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Create app.py
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app.py
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import gradio as gr
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import os
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from langchain_community.document_loaders import PyPDFLoader
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from langchain.text_splitter import RecursiveCharacterTextSplitter
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from langchain_community.vectorstores import Chroma
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from langchain.chains import ConversationalRetrievalChain
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from langchain_community.embeddings import HuggingFaceEmbeddings
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from langchain_community.llms import HuggingFacePipeline
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from langchain.chains import ConversationChain
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from langchain.memory import ConversationBufferMemory
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from langchain_community.llms import HuggingFaceEndpoint
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from pathlib import Path
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import chromadb
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from unidecode import unidecode
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from transformers import AutoTokenizer
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import transformers
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import torch
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import tqdm
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import accelerate
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import re
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# default_persist_directory = './chroma_HF/'
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list_llm = ["mistralai/Mistral-7B-Instruct-v0.2", "mistralai/Mixtral-8x7B-Instruct-v0.1", "mistralai/Mistral-7B-Instruct-v0.1", \
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"google/gemma-7b-it","google/gemma-2b-it", \
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"HuggingFaceH4/zephyr-7b-beta", "HuggingFaceH4/zephyr-7b-gemma-v0.1", \
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"meta-llama/Llama-2-7b-chat-hf", "microsoft/phi-2", \
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"TinyLlama/TinyLlama-1.1B-Chat-v1.0", "mosaicml/mpt-7b-instruct", "tiiuae/falcon-7b-instruct", \
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"google/flan-t5-xxl"
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]
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list_llm_simple = [os.path.basename(llm) for llm in list_llm]
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demo()
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