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Author SHA1 Message Date
ton aedc53bf86 Merge pull request 'update' (#17) from v0.6.0-output_text_image into main
Reviewed-on: #17
2026-07-15 05:17:56 +00:00
ton 286da3cf2c update 2026-07-15 12:16:59 +07:00
ton 7fa988313d Merge pull request 'update' (#16) from v0.6.0-output_text_image into main
Reviewed-on: #16
2026-07-15 05:15:31 +00:00
ton e5b19dd268 update 2026-07-15 12:14:32 +07:00
ton 0df4159261 Merge pull request 'update' (#15) from v0.6.0-output_text_image into main
Reviewed-on: #15
2026-07-15 05:11:05 +00:00
ton 45e8ded111 update 2026-07-15 12:10:36 +07:00
ton 9167ece0c0 Merge pull request 'v0.6.0' (#14) from v0.6.0 into main
Reviewed-on: #14
2026-07-15 04:57:47 +00:00
ton f45a036971 Merge pull request 'v0.6.0' (#12) from v0.6.0 into main
Reviewed-on: #12
2026-07-15 04:38:48 +00:00
3 changed files with 7 additions and 13 deletions
+1 -1
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@@ -1,6 +1,6 @@
name = "YiemAgent"
uuid = "e012c34b-7f78-48e0-971c-7abb83b6f0a2"
version = "0.6.0"
version = "0.6.2"
authors = ["narawat lamaiin <narawat@outlook.com>"]
[deps]
+1 -1
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@@ -474,7 +474,7 @@ function think(a::T)::NamedTuple{(:thoughtdict, :result_raw), Tuple{OrderedDict,
elseif thoughtdict["action_name"] == "SEARCH_WINE_DATABASE"
@info "YiemAgent think() 5 " @__LINE__
thoughtdict, result_raw = search_wine_database!(a, thoughtdict; useSQLLLM=true)
thoughtdict, result_raw = search_wine_database!(a, thoughtdict; useSQLLLM=false)
#WORKING result_raw will be a df. i need to get images so i can send to frontend
else
@info "YiemAgent think() 6 " @__LINE__
+5 -11
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@@ -519,11 +519,11 @@ function generatesql(a::T, searchterm::String,
# provide similar sql only for the first attempt
sql, distance = a.context.similarSQLVectorDB(searchterm)
similarSQL_ = sql !== nothing ? sql : "None"
# if sql is really close, just use it
if similarSQL_ != "None" && distance <= 0.1
return similarSQL_
end
# similarSQL_ = sql !== nothing ? sql : "None"
# # if sql is really close, just use it
# if similarSQL_ != "None" && distance <= 0.1
# return similarSQL_
# end
#CHANGE use find_related_tables_for_user_question and inject only related table schema instead
# of hard code table schema. CPU embedding is too slow. use embedding service on GPU.
@@ -541,12 +541,6 @@ function generatesql(a::T, searchterm::String,
<database_table_schema>
$table_schema
</database_table_schema>
<possible SQL for user's search term>
$similarSQL_
</possible SQL for user's search term>
<error_note>
$errornote
<error_note>
</internal_context_for_assistant>
"""
input = context * searchterm