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Create app.py
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app.py
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import gradio as gr
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from huggingface_hub import ModelCard, HfApi
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import requests
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import networkx as nx
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import matplotlib.pyplot as plt
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from collections import defaultdict
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from networkx.drawing.nx_pydot import graphviz_layout
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from io import BytesIO
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def get_model_names_from_yaml(url):
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"""Get a list of parent model names from the yaml file."""
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model_tags = []
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response = requests.get(url)
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if response.status_code == 200:
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model_tags.extend([item for item in response.content if '/' in str(item)])
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return model_tags
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def get_license_color(model):
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"""Get the color of the model based on its license."""
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try:
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card = ModelCard.load(model)
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license = card.data.to_dict()['license'].lower()
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# Define permissive licenses
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permissive_licenses = ['mit', 'bsd', 'apache-2.0', 'openrail'] # Add more as needed
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# Check license type
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if any(perm_license in license for perm_license in permissive_licenses):
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return 'lightgreen' # Permissive licenses
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else:
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return 'lightcoral' # Noncommercial or other licenses
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except Exception as e:
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print(f"Error retrieving license for {model}: {e}")
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return 'lightgray'
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def get_model_names(model, genealogy, found_models=None):
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"""Get a list of parent model names from the model id."""
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model_tags = []
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if found_models is None:
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found_models = []
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try:
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card = ModelCard.load(model)
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card_dict = card.data.to_dict() # Convert the ModelCard object to a dictionary
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license = card_dict['license']
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# Check the base_model in metadata
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if 'base_model' in card_dict:
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model_tags = card_dict['base_model']
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# Check the tags in metadata
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if 'tags' in card_dict and not model_tags:
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tags = card_dict['tags']
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model_tags = [model_name for model_name in tags if '/' in model_name]
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# Check for merge.yml and mergekit_config.yml if no model_tags found in the tags
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if not model_tags:
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model_tags.extend(get_model_names_from_yaml(f"https://huggingface.co/{model}/blob/main/merge.yml"))
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if not model_tags:
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model_tags.extend(get_model_names_from_yaml(f"https://huggingface.co/{model}/blob/main/mergekit_config.yml"))
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# Convert to a list if tags is not None or empty, else set to an empty list
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if not isinstance(model_tags, list):
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model_tags = [model_tags] if model_tags else []
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# Add found model names to the list
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found_models.extend(model_tags)
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# Record the genealogy
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for model_tag in model_tags:
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genealogy[model_tag].append(model)
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# Recursively check for more models
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for model_tag in model_tags:
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get_model_names(model_tag, genealogy, found_models)
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except Exception as e:
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print(f"Could not find model names for {model}: {e}")
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return found_models
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def find_root_nodes(G):
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""" Find all nodes in the graph with no predecessors """
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return [n for n, d in G.in_degree() if d == 0]
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def max_width_of_tree(G):
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""" Calculate the maximum width of the tree """
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max_width = 0
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for root in find_root_nodes(G):
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width_at_depth = calculate_width_at_depth(G, root)
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local_max_width = max(width_at_depth.values())
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max_width = max(max_width, local_max_width)
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return max_width
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def calculate_width_at_depth(G, root):
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""" Calculate width at each depth starting from a given root """
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depth_count = defaultdict(int)
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queue = [(root, 0)]
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while queue:
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node, depth = queue.pop(0)
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depth_count[depth] += 1
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for child in G.successors(node):
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queue.append((child, depth + 1))
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return depth_count
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def create_family_tree(start_model):
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genealogy = defaultdict(list)
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get_model_names(start_model, genealogy) # Assuming this populates the genealogy
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# Create a directed graph
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G = nx.DiGraph()
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# Add nodes and edges to the graph
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for parent, children in genealogy.items():
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for child in children:
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G.add_edge(parent, child)
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# Get max depth
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max_depth = nx.dag_longest_path_length(G) + 1
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# Get max width
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max_width = max_width_of_tree(G) + 1
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# Estimate plot size
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height = max(8, 1.6 * max_depth)
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width = max(8, 6 * max_width)
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# Set Graphviz layout attributes for a bottom-up tree
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plt.figure(figsize=(width, height))
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pos = graphviz_layout(G, prog="dot")
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# Determine node colors based on license
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node_colors = [get_license_color(node) for node in G.nodes()]
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clear_output()
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# Create a label mapping with line breaks
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labels = {node: node.replace("/", "\n") for node in G.nodes()}
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# Draw the graph
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nx.draw(G, pos, labels=labels, with_labels=True, node_color=node_colors, font_size=12, node_size=8_000, edge_color='black')
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# Create a legend for the colors
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legend_elements = [
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Patch(facecolor='lightgreen', label='Permissive'),
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Patch(facecolor='lightcoral', label='Noncommercial'),
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Patch(facecolor='lightgray', label='Unknown')
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]
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plt.legend(handles=legend_elements, loc='upper left')
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plt.title(f"{start_model}'s Family Tree", fontsize=20)
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# Instead of plt.show(), capture the plot as an image in memory
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img_buffer = BytesIO()
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plt.savefig(img_buffer, format='png')
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plt.close()
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img_buffer.seek(0) # Rewind the buffer to the beginning
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return img_buffer.getvalue()
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with gr.Blocks() as demo:
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gr.Markdown("# 🌳 Merge Family Tree")
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model_id = gr.Textbox(label="Model ID", value="mlabonne/NeuralBeagle-7B")
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btn = gr.Button("Create tree")
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btn.click(fn=create_family_tree, inputs=model_id, outputs=out)
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out = gr.Image()
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demo.launch()
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