04. Add web search module

Add web search module

step

1. Perform Naive RAG

2. Check relevance for searched documents (Groundedness Check)

3. (This tutorial) Add Web Search

Reference

• It's an extension from the previous tutorial, so there may be overlapping parts. Please refer to the previous tutorial for insufficient explanation.

Preferences

# !pip install -U langchain-teddynote

# Configuration file for managing API keys as environment variables
from dotenv import load_dotenv

# Load API key information
load_dotenv()

 True 

# Set up LangSmith tracking. https://smith.langchain.com
# !pip install -qU langchain-teddynote
from langchain_teddynote import logging

# Enter a project name.
logging.langsmith("CH17-LangGraph-Structures")

 Start tracking LangSmith. 
[Project name] 
CH17-LangGraph-Structures 

Basic PDF-based Retrieval Chain creation

Here, we create a Retrieval Chain based on PDF documents. Retrieval Chain with the simplest structure.

However, LangGraph creates Retirever and Chain separately. Only then can you do detailed processing for each node.

Reference

• As covered in the previous tutorial, we omit the detailed description.