#!/usr/bin/env python3
import os
import re
import glob
import streamlit as st
import streamlit.components.v1 as components
from transformers import pipeline
from urllib.parse import quote
from datetime import datetime
import pytz
# Page Configuration
st.set_page_config(
page_title="AI Knowledge Tree Builder ๐๐ฟ",
page_icon="๐ณโจ",
layout="wide",
initial_sidebar_state="auto",
)
# Predefined Knowledge Trees
trees = {
"Biology": """
0. Biology Core Rules and Future Exceptions
1. Central Dogma DNA RNA Protein
- Current CRISPR RNA editing ๐งช
- Research Gene therapy siRNA ๐ฌ
- Future Programmable genetics ๐
2. Cell Origin
- Current iPSCs organoids ๐ฆ
- Research Synthetic cells ๐ฌ
- Future De novo cell creation ๐
""",
"AI Topics": """
1. Major AI Industry Players ๐
1. Research Leaders ๐ฏ
- OpenAI: GPT-4 DALL-E Foundation Models ๐ต
- Google: PaLM Gemini LLMs ๐ฆ
- Anthropic: Claude Constitutional AI โก
""",
"Multiplayer Games": """
0. Fantasy Domain Introduction
1. Setting the Scene
- Current Create a high-fantasy realm ๐๏ธ
- Research Add domain-specific entities ๐งโโ๏ธ
- Future AI-generated worldbuilding ๐
"""
}
# Utility Functions
def sanitize_filename(text):
"""Sanitize text for use in filenames."""
safe_text = re.sub(r'[^\w\s-]', ' ', text)
safe_text = re.sub(r'\s+', ' ', safe_text)
return safe_text.strip()[:50]
def generate_timestamp_filename(query):
"""Generate a timestamped filename for saving files."""
central = pytz.timezone('US/Central')
current_time = datetime.now(central)
time_str = current_time.strftime("%I%M%p")
date_str = current_time.strftime("%m%d%Y")
safe_query = sanitize_filename(query)
return f"{time_str} {date_str} ({safe_query}).md"
def parse_outline_to_mermaid(outline_text):
"""Convert a tree outline to Mermaid syntax with clickable nodes."""
lines = outline_text.strip().split('\n')
nodes = []
edges = []
clicks = []
stack = []
for line in lines:
indent = len(line) - len(line.lstrip())
level = indent // 4 # 4 spaces per level
text = line.strip()
label = re.sub(r'^[#*\->\d\.\s]+', '', text).strip()
if label:
node_id = f"N{len(nodes)}"
nodes.append(f'{node_id}["{label}"]')
clicks.append(f'click {node_id} "?q={quote(label)}" _blank')
if stack:
parent_level = stack[-1][0]
if level > parent_level:
parent_id = stack[-1][1]
edges.append(f"{parent_id} --> {node_id}")
stack.append((level, node_id))
else:
while stack and stack[-1][0] >= level:
stack.pop()
if stack:
parent_id = stack[-1][1]
edges.append(f"{parent_id} --> {node_id}")
stack.append((level, node_id))
else:
stack.append((level, node_id))
return "graph TD\n" + "\n".join(nodes + edges + clicks)
def generate_mermaid_html(mermaid_code: str) -> str:
"""Generate HTML to center and display a Mermaid diagram."""
return f"""
<html>
<head>
<script src="https://cdn.jsdelivr.net/npm/mermaid/dist/mermaid.min.js"></script>
<style>
.centered-mermaid {{
display: flex;
justify-content: center;
margin: 20px auto;
}}
.mermaid {{
max-width: 800px;
}}
</style>
</head>
<body>
<div class="mermaid centered-mermaid">
{mermaid_code}
</div>
<script>
mermaid.initialize({{ startOnLoad: true }});
</script>
</body>
</html>
"""
def grow_tree(base_tree, new_node_name, parent_node):
"""Add a new node to the tree under a specified parent."""
lines = base_tree.strip().split('\n')
new_lines = []
added = False
for line in lines:
new_lines.append(line)
if parent_node in line and not added:
indent = len(line) - len(line.lstrip())
new_lines.append(f"{' ' * (indent + 4)}- {new_node_name} ๐ฑ")
added = True
return "\n".join(new_lines)
# AI Lookup
@st.cache_resource
def load_generator():
"""Load a text generation model for AI lookups."""
return pipeline("text-generation", model="distilgpt2")
# File Management
def FileSidebar():
"""Render a sidebar for managing Markdown files."""
st.sidebar.title("๐ Saved Interactions")
md_files = glob.glob("*.md")
for file in md_files:
col1, col2, col3 = st.sidebar.columns([1, 3, 1])
with col1:
if st.button("๐", key=f"open_{file}"):
with open(file, 'r') as f:
st.session_state['file_content'] = f.read()
st.session_state['selected_file'] = file
with col2:
st.write(file)
with col3:
if st.button("๐", key=f"delete_{file}"):
os.remove(file)
st.rerun()
if st.sidebar.button("Create New Note"):
filename = generate_timestamp_filename("New Note")
with open(filename, 'w') as f:
f.write("# New Note\n")
st.sidebar.success(f"Created {filename}")
# Main App Logic
st.title("๐ณ AI Knowledge Tree Builder ๐ฑ")
st.markdown("Grow, visualize, and explore knowledge trees with AI!")
# Handle Query Parameters
query_params = st.query_params
if 'q' in query_params:
query = query_params['q']
st.subheader(f"AI Lookup for: {query}")
generator = load_generator()
response = generator(query, max_length=50)[0]['generated_text']
st.write(f"**Response:** {response}")
filename = generate_timestamp_filename(query)
with open(filename, 'w') as f:
f.write(f"# Query: {query}\n\n## AI Response\n{response}")
st.success(f"Saved to {filename}")
else:
# Tree Selection and Interaction
if 'current_tree' not in st.session_state:
st.session_state['current_tree'] = trees["Biology"]
if 'selected_tree_name' not in st.session_state:
st.session_state['selected_tree_name'] = "Biology"
selected_tree = st.selectbox("Select Knowledge Tree", list(trees.keys()), key="tree_select")
if selected_tree != st.session_state['selected_tree_name']:
st.session_state['current_tree'] = trees[selected_tree]
st.session_state['selected_tree_name'] = selected_tree
# Tree Growth
new_node = st.text_input("Add New Node (e.g., 'ML Pipeline')")
parent_node = st.text_input("Parent Node to Attach To (e.g., 'Central Dogma')")
if st.button("Grow Tree ๐ฑ") and new_node and parent_node:
st.session_state['current_tree'] = grow_tree(st.session_state['current_tree'], new_node, parent_node)
st.success(f"Added '{new_node}' under '{parent_node}'!")
# Display Mermaid Diagram
st.markdown("### Knowledge Tree Visualization")
mermaid_code = parse_outline_to_mermaid(st.session_state['current_tree'])
mermaid_html = generate_mermaid_html(mermaid_code)
components.html(mermaid_html, height=600)
# AI Lookup
query = st.text_input("Enter Query for AI Lookup")
if st.button("Perform AI Lookup ๐ค") and query:
generator = load_generator()
response = generator(query, max_length=50)[0]['generated_text']
st.write(f"**AI Response:** {response}")
filename = generate_timestamp_filename(query)
with open(filename, 'w') as f:
f.write(f"# Query: {query}\n\n## AI Response\n{response}")
st.success(f"Saved to {filename}")
# File Viewer
if 'file_content' in st.session_state:
st.markdown("### Selected File")
st.markdown(st.session_state['file_content'])
# Sidebar
FileSidebar()
if __name__ == "__main__":
st.sidebar.markdown("Explore and grow your knowledge trees!")