fix(ai): cap quick chat generation

services/comms/atlasbot-deployment.yaml

@@ -131,6 +131,8 @@ spec:
               value: "600"
             - name: ATLASBOT_QUICK_TIME_BUDGET_SEC
               value: "15"
+            - name: ATLASBOT_FAST_NUM_PREDICT
+              value: "48"
             - name: ATLASBOT_SMART_TIME_BUDGET_SEC
               value: "45"
             - name: ATLASBOT_GENIUS_TIME_BUDGET_SEC

services/comms/scripts/atlasbot/bot.py

@@ -54,6 +54,7 @@ THINKING_INTERVAL_SEC = int(os.environ.get("ATLASBOT_THINKING_INTERVAL_SEC", "12
 QUICK_TIME_BUDGET_SEC = float(os.environ.get("ATLASBOT_QUICK_TIME_BUDGET_SEC", "15"))
 SMART_TIME_BUDGET_SEC = float(os.environ.get("ATLASBOT_SMART_TIME_BUDGET_SEC", "45"))
 GENIUS_TIME_BUDGET_SEC = float(os.environ.get("ATLASBOT_GENIUS_TIME_BUDGET_SEC", "180"))
+FAST_NUM_PREDICT = int(os.environ.get("ATLASBOT_FAST_NUM_PREDICT", "48"))
 OLLAMA_RETRIES = int(os.environ.get("ATLASBOT_OLLAMA_RETRIES", "2"))
 OLLAMA_SERIALIZE = os.environ.get("ATLASBOT_OLLAMA_SERIALIZE", "true").lower() != "false"
 
@@ -492,6 +493,12 @@ def _mode_heartbeat_sec(mode: str) -> int:
     return max(5, min(THINKING_INTERVAL_SEC, int(max(5.0, budget / 3.0))))
 
 
+def _mode_ollama_options(mode: str) -> dict[str, Any] | None:
+    if _normalize_mode(mode) == "fast":
+        return {"num_predict": max(8, FAST_NUM_PREDICT)}
+    return None
+
+
 # Matrix HTTP helper.
 def req(method: str, path: str, token: str | None = None, body=None, timeout=60, base: str | None = None):
     url = (base or BASE) + path
@@ -3085,17 +3092,19 @@ def _ollama_call_safe(
     system_override: str | None = None,
     model: str | None = None,
     timeout: float | None = None,
+    options: dict[str, Any] | None = None,
 ) -> str:
     try:
-        return _ollama_call(
+        kwargs: dict[str, Any] = {
-            hist_key,
+            "context": context,
-            prompt,
+            "use_history": False,
-            context=context,
+            "system_override": system_override,
-            use_history=False,
+            "model": model,
-            system_override=system_override,
+            "timeout": timeout,
-            model=model,
+        }
-            timeout=timeout,
+        if options:
-        )
+            kwargs["options"] = options
+        return _ollama_call(hist_key, prompt, **kwargs)
     except Exception:
         return fallback
 
@@ -4321,6 +4330,7 @@ def _open_ended_fast_single(
         system_override=_open_ended_system(),
         model=model,
         timeout=_mode_ollama_timeout_sec("fast"),
+        options=_mode_ollama_options("fast"),
     )
     if not _has_body_lines(reply):
         reply = _ollama_call_safe(
@@ -4331,6 +4341,7 @@ def _open_ended_fast_single(
             system_override=_open_ended_system(),
             model=model,
             timeout=_mode_ollama_timeout_sec("fast"),
+            options=_mode_ollama_options("fast"),
         )
     fallback = _fallback_fact_answer(prompt, fallback_context or context)
     if fallback and (_is_quantitative_prompt(prompt) or not _has_body_lines(reply)):
@@ -4512,6 +4523,7 @@ def _non_cluster_reply(prompt: str, *, history_lines: list[str], mode: str) -> s
         system_override=system,
         model=model,
         timeout=_mode_ollama_timeout_sec(mode),
+        options=_mode_ollama_options(mode),
     )
     reply = re.sub(r"\bconfidence\s*:\s*(high|medium|low)\b\.?\s*", "", reply, flags=re.IGNORECASE).strip()
     return _ensure_scores(reply)
@@ -4856,6 +4868,7 @@ def _ollama_call(
     system_override: str | None = None,
     model: str | None = None,
     timeout: float | None = None,
+    options: dict[str, Any] | None = None,
 ) -> str:
     system = system_override or (
         "System: You are Atlas, the Titan lab assistant for Atlas/Othrys. "
@@ -4891,6 +4904,8 @@ def _ollama_call(
     model_name = model or MODEL
     request_timeout = timeout if timeout is not None else OLLAMA_TIMEOUT_SEC
     payload = {"model": model_name, "messages": messages, "stream": False}
+    if options:
+        payload["options"] = options
     headers = {"Content-Type": "application/json"}
     if API_KEY:
         headers["x-api-key"] = API_KEY
@@ -4932,18 +4947,20 @@ def ollama_reply(
     use_history: bool = True,
     model: str | None = None,
     timeout: float | None = None,
+    options: dict[str, Any] | None = None,
 ) -> str:
     last_error = None
     for attempt in range(max(1, OLLAMA_RETRIES + 1)):
         try:
-            return _ollama_call(
+            kwargs: dict[str, Any] = {
-                hist_key,
+                "context": context,
-                prompt,
+                "use_history": use_history,
-                context=context,
+                "model": model,
-                use_history=use_history,
+                "timeout": timeout,
-                model=model,
+            }
-                timeout=timeout,
+            if options:
-            )
+                kwargs["options"] = options
+            return _ollama_call(hist_key, prompt, **kwargs)
         except Exception as exc:  # noqa: BLE001
             last_error = exc
             time.sleep(min(4, 2 ** attempt))

services/comms/scripts/tests/test_atlasbot_modes.py

@@ -82,7 +82,7 @@ class AtlasbotModeTests(TestCase):
         ]
         captured: dict[str, object] = {}
 
-        def fake_ollama_call(hist_key, prompt, *, context, use_history=True, system_override=None, model=None, timeout=None):
+        def fake_ollama_call(hist_key, prompt, *, context, use_history=True, system_override=None, model=None, timeout=None, options=None):
             captured["model"] = model
             captured["timeout"] = timeout
             captured["context"] = context
@@ -115,7 +115,7 @@ class AtlasbotModeTests(TestCase):
         ]
         seen: list[tuple[str, float]] = []
 
-        def fake_ollama_call(hist_key, prompt, *, context, use_history=True, system_override=None, model=None, timeout=None):
+        def fake_ollama_call(hist_key, prompt, *, context, use_history=True, system_override=None, model=None, timeout=None, options=None):
             seen.append((str(model), float(timeout or 0)))
             return "Atlas has a clear standout because the worker spread is healthy. Confidence: high"