README.md

Epstein Vectorized Database

This repository contains a vectorized derivative of publicly released U.S. House Oversight Committee Epstein estate documents. The database provides efficient semantic search and retrieval-augmented generation (RAG) capabilities via FAISS embeddings and metadata.

Database Contents

• epstein_index.faiss: FAISS vector index (384-dim, normalized embeddings via all-MiniLM-L6-v2, IndexFlatIP for cosine similarity)
• epstein_metadata.parquet: Metadata for each vector (id, filename, text_snippet, chars, words)
• epstein_metadata.jsonl: Same metadata in JSONL format

Total documents indexed: 25,800

Source Attribution

Original source: U.S. House Committee on Oversight and Government Reform public release "Oversight Committee Releases Additional Epstein Estate Documents" (November 12, 2025):
https://oversight.house.gov/release/oversight-committee-releases-additional-epstein-estate-documents/

Original dataset on HuggingFace:
tensonaut/EPSTEIN_FILES_20K

Usage

Load the index and metadata:

import faiss
import pandas as pd

index = faiss.read_index('epstein_index.faiss')
meta = pd.read_parquet('epstein_metadata.parquet')

Semantic search example:

from sentence_transformers import SentenceTransformer
import numpy as np

model = SentenceTransformer('all-MiniLM-L6-v2')
query = "your search query"
q_emb = model.encode([query], convert_to_numpy=True)
q_emb = q_emb / np.linalg.norm(q_emb, axis=1, keepdims=True)

D, I = index.search(q_emb.astype('float32'), k=10)  # top-10 results
results = meta.iloc[I[0]]

Usage Responsibilities

Users are responsible for:

• Using the dataset only for lawful purposes and in accordance with institutional and ethical review requirements
• Treating individuals mentioned in the documents with respect and avoiding sensationalism or misuse of sensitive material
• Clearly distinguishing model-generated content from verified facts, and citing primary sources appropriately
• Complying with applicable copyright law, privacy law, and institutional policies

NOT intended for:

• Fine-tuning language models without explicit legal review
• Harassment, doxing, or targeted attacks
• Attempts to deanonymize or circumvent existing redactions
• Making or amplifying unverified allegations as factual claims

Content Warning

The underlying corpus contains sensitive material related to:

• Sexual abuse and exploitation
• Trafficking and violence
• Unverified allegations, opinions, and speculation

Readers should approach with care and appropriate context.

Legal Disclaimer (Non-Authoritative)

• This is a derivative vectorized index only; the original documents are copyrighted by their respective authors and the U.S. House Committee on Oversight and Government Reform
• This dataset does not grant any license to reproduce or distribute the underlying documents beyond what may be permitted by law (fair use, etc.)
• Users are solely responsible for ensuring compliance with copyright, privacy, and institutional policies
• Seek independent legal counsel if using this corpus in a public-facing product or for model training at scale

Files

• epstein_index.faiss: FAISS IndexFlatIP (384-dim, normalized vectors)
• epstein_metadata.parquet: Parquet metadata table
• epstein_metadata.jsonl: JSONL metadata (one record per line)

License

This vectorized database is provided under the same legal constraints as the original House release. See "Usage Responsibilities" and "Legal Disclaimer" above. No original content is reproduced; only embeddings and metadata snippets are stored.