pip install contextkit
To get context from an LLM, use one of the helper functions to pull it.
If a function pulls a single context snippit it will return the text, if it return multiple it will return a dictionary.
import contextkit.read as rdEach read_x function is designed to work with a single argument, which
is the location of the resource. This typically means a URL or a file
path.
rd.read_url('https://www.answer.ai/')[:200]'Answer.AI\n\n * __\n * __\n\n# Answer.AI - Practical AI R&D\n\n##### Categories\n\nAll (33)\n\nai (20)\n\ncoding (5)\n\ncompany (2)\n\ncourses (1)\n\neducation (1)\n\ninterview (1)\n\nopen-source (14)\n\npolicy (4)\n\nproduct'
Other arguments are always optional, but can be useful at times. For
example, the heavy argument in
read_url
allows you to do a heavy scrape with a contactless browser using
playwrightnb.
rd.read_url('https://www.answer.ai/',heavy=True)[:200]'Answer.AI\n\n * __\n * __\n\n# Answer.AI - Practical AI R&D\n\n##### Categories\n\nAll (33)\n\nai (20)\n\ncoding (5)\n\ncompany (2)\n\ncourses (1)\n\neducation (1)\n\ninterview (1)\n\nopen-source (14)\n\npolicy (4)\n\nproduct'
Many have been creates so far, such as
[o for o in dir(rd) if o.startswith('read_')]['read_dir',
'read_file',
'read_gdoc',
'read_gh_file',
'read_gh_repo',
'read_gist',
'read_git_path',
'read_google_sheet',
'read_html',
'read_pdf',
'read_url',
'read_yt_transcript']