# Data Contracts — Ten31 Transcripts

Companion to docs 01/02. Defines the files the app produces/stores and the **real
SparkControl contract** (verified against the live backend). The `label-merge`
endpoint is the app's primary integration point.

---

## 1. `visual_timeline.json` (the app's primary output)

Rich, app-native record of who-was-speaking-when, inferred from the screen.
Times are **seconds relative to session `t0`** (the shared audio clock).

```jsonc
{
  "schema_version": "1.1",
  "session_id": "2026-06-05T14-03_zoom",
  "app": "zoom",                       // zoom | teams | signal | meet
  "adapter_version": "zoom-0.3.1",
  "t0_unix": 1749135780.123,
  "duration_sec": 2841.7,
  "fps_sampled": 3,
  "self_name": "Grant",                // user's name; segments from mic VAD
  "participants": [
    { "name": "Grant", "is_self": true },
    { "name": "Sarah Jones", "aliases": ["Sarah J"] },
    { "name": "Dmitri" }
  ],
  "segments": [
    { "start": 0.0,  "end": 4.5, "name": "Grant",       "confidence": 0.97, "source": "mic_vad" },
    { "start": 4.8,  "end": 9.3, "name": "Sarah Jones", "confidence": 0.82, "source": "vision" }
  ],
  "visual_gaps": [
    { "start": 120.4, "end": 138.9, "reason": "minimized" }   // reason: minimized | tab_switched
  ]
}
```
- Segments **may overlap** (crosstalk) — do not flatten.
- `source ∈ {vision, accessibility, fused, mic_vad}`.
- The user (mic-VAD `is_self`) is pre-seeded so the backend names them and
  enrolls their voiceprint on call one.

### 1.1 Mapping to the `label-merge` `timeline` field
`label-merge` wants a **flat JSON array** of `{start, end, name, confidence}`
(seconds). Build it by taking `segments` and dropping `source`:
```json
[{"start":0.0,"end":4.5,"name":"Grant","confidence":0.97},
 {"start":4.8,"end":9.3,"name":"Sarah Jones","confidence":0.82}]
```
When chunking, **slice to the chunk window and rebase to chunk-local seconds**
(subtract chunk start) before sending.

## 2. `manifest.json`
```jsonc
{
  "session_id": "2026-06-05T14-03_zoom",
  "app": "zoom",
  "t0_unix": 1749135780.123,
  "duration_sec": 2841.7,
  "audio": {
    "mixed":  { "file": "mixed_mono_16k.wav", "sr": 16000, "channels": 1, "sha256": "..." },
    "mic":    { "file": "mic.wav",    "sr": 16000, "channels": 1, "sha256": "..." },
    "system": { "file": "system.wav", "sr": 16000, "channels": 1, "sha256": "..." }
  },
  "chunking": { "enabled": true, "chunk_sec": 150, "chunks": 19 },
  "visual_timeline": "visual_timeline.json",
  "backend_result": "speakers.json",
  "adapter_versions": { "zoom": "0.3.1" },
  "app_version": "0.1.0"
}
```
(On the dual-channel path the backend gets `mic.wav` + `system.wav` directly; on
the mono fallback it gets `mixed_mono_16k.wav`. The mic track is the user's known
identity / VAD source. **Note:** the per-file `sha256` fields above are part of the
intended contract but are **not currently emitted** by the pipeline.)

---

## 3. SparkControl — connection (real)

- **Base URL (confirmed):** a private LAN host — a `.local` mDNS name (preferred
  over a raw IP; it survives IP changes) — configured in Settings or via the
  `SPARK_BACKEND_URL` env var, and **never committed**. Service-discovery JSON is at
  `GET /api/endpoints` (returns current vLLM / Parakeet / Kokoro URLs). All audio
  endpoints in §4–§5 hang off this base. **Make it a setting** so the host can
  change, and ship a neutral placeholder (`https://your-spark-backend.local`) as
  the default.
- **TLS:** Start9 self-signed Root CA. Supported path: install the Start9 Root CA
  into the System keychain (default trust then succeeds). Skip-verification is an
  **off-by-default, host-scoped** escape hatch (`InsecureTrustDelegate`, scoped to
  the configured backend host), not the default.
- **Auth:** **none on the LAN.** No token/key today.
- **Limits:** **200 MB/request** (`413` over); timeouts ~300 s (transcription),
  ~600 s (diarization). **Send audio requests SEQUENTIALLY** — concurrent audio
  trips a GPU FFT race → `503 + Retry-After`.
- **Transport:** `multipart/form-data`. Audio file field is **`file`** on the mono
  path, or **`mic_file`** + **`system_file`** on the dual-channel path (bytes, not
  base64/path).
- **All endpoints are synchronous** (no job IDs / polling).
- **Errors:** JSON `{"detail": "..."}`; `400` malformed, `413` too large, `503 +
  Retry-After` transient (retry after the interval).
- **Health/discovery:** `GET /api/status`, `GET /api/endpoints`, `GET /v1/models`.

---

## 4. ★ `POST /api/audio/label-merge` — the app's primary call

Diarize + name clusters from the visual timeline (majority temporal overlap),
with voiceprint fallback, optionally transcribed. Synchronous. **Stateless** —
the app owns the timeline and the voiceprint library.

**Multipart fields** — two audio shapes: **mono** (`file`) or **dual-channel**
(`mic_file` + `system_file`, preferred when the system track is healthy):
| field | required | notes |
|---|---|---|
| `file` | mono path | mixed-mono WAV (the chunk, when chunking) |
| `mic_file` | dual path | the user's mic track (chunk) — attributed to `self_name` |
| `system_file` | dual path | the remote/system track (chunk) |
| `self_name` | dual path | the user's name; the mic channel is attributed to them |
| `self_vad` | no | chunk-local windows where the mic is genuinely the user (active + louder than system) |
| `timeline` | **yes** | flat JSON array `[{"start","end","name","confidence"}]`, chunk-local seconds (§1.1); on the dual path it names only the remote speakers |
| `known_voiceprints` | no | JSON `{"<name>":[192 floats], ...}` from `VoiceprintStore` |
| `transcribe` | no | `"true"` to also return per-segment text (default false) |
| `min_overlap` | no | min fraction of a cluster's time overlapping the winning name (default `0.0`) |
| `voiceprint_threshold` | no | cosine sim to accept a voiceprint match (default `0.5`) |

```bash
curl -k -X POST https://<host>/api/audio/label-merge \
  -F "file=@chunk_003.wav" \
  -F 'timeline=[{"start":0,"end":4.5,"name":"Grant"},{"start":4.8,"end":9.3,"name":"Sarah Jones"}]' \
  -F 'known_voiceprints={"Grant":[/*192*/],"Sarah Jones":[/*192*/]}' \
  -F "transcribe=true"
```

**Response (`transcribe=true`):**
```jsonc
{
  "duration": 9.259,
  "speakers": [
    { "cluster": "Speaker_0", "name": "Grant",       "source": "visual",
      "overlap_confidence": 0.9866, "fingerprint": [/*192 floats*/] },
    { "cluster": "Speaker_1", "name": "Sarah Jones", "source": "voiceprint",
      "match_similarity": 0.71,     "fingerprint": [/*192 floats*/] }
  ],
  "segments": [
    { "start_ms": 0,    "end_ms": 4480, "speaker": "Grant",
      "text": "Good morning everyone. I think the energy thesis is strong this quarter." },
    { "start_ms": 4800, "end_ms": 9040, "speaker": "Sarah Jones",
      "text": "I agree, but I am worried about the lockup terms and the fee load this time." }
  ],
  "fingerprints": { "Grant": [/*192*/], "Sarah Jones": [/*192*/] },
  "models": { "diarization": "nvidia/diar_sortformer_4spk-v1",
              "embedding": "nvidia/speakerverification_en_titanet_large" }
}
```
- `transcribe=false` → segments are `{start_s, end_s, speaker, confidence}` (no text).
- **Resolution order per cluster:** `visual` → `voiceprint` (with
  `match_similarity`) → `Unknown_N` (`source:"unmatched"`, never mislabeled).
- **Persist `fingerprints`** keyed by name into `VoiceprintStore` (skip `Unknown_N`).
- **Diarizer caps at 4 speakers/chunk** and takes **no `num_speakers` hint** — chunk
  for larger/longer calls; names + voiceprints unify speakers across chunks.

---

## 5. Other SparkControl endpoints (reference / fallback)

### 5.1 `POST /v1/audio/transcriptions` (OpenAI-compatible, sync)
Plain STT. Fields: `file` (req), `model` (default `parakeet-tdt-0.6b-v3`),
`response_format` (`json` | `verbose_json` | `text`), `language`, `temperature`,
`prompt`. `verbose_json` returns word- **and** segment-level timestamps + full
`text`. Use only if you ever want transcript without speaker labels.

### 5.2 `POST /api/audio/diarize-chunk` (sync)
Field: `file`. Returns anonymous clusters `{start_s, end_s, speaker, confidence}`,
`speakers_detected`, and a 192-dim `fingerprints` map per local speaker. Use if
you ever want to do the merge client-side instead of via `label-merge` (not the
default path).

### 5.3 `POST /api/audio/transcribe-with-speakers` (sync)
Field: `file`. ASR + diarization merged into anonymous speaker-attributed blocks
`{start_ms, end_ms, speaker, text}`. (Anonymous — no naming. `label-merge` is the
named version.)

---

## 6. `speakers.json` — final stored output (target end state)

Per-chunk `label-merge` results concatenated, **timestamps offset back to session
(global) seconds**, names unified across chunks. This is the hand-off to the
user's downstream summarizer; the app stops here.

```jsonc
{
  "session_id": "2026-06-05T14-03_zoom",
  "app": "zoom",
  "duration_sec": 2841.7,
  "speakers": [
    { "name": "Grant",       "source": "visual",     "overlap_confidence": 0.99 },
    { "name": "Sarah Jones", "source": "voiceprint", "match_similarity": 0.71 },
    { "name": "Unknown_0",   "source": "unmatched" }
  ],
  "segments": [
    { "start": 0.0,   "end": 4.48,  "speaker": "Grant",       "text": "..." },
    { "start": 4.80,  "end": 9.04,  "speaker": "Sarah Jones", "text": "..." },
    { "start": 152.3, "end": 158.1, "speaker": "Unknown_0",   "text": "..." }
  ],
  "models": { "diarization": "nvidia/diar_sortformer_4spk-v1",
              "embedding": "nvidia/speakerverification_en_titanet_large",
              "transcription": "parakeet-tdt-0.6b-v3" }
}
```
(Convert backend `start_ms`/`end_ms` → seconds; add the chunk offset.)

## 7. `voiceprints.json` — local voiceprint library
```jsonc
{
  "Grant":       { "vector": [/*192 floats*/], "updated": "2026-06-05T14:51Z", "calls": 12 },
  "Sarah Jones": { "vector": [/*192 floats*/], "updated": "2026-06-02T09:10Z", "calls": 3 }
}
```
Loaded → `known_voiceprints` on every `label-merge` call. Updated from response
`fingerprints` for `visual`/high-confidence `voiceprint` speakers only. Never
stores `Unknown_N`. Update policy (`02 §2.9`): start = store latest with
`overlap_confidence ≥ ~0.8`; consider per-name running mean later.

## 8. Recap outputs (`transcript.md`, `recap.{html,json}`)
After `speakers.json` is assembled, the recap phase renders the human-readable
deliverables: a `transcript.md` (one line per diarized utterance) and an HTML
`recap.html`, backed by a structured `recap.json`. The recap's topic/summary
content is generated by the **backend LLM** (`POST /v1/chat/completions`, Qwen3);
the app owns the rendering and the in-app **speaker-name editor**, which can rewrite
names across `speakers.json`, the transcript, and the recap after the fact.