Hello HN!
The day has finally come to stop adding features and start sharing what I've been building the last 5-6 months.<p>It's a bit of CrewAI, OpenDevon, LangFuse/Cloud all in one, providing devs who prefer TypeScript an integrated framework thats provides a lot out of the box to start experimenting and building agents with.<p>It started after peeking at the LangChain docs a few times and never liking the example code. I began experimenting with automating a simple Jira request from the engineering team to add an index to one of our Google Spanner databases (for context I'm the DevOps/SRE lead for an AdTech company).<p>It incudes the tooling we're building out to automate processes from a DevOps/SRE perspective, which initially includes a configurable GitLab merge request AI reviewer.<p>The initial layer above Aider (<a href="https://aider.chat/" rel="nofollow">https://aider.chat/</a>) grew into coding agent and an autonomous agent with LLM-independent function calling with auto-generated function schemas.<p>And as testing via the CLI became unwieldy soon grew database persistence, tracing, a Web UI and human-in-the-loop functionality.<p>One of the more interesting additions is the new autonomous agent which generates Python code that can call the available functions.
Using the pyodide library the tool objects are proxied into the Python scope and executed in a WebAssembly sandbox.<p>As its able to perform multiple calls and validation logic in a single control loop, it can reduce the cost and latency, getting the most out of the frontier LLMs calls with better reasoning.<p>Benchmark runners for the autonomous agent and coding benchmarks are in the works to get some numbers on the capabilities so far. I'm looking forward to getting back to implementing all the ideas around improving the code and autonomous agents from a metacognitive perspective after spending time on docs, refactorings and tidying up recently.<p>Check it out at <a href="https://github.com/trafficguard/nous">https://github.com/trafficguard/nous</a>
This looks fantastic! I've been using aider and had my own scripts to automate some things with it, but this looks next level and beyond.<p>I wanted to try this out (specifically the web UI), so I configured the env file, adjusted the docker compose file, ran `docker compose up` and it "just works".<p>It would be great if there was a basic agent example or two pre-configured, so you can set this up and instantly get a better sense of how everything works from a more hands-on perspective.
If this isn't by Nous Research, may want to consider renaming (<a href="https://x.com/NousResearch" rel="nofollow">https://x.com/NousResearch</a>, <a href="https://nousresearch.com/" rel="nofollow">https://nousresearch.com/</a>)
I'm not entirely sure what this does? The initial paragraph goes into history and what other platforms do, but it doesn't say what problem this will solve for me. Then it continues with some features and screenshots, but I still don't know how to use this or why.
This looks too good. I have a B2B AI product, the features that exist in Nous easily outclass anything I could make in a reasonable timeline.<p>Maybe I should rewrite my app using Nous...
I'm having a hard time figuring out how much logic lives in Nous and how much in Aider for code changes - could you say some more about it?<p>Playing with the code agents do far I've found Aider to do many silly mistakes and revert its own changes in the next commit of the same task. On the other hand Plandex is more consistent but can get in a loop of splitting the take into way too small pieces and burning money. I'm interested to see other approaches coming up.
That's promising! Congratulations with launch. Considering adding to the specialized directory for AI agents and Frameworks to build them. Let me know if you need help.<p><a href="https://aiagentsdirectory.com/" rel="nofollow">https://aiagentsdirectory.com/</a>