jFA>dZddlmZddlZddlmZmZddlmZddl m Z m Z m Z ddl mZddlmZmZmZdd lmZdd lmZdd lmZmZdd lmZdd lmZmZmZm Z ddl!m"Z"e rddlm#Z#m$Z$e%Z&e'eZ(ee&e(fZ)ee e(fZ*GddedZ+Gddee&e(feZ,y)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 TypedDictoverride) deprecated) Callbacks)AsyncCallbackManagerCallbackManager)Document)RunnableRunnableConfigRunnableSerializable ensure_config)run_in_executor)#AsyncCallbackManagerForRetrieverRunCallbackManagerForRetrieverRunc@eZdZUdZded< ded< ded< ded<y) LangSmithRetrieverParamsz!LangSmith parameters for tracing.strls_retriever_name Optional[str]ls_vector_store_providerls_embedding_providerls_embedding_modelN)__name__ __module__ __qualname____doc____annotations__c/var/www/html/Fitness-lenito-AI-main/venv/lib/python3.12/site-packages/langchain_core/retrievers.pyrr8s)+++ ((%%r(rF)totalceZdZUdZedZdZded<dZded<dZ d ed < dZ d ed < e dfd Z ddZ e d ddZe d ddZe ddZ d dZedddddddd d!dZedddddddd d!dZxZS)" BaseRetrieveraK 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 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)arbitrary_types_allowedFbool_new_arg_supported_expects_other_argsNOptional[list[str]]tagsOptional[dict[str, Any]]metadatac t|d i||jtjk7rDt j dt d|j}tj|_||_t|dra|jtjk7rDt j dt d|j}tj|_ ||_ t|jj}|jddu|_|js.|jtjk(r d d}||_ tt!|j#hdz d kD|_y) 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_managercLKtd|j|d{S7wN)r_get_relevant_documents)selfquerys r)_aget_relevant_documentszABaseRetriever.__init_subclass__.._aget_relevant_documentss$-T43O3OQVWWWWs $"$>r=r>r9rr')r=r r>rreturnlist[Document])super__init_subclass__get_relevant_documentsr,warningswarnDeprecationWarningr<hasattrr8r?r parametersgetr/lensetkeysr0)clskwargsswapaswaprIr? __class__s r)rCzBaseRetriever.__init_subclass__sd !+F+  % %)M)M M MM7"   --D44  &+/C ' C2 3++}/T/TT MM8"   //E55  ',1C (s::;FF !+ !>d!J&&,, 0V0VV X X#& X X ,DC ( JOO%&)II JQ N r(c |j}|jdr|dd}n|jdr|dd}|j}t |S)z Get standard params for tracing. Retriever Ni)r)get_name startswithendswithlowerr)r=_kwargsdefault_retriever_names r)_get_ls_paramszBaseRetriever._get_ls_paramss_!% ! , ,[ 9%;AB%? " # , ,[ 9%;CR%@ "!7!=!=!?':PQQr(c t|}i|jdxsi|jd i|}tj|jdd|jdd|jd|j ||j }|jd||jdxs|j|jd d } |jr|ni}|jr|j|fd |i|}n|j|fi|}|j||S#t$r} |j| d} ~ wwxYw) 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") r4 callbacksNverboseFr2r_inheritable_tags local_tagsinheritable_metadatalocal_metadatarun_namerun_idnamerfr9r')rrJr\r configurer2r4on_retriever_startrVpopr0r/r<on_retriever_end Exceptionon_retriever_error r=inputconfigrOrccallback_managerr9kwargs_resultes r)invokezBaseRetriever.invokesk.v& zz*%+ !d!!+F+ +44 JJ{ # JJy%0#ZZ/yy!5== '99  J':4==?::h- :   $ 8 8fbG&&555'26=655eGwG  ( ( M   * *1 -  sAD22 E;E  Ec Kt|}i|jdxsi|jd i|}tj|jdd|jdd|jd|j ||j }|jd||jdxs|j|jd d d{} |jr|ni}|jr|j|fd |i|d{}n|j|fi|d{}|j|d{|S7u7=7#7 #t$r } |j| d{7d} ~ wwxYww) 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") r4r^Nr_Fr2r`rerfrgr9r')rrJr\rrir2r4rjrVrkr0r/r?rlrmrnros r)ainvokezBaseRetriever.ainvokes4v& zz*%+ !d!!+F+ 099 JJ{ # JJy%0#ZZ/yy!5== -??  J':4==?::h- @    $ 8 8fbG&&r9s r)r<z%BaseRetriever._get_relevant_documentsTsr(clKtd|j||jd{S7w)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)r9)rr<get_syncrzs r)r?z&BaseRetriever._aget_relevant_documentsbs:%   ( ( #,,.     s +424z0.1.46rvz1.0)since alternativeremoval)r^r2r4rec fi}|r||d<|r||d<|r||d<|r||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. r^r2r4re)rvr=r>r^r2r4rerOrqs r)rDz$BaseRetriever.get_relevant_documentsusUB"$ "+F;  !F6N !)F:  !)F: t{{5&3F33r(rxcKi}|r||d<|r||d<|r||d<|r||d<|j||fi|d{S7w)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. r^r2r4reN)rxrs r)r8z%BaseRetriever.aget_relevant_documentss_B"$ "+F;  !F6N !)F:  !)F: !T\\%:6::::s 6?=?)rOrr@None)rZrr@rr;)rprrqzOptional[RunnableConfig]rOrr@rA)r>rr9rr@rA)r>rr9rr@rA)r>rr^rr2r1r4r3rerrOrr@rA)r"r#r$r%r model_configr/r&r0r2r4r rCr\rvrxrr<r?rrDr8 __classcell__)rRs@r)r,r,Es>@ $L %$ %% $D $ *.H&-0 0 d R=A99":9MP9 99v,0<<)< <  <<|    *H        *M  &hHeD $$(-1"&)4)4 )4 " )4 + )4 )4)4 )4E)4VhIuE $$(-1"&);); ); " ); + ); );); );F);r(r,)-r% __future__rrEabcrrinspectrtypingrrr pydanticr typing_extensionsr r r langchain_core._apirlangchain_core.callbacksr langchain_core.callbacks.managerrrlangchain_core.documentsrlangchain_core.runnablesrrrrlangchain_core.runnables.configrrrrRetrieverInputlistRetrieverOutput RetrieverLikeRetrieverOutputLikerr,r'r(r)rs*##//77*.R- < x.89 sO34 y F;()HI3F;r(