feat: Twitter Spaces Integration

[slkzgm]

Relates to:

No specific issue linked. This PR addresses new community-driven features.

Risks

Low. Existing users who relied on Deepgram by default will still see no change unless they explicitly define a new TRANSCRIPTION_PROVIDER. Fallback logic preserves original behavior (Deepgram → OpenAI → Local).

Background

What does this PR do?

• Adds an optional TRANSCRIPTION_PROVIDER setting (deepgram, openai, or local) with fallback logic.
  • If not set, old behavior remains: Deepgram → OpenAI → Local.
• Moves Twitter Spaces plugins from agent-twitter-client into this repo for better flexibility and less friction in plugin development.
• Introduces an AI-driven Twitter Spaces flow:
  1. Automatic Space launch decisions (random chance, business hours, cooldown intervals).
  2. Multi-speaker logic with queue management (maxSpeakers).
  3. GPT-based filler/idle messages, optional STT/TTS bridging, local audio recording.
  4. Graceful shutdown and cooldown for repeated Spaces.

Flow Recap

1. Periodic Check

   • If no Space is running, possibly launch one by shouldLaunchSpace() (random chance, business hours, cooldown).
   • If a Space is running, manageCurrentSpace() handles speaker timeouts, occupancy updates, queue acceptance, etc.

2. Space Creation

   • Generates a SpaceConfig (topics from config or GPT).
   • Attaches plugins: audio recording, STT/TTS, idle monitor, etc.
   • Hooks into speakerRequest, occupancyUpdate, idleTimeout, etc.

3. Speaker Logic

   • Maintains an activeSpeakers array + a queue if at capacity (maxSpeakers).
   • Enforces speakerMaxDurationMs per speaker.
   • If a speaker is removed, accept next in queue if available.

4. Stopping

   • stopSpace() finalizes the Space, logs completion, clears states, etc.
   • Resumes periodic checks at a slower interval until the next launch is decided.

Configuration

A) .env / Environment Variables

# Transcription Provider
TRANSCRIPTION_PROVIDER=         # Default is local (possible values: deepgram, openai, local)
OPENAI_API_KEY=sk-...
DEEPGRAM_API_KEY=...

B) character.json → "twitterSpaces" Field

{
  // ...
  "twitterSpaces": {
    "maxSpeakers": 2,
    "topics": [
      "Blockchain Trends",
      "AI Innovations"
    ],
    "typicalDurationMinutes": 45,
    "idleKickTimeoutMs": 300000,
    "minIntervalBetweenSpacesMinutes": 60,
    "businessHoursOnly": true,
    "randomChance": 0.3,
    "enableIdleMonitor": true,
    "enableSttTts": true,
    "enableRecording": false,
    "voiceId": "21m00Tcm4TlvDq8ikWAM",
    "sttLanguage": "en",
    "gptModel": "gpt-3.5-turbo",
    "systemPrompt": "You are a helpful AI co-host assistant.",
    "speakerMaxDurationMs": 240000
  }
}

• maxSpeakers: number of concurrent speakers allowed.
• topics: if none are provided, GPT generates them dynamically.
• randomChance: probability for each check cycle to spawn a new Space.
• speakerMaxDurationMs: maximum time each speaker can speak before removal.

What kind of change is this?

• Features (new Twitter Spaces integration and optional transcription provider).
• Improvements (unified plugin development, more config options, fallback logic maintained).

Documentation changes needed?

Yes, minimal. We must mention:

• The new TRANSCRIPTION_PROVIDER in .env (optional).
• The new twitterSpaces config section in character.json.

Testing

Where should a reviewer start?

• Check transcription.service.ts to review the fallback logic.
• Check new or relocated Twitter Spaces integration files for the Space lifecycle (launch, speaker management, idle detection, etc.).

Detailed testing steps

1. Define TRANSCRIPTION_PROVIDER in .env (or leave it empty to keep old fallback).
2. Provide valid API keys if choosing deepgram or openai.
3. Define twitterSpaces.randomChance in character json to 1 (for 100% rate of starting a space)
4. Run the agent; verify that Spaces launch automatically, respect the chosen transcription provider, and handle multi-speaker logic as expected.

No special database migrations are needed. Basic local runs and logs confirm correct functioning.

Future Improvements

• More robust decision logic for accepting speakers, switching, and timeouts.
• Realtime API plugin for smoother, on-the-fly conversation handling.
• Solo Broadcast Mode: launch Spaces focused on a single host monologue with no external speakers.
• True VAD (Voice Activity Detection) to detect when a speaker finishes talking, instead of relying on manual mute/unmute cues.
• Advanced scheduling triggers (e.g., event-based or calendar-based).
• Analytics & insights for post-Space summaries or usage metrics.

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[github-actions]

Hi @slkzgm! Welcome to the ai16z community. Thanks for submitting your first pull request; your efforts are helping us accelerate towards AGI. We'll review it shortly. You are now a ai16z contributor!

[odilitime]

please add back the documentation

[lalalune]

Some conflicts that need review, we should prioritize getting this in since it's a pretty big push