> ## Documentation Index > Fetch the complete documentation index at: https://fal.ai/docs/llms.txt > Use this file to discover all available pages before exploring further. > ## Agent Instructions > fal has two developer products. Model APIs run hosted models through an API key. fal Serverless deploys your own Python apps and models on fal GPUs. > To call a hosted model, start with the [Quick Start](https://fal.ai/docs/documentation/quickstart.md) and the [Model APIs overview](https://fal.ai/docs/documentation/model-apis/overview.md). > To deploy your own model with fal Serverless, start with these pages: > - [Introduction to Serverless](https://fal.ai/docs/documentation/serverless/index.md): What fal Serverless is and the three ways to deploy on it. > - [Installation & Setup](https://fal.ai/docs/documentation/development/getting-started/installation.md): Install the fal CLI with `pip install fal` and authenticate. > - [Quick Start](https://fal.ai/docs/documentation/development/getting-started/quick-start.md): Build a Hello World app, test it with `fal run`, and ship it with `fal deploy`. > - [App Lifecycle](https://fal.ai/docs/documentation/development/app-lifecycle.md): How a `fal.App` goes from code to running runners. > - [Define Your Endpoints](https://fal.ai/docs/documentation/development/endpoints-overview.md): Structure the API endpoints that your app exposes. > - [Deploy to Production](https://fal.ai/docs/documentation/deployment/deploy-to-production.md): Persistent URLs, authentication modes, and automatic scaling. > - [Machine Types](https://fal.ai/docs/documentation/deployment/machine-types.md): Available GPU and CPU machine types and how to choose one. > - [Pricing](https://fal.ai/docs/documentation/serverless/pricing.md): Per-second billing and the runner states that are billed. > - [Scaling Parameter Reference](https://fal.ai/docs/documentation/deployment/scale-your-application.md): Parameters that control runners, concurrency, and scale to zero. > - [Optimizing Cold Starts](https://fal.ai/docs/documentation/serverless/optimizations/optimize-cold-starts.md): Causes of cold starts and ways to make them shorter. > - [Examples](https://fal.ai/docs/examples/index.md): Complete Serverless apps for image, video, audio, 3D, realtime, and multi-GPU workloads. > - [Migrating to fal](https://fal.ai/docs/documentation/development/migrating-to-fal.md): Guides to move an existing Docker server or an app from another platform to fal. > fal Serverless deploys need access that the fal team approves for each account. Request access at https://fal.ai/dashboard/serverless-get-started. # Sora 2 Text To Video API > API reference for Sora 2 Text To Video. Text-to-video endpoint for Sora 2, OpenAI's state-of-the-art video model capable of creating richly detailed, dynamic clips with audio from natural language or **Text To Video** **Endpoint:** `POST https://fal.run/fal-ai/sora-2/text-to-video` **Endpoint ID:** `fal-ai/sora-2/text-to-video` > **[Try it in the Playground](https://fal.ai/models/fal-ai/sora-2/text-to-video/playground)** > > Run this model interactively with your own prompts. ### Quick Start ```python title="Python" theme={null} import fal_client def on_queue_update(update): if isinstance(update, fal_client.InProgress): for log in update.logs: print(log["message"]) result = fal_client.subscribe( "fal-ai/sora-2/text-to-video", arguments={ "prompt": "A dramatic Hollywood breakup scene at dusk on a quiet suburban street. A man and a woman in their 30s face each other, speaking softly but emotionally, lips syncing to breakup dialogue. Cinematic lighting, warm sunset tones, shallow depth of field, gentle breeze moving autumn leaves, realistic natural sound, no background music" }, with_logs=True, on_queue_update=on_queue_update, ) print(result) ``` ```javascript title="JavaScript" theme={null} import { fal } from "@fal-ai/client"; const result = await fal.subscribe("fal-ai/sora-2/text-to-video", { input: { prompt: "A dramatic Hollywood breakup scene at dusk on a quiet suburban street. A man and a woman in their 30s face each other, speaking softly but emotionally, lips syncing to breakup dialogue. Cinematic lighting, warm sunset tones, shallow depth of field, gentle breeze moving autumn leaves, realistic natural sound, no background music" }, logs: true, onQueueUpdate: (update) => { if (update.status === "IN_PROGRESS") { update.logs.map((log) => log.message).forEach(console.log); } }, }); console.log(result.data); console.log(result.requestId); ``` ```bash title="cURL" theme={null} curl --request POST \ --url https://fal.run/fal-ai/sora-2/text-to-video \ --header "Authorization: Key $FAL_KEY" \ --header "Content-Type: application/json" \ --data '{ "prompt": "A dramatic Hollywood breakup scene at dusk on a quiet suburban street. A man and a woman in their 30s face each other, speaking softly but emotionally, lips syncing to breakup dialogue. Cinematic lighting, warm sunset tones, shallow depth of field, gentle breeze moving autumn leaves, realistic natural sound, no background music" }' ``` ### Input Schema **prompt** `string` *required* The text prompt describing the video you want to generate **resolution** `string` (default: 720p) The resolution of the generated video Default value: `"720p"` **aspect\_ratio** `AspectRatioEnum` (default: 16:9) The aspect ratio of the generated video Default value: `"16:9"` Possible values: `9:16`, `16:9` **duration** `DurationEnum` (default: 4) Duration of the generated video in seconds Default value: `"4"` Possible values: `4`, `8`, `12`, `16`, `20` **delete\_video** `boolean` (default: true) Whether to delete the video after generation for privacy reasons. If True, the video cannot be used for remixing and will be permanently deleted. Default value: `true` **model** `ModelEnum` (default: sora-2) The model to use for the generation. When the default model is selected, the latest snapshot of the model will be used - otherwise, select a specific snapshot of the model. Default value: `"sora-2"` Possible values: `sora-2`, `sora-2-2025-12-08`, `sora-2-2025-10-06` **detect\_and\_block\_ip** `boolean` (default: false) If enabled, the prompt (and image for image-to-video) will be checked for known intellectual property references and the request will be blocked if any are detected. **character\_ids** `list\` Up to two character IDs (from create-character) to use in the video. Refer to characters by name in the prompt. When set, only the OpenAI provider is used. ### Output Schema **video** `VideoFile` *required* The generated video **video\_id** `string` *required* The ID of the generated video **thumbnail** `ImageFile` Thumbnail image for the video **spritesheet** `ImageFile` Spritesheet image for the video ### Input Example ```json theme={null} { "prompt": "A dramatic Hollywood breakup scene at dusk on a quiet suburban street. A man and a woman in their 30s face each other, speaking softly but emotionally, lips syncing to breakup dialogue. Cinematic lighting, warm sunset tones, shallow depth of field, gentle breeze moving autumn leaves, realistic natural sound, no background music", "resolution": "720p", "aspect_ratio": "16:9", "duration": 4, "delete_video": true, "model": "sora-2", "detect_and_block_ip": false } ``` ### Output Example ```json theme={null} { "video": { "content_type": "video/mp4", "url": "https://storage.googleapis.com/falserverless/example_outputs/sora_t2v_output.mp4" }, "video_id": "video_123" } ``` **Pro** **Endpoint:** `POST https://fal.run/fal-ai/sora-2/text-to-video/pro` **Endpoint ID:** `fal-ai/sora-2/text-to-video/pro` > **[Try it in the Playground](https://fal.ai/models/fal-ai/sora-2/text-to-video/pro/playground)** > > Run this model interactively with your own prompts. ### Quick Start ```python title="Python" theme={null} import fal_client def on_queue_update(update): if isinstance(update, fal_client.InProgress): for log in update.logs: print(log["message"]) result = fal_client.subscribe( "fal-ai/sora-2/text-to-video/pro", arguments={ "prompt": "A dramatic Hollywood breakup scene at dusk on a quiet suburban street. A man and a woman in their 30s face each other, speaking softly but emotionally, lips syncing to breakup dialogue. Cinematic lighting, warm sunset tones, shallow depth of field, gentle breeze moving autumn leaves, realistic natural sound, no background music" }, with_logs=True, on_queue_update=on_queue_update, ) print(result) ``` ```javascript title="JavaScript" theme={null} import { fal } from "@fal-ai/client"; const result = await fal.subscribe("fal-ai/sora-2/text-to-video/pro", { input: { prompt: "A dramatic Hollywood breakup scene at dusk on a quiet suburban street. A man and a woman in their 30s face each other, speaking softly but emotionally, lips syncing to breakup dialogue. Cinematic lighting, warm sunset tones, shallow depth of field, gentle breeze moving autumn leaves, realistic natural sound, no background music" }, logs: true, onQueueUpdate: (update) => { if (update.status === "IN_PROGRESS") { update.logs.map((log) => log.message).forEach(console.log); } }, }); console.log(result.data); console.log(result.requestId); ``` ```bash title="cURL" theme={null} curl --request POST \ --url https://fal.run/fal-ai/sora-2/text-to-video/pro \ --header "Authorization: Key $FAL_KEY" \ --header "Content-Type: application/json" \ --data '{ "prompt": "A dramatic Hollywood breakup scene at dusk on a quiet suburban street. A man and a woman in their 30s face each other, speaking softly but emotionally, lips syncing to breakup dialogue. Cinematic lighting, warm sunset tones, shallow depth of field, gentle breeze moving autumn leaves, realistic natural sound, no background music" }' ``` ## Examples > A dramatic Hollywood breakup scene at dusk on a quiet suburban street. A man and a woman in their 30s face each other, speaking softly but emotionally, lips syncing to breakup dialogue. Cinematic lighting, warm sunset tones, shallow depth of field, gentle breeze moving autumn leaves, realistic natur...