added proj files

README.md

@@ -1,10 +1,10 @@
 ---
-title: Nsfw C0ffees Erotic Story Generator2
-emoji: 🐢
-colorFrom: blue
-colorTo: gray
+title: "[NSFW] C0ffee's Erotic Story Generator 2"
+emoji: 🍑
+colorFrom: gray
+colorTo: pink
 sdk: gradio
-sdk_version: 3.29.0
+sdk_version: 3.27.0
 app_file: app.py
 pinned: false
 ---

app.py

@@ -0,0 +1,100 @@
+import gradio as gr
+
+import nltk
+import string
+from transformers import GPT2LMHeadModel, GPT2Tokenizer, GenerationConfig, set_seed
+import random
+
+nltk.download('punkt')
+
+response_length = 200
+
+sentence_detector = nltk.data.load('tokenizers/punkt/english.pickle')
+
+tokenizer = GPT2Tokenizer.from_pretrained("gpt2-medium")
+tokenizer.truncation_side = 'right'
+
+# model = GPT2LMHeadModel.from_pretrained('checkpoint-50000')
+model = GPT2LMHeadModel.from_pretrained('coffeeee/nsfw-story-generator2')
+generation_config = GenerationConfig.from_pretrained('gpt2-medium')
+generation_config.max_new_tokens = response_length
+generation_config.pad_token_id = generation_config.eos_token_id
+def generate_response(outputs, new_prompt):
+
+    story_so_far = "\n".join(outputs[:int(1024 / response_length + 1)]) if outputs else ""
+
+    set_seed(random.randint(0, 4000000000))
+    inputs = tokenizer.encode(story_so_far + "\n" + new_prompt if story_so_far else new_prompt,
+                              return_tensors='pt', truncation=True,
+                              max_length=1024 - response_length)
+
+    output = model.generate(inputs, do_sample=True, generation_config=generation_config)
+
+    response = clean_paragraph(tokenizer.batch_decode(output)[0][(len(story_so_far) + 1 if story_so_far else 0):])
+    outputs.append(response)
+    return {
+        user_outputs: outputs,
+        story: (story_so_far + "\n" if story_so_far else "") + response,
+        prompt: None
+    }
+
+def undo(outputs):
+
+    outputs = outputs[:-1] if outputs else []
+    return {
+        user_outputs: outputs,
+        story: "\n".join(outputs) if outputs else None
+    }
+
+def clean_paragraph(entry):
+    paragraphs = entry.split('\n')
+
+    for i in range(len(paragraphs)):
+        split_sentences = nltk.tokenize.sent_tokenize(paragraphs[i], language='english')
+        if i == len(paragraphs) - 1 and split_sentences[:1][-1] not in string.punctuation:
+            paragraphs[i] = " ".join(split_sentences[:-1])
+
+    return capitalize_first_char("\n".join(paragraphs))
+
+def reset():
+    return {
+        user_outputs: [],
+        story: None
+    }
+
+def capitalize_first_char(entry):
+    for i in range(len(entry)):
+        if entry[i].isalpha():
+            return entry[:i] + entry[i].upper() + entry[i + 1:]
+    return entry
+
+with gr.Blocks(theme=gr.themes.Default(text_size='lg', font=[gr.themes.GoogleFont("Bitter"), "Arial", "sans-serif"])) as demo:
+
+    placeholder_text = '''
+    Disclaimer: everything this model generates is a work of fiction.
+    Content from this model WILL generate inappropriate and potentially offensive content.
+
+    Use at your own discretion. Please respect the Huggingface code of conduct.'''
+
+    story = gr.Textbox(label="Story", interactive=False, lines=20, placeholder=placeholder_text)
+    story.style(show_copy_button=True)
+
+    user_outputs = gr.State([])
+
+    prompt = gr.Textbox(label="Prompt", placeholder="Start a new story, or continue your current one!", lines=3, max_lines=3)
+
+    with gr.Row():
+        gen_button = gr.Button('Generate')
+        undo_button = gr.Button("Undo")
+        res_button = gr.Button("Reset")
+
+    prompt.submit(generate_response, [user_outputs, prompt], [user_outputs, story, prompt], scroll_to_output=True)
+    gen_button.click(generate_response, [user_outputs, prompt], [user_outputs, story, prompt], scroll_to_output=True)
+    undo_button.click(undo, user_outputs, [user_outputs, story], scroll_to_output=True)
+    res_button.click(reset, [], [user_outputs, story], scroll_to_output=True)
+
+# for local server; comment out for deploy
+
+demo.launch(inbrowser=True, server_name='0.0.0.0')
+
+