Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,102 +1,52 @@
 import streamlit as st
-import subprocess
 import sys
+import subprocess
 import os
 
-# --- AUTO-INSTALLER (Error Fixer) ---
-def install(package):
-    subprocess.check_call([sys.executable, "-m", "pip", "install", package])
+# --- FORCE INSTALLER (The "Fixer") ---
+def install_package(package):
+    try:
+        subprocess.check_call([sys.executable, "-m", "pip", "install", package])
+    except Exception as e:
+        st.error(f"Installation failed for {package}: {e}")
 
+# Check if Gemini is missing, then install it
 try:
     import google.generativeai as genai
 except ImportError:
-    install('google-generativeai')
-    import google.generativeai as genai
+    with st.spinner("🔧 Nexus Flow is self-repairing... Installing Gemini Library"):
+        install_package("google-generativeai")
+        import google.generativeai as genai
 
-# --- PAGE SETUP ---
+# --- PAGE CONFIG ---
 st.set_page_config(page_title="Nexus Flow AI Pro", page_icon="⚡", layout="wide")
 
-# Hide Faltu UI
-st.markdown("""
-    <style>
-    #MainMenu {visibility: hidden;}
-    footer {visibility: hidden;}
-    header {visibility: hidden;}
-    </style>
-    """, unsafe_allow_html=True)
-
-# --- API KEY CHECK ---
+# --- API KEY ---
 if "GOOGLE_API_KEY" in st.secrets:
     genai.configure(api_key=st.secrets["GOOGLE_API_KEY"])
 else:
-    st.error("⚠️ Sanjeev, Settings > Secrets mein GOOGLE_API_KEY missing hai!")
+    st.error("⚠️ Sanjeev, please add GOOGLE_API_KEY in Settings > Secrets!")
     st.stop()
 
-# --- BRAIN INSTRUCTIONS ---
-instruction = """
-You are Nexus Flow AI Pro, Sanjeev's expert digital partner.
-- REASONING: Think deep inside <thinking> tags.
-- IMAGES: Use [GENERATE_IMAGE: prompt] for visuals.
-- EXPERTISE: Video Editing (Punch Edit), Coding, and SAT prep.
-"""
+# --- THE BRAIN ---
+instruction = "You are Nexus Flow AI Pro, Sanjeev's digital avatar. Expert in Video Editing (Punch Edit) and Coding."
+model = genai.GenerativeModel("gemini-1.5-flash", system_instruction=instruction)
 
-# --- MODEL LOADING (With Backup) ---
-@st.cache_resource
-def load_model():
-    try:
-        return genai.GenerativeModel("gemini-1.5-flash", system_instruction=instruction)
-    except:
-        return genai.GenerativeModel("gemini-pro", system_instruction=instruction)
-
-model = load_model()
-
-# --- SESSION MEMORY ---
+# --- SIMPLE CHAT ---
 if "messages" not in st.session_state:
     st.session_state.messages = []
-if "chat" not in st.session_state:
-    st.session_state.chat = model.start_chat(history=[])
-
-# --- SIDEBAR ---
-with st.sidebar:
-    st.title("Nexus Flow Pro 🤖")
-    st.info("Status: Online & Connected")
-    if st.button("🗑️ Clear Chat"):
-        st.session_state.messages = []
-        st.session_state.chat = model.start_chat(history=[])
-        st.rerun()
 
-# --- CHAT INTERFACE ---
 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"])
 
 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("user"):
+        st.markdown(prompt)
+    
     with st.chat_message("assistant"):
-        with st.status("Nexus Flow is analyzing...", expanded=False):
-            try:
-                response = st.session_state.chat.send_message(prompt)
-                full_res = response.text
-                
-                # Parsing Logic
-                import urllib.parse
-                img_url = None
-                if "[GENERATE_IMAGE:" in full_res:
-                    import re
-                    raw_p = re.search(r'\[GENERATE_IMAGE:\s*(.*?)\]', full_res).group(1)
-                    img_url = f"https://image.pollinations.ai/prompt/{urllib.parse.quote(raw_p)}?width=1024&height=1024&nologo=true"
-                    final_ans = f"✅ Image created: **{raw_p}**"
-                elif "<thinking>" in full_res:
-                    final_ans = full_res.split("</thinking>")[1].strip()
-                else:
-                    final_ans = full_res
-            except Exception as e:
-                final_ans = f"Error: {e}"
-
-        st.markdown(final_ans)
-        if img_url: st.image(img_url)
-        st.session_state.messages.append({"role": "assistant", "content": final_ans, "image": img_url})
+        response = model.generate_content(prompt)
+        st.markdown(response.text)
+        st.session_state.messages.append({"role": "assistant", "content": response.text})