first stuff

app.py

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+import pysbd
+from txtai.embeddings import Embeddings
+import networkx as nx
+from tqdm import tqdm
+from txtai.graph import GraphFactory
+from datasets import load_dataset
+import streamlit as st
+import streamlit.components.v1 as components
+
+
+
+st.set_page_config(page_title="DebateKG")
+st.title("DebateKG - Automatic Policy Debate Case Creation")
+st.caption("github: https://github.com/Hellisotherpeople/DebateKG")
+
+
+
+
+
+dataset = load_dataset("Hellisotherpeople/DebateSum", split = "train")
+seg = pysbd.Segmenter(language="en", clean=False)
+
+
+embeddings = Embeddings({
+  "path": "entence-transformers/all-mpnet-base-v2",
+  "content": True,
+  "functions": [
+    {"name": "graph", "function": "graph.attribute"},
+  ],
+  "expressions": [
+      {"name": "topic", "expression": "graph(indexid, 'topic')"},
+      {"name": "topicrank", "expression": "graph(indexid, 'topicrank')"}
+  ],
+  "graph": {
+      "limit": 100,
+      "minscore": 0.10,
+      "topics": {
+          "terms": 4,
+          "resolution" : 100
+      }
+  }
+})
+
+embeddings.load("DebateSum_SemanticGraph_mpnet_extract.tar.gz")
+graph = embeddings.graph
+
+print(graph.backend.number_of_nodes(), graph.backend.number_of_edges())

requirements.txt

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+git+https://github.com/neuml/txtai#egg=txtai[graph,pipeline,similarity]
+datasets
+ipyplot
+tqdm
+pysbd