Update app.py

app.py

@@ -1,33 +1,76 @@
-
+import streamlit as st
 import os
-from flask import Flask, request, jsonify
-from huggingface_hub import HfApi
-
-app = Flask(__name__)
-TOKEN = os.getenv("HF_TOKEN")
-VAULT_ID = "DJ-Goanna-Coding/Mapping-and-Inventory-storage" # All feed the Librarian Vault
-api = HfApi(token=TOKEN)
-
-@app.route('/ignite_harvest', methods=['POST'])
-def catch_payload():
-    if not TOKEN:
-        return jsonify({"status": "ERROR", "message": "HF_TOKEN missing"}), 500
-    try:
-        payload = request.json
-        filename = payload.get("fileName", "swarm_shard.9293")
-        api.upload_file(
-            path_or_fileobj=payload.get("content", "").encode('utf-8'),
-            path_in_repo=f"ingested_core/{filename}",
-            repo_id=VAULT_ID,
-            repo_type="dataset"
-        )
-        return jsonify({"status": "CAUGHT_BY_SWARM", "file": filename}), 200
-    except Exception as e:
-        return jsonify({"status": "ERROR", "message": str(e)}), 500
-
-@app.route('/', methods=['GET'])
-def health_check():
-    return jsonify({"status": "SWARM_NODE_ONLINE"})
-
-if __name__ == "__main__":
-    app.run(host="0.0.0.0", port=7860)
+from smolagents import CodeAgent, HfApiModel, DuckDuckGoSearchTool
+from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, StorageContext, load_index_from_storage
+from datetime import datetime
+
+# --- 1. SOVEREIGN BRAIN SETUP ---
+# Powered by Qwen 2.5 72B for elite reasoning and code generation
+model = HfApiModel(model_id="Qwen/Qwen2.5-72B-Instruct", token=os.getenv("HF_TOKEN"))
+agent = CodeAgent(tools=[DuckDuckGoSearchTool()], model=model)
+
+st.set_page_config(page_title="TIA-ARCHITECT-CORE", page_icon="🧠", layout="wide")
+
+# --- 2. LIBRARIAN MEMORY (RAG Intelligence) ---
+INDEX_DIR = "./citadel_index"
+DATA_DIR = "./ingested_core" # Target for Termux harvest
+
+def initialize_memory():
+    if os.path.exists(DATA_DIR) and any(os.scandir(DATA_DIR)):
+        if not os.path.exists(INDEX_DIR):
+            documents = SimpleDirectoryReader(DATA_DIR).load_data()
+            index = VectorStoreIndex.from_documents(documents)
+            index.storage_context.persist(persist_dir=INDEX_DIR)
+        else:
+            storage_context = StorageContext.from_defaults(persist_dir=INDEX_DIR)
+            index = load_index_from_storage(storage_context)
+        return index
+    return None
+
+citadel_memory = initialize_memory()
+
+# --- 3. COMMAND INTERFACE (The HUD) ---
+st.title("🧠 TIA-ARCHITECT-CORE: SOVEREIGN ORACLE")
+st.subheader("777.1122 Alignment | Q.G.T.N.L. Citadel Mesh")
+
+with st.sidebar:
+    st.success("🟢 NODE ONLINE")
+    st.info(f"Substrate: Forever_Learning (321GB)")
+    if citadel_memory:
+        st.write("📚 **Librarian Status:** Phase-Locked")
+    else:
+        st.warning("⚠️ **Memory Status:** Awaiting Harvest")
+    
+    st.markdown("---")
+    st.write("**Active Districts:** D01 - D46")
+
+# --- 4. THE INTERFACE (Where the AI helps you) ---
+st.write("### 💬 Execute Citadel Command")
+user_query = st.chat_input("Commander, what is our next objective?")
+
+if user_query:
+    with st.chat_message("user"):
+        st.write(user_query)
+    
+    with st.chat_message("assistant"):
+        st.write("🚀 *T.I.A. is calculating via Citadel Mesh...*")
+        
+        # Priority 1: Search RAG Memory if available
+        if citadel_memory:
+            query_engine = citadel_memory.as_query_engine()
+            context_response = query_engine.query(user_query)
+            st.markdown(f"**Archive Resonance:** {context_response}")
+            
+        # Priority 2: Agentic Action (Python execution & Web search)
+        agent_response = agent.run(user_query)
+        st.write(agent_response)
+
+# --- 5. TELEMETRY ---
+with st.expander("📡 Mesh Telemetry"):
+    st.json({
+        "status": "OPERATOR_GRADE",
+        "alignment": "9,293",
+        "version": "v25.0.OMNI++",
+        "bridge": "Verified",
+        "timestamp": datetime.now().isoformat()
+    })