# 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](../assets/img/create_pipeline.png)

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](../README.md#start-edge-craft-rag-services-with-docker-compose)).  
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](../assets/img/milvus.png)

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](../assets/img/generator.png)

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](../assets/img/pipeline_operation.png)

### 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](../assets/img/kb_create.png)

When creating Knowledge base, please choose `Activated` option, since only the files in activated Knowledge base can be retrieved in ChatQnA
![upload_data](../assets/img/kb.png)

After knowledge base creation, you can upload the documents for retrieval.
![upload_data](../assets/img/upload_file.png)

Then, you can submit messages in the chat box in `Chat` page.
![chat_with_rag](../assets/img/chatqna.png)