# 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"
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"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"
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#: ../../source/examples/pdf_chatbot.rst:5
msgid "Example: PDF Chatbot📚"
msgstr "示例：PDF 聊天機器人📚"

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

#: ../../source/examples/pdf_chatbot.rst:9
msgid ""
"This example showcases how to build a PDF chatbot with local LLM and "
"Embedding models"
msgstr "這個範例展示了如何使用本地 LLM 和 embedding 模型建置 PDF 聊天機器人。"

#: ../../source/examples/pdf_chatbot.rst:11
msgid "**Used Technology**:"
msgstr "涉及技術"

#: ../../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>`_ 作為 LLM 模型託管服務"

#: ../../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>`_ 用於編排整個RAG管道"

#: ../../source/examples/pdf_chatbot.rst:17
msgid "@ `Streamlit <https://streamlit.io/>`_ for interactive UI"
msgstr "@ `Streamlit <https://streamlit.io/>`_ 用於交互式使用者介面"

#: ../../source/examples/pdf_chatbot.rst:19
msgid "**Detailed Explanation on the Demo Functionality** :"
msgstr "**關於演示功能的詳細說明**："

#: ../../source/examples/pdf_chatbot.rst:21
msgid ""
"Crafted a Dockerfile to simplify the process and ensure easy "
"reproducibility."
msgstr "製作了一個 Dockerfile，透過 Docker 簡化了部署流程並確保易於複現。"

#: ../../source/examples/pdf_chatbot.rst:23
msgid "Set up models with Xinference and expose two ports for accessing them."
msgstr "使用 Xinference 拉起 LLM 和 embedding 模型，並暴露兩個端口以存取它們。"

#: ../../source/examples/pdf_chatbot.rst:25
msgid ""
"Leverage Streamlit for seamless file uploads and interactive communication "
"with the chat engine."
msgstr "利用 Streamlit 實現無縫檔案上傳和與聊天引擎的互動通訊。"

#: ../../source/examples/pdf_chatbot.rst:27
msgid "5x faster doc embedding than OpenAI's API."
msgstr "文件嵌入速度比 OpenAI 的 API 快 5 倍。"

#: ../../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 "利用 GGML 的強大功能將模型置於 GPU 上運行，確保加速、減少等待返回的時間。"

#: ../../source/examples/pdf_chatbot.rst:31
msgid "**Source Code** :"
msgstr "**原始碼**"

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