a `g:A@sdZddlmZddlZddlmZmZddlmZddl m Z m Z m Z ddl mZddlmZmZdd lmZdd lmZdd lmZmZmZmZdd lmZe rdd lmZmZm Z e!Z"e#eZ$ee"e$fZ%ee e$fZ&GdddeddZ'Gdddee"e$feZ(dS)a**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 --> Retriever # Examples: ArxivRetriever, MergerRetriever **Main helpers:** .. code-block:: RetrieverInput, RetrieverOutput, RetrieverLike, RetrieverOutputLike, Document, Serializable, Callbacks, CallbackManagerForRetrieverRun, AsyncCallbackManagerForRetrieverRun ) annotationsN)ABCabstractmethod) signature) TYPE_CHECKINGAnyOptional) ConfigDict)Self TypedDict) deprecated)Document)RunnableRunnableConfigRunnableSerializable ensure_config)run_in_executor)#AsyncCallbackManagerForRetrieverRunCallbackManagerForRetrieverRun Callbacksc@s2eZdZUdZded<ded<ded<ded<dS) LangSmithRetrieverParamsz!LangSmith parameters for tracing.strls_retriever_name Optional[str]Zls_vector_store_providerZls_embedding_providerZls_embedding_modelN)__name__ __module__ __qualname____doc____annotations__rrg/var/www/html/cobodadashboardai.evdpl.com/venv/lib/python3.9/site-packages/langchain_core/retrievers.pyr7s rF)totalc s0eZdZUdZeddZdZded<dZded<dZ d ed <dZ d ed <d ddfdd Z d ddddZ d1ddd ddddZ d2ddd ddddZedddddd Zdd!ddd"d#Zed$d%d&d'ddddd(dd)d d d*d dd+d,d-Zed$d.d&d'ddddd(dd)d d d*d dd+d/d0ZZS)3 BaseRetrievera? Abstract base class for a Document retrieval system. A retrieval system is defined as something that can take string queries and return the most 'relevant' Documents from some source. Usage: A retriever follows the standard Runnable interface, and should be used via the standard Runnable methods of `invoke`, `ainvoke`, `batch`, `abatch`. Implementation: When implementing a custom retriever, the class should implement the `_get_relevant_documents` method to define the logic for retrieving documents. Optionally, an async native implementations can be provided by overriding the `_aget_relevant_documents` method. Example: A retriever that returns the first 5 documents from a list of documents .. code-block:: python from langchain_core.documents import Document from langchain_core.retrievers import BaseRetriever from typing import List class SimpleRetriever(BaseRetriever): docs: List[Document] k: int = 5 def _get_relevant_documents(self, query: str) -> List[Document]: """Return the first k documents from the list of documents""" return self.docs[:self.k] async def _aget_relevant_documents(self, query: str) -> List[Document]: """(Optional) async native implementation.""" return self.docs[:self.k] Example: A simple retriever based on a scikit-learn vectorizer .. code-block:: python from sklearn.metrics.pairwise import cosine_similarity class TFIDFRetriever(BaseRetriever, BaseModel): vectorizer: Any docs: List[Document] tfidf_array: Any k: int = 4 class Config: arbitrary_types_allowed = True def _get_relevant_documents(self, query: str) -> List[Document]: # Ip -- (n_docs,x), Op -- (n_docs,n_Feats) query_vec = self.vectorizer.transform([query]) # Op -- (n_docs,1) -- Cosine Sim with each doc results = cosine_similarity(self.tfidf_array, query_vec).reshape((-1,)) return [self.docs[i] for i in results.argsort()[-self.k :][::-1]] T)Zarbitrary_types_allowedFbool_new_arg_supported_expects_other_argsNzOptional[list[str]]tagszOptional[dict[str, Any]]metadatarNone)kwargsreturnc stjfi||jtjkrBtjdtdd|j}tj|_||_t|dr||j tj kr|tjdtdd|j }tj |_ ||_ t |jj }| ddu|_|js|j tj krddd d d d }||_ tt|hd dk|_dS)NzgRetrievers must implement abstract `_get_relevant_documents` method instead of `get_relevant_documents`) stacklevelaget_relevant_documentsziRetrievers must implement abstract `_aget_relevant_documents` method instead of `aget_relevant_documents` run_managerr rlist[Document])selfqueryr*cstd|j|IdHS)N)r_get_relevant_documents)r0r1rrr _aget_relevant_documentsszABaseRetriever.__init_subclass__.._aget_relevant_documents>r0r1r.r)super__init_subclass__get_relevant_documentsr"warningswarnDeprecationWarningr2hasattrr-r3r parametersgetr$lensetkeysr%)clsr)ZswapZaswapr;r3 __class__rr r5sD    zBaseRetriever.__init_subclass__rcKsL|}|dr |dd}n|dr6|dd}|}t|d}|S)z Get standard params for tracing.Z Retriever Ni)r)get_name startswithendswithlowerr)r0r)Zdefault_retriever_nameZ ls_paramsrrr _get_ls_paramss    zBaseRetriever._get_ls_paramsrzOptional[RunnableConfig]r/)inputconfigr)r*c Ksddlm}t|}i|dp"i|jfi|}|j|dd|dd|d|j||jd }|jd||d p~| | d dd }zB|j r|ni}|j r|j |fd |i|} n|j |fi|} Wn2ty} z|| WYd} ~ nd} ~ 00|| | SdS)aInvoke the retriever to get relevant documents. Main entry point for synchronous retriever invocations. Args: input: The query string. config: Configuration for the retriever. Defaults to None. kwargs: Additional arguments to pass to the retriever. Returns: List of relevant documents. Examples: .. code-block:: python retriever.invoke("query") r)CallbackManagerr' callbacksNverboseFr&rMZinheritable_tagsZ local_tagsinheritable_metadataZlocal_metadatarun_namerun_idnamerQr.) langchain_core.callbacks.managerrKrr<rH configurer&r'on_retriever_startrDpopr%r$r2 Exceptionon_retriever_erroron_retriever_end) r0rIrJr)rKrOcallback_managerr._kwargsresulterrr invokesP      zBaseRetriever.invokec s4ddlm}t|}i|dp"i|jfi|}|j|dd|dd|d|j||jd }|jd||d p~| | d dd IdH}zN|j r|ni}|j r|j |fd |i|IdH} n|j |fi|IdH} Wn8ty} z|| IdHWYd} ~ nd} ~ 00|| IdH| SdS)aAsynchronously invoke the retriever to get relevant documents. Main entry point for asynchronous retriever invocations. Args: input: The query string. config: Configuration for the retriever. Defaults to None. kwargs: Additional arguments to pass to the retriever. Returns: List of relevant documents. Examples: .. code-block:: python await retriever.ainvoke("query") r)AsyncCallbackManagerr'rLNrMFr&rNrPrQrRr.)rTr`rr<rHrUr&r'rVrDrWr%r$r3rXrYrZ) r0rIrJr)r`rOr[r.r\r]r^rrr ainvokesP      zBaseRetriever.ainvoker)r1r.r*cCsdS)zGet documents relevant to a query. Args: query: String to find relevant documents for. run_manager: The callback handler to use. Returns: List of relevant documents. Nrr0r1r.rrr r2Psz%BaseRetriever._get_relevant_documentsrcstd|j||dIdHS)zAsynchronously get documents relevant to a query. Args: query: String to find relevant documents for run_manager: The callback handler to use Returns: List of relevant documents N)r.)rr2Zget_syncrbrrr r3^s z&BaseRetriever._aget_relevant_documentsz0.1.46r_z1.0)Zsince alternativeZremoval)rLr&r'rPrr)r1rLr&r'rPr)r*cKsHi}|r||d<|r||d<|r(||d<|r4||d<|j||fi|S)a Retrieve documents relevant to a query. Users should favor using `.invoke` or `.batch` rather than `get_relevant_documents directly`. Args: query: string to find relevant documents for. callbacks: Callback manager or list of callbacks. Defaults to None. tags: Optional list of tags associated with the retriever. These tags will be associated with each call to this retriever, and passed as arguments to the handlers defined in `callbacks`. Defaults to None. metadata: Optional metadata associated with the retriever. This metadata will be associated with each call to this retriever, and passed as arguments to the handlers defined in `callbacks`. Defaults to None. run_name: Optional name for the run. Defaults to None. kwargs: Additional arguments to pass to the retriever. Returns: List of relevant documents. rLr&r'rP)r_r0r1rLr&r'rPr)rJrrr r6ps!z$BaseRetriever.get_relevant_documentsracsNi}|r||d<|r||d<|r(||d<|r4||d<|j||fi|IdHS)aAsynchronously get documents relevant to a query. Users should favor using `.ainvoke` or `.abatch` rather than `aget_relevant_documents directly`. Args: query: string to find relevant documents for. callbacks: Callback manager or list of callbacks. tags: Optional list of tags associated with the retriever. These tags will be associated with each call to this retriever, and passed as arguments to the handlers defined in `callbacks`. Defaults to None. metadata: Optional metadata associated with the retriever. This metadata will be associated with each call to this retriever, and passed as arguments to the handlers defined in `callbacks`. Defaults to None. run_name: Optional name for the run. Defaults to None. kwargs: Additional arguments to pass to the retriever. Returns: List of relevant documents. rLr&r'rPN)rardrrr r-s!z%BaseRetriever.aget_relevant_documents)N)N)rrrrr Z model_configr$rr%r&r'r5rHr_rarr2r3r r6r- __classcell__rrrAr r"Ds: =    2 ??   + r"))r __future__rr7abcrrinspectrtypingrrrZpydanticr Ztyping_extensionsr r Zlangchain_core._apir Zlangchain_core.documentsr Zlangchain_core.runnablesrrrrZlangchain_core.runnables.configrrTrrrrZRetrieverInputlistZRetrieverOutputZ RetrieverLikeZRetrieverOutputLikerr"rrrr s&