Upload 2 files

app.py

@@ -1,3 +1,4 @@
+
 from fastapi import FastAPI, Request, Header
 from fastapi.responses import HTMLResponse
 from fastapi.staticfiles import StaticFiles
@@ -7,6 +8,7 @@ import os, uuid
 from memory import MemoryVectorStore
 from auth import authorize
 from session import init_session_db, create_session, log_interaction, get_session_logs
+from diagnostics import run_diagnostics
 
 import gradio as gr
 from sentence_transformers import SentenceTransformer
@@ -18,28 +20,34 @@ index = faiss.IndexFlatL2(384)
 memory_text = []
 
 def autonomous_agent(input_text):
-    vec = model.encode([input_text])
-    index.add(vec)
-    memory_text.append(input_text)
+    try:
+        vec = model.encode([input_text])
+        index.add(vec)
+        memory_text.append(input_text)
+
+        if index.ntotal > 1:
+            D, I = index.search(vec, k=2)
+            related = memory_text[I[0][1]]
+            response = f"🧠 Memory Match: {related}
+🤖 Working on: {input_text}"
+        else:
+            response = f"🤖 Received: {input_text}
+🧠 No prior memory yet."
 
-    if index.ntotal > 1:
-        D, I = index.search(vec, k=2)
-        related = memory_text[I[0][1]]
-        response = f"🧠 Memory Match: {related}\n🤖 Working on: {input_text}"
-    else:
-        response = f"🤖 Received: {input_text}\n🧠 No prior memory yet."
+    except Exception as e:
+        diag = run_diagnostics()
+        response = f"❌ Error: {str(e)}
+🛠️ Diagnostics: {diag['status']}"
 
     return response
 
 ui = gr.Interface(fn=autonomous_agent, inputs="text", outputs="text", title="Autonomous AI Agent", description="Self-enhancing chatbot with vector memory.")
+ui.launch()
 
 app = FastAPI()
 memory = MemoryVectorStore()
 init_session_db()
 
-from gradio.asgi import ASGIApp
-app.mount("/gradio", ASGIApp(ui))
-
 app.add_middleware(
     CORSMiddleware,
     allow_origins=["*"], allow_credentials=True, allow_methods=["*"], allow_headers=["*"]
@@ -59,7 +67,8 @@ async def session_task(request: Request, x_api_key: str = Header(...)):
     session_id = data.get("session_id", create_session(user))
     memory.add(goal)
     ideas = memory.search(goal)
-    result = f"[Goal]: {goal}\\n[Related]: {ideas}\\n[Response]: 🚧 working on it..."
+    diag = run_diagnostics()
+    result = f"[Goal]: {goal}\n[Related]: {ideas}\n[Response]: 🚧 working on it...\n🛠️ System Status: {diag['status']}"
     memory.add(result)
     log_interaction(session_id, goal, result)
     return {"session_id": session_id, "output": result}
@@ -68,4 +77,8 @@ async def session_task(request: Request, x_api_key: str = Header(...)):
 def logs(sid: str):
     return get_session_logs(sid)
 
+@app.get("/diagnostics")
+async def diagnostics():
+    return run_diagnostics()
+
 app.mount("/static", StaticFiles(directory="static"), name="static")

diagnostics.py

@@ -0,0 +1,20 @@
+
+import platform
+import psutil
+import shutil
+
+def run_diagnostics():
+    report = {
+        "platform": platform.platform(),
+        "cpu_percent": psutil.cpu_percent(),
+        "memory": psutil.virtual_memory()._asdict(),
+        "disk": shutil.disk_usage("/"),
+        "status": "🟢 All systems functional"
+    }
+
+    if report["memory"]["percent"] > 90:
+        report["status"] = "🟡 High memory usage"
+    if report["cpu_percent"] > 85:
+        report["status"] = "🟡 High CPU load"
+
+    return report