V4

app.py

@@ -5,19 +5,42 @@ import transformers
 
 openai.api_key = os.environ["api"]
 
-generator = transformers.pipeline("text-generation", model="EleutherAI/gpt-neo-2.7B")
 
 def generateBlogTopics(prompt1):
-    response = generator("Generate blog topics on: {}. \n \n 1.  ".format(prompt1), max_length=100, do_sample=True, temperature=0.7)[0]["generated_text"]
-    return response
+    response = openai.Completion.create(
+        engine="text-davinci-002",
+        prompt="Generate blog topics on: {}. \n \n 1.  ".format(prompt1),
+        max_tokens=100,
+        n=1,
+        stop=None,
+        temperature=0.7,
+    )
+
+    return response.choices[0].text
 
 def generateBlogSections(prompt1):
-    response = generator("Expand the blog title in to high level blog sections: {} \n\n- Introduction: ".format(prompt1), max_length=100, do_sample=True, temperature=0.6)[0]["generated_text"]
-    return response
+    response = openai.Completion.create(
+        engine="text-davinci-002",
+        prompt="Expand the blog title in to high level blog sections: {} \n\n- Introduction: ".format(prompt1),
+        max_tokens=100,
+        n=1,
+        stop=None,
+        temperature=0.6,
+    )
+
+    return response.choices[0].text
 
 def blogSectionExpander(prompt1):
-    response = generator("Expand the blog section in to a detailed professional, witty and clever explanation.\n\n {}".format(prompt1), max_length=400, do_sample=True, temperature=0.7)[0]["generated_text"]
-    return response
+    response = openai.Completion.create(
+        engine="text-davinci-002",
+        prompt="Expand the blog section in to a detailed professional, witty and clever explanation.\n\n {}".format(prompt1),
+        max_tokens=400,
+        n=1,
+        stop=None,
+        temperature=0.7,
+    )
+
+    return response.choices[0].text
 
 input_text = gr.inputs.Textbox(lines=5, label="Enter prompt text here:")