Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,110 @@
-import altair as alt
-import numpy as np
-import pandas as pd
 import streamlit as st
+import google.generativeai as genai
+import urllib.parse
+import re
 
-"""
-# Welcome to Streamlit!
+# 1. Page Configuration & Custom CSS (Clean Interface)
+st.set_page_config(page_title="Nexus Flow AI Pro", page_icon="⚡", layout="wide")
+
+st.markdown("""
+    <style>
+    #MainMenu {visibility: hidden;}
+    footer {visibility: hidden;}
+    header {visibility: hidden;}
+    .stChatMessage { border-radius: 15px; margin-bottom: 10px; border: 1px solid #333; }
+    .stStatusWidget { border-radius: 10px; }
+    </style>
+    """, unsafe_allow_html=True)
 
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
+# 2. API Security (Secrets se Key uthayega)
+if "GOOGLE_API_KEY" in st.secrets:
+    genai.configure(api_key=st.secrets["GOOGLE_API_KEY"])
+else:
+    st.error("⚠️ Settings > Secrets mein 'GOOGLE_API_KEY' add karein!")
+    st.stop()
 
-In the meantime, below is an example of what you can do with just a few lines of code:
+# 3. The "ChatGPT" Brain Instructions
+instruction = """
+You are Nexus Flow AI Pro, the digital avatar of Sanjeev. 
+- REASONING: For complex questions, you MUST first think step-by-step inside <thinking> tags. 
+- IMAGES: If asked for a photo/image/drawing, respond ONLY with: [GENERATE_IMAGE: highly detailed English prompt]
+- STYLE: Speak in Hinglish. Be an expert in Video Editing (Punch Edit), Python, and SAT/JEE.
 """
 
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+# 4. Initialize Model & Memory
+@st.cache_resource
+def load_model():
+    return genai.GenerativeModel("gemini-1.5-flash", system_instruction=instruction)
+
+model = load_model()
+
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+if "chat_session" not in st.session_state:
+    st.session_state.chat_session = model.start_chat(history=[])
+
+# Sidebar
+with st.sidebar:
+    st.title("Nexus Flow Pro 🤖")
+    st.write("Owner: Sanjeev")
+    if st.button("🗑️ Clear Chat"):
+        st.session_state.messages = []
+        st.session_state.chat_session = model.start_chat(history=[])
+        st.rerun()
+
+# 5. Display Chat History
+for m in st.session_state.messages:
+    with st.chat_message(m["role"]):
+        st.markdown(m["content"])
+        if m.get("image"):
+            st.image(m["image"], caption="Generated by Nexus Flow")
+
+# 6. User Input & Processing
+if prompt := st.chat_input("Kaise help karu Sanjeev?"):
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    with st.chat_message("user"):
+        st.markdown(prompt)
+
+    with st.chat_message("assistant"):
+        final_ans = ""
+        img_url = None
+        
+        with st.status("Nexus Flow is thinking...", expanded=True) as status:
+            try:
+                # Get AI Response
+                response = st.session_state.chat_session.send_message(prompt)
+                full_res = response.text
+                
+                # Logic A: Deep Reasoning Parsing
+                if "<thinking>" in full_res:
+                    parts = full_res.split("</thinking>")
+                    thinking_process = parts[0].replace("<thinking>", "").strip()
+                    st.expander("🧠 My Reasoning Process", expanded=False).write(thinking_process)
+                    final_ans = parts[1].strip()
+                
+                # Logic B: Image Generation Parsing
+                if "[GENERATE_IMAGE:" in full_res:
+                    match = re.search(r'\[GENERATE_IMAGE:\s*(.*?)\]', full_res)
+                    if match:
+                        raw_prompt = match.group(1).strip()
+                        # Direct Image from Pollinations
+                        img_url = f"https://image.pollinations.ai/prompt/{urllib.parse.quote(raw_prompt)}?width=1024&height=1024&model=flux&nologo=true"
+                        final_ans = f"✅ Image Ready: **{raw_prompt}**"
+                
+                if not final_ans:
+                    final_ans = full_res
+                
+                status.update(label="Analysis Complete!", state="complete")
+                
+            except Exception as e:
+                final_ans = f"❌ Error: {str(e)}"
+                status.update(label="System Crash!", state="error")
+
+        # UI Update
+        st.markdown(final_ans)
+        if img_url:
+            st.image(img_url)
+        
+        # Save to Session
+        st.session_state.messages.append({"role": "assistant", "content": final_ans, "image": img_url})
+