mirror of
https://github.com/BerriAI/litellm.git
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feat(decisions): serve System One format at /v1/systemone and OpenAI format at /v1/decisions
The System One request format moves to /v1/systemone and /systemone. /v1/decisions and /decisions now accept the OpenAI Decisions API format, translate it into a System One request, route it through the same pipeline, and translate the answers back.
This commit is contained in:
mateo-berri
parent
df23f11e9b
commit
3339469e73
16 changed files with 696 additions and 58 deletions
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@ -62,6 +62,8 @@ GATEWAY_PATH_PREFIXES: tuple[str, ...] = (
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"/rerank",
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"/v1/decisions",
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"/decisions",
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"/v1/systemone",
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"/systemone",
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"/v1/ocr",
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"/ocr",
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"/v1/rag/",
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127
litellm/decisions/openai_transformation.py
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127
litellm/decisions/openai_transformation.py
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@ -0,0 +1,127 @@
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from collections.abc import Mapping, Sequence
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from typing import Final, assert_never
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from litellm.types.decisions import (
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ChoiceAnswer,
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DecisionAnswer,
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DecisionsResponse,
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DecisionsUsage,
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NoulAnswer,
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OpenAIChoiceAnswer,
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OpenAIChoiceProbability,
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OpenAIChoiceQuestion,
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OpenAIDecisionAnswer,
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OpenAIDecisionInputMessage,
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OpenAIDecisionQuestion,
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OpenAIDecisionRequestBody,
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OpenAIDecisionResponse,
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OpenAIDecisionUsage,
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OpenAIPredicateAnswer,
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OpenAIPredicateQuestion,
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OpenAIRefusalAnswer,
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OpenAIScoreAnswer,
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OpenAIScoreLevel,
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OpenAIScoreProbability,
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OpenAIScoreQuestion,
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ScoreAnswer,
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systemone_choice_key,
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)
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_OPENAI_ONLY_FIELDS: Final = frozenset({"input", "questions", "safety_identifier"})
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def _message_text(message: OpenAIDecisionInputMessage) -> str:
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if isinstance(message.content, str):
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return message.content
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return "\n\n".join(part.text for part in message.content)
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def _state(decision_input: str | Sequence[OpenAIDecisionInputMessage]) -> str:
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if isinstance(decision_input, str):
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return decision_input
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return "\n\n".join(_message_text(message) for message in decision_input)
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def _level_criterion(level: OpenAIScoreLevel) -> str:
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return level.label if level.description is None else f"{level.label}: {level.description}"
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def _systemone_question(question: OpenAIDecisionQuestion) -> Mapping[str, object]:
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match question:
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case OpenAIPredicateQuestion():
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return {"type": "noul", "instructions": question.instructions}
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case OpenAIChoiceQuestion():
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return {
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"type": "choice",
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"instructions": question.instructions,
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"criteria": {systemone_choice_key(option.value): option.description for option in question.choices},
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}
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case OpenAIScoreQuestion():
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return {
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"type": "score",
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"instructions": question.instructions,
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"criteria": [_level_criterion(level) for level in question.levels],
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}
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case _:
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assert_never(question)
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def to_systemone_request(
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request_data: Mapping[str, object], body: OpenAIDecisionRequestBody
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) -> Mapping[str, object]:
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return {
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**{key: value for key, value in request_data.items() if key not in _OPENAI_ONLY_FIELDS},
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"state": _state(body.input),
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"questions": {str(index): _systemone_question(question) for index, question in enumerate(body.questions)},
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}
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def _openai_answer(question: OpenAIDecisionQuestion, answer: DecisionAnswer | None) -> OpenAIDecisionAnswer:
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match question, answer:
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case OpenAIPredicateQuestion(), NoulAnswer():
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return OpenAIPredicateAnswer(name=question.name, probability=answer.noul)
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case OpenAIChoiceQuestion(), ChoiceAnswer():
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typed_values: Final = {systemone_choice_key(option.value): option.value for option in question.choices}
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return OpenAIChoiceAnswer(
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name=question.name,
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choice=typed_values.get(answer.choice, answer.choice),
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probabilities=tuple(
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OpenAIChoiceProbability(
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value=option.value,
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probability=answer.probabilities.get(systemone_choice_key(option.value), 0.0),
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)
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for option in question.choices
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),
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confidence=answer.confidence,
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)
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case OpenAIScoreQuestion(), ScoreAnswer():
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return OpenAIScoreAnswer(
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name=question.name,
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score=answer.score,
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probabilities=tuple(
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OpenAIScoreProbability(
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value=index, label=level.label, probability=answer.probabilities.get(str(index), 0.0)
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)
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for index, level in enumerate(question.levels)
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),
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confidence=answer.confidence,
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)
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case _:
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return OpenAIRefusalAnswer(name=question.name)
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def to_openai_response(
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response: DecisionsResponse, questions: Sequence[OpenAIDecisionQuestion], requested_model: str
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) -> OpenAIDecisionResponse:
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usage: Final = response.usage or DecisionsUsage()
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return OpenAIDecisionResponse(
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model=response.model or requested_model,
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answers=tuple(
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_openai_answer(question, response.answers.get(str(index))) for index, question in enumerate(questions)
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),
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usage=OpenAIDecisionUsage(
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input_tokens=usage.input_tokens,
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output_tokens=usage.output_tokens,
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total_tokens=usage.input_tokens + usage.output_tokens,
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),
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)
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@ -267,7 +267,7 @@ LAZY_FEATURES: Final[tuple[LazyFeature, ...]] = (
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LazyFeature(
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name="decisions",
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module_path="litellm.proxy.decisions_endpoints.endpoints",
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path_prefixes=("/v1/decisions", "/decisions"),
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path_prefixes=("/v1/decisions", "/decisions", "/v1/systemone", "/systemone"),
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),
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LazyFeature(
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name="claude_code_marketplace",
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@ -9521,6 +9521,30 @@
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]
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}
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},
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"/systemone": {
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"post": {
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"operationId": "systemone_systemone_post",
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"responses": {
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"200": {
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"content": {
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"application/json": {
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"schema": {}
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}
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},
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"description": "Successful Response"
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}
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},
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"security": [
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{
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"APIKeyHeader": []
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}
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],
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"summary": "Systemone",
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"tags": [
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"decisions"
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]
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}
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},
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"/v1/decisions": {
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"post": {
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"operationId": "decisions_v1_decisions_post",
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@ -9544,6 +9568,30 @@
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"decisions"
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]
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}
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},
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"/v1/systemone": {
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"post": {
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"operationId": "systemone_v1_systemone_post",
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"responses": {
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"200": {
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"content": {
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"application/json": {
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"schema": {}
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}
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},
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"description": "Successful Response"
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}
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},
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"security": [
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{
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"APIKeyHeader": []
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}
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],
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"summary": "Systemone",
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"tags": [
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"decisions"
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]
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}
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}
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}
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},
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@ -488,6 +488,8 @@ class LiteLLMRoutes(enum.Enum):
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"/v1/search/{search_tool_name}",
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"/decisions",
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"/v1/decisions",
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"/systemone",
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"/v1/systemone",
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# OCR
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"/ocr",
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"/v1/ocr",
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@ -30,6 +30,7 @@ _MANAGED_MODEL_ROUTES: Final = frozenset(
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"moderations",
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"rerank",
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"decisions",
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"systemone",
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"ocr",
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),
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)
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@ -74,6 +75,7 @@ _MODEL_ROUTE_KINDS: Final[
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"/audio/speech": "speech",
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"/rerank": "body",
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"/decisions": "body",
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"/systemone": "body",
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"/messages/count_tokens": "body",
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":countTokens": "path",
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}
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@ -1,39 +1,52 @@
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from collections.abc import Mapping
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from typing import Annotated, Final
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from fastapi import APIRouter, Depends, Request, Response
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from fastapi.responses import ORJSONResponse # pyright: ignore[reportDeprecated] # required endpoint contract
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from pydantic import TypeAdapter, ValidationError
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from litellm.decisions.openai_transformation import to_openai_response, to_systemone_request
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from litellm.exceptions import BadRequestError
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from litellm.proxy.auth.user_api_key_auth import UserAPIKeyAuth, user_api_key_auth
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from litellm.proxy.common_request_processing import ProxyBaseLLMRequestProcessing
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from litellm.types.decisions import DecisionsRequestBody
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from litellm.types.decisions import DecisionsRequestBody, DecisionsResponse, OpenAIDecisionRequestBody
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router: Final = APIRouter()
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_REQUEST_DATA_ADAPTER: Final[TypeAdapter[dict[str, object]]] = TypeAdapter(dict[str, object])
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_DECISIONS_REQUEST_BODY_ADAPTER: Final[TypeAdapter[DecisionsRequestBody]] = TypeAdapter(DecisionsRequestBody)
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_OPENAI_DECISION_REQUEST_BODY_ADAPTER: Final[TypeAdapter[OpenAIDecisionRequestBody]] = TypeAdapter(
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OpenAIDecisionRequestBody
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)
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_DECISIONS_RESPONSE_ADAPTER: Final[TypeAdapter[DecisionsResponse]] = TypeAdapter(DecisionsResponse)
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_GENERAL_SETTINGS_ADAPTER: Final[TypeAdapter[dict[str, object]]] = TypeAdapter(dict[str, object])
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_OPTIONAL_STRING_ADAPTER: Final[TypeAdapter[str | None]] = TypeAdapter(str | None)
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_OPTIONAL_FLOAT_ADAPTER: Final[TypeAdapter[float | None]] = TypeAdapter(float | None)
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@router.post(
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"/v1/decisions",
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dependencies=[Depends(user_api_key_auth)],
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response_class=ORJSONResponse, # pyright: ignore[reportDeprecated] # required endpoint contract
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tags=["decisions"],
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)
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@router.post(
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"/decisions",
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dependencies=[Depends(user_api_key_auth)],
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response_class=ORJSONResponse, # pyright: ignore[reportDeprecated] # required endpoint contract
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tags=["decisions"],
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)
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async def decisions(
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async def _invalid_request(
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raw_data: Mapping[str, object], error: ValidationError, user_api_key_dict: UserAPIKeyAuth
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) -> Exception:
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from litellm.proxy.proxy_server import proxy_logging_obj, version
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return await ProxyBaseLLMRequestProcessing(data=dict(raw_data))._handle_llm_api_exception(
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e=BadRequestError(
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message=f"Invalid Decisions request: {error}",
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model=str(raw_data.get("model", "")),
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llm_provider="",
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),
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user_api_key_dict=user_api_key_dict,
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proxy_logging_obj=proxy_logging_obj,
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version=version,
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)
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async def _process_systemone(
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request: Request,
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fastapi_response: Response,
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user_api_key_dict: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)],
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):
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user_api_key_dict: UserAPIKeyAuth,
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raw_data: Mapping[str, object],
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openai_body: OpenAIDecisionRequestBody | None,
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) -> object:
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from litellm.proxy.proxy_server import (
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general_settings as proxy_general_settings,
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)
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@ -55,7 +68,7 @@ async def decisions(
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user_temperature as proxy_user_temperature,
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)
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data: Final = _REQUEST_DATA_ADAPTER.validate_json(await request.body())
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data: Final = dict(raw_data if openai_body is None else to_systemone_request(raw_data, openai_body))
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general_settings: Final = _GENERAL_SETTINGS_ADAPTER.validate_python(proxy_general_settings)
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user_api_base: Final = _OPTIONAL_STRING_ADAPTER.validate_python(proxy_user_api_base)
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user_model: Final = _OPTIONAL_STRING_ADAPTER.validate_python(proxy_user_model)
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@ -63,7 +76,7 @@ async def decisions(
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processor: Final = ProxyBaseLLMRequestProcessing(data=data)
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try:
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_DECISIONS_REQUEST_BODY_ADAPTER.validate_python(data)
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return await processor.base_process_llm_request(
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result: Final[object] = await processor.base_process_llm_request(
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request=request,
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fastapi_response=fastapi_response,
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user_api_key_dict=user_api_key_dict,
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@ -81,18 +94,15 @@ async def decisions(
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user_api_base=user_api_base,
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version=version,
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)
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if openai_body is None or isinstance(result, Response):
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return result
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return to_openai_response(
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_DECISIONS_RESPONSE_ADAPTER.validate_python(result),
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openai_body.questions,
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str(data.get("model", "")),
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)
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except ValidationError as error:
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bad_request_error: Final = BadRequestError(
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message=f"Invalid Decisions request: {error}",
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model=str(data.get("model", "")),
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llm_provider="",
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)
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raise await processor._handle_llm_api_exception(
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e=bad_request_error,
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user_api_key_dict=user_api_key_dict,
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proxy_logging_obj=proxy_logging_obj,
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version=version,
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)
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raise await _invalid_request(raw_data=data, error=error, user_api_key_dict=user_api_key_dict)
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except Exception as error:
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raise await processor._handle_llm_api_exception(
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e=error,
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@ -100,3 +110,60 @@ async def decisions(
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proxy_logging_obj=proxy_logging_obj,
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version=version,
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)
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@router.post(
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"/v1/systemone",
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dependencies=[Depends(user_api_key_auth)],
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response_class=ORJSONResponse, # pyright: ignore[reportDeprecated] # required endpoint contract
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tags=["decisions"],
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)
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@router.post(
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"/systemone",
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dependencies=[Depends(user_api_key_auth)],
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response_class=ORJSONResponse, # pyright: ignore[reportDeprecated] # required endpoint contract
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tags=["decisions"],
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)
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async def systemone(
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request: Request,
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fastapi_response: Response,
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user_api_key_dict: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)],
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):
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return await _process_systemone(
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request=request,
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fastapi_response=fastapi_response,
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user_api_key_dict=user_api_key_dict,
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raw_data=_REQUEST_DATA_ADAPTER.validate_json(await request.body()),
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openai_body=None,
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)
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@router.post(
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"/v1/decisions",
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dependencies=[Depends(user_api_key_auth)],
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response_class=ORJSONResponse, # pyright: ignore[reportDeprecated] # required endpoint contract
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tags=["decisions"],
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)
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@router.post(
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"/decisions",
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dependencies=[Depends(user_api_key_auth)],
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response_class=ORJSONResponse, # pyright: ignore[reportDeprecated] # required endpoint contract
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tags=["decisions"],
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)
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async def decisions(
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request: Request,
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fastapi_response: Response,
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user_api_key_dict: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)],
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):
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raw_data: Final = _REQUEST_DATA_ADAPTER.validate_json(await request.body())
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try:
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openai_body: Final = _OPENAI_DECISION_REQUEST_BODY_ADAPTER.validate_python(raw_data)
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except ValidationError as error:
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raise await _invalid_request(raw_data=raw_data, error=error, user_api_key_dict=user_api_key_dict)
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return await _process_systemone(
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request=request,
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fastapi_response=fastapi_response,
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user_api_key_dict=user_api_key_dict,
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raw_data=raw_data,
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openai_body=openai_body,
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)
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|
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@ -1,5 +1,5 @@
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from collections.abc import Mapping, Sequence
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from typing import Annotated, Literal, TypeAlias
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from typing import Annotated, Final, Literal, TypeAlias
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from pydantic import ConfigDict, Field, PrivateAttr, model_validator, with_config
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from typing_extensions import ReadOnly, Required, TypedDict
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@ -125,3 +125,169 @@ class DecisionsResponse(LiteLLMPydanticObjectBase):
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@property
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def hidden_params(self) -> dict[str, object]: # mutable-ok: API requires mutation
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return self._hidden_params
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class OpenAIDecisionInputText(LiteLLMPydanticObjectBase):
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type: Literal["input_text"]
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text: str
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model_config = ConfigDict(extra="forbid", frozen=True)
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class OpenAIDecisionInputMessage(LiteLLMPydanticObjectBase):
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role: Literal["user"] = "user"
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type: Literal["message"] = "message"
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content: str | Sequence[OpenAIDecisionInputText]
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model_config = ConfigDict(extra="forbid", frozen=True)
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class OpenAIPredicateQuestion(LiteLLMPydanticObjectBase):
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type: Literal["predicate"]
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name: str | None = None
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instructions: str
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model_config = ConfigDict(extra="forbid", frozen=True)
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||||
|
||||
class OpenAIChoiceOption(LiteLLMPydanticObjectBase):
|
||||
value: str | bool
|
||||
description: str | None = None
|
||||
|
||||
model_config = ConfigDict(extra="forbid", frozen=True)
|
||||
|
||||
|
||||
def systemone_choice_key(value: str | bool) -> str:
|
||||
if isinstance(value, bool):
|
||||
return "true" if value else "false"
|
||||
return value
|
||||
|
||||
|
||||
class OpenAIChoiceQuestion(LiteLLMPydanticObjectBase):
|
||||
type: Literal["choice"]
|
||||
name: str | None = None
|
||||
instructions: str
|
||||
choices: Annotated[Sequence[OpenAIChoiceOption], Field(min_length=2, max_length=255)]
|
||||
|
||||
model_config = ConfigDict(extra="forbid", frozen=True)
|
||||
|
||||
@model_validator(mode="after")
|
||||
def require_unique_systemone_keys(self) -> "OpenAIChoiceQuestion":
|
||||
keys: Final = frozenset(systemone_choice_key(option.value) for option in self.choices)
|
||||
if len(keys) != len(self.choices):
|
||||
raise ValueError("Choice values must be unique, and a boolean cannot share its text with a string choice")
|
||||
return self
|
||||
|
||||
|
||||
class OpenAIScoreLevel(LiteLLMPydanticObjectBase):
|
||||
label: str
|
||||
description: str | None = None
|
||||
|
||||
model_config = ConfigDict(extra="forbid", frozen=True)
|
||||
|
||||
|
||||
class OpenAIScoreQuestion(LiteLLMPydanticObjectBase):
|
||||
type: Literal["score"]
|
||||
name: str | None = None
|
||||
instructions: str
|
||||
levels: Annotated[Sequence[OpenAIScoreLevel], Field(min_length=2, max_length=10)]
|
||||
|
||||
model_config = ConfigDict(extra="forbid", frozen=True)
|
||||
|
||||
|
||||
OpenAIDecisionQuestion: TypeAlias = Annotated[
|
||||
OpenAIPredicateQuestion | OpenAIChoiceQuestion | OpenAIScoreQuestion,
|
||||
Field(discriminator="type"),
|
||||
]
|
||||
|
||||
|
||||
class OpenAIDecisionRequestBody(LiteLLMPydanticObjectBase):
|
||||
input: str | Sequence[OpenAIDecisionInputMessage]
|
||||
questions: Annotated[Sequence[OpenAIDecisionQuestion], Field(min_length=1, max_length=200)]
|
||||
safety_identifier: str | None = None
|
||||
|
||||
model_config = ConfigDict(extra="allow", frozen=True)
|
||||
|
||||
|
||||
class OpenAIPredicateAnswer(LiteLLMPydanticObjectBase):
|
||||
type: Literal["predicate"] = "predicate"
|
||||
name: str | None
|
||||
probability: float
|
||||
|
||||
model_config = ConfigDict(frozen=True)
|
||||
|
||||
|
||||
class OpenAIChoiceProbability(LiteLLMPydanticObjectBase):
|
||||
value: str | bool
|
||||
probability: float
|
||||
|
||||
model_config = ConfigDict(frozen=True)
|
||||
|
||||
|
||||
class OpenAIChoiceAnswer(LiteLLMPydanticObjectBase):
|
||||
type: Literal["choice"] = "choice"
|
||||
name: str | None
|
||||
choice: str | bool
|
||||
probabilities: tuple[OpenAIChoiceProbability, ...]
|
||||
confidence: float
|
||||
|
||||
model_config = ConfigDict(frozen=True)
|
||||
|
||||
|
||||
class OpenAIScoreProbability(LiteLLMPydanticObjectBase):
|
||||
value: int
|
||||
label: str
|
||||
probability: float
|
||||
|
||||
model_config = ConfigDict(frozen=True)
|
||||
|
||||
|
||||
class OpenAIScoreAnswer(LiteLLMPydanticObjectBase):
|
||||
type: Literal["score"] = "score"
|
||||
name: str | None
|
||||
score: float
|
||||
probabilities: tuple[OpenAIScoreProbability, ...]
|
||||
confidence: float
|
||||
|
||||
model_config = ConfigDict(frozen=True)
|
||||
|
||||
|
||||
class OpenAIRefusalAnswer(LiteLLMPydanticObjectBase):
|
||||
type: Literal["refusal"] = "refusal"
|
||||
name: str | None
|
||||
|
||||
model_config = ConfigDict(frozen=True)
|
||||
|
||||
|
||||
OpenAIDecisionAnswer: TypeAlias = OpenAIPredicateAnswer | OpenAIChoiceAnswer | OpenAIScoreAnswer | OpenAIRefusalAnswer
|
||||
|
||||
|
||||
class OpenAIDecisionInputTokensDetails(LiteLLMPydanticObjectBase):
|
||||
cached_tokens: int = 0
|
||||
cache_write_tokens: int = 0
|
||||
|
||||
model_config = ConfigDict(frozen=True)
|
||||
|
||||
|
||||
class OpenAIDecisionOutputTokensDetails(LiteLLMPydanticObjectBase):
|
||||
reasoning_tokens: int = 0
|
||||
|
||||
model_config = ConfigDict(frozen=True)
|
||||
|
||||
|
||||
class OpenAIDecisionUsage(LiteLLMPydanticObjectBase):
|
||||
input_tokens: int
|
||||
input_tokens_details: OpenAIDecisionInputTokensDetails = OpenAIDecisionInputTokensDetails()
|
||||
output_tokens: int
|
||||
output_tokens_details: OpenAIDecisionOutputTokensDetails = OpenAIDecisionOutputTokensDetails()
|
||||
total_tokens: int
|
||||
|
||||
model_config = ConfigDict(frozen=True)
|
||||
|
||||
|
||||
class OpenAIDecisionResponse(LiteLLMPydanticObjectBase):
|
||||
model: str
|
||||
answers: tuple[OpenAIDecisionAnswer, ...]
|
||||
usage: OpenAIDecisionUsage
|
||||
|
||||
model_config = ConfigDict(frozen=True)
|
||||
|
|
|
|||
|
|
@ -788,6 +788,8 @@ API_ROUTE_TO_CALL_TYPES: Final[Mapping[str, Sequence[CallTypes]]] = {
|
|||
"/v1/search": [CallTypes.asearch, CallTypes.search],
|
||||
"/decisions": [CallTypes.adecisions, CallTypes.decisions],
|
||||
"/v1/decisions": [CallTypes.adecisions, CallTypes.decisions],
|
||||
"/systemone": [CallTypes.adecisions, CallTypes.decisions],
|
||||
"/v1/systemone": [CallTypes.adecisions, CallTypes.decisions],
|
||||
# Batches
|
||||
"/batches": [CallTypes.acreate_batch, CallTypes.create_batch],
|
||||
"/v1/batches": [CallTypes.acreate_batch, CallTypes.create_batch],
|
||||
|
|
|
|||
|
|
@ -16,7 +16,7 @@ from starlette.routing import Match
|
|||
|
||||
import litellm
|
||||
from litellm.proxy._lazy_features import LAZY_FEATURES, LazyFeature, attach_lazy_features
|
||||
from litellm.proxy.decisions_endpoints.endpoints import decisions
|
||||
from litellm.proxy.decisions_endpoints.endpoints import decisions, systemone
|
||||
from litellm.proxy.pass_through_endpoints.pass_through_endpoints import SafeRouteAdder
|
||||
from litellm.proxy.proxy_server import (
|
||||
app,
|
||||
|
|
@ -77,7 +77,7 @@ def client(monkeypatch: pytest.MonkeyPatch) -> Iterator[TestClient]:
|
|||
litellm.in_memory_llm_clients_cache.flush_cache()
|
||||
|
||||
|
||||
@pytest.mark.parametrize("endpoint", ("/v1/decisions", "/decisions"))
|
||||
@pytest.mark.parametrize("endpoint", ("/v1/systemone", "/systemone"))
|
||||
def test_proxy_decisions_route_returns_answers_and_cost(
|
||||
client: TestClient,
|
||||
respx_mock: respx.MockRouter,
|
||||
|
|
@ -126,7 +126,7 @@ def test_proxy_decisions_dispatches_typesafe_deployment(
|
|||
upstream: Final = respx_mock.post("https://api.typesafe.ai/v1/systemone").respond(json=_RESPONSE)
|
||||
|
||||
response: Final = client.post(
|
||||
"/v1/decisions",
|
||||
"/v1/systemone",
|
||||
json={
|
||||
"model": "jev",
|
||||
"state": {"source": "proxy-test"},
|
||||
|
|
@ -165,7 +165,7 @@ def test_proxy_decisions_sends_the_env_key_to_the_deployment_api_base(
|
|||
monkeypatch.setattr(litellm.proxy.proxy_server, "llm_router", router)
|
||||
upstream: Final = respx_mock.post("https://egress.example/perplexity/v1/decisions").respond(json=_RESPONSE)
|
||||
|
||||
response: Final = client.post("/v1/decisions", json=_REQUEST)
|
||||
response: Final = client.post("/v1/systemone", json=_REQUEST)
|
||||
|
||||
assert response.status_code == 200, response.text
|
||||
assert upstream.call_count == 1
|
||||
|
|
@ -177,7 +177,7 @@ def test_proxy_decisions_unknown_model_is_a_client_error(
|
|||
respx_mock: respx.MockRouter,
|
||||
) -> None:
|
||||
response: Final = client.post(
|
||||
"/v1/decisions",
|
||||
"/v1/systemone",
|
||||
json={
|
||||
"model": "missing-model",
|
||||
"state": "review",
|
||||
|
|
@ -210,7 +210,7 @@ def test_proxy_decisions_missing_required_field_is_a_client_error(
|
|||
) -> None:
|
||||
upstream: Final = respx_mock.post("https://api.perplexity.ai/v1/decisions").respond(json=_RESPONSE)
|
||||
|
||||
response: Final = client.post("/v1/decisions", json=request_body)
|
||||
response: Final = client.post("/v1/systemone", json=request_body)
|
||||
|
||||
assert response.status_code == 400, response.text
|
||||
assert not upstream.called
|
||||
|
|
@ -238,7 +238,7 @@ def test_proxy_decisions_dispatches_strands_decider(
|
|||
upstream: Final = respx_mock.post("https://strands.example/v1/systemone").respond(json=_STRANDS_RESPONSE)
|
||||
|
||||
response: Final = client.post(
|
||||
"/v1/decisions",
|
||||
"/v1/systemone",
|
||||
json={
|
||||
"model": "strands",
|
||||
"state": {"source": "proxy-test"},
|
||||
|
|
@ -266,7 +266,7 @@ def test_proxy_decisions_without_model_uses_the_proxy_default_model(
|
|||
upstream: Final = respx_mock.post("https://api.perplexity.ai/v1/decisions").respond(json=_RESPONSE)
|
||||
|
||||
response: Final = client.post(
|
||||
"/v1/decisions", json={key: value for key, value in _REQUEST.items() if key != "model"}
|
||||
"/v1/systemone", json={key: value for key, value in _REQUEST.items() if key != "model"}
|
||||
)
|
||||
|
||||
assert response.status_code == 200, response.text
|
||||
|
|
@ -275,6 +275,152 @@ def test_proxy_decisions_without_model_uses_the_proxy_default_model(
|
|||
assert json.loads(upstream.calls[0].request.content)["model"] == "pplx-decider-v1-27b"
|
||||
|
||||
|
||||
_OPENAI_FORMAT_REQUEST: Final[Mapping[str, object]] = {
|
||||
"model": "decider",
|
||||
"input": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": [
|
||||
{"type": "input_text", "text": "The package arrived with a broken screen."},
|
||||
{"type": "input_text", "text": "I want a refund."},
|
||||
],
|
||||
},
|
||||
{"role": "user", "content": "Order 1234."},
|
||||
],
|
||||
"questions": [
|
||||
{"type": "predicate", "name": "damaged", "instructions": "Does the customer report a damaged item?"},
|
||||
{
|
||||
"type": "choice",
|
||||
"instructions": "Should we refund?",
|
||||
"choices": [{"value": True, "description": "Refund now"}, {"value": "escalate"}],
|
||||
},
|
||||
{
|
||||
"type": "score",
|
||||
"name": "severity",
|
||||
"instructions": "How severe is the issue?",
|
||||
"levels": [{"label": "minor"}, {"label": "major", "description": "Product unusable"}],
|
||||
},
|
||||
{"type": "predicate", "name": "fraud", "instructions": "Is this fraud?"},
|
||||
],
|
||||
"safety_identifier": "end-user-1",
|
||||
}
|
||||
_SYSTEMONE_ANSWERS_FOR_OPENAI_REQUEST: Final[Mapping[str, object]] = {
|
||||
"model": "pplx-decider-v1-27b",
|
||||
"answers": {
|
||||
"0": {"type": "noul", "noul": 0.95},
|
||||
"1": {"type": "choice", "choice": "true", "confidence": 0.8, "probabilities": {"true": 0.9, "escalate": 0.1}},
|
||||
"2": {
|
||||
"type": "score",
|
||||
"score": 0.7,
|
||||
"confidence": 0.6,
|
||||
"legend": {"0": "minor", "1": "major: Product unusable"},
|
||||
"probabilities": {"0": 0.3, "1": 0.7},
|
||||
},
|
||||
},
|
||||
"usage": {"input_tokens": _INPUT_TOKENS, "output_tokens": _OUTPUT_TOKENS},
|
||||
}
|
||||
|
||||
|
||||
@pytest.mark.parametrize("endpoint", ("/v1/decisions", "/decisions"))
|
||||
def test_openai_format_decisions_translate_through_systemone(
|
||||
client: TestClient,
|
||||
respx_mock: respx.MockRouter,
|
||||
endpoint: str,
|
||||
) -> None:
|
||||
upstream: Final = respx_mock.post("https://api.perplexity.ai/v1/decisions").respond(
|
||||
json=_SYSTEMONE_ANSWERS_FOR_OPENAI_REQUEST
|
||||
)
|
||||
|
||||
response: Final = client.post(endpoint, json=_OPENAI_FORMAT_REQUEST)
|
||||
|
||||
assert response.status_code == 200, response.text
|
||||
assert json.loads(upstream.calls[0].request.content) == {
|
||||
"model": "pplx-decider-v1-27b",
|
||||
"state": "The package arrived with a broken screen.\n\nI want a refund.\n\nOrder 1234.",
|
||||
"questions": {
|
||||
"0": {"type": "noul", "instructions": "Does the customer report a damaged item?"},
|
||||
"1": {
|
||||
"type": "choice",
|
||||
"instructions": "Should we refund?",
|
||||
"criteria": {"true": "Refund now", "escalate": None},
|
||||
},
|
||||
"2": {
|
||||
"type": "score",
|
||||
"instructions": "How severe is the issue?",
|
||||
"criteria": ["minor", "major: Product unusable"],
|
||||
},
|
||||
"3": {"type": "noul", "instructions": "Is this fraud?"},
|
||||
},
|
||||
}
|
||||
body: Final = response.json()
|
||||
assert body["model"] == _SYSTEMONE_ANSWERS_FOR_OPENAI_REQUEST["model"]
|
||||
assert body["answers"] == [
|
||||
{"type": "predicate", "name": "damaged", "probability": 0.95},
|
||||
{
|
||||
"type": "choice",
|
||||
"name": None,
|
||||
"choice": True,
|
||||
"probabilities": [{"value": True, "probability": 0.9}, {"value": "escalate", "probability": 0.1}],
|
||||
"confidence": 0.8,
|
||||
},
|
||||
{
|
||||
"type": "score",
|
||||
"name": "severity",
|
||||
"score": 0.7,
|
||||
"probabilities": [
|
||||
{"value": 0, "label": "minor", "probability": 0.3},
|
||||
{"value": 1, "label": "major", "probability": 0.7},
|
||||
],
|
||||
"confidence": 0.6,
|
||||
},
|
||||
{"type": "refusal", "name": "fraud"},
|
||||
]
|
||||
assert body["usage"] == {
|
||||
"input_tokens": _INPUT_TOKENS,
|
||||
"input_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0},
|
||||
"output_tokens": _OUTPUT_TOKENS,
|
||||
"output_tokens_details": {"reasoning_tokens": 0},
|
||||
"total_tokens": _INPUT_TOKENS + _OUTPUT_TOKENS,
|
||||
}
|
||||
assert float(response.headers["x-litellm-response-cost"]) > 0
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"request_body",
|
||||
(
|
||||
_REQUEST,
|
||||
{
|
||||
"model": "decider",
|
||||
"input": "review",
|
||||
"questions": [
|
||||
{
|
||||
"type": "choice",
|
||||
"instructions": "Pick one",
|
||||
"choices": [{"value": True}, {"value": "true"}],
|
||||
}
|
||||
],
|
||||
},
|
||||
{
|
||||
"model": "decider",
|
||||
"input": [{"role": "user", "content": [{"type": "input_image", "image_url": "data:image/png;base64,AA=="}]}],
|
||||
"questions": [{"type": "predicate", "instructions": "Is this a defect?"}],
|
||||
},
|
||||
),
|
||||
ids=("systemone_body", "colliding_choice_values", "image_input"),
|
||||
)
|
||||
def test_openai_format_decisions_rejects_bodies_it_cannot_translate(
|
||||
client: TestClient,
|
||||
respx_mock: respx.MockRouter,
|
||||
request_body: Mapping[str, object],
|
||||
) -> None:
|
||||
upstream: Final = respx_mock.post("https://api.perplexity.ai/v1/decisions").respond(json=_RESPONSE)
|
||||
|
||||
response: Final = client.post("/v1/decisions", json=request_body)
|
||||
|
||||
assert response.status_code == 400, response.text
|
||||
assert not upstream.called
|
||||
|
||||
|
||||
def _decisions_feature() -> LazyFeature:
|
||||
return next(feature for feature in LAZY_FEATURES if feature.name == "decisions")
|
||||
|
||||
|
|
@ -301,6 +447,8 @@ def test_a_config_pass_through_at_v1_decisions_keeps_its_route_and_the_native_ap
|
|||
assert client.post("/v1/decisions", json={"model": "gpt-6-luna"}).json() == {"served_by": "pass-through"}
|
||||
assert _serving_endpoint(bare, "/v1/decisions") is pass_through
|
||||
assert _serving_endpoint(bare, "/decisions") is decisions
|
||||
assert _serving_endpoint(bare, "/v1/systemone") is systemone
|
||||
assert _serving_endpoint(bare, "/systemone") is systemone
|
||||
|
||||
|
||||
def test_with_lazy_routes_disabled_a_config_pass_through_at_v1_decisions_still_wins(
|
||||
|
|
|
|||
|
|
@ -75,7 +75,7 @@ describe("SystemOneUI integration", () => {
|
|||
render(<SystemOneUI accessToken="session-key" />);
|
||||
screen.getByRole("combobox", { name: "Decision endpoint" }).focus();
|
||||
await user.keyboard("{ArrowDown}");
|
||||
await user.click(await screen.findByRole("option", { name: "Decisions · /v1/decisions" }));
|
||||
await user.click(await screen.findByRole("option", { name: "System One · /v1/systemone" }));
|
||||
|
||||
expect(screen.getByRole("note", { name: "Decision endpoint notice" })).toHaveTextContent(
|
||||
"omit model to use the proxy's configured default.",
|
||||
|
|
@ -162,7 +162,7 @@ describe("SystemOneUI integration", () => {
|
|||
render(<SystemOneUI accessToken="session-key" />);
|
||||
screen.getByRole("combobox", { name: "Decision endpoint" }).focus();
|
||||
await user.keyboard("{ArrowDown}");
|
||||
await user.click(await screen.findByRole("option", { name: "Decisions · /v1/decisions" }));
|
||||
await user.click(await screen.findByRole("option", { name: "System One · /v1/systemone" }));
|
||||
const editor = screen.getByRole("textbox", { name: "System One JSON payload" });
|
||||
const draft = JSON.stringify({
|
||||
model: "my-decider",
|
||||
|
|
@ -185,12 +185,12 @@ describe("SystemOneUI integration", () => {
|
|||
|
||||
screen.getByRole("combobox", { name: "Decision endpoint" }).focus();
|
||||
await user.keyboard("{ArrowDown}");
|
||||
await user.click(await screen.findByRole("option", { name: "Decisions · /v1/decisions" }));
|
||||
await user.click(await screen.findByRole("option", { name: "System One · /v1/systemone" }));
|
||||
expect(editor).toHaveValue(draft);
|
||||
expect(screen.queryByText("Selected choice")).not.toBeInTheDocument();
|
||||
await user.click(screen.getByRole("button", { name: "Send" }));
|
||||
expect(await screen.findByText("Selected choice")).toBeInTheDocument();
|
||||
expect(mockFetch.mock.calls[1]?.[0]).toMatch(/\/v1\/decisions$/);
|
||||
expect(mockFetch.mock.calls[1]?.[0]).toMatch(/\/v1\/systemone$/);
|
||||
expect(JSON.parse(mockFetch.mock.calls[1]?.[1]?.body as string)).toEqual(JSON.parse(draft));
|
||||
});
|
||||
|
||||
|
|
@ -199,7 +199,7 @@ describe("SystemOneUI integration", () => {
|
|||
render(<SystemOneUI accessToken="session-key" />);
|
||||
screen.getByRole("combobox", { name: "Decision endpoint" }).focus();
|
||||
await user.keyboard("{ArrowDown}");
|
||||
await user.click(await screen.findByRole("option", { name: "Decisions · /v1/decisions" }));
|
||||
await user.click(await screen.findByRole("option", { name: "System One · /v1/systemone" }));
|
||||
const payload = { state: "An outage", questions: { urgent: { type: "noul", instructions: "Is this urgent?" } } };
|
||||
fireEvent.change(screen.getByRole("textbox", { name: "System One JSON payload" }), {
|
||||
target: { value: JSON.stringify(payload) },
|
||||
|
|
@ -207,7 +207,7 @@ describe("SystemOneUI integration", () => {
|
|||
expect(screen.getByRole("button", { name: "Send" })).toBeEnabled();
|
||||
await user.click(screen.getByRole("button", { name: "Send" }));
|
||||
expect(await screen.findByText("jev-1.13.0")).toBeInTheDocument();
|
||||
expect(mockFetch.mock.calls[0]?.[0]).toMatch(/\/v1\/decisions$/);
|
||||
expect(mockFetch.mock.calls[0]?.[0]).toMatch(/\/v1\/systemone$/);
|
||||
const body = JSON.parse(mockFetch.mock.calls[0]?.[1]?.body as string);
|
||||
expect(body).toEqual(payload);
|
||||
expect(body).not.toHaveProperty("model");
|
||||
|
|
@ -227,7 +227,7 @@ describe("SystemOneUI integration", () => {
|
|||
await screen.findByRole("button", { name: "Cancel request" });
|
||||
screen.getByRole("combobox", { name: "Decision endpoint" }).focus();
|
||||
await user.keyboard("{ArrowDown}");
|
||||
await user.click(await screen.findByRole("option", { name: "Decisions · /v1/decisions" }));
|
||||
await user.click(await screen.findByRole("option", { name: "System One · /v1/systemone" }));
|
||||
expect(mockFetch.mock.calls[0]?.[1]?.signal?.aborted).toBe(true);
|
||||
expect(screen.getByRole("button", { name: "Send" })).toBeEnabled();
|
||||
|
||||
|
|
@ -249,7 +249,7 @@ describe("SystemOneUI integration", () => {
|
|||
await user.click(screen.getByRole("button", { name: "Send" }));
|
||||
expect(await screen.findByText("jev-1.13.0")).toBeInTheDocument();
|
||||
expect(screen.getByText("Selected choice")).toBeInTheDocument();
|
||||
expect(mockFetch.mock.calls[1]?.[0]).toMatch(/\/v1\/decisions$/);
|
||||
expect(mockFetch.mock.calls[1]?.[0]).toMatch(/\/v1\/systemone$/);
|
||||
expect(mockFetch).toHaveBeenCalledTimes(2);
|
||||
});
|
||||
|
||||
|
|
|
|||
|
|
@ -42,11 +42,11 @@ export default function SystemOneUI({ accessToken, disabledPersonalKeyCreation =
|
|||
const [customApiKey, setCustomApiKey] = useState("");
|
||||
const [endpoint, setEndpoint] = useState<DecisionEndpoint>("/typesafe/v1/systemone");
|
||||
const [payloads, setPayloads] = useState<Record<DecisionEndpoint, string>>({
|
||||
"/v1/decisions": DECISIONS_EXAMPLE_PAYLOAD,
|
||||
"/v1/systemone": DECISIONS_EXAMPLE_PAYLOAD,
|
||||
"/typesafe/v1/systemone": EXAMPLE_PAYLOAD,
|
||||
});
|
||||
const rawPayload = payloads[endpoint];
|
||||
const examplePayload = endpoint === "/v1/decisions" ? DECISIONS_EXAMPLE_PAYLOAD : EXAMPLE_PAYLOAD;
|
||||
const examplePayload = endpoint === "/v1/systemone" ? DECISIONS_EXAMPLE_PAYLOAD : EXAMPLE_PAYLOAD;
|
||||
const activeController = useRef<AbortController | null>(null);
|
||||
const validation = useMemo(() => validateSystemOnePayload(rawPayload, endpoint), [rawPayload, endpoint]);
|
||||
const effectiveApiKey = apiKeySource === "session" ? accessToken || "" : customApiKey.trim();
|
||||
|
|
@ -105,7 +105,7 @@ export default function SystemOneUI({ accessToken, disabledPersonalKeyCreation =
|
|||
<Select
|
||||
value={endpoint}
|
||||
onValueChange={(value) => {
|
||||
if (value === "/v1/decisions" || value === "/typesafe/v1/systemone") {
|
||||
if (value === "/v1/systemone" || value === "/typesafe/v1/systemone") {
|
||||
clearRequestState();
|
||||
setEndpoint(value);
|
||||
}
|
||||
|
|
@ -113,11 +113,11 @@ export default function SystemOneUI({ accessToken, disabledPersonalKeyCreation =
|
|||
>
|
||||
<SelectTrigger className="w-80" aria-label="Decision endpoint">
|
||||
<SelectValue>
|
||||
{endpoint === "/v1/decisions" ? "Decisions · /v1/decisions" : "TypeSafe · /typesafe/v1/systemone"}
|
||||
{endpoint === "/v1/systemone" ? "System One · /v1/systemone" : "TypeSafe · /typesafe/v1/systemone"}
|
||||
</SelectValue>
|
||||
</SelectTrigger>
|
||||
<SelectContent>
|
||||
<SelectItem value="/v1/decisions">Decisions · /v1/decisions</SelectItem>
|
||||
<SelectItem value="/v1/systemone">System One · /v1/systemone</SelectItem>
|
||||
<SelectItem value="/typesafe/v1/systemone">TypeSafe · /typesafe/v1/systemone</SelectItem>
|
||||
</SelectContent>
|
||||
</Select>
|
||||
|
|
@ -182,11 +182,11 @@ export default function SystemOneUI({ accessToken, disabledPersonalKeyCreation =
|
|||
<Alert role="note" aria-label="Decision endpoint notice">
|
||||
<Info />
|
||||
<AlertTitle>
|
||||
{endpoint === "/v1/decisions" ? "Decision models · Jev format" : "TypeSafe Jev · System One"}
|
||||
{endpoint === "/v1/systemone" ? "Decision models · System One" : "TypeSafe Jev · System One"}
|
||||
</AlertTitle>
|
||||
<AlertDescription>
|
||||
{endpoint === "/v1/decisions"
|
||||
? "Sends choice, noul, and score questions through /v1/decisions. Replace the example model with a decision model configured on your proxy, or omit model to use the proxy's configured default."
|
||||
{endpoint === "/v1/systemone"
|
||||
? "Sends choice, noul, and score questions through /v1/systemone. Replace the example model with a decision model configured on your proxy, or omit model to use the proxy's configured default."
|
||||
: "Sends requests through /typesafe/v1/systemone and requires TYPESAFE_API_KEY on the proxy."}{" "}
|
||||
<a href={DECISION_MODELS_DISCUSSION_URL} target="_blank" rel="noopener noreferrer" className="underline">
|
||||
Give us feedback on what you want for decision models
|
||||
|
|
|
|||
|
|
@ -12,7 +12,7 @@ const request = {
|
|||
},
|
||||
provider_option: { enabled: true },
|
||||
};
|
||||
const validate = (value: unknown) => validateSystemOnePayload(JSON.stringify(value), "/v1/decisions");
|
||||
const validate = (value: unknown) => validateSystemOnePayload(JSON.stringify(value), "/v1/systemone");
|
||||
|
||||
describe("native decisions validation", () => {
|
||||
it("accepts structured Jev criteria, optional instructions, and provider extensions without dropping fields", () => {
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
import { z } from "zod";
|
||||
|
||||
export type DecisionEndpoint = "/v1/decisions" | "/typesafe/v1/systemone";
|
||||
export type DecisionEndpoint = "/v1/systemone" | "/typesafe/v1/systemone";
|
||||
|
||||
const decisionsJson = z.union([z.string(), z.record(z.string(), z.unknown()), z.array(z.unknown())]);
|
||||
const decisionInstructions = decisionsJson.nullish();
|
||||
|
|
|
|||
|
|
@ -54,7 +54,7 @@ export function validateSystemOnePayload(
|
|||
return invalid("syntax", `Invalid JSON syntax: ${json.message}`);
|
||||
}
|
||||
|
||||
const schema = endpoint === "/v1/decisions" ? decisionsRequestSchema : systemOneRequestSchema;
|
||||
const schema = endpoint === "/v1/systemone" ? decisionsRequestSchema : systemOneRequestSchema;
|
||||
const result = schema.safeParse(json.value);
|
||||
if (!result.success) {
|
||||
return {
|
||||
|
|
|
|||
74
ui/litellm-dashboard/src/lib/http/schema.d.ts
generated
vendored
74
ui/litellm-dashboard/src/lib/http/schema.d.ts
generated
vendored
|
|
@ -16180,6 +16180,23 @@ export interface paths {
|
|||
patch?: never;
|
||||
trace?: never;
|
||||
};
|
||||
"/systemone": {
|
||||
parameters: {
|
||||
query?: never;
|
||||
header?: never;
|
||||
path?: never;
|
||||
cookie?: never;
|
||||
};
|
||||
get?: never;
|
||||
put?: never;
|
||||
/** Systemone */
|
||||
post: operations["systemone_systemone_post"];
|
||||
delete?: never;
|
||||
options?: never;
|
||||
head?: never;
|
||||
patch?: never;
|
||||
trace?: never;
|
||||
};
|
||||
"/tag/daily/activity": {
|
||||
parameters: {
|
||||
query?: never;
|
||||
|
|
@ -22291,6 +22308,23 @@ export interface paths {
|
|||
patch?: never;
|
||||
trace?: never;
|
||||
};
|
||||
"/v1/systemone": {
|
||||
parameters: {
|
||||
query?: never;
|
||||
header?: never;
|
||||
path?: never;
|
||||
cookie?: never;
|
||||
};
|
||||
get?: never;
|
||||
put?: never;
|
||||
/** Systemone */
|
||||
post: operations["systemone_v1_systemone_post"];
|
||||
delete?: never;
|
||||
options?: never;
|
||||
head?: never;
|
||||
patch?: never;
|
||||
trace?: never;
|
||||
};
|
||||
"/v1/threads": {
|
||||
parameters: {
|
||||
query?: never;
|
||||
|
|
@ -72513,6 +72547,26 @@ export interface operations {
|
|||
};
|
||||
};
|
||||
};
|
||||
systemone_systemone_post: {
|
||||
parameters: {
|
||||
query?: never;
|
||||
header?: never;
|
||||
path?: never;
|
||||
cookie?: never;
|
||||
};
|
||||
requestBody?: never;
|
||||
responses: {
|
||||
/** @description Successful Response */
|
||||
200: {
|
||||
headers: {
|
||||
[name: string]: unknown;
|
||||
};
|
||||
content: {
|
||||
"application/json": unknown;
|
||||
};
|
||||
};
|
||||
};
|
||||
};
|
||||
get_tag_daily_activity_tag_daily_activity_get: {
|
||||
parameters: {
|
||||
query?: {
|
||||
|
|
@ -80787,6 +80841,26 @@ export interface operations {
|
|||
};
|
||||
};
|
||||
};
|
||||
systemone_v1_systemone_post: {
|
||||
parameters: {
|
||||
query?: never;
|
||||
header?: never;
|
||||
path?: never;
|
||||
cookie?: never;
|
||||
};
|
||||
requestBody?: never;
|
||||
responses: {
|
||||
/** @description Successful Response */
|
||||
200: {
|
||||
headers: {
|
||||
[name: string]: unknown;
|
||||
};
|
||||
content: {
|
||||
"application/json": unknown;
|
||||
};
|
||||
};
|
||||
};
|
||||
};
|
||||
create_threads_v1_threads_post: {
|
||||
parameters: {
|
||||
query?: never;
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue