dosubot[bot]
commented
12 months ago 🤖
Hi there,
Thank you for reaching out and providing a detailed description of your issue. It seems like you're trying to stop the agent from continuously generating new input.
In LangChain, there is a method called return_stopped_response that is used when the agent has been stopped due to max iterations. This method takes an early_stopping_method parameter. If the early_stopping_method is set to "force", the agent will stop immediately and return a constant string. If the early_stopping_method is set to "generate", the agent will do one final forward pass before stopping.
Here is the relevant code:
def return_stopped_response(
self,
early_stopping_method: str,
intermediate_steps: List[Tuple[AgentAction, str]],
**kwargs: Any,
) -> AgentFinish:
"""Return response when agent has been stopped due to max iterations."""
if early_stopping_method == "force":
# `force` just returns a constant string
return AgentFinish(
{"output": "Agent stopped due to iteration limit or time limit."}, ""
)
elif early_stopping_method == "generate":
# Generate does one final forward pass
thoughts = ""
for action, observation in intermediate_steps:
thoughts += action.log
thoughts += (
f"\n{self.observation_prefix}{observation}\n{self.llm_prefix}"
)
# Adding to the previous steps, we now tell the LLM to make a final pred
thoughts += (
"\n\nI now need to return a final answer based on the previous steps:"
)
new_inputs = {"agent_scratchpad": thoughts, "stop": self._stop}
full_inputs = {**kwargs, **new_inputs}
full_output = self.llm_chain.predict(**full_inputs)
# We try to extract a final answer
parsed_output = self.output_parser.parse(full_output)
if isinstance(parsed_output, AgentFinish):
# If we can extract, we send the correct stuff
return parsed_output
else:
# If we can extract, but the tool is not the final tool,
# we just return the full output
return AgentFinish({"output": full_output}, full_output)
else:
raise ValueError(
"early_stopping_method should be one of `force` or `generate`, "
f"got {early_stopping_method}"
)You can find this code in the libs/langchain/langchain/agents/agent.py file.
Please note that the return_stopped_response method does not have a default value for the early_stopping_method parameter. This means that the early_stopping_method parameter must be provided when calling the method. The method supports two values for early_stopping_method: "force" and "generate". If any other value is provided, the method raises a ValueError.
I hope this helps! If you have any other questions, feel free to ask.
Sources
- libs/langchain/tests/unit_tests/agents/test_agent.py
- libs/langchain/langchain/agents/agent.py
- libs/langchain/langchain/agents/openai_functions_agent/base.py
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ayushgupta-1
Issue you'd like to raise.
Hi everyone,
I'm trying to build my own conversational chatbot. When I run the code above, I got the following output:
May I know how can I stop the agent from keep generating new input? I already use the stop parameter, but seems like it doesn't work.
I follow the instruction from Langchain documentation here
Based on the documentation, the output shouldn't return so many New inputs and responses. Any help or advise will be greatly appreciated!
Suggestion:
No response