Re-Work of Our Pipeline Logic for Cycles #8339
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A great starting point to better understand cycles—and a fascinating example of cycles in action—is the ReAct pipeline. 👉 Check it out here: ReAct Haystack Notebook |
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hi, By looking at the documentation for pipelines https://docs.haystack.deepset.ai/docs/pipelines it is not evident the exact rule of what actually triggers a component in the pipeline. I saw some questions people asking about default values / pipeline inputs / connected inputs. So in terms of cycles, what if we have all nodes connected in a loop, with all nodes receiving pipeline inputs, but also all nodes are connected as well, and all node have some non-connected inputs which have default values. I know its hypothetical but if we plan to have a robust pipeline execution logic I believe it should be based on rules so it should be easy to answer where such pipeline will start its execution and how it works exactly. It should be possible to grasp the logic by just looking at pipeline diagram without actually testing it and then finding out how it works , or by looking in implementation - e.g. running queues vs waiting queues). I think a good documentation with deterministic rules would be helpful. |
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We plan to have a better explanation on how the new Pipeline logic will work. I agree that the current documentation is not the best explanation of the current state of the Pipeline though. We planned to write some more detailed documentation in the months but decided to put that on hold cause of the above rework. I completely agree that one should be able to understand how a Pipeline will run just by looking at it. My goal with this rework is exactly this, having a easily predictable way to undestand the execution flow of a Pipeline. Without knowing the whole nitty gritty of the internals. Though that's not easy at all. The main problems with our Pipelines are cycles. If you remove those completely you have a graph that is easy to sort and traverse, and thus execute. This new approach is the best effort really. Covering every use case is basically impossible. I test the Pipeline with the most common use cases, but predicting or knowing all possible graphs combinations and testing them is not feasible. The problem space is immense and I have no doubt that we'll discover use cases in the future that we can't support. I don't think we'll support every possible comination. Though I think this approach is the solution that solves most of the common problems. |
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hi @silvanocerza , I was am trying to test the following pipeline with a loop https://colab.research.google.com/drive/1YHJ8-NgGdtP3yRQXfyXSSKeAWZ2iYb3Y?usp=sharing and got confused about the order of execution. In particular , I am not sure the "sum_1" should run twice.. Can you please take a look ? thanks |
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The re-work of our pipeline logic for cycles has been released with Haystack 2.7: https://github.com/deepset-ai/haystack/releases/tag/v2.7.0 |
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With Haystack 2.0, our pipelines which also allow for loops and cycles became a lot more flexible than they were with Haystack 1.x.
However, we also noticed in the last few weeks that the current logic can have some issues when it comes to validation, as well as some unpredictable behaviour when there are cycles in the pipeline.
Overall, the problems we noticed happened in incredibly complex pipeline architectures, where components may run when they are not supposed to, the pipeline returned partial results etc.
So, we’ve worked on re-architecting the underlying pipeline logic to make sure pipelines with cycles run as expected no matter the architectural complexity of the pipeline.
What now?
Our re-work is not yet released because we need your help!
All our internal tests of the core logic are passing. We’re really confident in the robustness of the rework but given the wide range of possible ways to build a Pipeline we can’t know if we missed some small corner case.
That’s why we ask you, our community, for some help testing this out.
To test this new logic install directly from the
subgraphbranch with the following command:This is based on the latest
v2.5.1release and has the same set of features apart from the differentPipeline.run()logic.Once released, we also plan to write a nice blog post to explain the inner workings of this rework.
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