from flask import Flask, request, jsonify from huggingface_hub import HfApi import streamlit app = Flask(__name__) api = HfApi() @app.route('/search_datasets', methods=['GET']) def search_datasets(): query = request.args.get('query') datasets = api.list_datasets(search=query, full=True) return jsonify(datasets) @app.route('/run_inference', methods=['POST']) def run_inference(): model_id = request.json['model_id'] inputs = request.json['inputs'] # Assuming the model is compatible with the pipeline API from transformers import pipeline model_pipeline = pipeline(task="text-generation", model=model_id) results = model_pipeline(inputs) return jsonify(results) if __name__ == '__main__': app.run(debug=False)