Create app.py

app.py

@@ -0,0 +1,79 @@
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+# Load the tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained("deepseek-ai/DeepSeek-V3")
+model = AutoModelForCausalLM.from_pretrained(
+    "deepseek-ai/DeepSeek-V3",
+    torch_dtype=torch.float16,  # Use FP16 for efficiency
+    device_map="auto"           # Automatically use GPU if available
+)
+
+# Function to generate text
+def generate_text(prompt, max_length=100, temperature=0.7, top_k=50):
+    # Tokenize the input prompt
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+    
+    # Generate text
+    outputs = model.generate(
+        inputs["input_ids"],
+        max_length=max_length,
+        temperature=temperature,
+        top_k=top_k,
+        do_sample=True
+    )
+    
+    # Decode the generated text
+    generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return generated_text
+
+# Gradio interface
+def gradio_interface(prompt, max_length, temperature, top_k):
+    try:
+        output = generate_text(prompt, max_length, temperature, top_k)
+        return output
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Custom CSS for a fancy theme
+custom_css = """
+.gradio-container {
+    background: linear-gradient(135deg, #1e3c72, #2a5298);
+    color: white;
+    font-family: 'Arial', sans-serif;
+}
+h1 {
+    color: #ffd700;
+    text-align: center;
+}
+.description {
+    color: #ffffff;
+    text-align: center;
+    font-size: 16px;
+}
+.input-label, .output-label {
+    color: #ffffff;
+}
+.slider-label {
+    color: #ffffff;
+}
+"""
+
+# Create the Gradio app
+iface = gr.Interface(
+    fn=gradio_interface,
+    inputs=[
+        gr.Textbox(label="Enter your prompt", lines=3, placeholder="Once upon a time..."),
+        gr.Slider(minimum=10, maximum=200, value=100, label="Max Length"),
+        gr.Slider(minimum=0.1, maximum=1.0, value=0.7, label="Temperature"),
+        gr.Slider(minimum=1, maximum=100, value=50, label="Top-k Sampling")
+    ],
+    outputs=gr.Textbox(label="Generated Text", lines=10),
+    title="DreamWeaver AI",
+    description="Crafting Stories, One Prompt at a Time. Generate text using the DeepSeek-V3 model. Adjust the parameters to control the output.",
+    css=custom_css
+)
+
+# Launch the app
+iface.launch()