the company notes that grounding reduces but does not fully eliminate hallucinations.

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