Spaces:

awacke1
/

TransformersDiffusersNDatasets

Sleeping

App Files Files Community

awacke1 commited on Mar 6

Commit

9801d9a

verified ·

1 Parent(s): b6cb77e

Update app.py

Browse files

Files changed (1) hide show

app.py +116 -95

app.py CHANGED Viewed

@@ -1,13 +1,16 @@
-import streamlit as st
-from transformers import pipeline
 import os
-import glob
 import re
-import pytz
 from datetime import datetime
-import base64
-# 🌳🤖 AI Knowledge Tree Builder - Growing smarter with every click!
 st.set_page_config(
     page_title="AI Knowledge Tree Builder 📈🌿",
     page_icon="🌳✨",
@@ -16,7 +19,8 @@ st.set_page_config(
 )
 # Predefined Knowledge Trees
-BiologyAndLevel36MagicUsers = """
 0. Biology Core Rules and Future Exceptions
 1. Central Dogma DNA RNA Protein
 - Current CRISPR RNA editing 🧪
@@ -26,42 +30,32 @@ BiologyAndLevel36MagicUsers = """
 - Current iPSCs organoids 🦠
 - Research Synthetic cells 🔬
 - Future De novo cell creation 🚀
-"""
-AITopicsToInnovate1 = """
 1. Major AI Industry Players 🌐
    1. Research Leaders 🎯
       - OpenAI: GPT-4 DALL-E Foundation Models 🔵
       - Google: PaLM Gemini LLMs 🟦
       - Anthropic: Claude Constitutional AI ⚡
-"""
-MultiplayerGames = """
 0. Fantasy Domain Introduction
 1. Setting the Scene
 - Current Create a high-fantasy realm 🏞️
 - Research Add domain-specific entities 🧝‍♂️
 - Future AI-generated worldbuilding 🚀
-"""
-# Root Node with URLs
-RootNode = """
-0. Research Hub 🌐
-1. Awacke1 Profile
-- Link: [Hugging Face Profile](https://huggingface.co/awacke1) 📚
-2. TeachingCV App
-- Link: [TeachingCV](https://huggingface.co/spaces/awacke1/TeachingCV) 🖥️
-3. DeepResearchEvaluator App
-- Link: [DeepResearchEvaluator](https://huggingface.co/spaces/awacke1/DeepResearchEvaluator) 🔍
-"""
 # Utility Functions
 def sanitize_filename(text):
     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):
     central = pytz.timezone('US/Central')
     current_time = datetime.now(central)
     time_str = current_time.strftime("%I%M%p")
@@ -70,9 +64,11 @@ def generate_timestamp_filename(query):
     return f"{time_str} {date_str} ({safe_query}).md"
 def parse_outline_to_mermaid(outline_text):
     lines = outline_text.strip().split('\n')
     nodes = []
     edges = []
     stack = []
     for line in lines:
         indent = len(line) - len(line.lstrip())
@@ -82,6 +78,7 @@ def parse_outline_to_mermaid(outline_text):
         if label:
             node_id = f"N{len(nodes)}"
             nodes.append(f'{node_id}["{label}"]')
             if stack:
                 parent_level = stack[-1][0]
                 if level > parent_level:
@@ -97,9 +94,38 @@ def parse_outline_to_mermaid(outline_text):
                     stack.append((level, node_id))
             else:
                 stack.append((level, node_id))
-    return "graph TD\n" + "\n".join(nodes + edges)
 def grow_tree(base_tree, new_node_name, parent_node):
     lines = base_tree.strip().split('\n')
     new_lines = []
     added = False
@@ -111,89 +137,76 @@ def grow_tree(base_tree, new_node_name, parent_node):
             added = True
     return "\n".join(new_lines)
-def breed_trees(tree1, tree2, intersect_node):
-    lines1 = tree1.strip().split('\n')
-    lines2 = tree2.strip().split('\n')
-    new_lines = lines1.copy()
-    for line in lines2:
-        if intersect_node not in line and not any(line.strip() in l for l in lines1):
-            new_lines.append(line)
-    return "\n".join(new_lines)
-# Model Building Process
-def generate_model_pipeline():
-    return """
-    graph TD
-    A[Load Data 📊] --> B[Preprocess Data 🛠️]
-    B --> C[Train Model 🤖]
-    C --> D[Evaluate Model 📈]
-    D --> E[Deploy Model 🚀]
-    """
 # AI Lookup
 @st.cache_resource
 def load_generator():
     return pipeline("text-generation", model="distilgpt2")
-# Sidebar: File Management
-if 'selected_file' not in st.session_state:
-    st.session_state.selected_file = None
-st.sidebar.title("📁 Saved Interactions")
-md_files = glob.glob("*.md")
-for file in md_files:
-    if st.sidebar.button(file):
-        st.session_state.selected_file = file
-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}")
-    st.session_state.selected_file = filename
-# Main App
 st.title("🌳 AI Knowledge Tree Builder 🌱")
-st.markdown("Grow and visualize knowledge trees, build ML pipelines, and explore research!")
-if st.session_state.selected_file:
-    with open(st.session_state.selected_file, 'r') as f:
-        content = f.read()
-    st.markdown(content)
 else:
-    # Knowledge Tree Selection and Growth
-    trees = {
-        "Research Hub": RootNode,
-        "Biology": BiologyAndLevel36MagicUsers,
-        "AI Topics": AITopicsToInnovate1,
-        "Multiplayer Games": MultiplayerGames
-    }
-    selected_tree = st.selectbox("Select Knowledge Tree", list(trees.keys()))
-    current_tree = trees[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., 'Research Leaders')")
     if st.button("Grow Tree 🌱") and new_node and parent_node:
-        current_tree = grow_tree(current_tree, new_node, parent_node)
-        trees[selected_tree] = current_tree
         st.success(f"Added '{new_node}' under '{parent_node}'!")
-    # Tree Breeding
-    breed_with = st.selectbox("Breed With Another Tree", [t for t in trees.keys() if t != selected_tree])
-    intersect_node = st.text_input("Common Node for Breeding (e.g., 'Research')")
-    if st.button("Breed Trees 🌳"):
-        new_tree = breed_trees(current_tree, trees[breed_with], intersect_node)
-        trees[f"{selected_tree} + {breed_with}"] = new_tree
-        st.success(f"Created new tree: {selected_tree} + {breed_with}")
-    # Display Tree
-    mermaid_code = parse_outline_to_mermaid(current_tree)
     st.markdown("### Knowledge Tree Visualization")
-    st.mermaid(mermaid_code)
-    # Model Building Pipeline
-    st.markdown("### ML Model Building Pipeline")
-    st.mermaid(generate_model_pipeline())
     # AI Lookup
     query = st.text_input("Enter Query for AI Lookup")
@@ -206,5 +219,13 @@ else:
             f.write(f"# Query: {query}\n\n## AI Response\n{response}")
         st.success(f"Saved to {filename}")
 if __name__ == "__main__":
-    st.sidebar.markdown("Explore, grow, and innovate!")

+#!/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 📈🌿",
     page_icon="🌳✨",
 )
 # Predefined Knowledge Trees
+trees = {
+    "Biology": """
 0. Biology Core Rules and Future Exceptions
 1. Central Dogma DNA RNA Protein
 - Current CRISPR RNA editing 🧪
 - Current iPSCs organoids 🦠
 - Research Synthetic cells 🔬
 - Future De novo cell creation 🚀
+    """,
+    "AI Topics": """
 1. Major AI Industry Players 🌐
    1. Research Leaders 🎯
       - OpenAI: GPT-4 DALL-E Foundation Models 🔵
       - Google: PaLM Gemini LLMs 🟦
       - Anthropic: Claude Constitutional AI ⚡
+    """,
+    "Multiplayer Games": """
 0. Fantasy Domain Introduction
 1. Setting the Scene
 - Current Create a high-fantasy realm 🏞️
 - Research Add domain-specific entities 🧝‍♂️
 - Future AI-generated worldbuilding 🚀
+    """
+}
 # 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")
     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())
         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:
                     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
             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("📁 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("📂", 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("🗑", 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("🌳 AI Knowledge Tree Builder 🌱")
+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 🌱") 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")
             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!")