update

Reviewed-on: #1

Project.toml

@@ -1,7 +1,7 @@
 name = "YiemAgent"
 uuid = "e012c34b-7f78-48e0-971c-7abb83b6f0a2"
 authors = ["narawat lamaiin <narawat@outlook.com>"]
-version = "0.1.1"
+version = "0.1.3"
 
 [deps]
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
@@ -22,6 +22,6 @@ UUIDs = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
 
 [compat]
 DataFrames = "1.7.0"
-GeneralUtils = "0.1.0"
+GeneralUtils = "0.1, 0.2"
 LLMMCTS = "0.1.2"
 SQLLLM = "0.2.0"

src/llmfunction.jl

@@ -1,7 +1,8 @@
 module llmfunction
 
 export  virtualWineUserChatbox, jsoncorrection, checkinventory, # recommendbox,
-        virtualWineUserRecommendbox, userChatbox, userRecommendbox, extractWineAttributes_1
+        virtualWineUserRecommendbox, userChatbox, userRecommendbox, extractWineAttributes_1,
+        extractWineAttributes_2, paraphrase
 
 using HTTP, JSON3, URIs, Random, PrettyPrinting, UUIDs, Dates
 using GeneralUtils, SQLLLM
@@ -290,20 +291,20 @@ julia> result = checkinventory(agent, input)
 function checkinventory(a::T1, input::T2
   ) where {T1<:agent, T2<:AbstractString}
 
-  println("\n~~~ checkinventory order: $input ", @__FILE__, " ", @__LINE__)
+  println("\n~~~ checkinventory order: $input ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
   wineattributes_1 = extractWineAttributes_1(a, input)
   wineattributes_2 = extractWineAttributes_2(a, input)
 
   _inventoryquery = "retailer name: $(a.retailername), $wineattributes_1, $wineattributes_2"
   inventoryquery = "Retrieves winery, wine_name, vintage, region, country, wine_type, grape, serving_temperature, sweetness, intensity, tannin, acidity, tasting_notes, price and currency of wines that match the following criteria - {$_inventoryquery}"
-  println("~~~ checkinventory input: $inventoryquery ", @__FILE__, " ", @__LINE__)
+  println("~~~ checkinventory input: $inventoryquery ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
   # add suppport for similarSQLVectorDB
   textresult, rawresponse = SQLLLM.query(inventoryquery, a.func[:executeSQL], 
                         a.func[:text2textInstructLLM],
                         insertSQLVectorDB=a.func[:insertSQLVectorDB], 
                         similarSQLVectorDB=a.func[:similarSQLVectorDB])
 
-  println("\n~~~ checkinventory result ", @__FILE__, " ", @__LINE__)
+  println("\n~~~ checkinventory result ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
   println(textresult)
 
   return (result=textresult, rawresponse=rawresponse, success=true, errormsg=nothing)
@@ -325,234 +326,67 @@ julia>
 
 # TODO
   - [] update docstring
-  - [x] implement the function
+  - implement the function
 
 # Signature
 """
-# function extractWineAttributes_1(a::T1, input::T2)::String where {T1<:agent, T2<:AbstractString}
-
-#   systemmsg =
-#   """
-#   As a helpful sommelier, your task is to extract the user information from the user's query as much as possible to fill out user's preference form.
-
-#   At each round of conversation, the user will give you the current situation:
-#   User's query: ...
-
-#   You must follow the following guidelines:
-#     1) If specific information required in the preference form is not available in the query or there isn't any, mark with "NA" to indicate this.
-#       Additionally, words like 'any' or 'unlimited' mean no information is available.
-#     2) Do not generate other comments.
-
-#   You should then respond to the user with the following points:
-#   - reasoning: state your understanding of the current situation
-#   - wine_name: name of the wine
-#   - winery: name of the winery
-#   - vintage: the year of the wine
-#   - region: a region in a country where the wine is produced, such as Burgundy, Napa Valley, etc
-#   - country: a country where the wine is produced. Can be "Austria", "Australia", "France", "Germany", "Italy", "Portugal", "Spain", "United States"
-#   - wine_type: can be one of: "red", "white", "sparkling", "rose", "dessert" or "fortified"
-#   - grape_variety: the name of the primary grape used to make the wine
-#   - tasting_notes: a brief description of the wine's taste, such as "butter", "oak", "fruity", etc
-#   - wine_price: price of wine. For example, up to 100, less than 100, 20 to 100, 30-79.95 
-#   - occasion: the occasion the user is having the wine for
-#   - food_to_be_paired_with_wine: food that the user will be served with the wine such as poultry, fish, steak, etc
-  
-
-#   You should only respond in the user's preference form as described below:
-#   reasoning: ...
-#   winery: ...
-#   wine_name: ...
-#   vintage: ...
-#   region: ...
-#   country: ...
-#   wine_type: ...
-#   grape_variety: ...
-#   tasting_notes: ...
-#   wine_price: ...
-#   occasion: ...
-#   food_to_be_paired_with_wine: ...
-  
-#   Here are some example:
-#   User's query: red, Chenin Blanc, Riesling, under 20
-#   reasoning: ...
-#   winery: NA
-#   wine_name: NA
-#   vintage: NA
-#   region: NA
-#   country: NA
-#   wine_type: red
-#   grape_variety: Chenin Blanc, Riesling
-#   tasting_notes: NA
-#   wine_price: under 20
-#   occasion: NA
-#   food_to_be_paired_with_wine: NA
-
-#   User's query: Domaine du Collier Saumur Blanc 2019, France, white, Chenin Blanc
-#   reasoning: ...
-#   winery: Domaine du Collier 
-#   wine_name: Saumur Blanc
-#   vintage: 2019
-#   region: Saumur
-#   country: France
-#   wine_type: white
-#   grape_variety: Chenin Blanc
-#   tasting_notes: NA
-#   wine_price: 109
-#   occasion: NA
-#   food_to_be_paired_with_wine: NA
-
-#   Let's begin!
-#   """
-
-#   attributes = ["reasoning", "winery", "wine_name", "vintage", "region", "country", "wine_type", "grape_variety", "tasting_notes", "wine_price", "occasion", "food_to_be_paired_with_wine"]
-#   errornote = ""
-#   maxattempt = 5
-#   for attempt in 1:maxattempt
-
-#     usermsg =
-#     """
-#     User's query: $input
-#     $errornote
-#     """
-
-#     _prompt = 
-#     [
-#       Dict(:name=> "system", :text=> systemmsg),
-#       Dict(:name=> "user", :text=> usermsg)
-#     ]
-
-#     # put in model format
-#     prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
-#     prompt *=
-#       """
-#       <|start_header_id|>assistant<|end_header_id|>
-#       """
-
-#     try
-#       response = a.func[:text2textInstructLLM](prompt)
-#       response = GeneralUtils.remove_french_accents(response)
-
-#       # check wheter all attributes are in the response
-#       for word in attributes
-#         if !occursin(word, response)
-#           error("$word attribute is missing")
-#         end
-#       end
-
-#       responsedict = GeneralUtils.textToDict(response, attributes, rightmarker=":", symbolkey=true)
-
-#       for i ∈ attributes
-#         if length(JSON3.write(responsedict[Symbol(i)])) == 0
-#           error("$i is empty ", @__LINE__)
-#         end
-#       end
-
-#       #check if the following attributes has more than 1 name
-#       # responsedict[:grape_variety] = split(responsedict[:grape_variety], ',')[1]
-#       # responsedict[:grape_variety] = split(responsedict[:grape_variety], '/')[1]
-
-#       responsedict[:country] = split(responsedict[:country], ',')[1]
-#       responsedict[:country] = split(responsedict[:country], '/')[1]
-      
-#       responsedict[:region] = split(responsedict[:region], ',')[1]
-#       responsedict[:region] = split(responsedict[:region], '/')[1]
-
-#       delete!(responsedict, :reasoning)
-#       delete!(responsedict, :tasting_notes)
-#       delete!(responsedict, :occasion)
-#       delete!(responsedict, :food_to_be_paired_with_wine)
-
-#       # check if winery, wine_name, region, country, wine_type, grape_variety are in the query because sometime AI halucinates
-#       for i in [:grape_variety, :winery, :wine_name, :region]
-#         result = check_key_in_input(input, responsedict, attempt, maxattempt, i)
-#         if result === nothing
-#           # nothing wrong
-#         elseif result == "NA"
-#           responsedict[i] = "NA"
-#         else
-#           errornote = result
-#           error(errornote)
-#         end
-#       end
-
-#       # remove (some text)
-#       for (k, v) in responsedict
-#         _v = replace(v, r"\(.*?\)" => "")
-#         responsedict[k] = _v
-#       end
-
-#       result = ""
-#       for (k, v) in responsedict
-#         # some time LLM generate text with "(some comment)". this line removes it
-#         if !occursin("NA", v) && v != "" && !occursin("none", v) && !occursin("None", v)
-#           result *= "$k: $v, "
-#         end
-#       end
-
-#       #[PENDING] remove halucination. "highend dry white wine" --> "wine_type: white, occasion: special occasion, food_to_be_paired_with_wine: seafood, fish, country: France, Italy, USA, grape_variety: Chardonnay, Sauvignon Blanc, Pinot Grigio\nwine_notes: citrus, green apple, floral"
-      
-#       result = result[1:end-2]  # remove the ending ", "
-
-#       return result
-#     catch e
-#       io = IOBuffer()
-#       showerror(io, e)
-#       errorMsg = String(take!(io))
-#       st = sprint((io, v) -> show(io, "text/plain", v), stacktrace(catch_backtrace()))
-#       println("")
-#       println("Attempt $attempt. Error occurred: $errorMsg\n$st ", @__FILE__, " ", @__LINE__)
-#       println("")
-#     end
-#   end
-#   error("wineattributes_wordToNumber() failed to get a response")
-# end
 function extractWineAttributes_1(a::T1, input::T2)::String where {T1<:agent, T2<:AbstractString}
 
   systemmsg =
   """
   As a helpful sommelier, your task is to extract the user information from the user's query as much as possible to fill out user's preference form.
 
-  At each round of conversation, the user will give you the current situation:
+  At each round of conversation, the user will give you the following:
   User's query: ...
 
   You must follow the following guidelines:
-    1) If specific information required in the preference form is not available in the query or there isn't any, mark with "NA" to indicate this.
+    - If specific information required in the preference form is not available in the query or there isn't any, mark with "NA" to indicate this.
       Additionally, words like 'any' or 'unlimited' mean no information is available.
-    2) Do not generate other comments.
+    - Do not generate other comments.
 
-  You should then respond to the user with the following points:
+  You should then respond to the user with:
-  - reasoning: state your understanding of the current situation
+    Comprehension: state your understanding of the current situation
-  - wine_name: name of the wine
+    Wine_name: name of the wine
-  - winery: name of the winery
+    Winery: name of the winery
-  - vintage: the year of the wine
+    Vintage: the year of the wine
-  - region: a region (NOT a country) where the wine is produced, such as Burgundy, Napa Valley, etc
+    Region: a region (NOT a country) where the wine is produced, such as Burgundy, Napa Valley, etc
-  - country: a country where the wine is produced. Can be "Austria", "Australia", "France", "Germany", "Italy", "Portugal", "Spain", "United States"
+    Country: a country where the wine is produced. Can be "Austria", "Australia", "France", "Germany", "Italy", "Portugal", "Spain", "United States"
-  - wine_type: can be one of: "red", "white", "sparkling", "rose", "dessert" or "fortified"
+    Wine_type: can be one of: "red", "white", "sparkling", "rose", "dessert" or "fortified"
-  - grape_variety: the name of the primary grape used to make the wine
+    Grape_varietal: the name of the primary grape used to make the wine
-  - tasting_notes: a brief description of the wine's taste, such as "butter", "oak", "fruity", etc
+    Tasting_notes: a brief description of the wine's taste, such as "butter", "oak", "fruity", etc
-  - wine_price: price of wine. For example, up to 100, less than 100, 20 to 100, 30-79.95 
+    Wine_price: price range of wine.
-  - occasion: the occasion the user is having the wine for
+    Occasion: the occasion the user is having the wine for
-  - food_to_be_paired_with_wine: food that the user will be served with the wine such as poultry, fish, steak, etc
+    Food_to_be_paired_with_wine: food that the user will be served with the wine such as poultry, fish, steak, etc
 
-
+  You should only respond in format as described below:
-  You should only respond in the user's preference form (JSON) as described below:
+  Comprehension: ...
-  {"reasoning": ..., "winery": ..., "wine_name": ..., "vintage": ..., "region": ..., "country": ..., "wine_type": ..., "grape_variety": ..., "tasting_notes": ..., "wine_price": ..., "occasion": ..., "food_to_be_paired_with_wine": ...}
+  Wine_name: ...
+  Winery: ...
+  Vintage: ...
+  Region: ...
+  Country: ...
+  Wine_type:
+  Grape_varietal: ...
+  Tasting_notes: ...
+  Wine_price: ...
+  Occasion: ...
+  Food_to_be_paired_with_wine: ...
   
   Here are some example:
-  User's query: red, Chenin Blanc, Riesling, under 20
+  User's query: red, Chenin Blanc, Riesling, 20 USD
-  {"reasoning": ..., "winery": "NA", "wine_name": "NA", "vintage": "NA", "region": "NA", "country": "NA", "wine_type": "red", "grape_variety": "Chenin Blanc, Riesling", "tasting_notes": "NA", "wine_price": "under 20", "occasion": "NA", "food_to_be_paired_with_wine": "NA"}
+  {"reasoning": ..., "winery": "NA", "wine_name": "NA", "vintage": "NA", "region": "NA", "country": "NA", "wine_type": "red, white", "grape_varietal": "Chenin Blanc, Riesling", "tasting_notes": "NA", "wine_price": "0-20", "occasion": "NA", "food_to_be_paired_with_wine": "NA"}
 
   User's query: Domaine du Collier Saumur Blanc 2019, France, white, Chenin Blanc
-  {"reasoning": ..., "winery": "Domaine du Collier", "wine_name": "Saumur Blanc", "vintage": "2019", "region": "Saumur", "country": "France", "wine_type": "white", "grape_variety": "Chenin Blanc", "tasting_notes": "NA", "wine_price": "109", "occasion": "NA", "food_to_be_paired_with_wine": "NA"}
+  {"reasoning": ..., "winery": "Domaine du Collier", "wine_name": "Saumur Blanc", "vintage": "2019", "region": "Saumur", "country": "France", "wine_type": "white", "grape_varietal": "Chenin Blanc", "tasting_notes": "NA", "wine_price": "NA", "occasion": "NA", "food_to_be_paired_with_wine": "NA"}
 
   Let's begin!
   """
 
-  attributes = ["reasoning", "winery", "wine_name", "vintage", "region", "country", "wine_type", "grape_variety", "tasting_notes", "wine_price", "occasion", "food_to_be_paired_with_wine"]
+  header = ["Comprehension:", "Wine_name:", "Winery:", "Vintage:", "Region:", "Country:", "Wine_type:", "Grape_varietal:", "Tasting_notes:", "Wine_price:", "Occasion:", "Food_to_be_paired_with_wine:"]
+  dictkey = ["comprehension", "wine_name", "winery", "vintage", "region", "country", "wine_type", "grape_varietal", "tasting_notes", "wine_price", "occasion", "food_to_be_paired_with_wine"]
   errornote = ""
-  maxattempt = 5
-  for attempt in 1:maxattempt
   
+  for attempt in 1:5
     usermsg =
     """
     User's query: $input
@@ -566,76 +400,116 @@ function extractWineAttributes_1(a::T1, input::T2)::String where {T1<:agent, T2<
     ]
 
     # put in model format
-    prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
+    prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen")
-    prompt *=
+    response = a.func[:text2textInstructLLM](prompt)
-      """
+    response = GeneralUtils.remove_french_accents(response)
-      <|start_header_id|>assistant<|end_header_id|>
-      """
 
-    try
+    # check wheter all attributes are in the response
-      response = a.func[:text2textInstructLLM](prompt)
+    checkFlag = false
-      response = GeneralUtils.remove_french_accents(response)
+    for word in header
-
+      if !occursin(word, response)
-      # check wheter all attributes are in the response
+        errornote = "$word attribute is missing in previous attempts"
-      for word in attributes
+        println("Attempt $attempt $errornote ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
-        if !occursin(word, response)
+        checkFlag = true
-          error("$word attribute is missing")
+        break
-        end
       end
+    end
+    checkFlag == true ? continue : nothing
     
-      responsedict = copy(JSON3.read(response))
+    # check whether response has all header
+    detected_kw = GeneralUtils.detect_keyword(header, response)
+    if sum(values(detected_kw)) < length(header)
+      errornote = "\nYiemAgent extractWineAttributes_1() response does not have all header"
+      continue
+    elseif sum(values(detected_kw)) > length(header)
+      errornote = "\nYiemAgent extractWineAttributes_1() response has duplicated header"
+      continue
+    end
+    responsedict = GeneralUtils.textToDict(response, header; 
+                                            dictKey=dictkey, symbolkey=true)
 
-      delete!(responsedict, :reasoning)
+    delete!(responsedict, :comprehension)
-      delete!(responsedict, :tasting_notes)
+    delete!(responsedict, :tasting_notes)
-      delete!(responsedict, :occasion)
+    delete!(responsedict, :occasion)
-      delete!(responsedict, :food_to_be_paired_with_wine)
+    delete!(responsedict, :food_to_be_paired_with_wine)
 
-      # check if winery, wine_name, region, country, wine_type, grape_variety are in the query because sometime AI halucinates
+    println(@__FILE__, " ", @__LINE__)
-      for i in [:grape_variety, :winery, :wine_name, :region]
+    pprintln(responsedict)
-        content = responsedict[i]
+
-        if occursin(",", content)
+    # check if winery, wine_name, region, country, wine_type, grape_varietal's value are in the query because sometime AI halucinates
-          content = split(content, ",") # sometime AI generates multiple values e.g. "Chenin Blanc, Riesling"
+    checkFlag = false
-          content = strip.(content)
+    for i in dictkey
+      j = Symbol(i)
+      if j ∉ [:comprehension, :tasting_notes, :occasion, :food_to_be_paired_with_wine]
+        # in case j is wine_price it needs to be checked differently because its value is ranged
+        if j == :wine_price
+          if responsedict[:wine_price] != "NA" 
+            # check whether wine_price is in ranged number
+            if !occursin('-', responsedict[:wine_price]) 
+              errornote = "wine_price must be a range number"
+              println("Attempt $attempt $errornote ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
+              checkFlag = true
+              break
+            end
+
+            # check whether max wine_price is in the input
+            pricerange = split(responsedict[:wine_price], '-')
+            minprice = pricerange[1]
+            maxprice = pricerange[end]
+            if !occursin(maxprice, input)
+              responsedict[:wine_price] = "NA"
+            end
+            # price range like 100-100 is not good
+            if minprice == maxprice
+              errornote = "wine_price with minimum equals to maximum is not valid"
+              println("Attempt $attempt $errornote ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
+              checkFlag = true
+              break
+            end
+          end
         else
-          content = [content]
+          content = responsedict[j]
-        end
+          if typeof(content) <: AbstractVector
+            content = strip.(content)
+          elseif occursin(',', content)
+            content = split(content, ",") # sometime AI generates multiple values e.g. "Chenin Blanc, Riesling"
+            content = strip.(content)
+          else
+            content = [content]
+          end
 
-        for x in content
+          for x in content  #check whether price are mentioned in the input
-          if !occursin("NA", responsedict[i]) && !occursin(x, input)
+            if !occursin("NA", responsedict[j]) && !occursin(x, input)
-            errornote = "$x is not mentioned in the user query, you must only use the info from the query."
+              errornote = "$x is not mentioned in the user query, you must only use the info from the query."
-            error(errornote)
+              println("Attempt $attempt $errornote ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
+              checkFlag == true
+              break
+            end
           end
         end
       end
-
-      # remove (some text)
-      for (k, v) in responsedict
-        _v = replace(v, r"\(.*?\)" => "")
-        responsedict[k] = _v
-      end
-
-      result = ""
-      for (k, v) in responsedict
-        # some time LLM generate text with "(some comment)". this line removes it
-        if !occursin("NA", v) && v != "" && !occursin("none", v) && !occursin("None", v)
-          result *= "$k: $v, "
-        end
-      end
-
-      #[PENDING] remove halucination. "highend dry white wine" --> "wine_type: white, occasion: special occasion, food_to_be_paired_with_wine: seafood, fish, country: France, Italy, USA, grape_variety: Chardonnay, Sauvignon Blanc, Pinot Grigio\nwine_notes: citrus, green apple, floral"
-      
-      result = result[1:end-2]  # remove the ending ", "
-
-      return result
-    catch e
-      io = IOBuffer()
-      showerror(io, e)
-      errorMsg = String(take!(io))
-      st = sprint((io, v) -> show(io, "text/plain", v), stacktrace(catch_backtrace()))
-      println("")
-      println("Attempt $attempt. Error occurred: $errorMsg\n$st ", @__FILE__, " ", @__LINE__)
-      println("")
     end
+    checkFlag == true ? continue : nothing  # skip the rest code if true
+
+    # remove (some text)
+    for (k, v) in responsedict
+      _v = replace(v, r"\(.*?\)" => "")
+      responsedict[k] = _v
+    end
+
+    result = ""
+    for (k, v) in responsedict
+      # some time LLM generate text with "(some comment)". this line removes it
+      if !occursin("NA", v) && v != "" && !occursin("none", v) && !occursin("None", v)
+        result *= "$k: $v, "
+      end
+    end
+
+    #[PENDING] remove halucination. "highend dry white wine" --> "wine_type: white, occasion: special occasion, food_to_be_paired_with_wine: seafood, fish, country: France, Italy, USA, grape_varietal: Chardonnay, Sauvignon Blanc, Pinot Grigio\nwine_notes: citrus, green apple, floral"
+    
+    result = result[1:end-2]  # remove the ending ", "
+
+    return result
   end
   error("wineattributes_wordToNumber() failed to get a response")
 end
@@ -643,12 +517,13 @@ end
 """
 # TODO
  - [PENDING] "French dry white wines with medium bod" the LLM does not recognize sweetness. use LLM self questioning to solve.
+ - [PENDING] French Syrah, Viognier, under 100. LLM extract intensiry of 3-5. why?
 """
 function extractWineAttributes_2(a::T1, input::T2)::String where {T1<:agent, T2<:AbstractString}
 
   conversiontable =
   """
-  Conversion Table:
+  <Conversion Table>
   Intensity level:
     1 to 2: May correspond to "light-bodied" or a similar description.
     2 to 3: May correspond to "med light bodied", "medium light" or a similar description.
@@ -673,10 +548,9 @@ function extractWineAttributes_2(a::T1, input::T2)::String where {T1<:agent, T2<
     3 to 4: May correspond to "medium acidity" or a similar description.
     4 to 5: May correspond to "semi high acidity" or a similar description.
     4 to 5: May correspond to "high acidity" or a similar description.
+  </Conversion Table>
   """
 
-  # chathistory = vectorOfDictToText(a.chathistory)
-
   systemmsg =
   """
   As an helpful sommelier, your task is to fill out the user's preference form based on the corresponding words from the user's query.
@@ -688,106 +562,241 @@ function extractWineAttributes_2(a::T1, input::T2)::String where {T1<:agent, T2<
   The preference form requires the following information:
   sweetness, acidity, tannin, intensity
 
-  You must follow the following guidelines:
+  <You must follow the following guidelines>
     1) If specific information required in the preference form is not available in the query or there isn't any, mark with 'NA' to indicate this.
       Additionally, words like 'any' or 'unlimited' mean no information is available.
     2) Use the conversion table to convert the descriptive word level of sweetness, intensity, tannin, and acidity into a corresponding integer.
     3) Do not generate other comments.
+  </You must follow the following guidelines>
 
-  You should then respond to the user with the following points:
+  <You should then respond to the user with>
-  - reasoning: State your understanding of the current situation
+    Sweetness_keyword: The exact keywords in the user's query describing the sweetness level of the wine.
-  - sweetness: ( S ), where ( S ) represents integers indicating the range of sweetness levels. Example: 1-2
+    Sweetness: ( S ), where ( S ) represents integers indicating the range of sweetness levels. Example: 1-2
-  - acidity: ( A ), where ( A ) represents integers indicating the range of acidity level. Example: 3-5
+    Acidity_keyword: The exact keywords in the user's query describing the acidity level of the wine.
-  - tannin: ( T ), where ( T ) represents integers indicating the range of tannin level. Example: 1-3
+    Acidity: ( A ), where ( A ) represents integers indicating the range of acidity level. Example: 3-5
-  - intensity: ( I ), where ( I ) represents integers indicating the range of intensity level. Example: 2-4
+    Tannin_keyword: The exact keywords in the user's query describing the tannin level of the wine.
-  - notes: Anything you want to add
+    Tannin: ( T ), where ( T ) represents integers indicating the range of tannin level. Example: 1-3
+    Intensity_keyword: The exact keywords in the user's query describing the intensity level of the wine.
+    Intensity: ( I ), where ( I ) represents integers indicating the range of intensity level. Example: 2-4
+  </You should then respond to the user with>
 
-  You should only respond in the form as described below:
+  <You should only respond in format as described below>
-  reasoning: ...
+    Sweetness_keyword: ...
-  sweetness: ...
+    Sweetness: ...
-  acidity: ...
+    Acidity_keyword: ...
-  tannin: ...
+    Acidity: ...
-  intensity: ...
+    Tannin_keyword: ...
-  notes: ...
+    Tannin: ...
+    Intensity_keyword: ...
+    Intensity: ...
+  </You should only respond in format as described below>
+
+  <Here are some examples>
+    User's query: I want a wine with a medium-bodied, low acidity, medium tannin.
+    Sweetness_keyword: NA
+    Sweetness: NA
+    Acidity_keyword: low acidity
+    Acidity: 1-2
+    Tannin_keyword: medium tannin
+    Tannin: 3-4
+    Intensity_keyword: medium-bodied
+    Intensity: 3-4
+
+    User's query: German red wine, under 100, pairs with spicy food
+    Sweetness_keyword: NA
+    Sweetness: NA
+    Acidity_keyword: NA
+    Acidity: NA
+    Tannin_keyword: NA
+    Tannin: NA
+    Intensity_keyword: NA
+    Intensity: NA
+  </Here are some examples>
 
   Let's begin!
   """
+  header = ["Sweetness_keyword:", "Sweetness:", "Acidity_keyword:", "Acidity:", "Tannin_keyword:", "Tannin:", "Intensity_keyword:", "Intensity:"]
+  dictkey = ["sweetness_keyword", "sweetness", "acidity_keyword", "acidity", "tannin_keyword", "tannin", "intensity_keyword", "intensity"]
+  errornote = ""
 
-  # chathistory = vectorOfDictToText(a.chathistory)
+  for attempt in 1:10
-
+    usermsg =
-  usermsg =
-  """
-  $conversiontable
-  User's query: $input
-  """
-
-  _prompt = 
-  [
-    Dict(:name=> "system", :text=> systemmsg),
-    Dict(:name=> "user", :text=> usermsg)
-  ]
-
-  # put in model format
-  prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
-  prompt *=
     """
-    <|start_header_id|>assistant<|end_header_id|>
+    $conversiontable
+    User's query: $input
+    $errornote
     """
 
-  attributes = ["reasoning", "sweetness", "acidity", "tannin", "intensity", "notes"]
+    _prompt = 
+    [
+      Dict(:name=> "system", :text=> systemmsg),
+      Dict(:name=> "user", :text=> usermsg)
+    ]
+
+    # put in model format
+    prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen")
+
+    response = a.func[:text2textInstructLLM](prompt)
+    
+    # check whether response has all header
+    detected_kw = GeneralUtils.detect_keyword(header, response)
+    if sum(values(detected_kw)) < length(header)
+      errornote = "\nYiemAgent extractWineAttributes_2() response does not have all header"
+      continue
+    elseif sum(values(detected_kw)) > length(header)
+      errornote = "\nYiemAgent extractWineAttributes_2() response has duplicated header"
+      continue
+    end
+
+    responsedict = GeneralUtils.textToDict(response, header; 
+                                            dictKey=dictkey, symbolkey=true)
+
+    # check whether each describing keyword is in the input to prevent halucination
+    for i in ["sweetness", "acidity", "tannin", "intensity"]
+      keyword = Symbol(i * "_keyword")  # e.g. sweetness_keyword
+      value = responsedict[keyword]
+      if value != "NA" && !occursin(value, input)
+        errornote = "WARNING. Keyword $keyword: $value does not appear in the input. You must use information from the input only"
+        println("Attempt $attempt $errornote ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
+        continue
+      end
+
+      # if value == "NA" then responsedict[i] = "NA" 
+      # e.g. if sweetness_keyword == "NA" then sweetness = "NA"
+      if value == "NA"
+        responsedict[Symbol(i)] = "NA"
+      end
+    end
+
+    # some time LLM not put integer range
+    for (k, v) in responsedict
+      if !occursin("keyword", string(k))
+        if v !== "NA" && (!occursin('-', v) || length(v) > 5)
+          errornote = "WARNING: The non-range value {$k: $v} is not allowed. It should be specified in a range format, i.e. min-max."
+          println("Attempt $attempt $errornote ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
+          continue
+        end
+      end
+    end
+
+    # some time LLM says NA-2. Need to convert NA to 1
+    for (k, v) in responsedict
+      if occursin("NA", v) && occursin("-", v)
+        new_v = replace(v, "NA"=>"1")
+        responsedict[k] = new_v
+      end
+    end
+
+    result = ""
+    for (k, v) in responsedict
+      # some time LLM generate text with "(some comment)". this line removes it
+      if !occursin("NA", v)
+        result *= "$k: $v, "
+      end
+    end
+    result = result[1:end-2]  # remove the ending ", "
+
+    return result
+  end
+  error("wineattributes_wordToNumber() failed to get a response")
+end
+
+
+function paraphrase(text2textInstructLLM::Function, text::String)
+  systemmsg = 
+  """
+    Your name: N/A
+    Your vision: 
+      - You are a helpful assistant who help the user to paraphrase their text.
+    Your mission:
+      - To help paraphrase the user's text
+    Mission's objective includes:
+      - To help paraphrase the user's text
+    Your responsibility includes:
+      1) To help paraphrase the user's text
+    Your responsibility does NOT includes:
+      1) N/A
+    Your profile:
+      - N/A
+    Additional information:
+      - N/A
+
+    At each round of conversation, you will be given the following information:
+    Text: The user's given text 
+
+    You MUST follow the following guidelines:
+    - N/A
+
+    You should follow the following guidelines:
+    - N/A
+
+    You should then respond to the user with:
+    1) Paraphrase: Paraphrased text
+
+    You should only respond in format as described below:
+    Paraphrase: ...
+
+    Let's begin!
+  """
+
+  errornote = ""
+  response = nothing # placeholder for show when error msg show up
+
+
+  for attempt in 1:10
+    usermsg = """
+              Text: $text
+              $errornote
+              """
+
+    _prompt =
+      [
+        Dict(:name => "system", :text => systemmsg),
+        Dict(:name => "user", :text => usermsg)
+      ]
+
+    # put in model format
+    prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
+    prompt *= """
+              <|start_header_id|>assistant<|end_header_id|>
+              """
 
-  for attempt in 1:5
     try
-      response = a.func[:text2textInstructLLM](prompt)
+      response = text2textInstructLLM(prompt)
-      responsedict = GeneralUtils.textToDict(response, attributes, rightmarker=":", symbolkey=true)
+      # sometime the model response like this "here's how I would respond: ..."
+      if occursin("respond:", response)
+        errornote = "You don't need to intro your response"
+        error("\n~~~ paraphrase() response contain : ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
+      end
+      response = GeneralUtils.remove_french_accents(response)
+      response = replace(response, '*'=>"")
+      response = replace(response, '$' => "USD")
+      response = replace(response, '`' => "")
+      response = GeneralUtils.remove_french_accents(response)
 
-      for i ∈ attributes
+      header = ["Paraphrase:"]
-        if length(JSON3.write(responsedict[Symbol(i)])) == 0
+      dictkey = ["paraphrase"]
-          error("$i is empty ", @__LINE__)
+      responsedict = GeneralUtils.textToDict(response, header; 
+                                            dictKey=dictkey, symbolkey=true)
+
+      for i ∈ [:paraphrase]
+        if length(JSON3.write(responsedict[i])) == 0
+          error("$i is empty ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
         end
       end
 
-      delete!(responsedict, :reasoning)
+      # check if there are more than 1 key per categories
-      delete!(responsedict, :notes) # LLM traps. so it can add useless info here like comments.
+      for i ∈ [:paraphrase]
-
+        matchkeys = GeneralUtils.findMatchingDictKey(responsedict, i)
-      # some time LLM think the user mentioning acidity and tannin but actually didn't
+        if length(matchkeys) > 1
-      for (k, v) in responsedict
+          error("paraphrase() has more than one key per categories")
-        if k ∈ [:acidity, :tannin] && !occursin(string(k), input)
-          responsedict[k] = "NA"
         end
       end
 
-      # remove (some text)
+      println("\n~~~ paraphrase() ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
-      for (k, v) in responsedict
+      pprintln(Dict(responsedict))
-        _v = replace(v, r"\(.*?\)" => "")
-        responsedict[k] = _v
-      end
 
-      # some time LLM not put integer range
+      result = responsedict[:paraphrase]
-      for (k, v) in responsedict
-        responsedict[k] = v
-        if length(v) > 5
-          error("non-range is not allowed. $k $v")
-        end
-      end
-
-      # some time LLM says NA-2. Need to convert NA to 1
-      for (k, v) in responsedict
-        if occursin("NA", v) && occursin("-", v)
-          new_v = replace(v, "NA"=>"1")
-          responsedict[k] = new_v
-        end
-      end
-
-      result = ""
-      for (k, v) in responsedict
-        # some time LLM generate text with "(some comment)". this line removes it
-        if !occursin("NA", v)
-          result *= "$k: $v, "
-        end
-      end
-
-      result = result[1:end-2]  # remove the ending ", "
 
       return result
     catch e
@@ -795,153 +804,13 @@ function extractWineAttributes_2(a::T1, input::T2)::String where {T1<:agent, T2<
       showerror(io, e)
       errorMsg = String(take!(io))
       st = sprint((io, v) -> show(io, "text/plain", v), stacktrace(catch_backtrace()))
-      println("")
+      println("\nAttempt $attempt. Error occurred: $errorMsg\n$st ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
-      println("Attempt $attempt. Error occurred: $errorMsg\n$st")
-      println("")
     end
   end
-  error("wineattributes_wordToNumber() failed to get a response")
+  error("generatechat failed to generate a response")
 end
 
 
-# function recommendbox(a::T1, input::T2)::String where {T1<:agent, T2<:AbstractString}
-#   error("recommendbox")
-#   systemmsg =
-#   """
-#   As an helpful sommelier, your task is to fill out the user's preference form based on the corresponding words from the user's query.
-
-#   At each round of conversation, the user will give you the current situation:
-#   User's query: ...
-
-#   The preference form requires the following information:
-#   wine_type, price, occasion, food_to_be_paired_with_wine, country, grape_variety, flavors, aromas.
-
-#   You must follow the following guidelines:
-#     1) If specific information required in the preference form is not available in the query or there isn't any, mark with 'NA' to indicate this.
-#       Additionally, words like 'any' or 'unlimited' mean no information is available.
-#     2) Use the conversion table to convert the descriptive word level of sweetness, intensity, tannin, and acidity into a corresponding integer.
-#     3) Do not generate other comments.
-
-#   You should then respond to the user with the following points:
-#   - reasoning: State your understanding of the current situation
-#   - wine_type: Can be one of: "red", "white", "sparkling", "rose", "dessert" or "fortified"
-#   - price: Must be an integer representing the cost of the wine.
-#   - occasion: ...
-#   - food_to_be_paired_with_wine: food that the user will be served with wine
-#   - country: wine's country of origin
-#   - region: wine's region of origin such as Burgundy, Napa Valley
-#   - grape variety: a single name of grape used to make wine.
-#   - flavors: Names of items that the wine tastes like.
-#   - aromas: wine's aroma
-
-#   You should only respond in the form as described below:
-#   reasoning: ...
-#   wine_type: ...
-#   price: ...
-#   occasion: ...
-#   food_to_be_paired_with_wine: ...
-#   country: ...
-#   region: ...
-#   grape_variety: ...
-#   flavors: ...
-#   aromas: ...
-
-#   Let's begin!
-#   """
-
-#   attributes = ["reasoning", "wine_type", "price", "occasion", "food_to_be_paired_with_wine", "country", "region", "grape_variety", "flavors", "aromas"]
-#   errornote = ""
-#   for attempt in 1:5
-
-#     usermsg =
-#     """
-#     User's query: $input
-#     $errornote
-#     """
-
-#     _prompt = 
-#     [
-#       Dict(:name=> "system", :text=> systemmsg),
-#       Dict(:name=> "user", :text=> usermsg)
-#     ]
-
-#     # put in model format
-#     prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
-#     prompt *=
-#       """
-#       <|start_header_id|>assistant<|end_header_id|>
-#       """
-
-#     try
-#       response = a.func[:text2textInstructLLM](prompt)
-#       responsedict = GeneralUtils.textToDict(response, attributes, rightmarker=":", symbolkey=true)
-
-#       for i ∈ attributes
-#         if length(JSON3.write(responsedict[Symbol(i)])) == 0
-#           error("$i is empty ", @__LINE__)
-#         end
-#       end
-
-#       #[PENDING] check if the following attributes has more than 1 name
-#       x = length(split(responsedict[:grape_variety], ",")) * length(split(responsedict[:grape_variety], "/"))
-#       if x > 1
-#         errornote = "only a single name in grape_variety is allowed"
-#         error("only a single grape_variety name is allowed")
-#       end
-#       x = length(split(responsedict[:country], ",")) * length(split(responsedict[:country], "/"))
-#       if x > 1
-#         errornote = "only a single name in country is allowed"
-#         error("only a single country name is allowed")
-#       end
-#       x = length(split(responsedict[:region], ",")) * length(split(responsedict[:region], "/"))
-#       if x > 1
-#         errornote = "only a single name in region is allowed"
-#         error("only a single region name is allowed")
-#       end
-
-#       # check if grape_variety is mentioned in the input
-#       if responsedict[:grape_variety] != "NA" && !occursin(responsedict[:grape_variety], input)
-#         error("$(responsedict[:grape_variety]) is not mentioned in the input")
-#       end
-
-#       responsedict[:flavors] = replace(responsedict[:flavors], "notes"=>"")
-#       delete!(responsedict, :reasoning)
-#       delete!(responsedict, :tasting_notes)
-#       delete!(responsedict, :flavors)
-#       delete!(responsedict, :aromas)
-
-#       # remove (some text)
-#       for (k, v) in responsedict
-#         _v = replace(v, r"\(.*?\)" => "")
-#         responsedict[k] = _v
-#       end
-
-#       result = ""
-#       for (k, v) in responsedict
-#         # some time LLM generate text with "(some comment)". this line removes it
-#         if !occursin("NA", v) && v != "" && !occursin("none", v) && !occursin("None", v)
-#           result *= "$k: $v, "
-#         end
-#       end
-
-#       #[PENDING] remove halucination. "highend dry white wine" --> "wine_type: white, occasion: special occasion, food_to_be_paired_with_wine: seafood, fish, country: France, Italy, USA, grape_variety: Chardonnay, Sauvignon Blanc, Pinot Grigio\nwine_notes: citrus, green apple, floral"
-      
-#       result = result[1:end-2]  # remove the ending ", "
-
-#       return result
-#     catch e
-#       io = IOBuffer()
-#       showerror(io, e)
-#       errorMsg = String(take!(io))
-#       st = sprint((io, v) -> show(io, "text/plain", v), stacktrace(catch_backtrace()))
-#       println("")
-#       println("Attempt $attempt. Error occurred: $errorMsg\n$st")
-#       println("")
-#     end
-#   end
-#   error("wineattributes_wordToNumber() failed to get a response")
-# end
-
 
 """ Attemp to correct LLM response's incorrect JSON response.
 
@@ -1133,7 +1002,7 @@ end
 #         state[:isterminal] = true
 #         state[:reward] = 1
 #       end
-#       println("--> 5 Evaluator ", @__FILE__, " ", @__LINE__)
+#       println("--> 5 Evaluator ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
 #       pprintln(Dict(responsedict))
 #       return responsedict[:score]
 #     catch e

src/type.jl

@@ -11,8 +11,8 @@ abstract type agent end
 
 
 mutable struct companion <: agent
-  name::String  # agent name
   id::String    # agent id
+  systemmsg::Union{String, Nothing}
   maxHistoryMsg::Integer  # e.g. 21th and earlier messages will get summarized
 
   """ Memory
@@ -34,8 +34,8 @@ end
 function companion(
   text2textInstructLLM::Function
   ;
-  name::String= "Assistant",
   id::String= string(uuid4()),
+  systemmsg::Union{String, Nothing}= nothing,
   maxHistoryMsg::Integer= 20,
   chathistory::Vector{Dict{Symbol, String}} = Vector{Dict{Symbol, String}}(),
   )
@@ -48,13 +48,13 @@ function companion(
             )
 
   newAgent = companion(
-    name,
+                        id,
-    id,
+                        systemmsg,
-    maxHistoryMsg,
+                        maxHistoryMsg,
-    chathistory,
+                        chathistory,
-    memory,
+                        memory,
-    text2textInstructLLM
+                        text2textInstructLLM
-    )
+                      )
   
   return newAgent
 end
@@ -146,7 +146,6 @@ mutable struct sommelier <: agent
   """
   chathistory::Vector{Dict{Symbol, Any}}
   memory::Dict{Symbol, Any}
-
   func  # NamedTuple of functions 
 end
 
@@ -179,14 +178,17 @@ function sommelier(
       # ),
     )
 
-    memory = Dict{Symbol, Any}(
+  memory = Dict{Symbol, Any}(
-              :chatbox=> "",
+            :chatbox=> "",
-              :shortmem=> OrderedDict{Symbol, Any}(),
+            :shortmem=> OrderedDict{Symbol, Any}(
-              :events=> Vector{Dict{Symbol, Any}}(),
+              :available_wine=> [],
-              :state=> Dict{Symbol, Any}(
+              :found_wine=> [], # used by decisionMaker(). This is to prevent decisionMaker() keep presenting the same wines
-                :wine_presented_to_user=> "None",
+            ),
-              ),
+            :events=> Vector{Dict{Symbol, Any}}(),
-            )
+            :state=> Dict{Symbol, Any}(
+            ),
+            :recap=> OrderedDict{Symbol, Any}(),
+          )
 
   newAgent = sommelier(
     name,

src/util.jl

@@ -1,6 +1,7 @@
 module util
 
-export clearhistory, addNewMessage, vectorOfDictToText, eventdict, noises
+export clearhistory, addNewMessage, chatHistoryToText, eventdict, noises, createTimeline,
+        availableWineToText
 
 using UUIDs, Dates, DataStructures, HTTP, JSON3
 using GeneralUtils
@@ -106,7 +107,7 @@ function addNewMessage(a::T1, name::String, text::T2;
     error("name is not in agent.availableRole $(@__LINE__)")
   end
 
-  #[] summarize the oldest 10 message
+  #[PENDING] summarize the oldest 10 message
   if length(a.chathistory) > maximumMsg
     summarize(a.chathistory)
   else
@@ -138,7 +139,7 @@ julia> GeneralUtils.vectorOfDictToText(vecd, withkey=true)
 ```
 # Signature
 """
-function vectorOfDictToText(vecd::Vector; withkey=true)::String
+function chatHistoryToText(vecd::Vector; withkey=true)::String
   # Initialize an empty string to hold the final text
   text = ""
   
@@ -169,11 +170,34 @@ function vectorOfDictToText(vecd::Vector; withkey=true)::String
 end
 
 
+function availableWineToText(vecd::Vector)::String
+  # Initialize an empty string to hold the final text
+  rowtext = ""
+  # Loop through each dictionary in the input vector
+  for (i, d) in enumerate(vecd)
+    # Iterate over all key-value pairs in the dictionary
+    temp = []
+    for (k, v) in d
+      # Append the formatted string to the text variable
+      t = "$k:$v"
+      push!(temp, t)
+    end
+    _rowtext = join(temp, ',')
+    rowtext *= "$i) $_rowtext "
+  end
+  
+  return rowtext
+end
+
+
+
 function eventdict(;
   event_description::Union{String, Nothing}=nothing,
   timestamp::Union{DateTime, Nothing}=nothing,
   subject::Union{String, Nothing}=nothing,
-  action_or_dialogue::Union{String, Nothing}=nothing,
+  thought::Union{AbstractDict, Nothing}=nothing,
+  actionname::Union{String, Nothing}=nothing, # "CHAT", "CHECKINVENTORY", "PRESENTBOX", etc
+  actioninput::Union{String, Nothing}=nothing,
   location::Union{String, Nothing}=nothing,
   equipment_used::Union{String, Nothing}=nothing,
   material_used::Union{String, Nothing}=nothing,
@@ -184,7 +208,9 @@ function eventdict(;
       :event_description=> event_description,
       :timestamp=> timestamp,
       :subject=> subject,
-      :action_or_dialogue=> action_or_dialogue,
+      :thought=> thought,
+      :actionname=> actionname,
+      :actioninput=> actioninput,
       :location=> location,
       :equipment_used=> equipment_used,
       :material_used=> material_used,
@@ -194,6 +220,23 @@ function eventdict(;
 end
 
 
+function createTimeline(memory::T1; skiprecent::Integer=0) where {T1<:AbstractVector}
+  events = memory[1:end-skiprecent]
+
+  timeline = ""
+  for (i, event) in enumerate(events)
+    if event[:outcome] === nothing
+      timeline *= "$i) $(event[:subject])> $(event[:actioninput])\n"
+    else
+      timeline *= "$i) $(event[:subject])> $(event[:actioninput]) $(event[:outcome])\n"
+    end
+  end
+
+  return timeline
+end
+
+
+
 
 # """ Convert a single chat dictionary into LLM model instruct format.
 

test/config.json

@@ -31,26 +31,46 @@
       "description": "organization name"
   },
   "externalservice": {
-      "text2textinstruct": {
+    "loadbalancer": {
-          "mqtttopic": "/loadbalancer/requestingservice",
+      "mqtttopic": "/loadbalancer/requestingservice",
-          "description": "text to text service with instruct LLM",
+      "description": "text to text service with instruct LLM"
-          "llminfo": {
+    },
-              "name": "llama3instruct"
+    "text2textinstruct": {
-          }
+        "mqtttopic": "/loadbalancer/requestingservice",
-      },
+        "description": "text to text service with instruct LLM",
-      "virtualWineCustomer_1": {
+        "llminfo": {
-          "mqtttopic": "/virtualenvironment/winecustomer",
+            "name": "llama3instruct"
-          "description": "text to text service with instruct LLM that act as wine customer",
+        }
-          "llminfo": {
+    },
-              "name": "llama3instruct"
+    "virtualWineCustomer_1": {
-          }
+        "mqtttopic": "/virtualenvironment/winecustomer",
-      },
+        "description": "text to text service with instruct LLM that act as wine customer",
-      "text2textchat": {
+        "llminfo": {
-          "mqtttopic": "/loadbalancer/requestingservice",
+            "name": "llama3instruct"
-          "description": "text to text service with instruct LLM",
+        }
-          "llminfo": {
+    },
-              "name": "llama3instruct"
+    "text2textchat": {
-          }
+        "mqtttopic": "/loadbalancer/requestingservice",
-      }
+        "description": "text to text service with instruct LLM",
+        "llminfo": {
+            "name": "llama3instruct"
+        }
+    },
+    "wineDB" : {
+      "description": "A wine database connection info for LibPQ client",
+      "host": "192.168.88.12",
+      "port": 10201,
+      "dbname": "wineDB",
+      "user": "yiemtechnologies",
+      "password": "yiemtechnologies@Postgres_0.0"
+    },
+    "SQLVectorDB" : {
+      "description": "A wine database connection info for LibPQ client",
+      "host": "192.168.88.12",
+      "port": 10203,
+      "dbname": "SQLVectorDB",
+      "user": "yiemtechnologies",
+      "password": "yiemtechnologies@Postgres_0.0"
+    }
   }
 }

test/etc.jl

@@ -1,9 +0,0 @@
-using GeneralUtils
-
-response = "trajectory_evaluation:\nThe trajectory is correct so far. The thought accurately reflects the user's question, and the action taken is a valid attempt to retrieve data from the database that matches the specified criteria.\n\nanswer_evaluation:\nThe observation provides information about two red wines from Bordeaux rive droite in France, which partially answers the question. However, it does not provide a complete answer as it only lists the wine names and characteristics, but does not explicitly state whether there are any other wines that match the criteria.\n\naccepted_as_answer: No\n\nscore: 6\nThe trajectory is mostly correct, but the observation does not fully address the question.\n\nsuggestion: Consider adding more filters or parameters to the database query to retrieve a complete list of wines that match the specified criteria."
-
-responsedict = GeneralUtils.textToDict(response,
-            ["trajectory_evaluation", "answer_evaluation", "accepted_as_answer", "score", "suggestion"], 
-            rightmarker=":", symbolkey=true)
-
-

test/test_1.jl

@@ -8,31 +8,41 @@ using Base.Threads
 
 
 # load config
-config = JSON3.read("./test/config.json")
+config = JSON3.read("/appfolder/app/dev/YiemAgent/test/config.json")
 # config = copy(JSON3.read("../mountvolume/config.json"))
 
 
 function executeSQL(sql::T) where {T<:AbstractString}
-  DBconnection = LibPQ.Connection("host=192.168.88.12 port=10201 dbname=wineDB user=yiemtechnologies password=yiemtechnologies@Postgres_0.0")
+  host = config[:externalservice][:wineDB][:host]
+  port = config[:externalservice][:wineDB][:port]
+  dbname = config[:externalservice][:wineDB][:dbname]
+  user = config[:externalservice][:wineDB][:user]
+  password = config[:externalservice][:wineDB][:password]
+  DBconnection = LibPQ.Connection("host=$host port=$port dbname=$dbname user=$user password=$password")
   result = LibPQ.execute(DBconnection, sql)
   close(DBconnection)
   return result
 end
 
 function executeSQLVectorDB(sql)
-  DBconnection = LibPQ.Connection("host=192.168.88.12 port=10203 dbname=SQLVectorDB user=yiemtechnologies password=yiemtechnologies@Postgres_0.0")
+  host = config[:externalservice][:SQLVectorDB][:host]
+  port = config[:externalservice][:SQLVectorDB][:port]
+  dbname = config[:externalservice][:SQLVectorDB][:dbname]
+  user = config[:externalservice][:SQLVectorDB][:user]
+  password = config[:externalservice][:SQLVectorDB][:password]
+  DBconnection = LibPQ.Connection("host=$host port=$port dbname=$dbname user=$user password=$password")
   result = LibPQ.execute(DBconnection, sql)
   close(DBconnection)
   return result
 end
 
-function text2textInstructLLM(prompt::String)
+function text2textInstructLLM(prompt::String; maxattempt=3)
   msgMeta = GeneralUtils.generate_msgMeta(
-    config[:externalservice][:text2textinstruct][:mqtttopic];
+    config[:externalservice][:loadbalancer][:mqtttopic];
     msgPurpose="inference",
     senderName="yiemagent",
-    senderId=string(uuid4()),
+    senderId=sessionId,
-    receiverName="text2textinstruct",
+    receiverName="text2textinstruct_small",
     mqttBrokerAddress=config[:mqttServerInfo][:broker],
     mqttBrokerPort=config[:mqttServerInfo][:port],
   )
@@ -48,8 +58,20 @@ function text2textInstructLLM(prompt::String)
     )
   )
 
-  _response = GeneralUtils.sendReceiveMqttMsg(outgoingMsg; timeout=6000)
+  response = nothing
-  response = _response[:response][:text]
+  for attempts in 1:maxattempt
+    _response = GeneralUtils.sendReceiveMqttMsg(outgoingMsg; timeout=300, maxattempt=maxattempt)
+    payload = _response[:response]
+    if _response[:success] && payload[:text] !== nothing
+      response = _response[:response][:text]
+      break
+    else
+      println("\n<text2textInstructLLM()> attempt $attempts/$maxattempt failed ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
+      pprintln(outgoingMsg)
+      println("</text2textInstructLLM()> attempt $attempts/$maxattempt failed ", @__FILE__, ":", @__LINE__, " $(Dates.now())\n")
+      sleep(3)
+    end
+  end
 
   return response
 end
@@ -57,11 +79,11 @@ end
 # get text embedding from a LLM service
 function getEmbedding(text::T) where {T<:AbstractString}
   msgMeta = GeneralUtils.generate_msgMeta(
-    config[:externalservice][:text2textinstruct][:mqtttopic];
+    config[:externalservice][:loadbalancer][:mqtttopic];
     msgPurpose="embedding",
     senderName="yiemagent",
-    senderId=string(uuid4()),
+    senderId=sessionId,
-    receiverName="text2textinstruct",
+    receiverName="text2textinstruct_small",
     mqttBrokerAddress=config[:mqttServerInfo][:broker],
     mqttBrokerPort=config[:mqttServerInfo][:port],
   )
@@ -72,18 +94,16 @@ function getEmbedding(text::T) where {T<:AbstractString}
       :text => [text] # must be a vector of string
     )
   )
-  response = GeneralUtils.sendReceiveMqttMsg(outgoingMsg; timeout=6000)
+  response = GeneralUtils.sendReceiveMqttMsg(outgoingMsg; timeout=120)
   embedding = response[:response][:embeddings]
   return embedding
 end
 
 function findSimilarTextFromVectorDB(text::T1, tablename::T2, embeddingColumnName::T3,
-   vectorDB::Function; limit::Integer=1
+  vectorDB::Function; limit::Integer=1
-   )::DataFrame where {T1<:AbstractString, T2<:AbstractString, T3<:AbstractString}
+  )::DataFrame where {T1<:AbstractString, T2<:AbstractString, T3<:AbstractString}
-
   # get embedding from LLM service
   embedding = getEmbedding(text)[1]
-
   # check whether there is close enough vector already store in vectorDB. if no, add, else skip 
   sql = """
         SELECT *, $embeddingColumnName <-> '$embedding' as distance
@@ -95,29 +115,29 @@ function findSimilarTextFromVectorDB(text::T1, tablename::T2, embeddingColumnNam
   return df
 end
 
-
 function similarSQLVectorDB(query; maxdistance::Integer=100)
   tablename = "sqlllm_decision_repository"
   # get embedding of the query
   df = findSimilarTextFromVectorDB(query, tablename, 
                                   "function_input_embedding", executeSQLVectorDB)
+  # println(df[1, [:id, :function_output]])
   row, col = size(df)
   distance = row == 0 ? Inf : df[1, :distance]  
+  # distance = 100  # CHANGE this is for testing only
   if row != 0 && distance < maxdistance
     # if there is usable SQL, return it.
     output_b64 = df[1, :function_output_base64]   # pick the closest match
     output_str = String(base64decode(output_b64))
     rowid = df[1, :id]
-    println("\n~~~ found similar sql. row id $rowid, distance $distance ", @__FILE__, " ", @__LINE__)
+    println("\n~~~ found similar sql. row id $rowid, distance $distance ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
     return (dict=output_str, distance=distance)
   else
-    println("\n~~~ similar sql not found, max distance $maxdistance ", @__FILE__, " ", @__LINE__)
+    println("\n~~~ similar sql not found, max distance $maxdistance ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
     return (dict=nothing, distance=nothing)
   end
 end
 
-
+function insertSQLVectorDB(query::T1, SQL::T2; maxdistance::Integer=3) where {T1<:AbstractString, T2<:AbstractString}
-function insertSQLVectorDB(query::T1, SQL::T2; maxdistance::Integer=1) where {T1<:AbstractString, T2<:AbstractString}
   tablename = "sqlllm_decision_repository"
   # get embedding of the query
   # query = state[:thoughtHistory][:question]
@@ -134,8 +154,8 @@ function insertSQLVectorDB(query::T1, SQL::T2; maxdistance::Integer=1) where {T1
     sql = """
           INSERT INTO $tablename (function_input, function_output, function_output_base64, function_input_embedding) VALUES ('$query', '$sql_', '$sql_base64', '$query_embedding');
           """
-    println("\n~~~ added new decision to vectorDB ", @__FILE__, " ", @__LINE__)
+    # println("\n~~~ added new decision to vectorDB ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
-    println(sql)
+    # println(sql)
     _ = executeSQLVectorDB(sql)
   end
 end