fix: make planner schema copilot-compatible and silence usage warning

app/core/deep_agent.py

@@ -5,7 +5,6 @@ from __future__ import annotations
 import asyncio
 import json
 import logging
-import operator
 from collections.abc import AsyncGenerator, Awaitable, Callable
 from typing import Any, Literal, TypedDict
 
@@ -116,12 +115,12 @@ WORKER_CONFIG: dict[WorkerName, dict[str, Any]] = {
 _HOME_ORCHESTRATOR_SYSTEM = (
     "You are an orchestrator. Plan which workers should be invoked for the user request. "
     "Workers: task_agent, project_agent, note_agent, timeline_agent. "
-    "Return only the workers needed."
+    "Return JSON only with keys: tasks, floating_domain, memory_updates."
 )
 
 _FLOATING_ORCHESTRATOR_SYSTEM = (
     "You are an orchestrator for floating context. Pick focused workers and set floating_domain "
-    "as one of: tasks, projects, notes, timelines."
+    "as one of: tasks, projects, notes, timelines. Return JSON only with keys: tasks, floating_domain, memory_updates."
 )
 
 _HOME_SYNTH_SYSTEM = (
@@ -178,6 +177,78 @@ def _fallback_plan(message: str, floating: bool) -> WorkerPlan:
     return WorkerPlan(tasks=tasks, floating_domain=domain)
 
 
+def _extract_json_object(text: str) -> dict[str, Any] | None:
+    """Best-effort extraction of the first JSON object from model output."""
+    stripped = text.strip()
+    if not stripped:
+        return None
+
+    # Common case: model returns raw JSON object.
+    try:
+        payload = json.loads(stripped)
+        if isinstance(payload, dict):
+            return payload
+    except json.JSONDecodeError:
+        pass
+
+    # Fenced JSON block fallback.
+    if "```" in stripped:
+        parts = stripped.split("```")
+        for part in parts:
+            candidate = part.strip()
+            if candidate.startswith("json"):
+                candidate = candidate[4:].strip()
+            try:
+                payload = json.loads(candidate)
+                if isinstance(payload, dict):
+                    return payload
+            except json.JSONDecodeError:
+                continue
+
+    return None
+
+
+def _coerce_plan(payload: dict[str, Any], message: str, floating: bool) -> WorkerPlan:
+    """Normalize loose model JSON into a validated WorkerPlan."""
+    tasks_raw = payload.get("tasks")
+    tasks: list[WorkerTask] = []
+
+    if isinstance(tasks_raw, list):
+        for item in tasks_raw:
+            if not isinstance(item, dict):
+                continue
+            worker = item.get("worker")
+            instruction = item.get("instruction")
+            if isinstance(worker, str) and worker in WORKER_CONFIG and isinstance(instruction, str):
+                tasks.append(WorkerTask(worker=worker, instruction=instruction))
+
+    if not tasks:
+        return _fallback_plan(message, floating)
+
+    domain = payload.get("floating_domain")
+    floating_domain: FloatingDomain | None = None
+    if isinstance(domain, str) and domain in {"tasks", "projects", "notes", "timelines"}:
+        floating_domain = domain  # type: ignore[assignment]
+    elif floating:
+        floating_domain = WORKER_CONFIG[tasks[0].worker]["floating_domain"]
+
+    memory_updates: list[MemoryUpdate] = []
+    updates_raw = payload.get("memory_updates")
+    if isinstance(updates_raw, list):
+        for item in updates_raw:
+            if isinstance(item, dict):
+                key = item.get("key")
+                value = item.get("value")
+                if isinstance(key, str) and isinstance(value, str) and key and value:
+                    memory_updates.append(MemoryUpdate(key=key, value=value))
+
+    return WorkerPlan(
+        tasks=tasks,
+        floating_domain=floating_domain,
+        memory_updates=memory_updates,
+    )
+
+
 async def _plan_with_llm(message: str, context: dict[str, Any], floating: bool) -> WorkerPlan:
     llm = get_llm()
     system = _FLOATING_ORCHESTRATOR_SYSTEM if floating else _HOME_ORCHESTRATOR_SYSTEM
@@ -189,18 +260,28 @@ async def _plan_with_llm(message: str, context: dict[str, Any], floating: bool)
     }
     messages = [
         SystemMessage(content=system),
-        HumanMessage(content=json.dumps(prompt_payload, ensure_ascii=True)),
+        HumanMessage(
+            content=(
+                "Create a valid JSON object with this exact structure:\n"
+                '{"tasks":[{"worker":"task_agent|project_agent|note_agent|timeline_agent","instruction":"..."}],'
+                '"floating_domain":"tasks|projects|notes|timelines|null","memory_updates":[{"key":"...","value":"..."}]}\n\n'
+                "Rules:\n"
+                "- tasks must include at least one entry when possible\n"
+                "- use floating_domain only when relevant\n"
+                "- output JSON only (no markdown, no prose)\n\n"
+                f"Input:\n{json.dumps(prompt_payload, ensure_ascii=True)}"
+            )
+        ),
     ]
 
     try:
-        structured_llm = llm.with_structured_output(WorkerPlan)
-        plan = await structured_llm.ainvoke(messages)
-        if isinstance(plan, WorkerPlan):
-            if not plan.tasks:
-                return _fallback_plan(message, floating)
-            return plan
+        response = await llm.ainvoke(messages)
+        payload = _extract_json_object(_as_text(response.content))
+        if payload is None:
+            raise ValueError("planner returned non-JSON output")
+        return _coerce_plan(payload, message, floating)
     except Exception as exc:
-        logger.warning("deep_agent: structured planner failed, using fallback: %s", exc)
+        logger.warning("deep_agent: planner failed, using fallback: %s", exc)
 
     return _fallback_plan(message, floating)
 

app/core/llm.py

@@ -18,6 +18,7 @@ Switch providers by changing **LLM_MODEL** / **LLM_ROUTER_MODEL** in ``.env``
 from __future__ import annotations
 
 import os
+import warnings
 
 from openai import AsyncOpenAI
 import litellm
@@ -32,6 +33,14 @@ from app.config.settings import settings
 # Drop them silently instead of raising UnsupportedParamsError.
 litellm.drop_params = True
 
+# Some provider responses include a plain dict in the `usage` field where a
+# richer Pydantic model is expected. This warning is noisy but non-fatal.
+warnings.filterwarnings(
+    "ignore",
+    message=r"PydanticSerializationUnexpectedValue\(Expected `ResponseAPIUsage`",
+    category=UserWarning,
+)
+
 
 def _api_key_for_model(model: str) -> str | None:
     """Return the most appropriate API key for the given LiteLLM model string."""