Merge branch 'dev'

Author: neagualexa

.env.example

@@ -1,6 +1,11 @@
 OPENAI_API_KEY=test
 OPENAI_MODEL=test
-# for only use azureopenai
+
+# for use of googleai
+GOOGLE_AI_API_KEY=test
+GOOGLE_AI_MODEL=test
+
+# for use of azureopenai
 AZURE_OPENAI_API_KEY=test
 AZURE_OPENAI_ENDPOINT=test
 AZURE_OPENAI_API_VERSION=test

.github/workflows/dev.yml

@@ -2,7 +2,7 @@ name: Dev deployment of chatbot lambda function
 
 on:
   push:
-    branches-ignore: [main]
+    branches: [dev]
 
 jobs:
   test:

.github/workflows/main.yml

@@ -110,7 +110,8 @@ jobs:
       - name: Approve Production Deployment
         uses: trstringer/manual-approval@v1
         with:
-          approvers: approvers
+          approvers: neagualexa
+          # approvers: approvers
           minimum-approvals: 1
           timeout-minutes: 10
           secret: ${{ steps.generate_token.outputs.token }}

README.md

@@ -81,9 +81,9 @@ You can run the Python function itself. Make sure to have a main function in eit
 python src/module.py
 ```
 
-You can also use the `test_prompts.py` script to test the agents with example inputs from Lambda Feedback questions and synthetic conversations.
+You can also use the `testbench_agents.py` script to test the agents with example inputs from Lambda Feedback questions and synthetic conversations.
 ```bash
-python src/agents/utils/test_prompts.py
+python src/agents/utils/testbench_agents.py
 ```
 
 ### Building the Docker Image
@@ -113,7 +113,7 @@ docker run --env-file .env -it --name my-lambda-container -p 8080:8080 llm_chat
 This will start the evaluation function and expose it on port `8080` and it will be open to be curl:
 
 ```bash
-curl --location 'http://localhost:8080/2015-03-31/functions/function/invocations' --header 'Content-Type: application/json' --data '{"message":"hi","params":{"conversation_id":"12345Test"}}'
+curl --location 'http://localhost:8080/2015-03-31/functions/function/invocations' --header 'Content-Type: application/json' --data '{"message":"hi","params":{"conversation_id":"12345Test","conversation_history": [{"type":"user","content":"hi"}]}}'
 ```
 
 ### Call Docker Container From Postman
@@ -130,7 +130,8 @@ Body:
 {
     "message":"hi",
     "params":{
-        "conversation_id":"12345Test"
+        "conversation_id":"12345Test",
+        "conversation_history": [{"type":"user","content":"hi"}]
     }
 }
 ```
@@ -141,11 +142,12 @@ Body with optional Params:
     "message":"hi",
     "params":{
         "conversation_id":"12345Test",
-        "conversation_history":[" "],
+        "conversation_history":[{"type":"user","content":"hi"}],
         "summary":" ",
         "conversational_style":" ",
         "question_response_details": "",
-        "include_test_data": true
+        "include_test_data": true,
+        "agent_type": {agent_name}
     }
 }
 ```

index.py

@@ -8,8 +8,8 @@ def handler(event, context):
     """
     Lambda handler function
     """
-    # Log the input event TODO: remove this line
-    print("Received event:", json.dumps(event, indent=2))
+    # Log the input event for debugging purposes
+    # print("Received event:", json.dumps(event, indent=2))
 
     if "message" not in event:
         return {

src/agents/informational_agent/informational_agent.py

@@ -37,7 +37,7 @@ class State(TypedDict):
 
 class InformationalAgent:
     def __init__(self):
-        llm = OpenAILLMs()
+        llm = OpenAILLMs(temperature=0.25)
         self.llm = llm.get_llm()
         summarisation_llm = OpenAILLMs()
         self.summarisation_llm = summarisation_llm.get_llm()
@@ -66,7 +66,7 @@ def call_model(self, state: State, config: RunnableConfig) -> str:
         # Adding external student progress and question context details from data queries
         question_response_details = config["configurable"].get("question_response_details", "")
         if question_response_details:
-            system_message += f"## Known Question Materials: {question_response_details} \n\n"
+            system_message += f"## Known Learning Materials: {question_response_details} \n\n"
 
         # Adding summary and conversational style to the system message
         summary = state.get("summary", "")

src/agents/informational_agent/informational_prompts.py

@@ -7,12 +7,13 @@
 informational_role_prompt = """You are a highly skilled and patient AI tutor designed to assist me, the student, in discovering answers and mastering concepts. Your teaching style emphasizes student-centric learning, encouraging deep thinking, active engagement, and confidence building.
 
 ## Teaching Methods:
-Step-by-Step Learning: Break complex problems into smaller, manageable parts, solving one step at a time.
+Step-by-Step Learning: Break complex problems into smaller, manageable parts, solving one step at a time. Avoid giving the final answer upfront; instead, offer hints or intermediate steps to nudge the student toward the solution. Provide the full answer only when it’s clear the student needs it to move forward. If the student explicitly asks for the answer, direct them to the worked solutions or answer provided below, while encouraging them to engage with the chat for deeper understanding.
 Error Analysis: Treat mistakes as learning opportunities by helping students reflect on why they occurred and how to address them.
 Active Participation: Encourage students to take an active role in solving problems, providing guidance without overtaking their learning process.
-Tailored Feedback: Adapt your explanations, questions, and support to the student's level, needs, and progress.
+Tailored Feedback: Adapt your explanations, questions, and support to the student's level, needs, and progress. If the student is close to the solution, provide encouragement or subtle hints. If they seem stuck, gradually increase the specificity of your support.
 
 ## Key Qualities:
+Awareness: Use the known learning materials to base your responses on.
 Patience: Allow students ample time to think, process, and respond without rushing them.
 Clarity: Simplify complex ideas into clear, actionable steps.
 Encouragement: Celebrate student efforts and achievements to keep motivation high.

src/agents/socratic_agent/socratic_agent.py

@@ -37,7 +37,7 @@ class State(TypedDict):
 
 class SocraticAgent:
     def __init__(self):
-        llm = OpenAILLMs()
+        llm = OpenAILLMs(temperature=0.25)
         self.llm = llm.get_llm()
         summarisation_llm = OpenAILLMs()
         self.summarisation_llm = summarisation_llm.get_llm()

src/agents/utils/parse_json_to_prompt.py

@@ -99,9 +99,11 @@ def __init__(
 
 # questionAccessInformation type
 class CurrentPart:
-    def __init__(self, id: str = None, position: int = None):
+    def __init__(self, id: str = None, position: int = None, timeTakenPart: Optional[str] = None, markedDonePart: Optional[str] = None):
         self.id = id
         self.position = position
+        self.timeTakenPart = timeTakenPart
+        self.markedDonePart = markedDonePart
 
 class QuestionAccessInformation:
     def __init__(
@@ -138,25 +140,25 @@ def parse_json_to_prompt( questionSubmissionSummary: Optional[List[StudentWorkRe
     def format_response_area_details(responseArea: ResponseAreaDetails, studentSummary: List[StudentWorkResponseArea]) -> str:
         submissionDetails = "\n".join(
             [
-                f"My Latest Submission: {ra.latestSubmission.submission};\n"
-                f"My Latest Feedback Received: {ra.latestSubmission.feedback};\n"
-                f"Total Submissions: {ra.totalSubmissions};\n"
-                f"Total Wrong Submissions: {ra.totalWrongSubmissions};\n"
+                f"Latest Response: {ra.latestSubmission.submission};\n"
+                f"Latest Feedback Received: {ra.latestSubmission.feedback};\n"
+                f"Total Responses: {ra.totalSubmissions};\n"
+                f"Total Wrong Responses: {ra.totalWrongSubmissions};\n"
                 for ra in studentSummary
                 if ra.publishedResponseAreaId == responseArea.id and ra.latestSubmission
             ]
         )
 
         if not submissionDetails:
-            submissionDetails = 'My Latest Submission: none made;'
+            submissionDetails = 'Latest Response: none made;'
 
         return f"""
         ## Response Area: {responseArea.position + 1}
         {f'Area task: What is {responseArea.preResponseText} ?' if responseArea.preResponseText else ''}
         (Secret) Expected Answer: {responseArea.answer};
         {submissionDetails}"""
 
-    def format_part_details(part: PartDetails, currentPartId: str, summary: List[StudentWorkResponseArea]) -> str:
+    def format_part_details(part: PartDetails, currentPart: CurrentPart, summary: List[StudentWorkResponseArea]) -> str:
         if not part or not part.publishedResponseAreas:
             return ''
 
@@ -173,30 +175,30 @@ def format_part_details(part: PartDetails, currentPartId: str, summary: List[Stu
                 ]
             ) if part.publishedWorkedSolutionSections else f"No worked solutions for part ({convert_index_to_lowercase_letter(part.publishedPartPosition)});"
         )
-
         return f"""
-    # {'[CURRENTLY WORKING ON] ' if currentPartId == part.publishedPartId else ''}Part ({convert_index_to_lowercase_letter(part.publishedPartPosition)}):
+    # {'[CURRENTLY WORKING ON] ' if currentPart.id == part.publishedPartId else ''}Part ({convert_index_to_lowercase_letter(part.publishedPartPosition)}):
+    {f"Time spent on this part: {currentPart.timeTakenPart if currentPart.timeTakenPart is not None else 'No recorded duration'}" if currentPart.id == part.publishedPartId else ''}
     Part Content: {part.publishedPartContent.strip() if part.publishedPartContent else 'No content'};
     {responseAreas}
     {f'Final Part Answer: {part.publishedPartAnswerContent}' if part.publishedPartAnswerContent else 'No direct answer'}
     {workedSolutions}
 """
 
-    questionDetails = f"""This is the question I am currently working on. I am currently working on Part ({convert_index_to_lowercase_letter(questionAccessInformation.currentPart.position)}). Below, you'll find its details, including the parts of the question, my submissions for each response area, and feedback on my progress. This information highlights my efforts and progress so far. 
+    questionDetails = f"""This is the question I am currently working on. I am currently working on Part ({convert_index_to_lowercase_letter(questionAccessInformation.currentPart.position)}). Below, you'll find its details, including the parts of the question, my responses for each response area, and the feedback I received. This information highlights my efforts and progress so far. Use this this information to inform your understanding about the question materials provided to me and my work on them.
     Maths equations are in KaTex format, preserve them the same.
 
 # Question: {questionInformation.questionTitle};
     Guidance to Solve the Question: {questionInformation.questionGuidance or 'None'};
     Description of Question: {questionInformation.questionContent};
     Expected Time to Complete the Question: {f'{questionInformation.durationLowerBound} - {questionInformation.durationUpperBound} min;' if questionInformation.durationLowerBound and questionInformation.durationUpperBound else 'No specified duration.'}
-    Time Spent on the Question This Session: {questionAccessInformation.timeTaken or 'No recorded duration'} {f'since {questionAccessInformation.markedDone}' if questionAccessInformation.markedDone else {f'which is {questionAccessInformation.accessStatus}' if questionAccessInformation.accessStatus else ''}}; 
+    Time Spent on the Question today: {questionAccessInformation.timeTaken or 'No recorded duration'} {f'which is {questionAccessInformation.accessStatus}' if questionAccessInformation.accessStatus else ''} {f'{questionAccessInformation.markedDone}' if questionAccessInformation.markedDone else ''}; 
     """
 
     partsDetails = "\n".join(
         [
             format_part_details(
                 part,
-                questionAccessInformation.currentPart.id,
+                questionAccessInformation.currentPart,
                 questionSubmissionSummary
             ) for part in questionInformation.parts
         ]