Test

app.py

@@ -4,7 +4,7 @@ from huggingface_hub import InferenceClient
 """
 For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
 """
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+client = InferenceClient("Qwen/Qwen2.5-Coder-7B-Instruct")
 
 
 def respond(
@@ -15,7 +15,61 @@ def respond(
     temperature,
     top_p,
 ):
-    messages = [{"role": "system", "content": system_message}]
+    sytems = """ 
+### Instructions:
+Your task is to convert a question into a SQL query, given a Postgres database schema.
+Adhere to these rules:
+- **Deliberately go through the question and database schema word by word** to appropriately answer the question
+- **Use Table Aliases** to prevent ambiguity. For example, `SELECT table1.col1, table2.col1 FROM table1 JOIN table2 ON table1.id = table2.id`.
+- When creating a ratio, always cast the numerator as float
+
+### Input:
+Generate a SQL query that answers the question `{question}`.
+This query will run on a database whose schema is represented in this string:
+CREATE TABLE products (
+  product_id INTEGER PRIMARY KEY, -- Unique ID for each product
+  name VARCHAR(50), -- Name of the product
+  price DECIMAL(10,2), -- Price of each unit of the product
+  quantity INTEGER  -- Current quantity in stock
+);
+
+CREATE TABLE customers (
+   customer_id INTEGER PRIMARY KEY, -- Unique ID for each customer
+   name VARCHAR(50), -- Name of the customer
+   address VARCHAR(100) -- Mailing address of the customer
+);
+
+CREATE TABLE salespeople (
+  salesperson_id INTEGER PRIMARY KEY, -- Unique ID for each salesperson
+  name VARCHAR(50), -- Name of the salesperson
+  region VARCHAR(50) -- Geographic sales region
+);
+
+CREATE TABLE sales (
+  sale_id INTEGER PRIMARY KEY, -- Unique ID for each sale
+  product_id INTEGER, -- ID of product sold
+  customer_id INTEGER,  -- ID of customer who made purchase
+  salesperson_id INTEGER, -- ID of salesperson who made the sale
+  sale_date DATE, -- Date the sale occurred
+  quantity INTEGER -- Quantity of product sold
+);
+
+CREATE TABLE product_suppliers (
+  supplier_id INTEGER PRIMARY KEY, -- Unique ID for each supplier
+  product_id INTEGER, -- Product ID supplied
+  supply_price DECIMAL(10,2) -- Unit price charged by supplier
+);
+
+-- sales.product_id can be joined with products.product_id
+-- sales.customer_id can be joined with customers.customer_id
+-- sales.salesperson_id can be joined with salespeople.salesperson_id
+-- product_suppliers.product_id can be joined with products.product_id
+
+### Response:
+Based on your instructions, here is the SQL query I have generated to answer the question `{question}`:
+```sql
+"""
+    messages = [{"role": "system", "content": sytems}]
 
     for val in history:
         if val[0]:
@@ -46,7 +100,6 @@ For information on how to customize the ChatInterface, peruse the gradio docs: h
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
         gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
         gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
         gr.Slider(