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Merged
yaojin3616 merged 3 commits into from
Jun 11, 2026
Merged

feat: comprehensive updates to sandbox, agents, and UI #667

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a24b950
feat: comprehensive updates to sandbox, agents, and UI
yaojin3616 Jun 10, 2026
9660175
Merge remote-tracking branch 'origin/main' into feat/cumulative-updates
yaojin3616 Jun 10, 2026
ac86b66
Fix #636: optimize bwrap sandbox process tree cleanup on timeout
yaojin3616 Jun 10, 2026
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6 changes: 3 additions & 3 deletions backend/Dockerfile
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -16,11 +16,11 @@ COPY pyproject.toml ./
ARG CLAWITH_PIP_INDEX_URL
ARG CLAWITH_PIP_TRUSTED_HOST
RUN if [ -n "$CLAWITH_PIP_INDEX_URL" ] && [ -n "$CLAWITH_PIP_TRUSTED_HOST" ]; then \
pip install --no-cache-dir --index-url "$CLAWITH_PIP_INDEX_URL" --trusted-host "$CLAWITH_PIP_TRUSTED_HOST" .; \
pip install --no-cache-dir --index-url "$CLAWITH_PIP_INDEX_URL" --trusted-host "$CLAWITH_PIP_TRUSTED_HOST" . uv; \
elif [ -n "$CLAWITH_PIP_INDEX_URL" ]; then \
pip install --no-cache-dir --index-url "$CLAWITH_PIP_INDEX_URL" .; \
pip install --no-cache-dir --index-url "$CLAWITH_PIP_INDEX_URL" . uv; \
else \
pip install --no-cache-dir .; \
pip install --no-cache-dir . uv; \
fi

# ─── Production ─────────────────────────────────────────
Expand Down
50 changes: 31 additions & 19 deletions backend/alembic/versions/056_add_user_tenant_onboarding.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,25 +19,37 @@


def upgrade() -> None:
op.create_table(
"user_tenant_onboardings",
sa.Column("id", postgresql.UUID(as_uuid=True), primary_key=True, nullable=False),
sa.Column("user_id", postgresql.UUID(as_uuid=True), sa.ForeignKey("users.id", ondelete="CASCADE"), nullable=False),
sa.Column("tenant_id", postgresql.UUID(as_uuid=True), sa.ForeignKey("tenants.id", ondelete="CASCADE"), nullable=False),
sa.Column("status", sa.String(length=32), nullable=False, server_default="in_progress"),
sa.Column("current_step", sa.String(length=32), nullable=False, server_default="assistant"),
sa.Column("entry_mode", sa.String(length=32), nullable=False, server_default="create"),
sa.Column("personal_assistant_agent_id", postgresql.UUID(as_uuid=True), sa.ForeignKey("agents.id", ondelete="SET NULL"), nullable=True),
sa.Column("started_at", sa.DateTime(timezone=True), server_default=sa.func.now(), nullable=False),
sa.Column("completed_at", sa.DateTime(timezone=True), nullable=True),
sa.Column("updated_at", sa.DateTime(timezone=True), server_default=sa.func.now(), nullable=False),
sa.UniqueConstraint("user_id", "tenant_id", name="uq_user_tenant_onboarding"),
)
op.create_index("ix_user_tenant_onboardings_user_id", "user_tenant_onboardings", ["user_id"])
op.create_index("ix_user_tenant_onboardings_tenant_id", "user_tenant_onboardings", ["tenant_id"])
bind = op.get_bind()
inspector = sa.inspect(bind)

if "user_tenant_onboardings" not in inspector.get_table_names():
op.create_table(
"user_tenant_onboardings",
sa.Column("id", postgresql.UUID(as_uuid=True), primary_key=True, nullable=False),
sa.Column("user_id", postgresql.UUID(as_uuid=True), sa.ForeignKey("users.id", ondelete="CASCADE"), nullable=False),
sa.Column("tenant_id", postgresql.UUID(as_uuid=True), sa.ForeignKey("tenants.id", ondelete="CASCADE"), nullable=False),
sa.Column("status", sa.String(length=32), nullable=False, server_default="in_progress"),
sa.Column("current_step", sa.String(length=32), nullable=False, server_default="assistant"),
sa.Column("entry_mode", sa.String(length=32), nullable=False, server_default="create"),
sa.Column("personal_assistant_agent_id", postgresql.UUID(as_uuid=True), sa.ForeignKey("agents.id", ondelete="SET NULL"), nullable=True),
sa.Column("started_at", sa.DateTime(timezone=True), server_default=sa.func.now(), nullable=False),
sa.Column("completed_at", sa.DateTime(timezone=True), nullable=True),
sa.Column("updated_at", sa.DateTime(timezone=True), server_default=sa.func.now(), nullable=False),
sa.UniqueConstraint("user_id", "tenant_id", name="uq_user_tenant_onboarding"),
)

op.create_index("ix_user_tenant_onboardings_user_id", "user_tenant_onboardings", ["user_id"])
op.create_index("ix_user_tenant_onboardings_tenant_id", "user_tenant_onboardings", ["tenant_id"])


def downgrade() -> None:
op.drop_index("ix_user_tenant_onboardings_tenant_id", table_name="user_tenant_onboardings")
op.drop_index("ix_user_tenant_onboardings_user_id", table_name="user_tenant_onboardings")
op.drop_table("user_tenant_onboardings")
bind = op.get_bind()
inspector = sa.inspect(bind)

if "user_tenant_onboardings" in inspector.get_table_names():
indexes = [ix["name"] for ix in inspector.get_indexes("user_tenant_onboardings")]
if "ix_user_tenant_onboardings_tenant_id" in indexes:
op.drop_index("ix_user_tenant_onboardings_tenant_id", table_name="user_tenant_onboardings")
if "ix_user_tenant_onboardings_user_id" in indexes:
op.drop_index("ix_user_tenant_onboardings_user_id", table_name="user_tenant_onboardings")
op.drop_table("user_tenant_onboardings")
4 changes: 2 additions & 2 deletions backend/app/services/agent_tools.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -188,7 +188,6 @@ async def _get_tool_config(agent_id: Optional[uuid.UUID], tool_name: str) -> Opt
base_config = global_config or {}
tenant_config = {}
if tool_source == "builtin":
base_config = {}
tenant_config = await get_tenant_tool_config(db, agent_tenant_id, db_tool_name, config_schema)
# Merge: agent overrides global
merged = {**base_config, **tenant_config, **(agent_config or {})}
Expand All @@ -206,7 +205,7 @@ async def _get_tool_config(agent_id: Optional[uuid.UUID], tool_name: str) -> Opt
tenant_config = {}
if tool.source == "builtin":
tenant_config = await get_tenant_tool_config(db, agent_tenant_id, tool.name, tool.config_schema)
base_config = {} if tool.source == "builtin" else (tool.config or {})
base_config = tool.config or {}
merged = {**base_config, **tenant_config}
else:
merged = {}
Expand Down Expand Up @@ -8047,6 +8046,7 @@ async def _execute_code(
timeout=timeout,
work_dir=str(work_dir),
on_output=on_output,
agent_id=agent_id,
)

# Format result for user display
Expand Down
58 changes: 46 additions & 12 deletions backend/app/services/heartbeat.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -295,6 +295,7 @@ async def _execute_heartbeat(agent_id: uuid.UUID):
plaza_posts_made = 0 # hard limit: 1 new post per heartbeat
plaza_comments_made = 0 # hard limit: 2 comments per heartbeat
_hb_accumulated_usage = None
_hb_unsaved_usage = None

# Token tracking helpers
from app.services.token_tracker import (
Expand All @@ -304,6 +305,7 @@ async def _execute_heartbeat(agent_id: uuid.UUID):
estimate_token_usage_from_chars,
)
_hb_accumulated_usage = TokenUsage()
_hb_unsaved_usage = TokenUsage()

# Convert messages to LLMMessage format
llm_messages = [
Expand All @@ -312,6 +314,21 @@ async def _execute_heartbeat(agent_id: uuid.UUID):
]

for round_i in range(20): # More rounds for search + write + plaza
# Check token usage limit mid-loop (every 3 rounds)
if round_i > 0 and round_i % 3 == 0:
if agent_id and _hb_unsaved_usage.total_tokens > 0:
async with async_session() as db:
await record_token_usage(agent_id, _hb_unsaved_usage)
await db.commit()
_hb_unsaved_usage = TokenUsage()
from app.services.llm.caller import _get_agent_config
_, _token_limit_msg = await _get_agent_config(agent_id)
if _token_limit_msg:
logger.warning(f"[Heartbeat] Token limit exceeded mid-loop: {_token_limit_msg}")
await client.close()
reply = _token_limit_msg
break

try:
response = await client.complete(
messages=llm_messages,
Expand All @@ -330,11 +347,11 @@ async def _execute_heartbeat(agent_id: uuid.UUID):

# Track tokens for this round
usage = extract_token_usage(response.usage)
if usage:
_hb_accumulated_usage.add(usage)
else:
if not usage:
round_chars = sum(len(m.content or '') for m in llm_messages) + len(response.content or '')
_hb_accumulated_usage.add(estimate_token_usage_from_chars(round_chars))
usage = estimate_token_usage_from_chars(round_chars)
_hb_accumulated_usage.add(usage)
_hb_unsaved_usage.add(usage)

if response.tool_calls:
# Add assistant message with tool calls
Expand Down Expand Up @@ -423,8 +440,8 @@ async def _execute_heartbeat(agent_id: uuid.UUID):
# ── Phase 3: Write results back to DB (short transaction) ──
async with async_session() as db:
# Record accumulated heartbeat token usage
if _hb_accumulated_usage and _hb_accumulated_usage.total_tokens > 0:
await record_token_usage(agent_id, _hb_accumulated_usage)
if _hb_unsaved_usage and _hb_unsaved_usage.total_tokens > 0:
await record_token_usage(agent_id, _hb_unsaved_usage)
await db.commit()

# Log activity if not empty
Expand Down Expand Up @@ -687,8 +704,25 @@ async def run_agent_oneshot(

reply = ""
accumulated_usage = TokenUsage()
unsaved_usage = TokenUsage()

for round_i in range(max_rounds):
# Check token usage limit mid-loop (every 3 rounds)
if round_i > 0 and round_i % 3 == 0:
if agent_id and unsaved_usage.total_tokens > 0:
try:
await record_token_usage(agent_id, unsaved_usage)
except Exception as e:
logger.warning(f"[Oneshot] Failed to record token usage mid-loop: {e}")
unsaved_usage = TokenUsage()
from app.services.llm.caller import _get_agent_config
_, _token_limit_msg = await _get_agent_config(agent_id)
if _token_limit_msg:
logger.warning(f"[Oneshot] Token limit exceeded mid-loop: {_token_limit_msg}")
await client.close()
reply = _token_limit_msg
break

try:
response = await client.complete(
messages=llm_messages,
Expand All @@ -713,11 +747,11 @@ async def run_agent_oneshot(

# Track token usage
usage = extract_token_usage(response.usage)
if usage:
accumulated_usage.add(usage)
else:
if not usage:
round_chars = sum(len(m.content or "") for m in llm_messages) + len(response.content or "")
accumulated_usage.add(estimate_token_usage_from_chars(round_chars))
usage = estimate_token_usage_from_chars(round_chars)
accumulated_usage.add(usage)
unsaved_usage.add(usage)

if response.tool_calls:
llm_messages.append(LLMMessage(
Expand Down Expand Up @@ -769,9 +803,9 @@ async def run_agent_oneshot(
await client.close()

# ── Phase 3: Record token usage (best-effort) ───────────────────────────
if accumulated_usage.total_tokens > 0:
if unsaved_usage.total_tokens > 0:
try:
await record_token_usage(agent_id, accumulated_usage)
await record_token_usage(agent_id, unsaved_usage)
except Exception as e:
logger.warning(f"[Oneshot] Failed to record token usage: {e}")

Expand Down
71 changes: 51 additions & 20 deletions backend/app/services/llm/caller.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -93,14 +93,17 @@ def _sanitize_tool_calls_for_context(tool_calls: list[dict]) -> tuple[list[dict]
"Retry the tool call with `function.arguments` as one valid JSON object string."
)

sanitized.append({
new_tc = {
"id": tc.get("id", ""),
"type": tc.get("type") or "function",
"function": {
"name": tool_name,
"arguments": args_str,
},
})
}
if "_gemini_extra" in tc:
new_tc["_gemini_extra"] = tc["_gemini_extra"]
sanitized.append(new_tc)

return sanitized, None

Expand Down Expand Up @@ -497,6 +500,7 @@ async def _default_on_tool_call(data: dict):

max_tokens = get_max_tokens(model.provider, model.model, getattr(model, 'max_output_tokens', None))
_accumulated_usage = TokenUsage()
_unsaved_usage = TokenUsage()

# Tool-calling loop
for round_i in range(_max_tool_rounds):
Expand All @@ -518,6 +522,17 @@ async def _default_on_tool_call(data: dict):
content="🚨 仅剩 2 轮工具调用。请立即使用 upsert_focus_item 保存进度并设置续接触发器。",
))

# Check token usage limit mid-loop (every 3 rounds)
if round_i > 0 and round_i % 3 == 0:
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)
if _token_limit_msg:
logger.warning(f"[LLM] Token limit exceeded mid-loop: {_token_limit_msg}")
await client.close()
return _token_limit_msg

try:
# Use streaming API for real-time responses
async def _buffer_chunk(_text: str) -> None:
Expand All @@ -535,19 +550,21 @@ async def _buffer_chunk(_text: str) -> None:
)
except LLMError as e:
logger.error(f"[LLM] LLMError: provider={getattr(model, 'provider', '?')} model={getattr(model, 'model', '?')} {e}")
if agent_id and _accumulated_usage.total_tokens > 0:
await record_token_usage(agent_id, _accumulated_usage)
if agent_id and _unsaved_usage.total_tokens > 0:
await record_token_usage(agent_id, _unsaved_usage)
await client.close()
return f"[LLM Error] {e}"
except Exception as e:
logger.exception(f"[LLM] Unexpected error: {type(e).__name__}: {str(e)[:300]}")
if agent_id and _accumulated_usage.total_tokens > 0:
await record_token_usage(agent_id, _accumulated_usage)
if agent_id and _unsaved_usage.total_tokens > 0:
await record_token_usage(agent_id, _unsaved_usage)
await client.close()
return f"[LLM call error] {type(e).__name__}: {str(e)[:200]}"

# Track tokens for this round
_accumulated_usage.add(_usage_from_response_or_estimate(response, api_messages))
_usage_this_round = _usage_from_response_or_estimate(response, api_messages)
_accumulated_usage.add(_usage_this_round)
_unsaved_usage.add(_usage_this_round)

# Plain assistant text is not a stop condition. The model must finish
# explicitly via finish(content=...).
Expand All @@ -567,8 +584,8 @@ async def _buffer_chunk(_text: str) -> None:
finish_call = find_finish_call(sanitized_tool_calls)
if finish_call:
if finish_call.valid:
if agent_id and _accumulated_usage.total_tokens > 0:
await record_token_usage(agent_id, _accumulated_usage)
if agent_id and _unsaved_usage.total_tokens > 0:
await record_token_usage(agent_id, _unsaved_usage)
await client.close()
return finish_call.content

Expand Down Expand Up @@ -616,8 +633,8 @@ async def _buffer_chunk(_text: str) -> None:
))

# Record tokens even on "too many rounds" exit
if agent_id and _accumulated_usage.total_tokens > 0:
await record_token_usage(agent_id, _accumulated_usage)
if agent_id and _unsaved_usage.total_tokens > 0:
await record_token_usage(agent_id, _unsaved_usage)
await client.close()
return "[Error] Too many tool call rounds"

Expand Down Expand Up @@ -882,6 +899,7 @@ async def call_agent_llm_with_tools(
async def _try_model(model: LLMModel) -> tuple[str, bool, bool]:
"""Try to complete with a model. Returns (response, success, tool_executed)."""
_accumulated_usage = TokenUsage()
_unsaved_usage = TokenUsage()
tool_executed = False
try:
client = create_llm_client(
Expand All @@ -900,6 +918,17 @@ async def _try_model(model: LLMModel) -> tuple[str, bool, bool]:
# Tool-calling loop
api_messages = list(messages)
for round_i in range(max_rounds):
# Check token usage limit mid-loop (every 3 rounds)
if round_i > 0 and round_i % 3 == 0:
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)
if _token_limit_msg:
logger.warning(f"[call_agent_llm_with_tools] Token limit exceeded mid-loop: {_token_limit_msg}")
await client.close()
return _token_limit_msg, False, tool_executed

try:
response = await client.complete(
messages=api_messages,
Expand All @@ -910,12 +939,14 @@ async def _try_model(model: LLMModel) -> tuple[str, bool, bool]:
except Exception as e:
logger.error(f"[call_agent_llm_with_tools] Agent {agent_id}: LLM call error: {e}")
await client.close()
if agent_id and _accumulated_usage.total_tokens > 0:
await record_token_usage(agent_id, _accumulated_usage)
if agent_id and _unsaved_usage.total_tokens > 0:
await record_token_usage(agent_id, _unsaved_usage)
raise

# Track tokens for this round
_accumulated_usage.add(_usage_from_response_or_estimate(response, api_messages))
_usage_this_round = _usage_from_response_or_estimate(response, api_messages)
_accumulated_usage.add(_usage_this_round)
_unsaved_usage.add(_usage_this_round)

if not response.tool_calls:
if response.content:
Expand All @@ -932,8 +963,8 @@ async def _try_model(model: LLMModel) -> tuple[str, bool, bool]:
finish_call = find_finish_call(sanitized_tool_calls)
if finish_call:
if finish_call.valid:
if agent_id and _accumulated_usage.total_tokens > 0:
await record_token_usage(agent_id, _accumulated_usage)
if agent_id and _unsaved_usage.total_tokens > 0:
await record_token_usage(agent_id, _unsaved_usage)
await client.close()
return finish_call.content, True, tool_executed
api_messages.append(LLMMessage(
Expand Down Expand Up @@ -982,14 +1013,14 @@ async def _try_model(model: LLMModel) -> tuple[str, bool, bool]:
content=str(result),
))

if agent_id and _accumulated_usage.total_tokens > 0:
await record_token_usage(agent_id, _accumulated_usage)
if agent_id and _unsaved_usage.total_tokens > 0:
await record_token_usage(agent_id, _unsaved_usage)
await client.close()
return "[Error] Too many tool call rounds", False, tool_executed

except Exception as e:
if agent_id and _accumulated_usage.total_tokens > 0:
await record_token_usage(agent_id, _accumulated_usage)
if agent_id and _unsaved_usage.total_tokens > 0:
await record_token_usage(agent_id, _unsaved_usage)
return f"[Error] {e}", False, tool_executed

# Try primary model
Expand Down
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