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"""Util that calls Google Lens Search."""
from typing import Any, Dict, Optional, cast
import requests
from langchain_core.pydantic_v1 import BaseModel, Extra, SecretStr, root_validator
from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
class GoogleLensAPIWrapper(BaseModel):
"""Wrapper for SerpApi's Google Lens API
You can create SerpApi.com key by signing up at: https://serpapi.com/users/sign_up.
The wrapper uses the SerpApi.com python package:
https://serpapi.com/integrations/python
To use, you should have the environment variable ``SERPAPI_API_KEY``
set with your API key, or pass `serp_api_key` as a named parameter
to the constructor.
Example:
.. code-block:: python
from langchain_community.utilities import GoogleLensAPIWrapper
google_lens = GoogleLensAPIWrapper()
google_lens.run('langchain')
"""
serp_search_engine: Any
serp_api_key: Optional[SecretStr] = None
class Config:
"""Configuration for this pydantic object."""
extra = Extra.forbid
@root_validator()
def validate_environment(cls, values: Dict) -> Dict:
"""Validate that api key and python package exists in environment."""
values["serp_api_key"] = convert_to_secret_str(
get_from_dict_or_env(values, "serp_api_key", "SERPAPI_API_KEY")
)
return values
def run(self, query: str) -> str:
"""Run query through Google Trends with Serpapi"""
serpapi_api_key = cast(SecretStr, self.serp_api_key)
params = {
"engine": "google_lens",
"api_key": serpapi_api_key.get_secret_value(),
"url": query,
}
queryURL = f"https://serpapi.com/search?engine={params['engine']}&api_key={params['api_key']}&url={params['url']}"
response = requests.get(queryURL)
if response.status_code != 200:
return "Google Lens search failed"
responseValue = response.json()
if responseValue["search_metadata"]["status"] != "Success":
return "Google Lens search failed"
xs = ""
if (
"knowledge_graph" in responseValue
and len(responseValue["knowledge_graph"]) > 0
):
subject = responseValue["knowledge_graph"][0]
xs += f"Subject:{subject['title']}({subject['subtitle']})\n"
xs += f"Link to subject:{subject['link']}\n\n"
xs += "Related Images:\n\n"
for image in responseValue["visual_matches"]:
xs += f"Title: {image['title']}\n"
xs += f"Source({image['source']}): {image['link']}\n"
xs += f"Image: {image['thumbnail']}\n\n"
if "reverse_image_search" in responseValue:
xs += (
"Reverse Image Search"
+ f"Link: {responseValue['reverse_image_search']['link']}\n"
)
print(xs) # noqa: T201
docs = [xs]
return "\n\n".join(docs)
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