BenderV

Well, I think they should have kept calling it function... ^^'

It feels crazy to me that we are building "tool search" instead of building real tool with interface, state and available actions. Think how would you define a Calculator, a Browser, a Car...?

I think, notably, one of the errors has been to name functions calls "tools"...

Thanks for your answer.

I guess that it's only a matter of finetuning.

LLM have lots of experience with bash so I get they figure out how to work with it. They don't have experience with custom tools you provide it.

And also, LLM "tools" as we know it need better design (to show states, dynamic actions).

Given both, AI with the right tools will outperform AI with generic and uncontrolled tool.

I'm trying to understand what does it got to do with LLM size? Imho, right tools allow small models to perform better than undirected tool like bash to do everything. But I understand that this code is to show people how function calling is just a template for LLM.

Nice but sad to see lack of tools. Most your code is about the agent framework instead of specific to SWE.

I've built a SWE agent too (for fun), check it out => https://github.com/myriade-ai/autocode

Why do humans need a IDE when we could do anything in a shell? Interface give you the informations you need at a given moment and the actions you can take.

Here, the best time is defined as the highest chance of getting "some" visibility. Most posts quickly fade away.

You are right that there is lots of way to measure this but quality comments is way harder to judge and we don't have quantity traffic info.

Hey, Funnily, I had this idea/need recently. Just a message to encourage you in this direction !

Selfless plug, our own tool => https://www.myriade.ai

> I wish you luck in refining your differentiation. Can't agree more with you. It's about distribution (which Snowflake/Databricks/... have) or differentiation.

Still, chatting with your data is already working and useful for lots.

My 2 cents, building a tool in this space...

> Do you need an expert to verify if the answer from AI is correct?

If the underling data has a quality issue that is not obvious to a human, the AI will miss it too. Otherwise, the AI will correct it for you. But I would argue that it's highly probable that your expert would have missed it too... So, no, it's not a silver bullet yet, and the AI model often lacks enough context that humans have, and the capacity to take a step back.

> How is it time saved refining prompts instead of SQL?

I wouldn't call that "prompting". It's just a chat. I'm at least ~10x faster (for reasonable complex & interesting queries).

Awesome. Using Vue/Tailwind, I'm definitely interested in this. Maybe you could try to add examples of integrations with others frameworks? I'll play with it and give you my 2 cents.

Hi HN,

Over the past few weeks/months, I’ve been working on Autochat, a lightweight Python library designed to make building AI agents simple and intuitive.

The focus of Autochat is simplicity:

- Extend an AI assistant's functionality by adding Python functions directly, or even class.

- Hide all the complexities/particularities of the providers (openai, anthropic, …)

I’d love your feedback on this. If you’ve got ideas for features, use cases, or critiques, let me know!

Seems weird that to me that it make a front page on HN (from an European pov ; it's quite common)

First, congrats for the launch.

Copying the interface is not what I would call "not reinventing the wheel".

Not that you shouldn't have inspiration, but really I couldn't tell it was not linear...

Futhermore, I think it tell that your product lack AI-first design.

I'll admit that I didn't give much care about having a perfect and unique name. It's just a simple tool.

Hi HN community,

I wanted to share with you Ada, an open-source tool to accelerate data analysis using AI.

In short, it's a (very) lightweight mix between ChatGPT and Metabase.

I have been working around this idea for quite a while, in my spare time. The goal is to make data analysis fun and fast... just like when Tony Stark discover a new element with the help of Jarvis (https://youtu.be/Ddk9ci6geSs?si=Y6sBvZZn8779nPV8&t=32)

I'm sharing it because, while imperfect, I now use it quite regularly in my professional life, and I just learned that a Vietnam company is using it internally. So I figured some of you might be interested, and I would love to have your feedback.

I invite you to install it and try it yourself (https://github.com/BenderV/ada) Or you can try a demo at https://ada.universaldata.io

Best, Ben

PS: Since it’s currently based on OpenAI GPT4, you will need to have an OpenAI API Key.

Shameless plug - https://github.com/BenderV/ada

It's an open source BI tool that does just that.

I built Ada - https://github.com/BenderV/ada - a BI tool to leverage AI for data analysis. I use it every day now :)

Great since GPT4. However, I need to add some optimization because it's take time for the AI to explore databases / tables schema / structures.

Congrats for your launch !

I also built NL2SQL solution (relying on OpenAI).

My first version was a direct NL2SQL version, named Olympe - https://github.com/BenderV/olympe I used it quite a while but trying to plug it to real database (100+ tables, unprepared) was unsuccesful.

I switched to chat version, named Ada - https://github.com/BenderV/ada

IMHO, it's the way to go. The AI explore the database, it's connection, the data format & co. Plus, it help with ambiguity and feels more "natural".

Congrats on your project. Reliable CDC is hard to set up.

I worked a bit on the space, focusing on api instead of DB, which is in the end a quite different problem. My goal was to leverage LLM to auto-build connector on the fly.

I started by building a lightweight ETL, that I open-sourced (https://github.com/BenderV/universal-data).

I left the space because I realize that I didn't want to work on this problem, even though I believe in the "AI" approach, and think simplifying data transfer (or distributing compute) is one the key factor to scale data usage.

Shameless plug...

I recently open-sourced a small BI app to query a database in english. It only support Postgres for now (and it's far from perfect..)

https://github.com/BenderV/olympe

[Shameless plug] If you wish to try another, I built a small proof-of-concept here: https://www.olym.pe

(registration necessary)

I'm using Kagi in France. First time I'm not actively looking back to be on Google (which sometimes I still do). Congrats and continue your effort !

I'm guessing if you don't live in a big city (Paris, Lille, ...) & stay on low-level programming (like C), there is really less demands.

However, I guess most come down to your network, your confidence and how you represent yourself (having the same "cultural" code as experts).

My 2 cents is to treat yourself well first (a healthy mind for a good body), travel more, and work on public stuff / connect with others.

Agree with the point of the blog, but the biggest hurdle for me:

If you do a short and intensive sprint, Airpods usually will register a click and skip to the next song...

I recently removed my personal todo list.

I found that it was usually a way to not think about the different issues/projets I had in mind. Removing the todo list forced me to remember the list, to think about possible solutions or related task I wanted to do.

I was really, really productive for few weeks...

Unfortunately, I quickly fallback to my old habits of listing todo... Simply because I don't give myself proper time to think about what I want to do.

That’s really great! Congrats.

If you can do an Amazon/Audible integration, that would be awesome (and will let you build your recommendation system?).

From experience, I like to read the most populars/iconics books outside my perspective/pov, even though, if I had to grade them, it wouldn't be 5/5.

Maybe though, the most problematic of theses "ideological bubbles" is that people don't generally want to escape it.

Things I would like: * Date when you followed someone * Bookmarks api.

Doesn't seems to be it.

Lots of people are arguing really valid points. I recently switched to a Big Co after 4 start-ups - so I get /it/. I'm just wondering what part is due to inefficiency creeping in VS due to the size of an organisation.

Point being: what about SpaceX, Tesla or Stripe ?

Are they also slow ? with politics and no transparency & co ?