j8ddlmZddlZddlZddlmZmZmZmZddl m Z ddl m Z ddl mZejeZGddeZy) ) annotationsN)AnyListOptionalTuple)Document) Embeddings) VectorStoreczeZdZdZ ddZ d ddZ ddZdddZeddZ d ddZ d dd Z d d d Z d!d Z e d" d#d Zd$d Zd%dZd&dZd$dZd$dZd'dZd(dZy))Jaguara'`Jaguar API` vector store. See http://www.jaguardb.com See http://github.com/fserv/jaguar-sdk Example: .. code-block:: python from langchain_community.vectorstores.jaguar import Jaguar vectorstore = Jaguar( pod = 'vdb', store = 'mystore', vector_index = 'v', vector_type = 'cosine_fraction_float', vector_dimension = 1536, url='http://192.168.8.88:8080/fwww/', embedding=openai_model ) c||_||_||_||_||_||_ ddlm}|||_ d|_ y#t$r tdwxYw)Nr)JaguarHttpClientzrCould not import jaguardb-http-client python package. Please install it with `pip install -U jaguardb-http-client`) _pod_store _vector_index _vector_type_vector_dimension _embedding%jaguardb_http_client.JaguarHttpClientr ImportError_jag_token) selfpodstore vector_index vector_typevector_dimensionurl embeddingrs q/var/www/html/Fitness-lenito-AI-main/venv/lib/python3.12/site-packages/langchain_community/vectorstores/jaguar.py__init__zJaguar.__init__$sr  )'!1#  N%S)   O  s AAc|dk(r|jj}||_|jj||_|jdk(rt j dyy)aX login to jaguardb server with a jaguar_api_key or let self._jag find a key Args: pod (str): name of a Pod store (str): name of a vector store optional jaguar_api_key (str): API key of user to jaguardb server Returns: True if successful; False if not successful rz*E0001 error init(): invalid jaguar_api_keyFT)r getApiKey_jaguar_api_keyloginrloggererror)rjaguar_api_keys r"r'z Jaguar.login@sY R !YY002N-iioon5 ;;"  LLE Fc|jdz|jz} d}||z }|d|jd|jdz }|d|jdz }|d|d z }||d zz }|j |y ) z create the vector store on the backend database Args: metadata_str (str): columns and their types Returns: True if successful; False if not successful .z create store  (z vector(,z 'z'),z source char(256), v:text char(z),)N)rrrrrrun)r metadata_str text_sizepodstoreqs r"createz Jaguar.createWs99s?T[[0   X  r$$$%Xd.D.D-EQ GG r$##$C (( .yk << \C   r+c|jdk(rtjd|diS|jj ||j|}|j } t j|}|S#t$ricYSwxYw)z Run any query statement in jaguardb Args: query (str): query statement to jaguardb Returns: None for invalid token, or json result string rzE0005 error run(r0) rr(r)rposttextjsonloads Exception)rquerywithFileresptxtjss r"r1z Jaguar.runqsy ;;"  LL+E7!4 5Iyy~~eT[[(;ii CBI I sA66 BBc|jSN)rrs r" embeddingszJaguar.embeddingss r+Nc |j}|jdd}|jdd}|jdz|jzdz|z}d|z}|j |} | dk(rgS| d} |dk7r"g} |D]} | j |dz| z| }|j jt|} g}|d}| D]}|Dcgc] }t|}}d j|}|jdz|jz}d |zd z}||d z| zd z|zz }||jd d}|d|zdzz }|j |d} |j | d|dz }|Sd}| D]H}|Dcgc] }t|}}|j|||\}}}|dk7r-|jj|j|d}|sgcSd j|}|d |zz }d dj|zd z}|dd j|zd zz }|jdz|jz}d |zd z}||d z| zdz|zz }||jd d}|d|zdzz }|dk7r|j |d} n|j |d} |j | d|dz }K|Scc}wcc}w)a Add texts through the embeddings and add to the vectorstore. Args: texts: list of text strings to add to the jaguar vector store. metadatas: Optional list of metadatas associated with the texts. [{"m1": "v11", "m2": "v12", "m3": "v13", "filecol": "path_file1.jpg" }, {"m1": "v21", "m2": "v22", "m3": "v23", "filecol": "path_file2.jpg" }, {"m1": "v31", "m2": "v32", "m3": "v33", "filecol": "path_file3.jpg" }, {"m1": "v41", "m2": "v42", "m3": "v43", "filecol": "path_file4.jpg" }] kwargs: vector_index=name_of_vector_index file_column=name_of_file_column Returns: List of ids from adding the texts into the vectorstore file_columnrtext_tagr-ztextcol data rr/z insert into r.z ) values (''z\'z','')Fzid,'z ) values (T)rgetrrr1appendrembed_documentsliststrjoinreplace _parseMetarpostFiler)rtexts metadataskwargsvcolfilecolrH podstorevcolr5rAtextcol tag_textstrEidsivecxstr_vec values_commar4r@nvecvvecfilepathrc names_commas r" add_textszJaguar.add_textss*!!**]B/::j"-yy34s:TA  % XXa[ 8IV* r>I  C!!34E__44T%[A   A!+./3a3q63/"xx0 99s?T[[8"X-4TCZ')M9LHHAh&&sE2US[4''XXa' 2e9%Q"N 7A!+./3a3q63/'+y|W'M$dHb=++DKK1EB! !hhtn sTz) "UZZ%55; sxx'8 83 >> 99s?T[[8"X-4[3&0<?,NNAh&&sE2TCZ$&&b=!T*B!U+B 2e9%Q1"4 M00s K Kc |j}|j} |jj|} | D cgc] } t | } } dj | } |j dz|jz}d|zdz| zdzt |zdzt |zdz| z}|dz }||d|zz }|d j |}|d |zz }|d |zz }||d |zz }|j|}|gSg}|D]M}|d }|d}|d}i}||d<||D] }||}|||<t||}||f}|j|O|Scc} w)a Return Jaguar documents most similar to query, along with scores. Args: query: Text to look up documents similar to. k: Number of Documents to return. Defaults to 3. lambda_val: lexical match parameter for hybrid search. where: the where clause in select similarity. For example a where can be "rating > 3.0 and (state = 'NV' or state = 'CA')" args: extra options passed to select similarity kwargs: vector_index=vcol, vector_type=cosine_fraction_float Returns: List of Documents most similar to the query and score for each. List of Tuples of (doc, similarity_score): [ (doc, score), (doc, score), ...] r/r-zselect similarity(rOz','topk=z ,fetch_k=z,type=z,with_score=yes,with_text=yes&z ,metadata=z') from z where scorer9rM) page_contentmetadata) rrr embed_queryrTrUrrr1rrQ)rr=kfetch_kwhereargsrZr[r\vtyperEfstr_embeddingsqv_commar4r5metajarrdocs_with_scorerArpr9rMmdmmvdoctups r"similarity_search_with_scorez#Jaguar.similarity_search_with_scores2!!!!__007 *45*Q#a&*588N+99s?T[[0       !f     'l     ,,   tOA  88I&D $ $A Z( ""   U" "Axx{ <IBwKEf:DU)CBBuI$"AABBqE#r:C,C  " "3 '"e6sEc f|j|f|||d|}|Dcgc]\}}| c}}Scc}}w)a Return Jaguar documents most similar to query, along with scores. Args: query: Text to look up documents similar to. k: Number of Documents to return. Defaults to 5. where: the where clause in select similarity. For example a where can be "rating > 3.0 and (state = 'NV' or state = 'CA')" Returns: List of Documents most similar to the query )rtrvrZ)r) rr=rtrvrZr[docs_and_scoresr_s r"similarity_searchzJaguar.similarity_search-sK$<$;;  ey  1<KKNKKN& #''$Q#a&$'VX%%(s1C )rrTrrTrrTrrTrrr rTr!r )r)r* Optional[str]returnbool)r2rTr3rrNone)F)r=rTr>rrdict)rzOptional[Embeddings]rC)rY List[str]rZOptional[List[dict]]r[rrr)NNN)r=rTrtrrurrvrrwrrZOptional[List[str]]r[rrzList[Tuple[Document, float]])rNN) r=rTrtrrvrrZrr[rrzList[Document])r=rTr[rrrr)rYrr!r r rTrrTrrTrrTrrTrrrZrr*rr[rrr )rr)rrr[rrr)rr)rrTrr)rrr]rTrz Tuple[List[str], List[str], str])__name__ __module__ __qualname____doc__r#r'r6r1propertyrErmrrr classmethodrrrrrrrrWr+r"r r sj*      <)+% .  4* +/QQ(Q Q  Ql#")-NN N N  N  N'NN &Nf#)- 33 3 3 ' 3  3 3.  :+/(*     (& ,  &7&r+r ) __future__rr:loggingtypingrrrrlangchain_core.documentsrlangchain_core.embeddingsr langchain_core.vectorstoresr getLoggerrr(r rr+r"rs=" ---03   8 $y&[y&r+