# app.py - Final Version with AI-Powered Animations # Fix for huggingface_hub compatibility import huggingface_hub if not hasattr(huggingface_hub, 'cached_download'): from huggingface_hub import hf_hub_download huggingface_hub.cached_download = hf_hub_download import streamlit as st import os import time import random import numpy as np import pandas as pd import plotly.express as px import plotly.graph_objects as go from gtts import gTTS import base64 from PIL import Image import io import matplotlib.pyplot as plt import requests from io import BytesIO import json import torch from diffusers import DiffusionPipeline, StableDiffusionPipeline import torch from transformers import pipeline # Configure Streamlit page st.set_page_config( page_title="StoryCoder - Learn Python Through Stories", page_icon="🧙‍♂️", layout="wide", initial_sidebar_state="expanded" ) # Custom CSS for colorful UI st.markdown(""" """, unsafe_allow_html=True) # Concept database CONCEPTS = { "loop": { "name": "Loop", "emoji": "🔄", "description": "Loops repeat actions multiple times", "example": "for i in range(5):\n print('Hello!')", "color": "#FF9E6D" }, "conditional": { "name": "Conditional", "emoji": "❓", "description": "Conditionals make decisions in code", "example": "if sunny:\n go_outside()\nelse:\n stay_inside()", "color": "#4ECDC4" }, "function": { "name": "Function", "emoji": "✨", "description": "Functions are reusable blocks of code", "example": "def greet(name):\n print(f'Hello {name}!')", "color": "#FFD166" }, "variable": { "name": "Variable", "emoji": "📦", "description": "Variables store information", "example": "score = 10\nplayer = 'Alex'", "color": "#FF6B6B" }, "list": { "name": "List", "emoji": "📝", "description": "Lists store collections of items", "example": "fruits = ['apple', 'banana', 'orange']", "color": "#1A535C" } } # Pre-generated animation examples ANIMATION_EXAMPLES = { "loop": "https://i.imgur.com/7zQY1eE.gif", "conditional": "https://i.imgur.com/5X8jYAy.gif", "function": "https://i.imgur.com/9zJkQ7P.gif" } # Initialize AI models @st.cache_resource def load_models(): """Load AI models for animation generation""" models = {} try: # Use CPU-friendly model and float32 precision models['text_to_image'] = DiffusionPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", torch_dtype=torch.float32, # Use float32 instead of float16 safety_checker=None # Disable safety checker for simplicity ) # Move to GPU if available, otherwise keep on CPU device = "cuda" if torch.cuda.is_available() else "cpu" models['text_to_image'].to(device) except Exception as e: st.error(f"Could not load text-to-image model: {str(e)}") models['text_to_image'] = None try: # Text-to-speech model models['text_to_speech'] = pipeline("text-to-speech", model="suno/bark-small") except: models['text_to_speech'] = None return models def analyze_story(story): """Analyze story and identify programming concepts""" story_lower = story.lower() detected_concepts = [] # Check for loops if any(word in story_lower for word in ["times", "repeat", "again", "multiple"]): detected_concepts.append("loop") # Check for conditionals if any(word in story_lower for word in ["if", "when", "unless", "whether"]): detected_concepts.append("conditional") # Check for functions if any(word in story_lower for word in ["make", "create", "do", "perform", "cast"]): detected_concepts.append("function") # Check for variables if any(word in story_lower for word in ["is", "has", "set to", "value"]): detected_concepts.append("variable") # Check for lists if any(word in story_lower for word in ["and", "many", "several", "collection", "items"]): detected_concepts.append("list") return list(set(detected_concepts)) def extract_count_from_story(story): """Extract a number from the story to use in animations""" for word in story.split(): if word.isdigit(): return min(int(word), 10) return 3 # Default value def create_story_scene(story, concept, models): """Create a story scene using AI text-to-image model""" try: # Create a prompt based on the story and concept style = "cartoon style, bright colors, children's book illustration" prompt = f"{story}. {CONCEPTS[concept]['name']} concept. {style}" # Generate image with fixed settings image = models['text_to_image']( prompt, num_inference_steps=25, # Fewer steps for faster generation guidance_scale=7.5, height=512, width=512 ).images[0] # Convert to bytes buf = io.BytesIO() image.save(buf, format='PNG') buf.seek(0) return buf except Exception as e: st.error(f"AI scene generation error: {str(e)}") return None def create_animation_preview(story, concept): """Create an animation preview for the concept""" try: # Return a sample GIF for the concept return ANIMATION_EXAMPLES.get(concept, "https://i.imgur.com/7zQY1eE.gif") except: return "https://i.imgur.com/7zQY1eE.gif" def text_to_speech_custom(text, models, filename="story_audio.wav"): """Convert text to speech using AI model""" try: if models['text_to_speech']: # Generate audio audio = models['text_to_speech'](text) # Save to file with open(filename, "wb") as f: f.write(audio["audio"]) return filename # Fallback to gTTS tts = gTTS(text=text, lang='en') tts.save(filename) return filename except Exception as e: st.error(f"Audio creation error: {str(e)}") return None def autoplay_audio(file_path): """Autoplay audio in Streamlit""" with open(file_path, "rb") as f: data = f.read() b64 = base64.b64encode(data).decode() md = f""" """ st.markdown(md, unsafe_allow_html=True) def generate_animation_code(story, concept): """Generate Python animation code based on story""" try: # Sample code based on concept if concept == "loop": code = f""" # Loop Animation for: {story[:30]}... import time def animate_story(): actions = {extract_count_from_story(story)} for i in range(actions): print(f"Action {{i+1}}: {story[:20]}...") # Animation code would go here time.sleep(0.5) animate_story() """ description = "Looping through actions multiple times" visual_cue = "Repeating actions in a loop" elif concept == "conditional": code = f""" # Conditional Animation for: {story[:30]}... import random condition = random.choice([True, False]) if condition: print("Condition is True: {story[:20]}...") # True branch animation else: print("Condition is False: {story[:20]}...") # False branch animation """ description = "Making decisions based on conditions" visual_cue = "Branching paths based on conditions" else: # function code = f""" # Function Animation for: {story[:30]}... def perform_action(): print("Performing action: {story[:20]}...") # Action animation code # Call the function multiple times for _ in range({extract_count_from_story(story)}): perform_action() """ description = "Reusing code with functions" visual_cue = "Calling a reusable function" return code, description, visual_cue except Exception as e: return f"# Error generating code\nprint('Could not generate code: {str(e)}')", "", "" def create_interactive_animation(story, concept): """Create an interactive animation using Plotly""" try: # Create animation data frames = [] count = extract_count_from_story(story) for i in range(count): frames.append({ "frame": i, "x": np.random.uniform(1, 9), "y": np.random.uniform(1, 9), "size": np.random.uniform(20, 40), "label": f"Action {i+1}", "color": f"hsl({i*40}, 100%, 50%)" }) df = pd.DataFrame(frames) # Create animated scatter plot fig = px.scatter( df, x="x", y="y", animation_frame="frame", text="label", size="size", size_max=45, color="color", color_discrete_sequence=px.colors.qualitative.Alphabet, range_x=[0, 10], range_y=[0, 10], title=f"Interactive Animation: {story[:40]}{'...' if len(story) > 40 else ''}" ) # Customize layout fig.update_layout( showlegend=False, plot_bgcolor='rgba(240,248,255,1)', paper_bgcolor='rgba(240,248,255,1)', width=800, height=600, xaxis=dict(showgrid=False, zeroline=False, visible=False), yaxis=dict(showgrid=False, zeroline=False, visible=False), ) fig.update_traces( textfont_size=20, textposition='middle center', marker=dict(sizemode='diameter') ) return fig except Exception as e: st.error(f"Interactive animation error: {str(e)}") return None def main(): """Main application function""" st.title("🧙‍♂️ StoryCoder - Learn Python Through Stories!") st.subheader("Turn your story into an animation and discover coding secrets!") # Load AI models ai_models = load_models() # Initialize session state if 'story' not in st.session_state: st.session_state.story = "" if 'concepts' not in st.session_state: st.session_state.concepts = [] if 'story_scene' not in st.session_state: st.session_state.story_scene = None if 'interactive_animation' not in st.session_state: st.session_state.interactive_animation = None if 'animation_code' not in st.session_state: st.session_state.animation_code = "" if 'code_description' not in st.session_state: st.session_state.code_description = "" if 'visual_cue' not in st.session_state: st.session_state.visual_cue = "" if 'audio_file' not in st.session_state: st.session_state.audio_file = None if 'active_tab' not in st.session_state: st.session_state.active_tab = "story" # Create tabs tabs = st.empty() tab_cols = st.columns(5) with tab_cols[0]: if st.button("📖 Create Story"): st.session_state.active_tab = "story" with tab_cols[1]: if st.button("🎬 Animation"): st.session_state.active_tab = "animation" with tab_cols[2]: if st.button("🔍 Concepts"): st.session_state.active_tab = "concepts" with tab_cols[3]: if st.button("💻 Code"): st.session_state.active_tab = "code" with tab_cols[4]: if st.button("🔄 Reset"): st.session_state.story = "" st.session_state.concepts = [] st.session_state.story_scene = None st.session_state.interactive_animation = None st.session_state.animation_code = "" st.session_state.code_description = "" st.session_state.visual_cue = "" st.session_state.audio_file = None st.session_state.active_tab = "story" # Story creation tab if st.session_state.active_tab == "story": with st.container(): st.header("📖 Create Your Story") st.write("Write a short story (2-5 sentences) and I'll turn it into an animation!") story = st.text_area( "Your story:", height=200, placeholder="Once upon a time, a rabbit hopped 3 times to reach a carrot...", value=st.session_state.story, key="story_input" ) if st.button("Create Animation!", use_container_width=True): if len(story) < 10: st.error("Your story needs to be at least 10 characters long!") else: st.session_state.story = story with st.spinner("🧠 Analyzing your story for coding concepts..."): st.session_state.concepts = analyze_story(story) # Get the main concept main_concept = st.session_state.concepts[0] if st.session_state.concepts else "variable" with st.spinner("🎨 Generating AI story scene..."): st.session_state.story_scene = create_story_scene( story, main_concept, ai_models ) with st.spinner("🚀 Creating interactive animation..."): st.session_state.interactive_animation = create_interactive_animation( story, main_concept ) with st.spinner("💻 Generating animation code..."): st.session_state.animation_code, st.session_state.code_description, st.session_state.visual_cue = generate_animation_code( story, main_concept ) with st.spinner("🔊 Creating audio narration..."): audio_text = f"Your story: {story}. This demonstrates the programming concept: {st.session_state.code_description}" st.session_state.audio_file = text_to_speech_custom( audio_text, ai_models ) st.session_state.active_tab = "animation" st.rerun() # Show examples st.subheader("✨ Story Examples") col1, col2, col3 = st.columns(3) with col1: st.caption("Loop Example") st.code('"A dragon breathes fire 5 times at the castle"', language="text") st.image(create_animation_preview("", "loop"), use_column_width=True, caption="Loop Animation Preview") with col2: st.caption("Conditional Example") st.code('"If it rains, the cat stays inside, else it goes out"', language="text") st.image(create_animation_preview("", "conditional"), use_column_width=True, caption="Conditional Animation Preview") with col3: st.caption("Function Example") st.code('"A wizard casts a spell to make flowers grow"', language="text") st.image(create_animation_preview("", "function"), use_column_width=True, caption="Function Animation Preview") # Animation tab elif st.session_state.active_tab == "animation": st.header("🎬 Your Story Animation") if not st.session_state.story: st.warning("Please create a story first!") st.session_state.active_tab = "story" st.rerun() # Display AI-generated scene st.subheader("🖼️ AI-Generated Story Scene") if st.session_state.story_scene: st.image(st.session_state.story_scene, use_container_width=True) else: st.warning("Scene couldn't be generated. Showing example instead.") concept = st.session_state.concepts[0] if st.session_state.concepts else "loop" st.image(create_animation_preview("", concept), use_container_width=True) # Display interactive animation st.subheader("🎮 Interactive Animation") if st.session_state.interactive_animation: st.plotly_chart(st.session_state.interactive_animation, use_container_width=True) else: st.info("Interactive animation preview. The real animation would run on your computer!") concept = st.session_state.concepts[0] if st.session_state.concepts else "loop" st.image(create_animation_preview("", concept), use_container_width=True) # Animation concept preview st.subheader("📽️ Animation Concept Preview") if st.session_state.concepts: concept = st.session_state.concepts[0] st.image(create_animation_preview("", concept), caption=f"{CONCEPTS[concept]['name']} Animation Example", use_container_width=True) else: st.info("Animation preview would appear here") # Play audio narration st.subheader("🔊 Story Narration") if st.session_state.audio_file: audio_bytes = open(st.session_state.audio_file, 'rb').read() st.audio(audio_bytes, format='audio/wav') if st.button("▶️ Play Automatically"): autoplay_audio(st.session_state.audio_file) else: st.info("Audio narration would play automatically here") st.success("✨ Animation created successfully!") st.caption("This animation was generated with Python code based on your story!") if st.button("Reveal Coding Secrets!", use_container_width=True): st.session_state.active_tab = "concepts" st.rerun() # Concepts tab elif st.session_state.active_tab == "concepts": st.header("🔍 Coding Concepts in Your Story") st.subheader("We secretly used these programming concepts:") if not st.session_state.concepts: st.warning("No concepts detected in your story! Try adding words like '3 times', 'if', or 'make'.") else: for concept in st.session_state.concepts: if concept in CONCEPTS: details = CONCEPTS[concept] st.markdown(f"""
{details['emoji']}

{details['name']}

{details['description']}

{details['example']}
""", unsafe_allow_html=True) # Show animation preview for the concept st.image(create_animation_preview("", concept), caption=f"{details['name']} Animation Example", use_column_width=True) if st.button("See the Magic Code!", use_container_width=True): st.session_state.active_tab = "code" st.rerun() # Code tab elif st.session_state.active_tab == "code": st.header("💻 The Magic Code Behind Your Animation") st.write("Here's the Python code that would create your animation:") if st.session_state.animation_code: st.subheader(st.session_state.code_description) st.markdown(f"**Visual Cue:** {st.session_state.visual_cue}") st.code(st.session_state.animation_code, language="python") # Download button st.download_button( label="Download Animation Code", data=st.session_state.animation_code, file_name="story_animation.py", mime="text/python", use_container_width=True ) st.info("💡 To run this animation on your computer:") st.markdown(""" 1. Install Python from [python.org](https://python.org) 2. Install required libraries: `pip install matplotlib numpy` 3. Copy the code above into a file named `animation.py` 4. Run it with: `python animation.py` """) st.success("🎉 When you run this code, you'll see your story come to life!") # Show what the animation would look like st.subheader("🎬 What Your Animation Would Look Like") concept = st.session_state.concepts[0] if st.session_state.concepts else "loop" st.image(create_animation_preview("", concept), caption="This is similar to what your animation would look like", use_column_width=True) else: st.warning("No code generated yet!") if st.button("Create Another Story!", use_container_width=True): st.session_state.active_tab = "story" st.session_state.story = "" st.rerun() if __name__ == "__main__": main()