What happens to my Gradio response if Monetzly is down?

The SDK falls back to yielding your original token stream, so the user still receives a complete Gradio answer — just without ads for that request.

Do I need a manual fallback in Gradio?

The SDK handles fallback automatically, but wrapping the loop in your usual error handling is still good practice.

How-to guide

How to Handle Ad-Injection Errors in Gradio

This guide shows how to handle ad-injection errors in a Gradio app, the goal being to make sure the user still gets a reply if the ad service fails. It builds on the Monetzly gRPC service (no Python SDK exists for this stack), so the approach is specific to how Gradio produces and streams responses.

Overview

Monetization should never break your Gradio app. The Monetzly SDK is built for this: if the ad service connection fails or errors mid-stream, it falls back to yielding your original, un-injected token stream, so the user still gets a complete answer.

You should still wrap the injection loop in your normal error handling so a failure degrades to a plain Gradio response rather than a broken request.

Gradio apps are usually built for model demos, chat interfaces, and shareable AI prototypes, so handle ad-injection errors typically comes up while a user is mid-conversation, the moment where monetization has to be additive rather than disruptive.

How this works on Gradio

Gradio is Python. Drive the shipped tps_alter.proto gRPC service (or a Node sidecar) and yield injected tokens from a gr.ChatInterface generator fn for streaming output. Confirm the non-JS auth handshake before publishing.

Since Gradio is a Python stack with no official SDK, this task runs through the shipped tps_alter.proto gRPC service (or a Node sidecar); the auth handshake for a direct client is still TODO_VERIFY.

Steps

Wrap the injection loop in your standard Gradio error handling.
Rely on the SDK's automatic fallback to the original stream on ad-service failure.
Log injection failures so you can monitor fill and uptime separately from your model.

Integration snippet

TODO_VERIFY: Gradio uses the gRPC proto path, confirm the auth handshake with Monetzly before relying on this in production.

# No Python SDK. Generate stubs from tps_alter.proto and drive ProcessStream
# (see the FastAPI page for the full bidi loop), then in a streaming chat fn:
#
#   async def respond(message, history):
#       out = ""
#       async for token in inject(llm_tokens, message, session_id, api_key):
#           out += token
#           yield out
#
# TODO_VERIFY: auth handshake (API key placement) for a direct gRPC client.