Update app.py

app.py

@@ -1,59 +1,60 @@
-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
-# =========================
+import os
+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",
+    token=os.getenv("HF_TOKEN")  # secure access
+)
+
+llm = Llama(
+    model_path=model_path,
+    n_ctx=512,        # reduced to avoid OOM (important in 2026 Spaces)
+    n_threads=1       # safer for low resources
+)
+
+# =========================
+# CHAT FUNCTION
+# =========================
+def chat(prompt, history):
+    messages = []
+
+    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=300,
+        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, chatbot)
+
+# =========================
+# LAUNCH
+# =========================
 demo.launch()