self-tasking engine: persistent queue, idle-impulse + follow-up generators, approval mode

fjerkroa_bot/openai_responder.py

@@ -58,6 +58,31 @@ CONSOLIDATION_RESPONSE_FORMAT = {
     "type": "json_schema",
     "json_schema": {"name": "consolidation", "strict": True, "schema": CONSOLIDATION_SCHEMA},
 }
+# Follow-up task proposal (SPEC-005 TSK-08): one task or null
+TASKGEN_SCHEMA = {
+    "type": "object",
+    "properties": {
+        "task": {
+            "type": ["object", "null"],
+            "properties": {
+                "channel": {"type": ["string", "null"], "description": "Target channel, or null for the main chat channel."},
+                "prompt": {"type": "string", "description": "Instruction the assistant will act on when the task runs."},
+                "due_hours": {"type": "number", "description": "Hours from now until the task should run (0 = now)."},
+            },
+            "required": ["channel", "prompt", "due_hours"],
+            "additionalProperties": False,
+        }
+    },
+    "required": ["task"],
+    "additionalProperties": False,
+}
+TASKGEN_RESPONSE_FORMAT = {"type": "json_schema", "json_schema": {"name": "task_proposal", "strict": True, "schema": TASKGEN_SCHEMA}}
+TASKGEN_SYSTEM = (
+    "You plan the self-initiated actions of a Discord assistant. Given recent conversation summaries, propose AT MOST ONE follow-up"
+    " worth doing on the assistant's own initiative (ask how something announced went, revisit an open question, congratulate on an"
+    " event). Only propose something genuinely worthwhile — when in doubt, return a null task."
+)
+
 # Reply/ignore + factual pre-pass (SPEC-010 BEH-01): one cheap call
 CLASSIFIER_SCHEMA = {
     "type": "object",
@@ -381,6 +406,29 @@ class OpenAIResponder(AIResponder, LeonardoAIDrawMixIn):
         logging.info(f"edited {len(buffers)} image(s) on {model} from {len(handles)} input(s)")
         return buffers
 
+    async def propose_task(self) -> Optional[Dict[str, Any]]:
+        """One follow-up proposal from recent episodes on memory-model (TSK-08)."""
+        if "memory-model" not in self.config or self.store is None or not self.ledger.budget_ok():
+            return None
+        channel = self.config.get("chat-channel", "chat")
+        episodes = await asyncio.to_thread(self.store.recent_episodes, channel, 5)
+        if not episodes:
+            return None
+        episode_lines = "\n".join(f"- {episode}" for episode in episodes)
+        messages = [
+            {"role": "system", "content": TASKGEN_SYSTEM},
+            {"role": "user", "content": f"Recent conversation summaries in #{channel}:\n{episode_lines}"},
+        ]
+        try:
+            result = await openai_chat(
+                self.client, model=self.config["memory-model"], messages=messages, response_format=TASKGEN_RESPONSE_FORMAT
+            )
+            self._record_usage(result)
+            return json.loads(result.choices[0].message.content)
+        except Exception as err:
+            logging.warning(f"task proposal failed: {repr(err)}")
+        return None
+
     async def classify(self, message: Any, history_tail: List[Dict[str, Any]]) -> Optional[Dict[str, Any]]:
         """~100-token reply/factual/emoji verdict on classifier-model (BEH-01/03)."""
         if "classifier-model" not in self.config or not self.ledger.budget_ok():