Update app.py

app.py

@@ -1,42 +1,20 @@
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 import gradio as gr
-import requests
-from PIL import Image
-from io import BytesIO
-import base64
 
-api_url = "https://5cb20b40-572c-426f-9466-995256f9b6eb.id.repl.co/generate_image"
+tokenizer = AutoTokenizer.from_pretrained("merve/chatgpt-prompts-bart-long")
+model = AutoModelForSeq2SeqLM.from_pretrained("merve/chatgpt-prompts-bart-long", from_tf=True)
 
-def generate_image(model, prompt, seed, negative_prompt, sampler, steps):
-    data = "?model=" + model + "&prompt=" + prompt + "&seed=" + str(seed) + "&negative_prompt=" + negative_prompt + "&sampler=" + sampler + "&steps=" + str(steps)
-    response = requests.post(api_url + data, timeout=400)
-    if response.status_code == 200:
-        img_base64 = response.json()["url"]
-        img_bytes = base64.b64decode(img_base64)
-        img = Image.open(BytesIO(img_bytes))
-        return img
-    else:
-        return None
+def generate(prompt):
 
-dropdown_model = gr.inputs.Dropdown(['Seek.art MEGA', 'Deliberate', 'Dreamlike Photoreal', 'Realistic Vision'], label="Model", default="Seek.art MEGA")
-textbox_prompt = gr.inputs.Textbox(label="Prompt")
-number_seed = gr.inputs.Number(label="Seed", default=0)
-textbox_negative_prompt = gr.inputs.Textbox(label="Negative Prompt", default="")
-dropdown_sampler = gr.inputs.Dropdown(["k_lms", "k_heun", "k_euler", "k_euler_a", "k_dpm_2", "k_dpm_2_a", "DDIM", "k_dpm_fast", "k_dpm_adaptive", "k_dpmpp_2m", "k_dpmpp_2s_a", "k_dpmpp_sde"], label="Sampler", default="k_dpmpp_2s_a")
-number_steps = gr.inputs.Number(label="Steps", default=50)
+    batch = tokenizer(prompt, return_tensors="pt")
+    generated_ids = model.generate(batch["input_ids"], max_new_tokens=150)
+    output = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
+    return output[0]
 
-inputs = [dropdown_model, textbox_prompt, number_seed, textbox_negative_prompt, dropdown_sampler, number_steps]
+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()
 
-outputs = gr.outputs.Image(label="Generated Image", type="pil")
 
-interface = gr.Interface(
-    fn=generate_image, 
-    inputs=inputs, 
-    outputs=outputs, 
-    title="Image Generator",
-    description="Select options and enter a prompt to generate an image.",
-    examples=[],
-    layout="vertical",
-    theme="ParityError/Interstellar"  # Ihr spezifiziertes Theme
-)
-
-interface.launch()