Multilingual Sentiment Analysis API
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AI/ML2024

Multilingual Sentiment Analysis API

Real-time NLP inference across 12 languages

Project Overview

A high-performance NLP API built on fine-tuned multilingual transformer models (mBERT, XLM-RoBERTa). The service handles sentiment analysis, topic classification, named entity recognition, and keyword extraction as modular endpoints.

Deployed with FastAPI for async performance, containerized with Docker, and hosted with auto-scaling on cloud infrastructure. Average response time under 100ms with batch processing support.

12
Languages
<100ms
Latency
93%
Accuracy
500+
RPS

Gallery

Multilingual Sentiment Analysis API screenshot 1
Multilingual Sentiment Analysis API screenshot 2

Key Features

  1. Fine-tuned XLM-RoBERTa for 12 languages
  2. Async batch processing up to 500 req/s
  3. Redis caching for repeated queries
  4. OpenAPI / Swagger documentation
  5. Rate limiting & API key management

Technology Stack

PythonFastAPIHugging FacePyTorchDockerRedisPostgreSQL

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