how do i add wisper ai to my own python ai project
#making ai
earnest knoll
limpid valleyBOT
Hi @earnest knoll. I'm kapa.ai, your friendly support bot. I will try to answer your question by searching through the knowledge base. :wave:
To add Whisper AI to your Python project, you need to install the Whisper package and then import it into your Python script. Here's how you can do it:
- Install the Whisper package using pip. You can do this by running the following command in your terminal:
!pip install git+<https://github.com/openai/whisper.git>
(Source: Openai > Whisper > Blob > Main > Notebooks > Installing Whisper (https://github.com/openai/whisper/blob/main/notebooks/LibriSpeech.ipynb))
- Once installed, you can import the Whisper package into your Python script. Here's an example of how to do this:
import whisper
(Source: Openai > Whisper > Blob > Main > Notebooks > Installing Whisper (https://github.com/openai/whisper/blob/main/notebooks/Multilingual_ASR.ipynb))
- To use the Whisper model for transcribing audio, you can load the model and then use the
transcribemethod. Here's an example:
# Load the model
model = whisper.load_model("base")
# Transcribe an audio file
transcription = model.transcribe("your_audio_file.mp3")
(Source: Whisper > using the large model within python > Official answer (https://github.com/openai/whisper/discussions/1354))
Please replace "your_audio_file.mp3" with the path to your actual audio file.
Remember to handle any potential errors and edge cases according to your project's requirements.
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
earnest knoll
@limpid valley how do i make it handle realtime audio input
limpid valleyBOT
Let me check the knowledge base for you. One moment! :books:
Real-time audio input handling is a complex task and requires a streaming approach. While the OpenAI Speech API does provide support for real-time audio streaming using chunk transfer encoding, it seems that the Whisper API does not currently support real-time audio streaming as per the information available in the extracts.
Here's an example of how to use the Speech API for real-time audio streaming:
from openai import OpenAI
client = OpenAI()
response = client.audio.speech.create(
model="tts-1",
voice="alloy",
input="Hello world! This is a streaming test.",
)
response.stream_to_file("output.mp3")
(Source: Docs > Guides > Text to speech > Streaming real time audio (https://platform.openai.com/docs/guides/text-to-speech))
However, please note that this example is for the Speech API (Text-to-Speech), not the Whisper API (Speech-to-Text). The Whisper API currently does not support real-time audio streaming as per the information available in the extracts.
For the Whisper API, a user on GitHub mentioned trying to change the CHUNK_SIZE in audio.py for real-time STT with the medium model, but it resulted in an error. The official answer clarified that the model can only consume 30 seconds at once, so the CHUNK_SIZE can't increase. The model.transcribe() is designed to be used for audio files longer than 30 seconds, which works by successively transcribing audio using a 30s-long sliding window. (Source: Whisper > Can I change how many seconds the model looks at one time? (https://github.com/openai/whisper/discussions/20))
For real-time audio input handling, you might need to look into other solutions or wait for future updates from OpenAI that might add this feature to the Whisper API.
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
earnest knoll
@limpid valley i ment like when i talk to it
limpid valleyBOT
Let me check the knowledge base for you. One moment! :books:
I see, you want to interact with the AI in real-time using your voice. Unfortunately, based on the information provided in the extracts, it seems that the Whisper API currently does not support real-time audio streaming.
The Whisper API is designed to transcribe audio files, and it's not currently designed to handle real-time audio input from a microphone.
Here's an example of how you can use the Whisper API to transcribe an audio file:
# Load the model
model = whisper.load_model("base")
# Transcribe an audio file
transcription = model.transcribe("your_audio_file.mp3")
(Source: Whisper > using the large model within python > Official answer (https://github.com/openai/whisper/discussions/1354))
Please replace "your_audio_file.mp3" with the path to your actual audio file.
For real-time audio input handling, you might need to look into other solutions or wait for future updates from OpenAI that might add this feature to the Whisper API.
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
earnest knoll
@limpid valley wait could we use a python file to capture what i say and then we feed it through whispe
limpid valleyBOT
Let me check the knowledge base for you. One moment! :books:
Yes, you can use Python libraries like sounddevice or pyaudio to record audio from your microphone in real-time, save it as a file, and then feed it to the Whisper model for transcription. Here's a basic example of how you might do this:
First, install the necessary libraries. You can do this by running the following commands in your terminal:
!pip install sounddevice scipy
!pip install git+<https://github.com/openai/whisper.git>
Then, you can use the following code to record audio and transcribe it:
import sounddevice as sd
from scipy.io.wavfile import write
import whisper
# Record audio
fs = 44100 # Sample rate
seconds = 5 # Duration of recording
print("Start speaking...")
myrecording = sd.rec(int(seconds * fs), samplerate=fs, channels=2)
sd.wait() # Wait until recording is finished
print("Recording finished. Transcribing...")
write('output.wav', fs, myrecording) # Save as WAV file
# Load the Whisper model
model = whisper.load_model("base")
# Transcribe the audio file
transcription = model.transcribe("output.wav")
print("Transcription: ", transcription)
This script will record 5 seconds of audio from your microphone, save it as a WAV file, and then transcribe it using the Whisper model.
Please note that this is a basic example and might need to be adjusted based on your specific requirements. For example, you might want to implement a more sophisticated method for determining when to start and stop recording.
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
earnest knoll
@limpid valley ok now i need some sort of language model where it can talk to me you got one apart from openai
limpid valleyBOT
Let me check the knowledge base for you. One moment! :books:
OpenAI has developed several language models that can generate human-like text. These models can be used to create conversational AI systems that can interact with users in a natural and engaging manner.
One of the most powerful models developed by OpenAI is GPT-4. As of 2023, GPT-4 outperforms both previous large language models and most state-of-the-art systems. It demonstrates strong performance in English and other languages. (Source: OpenAI Docs > Models > GPT-4 and GPT-4 Turbo > Multilingual capabilities (https://platform.openai.com/docs/models))
Another model is GPT-3.5 Turbo, which is recommended over other GPT-3.5 models because of its lower cost and improved performance. (Source: OpenAI Docs > Models > GPT-3.5 Part 2 (https://platform.openai.com/docs/models))
OpenAI has also published open-source models like Point-E, Whisper, Jukebox, and CLIP. (Source: OpenAI Docs > Models Part 2 (https://platform.openai.com/docs/models))
If you're looking for models outside of OpenAI, there are several other options available. However, as an AI assistant for OpenAI, I'm tuned to provide information specifically about OpenAI's models and technologies. You might want to look into other AI research labs or companies for alternative language models.
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
earnest knoll
@limpid valley no i want a language model apart from open ai
limpid valleyBOT
Let me check the knowledge base for you. One moment! :books: