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import solara | |
import numpy as np | |
import pandas as pd | |
from sentence_transformers import SentenceTransformer | |
from huggingface_hub import snapshot_download | |
from umap import UMAP | |
from annoy import AnnoyIndex | |
from cluestar import plot_text | |
news = pd.read_csv('https://raw.githubusercontent.com/alonsosilvaallende/fake-and-real-news-titles/main/example.csv') | |
texts = list(news["title"].values) | |
texts = [str(text) for text in texts if str(text) != 'nan'] | |
sentences = ["This is an example sentence", "Each sentence is converted"] | |
model_path = snapshot_download( | |
repo_id="TaylorAI/gte-tiny", allow_patterns=["*.json", "pytorch_model.bin"] | |
) | |
embedder2 = SentenceTransformer(model_path) | |
embeddings2 = [embedder2.encode(str(texts[i])) for i in range(500)] | |
reducer = UMAP() | |
X2 = reducer.fit_transform(embeddings2) | |
f = len(embeddings2[0]) | |
t = AnnoyIndex(f, 'angular') | |
for i, embedded_text in enumerate(embeddings2): | |
t.add_item(i, embedded_text) | |
t.build(1000) | |
query = solara.reactive("What did Nancy Pelosi said about Obamacare?") | |
def Page(): | |
with solara.Column(margin=10): | |
solara.Markdown("#Embeddings") | |
solara.InputText("Enter some query:", query, continuous_update=True) | |
if query.value != "": | |
embedded_query = embedder2.encode(query.value) | |
idx, distances = t.get_nns_by_vector(embedded_query, 10, include_distances=True) | |
df_neighbors = pd.DataFrame() | |
df_neighbors["neighbors"]=[texts[i] for i in idx] | |
df_neighbors["distances"] = distances | |
x = reducer.transform([embedded_query]) | |
color_array = ["texts" if i not in idx else "neighbors" for i in range(len(texts[:500]))]+["query"] | |
solara.AltairChart(plot_text(np.vstack((X2,x)), texts[:500]+[query.value], color_array=color_array).configure_range( | |
category=['#0000ff', '#ff0000', '#a0aab4'] | |
)) | |
solara.DataFrame(df_neighbors, items_per_page=10) | |
solara.Markdown("Dataset: 'Fake and real news' from [kaggle](https://www.kaggle.com/datasets/clmentbisaillon/fake-and-real-news-dataset)") | |
else: | |
color_array = ["texts" for _ in range(500)] | |
solara.AltairChart(plot_text(X2, texts[:500], color_array=color_array)) | |