now you can load local activities via --local-activities

modified:   app.py
	modified:   research/activity15-choose-adventure.yaml

app.py

@@ -1712,6 +1712,24 @@ def cancel_generation(room_name):
         )
 
 
+def get_activity_content(file_path):
+    """
+    Load the activity content from either S3 or the local filesystem based on the configuration.
+    """
+    if app.config["LOCAL_ACTIVITIES"]:
+        # Load the activity YAML from a local file
+        with open(file_path, 'r') as file:
+            activity_yaml = file.read()
+    else:
+        # Load the activity YAML from S3
+        s3_client = boto3.client("s3")
+        bucket_name = os.environ.get("S3_BUCKET_NAME")
+        response = s3_client.get_object(Bucket=bucket_name, Key=file_path)
+        activity_yaml = response["Body"].read().decode("utf-8")
+
+    return yaml.safe_load(activity_yaml)
+
+
 def loop_through_steps_until_question(
     activity_content, activity_state, room_name, username
 ):
@@ -1810,12 +1828,7 @@ def loop_through_steps_until_question(
 
 
 def start_activity(room_name, s3_file_path, username):
-    s3_client = boto3.client("s3")
-    bucket_name = os.environ.get("S3_BUCKET_NAME")
-
-    response = s3_client.get_object(Bucket=bucket_name, Key=s3_file_path)
-    activity_yaml = response["Body"].read().decode("utf-8")
-    activity_content = yaml.safe_load(activity_yaml)
+    activity_content = get_activity_content(s3_file_path)
 
     with app.app_context():
         # Save the initial state to the database
@@ -1919,16 +1932,10 @@ def handle_activity_response(room_name, user_response, username):
         if not activity_state:
             return
 
-        # Load the activity YAML from S3
-        s3_client = boto3.client("s3")
-        bucket_name = os.environ.get("S3_BUCKET_NAME")
-        s3_file_path = activity_state.s3_file_path
+        # Load the activity content
+        activity_content = get_activity_content(activity_state.s3_file_path)
 
         try:
-            response = s3_client.get_object(Bucket=bucket_name, Key=s3_file_path)
-            activity_yaml = response["Body"].read().decode("utf-8")
-            activity_content = yaml.safe_load(activity_yaml)
-
             # Find the current section and step
             section = next(
                 s
@@ -2379,9 +2386,11 @@ if __name__ == "__main__":
 
     parser = argparse.ArgumentParser()
     parser.add_argument("--profile", help="AWS profile name", default=None)
+    parser.add_argument("--local-activities", action="store_true", help="Use local activity files instead of S3")
     args = parser.parse_args()
 
     # Set profile_name as a global attribute of the app object
     app.config["PROFILE_NAME"] = args.profile
+    app.config["LOCAL_ACTIVITIES"] = args.local_activities
 
     socketio.run(app, host="0.0.0.0", port=5001, use_reloader=True)

research/activity15-choose-adventure.yaml

@@ -7,10 +7,15 @@ sections:
   - section_id: "section_1"
     title: "The Escape Room Begins"
     steps:
-      - step_id: "step_1"
+
+      - step_id: "step_0"
         title: "Waking Up"
         content_blocks:
           - "You wake up in a dimly lit room with no memory of how you got there. The room is small and has a single door that is locked."
+
+      - step_id: "step_1"
+        title: "Explore"
+        content_blocks:
           - "You see a rug on the floor, a bookshelf with a book, and a safe on the wall."
           - "There is also an exit door, but it seems to be blocked by something."
           - "What do you do first? Look under the rug, examine the book, try to open the safe, or try to leave the room?"
@@ -39,12 +44,8 @@ sections:
             ai_feedback:
               tokens_for_ai: "Provide positive reinforcement and guide the user to make the next choice. Be flexible to classify actions that lead to finding hidden items. Use emojis like 👍 and 🌟."
           try_open_safe:
-            content_blocks:
-              - "You chose to try to open the safe. 🔒"
-              - "The safe is locked and requires both a key and a password to open."
             next_section_and_step: "section_4:step_1"
-            ai_feedback:
-              tokens_for_ai: "Provide positive reinforcement and guide the user to make the next choice. Be flexible to classify actions that lead to finding hidden items. Use emojis like 👍 and 🌟."
+
           try_leave_room:
             metadata_conditions:
               exit_key: true
@@ -95,8 +96,6 @@ sections:
               key: true
           continue_exploring:
             next_section_and_step: "section_1:step_1"
-            ai_feedback:
-              tokens_for_ai: "Provide positive reinforcement and guide the user to make the next choice. Be flexible to classify actions that lead to finding hidden items. Use emojis like 👍 and 🌟."
           find_coin:
             content_blocks:
               - "You chose to take a closer look under the rug. 🧺"
@@ -150,8 +149,6 @@ sections:
               password: true
           continue_exploring:
             next_section_and_step: "section_1:step_1"
-            ai_feedback:
-              tokens_for_ai: "Provide positive reinforcement and guide the user to make the next choice. Be flexible to classify actions that lead to finding hidden items. Use emojis like 👍 and 🌟."
           find_paper:
             content_blocks:
               - "You chose to take a closer look at the book. 📖"
@@ -211,8 +208,6 @@ sections:
               exit_key: true
           continue_exploring:
             next_section_and_step: "section_1:step_1"
-            ai_feedback:
-              tokens_for_ai: "Provide positive reinforcement and guide the user to make the next choice. Be flexible to classify actions that lead to finding hidden items. Use emojis like 👍 and 🌟."
           go_back:
             next_section_and_step: "section_3:step_1"
             ai_feedback: