deepgram-python-conversational-stt
/deepgram-python-conversational-stt
Obsługuje w Pythonie konwersacyjne STT Deepgram v2 (Flux, /v2/listen) z transkrypcją strumieniową świadomą tur i wykrywaniem końca wypowiedzi.
- Autor
- deepgram ↗
- Repozytorium
- deepgram-python-sdk ↗
- Licencja
- MIT
- Ostatnia zmiana repozytorium
- 27.10.2026
Ocena i bezpieczeństwo
- Pliki w paczce
- 1
- Skrypty
- 0
- Komentarze HTML
- 0
- Adresy URL w SKILL.md
- 4
Brak sygnałów. Repozytorium zmienione 27.10.2026, bez odwołań do wycofanych modeli i API.
MIT, otwarta: można używać i zmieniać, z zachowaniem informacji o autorze.
Co robi i kiedy
Obsługuje w Pythonie konwersacyjne STT Deepgram v2 (Flux, /v2/listen) z transkrypcją strumieniową świadomą tur i wykrywaniem końca wypowiedzi.
Wyzwalacze z opisu
Oryginalny opis (EN)
Use when writing or reviewing Python code in this repo that calls Deepgram Conversational STT v2 / Flux (`/v2/listen`) for turn-aware streaming transcription. Covers `client.listen.v2.connect(...)`, Flux models, end-of-turn detection. Use `deepgram-python-speech-to-text` for standard v1 ASR, `deepgram-python-voice-agent` for full-duplex interactive assistants. Triggers include "flux", "v2 listen", "conversational STT", "turn detection", "end of turn", "EOT", "listen.v2", "flux-general-en", "flux-general-multi".
Jak działa
- When to use this product
- Authentication
- Quick start
- Key parameters
- Events (server → client)
- Async equivalent
- API reference (layered)
- Gotchas
- Example files in this repo
- Related skills
Podgląd SKILL.md
---
name: deepgram-python-conversational-stt
description: Use when writing or reviewing Python code in this repo that calls Deepgram Conversational STT v2 / Flux (`/v2/listen`) for turn-aware streaming transcription. Covers `client.listen.v2.connect(...)`, Flux models, end-of-turn detection. Use `deepgram-python-speech-to-text` for standard v1 ASR, `deepgram-python-voice-agent` for full-duplex interactive assistants. Triggers include "flux", "v2 listen", "conversational STT", "turn detection", "end of turn", "EOT", "listen.v2", "flux-general-en", "flux-general-multi".
---
# Using Deepgram Conversational STT / Flux (Python SDK)
Turn-aware streaming STT at `/v2/listen` — optimized for conversational audio (end-of-turn detection, eager EOT, barge-in scenarios).
## When to use this product
- You're building a **conversational UI** and need explicit turn boundaries.
- You want **Flux models** (optimized for human-to-human or human-to-agent conversation).
- You want lower latency turn signals than v1 utterance_end.
**Use a different skill when:**
- You want general-purpose transcription (captions, batch, non-conversational) → `deepgram-python-speech-to-text`.
- You want a full interactive agent (STT + LLM + TTS) → `deepgram-python-voice-agent`.
- You want analytics (summarize/sentiment) → `deepgram-python-audio-intelligence`.
## Authentication
```python
import os
from dotenv import load_dotenv
load_dotenv()
from deepgram import DeepgramClient
client = DeepgramClient(api_key=os.environ["DEEPGRAM_API_KEY"])
```
Header: `Authorization: Token <api_key>`. WSS only — no REST path on v2.
## Quick start
```python
import threading, time
from pathlib import Path
from deepgram.core.events import EventType
from deepgram.listen.v2.types import (
ListenV2CloseStream,
ListenV2Connected,
ListenV2FatalError,
ListenV2TurnInfo,
)
with client.listen.v2.connect(
model="flux-general-en",
encoding="linear16",
sample_rate="16000",
) as conn:
def on_message(m):
if isinstance(m, ListenV2TurnInfo):
print(f"turn {m.turn_index} [{m.event}] {m.transcript}")
elif isinstance(m, dict): # untyped fallback
if m.get("type") == "TurnInfo":
print(f"turn {m.get('turn_index')} [{m.get('event')}] {m.get('transcript')}")
else:
print(f"event: {getattr(m, 'type', type(m).__name__)}")
conn.on(EventType.OPEN, lambda _: print("open"))
conn.on(EventType.MESSAGE, on_message)
conn.on(EventType.CLOSE, lambda _: print("close"))
conn.on(EventType.ERROR, lambda e: print(f"err: {type(e).__name__}: {e}"))
def send_audio():
for chunk in mic_chunks(): # 80ms recommended
conn.send_media(chunk)
time.sleep(0.01)
conn.send_close_stream(ListenV2CloseStream(type="CloseStream"))
threading.Thread(target=send_audio, daemon=True).start()
conn.start_listening()
```
## Key parameters
| Param | Notes |
|---|---|
| `model` | `flux-general-en` (English) or `flux-general-multi` (multilingual) — REQUIRED, must be a Flux model |
| `encoding` | `linear16`, `mulaw`, etc. Omit for containerized audio |
| `sample_rate` | String in the SDK signature, e.g. `"16000"` |
| `eager_eot_threshold` | Fire end-of-turn early at this confidence |
| `eot_threshold` | Primary end-of-turn confidence; set to `"1.0"` to suppress confidence-based endings |
| `eot_timeout_ms` | Time-based fallback turn end; still applies when `eot_threshold="1.0"` |
| `keyterm` | Bias for domain keywords |
| `mip_opt_out`, `tag` | Metadata / privacy flags |
| `language_hint` | **ONLY for `flux-general-multi`** |
| `authorization`, `request_options` | Override auth or request options |
**No `language` parameter** on v2 — language is implied by model (`flux-general-en`) or hinted via `language_hint` on multi.
For application-controlled turns, use `eot_threshold="1.0"` with a sufficiently large `eot_timeout_ms`, then call `conn.send_force_end_turn()` for the active turn. ForceEndTurn is available on Deepgram-hosted deployments, including EU and AU. On self-hosted deployments, it requires the 2026-09-15 release or later with `listen_v2 = true` and `listen_v2_force_end_turn = true` under `[features]`; see `examples/16-transcription-force-end-turn.py`.
## Events (server → client)
- `ListenV2Connected` — connection established
- `ListenV2ConfigureSuccess` / `ListenV2ConfigureFailure` — mid-session config changes
- `ListenV2TurnInfo` — per-turn transcript + event (`Update`, `EndOfTurn`, `EagerEndOfTurn`, ...) + `turn_index`
- `ListenV2FatalError` — terminal error
Client messages: `ListenV2Media`, `ListenV2Configure`, `ListenV2ForceEndTurn`, `ListenV2CloseStream`.
## Async equivalent
```python
from deepgram import AsyncDeepgramClient
client = AsyncDeepgramClient()
async with client.listen.v2.connect(model="flux-general-en", ...) as conn:
# same .on(...) handlers, then:
await conn.start_listening()
```
## API reference (layered)
1. **In-repo reference**: `reference.md` — "Listen V2 Connect".
2. **AsyncAPI (WSS)**: https://developers.deepgram.com/asyncapi.yaml
3. **Context7**: library ID `/llmstxt/developers_deepgram_llms_txt`.
4. **Product docs**:
- https://developers.deepgram.com/reference/speech-to-text/listen-flux
- https://developers.deepgram.com/docs/flux/quickstart
- https://developers.deepgram.com/docs/flux/language-prompting
## Gotchas
1. **`/v2/listen`, not `/v1/listen`.** Different route, different client path (`listen.v2` vs `listen.v1`).
2. **Flux models only.** `nova-3`, `base`, etc. will be rejected. Use `flux-general-en` or `flux-general-multi`.
3. **No `language` parameter.** Language is set by model choice. Use `language_hint` on `flux-general-multi`.
4. **`sample_rate` is a STRING** in the SDK (e.g. `"16000"`).
5. **Send ~80ms audio chunks** for best turn-detection latency.
6. **Close with `send_close_stream(ListenV2CloseStream(type="CloseStream"))`** — not `send_finalize` (that's v1).
7. **Messages may arrive as typed objects OR raw dicts** — the SDK uses a tagged union with `construct_type` for unknowns. Handle both branches (see `socket_client.py` patch in `.fernignore`).
8. **`socket_client.py` is patched / frozen** (see `.fernignore` → `src/deepgram/listen/v2/socket_client.py`). Don't overwrite that manual patch during regeneration; treat other `listen/v2` files as generated unless the regen workflow says otherwise.
9. **Omit `encoding`/`sample_rate` for containerized audio** (WAV, OGG, etc.) — the server detects them from the container.
## Example files in this repo
- `examples/14-transcription-live-websocket-v2.py`
- `tests/manual/listen/v2/connect/main.py`
## Related skills
- `deepgram-python-speech-to-text` — v1 general-purpose STT (REST + WSS)
- `deepgram-python-voice-agent` — full interactive assistant
## Central product skills
For cross-language Deepgram product knowledge — the consolidated API reference, documentation finder, focused runnable recipes, third-party integration examples, and MCP setup — install the central skills:
```bash
npx skills add deepgram/skills
```
This SDK ships language-idiomatic code skills; `deepgram/skills` ships cross-language product knowledge (see `api`, `docs`, `recipes`, `examples`, `starters`, `setup-mcp`).
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