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v0.6.0
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aedc53bf86
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+1
-1
@@ -1,6 +1,6 @@
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name = "YiemAgent"
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uuid = "e012c34b-7f78-48e0-971c-7abb83b6f0a2"
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version = "0.6.0"
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version = "0.6.2"
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authors = ["narawat lamaiin <narawat@outlook.com>"]
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[deps]
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+1
-1
@@ -474,7 +474,7 @@ function think(a::T)::NamedTuple{(:thoughtdict, :result_raw), Tuple{OrderedDict,
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elseif thoughtdict["action_name"] == "SEARCH_WINE_DATABASE"
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@info "YiemAgent think() 5 " @__LINE__
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thoughtdict, result_raw = search_wine_database!(a, thoughtdict; useSQLLLM=true)
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thoughtdict, result_raw = search_wine_database!(a, thoughtdict; useSQLLLM=false)
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#WORKING result_raw will be a df. i need to get images so i can send to frontend
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else
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@info "YiemAgent think() 6 " @__LINE__
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+5
-11
@@ -519,11 +519,11 @@ function generatesql(a::T, searchterm::String,
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# provide similar sql only for the first attempt
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sql, distance = a.context.similarSQLVectorDB(searchterm)
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similarSQL_ = sql !== nothing ? sql : "None"
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# if sql is really close, just use it
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if similarSQL_ != "None" && distance <= 0.1
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return similarSQL_
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end
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# similarSQL_ = sql !== nothing ? sql : "None"
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# # if sql is really close, just use it
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# if similarSQL_ != "None" && distance <= 0.1
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# return similarSQL_
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# end
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#CHANGE use find_related_tables_for_user_question and inject only related table schema instead
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# of hard code table schema. CPU embedding is too slow. use embedding service on GPU.
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@@ -541,12 +541,6 @@ function generatesql(a::T, searchterm::String,
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<database_table_schema>
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$table_schema
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</database_table_schema>
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<possible SQL for user's search term>
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$similarSQL_
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</possible SQL for user's search term>
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<error_note>
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$errornote
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<error_note>
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</internal_context_for_assistant>
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"""
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input = context * searchterm
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