# 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 "Exemple : Chatbot PDF 📚"

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

#: ../../source/examples/pdf_chatbot.rst:9
msgid ""
"This example showcases how to build a PDF chatbot with local LLM and "
"Embedding models"
msgstr ""
"Cet exemple montre comment construire un chatbot PDF en utilisant un LLM "
"local et un modèle d'embedding."

#: ../../source/examples/pdf_chatbot.rst:11
msgid "**Used Technology**:"
msgstr "**Technologies concernées** :"

#: ../../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>`_ en tant que service"
" d'hébergement de modèles LLM"

#: ../../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>`_ est utilisé pour "
"orchestrer l'ensemble du pipeline RAG."

#: ../../source/examples/pdf_chatbot.rst:17
msgid "@ `Streamlit <https://streamlit.io/>`_ for interactive UI"
msgstr ""
"@ `Streamlit <https://streamlit.io/>`_ pour l'interface utilisateur "
"interactive"

#: ../../source/examples/pdf_chatbot.rst:19
msgid "**Detailed Explanation on the Demo Functionality** :"
msgstr "**Description détaillée des fonctions de démonstration** :"

#: ../../source/examples/pdf_chatbot.rst:21
msgid ""
"Crafted a Dockerfile to simplify the process and ensure easy "
"reproducibility."
msgstr ""
"J'ai créé un Dockerfile qui simplifie le processus de déploiement via Docker"
" et garantit une reproductibilité facile."

#: ../../source/examples/pdf_chatbot.rst:23
msgid "Set up models with Xinference and expose two ports for accessing them."
msgstr ""
"Utilisez Xinference pour lancer les modèles LLM et d’embedding, et exposez "
"deux ports pour y accéder."

#: ../../source/examples/pdf_chatbot.rst:25
msgid ""
"Leverage Streamlit for seamless file uploads and interactive communication "
"with the chat engine."
msgstr ""
"Implémentez un téléchargement de fichiers fluide et une communication "
"interactive avec le moteur de chat en utilisant Streamlit."

#: ../../source/examples/pdf_chatbot.rst:27
msgid "5x faster doc embedding than OpenAI's API."
msgstr ""
"La vitesse d'embedding des documents est 5 fois plus rapide que celle de "
"l'API d'OpenAI."

#: ../../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 ""
"Utilisez la puissance de GGML pour exécuter le modèle sur GPU, garantissant "
"une accélération et réduisant le temps d'attente pour les retours."

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

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