update

src/interface.jl

@@ -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
@@ -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)

src/llmfunction.jl

@@ -406,9 +406,9 @@ function getdata_decisionMaker(state::Dict, context::Dict, text2textInstructLLM:
       ]
 
     # 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")
 
       header = ["Comprehension:", "Plan:", "Code:"]
       dictkey = ["comprehension", "plan", "code"]
@@ -627,12 +627,12 @@ function extractContent_dataframe(df::DataFrame, text2textInstructLLM::Function,
     ]
 
   # put in model format
-  prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen")
+  prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
   header = ["About_resulting_table:", "Search_summary:"]
   dictkey = ["about_resulting_table", "search_summary"]
 
   for i in 1:5
-    response = text2textInstructLLM(prompt)
+    response = text2textInstructLLM(prompt, modelsize="medium")
 
     kw = []
     # 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
-  prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen")
+  prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
   header = ["Table_name:"]
   dictkey = ["table_name"]
 
   for attempt in 1:5
     try
-      response = text2textInstructLLM(prompt)
+      response = text2textInstructLLM(prompt, modelsize="medium")
       responsedict = GeneralUtils.textToDict(response, header; 
                                             dictKey=dictkey, symbolkey=true)
       response = copy(JSON3.read(responsedict[:table_name]))
@@ -914,12 +914,12 @@ function compareState(question::String, highValueStateList::Vector{T},
     ]
 
     # put in model format
-    prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen")
+    prompt = GeneralUtils.formatLLMtext(_prompt; formatname="llama3instruct")
 
     header = ["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
     response = replace(response, "**"=>"")

system_prompt_template.jl

@@ -1,9 +1,9 @@
 """
 Default system message template:
 
-  <Your profile>
+  <Your role>
     - You are a helpful assistant
-  </Your profile>
+  </Your role>
   <Situation>
     - Describe the current situation
   </Situation>
@@ -18,7 +18,10 @@ Default system message template:
   </Your mission's objective includes>
   <Your responsibility includes>
     - 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>