Update app.py

app.py

@@ -33,11 +33,26 @@ st.markdown("""
         padding: 10px;
         border-radius: 10px;
     }
+    .title-container {
+        display: flex;
+        align-items: center;
+        gap: 20px;
+    }
+    .title-container img {
+        height: 80px;
+    }
     </style>
 """, unsafe_allow_html=True)
 
-st.title("🌈 Learning with Fun 🎓")
-st.subheader("Helping Kids Learn Through Interactive Books, Questions & Stories!")
+st.markdown("""
+<div class="title-container">
+    <img src="https://cdn-icons-png.flaticon.com/512/201/201623.png" alt="Kids Book">
+    <div>
+        <h1>🌈 Learning with Fun 🎓</h1>
+        <h4>Helping Kids Learn Through Interactive Books, Questions & Stories!</h4>
+    </div>
+</div>
+""", unsafe_allow_html=True)
 
 # ----------------------------- USER INPUT -----------------------------------
 grade = st.selectbox("Select your Grade", ["Grade 5", "Grade 6"])
@@ -46,6 +61,12 @@ subject = st.selectbox("Select Subject", ["Science", "Math", "English"])
 uploaded_files = st.file_uploader("Upload textbook files (PDF, DOCX, JPEG)", type=["pdf", "docx", "jpg", "jpeg"], accept_multiple_files=True)
 question = st.text_input("Ask your question in English or Urdu")
 
+submit_btn = st.button("💬 Submit Question")
+clear_btn = st.button("🧹 Clear")
+
+if clear_btn:
+    st.experimental_rerun()
+
 # ----------------------------- ENV VAR SETUP -----------------------------------
 groq_api_key = os.getenv("GROQ_API_KEY", "")
 if not groq_api_key:
@@ -56,7 +77,6 @@ temp_dir = tempfile.mkdtemp()
 
 # ------------------------- UTILITY FUNCTIONS -------------------------------
 def load_documents(uploaded_files):
-    """Load various file types into LangChain Document format."""
     docs = []
     for file in uploaded_files:
         ext = file.name.split(".")[-1].lower()
@@ -76,28 +96,22 @@ def load_documents(uploaded_files):
     return docs
 
 def split_documents(documents):
-    """Split documents into smaller chunks."""
     splitter = RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap=50)
     return splitter.split_documents(documents)
 
 def create_vector_store(chunks):
-    """Create FAISS vector DB from text chunks."""
     embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
     return FAISS.from_documents(chunks, embeddings)
 
 def retrieve_docs(query, vector_store):
-    """Search FAISS for relevant chunks."""
     return vector_store.similarity_search(query, k=3)
 
 def query_llm_groq(context, query, groq_api_key):
-    """Query GROQ LLaMA 3 API directly and return formatted answers."""
     url = "https://api.groq.com/openai/v1/chat/completions"
-
     headers = {
         "Authorization": f"Bearer {groq_api_key}",
         "Content-Type": "application/json"
     }
-
     prompt = f"""
     Context:
     {context}
@@ -109,7 +123,6 @@ def query_llm_groq(context, query, groq_api_key):
     1. A simple, educational explanation in English + Urdu.
     2. A creative storytelling version mixing English and Urdu.
     """
-
     data = {
         "model": "llama3-8b-8192",
         "messages": [
@@ -117,14 +130,12 @@ def query_llm_groq(context, query, groq_api_key):
         ],
         "temperature": 0.7
     }
-
     response = requests.post(url, headers=headers, json=data)
     response.raise_for_status()
     result = response.json()
     return result["choices"][0]["message"]["content"]
 
 def generate_audio(text, lang='ur'):
-    """Convert text to audio using gTTS and return playable audio HTML."""
     tts = gTTS(text, lang=lang)
     audio_path = os.path.join(temp_dir, "response.mp3")
     tts.save(audio_path)
@@ -135,7 +146,7 @@ def generate_audio(text, lang='ur'):
     return audio_html
 
 # ----------------------------- MAIN LOGIC ----------------------------------
-if question and uploaded_files and groq_api_key:
+if submit_btn and question and uploaded_files and groq_api_key:
     with st.spinner("Processing your documents and generating answer..."):
         documents = load_documents(uploaded_files)
         chunks = split_documents(documents)