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tonaerospace
2025-01-04 16:10:23 +07:00
parent 82167fe006
commit cff0d31ae6
4 changed files with 349 additions and 443 deletions
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461
src/llmfunction.jl
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@@ -1,7 +1,8 @@
module llmfunction
export virtualWineUserChatbox, jsoncorrection, checkinventory, # recommendbox,
virtualWineUserRecommendbox, userChatbox, userRecommendbox, extractWineAttributes_1
virtualWineUserRecommendbox, userChatbox, userRecommendbox, extractWineAttributes_1,
extractWineAttributes_2
using HTTP, JSON3, URIs, Random, PrettyPrinting, UUIDs, Dates
using GeneralUtils, SQLLLM
@@ -550,9 +551,8 @@ function extractWineAttributes_1(a::T1, input::T2)::String where {T1<:agent, T2<
attributes = ["reasoning", "winery", "wine_name", "vintage", "region", "country", "wine_type", "grape_variety", "tasting_notes", "wine_price", "occasion", "food_to_be_paired_with_wine"]
errornote = ""
maxattempt = 5
for attempt in 1:maxattempt
for attempt in 1:5
usermsg =
"""
User's query: $input
@@ -572,70 +572,63 @@ function extractWineAttributes_1(a::T1, input::T2)::String where {T1<:agent, T2<
<|start_header_id|>assistant<|end_header_id|>
"""
try
response = a.func[:text2textInstructLLM](prompt)
response = GeneralUtils.remove_french_accents(response)
response = a.func[:text2textInstructLLM](prompt)
response = GeneralUtils.remove_french_accents(response)
# check wheter all attributes are in the response
for word in attributes
if !occursin(word, response)
error("$word attribute is missing")
end
# check wheter all attributes are in the response
for word in attributes
if !occursin(word, response)
errornote = "$word attribute is missing in previous attempts"
println("Attempt $attempt $errornote ", @__FILE__, " ", @__LINE__)
continue
end
responsedict = copy(JSON3.read(response))
delete!(responsedict, :reasoning)
delete!(responsedict, :tasting_notes)
delete!(responsedict, :occasion)
delete!(responsedict, :food_to_be_paired_with_wine)
# check if winery, wine_name, region, country, wine_type, grape_variety are in the query because sometime AI halucinates
for i in [:grape_variety, :winery, :wine_name, :region]
content = responsedict[i]
if occursin(",", content)
content = split(content, ",") # sometime AI generates multiple values e.g. "Chenin Blanc, Riesling"
content = strip.(content)
else
content = [content]
end
for x in content
if !occursin("NA", responsedict[i]) && !occursin(x, input)
errornote = "$x is not mentioned in the user query, you must only use the info from the query."
error(errornote)
end
end
end
# remove (some text)
for (k, v) in responsedict
_v = replace(v, r"\(.*?\)" => "")
responsedict[k] = _v
end
result = ""
for (k, v) in responsedict
# some time LLM generate text with "(some comment)". this line removes it
if !occursin("NA", v) && v != "" && !occursin("none", v) && !occursin("None", v)
result *= "$k: $v, "
end
end
#[PENDING] remove halucination. "highend dry white wine" --> "wine_type: white, occasion: special occasion, food_to_be_paired_with_wine: seafood, fish, country: France, Italy, USA, grape_variety: Chardonnay, Sauvignon Blanc, Pinot Grigio\nwine_notes: citrus, green apple, floral"
result = result[1:end-2] # remove the ending ", "
return result
catch e
io = IOBuffer()
showerror(io, e)
errorMsg = String(take!(io))
st = sprint((io, v) -> show(io, "text/plain", v), stacktrace(catch_backtrace()))
println("")
println("Attempt $attempt. Error occurred: $errorMsg\n$st ", @__FILE__, " ", @__LINE__)
println("")
end
responsedict = copy(JSON3.read(response))
delete!(responsedict, :reasoning)
delete!(responsedict, :tasting_notes)
delete!(responsedict, :occasion)
delete!(responsedict, :food_to_be_paired_with_wine)
# check if winery, wine_name, region, country, wine_type, grape_variety are in the query because sometime AI halucinates
for i in [:grape_variety, :winery, :wine_name, :region]
content = responsedict[i]
if occursin(",", content)
content = split(content, ",") # sometime AI generates multiple values e.g. "Chenin Blanc, Riesling"
content = strip.(content)
else
content = [content]
end
for x in content
if !occursin("NA", responsedict[i]) && !occursin(x, input)
errornote = "$x is not mentioned in the user query, you must only use the info from the query."
println("Attempt $attempt $errornote ", @__FILE__, " ", @__LINE__)
continue
end
end
end
# remove (some text)
for (k, v) in responsedict
_v = replace(v, r"\(.*?\)" => "")
responsedict[k] = _v
end
result = ""
for (k, v) in responsedict
# some time LLM generate text with "(some comment)". this line removes it
if !occursin("NA", v) && v != "" && !occursin("none", v) && !occursin("None", v)
result *= "$k: $v, "
end
end
#[PENDING] remove halucination. "highend dry white wine" --> "wine_type: white, occasion: special occasion, food_to_be_paired_with_wine: seafood, fish, country: France, Italy, USA, grape_variety: Chardonnay, Sauvignon Blanc, Pinot Grigio\nwine_notes: citrus, green apple, floral"
result = result[1:end-2] # remove the ending ", "
return result
end
error("wineattributes_wordToNumber() failed to get a response")
end
@@ -643,6 +636,7 @@ end
"""
# TODO
- [PENDING] "French dry white wines with medium bod" the LLM does not recognize sweetness. use LLM self questioning to solve.
- [PENDING] French Syrah, Viognier, under 100. LLM extract intensiry of 3-5. why?
"""
function extractWineAttributes_2(a::T1, input::T2)::String where {T1<:agent, T2<:AbstractString}
@@ -675,8 +669,6 @@ function extractWineAttributes_2(a::T1, input::T2)::String where {T1<:agent, T2<
4 to 5: May correspond to "high acidity" or a similar description.
"""
# chathistory = vectorOfDictToText(a.chathistory)
systemmsg =
"""
As an helpful sommelier, your task is to fill out the user's preference form based on the corresponding words from the user's query.
@@ -695,254 +687,135 @@ function extractWineAttributes_2(a::T1, input::T2)::String where {T1<:agent, T2<
3) Do not generate other comments.
You should then respond to the user with the following points:
- reasoning: State your understanding of the current situation
- sweetness_keyword: The exact keywords in the user's query describing the sweetness level of the wine.
- sweetness: ( S ), where ( S ) represents integers indicating the range of sweetness levels. Example: 1-2
- acidity_keyword: The exact keywords in the user's query describing the acidity level of the wine.
- acidity: ( A ), where ( A ) represents integers indicating the range of acidity level. Example: 3-5
- tannin_keyword: The exact keywords in the user's query describing the tannin level of the wine.
- tannin: ( T ), where ( T ) represents integers indicating the range of tannin level. Example: 1-3
- intensity_keyword: The exact keywords in the user's query describing the intensity level of the wine.
- intensity: ( I ), where ( I ) represents integers indicating the range of intensity level. Example: 2-4
- notes: Anything you want to add
You should only respond in the form as described below:
reasoning: ...
sweetness: ...
acidity: ...
tannin: ...
intensity: ...
notes: ...
You should only respond in the form (JSON) as described below:
{
"sweetness_keyword": ...,
"sweetness": ...,
"acidity_keyword": ...,
"acidity": ...,
"tannin_keyword": ...,
"tannin": ...,
"intensity_keyword": ...,
"intensity": ...
}
Here are some examples:
User's query: I want a wine with a medium-bodied, low acidity, medium tannin.
{
"sweetness_keyword": "NA",
"sweetness": "NA",
"acidity_keyword": "low acidity",
"acidity": "1-2",
"tannin_keyword": "medium tannin",
"tannin": "3-4",
"intensity_keyword": "medium-bodied",
"intensity": "3-4"
}
User's query: German red wine, under 100, pairs with spicy food
{
"sweetness_keyword": "NA",
"sweetness": "NA",
"acidity_keyword": "NA",
"acidity": "NA",
"tannin_keyword": "NA",
"tannin": "NA",
"intensity_keyword": "NA",
"intensity": "NA"
}
Let's begin!
"""
# chathistory = vectorOfDictToText(a.chathistory)
usermsg =
"""
$conversiontable
User's query: $input
"""
_prompt =
[
Dict(:name=> "system", :text=> systemmsg),
Dict(:name=> "user", :text=> usermsg)
]
# put in model format
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
prompt *=
"""
<|start_header_id|>assistant<|end_header_id|>
"""
attributes = ["reasoning", "sweetness", "acidity", "tannin", "intensity", "notes"]
errornote = ""
for attempt in 1:5
try
response = a.func[:text2textInstructLLM](prompt)
responsedict = GeneralUtils.textToDict(response, attributes, rightmarker=":", symbolkey=true)
usermsg =
"""
$conversiontable
User's query: $input
$errornote
"""
for i ∈ attributes
if length(JSON3.write(responsedict[Symbol(i)])) == 0
error("$i is empty ", @__LINE__)
end
_prompt =
[
Dict(:name=> "system", :text=> systemmsg),
Dict(:name=> "user", :text=> usermsg)
]
# put in model format
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
prompt *=
"""
<|start_header_id|>assistant<|end_header_id|>
"""
response = a.func[:text2textInstructLLM](prompt)
responsedict = copy(JSON3.read(response))
# check whether each describing keyword is in the input to prevent halucination
for i in ["sweetness", "acidity", "tannin", "intensity"]
keyword = Symbol(i * "_keyword") # e.g. sweetness_keyword
value = responsedict[keyword]
if value != "NA" && !occursin(value, input)
errornote = "WARNING. Keyword $keyword: $value does not appear in the input. You must use information from the input only"
println("Attempt $attempt $errornote ", @__FILE__, " ", @__LINE__)
continue
end
delete!(responsedict, :reasoning)
delete!(responsedict, :notes) # LLM traps. so it can add useless info here like comments.
# some time LLM think the user mentioning acidity and tannin but actually didn't
for (k, v) in responsedict
if k ∈ [:acidity, :tannin] && !occursin(string(k), input)
responsedict[k] = "NA"
end
# if value == "NA" then responsedict[i] = "NA"
# e.g. if sweetness_keyword == "NA" then sweetness = "NA"
if value == "NA"
responsedict[Symbol(i)] = "NA"
end
# remove (some text)
for (k, v) in responsedict
_v = replace(v, r"\(.*?\)" => "")
responsedict[k] = _v
end
# some time LLM not put integer range
for (k, v) in responsedict
responsedict[k] = v
if length(v) > 5
error("non-range is not allowed. $k $v")
end
end
# some time LLM says NA-2. Need to convert NA to 1
for (k, v) in responsedict
if occursin("NA", v) && occursin("-", v)
new_v = replace(v, "NA"=>"1")
responsedict[k] = new_v
end
end
result = ""
for (k, v) in responsedict
# some time LLM generate text with "(some comment)". this line removes it
if !occursin("NA", v)
result *= "$k: $v, "
end
end
result = result[1:end-2] # remove the ending ", "
return result
catch e
io = IOBuffer()
showerror(io, e)
errorMsg = String(take!(io))
st = sprint((io, v) -> show(io, "text/plain", v), stacktrace(catch_backtrace()))
println("")
println("Attempt $attempt. Error occurred: $errorMsg\n$st")
println("")
end
# some time LLM not put integer range
for (k, v) in responsedict
if !occursin("keyword", string(k))
if !occursin('-', v) || length(v) > 5
errornote = "WARNING: The non-range value for $k is not allowed. It should be specified in a range format, such as min-max."
println("Attempt $attempt $errornote ", @__FILE__, " ", @__LINE__)
continue
end
end
end
# some time LLM says NA-2. Need to convert NA to 1
for (k, v) in responsedict
if occursin("NA", v) && occursin("-", v)
new_v = replace(v, "NA"=>"1")
responsedict[k] = new_v
end
end
result = ""
for (k, v) in responsedict
# some time LLM generate text with "(some comment)". this line removes it
if !occursin("NA", v)
result *= "$k: $v, "
end
end
result = result[1:end-2] # remove the ending ", "
return result
end
error("wineattributes_wordToNumber() failed to get a response")
end
# function recommendbox(a::T1, input::T2)::String where {T1<:agent, T2<:AbstractString}
# error("recommendbox")
# systemmsg =
# """
# As an helpful sommelier, your task is to fill out the user's preference form based on the corresponding words from the user's query.
# At each round of conversation, the user will give you the current situation:
# User's query: ...
# The preference form requires the following information:
# wine_type, price, occasion, food_to_be_paired_with_wine, country, grape_variety, flavors, aromas.
# You must follow the following guidelines:
# 1) If specific information required in the preference form is not available in the query or there isn't any, mark with 'NA' to indicate this.
# Additionally, words like 'any' or 'unlimited' mean no information is available.
# 2) Use the conversion table to convert the descriptive word level of sweetness, intensity, tannin, and acidity into a corresponding integer.
# 3) Do not generate other comments.
# You should then respond to the user with the following points:
# - reasoning: State your understanding of the current situation
# - wine_type: Can be one of: "red", "white", "sparkling", "rose", "dessert" or "fortified"
# - price: Must be an integer representing the cost of the wine.
# - occasion: ...
# - food_to_be_paired_with_wine: food that the user will be served with wine
# - country: wine's country of origin
# - region: wine's region of origin such as Burgundy, Napa Valley
# - grape variety: a single name of grape used to make wine.
# - flavors: Names of items that the wine tastes like.
# - aromas: wine's aroma
# You should only respond in the form as described below:
# reasoning: ...
# wine_type: ...
# price: ...
# occasion: ...
# food_to_be_paired_with_wine: ...
# country: ...
# region: ...
# grape_variety: ...
# flavors: ...
# aromas: ...
# Let's begin!
# """
# attributes = ["reasoning", "wine_type", "price", "occasion", "food_to_be_paired_with_wine", "country", "region", "grape_variety", "flavors", "aromas"]
# errornote = ""
# for attempt in 1:5
# usermsg =
# """
# User's query: $input
# $errornote
# """
# _prompt =
# [
# Dict(:name=> "system", :text=> systemmsg),
# Dict(:name=> "user", :text=> usermsg)
# ]
# # put in model format
# prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
# prompt *=
# """
# <|start_header_id|>assistant<|end_header_id|>
# """
# try
# response = a.func[:text2textInstructLLM](prompt)
# responsedict = GeneralUtils.textToDict(response, attributes, rightmarker=":", symbolkey=true)
# for i ∈ attributes
# if length(JSON3.write(responsedict[Symbol(i)])) == 0
# error("$i is empty ", @__LINE__)
# end
# end
# #[PENDING] check if the following attributes has more than 1 name
# x = length(split(responsedict[:grape_variety], ",")) * length(split(responsedict[:grape_variety], "/"))
# if x > 1
# errornote = "only a single name in grape_variety is allowed"
# error("only a single grape_variety name is allowed")
# end
# x = length(split(responsedict[:country], ",")) * length(split(responsedict[:country], "/"))
# if x > 1
# errornote = "only a single name in country is allowed"
# error("only a single country name is allowed")
# end
# x = length(split(responsedict[:region], ",")) * length(split(responsedict[:region], "/"))
# if x > 1
# errornote = "only a single name in region is allowed"
# error("only a single region name is allowed")
# end
# # check if grape_variety is mentioned in the input
# if responsedict[:grape_variety] != "NA" && !occursin(responsedict[:grape_variety], input)
# error("$(responsedict[:grape_variety]) is not mentioned in the input")
# end
# responsedict[:flavors] = replace(responsedict[:flavors], "notes"=>"")
# delete!(responsedict, :reasoning)
# delete!(responsedict, :tasting_notes)
# delete!(responsedict, :flavors)
# delete!(responsedict, :aromas)
# # remove (some text)
# for (k, v) in responsedict
# _v = replace(v, r"\(.*?\)" => "")
# responsedict[k] = _v
# end
# result = ""
# for (k, v) in responsedict
# # some time LLM generate text with "(some comment)". this line removes it
# if !occursin("NA", v) && v != "" && !occursin("none", v) && !occursin("None", v)
# result *= "$k: $v, "
# end
# end
# #[PENDING] remove halucination. "highend dry white wine" --> "wine_type: white, occasion: special occasion, food_to_be_paired_with_wine: seafood, fish, country: France, Italy, USA, grape_variety: Chardonnay, Sauvignon Blanc, Pinot Grigio\nwine_notes: citrus, green apple, floral"
# result = result[1:end-2] # remove the ending ", "
# return result
# catch e
# io = IOBuffer()
# showerror(io, e)
# errorMsg = String(take!(io))
# st = sprint((io, v) -> show(io, "text/plain", v), stacktrace(catch_backtrace()))
# println("")
# println("Attempt $attempt. Error occurred: $errorMsg\n$st")
# println("")
# end
# end
# error("wineattributes_wordToNumber() failed to get a response")
# end
""" Attemp to correct LLM response's incorrect JSON response.
# Arguments