Map the fields you need once in Gluedly, then pull compact JSON/Markdown into your LangChain ingestion step instead of parsing raw HTML inside your app.
Why teams use this integration
- Reduce token bloat before data reaches your prompt templates.
- Keep retrieval inputs schema-stable even when target sites change layout.
- Refresh chains and retrievers on your schedule with webhooks or live fetches.
Recommended setup
- Create a page in Gluedly and map the fields your chain expects.
- Schedule refreshes or trigger runs when source content changes.
- Fetch the latest data from the API and normalize it into LangChain documents.
- Store structured results in your vector store or pass them directly to a tool.
Example code
Use the latest structured data from Gluedly as the input layer for your AI stack.
# pip install langchain-gluedly
from langchain_gluedly import GluedlyLoader
loader = GluedlyLoader(
api_key="YOUR_WORKSPACE_KEY",
page_id=123,
base_url="https://gluedly.com/api/v1",
)
documents = loader.load()