Instead of trying to filter stale events inline (unreliable — the API
doesn't provide a way to correlate events to a specific response),
drain remaining events from a cancelled response before starting the
next one. On cancellation, send response.cancel and set a drain flag.
At the start of the next _process_context, read and discard events
until a terminal event arrives, ensuring a clean connection. Falls
back to reconnecting if draining times out.
When using previous_response_id, the server already knows its own
output from the previous response. Store the raw response output and,
on the next call, compare it against the items following the matched
input prefix — checking role and text content for messages, and call_id
for function calls. If the items match, skip them and send only truly
new input (user messages, tool results). Falls back to full context if
either the prefix or the output comparison fails.
Introduce a WebSocket variant of the OpenAI Responses API service that
maintains a persistent connection to wss://api.openai.com/v1/responses
for lower-latency inference. The WebSocket variant automatically uses
previous_response_id to send only incremental context when possible,
falling back to full context on reconnection or cache miss.
The WebSocket variant becomes the new default OpenAIResponsesLLMService,
and the HTTP variant is renamed to OpenAIResponsesHttpLLMService. Both
share a private base class with common settings, parameter building,
and run_inference (always HTTP) logic.
