Overview The ContentGenerator class is responsible for creating the initial presentation structure. It uses Google’s Gemini AI to generate a complete slide-by-slide breakdown including titles, content text, and metadata about visual needs (images/animations).
Class Definition from generators.content_generator import ContentGenerator content_gen = ContentGenerator()
Constructor Initializes the content generator with Google Gemini AI configuration.
Configuration:
Model : Uses Config.GEMINI_MODEL (configured in environment)Response Format : JSON (application/json MIME type)API Key : Configured via Config.GEMINI_API_KEY
Methods generate_content Generates complete presentation structure with slide content and visual requirements.
def generate_content ( topic : str , num_slides : int = 5 ) -> Dict
The presentation topic or subject matter
Number of slides to generate
Presentation content structure with slides data
Returns structure: { "topic" : "Newton's Laws of Motion" , "total_slides" : 5 , "slides" : [ { "slide_number" : 1 , "title" : "Introduction to Newton's Laws" , "content_text" : "Overview of the three fundamental laws" , "needs_image" : false , "image_keyword" : "" , "needs_animation" : false , "animation_description" : "" , "duration" : 6.0 } ] }
Total number of slides generated
Array of slide objects with content and metadata Show Slide Object Properties
Sequential slide number (1-indexed)
Main content text for the slide (2-4 sentences)
Whether this slide requires an image (mutually exclusive with animation)
Search keyword for image if needs_image is true
Whether this slide requires a Manim animation (mutually exclusive with image)
Detailed description of what to animate if needs_animation is true
Estimated slide duration in seconds (4-10 seconds typical)
Data Models SlideContent Pydantic model representing individual slide content.
class SlideContent ( BaseModel ): slide_number: int title: str content_text: str needs_image: bool image_keyword: str = "" needs_animation: bool animation_description: str = "" duration: float
Validation Rules:
Mutual Exclusivity : A slide cannot have both needs_animation=True and needs_image=TrueAuto-correction : If both flags are true, the generator prioritizes animation and clears image fields
PresentationContent Pydantic model for complete presentation structure.
class PresentationContent ( BaseModel ): topic: str total_slides: int slides: List[SlideContent]
Usage Example From backend/app.py:242-243:
# Step 1: Generate PPT content structure update_progress(generation_id, 10 , "generating_content" , "📝 Generating presentation content..." ) content_gen = ContentGenerator() content_data = content_gen.generate_content(topic, request.num_slides)
Output statistics: total = len (content_data[ 'slides' ]) text_only = sum ( 1 for s in content_data[ 'slides' ] if not s.get( 'needs_image' ) and not s.get( 'needs_animation' )) with_image = sum ( 1 for s in content_data[ 'slides' ] if s.get( 'needs_image' )) with_animation = sum ( 1 for s in content_data[ 'slides' ] if s.get( 'needs_animation' )) print ( f "Slide breakdown: Text= { text_only } Image= { with_image } Animation= { with_animation } " )
Content Generation Rules The generator follows specific rules enforced via the AI prompt:
Text-First Design : 70-80% of slides should be text-onlyImage Usage : Sparingly for people, places, objects, and static diagramsAnimation Usage : Very rarely (1-2 max) for concepts requiring motion visualizationMutual Exclusivity : Slides can have either image OR animation, never bothDuration Estimation : Based on content complexity (typically 4-10 seconds per slide)
File Persistence Generated content is automatically saved to:
Config.SLIDES_DIR / "{topic_sanitized}_content.json"
Filename Sanitization:
Max 30 characters from topic
Replaces spaces with underscores
Removes special characters (:, /, etc.)
Error Handling The generator includes comprehensive error handling:
try : response = self .model.generate_content(prompt) text = response.text.strip() # Clean markdown formatting text = text.replace( 'json' , '' ).replace( '`' , '' ).strip() # Parse and validate JSON content_data = json.loads(text) # Add missing fields if needed if 'topic' not in content_data: content_data[ 'topic' ] = topic if 'total_slides' not in content_data: content_data[ 'total_slides' ] = len (content_data[ 'slides' ]) # Fix mutual exclusivity violations for slide in content_data[ 'slides' ]: if slide.get( 'needs_animation' ) and slide.get( 'needs_image' ): if slide.get( 'animation_description' ): slide[ 'needs_image' ] = False slide[ 'image_keyword' ] = "" else : slide[ 'needs_animation' ] = False slide[ 'animation_description' ] = "" except Exception as e: print ( f "Content generation error: { e } " ) traceback.print_exc() raise