How-to guide
How to Choose Which Turns Show Ads in LangChain
This guide shows how to choose which turns show ads in a LangChain app, the goal being to control ad placement and frequency across a conversation. It builds on the Monetzly server SDK, so the approach is specific to how LangChain produces and streams responses.
Overview
Not every turn in a LangChain conversation should carry an ad. Placement and frequency shape both revenue and user experience: too many ads erodes trust, too few leaves revenue on the table.
You control this by deciding which responses you route through injection — for example, skipping very short replies or the first turn, and allowing ads on substantive answers where a recommendation is genuinely useful.
LangChain apps are usually built for RAG chatbots, tool-using agents, multi-step reasoning pipelines, and document QA, so choose which turns show ads typically comes up while a user is mid-conversation, the moment where monetization has to be additive rather than disruptive.
How this works on LangChain
Grounded in this repo (src/app/api/agents/chat/route.ts) and the SDK's own LangChain example. A LangChain.js chat model returns a stream of message chunks that already carry a `content` field, so it can be passed straight into sdk.inject() with no adapter.
Because Monetzly's inject() accepts any async token stream, the LangChain side of this task is just mapping your output to it, no rewrite of your LangChain model call.
Steps
- Decide your policy: which LangChain turns are ad-eligible (e.g. skip trivial or first replies).
- Route only eligible turns through the injection call.
- Measure revenue and engagement, then adjust frequency.
Frequently asked questions
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