init（初始化）

Scaffold a new Pipecat project by collecting configuration from the user and running pc init in non-interactive mode.

Arguments

/init [--output <PATH>]

• --output (optional): Directory where the project will be created. Defaults to the current directory.

Prerequisites

Check if pc is installed by running pc --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 pc init --list-options to get the current valid values for all fields. The output is 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 will be used as the directory name and project identifier.

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 pc init command using non-interactive flags:

pc init \
  --name <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] \
  --output <output_dir>

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 pc init command. Use --output to specify the output directory (from the --output argument, or default to ./<project_name>).

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 pc init fails with validation errors, show the error and help the user fix their choices.
• If the output directory already exists and is not empty, warn the user before proceeding.