RAG Agent

This RAG Agent uses GPT-4 Turbo LLM model with a simple prompt for straightforward integration.

How to Use this RAG Agent? 

Using Clarifai SDK

Export your PAT as an environment variable. Then, import and initialize the API Client.

Find your PAT in your security settings.

export CLARIFAI_PAT={your personal access token}

Upload your Data 

Upload you data in the Clarifai App to chat with RAG Agent.

from clarifai.rag import RAG

rag_agent = RAG.setup(
app_url= "https://clarifai.com/clarifai/rag-template",)
rag_agent.upload(folder_path = "/app/files", chunk_size= 512, chunk_overlap= 50)

folder_path  Folder path to the documents.

chunk_size: Chunk size for splitting the document.

chunk_overlap: The token overlap of each chunk when splitting.

Chat with the your Data  using RAG Agent

from clarifai.rag import RAG

rag_agent = RAG(workflow_url='https://clarifai.com/clarifai/rag-template/workflows/rag-agent-gpt4-turbo-naive')
rag_agent.chat(messages=[{"role":"human", "content":"What is Clarifai"}])

Using Workflow

To utilize RAG Agents, you can input a query through the Blue Plus Try your own Input button. This incorporates all the documents in the Inputs as external data in RAG.