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feat: remove single tool call case in new agent loop (#5504)

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* feat: remove single tool call case in new agent loop

* fix hitl test
This commit is contained in:
cthomas
2025-10-17 10:35:23 -07:00
committed by Caren Thomas
parent deb599f706
commit a03263aca2
1 changed files with 9 additions and 22 deletions
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31
letta/agents/letta_agent_v3.py
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@@ -281,7 +281,7 @@ class LettaAgentV3(LettaAgentV2):
step_progression = StepProgression.START
# TODO(@caren): clean this up
tool_call, content, agent_step_span, first_chunk, step_id, logged_step, step_start_ns, step_metrics = (
tool_calls, content, agent_step_span, first_chunk, step_id, logged_step, step_start_ns, step_metrics = (
None,
None,
None,
@@ -305,7 +305,7 @@ class LettaAgentV3(LettaAgentV2):
approval_request, approval_response = _maybe_get_approval_messages(messages)
if approval_request and approval_response:
tool_call = approval_request.tool_calls[0]
tool_calls = approval_request.tool_calls
content = approval_request.content
step_id = approval_request.step_id
step_metrics = await self.step_manager.get_step_metrics_async(step_id=step_id, actor=self.actor)
@@ -404,19 +404,12 @@ class LettaAgentV3(LettaAgentV2):
self._update_global_usage_stats(llm_adapter.usage)
# Handle the AI response with the extracted data (supports multiple tool calls)
# Gather tool calls. Approval paths specify a single tool call.
tool_calls_list: list[ToolCall] = []
if tool_call is not None:
tool_calls_list = [tool_call]
else:
# Prefer the new multi-call field from streaming adapters
# Handle the AI response with the extracted data (supports multiple tool calls)
# Gather tool calls. Approval paths specify a single tool call.
if hasattr(llm_adapter, "tool_calls") and llm_adapter.tool_calls:
tool_calls_list = llm_adapter.tool_calls
tool_calls = llm_adapter.tool_calls
elif llm_adapter.tool_call is not None:
tool_calls_list = [llm_adapter.tool_call]
else:
tool_calls_list = []
tool_calls = [llm_adapter.tool_call]
aggregated_persisted: list[Message] = []
tool_return_payload = (
@@ -424,11 +417,9 @@ class LettaAgentV3(LettaAgentV2):
if approval_response and approval_response.approvals and isinstance(approval_response.approvals[0], ToolReturn)
else None
)
primary_tool_call = tool_calls_list[0] if len(tool_calls_list) == 1 else None
persisted_messages, self.should_continue, self.stop_reason = await self._handle_ai_response(
tool_call=primary_tool_call,
tool_calls=tool_calls_list,
tool_calls=tool_calls,
valid_tool_names=[tool["name"] for tool in valid_tools],
agent_state=self.agent_state,
tool_rules_solver=self.tool_rules_solver,
@@ -592,8 +583,7 @@ class LettaAgentV3(LettaAgentV2):
is_approval: bool | None = None,
is_denial: bool | None = None,
denial_reason: str | None = None,
tool_call: ToolCall | None = None,
tool_calls: Optional[list[ToolCall]] = None,
tool_calls: list[ToolCall] = [],
tool_return: ToolReturn | None = None,
) -> tuple[list[Message], bool, LettaStopReason | None]:
"""
@@ -602,10 +592,7 @@ class LettaAgentV3(LettaAgentV2):
Unified approach: treats single and multi-tool calls uniformly to reduce code duplication.
"""
tool_calls = list(tool_calls) if tool_calls else []
if tool_call is not None and not tool_calls:
tool_calls = [tool_call]
first_tool_call = tool_calls[0] if tool_calls else tool_call
first_tool_call = tool_calls[0] if tool_calls else None
if tool_return is not None:
continue_stepping = True