feat: execute parallel tool calls sequentially

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "uipath-langchain"
-version = "0.4.10"
+version = "0.4.11"
 description = "Python SDK that enables developers to build and deploy LangGraph agents to the UiPath Cloud Platform"
 readme = { file = "README.md", content-type = "text/markdown" }
 requires-python = ">=3.11"

src/uipath_langchain/agent/exceptions/__init__.py

@@ -1,9 +1,11 @@
 from .exceptions import (
     AgentNodeRoutingException,
+    AgentStateException,
     AgentTerminationException,
 )
 
 __all__ = [
     "AgentNodeRoutingException",
+    "AgentStateException",
     "AgentTerminationException",
 ]

src/uipath_langchain/agent/exceptions/exceptions.py

@@ -9,3 +9,7 @@ class AgentNodeRoutingException(Exception):
 
 class AgentTerminationException(UiPathRuntimeError):
     pass
+
+
+class AgentStateException(Exception):
+    pass

src/uipath_langchain/agent/guardrails/actions/escalate_action.py

@@ -15,8 +15,9 @@
 )
 from uipath.runtime.errors import UiPathErrorCode
 
-from ...exceptions import AgentTerminationException
+from ...exceptions import AgentStateException, AgentTerminationException
 from ...react.types import AgentGuardrailsGraphState
+from ...react.utils import extract_current_tool_call_index, find_latest_ai_message
 from ..types import ExecutionStage
 from ..utils import _extract_tool_args_from_message, get_message_content
 from .base_action import GuardrailAction, GuardrailActionNode
@@ -420,9 +421,10 @@ def _process_tool_escalation_response(
         if not msgs or reviewed_field not in escalation_result:
             return {}
 
-        last_message = msgs[-1]
         if execution_stage == ExecutionStage.PRE_EXECUTION:
-            if not isinstance(last_message, AIMessage):
+            # Find the latest AI message instead of assuming last message is AI
+            ai_message = find_latest_ai_message(msgs)
+            if not ai_message:
                 return {}
 
             # Get reviewed tool calls args from escalation result
@@ -434,25 +436,40 @@ def _process_tool_escalation_response(
             if not isinstance(reviewed_tool_calls_args, dict):
                 return {}
 
-            # Find and update only the tool call with matching name
-            if last_message.tool_calls:
-                tool_calls = list(last_message.tool_calls)
-                for tool_call in tool_calls:
+            # Find the current tool call index for the specific tool
+            if ai_message.tool_calls:
+                tool_calls = list(ai_message.tool_calls)
+                current_index = extract_current_tool_call_index(msgs, tool_name)
+
+                # If we found the current index and it's valid
+                if current_index is not None and current_index < len(tool_calls):
+                    tool_call = tool_calls[current_index]
                     call_name = (
                         tool_call.get("name")
                         if isinstance(tool_call, dict)
                         else getattr(tool_call, "name", None)
                     )
+
+                    # Verify this is the correct tool by name
                     if call_name == tool_name:
-                        # Update args for the matching tool call
+                        # Update args for the specific tool call at current index
                         if isinstance(reviewed_tool_calls_args, dict):
                             if isinstance(tool_call, dict):
                                 tool_call["args"] = reviewed_tool_calls_args
                             else:
                                 tool_call.args = reviewed_tool_calls_args
-                        break
-                last_message.tool_calls = tool_calls
+
+                        ai_message.tool_calls = tool_calls
+                    else:
+                        raise AgentStateException(
+                            f"Tool call name [{call_name}] does not match expected tool name [{tool_name}]."
+                        )
+                else:
+                    return {}
+
         else:
+            # POST_EXECUTION: last message should be ToolMessage for tool escalation
+            last_message = msgs[-1]
             if not isinstance(last_message, ToolMessage):
                 return {}
 

src/uipath_langchain/agent/guardrails/actions/filter_action.py

@@ -8,8 +8,12 @@
 from uipath.runtime.errors import UiPathErrorCategory, UiPathErrorCode
 
 from uipath_langchain.agent.guardrails.types import ExecutionStage
+from uipath_langchain.agent.react.utils import (
+    extract_current_tool_call_index,
+    find_latest_ai_message,
+)
 
-from ...exceptions import AgentTerminationException
+from ...exceptions import AgentStateException, AgentTerminationException
 from ...react.types import AgentGuardrailsGraphState
 from .base_action import GuardrailAction, GuardrailActionNode
 
@@ -149,12 +153,9 @@ def _filter_tool_input_fields(
 
     # Find the AIMessage with tool calls
     # At PRE_EXECUTION, this is always the last message
-    ai_message = None
-    for i in range(len(msgs) - 1, -1, -1):
-        msg = msgs[i]
-        if isinstance(msg, AIMessage) and msg.tool_calls:
-            ai_message = msg
-            break
+    ai_message = find_latest_ai_message(msgs)
+    if ai_message is None or not ai_message.tool_calls:
+        return {}
 
     if ai_message is None:
         return {}
@@ -165,40 +166,47 @@ def _filter_tool_input_fields(
     tool_calls = list(ai_message.tool_calls)
     modified = False
 
-    for tool_call in tool_calls:
-        call_name = (
-            tool_call.get("name")
+    current_tool_call_index = extract_current_tool_call_index(msgs, tool_name)
+    if current_tool_call_index is None:
+        return {}
+
+    tool_call = tool_calls[current_tool_call_index]
+
+    call_name = (
+        tool_call.get("name")
+        if isinstance(tool_call, dict)
+        else getattr(tool_call, "name", None)
+    )
+
+    if call_name == tool_name:
+        # Get the current args
+        args = (
+            tool_call.get("args")
             if isinstance(tool_call, dict)
-            else getattr(tool_call, "name", None)
+            else getattr(tool_call, "args", None)
         )
 
-        if call_name == tool_name:
-            # Get the current args
-            args = (
-                tool_call.get("args")
-                if isinstance(tool_call, dict)
-                else getattr(tool_call, "args", None)
-            )
-
-            if args and isinstance(args, dict):
-                # Filter out the specified input fields
-                filtered_args = args.copy()
-                for field_ref in fields_to_filter:
-                    # Only filter input fields
-                    if (
-                        field_ref.source == FieldSource.INPUT
-                        and field_ref.path in filtered_args
-                    ):
-                        del filtered_args[field_ref.path]
-                        modified = True
-
-                # Update the tool call with filtered args
-                if isinstance(tool_call, dict):
-                    tool_call["args"] = filtered_args
-                else:
-                    tool_call.args = filtered_args
-
-            break
+        if args and isinstance(args, dict):
+            # Filter out the specified input fields
+            filtered_args = args.copy()
+            for field_ref in fields_to_filter:
+                # Only filter input fields
+                if (
+                    field_ref.source == FieldSource.INPUT
+                    and field_ref.path in filtered_args
+                ):
+                    del filtered_args[field_ref.path]
+                    modified = True
+
+            # Update the tool call with filtered args
+            if isinstance(tool_call, dict):
+                tool_call["args"] = filtered_args
+            else:
+                tool_call.args = filtered_args
+    else:
+        raise AgentStateException(
+            f"Tool call name [{call_name}] does not match expected tool name [{tool_name}]."
+        )
 
     if modified:
         ai_message.tool_calls = tool_calls

src/uipath_langchain/agent/react/agent.py

@@ -140,8 +140,7 @@ def create_agent(
     )
 
     for tool_name in tool_node_names:
-        builder.add_edge(tool_name, AgentGraphNode.AGENT)
-
+        builder.add_conditional_edges(tool_name, route_agent, target_node_names)
     builder.add_edge(AgentGraphNode.TERMINATE, END)
 
     return builder

src/uipath_langchain/agent/react/llm_node.py

@@ -3,11 +3,11 @@
 from typing import Literal, Sequence
 
 from langchain_core.language_models import BaseChatModel
-from langchain_core.messages import AIMessage, AnyMessage
+from langchain_core.messages import AIMessage, AnyMessage, ToolCall
 from langchain_core.tools import BaseTool
 
 from .constants import MAX_CONSECUTIVE_THINKING_MESSAGES
-from .types import AgentGraphState
+from .types import FLOW_CONTROL_TOOLS, AgentGraphState
 from .utils import count_consecutive_thinking_messages
 
 OPENAI_COMPATIBLE_CHAT_MODELS = (
@@ -33,6 +33,16 @@ def _get_required_tool_choice_by_model(
     return "any"
 
 
+def _filter_control_flow_tool_calls(
+    tool_calls: list[ToolCall],
+) -> list[ToolCall]:
+    """Remove control flow tools when multiple tool calls exist."""
+    if len(tool_calls) <= 1:
+        return tool_calls
+
+    return [tc for tc in tool_calls if tc.get("name") not in FLOW_CONTROL_TOOLS]
+
+
 def create_llm_node(
     model: BaseChatModel,
     tools: Sequence[BaseTool] | None = None,
@@ -74,6 +84,13 @@ async def llm_node(state: AgentGraphState):
                 f"LLM returned {type(response).__name__} instead of AIMessage"
             )
 
+        # filter out flow control tools when multiple tool calls exist
+        if response.tool_calls:
+            filtered_tool_calls = _filter_control_flow_tool_calls(response.tool_calls)
+            if len(filtered_tool_calls) != len(response.tool_calls):
+                # todo: this does not actually work, but fixing tool call modifying is a separate task
+                response.tool_calls = filtered_tool_calls
+
         return {"messages": [response]}
 
     return llm_node

src/uipath_langchain/agent/react/router.py

@@ -2,30 +2,13 @@
 
 from typing import Literal
 
-from langchain_core.messages import ToolCall
-from uipath.agent.react import END_EXECUTION_TOOL, RAISE_ERROR_TOOL
-
 from ..exceptions import AgentNodeRoutingException
-from .router_utils import validate_last_message_is_AI
-from .types import AgentGraphNode, AgentGraphState
-from .utils import count_consecutive_thinking_messages
-
-FLOW_CONTROL_TOOLS = [END_EXECUTION_TOOL.name, RAISE_ERROR_TOOL.name]
-
-
-def __filter_control_flow_tool_calls(
-    tool_calls: list[ToolCall],
-) -> list[ToolCall]:
-    """Remove control flow tools when multiple tool calls exist."""
-    if len(tool_calls) <= 1:
-        return tool_calls
-
-    return [tc for tc in tool_calls if tc.get("name") not in FLOW_CONTROL_TOOLS]
-
-
-def __has_control_flow_tool(tool_calls: list[ToolCall]) -> bool:
-    """Check if any tool call is of a control flow tool."""
-    return any(tc.get("name") in FLOW_CONTROL_TOOLS for tc in tool_calls)
+from .types import FLOW_CONTROL_TOOLS, AgentGraphNode, AgentGraphState
+from .utils import (
+    count_consecutive_thinking_messages,
+    extract_current_tool_call_index,
+    find_latest_ai_message,
+)
 
 
 def create_route_agent(thinking_messages_limit: int = 0):
@@ -40,50 +23,62 @@ def create_route_agent(thinking_messages_limit: int = 0):
 
     def route_agent(
         state: AgentGraphState,
-    ) -> list[str] | Literal[AgentGraphNode.AGENT, AgentGraphNode.TERMINATE]:
-        """Route after agent: handles all routing logic including control flow detection.
+    ) -> str | Literal[AgentGraphNode.AGENT, AgentGraphNode.TERMINATE]:
+        """Route after agent: handles sequential tool execution.
 
         Routing logic:
-        1. If multiple tool calls exist, filter out control flow tools (EndExecution, RaiseError)
-        2. If control flow tool(s) remain, route to TERMINATE
-        3. If regular tool calls remain, route to specific tool nodes (return list of tool names)
-        4. If no tool calls, handle consecutive completions
+        1. Get current tool call index from messages
+        2. If current tool call index is None (all tools completed), route to AGENT
+        3. If current tool call is a flow control tool, route to TERMINATE
+        4. Otherwise, route to the specific tool node
 
         Returns:
-            - list[str]: Tool node names for parallel execution
-            - AgentGraphNode.AGENT: For consecutive completions
+            - str: Single tool node name for sequential execution
+            - AgentGraphNode.AGENT: When all tool calls completed or no tool calls
             - AgentGraphNode.TERMINATE: For control flow termination
 
         Raises:
-            AgentNodeRoutingException: When encountering unexpected state (empty messages, non-AIMessage, or excessive completions)
+            AgentNodeRoutingException: When encountering unexpected state
         """
         messages = state.messages
-        last_message = validate_last_message_is_AI(messages)
-
-        tool_calls = list(last_message.tool_calls) if last_message.tool_calls else []
-        tool_calls = __filter_control_flow_tool_calls(tool_calls)
+        last_message = find_latest_ai_message(messages)
+        if last_message is None:
+            raise AgentNodeRoutingException(
+                "No AIMessage found in messages for routing."
+            )
 
-        if tool_calls and __has_control_flow_tool(tool_calls):
-            return AgentGraphNode.TERMINATE
+        if not last_message.tool_calls:
+            consecutive_thinking_messages = count_consecutive_thinking_messages(
+                messages
+            )
 
-        if tool_calls:
-            return [tc["name"] for tc in tool_calls]
+            if consecutive_thinking_messages > thinking_messages_limit:
+                raise AgentNodeRoutingException(
+                    f"Agent exceeded consecutive completions limit without producing tool calls "
+                    f"(completions: {consecutive_thinking_messages}, max: {thinking_messages_limit}). "
+                    f"This should not happen as tool_choice='required' is enforced at the limit."
+                )
 
-        consecutive_thinking_messages = count_consecutive_thinking_messages(messages)
+            if last_message.content:
+                return AgentGraphNode.AGENT
 
-        if consecutive_thinking_messages > thinking_messages_limit:
             raise AgentNodeRoutingException(
-                f"Agent exceeded consecutive completions limit without producing tool calls "
-                f"(completions: {consecutive_thinking_messages}, max: {thinking_messages_limit}). "
-                f"This should not happen as tool_choice='required' is enforced at the limit."
+                f"Agent produced empty response without tool calls "
+                f"(completions: {consecutive_thinking_messages}, has_content: False)"
             )
 
-        if last_message.content:
+        current_index = extract_current_tool_call_index(messages)
+
+        # all tool calls completed, go back to agent
+        if current_index is None:
             return AgentGraphNode.AGENT
 
-        raise AgentNodeRoutingException(
-            f"Agent produced empty response without tool calls "
-            f"(completions: {consecutive_thinking_messages}, has_content: False)"
-        )
+        current_tool_call = last_message.tool_calls[current_index]
+        current_tool_name = current_tool_call["name"]
+
+        if current_tool_name in FLOW_CONTROL_TOOLS:
+            return AgentGraphNode.TERMINATE
+
+        return current_tool_name
 
     return route_agent