Source code for langchain_community.utilities.serpapi

"""Chain that calls SerpAPI.

Heavily borrowed from
import os
import sys
from typing import Any, Dict, Optional, Tuple

import aiohttp
from langchain_core.pydantic_v1 import BaseModel, Extra, Field, root_validator
from langchain_core.utils import get_from_dict_or_env

[docs]class HiddenPrints: """Context manager to hide prints.""" def __enter__(self) -> None: """Open file to pipe stdout to.""" self._original_stdout = sys.stdout sys.stdout = open(os.devnull, "w") def __exit__(self, *_: Any) -> None: """Close file that stdout was piped to.""" sys.stdout.close() sys.stdout = self._original_stdout
[docs]class SerpAPIWrapper(BaseModel): """Wrapper around SerpAPI. To use, you should have the ``google-search-results`` python package installed, and the environment variable ``SERPAPI_API_KEY`` set with your API key, or pass `serpapi_api_key` as a named parameter to the constructor. Example: .. code-block:: python from langchain_community.utilities import SerpAPIWrapper serpapi = SerpAPIWrapper() """ search_engine: Any #: :meta private: params: dict = Field( default={ "engine": "google", "google_domain": "", "gl": "us", "hl": "en", } ) serpapi_api_key: Optional[str] = None aiosession: Optional[aiohttp.ClientSession] = None class Config: """Configuration for this pydantic object.""" extra = Extra.forbid arbitrary_types_allowed = True @root_validator() def validate_environment(cls, values: Dict) -> Dict: """Validate that api key and python package exists in environment.""" serpapi_api_key = get_from_dict_or_env( values, "serpapi_api_key", "SERPAPI_API_KEY" ) values["serpapi_api_key"] = serpapi_api_key try: from serpapi import GoogleSearch values["search_engine"] = GoogleSearch except ImportError: raise ImportError( "Could not import serpapi python package. " "Please install it with `pip install google-search-results`." ) return values
[docs] async def arun(self, query: str, **kwargs: Any) -> str: """Run query through SerpAPI and parse result async.""" return self._process_response(await self.aresults(query))
[docs] def run(self, query: str, **kwargs: Any) -> str: """Run query through SerpAPI and parse result.""" return self._process_response(self.results(query))
[docs] def results(self, query: str) -> dict: """Run query through SerpAPI and return the raw result.""" params = self.get_params(query) with HiddenPrints(): search = self.search_engine(params) res = search.get_dict() return res
[docs] async def aresults(self, query: str) -> dict: """Use aiohttp to run query through SerpAPI and return the results async.""" def construct_url_and_params() -> Tuple[str, Dict[str, str]]: params = self.get_params(query) params["source"] = "python" if self.serpapi_api_key: params["serp_api_key"] = self.serpapi_api_key params["output"] = "json" url = "" return url, params url, params = construct_url_and_params() if not self.aiosession: async with aiohttp.ClientSession() as session: async with session.get(url, params=params) as response: res = await response.json() else: async with self.aiosession.get(url, params=params) as response: res = await response.json() return res
[docs] def get_params(self, query: str) -> Dict[str, str]: """Get parameters for SerpAPI.""" _params = { "api_key": self.serpapi_api_key, "q": query, } params = {**self.params, **_params} return params
@staticmethod def _process_response(res: dict) -> str: """Process response from SerpAPI.""" if "error" in res.keys(): raise ValueError(f"Got error from SerpAPI: {res['error']}") if "answer_box_list" in res.keys(): res["answer_box"] = res["answer_box_list"] if "answer_box" in res.keys(): answer_box = res["answer_box"] if isinstance(answer_box, list): answer_box = answer_box[0] if "result" in answer_box.keys(): return answer_box["result"] elif "answer" in answer_box.keys(): return answer_box["answer"] elif "snippet" in answer_box.keys(): return answer_box["snippet"] elif "snippet_highlighted_words" in answer_box.keys(): return answer_box["snippet_highlighted_words"] else: answer = {} for key, value in answer_box.items(): if not isinstance(value, (list, dict)) and not ( isinstance(value, str) and value.startswith("http") ): answer[key] = value return str(answer) elif "events_results" in res.keys(): return res["events_results"][:10] elif "sports_results" in res.keys(): return res["sports_results"] elif "top_stories" in res.keys(): return res["top_stories"] elif "news_results" in res.keys(): return res["news_results"] elif "jobs_results" in res.keys() and "jobs" in res["jobs_results"].keys(): return res["jobs_results"]["jobs"] elif ( "shopping_results" in res.keys() and "title" in res["shopping_results"][0].keys() ): return res["shopping_results"][:3] elif "questions_and_answers" in res.keys(): return res["questions_and_answers"] elif ( "popular_destinations" in res.keys() and "destinations" in res["popular_destinations"].keys() ): return res["popular_destinations"]["destinations"] elif "top_sights" in res.keys() and "sights" in res["top_sights"].keys(): return res["top_sights"]["sights"] elif ( "images_results" in res.keys() and "thumbnail" in res["images_results"][0].keys() ): return str([item["thumbnail"] for item in res["images_results"][:10]]) snippets = [] if "knowledge_graph" in res.keys(): knowledge_graph = res["knowledge_graph"] title = knowledge_graph["title"] if "title" in knowledge_graph else "" if "description" in knowledge_graph.keys(): snippets.append(knowledge_graph["description"]) for key, value in knowledge_graph.items(): if ( isinstance(key, str) and isinstance(value, str) and key not in ["title", "description"] and not key.endswith("_stick") and not key.endswith("_link") and not value.startswith("http") ): snippets.append(f"{title} {key}: {value}.") for organic_result in res.get("organic_results", []): if "snippet" in organic_result.keys(): snippets.append(organic_result["snippet"]) elif "snippet_highlighted_words" in organic_result.keys(): snippets.append(organic_result["snippet_highlighted_words"]) elif "rich_snippet" in organic_result.keys(): snippets.append(organic_result["rich_snippet"]) elif "rich_snippet_table" in organic_result.keys(): snippets.append(organic_result["rich_snippet_table"]) elif "link" in organic_result.keys(): snippets.append(organic_result["link"]) if "buying_guide" in res.keys(): snippets.append(res["buying_guide"]) if "local_results" in res and isinstance(res["local_results"], list): snippets += res["local_results"] if ( "local_results" in res.keys() and isinstance(res["local_results"], dict) and "places" in res["local_results"].keys() ): snippets.append(res["local_results"]["places"]) if len(snippets) > 0: return str(snippets) else: return "No good search result found"