_default_params() — langchain Function Reference

Architecture documentation for the _default_params() function in base.py from the langchain codebase.

Function python LangChainCore LanguageModelBase calls 1 called by 1

Entity Profile

LangChainCore→ LanguageModelBase→ _default_params() — langchain Function Reference

Dependency Diagram

graph TD
  e0e30802_aee2_f5d8_c47e_5abb0cef21b6["_default_params()"]
  2a683305_667b_3567_cab9_9f77e29d4afa["BaseChatOpenAI"]
  e0e30802_aee2_f5d8_c47e_5abb0cef21b6 -->|defined in| 2a683305_667b_3567_cab9_9f77e29d4afa
  e95cffd6_730c_e04c_2b0a_73ea69b2dcb9["_default_params()"]
  e95cffd6_730c_e04c_2b0a_73ea69b2dcb9 -->|calls| e0e30802_aee2_f5d8_c47e_5abb0cef21b6
  e95cffd6_730c_e04c_2b0a_73ea69b2dcb9["_default_params()"]
  e0e30802_aee2_f5d8_c47e_5abb0cef21b6 -->|calls| e95cffd6_730c_e04c_2b0a_73ea69b2dcb9
  style e0e30802_aee2_f5d8_c47e_5abb0cef21b6 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/partners/openai/langchain_openai/chat_models/base.py lines 1036–1065

    def _default_params(self) -> dict[str, Any]:
        """Get the default parameters for calling OpenAI API."""
        exclude_if_none = {
            "presence_penalty": self.presence_penalty,
            "frequency_penalty": self.frequency_penalty,
            "seed": self.seed,
            "top_p": self.top_p,
            "logprobs": self.logprobs,
            "top_logprobs": self.top_logprobs,
            "logit_bias": self.logit_bias,
            "stop": self.stop or None,  # Also exclude empty list for this
            "max_tokens": self.max_tokens,
            "extra_body": self.extra_body,
            "n": self.n,
            "temperature": self.temperature,
            "reasoning_effort": self.reasoning_effort,
            "reasoning": self.reasoning,
            "verbosity": self.verbosity,
            "include": self.include,
            "service_tier": self.service_tier,
            "truncation": self.truncation,
            "store": self.store,
        }

        return {
            "model": self.model_name,
            "stream": self.streaming,
            **{k: v for k, v in exclude_if_none.items() if v is not None},
            **self.model_kwargs,
        }