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Source channel @githubtrending · Post #15085 · Aug 22
#python#chatbi#deepseek#llm#nl2sql#rag#sqlbot#text_to_sql#text2sql SQLBot is an easy-to-use intelligent system that turns natural language questions into SQL queries using advanced AI models and retrieval-augmented generation (RAG). You just need to set up your AI model and data source to start asking questions about your data. It integrates smoothly with other business systems and AI platforms, making it simple to add smart data querying to your apps. It also ensures data security with workspace-based resource isolation and fine-grained access control. You can quickly deploy it on a Linux server using Docker, enabling fast, secure, and intelligent data interaction without needing deep SQL knowledge. This saves you time and improves data accessibility. https://github.com/dataease/SQLBot
Search: #mongoengine
@djangoproject · Post #346 · 06/21/2017, 07:24 AM
http://mongoengine.org To get to grips with MongoEngine, there is extensive documentation, API references and a tutorial. You can find help by joining the MongoEngine Users mailing list or by chatting with other users on the #mongoengine IRC channel.
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@djangoproject · Post #364 · 07/04/2017, 03:25 AM
http://mongoengine.readthedocs.io/en/latest/index.html #MongoEngine is an Object-Document Mapper, written in #Python for working with #MongoDB. To install it, simply run #Django
@djangoproject · Post #373 · 07/05/2017, 06:39 AM
https://realpython.com/blog/python/introduction-to-mongodb-and-python/#.WMfv6BURLc4.linkedin #SQL vs #NoSQL #MongoDB #PyMongo #MongoEngine Conclusion
@djangoproject · Post #421 · 08/21/2017, 10:39 AM
https://alysivji.github.io/flask-part1-generating-html-pages-with-mongoengine-jinja2.html Generating HTML Pages from #MongoDB with #MongoEngine and #Jinja2 (Flask Part 1) Summary Overview of MongoDB Discussion of Object-Relational Mapping (#ORM) Use MongoEngine to get items out of MongoDB Render #HTML pages using Jinja2 Interact with #REST API to send emails with #Requests