Update app.py

app.py

@@ -1,97 +1,37 @@
 import os
 import gradio as gr
 from langchain_groq import ChatGroq
-from langchain_tavily import TavilySearch
+from langchain_core.prompts import ChatPromptTemplate
+
+system_prompt_ai_teacher = """
+You are Nimi AI, an AI Teacher at Resynclogic - Artificial Intelligence Research Institute.
+Your mission is to teach AI to beginners like you're explaining it to a 10-year-old.
+Use short sentences. Be friendly and encouraging.
+Always ask a small follow-up question.
+Always say you are “Nimi AI – AI Teacher, built at Resynclogic – Artificial Intelligence Research Institute.”
+"""
 
-# Load secrets from Hugging Face
 groq_api_key = os.environ.get("GROQ_API_KEY")
-tavily_api_key = os.environ.get("TAVILY_API_KEY")
 
-# Initialize LLM
 llm = ChatGroq(
     model_name="openai/gpt-oss-120b",
-    temperature=0,
+    temperature=0.7,
     groq_api_key=groq_api_key
 )
 
-# Initialize search
-search = TavilySearch(
-    max_results=5,
-    tavily_api_key=tavily_api_key
-)
-
-def search_agent(query):
-    if not query.strip():
-        return "Please enter a valid query."
-
-    res = search.invoke(query)
-    context = "\n".join([r["content"] for r in res.get("results", [])])
-
-    prompt = f"""
-    Using the following information from web search:
-    {context}
-
-    Question: {query}
-    Answer clearly and concisely:
-    """
-
-    response = llm.invoke(prompt)
-    return response.content.strip()
-
-custom_css = """
-body {
-    background: linear-gradient(135deg, #0f2027, #203a43, #2c5364);
-}
-
-.gradio-container {
-    max-width: 900px !important;
-    margin: auto;
-}
-
-#title {
-    font-size: 36px;
-    font-weight: 700;
-    text-align: center;
-    color: white;
-}
-
-#subtitle {
-    text-align: center;
-    color: #cfd8dc;
-    margin-bottom: 20px;
-}
-
-.card {
-    background: #111827;
-    border-radius: 16px;
-    padding: 24px;
-    box-shadow: 0px 10px 30px rgba(0,0,0,0.4);
-}
-"""
-
-with gr.Blocks(css=custom_css) as demo:
-    gr.Markdown("<div id='title'>Nithi's Search Assistant</div>")
-    gr.Markdown("<div id='subtitle'>Nithi's Search Agent</div>")
-
-    with gr.Column(elem_classes="card"):
-        query_input = gr.Textbox(
-            label="Enter your question",
-            placeholder="Enter your question",
-            lines=2
-        )
-
-        search_btn = gr.Button("Search", variant="primary")
+prompt = ChatPromptTemplate.from_messages([
+    ("system", system_prompt_ai_teacher),
+    ("human", "{user_input}")
+])
 
-        output_box = gr.Textbox(
-            label="AI Answer",
-            lines=10,
-            interactive=False
-        )
+chain = prompt | llm
 
-    search_btn.click(
-        fn=search_agent,
-        inputs=query_input,
-        outputs=output_box
-    )
+def predict(message, history):
+    response = chain.invoke({"user_input": message})
+    return response.content
 
-demo.launch()
+gr.ChatInterface(
+    predict,
+    title="NITHI'S CHATBOT – Nimi AI 🤖📘",
+    description="Beginner-friendly AI teacher. Ask anything about AI!"
+).launch()