weryai-chat

# WeryAI Chat Use the official WeryAI chat-completions API for general assistant chat and model lookup. This skill is intentionally broad but not specialized: it is for general conversation and prompt-response tasks, not blog writing, social copy, or email drafting. ## Example Prompts - `Ask a WeryAI chat model to explain retrieval augmented generation in plain English.` - `Send this messages array to WeryAI chat completions and return the assistant response.` - `List the currently available WeryAI chat models and their pricing.` - `Use GPT_5_4 for this one chat call instead of the default model.` ## Quick Summary - Main jobs: `general assistant chat`, `multi-turn chat`, `chat model lookup`, `prompt-response` - Default model: `GEMINI_3_1_PRO` - Main optional controls: `model`, `messages`, `maxTokens`, `temperature`, `topP` - Main trust signals: dry-run support, model lookup, OpenAI-compatible messages, explicit non-specialized scope ## Prerequisites - `WERYAI_API_KEY` must be set before calling the API. - Node.js `>=18` is required. - Real runs use the WeryAI chat completion API and may consume credits. ## When to use this skill Use this skill when the user wants: - a normal assistant-style answer - a direct chat-completions call - a multi-turn conversation via `messages` - model lookup or model selection before a chat run Do not use this skill when the user clearly wants: - blog writing - email drafting - ad copy - translation or summarization as the main task Those belong to the existing specialized `text/*` skills. ## OpenAI-compatible message shape This skill accepts standard chat-completions messages: ```json [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is artificial intelligence?" } ] ``` If you provide `messages`, they are passed through directly. If you provide only `prompt`, the runtime builds a simple messages array automatically. ## Commands ```sh # List available chat models node {baseDir}/scripts/models.js # Simple prompt-response chat node {baseDir}/scripts/write.js --json '{ "prompt":"Explain retrieval augmented generation in plain English", "temperature":0.7 }' # Explicit messages array node {baseDir}/scripts/write.js --json '{ "model":"GPT_5_4", "messages":[ {"role":"system","content":"You are concise and technical."}, {"role":"user","content":"Compare RAG and long-context prompting."} ] }' # Dry-run preview node {baseDir}/scripts/write.js --json '{ "prompt":"What is the difference between latency and throughput?" }' --dry-run ``` ## Workflow 1. If the user wants model choice or pricing context first, run `models.js`. 2. Use `write.js` for direct prompt-response or explicit `messages` chat. 3. Prefer `--dry-run` when validating payload shape without spending credits. 4. Return the assistant response directly when the call succeeds. ## Definition of Done - `models.js` returns the available chat models and pricing metadata. - `write.js` returns at least one assistant completion choice and non-empty text, or a clear API failure. ## Re-run Behavior - Re-running `models.js` is read-only and safe. - Re-running `write.js --dry-run` is safe and does not call the API. - Re-running `write.js` creates a fresh chat completion request and may consume additional credits. ## References - Official chat API summary: [references/chat-api.md](references/chat-api.md) - Chat completion API: [Chat Completion](https://docs.weryai.com/api-reference/chat/chat-completion) - Chat models API: [Get Chat Models List](https://docs.weryai.com/api-reference/chat/get-chat-models-list)