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Source channel @githubtrending · Post #14993 · Jul 24

#jupyter_notebook Retrieval Augmented Generation (RAG) helps large language models (LLMs) answer questions using up-to-date or private information by connecting them to external data sources, unlike fine-tuning which retrains the model on specific data. RAG is useful when you need current, dynamic information without costly retraining, making it ideal for tasks like customer support or knowledge management. Fine-tuning is better for deep expertise in a specialized field but requires more data and effort. Using RAG lets you get accurate, relevant answers quickly by combining the model’s language skills with fresh, specific data, improving usefulness and reliability. https://github.com/langchain-ai/rag-from-scratch

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TONlines – News

@tonlines · Post #7071 · 05/06/2025, 04:49 PM

Tribute Empowers Creators with Public API Access #Tribute#webhooks @TributeNewsEN introduces public API access keys, allowing for seamless data integration with external services. Currently, creators can utilize two webhooks for subscription management. Source: link @tonlines

NEWS 鏈新聞-ABMedia

@abmedia_news · Post #24369 · 05/05/2026, 08:03 AM

【🤖 AI人工智慧|Gemini API 推 Webhooks:Google 解決長任務輪詢痛點、Batch/Veo 可即時推送】 #Google#GeminiAPI#Webhooks Google 於 5 月 4 日上線 Gemini API Webhooks,解決長任務開發者頻繁輪詢的痛點。 該功能支援 Batch 與 Veo 2 結果主動推送,Logan Kilpatrick 稱此舉大幅優化 DevX。相較 OpenAI 專注消費端產品,Google 則選擇持續深耕開發者基建路線。 📍閱讀全文: https://abmedia.io/gemini-api-webhooks-event-driven-long-running-tasks-may-2026 📍 訂閱鏈新聞頻道:https://linktr.ee/abmedia.io