Explore Edge Craft RAG¶

ChatQnA with LLM Example in UI¶

Create Pipeline¶

To create a default pipeline, you need to click the Create Pipeline button in the Pipeline Setting page. create_pipeline

Then follow the pipeline create guide in UI to set your pipeline, please note that in Indexer Type you can set MilvusVector as indexer(Please make sure Milvus is enabled before set MilvusVector as indexer, you can refer to Enable Milvus).
if choosing MilvusVector, you need to verify vector uri first, please input ‘Your_IP:milvus_port’ then click Test button. Note that milvus_port is 19530 milvus

Then, In Generator config page, choose LLM Inference Type to Vllm.
In Large Language Model field, input your LLM_MODEL name, e.g. ‘Qwen/Qwen3-8B’.
In Vllm Url field, you need to input ‘IP:vllm_port’ then click Test button. Note that defaultly vllm_port is ‘8086’
(Note if the test fails, it might be because vLLM service not ready yet, you can wait for 30s and try again) generator

You can also create multiple pipelines or update/remove existing pipelines through the Operation field, but please note that active pipelines cannot be updated. pipeline_operation

Upload files & ChatQnA¶

After the pipeline creation, you can go to Knowledge Base page and click Create Knowledge Base button to create your knowledge base. upload_data

When creating Knowledge base, please choose Activated option, since only the files in activated Knowledge base can be retrieved in ChatQnA upload_data

After knowledge base creation, you can upload the documents for retrieval. upload_data

Then, you can submit messages in the chat box in Chat page. chat_with_rag