Upload 2 files

app.py

@@ -0,0 +1,152 @@
+def main():
+    from dotenv import load_dotenv
+    load_dotenv()
+
+    # Step_1 : Setup UI with streamlit (model provider, model, system prompt, web search query)
+    import requests
+    import streamlit as st
+    from streamlit_lottie import st_lottie
+
+    # ---------- Page Configuration ----------
+    st.set_page_config(
+        page_title="LangGraph AI Chatbot",
+        layout="centered",
+        initial_sidebar_state="collapsed"
+    )
+
+    # ----------------- CUSTOM CSS ------------------
+    st.markdown(
+        """
+        <style>
+            body {
+                background-color: #111827;
+                color: #d1d5db;
+                font-family: 'Segoe UI', sans-serif;
+            }
+            .sidebar-content {
+                background-color: #1f2937;
+                padding: 20px;
+            }
+            .chat-message {
+                padding: 10px;
+                border-radius: 10px;
+                margin-bottom: 10px;
+                font-size: 16px;
+            }
+            .user-message {
+                background-color: #374151;
+            }
+            .bot-message {
+                background-color: #4b5563;
+            }
+            .avatar {
+                width: 30px;
+                height: 30px;
+                border-radius: 50%;
+                margin-right: 10px;
+            }
+            button[kind="primary"] {
+                background-color: #10b981;
+                color: white;
+                border-radius: 10px;
+                border: none;
+            }
+        </style>
+        """,
+        unsafe_allow_html=True
+    )
+
+    # ---------- Lottie Animation ----------
+    def load_lottie_url(url: str):
+        r = requests.get(url)
+        if r.status_code != 200:
+            return None
+        return r.json()
+
+    lottie_ai = load_lottie_url("https://assets10.lottiefiles.com/packages/lf20_kkflmtur.json")
+    st_lottie(lottie_ai, height=200)
+
+
+    # ---------- Avatar Config ----------
+    USER_AVATAR = "https://cdn-icons-png.flaticon.com/512/9131/9131529.png"
+    AGENT_AVATAR = "https://cdn-icons-png.flaticon.com/512/4712/4712100.png"
+
+
+    # ---------- Title and Prompt ----------
+    st.title("AI Chatbot")
+    st.caption("Ask your AI agent anything — powered by Groq and LangGraph!")
+
+    # ---------- Initialize Session State ----------
+    if "chat_history" not in st.session_state:
+        st.session_state.chat_history = []
+
+    # ---------- Inputs ----------
+    MODEL_NAMES_GROQ = ["llama-3.3-70b-versatile", "llama3-70b-8192"]
+    system_prompt = st.text_area("Define your AI Agent : ", height=68, placeholder="Type your system prompt here...")
+    select_model  = st.selectbox("Select Model  (Groq Only) : ", MODEL_NAMES_GROQ)
+    allow_web_search = st.checkbox("Allow Web Search")
+    user_query = st.text_area("Enter you query :", height=150, placeholder="Ask Anything!")
+
+    API_URL = "https://ai-agent-backend-uzhn.onrender.com/chat"
+
+    # ---------- Chat History Display ----------
+    for entry in st.session_state.chat_history:
+        with st.chat_message("user", avatar=USER_AVATAR):
+            st.markdown(entry["user"])
+        with st.chat_message("assistant", avatar=AGENT_AVATAR):
+            st.markdown(entry["agent"])
+
+    # ---------- Submit Button ----------
+    if st.button("Ask Agent!"):
+        if user_query.strip():
+            # Step_2 : Connect with backend via URL
+        
+            payload = {
+                "model_name" : select_model,
+                "system_prompt" : system_prompt,
+                "messages" : [user_query],
+                "allow_search" : allow_web_search
+            }
+            with st.spinner("Thinking... 💭"):
+                try:
+                    response = requests.post(API_URL, json=payload)
+
+                    if response.status_code == 200:
+                        try:
+                            response_data = response.json()
+                        except ValueError:
+                            st.error("⚠️ Unable to parse the server response.")
+                            response_data = {"response": response.text}
+
+                        if isinstance(response_data, dict) and "error" in response_data:
+                                st.error(response_data["error"])
+                        else:
+                            final_response = (
+                                response_data if isinstance(response_data, str)
+                                else response_data .get("response", str(response_data))
+                            )
+
+                        # Display new message
+                        with st.chat_message("user", avatar=USER_AVATAR):
+                            st.markdown(user_query)
+                        with st.chat_message("assistant", avatar=AGENT_AVATAR):
+                            st.markdown(final_response)
+
+                        # Feedback section
+                        feedback = st.radio("Was this helpful?", ["👍 Yes", "👎 No"], horizontal=True)
+                        # Export option
+                        st.download_button(
+                            label = "📄 Download Response",
+                            data = final_response,
+                            file_name = "agent_response.txt",
+                            mime = "text/plain"
+                    )
+                    else:
+                        st.error(f"🚫 Server error: {response.status_code}")
+                except Exception as e:
+                    st.error(f"❌ Backend connection error: {e}")
+
+
+# End of main
+if __name__ == "__main__":
+    main()

requirements.txt

@@ -0,0 +1,4 @@
+streamlit
+requests
+python-dotenv
+streamlit-lottie