Update app.py

app.py

@@ -5,39 +5,18 @@ from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace
 from langchain_core.messages import AIMessage, HumanMessage, SystemMessage
 
 # Load Hugging Face API Token
+os.environ["HUGGINGFACEHUB_API_KEY"] = os.getenv("HF")
+os.environ["HF_TOKEN"] = os.getenv("HF")
 
-os.environ["HUGGINGFACEHUB_API_KEY"]= os.getenv("HF")
-os.environ["HF_TOKEN"]= os.getenv("HF")
-
-
-# model = HuggingFaceEndpoint(
-#     repo_id="deepseek-ai/DeepSeek-R1",
-#     provider="nebius",
-#     temperature=0.6,
-#     max_new_tokens=200, 
-#     task="conversational"
-# )
-
-# # Wrap it into ChatHuggingFace interface
-# llama_model = ChatHuggingFace(
-#     llm=model,
-#     repo_id="deepseek-ai/DeepSeek-R1",
-#     provider="nebius",
-#     temperature=0.6,
-#     max_new_tokens=200,
-#     task="conversational"
-# )
-
-
+# Initialize model
 model = HuggingFaceEndpoint(
     repo_id="meta-llama/Llama-3.2-3B-Instruct",
     provider="nebius",
     temperature=0.6,
-    max_new_tokens=300,  # Increase for more complete outputs
+    max_new_tokens=300,
     task="conversational"
 )
 
-# Wrap it into ChatHuggingFace interface
 llama_model = ChatHuggingFace(
     llm=model,
     repo_id="meta-llama/Llama-3.2-3B-Instruct",
@@ -50,8 +29,7 @@ llama_model = ChatHuggingFace(
 # Initialize session message history
 if "message_history" not in st.session_state:
     st.session_state.message_history = [
-        SystemMessage(
-            content="""
+        SystemMessage(content="""
 You are an expert career advisor specializing in analyzing job descriptions and providing actionable insights to help job seekers tailor their resumes and skills for maximum impact.
 
 Given a Job Description, extract and present the following sections using markdown formatting:
@@ -69,28 +47,58 @@ Recommend mini projects or learning paths to strengthen the candidate’s profil
 Provide practical and specific tips to improve the candidate's resume, using bullet points.
 
 Use **bold headings** for each section and markdown bullet points (`- `). Write in a professional yet friendly tone. Be concise, clear, and focused on actionable advice.
-"""
-        )
+""")
     ]
 
-# Input area
-st.title("🧠 Smart JD Analyzer")
-jd_input = st.text_area("📄 Paste Job Description Below:", height=300)
-
-# Analyze button
-if st.button("🔍 Analyze Job Description"):
+# --- PAGE CONFIG ---
+st.set_page_config(page_title="Smart JD Analyzer", page_icon="🧠", layout="wide")
+
+# --- STYLING ---
+st.markdown("""
+    <style>
+        .main-title { font-size: 36px; font-weight: bold; color: #4a7cfc; margin-bottom: 10px; }
+        .subtitle { font-size: 18px; color: #777777; margin-bottom: 30px; }
+        .textarea-style textarea {
+            border-radius: 10px;
+            padding: 20px;
+            font-size: 16px;
+        }
+        .output-container {
+            background-color: #f4f8ff;
+            border-radius: 10px;
+            padding: 25px;
+            margin-top: 20px;
+            box-shadow: 0 4px 8px rgba(0,0,0,0.05);
+        }
+    </style>
+""", unsafe_allow_html=True)
+
+# --- HEADER ---
+st.markdown('<div class="main-title">🧠 Smart JD Analyzer</div>', unsafe_allow_html=True)
+st.markdown('<div class="subtitle">Paste a job description to get technical skills, soft skills, mini-project ideas, and resume tips instantly!</div>', unsafe_allow_html=True)
+
+# --- INPUT ---
+jd_input = st.text_area("📄 Paste Job Description Below:", height=300, placeholder="Paste the full job description here...", key="jd_input", help="Paste any software/data-related JD here to analyze it.", label_visibility="visible")
+
+# --- BUTTON ---
+analyze = st.button("🔍 Analyze JD", use_container_width=True)
+
+# --- RESPONSE ---
+if analyze:
     if jd_input.strip():
-        with st.spinner("Analyzing..."):
-            # Add user message to memory
+        with st.spinner("Analyzing job description..."):
             st.session_state.message_history.append(HumanMessage(content=jd_input))
 
-            # Call model with full conversation context
             try:
                 response = llama_model.invoke(st.session_state.message_history)
-                # Save and display response
                 st.session_state.message_history.append(AIMessage(content=response.content))
-                st.markdown(response.content)
+
+                with st.container():
+                    st.markdown('<div class="output-container">', unsafe_allow_html=True)
+                    st.markdown("### 📝 **Analysis Output**")
+                    st.markdown(response.content, unsafe_allow_html=True)
+                    st.markdown("</div>", unsafe_allow_html=True)
             except Exception as e:
                 st.error(f"❌ Error occurred: {e}")
     else:
-        st.warning("Please paste a job description before clicking the button.")
+        st.warning("⚠️ Please enter a valid job description before analyzing.")