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from sentence_transformers import SentenceTransformer | |
import faiss | |
import os | |
import pickle | |
model = SentenceTransformer('all-MiniLM-L6-v2') | |
def load_documents(): | |
docs = [] | |
for filename in ["milindgatha.txt", "bhaktas.txt", "apologetics.txt", "poc_questions.txt", "satire_offerings.txt"]: | |
if os.path.exists(filename): | |
with open(filename, "r", encoding="utf-8") as f: | |
text = f.read() | |
chunks = text.split("\n\n") | |
for chunk in chunks: | |
docs.append(chunk.strip()) | |
return docs | |
texts = load_documents() | |
embeddings = model.encode(texts, convert_to_numpy=True) | |
dimension = embeddings.shape[1] | |
index = faiss.IndexFlatIP(dimension) | |
index.add(embeddings) | |
# Save FAISS index | |
faiss.write_index(index, "baba.index") | |
# Save texts list for retrieval | |
with open("texts.pkl", "wb") as f: | |
pickle.dump(texts, f) | |
print("Index and texts saved.") | |