ai_commands.py

@@ -1,4 +1,5 @@
 # ai command cogs
+import asyncio
 import logging
 import re
 import sys
@@ -17,7 +18,7 @@ from communication_subroutine import AI_QUERY_Q
 
 import ai_functions
 from constants import (
-    ASSISTANTS,
+    OLLAMA_WARM_MINUTES,
     DATA,
     GRAPHICS_PATH,
     INITIAL_TIME_WAIT,
@@ -101,74 +102,45 @@ class Events(commands.Cog):
             text = text[1900:]
 
     async def cog_load(self):
-        # The AI query worker must run regardless of the OpenAI guard below - it
-        # answers via handle_response, which works on Claude too. Start it first.
+        # The AI query worker answers via handle_response, so it works on every
+        # backend. Start it first.
         if not self.ai_query_worker.is_running():
             self.ai_query_worker.start()
-        self.logger.info("Starting personal assistants")
-        # Personal assistants use the OpenAI Assistants API (threads/runs), which
-        # has no Anthropic equivalent - skip cleanly when OpenAI isn't wired up
-        # (e.g. a Claude-only deployment) instead of crashing the cog load.
-        if OPENAICLIENT is None:
-            self.logger.warning(
-                "OPENAICLIENT niedostępny - osobiści asystenci (OpenAI Assistants API) wyłączeni"
-            )
-            return
-        # The bootstrap below must NEVER take the cog down with it. It calls the
-        # OpenAI Assistants API (beta threads/runs), which is a legacy surface -
-        # it now answers 404, and that exception propagated out of cog_load,
-        # failed the whole extension, and took EVERY AI command with it
-        # ($gadaj_teraz, $modele_ai, the conversation handler). Personal
-        # assistants are one optional feature; losing them must not disable the
-        # AI cog, which otherwise works fine on Claude and Ollama.
+        # Keeps a self-hosted model resident; it no-ops on any other provider.
+        if not self.ollama_warm_loop.is_running():
+            self.ollama_warm_loop.start()
+        # NOTE: there is no OpenAI-Assistants bootstrap any more. It called a
+        # sunset API (beta threads), 404'd, and failed the WHOLE extension -
+        # taking every AI command with it. Personal assistants now ride
+        # handle_response with per-user memory (ai_functions), so they work on
+        # Claude and Ollama too and nothing has to be created at startup.
+        self.logger.info("Osobiści asystenci: pamięć per-user, aktywny backend AI")
+
+    @tasks.loop(minutes=OLLAMA_WARM_MINUTES)
+    async def ollama_warm_loop(self):
+        """Keep a self-hosted model resident so users don't pay the load wait.
+
+        Loading is the slow part on a GPU shared with other users, so we
+        re-assert Ollama's keep_alive well inside its window. This preloads
+        WITHOUT generating - no tokens, no cost.
+
+        Hard guard: it does nothing unless the ACTIVE backend is Ollama. Firing
+        warm-ups at a metered API would burn tokens and money for nothing.
+        """
         try:
-            await self._start_personal_assistants()
+            if ai_functions.active_provider() != "ollama":
+                return
+            await ai_functions.warm_active_model()
         except Exception as exc:  # pylint: disable=broad-exception-caught
-            self.logger.warning(
-                "Osobiści asystenci (OpenAI Assistants API) wyłączeni - %s: %s. "
-                "Reszta AI (rozmowy, $gadaj_teraz, $modele_ai) działa normalnie.",
-                type(exc).__name__, exc,
-            )
+            self.logger.info("Rozgrzewanie Ollamy nieudane (nieszkodliwe): %s", exc)
 
-    async def _start_personal_assistants(self):
-        """Bootstrap the per-user OpenAI Assistants threads. Optional feature:
-        callers must treat a failure here as non-fatal (see cog_load)."""
-        for superfryta_id, superfryta in SPECJALNE_ZIEMNIACZKI.items():
-
-            if superfryta[4] != "":
-                self.logger.info(
-                    "Personal assistant for user: %s, exists id: %s,name: %s, owner: %s, special instructions: %s assistant id: %s ",
-                    superfryta_id,
-                    superfryta[0],
-                    superfryta[1],
-                    superfryta[2],
-                    superfryta[3],
-                    superfryta[4],
-                )
-                thread = await OPENAICLIENT.beta.threads.create()
-                self.logger.info("Thread id: %s", thread.id)
-                ASSISTANTS[superfryta[1]] = (
-                    superfryta[2],
-                    superfryta[4],
-                    superfryta[0],
-                    thread,
-                )
-            else:
-                self.logger.info(
-                    "Creating personal assistant for user: %s, id: %s,name: %s, owner: %s, special instructions: %s",
-                    superfryta_id,
-                    superfryta[0],
-                    superfryta[1],
-                    superfryta[2],
-                    superfryta[3],
-                )
-                await ai_functions.create_chat_assistant(
-                    superfryta_id, superfryta[0], superfryta[1], superfryta[2], superfryta[3]
-                )
-        self.logger.info("Started personal assistants")
+    @ollama_warm_loop.before_loop
+    async def before_ollama_warm_loop(self):
+        await self.bot.wait_until_ready()
 
     async def cog_unload(self):
         self.ai_query_worker.cancel()
+        self.ollama_warm_loop.cancel()
 
     @commands.hybrid_command(
         name="switch_dm_mode",
@@ -297,6 +269,15 @@ class Events(commands.Cog):
                 f"Teraz gadam przez **{nazwa_konfigu}** — "
                 f"{cfg.get('provider')} / {cfg.get('latest_model')}."
             )
+            if cfg.get("provider") == "ollama":
+                # Pay the (slow, shared-GPU) load cost NOW, in the background,
+                # so it lands on the operator switching backends rather than on
+                # whoever sends the first message. Not awaited: loading can take
+                # minutes and the command must answer immediately.
+                asyncio.create_task(ai_functions.warm_active_model())
+                message += (
+                    "\nRozgrzewam model w tle — pierwsza odpowiedź może chwilę potrwać."
+                )
             # Switched without pinning a model: show what else is on offer.
             if not model:
                 try:
@@ -430,8 +411,10 @@ class Events(commands.Cog):
                 if message.author.id == superfryta[0]:
                     self.logger.info("Specjalny ziemniak")
                     if self.armia[message.author.id] == Dm_Mode.SPECJALNY_ZIEMNIACZEK:
-                        #await self.bot.process_commands(message)
-                        await ai_functions.chat_with_assistant(message, superfryta[1])
+                        # superfryta = [discord_id, assistant_name, owner, instructions, legacy_assistant_id]
+                        await ai_functions.chat_with_personal_assistant(
+                            message, superfryta[2], superfryta[3]
+                        )
                         return
                     elif self.armia[message.author.id] == Dm_Mode.ECHO_ECHO:
                         await ai_functions.echo(message)

ai_functions.py

@@ -1,16 +1,21 @@
 import asyncio
 import json
 import logging
+import os
 import random
+import tempfile
 
 import openai
 import tiktoken
 import time
 from other_functions import discord_friendly_send
+import requests
+
 from constants import (
     AI_CONFIGS,
     AI_TIMEOUT_SECONDS,
-    ASSISTANTS,
+    ASSISTANT_MEMORY_FILE,
+    ASSISTANT_MEMORY_TURNS,
     CLAUDECLIENT,
     CYCLIC_WORDS,
     DEFAULT_AI_CONFIG,
@@ -21,6 +26,9 @@ from constants import (
     MESSAGE_TABLE,
     MESSAGE_TABLE_MUZYKA,
     OLLAMACLIENT,
+    OLLAMA_KEEP_ALIVE,
+    OLLAMA_PRELOAD_TIMEOUT,
+    OLLAMA_URL,
     OPENAICLIENT,
     SYSTEM_GPT_SETTINGS,
     WORD_REACTIONS,
@@ -290,6 +298,52 @@ async def _ollama_call(messages, model, cfg):
     return (resp.choices[0].message.content or "").strip()
 
 
+def _ollama_preload(model, keep_alive=None) -> bool:
+    """Load ``model`` into Ollama and keep it resident, generating NOTHING.
+
+    Ollama's /api/generate with a model and no prompt is the documented preload:
+    it pays the (slow, GPU-shared) load cost once and returns, producing no
+    tokens. Used to warm up on switch and to re-assert keep_alive periodically.
+
+    Blocking on purpose - callers wrap it in asyncio.to_thread.
+    """
+    if not OLLAMA_URL:
+        return False
+    logger = logging.getLogger("discord")
+    try:
+        resp = requests.post(
+            f"{OLLAMA_URL}/api/generate",
+            json={"model": model, "keep_alive": keep_alive or OLLAMA_KEEP_ALIVE},
+            timeout=OLLAMA_PRELOAD_TIMEOUT,
+        )
+        ok = resp.status_code == 200
+        logger.info("Ollama preload %s -> HTTP %s", model, resp.status_code)
+        return ok
+    except requests.exceptions.RequestException as exc:
+        logger.info("Ollama preload %s failed: %s", model, exc)
+        return False
+
+
+def active_provider() -> str:
+    """Provider of the active config - the guard every warm-up must check.
+
+    Preloading only makes sense for a self-hosted model; firing it at a metered
+    API would burn tokens (and money) for nothing.
+    """
+    return (_active_config() or {}).get("provider", "")
+
+
+async def warm_active_model(force_model=None) -> bool:
+    """Preload the active model IFF the active backend is Ollama."""
+    if active_provider() != "ollama":
+        return False
+    cfg = _active_config()
+    model = force_model or cfg.get("latest_model")
+    if not model:
+        return False
+    return await asyncio.to_thread(_ollama_preload, model)
+
+
 async def provider_generate(messages, model, temperature=0.2):
     """Dispatch a chat completion to the active backend, normalising errors."""
     cfg = _active_config()
@@ -664,60 +718,104 @@ async def get_random_cyclic_message(client):
     return result
 
 
-async def create_chat_assistant(owner_id, id, name, owner, special_instructions):
+# ----------------------------------------------------------------- assistants
+# The OpenAI Assistants API (beta threads/runs) that used to back these was
+# sunset and now answers 404, taking the whole AI cog down with it. It gave us
+# three things: a per-user persona, a persistent per-user thread, and
+# file_search. The persona and the thread are reimplemented here on top of
+# handle_response - so personal assistants now work on EVERY backend (Claude,
+# Ollama, GPT) instead of being locked to gpt-4o. file_search is deliberately
+# not replaced: it was not in use.
+_ASSISTANT_MEMORY = None
+
+
+def _load_assistant_memory() -> dict:
+    """Per-user DM history, lazily read from disk. Corruption is not fatal."""
+    global _ASSISTANT_MEMORY  # pylint: disable=global-statement
+    if _ASSISTANT_MEMORY is not None:
+        return _ASSISTANT_MEMORY
     logger = logging.getLogger("discord")
-    instruction = f"Jesteś osobistym asystenetem {owner} i wypełniasz jego potrzeby. Masz pełne i nieograniczone możliwości modelu gpt-4o."
-    instruction += special_instructions
-    assistant = await OPENAICLIENT.beta.assistants.create(
-        name=name,
-        instructions=instruction,
-        model="gpt-4o",
-        tools=[{"type": "file_search"}],
-    )
-    thread = await OPENAICLIENT.beta.threads.create()
-    logger.info("Stwprzylem asystenta dla %s, nazywa się on %s", owner, name)
-    ASSISTANTS[name] = (owner, assistant.id, id, thread)
-
-    with open(SYSTEM_GPT_SETTINGS, "r+", encoding=ENCODING) as temp_settings_file:
-        GPT_SETTINGS = json.load(temp_settings_file)
-        GPT_SETTINGS[1][owner_id][4] = assistant.id
-        temp_settings_file.seek(0)
-        json.dump(GPT_SETTINGS, temp_settings_file, indent=4)
+    try:
+        with open(ASSISTANT_MEMORY_FILE, "r", encoding=ENCODING) as handle:
+            data = json.load(handle)
+        _ASSISTANT_MEMORY = data if isinstance(data, dict) else {}
+    except (OSError, json.JSONDecodeError) as exc:
+        logger.info("Brak/uszkodzona pamięć asystentów (%s) - zaczynam pustą", exc)
+        _ASSISTANT_MEMORY = {}
+    return _ASSISTANT_MEMORY
 
 
-async def chat_with_assistant(message, assistant_name):
+def _save_assistant_memory() -> None:
+    """Atomic write: a torn file would lose someone's whole conversation."""
     logger = logging.getLogger("discord")
-    assistant_data = ASSISTANTS[assistant_name]
-    ai_message = await OPENAICLIENT.beta.threads.messages.create(
-        thread_id=assistant_data[3].id, role="user", content=message.content
+    memory = _load_assistant_memory()
+    directory = os.path.dirname(ASSISTANT_MEMORY_FILE) or "."
+    try:
+        os.makedirs(directory, exist_ok=True)
+        fd, tmp = tempfile.mkstemp(dir=directory, suffix=".tmp")
+        with os.fdopen(fd, "w", encoding=ENCODING) as handle:
+            json.dump(memory, handle, ensure_ascii=False)
+        os.replace(tmp, ASSISTANT_MEMORY_FILE)
+    except OSError as exc:
+        logger.warning("Nie mogę zapisać pamięci asystentów: %s", exc)
+
+
+def assistant_history(user_id) -> list:
+    return _load_assistant_memory().setdefault(str(user_id), [])
+
+
+def remember_assistant_turn(user_id, user_text, reply_text) -> list:
+    """Append one exchange and trim to the most recent turns.
+
+    A plain trim, not the AI summarisation used for the bar's shared memory:
+    these are private DMs and must not end up in a public 'legend'.
+    """
+    history = assistant_history(user_id)
+    history.append({"role": "user", "content": user_text})
+    history.append({"role": "assistant", "content": reply_text})
+    if len(history) > ASSISTANT_MEMORY_TURNS:
+        del history[: len(history) - ASSISTANT_MEMORY_TURNS]
+    _save_assistant_memory()
+    return history
+
+
+def build_assistant_messages(user_id, owner, special_instructions, prompt) -> list:
+    """System persona + this user's own history + the new turn."""
+    system = (
+        f"Jesteś osobistym asystentem {owner} i wypełniasz jego potrzeby. "
+        f"{special_instructions or ''}"
+    ).strip()
+    return (
+        [{"role": "system", "content": system}]
+        + list(assistant_history(user_id))
+        + [{"role": "user", "content": prompt}]
     )
-    logger.info(ai_message)
-    run = await OPENAICLIENT.beta.threads.runs.create_and_poll(
-        thread_id=assistant_data[3].id,
-        assistant_id=assistant_data[1],
-        instructions=f"Pisze do Ciebie {assistant_data[0]} udziel mu wszelkiej pomocy",
+
+
+async def chat_with_personal_assistant(message, owner, special_instructions):
+    """Answer a DM as this user's personal assistant, on the active backend.
+
+    request_type="NONE" with an explicit message list keeps this OUT of the
+    bar's shared memory - the conversation is carried by the per-user history
+    built above and stored separately.
+    """
+    logger = logging.getLogger("discord")
+    user_id = message.author.id
+    prompt = message.content
+    messages = build_assistant_messages(user_id, owner, special_instructions, prompt)
+    result, _table = await handle_response(
+        prompt,
+        False,
+        False,
+        [],
+        str(owner),
+        "NONE",
+        none_request=messages,
     )
-    done = False
-    while not done:
-        if run.status == "completed":
-            messsages = await OPENAICLIENT.beta.threads.messages.list(
-                thread_id=assistant_data[3].id
-            )
-            logger.info(messsages)
-            reply_content = messsages.data[0].content
-            logger.info(reply_content)
-            chat_response = ""
-            for block in reply_content:
-                logger.info(block.text.value)
-                chat_response += block.text.value
-                await discord_friendly_send(message.channel, chat_response)
-                # await message.channel.send(chat_response)
-            done = True
-        elif run.status == "cancelled":
-            await discord_friendly_send(message.channel, "Cos sie wywaliło")
-        else:
-            logger.info(run.status)
-        asyncio.sleep(5)
+    remember_assistant_turn(user_id, prompt, result)
+    logger.info("Asystent odpowiedział %s (%d znaków)", owner, len(result or ""))
+    await discord_friendly_send(message.channel, result)
+    return result
 
 
 async def echo(message):

constants.py

@@ -245,6 +245,16 @@ DELIVERED_DIR = os.getenv(
 )
 DELIVERED_MAX = int(os.getenv("CONJURER_DELIVERED_MAX", "10000"))
 
+# Personal DM assistants. Replaces the OpenAI Assistants API (threads/runs),
+# which was sunset and answers 404: the persona now rides handle_response, so it
+# works on EVERY backend, and the conversation lives here instead of on OpenAI's
+# server. Kept per user so private DMs never bleed into the bar's shared memory,
+# and trimmed to the most recent turns so it cannot grow without bound.
+ASSISTANT_MEMORY_FILE = os.getenv(
+    "CONJURER_ASSISTANT_MEMORY", os.path.join(_STATE_ROOT, "assistant_memory.json")
+)
+ASSISTANT_MEMORY_TURNS = int(os.getenv("CONJURER_ASSISTANT_MEMORY_TURNS", "40"))
+
 FILE_SERVICE_ADDRESS = os.getenv("CONJURER_FILE_SERVICE", "http://192.168.1.15:5000")
 RADIO_HARBOR_ADDRESS = os.getenv("CONJURER_RADIO_HARBOR", "http://192.168.1.15:54321")
 # Betoniarka (radio-operator service colocated with Liquidsoap). Falls back to
@@ -411,6 +421,19 @@ else:
 AI_TIMEOUT_SECONDS = int(os.getenv("CONJURER_AI_TIMEOUT_SECONDS", "120"))
 
 OLLAMA_URL = os.getenv("CONJURER_OLLAMA_URL", "").rstrip("/")
+# Keeping a self-hosted model resident. Loading it is the slow part (it is
+# offloaded to a GPU shared with other users), so we preload it - Ollama's
+# /api/generate with a model and NO prompt loads it and generates nothing, which
+# costs no tokens and no money. KEEP_ALIVE is how long Ollama should then hold
+# it; the warm loop re-asserts that well inside the window.
+# STRICTLY Ollama-only: doing this against a paid API would burn tokens for
+# nothing, so every caller checks the active provider first.
+OLLAMA_KEEP_ALIVE = os.getenv("CONJURER_OLLAMA_KEEP_ALIVE", "30m")
+OLLAMA_WARM_MINUTES = float(os.getenv("CONJURER_OLLAMA_WARM_MINUTES", "10"))
+# A preload waits for the model to finish loading, which on a shared GPU is the
+# slow path we are trying to move off the user's first message.
+OLLAMA_PRELOAD_TIMEOUT = int(os.getenv("CONJURER_OLLAMA_PRELOAD_TIMEOUT", "600"))
+
 OLLAMA_LATEST_MODEL = os.getenv("CONJURER_OLLAMA_MODEL", "llama3.1:8b")
 OLLAMA_CHEAP_MODEL = os.getenv("CONJURER_OLLAMA_CHEAP_MODEL", OLLAMA_LATEST_MODEL)
 if openai and OLLAMA_URL:

tests/unit/test_ai_provider_switch.py

@@ -394,3 +394,143 @@ def test_persist_survives_an_unreadable_settings_file(tmp_path, monkeypatch):
     broken.write_text("{ not json", encoding="utf-8")
     monkeypatch.setattr(ai_functions, "SYSTEM_GPT_SETTINGS", str(broken))
     ai_functions._persist_active_ai_config("gpt", model_for="gpt")  # must not raise
+
+
+# ----------------------------------------------- keep-warm (Ollama ONLY) ----
+# The money guard: preloading a self-hosted model is free, but firing the same
+# thing at a metered API would burn tokens for nothing. These pin that it can
+# only ever happen for Ollama.
+
+
+def test_warm_active_model_is_a_noop_for_paid_providers(monkeypatch):
+    called = []
+    monkeypatch.setattr(
+        ai_functions, "_ollama_preload", lambda *a, **k: called.append(a) or True
+    )
+    for paid in ("gpt", "claude"):
+        _reset_active(paid)
+        try:
+            assert asyncio.run(ai_functions.warm_active_model()) is False
+        finally:
+            _reset_active("gpt")
+    assert called == [], "a paid backend must never be preloaded"
+
+
+def test_warm_active_model_preloads_when_ollama_is_active(monkeypatch):
+    monkeypatch.setitem(
+        ai_functions.AI_CONFIGS,
+        "ollama",
+        {"provider": "ollama", "latest_model": "qwen2.5:7b", "cheap_model": "c"},
+    )
+    seen = {}
+    monkeypatch.setattr(
+        ai_functions, "_ollama_preload", lambda model, *a, **k: seen.update(model=model) or True
+    )
+    _reset_active("ollama")
+    try:
+        assert asyncio.run(ai_functions.warm_active_model()) is True
+    finally:
+        _reset_active("gpt")
+    assert seen["model"] == "qwen2.5:7b"
+
+
+def test_active_provider_reports_the_switch():
+    _reset_active("gpt")
+    assert ai_functions.active_provider() == "openai"
+    _reset_active("claude")
+    try:
+        assert ai_functions.active_provider() == "anthropic"
+    finally:
+        _reset_active("gpt")
+
+
+def test_preload_sends_no_prompt_so_it_generates_nothing(monkeypatch):
+    # Ollama's documented preload: a model and keep_alive, and NO prompt. If a
+    # prompt ever crept in, every warm-up would silently generate tokens.
+    sent = {}
+
+    class _Resp:
+        status_code = 200
+
+    monkeypatch.setattr(ai_functions, "OLLAMA_URL", "http://ollama:11434")
+    monkeypatch.setattr(
+        ai_functions.requests, "post",
+        lambda url, json=None, timeout=None: sent.update(url=url, body=json) or _Resp(),
+    )
+    assert ai_functions._ollama_preload("qwen2.5:7b") is True
+    assert sent["url"].endswith("/api/generate")
+    assert sent["body"]["model"] == "qwen2.5:7b"
+    assert "keep_alive" in sent["body"]
+    assert "prompt" not in sent["body"], "a preload must not generate"
+
+
+def test_preload_without_endpoint_is_a_noop(monkeypatch):
+    monkeypatch.setattr(ai_functions, "OLLAMA_URL", "")
+    assert ai_functions._ollama_preload("x") is False
+
+
+# ------------------------------------------- personal assistants (per user) --
+# Replaces the sunset OpenAI Assistants API. The two properties that matter:
+# each user's DM history is ISOLATED (private DMs must not leak into another
+# user's context or the bar's shared memory), and it stays BOUNDED.
+
+
+def _fresh_assistant_memory(tmp_path, monkeypatch, turns=40):
+    monkeypatch.setattr(
+        ai_functions, "ASSISTANT_MEMORY_FILE", str(tmp_path / "assistant_memory.json")
+    )
+    monkeypatch.setattr(ai_functions, "ASSISTANT_MEMORY_TURNS", turns)
+    monkeypatch.setattr(ai_functions, "_ASSISTANT_MEMORY", None)
+
+
+def test_assistant_history_is_isolated_per_user(tmp_path, monkeypatch):
+    _fresh_assistant_memory(tmp_path, monkeypatch)
+    ai_functions.remember_assistant_turn(111, "sekret Anny", "ok Anna")
+    ai_functions.remember_assistant_turn(222, "sekret Bartka", "ok Bartek")
+
+    anna = ai_functions.assistant_history(111)
+    bartek = ai_functions.assistant_history(222)
+    assert [m["content"] for m in anna] == ["sekret Anny", "ok Anna"]
+    assert [m["content"] for m in bartek] == ["sekret Bartka", "ok Bartek"]
+    assert "sekret Anny" not in str(bartek)   # no cross-user bleed
+
+
+def test_assistant_history_is_trimmed_to_the_bound(tmp_path, monkeypatch):
+    _fresh_assistant_memory(tmp_path, monkeypatch, turns=4)
+    for i in range(10):
+        ai_functions.remember_assistant_turn(1, f"u{i}", f"a{i}")
+    history = ai_functions.assistant_history(1)
+    assert len(history) == 4                          # bounded
+    assert history[-1]["content"] == "a9"             # newest kept
+    assert all("u0" != m["content"] for m in history)  # oldest dropped
+
+
+def test_assistant_history_survives_a_restart(tmp_path, monkeypatch):
+    _fresh_assistant_memory(tmp_path, monkeypatch)
+    ai_functions.remember_assistant_turn(7, "pamietaj", "pamietam")
+    # Simulate a restart: drop the in-memory cache, re-read from disk.
+    monkeypatch.setattr(ai_functions, "_ASSISTANT_MEMORY", None)
+    assert [m["content"] for m in ai_functions.assistant_history(7)] == [
+        "pamietaj",
+        "pamietam",
+    ]
+
+
+def test_assistant_messages_carry_persona_history_and_new_turn(tmp_path, monkeypatch):
+    _fresh_assistant_memory(tmp_path, monkeypatch)
+    ai_functions.remember_assistant_turn(5, "wczoraj", "odpowiedz")
+    msgs = ai_functions.build_assistant_messages(
+        5, "Towarzysz Młotek", "Mówisz po polsku.", "dzisiaj"
+    )
+    assert msgs[0]["role"] == "system"
+    assert "Towarzysz Młotek" in msgs[0]["content"]
+    assert "Mówisz po polsku." in msgs[0]["content"]
+    assert [m["content"] for m in msgs[1:]] == ["wczoraj", "odpowiedz", "dzisiaj"]
+
+
+def test_corrupt_assistant_memory_starts_empty_instead_of_crashing(tmp_path, monkeypatch):
+    path = tmp_path / "assistant_memory.json"
+    path.write_text("{ not json", encoding="utf-8")
+    monkeypatch.setattr(ai_functions, "ASSISTANT_MEMORY_FILE", str(path))
+    monkeypatch.setattr(ai_functions, "_ASSISTANT_MEMORY", None)
+    assert ai_functions.assistant_history(1) == []