m iZRddlZddlZddlmZddlmZmZddlmZddl m Z ddl m Z ddl mZddlmZdd lmZdd lmZdd lmZdd lmZejeZGd de eeZedgdZdeedeefdZ GddeZ!dS)N)Sequence)#AsyncCallbackManagerForRetrieverRunCallbackManagerForRetrieverRun)Document)BaseLanguageModel)BaseOutputParser)BasePromptTemplate)PromptTemplate) BaseRetriever)Runnable)override)LLMChainc>eZdZdZededeefdZdS)LineListOutputParserz"Output parser for a list of lines.textreturnc|d}ttd|S)N )stripsplitlistfilter)selfrliness C:\Users\Dell Inspiron 16\Desktop\tws\AgrotaPowerBi\back-agrota-powerbi\mcp-client-agrota\venv\Lib\site-packages\langchain_classic/retrievers/multi_query.pyparsezLineListOutputParser.parses5 ""4((F4''(((N)__name__ __module__ __qualname____doc__r strrrrrrrsJ,, )#)$s))))X)))rrquestionaYou are an AI language model assistant. Your task is to generate 3 different versions of the given user question to retrieve relevant documents from a vector database. By generating multiple perspectives on the user question, your goal is to help the user overcome some of the limitations of distance-based similarity search. Provide these alternative questions separated by newlines. Original question: {question})input_variablestemplate documentsrc:fdtDS)Nc2g|]\}}|d|v|S)Nr#).0idocr's r z%_unique_documents...s/ O O OFAsc2A26N6NC6N6N6Nr) enumerate)r's`r_unique_documentsr/-s% O O O Oi 22 O O OOrceZdZUdZeed<eed<dZeed<dZ e ed< dZ eed < e e d dfded ed ede d zd ed df dZde ded eefdZde ded ee fdZdee ded eefdZde ded eefdZde ded ee fdZdee ded eefdZdeed eefdZd S)MultiQueryRetrieverzGiven a query, use an LLM to write a set of queries. Retrieve docs for each query. Return the unique union of all retrieved docs. retriever llm_chainTverboser parser_keyFinclude_originalNllmpromptrcJt}||z|z}||||S)aRInitialize from llm using default template. Args: retriever: retriever to query documents from llm: llm for query generation using DEFAULT_QUERY_PROMPT prompt: The prompt which aims to generate several different versions of the given user query parser_key: DEPRECATED. `parser_key` is no longer used and should not be specified. include_original: Whether to include the original query in the list of generated queries. Returns: MultiQueryRetriever )r2r3r6)r)clsr2r7r8r5r6 output_parserr3s rfrom_llmzMultiQueryRetriever.from_llm?s?0-.. SL=0 s-    rquery run_managercK|||d{V}|jr|||||d{V}||S)Get relevant documents given a user query. Args: query: user query run_manager: the callback handler to use. Returns: Unique union of relevant documents from all generated queries N)agenerate_queriesr6appendaretrieve_documents unique_unionrr=r>queriesr's r_aget_relevant_documentsz,MultiQueryRetriever._aget_relevant_documents_s..ukBBBBBBBB   " NN5 ! ! !227KHHHHHHHH   +++rr$cK|jd|id|id{V}t|jtr|dn|}|jrt d||S)zGenerate queries based upon user input. 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