update

Manifest.toml

@@ -2,7 +2,7 @@
 
 julia_version = "1.11.2"
 manifest_format = "2.0"
-project_hash = "7276bacf2126ccf319f58f1cc1aab4f9a73ac360"
+project_hash = "6e88822413ea4a623cd914d84de127dc6c57fceb"
 
 [[deps.AliasTables]]
 deps = ["PtrArrays", "Random"]
@@ -306,11 +306,11 @@ version = "1.19.3+0"
 
 [[deps.LLMMCTS]]
 deps = ["GeneralUtils", "JSON3"]
-git-tree-sha1 = "5be792515b65e464d15ac8db6a9f6f6628c7d81a"
+git-tree-sha1 = "c8ad9715e78bbd19f5ac79e1f1cacf85f141449d"
 repo-rev = "main"
 repo-url = "https://git.yiem.cc/ton/LLMMCTS"
 uuid = "d76c5a4d-449e-4835-8cc4-dd86ec44f241"
-version = "0.1.0"
+version = "0.1.2"
 
 [[deps.LaTeXStrings]]
 git-tree-sha1 = "dda21b8cbd6a6c40d9d02a73230f9d70fed6918c"

Project.toml

@@ -1,7 +1,7 @@
 name = "SQLLLM"
 uuid = "2ebc79c7-cc10-4a3a-9665-d2e1d61e63d3"
 authors = ["narawat lamaiin <narawat@outlook.com>"]
-version = "0.1.0"
+version = "0.2.1"
 
 [deps]
 CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
@@ -24,4 +24,4 @@ UUIDs = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
 
 [compat]
 GeneralUtils = "0.1.0"
-LLMMCTS = "0.1.0"
+LLMMCTS = "0.1.2"

src/interface.jl

@@ -133,25 +133,27 @@ function decisionMaker(state::T1, context, text2textInstructLLM::Function,
 
   systemmsg = 
   """
-    You are a helpful assistant that get the data from a database to satisfy the user's query. 
+    You are a helpful assistant that find the data from a database to satisfy the user's query. 
     You are also eager to improve your helpfulness.
 
     At each round of conversation, the user will give you the current situation:
     User Query: ...
-    Hints: ...
+    Example: ...
     Your Q&A: ...
     Your work progress: ...
     Evaluation: Evaluation of the latest action and observation
     Suggestion: ...
     
-    You should consider the following guidelines:
+    You must follow the following guidelines:
+    - Keep SQL queries focused only on the provided information.
+
+    You should follow the following guidelines:
     - Do not create any table in the database
     - Column name can be the same in different tables. Refer to column comments to get more details by using TABLEINFO function
     - A junction table can be used to link tables together. Another use case is for filtering data.
     - If you can't find a single table that can be used to answer the user's query, try joining multiple tables to see if you can obtain the answer.
     - If you are unable to find the requested information, kindly inform the user, "The current data in our database does not provide the specific answer to your query".
     - Text information in the database usually stored in lower case. If your search returns empty, try using lower case to search.
-    - Do not use backticks (`). Use double quotes instead.
 
     You should then respond to the user with interleaving Understanding, Reasoning, Plan, Action:
     1) Understanding: 
@@ -161,7 +163,7 @@ function decisionMaker(state::T1, context, text2textInstructLLM::Function,
     3) Plan: Given the current circumstances, outline a detailed, step-by-step plan to accomplish the task. Be specific.
     4) Action_name (Must be aligned with your plan): Can be one of the following functions: 
         - TABLEINFO[list_of_table_name], which you can use to get the data type of a table column. "list_of_table_name" is a list of table name you want to get info. e.g. TABLEINFO["table name 1", "table name 2"]
-        - GETDATA[SQL], which you can use to get the data from the database. "SQL" is the single SQL command to be executed against the database.
+        - GETDATA[SQL], which you can use to get the data from the database. "SQL" is a single SQL command to be executed against the database.
           For more effective text search, it's necessary to use case-insensitivity and the ILIKE operator.
           Do not wrap the SQL as it will be executed against the database directly and SQL must be ended with ';'.
     5) Action_input: Input to the action
@@ -173,7 +175,6 @@ function decisionMaker(state::T1, context, text2textInstructLLM::Function,
     Plan: ...
     Action_name: ...
     Action_input: ...
-    Observation: ...
 
     Let's begin!
   """
@@ -203,7 +204,7 @@ function decisionMaker(state::T1, context, text2textInstructLLM::Function,
     """
     $(context[:tablelist])
     User query: $(state[:thoughtHistory][:question])
-    Hints: $similarSQL_
+    Example: $similarSQL_
     Your Q&A: $QandA
     Your work progress: $workprogress
     Evaluation: $(state[:evaluation])
@@ -226,18 +227,32 @@ function decisionMaker(state::T1, context, text2textInstructLLM::Function,
 
     try
       response = text2textInstructLLM(prompt)
+      println("\nSQL decisionMaker() rawresponse: ", response)
+
+      header = ["Understanding", "Reasoning", "Plan", "Action_name", "Action_input", "Observation"]
+
+      # detect if there are more than 1 key per categories
+      count = GeneralUtils.countGivenWords(response, header)
+      if sum(count) > length(header)
+        error("\nSQL decisionMaker() duplicated keywords", @__FILE__, " ", @__LINE__)
+      end
 
       # textToDict() search for action_input
-      responsedict = GeneralUtils.textToDict(response,
-                  ["Understanding", "Reasoning", "Plan", "Action_name", "Action_input", "Observation"], 
+      responsedict = GeneralUtils.textToDict(response, header, 
                   rightmarker=":", symbolkey=true, lowercasekey=true)
 
       delete!(responsedict, :observation)
 
-      # remove backticks
+      # remove backticks Error occurred: MethodError: no method matching occursin(::String, ::Vector{String})
       if occursin("```", responsedict[:action_input])
-        responsedict[:action_input] = 
-          GeneralUtils.extract_triple_backtick_text(responsedict[:action_input])
+        sql = GeneralUtils.extract_triple_backtick_text(responsedict[:action_input])[1]
+        if sql[1:4] == "sql\n"
+          sql = sql[5:end]
+        end
+        sql = split(sql, ';')   # some time there are comments in the sql
+        sql = sql[1] * ';'
+
+        responsedict[:action_input] = sql
       end
 
       toollist = ["TABLEINFO", "GETDATA"]
@@ -277,6 +292,7 @@ function decisionMaker(state::T1, context, text2textInstructLLM::Function,
       println("\n~~~ SQLLLM decisionMaker() Attempt $attempt. Error occurred: $errorMsg\n$st ", @__FILE__, " ", @__LINE__)
       println("")
     end
+
   end
   error("DecisionMaker failed to generate a thought ", response)
 end
@@ -302,7 +318,7 @@ julia>
 # Signature
 """
 function evaluator(state::T1, text2textInstructLLM::Function;
-  addSQLVectorDB::Union{Function, Nothing}=nothing
+  insertSQLVectorDB::Union{Function, Nothing}=nothing
   ) where {T1<:AbstractDict}
   
   # systemmsg = 
@@ -768,7 +784,7 @@ function transition(state::T, args::NamedTuple
   context = args[:context]
   executeSQL::Function = args[:executeSQL]
   text2textInstructLLM::Function = args[:text2textInstructLLM]
-  addSQLVectorDBF::Function = args[:addSQLVectorDB]
+  insertSQLVectorDB::Function = args[:insertSQLVectorDB]
   querySQLVectorDBF::Function = args[:querySQLVectorDB]
 
   # getting SQL from vectorDB
@@ -804,7 +820,7 @@ function transition(state::T, args::NamedTuple
   isterminal::Bool = haskey(response, :isterminal) ? response[:isterminal] : false
   newNodeKey, newstate = makeNewState(state, thoughtDict, rawresponse, JSON3.write(result), select, reward, isterminal)
   progressvalue::Integer = evaluatorF(newstate, text2textInstructLLM; 
-                                      addSQLVectorDB=addSQLVectorDBF)
+                                    insertSQLVectorDB=insertSQLVectorDB)
 
   return (newNodeKey=newNodeKey, newstate=newstate, progressvalue=progressvalue)
 end
@@ -887,7 +903,7 @@ julia> println(result)
 # Signature
 """
 function query(query::T, executeSQL::Function, text2textInstructLLM::Function;
-  addSQLVectorDB::Union{Function, Nothing}=nothing,
+  insertSQLVectorDB::Union{Function, Nothing}=nothing,
   similarSQLVectorDB::Union{Function, Nothing}=nothing,
   ) where {T<:AbstractString}
 
@@ -931,7 +947,7 @@ function query(query::T, executeSQL::Function, text2textInstructLLM::Function;
                     executeSQL=executeSQL, 
                     text2textInstructLLM=text2textInstructLLM,
                     querySQLVectorDB=similarSQLVectorDB,
-                    addSQLVectorDB=addSQLVectorDB,
+                    insertSQLVectorDB=insertSQLVectorDB,
                   )
 
   earlystop(state) = state[:reward] >= 8 ? true : false
@@ -945,8 +961,10 @@ function query(query::T, executeSQL::Function, text2textInstructLLM::Function;
   extracted = resultState[:thoughtHistory][latestKey]
 
   # add to vectorDB only if the answer is achieved and the state is terminal 
-  if addSQLVectorDB !== nothing && resultState[:isterminal] == true
-    addSQLVectorDB(resultState[:thoughtHistory][:question], sql)
+  if insertSQLVectorDB !== nothing && resultState[:isterminal] == true &&
+    resultState[:rawresponse] !== nothing
+
+    insertSQLVectorDB(resultState[:thoughtHistory][:question], sql)
   end
 
   return (text=extracted, rawresponse=resultState[:rawresponse]) 
@@ -1017,11 +1035,11 @@ function generatequestion(state::T1, context, text2textInstructLLM::Function;
 
   systemmsg = 
   """
-    You are a helpful assistant that generate multiple questions about the current situation.
+    You are a SQL expert that generate multiple questions about the current situation.
     
     At each round of conversation, the user will give you the current situation:
     User query: ...
-    Hints: ...
+    Example: ...
     Your work progress: ...
 
     About the tables in the database:
@@ -1035,6 +1053,9 @@ function generatequestion(state::T1, context, text2textInstructLLM::Function;
     3) Some information can be accessed by joining multiple tables.
     4) Do not generate any question or comments at the end.
 
+    You should follow the following guidelines:
+    - When querying data in the database, start with broad search terms and refine your query later for more precise results. 
+
     You should then respond to the user with:
     1) Understanding: 
         - State your understanding about the current situation.
@@ -1052,6 +1073,13 @@ function generatequestion(state::T1, context, text2textInstructLLM::Function;
     A3: ...
     ...
 
+    Here are some examples:
+    Q: What information in the hints is not necessary based on the query?
+    A: Country is not specified in the query thus it should not be included in an SQL
+
+    Q: How can I modify a SQL example to fit my specific query needs?
+    A: ...
+
     Let's begin!
   """
   
@@ -1071,7 +1099,7 @@ function generatequestion(state::T1, context, text2textInstructLLM::Function;
     """
     $(context[:tablelist])
     User query: $(state[:thoughtHistory][:question])
-    Hints: $similarSQL
+    Example: $similarSQL
     Your work progress: $workprogress
     $errornote
     $noise

src/llmfunction.jl

@@ -613,7 +613,7 @@ function SQLexecution(executeSQL::Function, sql::T
     tablesize = size(df)
     row, column = tablesize
     if row == 0  # if 0 row
-      error("The resulting table has 0 row. Possible causes: 1) You might be searching in the wrong place 2) There could be a typo in your search query.")
+      error("The resulting table has 0 row. Possible causes: 1) Your search criteria might be too specific. Relaxing some conditions could yield better results. Remember, you can always refine your search later. 2) There could be a typo in your search query. 3) You might be searching in the wrong place.")
     elseif column > 30
       error("SQL execution failed. An unexpected error occurred. Please try again.")
     end