algo for guarding AI on rails.

new file:   research/activity.yaml
	new file:   research/activity10.yaml
	new file:   research/activity11.yaml
	new file:   research/activity12.yaml
	new file:   research/activity2.yaml
	new file:   research/activity3.yaml
	new file:   research/activity4.yaml
	new file:   research/activity5.yaml
	new file:   research/activity6.yaml
	new file:   research/activity7.yaml
	new file:   research/activity8.yaml
	new file:   research/activity9.yaml
	new file:   research/guarded_ai.py

research/guarded_ai.py

@@ -0,0 +1,146 @@
+import yaml
+from openai import OpenAI
+
+client = OpenAI()
+
+
+# Load the YAML activity file
+def load_yaml_activity(file_path):
+    with open(file_path, "r") as file:
+        return yaml.safe_load(file)
+
+
+# Categorize the user's response using gpt-4o-mini
+def categorize_response(question, response, buckets, tokens_for_ai):
+    bucket_list = ", ".join(buckets)
+    messages = [
+        {
+            "role": "system",
+            "content": f"{tokens_for_ai} Categorize the following response into one of the following buckets: {bucket_list}.",
+        },
+        {
+            "role": "user",
+            "content": f"Question: {question}\nResponse: {response}\n\nCategory:",
+        },
+    ]
+
+    try:
+        completion = client.chat.completions.create(
+            model="gpt-4o-mini",
+            messages=messages,
+            max_tokens=10,
+            temperature=0,
+        )
+        category = (
+            completion.choices[0].message.content.strip().lower().replace(" ", "_")
+        )
+        return category
+    except Exception as e:
+        return f"Error: {e}"
+
+
+# Generate AI feedback using gpt-4o-mini
+def generate_ai_feedback(category, question, user_response, tokens_for_ai):
+    messages = [
+        {
+            "role": "system",
+            "content": "{tokens_for_ai} Generate a human-readable feedback message based on the following:",
+        },
+        {
+            "role": "user",
+            "content": f"Question: {question}\nResponse: {user_response}\nCategory: {category}",
+        },
+    ]
+
+    try:
+        completion = client.chat.completions.create(
+            model="gpt-4o-mini", messages=messages, max_tokens=250, temperature=0.7
+        )
+        feedback = completion.choices[0].message.content.strip()
+        return feedback
+    except Exception as e:
+        return f"Error: {e}"
+
+
+# Provide feedback based on the category
+def provide_feedback(
+    yaml_content, section_id, step_id, category, question, user_response
+):
+    section = next(
+        (s for s in yaml_content["sections"] if s["section_id"] == section_id), None
+    )
+    if not section:
+        return "Section not found."
+
+    step = next((s for s in section["steps"] if s["step_id"] == step_id), None)
+    if not step:
+        return "Step not found."
+
+    transition = step["transitions"].get(category, None)
+    if not transition:
+        return "Category not found."
+
+    feedback = "\n".join(transition["content_blocks"])
+    if "ai_feedback" in transition:
+        tokens_for_ai = (
+            step["tokens_for_ai"] + " " + transition["ai_feedback"]["tokens_for_ai"]
+        )
+        ai_feedback = generate_ai_feedback(
+            category, question, user_response, tokens_for_ai
+        )
+        feedback += f"\n\nAI Feedback: {ai_feedback}"
+
+    return feedback
+
+
+# Simulate the activity
+def simulate_activity(yaml_file_path):
+    yaml_content = load_yaml_activity(yaml_file_path)
+    max_attempts = yaml_content.get("default_max_attempts_per_step", 3)
+
+    for section in yaml_content["sections"]:
+        print(f"\nSection: {section['title']}\n")
+        for step in section["steps"]:
+            # Print all content blocks once per step
+            if "content_blocks" in step:
+                for block in step["content_blocks"]:
+                    print(block)
+            if "question" in step:
+                question = step["question"]
+            else:
+                # Skip classification and feedback if there's no question
+                continue
+
+            attempts = 0
+            while attempts < max_attempts:
+                if "question" in step:
+                    print(f"\nQuestion: {question}")
+
+                user_response = input("\nYour Response: ")
+
+                category = categorize_response(
+                    question, user_response, step["buckets"], step["tokens_for_ai"]
+                )
+                print(f"\nCategory: {category}")
+
+                feedback = provide_feedback(
+                    yaml_content,
+                    section["section_id"],
+                    step["step_id"],
+                    category,
+                    question,
+                    user_response,
+                )
+                print(f"\nFeedback: {feedback}")
+
+                if category == "correct":
+                    break
+
+                attempts += 1
+
+            if attempts == max_attempts:
+                print("\nMaximum attempts reached. Moving to the next step.")
+
+
+if __name__ == "__main__":
+    simulate_activity("activity12.yaml")