AI orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
Small utility that ease visualization of a Pipeline graph.
To use it we just need to add a new Then step in a scenario like so:
Scenario Outline: Running a correct Pipeline
Given a pipeline <kind>
When I run the Pipeline
Then draw it to file
Then it should return the expected result
And components ran in the expected order
The images will be saved in a test_pipeline_graphs folder in the project's root.
This just an utility step meant to be used locally to ease some debugging.
Proposed Changes:
Small utility that ease visualization of a Pipeline graph.
To use it we just need to add a new
Then
step in a scenario like so:The images will be saved in a
test_pipeline_graphs
folder in the project's root. This just an utility step meant to be used locally to ease some debugging.How did you test it?
I added a
Then
step to a scenario and run it.Notes for the reviewer
N/A
Checklist
fix:
,feat:
,build:
,chore:
,ci:
,docs:
,style:
,refactor:
,perf:
,test:
.