langchain/libs/community/langchain_community/retrievers/__init__.py
Robert Caulk 54adcd9e82
community[minor]: add AskNews retriever and AskNews tool (#21581)
We add a tool and retriever for the [AskNews](https://asknews.app)
platform with example notebooks.

The retriever can be invoked with:

```py
from langchain_community.retrievers import AskNewsRetriever

retriever = AskNewsRetriever(k=3)

retriever.invoke("impact of fed policy on the tech sector")
```

To retrieve 3 documents in then news related to fed policy impacts on
the tech sector. The included notebook also includes deeper details
about controlling filters such as category and time, as well as
including the retriever in a chain.

The tool is quite interesting, as it allows the agent to decide how to
obtain the news by forming a query and deciding how far back in time to
look for the news:

```py
from langchain_community.tools.asknews import AskNewsSearch
from langchain import hub
from langchain.agents import AgentExecutor, create_openai_functions_agent
from langchain_openai import ChatOpenAI

tool = AskNewsSearch()

instructions = """You are an assistant."""
base_prompt = hub.pull("langchain-ai/openai-functions-template")
prompt = base_prompt.partial(instructions=instructions)
llm = ChatOpenAI(temperature=0)
asknews_tool = AskNewsSearch()
tools = [asknews_tool]
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(
    agent=agent,
    tools=tools,
    verbose=True,
)

agent_executor.invoke({"input": "How is the tech sector being affected by fed policy?"})
```

---------

Co-authored-by: Emre <e@emre.pm>
2024-05-20 18:23:06 -07:00

243 lines
9.1 KiB
Python

"""**Retriever** class returns Documents given a text **query**.
It is more general than a vector store. A retriever does not need to be able to
store documents, only to return (or retrieve) it. Vector stores can be used as
the backbone of a retriever, but there are other types of retrievers as well.
**Class hierarchy:**
.. code-block::
BaseRetriever --> <name>Retriever # Examples: ArxivRetriever, MergerRetriever
**Main helpers:**
.. code-block::
Document, Serializable, Callbacks,
CallbackManagerForRetrieverRun, AsyncCallbackManagerForRetrieverRun
"""
import importlib
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from langchain_community.retrievers.arcee import (
ArceeRetriever,
)
from langchain_community.retrievers.arxiv import (
ArxivRetriever,
)
from langchain_community.retrievers.asknews import (
AskNewsRetriever,
)
from langchain_community.retrievers.azure_ai_search import (
AzureAISearchRetriever,
AzureCognitiveSearchRetriever,
)
from langchain_community.retrievers.bedrock import (
AmazonKnowledgeBasesRetriever,
)
from langchain_community.retrievers.bm25 import (
BM25Retriever,
)
from langchain_community.retrievers.breebs import (
BreebsRetriever,
)
from langchain_community.retrievers.chaindesk import (
ChaindeskRetriever,
)
from langchain_community.retrievers.chatgpt_plugin_retriever import (
ChatGPTPluginRetriever,
)
from langchain_community.retrievers.cohere_rag_retriever import (
CohereRagRetriever,
)
from langchain_community.retrievers.docarray import (
DocArrayRetriever,
)
from langchain_community.retrievers.dria_index import (
DriaRetriever,
)
from langchain_community.retrievers.elastic_search_bm25 import (
ElasticSearchBM25Retriever,
)
from langchain_community.retrievers.embedchain import (
EmbedchainRetriever,
)
from langchain_community.retrievers.google_cloud_documentai_warehouse import (
GoogleDocumentAIWarehouseRetriever,
)
from langchain_community.retrievers.google_vertex_ai_search import (
GoogleCloudEnterpriseSearchRetriever,
GoogleVertexAIMultiTurnSearchRetriever,
GoogleVertexAISearchRetriever,
)
from langchain_community.retrievers.kay import (
KayAiRetriever,
)
from langchain_community.retrievers.kendra import (
AmazonKendraRetriever,
)
from langchain_community.retrievers.knn import (
KNNRetriever,
)
from langchain_community.retrievers.llama_index import (
LlamaIndexGraphRetriever,
LlamaIndexRetriever,
)
from langchain_community.retrievers.metal import (
MetalRetriever,
)
from langchain_community.retrievers.milvus import (
MilvusRetriever,
)
from langchain_community.retrievers.outline import (
OutlineRetriever,
)
from langchain_community.retrievers.pinecone_hybrid_search import (
PineconeHybridSearchRetriever,
)
from langchain_community.retrievers.pubmed import (
PubMedRetriever,
)
from langchain_community.retrievers.qdrant_sparse_vector_retriever import (
QdrantSparseVectorRetriever,
)
from langchain_community.retrievers.rememberizer import (
RememberizerRetriever,
)
from langchain_community.retrievers.remote_retriever import (
RemoteLangChainRetriever,
)
from langchain_community.retrievers.svm import (
SVMRetriever,
)
from langchain_community.retrievers.tavily_search_api import (
TavilySearchAPIRetriever,
)
from langchain_community.retrievers.tfidf import (
TFIDFRetriever,
)
from langchain_community.retrievers.thirdai_neuraldb import NeuralDBRetriever
from langchain_community.retrievers.vespa_retriever import (
VespaRetriever,
)
from langchain_community.retrievers.weaviate_hybrid_search import (
WeaviateHybridSearchRetriever,
)
from langchain_community.retrievers.web_research import WebResearchRetriever
from langchain_community.retrievers.wikipedia import (
WikipediaRetriever,
)
from langchain_community.retrievers.you import (
YouRetriever,
)
from langchain_community.retrievers.zep import (
ZepRetriever,
)
from langchain_community.retrievers.zilliz import (
ZillizRetriever,
)
_module_lookup = {
"AmazonKendraRetriever": "langchain_community.retrievers.kendra",
"AmazonKnowledgeBasesRetriever": "langchain_community.retrievers.bedrock",
"ArceeRetriever": "langchain_community.retrievers.arcee",
"ArxivRetriever": "langchain_community.retrievers.arxiv",
"AskNewsRetriever": "langchain_community.retrievers.asknews",
"AzureAISearchRetriever": "langchain_community.retrievers.azure_ai_search",
"AzureCognitiveSearchRetriever": "langchain_community.retrievers.azure_ai_search",
"BM25Retriever": "langchain_community.retrievers.bm25",
"BreebsRetriever": "langchain_community.retrievers.breebs",
"ChaindeskRetriever": "langchain_community.retrievers.chaindesk",
"ChatGPTPluginRetriever": "langchain_community.retrievers.chatgpt_plugin_retriever",
"CohereRagRetriever": "langchain_community.retrievers.cohere_rag_retriever",
"DocArrayRetriever": "langchain_community.retrievers.docarray",
"DriaRetriever": "langchain_community.retrievers.dria_index",
"ElasticSearchBM25Retriever": "langchain_community.retrievers.elastic_search_bm25",
"EmbedchainRetriever": "langchain_community.retrievers.embedchain",
"GoogleCloudEnterpriseSearchRetriever": "langchain_community.retrievers.google_vertex_ai_search", # noqa: E501
"GoogleDocumentAIWarehouseRetriever": "langchain_community.retrievers.google_cloud_documentai_warehouse", # noqa: E501
"GoogleVertexAIMultiTurnSearchRetriever": "langchain_community.retrievers.google_vertex_ai_search", # noqa: E501
"GoogleVertexAISearchRetriever": "langchain_community.retrievers.google_vertex_ai_search", # noqa: E501
"KNNRetriever": "langchain_community.retrievers.knn",
"KayAiRetriever": "langchain_community.retrievers.kay",
"LlamaIndexGraphRetriever": "langchain_community.retrievers.llama_index",
"LlamaIndexRetriever": "langchain_community.retrievers.llama_index",
"MetalRetriever": "langchain_community.retrievers.metal",
"MilvusRetriever": "langchain_community.retrievers.milvus",
"OutlineRetriever": "langchain_community.retrievers.outline",
"PineconeHybridSearchRetriever": "langchain_community.retrievers.pinecone_hybrid_search", # noqa: E501
"PubMedRetriever": "langchain_community.retrievers.pubmed",
"QdrantSparseVectorRetriever": "langchain_community.retrievers.qdrant_sparse_vector_retriever", # noqa: E501
"RememberizerRetriever": "langchain_community.retrievers.rememberizer",
"RemoteLangChainRetriever": "langchain_community.retrievers.remote_retriever",
"SVMRetriever": "langchain_community.retrievers.svm",
"TFIDFRetriever": "langchain_community.retrievers.tfidf",
"TavilySearchAPIRetriever": "langchain_community.retrievers.tavily_search_api",
"VespaRetriever": "langchain_community.retrievers.vespa_retriever",
"WeaviateHybridSearchRetriever": "langchain_community.retrievers.weaviate_hybrid_search", # noqa: E501
"WebResearchRetriever": "langchain_community.retrievers.web_research",
"WikipediaRetriever": "langchain_community.retrievers.wikipedia",
"YouRetriever": "langchain_community.retrievers.you",
"ZepRetriever": "langchain_community.retrievers.zep",
"ZillizRetriever": "langchain_community.retrievers.zilliz",
"NeuralDBRetriever": "langchain_community.retrievers.thirdai_neuraldb",
}
def __getattr__(name: str) -> Any:
if name in _module_lookup:
module = importlib.import_module(_module_lookup[name])
return getattr(module, name)
raise AttributeError(f"module {__name__} has no attribute {name}")
__all__ = [
"AmazonKendraRetriever",
"AmazonKnowledgeBasesRetriever",
"ArceeRetriever",
"ArxivRetriever",
"AskNewsRetriever",
"AzureAISearchRetriever",
"AzureCognitiveSearchRetriever",
"BM25Retriever",
"BreebsRetriever",
"ChaindeskRetriever",
"ChatGPTPluginRetriever",
"CohereRagRetriever",
"DocArrayRetriever",
"DriaRetriever",
"ElasticSearchBM25Retriever",
"EmbedchainRetriever",
"GoogleCloudEnterpriseSearchRetriever",
"GoogleDocumentAIWarehouseRetriever",
"GoogleVertexAIMultiTurnSearchRetriever",
"GoogleVertexAISearchRetriever",
"KayAiRetriever",
"KNNRetriever",
"LlamaIndexGraphRetriever",
"LlamaIndexRetriever",
"MetalRetriever",
"MilvusRetriever",
"NeuralDBRetriever",
"OutlineRetriever",
"PineconeHybridSearchRetriever",
"PubMedRetriever",
"QdrantSparseVectorRetriever",
"RememberizerRetriever",
"RemoteLangChainRetriever",
"SVMRetriever",
"TavilySearchAPIRetriever",
"TFIDFRetriever",
"VespaRetriever",
"WeaviateHybridSearchRetriever",
"WebResearchRetriever",
"WikipediaRetriever",
"YouRetriever",
"ZepRetriever",
"ZillizRetriever",
]