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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
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src/interface.jl
+11 -11
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@@ -220,8 +220,8 @@ function decisionMaker(state::T1, context, text2textInstructLLM::Function,
]
# put in model format
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen")
response = text2textInstructLLM(prompt)
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
response = text2textInstructLLM(prompt, modelsize="medium")
# LLM tends to generate observation given that it is in the input
response =
@@ -271,7 +271,7 @@ function decisionMaker(state::T1, context, text2textInstructLLM::Function,
# check whether response has all header
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"
continue
elseif sum(values(detected_kw)) > length(header)
@@ -321,7 +321,7 @@ function decisionMaker(state::T1, context, text2textInstructLLM::Function,
# check whether response has all header
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"
continue
elseif sum(values(detected_kw)) > length(header)
@@ -446,12 +446,12 @@ function evaluator(state::T1, text2textInstructLLM::Function
]
# 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:"]
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
response = replace(response, "**"=>"")
@@ -459,7 +459,7 @@ function evaluator(state::T1, text2textInstructLLM::Function
# check whether response has all header
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"
continue
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
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen")
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
externalService = config[:externalservice][:text2textinstruct]
# apply LLM specific instruct format
@@ -998,7 +998,7 @@ function query(query::T, executeSQL::Function, text2textInstructLLM::Function;
LLMMCTS.runMCTS(initialstate, transition, transitionargs;
horizontalSampleExpansionPhase=3,
horizontalSampleSimulationPhase=2,
maxSimulationDepth=5,
maxSimulationDepth=5,
maxiterations=1,
explorationweight=1.0,
earlystop=earlystop,
@@ -1172,10 +1172,10 @@ function generatequestion(state::T1, context, text2textInstructLLM::Function;
]
# put in model format
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen")
prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
try
response = text2textInstructLLM(prompt)
response = text2textInstructLLM(prompt, modelsize="medium")
# check if response is valid
q_number = count("Q", response)