a bg8@svddlmZddlZddlZddlmZmZmZmZddl m Z ddl m Z ddl mZeeZGdddeZdS) ) annotationsN)AnyListOptionalTuple)Document) Embeddings) VectorStorec@sjeZdZdZddddddddddZdEd d d d d ZddddddZdFdd ddddZeddddZ dGdddddd d!Z dHdddd d d$dd%d&d'd(Z dIddd d$dd)d*d+d,Z ddd d-d.d/Z edJdddddddddd ddd0 d1d2Zddd3d4Zdddd5d6d7Zddd8d9Zddd:d;Zdddd?d@ZdddAdBdCdDZdS)KJaguara'`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 ) strintr)podstore vector_index vector_typevector_dimensionurl embeddingc Csd||_||_||_||_||_||_zddlm}WntyNtdYn0|||_ d|_ dS)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 _embeddingZ%jaguardb_http_client.JaguarHttpClientr ImportError_jag_token) selfr rrrrrrrr u/var/www/html/cobodadashboardai.evdpl.com/venv/lib/python3.9/site-packages/langchain_community/vectorstores/jaguar.py__init__$s    zJaguar.__init__rz Optional[str]bool)jaguar_api_keyreturncCsB|dkr|j}||_|j||_|jdkr>tddSdS)aX login to jaguardb server with a jaguar_api_key or let self._jag find a key Args: pod (str): name of a Pod store (str): name of a vector store optional jaguar_api_key (str): API key of user to jaguardb server Returns: True if successful; False if not successful rz*E0001 error init(): invalid jaguar_api_keyFT)rZ getApiKeyZ_jaguar_api_keyloginrloggererror)rr$r r r!r&@s   z Jaguar.loginNone) metadata_str text_sizer%cCsr|jd|j}d}||7}|d|jd|jd7}|d|jd7}|d|d 7}||d 7}||d S) 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)rr*r+podstoreqr r r!createWs  z Jaguar.createFdict)querywithFiler%cCsd|jdkr td|diS|j||j|}|j}zt|}|WSty^iYS0dS)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(r/N) rr'r(rposttextjsonloads Exception)rr5r6resptxtjsr r r!r0qs   z Jaguar.runzOptional[Embeddings])r%cCs|jSN)rrr r r! embeddingsszJaguar.embeddingsNz List[str]zOptional[List[dict]]r)texts metadataskwargsr%cKsv|j}|dd}|dd}|jd|jd|}d|}||} | dkrTgS| d} |dkrg} |D]} | |d| ql| }|jt|} g}|durFd }| D]}d d |D}d |}|jd|j}d |d}||d | d|7}|| dd}|d|d7}||d} || d|d7}qn,d }| D] }dd |D}| |||\}}}|dkr|j |j|d}|sgSd |}|d |7}dd |d}|dd |d7}|jd|j}d |d}||d | d|7}|| dd}|d|d7}|dkrL||d} n ||d} || d|d7}qN|S)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 Z file_columnrtext_tagr,ztextcol data NrcSsg|] }t|qSr r .0xr r r! z$Jaguar.add_texts..r.z insert into r-z ) values (''z\'z','')FzidcSsg|] }t|qSr rHrIr r r!rLrM,'z ) values (T)rgetrrr0appendrZembed_documentslistjoinreplace _parseMetarZpostFiler)rrBrCrDvcolfilecolrEZ podstorevcolr2r>ZtextcolZ tag_textstrAZidsiZvecZstr_vecZ values_commar1r=nvecvvecfilepathrcZ names_commar r r! add_textssh               zJaguar.add_textszOptional[List[str]]zList[Tuple[Document, float]])r5kfetch_kwhereargsrCrDr%cKsZ|j}|j} |j|} dd| D} d| } |jd|j} d|d| dt|dt|d | }|d 7}|d ur|d|7}|d urd |}|d |7}|d| 7}|d ur|d|7}||}|d urgSg}|D]l}|d}|d}|d}i}||d<|d ur6|D]}||}|||<qt ||d}||f}| |q|S)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), ...] cSsg|] }t|qSr rHrJfr r r!rLrMz7Jaguar.similarity_search_with_score..r.r,zselect similarity(rRz','topk=z ,fetch_k=z,type=z,with_score=yes,with_text=yesN&z ,metadata=z') from z where scorer8rP)Z page_contentmetadata) rrr embed_queryrVrrr r0rrT)rr5rdrerfrgrCrDrYvtyperAstr_embeddingsqv_commar1r2metaZjarrZdocs_with_scorer>rkr8rPmdmmvdoctupr r r!similarity_search_with_scoresj              z#Jaguar.similarity_search_with_scorezList[Document])r5rdrfrCrDr%cKs(|j|f|||d|}dd|DS)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 )rdrfrCcSsg|] \}}|qSr r )rJru_r r r!rLBrMz,Jaguar.similarity_search..)rw)rr5rdrfrCrDZdocs_and_scoresr r r!similarity_search-szJaguar.similarity_search)r5rDr%c Ks|j}|j}|j|}dd|D}d|}|jd|j}d|d|d|d} | d |7} || } t| t rt | d krd St | d } | d d krdSd S)z Detect if given text is anomalous from the dataset Args: query: Text to detect if it is anomaly Returns: True or False cSsg|] }t|qSr rHrhr r r!rLSrMz'Jaguar.is_anomalous..r.r,zselect anomalous(z, 'z ', 'type=rOz from rFZ anomalousZYEST) rrrrmrVrrr0 isinstancerUlenr9r:) rr5rDrYrnrArorpr1r2r>jdr r r! is_anomalousDs      zJaguar.is_anomalous) rBrrr rrrrrCr$rDr%c Ks>||||||||} | | | | j|| fi| | Sr?)r&clearra) clsrBrrr rrrrrCr$rDZjagstorer r r! from_textsas zJaguar.from_textscCs&|jd|j}d|}||dS)z\ Delete all records in jaguardb Args: No args Returns: None r,ztruncate store Nrrr0rr1r2r r r!r~xsz Jaguar.clear)zidsrDr%cKs<|jd|j}|D]"}d|d|d}||qdS)z Delete records in jaguardb by a list of zero-ids Args: pod (str): name of a Pod ids (List[str]): a list of zid as string Returns: Do not return anything r,z delete from z where zid='rNNr)rrrDr1rPr2r r r!deletes z Jaguar.deletecCsV|jd|j}d|}||}t|trr|r r r!counts z Jaguar.countcCs&|jd|j}d|}||dS)z` Drop or remove a store in jaguardb Args: no args Returns: None r,z drop store Nrrr r r!dropsz Jaguar.dropcCs|j|jdS)zY Logout to cleanup resources Args: no args Returns: None N)rlogoutrr@r r r!rsz Jaguar.logout)msgr%cCsBtdd$}td||ddWdn1s40YdS)Nz/tmp/debugjaguar.logazmsg=T)fileflush)openprint)rrrr r r!prts z Jaguar.prtz Tuple[List[str], List[str], str])nvmaprZr%c Csd}|dkr&t|}t|}n^g}g}||vrV|||||||}|D]$\}}||kr^||||q^dd|D}|||fS)NrcSsg|] }t|qSr rH)rJer r r!rLrMz%Jaguar._parseMeta..)rUkeysvaluesrTitems) rrrZr_r]r^rdvZvvec_sr r r!rXs     zJaguar._parseMeta)r)F)N)rbrcNNN)rbNN)Nr)__name__ __module__ __qualname____doc__r"r&r3r0propertyrArarwryr} classmethodrr~rrrrrrXr r r r!r s@VS (  r ) __future__rr9loggingtypingrrrrZlangchain_core.documentsrZlangchain_core.embeddingsrZlangchain_core.vectorstoresr getLoggerrr'r r r r r!s