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
138 lines
4.9 KiB
Python
138 lines
4.9 KiB
Python
"""Util that calls Google Search."""
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from typing import Any, Dict, List, Optional
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from langchain_core.pydantic_v1 import BaseModel, Extra, root_validator
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from langchain_core.utils import get_from_dict_or_env
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class GoogleSearchAPIWrapper(BaseModel):
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"""Wrapper for Google Search API.
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Adapted from: Instructions adapted from https://stackoverflow.com/questions/
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37083058/
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programmatically-searching-google-in-python-using-custom-search
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TODO: DOCS for using it
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1. Install google-api-python-client
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- If you don't already have a Google account, sign up.
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- If you have never created a Google APIs Console project,
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read the Managing Projects page and create a project in the Google API Console.
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- Install the library using pip install google-api-python-client
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2. Enable the Custom Search API
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- Navigate to the APIs & Services→Dashboard panel in Cloud Console.
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- Click Enable APIs and Services.
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- Search for Custom Search API and click on it.
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- Click Enable.
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URL for it: https://console.cloud.google.com/apis/library/customsearch.googleapis
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.com
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3. To create an API key:
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- Navigate to the APIs & Services → Credentials panel in Cloud Console.
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- Select Create credentials, then select API key from the drop-down menu.
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- The API key created dialog box displays your newly created key.
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- You now have an API_KEY
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Alternatively, you can just generate an API key here:
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https://developers.google.com/custom-search/docs/paid_element#api_key
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4. Setup Custom Search Engine so you can search the entire web
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- Create a custom search engine here: https://programmablesearchengine.google.com/.
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- In `What to search` to search, pick the `Search the entire Web` option.
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After search engine is created, you can click on it and find `Search engine ID`
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on the Overview page.
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"""
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search_engine: Any #: :meta private:
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google_api_key: Optional[str] = None
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google_cse_id: Optional[str] = None
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k: int = 10
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siterestrict: bool = False
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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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def _google_search_results(self, search_term: str, **kwargs: Any) -> List[dict]:
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cse = self.search_engine.cse()
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if self.siterestrict:
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cse = cse.siterestrict()
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res = cse.list(q=search_term, cx=self.google_cse_id, **kwargs).execute()
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return res.get("items", [])
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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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google_api_key = get_from_dict_or_env(
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values, "google_api_key", "GOOGLE_API_KEY"
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)
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values["google_api_key"] = google_api_key
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google_cse_id = get_from_dict_or_env(values, "google_cse_id", "GOOGLE_CSE_ID")
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values["google_cse_id"] = google_cse_id
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try:
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from googleapiclient.discovery import build
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except ImportError:
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raise ImportError(
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"google-api-python-client is not installed. "
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"Please install it with `pip install google-api-python-client"
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">=2.100.0`"
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)
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service = build("customsearch", "v1", developerKey=google_api_key)
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values["search_engine"] = service
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return values
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def run(self, query: str) -> str:
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"""Run query through GoogleSearch and parse result."""
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snippets = []
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results = self._google_search_results(query, num=self.k)
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if len(results) == 0:
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return "No good Google Search Result was found"
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for result in results:
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if "snippet" in result:
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snippets.append(result["snippet"])
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return " ".join(snippets)
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def results(
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self,
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query: str,
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num_results: int,
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search_params: Optional[Dict[str, str]] = None,
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) -> List[Dict]:
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"""Run query through GoogleSearch and return metadata.
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Args:
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query: The query to search for.
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num_results: The number of results to return.
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search_params: Parameters to be passed on search
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Returns:
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A list of dictionaries with the following keys:
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snippet - The description of the result.
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title - The title of the result.
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link - The link to the result.
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"""
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metadata_results = []
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results = self._google_search_results(
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query, num=num_results, **(search_params or {})
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)
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if len(results) == 0:
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return [{"Result": "No good Google Search Result was found"}]
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for result in results:
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metadata_result = {
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"title": result["title"],
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"link": result["link"],
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}
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if "snippet" in result:
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metadata_result["snippet"] = result["snippet"]
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metadata_results.append(metadata_result)
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return metadata_results
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