Reorganize project structure: clean up containers and prefect scripts

- Remove docker-learning folder (will rebuild from scratch)
- Clean up bo-containerized folder, keep only requirements.txt and core files
- Remove automated Branin functions from HITL workflow for true human-in-the-loop
- Reorganize prefect_scripts folder, move old scripts to sample_scripts
- Prepare structure for MongoDB integration and containerization

Author: Daniel0813

bo-containerized/Dockerfile

@@ -40,18 +40,6 @@
     subprocess.check_call([sys.executable, "-m", "pip", "install", "ax-platform"])
     from ax.service.ax_client import AxClient, ObjectiveProperties
 
-# Define our own Branin function since ax.utils.measurement.synthetic_functions might not be available
-def branin(x1, x2):
-    """Branin synthetic benchmark function"""
-    a = 1
-    b = 5.1 / (4 * np.pi**2)
-    c = 5 / np.pi
-    r = 6
-    s = 10
-    t = 1 / (8 * np.pi)
-    
-    return a * (x2 - b * x1**2 + c * x1 - r)**2 + s * (1 - t) * np.cos(x1) + s
-
 # Import Prefect and Slack for HITL workflow
 import asyncio
 from prefect import flow, get_run_logger, settings, task
@@ -61,7 +49,8 @@ def branin(x1, x2):
 from prefect.flow_runs import pause_flow_run
 
 class ExperimentInput(RunInput):
-    """Input model for experiment evaluation"""
+    """ Defines the data structure for human input
+    humans must provide objective_value (float) + optional notes"""
     objective_value: float
     notes: str = ""
 
@@ -105,12 +94,9 @@ def complete_experiment(ax_client: AxClient, trial_index: int, objective_value:
     ax_client.complete_trial(trial_index=trial_index, raw_data=objective_value)
 
 
-def evaluate_branin(parameters: Dict) -> float:
-    """Evaluate the Branin function for the given parameters (automated evaluation)"""
-    return float(branin(x1=parameters["x1"], x2=parameters["x2"]))
-
 def generate_api_instructions(parameters: Dict) -> str:
-    """Generate instructions for using the HuggingFace API to evaluate Branin function"""
+    """Generate instructions that is part of the Slack Message for 
+    using the HuggingFace API to evaluate Branin function"""
     x1_value = parameters['x1']
     x2_value = parameters['x2']
 
@@ -148,7 +134,7 @@ def generate_api_instructions(parameters: Dict) -> str:
 @flow(name="bo-hitl-slack-campaign")
 def run_bo_campaign(n_iterations: int = 5, random_seed: int = 42):
     """
-    Main Bayesian Optimization campaign with human-in-the-loop evaluation via Slack
+    Bayesian Optimization campaign with human-in-the-loop evaluation via Slack
     
     This implements a human-in-the-loop workflow:
     1. User runs Python script starting BO campaign with Ax