Delete rag_data.py

rag_data.py

@@ -1,41 +0,0 @@
-import numpy as np
-from rank_bm25 import BM25Okapi
-from sentence_transformers import SentenceTransformer
-
-from rag_config import (
-    CHUNKS_PATH,
-    THREADS_PATH,
-    MESSAGES_PATH,
-    EMBEDDINGS_PATH,
-    CHUNK_IDS_PATH,
-    load_json,
-    load_jsonl,
-)
-
-# Load base data
-chunks = load_jsonl(CHUNKS_PATH)
-threads = load_json(THREADS_PATH)
-messages = load_json(MESSAGES_PATH)
-
-# Map chunk_id -> chunk
-chunk_id_to_chunk = {c["chunk_id"]: c for c in chunks}
-
-# BM25 corpus
-corpus_tokens = [c["text"].split() for c in chunks]
-bm25 = BM25Okapi(corpus_tokens)
-
-# Semantic embeddings
-embeddings = np.load(EMBEDDINGS_PATH)  # (N, D)
-
-with CHUNK_IDS_PATH.open("r", encoding="utf-8") as f:
-    chunk_ids = load_json(CHUNK_IDS_PATH)
-
-# Map chunk_id -> index in embeddings
-chunk_index = {cid: i for i, cid in enumerate(chunk_ids)}
-
-# SentenceTransformer model (same as used in build_embeddings)
-SEM_MODEL_NAME = "sentence-transformers/all-MiniLM-L6-v2"
-sem_model = SentenceTransformer(SEM_MODEL_NAME)
-
-# Thread IDs for dropdown
-THREAD_OPTIONS = sorted(list(threads.keys()))