--- title: "OpenAI Video Generation" url: "/docs/providers/openai/videos" canonical_url: "https://docs.litellm.ai/docs/providers/openai/videos" type: "docs" last_updated: "2026-10-07" summary: "LiteLLM supports OpenAI's video generation models including Sora." related: - "/docs/providers/openai/text_to_speech" - "/docs/providers/openai/ultrafast" --- # OpenAI Video Generation > Index of all LiteLLM docs: https://docs.litellm.ai/llms.txt LiteLLM supports OpenAI's video generation models including Sora. ## Quick Start ### Required API Keys ```python import os os.environ["OPENAI_API_KEY"] = "your-api-key" ``` ### Basic Usage ```python from litellm import video_generation, video_content import os os.environ["OPENAI_API_KEY"] = "your-api-key" # Generate a video response = video_generation( prompt="A cat playing with a ball of yarn in a sunny garden", model="sora-2", seconds="8", size="720x1280" ) print(f"Video ID: {response.id}") print(f"Status: {response.status}") # Download video content when ready video_bytes = video_content( video_id=response.id, ) # Save to file with open("generated_video.mp4", "wb") as f: f.write(video_bytes) ``` ## **LiteLLM Proxy Usage** LiteLLM provides OpenAI API compatible video endpoints for complete video generation workflow: - `POST /v1/videos` - Generate new videos - `GET /v1/videos/{video_id}` - Check video generation status - `GET /v1/videos/{video_id}/content` - Download completed videos - `POST /v1/videos/{video_id}/remix` - Remix an existing video with a new prompt Each route is also served without the `/v1` prefix. **Setup** Add this to your litellm proxy config.yaml ```yaml model_list: - model_name: sora-2 litellm_params: model: openai/sora-2 api_key: os.environ/OPENAI_API_KEY ``` Start litellm ```bash litellm --config /path/to/config.yaml # RUNNING on http://0.0.0.0:4000 ``` Test video generation request ```bash curl --location 'http://localhost:4000/v1/videos' \ --header 'Content-Type: application/json' \ --header 'x-litellm-api-key: sk-' \ --data '{ "model": "sora-2", "prompt": "A beautiful sunset over the ocean" }' ``` Test video status request ```bash # Using custom-llm-provider header curl --location 'http://localhost:4000/v1/videos/video_id' \ --header 'Accept: application/json' \ --header 'x-litellm-api-key: sk-' \ --header 'custom-llm-provider: openai' ``` Test video retrieval request ```bash # Using custom-llm-provider header curl --location 'http://localhost:4000/v1/videos/video_id/content' \ --header 'Accept: application/json' \ --header 'x-litellm-api-key: sk-' \ --header 'custom-llm-provider: openai' \ --output video.mp4 # Or using query parameter curl --location 'http://localhost:4000/v1/videos/video_id/content?custom_llm_provider=openai' \ --header 'Accept: application/json' \ --header 'x-litellm-api-key: sk-' \ --output video.mp4 ``` Test video remix request ```bash # Using custom_llm_provider in request body curl --location --request POST 'http://localhost:4000/v1/videos/video_id/remix' \ --header 'Accept: application/json' \ --header 'Content-Type: application/json' \ --header 'x-litellm-api-key: sk-' \ --data '{ "prompt": "New remix instructions", "custom_llm_provider": "openai" }' # Or using custom-llm-provider header curl --location --request POST 'http://localhost:4000/v1/videos/video_id/remix' \ --header 'Accept: application/json' \ --header 'Content-Type: application/json' \ --header 'x-litellm-api-key: sk-' \ --header 'custom-llm-provider: openai' \ --data '{ "prompt": "New remix instructions" }' ``` ### Character, Edit, and Extension Routes OpenAI video routes supported by LiteLLM proxy: - `POST /v1/videos/characters` - `GET /v1/videos/characters/{character_id}` - `POST /v1/videos/edits` - `POST /v1/videos/extensions` #### `target_model_names` support on character creation `POST /v1/videos/characters` supports `target_model_names` for model-based routing (same behavior as video create). ```bash curl --location 'http://localhost:4000/v1/videos/characters' \ --header "Authorization: Bearer $LITELLM_API_KEY" \ -F 'name=hero' \ -F 'target_model_names=gpt-5.6-terra' \ -F 'video=@/path/to/character.mp4' ``` When `target_model_names` is used, LiteLLM returns an encoded character ID: ```json { "id": "character_...", "object": "character", "created_at": 1712697600, "name": "hero" } ``` Use that encoded ID directly on get: ```bash curl --location 'http://localhost:4000/v1/videos/characters/character_...' \ --header "Authorization: Bearer $LITELLM_API_KEY" ``` #### Encoded and non-encoded video IDs for edit/extension Both routes accept either plain or encoded `video.id`: - `POST /v1/videos/edits` - `POST /v1/videos/extensions` ```bash curl --location 'http://localhost:4000/v1/videos/edits' \ --header "Authorization: Bearer $LITELLM_API_KEY" \ --header 'Content-Type: application/json' \ --data '{ "prompt": "Make this brighter", "video": { "id": "video_..." } }' ``` ```bash curl --location 'http://localhost:4000/v1/videos/extensions' \ --header "Authorization: Bearer $LITELLM_API_KEY" \ --header 'Content-Type: application/json' \ --data '{ "prompt": "Continue this scene", "seconds": "4", "video": { "id": "video_..." } }' ``` #### `custom_llm_provider` input sources For these routes, `custom_llm_provider` may be supplied via: - header: `custom-llm-provider` - query: `?custom_llm_provider=...` - body: `custom_llm_provider` (and `extra_body.custom_llm_provider` where supported) Test OpenAI video generation request ```bash curl http://localhost:4000/v1/videos \ -H "Authorization: Bearer $LITELLM_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "sora-2", "prompt": "A cat playing with a ball of yarn in a sunny garden", "seconds": "8", "size": "720x1280" }' ``` ## Supported Models | Model Name | Description | Max Duration | Supported Sizes | |------------|-------------|--------------|-----------------| | sora-2 | OpenAI's latest video generation model | 8 seconds | 720x1280, 1280x720 | ## Video Generation Parameters - `prompt` (required): Text description of the desired video - `model` (optional): Model to use, defaults to "sora-2" - `seconds` (optional): Video duration in seconds (e.g., "8", "16") - `size` (optional): Video dimensions (e.g., "720x1280", "1280x720") - `input_reference` (optional): Reference image for video editing - `user` (optional): User identifier for tracking ## Video Content Retrieval ```python # Download video content video_bytes = video_content( video_id="video_1234567890" ) # Save to file with open("video.mp4", "wb") as f: f.write(video_bytes) ``` ## Complete Workflow ```python import litellm import time def generate_and_download_video(prompt): # Step 1: Generate video response = litellm.video_generation( prompt=prompt, model="sora-2", seconds="8", size="720x1280" ) video_id = response.id print(f"Video ID: {video_id}") # Step 2: Wait for processing (in practice, poll status) time.sleep(30) # Step 3: Download video video_bytes = litellm.video_content( video_id=video_id ) # Step 4: Save to file with open(f"video_{video_id}.mp4", "wb") as f: f.write(video_bytes) return f"video_{video_id}.mp4" # Usage video_file = generate_and_download_video( "A cat playing with a ball of yarn in a sunny garden" ) ``` ## Video Editing with Reference Images ```python # Video editing with reference image response = litellm.video_generation( prompt="Make the cat jump higher", input_reference=open("path/to/image.jpg", "rb"), # Reference image model="sora-2", seconds="8" ) print(f"Video ID: {response.id}") ``` ## Error Handling ```python from litellm.exceptions import BadRequestError, AuthenticationError try: response = video_generation( prompt="A cat playing with a ball of yarn" ) except AuthenticationError as e: print(f"Authentication failed: {e}") except BadRequestError as e: print(f"Bad request: {e}") ``` ## Related pages - [OpenAI - Text-to-speech](https://docs.litellm.ai/docs/providers/openai/text_to_speech.md) - [Fast & Ultrafast mode](https://docs.litellm.ai/docs/providers/openai/ultrafast.md)