mirror of
https://github.com/hwchase17/langchain
synced 2024-11-02 09:40:22 +00:00
86 lines
2.8 KiB
Python
86 lines
2.8 KiB
Python
"""Util that calls Google Lens Search."""
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from typing import Any, Dict, Optional, cast
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import requests
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from langchain_core.pydantic_v1 import BaseModel, Extra, SecretStr, root_validator
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from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
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class GoogleLensAPIWrapper(BaseModel):
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"""Wrapper for SerpApi's Google Lens API
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You can create SerpApi.com key by signing up at: https://serpapi.com/users/sign_up.
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The wrapper uses the SerpApi.com python package:
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https://serpapi.com/integrations/python
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To use, you should have the environment variable ``SERPAPI_API_KEY``
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set with your API key, or pass `serp_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 GoogleLensAPIWrapper
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google_lens = GoogleLensAPIWrapper()
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google_lens.run('langchain')
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"""
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serp_search_engine: Any
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serp_api_key: Optional[SecretStr] = None
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class Config:
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"""Configuration for this pydantic object."""
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extra = Extra.forbid
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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 and python package exists in environment."""
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values["serp_api_key"] = convert_to_secret_str(
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get_from_dict_or_env(values, "serp_api_key", "SERPAPI_API_KEY")
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)
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return values
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def run(self, query: str) -> str:
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"""Run query through Google Trends with Serpapi"""
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serpapi_api_key = cast(SecretStr, self.serp_api_key)
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params = {
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"engine": "google_lens",
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"api_key": serpapi_api_key.get_secret_value(),
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"url": query,
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}
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queryURL = f"https://serpapi.com/search?engine={params['engine']}&api_key={params['api_key']}&url={params['url']}"
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response = requests.get(queryURL)
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if response.status_code != 200:
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return "Google Lens search failed"
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responseValue = response.json()
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if responseValue["search_metadata"]["status"] != "Success":
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return "Google Lens search failed"
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xs = ""
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if len(responseValue["knowledge_graph"]) > 0:
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subject = responseValue["knowledge_graph"][0]
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xs += f"Subject:{subject['title']}({subject['subtitle']})\n"
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xs += f"Link to subject:{subject['link']}\n\n"
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xs += "Related Images:\n\n"
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for image in responseValue["visual_matches"]:
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xs += f"Title: {image['title']}\n"
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xs += f"Source({image['source']}): {image['link']}\n"
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xs += f"Image: {image['thumbnail']}\n\n"
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xs += (
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"Reverse Image Search"
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+ f"Link: {responseValue['reverse_image_search']['link']}\n"
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)
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print(xs) # noqa: T201
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docs = [xs]
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return "\n\n".join(docs)
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