mirror of
https://github.com/hwchase17/langchain
synced 2024-11-02 09:40:22 +00:00
ed58eeb9c5
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
193 lines
6.4 KiB
Python
193 lines
6.4 KiB
Python
"""Util that calls Google Search using the Serper.dev API."""
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from typing import Any, Dict, List, 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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from typing_extensions import Literal
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class GoogleSerperAPIWrapper(BaseModel):
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"""Wrapper around the Serper.dev Google Search API.
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You can create a free API key at https://serper.dev.
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To use, you should have the environment variable ``SERPER_API_KEY``
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set with your API key, or pass `serper_api_key` as a named parameter
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to the constructor.
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Example:
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.. code-block:: python
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from langchain_community.utilities import GoogleSerperAPIWrapper
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google_serper = GoogleSerperAPIWrapper()
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"""
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k: int = 10
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gl: str = "us"
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hl: str = "en"
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# "places" and "images" is available from Serper but not implemented in the
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# parser of run(). They can be used in results()
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type: Literal["news", "search", "places", "images"] = "search"
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result_key_for_type = {
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"news": "news",
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"places": "places",
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"images": "images",
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"search": "organic",
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}
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tbs: Optional[str] = None
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serper_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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serper_api_key = get_from_dict_or_env(
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values, "serper_api_key", "SERPER_API_KEY"
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)
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values["serper_api_key"] = serper_api_key
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return values
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def results(self, query: str, **kwargs: Any) -> Dict:
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"""Run query through GoogleSearch."""
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return self._google_serper_api_results(
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query,
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gl=self.gl,
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hl=self.hl,
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num=self.k,
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tbs=self.tbs,
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search_type=self.type,
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**kwargs,
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)
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def run(self, query: str, **kwargs: Any) -> str:
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"""Run query through GoogleSearch and parse result."""
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results = self._google_serper_api_results(
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query,
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gl=self.gl,
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hl=self.hl,
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num=self.k,
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tbs=self.tbs,
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search_type=self.type,
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**kwargs,
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)
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return self._parse_results(results)
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async def aresults(self, query: str, **kwargs: Any) -> Dict:
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"""Run query through GoogleSearch."""
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results = await self._async_google_serper_search_results(
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query,
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gl=self.gl,
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hl=self.hl,
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num=self.k,
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search_type=self.type,
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tbs=self.tbs,
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**kwargs,
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)
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return results
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async def arun(self, query: str, **kwargs: Any) -> str:
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"""Run query through GoogleSearch and parse result async."""
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results = await self._async_google_serper_search_results(
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query,
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gl=self.gl,
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hl=self.hl,
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num=self.k,
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search_type=self.type,
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tbs=self.tbs,
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**kwargs,
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)
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return self._parse_results(results)
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def _parse_snippets(self, results: dict) -> List[str]:
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snippets = []
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if results.get("answerBox"):
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answer_box = results.get("answerBox", {})
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if answer_box.get("answer"):
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return [answer_box.get("answer")]
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elif answer_box.get("snippet"):
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return [answer_box.get("snippet").replace("\n", " ")]
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elif answer_box.get("snippetHighlighted"):
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return answer_box.get("snippetHighlighted")
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if results.get("knowledgeGraph"):
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kg = results.get("knowledgeGraph", {})
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title = kg.get("title")
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entity_type = kg.get("type")
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if entity_type:
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snippets.append(f"{title}: {entity_type}.")
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description = kg.get("description")
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if description:
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snippets.append(description)
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for attribute, value in kg.get("attributes", {}).items():
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snippets.append(f"{title} {attribute}: {value}.")
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for result in results[self.result_key_for_type[self.type]][: self.k]:
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if "snippet" in result:
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snippets.append(result["snippet"])
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for attribute, value in result.get("attributes", {}).items():
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snippets.append(f"{attribute}: {value}.")
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if len(snippets) == 0:
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return ["No good Google Search Result was found"]
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return snippets
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def _parse_results(self, results: dict) -> str:
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return " ".join(self._parse_snippets(results))
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def _google_serper_api_results(
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self, search_term: str, search_type: str = "search", **kwargs: Any
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) -> dict:
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headers = {
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"X-API-KEY": self.serper_api_key or "",
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"Content-Type": "application/json",
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}
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params = {
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"q": search_term,
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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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response = requests.post(
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f"https://google.serper.dev/{search_type}", headers=headers, params=params
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)
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response.raise_for_status()
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search_results = response.json()
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return search_results
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async def _async_google_serper_search_results(
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self, search_term: str, search_type: str = "search", **kwargs: Any
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) -> dict:
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headers = {
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"X-API-KEY": self.serper_api_key or "",
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"Content-Type": "application/json",
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}
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url = f"https://google.serper.dev/{search_type}"
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params = {
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"q": search_term,
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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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if not self.aiosession:
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async with aiohttp.ClientSession() as session:
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async with session.post(
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url, params=params, headers=headers, raise_for_status=False
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) as response:
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search_results = await response.json()
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else:
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async with self.aiosession.post(
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url, params=params, headers=headers, raise_for_status=True
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) as response:
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search_results = await response.json()
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return search_results
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