Create app.py

app.py

@@ -0,0 +1,54 @@
+import os
+import pandas as pd
+
+from dotenv import load_dotenv
+
+from flask import request, Flask, jsonify
+
+from langchain.agents.agent_types import AgentType
+from langchain_experimental.agents.agent_toolkits import create_pandas_dataframe_agent
+
+from langchain_openai import ChatOpenAI
+
+load_dotenv()
+
+gpt35 = ChatOpenAI(
+    model_name="gpt-3.5-turbo",
+    api_key=os.environ.get("OPENAI_API_KEY"),
+    temperature=0
+)
+
+data_file = "dataset_43718.pq"
+bank_data = pd.read_parquet(data_file)
+
+pandas_agent = create_pandas_dataframe_agent(
+    llm=gpt35,
+    df=bank_data,
+    verbose=False,
+    agent_type=AgentType.OPENAI_FUNCTIONS,
+    allow_dangerous_code=True
+)
+
+dataframe_agent_api = Flask("DataFrame Agent")
+
+@dataframe_agent_api.get('/')
+def home():
+    return 'Welcome to the DataFrame Agent'
+
+@dataframe_agent_api.post('/v1/input')
+def predict():
+
+   user_input = request.get_data(as_text=True)
+
+   try:
+       response = pandas_agent.invoke(user_input)
+
+       prediction = response['output']
+
+   except Exception as e:
+       prediction = e
+        
+   return jsonify({'output': prediction})
+
+if __name__ == '__main__':
+    dataframe_agent_api.run(debug=True, host='0.0.0.0', port=8000)