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3b20b48473
* 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>
92 lines
2.9 KiB
Python
92 lines
2.9 KiB
Python
"""
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Utility functions for Interactions API.
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"""
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from typing import Any, Final, cast
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from litellm.llms.base_llm.interactions.transformation import BaseInteractionsAPIConfig
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from litellm.types.interactions import InteractionsAPIOptionalRequestParams
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# Valid optional parameter keys per OpenAPI spec
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INTERACTIONS_API_OPTIONAL_PARAMS: Final = {
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"tools",
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"system_instruction",
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"generation_config",
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"stream",
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"store",
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"background",
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"environment",
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"response_modalities",
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"response_format",
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"response_mime_type",
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"previous_interaction_id",
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"continuation_token",
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"agent_config",
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}
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def get_provider_interactions_api_config(
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provider: str,
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model: str | None = None,
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) -> BaseInteractionsAPIConfig | None:
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"""
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Get the interactions API config for the given provider.
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Args:
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provider: The LLM provider name
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model: Optional model name
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Returns:
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The provider-specific interactions API config, or None if not supported
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"""
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from litellm.types.utils import LlmProviders
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if provider == LlmProviders.GEMINI.value or provider == "gemini":
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from litellm.llms.gemini.interactions.transformation import (
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GoogleAIStudioInteractionsConfig,
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)
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return GoogleAIStudioInteractionsConfig()
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if provider in (LlmProviders.VERTEX_AI.value, LlmProviders.VERTEX_AI_BETA.value):
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from litellm.llms.vertex_ai.interactions.transformation import (
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VertexAIInteractionsConfig,
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)
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return VertexAIInteractionsConfig()
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return None
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class InteractionsAPIRequestUtils:
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"""Helper utils for constructing Interactions API requests."""
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@staticmethod
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def get_requested_interactions_api_optional_params(
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params: dict[str, Any],
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) -> InteractionsAPIOptionalRequestParams:
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"""
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Filter parameters to only include valid optional params per OpenAPI spec.
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Args:
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params: Dictionary of parameters to filter (typically from locals())
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Returns:
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Dict with only the valid optional parameters
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"""
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from litellm.utils import PreProcessNonDefaultParams
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custom_llm_provider: Final = params.pop("custom_llm_provider", None)
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special_params: Final = params.pop("kwargs", {})
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additional_drop_params: Final = params.pop("additional_drop_params", None)
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non_default_params: Final = PreProcessNonDefaultParams.base_pre_process_non_default_params(
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passed_params=params,
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special_params=special_params,
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custom_llm_provider=custom_llm_provider,
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additional_drop_params=additional_drop_params,
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default_param_values={k: None for k in INTERACTIONS_API_OPTIONAL_PARAMS},
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additional_endpoint_specific_params=["input", "model", "agent"],
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)
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return cast(InteractionsAPIOptionalRequestParams, non_default_params)
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