feat: make agent memory context limit configurable

backend/alembic/versions/v1_12_0_f066_configurable_memory_context.py

@@ -0,0 +1,65 @@
+"""Add configurable memory context limit to agents.
+
+Background:
+    The memory.md context limit was previously hardcoded to 2,000 characters.
+
+Scope:
+    Add a per-agent memory_context_max_chars column with a default value of 2,000.
+
+Idempotent:
+    The column is added only when it does not already exist.
+
+Revision ID: f066_configurable_memory_context
+Revises: f065_feishu_group_target
+Create Date: 2026-09-02
+"""
+
+from collections.abc import Sequence
+
+from alembic import op
+import sqlalchemy as sa
+
+
+revision: str = "f066_configurable_memory_context"
+down_revision: str | Sequence[str] | None = "f065_feishu_group_target"
+branch_labels: str | Sequence[str] | None = None
+depends_on: str | Sequence[str] | None = None
+
+
+def upgrade() -> None:
+    bind = op.get_bind()
+    inspector = sa.inspect(bind)
+
+    columns = {
+        column["name"]
+        for column in inspector.get_columns("agents")
+    }
+
+    if "memory_context_max_chars" not in columns:
+        op.add_column(
+            "agents",
+            sa.Column(
+                "memory_context_max_chars",
+                sa.Integer(),
+                nullable=False,
+                server_default=sa.text("2000"),
+            ),
+        )
+        op.alter_column(
+            "agents",
+            "memory_context_max_chars",
+            server_default=None,
+        )
+
+
+def downgrade() -> None:
+    bind = op.get_bind()
+    inspector = sa.inspect(bind)
+
+    columns = {
+        column["name"]
+        for column in inspector.get_columns("agents")
+    }
+
+    if "memory_context_max_chars" in columns:
+        op.drop_column("agents", "memory_context_max_chars")

backend/app/models/agent.py

@@ -96,6 +96,11 @@ class Agent(Base):
     cache_creation_tokens_month: Mapped[int] = mapped_column(Integer, default=0)
     cache_creation_tokens_total: Mapped[int] = mapped_column(Integer, default=0)
     context_window_size: Mapped[int] = mapped_column(Integer, default=100)
+    memory_context_max_chars: Mapped[int] = mapped_column(
+        Integer,
+        default=2000,
+        nullable=False,
+    )
     # Historical field name: this is the maximum number of model-decision turns
     # allowed for one Agent Run, not the number of tools executed.
     max_tool_rounds: Mapped[int] = mapped_column(Integer, default=50)

backend/app/schemas/schemas.py

@@ -297,6 +297,7 @@ class AgentOut(BaseModel):
     created_at: datetime
     last_active_at: datetime | None = None
     deleted_at: datetime | None = None
+    memory_context_max_chars: int = 2000
 
     model_config = {"from_attributes": True}
 
@@ -322,6 +323,11 @@ class AgentUpdate(BaseModel):
     heartbeat_active_hours: str | None = None
     timezone: str | None = None
     expires_at: datetime | None = None  # Admin only — extend agent expiry
+    memory_context_max_chars: int | None = Field(
+        default=None,
+        ge=0,
+        le=100000,
+    )
 
     @field_validator("timezone")
     @classmethod

backend/app/services/agent_context.py

@@ -437,6 +437,7 @@ async def build_agent_context(
     current_user_name: str | None = None,
     *,
     allowed_tool_names: Collection[str] | None = None,
+    memory_context_max_chars: int = 2000,
 ) -> tuple[str, str]:
     """Build Base Prompt V1 plus bounded, explicitly low-trust context data."""
     # `role_description` remains product metadata and is intentionally ignored by
@@ -463,12 +464,12 @@ async def build_agent_context(
 
     memory = await _read_file_safe(
         normalize_storage_key(f"{agent_id}/memory/memory.md"),
-        2000,
+        memory_context_max_chars,
     )
     if not memory:
         memory = await _read_file_safe(
             normalize_storage_key(f"{agent_id}/memory.md"),
-            2000,
+            memory_context_max_chars,
         )
     if memory.startswith("# "):
         memory = "\n".join(memory.split("\n")[1:]).strip()

backend/app/services/llm/caller.py

@@ -225,26 +225,44 @@ def _usage_from_response_or_estimate(response, api_messages: list[LLMMessage]) -
 # Helper Functions
 # ═══════════════════════════════════════════════════════════════════════════════
 
-async def _get_agent_config(agent_id) -> tuple[int, str | None]:
-    """Get agent config: max_tool_rounds and token limit status."""
+async def _get_agent_config(agent_id) -> tuple[int, int, str | None]:
+    """Get agent config: max_tool_rounds, memory context limit and token limit status."""
     if not agent_id:
-        return 50, None
+        return 50, 2000, None
 
     try:
         from app.models.agent import Agent as AgentModel
+
         async with async_session() as _db:
             _ar = await _db.execute(select(AgentModel).where(AgentModel.id == agent_id))
             _agent = _ar.scalar_one_or_none()
             if _agent:
                 max_rounds = _agent.max_tool_rounds or 50
+                memory_context_max_chars = (
+                    _agent.memory_context_max_chars
+                    if _agent.memory_context_max_chars is not None
+                    else 2000
+                )
                 if _agent.max_tokens_per_day and _agent.tokens_used_today >= _agent.max_tokens_per_day:
-                    return max_rounds, f"⚠️ Daily token usage has reached the limit ({_agent.tokens_used_today:,}/{_agent.max_tokens_per_day:,}). Please try again tomorrow or ask admin to increase the limit."
+                    return (
+                        max_rounds,
+                        memory_context_max_chars,
+                        f"⚠ Daily token usage has reached the limit "
+                        f"({_agent.tokens_used_today:,}/{_agent.max_tokens_per_day:,}). "
+                        "Please try again tomorrow or ask admin to increase the limit.",
+                    )
                 if _agent.max_tokens_per_month and _agent.tokens_used_month >= _agent.max_tokens_per_month:
-                    return max_rounds, f"⚠️ Monthly token usage has reached the limit ({_agent.tokens_used_month:,}/{_agent.max_tokens_per_month:,}). Please ask admin to increase the limit."
-                return max_rounds, None
+                    return (
+                        max_rounds,
+                        memory_context_max_chars,
+                        f"⚠ Monthly token usage has reached the limit "
+                        f"({_agent.tokens_used_month:,}/{_agent.max_tokens_per_month:,}). "
+                        "Please ask admin to increase the limit.",
+                    )
+                return max_rounds, memory_context_max_chars, None
     except Exception:
         pass
-    return 50, None
+    return 50, 2000, None
 
 
 async def _get_user_name(user_id) -> str | None:
@@ -495,7 +513,7 @@ async def call_llm(
 ) -> str:
     """Call LLM via unified client with function-calling tool loop."""
     # Get agent config for tool rounds
-    _max_tool_rounds, _token_limit_msg = await _get_agent_config(agent_id)
+    _max_tool_rounds, _memory_context_max_chars, _token_limit_msg = await _get_agent_config(agent_id)
     if _token_limit_msg:
         return _token_limit_msg
     if max_tool_rounds_override and max_tool_rounds_override < _max_tool_rounds:
@@ -549,6 +567,7 @@ async def _default_on_tool_call(data: dict):
         "",
         current_user_name=_user_name,
         allowed_tool_names=allowed_tool_names,
+        memory_context_max_chars=_memory_context_max_chars,
     )
     if system_prompt_suffix:
         dynamic_prompt = f"{dynamic_prompt}\n\n{system_prompt_suffix.strip()}"
@@ -647,7 +666,7 @@ async def _completion_failure(code: str, message: str) -> str:
             if agent_id and _unsaved_usage.total_tokens > 0:
                 await record_token_usage(agent_id, _unsaved_usage)
                 _unsaved_usage = TokenUsage()
-                _, _token_limit_msg = await _get_agent_config(agent_id)
+                _, _, _token_limit_msg = await _get_agent_config(agent_id)
                 if _token_limit_msg:
                     logger.warning(f"[LLM] Token limit exceeded mid-loop: {_token_limit_msg}")
                     await client.close()

backend/tests/test_agent_context.py

@@ -67,6 +67,45 @@ async def test_base_prompt_starts_with_name_and_soul_and_never_injects_self_role
     assert "call `finish`" not in static
     assert "return the exact final answer as normal Assistant content" in static
 
+@pytest.mark.asyncio
+async def test_memory_context_uses_configured_character_limit():
+    from app.services.agent_context import build_agent_context
+
+    agent_id = uuid.uuid4()
+    observed_limits = []
+
+    async def fake_read_file(key, max_chars=3000):
+        if key.endswith("/memory/memory.md"):
+            observed_limits.append(max_chars)
+            return "memory"
+        return ""
+
+    with (
+        patch("app.services.agent_context._read_file_safe", side_effect=fake_read_file),
+        patch(
+            "app.services.agent_context._load_skills_index",
+            new_callable=AsyncMock,
+            return_value="",
+        ),
+        patch(
+            "app.services.agent_context._load_relationships_from_db",
+            new_callable=AsyncMock,
+            return_value="",
+        ),
+        patch(
+            "app.services.timezone_utils.get_agent_timezone",
+            new_callable=AsyncMock,
+            return_value="UTC",
+        ),
+    ):
+        await build_agent_context(
+            agent_id,
+            "TestAgent",
+            allowed_tool_names={"wait"},
+            memory_context_max_chars=500,
+        )
+
+    assert observed_limits == [500]
 
 @pytest.mark.asyncio
 async def test_focus_mechanism_is_constant_but_tool_policy_follows_effective_tools():
@@ -228,4 +267,4 @@ async def test_experience_policy_is_short_and_only_names_enabled_operations():
     assert "read_experience" in read_only
     assert "propose_experience_draft" not in read_only
     assert "现有标签" not in read_only
-    assert "propose_experience_draft" in with_draft
+    assert "propose_experience_draft" in with_draft

backend/tests/test_finish_protocol.py

@@ -354,7 +354,7 @@ async def test_call_llm_returns_natural_assistant_stop_without_finish(monkeypatc
         _plain_response("Final answer."),
     ])
 
-    monkeypatch.setattr(caller, "_get_agent_config", lambda _agent_id: _async_return((3, None)))
+    monkeypatch.setattr(caller, "_get_agent_config", lambda _agent_id: _async_return((3, 2000, None)))
     monkeypatch.setattr(caller, "_get_user_name", lambda _user_id: _async_return("Ray"))
     monkeypatch.setattr(
         "app.services.agent_context.build_agent_context",
@@ -408,7 +408,7 @@ async def test_call_llm_routes_embedded_thinking_before_final_content(monkeypatc
     monkeypatch.setattr(
         caller,
         "_get_agent_config",
-        lambda _agent_id: _async_return((3, None)),
+        lambda _agent_id: _async_return((3, 2000, None)),
     )
     monkeypatch.setattr(
         caller,
@@ -471,7 +471,7 @@ async def test_call_llm_executes_exact_textual_tool_call_before_finishing(
     monkeypatch.setattr(
         caller,
         "_get_agent_config",
-        lambda _agent_id: _async_return((3, None)),
+        lambda _agent_id: _async_return((3, 2000, None)),
     )
     monkeypatch.setattr(
         caller,
@@ -553,7 +553,7 @@ async def test_call_llm_repairs_textual_result_instead_of_publishing_it(monkeypa
     monkeypatch.setattr(
         caller,
         "_get_agent_config",
-        lambda _agent_id: _async_return((3, None)),
+        lambda _agent_id: _async_return((3, 2000, None)),
     )
     monkeypatch.setattr(
         caller,
@@ -622,7 +622,7 @@ async def test_legacy_tool_loop_calls_saved_model_without_verified_tool_calling(
     model.supports_tool_calling = supports_tool_calling
     fake_client = FakeStreamClient([_finish_response("Final answer.")])
 
-    monkeypatch.setattr(caller, "_get_agent_config", lambda _agent_id: _async_return((50, None)))
+    monkeypatch.setattr(caller, "_get_agent_config", lambda _agent_id: _async_return((50, 2000, None)))
     monkeypatch.setattr(caller, "_get_user_name", lambda _user_id: _async_return("Ray"))
     monkeypatch.setattr(
         "app.services.agent_context.build_agent_context",
@@ -662,7 +662,7 @@ async def test_call_llm_truncated_output_repair_is_bounded(monkeypatch):
         _plain_response("Second partial response.", finish_reason="length"),
     ])
 
-    monkeypatch.setattr(caller, "_get_agent_config", lambda _agent_id: _async_return((50, None)))
+    monkeypatch.setattr(caller, "_get_agent_config", lambda _agent_id: _async_return((50, 2000, None)))
     monkeypatch.setattr(caller, "_get_user_name", lambda _user_id: _async_return("Ray"))
     monkeypatch.setattr(
         "app.services.agent_context.build_agent_context",
@@ -716,7 +716,7 @@ async def test_invalid_finish_does_not_stop_and_is_returned_as_tool_error(monkey
         _finish_response("Recovered final."),
     ])
 
-    monkeypatch.setattr(caller, "_get_agent_config", lambda _agent_id: _async_return((3, None)))
+    monkeypatch.setattr(caller, "_get_agent_config", lambda _agent_id: _async_return((3, 2000, None)))
     monkeypatch.setattr(caller, "_get_user_name", lambda _user_id: _async_return("Ray"))
     monkeypatch.setattr(
         "app.services.agent_context.build_agent_context",
@@ -766,7 +766,7 @@ async def test_repeated_invalid_finish_is_bounded_by_protocol_code(monkeypatch):
         _finish_response_with_arguments("{}"),
         _finish_response_with_arguments("{}"),
     ])
-    monkeypatch.setattr(caller, "_get_agent_config", lambda _agent_id: _async_return((50, None)))
+    monkeypatch.setattr(caller, "_get_agent_config", lambda _agent_id: _async_return((50, 2000, None)))
     monkeypatch.setattr(caller, "_get_user_name", lambda _user_id: _async_return("Ray"))
     monkeypatch.setattr(
         "app.services.agent_context.build_agent_context",
@@ -815,7 +815,7 @@ async def test_repeated_invalid_tool_json_is_bounded_by_protocol_code(monkeypatc
         ],
     )
     fake_client = FakeStreamClient([invalid] * 11)
-    monkeypatch.setattr(caller, "_get_agent_config", lambda _agent_id: _async_return((50, None)))
+    monkeypatch.setattr(caller, "_get_agent_config", lambda _agent_id: _async_return((50, 2000, None)))
     monkeypatch.setattr(caller, "_get_user_name", lambda _user_id: _async_return("Ray"))
     monkeypatch.setattr(
         "app.services.agent_context.build_agent_context",
@@ -867,7 +867,7 @@ async def test_invalid_write_file_json_gets_ten_bounded_repairs(monkeypatch):
         ],
     )
     fake_client = FakeStreamClient([invalid] * 11)
-    monkeypatch.setattr(caller, "_get_agent_config", lambda _agent_id: _async_return((50, None)))
+    monkeypatch.setattr(caller, "_get_agent_config", lambda _agent_id: _async_return((50, 2000, None)))
     monkeypatch.setattr(caller, "_get_user_name", lambda _user_id: _async_return("Ray"))
     monkeypatch.setattr(
         "app.services.agent_context.build_agent_context",
@@ -910,7 +910,7 @@ async def test_skip_tools_uses_natural_completion_without_any_tools(monkeypatch)
 
     fake_client = FakeStreamClient([_plain_response("Onboarding done.")])
 
-    monkeypatch.setattr(caller, "_get_agent_config", lambda _agent_id: _async_return((1, None)))
+    monkeypatch.setattr(caller, "_get_agent_config", lambda _agent_id: _async_return((1, 2000, None)))
     monkeypatch.setattr(caller, "_get_user_name", lambda _user_id: _async_return("Ray"))
     monkeypatch.setattr(
         "app.services.agent_context.build_agent_context",
@@ -997,8 +997,8 @@ async def mock_get_agent_config(agent_id):
         nonlocal configs_called
         configs_called += 1
         if configs_called > 1:
-            return 50, "⚠️ Daily token usage limit exceeded"
-        return 50, None
+            return 50, 2000, "⚠️ Daily token usage limit exceeded"
+        return 50, 2000, None
 
     monkeypatch.setattr(caller, "_get_agent_config", mock_get_agent_config)
     monkeypatch.setattr(caller, "_get_user_name", lambda _user_id: _async_return("Ray"))
@@ -1042,4 +1042,4 @@ async def _async_return(value):
 
 
 async def _async_append(items, value):
-    items.append(value)
+    items.append(value)