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app.py
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import gradio as gr
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import requests
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import os
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import time
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# Model configuration
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MODEL_ID = "chendren/deepseek-dnd-lora"
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API_URL = f"https://api-inference.huggingface.co/models/{MODEL_ID}"
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API_TOKEN = os.environ.get("HUGGINGFACE_TOKEN", "")
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headers = {"Authorization": f"Bearer {API_TOKEN}"}
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# Example prompts
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example_prompts = [
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"Create a D&D character with the following details: Race: Half-Elf, Class: Bard, Background: Entertainer",
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"Design a D&D adventure hook set in a dark forest with a mysterious cult",
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"Create a magical item for D&D 5e that would be suitable for a level 5 rogue",
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"Write a description for a fantasy tavern in a D&D setting called 'The Dragon\'s Rest'",
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"Create a D&D monster stat block for a new type of undead creature called 'Mist Wraith'",
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"Write a backstory for a Dragonborn Paladin who follows the Oath of Vengeance",
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]
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def generate_text(prompt, temperature=0.7, max_length=500, top_p=0.9, top_k=50, rep_penalty=1.1):
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"""
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Generate text using the Hugging Face Inference API
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If the API fails, provide instructions for manual testing
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"""
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full_prompt = f"You are a Dungeons & Dragons assistant. {prompt}"
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payload = {
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"inputs": full_prompt,
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"parameters": {
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"max_new_tokens": int(max_length),
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"temperature": float(temperature),
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"top_p": float(top_p),
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"top_k": int(top_k),
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"repetition_penalty": float(rep_penalty),
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"do_sample": True
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}
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}
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try:
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response = requests.post(API_URL, headers=headers, json=payload)
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if response.status_code == 200:
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result = response.json()
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if isinstance(result, list) and len(result) > 0:
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if "generated_text" in result[0]:
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return result[0]["generated_text"]
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else:
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return str(result[0])
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else:
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return str(result)
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elif response.status_code == 503:
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return (
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"⏳ The model is still loading or being processed by Hugging Face. "
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"This is normal for new or infrequently used models. Please try again in a few minutes.\n\n"
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"If the problem persists, you can also try using the model directly via code: "
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"https://huggingface.co/chendren/deepseek-dnd-lora#using-the-transformers-library"
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)
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else:
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return (
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f"⚠️ Error: API returned status code {response.status_code}\n\n"
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f"Response: {response.text}\n\n"
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"You can try again later or use the model directly with the code provided here: "
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"https://huggingface.co/chendren/deepseek-dnd-lora"
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)
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except Exception as e:
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return (
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f"⚠️ An error occurred: {str(e)}\n\n"
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"Check if the model is available or try using the model directly using the code examples: "
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"https://huggingface.co/chendren/deepseek-dnd-lora"
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)
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# Create the Gradio interface
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with gr.Blocks(title="D&D Content Generator", css="footer {visibility: hidden}") as demo:
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gr.Markdown(
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"""
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# 🐉 Dungeons & Dragons Content Generator
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This demo uses the [DeepSeek-R1-Distill-Qwen-7B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B) model fine-tuned on D&D content.
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Enter a prompt related to D&D content creation, or try one of the examples below.
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### Model Details
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- Base model: [deepseek-ai/DeepSeek-R1-Distill-Qwen-7B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B)
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- Fine-tuned with LoRA on 500 examples of D&D content
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- Specialized for creating characters, adventures, items, and more for D&D
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[View Model on Hugging Face](https://huggingface.co/chendren/deepseek-dnd-lora)
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"""
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)
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with gr.Row():
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with gr.Column():
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prompt = gr.Textbox(
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label="Prompt",
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placeholder="Enter your D&D content request...",
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lines=4
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)
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with gr.Row():
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submit_btn = gr.Button("Generate", variant="primary")
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clear_btn = gr.Button("Clear")
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with gr.Accordion("Advanced Parameters", open=False):
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temperature = gr.Slider(
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minimum=0.1, maximum=1.5, value=0.7, step=0.1,
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label="Temperature (creativity)",
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info="Higher values produce more creative but potentially less coherent output"
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)
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max_length = gr.Slider(
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minimum=100, maximum=1000, value=500, step=50,
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label="Maximum Length",
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info="Maximum number of tokens to generate"
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)
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top_p = gr.Slider(
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minimum=0.1, maximum=1.0, value=0.9, step=0.1,
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label="Top-p",
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info="Nucleus sampling probability threshold"
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)
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top_k = gr.Slider(
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minimum=1, maximum=100, value=50, step=5,
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label="Top-k",
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info="Number of highest probability tokens to consider"
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)
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rep_penalty = gr.Slider(
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minimum=1.0, maximum=2.0, value=1.1, step=0.1,
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label="Repetition Penalty",
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info="Penalizes repeated tokens (higher = less repetition)"
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)
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with gr.Column():
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output = gr.Textbox(
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label="Generated Output",
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placeholder="D&D content will appear here...",
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lines=20
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)
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gr.Examples(
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examples=example_prompts,
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inputs=prompt,
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outputs=output,
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fn=lambda x: generate_text(x),
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cache_examples=False
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)
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gr.Markdown(
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"""
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### Usage Tips
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| 155 |
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- Be specific in your prompts, including details like race, class, and level where applicable
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| 156 |
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- For character creation, specify race, class, background, and any other details
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| 157 |
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- For adventure hooks, specify setting, theme, and target party level
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| 158 |
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- For magic items, specify item type, rarity, and intended user
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| 159 |
+
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| 160 |
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### Credits
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| 161 |
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- Base model: [DeepSeek-R1-Distill-Qwen-7B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B)
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| 162 |
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- Fine-tuned by: [chendren](https://huggingface.co/chendren)
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| 163 |
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"""
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)
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# Set up event handlers
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submit_btn.click(
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fn=generate_text,
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inputs=[prompt, temperature, max_length, top_p, top_k, rep_penalty],
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| 170 |
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outputs=output
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| 171 |
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)
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| 172 |
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| 173 |
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clear_btn.click(
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fn=lambda: ("", ""),
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inputs=[],
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outputs=[prompt, output]
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)
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# Launch the app
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| 180 |
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if __name__ == "__main__":
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| 181 |
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demo.launch()
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