# Voice Assistant **Realtime speech processing over WebSocket — NVIDIA ASR · Agent orchestration · VoxCPM TTS** ![Python](https://img.shields.io/badge/Python-3.12%2B-3776AB?logo=python&logoColor=white) ![Protocol](https://img.shields.io/badge/WebSocket-Protocol%201.0-39485C) ![Release](https://img.shields.io/badge/Release-V1%20development-566575) A modular voice pipeline for streaming audio input, speech transcription, agent responses, and synthesized speech output. Built with FastAPI and asynchronous Python, with explicit session lifecycle, turn ownership, interruption, and provider cleanup. > **V1 scope:** NVIDIA STT and VoxCPM TTS are real providers; the Agent is a mock implementation. Production readiness and container deployment have not yet been validated. ## Contents - [Architecture](#architecture) - [Quickstart](#quickstart) - [Configuration](#configuration) - [WebSocket protocol](#websocket-protocol) - [Lifecycle and interruption](#lifecycle-and-interruption) - [Testing](#testing) - [Project structure](#project-structure) - [Known limitations](#known-limitations) - [Architecture Backbone & Abstraction Boundaries](#architecture-backbone--abstraction-boundaries) ## Architecture ```mermaid flowchart TB C[Audio Client] <-->|WebSocket /ws/audio · JSON + binary PCM| G[Audio Gateway · FastAPI] G --> P[VoicePipeline] P --- S[SessionState · session and audio sequence] P --- T[TurnManager · semantic turn state] G --> STT[NVIDIA ASR · STT per turn] STT -->|Transcript events| P P --> A[Mock Agent · per session] A -->|Response text| P P --> V[VoxCPM TTS · per session] V -->|PCM chunks| G G -->|Streamed audio| C ``` The **Audio Gateway** handles transport and protocol messages. **VoicePipeline** coordinates processing and task ownership. **SessionState** tracks session and audio sequence; **TurnManager** enforces turn transitions. A new STT adapter is created for each turn, while Agent and TTS adapters are created per session. ## Architecture Backbone & Abstraction Boundaries AgentVoice follows a **provider-independent architecture** built around explicit contracts, lifecycle ownership, and asynchronous streaming. The architecture separates five concerns: - **Transport:** WebSocket communication and protocol serialization. - **Orchestration:** Coordination of STT, Agent, and TTS execution. - **Lifecycle:** Session state, turn transitions, interruption, and task ownership. - **Provider contracts:** Abstract interfaces defining component behavior. - **Provider implementations:** Concrete integrations with NVIDIA, OCI Generative AI, and VoxCPM. ### Architectural Backbone ```mermaid flowchart TB Client["Web Client / Audio Client"] Gateway["Audio Gateway
FastAPI · WebSocket"] Pipeline["VoicePipeline
Orchestration & Streaming"] Session["SessionState
Session Lifecycle"] Turns["TurnManager
Semantic Turn Lifecycle"] subgraph Contracts["Provider Abstraction Layer"] direction LR STTA["STTAdapter
Abstract Contract"] AgentA["AgentAdapter
Abstract Contract"] TTSA["TTSAdapter
Abstract Contract"] end subgraph Implementations["Provider Implementation Layer"] direction LR Nvidia["NvidiaSTTAdapter"] OCI["OCIAgentAdapter"] Mock["MockAgentAdapter"] Vox["VoxCPMTTSAdapter"] end subgraph External["External AI Services"] ASR["NVIDIA ASR"] LLM["OCI Generative AI"] TTS["VoxCPM"] end Client <-->|"JSON Events + Binary PCM"| Gateway Gateway --> Pipeline Pipeline --- Session Pipeline --- Turns Pipeline --> STTA Pipeline --> AgentA Pipeline --> TTSA STTA -.->|implements| Nvidia AgentA -.->|implements| OCI AgentA -.->|implements| Mock TTSA -.->|implements| Vox Nvidia --> ASR OCI --> LLM Vox --> TTS ``` The `VoicePipeline` depends on provider contracts rather than concrete implementations. Provider selection is performed through configuration and dynamic factories. This allows implementations to evolve without requiring the Audio Gateway to understand provider-specific APIs. ### Provider Contracts | Abstraction | Contract | Implementations | Responsibility | |---|---|---|---| | Speech-to-text | `STTAdapter` | `NvidiaSTTAdapter`, `MockSTTAdapter` | Audio ingestion and transcript events | | Agent | `AgentAdapter` | `OCIAgentAdapter`, `MockAgentAdapter` | Text processing and conversational responses | | Text-to-speech | `TTSAdapter` | `VoxCPMTTSAdapter`, `MockTTSAdapter` | Speech synthesis and audio streaming | The `AgentAdapter` defines the common text-processing interface. OCI-specific incremental generation is currently exposed through an additional `stream()` method, with streaming capability detected by the orchestration layer. ### Runtime Composition Provider implementations are selected through environment configuration and resolved by the provider factory. ```mermaid flowchart LR Config["Environment YAML"] Catalog["Provider Catalog"] Factory["Provider Factories"] Contracts["Adapter Contracts"] Runtime["VoicePipeline"] Config --> Factory Catalog --> Factory Factory -->|Validate implementation| Contracts Factory -->|Instantiate providers| Runtime ``` The primary configuration components are: | Component | Location | |---|---| | Environment selection | `config/loader.py` | | Typed configuration | `config/models.py` | | Provider catalog | `config/providers.yaml` | | Dynamic provider loading | `providers.py` | | Session lifecycle | `domain/session.py` | | Semantic turn lifecycle | `turn_manager.py` | | Execution orchestration | `voice_pipeline.py` | ### Streaming Execution Backbone The streaming pipeline allows OCI Generative AI to continue producing text while VoxCPM synthesizes previously completed text segments. ```mermaid flowchart TB Input["Microphone / PCM Input"] Gateway["Audio Gateway"] STT["NVIDIA STT"] Transcript["Final Transcript"] subgraph Pipeline["VoicePipeline · Concurrent Execution"] direction TB Agent["OCIAgentAdapter.stream()"] Bridge["OCI SSE Async Bridge"] Chunker["TextChunker"] Queue["Bounded Segment Queue"] Synth["VoxCPM TTS Streaming"] Agent --> Bridge Bridge --> Chunker Chunker --> Queue Queue --> Synth end OCI["OCI Generative AI"] Vox["VoxCPM Service"] Output["WebSocket PCM Output"] Input --> Gateway Gateway --> STT STT --> Transcript Transcript --> Agent Agent <--> OCI Synth <--> Vox Synth --> Gateway Gateway --> Output ``` The pipeline uses bounded queues and asynchronous task coordination to support incremental generation, ordered synthesis, and cooperative cancellation. ### Lifecycle Ownership AgentVoice separates semantic state from asynchronous execution. ```mermaid flowchart LR Listening["LISTENING"] Processing["PROCESSING"] Speaking["SPEAKING"] Completed["COMPLETED"] Interrupted["INTERRUPTED"] Listening -->|"STT final"| Processing Processing -->|"First TTS segment"| Speaking Speaking -->|"Synthesis complete"| Completed Listening --> Interrupted Processing --> Interrupted Speaking --> Interrupted ``` **Ownership responsibilities:** | Component | Owns | |---|---| | Audio Gateway | WebSocket connection, protocol messages, provider cleanup coordination | | SessionState | Session lifecycle and audio sequence validation | | TurnManager | Semantic turn state transitions | | VoicePipeline | Turn execution task and Agent/TTS orchestration | | OCI streaming bridge | SSE reader, event queue, and stream closure | | Provider adapters | Provider-specific requests, connections, and data formats | Cancellation is cooperative. The system requests cancellation and waits for task termination, but termination of blocking external operations depends on the underlying provider and transport behavior. ### Architectural Extension Points The abstraction layer allows additional implementations to be introduced through the provider catalog. For example, a future LiteLLM integration could implement the Agent contract without requiring a redesign of the Gateway or the semantic turn lifecycle. ```mermaid flowchart TB Pipeline["VoicePipeline"] Contract["AgentAdapter"] OCI["OCIAgentAdapter
Current"] Mock["MockAgentAdapter
Testing"] Lite["LiteLLMAgentAdapter
Future"] Pipeline --> Contract Contract -.-> OCI Contract -.-> Mock Contract -.-> Lite ``` **Design principle:** transport, orchestration, lifecycle, and provider-specific integrations remain separate concerns. Provider independence is established through contracts and factories, while streaming and cancellation behavior are validated at their respective integration boundaries. ## Quickstart ### Requirements - Python 3.12 or newer and [uv](https://docs.astral.sh/uv/) - Accessible NVIDIA ASR and VoxCPM services - Run commands from the repository root (`config/` is resolved relative to the working directory) ### Install ```bash uv sync ``` ### Start the gateway With the configured provider services running: ```bash APP_ENV=development uv run uvicorn \ voice_assistant.audio_gateway.app.main:app \ --host 127.0.0.1 --port 8001 ``` Check availability: ```bash curl http://127.0.0.1:8001/ready # {"status":"ready"} ``` > `/ready` reports Gateway availability; it does **not** verify NVIDIA ASR or VoxCPM health. ## Configuration `APP_ENV` selects `config/.yaml`; the default is `development`. `config/providers.yaml` maps provider names to Python implementations and capability metadata. YAML data is validated using Pydantic models. | Component | Development provider | Configuration | | --- | --- | --- | | Speech-to-text | NVIDIA ASR | `127.0.0.1:9000`, `pt-BR`, punctuation enabled | | Agent | Mock Agent | In-process; simulated text response | | Text-to-speech | VoxCPM | `http://127.0.0.1:8000`, `openbmb/VoxCPM2`, `default` voice | To select another environment: ```bash APP_ENV=staging uv run uvicorn \ voice_assistant.audio_gateway.app.main:app \ --host 127.0.0.1 --port 8001 ``` The `staging` and `production` files are present, but deployment readiness for those environments has not been established. When services run in different containers or machines, replace loopback addresses with reachable service endpoints. ## WebSocket protocol | Property | Value | |---|---| | Endpoint | `ws://127.0.0.1:8001/ws/audio` | | Protocol version | `1.0` | | Input audio | PCM signed 16-bit little-endian, 16 kHz, mono | | Transport: | JSON control messages and binary PCM frames. | ### Typical exchange ```mermaid sequenceDiagram participant C as Client participant G as Audio Gateway participant P as VoicePipeline / Providers C->>G: session.start G-->>C: session.ready C->>G: audio.start G-->>C: turn.started loop Audio input C->>G: audio.chunk (turn_id, sequence_number) C->>G: Binary PCM frame P-->>G: STT partial events G-->>C: stt.partial end C->>G: audio.stop (turn_id) P-->>G: STT final transcript G-->>C: stt.final P-->>G: Agent response G-->>C: agent.response P-->>G: TTS PCM chunks G-->>C: Binary audio frames G-->>C: turn.ended ``` STT events may arrive while input audio is still streaming. Binary audio input is preceded by an `audio.chunk` control message containing `turn_id` and `sequence_number`. The Gateway limits each binary chunk to 64 KiB. ### Interruption and session closure - `interrupt` targets a `turn_id`. For a matching active turn, the Gateway cancels and awaits execution, aborts STT, releases turn state, and then acknowledges with `interrupted`. - `session.end` requests cleanup and session closure; successful completion is acknowledged with `session.ended`. - Errors are returned as structured `error` events (for example, `STT_START_FAILED` or `TURN_CANCEL_FAILED`). ## Lifecycle and interruption The system separates **semantic state** from **asynchronous execution**. `TurnManager` controls listening, processing, speaking, and completion; `VoicePipeline` owns the registered turn task. The Gateway coordinates provider shutdown and WebSocket delivery. Cancellation is cooperative: `task.cancel()` requests termination, and the Gateway awaits task completion before confirming a successful interruption. Startup rollback attempts to cancel any created task and abort a partially initialized STT provider. Failed cleanup is reported rather than represented as a successful retry. ## Testing Run the automated suite: ```bash uv run pytest -q ``` Run Gateway tests or targeted static checks: ```bash uv run pytest -q tests/test_gateway.py uv run ruff check src tests --select F401,F811,F821 ``` ### End-to-end smoke test With the Gateway, NVIDIA ASR, and VoxCPM services available: ```bash uv run python tools/voice_pipeline_smoke_test.py ``` The script reads `audios/chafik_normalize.wav` (16 kHz, mono, 16-bit PCM), sends audio over WebSocket, and checks for a final transcript, an Agent response, synthesized audio, and `turn.ended`. It writes raw output to `/tmp/voice_pipeline_response.pcm`. **Last verified checkpoint:** 142 automated tests passing; the full NVIDIA STT → Mock Agent → VoxCPM TTS smoke test completed successfully. These results describe the development environment, not a production SLA. ## Project structure ```text config/ Environment YAML and provider catalog src/voice_assistant/ audio_gateway/app/ WebSocket endpoint and protocol domain/ Session state and domain rules audio/ Canonical audio models stt/ STT contract, mock and NVIDIA adapter agent/ Agent contract and mock adapter tts/ TTS contract, mock and VoxCPM adapter config/ Typed configuration and loading voice_pipeline.py Turn execution and orchestration turn_manager.py Semantic turn state machine providers.py Provider factories tests/ Automated tests tools/ Integration and smoke scripts ``` ## Known limitations - **Mock Agent:** responses are simulated; the V1 does not yet include a production conversational agent. - **Cooperative cancellation:** a coroutine that ignores cancellation may remain active after a timeout. Logical session closure does not guarantee that all external resources have terminated. - **Provider availability:** readiness does not constitute an end-to-end health check. - **Development-oriented deployment:** loopback endpoints and a fixed smoke-test WAV are configured for local execution. - **Containers:** the repository's Dockerfile has not been implemented or validated for deployment. --- **Status:** V1 development baseline · Python 3.12+ · WebSocket protocol 1.0