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Project Tango

Project Tango is EdStratum Labs' private, persona-driven AI voice companion. It combines a Next.js WebRTC interface with a FastAPI/LiveKit agent backend and is self-hosted on Schubert at https://project-tango.schubert.life.

Stack

  • Next.js 15 App Router frontend and same-origin backend-for-frontend routes
  • FastAPI account, authorization, LiveKit token, dispatch, history, and memory APIs
  • LiveKit Agents SDK voice worker
  • PostgreSQL schema tango for users, sessions, persona policy, and memories
  • Deepgram Flux for English and Nova-3 tl for Tagalog speech recognition
  • ElevenLabs Flash v2.5 and the optional Jeremiah F5-TTS sidecar
  • LiteLLM-only model routing to local and approved hosted models

Account model

The interface is gated by a one-field generated-password login. FastAPI stores Argon2id password hashes, HMAC lookup digests, and opaque server-session token digests; plaintext passwords are shown only once when an admin creates or resets an account. Regular users see only their assigned personas, and each assignment may use the persona default model or an admin-selected allowlisted override. Administrators also see each persona's source default model on the main Tango screen and may choose any allowlisted model for their own next voice session. These session choices do not change the persona defaults or regular-user policy.

The admin dashboard lives at /admin. It includes the current source-controlled persona/model and voice-pipeline map alongside account provisioning. Accounts created in the dashboard are always regular users; the first admin is created with the backend bootstrap command documented in RB-04.

Development

See docs/setup.md for environment, migration, build, and deployment steps. The production architecture and security boundary are in docs/architecture.md. Repository agents must follow AGENTS.md before making any change.

About

Project Tango is an AI-powered web application providing specialized voice agents for diverse tasks. Built on a modern voice framework, it prioritizes ultra-low latency and real-time transcriptions using Deepgram STT, ElevenLabs TTS, and a hybrid LLM routing layer for a scalable, privacy-conscious experience.

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