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RobinElysia / repository
A high-performance Python backend service built with FastAPI, Transformers, and FAISS, designed for seamless remote model inference from Java backend systems. This module provides a scalable RESTful API for machine learning model serving with vector search capabilities.
This project is a high-performance Python backend service built with FastAPI, Transformers, and FAISS, designed to seamlessly integrate remote model inference from Java backend systems. The module provides a scalable RESTful API for efficient model inference services.
zh: README_ZH
The entry point main.py file handles basic configuration by prompting the user for essential settings, such as choosing between remote API invocation or local models.(√)
uv is installed in your environment, then run uv sync..env file and fill in the required parameters:# Remote Configuration
KEY="YOUR_API_KEY"
SECRET="YOUR_API_SECRET"
URL="URL"
# Choose either Remote or Local
# Local Configuration
PATH="PATH" # Model path (specify the folder only)
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