dosubot[bot]
commented
8 months ago 🤖
Hey @calvinweb! Good to see you again. I hope you're cracking the code like a pro today. Let's dive into this, shall we?
The llm.bind(stop=["\nObservation"]) line in the json_chat agent is indeed meaningful. This line is used to bind the language model with a stop sequence. In this case, the stop sequence is "\nObservation". This means that the language model will stop generating further output when it encounters this sequence.
Even though the json_chat agent relies on JSON for formatting its logic, the stop sequence is not related to the JSON format. It is a part of the language model's generation process. The language model generates text, and when it encounters the stop sequence, it stops generating further text. This is independent of how the generated text is formatted or used afterwards.
Here is the relevant code:
llm_with_stop = llm.bind(stop=["\nObservation"])In this line, llm is the language model, and bind is a method that binds the language model with a stop sequence. The stop sequence is passed as a list of strings. In this case, the stop sequence is ["\nObservation"].
In the context of language models, the stop parameter is used to specify a list of strings that the model should consider as end-of-text markers. When the model encounters any of these strings during the generation process, it stops generating further text.
This is evident from the following code snippet:
if isinstance(self.llm, BaseLanguageModel):
return self.llm.generate_prompt(
prompts,
stop,
callbacks=callbacks,
**self.llm_kwargs,
)
else:
results = self.llm.bind(stop=stop, **self.llm_kwargs).batch(
cast(List, prompts), {"callbacks": callbacks}
)Here, if self.llm is an instance of BaseLanguageModel, the stop parameter is passed directly to the generate_prompt method. Otherwise, stop is bound to self.llm before calling the batch method.
You can find more information about this in the LangChain codebase.
Sources
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steve-carpenter
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lin-calvin
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Example Code
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Description
https://github.com/langchain-ai/langchain/blob/ef75bb63ce5cc4fb76ba1631ebe582f56103ab7e/libs/langchain/langchain/agents/json_chat/base.py#L151 this seems useless because chat-json depends json to work,not this sort of completion
System Info
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Related Components