File size: 723 Bytes
0321eee |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 |
"""
This file contains the tools for the RAG workflow.
"""
import os
from groundx import GroundX
from dotenv import load_dotenv
load_dotenv()
client = GroundX(api_key=os.getenv("GROUNDX_API_KEY") or '')
def search_groundx_for_rag_context(query: str) -> str:
"""
Searches and retrieves relevant context from a knowledge base,
based on the user's query.
Args:
query: The search query supplied by the user.
Returns:
str: Relevant text content that can be used by the LLM to answer the query.
"""
response = client.search.content(
id=os.getenv("GROUNDX_BUCKET_ID"),
query=query,
n=10,
)
return response.search.text or "No relevant context found" |