voice-ai-integration

# Shengwang Integration ## Workflow ### Step 0: Ensure doc index exists (MANDATORY) > **⚠️ Execute this BEFORE any routing or code generation.** Check if `references/docs.txt` already exists. If it does, skip this step entirely. If it does not exist, download it: ```bash bash skills/voice-ai-integration/scripts/fetch-docs.sh ``` This downloads a static doc index from `doc.shengwang.cn` — no user data is sent. If download fails, proceed with local reference docs and fallback URLs. ### Step 1: Route to the correct product module Match the user's request to a product module using the route table. If the match is clear, route directly — do not ask extra questions. #### Route Table | User intent | Route to | |-------------|----------| | Credentials, AppID, REST auth | [general](references/general/credentials-and-auth.md) | | Generate Token, token server, AccessToken2 | [token-server](references/token-server/README.md) | | ConvoAI voice agent work | [conversational-ai](references/conversational-ai/README.md) | | RTC SDK integration | [rtc](references/rtc/README.md) | | RTM messaging / signaling | [rtm](references/rtm/README.md) | | Cloud Recording | [cloud-recording](references/cloud-recording/README.md) | | Download SDK, sample project, GitHub repo | Route to the relevant product module above | #### Product Recognition Aid When the user describes a use case without naming a product, use this to infer the match: | Product | What it does | Typical user says | |---------|-------------|-------------------| | ConvoAI | AI voice agent (ASR→LLM→TTS over RTC) | "AI语音", "voice bot", "对话式AI", "AI agent", "AI 客服" | | RTC SDK | Real-time audio/video between humans | "视频通话", "直播", "video call", "live streaming" | | RTM | Real-time messaging / signaling | "聊天", "消息", "chat", "signaling" | | Cloud Recording | Record RTC sessions server-side | "录制", "recording", "存档", "回看" | | Token generation | Generate RTC / RTM tokens | "token", "鉴权", "token server" | #### Common Combinations | Use case | Products needed | |----------|----------------| | AI voice assistant | ConvoAI (primary) + RTC SDK (client) | | AI voice assistant + chat history | ConvoAI + RTC SDK + RTM | | 1v1 / group video call | RTC SDK | | Video call + chat | RTC SDK + RTM | | Live streaming with recording | RTC SDK + Cloud Recording | | Record AI conversations | ConvoAI + RTC SDK + Cloud Recording | | Chat / messaging only | RTM | #### Routing Rules - Infer obvious context — do not ask if the answer is already clear - Do not ask product-specific configuration questions (providers, SDK versions, project structure) at this level; let the product module handle those - If the product is clear but the request mode is ambiguous (quickstart vs debugging vs feature), let the product module decide internally - If multiple products are needed, route to the primary product first, then address supporting products in order - ConvoAI has the most detailed internal routing (see its README.md); always delegate ConvoAI-specific decisions to its module #### When the product is still unclear If the route table and recognition aid above are not enough to determine the product: 1. Ask only for the missing detail that would change the routing decision 2. Ask at most one question at a time 3. Prefer natural wording over an interview script 4. Once the product is clear, produce a short routing recap and continue: **ZH:** ```text 已了解的信息 ───────────────────────────── 场景： [use case] 主要产品： [primary product] 配套产品： [supporting products / 无] ───────────────────────────── ``` **EN:** ```text What I have so far ───────────────────────────── Use case: [use case] Primary: [primary product] Supporting: [supporting products / none] ───────────────────────────── ``` Do not stop for a separate confirmation step — continue to the product module automatically. ### Step 2: Let the product module drive implementation Each product module follows its own workflow. Do not duplicate implementation logic here. Common pattern across modules: 1. Use local reference docs in `references/` first 2. Fetch remote docs via [doc-fetching.md](references/doc-fetching.md) only when local references are insufficient 3. Fallback to web search only after doc fetching has been attempted ## Runtime Requirements - `bash` and `curl` for local doc-fetch helper scripts - `git` for sample-repo inspection when the sample-aligned path is chosen - Network access to `doc.shengwang.cn`, `doc-mcp.shengwang.cn`, and `gitee.com` Network behavior: - `fetch-docs.sh` downloads a static file from `doc.shengwang.cn/llms.txt` — no user data is sent - `fetch-doc-content.sh` fetches a single doc page by URI from `doc-mcp.shengwang.cn` — only the doc URI is sent, no user context - `git clone` is used only for sample repo inspection from `gitee.com` — only the repo URL is sent Credential and service-activation requirements vary by product — see each product module and [general/credentials-and-auth.md](references/general/credentials-and-auth.md) for details. Never hardcode credentials. ## Safety & Consent Rules - Do not clone external repos into the user's main workspace by default — prefer a temporary path - Do not modify an existing user project until the user explicitly asks for code generation - Do not write secrets into project files — prefer env vars and example placeholders - Before performing network fetches or repo clones, state what will be downloaded - If a required dependency or credential is missing, stop and explain the blocker ## Download Rules - Use `git clone --depth 1 <url>` with HTTPS repo root URLs only - On any download failure: report the error, provide the URL for manual download, never silently skip ## Links - Console: https://console.shengwang.cn/ - Docs (CN): https://doc.shengwang.cn/ - GitHub: https://github.com/Shengwang-Community