[{"data":1,"prerenderedAt":3647},["ShallowReactive",2],{"\u002Fdevelopers\u002Fapi-docs\u002Fpathway-io\u002Fweaviate-app":3,"navigation-developers":963,"\u002Fdevelopers\u002Fapi-docs\u002Fpathway-io\u002Fweaviate":2954,"surr-\u002Fdevelopers\u002Fapi-docs\u002Fpathway-io\u002Fweaviate":3644},{"id":4,"title":5,"author":6,"body":7,"description":954,"extension":955,"meta":956,"navigation":723,"path":958,"seo":959,"sitemap":960,"stem":961,"__hash__":962},"content\u002F2.developers\u002F5.API-docs\u002F7.pathway-io\u002F470.weaviate.md","pw.io.weaviate",null,{"type":8,"value":9,"toc":947},"minimark",[10,14,31,43,48,75,81,85,100,104,118,235,250,264,279,290,464,467,473,480,629,632,825,828,943],[11,12,5],"h1",{"id":13},"pwioweaviate",[15,16,17,18,25,26,30],"p",{},"Pathway writes tables to a ",[19,20,24],"a",{"href":21,"rel":22},"https:\u002F\u002Fweaviate.io\u002F",[23],"nofollow","Weaviate"," collection with\n",[27,28,29],"code",{},"pw.io.weaviate.write",". The connector keeps the collection in sync with the\ntable: additions and updates upsert objects, and deletions remove them. The\ntarget collection must already exist — the connector never creates or alters its\nschema or vector index.",[15,32,33,37,38,42],{},[34,35,36],"strong",{},"NOTE",": This connector is available when using one of the following licenses only:\nPathway Live Data Framework Scale, Pathway Live Data Framework Enterprise. See\nthe ",[19,39,41],{"href":40},"\u002Fpricing","pricing page"," for details.",[44,45,47],"h2",{"id":46},"object-identity","Object identity",[15,49,50,51,54,55,58,59,62,63,66,67,70,71,74],{},"Weaviate addresses every object by a UUID. When a ",[27,52,53],{},"primary_key"," column is given,\nits value is encoded in that UUID exactly as ",[27,56,57],{},"weaviate.util.generate_uuid5"," does\n(",[27,60,61],{},"uuid5(NAMESPACE_DNS, str(key))","), so re-writing the same key upserts in place\nand the row for a key ",[27,64,65],{},"k"," can always be fetched with\n",[27,68,69],{},"collection.query.fetch_object_by_id(generate_uuid5(k))",". The key column is not\nstored as a property, which also lets it be named ",[27,72,73],{},"id"," — a name Weaviate\notherwise reserves and forbids as a property.",[15,76,77,78,80],{},"When ",[27,79,53],{}," is omitted, the UUID is derived from the row’s internal\nPathway key instead. Objects are still upserted in place, but there is no\ncolumn-value-based UUID to look them up by.",[44,82,84],{"id":83},"authentication","Authentication",[15,86,87,88,91,92,95,96,99],{},"Pass ",[27,89,90],{},"api_key"," to authenticate with Weaviate. Extra request headers can be\nsupplied through ",[27,93,94],{},"headers"," — for example to provide the API key of a\nserver-side vectorizer module (",[27,97,98],{},"{\"X-OpenAI-Api-Key\": \"...\"}",").",[44,101,103],{"id":102},"type-mapping","Type mapping",[15,105,106,107,109,110,113,114,117],{},"Every column other than ",[27,108,53],{}," and ",[27,111,112],{},"vector"," becomes an object property.\nWith Weaviate’s auto-schema, Pathway types are stored as follows. Declaring a\nproperty explicitly in the collection’s schema overrides this with the declared\ntype (for example, declare a property as ",[27,115,116],{},"int"," to preserve integer typing).",[119,120,121,137],"table",{},[122,123,124],"thead",{},[125,126,127,131,134],"tr",{},[128,129,130],"th",{},"Pathway type",[128,132,133],{},"Weaviate property type",[128,135,136],{},"Notes",[138,139,140,158,171,185,199,213],"tbody",{},[125,141,142,147,152],{},[143,144,145],"td",{},[27,146,116],{},[143,148,149],{},[27,150,151],{},"number",[143,153,154,155,157],{},"Stored as a number under auto-schema (read back as a float); declare the property as ",[27,156,116],{}," in the collection to keep integer typing.",[125,159,160,165,169],{},[143,161,162],{},[27,163,164],{},"float",[143,166,167],{},[27,168,151],{},[143,170],{},[125,172,173,178,183],{},[143,174,175],{},[27,176,177],{},"bool",[143,179,180],{},[27,181,182],{},"boolean",[143,184],{},[125,186,187,192,197],{},[143,188,189],{},[27,190,191],{},"str",[143,193,194],{},[27,195,196],{},"text",[143,198],{},[125,200,201,206,210],{},[143,202,203],{},[27,204,205],{},"bytes",[143,207,208],{},[27,209,196],{},[143,211,212],{},"Base64-encoded.",[125,214,215,224,229],{},[143,216,217,220,221],{},[27,218,219],{},"list[float]"," \u002F ",[27,222,223],{},"list[int]",[143,225,226],{},[27,227,228],{},"number[]",[143,230,231,232,234],{},"When the column is not the one passed as ",[27,233,112],{},".",[15,236,237,238,240,241,243,244,246,247,249],{},"The column passed as ",[27,239,112],{}," is stored as the object’s vector embedding (kept\nas 32-bit floats), not as a property. When ",[27,242,112],{}," is omitted, objects are\nwritten without an explicit vector — appropriate when the collection has a\nserver-side vectorizer. Weaviate reserves the property names ",[27,245,73],{}," and\n",[27,248,112],{},", so a non-key, non-vector column with either name is rejected.",[44,251,253,256,257,263],{"id":252},"pathway.io.weaviate.write",[34,254,255],{},"write","(",[258,259,262],"span",{"className":260},[261],"sphinx-paramslist","table, collection_name, *, primary_key=None, vector=None, http_host='localhost', http_port=8080, http_secure=False, api_key=None, headers=None, batch_size=100, concurrency=8, name=None, sort_by=None",")",[15,265,266,274,275,278],{},[19,267,271],{"className":268,"href":270},[269],"sphinx-source-url","https:\u002F\u002Fgithub.com\u002Fpathwaycom\u002Fpathway\u002Ftree\u002Fmain\u002Fpython\u002Fpathway\u002Fio\u002Fweaviate\u002F__init__.py#L16-L179",[258,272,273],{},"source","Writes a Pathway Live Data Framework table to a ",[19,276,24],{"href":21,"rel":277},[23],"\ncollection.",[15,280,281,282,285,286,289],{},"Each row addition (",[27,283,284],{},"diff = 1",") upserts an object and each row deletion\n(",[27,287,288],{},"diff = -1",") removes it, keeping the collection in sync with the table. The\ntarget collection must already exist. See the connector documentation for how\nobjects are identified, how each Pathway type is stored, and how to authenticate.",[291,292,293,456],"ul",{},[294,295,296,299],"li",{},[34,297,298],{},"Parameters",[291,300,301,313,321,342,358,366,374,385,394,414,422,430,440],{},[294,302,303,305,306,312],{},[34,304,119],{}," (",[19,307,309],{"href":308},"\u002Fdevelopers\u002Fapi-docs\u002Fpathway-table#pathway.Table",[27,310,311],{},"Table",") – The table to write.",[294,314,315,305,318,320],{},[34,316,317],{},"collection_name",[27,319,191],{},") – Name of the Weaviate collection to write to. It must\nalready exist.",[294,322,323,305,325,331,332,335,336,339,340,234],{},[34,324,53],{},[19,326,328],{"href":327},"\u002Fdevelopers\u002Fapi-docs\u002Fpathway#pathway.ColumnReference",[27,329,330],{},"ColumnReference"," | ",[27,333,334],{},"None",") – An optional column reference (e.g. ",[27,337,338],{},"table.doc_id",") whose\nvalues are used to derive each object’s UUID; the column is not stored\nas a property. When omitted, the UUID is derived from the row’s internal\nPathway key. The column must belong to ",[27,341,119],{},[294,343,344,305,346,331,350,335,352,355,356,234],{},[34,345,112],{},[19,347,348],{"href":327},[27,349,330],{},[27,351,334],{},[27,353,354],{},"table.embedding",") holding the\nvector embedding for each object. When given, that column is written as\nthe object’s vector and not as a property. The column must belong to\n",[27,357,119],{},[294,359,360,305,363,365],{},[34,361,362],{},"http_host",[27,364,191],{},") – Host of the Weaviate server.",[294,367,368,305,371,373],{},[34,369,370],{},"http_port",[27,372,116],{},") – Port of the Weaviate server.",[294,375,376,305,379,381,382,99],{},[34,377,378],{},"http_secure",[27,380,177],{},") – Whether the connection uses TLS (",[27,383,384],{},"https",[294,386,387,305,389,331,391,393],{},[34,388,90],{},[27,390,191],{},[27,392,334],{},") – An optional API key used to authenticate with Weaviate.",[294,395,396,305,398,401,402,404,405,407,408,410,411,413],{},[34,397,94],{},[27,399,400],{},"dict","[",[27,403,191],{},", ",[27,406,191],{},"] | ",[27,409,334],{},") – Optional additional headers sent with every request, e.g.\n",[27,412,98],{}," to authorize a server-side vectorizer.",[294,415,416,305,419,421],{},[34,417,418],{},"batch_size",[27,420,116],{},") – Number of objects grouped together per write.",[294,423,424,305,427,429],{},[34,425,426],{},"concurrency",[27,428,116],{},") – Maximum number of writes performed in parallel per worker.",[294,431,432,305,435,331,437,439],{},[34,433,434],{},"name",[27,436,191],{},[27,438,334],{},") – A unique name for the connector. If provided, this name will be used\nin logs and monitoring dashboards.",[294,441,442,305,445,401,448,401,451,455],{},[34,443,444],{},"sort_by",[27,446,447],{},"Optional",[27,449,450],{},"Iterable",[19,452,453],{"href":327},[27,454,330],{},"]]) – If specified, the output within each mini-batch will be sorted in\nascending order by the given columns. When multiple columns are\nprovided, the corresponding value tuples are compared lexicographically.",[294,457,458,461,334],{},[34,459,460],{},"Returns",[462,463],"br",{},[15,465,466],{},"Example:",[15,468,469,470,99],{},"Suppose you are building a document search pipeline and want to store embeddings\nin Weaviate running locally (e.g. via the official Docker image, which serves\nits API on port ",[27,471,472],{},"8080",[15,474,475,476,479],{},"Create the collection before starting the pipeline. 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weaviate",[258,511,234],{"class":512},"sAklC",[258,514,515],{"class":499},"classes",[258,517,234],{"class":512},[258,519,520],{"class":499},"config ",[258,522,496],{"class":495},[258,524,525],{"class":499}," Configure  \n",[258,527,529,532,535,537,539,543,546],{"class":491,"line":528},3,[258,530,531],{"class":499},"client ",[258,533,534],{"class":512},"=",[258,536,509],{"class":499},[258,538,234],{"class":512},[258,540,542],{"class":541},"sdLwU","connect_to_local",[258,544,545],{"class":512},"()",[258,547,548],{"class":499},"  \n",[258,550,552,555,557,561,563,566,568],{"class":491,"line":551},4,[258,553,554],{"class":499},"client",[258,556,234],{"class":512},[258,558,560],{"class":559},"s-wAU","collections",[258,562,234],{"class":512},[258,564,565],{"class":541},"create",[258,567,256],{"class":512},[258,569,548],{"class":541},[258,571,573,576,580,583],{"class":491,"line":572},5,[258,574,575],{"class":512},"    \"",[258,577,579],{"class":578},"sfyAc","Docs",[258,581,582],{"class":512},"\"",[258,584,585],{"class":512},",\n",[258,587,589,593,595,598,600,603,605,607],{"class":491,"line":588},6,[258,590,592],{"class":591},"s7ZW3","    vectorizer_config",[258,594,534],{"class":512},[258,596,597],{"class":541},"Configure",[258,599,234],{"class":512},[258,601,602],{"class":559},"Vectorizer",[258,604,234],{"class":512},[258,606,478],{"class":541},[258,608,609],{"class":512},"(),\n",[258,611,613],{"class":491,"line":612},7,[258,614,615],{"class":512},")\n",[258,617,619,621,623,626],{"class":491,"line":618},8,[258,620,554],{"class":499},[258,622,234],{"class":512},[258,624,625],{"class":541},"close",[258,627,628],{"class":512},"()\n",[15,630,631],{},"Define your Pathway Live Data Framework schema and build the table:",[481,633,635],{"className":483,"code":634,"language":485,"meta":486,"style":486},"import pathway as pw\nclass DocSchema(pw.Schema):\n    doc_id: int = 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.sx098{--shiki-default:#F78C6C}",{"title":486,"searchDepth":503,"depth":503,"links":948},[949,950,951,952],{"id":46,"depth":503,"text":47},{"id":83,"depth":503,"text":84},{"id":102,"depth":503,"text":103},{"id":252,"depth":503,"text":953},"write(table, collection_name, *, primary_key=None, vector=None, http_host='localhost', http_port=8080, http_secure=False, api_key=None, headers=None, batch_size=100, concurrency=8, name=None, sort_by=None)","Pathway writes tables to a Weaviate collection with\npw.io.weaviate.write. 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