init

Scaffold a new Pipecat project by collecting configuration from the user and running `pipecat init` in non-interactive mode. ## Arguments ``` /init [<target-dir>] ``` - `<target-dir>` (optional): Directory to create the project in. Defaults to a new directory named after the project. Use `.` for the current directory. ## Prerequisites Check if `pipecat` is installed by running `pipecat --version`. If not installed, tell the user to install it with `uv tool install pipecat-ai-cli` and stop. ## Discover Available Options Before asking the user any questions, run `pipecat init --list-options` to get the current valid values for all fields. The output is JSON: ```json { "bot_type": ["web", "telephony"], "transports": { "web": ["daily", "smallwebrtc"], "telephony": ["twilio", "telnyx", ...] }, "stt": ["deepgram_stt", "openai_stt", ...], "llm": ["openai_llm", "anthropic_llm", ...], "tts": ["cartesia_tts", "elevenlabs_tts", ...], "realtime": ["openai_realtime", "gemini_live_realtime", ...], "video": ["heygen_video", "tavus_video", "simli_video"] } ``` Use this data to populate the choices in every question below. Do NOT hardcode service lists — always use the values from `--list-options`. ## Configuration Flow Walk through the following questions to build the project configuration. After collecting all answers, show a summary and run the command. **Choosing the right interaction method:** - **AskUserQuestion** — Use for questions with a small, fixed set of options (bot type, pipeline mode, client framework, yes/no questions). This gives a clean clickable UI. - **Show list as text** — Use for questions with many options (STT, LLM, TTS, realtime, video, transports). Display the full list of available options from `--list-options` formatted as a readable list, then let the user reply with their choice in chat. ### Step 1: Project Name Ask the user for a project name. This is passed as the target directory (positionally) — the project is scaffolded in place in a directory of that name, and the project identifier is derived from it. ### Step 2: Bot Type Ask the user to choose a bot type: - **Web/Mobile** (`web`) - Browser or mobile app - **Telephony** (`telephony`) - Phone calls ### Step 3: Client Framework (web only) If the bot type is `web`, ask the user to choose a client framework: - **React** (`react`) - **Vanilla JS** (`vanilla`) - **None** (`none`) - Server only, no client generated If the user chose React, ask which dev server: - **Vite** (`vite`) - **Next.js** (`nextjs`) Skip this step entirely for telephony bots. ### Step 4: Transport Show the user the full list of available transports from `--list-options`, filtered by the selected bot type. Let the user reply with their choice. If the user chose a `daily_pstn` transport, ask for mode: - Dial-in (receive calls) → use `--daily-pstn-mode dial-in` - Dial-out (make calls) → use `--daily-pstn-mode dial-out` If the user chose a `twilio_daily_sip` transport, ask for mode: - Dial-in (receive calls) → use `--twilio-daily-sip-mode dial-in` - Dial-out (make calls) → use `--twilio-daily-sip-mode dial-out` Then ask if they want to add an additional transport for local testing. This is common — e.g. a telephony bot that also supports WebRTC for development. ### Step 5: Pipeline Mode Ask the user to choose a pipeline architecture: - **Cascade** (`cascade`) - STT → LLM → TTS pipeline - **Realtime** (`realtime`) - Speech-to-speech model ### Step 6: AI Services **If cascade mode**, show the full list of available options from `--list-options` for each service and let the user reply with their choice: 1. **Speech-to-Text (STT)** — Show all available STT services 2. **Language Model (LLM)** — Show all available LLM services 3. **Text-to-Speech (TTS)** — Show all available TTS services **If realtime mode**, show all available realtime services and let the user reply with their choice. For each service question, display the options as a numbered vertical list (one per line) so the user can easily scan and pick one. ### Step 7: Features Show the user the default feature settings and ask if they want to customize: **Defaults:** - Audio recording: No - Transcription logging: No - Video avatar service: None - Video input: No (web only) - Video output: No (web only) - Observability: No If they want to customize, ask about each feature. For video avatar service (web bots only), use the video options from `--list-options`. If a video avatar service is selected, video output is automatically enabled. ### Step 8: Deployment Ask if they want to generate Pipecat Cloud deployment files (Dockerfile, pcc-deploy.toml). Default is yes. If deploying to cloud, ask if they want to enable Krisp noise cancellation. Default is no. ## Building the Command After collecting all answers, build the `pipecat init` command using non-interactive flags. Lead with the project name as the positional target directory — the project is scaffolded in place there: ``` pipecat init <project_name> \ --bot-type <web|telephony> \ --transport <transport> \ --mode <cascade|realtime> \ [--stt <service>] \ [--llm <service>] \ [--tts <service>] \ [--realtime <service>] \ [--video <service>] \ [--client-framework <react|vanilla|none>] \ [--client-server <vite|nextjs>] \ [--daily-pstn-mode <dial-in|dial-out>] \ [--twilio-daily-sip-mode <dial-in|dial-out>] \ [--recording | --no-recording] \ [--transcription | --no-transcription] \ [--video-input | --no-video-input] \ [--video-output | --no-video-output] \ [--deploy-to-cloud | --no-deploy-to-cloud] \ [--enable-krisp | --no-enable-krisp] \ [--observability | --no-observability] \ [--eval | --no-eval] ``` Passing scaffold flags makes `pipecat init` run non-interactively (no prompts) and scaffold the runnable bot in place, alongside the coding-agent guide files it writes (AGENTS.md, CLAUDE.md). Use `.` as the target to scaffold into the current directory instead of a new one. For multiple transports, repeat the `--transport` flag (e.g. `--transport twilio --transport smallwebrtc`). ## Confirmation Before running the command, show the user a summary of their choices: - Project name - Bot type - Client framework (if web) - Transport(s) - Pipeline mode and services - Features enabled - Deployment target Ask the user to confirm before proceeding. If they want to change something, go back and re-ask that specific question. ## Running the Command Run the `pipecat init` command. The positional target directory controls where the project is created — use the `<target-dir>` argument if the user provided one, otherwise default to a new directory named after the project. If the command succeeds, show the user what was generated and suggest next steps: 1. `cd <project_name>/server` 2. Copy `.env.example` to `.env` and fill in API keys 3. Run the bot If deploying to cloud, also mention they can use `/pipecat-cloud:deploy` to deploy. ## Error Handling - If `pipecat init` fails with validation errors, show the error and help the user fix their choices. - If the target directory already exists and is not empty, warn the user before proceeding.