app.py

# app.py
import gradio as gr
from sentence_transformers import SentenceTransformer
import os

MODEL_NAME = "jackenmail/rag-embedder"   # 👈 Your trained model

print(f"Loading model: {MODEL_NAME}")
model = SentenceTransformer(MODEL_NAME)
print("Model ready!")

def embed(text: str):
    if not text.strip():
        return []
    return model.encode(text).tolist()

demo = gr.Interface(
    fn          = embed,
    inputs      = gr.Textbox(label="Input Text"),
    outputs     = gr.JSON(label="Embedding Vector"),
    title       = "RAG Embedder API",
    description = f"Powered by {MODEL_NAME}"
)

demo.launch()