Observed Signal · Apr 9, 2026 · Technical Release · Source: DEV Community · Impact: 1/5 · Sentiment: Neutral
Real-time OpenAI Streaming in Rails
A technical tutorial demonstrating how to stream token-by-token responses from OpenAI through a Rails app using Server-Sent Events (SSE) to a background job, ActionCable broadcasts, and Turbo Streams/Stimulus on the browser. The post provides concrete code examples: an ActionCable ChatStreamChannel, a StreamAiResponseJob that calls OpenAI::Client with streaming enabled (example uses model "gpt-4o"), a MessagesController that enqueues the job, and a Stimulus controller that appends tokens to the DOM. The author discusses error handling, performance considerations (use Sidekiq/Solid Queue, Redis adapter, and batch DB writes), and recommends broadcasting tokens for smooth UX while reducing frequent writes to the database.
Practical developer tutorial that documents a streaming architecture for conversational UIs; useful to engineers but not industry-shifting.
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Key Takeaways & Evidence Grounding
- Architecture: OpenAI SSE → Rails Background Job → ActionCable → Turbo Stream → Browser DOM
- Provides code examples including ChatStreamChannel, StreamAiResponseJob (uses OpenAI::Client with stream proc), and a Stimulus chat_stream_controller
- Example uses model parameter "gpt-4o" and broadcasts each token as it arrives via ActionCable
- Performance recommendations: run streaming jobs on Sidekiq/Solid Queue, set ActionCable adapter to Redis, and batch database writes (e.g., every 10 tokens or 500ms)
- Includes error-handling pattern that rescues streaming errors and broadcasts an error message while updating the message record
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Fixing Real-Time AI Chat Latency with SSE Streaming
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