Comprehensive 사용자 정의 솔루션 Tools for Every Need

Get access to 사용자 정의 솔루션 solutions that address multiple requirements. One-stop resources for streamlined workflows.

사용자 정의 솔루션

  • A modular FastAPI backend enabling automated document data extraction and parsing using Google Document AI and OCR.
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    What is DocumentAI-Backend?
    DocumentAI-Backend is a lightweight backend framework that automates extraction of text, form fields, and structured data from documents. It offers REST API endpoints for uploading PDFs or images, processes them via Google Document AI with OCR fallback, and returns parsed results in JSON. Built with Python, FastAPI, and Docker, it enables quick integration into existing systems, scalable deployments, and customization through configurable pipelines and middleware.
  • An AI agent framework orchestrating multiple translation agents to generate, refine, and evaluate machine translations collaboratively.
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    What is AI-Agentic Machine Translation?
    AI-Agentic Machine Translation is an open-source framework designed for research and development in machine translation. It orchestrates three core agents—a generator, an evaluator, and a refiner—to collaboratively produce, assess, and refine translations. Built on PyTorch and transformer models, the system supports supervised pre-training, reinforcement learning optimization, and configurable agent policies. Users can benchmark on standard datasets, track BLEU scores, and extend the pipeline with custom agents or reward functions to explore agentic collaboration in translation tasks.
  • A GitHub repo of modular AI agent recipes using LangChain and Python, showcasing memory, custom tools, and multi-step automation.
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    What is Advanced Agents Cookbooks?
    Advanced Agents Cookbooks is a community-driven GitHub project offering a library of AI agent recipes built on LangChain. It covers memory modules for context retention, custom tool integrations for external data and API calls, function-calling patterns for structured responses, chain-of-thought planning for complex decision-making, and multi-step workflow orchestration. Developers can use these ready-made examples to understand best practices, customize behavior, and accelerate the development of intelligent agents that automate tasks such as scheduling, data retrieval, and customer support.
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