Skip to main content

llama-index readers boarddocs integration

Project description

BoardDocs Loader

pip install llama-index-readers-boarddocs

This loader retrieves an agenda and associated material from a BoardDocs site.

This loader is not endorsed by, developed by, supported by, or in any way formally affiliated with Diligent Corporation.

Usage

To use this loader, you'll need to specify which BoardDocs site you want to load, as well as the committee on the site you want to scrape.

from llama_index.readers.boarddocs import BoardDocsReader

# For a site URL https://go.boarddocs.com/ca/redwood/Board.nsf/Public
# your site should be set to 'ca/redwood'
# You'll also need to specify which committee on the site you want to index,
# in this case A4EP6J588C05 is the Board of Trustees meeting.
loader = BoardDocsReader(site="ca/redwood", committee_id="A4EP6J588C05")

# You can optionally specify to load a specific set of meetings; if you don't
# pass in meeting_ids, the loader will attempt to load *all* meeting content.
# Since we're actually scraping a site, this can take a little while.
documents = loader.load_data(meeting_ids=["CPSNV9612DF1"])

This loader is designed to be used as a way to load data into LlamaIndex.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

llama_index_readers_boarddocs-0.3.0.tar.gz (3.5 kB view details)

Uploaded Source

Built Distribution

File details

Details for the file llama_index_readers_boarddocs-0.3.0.tar.gz.

File metadata

File hashes

Hashes for llama_index_readers_boarddocs-0.3.0.tar.gz
Algorithm Hash digest
SHA256 52a9ee940f9d925ccfcdeb8d62df11c8a806cde2d08fd18de8f2769adaacde9f
MD5 2a000c3f5f67a3f3cf3047e21ab65086
BLAKE2b-256 7e0198fe8e2d6ba121982424c4c8c76ab06dffbfe44773817b48f9dc77f5708d

See more details on using hashes here.

File details

Details for the file llama_index_readers_boarddocs-0.3.0-py3-none-any.whl.

File metadata

File hashes

Hashes for llama_index_readers_boarddocs-0.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 0722b9ba4aa17fa901c1b438c9ff3a7523dcb58de86406162d4fe5d4353f8cf6
MD5 ae2a24beb9e01c984c4fe2a24b5e813f
BLAKE2b-256 cfd581202481485af86315db0868876a9716a17f05ccaf7974a548d125ed90bd

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page