Update app.py

app.py

@@ -1,33 +1,102 @@
 import openai
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 import gradio as gr
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 import os
 
-secret = os.environ["Secret"]
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 #OpenAi call
-def regex(texts):
-    openai.api_key = (secret)
-    response = openai.Completion.create(
-      engine="code-davinci-002",
-      prompt= texts,
-          temperature=0,
-          max_tokens=750,
-          top_p=1,
-          frequency_penalty=0.0,
-          presence_penalty=0.0,
-          stop = (";", "/*", "</code>")
-    )
-    x = response.choices[0].text 
-    
-    return x
-
-# Function to elicit regex response from model
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+def gpt3(texts):
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+   openai.api_key = os.environ["Secret"]
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+   response = openai.Completion.create(
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+     engine="code-davinci-002",
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+     prompt= texts,
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+         temperature=0,
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+         max_tokens=750,
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+         top_p=1,
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+         frequency_penalty=0.0,
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+         presence_penalty=0.0,
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+         stop = (";", "/*", "</code>")
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+   )
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+   x = response.choices[0].text
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+  
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+   return x
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+# Function to elicit sql response from model
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 def greet(prompt):
-    txt= (f'''Perfect Regex Generator \n #Prompt: {prompt}\n#Regex:\n''')
-    regex = gpt3(txt)
-    return regex
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+   txt= (f'''/*Prompt: {prompt}*/ \n —-SQL Code:\n''')
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+   sql = gpt3(txt)
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+   return sql
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+
 
 
 #Code to set up Gradio UI
-iface = gr.Interface(greet, inputs = ["text"], outputs = "text",title="Natural Language to Regex", description="Enter any prompt and get a regex statement back! For better results, give it more context")
-iface.launch()
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+iface = gr.Interface(greet, inputs = ["text"], outputs = "text",title="Natural Language to SQL", description="Enter any prompt and get a SQL statement back! For better results, give it more context")
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+iface.launch()
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