How I rephase my user query by retriever tool?

[mraguth]

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Example Code

import ast
import re
from langchain.agents.agent_toolkits import create_retriever_tool
from langchain_community.vectorstores import FAISS
from langchain_core.example_selectors import SemanticSimilarityExampleSelector

# Create a vector store from the combined list of artists and albums
vector_db_f = FAISS.from_texts(names1, embeddings)
# Create a retriever from the vector store, retrieving the top 5 similar items
retriever_f = vector_db_f.as_retriever(search_kwargs={"k": 1})

# Description for the retriever tool
description = """
As an AI agent, your task is to match human query text with entries in the vector database. Use word cardinality to compare the frequency of each word in both texts, selecting the most similar proper nouns based on approximate spelling. Ensure accuracy by double-checking each word. Replace the human-given string with the best matches from the vector database, keeping the overall sentence structure intact.
"""

# Create the retriever tool with the specified name and description
retriever_tool = create_retriever_tool(
    retriever_f,
    name="search_proper_nouns",
    description=description,
)

Description

Can I have sample code either from Langgraph or Langchain by using above tool to replace my user query?
My objective is 'user query' need to be replaced by vector search before it goes to LLM. The code snippet I have here is below. Now I like to tie with either agent or langgraph. Please help.

import ast
import re
from langchain.agents.agent_toolkits import create_retriever_tool
from langchain_community.vectorstores import FAISS
from langchain_core.example_selectors import SemanticSimilarityExampleSelector

# Create a vector store from the combined list of artists and albums
vector_db_f = FAISS.from_texts(names1, embeddings)
# Create a retriever from the vector store, retrieving the top 5 similar items
retriever_f = vector_db_f.as_retriever(search_kwargs={"k": 1})

# Description for the retriever tool
description = """
As an AI agent, your task is to match human query text with entries in the vector database. Use word cardinality to compare the frequency of each word in both texts, selecting the most similar proper nouns based on approximate spelling. Ensure accuracy by double-checking each word. Replace the human-given string with the best matches from the vector database, keeping the overall sentence structure intact.
"""

# Create the retriever tool with the specified name and description
retriever_tool = create_retriever_tool(
    retriever_f,
    name="search_proper_nouns",
    description=description,
)

System Info

Name: langchain
Version: 0.3.2