Streaming Chat Inference

Streaming chat inference enables real-time AI chat interactions by streaming deterministic delta content responses across providers in the 0G Compute network. It reduces latency by sending real-time deltas back from the provider during generation.

Yes, streaming chat inference supports multi-turn conversations with history. You can send a user message to the broker, stream the results back, and maintain context across multiple conversational turns for live applications.

You track real-time fee settlement by performing post-inference accounting via the processResponse(providerAddress, chatID, usageData) function after streaming responses complete. This handles accounting across volatile network environments.

Yes, the streaming inference mechanism includes robust error handling and provides a fallback to non-streaming mode. This ensures reliable chat completions even when network environments become volatile or providers experience issues.

To initialize a broker for streaming chat, you call the broker with a user message to start a session and obtain metadata. This setup targets developers integrating conversational AI into live apps and customer support desks.