AI: add a self-hosted Ollama backend, and let the picker choose the model

The bot could talk to OpenAI or Anthropic; this adds Ollama as a third
provider so it can run against models hosted on our own box, and extends
the switch command to pick WHICH model - not just which backend.

Provider: Ollama exposes an OpenAI-compatible /v1 surface, so the client is
just openai.AsyncOpenAI(base_url=OLLAMA_URL + "/v1"). That reuses the
existing message format and the whole _map_openai_error mapping instead of
forking a second error taxonomy. There is no API key - the endpoint IS the
configuration, so the backend stays dormant (and refuses to be selected,
with a message naming the variable) until CONJURER_OLLAMA_URL is set, the
same way the Conan bridge behaves.

Model selection:
* list_provider_models() asks the SERVER for Ollama (/v1/models), so the
  picker shows what is actually pulled on the box rather than a hardcoded
  list. Hosted providers just report what they are wired to.
* set_active_model() pins the config's latest_model and persists it;
  cheap_model is left alone so the MUSIC path keeps its cheaper backend.
* $gadaj_teraz now takes "<config> [model]", and a new read-only $modele_ai
  lists what is available. Pinning an id Ollama does not have is rejected up
  front with the real list - otherwise the typo only surfaces later as a
  failed reply.

Two fixes this exposed:
* AI_CONFIGS now merges built-in defaults with the settings-file block
  instead of letting the file win outright. Every provider switch persists a
  "configs" block, so a file written by an older build would have
  permanently hidden ollama from the picker after an upgrade.
* _persist_active_ai_config assigns "configs" instead of setdefault, so a
  pinned model actually survives a restart.
* the hardcoded 120s response timeout is now CONJURER_AI_TIMEOUT_SECONDS - a
  self-hosted model on a modest GPU can legitimately need longer.

Tests cover: ollama appears in the picker, select_model maps the legacy
gpt-4o default instead of leaking it, model listing (server-queried, sorted,
de-duplicated, failure -> AIError, unconfigured -> auth), pinning (latest
only, blank/unknown rejected), and that provider_generate routes to the new
path. Suite: 68 unit + 70 integration green.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

ai_functions.py

@@ -9,6 +9,7 @@ import time
 from other_functions import discord_friendly_send
 from constants import (
     AI_CONFIGS,
+    AI_TIMEOUT_SECONDS,
     ASSISTANTS,
     CLAUDECLIENT,
     CYCLIC_WORDS,
@@ -19,6 +20,7 @@ from constants import (
     MEMORY_FIVE_SIARA,
     MESSAGE_TABLE,
     MESSAGE_TABLE_MUZYKA,
+    OLLAMACLIENT,
     OPENAICLIENT,
     SYSTEM_GPT_SETTINGS,
     WORD_REACTIONS,
@@ -92,11 +94,53 @@ def set_active_ai_config(name: str) -> dict:
         raise RuntimeError("klient Anthropic nie jest skonfigurowany (brak ANTHROPIC_API_KEY)")
     if provider == "openai" and OPENAICLIENT is None:
         raise RuntimeError("klient OpenAI nie jest skonfigurowany (brak OPENAI_API_KEY)")
+    if provider == "ollama" and OLLAMACLIENT is None:
+        raise RuntimeError("Ollama nie jest skonfigurowana (ustaw CONJURER_OLLAMA_URL)")
     _ACTIVE_CONFIG_NAME = name
     _persist_active_ai_config(name)
     return cfg
 
 
+async def list_provider_models(name: str = None):
+    """Model ids selectable for a config.
+
+    For Ollama this ASKS THE SERVER (its OpenAI-compatible /v1/models), so the
+    picker always reflects what is actually pulled on the box rather than a
+    hardcoded list. Hosted providers are not enumerated - we only report what
+    the config is wired to.
+    """
+    cfg = AI_CONFIGS.get(name or _ACTIVE_CONFIG_NAME) or _active_config()
+    if cfg.get("provider") == "ollama":
+        if OLLAMACLIENT is None:
+            raise AIError(
+                "auth",
+                RuntimeError("Ollama nie jest skonfigurowana (ustaw CONJURER_OLLAMA_URL)"),
+            )
+        try:
+            resp = await OLLAMACLIENT.models.list()
+        except Exception as exc:  # pylint: disable=broad-except
+            raise _map_openai_error(exc)
+        return sorted({item.id for item in resp.data})
+    return [m for m in (cfg.get("latest_model"), cfg.get("cheap_model")) if m]
+
+
+def set_active_model(model: str, name: str = None) -> dict:
+    """Pin the model a config uses for normal replies, and persist it.
+
+    Only ``latest_model`` is changed; ``cheap_model`` stays as configured so the
+    MUSIC path keeps its cheaper backend.
+    """
+    cfg_name = name or _ACTIVE_CONFIG_NAME
+    if cfg_name not in AI_CONFIGS:
+        raise KeyError(cfg_name)
+    if not model or not model.strip():
+        raise ValueError("pusta nazwa modelu")
+    cfg = AI_CONFIGS[cfg_name]
+    cfg["latest_model"] = model.strip()
+    _persist_active_ai_config(_ACTIVE_CONFIG_NAME)
+    return cfg
+
+
 def _persist_active_ai_config(name: str) -> None:
     """Best-effort write of the active-config choice into system_gpt_settings.json.
 
@@ -117,7 +161,10 @@ def _persist_active_ai_config(name: str) -> None:
         return
     if len(data) > 2 and isinstance(data[2], dict):
         data[2]["active"] = name
-        data[2].setdefault("configs", AI_CONFIGS)
+        # Assign (not setdefault): AI_CONFIGS is the in-memory truth and may
+        # carry a model pinned via set_active_model, which setdefault would
+        # silently drop on restart.
+        data[2]["configs"] = AI_CONFIGS
     else:
         data = data[:2] + [{"active": name, "configs": AI_CONFIGS}]
     try:
@@ -214,12 +261,37 @@ async def _anthropic_call(messages, model, cfg):
     return text.strip()
 
 
+async def _ollama_call(messages, model, cfg):
+    """Self-hosted counterpart of openai_call. Returns a plain string.
+
+    Ollama exposes an OpenAI-compatible /v1 surface, so the same message format
+    and the same error mapping apply - only the base_url and the model ids
+    differ. Chat Completions (not the Responses API) is what Ollama implements.
+    """
+    if OLLAMACLIENT is None:
+        raise AIError(
+            "auth",
+            RuntimeError("Ollama nie jest skonfigurowana (ustaw CONJURER_OLLAMA_URL)"),
+        )
+    try:
+        resp = await OLLAMACLIENT.chat.completions.create(
+            model=model,
+            messages=messages,
+            temperature=float(cfg.get("temperature", 0.2)),
+        )
+    except Exception as exc:  # pylint: disable=broad-except
+        raise _map_openai_error(exc)
+    return (resp.choices[0].message.content or "").strip()
+
+
 async def provider_generate(messages, model, temperature=0.2):
     """Dispatch a chat completion to the active backend, normalising errors."""
     cfg = _active_config()
     try:
         if cfg.get("provider") == "anthropic":
             return await _anthropic_call(messages, model, cfg)
+        if cfg.get("provider") == "ollama":
+            return await _ollama_call(messages, model, cfg)
         return await openai_call(messages, model, temperature)
     except AIError:
         raise
@@ -459,7 +531,7 @@ async def handle_response(
     try:
         # ...przygotowanie messages/system prompt/itp. jak masz...
         # retry/backoff + deadline (zachowuje Twoją semantykę logowania)
-        timeout_sec = 120
+        timeout_sec = AI_TIMEOUT_SECONDS
         deadline = time.time() + timeout_sec
         response = await asyncio.wait_for(
             provider_generate(messages=history_msgs, model=model_to_use),