正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

This is a tool that used GPT that lets you connect to PostgresDB or MongoDB, lets users type in questions, and it generates the query code (even advanced table joins), runs the code and returns the answer instantly. Like a query co-pilot. Here are my thoughts 👇🏻

Duy

2,217 subscribers

68,792 次观看 • 3 年前 •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

9 条评论

Dew 的头像

Dew3 年前

The on-site demo is connected to a MongoDB so the code output is in MongoDBs query syntax. Its been surprisingly accurate so far! From initial use the tool is able to handle multiple table joins and queries that would take me a decent amount of time to draft

Dew 的头像

Dew3 年前

I see this tool being incredible for getting a boilerplate code template or iterating for any query you have to run. So I'd love to see a built-in code editor! @usebink

Dew 的头像

Dew3 年前

Developers and data analysts should can take the code generated and then edit any inconsistent entity/metric definitions

Glenn Robuck 的头像

Glenn Robuck3 年前

Read the terms and privacy on this site. I would not recommend anyone in any company to use this tool. They basically lay claim to all data that flows through the tool. It's a massive data leak possibility. Everyone needs to be VERY careful of AI tools.

Wny Poker 的头像

Wny Poker3 年前

Predicting this will lead to a corporate wide memo at some unhappy company reminding devs to not give unauthorized access to company databases. LOL.

csunny 的头像

csunny3 年前

just all you need

Samia afrin 的头像

Samia afrin3 年前

This is amazing, i can save a lot of time doing market research

K2 的头像

K23 年前

Amazing. This is literally crazy. Now data analysts are too going to get replaced. Funny.

Bob 的头像

Bob3 年前

Couldn't someone grow their own with GPT3 in like an hour or two?

相关视频

A nice upgrade to ACE: a simple payload that lets you connect to your PC with a custom GTS server, and send any code to instantly execute it. You no longer have to enter any code manually on the DS. Here I used it to give myself all items.

A nice upgrade to ACE: a simple payload that lets you connect to your PC with a custom GTS server, and send any code to instantly execute it. You no longer have to enter any code manually on the DS. Here I used it to give myself all items.

RETIRE

15,590 次观看 • 1 年前

How to make Claude Code 10x better: Connect it with a tool that reviews your code and generates prompts for Claude to fix any issues with it automatically. Here is what this looks like:

How to make Claude Code 10x better: Connect it with a tool that reviews your code and generates prompts for Claude to fix any issues with it automatically. Here is what this looks like:

Santiago

98,881 次观看 • 8 个月前

So a new (very good) agentic coding tool has just been released Qoder lets you vibe code apps by describing what you want or assigning quests. - Plans the project structure - Generates the code/files - Runs terminal commands - Launch the app to test it Quick steps to use it:

So a new (very good) agentic coding tool has just been released Qoder lets you vibe code apps by describing what you want or assigning quests. - Plans the project structure - Generates the code/files - Runs terminal commands - Launch the app to test it Quick steps to use it:

Paul Couvert

121,198 次观看 • 9 个月前

AI-powered database co-pilot: Use Bink Connect a database and use Bink as a database query co-pilot that can generate, run, and iterate on queries from simple questions. This could make everyone a data analyst. Big market for this:

AI-powered database co-pilot: Use Bink Connect a database and use Bink as a database query co-pilot that can generate, run, and iterate on queries from simple questions. This could make everyone a data analyst. Big market for this:

AI Breakfast

41,100 次观看 • 3 年前

🚨 BREAKING: Someone just built a tool that generates and visualizes complex 3d particle systems just by typing a prompt. You tell it what you want, it builds the physics, and you export the react or three.js code instantly. 100% Free.

🚨 BREAKING: Someone just built a tool that generates and visualizes complex 3d particle systems just by typing a prompt. You tell it what you want, it builds the physics, and you export the react or three.js code instantly. 100% Free.

Simplifying AI

190,300 次观看 • 2 个月前

This SQL query looks like it should fail immediately. Instead, it runs and quietly returns the wrong result. Why doesn’t the database complain?

This SQL query looks like it should fail immediately. Instead, it runs and quietly returns the wrong result. Why doesn’t the database complain?

Google for Developers

11,376 次观看 • 4 个月前

Quick demo of Zero’s new background queries. Zero’s sync is query-based. Rather than specifying what data you want using rules or some other separate system, you just use queries. Right inside the client app, you do a query using a full sql-style language. You get filters, subqueries , limits, etc. Zero syncs the data backing these queries to the client. It’s important to realize Zero isn’t really a cache. It’s a replica. It’s eagerly replicating a precise snapshot of a slice of your database - the slice covered by the queries you have open. So there is never stale data in Zero. When you close a query we delete the rows uniquely returned by that query because we can no longer keep them up to date. Of course that kind of sucks for the common case of doing a query, navigating, then pressing “back”. Ideally we want that back nav to be fast. To address this Zero 0.17 adds background queries. You can add a ttl to a query and it will keep running and syncing in the background. This is much different than normal caching because this data stays up to date. If you make the same query again, the results will be *instantly* available *and already up to date with server*. If you make a different query the data from the background query is used client-side to answer the new query instantly if possible. This all happens completely automatically. Just by adding the ttl flag.

Quick demo of Zero’s new background queries. Zero’s sync is query-based. Rather than specifying what data you want using rules or some other separate system, you just use queries. Right inside the client app, you do a query using a full sql-style language. You get filters, subqueries , limits, etc. Zero syncs the data backing these queries to the client. It’s important to realize Zero isn’t really a cache. It’s a replica. It’s eagerly replicating a precise snapshot of a slice of your database - the slice covered by the queries you have open. So there is never stale data in Zero. When you close a query we delete the rows uniquely returned by that query because we can no longer keep them up to date. Of course that kind of sucks for the common case of doing a query, navigating, then pressing “back”. Ideally we want that back nav to be fast. To address this Zero 0.17 adds background queries. You can add a ttl to a query and it will keep running and syncing in the background. This is much different than normal caching because this data stays up to date. If you make the same query again, the results will be instantly available and already up to date with server. If you make a different query the data from the background query is used client-side to answer the new query instantly if possible. This all happens completely automatically. Just by adding the ttl flag.

Aaron Boodman

18,808 次观看 • 1 年前

Introducing Embra, a fast ChatGPT-like assistant that lives on your Mac desktop & integrates into your apps! Starting with Chrome. Use it to: - Access ChatGPT-like conversations instantly - Query documents or websites (even PDFs!) - Write context-rich docs, code, and emails 1/3

Introducing Embra, a fast ChatGPT-like assistant that lives on your Mac desktop & integrates into your apps! Starting with Chrome. Use it to: - Access ChatGPT-like conversations instantly - Query documents or websites (even PDFs!) - Write context-rich docs, code, and emails 1/3

Zach Tratar

817,096 次观看 • 3 年前

⚡️ LATEST: OpenAI has launched Agent Builder, a no-code tool that lets users create custom AI agents with API and service integrations.

⚡️ LATEST: OpenAI has launched Agent Builder, a no-code tool that lets users create custom AI agents with API and service integrations.

Cointelegraph

51,766 次观看 • 8 个月前

🚨BREAKING: Someone just built a tool that generates full 3D particle systems from a single text prompt. You describe what you want. It builds the simulation and you export production-ready React or Three.js code instantly. 100% Free.

🚨BREAKING: Someone just built a tool that generates full 3D particle systems from a single text prompt. You describe what you want. It builds the simulation and you export production-ready React or Three.js code instantly. 100% Free.

Rimsha Bhardwaj

155,940 次观看 • 2 个月前

DesignerGPT 👨‍🎨 My new plugin that lets you create any website directly in chatGPT! It seamlessly integrates with the stable diffusion plugin, and I didn't code that—GPT just knows how to use both. Absolutely unreal! 🤯 Websites are hosted on a remote server via @replit.

DesignerGPT 👨‍🎨 My new plugin that lets you create any website directly in chatGPT! It seamlessly integrates with the stable diffusion plugin, and I didn't code that—GPT just knows how to use both. Absolutely unreal! 🤯 Websites are hosted on a remote server via @replit.

Pietro Schirano

1,238,084 次观看 • 3 年前

i built a tool that lets you vibe-tweet. this is the future ladies and gents

i built a tool that lets you vibe-tweet. this is the future ladies and gents

Rob Hallam

109,542 次观看 • 10 个月前

Let Postgres own the Iceberg catalog and delegate analytics to DuckDB. The result => transactional lakehouse updates with fast analytical queries. This isn’t a concept. It’s exactly what pg_lake delivers today. pg_lake combines a set of extensions and components that let you query and modify Iceberg tables (and other lakehouse formats) directly from Postgres. DuckDB is used to accelerate analytical queries and runs in a sidecar process called pgduck_server, which communicates with Postgres during query execution. How it works (diagram below): 1. An application sends a query to Postgres to calculate unrealized PnL (Profit and Loss) for the Disney ticker. 2. Postgres parses the query and identifies the part that computes the average price from historical lakehouse data. 3. That part is forwarded to pgduck_server for accelerated execution. 4. pgduck_server delegates execution to DuckDB, which queries the lakehouse (reusing cached data if available). 5. DuckDB computes the average price and returns it to Postgres. 6. Postgres joins the result with local portfolio data and computes the unrealized PnL. 7. The final result is returned to the application.

Let Postgres own the Iceberg catalog and delegate analytics to DuckDB. The result => transactional lakehouse updates with fast analytical queries. This isn’t a concept. It’s exactly what pg_lake delivers today. pg_lake combines a set of extensions and components that let you query and modify Iceberg tables (and other lakehouse formats) directly from Postgres. DuckDB is used to accelerate analytical queries and runs in a sidecar process called pgduck_server, which communicates with Postgres during query execution. How it works (diagram below): 1. An application sends a query to Postgres to calculate unrealized PnL (Profit and Loss) for the Disney ticker. 2. Postgres parses the query and identifies the part that computes the average price from historical lakehouse data. 3. That part is forwarded to pgduck_server for accelerated execution. 4. pgduck_server delegates execution to DuckDB, which queries the lakehouse (reusing cached data if available). 5. DuckDB computes the average price and returns it to Postgres. 6. Postgres joins the result with local portfolio data and computes the unrealized PnL. 7. The final result is returned to the application.

Denis Magda

28,461 次观看 • 4 个月前

So ace. Google just released Gemini Code Wiki. A free too that generates interactive docs from any GitHub URL 🤯 The tool lets you: → Chat with Gemini to understand *any* repo → Visualize code structure → Create docs from public repos 100% free. Link in 🧵↓

So ace. Google just released Gemini Code Wiki. A free too that generates interactive docs from any GitHub URL 🤯 The tool lets you: → Chat with Gemini to understand any repo → Visualize code structure → Create docs from public repos 100% free. Link in 🧵↓

Charly Wargnier

66,844 次观看 • 5 个月前

Building AI agents and tools is getting ridiculously easy! Here is a pretty impressive FREE and Open-Source AI agent builder that runs on your computer. It's a desktop app you can install on Mac or Windows. Link: • Free • 100% no-code: You can type what you want, and the tool will build everything for you. • You can use local models like DeepSeek or Qwen, or connect to cloud models like GPT-4o, Claude, or Gemini with your API key. • You can turn the tools you build into MCP Servers. I recorded a quick video to show you how easy it is to build something from scratch.

Building AI agents and tools is getting ridiculously easy! Here is a pretty impressive FREE and Open-Source AI agent builder that runs on your computer. It's a desktop app you can install on Mac or Windows. Link: • Free • 100% no-code: You can type what you want, and the tool will build everything for you. • You can use local models like DeepSeek or Qwen, or connect to cloud models like GPT-4o, Claude, or Gemini with your API key. • You can turn the tools you build into MCP Servers. I recorded a quick video to show you how easy it is to build something from scratch.

Santiago

56,815 次观看 • 1 年前

I tested a new coding assistant on 34,568 lines of code. (Cursor could not achieve what this tool did.) AI models are improving every day: - Faster inference - Longer context lengths But are AI coding assistants advancing at the same rate? Can they truly understand your entire project? I tested Augment Code on my ai-engineering repo with ~35k lines of code. Augment Code is a powerful AI Assistant built for developers working with large, evolving codebases—needing an assistant that understands the full context of their projects. In the video demo below, I asked it to: - Merge two projects. - Answer a global context question. Here’s what happened: - It understood dependencies across both projects. - It merged them intelligently—without breaking anything. - It even created a README file for the merged project. - It answered my global query instantly, pulling from the full codebase. This is the difference between AI autocomplete and an AI engineer that truly understands your repo. Augment Code is powerful because it indexes your entire repo upfront. This way, it can answer questions instantly, no matter how large your project is. Lastly, Augment Code is fully compatible with VSCode, JetBrains, Vim, Slack, and more. Try them now, I have shared a link in the next tweet! Thanks to Augment Code for showing me their powerful AI coding assistant and working with me on this post.

I tested a new coding assistant on 34,568 lines of code. (Cursor could not achieve what this tool did.) AI models are improving every day: - Faster inference - Longer context lengths But are AI coding assistants advancing at the same rate? Can they truly understand your entire project? I tested Augment Code on my ai-engineering repo with ~35k lines of code. Augment Code is a powerful AI Assistant built for developers working with large, evolving codebases—needing an assistant that understands the full context of their projects. In the video demo below, I asked it to: - Merge two projects. - Answer a global context question. Here’s what happened: - It understood dependencies across both projects. - It merged them intelligently—without breaking anything. - It even created a README file for the merged project. - It answered my global query instantly, pulling from the full codebase. This is the difference between AI autocomplete and an AI engineer that truly understands your repo. Augment Code is powerful because it indexes your entire repo upfront. This way, it can answer questions instantly, no matter how large your project is. Lastly, Augment Code is fully compatible with VSCode, JetBrains, Vim, Slack, and more. Try them now, I have shared a link in the next tweet! Thanks to Augment Code for showing me their powerful AI coding assistant and working with me on this post.

Akshay 🚀

30,799 次观看 • 1 年前

We're excited to announce duckdb-skills, a DuckDB plugin for Claude Code! We think the embedded nature of DuckDB makes it a perfect companion for Claude in your local workflows. The skills supported include: + read-file and query – uses DuckDB's CLI to query data locally, unlocking easy access to any file that DuckDB can read. + read-memories – a clever idea to store your Claude memories in DuckDB and query them at blazing speed. These are powered by two additional skills: + attach-db – gives Claude a mechanism to manage DuckDB state through a .sql file linked to your project. + duckdb-docs – uses a remote DuckDB full-text search database to query the DuckDB docs and answer all of your (and Claude's own) questions.

We're excited to announce duckdb-skills, a DuckDB plugin for Claude Code! We think the embedded nature of DuckDB makes it a perfect companion for Claude in your local workflows. The skills supported include: + read-file and query – uses DuckDB's CLI to query data locally, unlocking easy access to any file that DuckDB can read. + read-memories – a clever idea to store your Claude memories in DuckDB and query them at blazing speed. These are powered by two additional skills: + attach-db – gives Claude a mechanism to manage DuckDB state through a .sql file linked to your project. + duckdb-docs – uses a remote DuckDB full-text search database to query the DuckDB docs and answer all of your (and Claude's own) questions.

DuckDB

60,551 次观看 • 2 个月前

This is an excellent feature of Grok4. The code you provide to Grok gets nicely formatted in a Markdown block. The play button lets you run your code in the browser. You can also easily copy or edit your code.

This is an excellent feature of Grok4. The code you provide to Grok gets nicely formatted in a Markdown block. The play button lets you run your code in the browser. You can also easily copy or edit your code.

tetsuo

1,054,866 次观看 • 10 个月前

You can now access AI directly from your database! Here is a step-by-step demo that uses GPT-4 to classify customer reviews from a MySQL dataset. And I'm only writing SQL instructions! You have to see it! The model acts as another table in the database. I can query it and join it with other tables. It's awesome! This is all thanks to mindshub. Here is their GitHub repository: They are sponsoring this post. Watch the video.

You can now access AI directly from your database! Here is a step-by-step demo that uses GPT-4 to classify customer reviews from a MySQL dataset. And I'm only writing SQL instructions! You have to see it! The model acts as another table in the database. I can query it and join it with other tables. It's awesome! This is all thanks to mindshub. Here is their GitHub repository: They are sponsoring this post. Watch the video.

Santiago

209,434 次观看 • 2 年前

GraphQL to TypeScript type, no code gen. Written purely in TypeScript type. With Prisma-like query syntax fully type-safe. Should cover almost all of the GraphQL specs, now. Here's a demo.

GraphQL to TypeScript type, no code gen. Written purely in TypeScript type. With Prisma-like query syntax fully type-safe. Should cover almost all of the GraphQL specs, now. Here's a demo.

SaltyAom

100,697 次观看 • 2 年前