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"""
streamlit run app.py --server.address 0.0.0.0
"""
from __future__ import annotations
import os
from time import time
import faiss
import pandas as pd
import streamlit as st
from open_clip import create_model_and_transforms
from openai import OpenAI
from qdrant_client import QdrantClient
from qdrant_client.http import models
if os.getenv("SPACE_ID"):
USE_HF_SPACE = True
os.environ["HF_HOME"] = "/data/.huggingface"
os.environ["HF_DATASETS_CACHE"] = "/data/.huggingface"
else:
USE_HF_SPACE = False
# for tokenizer
os.environ["TOKENIZERS_PARALLELISM"] = "false"
OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
QDRANT_API_ENDPOINT = os.environ.get("QDRANT_API_ENDPOINT")
QDRANT_API_KEY = os.environ.get("QDRANT_API_KEY")
if not QDRANT_API_ENDPOINT or not QDRANT_API_KEY:
raise ValueError("env: QDRANT_API_ENDPOINT or QDRANT_API_KEY is not set.")
@st.cache_resource
def get_model_preprocess():
model, _, preprocess = create_model_and_transforms(
"xlm-roberta-base-ViT-B-32", pretrained="laion5B-s13B-b90k"
)
return model, preprocess
@st.cache_resource
def get_qdrant_client():
qdrant_client = QdrantClient(
url=QDRANT_API_ENDPOINT,
api_key=QDRANT_API_KEY,
)
return qdrant_client
def app():
st.title("secon.dev site search")
if __name__ == "__main__":
app()
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