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I want to test parallel nodes and wrote an example that uses two separate tool nodes for addition and multiplication, instead of combining both operations into a single tool node. It works fine when I ask '1 + 2' or '3 * 4,' but an error occurs when I ask '1 + 2 and 3 * 4.' Does anyone know how to accomplish this? %%{init: {'flowchart': {'curve': 'linear'}}}%%
graph TD;
__start__([__start__]):::first
chatbot(chatbot)
add(add)
multiply(multiply)
__end__([__end__]):::last
__start__ --> chatbot;
add --> chatbot;
multiply --> chatbot;
chatbot -.-> add;
chatbot -.-> multiply;
chatbot -.-> __end__;
classDef default fill:#f2f0ff,line-height:1.2
classDef first fill-opacity:0
classDef last fill:#bfb6fc
code: from typing import Annotated
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.tools import tool
from langgraph.checkpoint import MemorySaver
from langgraph.constants import END, START
from typing_extensions import TypedDict
from langgraph.graph import StateGraph
from langgraph.graph.message import add_messages
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import ToolNode, tools_condition
class State(TypedDict):
messages: Annotated[list, add_messages]
@tool
def add(first_int: int, second_int: int) -> int:
"""
Calculate the sum of two numbers like 1 + 2
Args:
first_int (Optional[int]): first num
second_int (Optional[str]): second num
"""
return first_int + second_int
@tool
def multiply(first_int: int, second_int: int) -> int:
"""
Calculate the product of two numbers like 3 * 4
Args:
first_int (Optional[int]): first num
second_int (Optional[str]): second num
"""
return first_int * second_int
tools = [add, multiply]
assistant_prompt = ChatPromptTemplate.from_messages(
[
(
"system",
"you are an assistant for calculating",
),
("placeholder", "{messages}"),
]
)
llm = ChatOpenAI()
llm_with_tools = assistant_prompt | llm.bind_tools(tools)
def chatbot(state: State):
#new_state = state[-3:]
message = {"messages": [llm_with_tools.invoke(state)]}
return message
graph_builder = StateGraph(State)
graph_builder.add_node("chatbot", chatbot)
add_node = ToolNode(tools=[add])
multiply_node = ToolNode(tools=[multiply])
graph_builder.add_node("add", add_node)
graph_builder.add_node("multiply", multiply_node)
# -> list[Literal["add", "multiply", "__end__"]]
def route_tools(state: State):
next_node = tools_condition(state)
# If no tools are invoked, return to the user
if next_node == END:
return END
tool_calls = state["messages"][-1].tool_calls
target = []
if tool_calls:
for call in tool_calls:
target += [call["name"]]
return target # ["add", "multiply"]
return [END]
graph_builder.add_edge(START, "chatbot")
graph_builder.add_conditional_edges(
"chatbot",
route_tools,
)
graph_builder.add_edge("add", "chatbot")
graph_builder.add_edge("multiply", "chatbot")
# memory = SqliteSaver.from_conn_string(":memory:")
memory = MemorySaver()
graph = graph_builder.compile(checkpointer=memory)
config = {"configurable": {"thread_id": "1"}}
# print(graph.get_graph().draw_mermaid())
def _print_event(event: dict, _printed: set, max_length=1500):
message = event.get("messages")
if message:
if isinstance(message, list):
message = message[-1]
if message.id not in _printed:
msg_repr = message.pretty_repr(html=True)
if len(msg_repr) > max_length:
msg_repr = msg_repr[:max_length] + " ... (truncated)"
print(msg_repr)
_printed.add(message.id)
# while True:
# user_input = input("User: ")
# if user_input.lower() in ["quit", "exit", "q"]:
# print("Goodbye!")
# break
# _printed = set()
# events = graph.stream(
# {"messages": ("user", user_input)}, config, stream_mode="values"
# )
# for event in events:
# _print_event(event, _printed)
while True:
user_input = input("User: ")
if user_input.lower() in ["quit", "exit", "q"]:
print("Goodbye!")
break
_printed = set()
events = graph.stream(
{"messages": ("user", user_input)}, config, stream_mode="values"
)
for event in events:
_print_event(event, _printed)result: When the LLM is invoked with messages like the ones shown in the picture, an error occurs. |
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Answered by
vbarda
Aug 30, 2024
Replies: 1 comment 5 replies
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can you share a langsmith trace? |
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5 replies
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Here is the trace: https://smith.langchain.com/public/039e1b92-ba39-492d-8869-ba647dee5643/r |
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Hi, Is there any progress? |
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@modestme the issue you're encountering is because you're trying to send all tool calls to both tool nodes, but they only know how to handle a single tool. as a result, each tool node returns one correct tool message (with result of add/multiply) and one tool message with error (as it doesn't support the other tool by definition). as a result of that, LLM gets confused as it tries to fix that error. here is how you can achieve the desired behavior: add_node = ToolNode(tools=[add])
multiply_node = ToolNode(tools=[multiply])
def call_add(state):
messages = state["messages"]
tool_messages = add_node.invoke([messages[-1]])
return {"messages": [message for message in tool_messages if message.name == "add"]}
def call_multiply(state):
messages = state["messages"]
tool_messages = multiply_node.invoke([messages[-1]])
return {"messages": [message for message in tool_messages if message.name == "multiply"]}
graph_builder.add_node("add", call_add)
graph_builder.add_node("multiply", call_multiply)let me know if this helps! |
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Answer selected by
modestme
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Thanks, it work fine! |
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In addition to the filtering tool messages, it's also possible to directly modify the tool call in the message when invoking the tool. def call_add(state):
messages = state["messages"]
invoke_message = messages[-1].copy()
invoke_message.tool_calls = [tool_call for tool_call in invoke_message.tool_calls if tool_call["name"] == "add"]
tool_messages = add_node.invoke([invoke_message])
return {"messages": tool_messages}
def call_multiply(state):
messages = state["messages"]
invoke_message = messages[-1].copy()
invoke_message.tool_calls = [tool_call for tool_call in invoke_message.tool_calls if tool_call["name"] == "multiply"]
tool_messages = multiply_node.invoke([invoke_message])
return {"messages": tool_messages} |
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@modestme the issue you're encountering is because you're trying to send all tool calls to both tool nodes, but they only know how to handle a single tool. as a result, each tool node returns one correct tool message (with result of add/multiply) and one tool message with error (as it doesn't support the other tool by definition). as a result of that, LLM gets confused as it tries to fix that error. here is how you can achieve the desired behavior: