Add UI with default model for now

README.md

@@ -1,12 +1,38 @@
 ---
-title: Lab2
-emoji: 📈
+title: Fine-Tuned Llama 3.2 Chatbot
+emoji: 🦙
 colorFrom: blue
-colorTo: gray
+colorTo: purple
 sdk: gradio
-sdk_version: 6.0.0
+sdk_version: 4.44.0
 app_file: app.py
 pinned: false
+license: apache-2.0
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Fine-Tuned Llama 3.2 3B Chatbot
+
+This Space hosts a chatbot powered by a fine-tuned Llama 3.2 3B model.
+
+## Model Details
+
+- **Base Model:** Llama 3.2 3B Instruct
+- **Fine-tuning Method:** LoRA (Low-Rank Adaptation)
+- **Dataset:** FineTome-100k instruction dataset
+- **Format:** GGUF (q4_k_m quantization)
+- **Inference:** CPU-based using llama.cpp
+
+## Training
+
+The model was fine-tuned using:
+- Parameter Efficient Fine-Tuning (PEFT) with LoRA
+- 4-bit quantization during training
+- Trained on 100,000 high-quality instruction-response pairs
+
+## Usage
+
+Simply type your message in the chat box and the model will respond!
+
+## Course
+
+This project was completed as part of the ID2223 Scalable Machine Learning course at KTH.

app.py

@@ -0,0 +1,202 @@
+import gradio as gr
+from llama_cpp import Llama
+from huggingface_hub import hf_hub_download
+import os
+
+# Download a pre-made GGUF model from HuggingFace
+MODEL_NAME = "TheBloke/Llama-2-7B-Chat-GGUF"
+MODEL_FILE = "llama-2-7b-chat.Q4_K_M.gguf"
+
+print("📥 Downloading model from HuggingFace...")
+model_path = hf_hub_download(
+    repo_id=MODEL_NAME,
+    filename=MODEL_FILE,
+    local_dir="./models"
+)
+print(f"✅ Model downloaded to: {model_path}")
+
+print("🚀 Loading model...")
+llm = Llama(
+    model_path=model_path,
+    n_ctx=2048,
+    n_threads=4,
+    n_gpu_layers=0,
+    verbose=False
+)
+print("✅ Model loaded!")
+
+def chat(message, history):
+    prompt = "<|begin_of_text|>"
+    
+    for user_msg, bot_msg in history:
+        prompt += f"<|start_header_id|>user<|end_header_id|>\n\n{user_msg}<|eot_id|>"
+        prompt += f"<|start_header_id|>assistant<|end_header_id|>\n\n{bot_msg}<|eot_id|>"
+    
+    prompt += f"<|start_header_id|>user<|end_header_id|>\n\n{message}<|eot_id|>"
+    prompt += "<|start_header_id|>assistant<|end_header_id|>\n\n"
+    
+    response = llm(
+        prompt,
+        max_tokens=512,
+        temperature=0.7,
+        top_p=0.9,
+        stop=["<|eot_id|>", "<|start_header_id|>"],
+        echo=False
+    )
+    
+    return response['choices'][0]['text'].strip()
+
+# Ultra-modern CSS
+custom_css = """
+@import url('https://fonts.googleapis.com/css2?family=Space+Grotesk:wght@400;600;700&display=swap');
+
+* {
+    font-family: 'Space Grotesk', sans-serif !important;
+}
+
+.gradio-container {
+    background: linear-gradient(135deg, #1e3a8a 0%, #7c3aed 50%, #db2777 100%) !important;
+}
+
+#chatbot {
+    height: 650px !important;
+    border-radius: 24px !important;
+    border: 2px solid rgba(255,255,255,0.1) !important;
+    box-shadow: 0 25px 50px -12px rgba(0,0,0,0.5) !important;
+}
+
+.message {
+    padding: 18px 24px !important;
+    border-radius: 20px !important;
+    font-size: 15px !important;
+    margin: 8px 0 !important;
+    backdrop-filter: blur(10px) !important;
+    box-shadow: 0 8px 32px 0 rgba(31, 38, 135, 0.37) !important;
+}
+
+.user {
+    background: linear-gradient(135deg, rgba(147, 51, 234, 0.9) 0%, rgba(219, 39, 119, 0.9) 100%) !important;
+    color: white !important;
+    border: 1px solid rgba(255,255,255,0.2) !important;
+}
+
+.bot {
+    background: linear-gradient(135deg, rgba(59, 130, 246, 0.9) 0%, rgba(147, 51, 234, 0.9) 100%) !important;
+    color: white !important;
+    border: 1px solid rgba(255,255,255,0.2) !important;
+}
+
+button {
+    border-radius: 16px !important;
+    font-weight: 600 !important;
+    transition: all 0.3s ease !important;
+}
+
+button:hover {
+    transform: translateY(-2px) !important;
+    box-shadow: 0 12px 24px rgba(0,0,0,0.3) !important;
+}
+
+.primary {
+    background: linear-gradient(135deg, #9333ea 0%, #db2777 100%) !important;
+    border: none !important;
+}
+
+input, textarea {
+    border-radius: 16px !important;
+    border: 2px solid rgba(255,255,255,0.2) !important;
+    background: rgba(255,255,255,0.1) !important;
+    backdrop-filter: blur(10px) !important;
+    color: white !important;
+}
+
+input::placeholder, textarea::placeholder {
+    color: rgba(255,255,255,0.6) !important;
+}
+
+.prose {
+    color: white !important;
+}
+
+.prose h1 {
+    background: linear-gradient(135deg, #fbbf24 0%, #f59e0b 100%);
+    -webkit-background-clip: text;
+    -webkit-text-fill-color: transparent;
+    font-weight: 700 !important;
+}
+
+footer {
+    display: none !important;
+}
+"""
+
+with gr.Blocks(
+    theme=gr.themes.Glass(
+        primary_hue="purple",
+        secondary_hue="pink",
+    ),
+    css=custom_css,
+    title="🦙 Llama 3.2 AI"
+) as demo:
+    
+    gr.Markdown(
+        """
+        # 🦙 Llama Chat AI Assistant (TEST)
+        ### ⚡ Testing deployment with pre-trained model
+        """
+    )
+    
+    chatbot = gr.Chatbot(
+        elem_id="chatbot",
+        bubble_full_width=False,
+        avatar_images=(
+            "https://em-content.zobj.net/thumbs/120/apple/354/sparkles_2728.png",
+            "https://em-content.zobj.net/thumbs/120/apple/354/llama_1f999.png"
+        ),
+        height=650,
+        show_copy_button=True,
+        likeable=True
+    )
+    
+    with gr.Row():
+        msg = gr.Textbox(
+            placeholder="✨ Ask me anything...",
+            show_label=False,
+            scale=8,
+            container=False
+        )
+        submit = gr.Button("Send 🚀", scale=1, variant="primary", size="lg")
+    
+    gr.Examples(
+        examples=[
+            "🌍 What is the capital of France?",
+            "🧠 Explain quantum computing simply",
+            "💻 Write fibonacci in Python",
+            "😴 Tips for better sleep?",
+            "🔢 Continue: 2, 4, 6, 8...",
+            "📝 Write a haiku about AI",
+        ],
+        inputs=msg,
+        label="💡 Quick Start:"
+    )
+    
+    with gr.Accordion("ℹ️ Model Information", open=False):
+        gr.Markdown(
+            """
+            **Testing Model:**
+            - 🤖 Model: Llama 2 7B Chat (Pre-trained)
+            - ⚙️ Format: GGUF (q4_k_m quantization)
+            - 📝 Note: This is a test deployment. Will be replaced with fine-tuned model.
+            """
+        )
+    
+    clear = gr.ClearButton([msg, chatbot], value="🗑️ New Chat")
+    
+    submit.click(chat, [msg, chatbot], [chatbot])
+    submit.click(lambda: "", None, msg)
+    msg.submit(chat, [msg, chatbot], [chatbot])
+    msg.submit(lambda: "", None, msg)
+
+if __name__ == "__main__":
+    demo.queue()
+    demo.launch(share=False)

requirements.txt

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+gradio==4.44.0
+llama-cpp-python==0.2.90