SQL Queries & Data Management

from timbal import Agent, Tool
from timbal.platform.kbs.tables import create_table, import_records, query, get_tables, get_table

agent = Agent(
    name="SupportAnalyst",
    model="openai/gpt-4.1-mini",
    system_prompt=("""
        You are a support data manager. Help users add tickets to the database and analyze the data. Be conversational and helpful.
        
        Configuration:
        - org_id: 'your-org-id'
        - kb_id: 'your-kb-id' 
        - table_name: 'tickets'
        
        If the tickets table doesn't exist, create it immediately without asking for confirmation.
        Always use these configuration values when calling KB functions.
    """),
    tools=[
        Tool(handler=get_tables, description="Use it to check if a table it is already created"),
        Tool(handler=get_table, description="Use it to get the table definition"),
        Tool(handler=create_table, description="Use it to create the table"),
        Tool(handler=query, description="Use it to query the table"),
        Tool(handler=import_records, description="Use it to import records to the table")
    ]  # Add multiple KB functions as tools
) 

# First conversation: Adding records to the knowledge base
await agent(
    prompt="I need to add a new support ticket. Customer ID 103 reported a login issue with high priority."
).collect()

# Second conversation: Querying the data we just added
result2 = await agent(
    prompt="How many high priority tickets do we have from customer 103?"
).collect()

print(result2.output.collect_text())

# There is currently 1 high priority ticket from customer 103. Would you like to see more details or do anything else?