updated openai engine

Author: juedwards

AI_Vector_Tools/build_challenge_builder.py

@@ -0,0 +1,73 @@
+import os
+import asyncio
+import pandas as pd
+from openai import AsyncOpenAI
+import os
+
+client = AsyncOpenAI(api_key=os.getenv('OPENAI_API_KEY'))
+
+async def generate_gpt_response(subject, learning_outcomes, age_range, lesson_duration):
+    prompt = (
+        "Based on the following requirements:\n"
+        f"Subject: {subject}\n"
+        f"Learning Outcomes: {learning_outcomes}\n"
+        f"Age Range/Grade: {age_range}\n"
+        f"Lesson Duration: {lesson_duration}\n"
+        "Generate a Minecraft Education build challenge that includes:\n"
+        "a) A build challenge prompt for the students.\n"
+        "b) An explanation of the build that the teacher can expect to see.\n"
+        "c) Some ideas for assessment for that build challenge."
+    )
+
+    completion = await client.chat.completions.create(
+        model="gpt-3.5-turbo",
+        messages=[
+            {"role": "system", "content": "You are a helpful assistant."},
+            {"role": "user", "content": prompt}
+        ]
+    )
+
+    return completion.choices[-1].message.content.strip()
+
+def safe_filename(filename):
+    """Generate a safe filename by removing or replacing invalid characters."""
+    invalid_chars = '<>:"/\\|?*'
+    for char in invalid_chars:
+        filename = filename.replace(char, '-')
+    return filename[:200]  # Limit the filename length to 200 characters for compatibility
+
+async def process_and_save_response(row, base_dir):
+    response = await generate_gpt_response(row['Subject'], row['LearningOutcomes'], row['AgeRange'], row['LessonLength'])
+    
+    # Format the Markdown content
+    markdown_content = f"# Minecraft Mini Build Challenge\n\n" \
+                       f"**Subject:** {row['Subject']}\n\n" \
+                       f"**Learning Outcomes:** {row['LearningOutcomes']}\n\n" \
+                       f"**Age Range:** {row['AgeRange']}\n\n" \
+                       f"**Lesson Duration:** {row['LessonLength']}\n\n" \
+                       "---\n\n" \
+                       f"{response}"
+    
+    # Use the subject as the filename (or modify as needed to ensure uniqueness)
+    filename = safe_filename(row['Subject']) + ".md"
+    filepath = os.path.join(base_dir, filename)
+    
+    # Save the formatted content to a Markdown file
+    with open(filepath, 'w', encoding='utf-8') as file:
+        file.write(markdown_content)
+
+    print(f"Saved response to {filepath}")
+
+async def main():
+    csv_file_path = os.path.expanduser("~/Downloads/101ways.csv")
+    df = pd.read_csv(csv_file_path)
+
+    # Determine the base directory from the CSV file path
+    base_dir = os.path.dirname(csv_file_path)
+
+    # Process and save responses for each row
+    tasks = [process_and_save_response(row, base_dir) for _, row in df.iterrows()]
+    await asyncio.gather(*tasks)
+
+if __name__ == "__main__":
+    asyncio.run(main())