+#hvddlZddlZddlmZddlmZmZddlZddlZddl m Z GddejZ y)N) defaultdict)ListUnion) Predictionc beZdZdZdfd Zd deeeefdedede jfdZ xZ S) DatabricksRMa A retrieval module that uses Databricks Vector Search Endpoint to return the top-k embeddings for a given query. Args: databricks_index_name (str): Databricks vector search index to query databricks_endpoint (str): Databricks index endpoint url databricks_token (str): Databricks authentication token columns (list[str]): Column names to include in response filters_json (str, optional): JSON string for query filters k (int, optional): Number of top embeddings to retrieve. Defaults to 3. docs_id_column_name (str, optional): Column name for retrieved doc_ids to return. text_column_name (str, optional): Column name for retrieved text to return. Examples: Below is a code snippet that shows how to configure Databricks Vector Search endpoints: (example adapted from "Databricks: How to create and query a Vector Search Index: https://docs.databricks.com/en/generative-ai/create-query-vector-search.html#create-a-vector-search-index) ```python from databricks.vector_search.client import VectorSearchClient #Creating Vector Search Client client = VectorSearchClient() client.create_endpoint( name="your_vector_search_endpoint_name", endpoint_type="STANDARD" ) #Creating Vector Search Index using Python SDK #Example for Direct Vector Access Index index = client.create_direct_access_index( endpoint_name="your_databricks_host_url", index_name="your_index_name", primary_key="id", embedding_dimension=1024, embedding_vector_column="text_vector", schema={ "id": "int", "field2": "str", "field3": "float", "text_vector": "array"} ) llm = dspy.OpenAI(model="gpt-3.5-turbo") retriever_model = DatabricksRM(databricks_index_name = "your_index_name", databricks_endpoint = "your_databricks_host_url", databricks_token = "your_databricks_token", columns= ["id", "field2", "field3", "text_vector"], k=3) dspy.settings.configure(lm=llm, rm=retriever_model) ``` Below is a code snippet that shows how to query the Databricks Direct Vector Access Index using the forward() function. ```python self.retrieve = DatabricksRM(query=[1, 2, 3], query_type = 'vector') ``` c t |||s*tjj ds t d|s*tjj ds t d|s t d|s t d|r|ntjd|_|r|ntjd|_||_||_ ||_ ||_ ||_ ||_ y)N)kDATABRICKS_TOKENzMYou must supply databricks_token or set environment variable DATABRICKS_TOKENDATABRICKS_HOSTzOYou must supply databricks_endpoint or set environment variable DATABRICKS_HOSTz!You must supply vector index namezFYou must specify a list of column names to be included in the response)super__init__osenvironget ValueErrordatabricks_tokendatabricks_endpointdatabricks_index_namecolumns filters_jsonr docs_id_column_nametext_column_name) selfrrrrrr rr __class__s X/var/www/html/sandstorm/venv/lib/python3.12/site-packages/dspy/retrieve/databricks_rm.pyrzDatabricksRM.__init__Gs 1 7I(Jlm m"2::>>:K+Lno o$@A Aef f4D 0"**UgJh:M#6SUS]S]^oSp %:" (#6 0query query_typerreturncd|jdd}|j|jd}|dk(r!t|ts t d||d<n1|dk(r!t|t s t d ||d <n t d |r|n |j|d <tj|jd |jd||}|j}tt}g} d\} } |ddD]} t|dd| D]\} }| d|j k(r^|j dk(r3tj"|}| j%t |dn| j%t ||} | d|j&k(r|} | ddk(s|} || xx| z cc<t)|j+ddd|j}t-|Dcgc]\}}| c}}| Scc}}w)aSearch with Databricks Vector Search Client for self.k top results for query Args: query (Union[str, List[float]]): query to search for. query_type (str): 'vector' for Direct Vector Access Index and Delta Sync Index using self-managed vectors or 'text' for Delta Sync Index using model endpoint. Returns: dspy.Prediction: An object containing the retrieved results. zBearer zapplication/json) Authorizationz Content-Type)r num_resultsvectorz/Query must be a list of floats for query_vector query_vectortextz%Query must be a string for query_text query_textz5Invalid query type specified. Use 'vector' or 'text'.rz/api/2.0/vector-search/indexes/z/query)jsonheaders)NNresult data_arraymanifestrnamemetadata document_idscorec |dS)N)xs rz&DatabricksRM.forward..s 1rT)keyreverseN)docsdoc_ids)rrr isinstancelistrstrrrequestspostrrr(rfloatziprloadsappendrsorteditemsr)rrrrr)payloadresponseresultsr8r9r&r0data_rowcolval docs_dict sorted_docsdoc_s rforwardzDatabricksRM.forwardZs 't'<'<&=>.  ||66   !eT* !RSS&+GN # 6 !eS) !HII$)GL !TU U2>,DDUDU==''((GHbHbGcci j  --/5! e),7 H 3I >I Sv;$":":://:=$(JJsO s9]+C'DEs3x0Dv;$"7"77Dv;')E  J% J TZZ\~tLWdffU +>Q>'RR>s% G; )NNNNNidr&)r&N) __name__ __module__ __qualname____doc__rrr<rr?dspyrrO __classcell__)rs@rrr sJ9t1&9SU3U #349S#9S^a9Smqm|m|9Srr) r(r collectionsrtypingrrr=rVdspy.primitives.predictionrRetrieverr3rrr\s. # 1GS4==GSr