feat: add telemetry origin (#141)

* feat: anonymised telemetry to track usage patterns * add: PR suggestions * feat: add telemetry origin field * feat: fix POST definition --------- Co-authored-by: Siddharth Sharma <[email protected]> Co-authored-by: siddharth sharma <[email protected]>
metavoiceio · May 3, 2024 · dab7454 · dab7454
1 parent eebdcc6
commit dab7454
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Showing 4 changed files with 41 additions and 30 deletions.
diff --git a/README.md b/README.md
@@ -30,6 +30,7 @@ docker-compose up -d ui && docker-compose ps && docker-compose logs -f
 
 Server
 ```bash
+# navigate to <URL>/docs for API definitions
 docker-compose up -d server && docker-compose ps && docker-compose logs -f
 ```
 
@@ -102,7 +103,10 @@ tts.synthesise(text="This is a demo of text to speech by MetaVoice-1B, an open-s
 ```bash
 # You can use `--quantisation_mode int4` or `--quantisation_mode int8` for experimental faster inference. This will degrade the quality of the audio.
 # Note: int8 is slower than bf16/fp16 for undebugged reasons. If you want fast, try int4 which is roughly 2x faster than bf16/fp16.
+
+# navigate to <URL>/docs for API definitions
 poetry run python serving.py
+
 poetry run python app.py
 ```
 

diff --git a/app.py b/app.py
@@ -13,14 +13,14 @@
 from fam.llm.utils import check_audio_file
 
 #### setup model
-TTS_MODEL = tyro.cli(TTS)
+TTS_MODEL = tyro.cli(TTS, args=["--telemetry_origin", "webapp"])
 
 #### setup interface
 RADIO_CHOICES = ["Preset voices", "Upload target voice (atleast 30s)"]
 MAX_CHARS = 220
 PRESET_VOICES = {
     # female
-    "Bria": "https://cdn.themetavoice.xyz/speakers%2Fbria.mp3",
+    "Bria": "https://cdn.themetavoice.xyz/speakers/bria.mp3",
     # male
     "Alex": "https://cdn.themetavoice.xyz/speakers/alex.mp3",
     "Jacob": "https://cdn.themetavoice.xyz/speakers/jacob.wav",

diff --git a/fam/llm/fast_inference.py b/fam/llm/fast_inference.py
@@ -46,6 +46,7 @@ def __init__(
         output_dir: str = "outputs",
         quantisation_mode: Optional[Literal["int4", "int8"]] = None,
         first_stage_path: Optional[str] = None,
+        telemetry_origin: Optional[str] = None,
     ):
         """
         Initialise the TTS model.
@@ -60,6 +61,7 @@ def __init__(
                 - int4 for int4 weight-only quantisation,
                 - int8 for int8 weight-only quantisation.
             first_stage_path: path to first-stage LLM checkpoint. If provided, this will override the one grabbed from Hugging Face via `model_name`.
+            telemetry_origin: A string identifier that specifies the origin of the telemetry data sent to PostHog.
         """
 
         # NOTE: this needs to come first so that we don't change global state when we want to use
@@ -104,6 +106,7 @@ def __init__(
         self._seed = seed
         self._quantisation_mode = quantisation_mode
         self._model_name = model_name
+        self._telemetry_origin = telemetry_origin
 
     def synthesise(self, text: str, spk_ref_path: str, top_p=0.95, guidance_scale=3.0, temperature=1.0) -> str:
         """
@@ -183,6 +186,7 @@ def synthesise(self, text: str, spk_ref_path: str, top_p=0.95, guidance_scale=3.
                     "seed": self._seed,
                     "first_stage_ckpt": self._first_stage_ckpt,
                     "gpu": torch.cuda.get_device_name(0),
+                    "telemetry_origin": self._telemetry_origin,
                 },
             )
         )

diff --git a/serving.py b/serving.py
@@ -1,4 +1,3 @@
-import json
 import logging
 import shlex
 import subprocess
@@ -12,7 +11,7 @@
 import tyro
 import uvicorn
 from attr import dataclass
-from fastapi import Request
+from fastapi import File, Form, HTTPException, UploadFile, status
 from fastapi.responses import Response
 
 from fam.llm.fast_inference import TTS
@@ -50,55 +49,55 @@ class _GlobalState:
 GlobalState = _GlobalState()
 
 
-@dataclass(frozen=True)
-class TTSRequest:
-    text: str
-    speaker_ref_path: Optional[str] = None
-    guidance: float = 3.0
-    top_p: float = 0.95
-    top_k: Optional[int] = None
-
-
 @app.get("/health")
 async def health_check():
     return {"status": "ok"}
 
 
 @app.post("/tts", response_class=Response)
-async def text_to_speech(req: Request):
-    audiodata = await req.body()
-    payload = None
+async def text_to_speech(
+    text: str = Form(...),
+    speaker_ref_path: Optional[str] = Form(None),
+    guidance: float = Form(3.0),
+    top_p: float = Form(0.95),
+    audiodata: Optional[UploadFile] = File(None),
+):
+    # Ensure at least one of speaker_ref_path or audiodata is provided
+    if not audiodata and not speaker_ref_path:
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail="Either an audio file or a speaker reference path must be provided.",
+        )
+
     wav_out_path = None
 
     try:
-        headers = req.headers
-        payload = headers["X-Payload"]
-        payload = json.loads(payload)
-        tts_req = TTSRequest(**payload)
         with tempfile.NamedTemporaryFile(suffix=".wav") as wav_tmp:
-            if tts_req.speaker_ref_path is None:
+            if speaker_ref_path is None:
                 wav_path = _convert_audiodata_to_wav_path(audiodata, wav_tmp)
                 check_audio_file(wav_path)
             else:
                 # TODO: fix
-                wav_path = tts_req.speaker_ref_path
+                wav_path = speaker_ref_path
 
             if wav_path is None:
                 warnings.warn("Running without speaker reference")
-                assert tts_req.guidance is None
+                assert guidance is None
 
             wav_out_path = GlobalState.tts.synthesise(
-                text=tts_req.text,
+                text=text,
                 spk_ref_path=wav_path,
-                top_p=tts_req.top_p,
-                guidance_scale=tts_req.guidance,
+                top_p=top_p,
+                guidance_scale=guidance,
             )
 
         with open(wav_out_path, "rb") as f:
             return Response(content=f.read(), media_type="audio/wav")
     except Exception as e:
         # traceback_str = "".join(traceback.format_tb(e.__traceback__))
-        logger.exception(f"Error processing request {payload}")
+        logger.exception(
+            f"Error processing request. text: {text}, speaker_ref_path: {speaker_ref_path}, guidance: {guidance}, top_p: {top_p}"
+        )
         return Response(
             content="Something went wrong. Please try again in a few mins or contact us on Discord",
             status_code=500,
@@ -108,9 +107,9 @@ async def text_to_speech(req: Request):
             Path(wav_out_path).unlink(missing_ok=True)
 
 
-def _convert_audiodata_to_wav_path(audiodata, wav_tmp):
+def _convert_audiodata_to_wav_path(audiodata: UploadFile, wav_tmp):
     with tempfile.NamedTemporaryFile() as unknown_format_tmp:
-        if unknown_format_tmp.write(audiodata) == 0:
+        if unknown_format_tmp.write(audiodata.read()) == 0:
             return None
         unknown_format_tmp.flush()
 
@@ -129,7 +128,11 @@ def _convert_audiodata_to_wav_path(audiodata, wav_tmp):
     logging.root.setLevel(logging.INFO)
 
     GlobalState.config = tyro.cli(ServingConfig)
-    GlobalState.tts = TTS(seed=GlobalState.config.seed, quantisation_mode=GlobalState.config.quantisation_mode)
+    GlobalState.tts = TTS(
+        seed=GlobalState.config.seed,
+        quantisation_mode=GlobalState.config.quantisation_mode,
+        telemetry_origin="api_server",
+    )
 
     app.add_middleware(
         fastapi.middleware.cors.CORSMiddleware,