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yorekyorek
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updates for FabCon 2025
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6 files changed

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6 files changed

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‎db/demo/00-orchestration.sql‎

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declare @result_type varchar(50)
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declare @result_query nvarchar(max)
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declare @error nvarchar(max)
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exec [web].[orchestrate_request]
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--'find the samples created in 2025',
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--'show the last 5 samples',
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--'samples used by Davide at FabCon 2025',
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--'langchain samples',
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@result_type output,
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@result_query output,
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@error output
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select @result_type as result_type, @result_query as result_query, @error as error
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print @result_query

‎db/demo/01-semantic_search.sql‎

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declare @response nvarchar(max);
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declare @retval int;
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declare @samples nvarchar(max)
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declare @error nvarchar(max)
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declare @text nvarchar(1000) =
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--'find the samples created in 2025';
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--'show the last 5 samples';
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--'samples used by Davide at FabCon 2025';
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--'langchain samples';
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--'agentic rag demos';
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declare @qv vector(1536)
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exec @retval = web.get_embedding @text, @qv output, @error output with result sets none
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if (@retval != 0) begin
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select @error as error;
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return;
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end
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select top(10)
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s.id,
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s.name,
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s.created_on,
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least(
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vector_distance('cosine', e.[embedding], @qv),
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vector_distance('cosine', ne.[embedding], @qv),
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vector_distance('cosine', de.[embedding], @qv)
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) as cosine_distance
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from
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dbo.samples s
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inner join
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dbo.samples_embeddings e on e.id = s.id
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left join
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dbo.samples_notes_embeddings ne on e.id = ne.id
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left join
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dbo.samples_details_embeddings de on e.id = de.id
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order by
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cosine_distance asc;

‎db/demo/02-find_samples.sql‎

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exec [web].[find_samples]
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--'find the samples created in 2025';
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--'show the last 5 samples';
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--'samples used by Davide at FabCon 2025';
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'langchain samples';
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--'agentic rag demos';
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‎db/sql/04-find_samples_fabricsql.sql‎

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create or alter procedure [web].[find_samples] @text nvarchar(1000), @k int = null
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as
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set nocount on;
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declare @response nvarchar(max), @cached_response nvarchar(max);
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declare @retval int;
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declare @samples nvarchar(max)
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declare @error nvarchar(max)
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if trim(@text) = '' return;
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/* Get the embedding for the requested text */
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declare @qv vector(1536)
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exec @retval = web.get_embedding @text, @qv output, @error output with result sets none
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if (@retval != 0) begin
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select @error as error;
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return;
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end
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/* Check in the semantic cache to see if a similar question has been already answered */
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delete from [dbo].[semantic_cache] where query_date < dateadd(hour, -1, sysdatetime())
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select top(1) *, vector_distance('cosine', @qv, embedding) as d
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into #c
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from [dbo].[semantic_cache] order by d;
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--select * from #c
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select top(1) @cached_response = response from #c where d < 0.25
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if (@cached_response is not null) set @response = @cached_response
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/* If no cached response is available then generate a fresh answer */
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if (@response is null) begin
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/* Orchestrate answer */
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declare @rt varchar(50), @rq nvarchar(max)
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exec @retval = [web].[orchestrate_request] @text, @rt output, @rq output, @error output with result sets none
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if (@retval != 0) begin
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select @error as error;
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return;
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end
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--print @rt
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--print @rq
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/* Find the samples using T-SQL */
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if (@rt = 'SQL') begin
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declare @trq nvarchar(max) = trim(replace(replace(@rq, char(13), ' '), char(10), ' '));
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if (@trq like '%INSERT %' or @trq like '%UPDATE %' or @trq like '%DELETE %' or @trq like '%DROP %' or @trq like '%ALTER %' or @trq like '%CREATE %') begin
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--select @trq
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select 'NL2SQL' as [error], -1 as [error_code], 'Unauthorized SQL command requested' as [response]
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return -1
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end
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--print @rq
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create table #ts (id int, [name] nvarchar(100), [description] nvarchar(max), notes nvarchar(max), details json, distance_score float);
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insert into #ts exec sp_executesql @rq
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set @samples = cast((select * from #ts for json auto) as nvarchar(max))
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--print @samples
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/* If not results coming from SQL execution, try SEMANTIC anyway */
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if (@samples is null) begin
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set @rt = 'SQL+SEMANTIC'
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end
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end
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/* Find the samples most similar to the requested topic */
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if (@rt like '%SEMANTIC%') begin
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set @k = coalesce(@k, 50)
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-- Semantic Search
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drop table if exists #ss;
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select top(@k)
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s.id,
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[name], [description], [notes], [details],
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least(
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vector_distance('cosine', e.[embedding], @qv),
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vector_distance('cosine', ne.[embedding], @qv),
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vector_distance('cosine', de.[embedding], @qv)
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) as cosine_distance
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into
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#s
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from
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dbo.samples s
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inner join
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dbo.samples_embeddings e on e.id = s.id
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left join
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dbo.samples_notes_embeddings ne on e.id = ne.id
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left join
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dbo.samples_details_embeddings de on e.id = de.id
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order by
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cosine_distance asc;
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/* Prepare the JSON string with relevant results to be sent to LLM for evaluation */
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set @samples = (
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select
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[id], [name], [description], [notes], [details],
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100 * (1-cosine_distance) as similiarity_score
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from #s
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order by similiarity_score desc for json path
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)
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end
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--select @samples;
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if (@samples is not null) begin
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exec @retval = [web].[generate_answer] @text, @samples, @response output, @error output with result sets none;
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if (@retval != 0) begin
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select @error as error;
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return;
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end
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end else begin
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set @samples = '[]'
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set @response = '{}'
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end
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/* Cache results */
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insert into dbo.semantic_cache (query, [action], samples, embedding, query_date, response)
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values (@text, @rt + isnull(':' + @rq, ''), @samples, @qv, sysdatetime(), @response)
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end
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--select @response;
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select
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s.id,
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sr.result_position,
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s.[name],
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s.[description],
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sr.sample_summary,
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sr.thoughts,
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s.[url]--,
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--s.distance_score
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from
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openjson(@response, '$.result.choices[0].message') with (
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content nvarchar(max) '$.content'
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) m
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cross apply
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openjson(m.content, '$.samples') with (
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id int,
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result_position int,
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sample_summary nvarchar(max),
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thoughts nvarchar(max)
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) as sr
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inner join
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dbo.samples as s on s.id = sr.id
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order by
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sr.result_position
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‎db/sql/04-find_samples_langchain.sql‎

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create or alter procedure [web].[find_samples_langchain] @text nvarchar(1000), @k int = 10
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as
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set nocount on;
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declare @response nvarchar(max), @cached_response nvarchar(max);
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declare @retval int;
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declare @samples nvarchar(max)
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declare @error nvarchar(max)
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if trim(@text) = '' return;
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-- Get the embedding for the requested text
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declare @qv vector(1536)
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exec @retval = web.get_embedding @text, @qv output, @error output with result sets none
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if (@retval != 0) begin
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select @error as error;
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return;
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end
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-- Semantic Search
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select top(@k)
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s.id,
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[name], [description], [notes], [details],
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least(
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vector_distance('cosine', e.[embedding], @qv),
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vector_distance('cosine', ne.[embedding], @qv),
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vector_distance('cosine', de.[embedding], @qv)
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) as cosine_distance
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from
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dbo.samples s
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inner join
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dbo.samples_embeddings e on e.id = s.id
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left join
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dbo.samples_notes_embeddings ne on e.id = ne.id
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left join
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dbo.samples_details_embeddings de on e.id = de.id
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order by
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cosine_distance asc
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‎db/utils-scripts/test.sql‎

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exec [web].[find_samples] 'rag sample'
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go
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exec [web].[find_samples_langchain] 'any samples used at FabCon 2025?'
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go

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