From c33889200a68c8e448b07631a00d6a48851de66a Mon Sep 17 00:00:00 2001 From: Sameer Kankute Date: Mon, 16 Mar 2026 17:54:03 +0530 Subject: [PATCH] Add new videos endpoints --- litellm/proxy/video_endpoints/endpoints.py | 430 ++++++++++++++++++++- 1 file changed, 429 insertions(+), 1 deletion(-) diff --git a/litellm/proxy/video_endpoints/endpoints.py b/litellm/proxy/video_endpoints/endpoints.py index f7a71c10339..9e8784df0aa 100644 --- a/litellm/proxy/video_endpoints/endpoints.py +++ b/litellm/proxy/video_endpoints/endpoints.py @@ -16,7 +16,15 @@ from litellm.proxy.common_utils.openai_endpoint_utils import ( get_custom_llm_provider_from_request_query, ) from litellm.proxy.image_endpoints.endpoints import batch_to_bytesio -from litellm.types.videos.utils import decode_video_id_with_provider +from litellm.proxy.video_endpoints.utils import ( + encode_character_id_in_response, + extract_model_from_target_model_names, + get_custom_provider_from_data, +) +from litellm.types.videos.utils import ( + decode_character_id_with_provider, + decode_video_id_with_provider, +) router = APIRouter() @@ -504,3 +512,423 @@ async def video_remix( proxy_logging_obj=proxy_logging_obj, version=version, ) + + +@router.post( + "/v1/videos/characters", + dependencies=[Depends(user_api_key_auth)], + response_class=ORJSONResponse, + tags=["videos"], +) +@router.post( + "/videos/characters", + dependencies=[Depends(user_api_key_auth)], + response_class=ORJSONResponse, + tags=["videos"], +) +async def video_create_character( + request: Request, + fastapi_response: Response, + video: UploadFile = File(...), + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), +): + """ + Create a character from an uploaded video file. + + Follows the OpenAI Videos API spec: + https://platform.openai.com/docs/api-reference/videos/create-character + + Example: + ```bash + curl -X POST "http://localhost:4000/v1/videos/characters" \ + -H "Authorization: Bearer sk-1234" \ + -F "video=@character_video.mp4" \ + -F "name=my_character" + ``` + """ + from litellm.proxy.proxy_server import ( + general_settings, + llm_router, + proxy_config, + proxy_logging_obj, + select_data_generator, + user_api_base, + user_max_tokens, + user_model, + user_request_timeout, + user_temperature, + version, + ) + + data = await _read_request_body(request=request) + video_file = await batch_to_bytesio([video]) + if video_file: + data["video"] = video_file[0] + + target_model_name = extract_model_from_target_model_names( + data.get("target_model_names") + ) + if target_model_name and not data.get("model"): + data["model"] = target_model_name + + custom_llm_provider = ( + get_custom_llm_provider_from_request_headers(request=request) + or get_custom_llm_provider_from_request_query(request=request) + or get_custom_provider_from_data(data=data) + or "openai" + ) + data["custom_llm_provider"] = custom_llm_provider + + processor = ProxyBaseLLMRequestProcessing(data=data) + try: + response = await processor.base_process_llm_request( + request=request, + fastapi_response=fastapi_response, + user_api_key_dict=user_api_key_dict, + route_type="avideo_create_character", + proxy_logging_obj=proxy_logging_obj, + llm_router=llm_router, + general_settings=general_settings, + proxy_config=proxy_config, + select_data_generator=select_data_generator, + model=None, + user_model=user_model, + user_temperature=user_temperature, + user_request_timeout=user_request_timeout, + user_max_tokens=user_max_tokens, + user_api_base=user_api_base, + version=version, + ) + if target_model_name: + hidden_params = getattr(response, "_hidden_params", {}) or {} + provider_for_encoding = ( + hidden_params.get("custom_llm_provider") + or custom_llm_provider + or "openai" + ) + model_id_for_encoding = hidden_params.get("model_id") or data.get("model") + response = encode_character_id_in_response( + response=response, + custom_llm_provider=provider_for_encoding, + model_id=model_id_for_encoding, + ) + return response + except Exception as e: + raise await processor._handle_llm_api_exception( + e=e, + user_api_key_dict=user_api_key_dict, + proxy_logging_obj=proxy_logging_obj, + version=version, + ) + + +@router.get( + "/v1/videos/characters/{character_id}", + dependencies=[Depends(user_api_key_auth)], + response_class=ORJSONResponse, + tags=["videos"], +) +@router.get( + "/videos/characters/{character_id}", + dependencies=[Depends(user_api_key_auth)], + response_class=ORJSONResponse, + tags=["videos"], +) +async def video_get_character( + character_id: str, + request: Request, + fastapi_response: Response, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), +): + """ + Retrieve a character by ID. + + Follows the OpenAI Videos API spec: + https://platform.openai.com/docs/api-reference/videos/get-character + + Example: + ```bash + curl -X GET "http://localhost:4000/v1/videos/characters/char_123" \ + -H "Authorization: Bearer sk-1234" + ``` + """ + from litellm.proxy.proxy_server import ( + general_settings, + llm_router, + proxy_config, + proxy_logging_obj, + select_data_generator, + user_api_base, + user_max_tokens, + user_model, + user_request_timeout, + user_temperature, + version, + ) + + original_requested_character_id = character_id + data: Dict[str, Any] = {"character_id": character_id} + + decoded = decode_character_id_with_provider(character_id) + provider_from_id = decoded.get("custom_llm_provider") + model_id_from_decoded = decoded.get("model_id") + decoded_character_id = decoded.get("character_id") + if decoded_character_id: + data["character_id"] = decoded_character_id + + custom_llm_provider = ( + get_custom_llm_provider_from_request_headers(request=request) + or get_custom_llm_provider_from_request_query(request=request) + or await get_custom_llm_provider_from_request_body(request=request) + or provider_from_id + or "openai" + ) + data["custom_llm_provider"] = custom_llm_provider + + if model_id_from_decoded and llm_router: + resolved_model = llm_router.resolve_model_name_from_model_id( + model_id_from_decoded + ) + if resolved_model: + data["model"] = resolved_model + + processor = ProxyBaseLLMRequestProcessing(data=data) + try: + response = await processor.base_process_llm_request( + request=request, + fastapi_response=fastapi_response, + user_api_key_dict=user_api_key_dict, + route_type="avideo_get_character", + proxy_logging_obj=proxy_logging_obj, + llm_router=llm_router, + general_settings=general_settings, + proxy_config=proxy_config, + select_data_generator=select_data_generator, + model=None, + user_model=user_model, + user_temperature=user_temperature, + user_request_timeout=user_request_timeout, + user_max_tokens=user_max_tokens, + user_api_base=user_api_base, + version=version, + ) + if original_requested_character_id.startswith("character_"): + provider_for_encoding = provider_from_id or custom_llm_provider or "openai" + model_id_for_encoding = model_id_from_decoded + response = encode_character_id_in_response( + response=response, + custom_llm_provider=provider_for_encoding, + model_id=model_id_for_encoding, + ) + return response + except Exception as e: + raise await processor._handle_llm_api_exception( + e=e, + user_api_key_dict=user_api_key_dict, + proxy_logging_obj=proxy_logging_obj, + version=version, + ) + + +@router.post( + "/v1/videos/edits", + dependencies=[Depends(user_api_key_auth)], + response_class=ORJSONResponse, + tags=["videos"], +) +@router.post( + "/videos/edits", + dependencies=[Depends(user_api_key_auth)], + response_class=ORJSONResponse, + tags=["videos"], +) +async def video_edit( + request: Request, + fastapi_response: Response, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), +): + """ + Create a video edit job. + + Follows the OpenAI Videos API spec: + https://platform.openai.com/docs/api-reference/videos/create-edit + + Example: + ```bash + curl -X POST "http://localhost:4000/v1/videos/edits" \ + -H "Authorization: Bearer sk-1234" \ + -H "Content-Type: application/json" \ + -d '{"prompt": "Make it brighter", "video": {"id": "video_123"}}' + ``` + """ + from litellm.proxy.proxy_server import ( + general_settings, + llm_router, + proxy_config, + proxy_logging_obj, + select_data_generator, + user_api_base, + user_max_tokens, + user_model, + user_request_timeout, + user_temperature, + version, + ) + + body = await request.body() + data = orjson.loads(body) + + # Extract video_id from nested video object + video_ref = data.pop("video", {}) + video_id = video_ref.get("id", "") if isinstance(video_ref, dict) else "" + data["video_id"] = video_id + + decoded = decode_video_id_with_provider(video_id) + provider_from_id = decoded.get("custom_llm_provider") + model_id_from_decoded = decoded.get("model_id") + + custom_llm_provider = ( + get_custom_llm_provider_from_request_headers(request=request) + or get_custom_llm_provider_from_request_query(request=request) + or get_custom_provider_from_data(data=data) + or provider_from_id + or "openai" + ) + data["custom_llm_provider"] = custom_llm_provider + + if model_id_from_decoded and llm_router: + resolved_model = llm_router.resolve_model_name_from_model_id( + model_id_from_decoded + ) + if resolved_model: + data["model"] = resolved_model + + processor = ProxyBaseLLMRequestProcessing(data=data) + try: + return await processor.base_process_llm_request( + request=request, + fastapi_response=fastapi_response, + user_api_key_dict=user_api_key_dict, + route_type="avideo_edit", + proxy_logging_obj=proxy_logging_obj, + llm_router=llm_router, + general_settings=general_settings, + proxy_config=proxy_config, + select_data_generator=select_data_generator, + model=None, + user_model=user_model, + user_temperature=user_temperature, + user_request_timeout=user_request_timeout, + user_max_tokens=user_max_tokens, + user_api_base=user_api_base, + version=version, + ) + except Exception as e: + raise await processor._handle_llm_api_exception( + e=e, + user_api_key_dict=user_api_key_dict, + proxy_logging_obj=proxy_logging_obj, + version=version, + ) + + +@router.post( + "/v1/videos/extensions", + dependencies=[Depends(user_api_key_auth)], + response_class=ORJSONResponse, + tags=["videos"], +) +@router.post( + "/videos/extensions", + dependencies=[Depends(user_api_key_auth)], + response_class=ORJSONResponse, + tags=["videos"], +) +async def video_extension( + request: Request, + fastapi_response: Response, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), +): + """ + Create a video extension. + + Follows the OpenAI Videos API spec: + https://platform.openai.com/docs/api-reference/videos/create-extension + + Example: + ```bash + curl -X POST "http://localhost:4000/v1/videos/extensions" \ + -H "Authorization: Bearer sk-1234" \ + -H "Content-Type: application/json" \ + -d '{"prompt": "Continue the scene", "seconds": "5", "video": {"id": "video_123"}}' + ``` + """ + from litellm.proxy.proxy_server import ( + general_settings, + llm_router, + proxy_config, + proxy_logging_obj, + select_data_generator, + user_api_base, + user_max_tokens, + user_model, + user_request_timeout, + user_temperature, + version, + ) + + body = await request.body() + data = orjson.loads(body) + + # Extract video_id from nested video object + video_ref = data.pop("video", {}) + video_id = video_ref.get("id", "") if isinstance(video_ref, dict) else "" + data["video_id"] = video_id + + decoded = decode_video_id_with_provider(video_id) + provider_from_id = decoded.get("custom_llm_provider") + model_id_from_decoded = decoded.get("model_id") + + custom_llm_provider = ( + get_custom_llm_provider_from_request_headers(request=request) + or get_custom_llm_provider_from_request_query(request=request) + or get_custom_provider_from_data(data=data) + or provider_from_id + or "openai" + ) + data["custom_llm_provider"] = custom_llm_provider + + if model_id_from_decoded and llm_router: + resolved_model = llm_router.resolve_model_name_from_model_id( + model_id_from_decoded + ) + if resolved_model: + data["model"] = resolved_model + + processor = ProxyBaseLLMRequestProcessing(data=data) + try: + return await processor.base_process_llm_request( + request=request, + fastapi_response=fastapi_response, + user_api_key_dict=user_api_key_dict, + route_type="avideo_extension", + proxy_logging_obj=proxy_logging_obj, + llm_router=llm_router, + general_settings=general_settings, + proxy_config=proxy_config, + select_data_generator=select_data_generator, + model=None, + user_model=user_model, + user_temperature=user_temperature, + user_request_timeout=user_request_timeout, + user_max_tokens=user_max_tokens, + user_api_base=user_api_base, + version=version, + ) + except Exception as e: + raise await processor._handle_llm_api_exception( + e=e, + user_api_key_dict=user_api_key_dict, + proxy_logging_obj=proxy_logging_obj, + version=version, + )