lchoquel

6 ms·

1. 1.▲
   Why multi-step AI workflows need a new language?(pipelex.com)

   6 points by lchoquel 7mo ago|0 comments
2. 2.▲
   Show HN: Mthds – Beyond skills: a typed DSL for executable AI methods(mthds.ai)

   23 points by lchoquel 7mo ago|1 comments
3. 3.▲
   by lchoquel 8mo ago

   It looks good, lean and clean. The optional ontology is a nice surprise. I was hoping for an SDK like that to plug into Pipelex for building a Knowledge Graph as a source to our multi-step AI workflows, I'll give it a try!
4. 4.▲
   Agent memory: knowledge graphs aren't enough, we need a know-how graph(knowhowgraph.com)

   6 points by lchoquel 10mo ago|1 comments
5. 5.▲
   by lchoquel 10mo ago

   This is a viewpoint on how we represent know-how in AI systems: not just what an organization knows (knowledge graphs, RAG, etc.), but how it does repeatable cognitive work. Web version: < https://knowhowgraph.com/ >
6. 6.▲
   by lchoquel 11mo ago

   Working on it.
7. 7.▲
   by lchoquel 11mo ago

   Hi atombender, you have a point. The current runtime supports asynchronous operations with the limits of python asyncio and your CPU/RAM. But we designed our orchestration layer so that it could integrate easily with durable workflow p
8. 8.▲
   by lchoquel 11mo ago

   Hi teunlao, Currently, a failed step means you need to restart everything: we have started to add features that save intermediate states so you can recover from there but the recovery part is not finished. Our main strategy is to make Pipel
9. 9.▲
   by lchoquel 11mo ago

   We get this question of comparison to BAML often, so let me take the time to clarify the differences: Positioning: • Pipelex is an AI workflow orchestrator. You declare multi-step pipelines (.plx) with LLM calls, OCR/PDF extraction, im
10. 10.▲
    by lchoquel 11mo ago

    Hi cranberryturkey, currently, we offer an open-source API server that you can run on your infrastructure, directly or through our docker image: https://github.com/Pipelex/pipelex-api If what you're after is a hos
11. 11.▲
    by lchoquel 11mo ago

    When the business logic becomes complex, our motto which is to break it down into smaller problems, until they are manageable. Regarding large docs, I know what you mean and we've been there: at one point we considered focusing on that
12. 12.▲
    by lchoquel 11mo ago

    Hi novoreorx, the biggest difference is that in Pipelex workflows, we express the logic in our high-level language, rather than in Python or typescript. This makes it easier to collaborate between tech and non-tech people, like domain exper
13. 13.▲
    by lchoquel 11mo ago

    Hi Clafferty, Providing an MCP server was a no brainer and we have the first version available. But you're right, using "MCP as a client" is a question we have started asking ourselves too. But we haven't had the time to
14. 14.▲
    by lchoquel 11mo ago

    Yes! Clearly the introduction of LLMs into the mix raises the problem of throwing dice. The point of view we chose is: how to orchestrate the collaboration between AI, Software and people? With our aim to have repeatable workflows, this dro
15. 15.▲
    by lchoquel 11mo ago

    Thanks, Ronald! Yes, very interested in discussing integrations. Pipelex is super modular and open by design, so it should be a breeze.
16. 16.▲
    by lchoquel 11mo ago

    Hi RoyTyrell, I guess you could call it low-code, a new kind of no-code where we have natural language in the mix. But no, Pipelex does not generate a python-based agent: the pipelex script is interpreted at runtime.
17. 17.▲
    Show HN: Pipelex – Declarative language for repeatable AI workflows(github.com)

    122 points by lchoquel 11mo ago|27 comments