tools.py

import streamlit as st
from langchain.prompts.prompt import PromptTemplate
from supabase.client import Client, create_client
from langchain.tools.retriever import create_retriever_tool
from langchain_openai import OpenAIEmbeddings
from langchain_community.vectorstores import SupabaseVectorStore

supabase_url = st.secrets["SUPABASE_URL"]
supabase_key = st.secrets["SUPABASE_SERVICE_KEY"]
supabase: Client = create_client(supabase_url, supabase_key)


embeddings = OpenAIEmbeddings(
    openai_api_key=st.secrets["OPENAI_API_KEY"], model="text-embedding-ada-002"
)
vectorstore = SupabaseVectorStore(
    embedding=embeddings,
    client=supabase,
    table_name="documents",
    query_name="v_match_documents",
)


retriever_tool = create_retriever_tool(
    vectorstore.as_retriever(),
    name="Database_Schema",
    description="Search for database schema details",
)