15 Commits

Author SHA1 Message Date
narawat lamaiin
c0edf7dadf update 2025-04-04 15:04:02 +07:00
narawat lamaiin
c21f943b12 update 2025-04-01 21:17:15 +07:00
narawat lamaiin
b8fd772a28 update 2025-03-31 21:30:14 +07:00
narawat lamaiin
883f581b2a update 2025-03-22 15:34:00 +07:00
narawat lamaiin
5a890860a6 update 2025-03-22 09:42:51 +07:00
7d5bc14a09 mark new version 2025-03-21 10:13:53 +07:00
ton
37ba3a9d31 Merge pull request 'v0.1.3-dev' (#2) from v0.1.3-dev into main
Reviewed-on: #2
2025-03-21 03:09:16 +00:00
bfadd53033 update 2025-03-21 10:03:08 +07:00
8fc3afe348 update 2025-03-20 16:15:38 +07:00
c60037226a update 2025-03-13 19:11:20 +07:00
narawat lamaiin
db6c9c5f2b update 2025-03-07 13:34:15 +07:00
narawat lamaiin
6504099959 update 2025-01-31 09:50:44 +07:00
724b092bdb update 2025-01-30 21:28:49 +07:00
c56c3d02b0 update 2025-01-29 12:16:01 +07:00
ton
a7f3e29e9c Merge pull request 'WIP v0.1.2-dev' (#1) from v0.1.2-dev into main
Reviewed-on: #1
2025-01-25 07:30:18 +00:00
10 changed files with 1781 additions and 1242 deletions

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@@ -1,7 +1,7 @@
name = "YiemAgent"
uuid = "e012c34b-7f78-48e0-971c-7abb83b6f0a2"
authors = ["narawat lamaiin <narawat@outlook.com>"]
version = "0.1.2"
version = "0.1.4"
[deps]
DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"

File diff suppressed because it is too large Load Diff

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@@ -2,7 +2,7 @@ module llmfunction
export virtualWineUserChatbox, jsoncorrection, checkinventory, # recommendbox,
virtualWineUserRecommendbox, userChatbox, userRecommendbox, extractWineAttributes_1,
extractWineAttributes_2
extractWineAttributes_2, paraphrase
using HTTP, JSON3, URIs, Random, PrettyPrinting, UUIDs, Dates
using GeneralUtils, SQLLLM
@@ -291,24 +291,22 @@ julia> result = checkinventory(agent, input)
function checkinventory(a::T1, input::T2
) 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, $wineattributes_2"
inventoryquery = "Retrieves winery, wine_name, vintage, region, country, wine_type, grape, serving_temperature, sweetness, intensity, tannin, acidity, tasting_notes, price and currency of wines that match the following criteria - {$_inventoryquery}"
println("~~~ checkinventory input: $inventoryquery ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
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])
println("\n~~~ checkinventory result ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
println("\ncheckinventory result ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
println(textresult)
#[WORKING] when rawresponse is nothing, AI get errors
return (result=textresult, rawresponse=rawresponse, success=true, errormsg=nothing)
end
@@ -328,7 +326,7 @@ julia>
# TODO
- [] update docstring
- [x] implement the function
- implement the function
# Signature
"""
@@ -338,46 +336,63 @@ function extractWineAttributes_1(a::T1, input::T2)::String where {T1<:agent, T2<
"""
As a helpful sommelier, your task is to extract the user information from the user's query as much as possible to fill out user's preference form.
At each round of conversation, the user will give you the current situation:
At each round of conversation, the user will give you the following:
User's query: ...
You must follow the following guidelines:
1) If specific information required in the preference form is not available in the query or there isn't any, mark with "NA" to indicate this.
- If specific information required in the preference form is not available in the query or there isn't any, mark with "NA" to indicate this.
Additionally, words like 'any' or 'unlimited' mean no information is available.
2) Do not generate other comments.
- Do not generate other comments.
You should then respond to the user with the following points:
- reasoning: state your understanding of the current situation
- wine_name: name of the wine
- winery: name of the winery
- vintage: the year of the wine
- region: a region (NOT a country) where the wine is produced, such as Burgundy, Napa Valley, etc
- country: a country where the wine is produced. Can be "Austria", "Australia", "France", "Germany", "Italy", "Portugal", "Spain", "United States"
- 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
- tasting_notes: a brief description of the wine's taste, such as "butter", "oak", "fruity", etc
- wine_price: price range of wine.
- occasion: the occasion the user is having the wine for
- food_to_be_paired_with_wine: food that the user will be served with the wine such as poultry, fish, steak, etc
You should then respond to the user with:
Thought: state your understanding of the current situation
Wine_name: name of the wine
Winery: name of the winery
Vintage: the year of the wine
Region: a region (NOT a country) where the wine is produced, such as Burgundy, Napa Valley, etc
Country: a country where the wine is produced. Can be "Austria", "Australia", "France", "Germany", "Italy", "Portugal", "Spain", "United States"
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
Tasting_notes: a brief description of the wine's taste, such as "butter", "oak", "fruity", etc
Wine_price: price range of wine.
Occasion: the occasion the user is having the wine for
Food_to_be_paired_with_wine: food that the user will be served with the wine such as poultry, fish, steak, etc
You should only respond in the user's preference form (JSON) as described below:
{"reasoning": ..., "winery": ..., "wine_name": ..., "vintage": ..., "region": ..., "country": ..., "wine_type": ..., "grape_varietal": ..., "tasting_notes": ..., "wine_price": ..., "occasion": ..., "food_to_be_paired_with_wine": ...}
You should only respond in format as described below:
Thought: ...
Wine_name: ...
Winery: ...
Vintage: ...
Region: ...
Country: ...
Wine_type:
Grape_varietal: ...
Tasting_notes: ...
Wine_price: ...
Occasion: ...
Food_to_be_paired_with_wine: ...
Here are some example:
User's query: red, Chenin Blanc, Riesling, 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"}
User's query: Domaine du Collier Saumur Blanc 2019, France, white, Chenin Blanc
{"reasoning": ..., "winery": "Domaine du Collier", "wine_name": "Saumur Blanc", "vintage": "2019", "region": "Saumur", "country": "France", "wine_type": "white", "grape_varietal": "Chenin Blanc", "tasting_notes": "NA", "wine_price": "NA", "occasion": "NA", "food_to_be_paired_with_wine": "NA"}
User's query: Domaine du Collier Saumur Blanc 2019, France, white, Merlot
{"reasoning": ..., "winery": "Domaine du Collier", "wine_name": "Saumur Blanc", "vintage": "2019", "region": "Saumur", "country": "France", "wine_type": "white", "grape_varietal": "Merlot", "tasting_notes": "NA", "wine_price": "NA", "occasion": "NA", "food_to_be_paired_with_wine": "NA"}
Let's begin!
"""
attributes = ["reasoning", "winery", "wine_name", "vintage", "region", "country", "wine_type", "grape_varietal", "tasting_notes", "wine_price", "occasion", "food_to_be_paired_with_wine"]
header = ["Thought:", "Wine_name:", "Winery:", "Vintage:", "Region:", "Country:", "Wine_type:", "Grape_varietal:", "Tasting_notes:", "Wine_price:", "Occasion:", "Food_to_be_paired_with_wine:"]
dictkey = ["thought", "wine_name", "winery", "vintage", "region", "country", "wine_type", "grape_varietal", "tasting_notes", "wine_price", "occasion", "food_to_be_paired_with_wine"]
errornote = ""
for attempt in 1:5
for attempt in 1:10
#[WORKING] I should add generatequestion()
if attempt > 1
println("\nYiemAgent extractWineAttributes_1() attempt $attempt/10 ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
end
usermsg =
"""
User's query: $input
@@ -391,32 +406,35 @@ function extractWineAttributes_1(a::T1, input::T2)::String where {T1<:agent, T2<
]
# put in model format
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
prompt *=
"""
<|start_header_id|>assistant<|end_header_id|>
"""
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen")
response = a.func[:text2textInstructLLM](prompt)
response = GeneralUtils.remove_french_accents(response)
# check wheter all attributes are in the response
checkFlag = false
for word in attributes
for word in header
if !occursin(word, response)
errornote = "$word attribute is missing in previous attempts"
println("Attempt $attempt $errornote ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
println("Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
checkFlag = true
break
end
end
checkFlag == true ? continue : nothing
responsedict = copy(JSON3.read(response))
# check whether response has all header
detected_kw = GeneralUtils.detect_keyword(header, response)
if 0 values(detected_kw)
errornote = "\nYiemAgent extractWineAttributes_1() response does not have all header"
continue
elseif sum(values(detected_kw)) > length(header)
errornote = "\nYiemAgent extractWineAttributes_1() response has duplicated header"
continue
end
responsedict = GeneralUtils.textToDict(response, header;
dictKey=dictkey, symbolkey=true)
# convert
delete!(responsedict, :reasoning)
delete!(responsedict, :thought)
delete!(responsedict, :tasting_notes)
delete!(responsedict, :occasion)
delete!(responsedict, :food_to_be_paired_with_wine)
@@ -426,25 +444,34 @@ function extractWineAttributes_1(a::T1, input::T2)::String where {T1<:agent, T2<
# 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 attributes
for i in dictkey
j = Symbol(i)
if j [:reasoning, :tasting_notes, :occasion, :food_to_be_paired_with_wine]
if j [:thought, :tasting_notes, :occasion, :food_to_be_paired_with_wine]
# in case j is wine_price it needs to be checked differently because its value is ranged
if j == :wine_price
if responsedict[:wine_price] != "NA"
# check whether wine_price is in ranged number
if !occursin('-', responsedict[:wine_price])
errornote = "wine_price must be a range number"
println("Attempt $attempt $errornote ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
println("ERROR YiemAgent extractWineAttributes_1() $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
checkFlag = true
break
end
# check whether max wine_price is in the input
maxprice = split(responsedict[:wine_price], '-')[end]
pricerange = split(responsedict[:wine_price], '-')
minprice = pricerange[1]
maxprice = pricerange[end]
if !occursin(maxprice, input)
responsedict[:wine_price] = "NA"
end
# price range like 100-100 is not good
if minprice == maxprice
errornote = "wine_price with minimum equals to maximum is not valid"
println("ERROR YiemAgent extractWineAttributes_1() $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
checkFlag = true
break
end
end
else
content = responsedict[j]
@@ -457,18 +484,18 @@ function extractWineAttributes_1(a::T1, input::T2)::String where {T1<:agent, T2<
content = [content]
end
for x in content #BUG why x is "0-1500"
if !occursin("NA", responsedict[j]) && !occursin(x, input)
errornote = "$x is not mentioned in the user query, you must only use the info from the query."
println("Attempt $attempt $errornote ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
checkFlag == true
break
# for x in content #check whether price are mentioned in the input
# if !occursin("NA", responsedict[j]) && !occursin(x, input)
# errornote = "$x is not mentioned in the user query, you must only use the info from the query."
# println("ERROR YiemAgent extractWineAttributes_1() $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
# checkFlag == true
# break
# end
# end
end
end
end
end
end
checkFlag == true ? continue : nothing
checkFlag == true ? continue : nothing # skip the rest code if true
# remove (some text)
for (k, v) in responsedict
@@ -502,7 +529,7 @@ 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.
@@ -527,6 +554,7 @@ 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>
"""
systemmsg =
@@ -540,67 +568,64 @@ function extractWineAttributes_2(a::T1, input::T2)::String where {T1<:agent, T2<
The preference form requires the following information:
sweetness, acidity, tannin, intensity
You must follow the following guidelines:
<You must follow the following guidelines>
1) If specific information required in the preference form is not available in the query or there isn't any, mark with 'NA' to indicate this.
Additionally, words like 'any' or 'unlimited' mean no information is available.
2) Use the conversion table to convert the descriptive word level of sweetness, intensity, tannin, and acidity into a corresponding integer.
3) Do not generate other comments.
</You must follow the following guidelines>
You should then respond to the user with the following points:
- 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
<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.
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
</You should then respond to the user with>
You should only respond in the form (JSON) as described below:
{
"sweetness_keyword": ...,
"sweetness": ...,
"acidity_keyword": ...,
"acidity": ...,
"tannin_keyword": ...,
"tannin": ...,
"intensity_keyword": ...,
"intensity": ...
}
<You should only respond in format as described below>
Sweetness_keyword: ...
Sweetness: ...
Acidity_keyword: ...
Acidity: ...
Tannin_keyword: ...
Tannin: ...
Intensity_keyword: ...
Intensity: ...
</You should only respond in format as described below>
Here are some examples:
<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"
}
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"
}
Sweetness_keyword: NA
Sweetness: NA
Acidity_keyword: NA
Acidity: NA
Tannin_keyword: NA
Tannin: NA
Intensity_keyword: NA
Intensity: NA
</Here are some examples>
Let's begin!
"""
header = ["Sweetness_keyword:", "Sweetness:", "Acidity_keyword:", "Acidity:", "Tannin_keyword:", "Tannin:", "Intensity_keyword:", "Intensity:"]
dictkey = ["sweetness_keyword", "sweetness", "acidity_keyword", "acidity", "tannin_keyword", "tannin", "intensity_keyword", "intensity"]
errornote = ""
for attempt in 1:5
for attempt in 1:10
usermsg =
"""
$conversiontable
@@ -615,14 +640,22 @@ function extractWineAttributes_2(a::T1, input::T2)::String where {T1<:agent, T2<
]
# put in model format
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
prompt *=
"""
<|start_header_id|>assistant<|end_header_id|>
"""
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen")
response = a.func[:text2textInstructLLM](prompt)
responsedict = copy(JSON3.read(response))
# check whether response has all header
detected_kw = GeneralUtils.detect_keyword(header, response)
if 0 values(detected_kw)
errornote = "\nYiemAgent extractWineAttributes_2() response does not have all header"
continue
elseif sum(values(detected_kw)) > length(header)
errornote = "\nYiemAgent extractWineAttributes_2() response has duplicated header"
continue
end
responsedict = GeneralUtils.textToDict(response, header;
dictKey=dictkey, symbolkey=true)
# check whether each describing keyword is in the input to prevent halucination
for i in ["sweetness", "acidity", "tannin", "intensity"]
@@ -630,7 +663,7 @@ function extractWineAttributes_2(a::T1, input::T2)::String where {T1<:agent, T2<
value = responsedict[keyword]
if value != "NA" && !occursin(value, input)
errornote = "WARNING. Keyword $keyword: $value does not appear in the input. You must use information from the input only"
println("Attempt $attempt $errornote ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
println("Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
continue
end
@@ -646,7 +679,7 @@ function extractWineAttributes_2(a::T1, input::T2)::String where {T1<:agent, T2<
if !occursin("keyword", string(k))
if v !== "NA" && (!occursin('-', v) || length(v) > 5)
errornote = "WARNING: The non-range value {$k: $v} is not allowed. It should be specified in a range format, i.e. min-max."
println("Attempt $attempt $errornote ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
println("Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
continue
end
end
@@ -675,168 +708,121 @@ function extractWineAttributes_2(a::T1, input::T2)::String where {T1<:agent, T2<
end
# function concept(a::sommelier, thoughtDict)
# systemmsg =
# """
# Your name: N/A
# Situation:
# - You are a helpful assistant
# Your vision:
# - This is a good opportunity to help the user
# Your mission:
# - To describe the concept of a conversation
# Mission's objective includes:
# - To
# Your responsibility includes:
# 1) Given the situation, convey your thoughts to the user.
# Your responsibility excludes:
# 1) Asking or guiding the user to make a purchase
# 2) Processing sales orders or engaging in any other sales-related activities
# 3) Answering questions and offering additional services beyond just recommendations, such as delivery, box, gift wrapping, personalized messages. Customers can reach out to our sales at the store.
# Your profile:
# - You are a young professional in a big company.
# - You are avid party goer
# - You like beer.
# - You know nothing about wine.
# - You have a budget of 1500usd.
# Additional information:
# - your boss like spicy food.
# - your boss is a middle-aged man.
function paraphrase(text2textInstructLLM::Function, text::String)
systemmsg =
"""
Your name: N/A
Your vision:
- You are a helpful assistant who help the user to paraphrase their text.
Your mission:
- To help paraphrase the user's text
Mission's objective includes:
- To help paraphrase the user's text
Your responsibility includes:
1) To help paraphrase the user's text
Your responsibility does NOT includes:
1) N/A
Your profile:
- N/A
Additional information:
- N/A
# At each round of conversation, you will be given the following information:
# Your ongoing conversation with the user: ...
# Context: ...
# Your thoughts: Your current thoughts in your mind
At each round of conversation, you will be given the following information:
Text: The user's given text
# You MUST follow the following guidelines:
# - Do not offer additional services you didn't thought.
You MUST follow the following guidelines:
- N/A
# You should follow the following guidelines:
# - Focus on the latest conversation.
# - If the user interrupts, prioritize the user
# - Medium and full-bodied red wines should not be paired with spicy foods.
You should follow the following guidelines:
- N/A
# You should then respond to the user with:
# 1) Chat: Given the situation, How would you respond to the user to express your thoughts honestly and keep the conversation going smoothly?
You should then respond to the user with:
Paraphrase: Paraphrased text
# You should only respond in format as described below:
# Chat: ...
You should only respond in format as described below:
Paraphrase: ...
# Here are some examples of response format:
# Chat: "I see. Let me think about it. I'll get back to you with my recommendation."
Let's begin!
"""
# Let's begin!
# """
header = ["Paraphrase:"]
dictkey = ["paraphrase"]
# # a.memory[:shortmem][:available_wine] is a dataframe.
# context =
# if haskey(a.memory[:shortmem], :available_wine)
# "Available wines $(GeneralUtils.dfToString(a.memory[:shortmem][:available_wine]))"
# else
# "None"
# end
errornote = ""
response = nothing # placeholder for show when error msg show up
# chathistory = vectorOfDictToText(a.chathistory)
# errornote = ""
# response = nothing # placeholder for show when error msg show up
# for attempt in 1:10
# usermsg = """
# Your ongoing conversation with the user: $chathistory
# Contex: $context
# Your thoughts: $(thoughtDict[:understanding]) $(thoughtDict[:reasoning]) $(thoughtDict[:plan])
# $errornote
# """
for attempt in 1:10
usermsg = """
Text: $text
$errornote
"""
# _prompt =
# [
# Dict(:name => "system", :text => systemmsg),
# Dict(:name => "user", :text => usermsg)
# ]
_prompt =
[
Dict(:name => "system", :text => systemmsg),
Dict(:name => "user", :text => usermsg)
]
# # put in model format
# prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
# prompt *= """
# <|start_header_id|>assistant<|end_header_id|>
# """
# put in model format
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen")
# try
# response = a.func[:text2textInstructLLM](prompt)
# # sometime the model response like this "here's how I would respond: ..."
# if occursin("respond:", response)
# errornote = "You don't need to intro your response"
# error("generatechat() response contain : ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
# end
# response = GeneralUtils.remove_french_accents(response)
# response = replace(response, '*'=>"")
# response = replace(response, '$' => "USD")
# response = replace(response, '`' => "")
# response = GeneralUtils.remove_french_accents(response)
# responsedict = GeneralUtils.textToDict(response, ["Chat"],
# rightmarker=":", symbolkey=true, lowercasekey=true)
try
response = text2textInstructLLM(prompt)
# 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("\nparaphrase() response contain : ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
end
response = GeneralUtils.remove_french_accents(response)
response = replace(response, '*'=>"")
response = replace(response, '$' => "USD")
response = replace(response, '`' => "")
response = GeneralUtils.remove_french_accents(response)
# for i ∈ [:chat]
# if length(JSON3.write(responsedict[i])) == 0
# error("$i is empty ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
# end
# end
# check whether response has all header
detected_kw = GeneralUtils.detect_keyword(header, response)
if 0 values(detected_kw)
errornote = "\nYiemAgent paraphrase() response does not have all header"
continue
elseif sum(values(detected_kw)) > length(header)
errornote = "\nnYiemAgent paraphrase() response has duplicated header"
continue
end
# # check if there are more than 1 key per categories
# for i ∈ [:chat]
# matchkeys = GeneralUtils.findMatchingDictKey(responsedict, i)
# if length(matchkeys) > 1
# error("generatechat has more than one key per categories")
# end
# end
responsedict = GeneralUtils.textToDict(response, header;
dictKey=dictkey, symbolkey=true)
# # check if Context: is in chat
# if occursin("Context:", responsedict[:chat])
# error("Context: is in text. This is not allowed")
# end
for i [:paraphrase]
if length(JSON3.write(responsedict[i])) == 0
error("$i is empty ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
end
end
# println("\n~~~ generatechat() ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
# pprintln(Dict(responsedict))
# check if there are more than 1 key per categories
for i [:paraphrase]
matchkeys = GeneralUtils.findMatchingDictKey(responsedict, i)
if length(matchkeys) > 1
error("paraphrase() has more than one key per categories")
end
end
# # check whether an agent recommend wines before checking inventory or recommend wines
# # outside its inventory
# # ask LLM whether there are any winery mentioned in the response
# mentioned_winery = detectWineryName(a, responsedict[:chat])
# if mentioned_winery != "None"
# mentioned_winery = String.(strip.(split(mentioned_winery, ",")))
println("\nparaphrase() ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
pprintln(Dict(responsedict))
# # check whether the wine is in event
# isWineInEvent = false
# for winename in mentioned_winery
# for event in a.memory[:events]
# if event[:outcome] !== nothing && occursin(winename, event[:outcome])
# isWineInEvent = true
# break
# end
# end
# end
result = responsedict[:paraphrase]
# # if wine is mentioned but not in timeline or shortmem,
# # then the agent is not supposed to recommend the wine
# if isWineInEvent == false
# errornote = "Previously: You recommend a wine that is not in your inventory which is not allowed."
# error("Previously: You recommend a wine that is not in your inventory which is not allowed.")
# end
# end
# result = responsedict[:chat]
# 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("\nAttempt $attempt. Error occurred: $errorMsg\n$st ", Dates.now(), " ", @__FILE__, " ", @__LINE__)
# end
# end
# error("generatechat failed to generate a response")
# end
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("\nAttempt $attempt. Error occurred: $errorMsg\n$st ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
end
end
error("paraphrase() failed to generate a response")
end
@@ -998,7 +984,7 @@ end
# ]
# # put in model format
# prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
# prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen")
# prompt *=
# """
# <|start_header_id|>assistant<|end_header_id|>
@@ -1030,7 +1016,7 @@ 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

View File

@@ -107,7 +107,7 @@ function addNewMessage(a::T1, name::String, text::T2;
error("name is not in agent.availableRole $(@__LINE__)")
end
#[WORKING] summarize the oldest 10 message
#[PENDING] summarize the oldest 10 message
if length(a.chathistory) > maximumMsg
summarize(a.chathistory)
else
@@ -122,41 +122,47 @@ This function takes in a vector of dictionaries and outputs a single string wher
# Arguments
- `vecd::Vector`
a vector of dictionaries
A vector of dictionaries containing chat messages
- `withkey::Bool`
whether to include the key in the output text. Default is true
Whether to include the name as a prefix in the output text. Default is true
- `range::Union{Nothing,UnitRange,Int}`
Optional range of messages to include. If nothing, includes all messages
# Return
a string with the formatted dictionaries
# Returns
A formatted string where each line contains either:
- If withkey=true: "name> message\n"
- If withkey=false: "message\n"
# Example
```jldoctest
julia> using Revise
julia> using GeneralUtils
julia> vecd = [Dict(:name => "John", :text => "Hello"), Dict(:name => "Jane", :text => "Goodbye")]
julia> GeneralUtils.vectorOfDictToText(vecd, withkey=true)
"John> Hello\nJane> Goodbye\n"
```
# Signature
"""
function chatHistoryToText(vecd::Vector; withkey=true)::String
function chatHistoryToText(vecd::Vector; withkey=true, range=nothing)::String
# Initialize an empty string to hold the final text
text = ""
# Get the elements within the specified range, or all elements if no range provided
elements = isnothing(range) ? vecd : vecd[range]
# Determine whether to include the key in the output text or not
if withkey
# Loop through each dictionary in the input vector
for d in vecd
for d in elements
# Extract the 'name' and 'text' keys from the dictionary
name = d[:name]
_text = d[:text]
# Append the formatted string to the text variable
text *= "$name> $_text \n"
text *= "$name:> $_text \n"
end
else
# Loop through each dictionary in the input vector
for d in vecd
for d in elements
# Iterate over all key-value pairs in the dictionary
for (k, v) in d
# Append the formatted string to the text variable
@@ -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,
@@ -220,24 +255,62 @@ function eventdict(;
end
function createTimeline(memory::T1; skiprecent::Integer=0) where {T1<:AbstractVector}
events = memory[1:end-skiprecent]
""" Create a formatted timeline string from a sequence of events.
# 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
timeline *= "$i) $(event[:subject])> $(event[:actioninput])\n"
# Determine which indices to use - either provided range or full length
ind =
if eventindex !== nothing
[eventindex...]
else
timeline *= "$i) $(event[:subject])> $(event[:actioninput]) $(event[:outcome])\n"
1:length(events)
end
# Iterate through events and format each one
for (i, event) in zip(ind, events)
# If no outcome exists, format without outcome
if event[:outcome] === nothing
timeline *= "Event_$i $(event[:subject])> $(event[:actioninput])\n"
# If outcome exists, include it in formatting
else
timeline *= "Event_$i $(event[:subject])> $(event[:actioninput]) $(event[:outcome])\n"
end
end
# Return formatted timeline string
return timeline
end
# """ Convert a single chat dictionary into LLM model instruct format.
# # Llama 3 instruct format example

41
test/Manifest.toml Normal file
View File

@@ -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"

2
test/Project.toml Normal file
View File

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

View File

@@ -27,10 +27,14 @@
"description": "agent role"
},
"organization": {
"value": "yiem_hq",
"value": "yiem_branch_1",
"description": "organization name"
},
"externalservice": {
"loadbalancer": {
"mqtttopic": "/loadbalancer/requestingservice",
"description": "text to text service with instruct LLM"
},
"text2textinstruct": {
"mqtttopic": "/loadbalancer/requestingservice",
"description": "text to text service with instruct LLM",
@@ -51,6 +55,22 @@
"llminfo": {
"name": "llama3instruct"
}
},
"wineDB" : {
"description": "A wine database connection info for LibPQ client",
"host": "192.168.88.12",
"port": 10201,
"dbname": "wineDB",
"user": "yiemtechnologies",
"password": "yiemtechnologies@Postgres_0.0"
},
"SQLVectorDB" : {
"description": "A wine database connection info for LibPQ client",
"host": "192.168.88.12",
"port": 10203,
"dbname": "SQLVectorDB",
"user": "yiemtechnologies",
"password": "yiemtechnologies@Postgres_0.0"
}
}
}

View File

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

0
test/runtests.jl Normal file
View File

View File

@@ -8,31 +8,41 @@ using Base.Threads
# load config
config = JSON3.read("./test/config.json")
config = JSON3.read("/appfolder/app/dev/YiemAgent/test/config.json")
# config = copy(JSON3.read("../mountvolume/config.json"))
function executeSQL(sql::T) where {T<:AbstractString}
DBconnection = LibPQ.Connection("host=192.168.88.12 port=10201 dbname=wineDB user=yiemtechnologies password=yiemtechnologies@Postgres_0.0")
host = config[:externalservice][:wineDB][:host]
port = config[:externalservice][:wineDB][:port]
dbname = config[:externalservice][:wineDB][:dbname]
user = config[:externalservice][:wineDB][:user]
password = config[:externalservice][:wineDB][:password]
DBconnection = LibPQ.Connection("host=$host port=$port dbname=$dbname user=$user password=$password")
result = LibPQ.execute(DBconnection, sql)
close(DBconnection)
return result
end
function executeSQLVectorDB(sql)
DBconnection = LibPQ.Connection("host=192.168.88.12 port=10203 dbname=SQLVectorDB user=yiemtechnologies password=yiemtechnologies@Postgres_0.0")
host = config[:externalservice][:SQLVectorDB][:host]
port = config[:externalservice][:SQLVectorDB][:port]
dbname = config[:externalservice][:SQLVectorDB][:dbname]
user = config[:externalservice][:SQLVectorDB][:user]
password = config[:externalservice][:SQLVectorDB][:password]
DBconnection = LibPQ.Connection("host=$host port=$port dbname=$dbname user=$user password=$password")
result = LibPQ.execute(DBconnection, sql)
close(DBconnection)
return result
end
function text2textInstructLLM(prompt::String)
function text2textInstructLLM(prompt::String; maxattempt::Integer=2, modelsize::String="medium")
msgMeta = GeneralUtils.generate_msgMeta(
config[:externalservice][:text2textinstruct][:mqtttopic];
config[:externalservice][:loadbalancer][:mqtttopic];
msgPurpose="inference",
senderName="yiemagent",
senderId=string(uuid4()),
receiverName="text2textinstruct",
senderId=sessionId,
receiverName="text2textinstruct_$modelsize",
mqttBrokerAddress=config[:mqttServerInfo][:broker],
mqttBrokerPort=config[:mqttServerInfo][:port],
)
@@ -48,8 +58,20 @@ function text2textInstructLLM(prompt::String)
)
)
_response = GeneralUtils.sendReceiveMqttMsg(outgoingMsg; timeout=6000)
response = nothing
for attempts in 1:maxattempt
_response = GeneralUtils.sendReceiveMqttMsg(outgoingMsg; timeout=180, maxattempt=maxattempt)
payload = _response[:response]
if _response[:success] && payload[:text] !== nothing
response = _response[:response][:text]
break
else
println("\n<text2textInstructLLM()> attempt $attempts/$maxattempt failed ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
pprintln(outgoingMsg)
println("</text2textInstructLLM()> attempt $attempts/$maxattempt failed ", @__FILE__, ":", @__LINE__, " $(Dates.now())\n")
sleep(3)
end
end
return response
end
@@ -57,11 +79,11 @@ end
# get text embedding from a LLM service
function getEmbedding(text::T) where {T<:AbstractString}
msgMeta = GeneralUtils.generate_msgMeta(
config[:externalservice][:text2textinstruct][:mqtttopic];
config[:externalservice][:loadbalancer][:mqtttopic];
msgPurpose="embedding",
senderName="yiemagent",
senderId=string(uuid4()),
receiverName="text2textinstruct",
senderId=sessionId,
receiverName="textembedding",
mqttBrokerAddress=config[:mqttServerInfo][:broker],
mqttBrokerPort=config[:mqttServerInfo][:port],
)
@@ -72,7 +94,8 @@ function getEmbedding(text::T) where {T<:AbstractString}
:text => [text] # must be a vector of string
)
)
response = GeneralUtils.sendReceiveMqttMsg(outgoingMsg; timeout=6000)
response = GeneralUtils.sendReceiveMqttMsg(outgoingMsg; timeout=120, maxattempt=3)
embedding = response[:response][:embeddings]
return embedding
end
@@ -80,10 +103,8 @@ end
function findSimilarTextFromVectorDB(text::T1, tablename::T2, embeddingColumnName::T3,
vectorDB::Function; limit::Integer=1
)::DataFrame where {T1<:AbstractString, T2<:AbstractString, T3<:AbstractString}
# get embedding from LLM service
embedding = getEmbedding(text)[1]
# check whether there is close enough vector already store in vectorDB. if no, add, else skip
sql = """
SELECT *, $embeddingColumnName <-> '$embedding' as distance
@@ -95,29 +116,29 @@ function findSimilarTextFromVectorDB(text::T1, tablename::T2, embeddingColumnNam
return df
end
function similarSQLVectorDB(query; maxdistance::Integer=100)
tablename = "sqlllm_decision_repository"
# get embedding of the query
df = findSimilarTextFromVectorDB(query, tablename,
"function_input_embedding", executeSQLVectorDB)
# println(df[1, [:id, :function_output]])
row, col = size(df)
distance = row == 0 ? Inf : df[1, :distance]
# distance = 100 # CHANGE this is for testing only
if row != 0 && distance < maxdistance
# if there is usable SQL, return it.
output_b64 = df[1, :function_output_base64] # pick the closest match
output_str = String(base64decode(output_b64))
rowid = df[1, :id]
println("\n~~~ found similar sql. row id $rowid, distance $distance ", @__FILE__, " ", @__LINE__)
println("\n~~~ found similar sql. row id $rowid, distance $distance ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
return (dict=output_str, distance=distance)
else
println("\n~~~ similar sql not found, max distance $maxdistance ", @__FILE__, " ", @__LINE__)
println("\n~~~ similar sql not found, max distance $maxdistance ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
return (dict=nothing, distance=nothing)
end
end
function insertSQLVectorDB(query::T1, SQL::T2; maxdistance::Integer=1) where {T1<:AbstractString, T2<:AbstractString}
function insertSQLVectorDB(query::T1, SQL::T2; maxdistance::Integer=3) where {T1<:AbstractString, T2<:AbstractString}
tablename = "sqlllm_decision_repository"
# get embedding of the query
# query = state[:thoughtHistory][:question]
@@ -134,14 +155,14 @@ function insertSQLVectorDB(query::T1, SQL::T2; maxdistance::Integer=1) where {T1
sql = """
INSERT INTO $tablename (function_input, function_output, function_output_base64, function_input_embedding) VALUES ('$query', '$sql_', '$sql_base64', '$query_embedding');
"""
println("\n~~~ added new decision to vectorDB ", @__FILE__, " ", @__LINE__)
println(sql)
# println("\n~~~ added new decision to vectorDB ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
# println(sql)
_ = executeSQLVectorDB(sql)
end
end
function similarSommelierDecision(recentevents::T1; maxdistance::Integer=5
function similarSommelierDecision(recentevents::T1; maxdistance::Integer=3
)::Union{AbstractDict, Nothing} where {T1<:AbstractString}
tablename = "sommelier_decision_repository"
# find similar
@@ -214,7 +235,7 @@ a = YiemAgent.sommelier(
)
while true
println("your respond: ")
print("\nyour respond: ")
user_answer = readline()
response = YiemAgent.conversation(a, Dict(:text=> user_answer))
println("\n$response")
@@ -224,14 +245,13 @@ 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.
"""