ton/SQLLLM
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

update

Browse Source
This commit is contained in:
narawat lamaiin
2025-04-01 21:17:03 +07:00
parent bc0f735ab7
commit fd5ac82662
3 changed files with 25 additions and 22 deletions
Download Patch File Download Diff File Expand all files Collapse all files

22
src/interface.jl
View File

@@ -220,8 +220,8 @@ function decisionMaker(state::T1, context, text2textInstructLLM::Function,
] ]
# put in model format # put in model format
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen") prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
response = text2textInstructLLM(prompt) response = text2textInstructLLM(prompt, modelsize="medium")
# LLM tends to generate observation given that it is in the input # LLM tends to generate observation given that it is in the input
response = response =
@@ -271,7 +271,7 @@ function decisionMaker(state::T1, context, text2textInstructLLM::Function,
# check whether response has all header # check whether response has all header
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 = "\nSQLLLM decisionMaker() response does not have all header" errornote = "\nSQLLLM decisionMaker() response does not have all header"
continue continue
elseif sum(values(detected_kw)) > length(header) elseif sum(values(detected_kw)) > length(header)
@@ -321,7 +321,7 @@ function decisionMaker(state::T1, context, text2textInstructLLM::Function,
# check whether response has all header # check whether response has all header
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 = "\nSQL decisionMaker() response does not have all header" errornote = "\nSQL decisionMaker() response does not have all header"
continue continue
elseif sum(values(detected_kw)) > length(header) elseif sum(values(detected_kw)) > length(header)
@@ -446,12 +446,12 @@ function evaluator(state::T1, text2textInstructLLM::Function
] ]
# put in model format # put in model format
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen") prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
header = ["Trajectory_evaluation:", "Answer_evaluation:", "Accepted_as_answer:", "Score:", "Suggestion:"] header = ["Trajectory_evaluation:", "Answer_evaluation:", "Accepted_as_answer:", "Score:", "Suggestion:"]
dictkey = ["trajectory_evaluation", "answer_evaluation", "accepted_as_answer", "score", "suggestion"] dictkey = ["trajectory_evaluation", "answer_evaluation", "accepted_as_answer", "score", "suggestion"]
response = text2textInstructLLM(prompt) response = text2textInstructLLM(prompt, modelsize="medium")
# sometime LLM output something like **Comprehension**: which is not expected # sometime LLM output something like **Comprehension**: which is not expected
response = replace(response, "**"=>"") response = replace(response, "**"=>"")
@@ -459,7 +459,7 @@ function evaluator(state::T1, text2textInstructLLM::Function
# check whether response has all header # check whether response has all header
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 = "\nSQL evaluator() response does not have all header" errornote = "\nSQL evaluator() response does not have all header"
continue continue
elseif sum(values(detected_kw)) > length(header) elseif sum(values(detected_kw)) > length(header)
@@ -601,7 +601,7 @@ function reflector(config::T1, state::T2)::String where {T1<:AbstractDict, T2<:A
] ]
# put in model format # put in model format
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen") prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
externalService = config[:externalservice][:text2textinstruct] externalService = config[:externalservice][:text2textinstruct]
# apply LLM specific instruct format # apply LLM specific instruct format
@@ -998,7 +998,7 @@ function query(query::T, executeSQL::Function, text2textInstructLLM::Function;
LLMMCTS.runMCTS(initialstate, transition, transitionargs; LLMMCTS.runMCTS(initialstate, transition, transitionargs;
horizontalSampleExpansionPhase=3, horizontalSampleExpansionPhase=3,
horizontalSampleSimulationPhase=2, horizontalSampleSimulationPhase=2,
maxSimulationDepth=5, maxSimulationDepth=5,
maxiterations=1, maxiterations=1,
explorationweight=1.0, explorationweight=1.0,
earlystop=earlystop, earlystop=earlystop,
@@ -1172,10 +1172,10 @@ function generatequestion(state::T1, context, text2textInstructLLM::Function;
] ]
# put in model format # put in model format
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen") prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
try try
response = text2textInstructLLM(prompt) response = text2textInstructLLM(prompt, modelsize="medium")
# check if response is valid # check if response is valid
q_number = count("Q", response) q_number = count("Q", response)

16
src/llmfunction.jl
View File

@@ -406,9 +406,9 @@ function getdata_decisionMaker(state::Dict, context::Dict, text2textInstructLLM:
] ]
# put in model format # put in model format
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen") prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
try try
response = text2textInstructLLM(prompt) response = text2textInstructLLM(prompt, modelsize="medium")
header = ["Comprehension:", "Plan:", "Code:"] header = ["Comprehension:", "Plan:", "Code:"]
dictkey = ["comprehension", "plan", "code"] dictkey = ["comprehension", "plan", "code"]
@@ -627,12 +627,12 @@ function extractContent_dataframe(df::DataFrame, text2textInstructLLM::Function,
] ]
# put in model format # put in model format
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen") prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
header = ["About_resulting_table:", "Search_summary:"] header = ["About_resulting_table:", "Search_summary:"]
dictkey = ["about_resulting_table", "search_summary"] dictkey = ["about_resulting_table", "search_summary"]
for i in 1:5 for i in 1:5
response = text2textInstructLLM(prompt) response = text2textInstructLLM(prompt, modelsize="medium")
kw = [] kw = []
# use for loop and detect_keyword function to get the exact variation of each keyword in the text then push to kw list # use for loop and detect_keyword function to get the exact variation of each keyword in the text then push to kw list
@@ -762,13 +762,13 @@ function getTableNameFromSQL(sql::T, text2textInstructLLM::Function)::Vector{Str
] ]
# put in model format # put in model format
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen") prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
header = ["Table_name:"] header = ["Table_name:"]
dictkey = ["table_name"] dictkey = ["table_name"]
for attempt in 1:5 for attempt in 1:5
try try
response = text2textInstructLLM(prompt) response = text2textInstructLLM(prompt, modelsize="medium")
responsedict = GeneralUtils.textToDict(response, header; responsedict = GeneralUtils.textToDict(response, header;
dictKey=dictkey, symbolkey=true) dictKey=dictkey, symbolkey=true)
response = copy(JSON3.read(responsedict[:table_name])) response = copy(JSON3.read(responsedict[:table_name]))
@@ -914,12 +914,12 @@ function compareState(question::String, highValueStateList::Vector{T},
] ]
# put in model format # put in model format
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen") prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
header = ["Comparison:", "Rationale:", "Selected_response_number:"] header = ["Comparison:", "Rationale:", "Selected_response_number:"]
dictkey = ["comparison", "rationale", "selected_response_number"] dictkey = ["comparison", "rationale", "selected_response_number"]
response = text2textInstructLLM(prompt) response = text2textInstructLLM(prompt, modelsize="medium")
# sometime LLM output something like **Comprehension**: which is not expected # sometime LLM output something like **Comprehension**: which is not expected
response = replace(response, "**"=>"") response = replace(response, "**"=>"")

9
system_prompt_template.jl
View File

@@ -1,9 +1,9 @@
""" """
Default system message template: Default system message template:
<Your profile> <Your role>
- You are a helpful assistant - You are a helpful assistant
</Your profile> </Your role>
<Situation> <Situation>
- Describe the current situation - Describe the current situation
</Situation> </Situation>
@@ -18,7 +18,10 @@ Default system message template:
</Your mission's objective includes> </Your mission's objective includes>
<Your responsibility includes> <Your responsibility includes>
- state the mini goals that fall under your responsibility - state the mini goals that fall under your responsibility
</Your responsibility includes> </Your responsibility includes>
<Your responsibility does NOT includes>
-
</Your responsibility does NOT includes>
<At each round of conversation, you will be given the following> <At each round of conversation, you will be given the following>
</At each round of conversation, you will be given the following> </At each round of conversation, you will be given the following>