Embeddings + FAISS Integration

from synapsai import SynapsAI
import numpy as np
import faiss

client = SynapsAI()

texts = ["Alpha example", "Beta features", "Gamma release notes"]
embeddings = [client.embeddings.create(model="<YOUR_EMBEDDING_MODEL_ID>", input=t).data[0].embedding for t in texts]

d = len(embeddings[0])
index = faiss.IndexFlatL2(d)
index.add(np.array(embeddings).astype("float32"))

q_emb = client.embeddings.create(model="<YOUR_EMBEDDING_MODEL_ID>", input="Tell me about release features").data[0].embedding
D, I = index.search(np.array([q_emb]).astype("float32"), k=2)
print("Top indices:", I[0], "distances:", D[0])