# SOME DESCRIPTIVE TITLE.
# Copyright (C) 2023, Xorbits Inc.
# This file is distributed under the same license as the Xinference package.
# FIRST AUTHOR <EMAIL@ADDRESS>, 2023.
#
#, fuzzy
msgid ""
msgstr ""
"Project-Id-Version: Xinference\n"
"Report-Msgid-Bugs-To: \n"
"POT-Creation-Date: 2023-11-01 10:48+0800\n"
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
"Language-Team: ko <LL@li.org>\n"
"Language: ko\n"
"MIME-Version: 1.0\n"
"Content-Type: text/plain; charset=utf-8\n"
"Content-Transfer-Encoding: 8bit\n"
"Plural-Forms: nplurals=1; plural=0;\n"
"Generated-By: Babel 2.18.0\n"

#: ../../source/examples/pdf_chatbot.rst:5
msgid "Example: PDF Chatbot📚"
msgstr "예시: PDF 채팅봇 📚"

#: ../../source/examples/pdf_chatbot.rst:7
msgid "**Description**:"
msgstr "**설명**:"

#: ../../source/examples/pdf_chatbot.rst:9
msgid ""
"This example showcases how to build a PDF chatbot with local LLM and "
"Embedding models"
msgstr "이 예제는 로컬 LLM과 임베딩 모델을 사용하여 PDF 챗봇을 구축하는 방법을 보여줍니다."

#: ../../source/examples/pdf_chatbot.rst:11
msgid "**Used Technology**:"
msgstr "**관련 기술**:"

#: ../../source/examples/pdf_chatbot.rst:13
msgid ""
"@ `Xinference <https://github.com/xorbitsai/inference>`_ as a LLM model "
"hosting service"
msgstr ""
"@ `Xinference <https://github.com/xorbitsai/inference>`_ 를 LLM 모델 호스팅 서비스로 "
"사용"

#: ../../source/examples/pdf_chatbot.rst:15
msgid ""
"@ `LlamaIndex <https://github.com/run-llama/llama_index>`_ for orchestrating"
" the entire RAG pipeline"
msgstr ""
"@ `LlamaIndex <https://github.com/run-llama/llama_index>`_ 는 전체 RAG 파이프라인을 "
"오케스트레이션하는 데 사용됩니다."

#: ../../source/examples/pdf_chatbot.rst:17
msgid "@ `Streamlit <https://streamlit.io/>`_ for interactive UI"
msgstr "@ `Streamlit <https://streamlit.io/>`_ 는 대화형 사용자 인터페이스에 사용됩니다."

#: ../../source/examples/pdf_chatbot.rst:19
msgid "**Detailed Explanation on the Demo Functionality** :"
msgstr "**데모 기능에 대한 상세 설명**:"

#: ../../source/examples/pdf_chatbot.rst:21
msgid ""
"Crafted a Dockerfile to simplify the process and ensure easy "
"reproducibility."
msgstr "Dockerfile을 작성하여 Docker를 통해 배포 프로세스를 간소화하고 쉽게 재현할 수 있도록 했습니다."

#: ../../source/examples/pdf_chatbot.rst:23
msgid "Set up models with Xinference and expose two ports for accessing them."
msgstr "Xinference를 사용하여 LLM과 임베딩 모델을 띄우고, 이에 접근할 수 있도록 두 개의 포트를 노출합니다."

#: ../../source/examples/pdf_chatbot.rst:25
msgid ""
"Leverage Streamlit for seamless file uploads and interactive communication "
"with the chat engine."
msgstr "Streamlit을 사용하여 원활한 파일 업로드와 채팅 엔진과의 상호작용 통신을 구현합니다."

#: ../../source/examples/pdf_chatbot.rst:27
msgid "5x faster doc embedding than OpenAI's API."
msgstr "OpenAI의 API보다 문서 임베딩 속도가 5배 빠릅니다."

#: ../../source/examples/pdf_chatbot.rst:29
msgid ""
"Leveraging the power of GGML to offload models to the GPU, ensuring swift "
"acceleration. Less long waits for returns."
msgstr "GGML의 강력한 기능을 활용하여 모델을 GPU에서 실행함으로써 가속화하고 응답 대기 시간을 줄입니다."

#: ../../source/examples/pdf_chatbot.rst:31
msgid "**Source Code** :"
msgstr "**소스 코드**"

#: ../../source/examples/pdf_chatbot.rst:32
msgid ""
"`PDF Chatbot <https://github.com/onesuper/PDF-Chatbot-Local-LLM-"
"Embeddings>`_"
msgstr ""
