[feat] update some feature

sync code of  fastrtc,
add text support through datachannel,
fix safari connect problem
support chat without camera or mic

backend/fastrtc/speech_to_text/__init__.py

@@ -0,0 +1,3 @@
+from .stt_ import MoonshineSTT, get_stt_model, stt_for_chunks
+
+__all__ = ["get_stt_model", "MoonshineSTT", "get_stt_model", "stt_for_chunks"]

backend/fastrtc/speech_to_text/stt_.py

@@ -0,0 +1,76 @@
+from functools import lru_cache
+from pathlib import Path
+from typing import Literal, Protocol
+
+import click
+import librosa
+import numpy as np
+from numpy.typing import NDArray
+
+from ..utils import AudioChunk, audio_to_float32
+
+curr_dir = Path(__file__).parent
+
+
+class STTModel(Protocol):
+    def stt(self, audio: tuple[int, NDArray[np.int16 | np.float32]]) -> str: ...
+
+
+class MoonshineSTT(STTModel):
+    def __init__(
+        self, model: Literal["moonshine/base", "moonshine/tiny"] = "moonshine/base"
+    ):
+        try:
+            from moonshine_onnx import MoonshineOnnxModel, load_tokenizer
+        except (ImportError, ModuleNotFoundError):
+            raise ImportError(
+                "Install fastrtc[stt] for speech-to-text and stopword detection support."
+            )
+
+        self.model = MoonshineOnnxModel(model_name=model)
+        self.tokenizer = load_tokenizer()
+
+    def stt(self, audio: tuple[int, NDArray[np.int16 | np.float32]]) -> str:
+        sr, audio_np = audio  # type: ignore
+        if audio_np.dtype == np.int16:
+            audio_np = audio_to_float32(audio)
+        if sr != 16000:
+            audio_np: NDArray[np.float32] = librosa.resample(
+                audio_np, orig_sr=sr, target_sr=16000
+            )
+        if audio_np.ndim == 1:
+            audio_np = audio_np.reshape(1, -1)
+        tokens = self.model.generate(audio_np)
+        return self.tokenizer.decode_batch(tokens)[0]
+
+
+@lru_cache
+def get_stt_model(
+    model: Literal["moonshine/base", "moonshine/tiny"] = "moonshine/base",
+) -> STTModel:
+    import os
+
+    os.environ["TOKENIZERS_PARALLELISM"] = "false"
+    m = MoonshineSTT(model)
+    from moonshine_onnx import load_audio
+
+    audio = load_audio(str(curr_dir / "test_file.wav"))
+    print(click.style("INFO", fg="green") + ":\t  Warming up STT model.")
+
+    m.stt((16000, audio))
+    print(click.style("INFO", fg="green") + ":\t  STT model warmed up.")
+    return m
+
+
+def stt_for_chunks(
+    stt_model: STTModel,
+    audio: tuple[int, NDArray[np.int16 | np.float32]],
+    chunks: list[AudioChunk],
+) -> str:
+    sr, audio_np = audio
+    return " ".join(
+        [
+            stt_model.stt((sr, audio_np[chunk["start"] : chunk["end"]]))
+            for chunk in chunks
+        ]
+    )