Upload app.py

app.py

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+import gradio as gr
+from llama_cpp import Llama
+from huggingface_hub import hf_hub_download
+
+# =========================
+# LOAD MODEL FROM HF REPO
+# =========================
+model_path = hf_hub_download(
+    repo_id="Mikecode123/ALX",
+    filename="qwen2-1_5b-instruct-q4_0.gguf"
+)
+
+llm = Llama(
+    model_path=model_path,
+    n_ctx=1024,
+    n_threads=2
+)
+
+# =========================
+# CHAT FUNCTION
+# =========================
+def chat(prompt, history):
+    messages = []
+
+    # convert gradio history to chat format
+    for user_msg, bot_msg in history:
+        messages.append({"role": "user", "content": user_msg})
+        messages.append({"role": "assistant", "content": bot_msg})
+
+    messages.append({"role": "user", "content": prompt})
+
+    output = llm.create_chat_completion(
+        messages=messages,
+        max_tokens=500,
+        temperature=0.7
+    )
+
+    response = output["choices"][0]["message"]["content"]
+
+    history.append((prompt, response))
+    return "", history
+
+# =========================
+# GRADIO UI
+# =========================
+with gr.Blocks() as demo:
+    gr.Markdown("# 🧠 Qwen GGUF AI (Living Legend Build)")
+
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox(label="Ask your AI")
+    clear = gr.Button("Clear")
+
+    msg.submit(chat, [msg, chatbot], [msg, chatbot])
+    clear.click(lambda: None, None, chatbot)
+
+# =========================
+# LAUNCH
+# =========================
+demo.launch()