Vanna: Trợ lý thông minh nghiệp vụ AI của bạn

Still Looking at Text-to-SQL? You're OUT! It's Now RAG2SQL! (Step-by-step)

In this episode, join Angelina and Mehdi, for a discussion about RAG2SQL or RAG2Database, which is an extension of the hot Text-to-SQL concept last year. A lot of the Text-to-SQL apps failed, why? Check our episode out! Who's Angelina: https://www.linkedin.com/in/meetangelina/ Who's Mehdi: https://www.linkedin.com/in/mehdiallahyari/ 🔨Code: https://github.com/mallahyari/twosetai/blob/main/05_sqlite-openai-vanna-vannadb.ipynb 00:00 Intro 00:07 Why is talking to your database business critical? 00:45 What is RAG (retrieval augmented generation) to SQL? 00:58 Introduce Vanna 01:21 What kind of database can it talk to? 01:49 Text-to-SQL? 02:10 How's RAG-to-SQL different? 04:00 What does the RAT-to-SQL training phase do? 05:52 Is there real training done? 08:44 Step-by-step tutorial (Jupyter Notebook) of how it works with a SQLite databae 09:55 How to download a SQLite database on Kaggle 15:10 What more does it offer? (👉 shh... free UI! and more!) 15:47 Compare with DataDM 16:26 Performance 19:31 If you are a company with bunch of predefined SQL queries, what do you do? 20:10 Are challenges like loss-in-the-middle still applicable? 🧰 Our video editing tool is this one!: https://get.descript.com/nf5cum9nj1m8 🦄 Any specific contents you wish to learn from us? Sign up here: https://noteforms.com/forms/twosetai-youtube-content-sqezrz 🖼️ Blogpost for today: DataDM: https://open.substack.com/pub/mlnotes/p/datadm-your-private-data-visualization?r=164sm1&utm_campaign=post&utm_medium=web AI SQL Accuracy: Testing different LLMs + context strategies to maximize SQL generation accuracy: https://vanna.ai/blog/ai-sql-accuracy.html 🔨 Implementation: Vanna AI: https://github.com/vanna-ai/vanna 📬 Don't miss out on the latest updates - Subscribe to our newsletter: https://mlnotes.substack.com/ 📚 If you'd like to learn more about RAG systems, check out our book on the RAG system: https://angelinamagr.gumroad.com/ 🕴️ Our consulting firm: We help companies that don't want to miss the boat of the current wave of AI advancement by integrating these solutions into their business operations and products. https://www.transformaistudio.com/ Stay tuned for more content! 🎥 Thanks you for watching! 🙌

IA para Bases de Datos! Vanna AI es una inteligencia artificial creada con Python para SQL que se entrena sobre tu esquema de base de datos. Le preguntas lo que quieras con lenguaje natural y te genera la Query y muestra el resultado de la consulta. 🔗 “vanna.ai” #programacion #programadores #basededatos #sql #ia #inteligenciaartificial #informatica #tecnologia #aprendeentiktok #aprendecontiktok

【效果炸裂💥】Vanna.AI + Plotly构建基于AI的SQL数据分析与可视化应用

#vanna #plotly #openai 推荐一个目前全网价格最实惠的合租平台，ChatGPT，MidJourney，奈飞，迪士尼，苹果TV等热门软件应有尽有 - https://dub.sh/unibus ，首单9折优惠 - 优惠码 01Coder 曾经一期视频我介绍了基于AI的文本转SQL工具Vanna.AI - https://youtu.be/mixwxOLSeFE?si=2jcnuh2eZoUCSXfh 本期视频我会再度介绍Vanna.AI。我会基于一个NBA球员2024赛季投篮数据集，演示Vanna.AI在不同数据分析和可视化应用场景中的使用，并且介绍强大的Python可视化工具包Plotly。 如果您喜欢这个视频并希望请我喝一杯咖啡，欢迎前往我的BuyMeACoffee页面 👉 https://www.buymeacoffee.com/01coder Vanna https://vanna.ai/ Plotly https://plotly.com/python/ 相关NBA数据集 https://www.kaggle.com/datasets/mexwell/nba-shots 示例代码 https://github.com/sugarforever/OpenAI-Tutorials/blob/main/vanna_sqlite_nba_shots.ipynb - 关注我的Twitter: https://twitter.com/verysmallwoods - 关注我的Bilibili: https://space.bilibili.com/615957867/ - 如果您有任何问题或者建议，欢迎通过邮件联系我：0001coder@gmail.com 【AI技术视频】播放列表 https://www.youtube.com/playlist?list=PL2fGiugrNoojhDVpc5_y2dFpM16zjr-3n 章节 00:00 本期视频介绍 00:56 Vanna架构简介 02:42 示例数据集简介 03:49 演示环境准备 06:48 场景1 - NBA赛季投篮总数 08:37 场景2 - 投篮最多球员计算 09:43 Vanna核心函数简析 12:37 场景3 - 东契奇投篮命中率 15:28 场景4 - 可视化命中率前三的球员数据 18:49 Plotly实现高度可定制的数据可视化 20:59 场景5 - 按投篮距离计算投篮次数