Update app.py

app.py

@@ -1,79 +1,71 @@
-import os
-import gradio as gr
-import requests
-import json
+        reply = data["choices"][0]["message"]["content"]
+        reply = reply.replace("Step", "➡️ Step")  # Optional formatting
+    except Exception as e:
+        reply = f"⚠️ Error: {str(e)}"
+
+    history.append({"role": "user", "content": message})
+    history.append({"role": "assistant", "content": reply})
+
+    save_memory(history)
+    return history, history
 
-HF_TOKEN = os.getenv("HF_TOKEN")
-MEMORY_FILE = "memory.json"
 
 # ----------------
-# Web search
+# Greeting Function
 # ----------------
-def search_web(query):
-    try:
-        url = "https://api.duckduckgo.com/"
-        params = {"q": query, "format": "json", "no_html": 1, "skip_disambig": 1}
-        response = requests.get(url, params=params)
-        data = response.json()
-        if data.get("AbstractText"):
-            return data["AbstractText"]
-        elif data.get("RelatedTopics"):
-            topics = [t.get("Text", "") for t in data["RelatedTopics"] if "Text" in t]
-            return " ".join(topics[:3])
-        else:
-            return "No useful information found."
-    except Exception as e:
-        return f"Search error: {e}"
+def eduai_greeting():
+    return [{"role": "assistant", "content": "👋 Hey there! I'm **EduAI**, your smart study assistant. How can I help you today?"}]
+
 
 # ----------------
-# Memory
+# UI Components
 # ----------------
-def load_memory():
-    if os.path.exists(MEMORY_FILE):
-        with open(MEMORY_FILE, "r") as f:
-            return json.load(f)
-    return []
+with gr.Blocks(theme=gr.themes.Soft(primary_hue="indigo")) as demo:
+    gr.Markdown(
+        """
+        <h1 style="text-align:center; color:#4C1D95;">✨ EduAI — Your Personal Study Assistant ✨</h1>
+        <p style="text-align:center;">Ask me about <b>Science, Math, IT, AI, or Languages</b> — I’ll explain everything step-by-step!</p>
+        """
+    )
+
+    chatbot = gr.Chatbot(
+        label="EduAI Chat",
+        height=450,
+        bubble_full_width=False,
+        avatar_images=("https://cdn-icons-png.flaticon.com/512/4712/4712104.png", None)
+    )
+
+    context_input = gr.Textbox(
+        label="🔧 Context (Optional)",
+        placeholder="Add custom instructions for EduAI (e.g., 'Explain like I’m 16 years old')",
+        lines=2
+    )
 
-def save_memory(memory):
-    with open(MEMORY_FILE, "w") as f:
-        json.dump(memory, f)
+    msg = gr.Textbox(
+        label="💬 Type your question",
+        placeholder="Ask me anything...",
+    )
+
+    clear_btn = gr.Button("🧹 Clear Chat", variant="secondary")
+
+    # ----------------
+    # Logic Connections
+    # ----------------
+    msg.submit(
+        chat_with_model,
+        [msg, chatbot, context_input],
+        [chatbot, chatbot]
+    )
+
+    msg.submit(lambda: "", None, msg)
+
+    clear_btn.click(lambda: ([], []), None, [chatbot, chatbot])
+
+    demo.load(eduai_greeting, None, chatbot)
 
-memory = load_memory()
 
 # ----------------
-# Chat function
+# Run App
 # ----------------
-def chat_with_model(message, history, context):
-    if not isinstance(history, list):
-        history = []
-
-    if message.lower().startswith("search "):
-        query = message[7:]
-        result = search_web(query)
-        history.append({"role": "user", "content": message})
-        history.append({"role": "assistant", "content": f"🔎 {result}"})
-        save_memory(history)
-        return history, history
-
-    conversation = [
-        {"role": "system", "content": (
-            "You are EduAI, a multilingual educational AI assistant created by a Sri Lankan student named Wafa Fazly. "
-            "Explain clearly, step-by-step, with Markdown and LaTeX for math."
-        )}
-    ]
-
-    for msg_obj in history[-5:]:
-        conversation.append(msg_obj)
-
-    conversation.append({"role": "user", "content": message})
-
-    try:
-        response = requests.post(
-            "https://router.huggingface.co/v1/chat/completions",
-            headers={"Authorization": f"Bearer {HF_TOKEN}", "Content-Type": "application/json"},
-            json={"model": "deepseek-ai/DeepSeek-V3.2-Exp:novita", "messages": conversation}
-        )
-        data = response.json()
-        reply = data["choices"][0]["message"]["content"]
-
-        reply = reply.replace("Step
+if __name__ == "__main__":
+    demo.launch()