_acall() — langchain Function Reference

Architecture documentation for the _acall() function in llms.py from the langchain codebase.

Function python LangChainCore LanguageModelBase calls 3

Entity Profile

LangChainCore→ LanguageModelBase→ _acall() — langchain Function Reference

Dependency Diagram

graph TD
  40512e45_7b9d_dbee_2106_59fc9edca16c["_acall()"]
  c95a497f_938f_2be9_842e_087a0766cf00["AnthropicLLM"]
  40512e45_7b9d_dbee_2106_59fc9edca16c -->|defined in| c95a497f_938f_2be9_842e_087a0766cf00
  3f0a5215_29d7_44ca_e135_a3f37294ae0c["_astream()"]
  40512e45_7b9d_dbee_2106_59fc9edca16c -->|calls| 3f0a5215_29d7_44ca_e135_a3f37294ae0c
  5b0cfa0b_130d_960a_411e_cc97a2c28a93["_get_anthropic_stop()"]
  40512e45_7b9d_dbee_2106_59fc9edca16c -->|calls| 5b0cfa0b_130d_960a_411e_cc97a2c28a93
  04edfbcc_f913_d95a_6261_c2a81f9f570e["_format_messages()"]
  40512e45_7b9d_dbee_2106_59fc9edca16c -->|calls| 04edfbcc_f913_d95a_6261_c2a81f9f570e
  style 40512e45_7b9d_dbee_2106_59fc9edca16c fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/partners/anthropic/langchain_anthropic/llms.py lines 302–332

    async def _acall(
        self,
        prompt: str,
        stop: list[str] | None = None,
        run_manager: AsyncCallbackManagerForLLMRun | None = None,
        **kwargs: Any,
    ) -> str:
        """Call out to Anthropic's completion endpoint asynchronously."""
        if self.streaming:
            completion = ""
            async for chunk in self._astream(
                prompt=prompt,
                stop=stop,
                run_manager=run_manager,
                **kwargs,
            ):
                completion += chunk.text
            return completion

        stop = self._get_anthropic_stop(stop)
        params = {**self._default_params, **kwargs}

        # Remove parameters not supported by Messages API
        params = {k: v for k, v in params.items() if k != "max_tokens_to_sample"}

        response = await self.async_client.messages.create(
            messages=self._format_messages(prompt),
            stop_sequences=stop if stop else None,
            **params,
        )
        return response.content[0].text