update

Reviewed-on: #4

Manifest.toml

@@ -1,8 +1,8 @@
 # This file is machine-generated - editing it directly is not advised
 
-julia_version = "1.11.2"
+julia_version = "1.11.4"
 manifest_format = "2.0"
-project_hash = "b483014657ef9f0fde60d7258585b291d6f0eeca"
+project_hash = "cb7f3c57318e927e8ac4dc2dea9acdcace566ed1"
 
 [[deps.AliasTables]]
 deps = ["PtrArrays", "Random"]
@@ -120,9 +120,9 @@ version = "1.11.0"
 
 [[deps.Distributions]]
 deps = ["AliasTables", "FillArrays", "LinearAlgebra", "PDMats", "Printf", "QuadGK", "Random", "SpecialFunctions", "Statistics", "StatsAPI", "StatsBase", "StatsFuns"]
-git-tree-sha1 = "3101c32aab536e7a27b1763c0797dba151b899ad"
+git-tree-sha1 = "0b4190661e8a4e51a842070e7dd4fae440ddb7f4"
 uuid = "31c24e10-a181-5473-b8eb-7969acd0382f"
-version = "0.25.113"
+version = "0.25.118"
 
     [deps.Distributions.extensions]
     DistributionsChainRulesCoreExt = "ChainRulesCore"
@@ -158,9 +158,9 @@ version = "0.1.10"
 
 [[deps.FileIO]]
 deps = ["Pkg", "Requires", "UUIDs"]
-git-tree-sha1 = "2dd20384bf8c6d411b5c7370865b1e9b26cb2ea3"
+git-tree-sha1 = "b66970a70db13f45b7e57fbda1736e1cf72174ea"
 uuid = "5789e2e9-d7fb-5bc7-8068-2c6fae9b9549"
-version = "1.16.6"
+version = "1.17.0"
 weakdeps = ["HTTP"]
 
     [deps.FileIO.extensions]
@@ -168,9 +168,9 @@ weakdeps = ["HTTP"]
 
 [[deps.FilePathsBase]]
 deps = ["Compat", "Dates"]
-git-tree-sha1 = "7878ff7172a8e6beedd1dea14bd27c3c6340d361"
+git-tree-sha1 = "3bab2c5aa25e7840a4b065805c0cdfc01f3068d2"
 uuid = "48062228-2e41-5def-b9a4-89aafe57970f"
-version = "0.9.22"
+version = "0.9.24"
 weakdeps = ["Mmap", "Test"]
 
     [deps.FilePathsBase.extensions]
@@ -200,11 +200,9 @@ version = "1.11.0"
 
 [[deps.GeneralUtils]]
 deps = ["CSV", "DataFrames", "DataStructures", "Dates", "Distributions", "JSON3", "MQTTClient", "PrettyPrinting", "Random", "SHA", "UUIDs"]
-git-tree-sha1 = "978d9a5c3fc30205dd72d4a2a2ed4fa85ebee5cf"
+path = "/appfolder/app/dev/GeneralUtils"
-repo-rev = "main"
-repo-url = "https://git.yiem.cc/ton/GeneralUtils"
 uuid = "c6c72f09-b708-4ac8-ac7c-2084d70108fe"
-version = "0.1.0"
+version = "0.2.3"
 
 [[deps.HTTP]]
 deps = ["Base64", "CodecZlib", "ConcurrentUtilities", "Dates", "ExceptionUnwrapping", "Logging", "LoggingExtras", "MbedTLS", "NetworkOptions", "OpenSSL", "PrecompileTools", "Random", "SimpleBufferStream", "Sockets", "URIs", "UUIDs"]
@@ -214,9 +212,9 @@ version = "1.10.13"
 
 [[deps.HypergeometricFunctions]]
 deps = ["LinearAlgebra", "OpenLibm_jll", "SpecialFunctions"]
-git-tree-sha1 = "b1c2585431c382e3fe5805874bda6aea90a95de9"
+git-tree-sha1 = "68c173f4f449de5b438ee67ed0c9c748dc31a2ec"
 uuid = "34004b35-14d8-5ef3-9330-4cdb6864b03a"
-version = "0.3.25"
+version = "0.3.28"
 
 [[deps.ICU_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
@@ -260,9 +258,9 @@ uuid = "41ab1584-1d38-5bbf-9106-f11c6c58b48f"
 version = "1.3.0"
 
 [[deps.IrrationalConstants]]
-git-tree-sha1 = "630b497eafcc20001bba38a4651b327dcfc491d2"
+git-tree-sha1 = "e2222959fbc6c19554dc15174c81bf7bf3aa691c"
 uuid = "92d709cd-6900-40b7-9082-c6be49f344b6"
-version = "0.2.2"
+version = "0.2.4"
 
 [[deps.IterTools]]
 git-tree-sha1 = "42d5f897009e7ff2cf88db414a389e5ed1bdd023"
@@ -305,12 +303,10 @@ uuid = "b39eb1a6-c29a-53d7-8c32-632cd16f18da"
 version = "1.19.3+0"
 
 [[deps.LLMMCTS]]
-deps = ["GeneralUtils", "JSON3"]
+deps = ["GeneralUtils", "JSON3", "PrettyPrinting"]
-git-tree-sha1 = "d8c653b8fafbd3757b7332985efaf1fdb8b6fe97"
+path = "/appfolder/app/dev/LLMMCTS"
-repo-rev = "main"
-repo-url = "https://git.yiem.cc/ton/LLMMCTS"
 uuid = "d76c5a4d-449e-4835-8cc4-dd86ec44f241"
-version = "0.1.2"
+version = "0.1.4"
 
 [[deps.LaTeXStrings]]
 git-tree-sha1 = "dda21b8cbd6a6c40d9d02a73230f9d70fed6918c"
@@ -370,9 +366,9 @@ version = "1.11.0"
 
 [[deps.LogExpFunctions]]
 deps = ["DocStringExtensions", "IrrationalConstants", "LinearAlgebra"]
-git-tree-sha1 = "a2d09619db4e765091ee5c6ffe8872849de0feea"
+git-tree-sha1 = "13ca9e2586b89836fd20cccf56e57e2b9ae7f38f"
 uuid = "2ab3a3ac-af41-5b50-aa03-7779005ae688"
-version = "0.3.28"
+version = "0.3.29"
 
     [deps.LogExpFunctions.extensions]
     LogExpFunctionsChainRulesCoreExt = "ChainRulesCore"
@@ -475,7 +471,7 @@ version = "0.3.27+1"
 [[deps.OpenLibm_jll]]
 deps = ["Artifacts", "Libdl"]
 uuid = "05823500-19ac-5b8b-9628-191a04bc5112"
-version = "0.8.1+2"
+version = "0.8.1+4"
 
 [[deps.OpenSSL]]
 deps = ["BitFlags", "Dates", "MozillaCACerts_jll", "OpenSSL_jll", "Sockets"]
@@ -493,7 +489,7 @@ version = "3.0.15+1"
 deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "Libdl", "Pkg"]
 git-tree-sha1 = "13652491f6856acfd2db29360e1bbcd4565d04f1"
 uuid = "efe28fd5-8261-553b-a9e1-b2916fc3738e"
-version = "0.5.5+0"
+version = "0.5.5+2"
 
 [[deps.OrderedCollections]]
 git-tree-sha1 = "12f1439c4f986bb868acda6ea33ebc78e19b95ad"
@@ -502,9 +498,9 @@ version = "1.7.0"
 
 [[deps.PDMats]]
 deps = ["LinearAlgebra", "SparseArrays", "SuiteSparse"]
-git-tree-sha1 = "949347156c25054de2db3b166c52ac4728cbad65"
+git-tree-sha1 = "48566789a6d5f6492688279e22445002d171cf76"
 uuid = "90014a1f-27ba-587c-ab20-58faa44d9150"
-version = "0.11.31"
+version = "0.11.33"
 
 [[deps.Parsers]]
 deps = ["Dates", "PrecompileTools", "UUIDs"]
@@ -556,15 +552,15 @@ uuid = "de0858da-6303-5e67-8744-51eddeeeb8d7"
 version = "1.11.0"
 
 [[deps.PtrArrays]]
-git-tree-sha1 = "77a42d78b6a92df47ab37e177b2deac405e1c88f"
+git-tree-sha1 = "1d36ef11a9aaf1e8b74dacc6a731dd1de8fd493d"
 uuid = "43287f4e-b6f4-7ad1-bb20-aadabca52c3d"
-version = "1.2.1"
+version = "1.3.0"
 
 [[deps.QuadGK]]
 deps = ["DataStructures", "LinearAlgebra"]
-git-tree-sha1 = "cda3b045cf9ef07a08ad46731f5a3165e56cf3da"
+git-tree-sha1 = "9da16da70037ba9d701192e27befedefb91ec284"
 uuid = "1fd47b50-473d-5c70-9696-f719f8f3bcdc"
-version = "2.11.1"
+version = "2.11.2"
 
     [deps.QuadGK.extensions]
     QuadGKEnzymeExt = "Enzyme"
@@ -623,11 +619,9 @@ version = "0.7.0"
 
 [[deps.SQLLLM]]
 deps = ["CSV", "DataFrames", "DataStructures", "Dates", "FileIO", "GeneralUtils", "HTTP", "JSON3", "LLMMCTS", "LibPQ", "PrettyPrinting", "Random", "Revise", "StatsBase", "Tables", "URIs", "UUIDs"]
-git-tree-sha1 = "45e660e44de0950a5e5f92d467298d8b768b6023"
+path = "/appfolder/app/dev/SQLLLM"
-repo-rev = "main"
-repo-url = "https://git.yiem.cc/ton/SQLLLM"
 uuid = "2ebc79c7-cc10-4a3a-9665-d2e1d61e63d3"
-version = "0.2.0"
+version = "0.2.4"
 
 [[deps.SQLStrings]]
 git-tree-sha1 = "55de0530689832b1d3d43491ee6b67bd54d3323c"
@@ -672,9 +666,9 @@ version = "1.11.0"
 
 [[deps.SpecialFunctions]]
 deps = ["IrrationalConstants", "LogExpFunctions", "OpenLibm_jll", "OpenSpecFun_jll"]
-git-tree-sha1 = "2f5d4697f21388cbe1ff299430dd169ef97d7e14"
+git-tree-sha1 = "64cca0c26b4f31ba18f13f6c12af7c85f478cfde"
 uuid = "276daf66-3868-5448-9aa4-cd146d93841b"
-version = "2.4.0"
+version = "2.5.0"
 
     [deps.SpecialFunctions.extensions]
     SpecialFunctionsChainRulesCoreExt = "ChainRulesCore"
@@ -699,16 +693,16 @@ uuid = "82ae8749-77ed-4fe6-ae5f-f523153014b0"
 version = "1.7.0"
 
 [[deps.StatsBase]]
-deps = ["DataAPI", "DataStructures", "LinearAlgebra", "LogExpFunctions", "Missings", "Printf", "Random", "SortingAlgorithms", "SparseArrays", "Statistics", "StatsAPI"]
+deps = ["AliasTables", "DataAPI", "DataStructures", "LinearAlgebra", "LogExpFunctions", "Missings", "Printf", "Random", "SortingAlgorithms", "SparseArrays", "Statistics", "StatsAPI"]
-git-tree-sha1 = "5cf7606d6cef84b543b483848d4ae08ad9832b21"
+git-tree-sha1 = "29321314c920c26684834965ec2ce0dacc9cf8e5"
 uuid = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
-version = "0.34.3"
+version = "0.34.4"
 
 [[deps.StatsFuns]]
 deps = ["HypergeometricFunctions", "IrrationalConstants", "LogExpFunctions", "Reexport", "Rmath", "SpecialFunctions"]
-git-tree-sha1 = "b423576adc27097764a90e163157bcfc9acf0f46"
+git-tree-sha1 = "35b09e80be285516e52c9054792c884b9216ae3c"
 uuid = "4c63d2b9-4356-54db-8cca-17b64c39e42c"
-version = "1.3.2"
+version = "1.4.0"
 
     [deps.StatsFuns.extensions]
     StatsFunsChainRulesCoreExt = "ChainRulesCore"

Project.toml

@@ -1,9 +1,10 @@
 name = "YiemAgent"
 uuid = "e012c34b-7f78-48e0-971c-7abb83b6f0a2"
 authors = ["narawat lamaiin <narawat@outlook.com>"]
-version = "0.1.3"
+version = "0.3.0"
 
 [deps]
+CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
 Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
@@ -21,7 +22,5 @@ URIs = "5c2747f8-b7ea-4ff2-ba2e-563bfd36b1d4"
 UUIDs = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
 
 [compat]
+CSV = "0.10.15"
 DataFrames = "1.7.0"
-GeneralUtils = "0.1, 0.2"
-LLMMCTS = "0.1.2"
-SQLLLM = "0.2.0"

fast_inference_guideline.txt

@@ -0,0 +1,72 @@
+To make **LLM-driven inference** fast while maintaining its dynamic capabilities, there are a few practices or approaches to avoid, as they could lead to performance bottlenecks or inefficiencies. Here's what *not* to do:
+
+---
+
+### **1. Avoid Using Overly Large Models for Every Query**
+While larger LLMs like GPT-4 provide high accuracy and nuanced responses, they may slow down real-time processing due to their computational complexity. Instead:
+- Use distilled or smaller models (e.g., GPT-3.5 Turbo or fine-tuned versions) for faster inference without compromising much on quality.
+
+---
+
+### **2. Avoid Excessive Entity Preprocessing**
+Don’t rely on overly complicated preprocessing steps (like advanced NER models or regex-heavy pipelines) to extract entities from the query before invoking the LLM. This could add latency. Instead:
+- Design efficient prompts that allow the LLM to extract entities and generate responses simultaneously.
+
+---
+
+### **3. Avoid Asking the LLM Multiple Separate Questions**
+Running the LLM for multiple subtasks—for example, entity extraction first and response generation second—can significantly slow down the pipeline. Instead:
+- Create prompts that combine tasks into one pass, e.g., *"Identify the city name and generate a weather response for this query: 'What's the weather in London?'"*.
+
+---
+
+### **4. Don’t Overload the LLM with Context History**
+Excessively lengthy conversation history or irrelevant context in your prompts can slow down inference times. Instead:
+- Provide only the relevant context for each query, trimming unnecessary parts of the conversation.
+
+---
+
+### **5. Avoid Real-Time Dependence on External APIs**
+Using external APIs to fetch supplementary data (e.g., weather details or location info) during every query can introduce latency. Instead:
+- Pre-fetch API data asynchronously and use the LLM to integrate it dynamically into responses.
+
+---
+
+### **6. Avoid Running LLM on Underpowered Hardware**
+Running inference on CPUs or low-spec GPUs will result in slower response times. Instead:
+- Deploy the LLM on optimized infrastructure (e.g., high-performance GPUs like NVIDIA A100 or cloud platforms like Azure AI) to reduce latency.
+
+---
+
+### **7. Skip Lengthy Generative Prompts**
+Avoid prompts that encourage the LLM to produce overly detailed or verbose responses, as these take longer to process. Instead:
+- Use concise prompts that focus on generating actionable or succinct answers.
+
+---
+
+### **8. Don’t Ignore Optimization Techniques**
+Failing to optimize your LLM setup can drastically impact performance. For example:
+- Avoid skipping techniques like model quantization (reducing numerical precision to speed up inference) or distillation (training smaller models).
+
+---
+
+### **9. Don’t Neglect Response Caching**
+While you may not want a full caching system to avoid sunk costs, dismissing lightweight caching entirely can impact speed. Instead:
+- Use temporary session-based caching for very frequent queries, without committing to a full-fledged cache infrastructure.
+
+---
+
+### **10. Avoid One-Size-Fits-All Solutions**
+Applying the same LLM inference method to all queries—whether simple or complex—will waste processing resources. Instead:
+- Route basic queries to faster, specialized models and use the LLM for nuanced or multi-step queries only.
+
+---
+
+### Summary: Focus on Efficient Design
+By avoiding these pitfalls, you can ensure that LLM-driven inference remains fast and responsive:
+- Optimize prompts.
+- Use smaller models for simpler queries.
+- Run the LLM on high-performance hardware.
+- Trim unnecessary preprocessing or contextual steps.
+
+Would you like me to help refine a prompt or suggest specific tools to complement your implementation? Let me know!

src/llmfunction.jl

@@ -1,10 +1,10 @@
 module llmfunction
 
-export  virtualWineUserChatbox, jsoncorrection, checkinventory, # recommendbox,
+export  virtualWineUserChatbox, jsoncorrection, checkwine, # recommendbox,
         virtualWineUserRecommendbox, userChatbox, userRecommendbox, extractWineAttributes_1,
         extractWineAttributes_2, paraphrase
 
-using HTTP, JSON3, URIs, Random, PrettyPrinting, UUIDs, Dates
+using HTTP, JSON3, URIs, Random, PrettyPrinting, UUIDs, Dates, DataFrames
 using GeneralUtils, SQLLLM
 using ..type, ..util
 
@@ -288,23 +288,47 @@ julia> result = checkinventory(agent, input)
 
 # Signature
 """
-function checkinventory(a::T1, input::T2
+function checkwine(a::T1, input::T2; maxattempt::Int=3
   ) where {T1<:agent, T2<:AbstractString}
 
-  println("\n~~~ checkinventory order: $input ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
+  println("\ncheckinventory order: $input ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
   wineattributes_1 = extractWineAttributes_1(a, input)
   wineattributes_2 = extractWineAttributes_2(a, input)
 
-  _inventoryquery = "retailer name: $(a.retailername), $wineattributes_1, $wineattributes_2"
+  # placeholder
-  inventoryquery = "Retrieves winery, wine_name, vintage, region, country, wine_type, grape, serving_temperature, sweetness, intensity, tannin, acidity, tasting_notes, price and currency of wines that match the following criteria - {$_inventoryquery}"
+  textresult = nothing
-  println("~~~ checkinventory input: $inventoryquery ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
+  rawresponse = nothing
-  # add suppport for similarSQLVectorDB
+  
-  textresult, rawresponse = SQLLLM.query(inventoryquery, a.func[:executeSQL], 
+  for i in 1:maxattempt
-                        a.func[:text2textInstructLLM],
-                        insertSQLVectorDB=a.func[:insertSQLVectorDB], 
-                        similarSQLVectorDB=a.func[:similarSQLVectorDB])
 
-  println("\n~~~ checkinventory result ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
+    #CHANGE if you want to add retailer name
+    # _inventoryquery = "retailer name: $(a.retailername), $wineattributes_1, $wineattributes_2"
+    _inventoryquery = "$wineattributes_1, $wineattributes_2"
+    
+    retrieve_attributes = ["winery", "wine_name", "wine_id", "vintage", "region", "country", "wine_type", "grape", "serving_temperature", "sweetness", "intensity", "tannin", "acidity", "tasting_notes", "price", "currency"]
+    inventoryquery = "Retrieves $retrieve_attributes of wines that match the following criteria - {$_inventoryquery}"
+    println("\ncheckinventory input: $inventoryquery ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
+    # add suppport for similarSQLVectorDB
+    textresult, rawresponse = SQLLLM.query(inventoryquery, a.func[:executeSQL], 
+                          a.func[:text2textInstructLLM];
+                          insertSQLVectorDB=a.func[:insertSQLVectorDB], 
+                          similarSQLVectorDB=a.func[:similarSQLVectorDB],
+                          llmFormatName="qwen3")
+    # check if all of retrieve_attributes appears in textresult
+    isin = [occursin(x, textresult) for x in retrieve_attributes]
+    # check if rawresponse type is DataFrame so that I can check for column
+    if typeof(rawresponse) == DataFrame && 
+      !occursin("The resulting table has 0 row", textresult) &&
+      !all(isin)
+      
+      errornote = "Not all of $retrieve_attributes appear in search result"
+      println("\nERROR YiemAgent checkwine() $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
+      continue
+    else
+      break
+    end
+  end
+  println("\ncheckinventory result ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
   println(textresult)
 
   return (result=textresult, rawresponse=rawresponse, success=true, errormsg=nothing)
@@ -330,142 +354,218 @@ julia>
 
 # Signature
 """
-function extractWineAttributes_1(a::T1, input::T2)::String where {T1<:agent, T2<:AbstractString}
+function extractWineAttributes_1(a::T1, input::T2; maxattempt=10
+  )::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 following:
-  User's query: ...
+   - The query: the query provided by the user.
 
   You must follow the following guidelines:
-    - 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 "N/A" to indicate this.
       Additionally, words like 'any' or 'unlimited' mean no information is available.
     - Do not generate other comments.
 
   You should then respond to the user with:
-    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, such as Burgundy, Bordeaux, Champagne, Napa Valley, Tuscany, California, Oregon, etc
-    Region: a region (NOT a country) where the wine is produced, such as Burgundy, Napa Valley, etc
+    country: a country where 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_varietal: 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 word describe the wine's flavor, such as "butter", "oak", "fruity", "raspberry", "earthy", "floral", etc
-    Tasting_notes: a brief description of the wine's taste, such as "butter", "oak", "fruity", etc
+    wine_price_min: minimum price range of wine. Example: For wine price 20, wine_price_min will be 0. For wine price 10 to 100, wine_price_min will be 10.
-    Wine_price: price range of wine.
+    wine_price_max: maximum price range of wine. Example: For wine price 20, wine_price_max will be 20. For wine price 10 to 100, wine_price_max will be 100.
-    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 JSON format as described below:
-  Comprehension: ...
+    {
-  Wine_name: ...
+      "wine_name": "...",
-  Winery: ...
+      "winery": "...",
-  Vintage: ...
+      "vintage": "...",
-  Region: ...
+      "region": "...",
-  Country: ...
+      "country": "...",
-  Wine_type:
+      "wine_type": "...",
-  Grape_varietal: ...
+      "grape_varietal": "...",
-  Tasting_notes: ...
+      "tasting_notes": "...",
-  Wine_price: ...
+      "wine_price_min": "...",
-  Occasion: ...
+      "wine_price_max": "...",
-  Food_to_be_paired_with_wine: ...
+      "occasion": "...",
-  
+      "food_to_be_paired_with_wine": "..."
-  Here are some example:
+    }
-  User's query: red, Chenin Blanc, Riesling, 20 USD
+    
-  {"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"}
+    Here are some example:
-
+    
-  User's query: Domaine du Collier Saumur Blanc 2019, France, white, Chenin Blanc
+    User's query: red, Chenin Blanc, Riesling, 20 USD from Tuscany, Italy or Napa Valley, USA
-  {"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"}
+    {
-
+      "wine_name": "N/A",
-  Let's begin!
+      "winery": "N/A",
+      "vintage": "N/A",
+      "region": "Tuscany or Napa Valley",
+      "country": "Italy or United States",
+      "wine_type": "red or white",
+      "grape_varietal": "Chenin Blanc or Riesling",
+      "tasting_notes": "citrus",
+      "wine_price_min": "0",
+      "wine_price_max": "20",
+      "occasion": "N/A",
+      "food_to_be_paired_with_wine": "N/A"
+    }
+    
+    User's query: Domaine du Collier Saumur Blanc 2019, France, white, Merlot
+    {
+      "wine_name": "Saumur Blanc",
+      "winery": "Domaine du Collier",
+      "vintage": "2019",
+      "region": "Saumur",
+      "country": "France",
+      "wine_type": "white",
+      "grape_varietal": "Merlot",
+      "tasting_notes": "plum",
+      "wine_price_min": "N/A",
+      "wine_price_max": "N/A",
+      "occasion": "N/A",
+      "food_to_be_paired_with_wine": "N/A"
+    }
+    
+    Let's begin!
   """
 
-  header = ["Comprehension:", "Wine_name:", "Winery:", "Vintage:", "Region:", "Country:", "Wine_type:", "Grape_varietal:", "Tasting_notes:", "Wine_price:", "Occasion:", "Food_to_be_paired_with_wine:"]
+  requiredKeys = [:wine_name, :winery, :vintage, :region, :country, :wine_type, :grape_varietal, :tasting_notes, :wine_price_min, :wine_price_max, :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 = "N/A"
-  errornote = ""
-  
-  for attempt in 1:5
-    usermsg =
-    """
-    User's query: $input
-    $errornote
-    """
 
-    _prompt = 
+  for attempt in 1:maxattempt
+    usermsg =
+      """
+      $input
+      """
+    context = 
+      """
+      <context>
+      P.S. $errornote
+      </context>
+      /no_think
+      """
+
+    unformatPrompt = 
     [
       Dict(:name=> "system", :text=> systemmsg),
       Dict(:name=> "user", :text=> usermsg)
     ]
 
     # put in model format
-    prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen")
+    prompt = GeneralUtils.formatLLMtext(unformatPrompt, a.llmFormatName)
-    response = a.func[:text2textInstructLLM](prompt)
+    # add info
+    prompt = prompt * context
+
+    response = a.func[:text2textInstructLLM](prompt; modelsize="medium", senderId=a.id)
+    response = GeneralUtils.deFormatLLMtext(response, a.llmFormatName)
     response = GeneralUtils.remove_french_accents(response)
+    think, response = GeneralUtils.extractthink(response)
 
-    # check wheter all attributes are in the response
+    responsedict = nothing
-    checkFlag = false
+    try
-    for word in header
+      responsedict = copy(JSON3.read(response))  
-      if !occursin(word, response)
+    catch
-        errornote = "$word attribute is missing in previous attempts"
+      println("\nERROR YiemAgent extractWineAttributes_1() failed to parse response: $response ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
-        println("Attempt $attempt $errornote ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
+      continue
-        checkFlag = true
-        break
-      end
     end
-    checkFlag == true ? continue : nothing
+
+    # check whether all answer's key points are in responsedict
+    _responsedictKey = keys(responsedict)
+    responsedictKey = [i for i in _responsedictKey] # convert into a list
+    is_requiredKeys_in_responsedictKey = [i ∈ responsedictKey for i in requiredKeys]
+
+    if length(is_requiredKeys_in_responsedictKey) > length(requiredKeys)
+      errornote = "Your previous attempt has more key points than answer's required key points."
+      println("\nERROR YiemAgent extractWineAttributes_1() $errornote --> $response ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
+      continue
+    elseif !all(is_requiredKeys_in_responsedictKey)
+      zeroind = findall(x -> x == 0, is_requiredKeys_in_responsedictKey)
+      missingkeys = [requiredKeys[i] for i in zeroind]
+      errornote = "$missingkeys are missing from your previous response"
+      println("\nERROR YiemAgent extractWineAttributes_1() $errornote --> $response ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
+      continue
+    end
+
+    # # check whether response has all header
+    # detected_kw = GeneralUtils.detect_keyword(header, response)
+    # kwvalue = [i for i in values(detected_kw)]
+    # zeroind = findall(x -> x == 0, kwvalue)
+    # missingkeys = [header[i] for i in zeroind]
+    # if 0 ∈ values(detected_kw)
+    #   errornote = "$missingkeys are missing from your previous response"
+    #   println("\nERROR YiemAgent decisionMaker() $errornote:\n$response ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
+    #   continue
+    # elseif sum(values(detected_kw)) > length(header)
+    #   errornote = "Your previous attempt has duplicated points"
+    #   println("\nERROR YiemAgent decisionMaker() $errornote:\n$response ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
+    #   continue
+    # end
     
-    # check whether response has all header
+    # # check whether response has all answer's key points
-    detected_kw = GeneralUtils.detect_keyword(header, response)
+    # detected_kw = GeneralUtils.detect_keyword(header, response)
-    if sum(values(detected_kw)) < length(header)
+    # if 0 ∈ values(detected_kw)
-      errornote = "\nYiemAgent extractWineAttributes_1() response does not have all header"
+    #   errornote = "In your previous attempts, the response does not have all answer's key points"
-      continue
+    #   println("\nYiemAgent extractWineAttributes_1() Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
-    elseif sum(values(detected_kw)) > length(header)
+    #   continue
-      errornote = "\nYiemAgent extractWineAttributes_1() response has duplicated header"
+    # elseif sum(values(detected_kw)) > length(header)
-      continue
+    #   errornote = "In your previous attempts, the response has duplicated answer's key points"
-    end
+    #   println("\nYiemAgent extractWineAttributes_1() Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
-    responsedict = GeneralUtils.textToDict(response, header; 
+    #   println(response)
-                                            dictKey=dictkey, symbolkey=true)
+    #   continue
+    # end
+    # responsedict = GeneralUtils.textToDict(response, header; 
+    #                                         dictKey=dictkey, symbolkey=true)
 
-    delete!(responsedict, :comprehension)
+    removekeys = [:thought, :tasting_notes, :occasion, :food_to_be_paired_with_wine, :vintage]
+    for i in removekeys
+      delete!(responsedict, i)
+    end
+
+
+
+    delete!(responsedict, :thought)
     delete!(responsedict, :tasting_notes)
     delete!(responsedict, :occasion)
     delete!(responsedict, :food_to_be_paired_with_wine)
-
+    delete!(responsedict, :vintage)
-    println(@__FILE__, " ", @__LINE__)
-    pprintln(responsedict)
 
     # check if winery, wine_name, region, country, wine_type, grape_varietal's value are in the query because sometime AI halucinates
     checkFlag = false
-    for i in dictkey
+    for i in requiredKeys
       j = Symbol(i)
-      if j ∉ [:comprehension, :tasting_notes, :occasion, :food_to_be_paired_with_wine]
+      if j ∉ removekeys
         # 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" 
+          if responsedict[:wine_price] != "N/A" 
             # check whether wine_price is in ranged number
-            if !occursin('-', responsedict[:wine_price]) 
+            if !occursin("to", responsedict[:wine_price]) 
-              errornote = "wine_price must be a range number"
+              errornote = "In your previous attempt, the 'wine_price' was set to $(responsedict[:wine_price]) which is not a correct format. Please adjust it accordingly."
-              println("Attempt $attempt $errornote ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
+              println("\nERROR YiemAgent extractWineAttributes_1() $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
               checkFlag = true
               break
             end
 
-            # check whether max wine_price is in the input
+            # # check whether max wine_price is in the input
-            pricerange = split(responsedict[:wine_price], '-')
+            # pricerange = split(responsedict[:wine_price], '-')
-            minprice = pricerange[1]
+            # minprice = pricerange[1]
-            maxprice = pricerange[end]
+            # maxprice = pricerange[end]
-            if !occursin(maxprice, input)
+            # if !occursin(maxprice, input)
-              responsedict[:wine_price] = "NA"
+            #   responsedict[:wine_price] = "N/A"
-            end
+            # end
-            # price range like 100-100 is not good
+            # # price range like 100-100 is not good
-            if minprice == maxprice
+            # if minprice == maxprice
-              errornote = "wine_price with minimum equals to maximum is not valid"
+            #   errornote = "In your previous attempt, you inputted 'wine_price' with a 'minimum' value equaling the 'maximum', which is not valid."
-              println("Attempt $attempt $errornote ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
+            #   println("\nERROR YiemAgent extractWineAttributes_1() $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
-              checkFlag = true
+            #   checkFlag = true
-              break
+            #   break
-            end
+            # end
           end
         else
           content = responsedict[j]
@@ -478,14 +578,14 @@ function extractWineAttributes_1(a::T1, input::T2)::String where {T1<:agent, T2<
             content = [content]
           end
 
-          for x in content  #check whether price are mentioned in the input
+          # for x in content  #check whether price are mentioned in the input
-            if !occursin("NA", responsedict[j]) && !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."
-              println("Attempt $attempt $errornote ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
+          #     println("ERROR YiemAgent extractWineAttributes_1() $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
-              checkFlag == true
+          #     checkFlag == true
-              break
+          #     break
-            end
+          #   end
-          end
+          # end
         end
       end
     end
@@ -500,7 +600,7 @@ function extractWineAttributes_1(a::T1, input::T2)::String where {T1<:agent, T2<
     result = ""
     for (k, v) in responsedict
       # some time LLM generate text with "(some comment)". this line removes it
-      if !occursin("NA", v) && v != "" && !occursin("none", v) && !occursin("None", v)
+      if !occursin("N/A", v) && v != "" && !occursin("none", v) && !occursin("None", v)
         result *= "$k: $v, "
       end
     end
@@ -523,7 +623,7 @@ function extractWineAttributes_2(a::T1, input::T2)::String where {T1<:agent, T2<
 
   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.
@@ -548,149 +648,177 @@ 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>
+  </conversion_table>
   """
 
   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:
+  At each round of conversation, you will be given the following information:
-  Conversion Table: ...
+  conversion_table: a conversion table that maps descriptive words to their corresponding integer levels
-  User's query: ...
+  query: the words from the user's query that describe their preferences
 
   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.
+    1) If specific information required in the preference form is not available in the query or there isn't any, mark with 'N/A' 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:
-
+    sweetness_keyword: The exact keywords in the user's query describing the sweetness level of the wine.
-  <You should then respond to the user with>
+    sweetness: ( S ), where ( S ) represents integers indicating the range of sweetness levels. Example: 1-2
-    Sweetness_keyword: The exact keywords in the user's query describing the sweetness level of the wine.
+    acidity_keyword: The exact keywords in the user's query describing the acidity level of the wine.
-    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_keyword: The exact keywords in the user's query describing the tannin level of the wine.
-    Acidity: ( A ), where ( A ) represents integers indicating the range of acidity level. Example: 3-5
+    tannin: ( T ), where ( T ) represents integers indicating the range of tannin level. Example: 1-3
-    Tannin_keyword: The exact keywords in the user's query describing the tannin level of the wine.
+    intensity_keyword: The exact keywords in the user's query describing the intensity level of the wine.
-    Tannin: ( T ), where ( T ) represents integers indicating the range of tannin level. Example: 1-3
+    intensity: ( I ), where ( I ) represents integers indicating the range of intensity level. Example: 2-4
-    Intensity_keyword: The exact keywords in the user's query describing the intensity level of the wine.
+  You should only respond in JSON format as described below:
-    Intensity: ( I ), where ( I ) represents integers indicating the range of intensity level. Example: 2-4
+  {
-  </You should then respond to the user with>
+    "sweetness_keyword": "...",
-
+    "sweetness": "...",
-  <You should only respond in format as described below>
+    "acidity_keyword": "...",
-    Sweetness_keyword: ...
+    "acidity": "...",
-    Sweetness: ...
+    "tannin_keyword": "...",
-    Acidity_keyword: ...
+    "tannin": "...",
-    Acidity: ...
+    "intensity_keyword": "...",
-    Tannin_keyword: ...
+    "intensity": "..."
-    Tannin: ...
+  }
-    Intensity_keyword: ...
+    
-    Intensity: ...
+  Here are some examples:
-  </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
+    "sweetness_keyword": "N/A",
-    Acidity_keyword: low acidity
+    "sweetness": "N/A",
-    Acidity: 1-2
+    "acidity_keyword": "low acidity",
-    Tannin_keyword: medium tannin
+    "acidity": "1-2",
-    Tannin: 3-4
+    "tannin_keyword": "medium tannin",
-    Intensity_keyword: medium-bodied
+    "tannin": "3-4",
-    Intensity: 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
+    "sweetness_keyword": "N/A",
-    Acidity_keyword: NA
+    "sweetness": "N/A",
-    Acidity: NA
+    "acidity_keyword": "N/A",
-    Tannin_keyword: NA
+    "acidity": "N/A",
-    Tannin: NA
+    "tannin_keyword": "N/A",
-    Intensity_keyword: NA
+    "tannin": "N/A",
-    Intensity: NA
+    "intensity_keyword": "N/A",
-  </Here are some examples>
+    "intensity": "N/A"
+    }
 
   Let's begin!
   """
-  header = ["Sweetness_keyword:", "Sweetness:", "Acidity_keyword:", "Acidity:", "Tannin_keyword:", "Tannin:", "Intensity_keyword:", "Intensity:"]
+  requiredKeys = [: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 = ""
+  # 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 = "N/A"
 
   for attempt in 1:10
-    usermsg =
+    context =
     """
     $conversiontable
-    User's query: $input
+    <query> 
-    $errornote
+    $input
+    </query>
+    P.S. $errornote
+    /no_think
     """
 
-    _prompt = 
+    unformatPrompt = 
     [
       Dict(:name=> "system", :text=> systemmsg),
-      Dict(:name=> "user", :text=> usermsg)
     ]
 
     # put in model format
-    prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen")
+    prompt = GeneralUtils.formatLLMtext(unformatPrompt, a.llmFormatName)
+    # add info
+    prompt = prompt * context
 
-    response = a.func[:text2textInstructLLM](prompt)
+    response = a.func[:text2textInstructLLM](prompt; modelsize="medium", senderId=a.id)
-    
+    response = GeneralUtils.deFormatLLMtext(response, a.llmFormatName)
-    # check whether response has all header
+    response = GeneralUtils.remove_french_accents(response)
-    detected_kw = GeneralUtils.detect_keyword(header, response)
+    think, response = GeneralUtils.extractthink(response)
-    if sum(values(detected_kw)) < length(header)
+
-      errornote = "\nYiemAgent extractWineAttributes_2() response does not have all header"
+    responsedict = nothing
-      continue
+    try
-    elseif sum(values(detected_kw)) > length(header)
+      responsedict = copy(JSON3.read(response))  
-      errornote = "\nYiemAgent extractWineAttributes_2() response has duplicated header"
+    catch
+      println("\nERROR YiemAgent extractWineAttributes_2() failed to parse response: $response ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
       continue
     end
 
-    responsedict = GeneralUtils.textToDict(response, header; 
+    # check whether all answer's key points are in responsedict
-                                            dictKey=dictkey, symbolkey=true)
+    _responsedictKey = keys(responsedict)
+    responsedictKey = [i for i in _responsedictKey] # convert into a list
+    is_requiredKeys_in_responsedictKey = [i ∈ responsedictKey for i in requiredKeys]
+
+    if length(is_requiredKeys_in_responsedictKey) > length(requiredKeys)
+      errornote = "Your previous attempt has more key points than answer's required key points."
+      println("\nERROR YiemAgent extractWineAttributes_2() $errornote --> $response ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
+      continue
+    elseif !all(is_requiredKeys_in_responsedictKey)
+      zeroind = findall(x -> x == 0, is_requiredKeys_in_responsedictKey)
+      missingkeys = [requiredKeys[i] for i in zeroind]
+      errornote = "$missingkeys are missing from your previous response"
+      println("\nERROR YiemAgent extractWineAttributes_2() $errornote --> $response ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
+      continue
+    end
 
     # 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)
+      if value != "N/A" && !occursin(value, input)
-        errornote = "WARNING. Keyword $keyword: $value does not appear in the input. You must use information from the input only"
+        errornote = "In your previous attempt, 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__)
+        println("\nERROR YiemAgent extractWineAttributes_2() Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
         continue
       end
 
-      # if value == "NA" then responsedict[i] = "NA" 
+      # if value == "N/A" then responsedict[i] = "N/A" 
-      # e.g. if sweetness_keyword == "NA" then sweetness = "NA"
+      # e.g. if sweetness_keyword == "N/A" then sweetness = "N/A"
-      if value == "NA"
+      if value == "N/A"
-        responsedict[Symbol(i)] = "NA"
+        responsedict[Symbol(i)] = "N/A"
       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)
+        if v !== "N/A" && (!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__)
+          println("\nERROR YiemAgent extractWineAttributes_2() Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
           continue
         end
       end
     end
 
-    # some time LLM says NA-2. Need to convert NA to 1
+    # some time LLM says N/A-2. Need to convert N/A to 1
     for (k, v) in responsedict
-      if occursin("NA", v) && occursin("-", v)
+      if occursin("N/A", v) && occursin("-", v)
-        new_v = replace(v, "NA"=>"1")
+        new_v = replace(v, "N/A"=>"1")
         responsedict[k] = new_v
       end
     end
 
+    # delete some key words from responsedict
+    for (k, v) in responsedict
+      if k ∈ [:sweetness_keyword, :acidity_keyword, :tannin_keyword, :intensity_keyword]
+        delete!(responsedict, k)
+      end
+    end
+
     result = ""
     for (k, v) in responsedict
       # some time LLM generate text with "(some comment)". this line removes it
-      if !occursin("NA", v)
+      if !occursin("N/A", v)
         result *= "$k: $v, "
       end
     end
@@ -731,22 +859,26 @@ function paraphrase(text2textInstructLLM::Function, text::String)
     - N/A
 
     You should then respond to the user with:
-    1) Paraphrase: Paraphrased text
+    Paraphrase: Paraphrased text
 
     You should only respond in format as described below:
     Paraphrase: ...
 
     Let's begin!
   """
+      #[WORKING] use JSON3 the same as extractWineAttributes_1 is better
+  #[WORKING] change this function to use the same format use decisionMater
+  header = ["Paraphrase:"]
+  dictkey = ["paraphrase"]
 
-  errornote = ""
+  errornote = "N/A"
   response = nothing # placeholder for show when error msg show up
 
 
   for attempt in 1:10
     usermsg = """
               Text: $text
-              $errornote
+              P.S. $errornote
               """
 
     _prompt =
@@ -756,17 +888,16 @@ function paraphrase(text2textInstructLLM::Function, text::String)
       ]
 
     # put in model format
-    prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
+    prompt = GeneralUtils.formatLLMtext(_prompt, a.llmFormatName)
-    prompt *= """
-              <|start_header_id|>assistant<|end_header_id|>
-              """
 
     try
       response = text2textInstructLLM(prompt)
+      response = GeneralUtils.deFormatLLMtext(response, a.llmFormatName)
+      think, response = GeneralUtils.extractthink(response)
       # 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__)
+        error("\nparaphrase() response contain : ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
       end
       response = GeneralUtils.remove_french_accents(response)
       response = replace(response, '*'=>"")
@@ -774,14 +905,22 @@ function paraphrase(text2textInstructLLM::Function, text::String)
       response = replace(response, '`' => "")
       response = GeneralUtils.remove_french_accents(response)
 
-      header = ["Paraphrase:"]
+      # check whether response has all answer's key points
-      dictkey = ["paraphrase"]
+      detected_kw = GeneralUtils.detect_keyword(header, response)
+      if 0 ∈ values(detected_kw)
+        errornote = "\nYiemAgent paraphrase() response does not have all answer's key points"
+        continue
+      elseif sum(values(detected_kw)) > length(header)
+        errornote = "\nnYiemAgent paraphrase() response has duplicated answer's key points"
+        continue
+      end
+
       responsedict = GeneralUtils.textToDict(response, header; 
                                             dictKey=dictkey, symbolkey=true)
 
       for i ∈ [:paraphrase]
         if length(JSON3.write(responsedict[i])) == 0
-          error("$i is empty ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
+          error("$i is empty ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
         end
       end
 
@@ -793,7 +932,7 @@ function paraphrase(text2textInstructLLM::Function, text::String)
         end
       end
 
-      println("\n~~~ paraphrase() ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
+      println("\nparaphrase() ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
       pprintln(Dict(responsedict))
 
       result = responsedict[:paraphrase]
@@ -804,10 +943,10 @@ function paraphrase(text2textInstructLLM::Function, text::String)
       showerror(io, e)
       errorMsg = String(take!(io))
       st = sprint((io, v) -> show(io, "text/plain", v), stacktrace(catch_backtrace()))
-      println("\nAttempt $attempt. Error occurred: $errorMsg\n$st ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
+      println("\nAttempt $attempt. Error occurred: $errorMsg\n$st ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
     end
   end
-  error("generatechat failed to generate a response")
+  error("paraphrase() failed to generate a response")
 end
 
 
@@ -970,7 +1109,7 @@ end
 #   ]
 
 #   # put in model format
-#   prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
+#   prompt = GeneralUtils.formatLLMtext(_prompt, "granite3")
 #   prompt *=
 #     """
 #     <|start_header_id|>assistant<|end_header_id|>
@@ -1002,7 +1141,7 @@ end
 #         state[:isterminal] = true
 #         state[:reward] = 1
 #       end
-#       println("--> 5 Evaluator ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
+#       println("--> 5 Evaluator ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
 #       pprintln(Dict(responsedict))
 #       return responsedict[:score]
 #     catch e

src/type.jl

@@ -1,6 +1,6 @@
 module type
   
-export agent, sommelier, companion
+export agent, sommelier, companion, virtualcustomer
 
 using Dates, UUIDs, DataStructures, JSON3
 using GeneralUtils
@@ -9,11 +9,44 @@ using GeneralUtils
 
 abstract type agent end
 
-
 mutable struct companion <: agent
+  name::String  # agent name
   id::String    # agent id
-  systemmsg::Union{String, Nothing}
+  systemmsg::String # system message
+  tools::Dict  # tools
   maxHistoryMsg::Integer  # e.g. 21th and earlier messages will get summarized
+  chathistory::Vector{Dict{Symbol, Any}}
+  memory::Dict{Symbol, Any}
+  func::NamedTuple  # NamedTuple of functions 
+  llmFormatName::String
+end
+
+function companion(
+  func::NamedTuple  # NamedTuple of functions
+  ;
+  name::String= "Assistant",
+  id::String= GeneralUtils.uuid4snakecase(), 
+  maxHistoryMsg::Integer= 20,
+  chathistory::Vector{Dict{Symbol, String}} = Vector{Dict{Symbol, String}}(),
+  llmFormatName::String= "granite3",
+  systemmsg::String=
+    """
+      Your name: $name
+      Your sex: Female
+      Your role: You are a helpful assistant.
+      You should follow the following guidelines:
+      - Focus on the latest conversation.
+      - Your like to be short and concise.
+
+      Let's begin!
+      """,
+  )
+
+  tools = Dict( # update input format
+      "CHATBOX"=> Dict(
+        :description => "- CHATBOX which you can use to talk with the user. The input is your intentions for the dialogue. Be specific.",
+      ),
+    )
 
   """ Memory
     Ref: Chat prompt format https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/discussions/3
@@ -22,45 +55,31 @@ mutable struct companion <: agent
       Dict(:name=>"user", :text=> "Wassup!", :timestamp=> Dates.now()),
       Dict(:name=>"assistant", :text=> "Hi I'm your assistant.", :timestamp=> Dates.now()),
     ]
-
   """
-  chathistory::Vector{Dict{Symbol, Any}}
-  memory::Dict{Symbol, Any}
-
-  # communication function
-  text2textInstructLLM::Function
-end
-
-function companion(
-  text2textInstructLLM::Function
-  ;
-  id::String= string(uuid4()),
-  systemmsg::Union{String, Nothing}= nothing,
-  maxHistoryMsg::Integer= 20,
-  chathistory::Vector{Dict{Symbol, String}} = Vector{Dict{Symbol, String}}(),
-  )
-
   memory = Dict{Symbol, Any}(
-              :chatbox=> "",
+            :events=> Vector{Dict{Symbol, Any}}(),
-              :shortmem=> OrderedDict{Symbol, Any}(),
+            :state=> Dict{Symbol, Any}(), # state of the agent
-              :events=> Vector{Dict{Symbol, Any}}(),
+            :recap=> OrderedDict{Symbol, Any}(),  # recap summary of the conversation
-              :state=> Dict{Symbol, Any}(),
+          )
-            )
 
   newAgent = companion(
-                        id,
+    name,
-                        systemmsg,
+    id,
-                        maxHistoryMsg,
+    systemmsg,
-                        chathistory,
+    tools,
-                        memory,
+    maxHistoryMsg,
-                        text2textInstructLLM
+    chathistory,
-                      )
+    memory,
+    func,
+    llmFormatName
+    )
   
   return newAgent
 end
 
 
 
+
 """ A sommelier agent.
 
 # Arguments
@@ -134,19 +153,10 @@ mutable struct sommelier <: agent
   retailername::String
   tools::Dict   
   maxHistoryMsg::Integer  # e.g. 21th and earlier messages will get summarized
-
-  """ Memory
-    Ref: Chat prompt format https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/discussions/3
-    NO "system" message in chathistory because I want to add it at the inference time
-    chathistory= [
-      Dict(:name=>"user", :text=> "Wassup!", :timestamp=> Dates.now()),
-      Dict(:name=>"assistant", :text=> "Hi I'm your assistant.", :timestamp=> Dates.now()),
-    ]
-
-  """
   chathistory::Vector{Dict{Symbol, Any}}
   memory::Dict{Symbol, Any}
   func  # NamedTuple of functions 
+  llmFormatName::String
 end
 
 function sommelier(
@@ -157,6 +167,7 @@ function sommelier(
   retailername::String= "retailer_name",
   maxHistoryMsg::Integer= 20,
   chathistory::Vector{Dict{Symbol, String}} = Vector{Dict{Symbol, String}}(),
+  llmFormatName::String= "granite3"
   )
 
   tools = Dict( # update input format
@@ -170,24 +181,26 @@ function sommelier(
         :input => """<input>Input is a JSON-formatted string that contains a detailed and precise search query.</input><input example>{\"wine type\": \"rose\", \"price\": \"max 35\", \"sweetness level\": \"sweet\", \"intensity level\": \"light bodied\", \"Tannin level\": \"low\", \"Acidity level\": \"low\"}</input example>""",
         :output => """<output>Output are wines that match the search query in JSON format.""",
       ),
-      # "finalanswer"=> Dict(
-      #   :description => "<tool description>Useful for when you are ready to recommend wines to the user.</tool description>",
-      #   :input => """<input format>{\"finalanswer\": \"some text\"}.</input format><input example>{\"finalanswer\": \"I recommend Zena Crown Vista\"}</input example>""",
-      #   :output => "" ,
-      #   :func => nothing,
-      # ),
     )
 
+  """ Memory
+    Ref: Chat prompt format https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/discussions/3
+    NO "system" message in chathistory because I want to add it at the inference time
+    chathistory= [
+      Dict(:name=>"user", :text=> "Wassup!", :timestamp=> Dates.now()),
+      Dict(:name=>"assistant", :text=> "Hi I'm your assistant.", :timestamp=> Dates.now()),
+    ]
+  """
   memory = Dict{Symbol, Any}(
-            :chatbox=> "",
             :shortmem=> OrderedDict{Symbol, Any}(
-              :available_wine=> [],
+              :db_search_result=> Any[],
-              :found_wine=> [], # used by decisionMaker(). This is to prevent decisionMaker() keep presenting the same wines
+              :scratchpad=> "", #[PENDING] should be a dict e.g. Dict(:database_search_result=>Dict(:wines=> "", :search_query=> ""))
             ),
             :events=> Vector{Dict{Symbol, Any}}(),
             :state=> Dict{Symbol, Any}(
             ),
             :recap=> OrderedDict{Symbol, Any}(),
+            
           )
 
   newAgent = sommelier(
@@ -198,7 +211,82 @@ function sommelier(
     maxHistoryMsg,
     chathistory,
     memory,
-    func
+    func,
+    llmFormatName
+    )
+  
+  return newAgent
+end
+
+
+mutable struct virtualcustomer <: agent
+  name::String  # agent name
+  id::String    # agent id
+  systemmsg::String # system message
+  tools::Dict   
+  maxHistoryMsg::Integer  # e.g. 21th and earlier messages will get summarized
+  chathistory::Vector{Dict{Symbol, Any}}
+  memory::Dict{Symbol, Any}
+  func  # NamedTuple of functions 
+  llmFormatName::String
+end
+
+function virtualcustomer(
+  func,  # NamedTuple of functions
+  ;
+  name::String= "Assistant",
+  id::String= string(uuid4()),
+  maxHistoryMsg::Integer= 20,
+  chathistory::Vector{Dict{Symbol, String}} = Vector{Dict{Symbol, String}}(),
+  llmFormatName::String= "granite3",
+  systemmsg::String=
+    """
+      Your name: $name
+      Your sex: Female
+      Your role: You are a helpful assistant.
+      You should follow the following guidelines:
+      - Focus on the latest conversation.
+      - Your like to be short and concise.
+
+      Let's begin!
+      """,
+  )
+
+  tools = Dict( # update input format
+      "chatbox"=> Dict(
+        :description => "<askbox tool description>Useful for when you need to ask the user for more context. Do not ask the user their own question.</askbox tool description>",
+        :input => """<input>Input is a text in JSON format.</input><input example>{\"Q1\": \"How are you doing?\", \"Q2\": \"How may I help you?\"}</input example>""",
+        :output => "" ,
+      ),
+    )
+
+  """ Memory
+    Ref: Chat prompt format https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/discussions/3
+    NO "system" message in chathistory because I want to add it at the inference time
+    chathistory= [
+      Dict(:name=>"user", :text=> "Wassup!", :timestamp=> Dates.now()),
+      Dict(:name=>"assistant", :text=> "Hi I'm your assistant.", :timestamp=> Dates.now()),
+    ]
+  """
+  memory = Dict{Symbol, Any}(
+            :shortmem=> OrderedDict{Symbol, Any}(
+            ),
+            :events=> Vector{Dict{Symbol, Any}}(),
+            :state=> Dict{Symbol, Any}(
+            ),
+            :recap=> OrderedDict{Symbol, Any}(),
+          )
+
+  newAgent = virtualcustomer(
+    name,
+    id,
+    systemmsg,
+    tools,
+    maxHistoryMsg,
+    chathistory,
+    memory,
+    func,
+    llmFormatName
     )
   
   return newAgent

src/util.jl

@@ -1,7 +1,7 @@
 module util
 
 export clearhistory, addNewMessage, chatHistoryToText, eventdict, noises, createTimeline,
-        availableWineToText
+        availableWineToText, createEventsLog, createChatLog
 
 using UUIDs, Dates, DataStructures, HTTP, JSON3
 using GeneralUtils
@@ -122,47 +122,53 @@ This function takes in a vector of dictionaries and outputs a single string wher
 
 # Arguments
   - `vecd::Vector`
-    a vector of dictionaries
+    A vector of dictionaries containing chat messages
   - `withkey::Bool` 
-    whether to include the key in the output text. Default is true
+    Whether to include the name as a prefix in the output text. Default is true
+  - `range::Union{Nothing,UnitRange,Int}` 
+    Optional range of messages to include. If nothing, includes all messages
 
-# Return
+# Returns
-  a string with the formatted dictionaries
+  A formatted string where each line contains either:
+  - If withkey=true: "name> message\n"
+  - If withkey=false: "message\n"
 
 # Example
-```jldoctest
+
 julia> using Revise
 julia> using GeneralUtils
 julia> vecd = [Dict(:name => "John", :text => "Hello"), Dict(:name => "Jane", :text => "Goodbye")]
 julia> GeneralUtils.vectorOfDictToText(vecd, withkey=true)
 "John> Hello\nJane> Goodbye\n"
 ```
-# Signature
 """
-function chatHistoryToText(vecd::Vector; withkey=true)::String
+function chatHistoryToText(vecd::Vector; withkey=true, range=nothing)::String
   # Initialize an empty string to hold the final text
   text = ""
   
+  # Get the elements within the specified range, or all elements if no range provided
+  elements = isnothing(range) ? vecd : vecd[range]
+  
   # Determine whether to include the key in the output text or not
   if withkey
-      # Loop through each dictionary in the input vector
+    # Loop through each dictionary in the input vector
-      for d in vecd
+    for d in elements
-          # Extract the 'name' and 'text' keys from the dictionary
+        # Extract the 'name' and 'text' keys from the dictionary
-          name = d[:name]
+        name = titlecase(d[:name])
-          _text = d[:text]
+        _text = d[:text]
-          
+        
-          # Append the formatted string to the text variable
+        # Append the formatted string to the text variable
-          text *= "$name> $_text \n"
+        text *= "$name> $_text \n"
       end
   else
-      # Loop through each dictionary in the input vector
+    # Loop through each dictionary in the input vector
-      for d in vecd
+    for d in elements
-          # Iterate over all key-value pairs in the dictionary
+        # Iterate over all key-value pairs in the dictionary
-          for (k, v) in d
+        for (k, v) in d
-              # Append the formatted string to the text variable
+            # Append the formatted string to the text variable
-              text *= "$v \n"
+            text *= "$v \n"
-          end
+        end
-      end
+    end
   end
   
   # Return the final text
@@ -191,6 +197,35 @@ end
 
 
 
+""" Create a dictionary representing an event with optional details.
+
+# Arguments
+  - `event_description::Union{String, Nothing}`
+    A description of the event
+  - `timestamp::Union{DateTime, Nothing}`
+    The time when the event occurred
+  - `subject::Union{String, Nothing}`
+    The subject or entity associated with the event
+  - `thought::Union{AbstractDict, Nothing}`
+    Any associated thoughts or metadata
+  - `actionname::Union{String, Nothing}`
+    The name of the action performed (e.g., "CHAT", "CHECKINVENTORY")
+  - `actioninput::Union{String, Nothing}`
+    Input or parameters for the action
+  - `location::Union{String, Nothing}`
+    Where the event took place
+  - `equipment_used::Union{String, Nothing}`
+    Equipment involved in the event
+  - `material_used::Union{String, Nothing}`
+    Materials used during the event
+  - `outcome::Union{String, Nothing}`
+    The result or consequence of the event after action execution
+  - `note::Union{String, Nothing}`
+    Additional notes or comments
+
+# Returns
+  A dictionary with event details as symbol-keyed key-value pairs
+"""
 function eventdict(;
   event_description::Union{String, Nothing}=nothing,
   timestamp::Union{DateTime, Nothing}=nothing,
@@ -204,255 +239,173 @@ function eventdict(;
   outcome::Union{String, Nothing}=nothing,
   note::Union{String, Nothing}=nothing,
   )
-  return Dict{Symbol, Any}(
+
-      :event_description=> event_description,
+  d = Dict{Symbol, Any}(
-      :timestamp=> timestamp,
+    :event_description=> event_description,
-      :subject=> subject,
+    :timestamp=> timestamp,
-      :thought=> thought,
+    :subject=> subject,
-      :actionname=> actionname,
+    :thought=> thought,
-      :actioninput=> actioninput,
+    :actionname=> actionname,
-      :location=> location,
+    :actioninput=> actioninput,
-      :equipment_used=> equipment_used,
+    :location=> location,
-      :material_used=> material_used,
+    :equipment_used=> equipment_used,
-      :outcome=> outcome,
+    :material_used=> material_used,
-      :note=> note,
+    :outcome=> outcome,
-    )
+    :note=> note,
+  )
+
+  return d
 end
 
 
-function createTimeline(memory::T1; skiprecent::Integer=0) where {T1<:AbstractVector}
+""" Create a formatted timeline string from a sequence of events.
-  events = memory[1:end-skiprecent]
 
+# Arguments
+  - `events::T1`
+    Vector of event dictionaries containing subject, actioninput and optional outcome fields
+    Each event dictionary should have the following keys:
+    - :subject - The subject or entity performing the action
+    - :actioninput - The action or input performed by the subject
+    - :outcome - (Optional) The result or outcome of the action
+
+# Returns
+  - `timeline::String`
+    A formatted string representing the events with their subjects, actions, and optional outcomes
+    Format: "{index}) {subject}> {actioninput} {outcome}\n" for each event
+
+# Example
+
+events = [
+  Dict(:subject => "User", :actioninput => "Hello", :outcome => nothing),
+  Dict(:subject => "Assistant", :actioninput => "Hi there!", :outcome => "with a smile")
+]
+timeline = createTimeline(events)
+# 1) User> Hello
+# 2) Assistant> Hi there! with a smile
+
+"""
+function createTimeline(events::T1; eventindex::Union{UnitRange, Nothing}=nothing
+  ) where {T1<:AbstractVector}
+  # Initialize empty timeline string
   timeline = ""
-  for (i, event) in enumerate(events)
+  
-    if event[:outcome] === nothing
+  # Determine which indices to use - either provided range or full length
-      timeline *= "$i) $(event[:subject])> $(event[:actioninput])\n"
+  ind = 
+    if eventindex !== nothing
+      [eventindex...]
     else
-      timeline *= "$i) $(event[:subject])> $(event[:actioninput]) $(event[:outcome])\n"
+      1:length(events)
+    end
+
+  #[WORKING] Iterate through events and format each one
+  for i in ind
+    event = events[i]
+    # If no outcome exists, format without outcome
+    # if event[:actionname] == "CHATBOX"
+    #   timeline *= "Event_$i $(event[:subject])> action_name: $(event[:actionname]), action_input: $(event[:actioninput])\n"
+    # elseif event[:actionname] == "CHECKINVENTORY" && event[:outcome] === nothing
+    #   timeline *= "Event_$i $(event[:subject])> action_name: $(event[:actionname]), action_input: $(event[:actioninput]), observation: Not done yet.\n"
+    # If outcome exists, include it in formatting  
+    if event[:actionname] == "CHECKWINE"
+      timeline *= "Event_$i $(event[:subject])> action_name: $(event[:actionname]), action_input: $(event[:actioninput]), observation: $(event[:outcome])\n"
+    else
+      timeline *= "Event_$i $(event[:subject])> action_name: $(event[:actionname]), action_input: $(event[:actioninput])\n"
     end
   end
 
+  # Return formatted timeline string
   return timeline
 end
+# function createTimeline(events::T1; eventindex::Union{UnitRange, Nothing}=nothing
+#   ) where {T1<:AbstractVector}
+#   # Initialize empty timeline string
+#   timeline = ""
+  
+#   # Determine which indices to use - either provided range or full length
+#   ind = 
+#     if eventindex !== nothing
+#       [eventindex...]
+#     else
+#       1:length(events)
+#     end
+
+#   # Iterate through events and format each one
+#   for i in ind
+#     event = events[i]
+#     # If no outcome exists, format without outcome
+#     if event[:outcome] === nothing
+#       timeline *= "Event_$i $(event[:subject])> action_name: $(event[:actionname]), action_input: $(event[:actioninput]), observation: Not done yet.\n"
+#     # If outcome exists, include it in formatting  
+#     else
+#       timeline *= "Event_$i $(event[:subject])> action_name: $(event[:actionname]), action_input: $(event[:actioninput]), observation: $(event[:outcome])\n"
+#     end
+#   end
+
+#   # Return formatted timeline string
+#   return timeline
+# end
+
+
+function createEventsLog(events::T1; index::Union{UnitRange, Nothing}=nothing
+  ) where {T1<:AbstractVector}
+  # Initialize empty log array
+  log = Dict{Symbol, String}[]
+
+  # Determine which indices to use - either provided range or full length
+  ind = 
+    if index !== nothing
+      [index...]
+    else
+      1:length(events)
+    end
+
+  # Iterate through events and format each one
+  for i in ind
+    event = events[i]
+    # If no outcome exists, format without outcome
+    if event[:outcome] === nothing
+      subject = event[:subject]
+      actioninput = event[:actioninput]
+      d = Dict{Symbol, String}(:name=>subject, :text=>actioninput)
+      push!(log, d)
+    else
+      subject = event[:subject]
+      actioninput = event[:actioninput]
+      outcome = event[:outcome]
+      str = "Action: $actioninput Outcome: $outcome"
+      d = Dict{Symbol, String}(:name=>subject, :text=>str)
+      push!(log, d)
+    end
+  end
+
+  return log
+end
 
 
+function createChatLog(chatdict::T1; index::Union{UnitRange, Nothing}=nothing
+  ) where {T1<:AbstractVector}
+  # Initialize empty log array
+  log = Dict{Symbol, String}[]
 
+  # Determine which indices to use - either provided range or full length
+  ind = 
+    if index !== nothing
+      [index...]
+    else
+      1:length(chatdict)
+    end
 
-# """ Convert a single chat dictionary into LLM model instruct format.
+  # Iterate through events and format each one
+  for i in ind
+    event = chatdict[i]
+    subject = event[:name]
+    text = event[:text]
+    d = Dict{Symbol, String}(:name=>subject, :text=>text)
+    push!(log, d)
+  end
 
-# # Llama 3 instruct format example
+  return log
-#   <|system|>
+end
-#   You are a helpful AI assistant.<|end|>
-#   <|user|>
-#   I am going to Paris, what should I see?<|end|>
-#   <|assistant|>
-#   Paris, the capital of France, is known for its stunning architecture, art museums."<|end|>
-#   <|user|>
-#   What is so great about #1?<|end|>
-#   <|assistant|>
-
-
-# # Arguments
-#   - `name::T`
-#     message owner name e.f. "system", "user" or "assistant"
-#   - `text::T`
-
-# # Return
-#   - `formattedtext::String`
-#     text formatted to model format
-
-# # Example
-# ```jldoctest
-# julia> using Revise
-# julia> using YiemAgent
-# julia> d = Dict(:name=> "system",:text=> "You are a helpful, respectful and honest assistant.",)
-# julia> formattedtext = YiemAgent.formatLLMtext_phi3instruct(d[:name], d[:text])
-
-# ```
-
-# Signature
-# """
-# function formatLLMtext_phi3instruct(name::T, text::T) where {T<:AbstractString}
-#   formattedtext = 
-#   """
-#   <|$name|>
-#   $text<|end|>\n
-#   """
-
-#   return formattedtext
-# end
-
-
-# """ Convert a single chat dictionary into LLM model instruct format.
-
-# # Llama 3 instruct format example
-#   <|begin_of_text|>
-#   <|start_header_id|>system<|end_header_id|>
-#   You are a helpful assistant.
-#   <|eot_id|>
-#   <|start_header_id|>user<|end_header_id|>
-#   Get me an icecream.
-#   <|eot_id|>
-#   <|start_header_id|>assistant<|end_header_id|>
-#   Go buy it yourself at 7-11.
-#   <|eot_id|>
-
-# # Arguments
-#   - `name::T`
-#     message owner name e.f. "system", "user" or "assistant"
-#   - `text::T`
-
-# # Return
-#   - `formattedtext::String`
-#     text formatted to model format
-
-# # Example
-# ```jldoctest
-# julia> using Revise
-# julia> using YiemAgent
-# julia> d = Dict(:name=> "system",:text=> "You are a helpful, respectful and honest assistant.",)
-# julia> formattedtext = YiemAgent.formatLLMtext_llama3instruct(d[:name], d[:text])
-# "<|begin_of_text|>\n  <|start_header_id|>system<|end_header_id|>\n  You are a helpful, respectful and honest assistant.\n  <|eot_id|>\n"
-# ```
-
-# Signature
-# """
-# function formatLLMtext_llama3instruct(name::T, text::T) where {T<:AbstractString}
-#   formattedtext = 
-#   if name == "system"
-#     """
-#     <|begin_of_text|>
-#     <|start_header_id|>$name<|end_header_id|>
-#     $text
-#     <|eot_id|>
-#     """
-#   else
-#     """
-#     <|start_header_id|>$name<|end_header_id|>
-#     $text
-#     <|eot_id|>
-#     """
-#   end
-
-#   return formattedtext
-# end
-
-
-
-# """ Convert a chat messages in vector of dictionary into LLM model instruct format.
-
-# # Arguments
-#   - `messages::Vector{Dict{Symbol, T}}`
-#     message owner name e.f. "system", "user" or "assistant"
-#   - `formatname::T`
-#     format name to be used
-
-# # Return
-#   - `formattedtext::String`
-#     text formatted to model format
-
-# # Example
-# ```jldoctest
-# julia> using Revise
-# julia> using YiemAgent
-# julia> chatmessage = [
-#           Dict(:name=> "system",:text=> "You are a helpful, respectful and honest assistant.",),
-#           Dict(:name=> "user",:text=> "list me all planets in our solar system.",),
-#           Dict(:name=> "assistant",:text=> "I'm sorry. I don't know. You tell me.",),
-#         ]
-# julia> formattedtext = YiemAgent.formatLLMtext(chatmessage, "llama3instruct")
-# "<|begin_of_text|>\n  <|start_header_id|>system<|end_header_id|>\n  You are a helpful, respectful and honest assistant.\n  <|eot_id|>\n  <|start_header_id|>user<|end_header_id|>\n  list me all planets in our solar system.\n  <|eot_id|>\n  <|start_header_id|>assistant<|end_header_id|>\n  I'm sorry. I don't know. You tell me.\n  <|eot_id|>\n"
-# ```
-
-# # Signature
-# """
-# function formatLLMtext(messages::Vector{Dict{Symbol, T}}, 
-#                       formatname::String="llama3instruct") where {T<:Any}
-#   f = if formatname == "llama3instruct"
-#     formatLLMtext_llama3instruct
-#   elseif formatname == "mistral"
-#     # not define yet
-#   elseif formatname == "phi3instruct"
-#     formatLLMtext_phi3instruct
-#   else
-#     error("$formatname template not define yet")
-#   end
-
-#   str = ""
-#   for t in messages
-#     str *= f(t[:name], t[:text])
-#   end
-
-#   # add <|assistant|> so that the model don't generate it and I don't need to clean it up later
-#   if formatname == "phi3instruct"
-#     str *= "<|assistant|>\n"
-#   end
-
-#   return str
-# end
-
-
-# """
-
-#   Arguments\n
-#   -----
-    
-#   Return\n
-#   -----
-
-#   Example\n
-#   -----
-#   ```jldoctest
-#   julia> 
-#   ```
-
-#   TODO\n
-#   -----
-#     [] update docstring
-#     [PENDING] implement the function
-
-#   Signature\n
-#   -----
-# """
-# function iterativeprompting(a::T, prompt::String, verification::Function) where {T<:agent}
-#   msgMeta = GeneralUtils.generate_msgMeta(
-#     a.config[:externalService][:text2textinstruct],
-#     senderName= "iterativeprompting",
-#     senderId= a.id,
-#     receiverName= "text2textinstruct",
-#   )
-
-#   outgoingMsg = Dict(
-#     :msgMeta=> msgMeta,
-#     :payload=> Dict(
-#       :text=> prompt,
-#     )
-#   )
-
-#   success = nothing
-#   result = nothing
-#   critique = ""
-
-#   # iteration loop
-#   while true
-#     # send prompt to LLM
-#     response = GeneralUtils.sendReceiveMqttMsg(outgoingMsg)
-#     error("--> iterativeprompting")
-#     # check for correctness and get feedback
-#     success, _critique = verification(response)
-
-#     if success
-#       result = response
-#       break
-#     else  
-#       # add critique to prompt
-#       critique *= _critique * "\n"
-#       replace!(prompt, "Critique: ..." => "Critique: $critique")
-#     end
-#   end
-  
-#   return (success=success, result=result)
-# end
 
 
 

test/Manifest.toml

@@ -0,0 +1,41 @@
+# This file is machine-generated - editing it directly is not advised
+
+julia_version = "1.11.4"
+manifest_format = "2.0"
+project_hash = "71d91126b5a1fb1020e1098d9d492de2a4438fd2"
+
+[[deps.Base64]]
+uuid = "2a0f44e3-6c83-55bd-87e4-b1978d98bd5f"
+version = "1.11.0"
+
+[[deps.InteractiveUtils]]
+deps = ["Markdown"]
+uuid = "b77e0a4c-d291-57a0-90e8-8db25a27a240"
+version = "1.11.0"
+
+[[deps.Logging]]
+uuid = "56ddb016-857b-54e1-b83d-db4d58db5568"
+version = "1.11.0"
+
+[[deps.Markdown]]
+deps = ["Base64"]
+uuid = "d6f4376e-aef5-505a-96c1-9c027394607a"
+version = "1.11.0"
+
+[[deps.Random]]
+deps = ["SHA"]
+uuid = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+version = "1.11.0"
+
+[[deps.SHA]]
+uuid = "ea8e919c-243c-51af-8825-aaa63cd721ce"
+version = "0.7.0"
+
+[[deps.Serialization]]
+uuid = "9e88b42a-f829-5b0c-bbe9-9e923198166b"
+version = "1.11.0"
+
+[[deps.Test]]
+deps = ["InteractiveUtils", "Logging", "Random", "Serialization"]
+uuid = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+version = "1.11.0"

test/Project.toml

@@ -0,0 +1,2 @@
+[deps]
+Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"

test/config.json

@@ -27,7 +27,7 @@
       "description": "agent role"
   },
   "organization": {
-      "value": "yiem_hq",
+      "value": "yiem_branch_1",
       "description": "organization name"
   },
   "externalservice": {

test/test_1.jl

@@ -36,13 +36,18 @@ function executeSQLVectorDB(sql)
   return result
 end
 
-function text2textInstructLLM(prompt::String; maxattempt=3)
+function text2textInstructLLM(prompt::String; maxattempt::Integer=3, modelsize::String="medium",
+    llmkwargs=Dict(
+      :num_ctx => 32768,
+      :temperature => 0.1,
+    )
+  )
   msgMeta = GeneralUtils.generate_msgMeta(
     config[:externalservice][:loadbalancer][:mqtttopic];
     msgPurpose="inference",
     senderName="yiemagent",
     senderId=sessionId,
-    receiverName="text2textinstruct_small",
+    receiverName="text2textinstruct_$modelsize",
     mqttBrokerAddress=config[:mqttServerInfo][:broker],
     mqttBrokerPort=config[:mqttServerInfo][:port],
   )
@@ -51,16 +56,13 @@ function text2textInstructLLM(prompt::String; maxattempt=3)
     :msgMeta => msgMeta,
     :payload => Dict(
       :text => prompt,
-      :kwargs => Dict(
+      :kwargs => llmkwargs
-        :num_ctx => 16384,
-        :temperature => 0.2,
-      )
     )
   )
 
   response = nothing
   for attempts in 1:maxattempt
-    _response = GeneralUtils.sendReceiveMqttMsg(outgoingMsg; timeout=300, maxattempt=maxattempt)
+    _response = GeneralUtils.sendReceiveMqttMsg(outgoingMsg; timeout=180, maxattempt=maxattempt)
     payload = _response[:response]
     if _response[:success] && payload[:text] !== nothing
       response = _response[:response][:text]
@@ -83,7 +85,7 @@ function getEmbedding(text::T) where {T<:AbstractString}
     msgPurpose="embedding",
     senderName="yiemagent",
     senderId=sessionId,
-    receiverName="text2textinstruct_small",
+    receiverName="textembedding",
     mqttBrokerAddress=config[:mqttServerInfo][:broker],
     mqttBrokerPort=config[:mqttServerInfo][:port],
   )
@@ -94,7 +96,8 @@ function getEmbedding(text::T) where {T<:AbstractString}
       :text => [text] # must be a vector of string
     )
   )
-  response = GeneralUtils.sendReceiveMqttMsg(outgoingMsg; timeout=120)
+
+  response = GeneralUtils.sendReceiveMqttMsg(outgoingMsg; timeout=120, maxattempt=3)
   embedding = response[:response][:embeddings]
   return embedding
 end
@@ -161,7 +164,7 @@ function insertSQLVectorDB(query::T1, SQL::T2; maxdistance::Integer=3) where {T1
 end
 
 
-function similarSommelierDecision(recentevents::T1; maxdistance::Integer=5
+function similarSommelierDecision(recentevents::T1; maxdistance::Integer=3
   )::Union{AbstractDict, Nothing} where {T1<:AbstractString}
   tablename = "sommelier_decision_repository"
   # find similar
@@ -194,7 +197,7 @@ function insertSommelierDecision(recentevents::T1, decision::T2; maxdistance::In
   row, col = size(df)
   distance = row == 0 ? Inf : df[1, :distance]
   if row == 0 || distance > maxdistance # no close enough SQL stored in the database
-    recentevents_embedding = a.func[:getEmbedding](recentevents)[1]
+    recentevents_embedding = getEmbedding(recentevents)[1]
     recentevents = replace(recentevents, "'" => "")
     decision_json = JSON3.write(decision)
     decision_base64 = base64encode(decision_json)
@@ -234,7 +237,7 @@ a = YiemAgent.sommelier(
 )
 
 while true
-  println("your respond: ")
+  print("\nyour respond: ")
   user_answer = readline()
   response = YiemAgent.conversation(a, Dict(:text=> user_answer))
   println("\n$response")
@@ -244,14 +247,13 @@ end
 # response = YiemAgent.conversation(a, Dict(:text=> "I want to get a French red wine under 100."))
 
 
-
+"""
-
+hello I want to get a bottle of red wine for my boss. I have a budget around 50 dollars. Show me some options.
-
+
-
+I have no idea about his wine taste but he likes spicy food.
-
+
-
+
-
+"""
-