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| import streamlit as st | |
| import ast | |
| import base64 | |
| import streamlit.components.v1 as components | |
| from transformers import pipeline | |
| from gtts import gTTS | |
| st.set_page_config(page_title="AR/VR Code Visualizer", layout="wide") | |
| st.title("👓 AR/VR Code Visualizer with Call Relationships + Narration") | |
| def load_model(): | |
| return pipeline("summarization", model="philschmid/bart-large-cnn-samsum") | |
| summarizer = load_model() | |
| uploaded_file = st.file_uploader("📁 Upload a Python file", type=["py"]) | |
| if uploaded_file: | |
| code = uploaded_file.read().decode("utf-8") | |
| st.code(code, language="python") | |
| # Parse AST for functions and call relationships | |
| tree = ast.parse(code) | |
| class FunctionCallVisitor(ast.NodeVisitor): | |
| def __init__(self): | |
| self.calls = {} | |
| def visit_FunctionDef(self, node): | |
| caller = node.name | |
| self.calls[caller] = [] | |
| for child in ast.walk(node): | |
| if isinstance(child, ast.Call) and isinstance(child.func, ast.Name): | |
| self.calls[caller].append(child.func.id) | |
| self.generic_visit(node) | |
| visitor = FunctionCallVisitor() | |
| visitor.visit(tree) | |
| call_graph = visitor.calls | |
| all_functions = list(call_graph.keys()) | |
| # Show call relationships | |
| st.subheader("📊 Call Relationships") | |
| for fn, callees in call_graph.items(): | |
| st.write(f"🔹 `{fn}` calls: {', '.join(callees) if callees else 'None'}") | |
| # Hugging Face summarization | |
| prompt = f"Explain the structure and purpose of the following functions and how they call each other: {call_graph}" | |
| summary = summarizer(prompt, max_length=60, min_length=15, do_sample=False) | |
| summary_text = summary[0]['summary_text'] | |
| st.success(summary_text) | |
| # Voice narration | |
| st.subheader("🔊 Voice Narration of Code Summary") | |
| tts = gTTS(text=summary_text) | |
| tts.save("summary.mp3") | |
| audio_file = open("summary.mp3", "rb") | |
| st.audio(audio_file.read(), format="audio/mp3") | |
| # Generate A-Frame scene | |
| def generate_aframe(call_graph): | |
| spacing = 3 | |
| boxes = [] | |
| lines = [] | |
| positions = {} | |
| for i, fn in enumerate(call_graph): | |
| x = i * spacing | |
| positions[fn] = (x, 1, -3) | |
| boxes.append(f''' | |
| <a-box position="{x} 1 -3" depth="0.5" height="0.5" width="2" color="#FFC65D"></a-box> | |
| <a-text value="{fn}" position="{x} 1.8 -3" align="center" color="#000"></a-text> | |
| ''') | |
| for caller, callees in call_graph.items(): | |
| for callee in callees: | |
| if callee in positions: | |
| x1, y1, z1 = positions[caller] | |
| x2, y2, z2 = positions[callee] | |
| lines.append(f''' | |
| <a-entity line="start: {x1} {y1} {z1}; end: {x2} {y2} {z2}; color: red"></a-entity> | |
| ''') | |
| html = f''' | |
| <!DOCTYPE html> | |
| <html> | |
| <head> | |
| <script src="https://aframe.io/releases/1.3.0/aframe.min.js"></script> | |
| </head> | |
| <body> | |
| <a-scene background="color: #ECECEC"> | |
| <a-entity position="0 1.6 3"> | |
| <a-camera wasd-controls-enabled="true" look-controls-enabled="true"></a-camera> | |
| </a-entity> | |
| <a-light type="ambient" color="#FFF"></a-light> | |
| <a-plane rotation="-90 0 0" width="40" height="40" color="#7BC8A4"></a-plane> | |
| {''.join(boxes)} | |
| {''.join(lines)} | |
| </a-scene> | |
| </body> | |
| </html> | |
| ''' | |
| return html | |
| aframe_html = generate_aframe(call_graph) | |
| b64 = base64.b64encode(aframe_html.encode()).decode() | |
| data_url = f"data:text/html;base64,{b64}" | |
| st.subheader("🌐 3D Call Relationship Visualization") | |
| components.iframe(data_url, height=500) | |
| else: | |
| st.info("Upload a Python file to visualize its structure, relationships, and get narrated summary.") | |