Merge branch 'mued_api_adopted' into dev

Author: neagualexa

README.md

@@ -1,6 +1,7 @@
-# Lambda Feedback Chat Function Boilerplate
+# reflectiveChatFunction
 
-This repository contains the code needed to develop a modular chatbot to be used on Lambda-Feedback platform [written in Python].
+This repository contains the code for a modular Socratic chatbot to be used on Lambda-Feedback platform [written in Python].
+More details about the chatbot's behaviour in [User Documentation](docs/user.md).
 
 ## Quickstart
 

config.json

@@ -1,3 +1,3 @@
 {
-  "ChatFunctionName": ""
+  "ChatFunctionName": "reflectiveChatFunction"
 }

docs/dev.md

@@ -1,14 +1,40 @@
-# YourFunctionName
-*Brief description of what this chat function does, from the developer perspective*
+# reflectiveChatFunction
+This chatbot aims to respond to all relevant tasks the student requests by emphasising self-reflection through asking the student follow-up questions. The Chatbot is aware of the Question details, answer, worked solution and guidance from the lecturer.
+
+Some technical details:
+<pre style="white-space: pre-wrap;">
+<code>LLM model: gpt-4o-mini (OpenAI)
+response time (on average): 10 seconds
+
+Helping approach: always responds with a follow-up question
+</code>
+</pre>
 
 ## Inputs
-*Specific input parameters which can be supplied when the calling this chat function.*
+Body:
+```JSON
+{
+    "message":"hi",
+    "params":{
+        "conversation_id":"12345Test",
+        "conversation_history":[{"type":"user","content":"hi"}],
+        "include_test_data": true,
+    }
+}
+```
 
 ## Outputs
-*Output schema/values for this function*
-
-## Examples
-*List of example inputs and outputs for this function, each under a different sub-heading*
+```JSON
+{
+    "chatbotResponse":"hi back",
+    "metadata": {
+        "summary": "",
+        "conversational_style": "",
+        "conversation_history": [],
+    },
+    "processing_time": 0
+}
+```
 
 ## Testing the Chat Function
 

docs/user.md

@@ -1,3 +1,12 @@
-# YourChatFunctionName
+# Reflective Chatbot
 
-Teacher- & Student-facing documentation for this function.
+This chatbot aims to respond to all relevant tasks the student requests by emphasising self-reflection through asking the student follow-up questions. The Chatbot is aware of the Question details, answer, worked solution and guidance from the lecturer.
+
+Some technical details:
+<pre style="white-space: pre-wrap;">
+<code>LLM model: gpt-4o-mini (OpenAI)
+response time (on average): 10 seconds
+
+Helping approach: always responds with a follow-up question
+</code>
+</pre>

index.py

@@ -1,52 +1,36 @@
 import json
+from pydantic import ValidationError
+
+from lf_toolkit.chat import ChatRequest
 from src.module import chat_module
-from src.agent.utils.types import JsonType
 
-def handler(event: JsonType, context):
+
+def handler(event, context):
     """
     Lambda handler function
     """
-    # Log the input event for debugging purposes
-    # print("Received event:", " ".join(json.dumps(event, indent=2).splitlines()))
-
     if "body" in event:
         try:
             event = json.loads(event["body"])
         except json.JSONDecodeError:
             return {
                 "statusCode": 400,
-                "body": "Invalid JSON format in the body or body not found. Please check the input."
+                "body": "Invalid JSON format in the body. Please check the input.",
             }
 
-    if "message" not in event:
-        return {
-            "statusCode": 400,
-            "body": "Missing 'message' key in event. Please confirm the key in the json body."
-        }
-    if "params" not in event:
-        return {
-            "statusCode": 400,
-            "body": "Missing 'params' key in event. Please confirm the key in the json body. Make sure it contains the necessary conversation_id."
-        }
-    
-    message = event.get("message")
-    params = event.get("params")
+    try:
+        request = ChatRequest.model_validate(event)
+    except ValidationError as e:
+        return {"statusCode": 400, "body": e.json()}
 
     try:
-        chatbot_response = chat_module(message, params)
+        result = chat_module(request)
     except Exception as e:
         return {
             "statusCode": 500,
-            "body": f"An error occurred within the chat_module(): {str(e)}"
+            "body": f"An error occurred within the chat_module(): {str(e)}",
         }
 
-    # Create a response
-    response = {
-        "statusCode": 200,
-        "body": json.dumps(chatbot_response)
-    }
-
-    # Log the response for debugging purposes
+    response = {"statusCode": 200, "body": result.model_dump_json()}
     print("Returning response:", " ".join(json.dumps(response, indent=2).splitlines()))
-
-    return response
+    return response

src/agent/agent.py

@@ -181,7 +181,8 @@ def invoke_base_agent(query: str, conversation_history: list, summary: str, conv
     print(f'in invoke_base_agent(), thread_id = {session_id}')
 
     config = {"configurable": {"thread_id": session_id, "summary": summary, "conversational_style": conversationalStyle, "question_response_details": question_response_details}}
-    response_events = agent.app.invoke({"messages": conversation_history, "summary": summary, "conversational_style": conversationalStyle}, config=config, stream_mode="values") #updates
+    messages = conversation_history + [HumanMessage(content=query)]
+    response_events = agent.app.invoke({"messages": messages, "summary": summary, "conversational_style": conversationalStyle}, config=config, stream_mode="values") #updates
     pretty_printed_response = agent.pretty_response_value(response_events) # get last event/ai answer in the response
 
     # Gather Metadata from the agent

src/agent/prompts.py

@@ -1,5 +1,5 @@
-# 
-# NOTE: Default prompts generated with the help of ChatGPT GPT-4o Nov 2024
+# NOTE:
+# PROMPTS generated with the help of Claude 4
 # 
 # Description of the prompts:
 # 
@@ -14,8 +14,36 @@
 # 
 
 # 1. Role Prompt
-role_prompt = "You are an excellent tutor that aims to provide clear and concise explanations to students. I am the student. Your task is to answer my questions and provide guidance on the topic discussed. Ensure your responses are accurate, informative, and tailored to my level of understanding and conversational preferences. If I seem to be struggling or am frustrated, refer to my progress so far and the time I spent on the question vs the expected guidance. If I ask about a topic that is irrelevant, then say 'I'm not familiar with that topic, but I can help you with the [topic]. You do not need to end your messages with a concluding statement.\n\n"
-
+role_prompt = """You are a Socratic tutor who guides students to discover knowledge through thoughtful questioning rather than direct instruction. Your primary goal is to help students think critically and arrive at understanding through their own reasoning.
+
+**Core Behavior:**
+- ALWAYS end your response with a follow-up question that encourages deeper thinking
+- Guide students to discover answers through strategic questioning rather than providing direct explanations
+- Ask questions that build upon the student's current understanding
+- Use questions to reveal gaps in knowledge or misconceptions
+- Encourage students to explain their reasoning and thought processes
+
+**Question Types to Use:**
+- Clarifying questions: "What do you mean when you say...?"
+- Assumption-probing questions: "What assumptions are you making here?"
+- Evidence-based questions: "What evidence supports your thinking?"
+- Perspective questions: "How might someone who disagrees respond?"
+- Implication questions: "If that's true, what does that imply about...?"
+- Meta-questions: "Why do you think this question is important?"
+
+**Guidelines:**
+- When a student asks a direct question, respond with a counter-question that guides them toward the answer
+- If providing any information, immediately follow with a question that challenges them to apply or extend that knowledge
+- Adapt your questioning style to the student's level and subject matter
+- If a student seems frustrated, ask questions about their thought process to identify where they're getting stuck
+- Never provide complete answers—always leave room for the student to think and respond
+
+**Example Interaction Style:**
+Student: "What's the derivative of x²?"
+Tutor: "Let's think about this step by step. What does a derivative represent in this physics question, and how might we approach finding the rate of change of x²?"
+
+Remember: Your role is to be the question-asker, not the answer-giver. Every response should end with a thoughtful question that moves the student's understanding forward. If the student seems to be struggling or am frustrated, refer to their progress so far and the time they spent on the question vs the expected guidance. If they ask about a topic that is irrelevant, then say 'I'm not familiar with that topic, but I can help you with the [topic]. You do not need to end your messages with a concluding statement.
+"""
 # 2. Summary Prompts
 summary_guidelines = """Ensure the summary is: