import {
tool,
createAgent,
createMiddleware,
ToolMessage,
context,
type ToolRuntime,
} from "langchain";
import { MemorySaver, Command } from "@langchain/langgraph";
import { ChatOpenAI } from "@langchain/openai";
import { v4 as uuidv4 } from "uuid";
import { z } from "zod";
// A skill that can be progressively disclosed to the agent
const SkillSchema = z.object({
name: z.string(), // Unique identifier for the skill
description: z.string(), // 1-2 sentence description to show in system prompt
content: z.string(), // Full skill content with detailed instructions
});
type Skill = z.infer<typeof SkillSchema>;
const SKILLS: Skill[] = [
{
name: "sales_analytics",
description:
"Database schema and business logic for sales data analysis including customers, orders, and revenue.",
content: context`
# Sales Analytics Schema
## Tables
### customers
- customer_id (PRIMARY KEY)
- name
- email
- signup_date
- status (active/inactive)
- customer_tier (bronze/silver/gold/platinum)
### orders
- order_id (PRIMARY KEY)
- customer_id (FOREIGN KEY -> customers)
- order_date
- status (pending/completed/cancelled/refunded)
- total_amount
- sales_region (north/south/east/west)
### order_items
- item_id (PRIMARY KEY)
- order_id (FOREIGN KEY -> orders)
- product_id
- quantity
- unit_price
- discount_percent
## Business Logic
**Active customers**: status = 'active' AND signup_date <= CURRENT_DATE - INTERVAL '90 days'
**Revenue calculation**:
Only count orders with status = 'completed'. Use total_amount from orders table,
which already accounts for discounts.
**Customer lifetime value (CLV)**:
Sum of all completed order amounts for a customer.
**High-value orders**:
Orders with total_amount > 1000
## Example Query
-- Get top 10 customers by revenue in the last quarter
SELECT
c.customer_id,
c.name,
c.customer_tier,
SUM(o.total_amount) as total_revenue
FROM customers c
JOIN orders o ON c.customer_id = o.customer_id
WHERE o.status = 'completed'
AND o.order_date >= CURRENT_DATE - INTERVAL '3 months'
GROUP BY c.customer_id, c.name, c.customer_tier
ORDER BY total_revenue DESC
LIMIT 10;`,
},
{
name: "inventory_management",
description:
"Database schema and business logic for inventory tracking including products, warehouses, and stock levels.",
content: context`
# Inventory Management Schema
## Tables
### products
- product_id (PRIMARY KEY)
- product_name
- sku
- category
- unit_cost
- reorder_point (minimum stock level before reordering)
- discontinued (boolean)
### warehouses
- warehouse_id (PRIMARY KEY)
- warehouse_name
- location
- capacity
### inventory
- inventory_id (PRIMARY KEY)
- product_id (FOREIGN KEY -> products)
- warehouse_id (FOREIGN KEY -> warehouses)
- quantity_on_hand
- last_updated
### stock_movements
- movement_id (PRIMARY KEY)
- product_id (FOREIGN KEY -> products)
- warehouse_id (FOREIGN KEY -> warehouses)
- movement_type (inbound/outbound/transfer/adjustment)
- quantity (positive for inbound, negative for outbound)
- movement_date
- reference_number
## Business Logic
**Available stock**:
quantity_on_hand from inventory table where quantity_on_hand > 0
**Products needing reorder**:
Products where total quantity_on_hand across all warehouses is
less than or equal to the product's reorder_point
**Active products only**:
Exclude products where discontinued = true unless specifically
analyzing discontinued items
**Stock valuation**:
quantity_on_hand * unit_cost for each product
## Example Query
-- Find products below reorder point across all warehouses
SELECT
p.product_id,
p.product_name,
p.reorder_point,
SUM(i.quantity_on_hand) as total_stock,
p.unit_cost,
(p.reorder_point - SUM(i.quantity_on_hand)) as units_to_reorder
FROM products p
JOIN inventory i ON p.product_id = i.product_id
WHERE p.discontinued = false
GROUP BY p.product_id, p.product_name, p.reorder_point, p.unit_cost
HAVING SUM(i.quantity_on_hand) <= p.reorder_point
ORDER BY units_to_reorder DESC;`,
},
];
// const loadSkill = tool(
// async ({ skillName }) => {
// // Find and return the requested skill
// const skill = SKILLS.find((s) => s.name === skillName);
// if (skill) {
// return `Loaded skill: ${skillName}\n\n${skill.content}`;
// }
// // Skill not found
// const available = SKILLS.map((s) => s.name).join(", ");
// return `Skill '${skillName}' not found. Available skills: ${available}`;
// },
// {
// name: "load_skill",
// description: `Load the full content of a skill into the agent's context.
// Use this when you need detailed information about how to handle a specific
// type of request. This will provide you with comprehensive instructions,
// policies, and guidelines for the skill area.`,
// schema: z.object({
// skillName: z.string().describe("The name of the skill to load"),
// }),
// }
// );
// Build skills prompt from the SKILLS list
const skillsPrompt = SKILLS.map(
(skill) => `- **${skill.name}**: ${skill.description}`
).join("\n");
const skillMiddleware = createMiddleware({
name: "skillMiddleware",
tools: [loadSkill],
wrapModelCall: async (request, handler) => {
// Build the skills addendum
const skillsAddendum =
`\n\n## Available Skills\n\n${skillsPrompt}\n\n` +
"Use the load_skill tool when you need detailed information " +
"about handling a specific type of request.";
// Append to system prompt
const newSystemPrompt = request.systemPrompt + skillsAddendum;
return handler({
...request,
systemPrompt: newSystemPrompt,
});
},
});
const model = new ChatOpenAI({
model: "gpt-4.1-mini",
temperature: 0,
});
// Create the agent with skill support
const agent = createAgent({
model,
systemPrompt:
"You are a SQL query assistant that helps users " +
"write queries against business databases.",
middleware: [skillMiddleware],
checkpointer: new MemorySaver(),
});
// Configuration for this conversation thread
const threadId = uuidv4();
const config = { configurable: { thread_id: threadId } };
// Ask for a SQL query
const result = await agent.invoke(
{
messages: [
{
role: "user",
content:
"Write a SQL query to find all customers " +
"who made orders over $1000 in the last month",
},
],
},
config
);
// Print the conversation
for (const message of result.messages) {
console.log(`${message.type}: ${message.content}`);
}
