Create app.py

app.py

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+# =====================
+# 🦁 SIMBA AI - First African LLM (FAST VERSION)
+# =====================
+# Optimized for free Hugging Face hosting
+# Uses DialoGPT-large - Fast & Reliable
+# =====================
+
+import gradio as gr
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+from sentence_transformers import SentenceTransformer
+import faiss
+import numpy as np
+import time
+
+print("🚀 Initializing Simba AI - Fast African LLM...")
+
+# =====================
+# LOAD AI MODEL - OPTIMIZED
+# =====================
+
+# Using DialoGPT-large - Fast, reliable, works on free tier
+model_name = "microsoft/DialoGPT-large"
+
+try:
+    print("📥 Loading optimized AI model...")
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    tokenizer.pad_token = tokenizer.eos_token
+
+    model = AutoModelForCausalLM.from_pretrained(
+        model_name,
+        torch_dtype=torch.float16,
+        device_map="auto",
+    )
+    print("✅ Simba AI Model Loaded Successfully! (Fast Version)")
+    
+except Exception as e:
+    print(f"❌ Model loading error: {e}")
+    print("🔄 Using even lighter model...")
+    model_name = "microsoft/DialoGPT-medium"
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    tokenizer.pad_token = tokenizer.eos_token
+    model = AutoModelForCausalLM.from_pretrained(model_name)
+    print("✅ Light model loaded!")
+
+# =====================
+# AFRICAN KNOWLEDGE BASE
+# =====================
+
+simba_knowledge_base = [
+    # CODING
+    {"question": "Python add function", "answer": "def add(a, b): return a + b"},
+    {"question": "Factorial function", "answer": "def factorial(n): return 1 if n == 0 else n * factorial(n-1)"},
+    {"question": "Reverse string function", "answer": "def reverse_string(s): return s[::-1]"},
+    {"question": "Check even number", "answer": "def is_even(n): return n % 2 == 0"},
+    {"question": "Multiply function", "answer": "def multiply(x, y): return x * y"},
+    {"question": "Yoruba greeting function", "answer": "def yoruba_greeting(): return 'Báwo ni'"},
+    
+    # MATH
+    {"question": "15 + 27", "answer": "42"},
+    {"question": "8 × 7", "answer": "56"},
+    {"question": "100 - 45", "answer": "55"},
+    {"question": "12 × 12", "answer": "144"},
+    {"question": "25% of 200", "answer": "50"},
+    {"question": "9 × 6", "answer": "54"},
+    
+    # YORUBA
+    {"question": "Hello in Yoruba", "answer": "Báwo ni"},
+    {"question": "Thank you in Yoruba", "answer": "Ẹ sé"},
+    {"question": "How are you in Yoruba", "answer": "Ṣe daadaa ni"},
+    {"question": "Good morning in Yoruba", "answer": "Ẹ káàrọ̀"},
+    {"question": "Good night in Yoruba", "answer": "O dàárọ̀"},
+    {"question": "Please in Yoruba", "answer": "Jọ̀wọ́"},
+    {"question": "Welcome in Yoruba", "answer": "Káàbọ̀"},
+    
+    # SWAHILI
+    {"question": "Hello in Swahili", "answer": "Hujambo"},
+    {"question": "Thank you in Swahili", "answer": "Asante"},
+    {"question": "How are you in Swahili", "answer": "Habari yako"},
+    {"question": "Good morning in Swahili", "answer": "Habari za asubuhi"},
+    
+    # IGBO
+    {"question": "Hello in Igbo", "answer": "Nnọọ"},
+    {"question": "Thank you in Igbo", "answer": "Daalụ"},
+    {"question": "How are you in Igbo", "answer": "Kedu ka ị mere?"},
+    
+    # HAUSA
+    {"question": "Hello in Hausa", "answer": "Sannu"},
+    {"question": "Thank you in Hausa", "answer": "Na gode"},
+    {"question": "How are you in Hausa", "answer": "Yaya lafiya?"},
+    
+    # AFRICAN INNOVATION
+    {"question": "M-Pesa", "answer": "Mobile money service launched in Kenya in 2007, revolutionized banking"},
+    {"question": "Andela", "answer": "Trains African software developers for global tech companies"},
+    {"question": "Flutterwave", "answer": "Nigerian fintech company providing payment infrastructure across Africa"},
+    {"question": "Paystack", "answer": "Nigerian payment processing company acquired by Stripe for $200M"},
+    
+    # SIMBA AI IDENTITY
+    {"question": "What is Simba AI", "answer": "Simba AI is the first African Large Language Model, specializing in African languages, coding, and mathematics"},
+    {"question": "Simba AI purpose", "answer": "To advance African AI innovation and make AI accessible for African languages and contexts"},
+]
+
+print(f"✅ African Knowledge Base: {len(simba_knowledge_base)} expert entries")
+
+# =====================
+# FAST SEARCH SYSTEM
+# =====================
+
+try:
+    print("🔍 Loading fast search system...")
+    embedder = SentenceTransformer('all-MiniLM-L6-v2')
+    
+    # Build search index
+    questions = [item["question"] for item in simba_knowledge_base]
+    question_embeddings = embedder.encode(questions)
+
+    dimension = question_embeddings.shape[1]
+    index = faiss.IndexFlatIP(dimension)
+    faiss.normalize_L2(question_embeddings)
+    index.add(question_embeddings)
+
+    print("✅ Fast Search System Ready!")
+except Exception as e:
+    print(f"❌ Search system error: {e}")
+    index = None
+
+def simba_search(query, top_k=3):
+    """Fast search African knowledge base"""
+    if index is None:
+        return simba_knowledge_base[:top_k]
+    
+    try:
+        query_embedding = embedder.encode([query])
+        faiss.normalize_L2(query_embedding)
+        
+        scores, indices = index.search(query_embedding, top_k)
+        
+        results = []
+        for i, idx in enumerate(indices[0]):
+            if idx < len(simba_knowledge_base):
+                results.append({
+                    "question": simba_knowledge_base[idx]["question"],
+                    "answer": simba_knowledge_base[idx]["answer"],
+                    "score": scores[0][i]
+                })
+        
+        return results
+    except Exception as e:
+        return simba_knowledge_base[:top_k]
+
+# =====================
+# FAST SIMBA AI CHAT FUNCTION
+# =====================
+
+def simba_ai_chat(message, history):
+    """Fast chat function with timeout protection"""
+    
+    start_time = time.time()
+    
+    # Quick responses for common greetings (instant)
+    quick_responses = {
+        "hello": "🦁 Báwo ni! Hello! I'm Simba AI, the first African LLM. I specialize in African languages, coding, and mathematics. How can I assist you today?",
+        "hi": "🦁 Báwo ni! Welcome to Simba AI - Africa's first Large Language Model!",
+        "hey": "🦁 Hello! I'm Simba AI. Ask me about African languages, Python coding, or math problems!",
+        "hola": "🦁 Báwo ni! I see you speak Spanish. I specialize in African languages like Yoruba, Swahili, Igbo, and Hausa!",
+    }
+    
+    lower_message = message.lower().strip()
+    if lower_message in quick_responses:
+        return quick_responses[lower_message]
+    
+    try:
+        # Search for relevant knowledge
+        search_results = simba_search(message, top_k=2)
+        
+        # Build smart context
+        context = "📚 African Knowledge:\n"
+        for i, result in enumerate(search_results, 1):
+            context += f"{i}. {result['question']}: {result['answer']}\n"
+        
+        # Optimized prompt for DialoGPT
+        prompt = f"User: {message}\nAfrican Knowledge: {context}\nSimba AI:"
+        
+        # Fast generation
+        inputs = tokenizer.encode(prompt, return_tensors="pt", max_length=512, truncation=True)
+        
+        with torch.no_grad():
+            outputs = model.generate(
+                inputs,
+                max_new_tokens=100,
+                temperature=0.7,
+                do_sample=True,
+                pad_token_id=tokenizer.eos_token_id,
+                repetition_penalty=1.1,
+                num_return_sequences=1,
+            )
+        
+        response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+        
+        # Extract just the Simba AI response
+        if "Simba AI:" in response:
+            final_response = response.split("Simba AI:")[-1].strip()
+        else:
+            final_response = response[len(prompt):].strip()
+        
+        # Add African flair
+        if not final_response.startswith("🦁"):
+            final_response = f"🦁 {final_response}"
+            
+        response_time = time.time() - start_time
+        print(f"✅ Response generated in {response_time:.2f} seconds")
+        
+        return final_response
+        
+    except Exception as e:
+        error_msg = f"🦁 Simba AI is thinking... Please try again! (Error: {str(e)})"
+        print(f"❌ Generation error: {e}")
+        return error_msg
+
+# =====================
+# FAST GRADIO INTERFACE
+# =====================
+
+# African theme CSS
+css = """
+.gradio-container {
+    font-family: 'Arial', sans-serif;
+}
+.header {
+    text-align: center;
+    padding: 25px;
+    background: linear-gradient(135deg, #ff7e5f, #feb47b);
+    color: white;
+    border-radius: 15px;
+    margin-bottom: 20px;
+    border: 2px solid #e65c50;
+}
+.african-pattern {
+    background: linear-gradient(45deg, #ff7e5f 25%, transparent 25%), 
+                linear-gradient(-45deg, #ff7e5f 25%, transparent 25%), 
+                linear-gradient(45deg, transparent 75%, #ff7e5f 75%), 
+                linear-gradient(-45deg, transparent 75%, #ff7e5f 75');
+    background-size: 20px 20px;
+    background-position: 0 0, 0 10px, 10px -10px, -10px 0px;
+    opacity: 0.1;
+}
+"""
+
+# Create fast interface
+with gr.Blocks(css=css, theme=gr.themes.Soft()) as demo:
+    
+    gr.HTML("""
+    <div class="header">
+        <h1>🦁 Simba AI - First African LLM</h1>
+        <h3>Fast & Optimized - African Languages, Coding & Mathematics</h3>
+        <p>Powered by DialoGPT-large • Responses in 5-15 seconds</p>
+    </div>
+    """)
+    
+    chatbot = gr.Chatbot(
+        label="🦁 Chat with Simba AI",
+        height=500,
+        show_copy_button=True,
+        placeholder="Ask about African languages, Python coding, or math..."
+    )
+    
+    with gr.Row():
+        msg = gr.Textbox(
+            label="Your message",
+            placeholder="Type your question here...",
+            lines=2,
+            scale=4
+        )
+        send_btn = gr.Button("🚀 Ask Simba AI", variant="primary", scale=1)
+    
+    with gr.Row():
+        clear_btn = gr.Button("🧹 Clear Chat")
+        info_btn = gr.Button("ℹ️ About Simba AI")
+    
+    # Quick action examples
+    gr.Examples(
+        examples=[
+            "Hello",
+            "How do you say thank you in Yoruba?",
+            "Write Python function to add numbers",
+            "What is 15 + 27?",
+            "Tell me about M-Pesa",
+            "How are you in Swahili?",
+            "Create factorial function",
+            "Calculate 8 × 7"
+        ],
+        inputs=msg,
+        label="💡 Quick Actions:"
+    )
+    
+    # Event handlers
+    def respond(message, chat_history):
+        bot_message = simba_ai_chat(message, chat_history)
+        chat_history.append((message, bot_message))
+        return "", chat_history
+    
+    def show_info():
+        return [("", "🦁 **Simba AI - First African LLM**\n\n**Capabilities:**\n• African Languages: Yoruba, Swahili, Igbo, Hausa\n• Python Coding & Programming\n• Mathematics & Problem Solving\n• African Tech Innovation\n\n**Powered by:** DialoGPT-large + African Knowledge Base\n**Response Time:** 5-15 seconds\n**Mission:** Advance African AI Innovation")]
+    
+    msg.submit(respond, [msg, chatbot], [msg, chatbot])
+    send_btn.click(respond, [msg, chatbot], [msg, chatbot])
+    clear_btn.click(lambda: None, None, chatbot, queue=False)
+    info_btn.click(show_info, None, chatbot)
+
+# =====================
+# LAUNCH
+# =====================
+
+if __name__ == "__main__":
+    print("🎯 Simba AI is ready! Launching interface...")
+    demo.launch(
+        debug=True,
+        share=True,
+        show_error=True
+    )