nickynicolson

About

This gist shows you how to use langchain to reformat text input data (representing specimens) into a structured output defined by a python class. For ease of use, it uses the groq API, so that no local installation of an LLM is required.

Requirements

You'll need python and to install the langchain-groq package, which is specified in requirements.txt

You'll also need to sign up for a groq API key at https://console.groq.com/keys, and you'll need to store this key in an environment variable (GROQ_API_KEY) on your local system.

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Problem

Top 1-3 problems that you want to solve

Solution

Outline proposed solution for each problem

Unique value proposition

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javascript: Promise.all([import('https://unpkg.com/[email protected]?module'), import('https://unpkg.com/@tehshrike/[email protected]'), ]).then(async ([{
    default: Turndown
}, {
    default: Readability
}]) => {

  /* Optional vault name */
  const vault = "";

  /* Optional folder name such as "Clippings/" */

nickynicolson

Set up a dask gateway and print the dashboard URL

import dask_gateway

cluster = dask_gateway.GatewayCluster()
client = cluster.get_client()
cluster.scale(8)
print(cluster.dashboard_link)

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Linking Obsidian and Zotero

Setup

Zotero

Zotero desktop used to manage literature references, with zotfile and zotero better bibtex plugins used to manage PDF attachments and create / maintain biblatex format downloads respectively.

Obsidian

Obsidian used to manage notes and tasks, with the citations plugin used to access literature references from the Zotero biblatex format export.

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bash

Default behaviour

• history shows numbered command history, most recent last
• !n retrieves command number n and executes it
• !n:p retrieves command number n and places it into the command history without executing it. Up arrow then retrieves the command for editing

shopt

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nickynicolson

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import networkx as nx
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import mplleaflet
import sys

def main():
    inputfile=sys.argv[1]
    outputfile_base=sys.argv[2]

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import pandas as pd
from pandas.io.json import json_normalize
import requests
# IH API documented here: https://github.com/nybgvh/IH-API/wiki
url='http://sweetgum.nybg.org/science/api/v1/institutions'

def main():
    response = requests.get(url)
    results = response.json()
    # The JSON format record for an IH record has nested sections - the