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Syllabus-Formatter

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Kuberwastaken commited on Jun 6, 2025

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24aa2f9

1 Parent(s): 91d285a

formatter

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Files changed (9) hide show

app.py +339 -0
public/Content-Meta/Dotnotes.json +0 -0
public/Content-Meta/FifteenFourteen.json +1023 -0
public/Content-Meta/StudyX.json +0 -0
public/Content-Meta/UnifiedContent.json +0 -0
public/Content-Meta/syllabus.json +0 -0
public/Content-Meta/videos.json +0 -0
scripts/requirements.txt +0 -0
scripts/syllabus_formatter.py +386 -0

app.py ADDED Viewed

	@@ -0,0 +1,339 @@

+import gradio as gr
+import json
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+import logging
+from pathlib import Path
+import tempfile
+import time
+# Setup logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+class SyllabusFormatter:
+    def __init__(self, model_name="microsoft/Phi-3-mini-4k-instruct"):
+        self.model_name = model_name
+        self.tokenizer = None
+        self.model = None
+        self.pipe = None
+        self.processed_count = 0
+        self.total_count = 0
+    def setup_model(self):
+        """Download and setup the Phi model"""
+        try:
+            # Load tokenizer
+            self.tokenizer = AutoTokenizer.from_pretrained(
+                self.model_name,
+                trust_remote_code=True
+            )
+            # Load model with 8-bit quantization for efficiency
+            self.model = AutoModelForCausalLM.from_pretrained(
+                self.model_name,
+                torch_dtype=torch.float16,
+                device_map="auto",
+                trust_remote_code=True,
+                load_in_8bit=True
+            )
+            # Create pipeline
+            self.pipe = pipeline(
+                "text-generation",
+                model=self.model,
+                tokenizer=self.tokenizer,
+                max_new_tokens=2048,
+                temperature=0.1,
+                do_sample=True,
+                top_p=0.9,
+                repetition_penalty=1.1
+            )
+            logger.info("Model setup complete!")
+            return True
+        except Exception as e:
+            logger.error(f"Error setting up model: {str(e)}")
+            return False
+    def create_formatting_prompt(self, unit_content: str, unit_name: str, subject_name: str = "") -> str:
+        """Create a very clear, focused prompt for formatting syllabus content"""
+        prompt = f"""<|system|>You are a professional academic syllabus formatter. Your ONLY job is to take badly formatted syllabus content and make it beautifully organized and readable.
+RULES:
+1. PRESERVE every single word, topic, and concept from the original
+2. NEVER add explanations, examples, or new content
+3. ONLY restructure and format the existing text
+4. Use clear headings, bullet points, and logical grouping
+5. Separate different topics with proper spacing
+6. Make it scannable and easy to read
+FORMAT STYLE:
+- Use main topic headings with proper capitalization
+- Group related subtopics under main topics
+- Use bullet points (•) for lists of concepts
+- Use sub-bullets (◦) for details under main bullets
+- Separate major sections with line breaks
+- Keep technical terms exactly as written<|end|>
+<|user|>Subject: {subject_name}
+Unit: {unit_name}
+Original content (poorly formatted):
+{unit_content}
+Task: Reformat this content to be beautifully organized and readable. Do NOT add any new information - only restructure what's already there. Make it professional and easy to scan.<|end|>
+<|assistant|>"""
+        return prompt
+    def format_unit_content(self, unit_content: str, unit_name: str, subject_name: str = "", progress=None) -> str:
+        """Format a single unit's content using the AI model"""
+        try:
+            # Create prompt
+            prompt = self.create_formatting_prompt(unit_content, unit_name, subject_name)
+            # Generate formatted content
+            response = self.pipe(prompt)
+            # Extract formatted content
+            generated_text = response[0]['generated_text']
+            assistant_start = generated_text.find("<|assistant|>")
+            if assistant_start != -1:
+                formatted_content = generated_text[assistant_start + len("<|assistant|>"):].strip()
+            else:
+                formatted_content = generated_text.strip()
+            # Clean up and validate
+            formatted_content = self.clean_generated_content(formatted_content)
+            if not self.validate_formatted_content(unit_content, formatted_content):
+                return unit_content
+            return formatted_content
+        except Exception as e:
+            logger.error(f"Error formatting content: {str(e)}")
+            return unit_content
+    def validate_formatted_content(self, original: str, formatted: str) -> bool:
+        """Validate that formatted content preserves all important information"""
+        # Basic validation
+        if len(formatted) < len(original) * 0.4:
+            return False
+        return True
+    def clean_generated_content(self, content: str) -> str:
+        """Clean up generated content"""
+        # Remove special tokens
+        for token in ["<|system|>", "<|user|>", "<|assistant|>"]:
+            content = content.replace(token, "")
+        # Clean up extra whitespace
+        content = "\n".join(line.strip() for line in content.split("\n") if line.strip())
+        return content
+    def process_syllabus_file(self, syllabus_data: dict, progress=gr.Progress()) -> dict:
+        """Process the entire syllabus file with progress updates"""
+        try:
+            # Count total units
+            total_units = 0
+            processed = 0
+            def count_units(data):
+                count = 0
+                if isinstance(data, dict):
+                    for value in data.values():
+                        if isinstance(value, dict):
+                            count += count_units(value)
+                        elif isinstance(value, str) and "Unit" in str(value):
+                            count += 1
+                return count
+            total_units = count_units(syllabus_data.get("syllabus", {}))
+            logger.info(f"Total units to process: {total_units}")
+            # Process each branch
+            for branch_name, branch_data in syllabus_data.get("syllabus", {}).items():
+                if not isinstance(branch_data, dict):
+                    continue
+                # Process each semester
+                for sem_name, sem_data in branch_data.items():
+                    if not isinstance(sem_data, dict):
+                        continue
+                    # Process each subject
+                    for subject_name, subject_data in sem_data.items():
+                        if not isinstance(subject_data, dict) or "content" not in subject_data:
+                            continue
+                        content = subject_data["content"]
+                        if not isinstance(content, dict):
+                            continue
+                        # Format each unit
+                        for unit_name, unit_content in content.items():
+                            if not unit_name.startswith("Unit") or not isinstance(unit_content, str):
+                                continue
+                            processed += 1
+                            progress(processed / total_units, desc=f"Processing {unit_name} in {subject_name}...")
+                            # Format the unit content
+                            formatted_content = self.format_unit_content(
+                                unit_content,
+                                unit_name,
+                                subject_name
+                            )
+                            # Update the content
+                            syllabus_data["syllabus"][branch_name][sem_name][subject_name]["content"][unit_name] = formatted_content
+            # Add formatting metadata
+            if "metadata" not in syllabus_data:
+                syllabus_data["metadata"] = {}
+            syllabus_data["metadata"].update({
+                "lastFormatted": time.strftime("%Y-%m-%dT%H:%M:%SZ"),
+                "formattingModel": "Phi-3 Mini",
+                "unitsProcessed": processed,
+                "version": "1.0"
+            })
+            return syllabus_data
+        except Exception as e:
+            logger.error(f"Error processing syllabus: {str(e)}")
+            raise gr.Error(f"Error processing syllabus: {str(e)}")
+# Initialize the formatter
+formatter = None
+def setup_formatter():
+    global formatter
+    if formatter is None:
+        formatter = SyllabusFormatter()
+        return formatter.setup_model()
+    return True
+def process_file(file):
+    """Process the uploaded syllabus file"""
+    try:
+        # Setup formatter if needed
+        if not setup_formatter():
+            raise gr.Error("Failed to setup the formatting model. Please try again.")
+        # Read and parse JSON
+        content = file.read()
+        syllabus_data = json.loads(content)
+        # Process syllabus
+        formatted_data = formatter.process_syllabus_file(syllabus_data)
+        # Save to temporary file
+        with tempfile.NamedTemporaryFile(mode='w', suffix='.json', delete=False) as tmp:
+            json.dump(formatted_data, tmp, indent=2)
+            return tmp.name
+    except json.JSONDecodeError:
+        raise gr.Error("Invalid JSON file. Please check your syllabus file format.")
+    except Exception as e:
+        raise gr.Error(f"Error processing file: {str(e)}")
+# Custom theme
+theme = gr.themes.Soft(
+    primary_hue="indigo",
+    secondary_hue="blue",
+).set(
+    body_background_fill="#fafafa",
+    body_background_fill_dark="#1a1a1a",
+    button_primary_background_fill="*primary_500",
+    button_primary_background_fill_hover="*primary_600"
+)
+# Gradio interface
+title = "📚 Syllabus Formatter"
+description = """
+Transform your syllabus into a beautifully formatted, easy-to-read document using AI.
+### Features:
+- Preserves all original content
+- Improves readability and organization
+- Creates logical grouping and sections
+- Adds professional formatting
+Simply upload your JSON syllabus file and get a formatted version back!
+"""
+css = """
+.feedback {
+    margin-top: 20px;
+    padding: 10px;
+    border-radius: 8px;
+    background-color: #f0f9ff;
+    border: 1px solid #bae6fd;
+}
+.dark .feedback {
+    background-color: #082f49;
+    border-color: #075985;
+}
+"""
+with gr.Blocks(theme=theme, css=css) as iface:
+    gr.Markdown(f"# {title}")
+    gr.Markdown(description)
+    with gr.Row():
+        with gr.Column():
+            file_input = gr.File(
+                label="Upload Syllabus JSON",
+                file_types=[".json"],
+                file_count="single"
+            )
+            process_btn = gr.Button("🪄 Format Syllabus", variant="primary")
+    output_file = gr.File(
+        label="Download Formatted Syllabus",
+        file_count="single",
+        type="file",
+        interactive=False
+    )
+    with gr.Row():
+        feedback = gr.Markdown(
+            value="Upload a JSON syllabus file to begin...",
+            elem_classes=["feedback"]
+        )
+    def update_feedback(file):
+        return "Processing your syllabus... This may take a few minutes depending on the size."
+    # Setup click event
+    process_btn.click(
+        fn=update_feedback,
+        inputs=[file_input],
+        outputs=[feedback],
+        queue=False
+    ).then(
+        fn=process_file,
+        inputs=[file_input],
+        outputs=[output_file]
+    ).success(
+        fn=lambda: "✨ Syllabus formatting complete! You can now download the formatted file.",
+        outputs=[feedback]
+    )
+    gr.Markdown("""
+    ### 📝 Notes:
+    - The formatter preserves all original content while improving organization
+    - Processing time depends on the size of your syllabus
+    - For large files, please be patient as the AI processes each section
+    Made with ❤️ using Microsoft's Phi-3 Mini model
+    """)
+# Launch in dev mode
+if __name__ == "__main__":
+    iface.launch()

public/Content-Meta/Dotnotes.json ADDED Viewed