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A very quick edit I made after finding this animation. Kevin & Elysia simply alltime favorites โ™ฅ๏ธ๐Ÿ™ #KevinKaslana #elysia #kevely #phairene

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็›ธๅ…ณ่ง†้ข‘

How do you build an end-to-end agentic RAG app? Lucky for you, you can just run two commands: โ€˜pip install elysia-aiโ€™ and โ€™elysia startโ€™ I wrote a massive blog post detailing all the things we built into this ๐—ผ๐—ฝ๐—ฒ๐—ป ๐˜€๐—ผ๐˜‚๐—ฟ๐—ฐ๐—ฒ ๐—ฒ๐—ป๐—ฑ-๐˜๐—ผ-๐—ฒ๐—ป๐—ฑ ๐—ฎ๐—ด๐—ฒ๐—ป๐˜๐—ถ๐—ฐ ๐—ฅ๐—”๐—š ๐—ณ๐—ฟ๐—ฎ๐—บ๐—ฒ๐˜„๐—ผ๐—ฟ๐—ธ: But if you don't have time to read though that, hereโ€™s the TLDR version ๐Ÿ”ฝ Instead of the typical "text in, text out" approach, Elysia uses a decision tree architecture where intelligent agents determine the best tools to use, evaluate results, and decide whether to continue or complete their tasks. It's an AI that actually thinks through problems step-by-step in a controllable, user-understandable format. The three main things that set Elysia apart: 1๏ธโƒฃ ๐——๐—ฒ๐—ฐ๐—ถ๐˜€๐—ถ๐—ผ๐—ป ๐—ง๐—ฟ๐—ฒ๐—ฒ๐˜€ ๐˜„๐—ถ๐˜๐—ต ๐—ฆ๐—บ๐—ฎ๐—ฟ๐˜ ๐—”๐—ด๐—ฒ๐—ป๐˜๐˜€: Each node has a decision agent with global context awareness. They evaluate past actions, current state, and future possibilities to choose the optimal tool. Plus, they can handle errors intelligently โ€“ if something fails, they'll try a different approach rather than just giving up. 2๏ธโƒฃ ๐——๐˜†๐—ป๐—ฎ๐—บ๐—ถ๐—ฐ ๐——๐—ถ๐˜€๐—ฝ๐—น๐—ฎ๐˜†๐˜€: Elysia chooses from seven display formats โ€“ tables, e-commerce cards, tickets, conversations, documents, charts, and more. It analyzes your data structure and automatically picks the most appropriate way to present information. 3๏ธโƒฃ ๐—”๐˜‚๐˜๐—ผ๐—บ๐—ฎ๐˜๐—ถ๐—ฐ ๐——๐—ฎ๐˜๐—ฎ ๐—˜๐˜…๐—ฝ๐—ฒ๐—ฟ๐˜๐—ถ๐˜€๐—ฒ: Unlike traditional RAG systems that perform blind searches, Elysia analyzes your collections first. It understands your data structure, creates summaries, generates metadata, and uses this knowledge to handle complex queries intelligently. The frontend displays the entire decision tree as it's traversed, showing you exactly why it made each choice. No more black-box AI systems โ€“ you get complete transparency into the reasoning process. We built Elysia to be the successor to Verba, taking everything we learned about RAG applications and pushing it to the next level. It's not just about retrieving and generating anymore โ€“ ๐—ถ๐˜'๐˜€ ๐—ฎ๐—ฏ๐—ผ๐˜‚๐˜ ๐—ฐ๐—ฟ๐—ฒ๐—ฎ๐˜๐—ถ๐—ป๐—ด ๐—”๐—œ ๐—ฎ๐˜€๐˜€๐—ถ๐˜€๐˜๐—ฎ๐—ป๐˜๐˜€ ๐˜๐—ต๐—ฎ๐˜ ๐˜๐—ฟ๐˜‚๐—น๐˜† ๐˜‚๐—ป๐—ฑ๐—ฒ๐—ฟ๐˜€๐˜๐—ฎ๐—ป๐—ฑ ๐—ฐ๐—ผ๐—ป๐˜๐—ฒ๐˜…๐˜ ๐—ฎ๐—ป๐—ฑ ๐—ฝ๐—ฟ๐—ฒ๐˜€๐—ฒ๐—ป๐˜ ๐—ถ๐—ป๐—ณ๐—ผ๐—ฟ๐—บ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—ฒ๐—ณ๐—ณ๐—ฒ๐—ฐ๐˜๐—ถ๐˜ƒ๐—ฒ๐—น๐˜†. GitHub: Demo: Get started:

Victoria Slocum

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