Create ai_agent.py

ai_agent.py

@@ -0,0 +1,37 @@
+import getpass
+import os
+import pandas as pd
+import tabulate
+from sqlalchemy import create_engine
+
+from langchain_community.utilities import SQLDatabase
+from langchain_community.agent_toolkits import create_sql_agent
+from langchain_openai import ChatOpenAI
+from langchain.output_parsers.openai_tools import JsonOutputKeyToolsParser
+from langchain_experimental.agents import create_pandas_dataframe_agent
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_experimental.tools import PythonAstREPLTool
+from langchain_experimental.agents import create_pandas_dataframe_agent
+
+# Get the API key
+api_key = os.getenv('OPENAI_API_KEY')
+llm = ChatOpenAI(model="gpt-3.5-turbo", temperature=0.5)
+
+def sql_agent(file, agent_input):
+    # Read the uploaded file into a DataFrame
+    df = pd.read_csv(file)
+    # Create SQLAlchemy engine
+    engine = create_engine("sqlite:///uploaded_data.db")
+    # Write the DataFrame to the SQLite database
+    df.to_sql("uploaded_data", engine, index=False, if_exists='replace')
+    db = SQLDatabase(engine=engine)
+    # Create SQL agent
+    agent_executor = create_sql_agent(llm, db=db, agent_type="openai-tools", verbose=True)
+    agent_output = agent_executor.invoke(agent_input)
+    return agent_output
+
+def pandas_agent(file, agent_input):
+    df = pd.read_csv(file)
+    agent = create_pandas_dataframe_agent(llm, df, agent_type="openai-tools", verbose=True)
+    agent_output = agent.invoke(agent_input)
+    return agent_output