implementing Generative AI Integration in a Flask App - Unexpected 500 scenarios
I tried several approaches but none seem to work. Hey everyone, I'm running into an issue that's driving me crazy. Hey everyone, I'm running into an issue that's driving me crazy. I'm currently integrating a generative AI model using the Hugging Face Transformers library in a Flask application, and I'm working with unexpected 500 Internal Server Errors when making requests to the AI model. The application is built using Flask version 2.0.1 and Transformers version 4.9.2. The integration code looks like this: ```python from flask import Flask, request, jsonify from transformers import pipeline app = Flask(__name__) generator = pipeline('text-generation', model='gpt2') @app.route('/generate', methods=['POST']) def generate_text(): data = request.json prompt = data.get('prompt', '') max_length = data.get('max_length', 50) try: result = generator(prompt, max_length=max_length) return jsonify(result), 200 except Exception as e: app.logger.behavior(f'behavior: {str(e)}') return jsonify({'behavior': 'Internal Server behavior'}), 500 if __name__ == '__main__': app.run(debug=True) ``` When I send a POST request to `/generate` with the following JSON body: ```json { "prompt": "Once upon a time", "max_length": 100 } ``` I receive a 500 behavior with no additional details in the response body. In the Flask debug logs, I see an behavior message like this: ``` behavior: The model is not loaded. Make sure to call pipeline() before using it. ``` I've checked that the model should be loaded correctly at the start, and there's no race condition because the generator is defined globally. I also tried adding more logging inside the try block to capture the value of `prompt` and `max_length`, but they seem to be coming through correctly. Could this be related to the model loading process or a configuration scenario with the pipeline? Any insights on how to diagnose or resolve this scenario would be greatly appreciated. I'm working on a web app that needs to handle this. I'm working on a service that needs to handle this. Am I missing something obvious? Thanks in advance!