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* feat(interactions): continue requires_continuation long decodes with continuation_token hops A foreground Interactions request stops at Google's per-hop output cap with status requires_continuation and a continuation_token. litellm now re-posts the request with previous_interaction_id and continuation_token until the status moves on, merging the hops into one interaction (last id, every hop's steps, summed usage with initial_input_tokens from hop 1), for non-streaming and streaming calls. continuation_token is accepted as a request param, and requires_continuation is a known status for billing. * refactor(gemini interactions): validate streaming chunks with model_validate * fix(interactions): keep the held completion across stream hops, stop on a repeated continuation_token, follow the spec redirect * fix(interactions): add grounding_tool_count per tool type, stop on any seen continuation_token, keep streaming past a [DONE] frame when a hop is pending * ci(interactions): point the spec canary at aistudio.google.com, where Google moved the Interactions OpenAPI spec * test(interactions): scripted Google ends each long decode hop with a [DONE] frame * refactor(interactions): pass requires_continuation and continuation_token through instead of looping hops in the proxy The caller drives the continuation, the same as against Google directly. /interactions accepts continuation_token in place of input so a resume request needs no input. * test(proxy): assert the accepted /interactions bodies pass the required-param check * fix(proxy): keep the router default fallback for input on /interactions, continuation_token stands in for it --------- Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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