all of this was vibecoded. i just asked claude to fix all my bugs and he actually overhauled shit woaw. he only changed the name and position of a couple functions so if i want to write more things it should be fine. i love claude i love antrhopic i love vibecoding @claude make me a million dollars in a day make no mistake

main.py

@@ -6,19 +6,22 @@ import ollama
 import websockets
 from pathlib import Path
 from websockets.server import serve
-from datetime import datetime
+from utils import nots, now_str
 
 chatmodel = "hf.co/Stetsoncody/Llama-3.2-3B-Instruct-abliterated-GGUF:Q4_K_M"
 embedmodel = 'hf.co/CompendiumLabs/bge-base-en-v1.5-gguf'
 
+# resolve config relative to this script, not whatever dir it happens to get launched from
+SCRIPT_DIR = Path(__file__).resolve().parent
+CONFIG_DIR = SCRIPT_DIR / "config"
 
-def times() -> str:
-    return datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+try:
+    AUTH_TOKEN = (CONFIG_DIR / "auth_token.txt").read_text(encoding="utf-8").strip()
+except FileNotFoundError:
+    raise SystemExit("no config/auth_token.txt found — run setup_wizard.py first")
 
-def nots(line: str) -> str:
-    if line.startswith("[") and "]" in line:
-        return line.split("]", 1)[1].lstrip()
-    return line
+# only one generation at a time, we've got one cpu running one model here
+chat_semaphore = asyncio.Semaphore(1)
 
 
 # THANK YOU GUY FROM HUGGING FACE THAT MADE ALL THIS SO THAT I DON'T HAVE TO THINK I LOVE YOU
@@ -29,7 +32,7 @@ VECTOR_DB = []
 
 def add_chunk_to_database(chunk):
     embedding = ollama.embed(model=embedmodel, input=chunk)['embeddings'][0]
-    VECTOR_DB.append((chunk, embedding))
+    return embedding
 
 def cosine_similarity(a, b):
     dot_product = sum([x * y for x, y in zip(a, b)])
@@ -47,35 +50,43 @@ def retrieve(query, top_n=5):
     return similarities[:top_n]
 
 def rebuild_vector_db(longterm_lines: list[str]):
-    VECTOR_DB.clear()
+    global VECTOR_DB
+    existing = dict(VECTOR_DB)  # chunk -> embedding, so we don't re-embed stuff we already have
+    new_db = []
+    added = 0
     for i, chunk in enumerate(longterm_lines):
-        add_chunk_to_database(chunk)
-        print(f"[{times()}] Added chunk {i+1}/{len(longterm_lines)} to the database")
-
-interaction_count = 0
+        embedding = existing.get(chunk)
+        if embedding is None:
+            embedding = add_chunk_to_database(chunk)
+            added += 1
+            print(f"[{now_str()}] embedded new chunk {added} ({i+1}/{len(longterm_lines)})")
+        new_db.append((chunk, embedding))
+    VECTOR_DB = new_db
 
 
 async def ollamachat(websocket):
-    global interaction_count
     try:
         # bot sends one json payload with everything main needs
         raw = await websocket.recv()
         payload = json.loads(raw)
 
+        if payload.get("auth_token") != AUTH_TOKEN:
+            await websocket.send(json.dumps({"error": "bad auth token"}))
+            return
+
         system_prompt = payload["system_prompt"]
         user_input    = payload["user_input"]
         shortterm     = payload.get("shortterm", [])   # list of strings
         longterm      = payload.get("longterm", [])    # list of strings
 
-        interaction_count += 1
-
-        # rebuild vector db if bot signals it (every 150 interactions bot sends full longterm)
-        if payload.get("rebuild_vectors"):
-            rebuild_vector_db(longterm)
-            print(f"[{times()}] Vector DB rebuilt with {len(longterm)} chunks")
+        # rebuild vector db if bot signals it (every 150 interactions bot sends full longterm),
+        # or if we come up empty but longterm isn't — e.g. we just restarted and lost VECTOR_DB
+        if payload.get("rebuild_vectors") or (not VECTOR_DB and longterm):
+            await asyncio.to_thread(rebuild_vector_db, longterm)
+            print(f"[{now_str()}] Vector DB reconciled, {len(VECTOR_DB)} chunks")
 
         user_query = nots(user_input)
-        retrieved_knowledge = retrieve(user_query) if VECTOR_DB else []
+        retrieved_knowledge = await asyncio.to_thread(retrieve, user_query) if VECTOR_DB else []
 
         # rag chunks go in system so they don't pollute turn history
         rag_block = ""
@@ -151,24 +162,26 @@ async def ollamachat(websocket):
 
         messages.insert(0, {"role": "system", "content": system_prompt + rag_block})
 
-        params = json.loads(Path("config/params.json").read_text())
+        params = json.loads((CONFIG_DIR / "params.json").read_text())
 
-        response = ollama.chat(
-            model=chatmodel,
-            messages=messages,
-            options=params,
-        )
+        async with chat_semaphore:
+            response = await asyncio.to_thread(
+                ollama.chat,
+                model=chatmodel,
+                messages=messages,
+                options=params,
+            )
 
         # strip <think> blocks in case the model ignores think=False, thank you claude
         bot_reply = re.sub(r'<think>.*?</think>', '', response["message"]["content"], flags=re.DOTALL).strip()
 
         print(messages)
-        print(f"[{times()}] reply: {bot_reply}\n")
+        print(f"[{now_str()}] reply: {bot_reply}\n")
 
         await websocket.send(json.dumps({"ok": bot_reply}))
 
     except Exception as e:
-        error_msg = f"[{times()}] error in ollamachat: {e}"
+        error_msg = f"[{now_str()}] error in ollamachat: {e}"
         print(error_msg)
         try:
             await websocket.send(json.dumps({"error": error_msg}))
@@ -177,7 +190,7 @@ async def ollamachat(websocket):
 
 
 async def main():
-    print(f"[{times()}] hosting on ws://0.0.0.0:8765")
+    print(f"[{now_str()}] hosting on ws://0.0.0.0:8765")
     async with serve(ollamachat, "0.0.0.0", 8765, ping_interval=None, ping_timeout=None):
         await asyncio.Future()