From e7a3aa6123b42cd2e42b2eabb3f20295285ca743 Mon Sep 17 00:00:00 2001
From: James Juniper <217263268+jjuniper-dev@users.noreply.github.com>
Date: Sun, 21 Jun 2026 14:37:29 -0400
Subject: [PATCH 1/5] voxcpm phone assistant bridge

---
 .gitignore                    |    1 +
 README.md                     |   16 +-
 app.py                        |   10 +-
 lora_ft_webui.py              |   10 +-
 pyproject.toml                |    2 +-
 src/voxcpm/phone_assistant.py | 1004 +++++++++++++++++++++++++++++++++
 tests/test_phone_assistant.py |   37 ++
 uv.lock                       |  454 ---------------
 8 files changed, 1076 insertions(+), 458 deletions(-)
 create mode 100644 src/voxcpm/phone_assistant.py
 create mode 100644 tests/test_phone_assistant.py

diff --git a/.gitignore b/.gitignore
index f7fa9812..25971f25 100644
--- a/.gitignore
+++ b/.gitignore
@@ -5,3 +5,4 @@ voxcpm.egg-info
 .DS_Store
 ./pretrained_models/
 app_local.py
+.voxcpm-phone-profiles/
diff --git a/README.md b/README.md
index 0b31c85e..e15fb062 100644
--- a/README.md
+++ b/README.md
@@ -247,6 +247,20 @@ python app.py --device auto
 
 Supported values are `auto`, `cpu`, `mps`, `cuda`, and `cuda:N`. On Apple Silicon Macs, `auto` uses MPS when available.
 
+### Phone Assistant Bridge
+
+For a mobile-first assistant flow with voice input, webhook-backed replies, and VoxCPM voice cloning:
+
+```bash
+voxcpm-assistant --port 8809
+```
+
+Use a clean reference sample plus an exact transcript for the highest-quality cloned voice. If you connect a webhook, the app POSTs the user message and conversation history and expects a reply in plain text or in a `reply` field.
+If you want phone microphone dictation, install the optional ASR dependency separately with `pip install funasr`.
+You can also save a named voice enrollment once and reuse it later from the app's profile panel.
+By default, the assistant loads the saved `reddit-female` profile if it exists.
+To wire in your PCA backend automatically, set `PCA_BACKEND_URL` plus optional `PCA_BACKEND_TOKEN`, `PCA_ASSISTANT_CONTEXT`, and `PCA_BACKEND_MODE=auto|openai|custom` before launching.
+
 ### 🚢 Production Deployment (Nano-vLLM)
 
 For high-throughput serving, use **[Nano-vLLM-VoxCPM](https://github.com/a710128/nanovllm-voxcpm)** — a dedicated inference engine built on Nano-vLLM with concurrent request support and an async API.
@@ -627,4 +641,4 @@ VoxCPM model weights and code are open-sourced under the [Apache-2.0](LICENSE) l
 
 ## ⭐ Star History
 
-[Star History Chart](https://star-history.com/#OpenBMB/VoxCPM&Date)
\ No newline at end of file
+[Star History Chart](https://star-history.com/#OpenBMB/VoxCPM&Date)
diff --git a/app.py b/app.py
index 95eac945..dd889c73 100644
--- a/app.py
+++ b/app.py
@@ -5,9 +5,13 @@
 import numpy as np
 import gradio as gr
 from typing import Optional, Tuple
-from funasr import AutoModel
 from pathlib import Path
 
+try:
+    from funasr import AutoModel
+except ImportError:  # Optional dependency for ASR-assisted prompt transcription
+    AutoModel = None
+
 os.environ["TOKENIZERS_PARALLELISM"] = "false"
 
 import voxcpm
@@ -245,6 +249,10 @@ def get_or_load_voxcpm(self) -> voxcpm.VoxCPM:
         return self.voxcpm_model
 
     def get_or_load_asr_model(self) -> AutoModel:
+        if AutoModel is None:
+            raise RuntimeError(
+                "funasr is not installed. Install the optional ASR dependency to enable prompt transcription."
+            )
         if self.asr_model is not None:
             return self.asr_model
         logger.info(
diff --git a/lora_ft_webui.py b/lora_ft_webui.py
index e4a68228..6bd03283 100644
--- a/lora_ft_webui.py
+++ b/lora_ft_webui.py
@@ -22,7 +22,11 @@
 from voxcpm.core import VoxCPM
 from voxcpm.model.voxcpm import LoRAConfig
 import numpy as np
-from funasr import AutoModel
+
+try:
+    from funasr import AutoModel
+except ImportError:  # Optional dependency for ASR-assisted prompt transcription
+    AutoModel = None
 
 # --- Localization ---
 LANG_DICT = {
@@ -121,6 +125,10 @@ def detect_sample_rate(pretrained_path: str) -> Optional[int]:
 
 def get_or_load_asr_model():
     global asr_model
+    if AutoModel is None:
+        raise RuntimeError(
+            "funasr is not installed. Install the optional ASR dependency to enable prompt transcription."
+        )
     if asr_model is None:
         print("Loading ASR model (SenseVoiceSmall)...", file=sys.stderr)
         device = "cuda:0" if torch.cuda.is_available() else "cpu"
diff --git a/pyproject.toml b/pyproject.toml
index 45ae2ee3..b532da3f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -44,7 +44,6 @@ dependencies = [
     "soundfile",
     "librosa",
     "matplotlib",
-    "funasr",
     "spaces",
     "argbind",
     "safetensors"
@@ -62,6 +61,7 @@ dev = [
 
 [project.scripts]
 voxcpm = "voxcpm.cli:main"
+voxcpm-assistant = "voxcpm.phone_assistant:main"
 
 [project.urls]
 Homepage = "https://github.com/OpenBMB/VoxCPM"
diff --git a/src/voxcpm/phone_assistant.py b/src/voxcpm/phone_assistant.py
new file mode 100644
index 00000000..29856538
--- /dev/null
+++ b/src/voxcpm/phone_assistant.py
@@ -0,0 +1,1004 @@
+from __future__ import annotations
+
+import argparse
+import json
+import logging
+import os
+import sys
+import shutil
+from pathlib import Path
+from typing import Any, Optional
+
+import gradio as gr
+import numpy as np
+import requests
+
+try:
+    import torch
+except ImportError:  # pragma: no cover - torch is required by the project
+    torch = None
+
+try:
+    from funasr import AutoModel
+except ImportError:  # Optional dependency for speech-to-text input / transcripts
+    AutoModel = None
+
+from voxcpm.core import VoxCPM
+from voxcpm.model.utils import resolve_runtime_device
+
+os.environ["TOKENIZERS_PARALLELISM"] = "false"
+
+logger = logging.getLogger(__name__)
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s - %(levelname)s - %(message)s",
+    handlers=[logging.StreamHandler(sys.stdout)],
+)
+
+DEFAULT_MODEL_ID = "openbmb/VoxCPM2"
+DEFAULT_ASR_MODEL_ID = "iic/SenseVoiceSmall"
+PROFILE_DIR = Path.cwd() / ".voxcpm-phone-profiles"
+DEFAULT_BACKEND_URL = os.environ.get("PCA_BACKEND_URL", "").strip()
+DEFAULT_BACKEND_TOKEN = os.environ.get("PCA_BACKEND_TOKEN", "").strip()
+DEFAULT_BACKEND_CONTEXT = os.environ.get("PCA_ASSISTANT_CONTEXT", "").strip()
+DEFAULT_BACKEND_MODE = os.environ.get("PCA_BACKEND_MODE", "auto").strip().lower()
+
+APP_THEME = gr.themes.Soft(
+    primary_hue="cyan",
+    secondary_hue="orange",
+    neutral_hue="slate",
+    font=[gr.themes.GoogleFont("Space Grotesk"), "IBM Plex Sans", "sans-serif"],
+)
+
+APP_CSS = """
+:root {
+    --bg0: #07111e;
+    --bg1: #0d1727;
+    --bg2: rgba(12, 20, 34, 0.78);
+    --stroke: rgba(170, 210, 255, 0.16);
+    --text: #edf4ff;
+    --muted: #9fb0c8;
+    --accent: #65f0ff;
+    --accent2: #ffba6e;
+    --shadow: 0 24px 80px rgba(0, 0, 0, 0.35);
+}
+
+body, .gradio-container {
+    background:
+        radial-gradient(circle at top left, rgba(101, 240, 255, 0.20), transparent 34%),
+        radial-gradient(circle at 85% 15%, rgba(255, 186, 110, 0.14), transparent 24%),
+        linear-gradient(180deg, #07111e 0%, #091422 50%, #050a12 100%) !important;
+    color: var(--text) !important;
+}
+
+.assistant-shell {
+    max-width: 1180px;
+    margin: 0 auto;
+    padding: 18px 16px 28px;
+}
+
+.assistant-hero {
+    border: 1px solid var(--stroke);
+    border-radius: 28px;
+    padding: 22px 22px 20px;
+    background: linear-gradient(180deg, rgba(19, 29, 48, 0.95), rgba(11, 18, 31, 0.88));
+    box-shadow: var(--shadow);
+    margin-bottom: 16px;
+}
+
+.assistant-kicker {
+    letter-spacing: 0.16em;
+    text-transform: uppercase;
+    font-size: 0.72rem;
+    color: var(--accent);
+    margin-bottom: 10px;
+}
+
+.assistant-hero h1 {
+    margin: 0;
+    font-size: clamp(2rem, 5vw, 3.75rem);
+    line-height: 0.98;
+    letter-spacing: -0.05em;
+}
+
+.assistant-hero p {
+    margin: 12px 0 0;
+    color: var(--muted);
+    max-width: 70ch;
+    font-size: 1rem;
+}
+
+.assistant-grid {
+    display: grid;
+    grid-template-columns: 1.35fr 1fr;
+    gap: 16px;
+    align-items: start;
+}
+
+.panel {
+    border: 1px solid var(--stroke);
+    border-radius: 24px;
+    background: var(--bg2);
+    backdrop-filter: blur(18px);
+    box-shadow: var(--shadow);
+    padding: 16px;
+}
+
+.panel-title {
+    color: var(--text);
+    font-size: 0.74rem;
+    text-transform: uppercase;
+    letter-spacing: 0.18em;
+    margin-bottom: 10px;
+}
+
+.gradio-container .gr-button.primary,
+.gradio-container .gr-button.gr-button-primary {
+    background: linear-gradient(135deg, var(--accent), #7bdbff) !important;
+    color: #03131b !important;
+    border: 0 !important;
+    font-weight: 700 !important;
+    box-shadow: 0 12px 30px rgba(101, 240, 255, 0.22);
+}
+
+.gradio-container .gr-button.secondary {
+    border: 1px solid var(--stroke) !important;
+    background: rgba(255, 255, 255, 0.03) !important;
+}
+
+.gradio-container textarea,
+.gradio-container input,
+.gradio-container .wrap {
+    color: var(--text) !important;
+}
+
+.gradio-container .tab-nav {
+    gap: 8px;
+}
+
+.gradio-container .chatbot {
+    min-height: 460px;
+}
+
+.gradio-container .gr-box,
+.gradio-container .gr-panel {
+    border-color: var(--stroke) !important;
+}
+
+@media (max-width: 980px) {
+    .assistant-grid {
+        grid-template-columns: 1fr;
+    }
+}
+
+@media (max-width: 640px) {
+    .assistant-shell {
+        padding: 10px 8px 22px;
+    }
+
+    .assistant-hero {
+        padding: 18px 16px 16px;
+        border-radius: 22px;
+    }
+
+    .panel {
+        border-radius: 20px;
+        padding: 14px;
+    }
+}
+"""
+
+
+def _clean_text(value: Optional[str]) -> str:
+    return (value or "").strip()
+
+
+def _normalize_spaces(value: str) -> str:
+    return " ".join(value.replace("\n", " ").split())
+
+
+def _format_history(history: list[tuple[str, str]]) -> list[tuple[str, str]]:
+    return history or []
+
+
+def _build_final_text(text: str, control: str) -> str:
+    text = _normalize_spaces(_clean_text(text))
+    control = _normalize_spaces(_clean_text(control))
+    return f"({control}){text}" if control else text
+
+
+def _extract_reply_text(payload: Any) -> str:
+    if isinstance(payload, str):
+        return payload.strip()
+
+    if isinstance(payload, dict):
+        for key in ("reply", "text", "message", "content", "answer"):
+            value = payload.get(key)
+            if isinstance(value, str) and value.strip():
+                return value.strip()
+
+        choices = payload.get("choices")
+        if isinstance(choices, list) and choices:
+            first = choices[0]
+            if isinstance(first, dict):
+                message = first.get("message")
+                if isinstance(message, dict):
+                    content = message.get("content")
+                    if isinstance(content, str) and content.strip():
+                        return content.strip()
+                content = first.get("text")
+                if isinstance(content, str) and content.strip():
+                    return content.strip()
+
+        data = payload.get("data")
+        if isinstance(data, str) and data.strip():
+            return data.strip()
+
+    return ""
+
+
+def _build_backend_messages(
+    user_message: str,
+    history: list[tuple[str, str]],
+    assistant_context: str,
+) -> list[dict[str, str]]:
+    messages: list[dict[str, str]] = []
+    assistant_context = _clean_text(assistant_context)
+    if assistant_context:
+        messages.append({"role": "system", "content": assistant_context})
+
+    for user_turn, assistant_turn in history:
+        if _clean_text(user_turn):
+            messages.append({"role": "user", "content": user_turn})
+        if _clean_text(assistant_turn):
+            messages.append({"role": "assistant", "content": assistant_turn})
+
+    messages.append({"role": "user", "content": user_message})
+    return messages
+
+
+def _profile_path(profile_name: str) -> Path:
+    safe_name = "".join(ch for ch in profile_name.strip().lower() if ch.isalnum() or ch in ("-", "_"))
+    if not safe_name:
+        safe_name = "default"
+    return PROFILE_DIR / f"{safe_name}.json"
+
+
+def _copy_reference_audio(source_path: str, profile_name: str) -> str:
+    PROFILE_DIR.mkdir(parents=True, exist_ok=True)
+    source = Path(source_path)
+    suffix = source.suffix or ".wav"
+    target_name = "".join(ch for ch in profile_name.strip().lower() if ch.isalnum() or ch in ("-", "_")) or "default"
+    target = PROFILE_DIR / f"{target_name}{suffix}"
+    shutil.copy2(source, target)
+    return str(target)
+
+
+def _load_profile(profile_name: str) -> dict[str, Any]:
+    path = _profile_path(profile_name)
+    if not path.exists():
+        raise FileNotFoundError(f"Voice profile not found: {profile_name}")
+    return json.loads(path.read_text(encoding="utf-8"))
+
+
+def _save_profile(profile_name: str, payload: dict[str, Any]) -> str:
+    PROFILE_DIR.mkdir(parents=True, exist_ok=True)
+    path = _profile_path(profile_name)
+    path.write_text(json.dumps(payload, indent=2, ensure_ascii=False), encoding="utf-8")
+    return str(path)
+
+
+class PhoneAssistantRuntime:
+    def __init__(
+        self,
+        model_id: str = DEFAULT_MODEL_ID,
+        device: str = "auto",
+        load_denoiser: bool = True,
+        optimize: bool = True,
+        zipenhancer_model_path: str | None = None,
+    ) -> None:
+        self._model_id = model_id
+        self.device = resolve_runtime_device(device, "cuda")
+        self.optimize = optimize and self.device.startswith("cuda")
+        self.load_denoiser = load_denoiser
+        self.zipenhancer_model_path = zipenhancer_model_path
+        self._model: Optional[VoxCPM] = None
+        self._asr_model: Optional[Any] = None
+        self._asr_device = "cuda:0" if self.device.startswith("cuda") else "cpu"
+
+    def model(self) -> VoxCPM:
+        if self._model is not None:
+            return self._model
+
+        logger.info("Loading VoxCPM model: %s", self._model_id)
+        self._model = VoxCPM.from_pretrained(
+            hf_model_id=self._model_id,
+            load_denoiser=self.load_denoiser,
+            zipenhancer_model_id=self.zipenhancer_model_path
+            if self.zipenhancer_model_path
+            else None,
+            optimize=self.optimize,
+            device=self.device,
+        )
+        logger.info("VoxCPM loaded successfully.")
+        return self._model
+
+    def asr_model(self):
+        if AutoModel is None:
+            raise RuntimeError(
+                "Speech-to-text is not installed. Type your message manually or install the optional ASR dependency."
+            )
+        if self._asr_model is not None:
+            return self._asr_model
+
+        logger.info("Loading ASR model: %s on %s", DEFAULT_ASR_MODEL_ID, self._asr_device)
+        self._asr_model = AutoModel(
+            model=DEFAULT_ASR_MODEL_ID,
+            disable_update=True,
+            log_level="ERROR",
+            device=self._asr_device,
+        )
+        return self._asr_model
+
+    def transcribe(self, audio_path: Optional[str]) -> str:
+        if not audio_path:
+            return ""
+        if not Path(audio_path).exists():
+            raise FileNotFoundError(f"Audio file does not exist: {audio_path}")
+
+        result = self.asr_model().generate(
+            input=audio_path,
+            language="auto",
+            use_itn=True,
+        )
+
+        if not result:
+            return ""
+        transcript = result[0].get("text", "")
+        if not isinstance(transcript, str):
+            return ""
+        return transcript.split("|>")[-1].strip()
+
+    def synthesize(
+        self,
+        *,
+        text: str,
+        reference_audio: Optional[str],
+        reference_transcript: Optional[str],
+        control: Optional[str],
+        normalize: bool,
+        denoise: bool,
+        cfg_value: float,
+        inference_timesteps: int,
+        auto_transcribe_reference: bool,
+    ) -> tuple[int, np.ndarray, str]:
+        model = self.model()
+
+        target_text = _build_final_text(text, control or "")
+        reference_audio = _clean_text(reference_audio) or None
+        reference_transcript = _clean_text(reference_transcript) or None
+
+        if reference_audio and not reference_transcript and auto_transcribe_reference:
+            try:
+                reference_transcript = self.transcribe(reference_audio)
+            except Exception as exc:  # pragma: no cover - depends on optional ASR
+                logger.warning("Reference transcription failed: %s", exc)
+
+        kwargs: dict[str, Any] = dict(
+            text=target_text,
+            cfg_value=float(cfg_value),
+            inference_timesteps=int(inference_timesteps),
+            normalize=bool(normalize),
+            denoise=bool(denoise and reference_audio),
+        )
+
+        if reference_audio:
+            kwargs["reference_wav_path"] = reference_audio
+            if reference_transcript:
+                kwargs["prompt_wav_path"] = reference_audio
+                kwargs["prompt_text"] = reference_transcript
+
+        logger.info("Generating audio: cfg=%s steps=%s reference=%s", cfg_value, inference_timesteps, bool(reference_audio))
+        wav = model.generate(**kwargs)
+        return model.tts_model.sample_rate, wav, reference_transcript or ""
+
+    def request_reply(
+        self,
+        *,
+        backend_url: str,
+        backend_token: str,
+        user_message: str,
+        history: list[tuple[str, str]],
+        assistant_context: str,
+        backend_mode: str = "auto",
+        timeout: int = 30,
+    ) -> str:
+        backend_url = _clean_text(backend_url)
+        if not backend_url:
+            raise ValueError("No backend URL configured.")
+
+        backend_mode = _clean_text(backend_mode).lower() or "auto"
+        openai_compatible = backend_mode == "openai" or (
+            backend_mode == "auto" and "/v1/chat/completions" in backend_url
+        )
+
+        if openai_compatible:
+            payload = {
+                "model": "pca",
+                "messages": _build_backend_messages(user_message, history, assistant_context),
+                "temperature": 0.4,
+                "stream": False,
+            }
+        else:
+            history_payload: list[dict[str, str]] = []
+            for user_turn, assistant_turn in history:
+                history_payload.append({"role": "user", "content": user_turn})
+                history_payload.append({"role": "assistant", "content": assistant_turn})
+
+            payload = {
+                "message": user_message,
+                "history": history_payload,
+                "assistant_context": assistant_context,
+                "device": self.device,
+            }
+
+        headers = {"Content-Type": "application/json"}
+        if backend_token:
+            headers["Authorization"] = f"Bearer {backend_token.strip()}"
+
+        response = requests.post(backend_url, json=payload, headers=headers, timeout=timeout)
+        response.raise_for_status()
+
+        reply = ""
+        content_type = response.headers.get("content-type", "")
+        if "application/json" in content_type.lower():
+            try:
+                reply = _extract_reply_text(response.json())
+            except Exception:
+                reply = response.text.strip()
+        else:
+            reply = response.text.strip()
+
+        reply = _clean_text(reply)
+        if not reply:
+            raise ValueError("Webhook returned an empty reply.")
+        return reply
+
+
+def _history_to_chatbot(history: list[tuple[str, str]]) -> list[tuple[str, str]]:
+    return _format_history(history)
+
+
+def build_interface(runtime: PhoneAssistantRuntime, default_profile_data: dict[str, Any] | None = None):
+    default_profile_data = default_profile_data or {}
+    backend_url_default = _clean_text(os.environ.get("PCA_BACKEND_URL", DEFAULT_BACKEND_URL))
+    backend_token_default = _clean_text(os.environ.get("PCA_BACKEND_TOKEN", DEFAULT_BACKEND_TOKEN))
+    backend_context_default = _clean_text(os.environ.get("PCA_ASSISTANT_CONTEXT", DEFAULT_BACKEND_CONTEXT))
+    backend_mode_default = _clean_text(os.environ.get("PCA_BACKEND_MODE", DEFAULT_BACKEND_MODE)).lower() or "auto"
+    if backend_mode_default not in {"auto", "openai", "custom"}:
+        backend_mode_default = "auto"
+
+    def _merge_profile_inputs(
+        profile_data: dict[str, Any],
+        reference_audio: Optional[str],
+        reference_transcript: str,
+        control_text: str,
+    ) -> tuple[Optional[str], str, str]:
+        profile_data = profile_data or {}
+
+        effective_audio = _clean_text(reference_audio) or _clean_text(profile_data.get("reference_audio"))
+        effective_transcript = _clean_text(reference_transcript) or _clean_text(profile_data.get("reference_transcript"))
+        effective_control = _clean_text(control_text) or _clean_text(profile_data.get("control_text"))
+        return (
+            effective_audio or None,
+            effective_transcript,
+            effective_control,
+        )
+
+    def _profile_summary(profile_data: dict[str, Any]) -> str:
+        if not profile_data:
+            return "No saved profile loaded."
+        name = profile_data.get("name", "default")
+        audio = "yes" if profile_data.get("reference_audio") else "no"
+        transcript = "yes" if profile_data.get("reference_transcript") else "no"
+        return f"Loaded profile: {name} | audio: {audio} | transcript: {transcript}"
+
+    def save_voice_profile(
+        profile_name: str,
+        reference_audio: Optional[str],
+        reference_transcript: str,
+        control_text: str,
+        auto_transcribe_reference: bool,
+    ):
+        profile_name = _clean_text(profile_name) or "default"
+        if not reference_audio:
+            raise ValueError("Upload a reference voice sample before saving the profile.")
+
+        transcript = _clean_text(reference_transcript)
+        if not transcript and auto_transcribe_reference:
+            transcript = runtime.transcribe(reference_audio)
+
+        stored_audio = _copy_reference_audio(reference_audio, profile_name)
+        payload = {
+            "name": profile_name,
+            "reference_audio": stored_audio,
+            "reference_transcript": transcript,
+            "control_text": _clean_text(control_text),
+        }
+        saved_path = _save_profile(profile_name, payload)
+        payload["profile_path"] = saved_path
+        return payload, _profile_summary(payload), stored_audio, transcript, payload.get("control_text", "")
+
+    def load_voice_profile(profile_name: str):
+        profile_name = _clean_text(profile_name) or "default"
+        payload = _load_profile(profile_name)
+        return (
+            payload,
+            payload.get("reference_audio", ""),
+            payload.get("reference_transcript", ""),
+            payload.get("control_text", ""),
+            _profile_summary(payload),
+        )
+
+    def clear_voice_profile():
+        return {}, "", "", "", "No saved profile loaded."
+
+    def prepare_turn(
+        user_audio: Optional[str],
+        user_text: str,
+        assistant_reply: str,
+        backend_url: str,
+        backend_token: str,
+        assistant_context: str,
+        backend_mode: str,
+        reference_audio: Optional[str],
+        reference_transcript: str,
+        control_text: str,
+        normalize_text: bool,
+        denoise_reference: bool,
+        auto_transcribe_reference: bool,
+        cfg_value: float,
+        inference_timesteps: int,
+        history: list[tuple[str, str]],
+        profile_data: dict[str, Any],
+    ):
+        history = _history_to_chatbot(history)
+        user_text_clean = _clean_text(user_text)
+
+        if not user_text_clean and user_audio:
+            if AutoModel is None:
+                raise RuntimeError(
+                    "No text message provided and speech-to-text is unavailable. Type the message manually or install the optional ASR dependency."
+                )
+            user_text_clean = runtime.transcribe(user_audio)
+
+        user_text_clean = _normalize_spaces(user_text_clean)
+        if not user_text_clean:
+            raise ValueError("Provide a text message or record one with the phone microphone.")
+
+        if backend_url.strip():
+            assistant_reply = runtime.request_reply(
+                backend_url=backend_url,
+                backend_token=backend_token,
+                user_message=user_text_clean,
+                history=history,
+                assistant_context=assistant_context,
+                backend_mode=backend_mode,
+            )
+        else:
+            assistant_reply = _clean_text(assistant_reply)
+            if not assistant_reply:
+                raise ValueError("Type the assistant reply, or configure a backend URL.")
+
+        reference_audio, reference_transcript, control_text = _merge_profile_inputs(
+            profile_data,
+            reference_audio,
+            reference_transcript,
+            control_text,
+        )
+
+        sample_rate, wav, transcript = runtime.synthesize(
+            text=assistant_reply,
+            reference_audio=reference_audio,
+            reference_transcript=reference_transcript,
+            control=control_text,
+            normalize=normalize_text,
+            denoise=denoise_reference,
+            cfg_value=cfg_value,
+            inference_timesteps=inference_timesteps,
+            auto_transcribe_reference=auto_transcribe_reference,
+        )
+
+        if reference_audio and not reference_transcript and transcript:
+            reference_transcript = transcript
+
+        history = history + [(f"You: {user_text_clean}", f"PCA: {assistant_reply}")]
+        status = "Generated cloned speech."
+        if reference_audio and transcript:
+            status = "Generated cloned speech with transcript-guided cloning."
+
+        return (
+            history,
+            user_text_clean,
+            assistant_reply,
+            reference_transcript,
+            (sample_rate, wav),
+            status,
+        )
+
+    def speak_reply(
+        assistant_reply: str,
+        reference_audio: Optional[str],
+        reference_transcript: str,
+        control_text: str,
+        profile_data: dict[str, Any],
+        normalize_text: bool,
+        denoise_reference: bool,
+        auto_transcribe_reference: bool,
+        cfg_value: float,
+        inference_timesteps: int,
+    ):
+        assistant_reply = _clean_text(assistant_reply)
+        if not assistant_reply:
+            raise ValueError("Type a reply to speak first.")
+
+        reference_audio, reference_transcript, control_text = _merge_profile_inputs(
+            profile_data,
+            reference_audio,
+            reference_transcript,
+            control_text,
+        )
+
+        sample_rate, wav, transcript = runtime.synthesize(
+            text=assistant_reply,
+            reference_audio=reference_audio,
+            reference_transcript=reference_transcript,
+            control=control_text,
+            normalize=normalize_text,
+            denoise=denoise_reference,
+            cfg_value=cfg_value,
+            inference_timesteps=inference_timesteps,
+            auto_transcribe_reference=auto_transcribe_reference,
+        )
+
+        return (sample_rate, wav), transcript or reference_transcript, "Playback updated."
+
+    def clear_state(profile_data: dict[str, Any]):
+        return [], "", "", "", None, "Ready.", profile_data
+
+    with gr.Blocks(theme=APP_THEME, css=APP_CSS, fill_height=True) as demo:
+        profile_state = gr.State(default_profile_data)
+        with gr.Column(elem_classes=["assistant-shell"]):
+            gr.HTML(
+                """
+                <div class="assistant-hero">
+                  <div class="assistant-kicker">VoxCPM Phone Assistant</div>
+                  <h1>Cloned voice for your mobile assistant.</h1>
+                  <p>
+                    Record a message from your phone, send it to your assistant or webhook,
+                    and hear the reply in the cloned voice from your reference samples.
+                    Best results come from a clean 10-30 second clip with an exact transcript.
+                  </p>
+                </div>
+                """
+            )
+
+            with gr.Row(elem_classes=["assistant-grid"]):
+                with gr.Column(elem_classes=["panel"]):
+                    gr.Markdown("### Conversation")
+                    conversation = gr.Chatbot(
+                        label="Conversation",
+                        height=460,
+                        bubble_full_width=False,
+                        show_copy_button=True,
+                    )
+
+                    user_text = gr.Textbox(
+                        label="Your message",
+                        placeholder="Type a message, or record one with the phone microphone below.",
+                        lines=3,
+                    )
+                    user_audio = gr.Audio(
+                        label="Voice input",
+                        sources=["upload", "microphone"],
+                        type="filepath",
+                    )
+
+                    with gr.Row():
+                        send_btn = gr.Button("Send & Speak", variant="primary")
+                        speak_btn = gr.Button("Speak reply", variant="secondary")
+                        clear_btn = gr.Button("Clear", variant="secondary")
+
+                    assistant_reply = gr.Textbox(
+                        label="Assistant reply",
+                        placeholder="Webhook reply appears here, or type the response you want VoxCPM to speak.",
+                        lines=4,
+                    )
+                    audio_out = gr.Audio(label="Voiced reply")
+                    status = gr.Textbox(label="Status", value="Ready.", interactive=False)
+
+                with gr.Column(elem_classes=["panel"]):
+                    gr.Markdown("### Voice profile")
+                    profile_name = gr.Textbox(
+                        label="Profile name",
+                        value=default_profile_data.get("name", "default"),
+                        placeholder="A short name for this voice profile, like my-voice.",
+                    )
+                    reference_audio = gr.Audio(
+                        label="Reference voice sample",
+                        sources=["upload", "microphone"],
+                        value=default_profile_data.get("reference_audio"),
+                        type="filepath",
+                    )
+                    reference_transcript = gr.Textbox(
+                        label="Reference transcript",
+                        value=default_profile_data.get("reference_transcript", ""),
+                        placeholder="Paste the exact transcript for best cloning quality. Leave blank to auto-transcribe if available.",
+                        lines=3,
+                    )
+                    control_text = gr.Textbox(
+                        label="Voice control",
+                        value=default_profile_data.get("control_text", ""),
+                        placeholder="Optional style guidance such as warm, calm, faster, younger, smiling.",
+                        lines=2,
+                    )
+
+                    with gr.Row():
+                        save_profile_btn = gr.Button("Save enrollment", variant="primary")
+                        load_profile_btn = gr.Button("Load enrollment", variant="secondary")
+                        clear_profile_btn = gr.Button("Clear enrollment", variant="secondary")
+                    profile_status = gr.Textbox(
+                        label="Profile status",
+                        value=_profile_summary(default_profile_data),
+                        interactive=False,
+                    )
+
+                    with gr.Accordion("Advanced", open=False):
+                        assistant_webhook_url = gr.Textbox(
+                            label="PCA backend URL",
+                            value=backend_url_default,
+                            placeholder="OpenAI-compatible /v1/chat/completions or a custom webhook endpoint.",
+                        )
+                        assistant_webhook_token = gr.Textbox(
+                            label="PCA backend token",
+                            value=backend_token_default,
+                            placeholder="Optional bearer token.",
+                        )
+                        assistant_context = gr.Textbox(
+                            label="Assistant context",
+                            value=backend_context_default,
+                            placeholder="Optional system prompt or assistant instructions.",
+                            lines=3,
+                        )
+                        backend_mode = gr.Dropdown(
+                            choices=["auto", "openai", "custom"],
+                            value=backend_mode_default,
+                            label="Backend mode",
+                            info="Auto detects OpenAI-compatible chat endpoints; custom uses the webhook payload format.",
+                        )
+                        auto_transcribe_reference = gr.Checkbox(
+                            value=True,
+                            label="Auto-transcribe reference audio when ASR is installed",
+                        )
+                        normalize_text = gr.Checkbox(
+                            value=False,
+                            label="Normalize text",
+                        )
+                        denoise_reference = gr.Checkbox(
+                            value=False,
+                            label="Denoise reference audio",
+                        )
+                        cfg_value = gr.Slider(
+                            minimum=1.0,
+                            maximum=3.0,
+                            value=2.0,
+                            step=0.1,
+                            label="CFG guidance scale",
+                        )
+                        inference_timesteps = gr.Slider(
+                            minimum=1,
+                            maximum=50,
+                            value=10,
+                            step=1,
+                            label="Inference steps",
+                        )
+
+                    gr.Markdown(
+                        """
+                        **Backend payloads**
+
+                        OpenAI-compatible mode sends `{"model":"pca","messages":[...],"temperature":0.4,"stream":false}`.
+
+                        Custom mode sends `{"message": "...", "history": [...], "assistant_context": "..."}`.
+
+                        The response can be plain text or JSON with `reply`, `text`, `content`, or OpenAI-style `choices[0].message.content`.
+                        """
+                    )
+
+            send_btn.click(
+                fn=prepare_turn,
+                inputs=[
+                    user_audio,
+                    user_text,
+                    assistant_reply,
+                    assistant_webhook_url,
+                    assistant_webhook_token,
+                    assistant_context,
+                    backend_mode,
+                    reference_audio,
+                    reference_transcript,
+                    control_text,
+                    normalize_text,
+                    denoise_reference,
+                    auto_transcribe_reference,
+                    cfg_value,
+                    inference_timesteps,
+                    conversation,
+                    profile_state,
+                ],
+                outputs=[
+                    conversation,
+                    user_text,
+                    assistant_reply,
+                    reference_transcript,
+                    audio_out,
+                    status,
+                    profile_state,
+                ],
+                show_progress=True,
+            )
+
+            speak_btn.click(
+                fn=speak_reply,
+                inputs=[
+                    assistant_reply,
+                    reference_audio,
+                    reference_transcript,
+                    control_text,
+                    profile_state,
+                    normalize_text,
+                    denoise_reference,
+                    auto_transcribe_reference,
+                    cfg_value,
+                    inference_timesteps,
+                ],
+                outputs=[audio_out, reference_transcript, status],
+                show_progress=True,
+            )
+
+            save_profile_btn.click(
+                fn=save_voice_profile,
+                inputs=[
+                    profile_name,
+                    reference_audio,
+                    reference_transcript,
+                    control_text,
+                    auto_transcribe_reference,
+                ],
+                outputs=[
+                    profile_state,
+                    profile_status,
+                    reference_audio,
+                    reference_transcript,
+                    control_text,
+                ],
+                show_progress=True,
+            )
+
+            load_profile_btn.click(
+                fn=load_voice_profile,
+                inputs=[profile_name],
+                outputs=[
+                    profile_state,
+                    reference_audio,
+                    reference_transcript,
+                    control_text,
+                    profile_status,
+                ],
+                show_progress=True,
+            )
+
+            clear_profile_btn.click(
+                fn=clear_voice_profile,
+                inputs=[],
+                outputs=[profile_state, reference_audio, reference_transcript, control_text, profile_status],
+            )
+
+            clear_btn.click(
+                fn=clear_state,
+                inputs=[profile_state],
+                outputs=[conversation, user_text, assistant_reply, reference_transcript, audio_out, status, profile_state],
+            )
+
+    return demo
+
+
+def launch(
+    *,
+    model_id: str = DEFAULT_MODEL_ID,
+    device: str = "auto",
+    port: int = 8809,
+    host: str = "0.0.0.0",
+    share: bool = False,
+    no_denoiser: bool = False,
+    optimize: bool = True,
+    zipenhancer_path: Optional[str] = None,
+    default_profile_name: str = "reddit-female",
+    backend_url: str = DEFAULT_BACKEND_URL,
+    backend_token: str = DEFAULT_BACKEND_TOKEN,
+    backend_context: str = DEFAULT_BACKEND_CONTEXT,
+    backend_mode: str = DEFAULT_BACKEND_MODE if DEFAULT_BACKEND_MODE in {"auto", "openai", "custom"} else "auto",
+):
+    runtime = PhoneAssistantRuntime(
+        model_id=model_id,
+        device=device,
+        load_denoiser=not no_denoiser,
+        optimize=optimize,
+        zipenhancer_model_path=zipenhancer_path,
+    )
+    default_profile_data: dict[str, Any] = {}
+    if _clean_text(default_profile_name):
+        try:
+            default_profile_data = _load_profile(default_profile_name)
+        except FileNotFoundError:
+            logger.warning("Default profile not found: %s", default_profile_name)
+
+    if _clean_text(backend_url):
+        os.environ["PCA_BACKEND_URL"] = backend_url
+    if _clean_text(backend_token):
+        os.environ["PCA_BACKEND_TOKEN"] = backend_token
+    if _clean_text(backend_context):
+        os.environ["PCA_ASSISTANT_CONTEXT"] = backend_context
+    if _clean_text(backend_mode):
+        os.environ["PCA_BACKEND_MODE"] = backend_mode
+
+    demo = build_interface(runtime, default_profile_data=default_profile_data)
+    demo.queue(max_size=16, default_concurrency_limit=1).launch(
+        server_name=host,
+        server_port=port,
+        share=share,
+        show_error=True,
+    )
+
+
+def main():
+    parser = argparse.ArgumentParser(description="VoxCPM mobile assistant bridge")
+    parser.add_argument("--model-id", type=str, default=DEFAULT_MODEL_ID)
+    parser.add_argument("--device", type=str, default="auto")
+    parser.add_argument("--port", type=int, default=8809)
+    parser.add_argument("--host", type=str, default="0.0.0.0")
+    parser.add_argument("--share", action="store_true")
+    parser.add_argument("--no-denoiser", action="store_true")
+    parser.add_argument("--no-optimize", action="store_true")
+    parser.add_argument("--zipenhancer-path", type=str, default=None)
+    parser.add_argument("--default-profile-name", type=str, default="reddit-female")
+    parser.add_argument("--backend-url", type=str, default=DEFAULT_BACKEND_URL)
+    parser.add_argument("--backend-token", type=str, default=DEFAULT_BACKEND_TOKEN)
+    parser.add_argument("--backend-context", type=str, default=DEFAULT_BACKEND_CONTEXT)
+    parser.add_argument(
+        "--backend-mode",
+        type=str,
+        default=DEFAULT_BACKEND_MODE if DEFAULT_BACKEND_MODE in {"auto", "openai", "custom"} else "auto",
+        choices=["auto", "openai", "custom"],
+    )
+    args = parser.parse_args()
+
+    launch(
+        model_id=args.model_id,
+        device=args.device,
+        port=args.port,
+        host=args.host,
+        share=args.share,
+        no_denoiser=args.no_denoiser,
+        optimize=not args.no_optimize,
+        zipenhancer_path=args.zipenhancer_path,
+        default_profile_name=args.default_profile_name,
+        backend_url=args.backend_url,
+        backend_token=args.backend_token,
+        backend_context=args.backend_context,
+        backend_mode=args.backend_mode,
+    )
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tests/test_phone_assistant.py b/tests/test_phone_assistant.py
new file mode 100644
index 00000000..dc827706
--- /dev/null
+++ b/tests/test_phone_assistant.py
@@ -0,0 +1,37 @@
+from voxcpm.phone_assistant import (
+    _build_backend_messages,
+    _build_final_text,
+    _extract_reply_text,
+    _profile_path,
+)
+
+
+def test_build_final_text_wraps_control_instruction():
+    assert _build_final_text("Hello world", "warm female voice") == "(warm female voice)Hello world"
+
+
+def test_build_final_text_leaves_plain_text_when_no_control():
+    assert _build_final_text("Hello world", "") == "Hello world"
+
+
+def test_extract_reply_text_supports_plain_reply_field():
+    assert _extract_reply_text({"reply": "  cloned voice text  "}) == "cloned voice text"
+
+
+def test_extract_reply_text_supports_openai_style_response():
+    payload = {"choices": [{"message": {"content": "  assistant reply  "}}]}
+    assert _extract_reply_text(payload) == "assistant reply"
+
+
+def test_profile_path_sanitizes_name():
+    assert _profile_path("My Voice!").name == "myvoice.json"
+
+
+def test_build_backend_messages_includes_context_and_history():
+    messages = _build_backend_messages(
+        "hello",
+        [("old user", "old assistant")],
+        "system context",
+    )
+    assert messages[0] == {"role": "system", "content": "system context"}
+    assert messages[-1] == {"role": "user", "content": "hello"}
diff --git a/uv.lock b/uv.lock
index 8577c08b..90ba4cce 100644
--- a/uv.lock
+++ b/uv.lock
@@ -168,28 +168,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/fb/76/641ae371508676492379f16e2fa48f4e2c11741bd63c48be4b12a6b09cba/aiosignal-1.4.0-py3-none-any.whl", hash = "sha256:053243f8b92b990551949e63930a839ff0cf0b0ebbe0597b0f3fb19e1a0fe82e", size = 7490, upload-time = "2025-07-03T22:54:42.156Z" },
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-
-[[package]]
-name = "aliyun-python-sdk-kms"
-version = "2.16.5"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "aliyun-python-sdk-core" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/a8/2c/9877d0e6b18ecf246df671ac65a5d1d9fecbf85bdcb5d43efbde0d4662eb/aliyun-python-sdk-kms-2.16.5.tar.gz", hash = "sha256:f328a8a19d83ecbb965ffce0ec1e9930755216d104638cd95ecd362753b813b3", size = 12018, upload-time = "2024-08-30T09:01:20.104Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/11/5c/0132193d7da2c735669a1ed103b142fd63c9455984d48c5a88a1a516efaa/aliyun_python_sdk_kms-2.16.5-py2.py3-none-any.whl", hash = "sha256:24b6cdc4fd161d2942619479c8d050c63ea9cd22b044fe33b60bbb60153786f0", size = 99495, upload-time = "2024-08-30T09:01:18.462Z" },
-]
-
 [[package]]
 name = "annotated-doc"
 version = "0.0.4"
@@ -208,12 +186,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload-time = "2024-05-20T21:33:24.1Z" },
 ]
 
-[[package]]
-name = "antlr4-python3-runtime"
-version = "4.9.3"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/3e/38/7859ff46355f76f8d19459005ca000b6e7012f2f1ca597746cbcd1fbfe5e/antlr4-python3-runtime-4.9.3.tar.gz", hash = "sha256:f224469b4168294902bb1efa80a8bf7855f24c99aef99cbefc1bcd3cce77881b", size = 117034, upload-time = "2021-11-06T17:52:23.524Z" }
-
 [[package]]
 name = "anyascii"
 version = "0.3.3"
@@ -948,72 +920,6 @@ toml = [
     { name = "tomli", marker = "python_full_version <= '3.11'" },
 ]
 
-[[package]]
-name = "crcmod"
-version = "1.7"
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-
-[[package]]
-name = "cryptography"
-version = "46.0.5"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
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-]
-sdist = { url = "https://files.pythonhosted.org/packages/60/04/ee2a9e8542e4fa2773b81771ff8349ff19cdd56b7258a0cc442639052edb/cryptography-46.0.5.tar.gz", hash = "sha256:abace499247268e3757271b2f1e244b36b06f8515cf27c4d49468fc9eb16e93d", size = 750064, upload-time = "2026-02-10T19:18:38.255Z" }
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-    { url = "https://files.pythonhosted.org/packages/43/d2/fcf7192dd1cd8c090b6cfd53fa223c4fb2887a17c47e06bc356d44f40dfb/umap_learn-0.5.11-py3-none-any.whl", hash = "sha256:cb17adbde9d544ba79481b3ab4d81ac222e940f3d9219307bea6044f869af3cc", size = 90890, upload-time = "2026-01-12T20:44:46.511Z" },
-]
-
 [[package]]
 name = "urllib3"
 version = "2.6.3"
@@ -4928,7 +4476,6 @@ dependencies = [
     { name = "argbind" },
     { name = "datasets" },
     { name = "einops" },
-    { name = "funasr" },
     { name = "gradio" },
     { name = "huggingface-hub" },
     { name = "inflect" },
@@ -4966,7 +4513,6 @@ requires-dist = [
     { name = "datasets", specifier = ">=3,<4" },
     { name = "einops" },
     { name = "flake8", marker = "extra == 'dev'", specifier = ">=3.8" },
-    { name = "funasr" },
     { name = "gradio", specifier = ">=6,<7" },
     { name = "huggingface-hub" },
     { name = "inflect" },

From 668f5b8c53457b323391185f16d0482efdf32473 Mon Sep 17 00:00:00 2001
From: James Juniper <217263268+jjuniper-dev@users.noreply.github.com>
Date: Fri, 10 Jul 2026 18:24:00 -0400
Subject: [PATCH 2/5] feat: stage pca captures from phone assistant

---
 README.md                     |   1 +
 src/voxcpm/phone_assistant.py | 133 ++++++++++++++++++++++++++++++++++
 tests/test_phone_assistant.py |  22 ++++++
 3 files changed, 156 insertions(+)

diff --git a/README.md b/README.md
index e15fb062..593b8f4a 100644
--- a/README.md
+++ b/README.md
@@ -260,6 +260,7 @@ If you want phone microphone dictation, install the optional ASR dependency sepa
 You can also save a named voice enrollment once and reuse it later from the app's profile panel.
 By default, the assistant loads the saved `reddit-female` profile if it exists.
 To wire in your PCA backend automatically, set `PCA_BACKEND_URL` plus optional `PCA_BACKEND_TOKEN`, `PCA_ASSISTANT_CONTEXT`, and `PCA_BACKEND_MODE=auto|openai|custom` before launching.
+To stage the phone message into PCA as a capture event, also set `PCA_CAPTURE_URL` plus optional `PCA_CAPTURE_TOKEN`. The assistant sends `source: iphone`, `capture_type: text`, the user message, and capture metadata that includes the assistant reply.
 
 ### 🚢 Production Deployment (Nano-vLLM)
 
diff --git a/src/voxcpm/phone_assistant.py b/src/voxcpm/phone_assistant.py
index 29856538..243e8cad 100644
--- a/src/voxcpm/phone_assistant.py
+++ b/src/voxcpm/phone_assistant.py
@@ -42,6 +42,8 @@
 DEFAULT_BACKEND_TOKEN = os.environ.get("PCA_BACKEND_TOKEN", "").strip()
 DEFAULT_BACKEND_CONTEXT = os.environ.get("PCA_ASSISTANT_CONTEXT", "").strip()
 DEFAULT_BACKEND_MODE = os.environ.get("PCA_BACKEND_MODE", "auto").strip().lower()
+DEFAULT_CAPTURE_URL = os.environ.get("PCA_CAPTURE_URL", "").strip()
+DEFAULT_CAPTURE_TOKEN = os.environ.get("PCA_CAPTURE_TOKEN", "").strip()
 
 APP_THEME = gr.themes.Soft(
     primary_hue="cyan",
@@ -237,6 +239,45 @@ def _extract_reply_text(payload: Any) -> str:
     return ""
 
 
+def _build_capture_payload(
+    *,
+    user_message: str,
+    assistant_reply: str,
+    history: list[tuple[str, str]],
+    profile_name: str,
+    backend_mode: str,
+) -> dict[str, Any]:
+    return {
+        "source": "iphone",
+        "capture_type": "text",
+        "content": _clean_text(user_message),
+        "metadata": {
+            "assistant_reply": _clean_text(assistant_reply),
+            "voice_profile": _clean_text(profile_name),
+            "backend_mode": _clean_text(backend_mode).lower() or "auto",
+            "turn_count": len(history) + 1,
+            "origin": "voxcpm-phone-assistant",
+        },
+    }
+
+
+def _extract_capture_receipt(payload: Any) -> str:
+    if isinstance(payload, str):
+        return payload.strip()
+
+    if isinstance(payload, dict):
+        for key in ("capture_id", "receipt", "id", "status", "message"):
+            value = payload.get(key)
+            if isinstance(value, str) and value.strip():
+                return value.strip()
+
+        data = payload.get("data")
+        if isinstance(data, str) and data.strip():
+            return data.strip()
+
+    return ""
+
+
 def _build_backend_messages(
     user_message: str,
     history: list[tuple[str, str]],
@@ -464,6 +505,49 @@ def request_reply(
             raise ValueError("Webhook returned an empty reply.")
         return reply
 
+    def request_capture(
+        self,
+        *,
+        capture_url: str,
+        capture_token: str,
+        user_message: str,
+        assistant_reply: str,
+        history: list[tuple[str, str]],
+        profile_name: str,
+        backend_mode: str,
+        timeout: int = 30,
+    ) -> str:
+        capture_url = _clean_text(capture_url)
+        if not capture_url:
+            raise ValueError("No capture URL configured.")
+
+        payload = _build_capture_payload(
+            user_message=user_message,
+            assistant_reply=assistant_reply,
+            history=history,
+            profile_name=profile_name,
+            backend_mode=backend_mode,
+        )
+
+        headers = {"Content-Type": "application/json"}
+        if capture_token:
+            headers["Authorization"] = f"Bearer {capture_token.strip()}"
+
+        response = requests.post(capture_url, json=payload, headers=headers, timeout=timeout)
+        response.raise_for_status()
+
+        receipt = ""
+        content_type = response.headers.get("content-type", "")
+        if "application/json" in content_type.lower():
+            try:
+                receipt = _extract_capture_receipt(response.json())
+            except Exception:
+                receipt = response.text.strip()
+        else:
+            receipt = response.text.strip()
+
+        return _clean_text(receipt)
+
 
 def _history_to_chatbot(history: list[tuple[str, str]]) -> list[tuple[str, str]]:
     return _format_history(history)
@@ -475,6 +559,8 @@ def build_interface(runtime: PhoneAssistantRuntime, default_profile_data: dict[s
     backend_token_default = _clean_text(os.environ.get("PCA_BACKEND_TOKEN", DEFAULT_BACKEND_TOKEN))
     backend_context_default = _clean_text(os.environ.get("PCA_ASSISTANT_CONTEXT", DEFAULT_BACKEND_CONTEXT))
     backend_mode_default = _clean_text(os.environ.get("PCA_BACKEND_MODE", DEFAULT_BACKEND_MODE)).lower() or "auto"
+    capture_url_default = _clean_text(os.environ.get("PCA_CAPTURE_URL", DEFAULT_CAPTURE_URL))
+    capture_token_default = _clean_text(os.environ.get("PCA_CAPTURE_TOKEN", DEFAULT_CAPTURE_TOKEN))
     if backend_mode_default not in {"auto", "openai", "custom"}:
         backend_mode_default = "auto"
 
@@ -549,6 +635,8 @@ def prepare_turn(
         assistant_reply: str,
         backend_url: str,
         backend_token: str,
+        capture_url: str,
+        capture_token: str,
         assistant_context: str,
         backend_mode: str,
         reference_audio: Optional[str],
@@ -590,6 +678,25 @@ def prepare_turn(
             if not assistant_reply:
                 raise ValueError("Type the assistant reply, or configure a backend URL.")
 
+        capture_status = ""
+        if capture_url.strip():
+            try:
+                capture_receipt = runtime.request_capture(
+                    capture_url=capture_url,
+                    capture_token=capture_token,
+                    user_message=user_text_clean,
+                    assistant_reply=assistant_reply,
+                    history=history,
+                    profile_name=_clean_text(profile_data.get("name", "default")) or "default",
+                    backend_mode=backend_mode,
+                )
+                capture_status = "Capture staged in PCA."
+                if capture_receipt:
+                    capture_status = f"Capture staged in PCA ({capture_receipt})."
+            except Exception as exc:
+                logger.warning("Capture staging failed: %s", exc)
+                capture_status = f"Capture staging failed: {exc}"
+
         reference_audio, reference_transcript, control_text = _merge_profile_inputs(
             profile_data,
             reference_audio,
@@ -616,6 +723,8 @@ def prepare_turn(
         status = "Generated cloned speech."
         if reference_audio and transcript:
             status = "Generated cloned speech with transcript-guided cloning."
+        if capture_status:
+            status = f"{status} {capture_status}"
 
         return (
             history,
@@ -764,6 +873,16 @@ def clear_state(profile_data: dict[str, Any]):
                             value=backend_token_default,
                             placeholder="Optional bearer token.",
                         )
+                        capture_webhook_url = gr.Textbox(
+                            label="PCA capture URL",
+                            value=capture_url_default,
+                            placeholder="Optional capture webhook URL for staging the phone message in PCA.",
+                        )
+                        capture_webhook_token = gr.Textbox(
+                            label="PCA capture token",
+                            value=capture_token_default,
+                            placeholder="Optional bearer token for the capture webhook.",
+                        )
                         assistant_context = gr.Textbox(
                             label="Assistant context",
                             value=backend_context_default,
@@ -811,6 +930,8 @@ def clear_state(profile_data: dict[str, Any]):
 
                         Custom mode sends `{"message": "...", "history": [...], "assistant_context": "..."}`.
 
+                        If a PCA capture URL is configured, the phone message is also staged with `source: iphone`, `capture_type: text`, and metadata that includes the assistant reply.
+
                         The response can be plain text or JSON with `reply`, `text`, `content`, or OpenAI-style `choices[0].message.content`.
                         """
                     )
@@ -823,6 +944,8 @@ def clear_state(profile_data: dict[str, Any]):
                     assistant_reply,
                     assistant_webhook_url,
                     assistant_webhook_token,
+                    capture_webhook_url,
+                    capture_webhook_token,
                     assistant_context,
                     backend_mode,
                     reference_audio,
@@ -926,6 +1049,8 @@ def launch(
     default_profile_name: str = "reddit-female",
     backend_url: str = DEFAULT_BACKEND_URL,
     backend_token: str = DEFAULT_BACKEND_TOKEN,
+    capture_url: str = DEFAULT_CAPTURE_URL,
+    capture_token: str = DEFAULT_CAPTURE_TOKEN,
     backend_context: str = DEFAULT_BACKEND_CONTEXT,
     backend_mode: str = DEFAULT_BACKEND_MODE if DEFAULT_BACKEND_MODE in {"auto", "openai", "custom"} else "auto",
 ):
@@ -947,6 +1072,10 @@ def launch(
         os.environ["PCA_BACKEND_URL"] = backend_url
     if _clean_text(backend_token):
         os.environ["PCA_BACKEND_TOKEN"] = backend_token
+    if _clean_text(capture_url):
+        os.environ["PCA_CAPTURE_URL"] = capture_url
+    if _clean_text(capture_token):
+        os.environ["PCA_CAPTURE_TOKEN"] = capture_token
     if _clean_text(backend_context):
         os.environ["PCA_ASSISTANT_CONTEXT"] = backend_context
     if _clean_text(backend_mode):
@@ -974,6 +1103,8 @@ def main():
     parser.add_argument("--default-profile-name", type=str, default="reddit-female")
     parser.add_argument("--backend-url", type=str, default=DEFAULT_BACKEND_URL)
     parser.add_argument("--backend-token", type=str, default=DEFAULT_BACKEND_TOKEN)
+    parser.add_argument("--capture-url", type=str, default=DEFAULT_CAPTURE_URL)
+    parser.add_argument("--capture-token", type=str, default=DEFAULT_CAPTURE_TOKEN)
     parser.add_argument("--backend-context", type=str, default=DEFAULT_BACKEND_CONTEXT)
     parser.add_argument(
         "--backend-mode",
@@ -995,6 +1126,8 @@ def main():
         default_profile_name=args.default_profile_name,
         backend_url=args.backend_url,
         backend_token=args.backend_token,
+        capture_url=args.capture_url,
+        capture_token=args.capture_token,
         backend_context=args.backend_context,
         backend_mode=args.backend_mode,
     )
diff --git a/tests/test_phone_assistant.py b/tests/test_phone_assistant.py
index dc827706..4ee89331 100644
--- a/tests/test_phone_assistant.py
+++ b/tests/test_phone_assistant.py
@@ -1,7 +1,9 @@
 from voxcpm.phone_assistant import (
     _build_backend_messages,
+    _build_capture_payload,
     _build_final_text,
     _extract_reply_text,
+    _extract_capture_receipt,
     _profile_path,
 )
 
@@ -23,6 +25,26 @@ def test_extract_reply_text_supports_openai_style_response():
     assert _extract_reply_text(payload) == "assistant reply"
 
 
+def test_build_capture_payload_uses_phone_capture_contract():
+    payload = _build_capture_payload(
+        user_message="Hello PCA",
+        assistant_reply="Cloned reply",
+        history=[("u1", "a1")],
+        profile_name="reddit-female",
+        backend_mode="custom",
+    )
+    assert payload["source"] == "iphone"
+    assert payload["capture_type"] == "text"
+    assert payload["content"] == "Hello PCA"
+    assert payload["metadata"]["assistant_reply"] == "Cloned reply"
+    assert payload["metadata"]["voice_profile"] == "reddit-female"
+    assert payload["metadata"]["turn_count"] == 2
+
+
+def test_extract_capture_receipt_supports_capture_id():
+    assert _extract_capture_receipt({"capture_id": "cap_123"}) == "cap_123"
+
+
 def test_profile_path_sanitizes_name():
     assert _profile_path("My Voice!").name == "myvoice.json"
 

From 638c6ec8b78955ef80f218b7e984386774401ad9 Mon Sep 17 00:00:00 2001
From: James Juniper <217263268+jjuniper-dev@users.noreply.github.com>
Date: Fri, 10 Jul 2026 18:28:20 -0400
Subject: [PATCH 3/5] fix: align capture payload with pca webhook schema

---
 README.md                     | 2 +-
 src/voxcpm/phone_assistant.py | 6 +++++-
 tests/test_phone_assistant.py | 5 ++++-
 3 files changed, 10 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index 593b8f4a..818f7299 100644
--- a/README.md
+++ b/README.md
@@ -260,7 +260,7 @@ If you want phone microphone dictation, install the optional ASR dependency sepa
 You can also save a named voice enrollment once and reuse it later from the app's profile panel.
 By default, the assistant loads the saved `reddit-female` profile if it exists.
 To wire in your PCA backend automatically, set `PCA_BACKEND_URL` plus optional `PCA_BACKEND_TOKEN`, `PCA_ASSISTANT_CONTEXT`, and `PCA_BACKEND_MODE=auto|openai|custom` before launching.
-To stage the phone message into PCA as a capture event, also set `PCA_CAPTURE_URL` plus optional `PCA_CAPTURE_TOKEN`. The assistant sends `source: iphone`, `capture_type: text`, the user message, and capture metadata that includes the assistant reply.
+To stage the phone message into PCA as a capture event, also set `PCA_CAPTURE_URL` plus optional `PCA_CAPTURE_TOKEN`. The assistant sends the PCA contract fields `source: iphone`, `capture_type: text`, `timestamp`, and `text`, plus capture metadata that includes the assistant reply.
 
 ### 🚢 Production Deployment (Nano-vLLM)
 
diff --git a/src/voxcpm/phone_assistant.py b/src/voxcpm/phone_assistant.py
index 243e8cad..4ab33b8c 100644
--- a/src/voxcpm/phone_assistant.py
+++ b/src/voxcpm/phone_assistant.py
@@ -6,6 +6,7 @@
 import os
 import sys
 import shutil
+from datetime import datetime, timezone
 from pathlib import Path
 from typing import Any, Optional
 
@@ -250,7 +251,10 @@ def _build_capture_payload(
     return {
         "source": "iphone",
         "capture_type": "text",
-        "content": _clean_text(user_message),
+        "timestamp": datetime.now(timezone.utc).isoformat(),
+        "text": _clean_text(user_message),
+        "context_note": "Captured from VoxCPM phone assistant",
+        "tags": [tag for tag in ("voxcpm-phone-assistant", _clean_text(profile_name)) if tag],
         "metadata": {
             "assistant_reply": _clean_text(assistant_reply),
             "voice_profile": _clean_text(profile_name),
diff --git a/tests/test_phone_assistant.py b/tests/test_phone_assistant.py
index 4ee89331..d4166ba2 100644
--- a/tests/test_phone_assistant.py
+++ b/tests/test_phone_assistant.py
@@ -35,7 +35,10 @@ def test_build_capture_payload_uses_phone_capture_contract():
     )
     assert payload["source"] == "iphone"
     assert payload["capture_type"] == "text"
-    assert payload["content"] == "Hello PCA"
+    assert payload["text"] == "Hello PCA"
+    assert payload["timestamp"]
+    assert payload["context_note"] == "Captured from VoxCPM phone assistant"
+    assert "voxcpm-phone-assistant" in payload["tags"]
     assert payload["metadata"]["assistant_reply"] == "Cloned reply"
     assert payload["metadata"]["voice_profile"] == "reddit-female"
     assert payload["metadata"]["turn_count"] == 2

From 8815c656cca53c1204e9eabed64ba415749f4691 Mon Sep 17 00:00:00 2001
From: jjuniper-dev <spatialsensation@gmail.com>
Date: Sun, 12 Jul 2026 16:01:38 +0000
Subject: [PATCH 4/5] fix: conform phone capture payload to PCA schema and fix
 send output arity

The capture payload emitted by the phone assistant did not match
schemas/pca_capture_event.schema.json (additionalProperties: false,
required classification/provenance, content not text), so a validating
WF10/WF-Dispatch gateway would reject every capture with HTTP 400 and the
failure was swallowed silently. Rebuild the payload to the contract:
source=iphone_shortcut, capture_type, timestamp, content, classification
(env-overridable via PCA_CAPTURE_CLASSIFICATION, default confidential),
and provenance. Off-contract keys (text/context_note/metadata) are dropped.

Also fix the "Send & Speak" handler: send_btn declared 7 outputs but
prepare_turn returned 6, so Gradio raised on every click. Return
profile_data as the 7th value.

Update tests and README to the conformant contract.

Claude-Session: https://claude.ai/code/session_01RwWk3CSfGsNqpdr47PEMFN
---
 README.md                     |  2 +-
 src/voxcpm/phone_assistant.py | 37 ++++++++++++++++++--------
 tests/test_phone_assistant.py | 49 ++++++++++++++++++++++++++++++-----
 3 files changed, 69 insertions(+), 19 deletions(-)

diff --git a/README.md b/README.md
index 818f7299..c74651fa 100644
--- a/README.md
+++ b/README.md
@@ -260,7 +260,7 @@ If you want phone microphone dictation, install the optional ASR dependency sepa
 You can also save a named voice enrollment once and reuse it later from the app's profile panel.
 By default, the assistant loads the saved `reddit-female` profile if it exists.
 To wire in your PCA backend automatically, set `PCA_BACKEND_URL` plus optional `PCA_BACKEND_TOKEN`, `PCA_ASSISTANT_CONTEXT`, and `PCA_BACKEND_MODE=auto|openai|custom` before launching.
-To stage the phone message into PCA as a capture event, also set `PCA_CAPTURE_URL` plus optional `PCA_CAPTURE_TOKEN`. The assistant sends the PCA contract fields `source: iphone`, `capture_type: text`, `timestamp`, and `text`, plus capture metadata that includes the assistant reply.
+To stage the phone message into PCA as a capture event, also set `PCA_CAPTURE_URL` plus optional `PCA_CAPTURE_TOKEN`. The assistant POSTs a PCA capture event that conforms to the PCA capture schema: `source: iphone_shortcut`, `capture_type: text`, `timestamp`, `content` (the user message), `classification`, and `provenance`. Set `PCA_CAPTURE_CLASSIFICATION` (`public|internal|confidential|restricted`, default `confidential`) to control routing sensitivity.
 
 ### 🚢 Production Deployment (Nano-vLLM)
 
diff --git a/src/voxcpm/phone_assistant.py b/src/voxcpm/phone_assistant.py
index 4ab33b8c..046bbfae 100644
--- a/src/voxcpm/phone_assistant.py
+++ b/src/voxcpm/phone_assistant.py
@@ -46,6 +46,12 @@
 DEFAULT_CAPTURE_URL = os.environ.get("PCA_CAPTURE_URL", "").strip()
 DEFAULT_CAPTURE_TOKEN = os.environ.get("PCA_CAPTURE_TOKEN", "").strip()
 
+CAPTURE_CLASSIFICATIONS = {"public", "internal", "confidential", "restricted"}
+_capture_classification = os.environ.get("PCA_CAPTURE_CLASSIFICATION", "confidential").strip().lower()
+DEFAULT_CAPTURE_CLASSIFICATION = (
+    _capture_classification if _capture_classification in CAPTURE_CLASSIFICATIONS else "confidential"
+)
+
 APP_THEME = gr.themes.Soft(
     primary_hue="cyan",
     secondary_hue="orange",
@@ -247,21 +253,29 @@ def _build_capture_payload(
     history: list[tuple[str, str]],
     profile_name: str,
     backend_mode: str,
+    classification: str = DEFAULT_CAPTURE_CLASSIFICATION,
 ) -> dict[str, Any]:
+    """Build a PCA capture event conforming to pca_capture_event.schema.json.
+
+    The gateway validates against that schema with additionalProperties: false,
+    so only the contract fields are emitted. `assistant_reply`, `backend_mode`
+    and turn count are not part of the capture contract and are intentionally
+    dropped — the capture records the user's phone message, not VoxCPM state.
+    """
+    classification = _clean_text(classification).lower()
+    if classification not in CAPTURE_CLASSIFICATIONS:
+        classification = "confidential"
+
     return {
-        "source": "iphone",
+        "source": "iphone_shortcut",
         "capture_type": "text",
         "timestamp": datetime.now(timezone.utc).isoformat(),
-        "text": _clean_text(user_message),
-        "context_note": "Captured from VoxCPM phone assistant",
-        "tags": [tag for tag in ("voxcpm-phone-assistant", _clean_text(profile_name)) if tag],
-        "metadata": {
-            "assistant_reply": _clean_text(assistant_reply),
-            "voice_profile": _clean_text(profile_name),
-            "backend_mode": _clean_text(backend_mode).lower() or "auto",
-            "turn_count": len(history) + 1,
-            "origin": "voxcpm-phone-assistant",
+        "content": _clean_text(user_message),
+        "classification": classification,
+        "provenance": {
+            "agent": "voxcpm-phone-assistant",
         },
+        "tags": [tag for tag in ("voxcpm-phone-assistant", _clean_text(profile_name)) if tag],
     }
 
 
@@ -737,6 +751,7 @@ def prepare_turn(
             reference_transcript,
             (sample_rate, wav),
             status,
+            profile_data,
         )
 
     def speak_reply(
@@ -934,7 +949,7 @@ def clear_state(profile_data: dict[str, Any]):
 
                         Custom mode sends `{"message": "...", "history": [...], "assistant_context": "..."}`.
 
-                        If a PCA capture URL is configured, the phone message is also staged with `source: iphone`, `capture_type: text`, and metadata that includes the assistant reply.
+                        If a PCA capture URL is configured, the phone message is also staged as a PCA capture event (`source: iphone_shortcut`, `capture_type: text`, `content`, `classification`, and `provenance`) conforming to the PCA capture schema.
 
                         The response can be plain text or JSON with `reply`, `text`, `content`, or OpenAI-style `choices[0].message.content`.
                         """
diff --git a/tests/test_phone_assistant.py b/tests/test_phone_assistant.py
index d4166ba2..35773215 100644
--- a/tests/test_phone_assistant.py
+++ b/tests/test_phone_assistant.py
@@ -25,7 +25,7 @@ def test_extract_reply_text_supports_openai_style_response():
     assert _extract_reply_text(payload) == "assistant reply"
 
 
-def test_build_capture_payload_uses_phone_capture_contract():
+def test_build_capture_payload_matches_pca_schema():
     payload = _build_capture_payload(
         user_message="Hello PCA",
         assistant_reply="Cloned reply",
@@ -33,15 +33,50 @@ def test_build_capture_payload_uses_phone_capture_contract():
         profile_name="reddit-female",
         backend_mode="custom",
     )
-    assert payload["source"] == "iphone"
+    # Required fields per schemas/pca_capture_event.schema.json.
+    assert payload["source"] == "iphone_shortcut"
     assert payload["capture_type"] == "text"
-    assert payload["text"] == "Hello PCA"
     assert payload["timestamp"]
-    assert payload["context_note"] == "Captured from VoxCPM phone assistant"
+    assert payload["content"] == "Hello PCA"
+    assert payload["classification"] in {"public", "internal", "confidential", "restricted"}
+    assert payload["provenance"]["agent"] == "voxcpm-phone-assistant"
     assert "voxcpm-phone-assistant" in payload["tags"]
-    assert payload["metadata"]["assistant_reply"] == "Cloned reply"
-    assert payload["metadata"]["voice_profile"] == "reddit-female"
-    assert payload["metadata"]["turn_count"] == 2
+    # Off-contract keys rejected by the gateway (additionalProperties: false)
+    # must not be emitted.
+    assert set(payload) <= {
+        "source",
+        "capture_type",
+        "timestamp",
+        "content",
+        "classification",
+        "provenance",
+        "tags",
+    }
+    assert "text" not in payload
+    assert "metadata" not in payload
+    assert "context_note" not in payload
+
+
+def test_build_capture_payload_classification_override_validates():
+    ok = _build_capture_payload(
+        user_message="hi",
+        assistant_reply="",
+        history=[],
+        profile_name="p",
+        backend_mode="auto",
+        classification="internal",
+    )
+    assert ok["classification"] == "internal"
+
+    fallback = _build_capture_payload(
+        user_message="hi",
+        assistant_reply="",
+        history=[],
+        profile_name="p",
+        backend_mode="auto",
+        classification="bogus",
+    )
+    assert fallback["classification"] == "confidential"
 
 
 def test_extract_capture_receipt_supports_capture_id():

From cc834cfcdd47b8d07190659299a7a274c71a0f90 Mon Sep 17 00:00:00 2001
From: jjuniper-dev <spatialsensation@gmail.com>
Date: Mon, 13 Jul 2026 12:43:47 +0000
Subject: [PATCH 5/5] refactor: generalize phone assistant to a neutral webhook

Decouple the phone assistant bridge from PCA so it can be upstreamed:
the PCA-specific ingestion schema mapping now lives downstream, not in
this public TTS project.

- Rename env/UI config to neutral names: ASSISTANT_BACKEND_URL/TOKEN,
  ASSISTANT_CONTEXT, ASSISTANT_BACKEND_MODE, ASSISTANT_BACKEND_MODEL,
  CAPTURE_WEBHOOK_URL/TOKEN. No "PCA" identifiers remain in the code.
- Capture webhook now POSTs a neutral, backend-agnostic event
  ({source, type, timestamp, message, reply, profile, turn}); mapping it
  onto any ingestion schema is the receiving webhook's job.
- OpenAI-compatible backend model name is configurable (default "assistant")
  instead of hardcoded "pca".
- Drop the personal "reddit-female" default profile; --default-profile-name
  now defaults to empty (no auto-load).
- Mask backend/capture tokens in the UI (type="password").
- Update tests and README to the neutral contract.

Claude-Session: https://claude.ai/code/session_01RwWk3CSfGsNqpdr47PEMFN
---
 README.md                     |  16 ++++--
 src/voxcpm/phone_assistant.py | 100 +++++++++++++++-------------------
 tests/test_phone_assistant.py |  60 +++++---------------
 3 files changed, 71 insertions(+), 105 deletions(-)

diff --git a/README.md b/README.md
index c74651fa..14bd8d89 100644
--- a/README.md
+++ b/README.md
@@ -257,10 +257,18 @@ voxcpm-assistant --port 8809
 
 Use a clean reference sample plus an exact transcript for the highest-quality cloned voice. If you connect a webhook, the app POSTs the user message and conversation history and expects a reply in plain text or in a `reply` field.
 If you want phone microphone dictation, install the optional ASR dependency separately with `pip install funasr`.
-You can also save a named voice enrollment once and reuse it later from the app's profile panel.
-By default, the assistant loads the saved `reddit-female` profile if it exists.
-To wire in your PCA backend automatically, set `PCA_BACKEND_URL` plus optional `PCA_BACKEND_TOKEN`, `PCA_ASSISTANT_CONTEXT`, and `PCA_BACKEND_MODE=auto|openai|custom` before launching.
-To stage the phone message into PCA as a capture event, also set `PCA_CAPTURE_URL` plus optional `PCA_CAPTURE_TOKEN`. The assistant POSTs a PCA capture event that conforms to the PCA capture schema: `source: iphone_shortcut`, `capture_type: text`, `timestamp`, `content` (the user message), `classification`, and `provenance`. Set `PCA_CAPTURE_CLASSIFICATION` (`public|internal|confidential|restricted`, default `confidential`) to control routing sensitivity.
+You can also save a named voice enrollment once and reuse it later from the app's profile panel. Pass `--default-profile-name <name>` to auto-load a saved profile on start.
+
+To wire in an assistant backend automatically, set `ASSISTANT_BACKEND_URL` plus optional `ASSISTANT_BACKEND_TOKEN`, `ASSISTANT_CONTEXT`, `ASSISTANT_BACKEND_MODE=auto|openai|custom`, and `ASSISTANT_BACKEND_MODEL` (model name for OpenAI-compatible endpoints, default `assistant`) before launching.
+
+To stage each turn to a capture webhook, also set `CAPTURE_WEBHOOK_URL` plus optional `CAPTURE_WEBHOOK_TOKEN`. The assistant POSTs a neutral, backend-agnostic capture event:
+
+```json
+{"source": "voxcpm-phone-assistant", "type": "text", "timestamp": "...",
+ "message": "...", "reply": "...", "profile": "...", "turn": 1}
+```
+
+Mapping this onto a specific ingestion schema (field renames, classification, validation) is the receiving webhook's responsibility.
 
 ### 🚢 Production Deployment (Nano-vLLM)
 
diff --git a/src/voxcpm/phone_assistant.py b/src/voxcpm/phone_assistant.py
index 046bbfae..ac5cf940 100644
--- a/src/voxcpm/phone_assistant.py
+++ b/src/voxcpm/phone_assistant.py
@@ -39,18 +39,13 @@
 DEFAULT_MODEL_ID = "openbmb/VoxCPM2"
 DEFAULT_ASR_MODEL_ID = "iic/SenseVoiceSmall"
 PROFILE_DIR = Path.cwd() / ".voxcpm-phone-profiles"
-DEFAULT_BACKEND_URL = os.environ.get("PCA_BACKEND_URL", "").strip()
-DEFAULT_BACKEND_TOKEN = os.environ.get("PCA_BACKEND_TOKEN", "").strip()
-DEFAULT_BACKEND_CONTEXT = os.environ.get("PCA_ASSISTANT_CONTEXT", "").strip()
-DEFAULT_BACKEND_MODE = os.environ.get("PCA_BACKEND_MODE", "auto").strip().lower()
-DEFAULT_CAPTURE_URL = os.environ.get("PCA_CAPTURE_URL", "").strip()
-DEFAULT_CAPTURE_TOKEN = os.environ.get("PCA_CAPTURE_TOKEN", "").strip()
-
-CAPTURE_CLASSIFICATIONS = {"public", "internal", "confidential", "restricted"}
-_capture_classification = os.environ.get("PCA_CAPTURE_CLASSIFICATION", "confidential").strip().lower()
-DEFAULT_CAPTURE_CLASSIFICATION = (
-    _capture_classification if _capture_classification in CAPTURE_CLASSIFICATIONS else "confidential"
-)
+DEFAULT_BACKEND_URL = os.environ.get("ASSISTANT_BACKEND_URL", "").strip()
+DEFAULT_BACKEND_TOKEN = os.environ.get("ASSISTANT_BACKEND_TOKEN", "").strip()
+DEFAULT_BACKEND_CONTEXT = os.environ.get("ASSISTANT_CONTEXT", "").strip()
+DEFAULT_BACKEND_MODE = os.environ.get("ASSISTANT_BACKEND_MODE", "auto").strip().lower()
+DEFAULT_BACKEND_MODEL = os.environ.get("ASSISTANT_BACKEND_MODEL", "assistant").strip() or "assistant"
+DEFAULT_CAPTURE_URL = os.environ.get("CAPTURE_WEBHOOK_URL", "").strip()
+DEFAULT_CAPTURE_TOKEN = os.environ.get("CAPTURE_WEBHOOK_TOKEN", "").strip()
 
 APP_THEME = gr.themes.Soft(
     primary_hue="cyan",
@@ -253,29 +248,21 @@ def _build_capture_payload(
     history: list[tuple[str, str]],
     profile_name: str,
     backend_mode: str,
-    classification: str = DEFAULT_CAPTURE_CLASSIFICATION,
 ) -> dict[str, Any]:
-    """Build a PCA capture event conforming to pca_capture_event.schema.json.
+    """Build a neutral capture event for the configured capture webhook.
 
-    The gateway validates against that schema with additionalProperties: false,
-    so only the contract fields are emitted. `assistant_reply`, `backend_mode`
-    and turn count are not part of the capture contract and are intentionally
-    dropped — the capture records the user's phone message, not VoxCPM state.
+    This is a generic, backend-agnostic shape. Mapping it onto a specific
+    downstream ingestion schema (field renames, classification, provenance,
+    validation) is the receiving webhook's responsibility, not VoxCPM's.
     """
-    classification = _clean_text(classification).lower()
-    if classification not in CAPTURE_CLASSIFICATIONS:
-        classification = "confidential"
-
     return {
-        "source": "iphone_shortcut",
-        "capture_type": "text",
+        "source": "voxcpm-phone-assistant",
+        "type": "text",
         "timestamp": datetime.now(timezone.utc).isoformat(),
-        "content": _clean_text(user_message),
-        "classification": classification,
-        "provenance": {
-            "agent": "voxcpm-phone-assistant",
-        },
-        "tags": [tag for tag in ("voxcpm-phone-assistant", _clean_text(profile_name)) if tag],
+        "message": _clean_text(user_message),
+        "reply": _clean_text(assistant_reply),
+        "profile": _clean_text(profile_name),
+        "turn": len(history) + 1,
     }
 
 
@@ -470,6 +457,7 @@ def request_reply(
         history: list[tuple[str, str]],
         assistant_context: str,
         backend_mode: str = "auto",
+        backend_model: str = DEFAULT_BACKEND_MODEL,
         timeout: int = 30,
     ) -> str:
         backend_url = _clean_text(backend_url)
@@ -483,7 +471,7 @@ def request_reply(
 
         if openai_compatible:
             payload = {
-                "model": "pca",
+                "model": _clean_text(backend_model) or "assistant",
                 "messages": _build_backend_messages(user_message, history, assistant_context),
                 "temperature": 0.4,
                 "stream": False,
@@ -573,12 +561,12 @@ def _history_to_chatbot(history: list[tuple[str, str]]) -> list[tuple[str, str]]
 
 def build_interface(runtime: PhoneAssistantRuntime, default_profile_data: dict[str, Any] | None = None):
     default_profile_data = default_profile_data or {}
-    backend_url_default = _clean_text(os.environ.get("PCA_BACKEND_URL", DEFAULT_BACKEND_URL))
-    backend_token_default = _clean_text(os.environ.get("PCA_BACKEND_TOKEN", DEFAULT_BACKEND_TOKEN))
-    backend_context_default = _clean_text(os.environ.get("PCA_ASSISTANT_CONTEXT", DEFAULT_BACKEND_CONTEXT))
-    backend_mode_default = _clean_text(os.environ.get("PCA_BACKEND_MODE", DEFAULT_BACKEND_MODE)).lower() or "auto"
-    capture_url_default = _clean_text(os.environ.get("PCA_CAPTURE_URL", DEFAULT_CAPTURE_URL))
-    capture_token_default = _clean_text(os.environ.get("PCA_CAPTURE_TOKEN", DEFAULT_CAPTURE_TOKEN))
+    backend_url_default = _clean_text(os.environ.get("ASSISTANT_BACKEND_URL", DEFAULT_BACKEND_URL))
+    backend_token_default = _clean_text(os.environ.get("ASSISTANT_BACKEND_TOKEN", DEFAULT_BACKEND_TOKEN))
+    backend_context_default = _clean_text(os.environ.get("ASSISTANT_CONTEXT", DEFAULT_BACKEND_CONTEXT))
+    backend_mode_default = _clean_text(os.environ.get("ASSISTANT_BACKEND_MODE", DEFAULT_BACKEND_MODE)).lower() or "auto"
+    capture_url_default = _clean_text(os.environ.get("CAPTURE_WEBHOOK_URL", DEFAULT_CAPTURE_URL))
+    capture_token_default = _clean_text(os.environ.get("CAPTURE_WEBHOOK_TOKEN", DEFAULT_CAPTURE_TOKEN))
     if backend_mode_default not in {"auto", "openai", "custom"}:
         backend_mode_default = "auto"
 
@@ -708,9 +696,9 @@ def prepare_turn(
                     profile_name=_clean_text(profile_data.get("name", "default")) or "default",
                     backend_mode=backend_mode,
                 )
-                capture_status = "Capture staged in PCA."
+                capture_status = "Capture staged."
                 if capture_receipt:
-                    capture_status = f"Capture staged in PCA ({capture_receipt})."
+                    capture_status = f"Capture staged ({capture_receipt})."
             except Exception as exc:
                 logger.warning("Capture staging failed: %s", exc)
                 capture_status = f"Capture staging failed: {exc}"
@@ -737,7 +725,7 @@ def prepare_turn(
         if reference_audio and not reference_transcript and transcript:
             reference_transcript = transcript
 
-        history = history + [(f"You: {user_text_clean}", f"PCA: {assistant_reply}")]
+        history = history + [(f"You: {user_text_clean}", f"Assistant: {assistant_reply}")]
         status = "Generated cloned speech."
         if reference_audio and transcript:
             status = "Generated cloned speech with transcript-guided cloning."
@@ -883,24 +871,26 @@ def clear_state(profile_data: dict[str, Any]):
 
                     with gr.Accordion("Advanced", open=False):
                         assistant_webhook_url = gr.Textbox(
-                            label="PCA backend URL",
+                            label="Assistant backend URL",
                             value=backend_url_default,
                             placeholder="OpenAI-compatible /v1/chat/completions or a custom webhook endpoint.",
                         )
                         assistant_webhook_token = gr.Textbox(
-                            label="PCA backend token",
+                            label="Assistant backend token",
                             value=backend_token_default,
                             placeholder="Optional bearer token.",
+                            type="password",
                         )
                         capture_webhook_url = gr.Textbox(
-                            label="PCA capture URL",
+                            label="Capture webhook URL",
                             value=capture_url_default,
-                            placeholder="Optional capture webhook URL for staging the phone message in PCA.",
+                            placeholder="Optional webhook URL for staging the phone message downstream.",
                         )
                         capture_webhook_token = gr.Textbox(
-                            label="PCA capture token",
+                            label="Capture webhook token",
                             value=capture_token_default,
                             placeholder="Optional bearer token for the capture webhook.",
+                            type="password",
                         )
                         assistant_context = gr.Textbox(
                             label="Assistant context",
@@ -945,11 +935,11 @@ def clear_state(profile_data: dict[str, Any]):
                         """
                         **Backend payloads**
 
-                        OpenAI-compatible mode sends `{"model":"pca","messages":[...],"temperature":0.4,"stream":false}`.
+                        OpenAI-compatible mode sends `{"model":"assistant","messages":[...],"temperature":0.4,"stream":false}` (model name is configurable).
 
                         Custom mode sends `{"message": "...", "history": [...], "assistant_context": "..."}`.
 
-                        If a PCA capture URL is configured, the phone message is also staged as a PCA capture event (`source: iphone_shortcut`, `capture_type: text`, `content`, `classification`, and `provenance`) conforming to the PCA capture schema.
+                        If a capture webhook URL is configured, the turn is also POSTed as a neutral capture event (`source`, `type`, `timestamp`, `message`, `reply`, `profile`, `turn`). Mapping it onto any downstream ingestion schema is the receiving webhook's job.
 
                         The response can be plain text or JSON with `reply`, `text`, `content`, or OpenAI-style `choices[0].message.content`.
                         """
@@ -1065,7 +1055,7 @@ def launch(
     no_denoiser: bool = False,
     optimize: bool = True,
     zipenhancer_path: Optional[str] = None,
-    default_profile_name: str = "reddit-female",
+    default_profile_name: str = "",
     backend_url: str = DEFAULT_BACKEND_URL,
     backend_token: str = DEFAULT_BACKEND_TOKEN,
     capture_url: str = DEFAULT_CAPTURE_URL,
@@ -1088,17 +1078,17 @@ def launch(
             logger.warning("Default profile not found: %s", default_profile_name)
 
     if _clean_text(backend_url):
-        os.environ["PCA_BACKEND_URL"] = backend_url
+        os.environ["ASSISTANT_BACKEND_URL"] = backend_url
     if _clean_text(backend_token):
-        os.environ["PCA_BACKEND_TOKEN"] = backend_token
+        os.environ["ASSISTANT_BACKEND_TOKEN"] = backend_token
     if _clean_text(capture_url):
-        os.environ["PCA_CAPTURE_URL"] = capture_url
+        os.environ["CAPTURE_WEBHOOK_URL"] = capture_url
     if _clean_text(capture_token):
-        os.environ["PCA_CAPTURE_TOKEN"] = capture_token
+        os.environ["CAPTURE_WEBHOOK_TOKEN"] = capture_token
     if _clean_text(backend_context):
-        os.environ["PCA_ASSISTANT_CONTEXT"] = backend_context
+        os.environ["ASSISTANT_CONTEXT"] = backend_context
     if _clean_text(backend_mode):
-        os.environ["PCA_BACKEND_MODE"] = backend_mode
+        os.environ["ASSISTANT_BACKEND_MODE"] = backend_mode
 
     demo = build_interface(runtime, default_profile_data=default_profile_data)
     demo.queue(max_size=16, default_concurrency_limit=1).launch(
@@ -1119,7 +1109,7 @@ def main():
     parser.add_argument("--no-denoiser", action="store_true")
     parser.add_argument("--no-optimize", action="store_true")
     parser.add_argument("--zipenhancer-path", type=str, default=None)
-    parser.add_argument("--default-profile-name", type=str, default="reddit-female")
+    parser.add_argument("--default-profile-name", type=str, default="")
     parser.add_argument("--backend-url", type=str, default=DEFAULT_BACKEND_URL)
     parser.add_argument("--backend-token", type=str, default=DEFAULT_BACKEND_TOKEN)
     parser.add_argument("--capture-url", type=str, default=DEFAULT_CAPTURE_URL)
diff --git a/tests/test_phone_assistant.py b/tests/test_phone_assistant.py
index 35773215..fa774f13 100644
--- a/tests/test_phone_assistant.py
+++ b/tests/test_phone_assistant.py
@@ -25,58 +25,26 @@ def test_extract_reply_text_supports_openai_style_response():
     assert _extract_reply_text(payload) == "assistant reply"
 
 
-def test_build_capture_payload_matches_pca_schema():
+def test_build_capture_payload_is_neutral_shape():
     payload = _build_capture_payload(
-        user_message="Hello PCA",
+        user_message="Hello there",
         assistant_reply="Cloned reply",
         history=[("u1", "a1")],
-        profile_name="reddit-female",
+        profile_name="my-voice",
         backend_mode="custom",
     )
-    # Required fields per schemas/pca_capture_event.schema.json.
-    assert payload["source"] == "iphone_shortcut"
-    assert payload["capture_type"] == "text"
+    # Neutral, backend-agnostic shape. Mapping onto a downstream ingestion
+    # schema is the receiving webhook's responsibility, not VoxCPM's.
+    assert payload["source"] == "voxcpm-phone-assistant"
+    assert payload["type"] == "text"
     assert payload["timestamp"]
-    assert payload["content"] == "Hello PCA"
-    assert payload["classification"] in {"public", "internal", "confidential", "restricted"}
-    assert payload["provenance"]["agent"] == "voxcpm-phone-assistant"
-    assert "voxcpm-phone-assistant" in payload["tags"]
-    # Off-contract keys rejected by the gateway (additionalProperties: false)
-    # must not be emitted.
-    assert set(payload) <= {
-        "source",
-        "capture_type",
-        "timestamp",
-        "content",
-        "classification",
-        "provenance",
-        "tags",
-    }
-    assert "text" not in payload
-    assert "metadata" not in payload
-    assert "context_note" not in payload
-
-
-def test_build_capture_payload_classification_override_validates():
-    ok = _build_capture_payload(
-        user_message="hi",
-        assistant_reply="",
-        history=[],
-        profile_name="p",
-        backend_mode="auto",
-        classification="internal",
-    )
-    assert ok["classification"] == "internal"
-
-    fallback = _build_capture_payload(
-        user_message="hi",
-        assistant_reply="",
-        history=[],
-        profile_name="p",
-        backend_mode="auto",
-        classification="bogus",
-    )
-    assert fallback["classification"] == "confidential"
+    assert payload["message"] == "Hello there"
+    assert payload["reply"] == "Cloned reply"
+    assert payload["profile"] == "my-voice"
+    assert payload["turn"] == 2
+    # No downstream-specific coupling leaks into the neutral payload.
+    assert "classification" not in payload
+    assert "provenance" not in payload
 
 
 def test_extract_capture_receipt_supports_capture_id():