3fi7dZddlmZddlmZddlmZmZddlm Z ddl m Z ddl m Z ddlmZdd lmZGd d eZGd d eZ ddZ ddZ ddZe dddGddeZy)z=Combine many documents together by recursively reducing them.) annotations)Callable)AnyProtocol) deprecated) Callbacks)Document) ConfigDict)BaseCombineDocumentsChainceZdZdZddZy)CombineDocsProtocol&Interface for the combine_docs method.c y)rNselfdocskwargss o/var/www/auto_recruiter/arenv/lib/python3.12/site-packages/langchain_classic/chains/combine_documents/reduce.py__call__zCombineDocsProtocol.__call__sNrlist[Document]rrreturnstr__name__ __module__ __qualname____doc__rrrrr r s 05rr ceZdZdZddZy)AsyncCombineDocsProtocolrc Kyw)z,Async interface for the combine_docs method.Nrrs rrz!AsyncCombineDocsProtocol.__call__ssNrrrrrr"r"s 0;rr"c g}g}|D]V}|j|||fi|}||kDs#t|dk(r d}t||j|dd|dd}X|j||S)aSplit `Document` objects to subsets that each meet a cumulative len. constraint. Args: docs: The full list of `Document` objects. length_func: Function for computing the cumulative length of a set of `Document` objects. token_max: The maximum cumulative length of any subset of `Document` objects. **kwargs: Arbitrary additional keyword params to pass to each call of the `length_func`. Returns: A `list[list[Document]]`. zLA single document was longer than the context length, we cannot handle this.N)appendlen ValueError) r length_func token_maxrnew_result_doc_list_sub_result_docsdoc _num_tokensmsgs rsplit_list_of_docsr1s& 5$!"2=f=  "#$).!o%  & &'7'< =/4  5/0 rc J||fi|}|djjDcic]\}}|t|}}}|ddD]G}|jjD](\}}||vr||xxd|z cc<t|||<*It||Scc}}w)Execute a collapse function on a set of documents and merge their metadatas. Args: docs: A list of `Document` objects to combine. combine_document_func: A function that takes in a list of `Document` objects and optionally addition keyword parameters and combines them into a single string. **kwargs: Arbitrary additional keyword params to pass to the `combine_document_func`. Returns: A single `Document` with the output of `combine_document_func` for the page content and the combined metadata's of all the input documents. All metadata values are strings, and where there are overlapping keys across documents the values are joined by `', '`. rr%N,  page_contentmetadatar7itemsrr rcombine_document_funcrresultkvcombined_metadatar.s r collapse_docsr@Cs*#4 26 2F/3Aw/?/?/E/E/GHtq!CFHHABx.LL&&( .DAq%%!!$"QC0$'*1v!!$  .. 2C DDIsBcfK||fi|d{}|djjDcic]\}}|t|}}}|ddD]G}|jjD](\}}||vr||xxd|z cc<t|||<*It||S7cc}}ww)r3Nrr%r4r5r8r:s racollapse_docsrBcs*)88 8F/3Aw/?/?/E/E/GHtq!CFHHABx.LL&&( .DAq%%!!$"QC0$'*1v!!$  .. 2C DD9Hs! B1B)$B1B+ A B1+B1z0.3.1z1.0zThis class is deprecated. Please see the migration guide here for a recommended replacement: https://python.langchain.com/docs/versions/migrating_chains/map_reduce_chain/)sinceremovalmessageceZdZUdZded< dZded< dZded < dZd ed < ed d Z e ddZ d ddZ d ddZ d ddZ d ddZe ddZy)ReduceDocumentsChaina Combine documents by recursively reducing them. This involves - `combine_documents_chain` - `collapse_documents_chain` `combine_documents_chain` is ALWAYS provided. This is final chain that is called. We pass all previous results to this chain, and the output of this chain is returned as a final result. `collapse_documents_chain` is used if the documents passed in are too many to all be passed to `combine_documents_chain` in one go. In this case, `collapse_documents_chain` is called recursively on as big of groups of documents as are allowed. Example: ```python from langchain_classic.chains import ( StuffDocumentsChain, LLMChain, ReduceDocumentsChain, ) from langchain_core.prompts import PromptTemplate from langchain_openai import OpenAI # This controls how each document will be formatted. Specifically, # it will be passed to `format_document` - see that function for more # details. document_prompt = PromptTemplate( input_variables=["page_content"], template="{page_content}" ) document_variable_name = "context" model = OpenAI() # The prompt here should take as an input variable the # `document_variable_name` prompt = PromptTemplate.from_template("Summarize this content: {context}") llm_chain = LLMChain(llm=model, prompt=prompt) combine_documents_chain = StuffDocumentsChain( llm_chain=llm_chain, document_prompt=document_prompt, document_variable_name=document_variable_name, ) chain = ReduceDocumentsChain( combine_documents_chain=combine_documents_chain, ) # If we wanted to, we could also pass in collapse_documents_chain # which is specifically aimed at collapsing documents BEFORE # the final call. prompt = PromptTemplate.from_template("Collapse this content: {context}") llm_chain = LLMChain(llm=model, prompt=prompt) collapse_documents_chain = StuffDocumentsChain( llm_chain=llm_chain, document_prompt=document_prompt, document_variable_name=document_variable_name, ) chain = ReduceDocumentsChain( combine_documents_chain=combine_documents_chain, collapse_documents_chain=collapse_documents_chain, ) ``` r combine_documents_chainNz BaseCombineDocumentsChain | Nonecollapse_documents_chaini intr+ int | Nonecollapse_max_retriesTforbid)arbitrary_types_allowedextracJ|j |jS|jS)N)rIrHrs r_collapse_chainz$ReduceDocumentsChain._collapse_chains&  ( ( 400 0+++rc r|j|f||d|\}}|jjd||d|S)aCombine multiple documents recursively. Args: docs: List of documents to combine, assumed that each one is less than `token_max`. token_max: Recursively creates groups of documents less than this number of tokens. callbacks: Callbacks to be passed through **kwargs: additional parameters to be passed to LLM calls (like other input variables besides the documents) Returns: The first element returned is the single string output. The second element returned is a dictionary of other keys to return. r+ callbacksrrUr) _collapserH combine_docsrrr+rUr result_docs_s rrXz!ReduceDocumentsChain.combine_docssb,(      Q 9t++88    rcK|j|f||d|d{\}}|jjd||d|d{S7.7w)aAsync combine multiple documents recursively. Args: docs: List of documents to combine, assumed that each one is less than `token_max`. token_max: Recursively creates groups of documents less than this number of tokens. callbacks: Callbacks to be passed through **kwargs: additional parameters to be passed to LLM calls (like other input variables besides the documents) Returns: The first element returned is the single string output. The second element returned is a dictionary of other keys to return. rTNrVr) _acollapserH acombine_docsrYs rr^z"ReduceDocumentsChain.acombine_docss|, /t       Q @T11??       s!AA )AA A Ac |}jj}||fi|}dfd }|xs j} d} |||| kDrwt||| fi|} | D cgc]} t | |fi|}} ||fi|}| dz } j r-| j k(rdj d| d} t | ||| kDrw|ifScc} w)NcBjjd|d|SN)input_documentsrUr)rRrunrrrUrs r_collapse_docs_funcz;ReduceDocumentsChain._collapse.._collapse_docs_func@s3+4''++ $# rrr%Exceed 7 tries to collapse document to  tokens.r)rH prompt_lengthr+r1r@rLr)rrr+rUrrZr* num_tokensre _token_maxretriesr,docs_r0s` ` rrWzReduceDocumentsChain._collapse5s 22@@  77  0$.. $j)@"4# # 1e%8CFCK%[;F;J qLG((W8Q8Q-Q 9 9:;..8\C o%!$j)@"BsB?cK|}jj}||fi|}dfd }|xs j} d} ||| kDrt||| fi|} | D cgc]} t | |fi|d{}} ||fi|}| dz } j r-| j k(rdj d| d} t | ||| kDr|ifS7[cc} ww)Nc^Kjjd|d|d{S7wra)rRarunrds rrez._collapse_docs_funcgsA2--22 $# s #-+-rr%rfrgrhr)rHrir+r1rBrLr)rjs` ` rr]zReduceDocumentsChain._acollapse\s' 22@@  77  0$.. $j)@"4# # 1%U,?J6JJJK%[;F;J qLG((W8Q8Q-Q 9 9:;..8\C o%!$j)@"BKs1ACC -C .C 4ACC C  Ccy)Nreduce_documents_chainrrQs r _chain_typez ReduceDocumentsChain._chain_types'r)rr )NN) rrr+rKrUrrrrztuple[str, dict]) rrr+rKrUrrrrztuple[list[Document], dict])rr)rrrr __annotations__rIr+rLr model_configpropertyrRrXr^rWr]rtrrrrGrGs>@76BF>E Is (,*+ $L ,,!%#            J!%#            J!%# %%% %  % % %T!%# %%% %  % % %N((rrGN) rrr*rr+rJrrrzlist[list[Document]])rrr;r rrrr )rrr;r"rrrr )r __future__rcollections.abcrtypingrrlangchain_core._apirlangchain_core.callbacksrlangchain_core.documentsr pydanticr /langchain_classic.chains.combine_documents.baser r r"r1r@rBrGrrrrsC"$ *.-U5(5;x;" """ "  "JE E.EE E@E E3EE E@   X y(4y(y(r