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"""

Obtain data from https://sectors.app

Accompanying course material: https://sectors.app/bulletin/ai-search

"""

from dotenv import load_dotenv

import pandas as pd

from langchain_community.utilities import SQLDatabase

from sqlalchemy import create_engine

from langchain_groq import ChatGroq

from langchain_community.agent_toolkits import create_sql_agent

import os

# from langchain_deepseek import ChatDeepSeek

load_dotenv()

if not os.path.exists('industry.db'):

print("Creating industry.db")

df = pd.read_csv('./datasets/industry-leaders-full.csv')

engine = create_engine('sqlite:///industry.db')

df.to_sql("industry", engine, index=False, if_exists='replace')

else:

# connect to the existing database, dont create

engine = create_engine('sqlite:///industry.db')

db = SQLDatabase(engine=engine)

print(db.get_usable_table_names())

# query = "SELECT * FROM industry WHERE sub_industry LIKE '%banks%'"

query2 = "SELECT * FROM industry WHERE total_market_cap > 1e14"

print(db.run(query2))

llm = ChatGroq(

model_name="llama-3.3-70b-versatile" # Updated from deprecated llama3-70b-8192

)

# llm = ChatDeepSeek(

# model="deepseek-chat"

# )

agent_executor = create_sql_agent(llm, db=db, agent_type="tool-calling", verbose=True)

agent_executor.invoke({

"input": "what are the top market cap gainers for companies in the coal industry? Return in markdown table."

})