langchain/libs/community/langchain_community/utilities/google_serper.py
Bagatur ed58eeb9c5
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
2023-12-11 13:53:30 -08:00

193 lines
6.4 KiB
Python

"""Util that calls Google Search using the Serper.dev API."""
from typing import Any, Dict, List, Optional
import aiohttp
import requests
from langchain_core.pydantic_v1 import BaseModel, root_validator
from langchain_core.utils import get_from_dict_or_env
from typing_extensions import Literal
class GoogleSerperAPIWrapper(BaseModel):
"""Wrapper around the Serper.dev Google Search API.
You can create a free API key at https://serper.dev.
To use, you should have the environment variable ``SERPER_API_KEY``
set with your API key, or pass `serper_api_key` as a named parameter
to the constructor.
Example:
.. code-block:: python
from langchain_community.utilities import GoogleSerperAPIWrapper
google_serper = GoogleSerperAPIWrapper()
"""
k: int = 10
gl: str = "us"
hl: str = "en"
# "places" and "images" is available from Serper but not implemented in the
# parser of run(). They can be used in results()
type: Literal["news", "search", "places", "images"] = "search"
result_key_for_type = {
"news": "news",
"places": "places",
"images": "images",
"search": "organic",
}
tbs: Optional[str] = None
serper_api_key: Optional[str] = None
aiosession: Optional[aiohttp.ClientSession] = None
class Config:
"""Configuration for this pydantic object."""
arbitrary_types_allowed = True
@root_validator()
def validate_environment(cls, values: Dict) -> Dict:
"""Validate that api key exists in environment."""
serper_api_key = get_from_dict_or_env(
values, "serper_api_key", "SERPER_API_KEY"
)
values["serper_api_key"] = serper_api_key
return values
def results(self, query: str, **kwargs: Any) -> Dict:
"""Run query through GoogleSearch."""
return self._google_serper_api_results(
query,
gl=self.gl,
hl=self.hl,
num=self.k,
tbs=self.tbs,
search_type=self.type,
**kwargs,
)
def run(self, query: str, **kwargs: Any) -> str:
"""Run query through GoogleSearch and parse result."""
results = self._google_serper_api_results(
query,
gl=self.gl,
hl=self.hl,
num=self.k,
tbs=self.tbs,
search_type=self.type,
**kwargs,
)
return self._parse_results(results)
async def aresults(self, query: str, **kwargs: Any) -> Dict:
"""Run query through GoogleSearch."""
results = await self._async_google_serper_search_results(
query,
gl=self.gl,
hl=self.hl,
num=self.k,
search_type=self.type,
tbs=self.tbs,
**kwargs,
)
return results
async def arun(self, query: str, **kwargs: Any) -> str:
"""Run query through GoogleSearch and parse result async."""
results = await self._async_google_serper_search_results(
query,
gl=self.gl,
hl=self.hl,
num=self.k,
search_type=self.type,
tbs=self.tbs,
**kwargs,
)
return self._parse_results(results)
def _parse_snippets(self, results: dict) -> List[str]:
snippets = []
if results.get("answerBox"):
answer_box = results.get("answerBox", {})
if answer_box.get("answer"):
return [answer_box.get("answer")]
elif answer_box.get("snippet"):
return [answer_box.get("snippet").replace("\n", " ")]
elif answer_box.get("snippetHighlighted"):
return answer_box.get("snippetHighlighted")
if results.get("knowledgeGraph"):
kg = results.get("knowledgeGraph", {})
title = kg.get("title")
entity_type = kg.get("type")
if entity_type:
snippets.append(f"{title}: {entity_type}.")
description = kg.get("description")
if description:
snippets.append(description)
for attribute, value in kg.get("attributes", {}).items():
snippets.append(f"{title} {attribute}: {value}.")
for result in results[self.result_key_for_type[self.type]][: self.k]:
if "snippet" in result:
snippets.append(result["snippet"])
for attribute, value in result.get("attributes", {}).items():
snippets.append(f"{attribute}: {value}.")
if len(snippets) == 0:
return ["No good Google Search Result was found"]
return snippets
def _parse_results(self, results: dict) -> str:
return " ".join(self._parse_snippets(results))
def _google_serper_api_results(
self, search_term: str, search_type: str = "search", **kwargs: Any
) -> dict:
headers = {
"X-API-KEY": self.serper_api_key or "",
"Content-Type": "application/json",
}
params = {
"q": search_term,
**{key: value for key, value in kwargs.items() if value is not None},
}
response = requests.post(
f"https://google.serper.dev/{search_type}", headers=headers, params=params
)
response.raise_for_status()
search_results = response.json()
return search_results
async def _async_google_serper_search_results(
self, search_term: str, search_type: str = "search", **kwargs: Any
) -> dict:
headers = {
"X-API-KEY": self.serper_api_key or "",
"Content-Type": "application/json",
}
url = f"https://google.serper.dev/{search_type}"
params = {
"q": search_term,
**{key: value for key, value in kwargs.items() if value is not None},
}
if not self.aiosession:
async with aiohttp.ClientSession() as session:
async with session.post(
url, params=params, headers=headers, raise_for_status=False
) as response:
search_results = await response.json()
else:
async with self.aiosession.post(
url, params=params, headers=headers, raise_for_status=True
) as response:
search_results = await response.json()
return search_results