Create app.py

app.py

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+import gradio as gr
+from tools import FreightAgent, EXAMPLE_QUERIES
+from utils import initialize_database
+from smolagents import CodeAgent, OpenAIServerModel
+import os
+from dotenv import load_dotenv
+from sql_data import sql_query, get_schema, get_csv_as_dataframe
+
+# Load environment variables
+load_dotenv()
+
+# Initialize the database if it doesn't exist
+if not os.path.exists("freights.db"):
+    csv_url = "https://huggingface.co/datasets/sasu-SpidR/fretmaritime/resolve/main/freights.csv"
+    initialize_database(csv_url)
+
+# Create the main agent
+model_id = "gpt-4.1-mini"
+model = OpenAIServerModel(model_id=model_id, api_key=os.environ["OPENAI_API_KEY"])
+
+agent = CodeAgent(tools=[sql_query, get_schema, get_csv_as_dataframe], model=model)
+
+def run_agent(question: str) -> str:
+    """
+    Run the agent with the given question.
+    This ReAct Agent can make request to give you information about the freight data.
+
+    Args:
+        question: The question to run the agent with.
+    Returns:
+        The response of the agent.
+    """
+    return agent.run(question,max_steps=5)
+
+
+if __name__ == "__main__":
+    gr.Interface(
+        fn=run_agent,
+        inputs=gr.Textbox(lines=7, label="Question"),
+        outputs=gr.Textbox(),
+        title="Freight Agent MCP",
+        description="Ask a question about the freight data in natural language",
+        examples=EXAMPLE_QUERIES if "EXAMPLE_QUERIES" in globals() else None
+    ).launch(mcp_server=True)
+