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https://github.com/hwchase17/langchain.git
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community[major], core[patch], langchain[patch], experimental[patch]: Create langchain-community (#14463)
Moved the following modules to new package langchain-community in a backwards compatible fashion: ``` mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community ``` Moved the following to core ``` mv langchain/langchain/utils/json_schema.py core/langchain_core/utils mv langchain/langchain/utils/html.py core/langchain_core/utils mv langchain/langchain/utils/strings.py core/langchain_core/utils cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py rm langchain/langchain/utils/env.py ``` See .scripts/community_split/script_integrations.sh for all changes
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GitHub
138
libs/community/langchain_community/utilities/searchapi.py
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138
libs/community/langchain_community/utilities/searchapi.py
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from typing import Any, Dict, Optional
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import aiohttp
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import requests
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from langchain_core.pydantic_v1 import BaseModel, root_validator
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from langchain_core.utils import get_from_dict_or_env
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class SearchApiAPIWrapper(BaseModel):
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"""
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Wrapper around SearchApi API.
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To use, you should have the environment variable ``SEARCHAPI_API_KEY``
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set with your API key, or pass `searchapi_api_key`
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as a named parameter to the constructor.
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Example:
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.. code-block:: python
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from langchain_community.utilities import SearchApiAPIWrapper
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searchapi = SearchApiAPIWrapper()
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"""
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# Use "google" engine by default.
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# Full list of supported ones can be found in https://www.searchapi.io docs
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engine: str = "google"
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searchapi_api_key: Optional[str] = None
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aiosession: Optional[aiohttp.ClientSession] = None
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class Config:
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"""Configuration for this pydantic object."""
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arbitrary_types_allowed = True
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@root_validator()
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def validate_environment(cls, values: Dict) -> Dict:
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"""Validate that API key exists in environment."""
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searchapi_api_key = get_from_dict_or_env(
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values, "searchapi_api_key", "SEARCHAPI_API_KEY"
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)
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values["searchapi_api_key"] = searchapi_api_key
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return values
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def run(self, query: str, **kwargs: Any) -> str:
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results = self.results(query, **kwargs)
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return self._result_as_string(results)
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async def arun(self, query: str, **kwargs: Any) -> str:
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results = await self.aresults(query, **kwargs)
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return self._result_as_string(results)
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def results(self, query: str, **kwargs: Any) -> dict:
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results = self._search_api_results(query, **kwargs)
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return results
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async def aresults(self, query: str, **kwargs: Any) -> dict:
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results = await self._async_search_api_results(query, **kwargs)
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return results
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def _prepare_request(self, query: str, **kwargs: Any) -> dict:
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return {
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"url": "https://www.searchapi.io/api/v1/search",
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"headers": {
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"Authorization": f"Bearer {self.searchapi_api_key}",
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},
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"params": {
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"engine": self.engine,
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"q": query,
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**{key: value for key, value in kwargs.items() if value is not None},
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},
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}
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def _search_api_results(self, query: str, **kwargs: Any) -> dict:
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request_details = self._prepare_request(query, **kwargs)
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response = requests.get(
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url=request_details["url"],
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params=request_details["params"],
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headers=request_details["headers"],
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)
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response.raise_for_status()
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return response.json()
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async def _async_search_api_results(self, query: str, **kwargs: Any) -> dict:
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"""Use aiohttp to send request to SearchApi API and return results async."""
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request_details = self._prepare_request(query, **kwargs)
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if not self.aiosession:
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async with aiohttp.ClientSession() as session:
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async with session.get(
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url=request_details["url"],
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headers=request_details["headers"],
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params=request_details["params"],
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raise_for_status=True,
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) as response:
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results = await response.json()
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else:
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async with self.aiosession.get(
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url=request_details["url"],
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headers=request_details["headers"],
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params=request_details["params"],
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raise_for_status=True,
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) as response:
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results = await response.json()
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return results
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@staticmethod
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def _result_as_string(result: dict) -> str:
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toret = "No good search result found"
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if "answer_box" in result.keys() and "answer" in result["answer_box"].keys():
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toret = result["answer_box"]["answer"]
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elif "answer_box" in result.keys() and "snippet" in result["answer_box"].keys():
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toret = result["answer_box"]["snippet"]
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elif "knowledge_graph" in result.keys():
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toret = result["knowledge_graph"]["description"]
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elif "organic_results" in result.keys():
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snippets = [
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r["snippet"] for r in result["organic_results"] if "snippet" in r.keys()
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]
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toret = "\n".join(snippets)
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elif "jobs" in result.keys():
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jobs = [
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r["description"] for r in result["jobs"] if "description" in r.keys()
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]
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toret = "\n".join(jobs)
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elif "videos" in result.keys():
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videos = [
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f"""Title: "{r["title"]}" Link: {r["link"]}"""
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for r in result["videos"]
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if "title" in r.keys()
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]
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toret = "\n".join(videos)
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elif "images" in result.keys():
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images = [
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f"""Title: "{r["title"]}" Link: {r["original"]["link"]}"""
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for r in result["images"]
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if "original" in r.keys()
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]
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toret = "\n".join(images)
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return toret
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