code: """Chain that makes API calls and summarizes the responses to answer a question."""
  from __future__ import annotations
  
  from typing import Any, Dict, List, Optional, Sequence, Tuple
  from urllib.parse import urlparse
  
  from langchain_community.utilities.requests import TextRequestsWrapper
  from langchain_core.callbacks import (
      AsyncCallbackManagerForChainRun,
      CallbackManagerForChainRun,
  )
  from langchain_core.language_models import BaseLanguageModel
  from langchain_core.prompts import BasePromptTemplate
  from langchain_core.pydantic_v1 import Field, root_validator
  
  from langchain.chains.api.prompt import API_RESPONSE_PROMPT, API_URL_PROMPT
  from langchain.chains.base import Chain
  from langchain.chains.llm import LLMChain
  
  
  def _extract_scheme_and_domain(url: str) -> Tuple[str, str]:
      """Extract the scheme + domain from a given URL.
  
      Args:
          url (str): The input URL.
  
      Returns:
          return a 2-tuple of scheme and domain
      """
      parsed_uri = urlparse(url)
      return parsed_uri.scheme, parsed_uri.netloc
  
  
  def _check_in_allowed_domain(url: str, limit_to_domains: Sequence[str]) -> bool:
      """Check if a URL is in the allowed domains.
  
      Args:
          url (str): The input URL.
          limit_to_domains (Sequence[str]): The allowed domains.
  
      Returns:
          bool: True if the URL is in the allowed domains, False otherwise.
      """
      scheme, domain = _extract_scheme_and_domain(url)
  
      for allowed_domain in limit_to_domains:
          allowed_scheme, allowed_domain = _extract_scheme_and_domain(allowed_domain)
          if scheme == allowed_scheme and domain == allowed_domain:
              return True
      return False
  
  
  class APIChain(Chain):
      """Chain that makes API calls and summarizes the responses to answer a question.
  
      *Security Note*: This API chain uses the requests toolkit
          to make GET, POST, PATCH, PUT, and DELETE requests to an API.
  
          Exercise care in who is allowed to use this chain. If exposing
          to end users, consider that users will be able to make arbitrary
          requests on behalf of the server hosting the code. For example,
          users could ask the server to make a request to a private API
          that is only accessible from the server.
  
          Control access to who can submit issue requests using this toolkit and
          what network access it has.
  
          See https://python.langchain.com/docs/security for more information.
      """
  
      api_request_chain: LLMChain
      api_answer_chain: LLMChain
      requests_wrapper: TextRequestsWrapper = Field(exclude=True)
      api_docs: str
      question_key: str = "question"  #: :meta private:
      output_key: str = "output"  #: :meta private:
      limit_to_domains: Optional[Sequence[str]]
      """Use to limit the domains that can be accessed by the API chain.
      
      * For example, to limit to just the domain `https://www.example.com`, set
          `limit_to_domains=["https://www.example.com"]`.
          
      * The default value is an empty tuple, which means that no domains are
        allowed by default. By design this will raise an error on instantiation.
      * Use a None if you want to allow all domains by default -- this is not
        recommended for security reasons, as it would allow malicious users to
        make requests to arbitrary URLS including internal APIs accessible from
        the server.
      """
  
      @property
      def input_keys(self) -> List[str]:
          """Expect input key.
  
          :meta private:
          """
          return [self.question_key]
  
      @property
      def output_keys(self) -> List[str]:
          """Expect output key.
  
          :meta private:
          """
          return [self.output_key]
  
      @root_validator(pre=True)
      def validate_api_request_prompt(cls, values: Dict) -> Dict:
          """Check that api request prompt expects the right variables."""
          input_vars = values["api_request_chain"].prompt.input_variables
          expected_vars = {"question", "api_docs"}
          if set(input_vars) != expected_vars:
              raise ValueError(
                  f"Input variables should be {expected_vars}, got {input_vars}"
              )
          return values
  
      @root_validator(pre=True)
      def validate_limit_to_domains(cls, values: Dict) -> Dict:
          """Check that allowed domains are valid."""
          if "limit_to_domains" not in values:
              raise ValueError(
                  "You must specify a list of domains to limit access using "
                  "`limit_to_domains`"
              )
          if not values["limit_to_domains"] and values["limit_to_domains"] is not None:
              raise ValueError(
                  "Please provide a list of domains to limit access using "
                  "`limit_to_domains`."
              )
          return values
  
      @root_validator(pre=True)
      def validate_api_answer_prompt(cls, values: Dict) -> Dict:
          """Check that api answer prompt expects the right variables."""
          input_vars = values["api_answer_chain"].prompt.input_variables
          expected_vars = {"question", "api_docs", "api_url", "api_response"}
          if set(input_vars) != expected_vars:
              raise ValueError(
                  f"Input variables should be {expected_vars}, got {input_vars}"
              )
          return values
  
      def _call(
          self,
          inputs: Dict[str, Any],
          run_manager: Optional[CallbackManagerForChainRun] = None,
      ) -> Dict[str, str]:
          _run_manager = run_manager or CallbackManagerForChainRun.get_noop_manager()
          question = inputs[self.question_key]
          api_url = self.api_request_chain.predict(
              question=question,
              api_docs=self.api_docs,
              callbacks=_run_manager.get_child(),
          )
          _run_manager.on_text(api_url, color="green", end="\n", verbose=self.verbose)
          api_url = api_url.strip()
          if self.limit_to_domains and not _check_in_allowed_domain(
              api_url, self.limit_to_domains
          ):
              raise ValueError(
                  f"{api_url} is not in the allowed domains: {self.limit_to_domains}"
              )
          api_response = self.requests_wrapper.get(api_url)
          _run_manager.on_text(
              str(api_response), color="yellow", end="\n", verbose=self.verbose
          )
          answer = self.api_answer_chain.predict(
              question=question,
              api_docs=self.api_docs,
              api_url=api_url,
              api_response=api_response,
              callbacks=_run_manager.get_child(),
          )
          return {self.output_key: answer}
  
      async def _acall(
          self,
          inputs: Dict[str, Any],
          run_manager: Optional[AsyncCallbackManagerForChainRun] = None,
      ) -> Dict[str, str]:
          _run_manager = run_manager or AsyncCallbackManagerForChainRun.get_noop_manager()
          question = inputs[self.question_key]
          api_url = await self.api_request_chain.apredict(
              question=question,
              api_docs=self.api_docs,
              callbacks=_run_manager.get_child(),
          )
          await _run_manager.on_text(
              api_url, color="green", end="\n", verbose=self.verbose
          )
          api_url = api_url.strip()
          if self.limit_to_domains and not _check_in_allowed_domain(
              api_url, self.limit_to_domains
          ):
              raise ValueError(
                  f"{api_url} is not in the allowed domains: {self.limit_to_domains}"
              )
          api_response = await self.requests_wrapper.aget(api_url)
          await _run_manager.on_text(
              str(api_response), color="yellow", end="\n", verbose=self.verbose
          )
          answer = await self.api_answer_chain.apredict(
              question=question,
              api_docs=self.api_docs,
              api_url=api_url,
              api_response=api_response,
              callbacks=_run_manager.get_child(),
          )
          return {self.output_key: answer}
  
      @classmethod
      def from_llm_and_api_docs(
          cls,
          llm: BaseLanguageModel,
          api_docs: str,
          headers: Optional[dict] = None,
          api_url_prompt: BasePromptTemplate = API_URL_PROMPT,
          api_response_prompt: BasePromptTemplate = API_RESPONSE_PROMPT,
          limit_to_domains: Optional[Sequence[str]] = tuple(),
          **kwargs: Any,
      ) -> APIChain:
          """Load chain from just an LLM and the api docs."""
          get_request_chain = LLMChain(llm=llm, prompt=api_url_prompt)
          requests_wrapper = TextRequestsWrapper(headers=headers)
          get_answer_chain = LLMChain(llm=llm, prompt=api_response_prompt)
          return cls(
              api_request_chain=get_request_chain,
              api_answer_chain=get_answer_chain,
              requests_wrapper=requests_wrapper,
              api_docs=api_docs,
              limit_to_domains=limit_to_domains,
              **kwargs,
          )
  
      @property
      def _chain_type(self) -> str:
          return "api_chain"
  
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