update

test/runtest.jl

@@ -1,5 +1,5 @@
 using Revise      # remove when this package is completed
-using YiemAgent, GeneralUtils, JSON3, MQTTClient, Dates, UUIDs, LibPQ
+using YiemAgent, GeneralUtils, JSON3, MQTTClient, Dates, UUIDs, LibPQ, Base64, DataFrames
 using Base.Threads
 
 # ---------------------------------------------- 100 --------------------------------------------- #
@@ -55,20 +55,127 @@ function text2textInstructLLM(prompt::String)
   return response
 end
 
-  # Instantiate an agent
-  a = YiemAgent.sommelier(
-    text2textInstructLLM,
-    executeSQL;
-    name="assistant",
-    id="testingSessionID",  # agent instance id
+function executeSQLVectorDB(sql)
+  DBconnection = LibPQ.Connection("host=192.168.88.12 port=5433 dbname=SQLVectorDB user=yiemtechnologies@gmail.com password=yiem@Postgres_0.0")
+  result = LibPQ.execute(DBconnection, sql)
+  close(DBconnection)
+  return result
+end
+
+function addSQLVectorDB(state)
+  # get embedding of the query
+  query = [state[:thoughtHistory][:question]]
+  msgMeta = GeneralUtils.generate_msgMeta(
+    config[:externalservice][:text2textinstruct][:mqtttopic];
+    msgPurpose= "embedding",
+    senderName= "yiemagent",
+    senderId= string(uuid4()),
+    receiverName= "text2textinstruct",
+    mqttBrokerAddress= config[:mqttServerInfo][:broker],
+    mqttBrokerPort= config[:mqttServerInfo][:port],
   )
 
+  outgoingMsg = Dict(
+    :msgMeta=> msgMeta,
+    :payload=> Dict(
+      :text=> query
+      )
+    )
+  response = GeneralUtils.sendReceiveMqttMsg(outgoingMsg)
+  embedding = response[:response][:embeddings][1]
+
+  # check whether there is close enough vector already store in vectorDB. if no, add, else skip 
+  sql =
+    """
+    SELECT *, embedding <-> '$embedding' as distance
+    FROM sql_statement_repository
+    ORDER BY distance LIMIT 1;
+    """
+  response = executeSQLVectorDB(sql)
+  df = DataFrame(response)
+  row, col = size(df)
+  distance = row == 0 ? Inf : df[1, :distance]
+  if row == 0 || distance > 10 # no close enough SQL stored in the database
+    latestKey, _ = GeneralUtils.findHighestIndexKey(state[:thoughtHistory], :action_input)
+    _sqlStatement = state[:thoughtHistory][latestKey]
+    if occursin("SELECT", _sqlStatement)  # make sure it is an SQL statement before adding into DB
+      sqlStatementBase64 = base64encode(_sqlStatement)
+      sqlStatement = replace(_sqlStatement, "'"=>"")
+      sql =
+      """
+      INSERT INTO sql_statement_repository (question, sql_statement, sql_statement_base64, embedding) VALUES ('$query', '$sqlStatement', '$sqlStatementBase64', '$embedding');
+      """
+      _ = executeSQLVectorDB(sql)
+      println("--> added new SQL statement to vectorDB ", @__FILE__, " ", @__LINE__)
+      println(sqlStatement)
+    end
+  end
+end
+
+function querySQLVectorDB(state)
+
+  # provide similarSQL at the first time thinking only
+  latestKey, _ = GeneralUtils.findHighestIndexKey(state[:thoughtHistory], :action_input)
+  if latestKey === nothing
+    # get embedding of the query
+    query = [state[:thoughtHistory][:question]]
+    msgMeta = GeneralUtils.generate_msgMeta(
+      config[:externalservice][:text2textinstruct][:mqtttopic];
+      msgPurpose= "embedding",
+      senderName= "yiemagent",
+      senderId= string(uuid4()),
+      receiverName= "text2textinstruct",
+      mqttBrokerAddress= config[:mqttServerInfo][:broker],
+      mqttBrokerPort= config[:mqttServerInfo][:port],
+    )
+
+    outgoingMsg = Dict(
+      :msgMeta=> msgMeta,
+      :payload=> Dict(
+        :text=> query
+        )
+      )
+    response = GeneralUtils.sendReceiveMqttMsg(outgoingMsg)
+    embedding = response[:response][:embeddings][1]
+
+    # check whether there is close enough vector already store in vectorDB. if no, add, else skip 
+    sql =
+    """
+    SELECT *, embedding <-> '$embedding' as distance
+    FROM sql_statement_repository
+    ORDER BY distance LIMIT 1;
+    """
+    response = executeSQLVectorDB(sql)
+    df = DataFrame(response)
+    row, col = size(df)
+    distance = row == 0 ? Inf : df[1, :distance]
+    if row != 0 && distance < 100
+      # if there is usable SQL, return it.
+      sqlStatementBase64 = df[1, :sql_statement_base64]
+      sqlStatement = String(base64decode(sqlStatementBase64))
+      println("--> getting SQL statement from vectorDB ", @__FILE__, " ", @__LINE__)
+      println(sqlStatement)
+      return sqlStatement
+    else
+      return nothing
+    end
+  end
+  return nothing
+end
+
+
+# Instantiate an agent
+a = YiemAgent.sommelier(
+  text2textInstructLLM,
+  executeSQL,
+  querySQLVectorDB,
+  addSQLVectorDB;
+  name= "Janie",
+  id= sessionId,  # agent instance id
+)
+
 function main()
-  userinput = "Hello, I would like a get a bottle of wine."
   for i in 1:10
-    response = YiemAgent.conversation(a, Dict(:text=> userinput))
-    println("")
-    println("--> assistant response: \n", response)
     userinput = ""
     for i in 1:3
       if userinput == ""
@@ -79,6 +186,9 @@ function main()
         break
       end
     end
+    response = YiemAgent.conversation(a, Dict(:text=> userinput))
+    println("")
+    println("--> assistant response: \n", response)
   end
 end
 
@@ -87,8 +197,13 @@ main()
 """
   I'm joining a graduation party this evening. I want a bottle of dry white wine from the US. I'm ok with any price range.
   Well, the party is small casual with close friends and no food serving.
-  I'm open to suggestion since I have no specific idea about wine.
+  I'm open to suggestion since I have no specific idea.
   I'm ok with any region.
+
+
+
+
+  The input is instructions on how you want the presentation to be conducted.
 """