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| import plotly.express as px | |
| import streamlit as st | |
| from sentence_transformers import SentenceTransformer | |
| import umap.umap_ as umap | |
| import pandas as pd | |
| import os | |
| def app(): | |
| st.title("SDG Embedding Visualisation") | |
| with st.spinner("👑 load language model (sentence transformer)"): | |
| model_name = 'sentence-transformers/all-MiniLM-L6-v2' | |
| model = SentenceTransformer(model_name) | |
| with st.spinner("👑 load and embed SDG texts"): | |
| df_osdg = pd.read_csv('https://zenodo.org/record/5550238/files/osdg-community-dataset-v21-09-30.csv',sep='\t') | |
| df_osdg = df_osdg[df_osdg['agreement']>.95] | |
| df_osdg = df_osdg[df_osdg['labels_positive']>4] | |
| #df_osdg = df_osdg[:1000] | |
| _lab_dict = {0: 'no_cat', | |
| 1:'SDG 1 - No poverty', | |
| 2:'SDG 2 - Zero hunger', | |
| 3:'SDG 3 - Good health and well-being', | |
| 4:'SDG 4 - Quality education', | |
| 5:'SDG 5 - Gender equality', | |
| 6:'SDG 6 - Clean water and sanitation', | |
| 7:'SDG 7 - Affordable and clean energy', | |
| 8:'SDG 8 - Decent work and economic growth', | |
| 9:'SDG 9 - Industry, Innovation and Infrastructure', | |
| 10:'SDG 10 - Reduced inequality', | |
| 11:'SDG 11 - Sustainable cities and communities', | |
| 12:'SDG 12 - Responsible consumption and production', | |
| 13:'SDG 13 - Climate action', | |
| 14:'SDG 14 - Life below water', | |
| 15:'SDG 15 - Life on land', | |
| 16:'SDG 16 - Peace, justice and strong institutions', | |
| 17:'SDG 17 - Partnership for the goals',} | |
| labels = [_lab_dict[lab] for lab in df_osdg['sdg'] ] | |
| #keys = list(df_osdg['keys']) | |
| docs = list(df_osdg['text']) | |
| docs_embeddings = model.encode(docs) | |
| with st.spinner("👑 map to 3D for visualisation"): | |
| n_neighbors = 15 | |
| n_components = 3 | |
| random_state =42 | |
| umap_model = (umap.UMAP(n_neighbors=n_neighbors, | |
| n_components=n_components, | |
| metric='cosine', | |
| random_state=random_state) | |
| .fit(docs_embeddings)) | |
| docs_umap = umap_model.transform(docs_embeddings) | |
| with st.spinner("👑 create visualisation"): | |
| fig = px.scatter_3d( | |
| docs_umap, x=0, y=1, z=2, | |
| color=labels, | |
| opacity = .5)#, hover_data=[keys]) | |
| fig.update_scenes(xaxis_visible=False, yaxis_visible=False,zaxis_visible=False ) | |
| fig.update_traces(marker_size=4) | |
| st.plotly_chart(fig) |