Agent-4 Update

app.py

@@ -3,6 +3,7 @@ import os
 import copy
 import sqlite3
 import operator
+import pandas as pd
 from math import ceil
 from fastapi import FastAPI, Query
 from contextlib import asynccontextmanager
@@ -25,7 +26,8 @@ session_state = {
     "report_data": None,
     "final_report": None,
     "dependencies": None,
-    "updated_roadmap": None
+    "updated_roadmap": None,
+    "chapter_analysis": None
 }
 
 
@@ -500,11 +502,32 @@ def shift_the_roadmap(roadmap, max_hours_per_day, ratio=(80, 20), dependencies=N
     return roadmap, extra_day_tasks
 
 def update_roadmap(current_roadmap, current_dayNumber, max_hours_per_day, dependencies, no_of_revision_days = 2):
-    if current_dayNumber == 1:
+    if current_dayNumber <= 1 or current_dayNumber > len(current_roadmap):
         return current_roadmap
     current_roadmap = copy.deepcopy(current_roadmap)
     day_index = current_dayNumber-2
     test_index = None
+
+    if "supplementary_tasks" in current_roadmap[day_index]:
+        current_roadmap[day_index+1]['supplementary_tasks'] = []
+        for subject in current_roadmap[day_index]["supplementary_tasks"]:
+            subject_name = subject["name"]
+            tasks = subject["tasks"]
+
+            # Separate completed and incomplete tasks
+            incomplete_tasks = [task for task in tasks if task['task_completed'] == False]
+            completed_tasks = [task for task in tasks if task['task_completed'] == True]
+
+            for task in incomplete_tasks:
+                task['rescheduled'] += 1
+            # Move incomplete tasks to next day
+            if incomplete_tasks:
+                current_roadmap[day_index+1]['supplementary_tasks'].append({
+                                                                            "name":subject_name, 
+                                                                            "tasks":incomplete_tasks
+                                                                          })
+            # Keep only completed tasks in the previous day
+            subject["tasks"] = completed_tasks
     
     # Check if a test exists in any specified day
     for day in current_roadmap['schedule']:
@@ -1193,6 +1216,140 @@ def answer_user_query(prompt):
     data = fetch_data_from_sql(query)
     return generate_nl_from_sql_output(prompt, data)
 
+## Agent 4 - Analysis and Accountability Agent
+class Plan(BaseModel):
+    result: Literal["More Tasks", "Revise Chapter", "Strong Chapter"] = Field(
+    ..., description="""In general what is needed to be done to make the student perform
+                        better in this concept the next time?"""
+    )
+    tasks: List[Literal["Concept Understanding", "Question Practice", "Revision", "Test", "No Tasks"]] = Field(
+    ..., description="""If more tasks are needed to be scheduled for the student, what kind
+                        of tasks must be scheduled for the student to perform better the
+                        next time?"""
+    )
+
+class Analysis(BaseModel):
+    correct_answers: int = Field(
+        ..., description="Count and find out the number of 'Correct?' keys with True as the value"
+        )
+    why_correct: str = Field(
+        ..., description="""Give a deep analysis on which area must the student be strong in, in order to answer
+                            the questions which were answered correctly"""
+        )
+    wrong_answers: int = Field(
+        ..., description="ount and find out the number of 'Correct?' keys with False as the value"
+        )
+    why_wrong: str = Field(
+        ..., description="""Give a deep analysis on which area should the student be weak in, to answer
+                            those questions incorrectly"""
+        )
+    action: Plan = Field(
+        ..., description="""Deeply analyze the difficulty levels of the answered questions
+                            along with the change in the ELO scores, as the student gives right and
+                            wrong answers. With this analysis, determine what would the student
+                            require more of to perform better the next time."""
+    )
+
+analyzer = llm.with_structured_output(Analysis)
+
+def get_llm_response(data):
+    response = analyzer.invoke(
+        [
+            SystemMessage(
+                content=f"""You are a smart AI mentor who is an expert in making sure that the students prepare
+                perfectly for their JEE examinaton. In order to make sure of this, you are asking a set of 5
+                questions to the student from the list of subtopics, which the student claims to have completed.
+
+                Now, once the student answers all those 5 questions. You will be given with all the details you need
+                to analyze how good the student has performed. The details which will be given to you are:
+
+                1). The Subject from which the question was asked. Which will be
+                    either Physics, Chemistry, or Maths
+                2). The Chapter from which the question was asked from.
+                3). The tag of the Question - It tells the kind of work the student
+                    needs to do, to answer that question. Which will be either
+                    Concept Understanding, Question Practice, Revision or Test.
+                4). The Complexity level of the question.  Which will be  either
+                    Easy, Hard or Medium.
+                5). The Questions which were asked to the student.
+                6). The 4 options which were given to the student.
+                7). The Option that was selected by the student.
+                8). The Correct Option.
+                9). Whether the student has answered the question correctly or not.
+                10). The ELO score of the student after answering that question.
+
+                Your job is to strictly follow the given output structure the whole time you would
+                be producing the analysis. You will not deviate in any manner from the given output
+                json structure, if you do so then the whole application will crash.
+
+                The complete data Required to analyze the student's performance is given to you here:
+                {data}
+                """
+            ),
+            HumanMessage(
+                content=f"""Perform the analysis with absolute accuracy and make no mistake.
+                The analysis will be used to understand whether the student actually knows something
+                in that subtopic of the subject, or he has just marked it as completed just for the
+                sake of it. Make sure your output is perfectly formatted with the given structure"""
+            ),
+        ]
+    )
+    return response
+
+    
+def ag4_update_roadmap(test_data, roadmap, chapter_analysis, current_dayNumber):
+    data_dict = test_data.to_dict(orient="records")
+    response = get_llm_response(
+        json.dumps(data_dict, indent=4)
+        ).model_dump()
+
+    subject = data_dict[0]["Subject"]
+    chapter = data_dict[0]["Chapter"]
+
+    analysis = {
+        "subject": subject,
+        "chapter": chapter,
+        "positives": response['why_correct'],
+        "negatives": response['why_wrong'],
+    }
+    chapter_analysis.append(analysis)
+
+    if response['action']['tasks'][0] != "No Tasks":
+        tasks = {
+                  "Physics": [],
+                  "Chemistry": [],
+                  "Maths": []
+                }
+
+        for task in response['action']['tasks']:
+            tasks[subject].append({
+                "ChapterName": chapter,
+                "type": task,
+                "rescheduled": 0,
+                "completed": False,
+                "completion_timestamp": None
+            })
+
+        day = roadmap['schedule'][current_dayNumber]
+        if "supplementary_tasks" not in day:
+            day["supplementary_tasks"] = [{
+                                           "name":"Physics",
+                                           "tasks":[]
+                                         },{
+                                           "name":"Chemistry",
+                                           "tasks":[]
+                                         },{
+                                           "name":"Maths",
+                                           "tasks":[]
+                                         }]
+        for sub in day["supplementary_tasks"]:
+            sub_name = sub["name"]
+            for task in tasks[sub_name]:
+                if task not in sub["tasks"]:
+                    sub["tasks"].append(task)
+
+    session_state['updated_roadmap'] = roadmap
+    session_state['chapter_analysis'] = chapter_analysis
 
 @app.get("/", response_class=HTMLResponse)
 def root():
@@ -1469,4 +1626,148 @@ def agent3(query: str = Query(..., description="User's message to the chatbot"))
         return {"chat_response": {
             "role": "assistant",
             "message": f"Sorry, I encountered an error: {e}"
-        }}
+        }}
+    
+# --- AGENT 4: Accountability and Analysis Agent
+df = pd.DataFrame([
+    {
+        "Subject": "Physics",
+        "Chapter": "Vectors",
+        "Question Tag": "Concept Understanding",
+        "Question Complexity": "Easy",
+        "Question": "The vector projection of a vector on y-axis is",
+        "Options Given": "(a) 5 (b) 4 (c) 3 (d) Zero",
+        "Correct Option": "d",
+        "Selected Option": "d",
+        "Correct?": True,
+        "ELO Score": 1200
+    },
+    {
+        "Subject": "Physics",
+        "Chapter": "Vectors",
+        "Question Tag": "Concept Understanding",
+        "Question Complexity": "Easy",
+        "Question": "Position of a particle in a rectangular coordinate system is (3, 2, 5). Then its position vector will be",
+        "Options Given": "(a) 3i + 2j + 5k (b) 2i + 3j + 5k (c) 5i + 2j + 3k (d) None of these",
+        "Correct Option": "a",
+        "Selected Option": "b",
+        "Correct?": False,
+        "ELO Score": 1170
+    },
+    {
+        "Subject": "Physics",
+        "Chapter": "Vectors",
+        "Question Tag": "Question Practice",
+        "Question Complexity": "Easy",
+        "Question": "If a particle moves from point P (2,3,5) to point Q (3,4,5), its displacement vector is",
+        "Options Given": "(a) i + j (b) i + j + k (c) 2i + 2j (d) None of these",
+        "Correct Option": "a",
+        "Selected Option": "a",
+        "Correct?": True,
+        "ELO Score": 1185
+    },
+    {
+        "Subject": "Physics",
+        "Chapter": "Vectors",
+        "Question Tag": "Concept Understanding",
+        "Question Complexity": "Medium",
+        "Question": "A particle moving eastwards with 5 m/s. In 10 s the velocity changes to 5 m/s northwards. The average acceleration is",
+        "Options Given": "(a) 1/2 m/s² NE (b) 1/2 m/s² North (c) 1/2 m/s² NW (d) Zero",
+        "Correct Option": "a",
+        "Selected Option": "a",
+        "Correct?": True,
+        "ELO Score": 1225
+    },
+    {
+        "Subject": "Physics",
+        "Chapter": "Vectors",
+        "Question Tag": "Question Practice",
+        "Question Complexity": "Medium",
+        "Question": "A river is flowing west to east with 5 m/min. A man can swim in still water at 10 m/min. Which direction should he swim to reach the south bank in shortest path?",
+        "Options Given": "(a) 30° E of S (b) 60° E of N (c) South (d) 30° W of N",
+        "Correct Option": "c",
+        "Selected Option": "a",
+        "Correct?": False,
+        "ELO Score": 1190
+    },
+    {
+        "Subject": "Physics",
+        "Chapter": "Vectors",
+        "Question Tag": "Revision",
+        "Question Complexity": "Medium",
+        "Question": "Find a vector perpendicular to A = 2i + 3j in the same plane.",
+        "Options Given": "(a) -3i + 2j (b) 3i - 2j (c) i + j (d) None",
+        "Correct Option": "a",
+        "Selected Option": "a",
+        "Correct?": True,
+        "ELO Score": 1230
+    },
+    {
+        "Subject": "Physics",
+        "Chapter": "Vectors",
+        "Question Tag": "Revision",
+        "Question Complexity": "Medium",
+        "Question": "Two vectors A and B have same magnitude. If their resultant is perpendicular to A, what is the angle between A and B?",
+        "Options Given": "(a) 60° (b) 120° (c) 135° (d) None",
+        "Correct Option": "b",
+        "Selected Option": "b",
+        "Correct?": True,
+        "ELO Score": 1260
+    },
+    {
+        "Subject": "Physics",
+        "Chapter": "Vectors",
+        "Question Tag": "Test",
+        "Question Complexity": "Hard",
+        "Question": "A man walks 500 m and turns by 60° five times. What is displacement after 5th turn?",
+        "Options Given": "(a) 500 m (b) 1000 m (c) 500√3 m (d) None",
+        "Correct Option": "a",
+        "Selected Option": "c",
+        "Correct?": False,
+        "ELO Score": 1210
+    },
+    {
+        "Subject": "Physics",
+        "Chapter": "Vectors",
+        "Question Tag": "Test",
+        "Question Complexity": "Hard",
+        "Question": "Rain is falling vertically at 3 m/s and a man moves north at 4 m/s. Direction to hold umbrella?",
+        "Options Given": "(a) 37° N of vertical (b) 37° S of vertical (c) 53° N of vertical (d) 53° S of vertical",
+        "Correct Option": "c",
+        "Selected Option": "c",
+        "Correct?": True,
+        "ELO Score": 1265
+    },
+    {
+        "Subject": "Physics",
+        "Chapter": "Vectors",
+        "Question Tag": "Test",
+        "Question Complexity": "Hard",
+        "Question": "Which set of forces cannot be in equilibrium?",
+        "Options Given": "(a) 10N,10N,5N (b) 5N,7N,9N (c) 8N,4N,13N (d) 9N,6N,5N",
+        "Correct Option": "c",
+        "Selected Option": "c",
+        "Correct?": True,
+        "ELO Score": 1310
+    }
+])
+df.sort_values(by=['Correct?'], ascending=False, inplace=True)
+
+@app.get("/agent4")
+def agent4(
+    df: pd.DataFrame = Query(df, description="Dataframe of the Results of the students test"),
+    current_dayNumber: int = Query(2, description="Today's day number for scheduling tasks"),
+):
+    """
+    Agent 4 - Accountability and Analysis Agent.
+    """
+    if session_state['updated_roadmap']:
+        before = session_state['updated_roadmap']
+    else:
+        before = session_state['data']
+    ag4_update_roadmap(df, before, session_state["task_analysis"], current_dayNumber)
+
+    return {
+        "original_roadmap": before,
+        "updated_roadmap": session_state["updated_roadmap"]
+    }