:mag: 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.
Describe the bug
query_embedder, retriever Connecting components raises an error.
Error message
PipelineConnectError: 'query_embedder.embedding does not exist. Output connections of query_embedder are: documents (type List[Document])
Expected behavior
Not raise any errors. Connect is made between query and retriever
Describe the bug query_embedder, retriever Connecting components raises an error.
Error message PipelineConnectError: 'query_embedder.embedding does not exist. Output connections of query_embedder are: documents (type List[Document])
Expected behavior Not raise any errors. Connect is made between query and retriever
To Reproduce
FAQ Check
System: