o ưi_R@sddlmZddlmZmZmZmZmZmZmZddl Z ddl m Z ddl Z ddl mZddlmZddlmZddlmZmZmZmZdd lmZdd lmZdd lmZmZdd lm Z m!Z!erkdd l"m#Z$e$Z%neZ%GdddeZ&dS))datetime) TYPE_CHECKINGAnyDictListOptionalTupleUnionN) RequestFiles)RUNWAYML_DEFAULT_API_VERSIONBaseLLMException)BaseVideoConfig)AsyncHTTPHandler HTTPHandler_get_httpx_clientget_async_httpx_client)get_secret_str)GenericLiteLLMParams) VideoCreateOptionalRequestParams VideoObject)encode_video_id_with_providerextract_original_video_id)Loggingcs*eZdZdZfddZdedefddZdeded e de fd d Z dId e dede ede ede f ddZdede ede defddZdededede ded e dee eeffddZ dIdedejdede ede e def ddZdedefd d!Zd"e edefd#d$Z dJd%ededed e d&e edeee ff d'd(Zd)e eefdefd*d+Zdejdedefd,d-Z dejdedefd.d/Z! dJd%edededed e d0e e eefdeee ffd1d2Z" dJdejdede edefd3d4Z# dKdeded e d5e ed6e ed7e ed8e e eefdeee ffd9d:Z$ dJdejdede ede eeffd;d<Z%d%ededed e deee ff d=d>Z&dejdedefd?d@Z'd%ededed e deee ff dAdBZ( dJdejdede edefdCdDZ)dEedFed e*e ej+fde,fdGdHZ-Z.S)LRunwayMLVideoConfiga Configuration class for RunwayML video generation. RunwayML uses a task-based API where: 1. POST /v1/image_to_video creates a task 2. The task returns immediately with a task ID 3. Client must poll or wait for task completion cstdSN)super__init__)self __class__b/home/app/Keep/.python/lib/python3.10/site-packages/litellm/llms/runwayml/videos/transformation.pyr+szRunwayMLVideoConfig.__init__modelreturncCsgdS)a& Get the list of supported OpenAI parameters for video generation. Maps OpenAI params to RunwayML equivalents: - prompt -> promptText - input_reference -> promptImage - size -> ratio (e.g., "1280x720" -> "1280:720") - seconds -> duration )r#promptinput_referencesecondssizeuser extra_headersr!)rr#r!r!r"get_supported_openai_params.s z/RunwayMLVideoConfig.get_supported_openai_paramsvideo_create_optional_params drop_paramsc Csi}d|vr|d}||d<d|vr'|d}t|tr'd|vr'|dd|d<d|vrR|d}|durRzt|tr?tt|nt||d <Wn ttfyQYnw||}|D] \} } | |vrg| || <q[|S) a Map OpenAI parameters to RunwayML format. Mappings: - prompt -> promptText - input_reference -> promptImage - size -> ratio (convert "WIDTHxHEIGHT" to "WIDTH:HEIGHT") - seconds -> duration (convert to integer) r&Z promptImager(x:ratior'Nduration) isinstancestrreplaceintfloat ValueError TypeErrorr+items) rr,r#r-Z mapped_paramsr&r(r'Zsupported_openai_paramskeyvaluer!r!r"map_openai_paramsAs,& z%RunwayMLVideoConfig.map_openai_paramsNheadersapi_keylitellm_paramscCsZ|r |jr |p |j}|ptjptdptd}|durtd|d|tdd|S)z Validate environment and set up authentication headers. RunwayML uses Bearer token authentication via RUNWAYML_API_SECRET. ZRUNWAYML_API_SECRETZRUNWAYML_API_KEYNzeRunwayML API key is required. Set RUNWAYML_API_SECRET environment variable or pass api_key parameter.zBearer zapplication/json) AuthorizationzX-Runway-Versionz Content-Type)r>litellmrr7updater )rr=r#r>r?r!r!r"validate_environmentps& z(RunwayMLVideoConfig.validate_environmentapi_basecCs|durd}|dS)z Get the base URL for RunwayML API. The specific endpoint path will be added in the transform methods. Nzhttps://api.dev.runwayml.com/v1/)rstrip)rr#rDr?r!r!r"get_complete_urls  z$RunwayMLVideoConfig.get_complete_urlr%$video_create_optional_request_paramsc Cs,||d}||g}|d} ||| fS)aB Transform the video creation request for RunwayML API. RunwayML expects: { "model": "gen4_turbo", "promptImage": "https://... or data:image/...", "promptText": "description", "ratio": "1280:720", "duration": 5 } )r#Z promptTextz/image_to_video)rB) rr#r%rDrHr?r= request_dataZ files_listZ full_api_baser!r!r"transform_video_create_requests   z2RunwayMLVideoConfig.transform_video_create_request raw_response logging_objcustom_llm_providerrIc Cs|}|ddd||dd||dd}d|vr7|dr7t|dtr1|dd n|d|d <d |vrE||d |d <d |vsMd|vr\|d d|ddd|d<|rd|vrh|d|d<d|vr|d}t|trd|vr|dd|d<d|vrt|d|d<tdi|} |r| j rt | j ||| _ i} | rt | dr| j rz t | j | d<Wn ttfyYnw| | _| S)ax Transform the RunwayML video creation response. RunwayML returns a task object that looks like: { "id": "task_123...", "status": "PENDING" | "RUNNING" | "SUCCEEDED" | "FAILED", "output": ["https://...video.mp4"] (when succeeded) } We map this to OpenAI VideoObject format. idvideostatuspending createdAtrNobjectrQZ created_atoutputr output_url completedAt completed_at failureCodefailureunknownVideo generation failedcodemessageerrorr#r0r/r.r(r1r'Zduration_secondsNr!)jsonget_map_runway_status_parse_runway_timestampr2listr3r4rrNrhasattrr'r6r7r8usage) rr#rKrLrMrI response_data video_datar0 video_objZ usage_datar!r!r"transform_video_create_responsesF &     z3RunwayMLVideoConfig.transform_video_create_response runway_statuscCs"ddddddd}||dS)z Map RunwayML status to OpenAI status format. RunwayML statuses: PENDING, RUNNING, SUCCEEDED, FAILED, CANCELLED OpenAI statuses: queued, in_progress, completed, failed ZqueuedZ in_progress completedfailed)PENDINGRUNNINGZ SUCCEEDEDFAILED CANCELLED THROTTLED)rcupper)rrmZ status_mapr!r!r"rdsz&RunwayMLVideoConfig._map_runway_status timestamp_strc CsB|sdSzt|dd}t|WSttfy YdSw)z Convert RunwayML ISO 8601 timestamp to Unix timestamp. RunwayML returns timestamps like: "2025-11-11T21:48:50.448Z" We need to convert to Unix timestamp (seconds since epoch). rZz+00:00)r fromisoformatr4r5 timestampr7AttributeError)rrvdtr!r!r"re!sz+RunwayMLVideoConfig._parse_runway_timestampvideo_idvariantc Cs"t|}|d|}i}||fS)a Transform the video content request for RunwayML API. RunwayML doesn't have a separate content download endpoint. The video URL is returned in the task output field. We'll retrieve the task and extract the video URL. /tasks/r) rr|rDr?r=r}original_video_idurlparamsr!r!r"transform_video_content_request3sz3RunwayMLVideoConfig.transform_video_content_requestricCsd}d|vr|dr|d}t|tr|dn|}|sB|dd}|dvr-td|d|d kr>|d d }td |td |S)z~ Helper method to extract video URL from RunwayML response. Shared between sync and async transforms. NrVrrQUNKNOWN)rprqrtz#Video is still processing (status: z). Please wait and try again.rrr[z Unknown errorzVideo generation failed: z