> ## Documentation Index > Fetch the complete documentation index at: https://docs.reactor.inc/llms.txt > Use this file to discover all available pages before exploring further. > ## Agent Instructions > To build and serve your own model, start at /deploy/development/quickstart and /deploy/development/overview. Deploying is the default path: reactor init scaffolds a workspace, reactor auth login authenticates, and reactor model deploy registers the model, publishes the release with the weights/ folder, and activates it on Reactor's GPUs, in one command from that workspace. Docker must be running, because the publish step builds the image locally. Bump model.version in reactor.yaml before redeploying a change, because a release that already has an image is reactivated as it is. Deployment access is granted per account, so contact team@reactor.inc if a deploy is refused. Every key in reactor.yaml is documented at /deploy/platform/reactor-yaml. Model code imports reactor_runtime; Python client code imports reactor_sdk. The runtime overview explains the model interface. Running the model on your own machine with reactor run is optional and needs a GPU you attach with --gpus; /deploy/development/local-testing covers that loop and pairs a complete brightness model with a Python client test in a separate brightness-test workspace. > Reactor hosts multiple models, each with its own connect slug (modelName) and command/event schema. The catalog of every model — slug, typed SDK package, and links to its schema — is at /model-api-reference/overview. Some models expose one slug per experience (e.g. HappyOyster); always take the slug from the model's own pages, never guess it. > Fastest path to a working app: `npx create-reactor-app my-app --model=` scaffolds a complete app with secure auth wired up. Typed TypeScript SDKs are published as @reactor-models/; Python uses the base reactor-sdk package. > Auth: exchange an API key (rk_...) for a JWT via POST https://api.reactor.inc/tokens from your server. Never put the API key in client-side code. > Append .md to any docs URL for clean Markdown. Search these docs via the MCP server at https://docs.reactor.inc/mcp. # Vidu S2-Avatar prompt guide > Write personas and greetings, tune turn-taking, and change the character's look live. Vidu S2-Avatar has no scene prompt. You shape the character with five inputs: the image you build the avatar from, the `persona` and `greeting` you send with `start_call`, the text you send with `say`, and the reference images you give it during the call. This page covers each one. ## Image For the image input, use one image of one person. Use a full-body or half-body shot with the face clearly visible. The avatar keeps this look for every call, so pick an image that matches the character you plan to write. * Use one person per image. Other people in the frame can confuse the avatar. * Use a front-facing or three-quarter view, with even light on the face. * A phone photo is fine. The model applies its EXIF orientation, so it arrives upright. ## Persona `persona` is required on `start_call`. It says who the character is and how it behaves. It can be up to 50,000 characters, but a short, specific persona usually works better than a long one. A good persona covers four things: | Part | What it says | Example | | - | - | - | | Identity | Name, role, and setting. | `You are Tina, a guide at a sea-life museum.` | | Manner | Tone and attitude. | `You are warm and curious, never formal.` | | Length | How long each answer is. | `Answer in one or two short sentences.` | | Limits | What the character does not do or talk about. | `If asked about prices, say the desk can help.` | Compare these two personas:
You are a helpful assistant.
You are Tina, a guide at a sea-life museum. You are warm and curious, and you love octopuses. Answer in one or two short sentences, then ask the user a question. If asked about tickets or prices, say the front desk can help.
The first persona gives the character no voice of its own, so it answers like a generic assistant. The second gives it a name, a setting, a manner, and a clear limit on length. Keep answers short. The character speaks every word it generates, and a long answer is a long wait before the user can reply. The `llm.max_tokens` setting, 50 by default, also caps each reply. See [Tune replies](#tune-replies). Set `persona_enhance: true` to let the model expand a short persona into a fuller one before the call starts. Use it when you have only a line or two. Leave it off when you wrote the persona with care and want it used as is. ## Greeting `greeting` is optional, up to 200 characters. It says what the character says or does first, before you speak. Without it, the character waits for you. Treat the greeting as a short instruction for the opening. For example: ```text theme={"theme":{"light":"github-light","dark":"github-dark-high-contrast"}} Say hello, wave, and ask what brought them to the museum today. ``` The character generates the opening from this instruction. Test the result in a call if specific words or gestures matter to your app. ## Send text with `say` `say` sends text as if you had spoken it, up to 2,000 characters. Use it for typed chat, for a scripted demo, or to test a persona without a microphone. The character answers on the tracks, the same as it answers speech. `say` is input from the user's side of the conversation, not a line for the character. To change what the character says or how it behaves, change the persona with `update_call`. ## Choose a language and a voice `start_call` accepts an optional `language` field. If you omit it, the model follows the conversation. The examples in this guide use English. Call `list_voices` to see the voices you can use. Each built-in voice has a `description` and an `accent`. Pick one that fits the image and the persona, and pass its `voice` to `start_call`. You can change it mid-call with `update_call`; the new voice starts after the current sentence. ## Tune turn-taking `vad` controls when the character decides you have finished speaking. | Goal | Adjustment | | - | - | | Ignore more noise | Raise `vad.threshold` from its `0.5` default; try `0.7`. | | Allow longer pauses | Raise `vad.silence_duration_ms` from `400`; try `1200`. | | Answer sooner | Lower `vad.silence_duration_ms` from `400`; try `250`. | | Interrupt right away | Set `vad.type` to `semantic`. | The default `server` mode filters back-channel sounds, such as "mm-hm", and background noise. The threshold and silence settings above apply to this mode. With `semantic`, the character stops when the user starts speaking. To stop it from your app, send `interrupt`. ## Tune replies `llm` controls how the character generates each reply. * `max_tokens`, 50 by default, caps the length of one reply. Raise it for a storyteller; keep it low for quick back-and-forth. * `temperature` sets how varied the replies are. Lower values give steadier, more predictable answers. * `frequency_penalty` adjusts repetition. `1` is neutral; lower values encourage repeated wording, and higher values discourage it. * `seed` sets the random seed for reply generation. `-1` picks a random seed. Change `vad` and `llm` mid-call with `update_call`. They apply on the next turn. ## Change the look mid-call `set_reference_images` gives the character up to three images to pick up while it talks. Use `kind` to tell the model what each image represents: | Kind | Effect | Example `text` | | - | - | - | | `object` | The character holds or shows the object. | `She holds up the seashell.` | | `garment` | The character wears the outfit. | `She puts on the denim jacket.` | | `background` | The scene behind the character changes. | `She stands on a beach at sunset.` | If you omit `kind`, the model looks at the image and guesses whether it is an object, a garment, or a background. Set `kind` when an image contains more than one possible target, such as a jacket against a distinctive background. `text` is optional, one sentence of up to 200 characters. Use it to say what happens, in the same plain way you would describe the change to a person. Images must be publicly fetchable URLs. Use an image with a plain background for an object or a garment, so the character picks up the item and not its surroundings. Give each new reference image its own `image_id` and keep the IDs you use. To remove a specific image, send its ID with `clear_reference_images`. Omit `image_ids` to undo the most recent `set_reference_images` command. ## Handle content refusals Vidu S2-Avatar is moderated. A refused request arrives as `command_error` with `code: "CONTENT_POLICY"`. A call stopped for its content ends with `end_reason: "content_policy"`, and `last_error.reason` says why. Show that reason to the user rather than retrying the same text. ## See also * [Schema](/model-api-reference/vidu-s2-avatar/schema): every command, parameter, and message. * [Tutorial](/model-api-reference/vidu-s2-avatar/tutorial): build a browser call from start to finish. * [Content moderation](/resources/content-moderation): how Reactor moderates the models it serves.