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Apache Burr: Build reliable AI agents and applications

burr.apache.org

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Re: Apache Burr: Build reliable AI agents and applications

#71

Post by cpard »

kristjansson wrote: post #25
brotchie wrote: post #6

I'm still on the fence about agent frameworks, they have their place, and it depends on the nature of the agent: e.g. "Low latency, return a good enough response in 3 seconds, vs. working for 3 hours on a problem." BUT, if you boil it down, an agent really is context building, making an LLM call, executing requested tool calls, parsing the final model output, returning it to some frontend. There's extensions like mem…

Obscuring core logic is the most egregious part of most agent frameworks. One needs a clear view of what, exactly, is being sent to the underlying language model, and what's coming back. Everything in an 'agentic' application is realized as a sequence of tokens or a call to a provider eventually. It should be clear and obvious from ~all layers of the app what that's going to look like.

Most framework vendors don’t have an incentive to make things less obscure. The agent framework is free/open source and they make money primarily from selling observability products for agents. Even if they don’t intentionally obscure things, they just don’t have the motivation to optimize that part.

Re: Apache Burr: Build reliable AI agents and applications

#72

Post by doublerabbit »

flakiness wrote: post #35

Wow, such a un-apache-y homepage I've ever seen, vs. the canonical one: https://httpd.apache.org/ (And wow, they still keep releasing it!)

Here's another ancient relic of a website design. They even used a free template from back in the day.

https://tcl.apache.org/rivet/

Re: Apache Burr: Build reliable AI agents and applications

#73

Post by doublerabbit »

pramodbiligiri wrote: post #42
vanuatu wrote: post #11

vibe coded landing page reddit user testimonial framework is for state machines why man..

How does one know that a website is "vibe coded"? Any good indicators?

The flair is a big give away. View source. Look for the SVGs.

Re: Apache Burr: Build reliable AI agents and applications

#74

Post by toddmorey »

brotchie wrote: post #6

I'm still on the fence about agent frameworks, they have their place, and it depends on the nature of the agent: e.g. "Low latency, return a good enough response in 3 seconds, vs. working for 3 hours on a problem." BUT, if you boil it down, an agent really is context building, making an LLM call, executing requested tool calls, parsing the final model output, returning it to some frontend. There's extensions like mem…

Anthropic seems to agree with you as more recent Claude updates have it just building task specific harnesses as needed.

Re: Apache Burr: Build reliable AI agents and applications

#75

Post by andai »

sdesol wrote: post #70
peterbell_nyc wrote: post #53

Earlier quoted context omitted.

For me the heart of an agentic system is NOT using agents (except when you really have to). Components of a working system include: - Pipelines/recipes to describe multi-step flows (deterministic, agentic and HiTL steps), loops, conditionals, exit-on's for max loop iteractions, etc - The logistics to actually run the model and HiTL steps reliably across multiple agent worker pools - Management and delivery (and secur…

Can you comment more on > Context management so the right agents have the right context for the right sessions at the right time I'm going to do a show HN tomorrow that explains how you can give your agents years of experience. The basic idea is, you would commit in your repo or download manifests (JSON files) that can be converted to "Brains" (SQLite databases). Each brain can have its own properties. For example, I…

(I'm not the guy but) That's funny, I had the same idea the other day. Keeping summaries of files. Haven't tested that yet.

Another thing I've been thinking is how, most parts of a file are not relevant to the whole system.

Like there are parts where they intersect, and those seem to be the most important ones for capturing the big picture. You wanna be able to see the entire "skeleton".

So I thought the summary maybe shouldn't be English but it should be a subset of the code — the subset that's relevant to the rest of the program.

`grep import` gets you 90% of the way there.

Re: Apache Burr: Build reliable AI agents and applications

#76

Post by sgc »

nico wrote: post #43

On a tangent, can anyone recommend good coding agent orchestration tools or platform? Something to launch, manage and monitor codex or claude agents in multiple machines Ideally self-hostable/open source I know claude code has a lot of that internally built in already, but it’s claude-only

I was looking at their docs and Burr has agent cookbooks to get started with this, and it can handle multi-machine workflows. Is this not what you were looking for? I am not sure how it integrates and uses skills etc, but it seems like it should work to me.

https://burr.apache.org/docs/examples/agents/

Re: Apache Burr: Build reliable AI agents and applications

#77

Post by dd8601fn »

brotchie wrote: post #6

I'm still on the fence about agent frameworks, they have their place, and it depends on the nature of the agent: e.g. "Low latency, return a good enough response in 3 seconds, vs. working for 3 hours on a problem." BUT, if you boil it down, an agent really is context building, making an LLM call, executing requested tool calls, parsing the final model output, returning it to some frontend. There's extensions like mem…

I’ve said something similar about dozens of frontend frameworks. It’s massive abstraction and convolution for some future payoff that’s obviously never going to happen.

But sometimes people just need something to do, or something fun to play with, and “the next guy” rarely matters that much… so who cares that you’ve saddled them with the result of your paid playtime?

Re: Apache Burr: Build reliable AI agents and applications

#78

Post by hilariously »

tcdent wrote: post #15
hilariously wrote: post #10

Earlier quoted context omitted.

Couldn't agree more - tried to convince a business that doubling down on OpenClaw wasn't going to solve problems except for some 0-1 stuff, and that almost immediately they'd run into roadblocks because most of the product wouldn't serve their use case. 4 months of mostly spinning their wheels later they launched a really lackluster OC product that's effectively DOA.

OpenClaw is an application, not a harness. Yes, it contains a harness, but it is a complete product. When building an agentic workflow there are enough primitives that rewriting them from scratch every time makes zero sense. What is a tool? How does the LLM understand the tool? Formatting a native function into a serializable input/output pattern makes sense to generalize and that does not need to exist repeated in e…

Sure, but that seems liked two different points.

One, obviously yes OC contains a lot more than a harness, but my point was that it was too much for their use case and constrained their choices, not enabled them, and that choosing the right layer of abstraction is important.

There's good indirection/abstraction and there's ones that do not serve your use case, eg what was obviously day one regarding Langchain.

Re: Apache Burr: Build reliable AI agents and applications

#79

Post by sdesol »

andai wrote: post #75
sdesol wrote: post #70

Earlier quoted context omitted.

Can you comment more on > Context management so the right agents have the right context for the right sessions at the right time I'm going to do a show HN tomorrow that explains how you can give your agents years of experience. The basic idea is, you would commit in your repo or download manifests (JSON files) that can be converted to "Brains" (SQLite databases). Each brain can have its own properties. For example, I…

(I'm not the guy but) That's funny, I had the same idea the other day. Keeping summaries of files. Haven't tested that yet. Another thing I've been thinking is how, most parts of a file are not relevant to the whole system. Like there are parts where they intersect, and those seem to be the most important ones for capturing the big picture. You wanna be able to see the entire "skeleton". So I thought the summary mayb…

If you include the following:

https://github.com/gitsense/chat/blob/main/base-state/analyz...

In your chat with AI, include the above file and let it know what your requirements are and I can create the analyzer and include it.

You can also think of my tool as data prepping tool. So if you have a clear prompt the AI can review the file during analysis and remove all unnecessary code so the extracted metadata will the stripped text which you can use search against.

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