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Merge pull request #247 from pipecat-ai/aleix/twilio-updates

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some twilio updates
This commit is contained in:
Aleix Conchillo Flaqué
2024-06-21 10:14:40 -07:00
committed by GitHub
parent e195941aa5 0075dd8386
commit f9ecce739e
16 changed files with 178 additions and 128 deletions
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9
CHANGELOG.md
View File

@@ -9,6 +9,12 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
### Added
- Added new `FastAPIWebsocketTransport`. This is a new websocket transport that
can be integrated with FastAPI websockets.
- Added new `TwilioFrameSerializer`. This is a new serializer that knows how to
serialize and deserialize audio frames from Twilio.
- Added Daily transport event: `on_dialout_answered`. See
https://reference-python.daily.co/api_reference.html#daily.EventHandler
@@ -16,6 +22,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
### Other
- Added `twilio-chatbot`. This is an example that shows how to integrate Twilio
phone numbers with a Pipecat bot.
- Updated `07f-interruptible-azure.py` to use `AzureLLMService`,
`AzureSTTService` and `AzureTTSService`.

17
examples/README.md
View File

@@ -32,14 +32,15 @@ Next, follow the steps in the README for each demo.
## Projects:
| Project | Description | Services |
| -------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------- |
| [Simple Chatbot](simple-chatbot) | Basic voice-driven conversational bot. A good starting point for learning the flow of the framework. | Deepgram, OpenAI, Daily, Daily Prebuilt UI |
| [Storytelling Chatbot](storytelling-chatbot) | Stitches together multiple third-party services to create a collaborative storytime experience. | Deepgram, ElevenLabs, Open AI, Fal, Daily, Custom UI |
| [Translation Chatbot](translation-chatbot) | Listens for user speech, then translates that speech to Spanish and speaks the translation back. Demonstrates multi-participant use-cases. | Deepgram, Azure, OpenAI, Daily, Daily Prebuilt UI |
| [Moondream Chatbot](moondream-chatbot) | Demonstrates how to add vision capabilities to GPT4. **Note: works best with a GPU** | Deepgram, OpenAI, Moondream, Daily, Daily Prebuilt UI |
| Function-calling Chatbot (TBC) | A chatbot that can call functions in response to user input. | Deepgram, OpenAI, Fireworks, Daily, Daily Prebuilt UI |
| [Dialin Chatbot](dialin-chatbot) | A chatbot that connects to an incoming phone call from Daily or Twilio. | Deepgram, OpenAI, ElevenLabs, Daily, Twilio |
| Project | Description | Services |
|----------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------|
| [Simple Chatbot](simple-chatbot) | Basic voice-driven conversational bot. A good starting point for learning the flow of the framework. | Deepgram, ElevenLabs, OpenAI, Daily, Daily Prebuilt UI |
| [Storytelling Chatbot](storytelling-chatbot) | Stitches together multiple third-party services to create a collaborative storytime experience. | Deepgram, ElevenLabs, OpenAI, Fal, Daily, Custom UI |
| [Translation Chatbot](translation-chatbot) | Listens for user speech, then translates that speech to Spanish and speaks the translation back. Demonstrates multi-participant use-cases. | Deepgram, Azure, OpenAI, Daily, Daily Prebuilt UI |
| [Moondream Chatbot](moondream-chatbot) | Demonstrates how to add vision capabilities to GPT4. **Note: works best with a GPU** | Deepgram, ElevenLabs, OpenAI, Moondream, Daily, Daily Prebuilt UI |
| [Patient intake](patient-intake) | A chatbot that can call functions in response to user input. | Deepgram, ElevenLabs, OpenAI, Daily, Daily Prebuilt UI |
| [Dialin Chatbot](dialin-chatbot) | A chatbot that connects to an incoming phone call from Daily or Twilio. | Deepgram, ElevenLabs, OpenAI, Daily, Twilio |
| [Twilio Chatbot](twilio-chatbot) | A chatbot that connects to an incoming phone call from Twilio. | Deepgram, ElevenLabs, OpenAI, Daily, Twilio |
> [!IMPORTANT]
> These example projects use Daily as a WebRTC transport and can be joined using their hosted Prebuilt UI.

32
examples/twilio-chatbot/README.md
View File

@@ -7,6 +7,7 @@ This project is a FastAPI-based chatbot that integrates with Twilio to handle We
- [Features](#features)
- [Requirements](#requirements)
- [Installation](#installation)
- [Configure Twilio URLs](#configure-twilio-urls)
- [Running the Application](#running-the-application)
- [Usage](#usage)
@@ -38,11 +39,19 @@ This project is a FastAPI-based chatbot that integrates with Twilio to handle We
```
3. **Create .env**:
create .env based on .env.example
create .env based on env.example
4. **Install ngrok**:
Follow the instructions on the [ngrok website](https://ngrok.com/download) to download and install ngrok.
## Configure Twilio URLs
1. **Update the Twilio Webhook**:
Copy the ngrok URL and update your Twilio phone number webhook URL to `http://<ngrok_url>/start_call`.
2. **Update the streams.xml**:
Copy the ngrok URL and update templates/streams.xml with `wss://<ngrok_url>/ws`.
## Running the Application
### Using Python
@@ -57,13 +66,6 @@ This project is a FastAPI-based chatbot that integrates with Twilio to handle We
```sh
ngrok http 8765
```
3. **Update the Twilio Webhook**:
Copy the ngrok URL and update your Twilio phone number webhook URL to `http://<ngrok_url>/start_call`.
3. **Update the streams.xml**:
Copy the ngrok URL and update your .xml URL to `wss://<ngrok_url>/ws`.
### Using Docker
1. **Build the Docker image**:
@@ -73,22 +75,8 @@ This project is a FastAPI-based chatbot that integrates with Twilio to handle We
2. **Run the Docker container**:
```sh
docker build -t twilio-chatbot .
docker run -it --rm -p 8765:8765 twilio-chatbot
```
3. **Start ngrok**:
In a new terminal, start ngrok to tunnel the local server:
```sh
ngrok http 8765
```
4. **Update the Twilio Webhook**:
Copy the ngrok URL and update your Twilio phone number webhook URL to `http://<ngrok_url>/start_call`.
5. **Update the streams.xml**:
Copy the ngrok URL and update your .xml URL to `wss://<ngrok_url>/ws`.
## Usage
To start a call, simply make a call to your Twilio phone number. The webhook URL will direct the call to your FastAPI application, which will handle it accordingly.

12
examples/twilio-chatbot/test_bot.py → examples/twilio-chatbot/bot.py
View File

@@ -2,7 +2,7 @@ import aiohttp
import os
import sys
from pipecat.frames.frames import LLMMessagesFrame, Frame, AudioRawFrame
from pipecat.frames.frames import EndFrame, LLMMessagesFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -10,8 +10,6 @@ from pipecat.processors.aggregators.llm_response import (
LLMAssistantResponseAggregator,
LLMUserResponseAggregator
)
from pipecat.processors.frame_processor import FrameProcessor, FrameDirection
from pipecat.services.openai import OpenAILLMService
from pipecat.services.deepgram import DeepgramSTTService
from pipecat.services.elevenlabs import ElevenLabsTTSService
@@ -32,10 +30,8 @@ async def run_bot(websocket_client):
transport = FastAPIWebsocketTransport(
websocket=websocket_client,
params=FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
add_wav_header=False,
transcription_enabled=False,
vad_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
vad_audio_passthrough=True
@@ -57,7 +53,7 @@ async def run_bot(websocket_client):
messages = [
{
"role": "system",
"content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
"content": "You are a helpful LLM in an audio call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
},
]
@@ -83,6 +79,10 @@ async def run_bot(websocket_client):
{"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMMessagesFrame(messages)])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
await task.queue_frames([EndFrame()])
runner = PipelineRunner(handle_sigint=False)
await runner.run(task)

0
examples/twilio-chatbot/.env.example → examples/twilio-chatbot/env.example
View File

8
examples/twilio-chatbot/server.py
View File

@@ -1,8 +1,10 @@
from fastapi import FastAPI, WebSocket, WebSocketDisconnect
from fastapi.middleware.cors import CORSMiddleware
import uvicorn
from fastapi import FastAPI, WebSocket
from fastapi.middleware.cors import CORSMiddleware
from starlette.responses import HTMLResponse
from test_bot import run_bot
from bot import run_bot
app = FastAPI()

2
examples/twilio-chatbot/templates/streams.xml
View File

@@ -4,4 +4,4 @@
<Stream url="wss://<your server url>/ws"></Stream>
</Connect>
<Pause length="40"/>
</Response>
</Response>

28
linux-py3.10-requirements.txt
View File

@@ -81,7 +81,7 @@ fal-client==0.4.0
# via pipecat-ai (pyproject.toml)
faster-whisper==1.0.2
# via pipecat-ai (pyproject.toml)
filelock==3.15.1
filelock==3.15.3
# via
# huggingface-hub
# pyht
@@ -113,7 +113,7 @@ google-api-core[grpc]==2.19.0
# google-ai-generativelanguage
# google-api-python-client
# google-generativeai
google-api-python-client==2.133.0
google-api-python-client==2.134.0
# via google-generativeai
google-auth==2.30.0
# via
@@ -157,7 +157,7 @@ httpx==0.27.0
# openpipe
httpx-sse==0.4.0
# via fal-client
huggingface-hub==0.23.3
huggingface-hub==0.23.4
# via
# faster-whisper
# timm
@@ -183,23 +183,23 @@ jsonpatch==1.33
# via langchain-core
jsonpointer==3.0.0
# via jsonpatch
langchain==0.2.3
langchain==0.2.5
# via
# langchain-community
# pipecat-ai (pyproject.toml)
langchain-community==0.2.4
langchain-community==0.2.5
# via pipecat-ai (pyproject.toml)
langchain-core==0.2.5
langchain-core==0.2.9
# via
# langchain
# langchain-community
# langchain-openai
# langchain-text-splitters
langchain-openai==0.1.8
langchain-openai==0.1.9
# via pipecat-ai (pyproject.toml)
langchain-text-splitters==0.2.1
# via langchain
langsmith==0.1.77
langsmith==0.1.81
# via
# langchain
# langchain-community
@@ -273,9 +273,9 @@ openai==1.26.0
# pipecat-ai (pyproject.toml)
openpipe==4.14.0
# via pipecat-ai (pyproject.toml)
orjson==3.10.4
orjson==3.10.5
# via langsmith
packaging==23.2
packaging==24.1
# via
# huggingface-hub
# langchain-core
@@ -289,7 +289,7 @@ pillow==10.3.0
# torchvision
pluggy==1.5.0
# via pytest
proto-plus==1.23.0
proto-plus==1.24.0
# via
# google-ai-generativelanguage
# google-api-core
@@ -380,7 +380,7 @@ sniffio==1.3.1
# openai
sounddevice==0.4.7
# via pipecat-ai (pyproject.toml)
sqlalchemy==2.0.30
sqlalchemy==2.0.31
# via
# langchain
# langchain-community
@@ -388,7 +388,7 @@ sympy==1.12.1
# via
# onnxruntime
# torch
tenacity==8.3.0
tenacity==8.4.1
# via
# langchain
# langchain-community
@@ -442,7 +442,7 @@ typing-inspect==0.9.0
# via dataclasses-json
uritemplate==4.1.1
# via google-api-python-client
urllib3==2.2.1
urllib3==2.2.2
# via requests
verboselogs==1.7
# via deepgram-sdk

28
macos-py3.10-requirements.txt
View File

@@ -81,7 +81,7 @@ fal-client==0.4.0
# via pipecat-ai (pyproject.toml)
faster-whisper==1.0.2
# via pipecat-ai (pyproject.toml)
filelock==3.15.1
filelock==3.15.3
# via
# huggingface-hub
# pyht
@@ -112,7 +112,7 @@ google-api-core[grpc]==2.19.0
# google-ai-generativelanguage
# google-api-python-client
# google-generativeai
google-api-python-client==2.133.0
google-api-python-client==2.134.0
# via google-generativeai
google-auth==2.30.0
# via
@@ -154,7 +154,7 @@ httpx==0.27.0
# openpipe
httpx-sse==0.4.0
# via fal-client
huggingface-hub==0.23.3
huggingface-hub==0.23.4
# via
# faster-whisper
# timm
@@ -180,23 +180,23 @@ jsonpatch==1.33
# via langchain-core
jsonpointer==3.0.0
# via jsonpatch
langchain==0.2.3
langchain==0.2.5
# via
# langchain-community
# pipecat-ai (pyproject.toml)
langchain-community==0.2.4
langchain-community==0.2.5
# via pipecat-ai (pyproject.toml)
langchain-core==0.2.5
langchain-core==0.2.9
# via
# langchain
# langchain-community
# langchain-openai
# langchain-text-splitters
langchain-openai==0.1.8
langchain-openai==0.1.9
# via pipecat-ai (pyproject.toml)
langchain-text-splitters==0.2.1
# via langchain
langsmith==0.1.77
langsmith==0.1.81
# via
# langchain
# langchain-community
@@ -239,9 +239,9 @@ openai==1.26.0
# pipecat-ai (pyproject.toml)
openpipe==4.14.0
# via pipecat-ai (pyproject.toml)
orjson==3.10.4
orjson==3.10.5
# via langsmith
packaging==23.2
packaging==24.1
# via
# huggingface-hub
# langchain-core
@@ -255,7 +255,7 @@ pillow==10.3.0
# torchvision
pluggy==1.5.0
# via pytest
proto-plus==1.23.0
proto-plus==1.24.0
# via
# google-ai-generativelanguage
# google-api-core
@@ -346,7 +346,7 @@ sniffio==1.3.1
# openai
sounddevice==0.4.7
# via pipecat-ai (pyproject.toml)
sqlalchemy==2.0.30
sqlalchemy==2.0.31
# via
# langchain
# langchain-community
@@ -354,7 +354,7 @@ sympy==1.12.1
# via
# onnxruntime
# torch
tenacity==8.3.0
tenacity==8.4.1
# via
# langchain
# langchain-community
@@ -406,7 +406,7 @@ typing-inspect==0.9.0
# via dataclasses-json
uritemplate==4.1.1
# via google-api-python-client
urllib3==2.2.1
urllib3==2.2.2
# via requests
verboselogs==1.7
# via deepgram-sdk

42
src/pipecat/serializers/TwilioFrameSerializer.py
View File

@@ -1,42 +0,0 @@
import base64
import json
from pipecat.frames.frames import AudioRawFrame, Frame
from pipecat.serializers.base_serializer import FrameSerializer
from pipecat.utils.audio import ulaw_8000_to_pcm_16000, pcm_16000_to_ulaw_8000
class TwilioFrameSerializer(FrameSerializer):
SERIALIZABLE_TYPES = {
AudioRawFrame: "audio",
}
def __init__(self):
self.sid = None
def serialize(self, frame: AudioRawFrame) -> dict:
data = frame.audio
serialized_data = pcm_16000_to_ulaw_8000(data)
payload = base64.b64encode(serialized_data).decode('utf-8')
answer_dict = {"event": "media",
"streamSid": self.sid,
"media": {"payload": payload}}
return answer_dict
def deserialize(self, message: bytes) -> AudioRawFrame | None:
data = json.loads(message)
if not self.sid:
self.sid = data['streamSid'] if data.get("streamSid") else None
if data['event'] != 'media':
return None
else:
payload_base64 = data['media']['payload']
payload = base64.b64decode(payload_base64)
deserialized_data = ulaw_8000_to_pcm_16000(payload)
audio_frame = AudioRawFrame(audio=deserialized_data, num_channels=1, sample_rate=16000)
return audio_frame

4
src/pipecat/serializers/base_serializer.py
View File

@@ -12,9 +12,9 @@ from pipecat.frames.frames import Frame
class FrameSerializer(ABC):
@abstractmethod
def serialize(self, frame: Frame) -> bytes:
def serialize(self, frame: Frame) -> str | bytes | None:
pass
@abstractmethod
def deserialize(self, data: bytes) -> Frame | None:
def deserialize(self, data: str | bytes) -> Frame | None:
pass

4
src/pipecat/serializers/protobuf.py
View File

@@ -26,7 +26,7 @@ class ProtobufFrameSerializer(FrameSerializer):
def __init__(self):
pass
def serialize(self, frame: Frame) -> bytes:
def serialize(self, frame: Frame) -> str | bytes | None:
proto_frame = frame_protos.Frame()
if type(frame) not in self.SERIALIZABLE_TYPES:
raise ValueError(
@@ -41,7 +41,7 @@ class ProtobufFrameSerializer(FrameSerializer):
result = proto_frame.SerializeToString()
return result
def deserialize(self, data: bytes) -> Frame | None:
def deserialize(self, data: str | bytes) -> Frame | None:
"""Returns a Frame object from a Frame protobuf. Used to convert frames
passed over the wire as protobufs to Frame objects used in pipelines
and frame processors.

55
src/pipecat/serializers/twilio.py Normal file
View File

@@ -0,0 +1,55 @@
#
# Copyright (c) 2024, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
import base64
import json
from pipecat.frames.frames import AudioRawFrame, Frame
from pipecat.serializers.base_serializer import FrameSerializer
from pipecat.utils.audio import ulaw_8000_to_pcm_16000, pcm_16000_to_ulaw_8000
class TwilioFrameSerializer(FrameSerializer):
SERIALIZABLE_TYPES = {
AudioRawFrame: "audio",
}
def __init__(self):
self._sid = None
def serialize(self, frame: Frame) -> str | bytes | None:
if not isinstance(frame, AudioRawFrame):
return None
data = frame.audio
serialized_data = pcm_16000_to_ulaw_8000(data)
payload = base64.b64encode(serialized_data).decode("utf-8")
answer = {
"event": "media",
"streamSid": self._sid,
"media": {
"payload": payload
}
}
return json.dumps(answer)
def deserialize(self, data: str | bytes) -> Frame | None:
message = json.loads(data)
if not self._sid:
self._sid = message["streamSid"] if "streamSid" in message else None
if message["event"] != "media":
return None
else:
payload_base64 = message["media"]["payload"]
payload = base64.b64decode(payload_base64)
deserialized_data = ulaw_8000_to_pcm_16000(payload)
audio_frame = AudioRawFrame(audio=deserialized_data, num_channels=1, sample_rate=16000)
return audio_frame

52
src/pipecat/transports/network/fastapi_websocket.py
View File

@@ -1,12 +1,18 @@
#
# Copyright (c) 2024, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
import asyncio
import io
import wave
from fastapi import WebSocket
from typing import Awaitable, Callable
from pydantic.main import BaseModel
from pipecat.serializers.TwilioFrameSerializer import TwilioFrameSerializer
from pipecat.serializers.twilio import TwilioFrameSerializer
from pipecat.frames.frames import AudioRawFrame, StartFrame
from pipecat.processors.frame_processor import FrameProcessor
from pipecat.serializers.base_serializer import FrameSerializer
@@ -16,6 +22,15 @@ from pipecat.transports.base_transport import BaseTransport, TransportParams
from loguru import logger
try:
from fastapi import WebSocket
from starlette.websockets import WebSocketState
except ModuleNotFoundError as e:
logger.error(f"Exception: {e}")
logger.error(
"In order to use FastAPI websockets, you need to `pip install pipecat-ai[websocket]`.")
raise Exception(f"Missing module: {e}")
class FastAPIWebsocketParams(TransportParams):
add_wav_header: bool = False
@@ -30,7 +45,12 @@ class FastAPIWebsocketCallbacks(BaseModel):
class FastAPIWebsocketInputTransport(BaseInputTransport):
def __init__(self, websocket: WebSocket, params: FastAPIWebsocketParams, callbacks: FastAPIWebsocketCallbacks, **kwargs):
def __init__(
self,
websocket: WebSocket,
params: FastAPIWebsocketParams,
callbacks: FastAPIWebsocketCallbacks,
**kwargs):
super().__init__(params, **kwargs)
self._websocket = websocket
@@ -43,7 +63,8 @@ class FastAPIWebsocketInputTransport(BaseInputTransport):
self._receive_task = self.get_event_loop().create_task(self._receive_messages())
async def stop(self):
await self._websocket.close()
if self._websocket.client_state != WebSocketState.DISCONNECTED:
await self._websocket.close()
await super().stop()
async def _receive_messages(self):
@@ -58,6 +79,7 @@ class FastAPIWebsocketInputTransport(BaseInputTransport):
await self._callbacks.on_client_disconnected(self._websocket)
class FastAPIWebsocketOutputTransport(BaseOutputTransport):
def __init__(self, websocket: WebSocket, params: FastAPIWebsocketParams, **kwargs):
@@ -92,17 +114,23 @@ class FastAPIWebsocketOutputTransport(BaseOutputTransport):
frame = wav_frame
payload = self._params.serializer.serialize(frame)
future = asyncio.run_coroutine_threadsafe(
self._websocket.send_json(payload), self.get_event_loop())
future.result()
if payload:
future = asyncio.run_coroutine_threadsafe(
self._websocket.send_text(payload), self.get_event_loop())
future.result()
self._audio_buffer = self._audio_buffer[self._params.audio_frame_size:]
class FastAPIWebsocketTransport(BaseTransport):
def __init__(self, websocket: WebSocket, params: FastAPIWebsocketParams = FastAPIWebsocketParams(), input_name: str | None = None, output_name: str | None = None, loop: asyncio.AbstractEventLoop | None = None):
def __init__(
self,
websocket: WebSocket,
params: FastAPIWebsocketParams = FastAPIWebsocketParams(),
input_name: str | None = None,
output_name: str | None = None,
loop: asyncio.AbstractEventLoop | None = None):
super().__init__(input_name=input_name, output_name=output_name, loop=loop)
self._params = params
@@ -111,8 +139,10 @@ class FastAPIWebsocketTransport(BaseTransport):
on_client_disconnected=self._on_client_disconnected
)
self._input = FastAPIWebsocketInputTransport(websocket, self._params, self._callbacks, name=self._input_name)
self._output = FastAPIWebsocketOutputTransport(websocket, self._params, name=self._output_name)
self._input = FastAPIWebsocketInputTransport(
websocket, self._params, self._callbacks, name=self._input_name)
self._output = FastAPIWebsocketOutputTransport(
websocket, self._params, name=self._output_name)
# Register supported handlers. The user will only be able to register
# these handlers.

9
src/pipecat/transports/network/websocket_server.py
View File

@@ -4,11 +4,9 @@
# SPDX-License-Identifier: BSD 2-Clause License
#
import asyncio
import io
import wave
import websockets
from typing import Awaitable, Callable
from pydantic.main import BaseModel
@@ -23,6 +21,13 @@ from pipecat.transports.base_transport import BaseTransport, TransportParams
from loguru import logger
try:
import websockets
except ModuleNotFoundError as e:
logger.error(f"Exception: {e}")
logger.error("In order to use websockets, you need to `pip install pipecat-ai[websocket]`.")
raise Exception(f"Missing module: {e}")
class WebsocketServerParams(TransportParams):
add_wav_header: bool = False

4
src/pipecat/utils/audio.py
View File

@@ -33,6 +33,7 @@ def calculate_audio_volume(audio: bytes, sample_rate: int) -> float:
def exp_smoothing(value: float, prev_value: float, factor: float) -> float:
return prev_value + factor * (value - prev_value)
def ulaw_8000_to_pcm_16000(ulaw_8000_bytes):
# Convert μ-law to PCM
pcm_8000_bytes = audioop.ulaw2lin(ulaw_8000_bytes, 2)
@@ -42,6 +43,7 @@ def ulaw_8000_to_pcm_16000(ulaw_8000_bytes):
return pcm_16000_bytes
def pcm_16000_to_ulaw_8000(pcm_16000_bytes):
# Resample from 16000 Hz to 8000 Hz
pcm_8000_bytes = audioop.ratecv(pcm_16000_bytes, 2, 1, 16000, 8000, None)[0]
@@ -49,4 +51,4 @@ def pcm_16000_to_ulaw_8000(pcm_16000_bytes):
# Convert PCM to μ-law
ulaw_8000_bytes = audioop.lin2ulaw(pcm_8000_bytes, 2)
return ulaw_8000_bytes
return ulaw_8000_bytes