What is the easiest way to implement a human in the loop workflow using LangChain versus building a custom approval queue in Slack?
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
What is the easiest way to implement a human in the loop workflow using LangChain versus building a custom approval queue in Slack?
2 real searches · 1 real-search pass
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
Classifying 2 queries…
Searches and sources
ChatGPT2 real searches · gpt-6
LangGraph human in the loop interrupt checkpoint persistence official docs Slack approval workflow Google ↗
Slack Block Kit interactive messages actions request URL official docs Google ↗
- LangGraph interrupts · docs.langchain.com
- LangChain human-in-the-loop middleware · docs.langchain.com
- docs/src/oss/langchain/human-in-the-loop.mdx at main · langchain-ai/docs · github.com
- docs/src/oss/langgraph/interrupts.mdx at main · langchain-ai/docs · github.com
- Creating interactive messages · docs.slack.dev
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
LangGraph human in the loop interrupt checkpoint persistence official docs Slack approval workflow OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 | |
Slack Block Kit interactive messages actions request URL official docs OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 |