feat(agent): implement llm_messages_limit handling at llm_node

pyproject.toml

@@ -1,11 +1,11 @@
 [project]
 name = "uipath-langchain"
-version = "0.4.11"
+version = "0.4.12"
 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"
 dependencies = [
-    "uipath>=2.5.10,<2.6.0",
+    "uipath>=2.5.15,<2.6.0",
     "uipath-runtime>=0.5.1,<0.6.0",
     "langgraph>=1.0.0, <2.0.0",
     "langchain-core>=1.2.5, <2.0.0",

src/uipath_langchain/agent/exceptions/exceptions.py

@@ -1,4 +1,4 @@
-"""Exceptions for the basic agent loop."""
+"""Exceptions for the agent graph."""
 
 from uipath.runtime.errors import UiPathRuntimeError
 

src/uipath_langchain/agent/react/agent.py

@@ -1,4 +1,3 @@
-import os
 from typing import Callable, Sequence, Type, TypeVar
 
 from langchain_core.language_models import BaseChatModel
@@ -66,8 +65,6 @@ def create_agent(
     if config is None:
         config = AgentGraphConfig()
 
-    os.environ["LANGCHAIN_RECURSION_LIMIT"] = str(config.recursion_limit)
-
     agent_tools = list(tools)
     flow_control_tools: list[BaseTool] = (
         [] if config.is_conversational else create_flow_control_tools(output_schema)
@@ -109,7 +106,11 @@ def create_agent(
     builder.add_edge(START, AgentGraphNode.INIT)
 
     llm_node = create_llm_node(
-        model, llm_tools, config.thinking_messages_limit, config.is_conversational
+        model,
+        llm_tools,
+        config.is_conversational,
+        config.llm_messages_limit,
+        config.thinking_messages_limit,
     )
     llm_with_guardrails_subgraph = create_llm_guardrails_subgraph(
         (AgentGraphNode.LLM, llm_node), guardrails, input_schema=input_schema

src/uipath_langchain/agent/react/constants.py

@@ -1 +1,2 @@
-MAX_CONSECUTIVE_THINKING_MESSAGES = 0
+DEFAULT_MAX_CONSECUTIVE_THINKING_MESSAGES = 0
+DEFAULT_MAX_LLM_MESSAGES = 25

src/uipath_langchain/agent/react/llm_node.py

@@ -5,8 +5,13 @@
 from langchain_core.language_models import BaseChatModel
 from langchain_core.messages import AIMessage, AnyMessage, ToolCall
 from langchain_core.tools import BaseTool
+from uipath.runtime.errors import UiPathErrorCategory, UiPathErrorCode
 
-from .constants import MAX_CONSECUTIVE_THINKING_MESSAGES
+from ..exceptions import AgentTerminationException
+from .constants import (
+    DEFAULT_MAX_CONSECUTIVE_THINKING_MESSAGES,
+    DEFAULT_MAX_LLM_MESSAGES,
+)
 from .types import FLOW_CONTROL_TOOLS, AgentGraphState
 from .utils import count_consecutive_thinking_messages
 
@@ -46,8 +51,9 @@ def _filter_control_flow_tool_calls(
 def create_llm_node(
     model: BaseChatModel,
     tools: Sequence[BaseTool] | None = None,
-    thinking_messages_limit: int = MAX_CONSECUTIVE_THINKING_MESSAGES,
     is_conversational: bool = False,
+    llm_messages_limit: int = DEFAULT_MAX_LLM_MESSAGES,
+    thinking_messages_limit: int = DEFAULT_MAX_CONSECUTIVE_THINKING_MESSAGES,
 ):
     """Create LLM node with dynamic tool_choice enforcement.
 
@@ -57,6 +63,8 @@ def create_llm_node(
     Args:
         model: The chat model to use
         tools: Available tools to bind
+        is_conversational: Whether this is a conversational agent
+        llm_messages_limit: Maximum number of LLM calls allowed per execution
         thinking_messages_limit: Max consecutive LLM responses without tool calls
             before enforcing tool usage. 0 = force tools every time.
     """
@@ -67,6 +75,15 @@ def create_llm_node(
     async def llm_node(state: AgentGraphState):
         messages: list[AnyMessage] = state.messages
 
+        agent_ai_messages = sum(1 for msg in messages if isinstance(msg, AIMessage))
+        if agent_ai_messages >= llm_messages_limit:
+            raise AgentTerminationException(
+                code=UiPathErrorCode.EXECUTION_ERROR,
+                title=f"Maximum iterations of '{llm_messages_limit}' reached.",
+                detail="Verify the agent's trajectory or consider increasing the max iterations in the agent's settings.",
+                category=UiPathErrorCategory.USER,
+            )
+
         consecutive_thinking_messages = count_consecutive_thinking_messages(messages)
 
         if (

src/uipath_langchain/agent/react/types.py

@@ -64,13 +64,15 @@ class AgentGraphNode(StrEnum):
 
 
 class AgentGraphConfig(BaseModel):
-    recursion_limit: int = Field(
-        default=50, ge=1, description="Maximum recursion limit for the agent graph"
+    llm_messages_limit: int = Field(
+        default=25,
+        ge=1,
+        description="Maximum number of LLM calls allowed per agent execution",
     )
     thinking_messages_limit: int = Field(
         default=0,
         ge=0,
-        description="Max consecutive thinking messages before enforcing tool usage. 0 = force tools every time.",
+        description="Max consecutive thinking messages before enforcing tool calling. 0 = force tool calling every time.",
     )
     is_conversational: bool = Field(
         default=False, description="If set, creates a graph for conversational agents"