update
This commit is contained in:
@@ -318,14 +318,14 @@ function decisionMaker(a::T; recent::Integer=5)::Dict{Symbol,Any} where {T<:agen
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delete!(responsedict, :mentioned_winery)
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# cache decision dict into vectorDB, this should be after new message is added to a.memory[:events]
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println("\n~~~ Do you want to cache decision dict? (y/n)")
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user_answer = readline()
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if user_answer == "y"
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timeline = timeline
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decisiondict = responsedict
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a.func[:insertSommelierDecision](timeline, decisiondict)
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end
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# #CHANGE cache decision dict into vectorDB, this should be after new message is added to a.memory[:events]
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# println("\n~~~ Do you want to cache decision dict? (y/n)")
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# user_answer = readline()
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# if user_answer == "y"
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# timeline = timeline
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# decisiondict = responsedict
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# a.func[:insertSommelierDecision](timeline, decisiondict)
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# end
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return responsedict
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catch e
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@@ -1,7 +1,7 @@
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module llmfunction
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export virtualWineUserChatbox, jsoncorrection, checkinventory, # recommendbox,
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virtualWineUserRecommendbox, userChatbox, userRecommendbox
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virtualWineUserRecommendbox, userChatbox, userRecommendbox, extractWineAttributes_1
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using HTTP, JSON3, URIs, Random, PrettyPrinting, UUIDs, Dates
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using GeneralUtils, SQLLLM
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@@ -300,7 +300,7 @@ function checkinventory(a::T1, input::T2
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# add suppport for similarSQLVectorDB
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textresult, rawresponse = SQLLLM.query(inventoryquery, a.func[:executeSQL],
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a.func[:text2textInstructLLM],
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addSQLVectorDB=a.func[:insertSQLVectorDB],
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insertSQLVectorDB=a.func[:insertSQLVectorDB],
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similarSQLVectorDB=a.func[:similarSQLVectorDB])
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println("\n~~~ checkinventory result ", @__FILE__, " ", @__LINE__)
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@@ -329,30 +329,203 @@ julia>
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# Signature
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"""
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# function extractWineAttributes_1(a::T1, input::T2)::String where {T1<:agent, T2<:AbstractString}
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# systemmsg =
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# """
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# 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.
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# At each round of conversation, the user will give you the current situation:
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# User's query: ...
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# You must follow the following guidelines:
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# 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.
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# Additionally, words like 'any' or 'unlimited' mean no information is available.
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# 2) Do not generate other comments.
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# You should then respond to the user with the following points:
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# - reasoning: state your understanding of the current situation
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# - wine_name: name of the wine
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# - winery: name of the winery
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# - vintage: the year of the wine
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# - region: a region in a country where the wine is produced, such as Burgundy, Napa Valley, etc
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# - country: a country where the wine is produced. Can be "Austria", "Australia", "France", "Germany", "Italy", "Portugal", "Spain", "United States"
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# - wine_type: can be one of: "red", "white", "sparkling", "rose", "dessert" or "fortified"
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# - grape_variety: the name of the primary grape used to make the wine
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# - tasting_notes: a brief description of the wine's taste, such as "butter", "oak", "fruity", etc
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# - wine_price: price of wine. For example, up to 100, less than 100, 20 to 100, 30-79.95
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# - occasion: the occasion the user is having the wine for
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# - food_to_be_paired_with_wine: food that the user will be served with the wine such as poultry, fish, steak, etc
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# You should only respond in the user's preference form as described below:
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# reasoning: ...
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# winery: ...
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# wine_name: ...
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# vintage: ...
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# region: ...
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# country: ...
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# wine_type: ...
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# grape_variety: ...
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# tasting_notes: ...
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# wine_price: ...
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# occasion: ...
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# food_to_be_paired_with_wine: ...
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# Here are some example:
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# User's query: red, Chenin Blanc, Riesling, under 20
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# reasoning: ...
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# winery: NA
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# wine_name: NA
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# vintage: NA
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# region: NA
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# country: NA
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# wine_type: red
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# grape_variety: Chenin Blanc, Riesling
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# tasting_notes: NA
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# wine_price: under 20
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# occasion: NA
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# food_to_be_paired_with_wine: NA
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# User's query: Domaine du Collier Saumur Blanc 2019, France, white, Chenin Blanc
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# reasoning: ...
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# winery: Domaine du Collier
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# wine_name: Saumur Blanc
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# vintage: 2019
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# region: Saumur
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# country: France
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# wine_type: white
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# grape_variety: Chenin Blanc
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# tasting_notes: NA
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# wine_price: 109
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# occasion: NA
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# food_to_be_paired_with_wine: NA
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# Let's begin!
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# """
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# attributes = ["reasoning", "winery", "wine_name", "vintage", "region", "country", "wine_type", "grape_variety", "tasting_notes", "wine_price", "occasion", "food_to_be_paired_with_wine"]
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# errornote = ""
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# maxattempt = 5
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# for attempt in 1:maxattempt
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# usermsg =
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# """
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# User's query: $input
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# $errornote
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# """
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# _prompt =
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# [
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# Dict(:name=> "system", :text=> systemmsg),
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# Dict(:name=> "user", :text=> usermsg)
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# ]
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# # put in model format
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# prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
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# prompt *=
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# """
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# <|start_header_id|>assistant<|end_header_id|>
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# """
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# try
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# response = a.func[:text2textInstructLLM](prompt)
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# response = GeneralUtils.remove_french_accents(response)
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# # check wheter all attributes are in the response
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# for word in attributes
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# if !occursin(word, response)
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# error("$word attribute is missing")
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# end
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# end
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# responsedict = GeneralUtils.textToDict(response, attributes, rightmarker=":", symbolkey=true)
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# for i ∈ attributes
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# if length(JSON3.write(responsedict[Symbol(i)])) == 0
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# error("$i is empty ", @__LINE__)
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# end
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# end
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# #check if the following attributes has more than 1 name
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# # responsedict[:grape_variety] = split(responsedict[:grape_variety], ',')[1]
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# # responsedict[:grape_variety] = split(responsedict[:grape_variety], '/')[1]
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# responsedict[:country] = split(responsedict[:country], ',')[1]
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# responsedict[:country] = split(responsedict[:country], '/')[1]
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# responsedict[:region] = split(responsedict[:region], ',')[1]
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# responsedict[:region] = split(responsedict[:region], '/')[1]
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# delete!(responsedict, :reasoning)
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# delete!(responsedict, :tasting_notes)
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# delete!(responsedict, :occasion)
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# delete!(responsedict, :food_to_be_paired_with_wine)
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# # check if winery, wine_name, region, country, wine_type, grape_variety are in the query because sometime AI halucinates
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# for i in [:grape_variety, :winery, :wine_name, :region]
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# result = check_key_in_input(input, responsedict, attempt, maxattempt, i)
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# if result === nothing
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# # nothing wrong
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# elseif result == "NA"
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# responsedict[i] = "NA"
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# else
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# errornote = result
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# error(errornote)
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# end
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# end
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# # remove (some text)
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# for (k, v) in responsedict
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# _v = replace(v, r"\(.*?\)" => "")
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# responsedict[k] = _v
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# end
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# result = ""
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# for (k, v) in responsedict
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# # some time LLM generate text with "(some comment)". this line removes it
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# if !occursin("NA", v) && v != "" && !occursin("none", v) && !occursin("None", v)
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# result *= "$k: $v, "
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# end
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# end
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# #[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"
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# result = result[1:end-2] # remove the ending ", "
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# return result
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# catch e
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# io = IOBuffer()
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# showerror(io, e)
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# errorMsg = String(take!(io))
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# st = sprint((io, v) -> show(io, "text/plain", v), stacktrace(catch_backtrace()))
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# println("")
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# println("Attempt $attempt. Error occurred: $errorMsg\n$st ", @__FILE__, " ", @__LINE__)
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# println("")
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# end
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# end
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# error("wineattributes_wordToNumber() failed to get a response")
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# end
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function extractWineAttributes_1(a::T1, input::T2)::String where {T1<:agent, T2<:AbstractString}
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systemmsg =
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"""
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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.
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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.
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At each round of conversation, the user will give you the current situation:
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User's query: ...
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The preference form requires the following information:
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wine_type, price, occasion, food_to_be_paired_with_wine, region, country, grape_variety, flavors, aromas.
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You must follow the following guidelines:
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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.
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Additionally, words like 'any' or 'unlimited' mean no information is available.
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2) Use the conversion table to convert the descriptive word level of sweetness, intensity, tannin, and acidity into a corresponding integer.
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3) Do not generate other comments.
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2) Do not generate other comments.
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You should then respond to the user with the following points:
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- reasoning: state your understanding of the current situation
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- wine_name: name of the wine
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- winery: name of the winery
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- vintage: the year of the wine
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- region: a region in a country where the wine is produced, such as Burgundy, Napa Valley, etc
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- region: a region (NOT a country) where the wine is produced, such as Burgundy, Napa Valley, etc
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- country: a country where the wine is produced. Can be "Austria", "Australia", "France", "Germany", "Italy", "Portugal", "Spain", "United States"
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- wine_type: can be one of: "red", "white", "sparkling", "rose", "dessert" or "fortified"
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- grape_variety: the name of the primary grape used to make the wine
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@@ -362,33 +535,15 @@ function extractWineAttributes_1(a::T1, input::T2)::String where {T1<:agent, T2<
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- food_to_be_paired_with_wine: food that the user will be served with the wine such as poultry, fish, steak, etc
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You should only respond in the form as described below:
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reasoning: ...
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winery: ...
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wine_name: ...
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vintage: ...
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region: ...
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country: ...
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wine_type: ...
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grape_variety: ...
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tasting_notes: ...
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wine_price: ...
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occasion: ...
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food_to_be_paired_with_wine: ...
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You should only respond in the user's preference form (JSON) as described below:
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{"reasoning": ..., "winery": ..., "wine_name": ..., "vintage": ..., "region": ..., "country": ..., "wine_type": ..., "grape_variety": ..., "tasting_notes": ..., "wine_price": ..., "occasion": ..., "food_to_be_paired_with_wine": ...}
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Here are some example:
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reasoning: ...
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winery: Domaine du Collier
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wine_name: Saumur Blanc
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vintage: 2019
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region: Saumur
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country: France
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wine_type: white
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grape_variety: Chenin Blanc
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tasting_notes: NA
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wine_price: 109
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occasion: NA
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food_to_be_paired_with_wine: NA
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User's query: red, Chenin Blanc, Riesling, under 20
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{"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"}
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User's query: Domaine du Collier Saumur Blanc 2019, France, white, Chenin Blanc
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{"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"}
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Let's begin!
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"""
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@@ -428,23 +583,7 @@ function extractWineAttributes_1(a::T1, input::T2)::String where {T1<:agent, T2<
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end
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end
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responsedict = GeneralUtils.textToDict(response, attributes, rightmarker=":", symbolkey=true)
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for i ∈ attributes
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if length(JSON3.write(responsedict[Symbol(i)])) == 0
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error("$i is empty ", @__LINE__)
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end
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end
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#check if the following attributes has more than 1 name
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responsedict[:grape_variety] = split(responsedict[:grape_variety], ',')[1]
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responsedict[:grape_variety] = split(responsedict[:grape_variety], '/')[1]
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responsedict[:country] = split(responsedict[:country], ',')[1]
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responsedict[:country] = split(responsedict[:country], '/')[1]
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responsedict[:region] = split(responsedict[:region], ',')[1]
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responsedict[:region] = split(responsedict[:region], '/')[1]
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responsedict = copy(JSON3.read(response))
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delete!(responsedict, :reasoning)
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delete!(responsedict, :tasting_notes)
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