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from __future__ import annotations
import json
import shutil
import subprocess
import tempfile
from datetime import datetime, timedelta
from functools import lru_cache
from pathlib import Path
from huggingface_hub import hf_hub_download
import gradio as gr
from modular_graph_and_candidates import build_graph_json, generate_html, build_timeline_json, generate_timeline_html
def _escape_srcdoc(text: str) -> str:
"""Escape for inclusion inside an <iframe srcdoc="β¦"> attribute."""
return (
text.replace("&", "&")
.replace("\"", """)
.replace("'", "'")
.replace("<", "<")
.replace(">", ">")
)
HF_MAIN_REPO = "https://github.com/huggingface/transformers"
CACHE_REPO = "Molbap/hf_cached_embeds_log"
def _fetch_from_cache_repo(kind: str, sim_method: str, threshold: float, multimodal: bool):
repo_id = CACHE_REPO
latest_fp = hf_hub_download(repo_id=repo_id, filename="latest.json", repo_type="dataset")
info = json.loads(Path(latest_fp).read_text(encoding="utf-8"))
sha = info.get("sha")
key = f"{sha}/{sim_method}-{threshold:.2f}-m{int(multimodal)}"
html_fp = hf_hub_download(repo_id=repo_id, filename=f"{kind}/{key}.html", repo_type="dataset")
json_fp = hf_hub_download(repo_id=repo_id, filename=f"{kind}/{key}.json", repo_type="dataset")
raw_html = Path(html_fp).read_text(encoding="utf-8")
json_text = Path(json_fp).read_text(encoding="utf-8")
iframe_html = f'<iframe style="width:100%;height:85vh;border:none;" srcdoc="{_escape_srcdoc(raw_html)}"></iframe>'
tmp = Path(tempfile.mkstemp(suffix=("_timeline.json" if kind == "timeline" else ".json"))[1])
tmp.write_text(json_text, encoding="utf-8")
return iframe_html, str(tmp)
def run_graph(repo_url: str, threshold: float, multimodal: bool, sim_method: str):
return _fetch_from_cache_repo("graph", sim_method, threshold, multimodal)
def run_timeline(repo_url: str, threshold: float, multimodal: bool, sim_method: str):
return _fetch_from_cache_repo("timeline", sim_method, threshold, multimodal)
# βββββββββββββββββββββββββββββ UI ββββββββββββββββββββββββββββββββββββββββββββββββ
CUSTOM_CSS = """
#graph_html iframe, #timeline_html iframe {height:85vh !important; width:100% !important; border:none;}
"""
with gr.Blocks(css=CUSTOM_CSS) as demo:
gr.Markdown("## π Modularβcandidate explorer for π€ Transformers")
with gr.Tabs():
with gr.Tab("Dependency Graph"):
with gr.Row():
repo_in = gr.Text(value=HF_MAIN_REPO, label="Repo / fork URL")
thresh = gr.Slider(0.50, 0.95, value=0.5, step=0.01, label="Similarity β₯")
multi_cb = gr.Checkbox(label="Only multimodal models")
sim_radio = gr.Radio(["jaccard", "embedding"], value="jaccard", label="Similarity metric")
go_btn = gr.Button("Build graph")
graph_html_out = gr.HTML(elem_id="graph_html", show_label=False)
graph_json_out = gr.File(label="Download graph.json")
go_btn.click(run_graph, [repo_in, thresh, multi_cb, sim_radio], [graph_html_out, graph_json_out])
with gr.Tab("Chronological Timeline"):
with gr.Row():
timeline_repo_in = gr.Text(value=HF_MAIN_REPO, label="Repo / fork URL")
timeline_thresh = gr.Slider(0.50, 0.95, value=0.5, step=0.01, label="Similarity β₯")
timeline_multi_cb = gr.Checkbox(label="Only multimodal models")
timeline_sim_radio = gr.Radio(["jaccard", "embedding"], value="jaccard", label="Similarity metric")
timeline_btn = gr.Button("Build timeline")
timeline_html_out = gr.HTML(elem_id="timeline_html", show_label=False)
timeline_json_out = gr.File(label="Download timeline.json")
timeline_btn.click(run_timeline, [timeline_repo_in, timeline_thresh, timeline_multi_cb, timeline_sim_radio], [timeline_html_out, timeline_json_out])
if __name__ == "__main__":
demo.launch(allowed_paths=["static"]) |