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import os
from dotenv import load_dotenv
from langchain_community.utilities import SQLDatabase
from langchain_community.agent_toolkits import create_sql_agent
from langchain_openai import ChatOpenAI
from huggingface_hub import notebook_login
# from huggingface_hub import hf_secrets
# Load environment variables from .env file
def initiate_chat(querry):
load_dotenv()
notebook_login()
# Set environment variables for API keys
# os.environ["OPENAI_API_KEY"] = os.getenv("OPENAI_API_KEY")
# os.environ["LANGCHAIN_API_KEY"] = os.getenv("LANGCHAIN_API_KEY")
# os.environ["LANGCHAIN_TRACING_V2"] = "true"
# Define the SQL database URI
db_uri = "sqlite:///db.db"
# Initialize the SQLDatabase object
db = SQLDatabase.from_uri(db_uri)
import os
api_key = os.getenv("open_ai")
# Initialize the ChatOpenAI object with the desired model
llm = ChatOpenAI(model="gpt-3.5-turbo", temperature=0, api_key=api_key)
# llm = ChatOpenAI(model="gpt-3.5-turbo", temperature=0)
# Create the SQL agent
agent_executor = create_sql_agent(llm, db=db, agent_type="openai-tools", verbose=True)
# Define the query to get the sum of all salaries
# Execute the query using the agent
try:
result = agent_executor.invoke(querry)
return result
except Exception as e:
print(f"Error: {e}")
return "Error: " + str(e)
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