Add application file

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# Initialize the model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained("defog/sqlcoder-70b-alpha")
+model = AutoModelForCausalLM.from_pretrained("defog/sqlcoder-70b-alpha")
+
+def generate_sql(prompt):
+    """Generate SQL code based on the provided prompt"""
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+    
+    # Generate SQL code
+    outputs = model.generate(
+        inputs.input_ids,
+        max_length=1024,
+        temperature=0.1,
+        do_sample=True,
+        pad_token_id=tokenizer.eos_token_id
+    )
+    
+    # Decode the generated SQL
+    sql_code = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    
+    return sql_code
+
+# Create Gradio interface
+demo = gr.Interface(
+    fn=generate_sql,
+    inputs=gr.Textbox(lines=5, placeholder="Describe the SQL query you need..."),
+    outputs=gr.Textbox(lines=10, label="Generated SQL"),
+    title="SQL Code Generator",
+    description="Generate SQL code using defog/sqlcoder-70b-alpha. Enter your request in natural language."
+)
+
+# Launch the app
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+gradio>=3.50.0
+transformers>=4.30.0
+torch>=2.0.0
+accelerate>=0.20.0