bartowski1182

In addition to a significant decrease in hepatic lipid accumulation in the IOE group, which inhibited energy intake by propionate enrichment, hepatic lipids were also significantly reduced in the mice in the IOP group, which was largely enriched with butyrate. Compared with the IOE group, IOP had a stronger regulatory effect on hepatic metabolism and triglyceride metabolism and higher levels of TCA cycle in the host. In addition, butyrate has the ability to promote browning of white adipose tissue (WAT) to brown adipose tissue (BAT).^[@ref39],[@ref40]^ WAT stores energy, whereas BAT uses energy for heating and consequently host energy expenditure increases.^[@ref41],[@ref42]^ However, adipose tissue weight does not change after WAT browning.^[@ref43]^ Therefore, the weight of adipose tissue of mice in the IOP group dominated by butyrate was greater than that of the mice in the IOE group dominated by propionate.

In conclusion ([Figure [7](#fig7){ref-type="fig"}](#fig7){ref-type="fig"}C), the improvement of ob

niklasmtj

name: "CI"

on:
  - pull_request

jobs:
  ci:
    runs-on: ubuntu-latest
    steps:
      - name: "Checkout"

ashhadulislam

import streamlit as st
import requests
base_url = "http://localhost:8283/"
headers = {"accept": "application/json"}


st.title("MemGPT Connected Bot")
# check if memgpt server and agents are available

agent_name="agent_1"

langecrew

[
    {
        "model": "gpt-4",
        "api_key": "PASTE_YOUR_API_KEY_HERE"
    },
    {
        "model": "gpt-4-1106-preview",
        "api_key": "PASTE_YOUR_API_KEY_HERE"
    },
    {

langecrew

[
    {
        "model": "gpt-4",
        "api_key": "PASTE_YOUR_API_KEY_HERE"
    },
    {
        "model": "gpt-4-1106-preview",
        "api_key": "PASTE_YOUR_API_KEY_HERE"
    },
    {

mberman84

import os
import autogen
import memgpt.autogen.memgpt_agent as memgpt_autogen
import memgpt.autogen.interface as autogen_interface 
import memgpt.agent as agent
import memgpt.system as system
import memgpt.utils as utils
import memgpt.presets as presets
import memgpt.constants as constants
import memgpt.personas.personas as personas

datasciencemonkey

# %%
# this is run from /notebooks on paperspace
from huggingface_hub import login
from dotenv import load_dotenv

load_dotenv("/notebooks/.env")
import os
os.environ["TOKENIZERS_PARALLELISM"]="false"
login(token=os.getenv("HUGGINGFACE_TOKEN"))

Sharktheone

The installation script has moved to this repository

younesbelkada

# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software

sadasant

This gpt() function reads input from the command line and then sends a formatted JSON object to the OpenAI API for the GPT-4 model. It properly escapes special characters and checks for the .env file containing the OpenAI API key.

Usage:

• Load the function into your environment: source gpt.sh.
• Make sure to have an .env file in the current directory with the OPENAI_API_KEY.
• Pipe anything itno it, and also add a prompt, example:

git diff main | gpt "As a programmer, review this diff. Provide feedback only if necessary. Be brief"