skull8888888

8 ms·

1. 31.▲
   by skull8888888 2y ago

   For me Agent is essentially a decision making machine. I had many iterations on the software around building agents and Flow is the culmination of all of the learnings. For some reason some LLM specific examples just slipped of my mind beca
2. 32.▲
   by skull8888888 2y ago

   oh, got it :)
3. 33.▲
   by skull8888888 2y ago

   - AI auditor of Otel traces - wealth manager advisor - AI data engineer to name most interesting cases without giving too much details but also many chat bots and assistants too
4. 34.▲
   by skull8888888 2y ago

   Totally makes, don't know why I missed agent specific examples... will add them asap. I focused on the Agent because it was initially built for that internally. But you are right, for the release I made it extremely general and to be u
5. 35.▲
   by skull8888888 2y ago

   Noted. I had no intention to be disrespectful in any sense. Just pointing out flaws and reasons why and how current project came to be.
6. 36.▲
   by skull8888888 2y ago

   Thank you for the kind words! Feel free to join our discord https://discord.gg/nNFUUDAKub and discuss stuff there. Also ping me there any time, always happy to help you onboard!
7. 37.▲
   by skull8888888 2y ago

   Totally agree, I encourage you to give Flow a try! Would be more than happy to help you onboard. Also would love to hear if anything is missing.
8. 38.▲
   by skull8888888 2y ago

   Also curious, what kind of agents are you building with LangGraph. Would be more than happy to help you onboard to Flow!
9. 39.▲
   by skull8888888 2y ago

   Thank you! Good question. Behind the scenes, state is manage via Semaphore. So each call to .get(...) acquires a semaphore with a single permit so it essentially guarantees thread-safety. Check out how the state is implemented here https:&
10. 40.▲
    by skull8888888 2y ago

    My main company is Laminar ( https://www.lmnr.ai ) and we actually help folks ship reliable LLM software to prod. We've seen many of our clients successfully do that. Although, the entire space is very new for sure and things
11. 41.▲
    by skull8888888 2y ago

    Thanks! Yep, retry and durability guarantee is on the roadmap for sure, I also wanted to start working on the serverless offering. What kind of workflows are you building with temporal?
12. 42.▲
    by skull8888888 2y ago

    thanks for sharing, looks very interesting! Although, it seems to be very high level and hides all the details behind prompt string. I tend to dislike that kind of things. I designed Flow to be as bare bone as possible and give all control
13. 43.▲
    by skull8888888 2y ago

    True, graph is not wrong per se, but in my experience I saw a lot of problems, the moment it starts to be a little more dynamic. Main problem is predefined edges. That's where you bump into things like conditional edges, cycles edges a
14. 44.▲
    by skull8888888 2y ago

    In some sense yes, task dependencies do form a graph. However, what I meant when I was saying that graph is a wrong abstraction, is that predefined edges is a not the best of writing code when dealing with dynamic systems such as AI Agents.
15. 45.▲
    Show HN: Flow – A dynamic task engine for building AI agents(github.com)

    160 points by skull8888888 2y ago|50 comments
16. 46.▲
    by skull8888888 2y ago

    You are welcome! The easiest way to get started with BAML on Laminar is with our pipeline builder and Structured Output template. Check out the docs here ( https://docs.lmnr.ai/pipeline/introduction )
17. 47.▲
    by skull8888888 2y ago

    Thank you! If langtrace sends Otel spans over http or grps we can ingest it! How would one join OTEL GenAI comittee?
18. 48.▲
    by skull8888888 2y ago

    Have you tried BAML ( https://github.com/boundaryml/baml )? It's really good at structured output parsing. We integrated it directly into our pipeline builder.
19. 49.▲
    by skull8888888 2y ago

    Thank you! Yes, our pipeline builder is a way to build LLM pipelines and expose them as API endpoints! All hosted and managed by Laminar.
20. 50.▲
    by skull8888888 2y ago

    Hey there, answered similar question here https://news.ycombinator.com/item?id=41453674 We really like langfuse, the team and the product. Compared to it: * We send and ingest Otel traces with GenAI semconv * Provide semant
21. 51.▲
    by skull8888888 2y ago

    Thank you! By that we mean, all processing, i.e. data, forward run, evaluator run is done locally in, let's say, Jupyter Notebook. While it's running locally, it sends all the run data / stats to the server for storage and pr
22. 52.▲
    by skull8888888 2y ago

    Hey there, by semantic we mean, embedding text and storing it in the vector DB. Regarding scale, we thought a lot about it, and that's why we process span in the background queue. Tradeoff would be that indexing / embedding would
23. 53.▲
    by skull8888888 2y ago

    Hey there, we priced it that way because of our very generous free tier. Your suggestion of usage based pricing also makes sense. So, in our case it might be something: if you pass 50k spans, then you pay something like $0.001 (not a final
24. 54.▲
    by skull8888888 2y ago

    Yes! Our pipeline builder is pretty versatile. You can define conditional routing, parallel branches, and cycles. Right now we support LLM node and util nodes (json extractor). If you can defined your logic purely from those nodes (and in m
25. 55.▲
    by skull8888888 2y ago

    Now that you mentioned it, > warnings and errors that mislead you it really makes sense. I guess what I was pointing into, is that when you have really rich text (in your case it would be error descriptions), searching over them semantic
26. 56.▲
    by skull8888888 2y ago

    Hey there, apologies for the late reply. > Could you clarify why would some need to analyze LLMs out of all the things? When you want to understand trends of the output of your Agent / RAG on scale, without looking manually at each
27. 57.▲
    by skull8888888 2y ago

    Hey there! Good question. Our main distinguishing features are: * Ingestion of Otel traces * Semantic events-based analytics * Semantically searchable traces * High performance, reliability and efficiency out of the box, thanks to our stack
28. 58.▲
    by skull8888888 2y ago

    Thank you!
29. 59.▲
    by skull8888888 2y ago

    You mean like triggering another processing pipeline from the output of current processing pipeline?
30. 60.▲
    by skull8888888 2y ago

    Thank you! We thought a lot about what would make a great title but couldn't really find anything else which would convey info as densely as current title. We also love our current stack :). I think Rust is perfect language to handle s