Update app.py

app.py

@@ -5,14 +5,18 @@ tokenizer = AutoTokenizer.from_pretrained("merve/chatgpt-prompts-bart-long")
 model = AutoModelForSeq2SeqLM.from_pretrained("merve/chatgpt-prompts-bart-long", from_tf=True)
 
 def generate(prompt):
+    profession = "example profession"  # Replace with your desired profession
+    description = "example"  # Replace with your desired description
 
-    batch = tokenizer(prompt, return_tensors="pt")
-    generated_ids = model.generate(batch["input_ids"], max_new_tokens=150)
+    formatted_prompt = f"You are an expert at {profession} who always {description}.\n\n"
+
+    batch = tokenizer(formatted_prompt, return_tensors="pt")
+    generated_ids = model.generate(batch["input_ids"], max_length=200, num_return_sequences=1)
     output = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
     return output[0]
 
-input_component = gr.Textbox(label = "Input a persona, e.g. photographer", value = "photographer")
-output_component = gr.Textbox(label = "Prompt")
+input_component = gr.Textbox(label="Input a persona, e.g. photographer", value="photographer")
+output_component = gr.Textbox(label="Prompt")
 examples = [["photographer"], ["developer"]]
-description = "This app generates ChatGPT prompts, it's based on a BART model trained on [this dataset](https://huggingface.co/datasets/fka/awesome-chatgpt-prompts). 📓 Simply enter a persona that you want the prompt to be generated based on. 🧙🏻🧑🏻‍🚀🧑🏻‍🎨🧑🏻‍🔬🧑🏻‍💻🧑🏼‍🏫🧑🏽‍🌾"
-gr.Interface(generate, inputs = input_component, outputs=output_component, examples=examples, title = "👨🏻‍🎤 ChatGPT Prompt Generator 👨🏻‍🎤", description=description).launch()
+description = "This app generates ChatGPT prompts. Enter a persona you want the prompt to be based on."
+gr.Interface(generate, inputs=input_component, outputs=output_component, examples=examples, title="👨🏻‍🎤 ChatGPT Prompt Generator 👨🏻‍🎤", description=description).launch()