mirror of
https://github.com/openswarm-ai/openswarm.git
synced 2026-09-26 19:44:51 +02:00
[aidan] ui/ux: hide noisy memory/mode from chat title, fix token bug
Drop the inline 'Memory N% full' pill from AgentChat and the mode label from AgentCard so the chat header stays quiet until tools are connected. Backend now emits agent:context_update after compact and clear so the session token counters reflect the trimmed history instead of stale pre-compact totals, with a new _estimate_post_compact_input helper and matching invariants in test_v2_invariants.
This commit is contained in:
@@ -53,6 +53,7 @@ from backend.apps.agents.manager.prompt.tool_catalog import (
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from backend.apps.agents.core.aux_llm import _safe_resp_text, clean_short_label, aux_max_tokens_for
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from backend.apps.agents.manager.session.history_compaction import (
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_build_history_prefix,
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_estimate_post_compact_input,
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_get_branch_messages,
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_truncate_large_tool_result,
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)
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@@ -377,6 +378,35 @@ class AgentManager:
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session.compacted_through_msg_id = last_id
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return True
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async def _emit_context_update(
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self,
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session_id: str,
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session: AgentSession,
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*,
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input_tokens: int | None = None,
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output_tokens: int | None = None,
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cache_read_tokens: int = 0,
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cache_read_pct: float = 0.0,
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) -> None:
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if input_tokens is None:
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input_tokens = int(session.tokens.get("input", 0) or 0)
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if output_tokens is None:
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output_tokens = int(session.tokens.get("output", 0) or 0)
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session.tokens["input"] = input_tokens
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session.tokens["output"] = output_tokens
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ctx_window = max(1, getattr(session, "context_window", 0) or 200_000)
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await ws_manager.send_to_session(session_id, "agent:context_update", {
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"session_id": session_id,
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"input_tokens": input_tokens,
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"output_tokens": output_tokens,
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"cache_read_tokens": cache_read_tokens,
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"cache_read_pct": cache_read_pct,
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"ctx_used_pct": round(input_tokens / ctx_window, 4) if input_tokens else 0.0,
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"context_window": ctx_window,
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"framework_overhead_tokens": session.framework_overhead_tokens,
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"active_mcps": list(session.active_mcps),
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})
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def _build_prompt_content(self, prompt: str, images: list | None = None, context_paths: list | None = None, forced_tools: list[str] | None = None, attached_skills: list | None = None, api_type: str = "anthropic", model: str = ""):
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return _build_prompt_content(prompt, images, context_paths, forced_tools, attached_skills, api_type, model)
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@@ -1813,11 +1843,18 @@ class AgentManager:
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# zero latency on the user's turn.
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try:
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if self._maybe_compact(session):
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new_input = _estimate_post_compact_input(session)
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await ws_manager.send_to_session(session_id, "agent:context_status", {
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"session_id": session_id,
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"reason": "compacted",
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"compacted_through_msg_id": session.compacted_through_msg_id,
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})
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await self._emit_context_update(
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session_id,
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session,
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input_tokens=new_input,
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output_tokens=session.tokens.get("output", 0),
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)
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except Exception:
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logger.exception("compaction failed; proceeding without it")
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@@ -2,6 +2,7 @@ from backend.config.Apps import SubApp
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from backend.apps.agents.agent_manager import agent_manager
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from backend.apps.agents.core.ws_manager import ws_manager
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from backend.apps.agents.core.models import AgentConfig, ApprovalResponse
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from backend.apps.agents.manager.session.history_compaction import _estimate_post_compact_input
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from contextlib import asynccontextmanager
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from fastapi import WebSocket, WebSocketDisconnect, HTTPException
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from fastapi.responses import JSONResponse
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@@ -304,6 +305,12 @@ async def compact_session(session_id: str):
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"reason": "compacted",
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"compacted_through_msg_id": session.compacted_through_msg_id,
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})
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await agent_manager._emit_context_update(
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session_id,
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session,
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input_tokens=_estimate_post_compact_input(session),
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output_tokens=session.tokens.get("output", 0),
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)
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except Exception:
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pass
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return {"ok": True, "compacted": fired}
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@@ -329,6 +336,12 @@ async def clear_session(session_id: str):
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"status": session.status,
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"session": session.model_dump(mode="json"),
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})
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await agent_manager._emit_context_update(
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session_id,
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session,
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input_tokens=0,
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output_tokens=0,
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)
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except Exception:
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pass
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return {"ok": True}
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@@ -817,4 +830,3 @@ async def subscriptions_disconnect(body: dict):
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return {"ok": False, "error": "Connection not found"}
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except Exception as e:
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raise HTTPException(status_code=500, detail=str(e))
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@@ -71,6 +71,39 @@ def _build_history_prefix(messages, cutoff_msg_id: str | None = None) -> str:
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return "<prior_conversation>\n" + "\n".join(lines) + "\n</prior_conversation>"
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def _estimate_post_compact_input(session) -> int:
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"""Return a conservative token estimate after compaction trims history."""
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try:
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messages = _get_branch_messages(session)
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cutoff_msg_id = getattr(session, "compacted_through_msg_id", None)
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if cutoff_msg_id:
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skip_idx = next(
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(i for i, m in enumerate(messages) if m.id == cutoff_msg_id),
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-1,
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)
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if skip_idx >= 0:
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messages = messages[skip_idx + 1:]
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surviving_chars = 0
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for message in messages:
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if getattr(message, "hidden", False):
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continue
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content = getattr(message, "content", "")
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if isinstance(content, str):
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serialized = content
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else:
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try:
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serialized = json.dumps(content, ensure_ascii=False)
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except Exception:
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serialized = str(content)
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surviving_chars += len(serialized)
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framework_overhead = int(getattr(session, "framework_overhead_tokens", 0) or 0)
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summary_overhead = 200 if cutoff_msg_id else 0
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return max(0, framework_overhead + summary_overhead + (surviving_chars // 4))
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except Exception:
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logger.debug("post-compact token estimate failed", exc_info=True)
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return max(0, int(getattr(session, "framework_overhead_tokens", 0) or 0))
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def _truncate_large_tool_result(content: object, session_id: str, msg_id: str, max_bytes: int = 50_000) -> tuple[object, str | None]:
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"""Spill a large tool_result body to disk, return a truncated
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inline replacement plus the on-disk path (or None if untouched).
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@@ -784,6 +784,66 @@ def test_compact_threshold_default():
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assert s.context_window == 200_000
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def test_post_compact_estimate_excludes_compacted_messages():
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from backend.apps.agents.core.models import AgentSession, Message
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from backend.apps.agents.manager.session.history_compaction import (
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_estimate_post_compact_input,
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)
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messages = [
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Message(id=f"m{i}", role="user", content=("old" * 1000 if i < 6 else "keep"))
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for i in range(8)
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]
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s = AgentSession(id="x", name="t", model="sonnet", mode="agent")
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s.messages = messages
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s.compacted_through_msg_id = "m5"
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s.framework_overhead_tokens = 100
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assert _estimate_post_compact_input(s) == 100 + 200 + (len("keepkeep") // 4)
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@pytest.mark.asyncio
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async def test_context_update_emitter_refreshes_session_tokens(monkeypatch):
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import backend.apps.agents.agent_manager as agent_manager_module
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from backend.apps.agents.agent_manager import AgentManager
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from backend.apps.agents.core.models import AgentSession
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sent = []
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async def fake_send_to_session(session_id, event, payload):
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sent.append((session_id, event, payload))
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monkeypatch.setattr(
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agent_manager_module.ws_manager,
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"send_to_session",
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fake_send_to_session,
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)
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s = AgentSession(id="x", name="t", model="sonnet", mode="agent")
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s.context_window = 1_000
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s.tokens = {"input": 900, "output": 7}
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s.framework_overhead_tokens = 42
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s.active_mcps = ["github"]
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await AgentManager()._emit_context_update("x", s, input_tokens=250)
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assert s.tokens == {"input": 250, "output": 7}
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assert sent == [(
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"x",
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"agent:context_update",
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{
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"session_id": "x",
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"input_tokens": 250,
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"output_tokens": 7,
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"cache_read_tokens": 0,
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"cache_read_pct": 0.0,
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"ctx_used_pct": 0.25,
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"context_window": 1_000,
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"framework_overhead_tokens": 42,
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"active_mcps": ["github"],
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},
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)]
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# ===========================================================================
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# Group L, Sentence-case display (the parseMcpToolName fix)
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# ===========================================================================
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@@ -1041,42 +1041,17 @@ const AgentChat: React.FC<AgentChatProps> = ({ sessionId: sessionIdProp, onClose
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);
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})()}
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{(() => {
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const liveWindow = session.context_window || contextEstimate.limit || 200_000;
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const liveInput = session.tokens?.input ?? 0;
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const pct = liveInput > 0
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? Math.min(1, liveInput / Math.max(1, liveWindow))
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: (contextEstimate.used / Math.max(1, liveWindow));
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const mcpCount = session.active_mcps?.length ?? 0;
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// Quiet until it matters: hide the memory meter until the chat is filling up,
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// and hide the tool count unless tools are actually connected.
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const showMemory = pct >= 0.60;
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const showTools = mcpCount > 0;
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if (!showMemory && !showTools) return null;
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const pctTxt = `${Math.round(pct * 100)}%`;
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const memColor = pct >= 0.85 ? '#ef4444' : '#f59e0b';
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const tip = [
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showMemory ? `Memory ${pctTxt} full. As the chat fills up, the oldest messages start dropping out.` : null,
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showTools ? `${mcpCount} tool${mcpCount === 1 ? '' : 's'} connected.` : null,
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].filter(Boolean).join('\n');
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if (mcpCount === 0) return null;
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return (
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<Typography
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variant="caption"
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sx={{ display: 'inline-flex', alignItems: 'center', gap: 0.5, fontVariantNumeric: 'tabular-nums' }}
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title={tip}
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title={`${mcpCount} tool${mcpCount === 1 ? '' : 's'} connected.`}
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>
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{showMemory && (
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<Box component="span" sx={{ color: memColor, fontWeight: 500 }}>
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Memory {pctTxt} full
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</Box>
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)}
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{showMemory && showTools && (
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<Box component="span" sx={{ color: c.text.ghost }}>·</Box>
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)}
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{showTools && (
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<Box component="span" sx={{ color: c.text.tertiary }}>
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{mcpCount} tool{mcpCount === 1 ? '' : 's'}
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</Box>
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)}
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<Box component="span" sx={{ color: c.text.tertiary }}>
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{mcpCount} tool{mcpCount === 1 ? '' : 's'}
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</Box>
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</Typography>
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);
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})()}
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@@ -818,9 +818,6 @@ const AgentCard: React.FC<Props> = ({
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<Typography variant="caption" sx={{ color: c.text.tertiary }}>
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{friendlyModelLabel}
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</Typography>
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<Typography variant="caption" sx={{ color: c.text.tertiary }}>
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{session.mode}
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</Typography>
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<Typography variant="caption" sx={{ color: c.text.tertiary }}>
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<ElapsedTimer messages={session.messages} status={session.status} />
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</Typography>
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