Create app.py

app.py

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+import gradio as gr
+from unsloth import FastLanguageModel
+import torch
+import time
+
+# ----------------------------
+# 🚀 Load Model (cached)
+# ----------------------------
+@gr.cache
+def load_model():
+    max_seq_length = 1024
+    model, tokenizer = FastLanguageModel.from_pretrained(
+        model_name="umarfarzan/my-finetuned-model2-lora",
+        max_seq_length=max_seq_length,
+        dtype=None,
+        load_in_4bit=True
+    )
+    FastLanguageModel.for_inference(model)
+    return model, tokenizer
+
+print("Loading model...")
+model, tokenizer = load_model()
+print("✅ Model loaded successfully!")
+
+# ----------------------------
+# 💡 Generate Training Program
+# ----------------------------
+def generate_training_program(
+    instruction,
+    max_tokens=5500,
+    temperature=0.7,
+    top_p=0.9
+):
+    """Generate a training program based on user instruction"""
+    
+    # Build prompt in Alpaca format
+    prompt_text = f"""Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
+
+### Instruction:
+{instruction}
+
+### Input:
+
+
+### Response:
+"""
+    
+    # Tokenize
+    inputs = tokenizer([prompt_text], return_tensors="pt").to("cuda")
+    
+    # Generate with progress
+    start_time = time.time()
+    
+    outputs = model.generate(
+        **inputs,
+        max_new_tokens=max_tokens,
+        temperature=temperature,
+        top_p=top_p,
+        do_sample=True,
+        use_cache=True
+    )
+    
+    generation_time = time.time() - start_time
+    
+    # Decode
+    generated_text = tokenizer.batch_decode(outputs, skip_special_tokens=True)[0]
+    
+    # Extract only the response part (after "### Response:")
+    if "### Response:" in generated_text:
+        response = generated_text.split("### Response:")[-1].strip()
+    else:
+        response = generated_text
+    
+    return response, f"⏱️ Generated in {generation_time:.2f} seconds"
+
+# ----------------------------
+# 🎨 Gradio Interface
+# ----------------------------
+# Custom CSS for beautiful styling
+custom_css = """
+.gradio-container {
+    font-family: 'Inter', sans-serif;
+}
+.main-header {
+    text-align: center;
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    color: white;
+    padding: 2rem;
+    border-radius: 10px;
+    margin-bottom: 2rem;
+}
+.example-box {
+    background: #f8f9fa;
+    padding: 1rem;
+    border-radius: 8px;
+    border-left: 4px solid #667eea;
+}
+"""
+
+# Example prompts
+examples = [
+    ["Design a detailed 1-week training program titled 'The Leader's Blueprint for Strategic Problem-Solving' for mid-level to senior-level managers, team leads, and high-potential employees."],
+    ["Create a 3-day workshop on effective communication skills for remote teams."],
+    ["Develop a 5-day leadership bootcamp for new managers focusing on team management and conflict resolution."],
+    ["Design a half-day training session on data-driven decision making for executives."],
+    ["Create a 2-week onboarding program for new software engineers including technical and cultural training."],
+]
+
+# Build interface
+with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
+    
+    # Header
+    gr.HTML("""
+        <div class="main-header">
+            <h1>🎯 AI Training Program Generator</h1>
+            <p style="font-size: 1.1rem; margin-top: 0.5rem;">
+                Generate comprehensive, professional training programs instantly using AI
+            </p>
+        </div>
+    """)
+    
+    # Description
+    gr.Markdown("""
+    ### ✨ How it works
+    Simply describe the training program you need, and our AI will generate a detailed, structured curriculum complete with:
+    - Day-by-day breakdown
+    - Learning objectives
+    - Activities and exercises
+    - Materials needed
+    - Assessment methods
+    """)
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            # Input section
+            instruction_input = gr.Textbox(
+                label="📝 Training Program Description",
+                placeholder="Example: Design a 1-week training program on strategic problem-solving for managers...",
+                lines=5,
+                info="Describe what type of training program you need"
+            )
+            
+            # Advanced settings (collapsed by default)
+            with gr.Accordion("⚙️ Advanced Settings", open=False):
+                max_tokens_slider = gr.Slider(
+                    minimum=500,
+                    maximum=8000,
+                    value=5500,
+                    step=100,
+                    label="Max Output Length",
+                    info="Longer programs need more tokens"
+                )
+                temperature_slider = gr.Slider(
+                    minimum=0.1,
+                    maximum=1.5,
+                    value=0.7,
+                    step=0.1,
+                    label="Creativity (Temperature)",
+                    info="Higher = more creative, Lower = more focused"
+                )
+                top_p_slider = gr.Slider(
+                    minimum=0.5,
+                    maximum=1.0,
+                    value=0.9,
+                    step=0.05,
+                    label="Diversity (Top-p)",
+                    info="Controls output diversity"
+                )
+            
+            generate_btn = gr.Button("🚀 Generate Training Program", variant="primary", size="lg")
+        
+        with gr.Column(scale=1):
+            # Output section
+            output_text = gr.Textbox(
+                label="📋 Generated Training Program",
+                lines=25,
+                show_copy_button=True,
+                info="Your custom training program will appear here"
+            )
+            generation_info = gr.Textbox(
+                label="ℹ️ Generation Info",
+                interactive=False,
+                show_label=False
+            )
+    
+    # Examples
+    gr.Markdown("### 💡 Example Prompts - Click to try!")
+    gr.Examples(
+        examples=examples,
+        inputs=[instruction_input],
+        label="Quick Start Examples"
+    )
+    
+    # Footer info
+    gr.Markdown("""
+    ---
+    ### 📌 Tips for Best Results:
+    - **Be specific**: Include duration (1 week, 3 days, etc.), target audience, and focus areas
+    - **Add context**: Mention skill level, industry, or specific challenges to address
+    - **Iterate**: Generate multiple versions and pick the best elements from each
+    
+    ### 🤖 Model Information:
+    - **Base Model**: Qwen2.5-7B fine-tuned with LoRA
+    - **Fine-tuning**: Custom training on professional development curricula
+    - **Optimization**: 4-bit quantization for efficient inference
+    """)
+    
+    # Connect button to function
+    generate_btn.click(
+        fn=generate_training_program,
+        inputs=[
+            instruction_input,
+            max_tokens_slider,
+            temperature_slider,
+            top_p_slider
+        ],
+        outputs=[output_text, generation_info],
+        api_name="generate"
+    )
+
+# ----------------------------
+# 🚀 Launch
+# ----------------------------
+if __name__ == "__main__":
+    demo.queue(max_size=10)  # Enable queue for better UX
+    demo.launch(
+        share=False,
+        show_error=True,
+        server_name="0.0.0.0",
+        server_port=7860
+    )