Update app.py

app.py

@@ -4,45 +4,40 @@ from huggingface_hub import hf_hub_download
 import gradio as gr
 import time
 
-
-
+# Download the model from Hugging Face
 model_path = hf_hub_download(
-    repo_id="omeryentur/phi-3-sql",
-    filename="phi-3-sql.Q4_K_M.gguf",
+    repo_id="omeryentur/phi-3-sql", 
+    filename="phi-3-sql.Q4_K_M.gguf", 
     use_auth_token=True
 )
 
+# Initialize the Llama model
 llm = Llama(
-    model_path=model_path,
-    n_ctx=512,
+    model_path=model_path, 
+    n_ctx=512, 
     n_threads=1,
 )
 
-def generate_sql_query(text_input_schema:str,text_input_question: str):
-    global pattern_counter
-    
+def generate_sql_query(text_input_schema: str, text_input_question: str):
     try:
-        prompt = f"""<|system|>
-            {text_input_schema}
-
-            <|user|>
-            {text_input_question}
-
-            <|sql|>"""
+        # Construct the prompt for the model
+        prompt = f"""<|system|> {text_input_schema} <|user|> {text_input_question} <|sql|>"""
         
+        # Generate SQL query
         completion = llm(
-            prompt,
-            max_tokens=512,
-            temperature=0,
+            prompt, 
+            max_tokens=512, 
+            temperature=0, 
             stop=["<end_of_turn>"]
         )
         
-        generated_pattern = completion['choices'][0]['text'].strip()     
+        # Extract and return the generated SQL query
+        generated_pattern = completion['choices'][0]['text'].strip()
         return generated_pattern
-        
     except Exception as e:
-        return {"error": e}
+        return {"error": str(e)}
 
+# Create Gradio interface
 with gr.Blocks() as demo:
     gr.Markdown("# Sql Query")
     
@@ -51,14 +46,14 @@ with gr.Blocks() as demo:
             text_input_schema = gr.TextArea(label="Schema")
             text_input_question = gr.Textbox(label="question")
             generate_btn = gr.Button("Create Sql Query")
-        
+    
     with gr.Row():
         with gr.Column():
             output = gr.JSON(label="Sql Query:")
     
     generate_btn.click(
-        fn=generate_sql_query,
-        inputs=[text_input_schema,text_input_question],
+        fn=generate_sql_query, 
+        inputs=[text_input_schema, text_input_question], 
         outputs=[output]
     )