diff --git a/litellm/cost_calculator.py b/litellm/cost_calculator.py index 37a79e2f6d4..457baddd232 100644 --- a/litellm/cost_calculator.py +++ b/litellm/cost_calculator.py @@ -557,9 +557,10 @@ def cost_per_token( ) elif call_type == "atranscription" or call_type == "transcription": if _transcription_usage_has_token_details(usage_block): - return openai_cost_per_token( + return generic_cost_per_token( model=model_without_prefix, usage=usage_block, + custom_llm_provider=custom_llm_provider, service_tier=service_tier, data_residency=data_residency, ) diff --git a/litellm/litellm_core_utils/realtime_streaming.py b/litellm/litellm_core_utils/realtime_streaming.py index 10056d64a20..2da63554b75 100644 --- a/litellm/litellm_core_utils/realtime_streaming.py +++ b/litellm/litellm_core_utils/realtime_streaming.py @@ -955,6 +955,7 @@ class RealTimeStreaming: transcript = event.get("transcript", "") self._collect_user_input_from_backend_event(cast(dict, event)) self.store_message(event_str) + self._capture_transcription_usage(event) await self._send_event_to_client(event, event_str) blocked = await self.run_realtime_guardrails( cast(str, transcript), diff --git a/litellm/llms/gemini/audio_transcription/__init__.py b/litellm/llms/gemini/audio_transcription/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/litellm/llms/gemini/audio_transcription/transformation.py b/litellm/llms/gemini/audio_transcription/transformation.py new file mode 100644 index 00000000000..8b7733fa3c8 --- /dev/null +++ b/litellm/llms/gemini/audio_transcription/transformation.py @@ -0,0 +1,250 @@ +import base64 +from collections.abc import Mapping, Sequence +from typing import Final + +from httpx import Headers, Response + +from litellm.litellm_core_utils.audio_utils.utils import ( + normalize_transcription_language_to_bcp47, + process_audio_file, +) +from litellm.llms.base_llm.audio_transcription.transformation import ( + AudioTranscriptionRequestData, + BaseAudioTranscriptionConfig, +) +from litellm.llms.base_llm.chat.transformation import BaseLLMException +from litellm.llms.gemini.common_utils import GeminiError, GeminiModelInfo +from litellm.types.llms.gemini_audio_transcription import ( + GeminiTranscriptionAudioInput, + GeminiTranscriptionConfig, + GeminiTranscriptionInteractionRequest, + GeminiTranscriptionInteractionResponse, + GeminiTranscriptionWordAnnotation, +) +from litellm.types.llms.openai import ( + AllMessageValues, + OpenAIAudioTranscriptionOptionalParams, +) +from litellm.types.utils import ( + FileTypes, + TranscriptionResponse, + TranscriptionUsageInputTokenDetailsObject, + TranscriptionUsageTokensObject, +) + +INTERACTIONS_API_REVISION: Final = "2026-05-20" +WORD_INFO_ANNOTATION_TYPE: Final = "word_info" + + +class GeminiAudioTranscriptionConfig(BaseAudioTranscriptionConfig): + """ + Maps OpenAI /v1/audio/transcriptions onto the Gemini Interactions API + (POST /v1beta/interactions) for transcription models like + gemini-3.5-transcribe. https://ai.google.dev/gemini-api/docs/transcribe + """ + + def get_supported_openai_params( + self, model: str + ) -> list[OpenAIAudioTranscriptionOptionalParams]: # mutable-ok: BaseAudioTranscriptionConfig signature + return ["language", "response_format", "timestamp_granularities"] # mutable-ok: base contract returns a list + + def map_openai_params( + self, + non_default_params: Mapping[str, object], + optional_params: Mapping[str, object], + model: str, + drop_params: bool, + ) -> dict: # mutable-ok: BaseAudioTranscriptionConfig signature + supported_params: Final = frozenset(self.get_supported_openai_params(model)) + accepted: Final = tuple((k, v) for k, v in non_default_params.items() if k in supported_params) + return dict((*optional_params.items(), *accepted)) # mutable-ok: base contract returns a plain dict + + def get_error_class( + self, + error_message: str, + status_code: int, + headers: dict | Headers, # mutable-ok: base signature and BaseLLMException take dict | Headers + ) -> BaseLLMException: + return GeminiError(status_code=status_code, message=error_message, headers=headers) + + def validate_environment( + self, + headers: Mapping[str, str], + model: str, + messages: Sequence[AllMessageValues], + optional_params: Mapping[str, object], + litellm_params: Mapping[str, object], + api_key: str | None = None, + api_base: str | None = None, + ) -> dict: # mutable-ok: BaseAudioTranscriptionConfig signature + resolved_api_key: Final = GeminiModelInfo.get_api_key(api_key) + if not resolved_api_key: + raise GeminiError( + status_code=401, + message="Google API key is required. Set GOOGLE_API_KEY or GEMINI_API_KEY environment variable.", + ) + return { # mutable-ok: the http handler passes these headers straight to httpx + **headers, + "Content-Type": "application/json", + "x-goog-api-key": resolved_api_key, + "Api-Revision": INTERACTIONS_API_REVISION, + } + + def get_complete_url( + self, + api_base: str | None, + api_key: str | None, + model: str, + optional_params: Mapping[str, object], + litellm_params: Mapping[str, object], + stream: bool | None = None, + ) -> str: + resolved_api_base: Final = GeminiModelInfo.get_api_base(api_base) + return f"{resolved_api_base}/v1beta/interactions" + + def transform_audio_transcription_request( + self, + model: str, + audio_file: FileTypes, + optional_params: Mapping[str, object], + litellm_params: Mapping[str, object], + ) -> AudioTranscriptionRequestData: + processed_audio: Final = process_audio_file(audio_file) + audio_input: Final = GeminiTranscriptionAudioInput( + type="audio", + data=base64.b64encode(processed_audio.file_content).decode("utf-8"), + mime_type=processed_audio.content_type, + ) + request: Final = _build_interaction_request( + model=model, + audio_input=audio_input, + transcription_config=_build_transcription_config(optional_params), + ) + return AudioTranscriptionRequestData(data=dict(request)) # mutable-ok: AudioTranscriptionRequestData wants dict + + def transform_audio_transcription_response( + self, + raw_response: Response, + ) -> TranscriptionResponse: + try: + response_json: Final = raw_response.json() + except ValueError: + raise GeminiError( + status_code=raw_response.status_code, + message=f"Received non-JSON response from Gemini Interactions API: {raw_response.text}", + ) + parsed: Final = GeminiTranscriptionInteractionResponse.model_validate(response_json) + if parsed.status != "completed": + raise GeminiError( + status_code=raw_response.status_code, + message=f"Gemini transcription interaction did not complete (status={parsed.status}): {raw_response.text}", + ) + text_contents: Final = tuple( + content + for step in parsed.steps + for content in step.content + if content.type == "text" and content.text is not None + ) + response: Final = TranscriptionResponse(text=" ".join(content.text or "" for content in text_contents)) + response["task"] = "transcribe" + words: Final = tuple( + word + for content in text_contents + for annotation in content.annotations + if (word := _annotation_to_word(annotation)) is not None + ) + if words: + response["words"] = list(words) # mutable-ok: verbose_json words is a JSON array + last_word_end: Final = words[-1].get("end") + if last_word_end is not None: + response["duration"] = last_word_end + if parsed.usage is not None: + audio_tokens: Final = sum( + by_modality.tokens + for by_modality in parsed.usage.input_tokens_by_modality + if by_modality.modality == "audio" + ) + response.usage = TranscriptionUsageTokensObject( + type="tokens", + input_tokens=parsed.usage.total_input_tokens, + output_tokens=parsed.usage.total_output_tokens, + total_tokens=parsed.usage.total_tokens, + input_token_details=TranscriptionUsageInputTokenDetailsObject( + audio_tokens=audio_tokens, + text_tokens=parsed.usage.total_input_tokens - audio_tokens, + ), + ) + return response + + +_EMPTY_TRANSCRIPTION_CONFIG: Final[GeminiTranscriptionConfig] = {} +_WORD_TIMESTAMP_CONFIG: Final[GeminiTranscriptionConfig] = { + "mode": { + "type": "verbatim", + "timestamp_granularities": ("word",), + "diarization_mode": "speaker", + }, +} + + +def _build_interaction_request( + model: str, + audio_input: GeminiTranscriptionAudioInput, + transcription_config: GeminiTranscriptionConfig, +) -> GeminiTranscriptionInteractionRequest: + if not transcription_config: + bare_request: Final[GeminiTranscriptionInteractionRequest] = { + "model": model.removeprefix("gemini/"), + "input": (audio_input,), + } + return bare_request + configured_request: Final[GeminiTranscriptionInteractionRequest] = { + "model": model.removeprefix("gemini/"), + "input": (audio_input,), + "generation_config": {"transcription_config": transcription_config}, + } + return configured_request + + +def _language_config(language: object) -> GeminiTranscriptionConfig: + if not isinstance(language, str) or not language: + return _EMPTY_TRANSCRIPTION_CONFIG + language_config: Final[GeminiTranscriptionConfig] = { + "language_codes": (normalize_transcription_language_to_bcp47(language),), + } + return language_config + + +def _timestamp_config(timestamp_granularities: object) -> GeminiTranscriptionConfig: + if isinstance(timestamp_granularities, list) and "word" in timestamp_granularities: + return _WORD_TIMESTAMP_CONFIG + return _EMPTY_TRANSCRIPTION_CONFIG + + +def _build_transcription_config(optional_params: Mapping[str, object]) -> GeminiTranscriptionConfig: + transcription_config: Final[GeminiTranscriptionConfig] = { + **_language_config(optional_params.get("language")), + **_timestamp_config(optional_params.get("timestamp_granularities")), + } + return transcription_config + + +def _annotation_to_word(annotation: GeminiTranscriptionWordAnnotation) -> Mapping[str, str | float] | None: + if annotation.type != WORD_INFO_ANNOTATION_TYPE or annotation.text is None: + return None + entries: Final = ( + ("word", annotation.text), + ("start", _parse_offset_seconds(annotation.start_offset)), + ("end", _parse_offset_seconds(annotation.end_offset)), + ("speaker", annotation.speaker), + ) + return {key: value for key, value in entries if value is not None} # mutable-ok: word entries serialize to JSON + + +def _parse_offset_seconds(offset: str | None) -> float | None: + if offset is None or not offset.endswith("s"): + return None + try: + return float(offset[:-1]) + except ValueError: + return None diff --git a/litellm/llms/gemini/realtime/transformation.py b/litellm/llms/gemini/realtime/transformation.py index 51801e91356..a3b6381306e 100644 --- a/litellm/llms/gemini/realtime/transformation.py +++ b/litellm/llms/gemini/realtime/transformation.py @@ -4,7 +4,7 @@ This file contains the transformation logic for the Gemini realtime API. import json from collections import OrderedDict -from collections.abc import Mapping +from collections.abc import Mapping, Sequence from typing import Any, Final, cast import litellm @@ -53,6 +53,7 @@ from litellm.types.llms.vertex_ai import ( ) from litellm.types.realtime import ( ALL_DELTA_TYPES, + RealtimeInputAudioTranscriptionUsage, RealtimeModalityResponseTransformOutput, RealtimeResponseTransformInput, RealtimeResponseTypedDict, @@ -95,6 +96,18 @@ def _gemini_live_speech_config(voice: object) -> Mapping[str, object] | None: return VertexGeminiConfig()._map_audio_params({"voice": voice}) +# Google bills Live transcription at an estimated 25 audio tokens/sec of input and +# 175 text tokens/min of output (ai.google.dev/gemini-api/docs/pricing). +GEMINI_LIVE_TRANSCRIBE_AUDIO_TOKENS_PER_SECOND: Final = 25 +GEMINI_LIVE_TRANSCRIBE_OUTPUT_TEXT_TOKENS_PER_MINUTE: Final = 175 +PCM16_INPUT_AUDIO_BYTES_PER_SECOND: Final = 48000 + + +def _base64_decoded_byte_count(data: str) -> int: + padding: Final = 2 if data.endswith("==") else 1 if data.endswith("=") else 0 + return max(len(data) * 3 // 4 - padding, 0) + + class GeminiRealtimeConfig(BaseRealtimeConfig): _TOOL_CALL_ID_TO_NAME_MAX = 256 # LRU cap for call_id→name mapping @@ -104,6 +117,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): # Gemini Live sometimes emits usageMetadata in a standalone frame between # turns; buffer it here so the next response.done carries the token counts. self._pending_usage_metadata: dict | None = None + self._unbilled_input_audio_bytes: int = 0 def is_setup_message(self, msg_obj: dict) -> bool: return "setup" in msg_obj @@ -384,17 +398,25 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): return bool(entry.get("gemini_native_audio") or entry.get("gemini_audio_only_live")) @staticmethod - def _coerce_response_modalities(model: str, modalities: list[Any]) -> list[str]: - """Map unsupported TEXT responseModalities to AUDIO for audio-only Live models.""" - normalized: Final = [ + def _is_text_only_live_model(model: str) -> bool: + return GeminiRealtimeConfig._model_cost_entry(model).get("mode") == "audio_transcription" + + @staticmethod + def _default_response_modality(model: str) -> GeminiResponseModalities: + return "TEXT" if GeminiRealtimeConfig._is_text_only_live_model(model) else "AUDIO" + + @staticmethod + def _coerce_response_modalities(model: str, modalities: Sequence[Any]) -> tuple[str, ...]: + """Swap responseModalities a Live model cannot produce: TEXT to AUDIO for + audio-only models, AUDIO to TEXT for text-only ones (e.g. transcribe-live).""" + normalized: Final = tuple( modality.upper() if isinstance(modality, str) else str(modality).upper() for modality in modalities - ] - if not GeminiRealtimeConfig._is_audio_only_live_model(model): - return normalized - if "TEXT" not in normalized: - return normalized - without_text: Final = [modality for modality in normalized if modality != "TEXT"] - return without_text if without_text else ["AUDIO"] + ) + if GeminiRealtimeConfig._is_audio_only_live_model(model) and "TEXT" in normalized: + return tuple(modality for modality in normalized if modality != "TEXT") or ("AUDIO",) + if GeminiRealtimeConfig._is_text_only_live_model(model) and "AUDIO" in normalized: + return tuple(modality for modality in normalized if modality != "AUDIO") or ("TEXT",) + return normalized @staticmethod def _finalize_gemini_live_setup(model: str, setup: dict[str, Any]) -> dict[str, Any]: @@ -436,7 +458,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): if session_configuration_request is None: generation_config: Final = new_overrides.setdefault("generationConfig", {}) - generation_config.setdefault("responseModalities", ["AUDIO"]) + generation_config.setdefault("responseModalities", [GeminiRealtimeConfig._default_response_modality(model)]) new_overrides.setdefault("inputAudioTranscription", {}) new_overrides["model"] = f"models/{model}" verbose_logger.debug("Gemini Realtime: Sending initial setup with tools to backend") @@ -558,9 +580,10 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): return self._handle_conversation_item(json_message) if msg_type == "input_audio_buffer.append": - realtime_input_dict["audio"] = HttpxBlobType( - mimeType=self.get_audio_mime_type(), data=json_message["audio"] - ) + audio_b64: Final = json_message["audio"] + if isinstance(audio_b64, str): + self._unbilled_input_audio_bytes += _base64_decoded_byte_count(audio_b64) + realtime_input_dict["audio"] = HttpxBlobType(mimeType=self.get_audio_mime_type(), data=audio_b64) realtime_input_dict = cast( BidiGenerateContentRealtimeInput, @@ -1151,6 +1174,23 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): raise ValueError(f"Unknown openai event: {key}, value: {value}") return openai_event + def _consume_input_transcription_usage_estimate(self, model: str) -> RealtimeInputAudioTranscriptionUsage | None: + """Gemini Live sends no usageMetadata for transcribe sessions; estimate billing from streamed audio duration.""" + if self._unbilled_input_audio_bytes <= 0 or not self._is_text_only_live_model(model): + return None + audio_seconds: Final = self._unbilled_input_audio_bytes / PCM16_INPUT_AUDIO_BYTES_PER_SECOND + self._unbilled_input_audio_bytes = 0 + audio_tokens: Final = round(audio_seconds * GEMINI_LIVE_TRANSCRIBE_AUDIO_TOKENS_PER_SECOND) + output_tokens: Final = round(audio_seconds * GEMINI_LIVE_TRANSCRIBE_OUTPUT_TEXT_TOKENS_PER_MINUTE / 60) + usage: Final[RealtimeInputAudioTranscriptionUsage] = { + "type": "tokens", + "input_tokens": audio_tokens, + "output_tokens": output_tokens, + "total_tokens": audio_tokens + output_tokens, + "input_token_details": {"text_tokens": 0, "audio_tokens": audio_tokens}, + } + return usage + def transform_realtime_response( self, message: str | bytes, @@ -1190,6 +1230,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): if isinstance(server_content, dict): input_tx: Final = server_content.get("inputTranscription") if isinstance(input_tx, dict) and input_tx.get("text"): + transcription_usage: Final = self._consume_input_transcription_usage_estimate(model) returned_message.append( cast( OpenAIRealtimeEvents, @@ -1199,6 +1240,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): "transcript": input_tx["text"], "item_id": f"item_{uuid.uuid4()}", "content_index": 0, + **({} if transcription_usage is None else {"usage": transcription_usage}), }, ) ) @@ -1235,6 +1277,12 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): ) ) + # Transcription-only models emit generationComplete with no prior + # modelTurn delta; there is no started OpenAI response to close, so + # drop it and let siblings (turnComplete, usageMetadata) process. + if current_delta_type is None and "modelTurn" not in server_content: + server_content.pop("generationComplete", None) + # Mark transcription-only serverContent as handled so the main loop # skips it; sibling keys like toolCall are still processed below. _model_content_keys: Final = { @@ -1583,7 +1631,9 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): ``` """ - response_modalities: Final[list[GeminiResponseModalities]] = ["AUDIO"] + response_modalities: Final[list[GeminiResponseModalities]] = [ + GeminiRealtimeConfig._default_response_modality(model) + ] output_audio_transcription: Final = False # if "audio" in model: ## UNCOMMENT THIS WHEN AUDIO IS SUPPORTED # output_audio_transcription = True diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index dd367e875de..7f5e41d45ce 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -51340,6 +51340,47 @@ "supports_audio_output": true, "tpm": 250000 }, + "gemini/gemini-3.5-transcribe": { + "input_cost_per_audio_token": 2e-06, + "input_cost_per_token": 2e-06, + "litellm_provider": "gemini", + "mode": "audio_transcription", + "output_cost_per_token": 1.2e-05, + "source": "https://ai.google.dev/gemini-api/docs/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ], + "supported_modalities": [ + "text", + "audio" + ], + "supported_output_modalities": [ + "text" + ], + "supports_audio_input": true, + "tpm": 800000, + "rpm": 2000 + }, + "gemini/gemini-3.5-transcribe-live": { + "input_cost_per_audio_token": 3.5e-06, + "input_cost_per_token": 3.5e-06, + "litellm_provider": "gemini", + "mode": "audio_transcription", + "output_cost_per_token": 2.1e-05, + "source": "https://ai.google.dev/gemini-api/docs/pricing", + "supported_endpoints": [ + "/v1/realtime" + ], + "supported_modalities": [ + "audio" + ], + "supported_output_modalities": [ + "text" + ], + "supports_audio_input": true, + "tpm": 250000, + "rpm": 10 + }, "perplexity/pplx-embed-context-v1-0.6b": { "input_cost_per_token": 8e-09, "litellm_provider": "perplexity", diff --git a/litellm/types/llms/gemini_audio_transcription.py b/litellm/types/llms/gemini_audio_transcription.py new file mode 100644 index 00000000000..cb12e0f45b8 --- /dev/null +++ b/litellm/types/llms/gemini_audio_transcription.py @@ -0,0 +1,81 @@ +from typing import Literal, Required + +from pydantic import BaseModel, ConfigDict +from typing_extensions import ReadOnly, TypedDict + + +class GeminiTranscriptionAudioInput(TypedDict): + type: ReadOnly[Literal["audio"]] + data: ReadOnly[str] + mime_type: ReadOnly[str] + + +class GeminiTranscriptionVerbatimMode(TypedDict, total=False): + type: ReadOnly[Required[Literal["verbatim"]]] + timestamp_granularities: ReadOnly[tuple[Literal["word"], ...]] + diarization_mode: ReadOnly[Literal["speaker"]] + + +class GeminiTranscriptionConfig(TypedDict, total=False): + language_codes: ReadOnly[tuple[str, ...]] + mode: ReadOnly[GeminiTranscriptionVerbatimMode] + + +class GeminiTranscriptionGenerationConfig(TypedDict): + transcription_config: ReadOnly[GeminiTranscriptionConfig] + + +class GeminiTranscriptionInteractionRequest(TypedDict, total=False): + model: ReadOnly[Required[str]] + input: ReadOnly[Required[tuple[GeminiTranscriptionAudioInput, ...]]] + generation_config: ReadOnly[GeminiTranscriptionGenerationConfig] + + +class GeminiTranscriptionWordAnnotation(BaseModel): + model_config = ConfigDict(extra="ignore") + + type: str | None = None + text: str | None = None + speaker: str | None = None + start_offset: str | None = None + end_offset: str | None = None + + +class GeminiTranscriptionContent(BaseModel): + model_config = ConfigDict(extra="ignore") + + type: str | None = None + text: str | None = None + annotations: tuple[GeminiTranscriptionWordAnnotation, ...] = () + + +class GeminiTranscriptionStep(BaseModel): + model_config = ConfigDict(extra="ignore") + + type: str | None = None + content: tuple[GeminiTranscriptionContent, ...] = () + + +class GeminiTranscriptionModalityTokens(BaseModel): + model_config = ConfigDict(extra="ignore") + + modality: str | None = None + tokens: int = 0 + + +class GeminiTranscriptionUsage(BaseModel): + model_config = ConfigDict(extra="ignore") + + total_tokens: int = 0 + total_input_tokens: int = 0 + total_output_tokens: int = 0 + input_tokens_by_modality: tuple[GeminiTranscriptionModalityTokens, ...] = () + + +class GeminiTranscriptionInteractionResponse(BaseModel): + model_config = ConfigDict(extra="ignore") + + id: str | None = None + status: str | None = None + usage: GeminiTranscriptionUsage | None = None + steps: tuple[GeminiTranscriptionStep, ...] = () diff --git a/litellm/types/realtime.py b/litellm/types/realtime.py index cbd7a8b7ecb..17dc70126f3 100644 --- a/litellm/types/realtime.py +++ b/litellm/types/realtime.py @@ -162,3 +162,16 @@ class RealtimeErrorDetail(TypedDict): class RealtimeErrorEvent(TypedDict): type: ReadOnly[Literal["error"]] error: ReadOnly[RealtimeErrorDetail] + + +class RealtimeInputAudioTranscriptionUsageInputTokenDetails(TypedDict): + text_tokens: ReadOnly[int] + audio_tokens: ReadOnly[int] + + +class RealtimeInputAudioTranscriptionUsage(TypedDict): + type: ReadOnly[Literal["tokens"]] + input_tokens: ReadOnly[int] + output_tokens: ReadOnly[int] + total_tokens: ReadOnly[int] + input_token_details: ReadOnly[RealtimeInputAudioTranscriptionUsageInputTokenDetails] diff --git a/litellm/utils.py b/litellm/utils.py index 54f97ccae54..a26b2c5b440 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -8503,6 +8503,12 @@ class ProviderConfigManager: ) return VertexAIAudioTranscriptionConfig() + elif litellm.LlmProviders.GEMINI == provider: + from litellm.llms.gemini.audio_transcription.transformation import ( + GeminiAudioTranscriptionConfig, + ) + + return GeminiAudioTranscriptionConfig() return None @staticmethod diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index dd367e875de..7f5e41d45ce 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -51340,6 +51340,47 @@ "supports_audio_output": true, "tpm": 250000 }, + "gemini/gemini-3.5-transcribe": { + "input_cost_per_audio_token": 2e-06, + "input_cost_per_token": 2e-06, + "litellm_provider": "gemini", + "mode": "audio_transcription", + "output_cost_per_token": 1.2e-05, + "source": "https://ai.google.dev/gemini-api/docs/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ], + "supported_modalities": [ + "text", + "audio" + ], + "supported_output_modalities": [ + "text" + ], + "supports_audio_input": true, + "tpm": 800000, + "rpm": 2000 + }, + "gemini/gemini-3.5-transcribe-live": { + "input_cost_per_audio_token": 3.5e-06, + "input_cost_per_token": 3.5e-06, + "litellm_provider": "gemini", + "mode": "audio_transcription", + "output_cost_per_token": 2.1e-05, + "source": "https://ai.google.dev/gemini-api/docs/pricing", + "supported_endpoints": [ + "/v1/realtime" + ], + "supported_modalities": [ + "audio" + ], + "supported_output_modalities": [ + "text" + ], + "supports_audio_input": true, + "tpm": 250000, + "rpm": 10 + }, "perplexity/pplx-embed-context-v1-0.6b": { "input_cost_per_token": 8e-09, "litellm_provider": "perplexity", diff --git a/tests/test_litellm/litellm_core_utils/test_realtime_streaming.py b/tests/test_litellm/litellm_core_utils/test_realtime_streaming.py index 61b63e2b917..1b71c2f1f9b 100644 --- a/tests/test_litellm/litellm_core_utils/test_realtime_streaming.py +++ b/tests/test_litellm/litellm_core_utils/test_realtime_streaming.py @@ -2957,3 +2957,65 @@ async def test_log_messages_routes_async_logging_through_bounded_worker(): logging_obj.success_handler.assert_not_called() # the bare create_task path must no longer be used for success logging mock_create_task.assert_not_called() + + +@pytest.mark.asyncio +async def test_provider_config_path_captures_transcription_usage(): + """A transcription.completed event with usage from the provider transform must + land in the logged messages so realtime cost calculation can bill it.""" + from typing import Final + + from litellm.types.realtime import RealtimeInputAudioTranscriptionUsage, RealtimeResponseTypedDict + + client_ws: Final = MagicMock() + client_ws.send_text = AsyncMock() + backend_ws: Final = MagicMock() + backend_ws.send = AsyncMock() + logging_obj: Final = MagicMock() + + usage: Final[RealtimeInputAudioTranscriptionUsage] = { + "type": "tokens", + "input_tokens": 50, + "output_tokens": 6, + "total_tokens": 56, + "input_token_details": {"text_tokens": 0, "audio_tokens": 50}, + } + transform_output: Final[RealtimeResponseTypedDict] = { + "response": { + "type": "conversation.item.input_audio_transcription.completed", + "event_id": "event_1", + "transcript": "ahoy", + "item_id": "item_1", + "content_index": 0, + "usage": usage, + }, + "current_output_item_id": None, + "current_response_id": None, + "current_delta_chunks": None, + "current_conversation_id": None, + "current_item_chunks": None, + "current_delta_type": None, + "session_configuration_request": None, + } + provider_config: Final = MagicMock() + provider_config.transform_realtime_request = MagicMock(return_value=()) + provider_config.transform_realtime_response = MagicMock(return_value=transform_output) + + streaming: Final = RealTimeStreaming( + client_ws, + backend_ws, + logging_obj, + provider_config=provider_config, + model="gemini-3.5-transcribe-live", + ) + + await streaming._handle_provider_config_message("{}") + + usage_events: Final = tuple( + message + for message in streaming.messages + if isinstance(message, dict) + and message.get("type") == "conversation.item.input_audio_transcription.completed" + and message.get("usage") == usage + ) + assert len(usage_events) == 1 diff --git a/tests/test_litellm/llms/gemini/audio_transcription/__init__.py b/tests/test_litellm/llms/gemini/audio_transcription/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/test_litellm/llms/gemini/audio_transcription/test_gemini_audio_transcription_transformation.py b/tests/test_litellm/llms/gemini/audio_transcription/test_gemini_audio_transcription_transformation.py new file mode 100644 index 00000000000..fef037974a7 --- /dev/null +++ b/tests/test_litellm/llms/gemini/audio_transcription/test_gemini_audio_transcription_transformation.py @@ -0,0 +1,248 @@ +import base64 +import json + +import httpx +import pytest + + +import litellm +from litellm.llms.gemini.audio_transcription.transformation import ( + GeminiAudioTranscriptionConfig, +) +from litellm.llms.gemini.common_utils import GeminiError +from litellm.types.utils import LlmProviders +from litellm.utils import ProviderConfigManager + +AUDIO_BYTES = b"RIFF....WAVEfmt fake-wav-bytes" + +COMPLETED_RESPONSE = { + "id": "v1_abc123", + "status": "completed", + "usage": { + "total_tokens": 200, + "total_input_tokens": 200, + "input_tokens_by_modality": [ + {"modality": "text", "tokens": 1}, + {"modality": "audio", "tokens": 199}, + ], + "total_output_tokens": 0, + }, + "steps": [ + { + "type": "model_generation", + "content": [ + { + "type": "text", + "text": "Hello world.", + "annotations": [ + { + "type": "word_info", + "text": "Hello", + "speaker": "spk:0", + "start_offset": "0.100s", + "end_offset": "0.400s", + }, + { + "type": "word_info", + "text": "world.", + "speaker": "spk:1", + "start_offset": "0.500s", + "end_offset": "0.900s", + }, + ], + } + ], + } + ], +} + + +def make_response(payload): + return httpx.Response(200, json=payload, request=httpx.Request("POST", "https://example.test")) + + +@pytest.fixture +def config(): + return GeminiAudioTranscriptionConfig() + + +def test_provider_config_manager_returns_gemini_config(): + provider_config = ProviderConfigManager.get_provider_audio_transcription_config( + model="gemini-3.5-transcribe", provider=LlmProviders.GEMINI + ) + assert isinstance(provider_config, GeminiAudioTranscriptionConfig) + + +class TestValidateEnvironment: + def test_sets_api_key_and_revision_headers(self, config): + headers = config.validate_environment( + headers={}, + model="gemini-3.5-transcribe", + messages=[], + optional_params={}, + litellm_params={}, + api_key="test-key", + ) + assert headers["x-goog-api-key"] == "test-key" + assert headers["Api-Revision"] == "2026-05-20" + assert headers["Content-Type"] == "application/json" + + def test_missing_api_key_raises(self, config, monkeypatch): + monkeypatch.delenv("GOOGLE_API_KEY", raising=False) + monkeypatch.delenv("GEMINI_API_KEY", raising=False) + with pytest.raises(GeminiError) as excinfo: + config.validate_environment( + headers={}, + model="gemini-3.5-transcribe", + messages=[], + optional_params={}, + litellm_params={}, + ) + assert excinfo.value.status_code == 401 + + +class TestGetCompleteUrl: + def test_defaults_to_interactions_endpoint(self, config): + url = config.get_complete_url( + api_base=None, + api_key=None, + model="gemini-3.5-transcribe", + optional_params={}, + litellm_params={}, + ) + assert url == "https://generativelanguage.googleapis.com/v1beta/interactions" + + def test_api_base_override(self, config): + url = config.get_complete_url( + api_base="http://localhost:8080", + api_key=None, + model="gemini-3.5-transcribe", + optional_params={}, + litellm_params={}, + ) + assert url == "http://localhost:8080/v1beta/interactions" + + +class TestTransformRequest: + def test_builds_json_interaction_request(self, config): + request_data = config.transform_audio_transcription_request( + model="gemini/gemini-3.5-transcribe", + audio_file=("sample.wav", AUDIO_BYTES, "audio/wav"), + optional_params={}, + litellm_params={}, + ) + assert request_data.files is None + assert json.loads(json.dumps(request_data.data)) == { + "model": "gemini-3.5-transcribe", + "input": [ + { + "type": "audio", + "data": base64.b64encode(AUDIO_BYTES).decode("utf-8"), + "mime_type": "audio/wav", + } + ], + } + + def test_language_maps_to_bcp47_language_codes(self, config): + request_data = config.transform_audio_transcription_request( + model="gemini-3.5-transcribe", + audio_file=("sample.wav", AUDIO_BYTES, "audio/wav"), + optional_params={"language": "en"}, + litellm_params={}, + ) + transcription_config = request_data.data["generation_config"]["transcription_config"] + assert json.loads(json.dumps(transcription_config)) == {"language_codes": ["en-US"]} + + def test_word_timestamp_granularity_maps_to_verbatim_diarization_mode(self, config): + request_data = config.transform_audio_transcription_request( + model="gemini-3.5-transcribe", + audio_file=("sample.wav", AUDIO_BYTES, "audio/wav"), + optional_params={"timestamp_granularities": ["word"]}, + litellm_params={}, + ) + transcription_config = request_data.data["generation_config"]["transcription_config"] + assert json.loads(json.dumps(transcription_config)) == { + "mode": { + "type": "verbatim", + "timestamp_granularities": ["word"], + "diarization_mode": "speaker", + } + } + + def test_segment_granularity_sends_no_mode(self, config): + request_data = config.transform_audio_transcription_request( + model="gemini-3.5-transcribe", + audio_file=("sample.wav", AUDIO_BYTES, "audio/wav"), + optional_params={"timestamp_granularities": ["segment"]}, + litellm_params={}, + ) + assert "generation_config" not in request_data.data + + +class TestTransformResponse: + def test_completed_interaction_maps_to_transcription_response(self, config): + response = config.transform_audio_transcription_response(make_response(COMPLETED_RESPONSE)) + assert response.text == "Hello world." + assert response["task"] == "transcribe" + assert response["words"] == [ + {"word": "Hello", "start": 0.1, "end": 0.4, "speaker": "spk:0"}, + {"word": "world.", "start": 0.5, "end": 0.9, "speaker": "spk:1"}, + ] + assert response["duration"] == 0.9 + assert response.usage.input_tokens == 200 + assert response.usage.output_tokens == 0 + assert response.usage.total_tokens == 200 + assert response.usage.input_token_details.audio_tokens == 199 + assert response.usage.input_token_details.text_tokens == 1 + + def test_non_completed_status_raises(self, config): + with pytest.raises(GeminiError, match="did not complete"): + config.transform_audio_transcription_response( + make_response({**COMPLETED_RESPONSE, "status": "in_progress"}) + ) + + def test_non_json_response_raises(self, config): + raw = httpx.Response(200, text="oops", request=httpx.Request("POST", "https://example.test")) + with pytest.raises(GeminiError, match="non-JSON"): + config.transform_audio_transcription_response(raw) + + def test_word_without_offsets_survives(self, config): + payload = json.loads(json.dumps(COMPLETED_RESPONSE)) + payload["steps"][0]["content"][0]["annotations"] = [{"type": "word_info", "text": "Hello"}] + response = config.transform_audio_transcription_response(make_response(payload)) + assert response["words"] == [{"word": "Hello"}] + assert response.get("duration") is None + + +class TestCostRegression: + @pytest.fixture + def local_cost_map(self, monkeypatch): + monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True") + monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url="")) + + def test_registry_entries(self, local_cost_map): + batch_entry = litellm.model_cost["gemini/gemini-3.5-transcribe"] + assert batch_entry["mode"] == "audio_transcription" + assert batch_entry["input_cost_per_audio_token"] == 2e-06 + assert batch_entry["input_cost_per_token"] == 2e-06 + assert batch_entry["output_cost_per_token"] == 1.2e-05 + assert batch_entry["supported_endpoints"] == ["/v1/audio/transcriptions"] + + live_entry = litellm.model_cost["gemini/gemini-3.5-transcribe-live"] + assert live_entry["mode"] == "audio_transcription" + assert live_entry["input_cost_per_audio_token"] == 3.5e-06 + assert live_entry["input_cost_per_token"] == 3.5e-06 + assert live_entry["output_cost_per_token"] == 2.1e-05 + assert live_entry["supported_endpoints"] == ["/v1/realtime"] + + def test_completion_cost_bills_provider_reported_tokens(self, config, local_cost_map): + payload = json.loads(json.dumps(COMPLETED_RESPONSE)) + payload["usage"]["total_output_tokens"] = 10 + payload["usage"]["total_tokens"] = 210 + response = config.transform_audio_transcription_response(make_response(payload)) + cost = litellm.completion_cost( + completion_response=response, + model="gemini/gemini-3.5-transcribe", + call_type="transcription", + ) + assert cost == pytest.approx(199 * 2e-06 + 1 * 2e-06 + 10 * 1.2e-05) diff --git a/tests/test_litellm/llms/gemini/realtime/test_gemini_realtime_transformation.py b/tests/test_litellm/llms/gemini/realtime/test_gemini_realtime_transformation.py index 42e330925a0..c362efbfffa 100644 --- a/tests/test_litellm/llms/gemini/realtime/test_gemini_realtime_transformation.py +++ b/tests/test_litellm/llms/gemini/realtime/test_gemini_realtime_transformation.py @@ -1864,3 +1864,258 @@ def test_map_openai_params_drops_stock_voice_case_insensitively(): passthrough = cfg.map_openai_params(optional_params={}, non_default_params={"voice": "Kore"}) assert passthrough["generationConfig"]["speechConfig"]["voiceConfig"]["prebuiltVoiceConfig"]["voiceName"] == "Kore" + + +@pytest.fixture(autouse=False) +def patch_gemini_transcribe_live_cost_map_entry(monkeypatch): + """Inject the gemini-3.5-transcribe-live registry entry locally. + + litellm.model_cost is fetched from main branch at import time, so in CI + the entry may not exist yet. Also stamp supported_output_modalities on a + chat model to prove mode, not output modalities, drives the discriminator. + """ + for m in ["gemini-3.5-transcribe-live", "gemini/gemini-3.5-transcribe-live"]: + entry = dict(litellm.model_cost.get(m, {})) + entry["mode"] = "audio_transcription" + monkeypatch.setitem(litellm.model_cost, m, entry) + chat_entry = dict(litellm.model_cost.get("gemini-2.5-flash", {})) + chat_entry["supported_output_modalities"] = ["text"] + monkeypatch.setitem(litellm.model_cost, "gemini-2.5-flash", chat_entry) + + +@pytest.mark.parametrize("model", ["gemini-3.5-transcribe-live", "gemini/gemini-3.5-transcribe-live"]) +def test_gemini_transcribe_live_eager_setup_uses_text_modality(model, patch_gemini_transcribe_live_cost_map_entry): + """Regression: the hardcoded AUDIO eager setup closes transcribe-live sessions with 1007.""" + config = GeminiRealtimeConfig() + + setup = json.loads(config.session_configuration_request(model))["setup"] + + assert setup["generationConfig"]["responseModalities"] == ["TEXT"] + + +def test_gemini_transcribe_live_session_update_defaults_to_text_modality( + patch_gemini_transcribe_live_cost_map_entry, +): + config = GeminiRealtimeConfig() + session_update = { + "type": "session.update", + "session": {"instructions": "Transcribe the audio."}, + } + + messages = config.transform_realtime_request( + json.dumps(session_update), + "gemini-3.5-transcribe-live", + session_configuration_request=None, + ) + + setup = json.loads(messages[0])["setup"] + assert setup["generationConfig"]["responseModalities"] == ["TEXT"] + + +@pytest.mark.parametrize("modalities", [["audio"], ["audio", "text"]]) +def test_gemini_transcribe_live_coerces_audio_modality_to_text(modalities, patch_gemini_transcribe_live_cost_map_entry): + config = GeminiRealtimeConfig() + session_update = { + "type": "session.update", + "session": {"modalities": modalities}, + } + + messages = config.transform_realtime_request( + json.dumps(session_update), + "gemini-3.5-transcribe-live", + session_configuration_request=None, + ) + + setup = json.loads(messages[0])["setup"] + assert setup["generationConfig"]["responseModalities"] == ["TEXT"] + + +def test_gemini_chat_model_with_text_output_modalities_keeps_audio_eager_setup( + patch_gemini_transcribe_live_cost_map_entry, +): + """Chat entries also declare supported_output_modalities ["text"]; they must keep AUDIO.""" + config = GeminiRealtimeConfig() + + setup = json.loads(config.session_configuration_request("gemini-2.5-flash"))["setup"] + + assert setup["generationConfig"]["responseModalities"] == ["AUDIO"] + + +def test_generation_complete_without_prior_delta_keeps_turn_usage(patch_gemini_audio_cost_map_entries): + from typing import Final + + from litellm.types.llms.gemini import BidiGenerateContentServerMessage + from litellm.types.realtime import RealtimeResponseTransformInput + + config: Final = GeminiRealtimeConfig() + turn_end_frame: Final[BidiGenerateContentServerMessage] = { + "serverContent": {"generationComplete": True, "turnComplete": True}, + "usageMetadata": { + "promptTokenCount": 200, + "totalTokenCount": 200, + "promptTokensDetails": [ + {"modality": "AUDIO", "tokenCount": 199}, + {"modality": "TEXT", "tokenCount": 1}, + ], + }, + } + transform_input: Final[RealtimeResponseTransformInput] = { + "session_configuration_request": None, + "current_output_item_id": None, + "current_response_id": None, + "current_conversation_id": None, + "current_delta_chunks": None, + "current_item_chunks": None, + "current_delta_type": None, + } + + result: Final = config.transform_realtime_response( + json.dumps(turn_end_frame), + "gemini-3.5-transcribe-live", + MagicMock(), + realtime_response_transform_input=transform_input, + ) + + done_events: Final = tuple(event for event in result["response"] if event["type"] == "response.done") + assert len(done_events) == 1 + assert done_events[0]["response"]["usage"]["input_tokens"] == 200 + + +def test_bare_generation_complete_without_prior_delta_is_dropped(patch_gemini_audio_cost_map_entries): + from typing import Final + + from litellm.types.llms.gemini import BidiGenerateContentServerMessage + from litellm.types.realtime import RealtimeResponseTransformInput + + config: Final = GeminiRealtimeConfig() + bare_frame: Final[BidiGenerateContentServerMessage] = {"serverContent": {"generationComplete": True}} + transform_input: Final[RealtimeResponseTransformInput] = { + "session_configuration_request": None, + "current_output_item_id": None, + "current_response_id": None, + "current_conversation_id": None, + "current_delta_chunks": None, + "current_item_chunks": None, + "current_delta_type": None, + } + + result: Final = config.transform_realtime_response( + json.dumps(bare_frame), + "gemini-3.5-transcribe-live", + MagicMock(), + realtime_response_transform_input=transform_input, + ) + + assert result["response"] == [] + + +def _input_audio_append_message(raw_byte_count: int) -> str: + import base64 + + return json.dumps( + {"type": "input_audio_buffer.append", "audio": base64.b64encode(b"\x00" * raw_byte_count).decode()} + ) + + +def test_transcribe_live_completed_event_carries_estimated_usage(patch_gemini_transcribe_live_cost_map_entry): + """Gemini Live sends no usageMetadata for transcribe sessions, so LiteLLM bills + from streamed audio duration at Google's published estimate (25 audio tok/sec in, + 175 text tok/min out): 96000 pcm16 bytes = 2s at 24kHz -> 50 in / 6 out.""" + from typing import Final + + from litellm.types.llms.gemini import BidiGenerateContentServerMessage + from litellm.types.realtime import RealtimeInputAudioTranscriptionUsage, RealtimeResponseTransformInput + + config: Final = GeminiRealtimeConfig() + config.transform_realtime_request(_input_audio_append_message(96000), "gemini-3.5-transcribe-live") + + transcript_frame: Final[BidiGenerateContentServerMessage] = { + "serverContent": {"inputTranscription": {"text": "ahoy there"}} + } + transform_input: Final[RealtimeResponseTransformInput] = { + "session_configuration_request": None, + "current_output_item_id": None, + "current_response_id": None, + "current_conversation_id": None, + "current_delta_chunks": None, + "current_item_chunks": None, + "current_delta_type": None, + } + + result: Final = config.transform_realtime_response( + json.dumps(transcript_frame), + "gemini-3.5-transcribe-live", + MagicMock(), + realtime_response_transform_input=transform_input, + ) + + completed: Final = tuple( + event + for event in result["response"] + if event["type"] == "conversation.item.input_audio_transcription.completed" + ) + assert len(completed) == 1 + assert completed[0]["transcript"] == "ahoy there" + expected_usage: Final[RealtimeInputAudioTranscriptionUsage] = { + "type": "tokens", + "input_tokens": 50, + "output_tokens": 6, + "total_tokens": 56, + "input_token_details": {"text_tokens": 0, "audio_tokens": 50}, + } + assert completed[0]["usage"] == expected_usage + + second: Final = config.transform_realtime_response( + json.dumps(transcript_frame), + "gemini-3.5-transcribe-live", + MagicMock(), + realtime_response_transform_input=transform_input, + ) + second_completed: Final = tuple( + event + for event in second["response"] + if event["type"] == "conversation.item.input_audio_transcription.completed" + ) + assert len(second_completed) == 1 + assert "usage" not in second_completed[0] + + +def test_non_transcription_live_model_completed_event_has_no_usage(patch_gemini_audio_cost_map_entries): + """Conversational Live models get their audio tokens from usageMetadata via + response.done; attaching estimated usage to their transcription events would + double-bill, so the estimate is gated to audio_transcription-mode models.""" + from typing import Final + + from litellm.types.llms.gemini import BidiGenerateContentServerMessage + from litellm.types.realtime import RealtimeResponseTransformInput + + config: Final = GeminiRealtimeConfig() + config.transform_realtime_request(_input_audio_append_message(96000), "gemini-3.1-flash-live-preview") + + transcript_frame: Final[BidiGenerateContentServerMessage] = { + "serverContent": {"inputTranscription": {"text": "ahoy there"}} + } + transform_input: Final[RealtimeResponseTransformInput] = { + "session_configuration_request": None, + "current_output_item_id": None, + "current_response_id": None, + "current_conversation_id": None, + "current_delta_chunks": None, + "current_item_chunks": None, + "current_delta_type": None, + } + + result: Final = config.transform_realtime_response( + json.dumps(transcript_frame), + "gemini-3.1-flash-live-preview", + MagicMock(), + realtime_response_transform_input=transform_input, + ) + + completed: Final = tuple( + event + for event in result["response"] + if event["type"] == "conversation.item.input_audio_transcription.completed" + ) + assert len(completed) == 1 + assert "usage" not in completed[0] diff --git a/tests/test_litellm/test_cost_calculator.py b/tests/test_litellm/test_cost_calculator.py index 8fce9ba080c..0c99d128e14 100644 --- a/tests/test_litellm/test_cost_calculator.py +++ b/tests/test_litellm/test_cost_calculator.py @@ -343,6 +343,31 @@ def test_transcription_cost_uses_token_pricing(_local_model_cost_map): assert pytest.approx(cost, rel=1e-6) == expected_cost +def test_transcription_token_pricing_is_provider_aware(_local_model_cost_map): + """Regression: the token-priced transcription path hardcoded provider openai, + so gemini transcription models raised "This model isn't mapped yet".""" + from litellm import completion_cost + + usage = Usage( + prompt_tokens=200, + completion_tokens=10, + total_tokens=210, + prompt_tokens_details=PromptTokensDetailsWrapper(text_tokens=1, audio_tokens=199), + ) + response = TranscriptionResponse(text="demo text") + response.usage = usage + + cost = completion_cost( + completion_response=response, + model="gemini/gemini-3.5-transcribe", + custom_llm_provider="gemini", + call_type="atranscription", + ) + + expected_cost = (199 * 2e-06) + (1 * 2e-06) + (10 * 1.2e-05) + assert pytest.approx(cost, rel=1e-6) == expected_cost + + def test_transcription_cost_falls_back_to_duration(_local_model_cost_map): from litellm import completion_cost