Upload dism.py

dism.py

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+import nltk
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+
+# Download necessary NLTK data
+nltk.download('punkt')
+
+# Load the OmniParser model and tokenizer
+model_name = "microsoft/OmniParser"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+
+# SQLBot function to generate SQL commands
+def generate_sql_with_omnparser(query):
+    # Encode the input query
+    inputs = tokenizer.encode(query, return_tensors="pt")
+
+    # Generate SQL command
+    outputs = model.generate(inputs, max_length=50)
+    
+    # Decode the generated SQL command
+    sql_command = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return sql_command
+
+# SQLBot function with personality
+def sqlbot(query):
+    gpt_sql_command = generate_sql_with_omnparser(query)
+    
+    # Adding personality to the bot
+    if "create table" in query.lower():
+        response = f"Alright, rolling up my sleeves to create that table for you! Here it is:\n{gpt_sql_command}"
+    elif "select" in query.lower():
+        response = f"Got it! Fetching the data you need:\n{gpt_sql_command}"
+    elif "show tables" in query.lower():
+        response = f"Let me show you all the tables you've got:\n{gpt_sql_command}"
+    elif "insert" in query.lower():
+        response = f"Great! Adding new records as requested:\n{gpt_sql_command}"
+    elif "update" in query.lower():
+        response = f"Time to make some updates! Here you go:\n{gpt_sql_command}"
+    elif "delete" in query.lower():
+        response = f"Okay, we're deleting those records:\n{gpt_sql_command}"
+    else:
+        response = f"Here's what I found:\n{gpt_sql_command}"
+    
+    return response
+
+# Example usage
+user_query = "Create table employees with name age department"
+generated_sql = sqlbot(user_query)
+print(generated_sql)
+
+# Another example usage
+user_query = "Insert into users (name, age) values ('Alice', 30)"
+generated_sql = sqlbot(user_query)
+print(generated_sql)