Update Magic AI Storybook for Bookworm and new OpenAI API
This commit is contained in:
Melissa LeBlanc-Williams
parent
5047c10377
commit
c354179e0c
3 changed files with 28 additions and 54 deletions
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@ -2,15 +2,13 @@
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#
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# SPDX-License-Identifier: MIT
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from queue import Queue
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import time
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import speech_recognition as sr
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class Listener:
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def __init__(
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self, api_key, energy_threshold=300, phrase_timeout=3.0, record_timeout=30
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self, api_key, energy_threshold=300, record_timeout=30
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):
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self.listener_handle = None
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self.microphone = sr.Microphone()
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@ -18,62 +16,31 @@ class Listener:
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self.recognizer.energy_threshold = energy_threshold
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self.recognizer.dynamic_energy_threshold = False
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self.recognizer.pause_threshold = 1
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self.last_sample = bytes()
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self.phrase_time = time.monotonic()
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self.phrase_timeout = phrase_timeout
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with self.microphone as source:
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self.recognizer.adjust_for_ambient_noise(
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source
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) # we only need to calibrate once, before we start listening
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self.record_timeout = record_timeout
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self.phrase_complete = False
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self.data_queue = Queue()
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self._audio = None
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self.listener_handle = None
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self.api_key = api_key
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def listen(self, ready_callback=None):
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print("Start listening...")
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self.phrase_complete = False
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start = time.monotonic()
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self._start_listening()
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if ready_callback:
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ready_callback()
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while (
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self.listener_handle and not self.speech_waiting()
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) or not self.phrase_complete:
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if self.phrase_time and time.monotonic() > start + self.phrase_timeout:
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self.last_sample = bytes()
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self.phrase_complete = True
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self.phrase_time = time.monotonic() - start
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):
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time.sleep(0.1)
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self.stop_listening()
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def _save_audio_callback(self, _, audio):
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print("Saving audio")
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data = audio.get_raw_data()
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self.data_queue.put(data)
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def _get_audio(self):
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"""Concatenate and convert the queued raw data back to audio and return it"""
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start = time.monotonic()
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if self.speech_waiting():
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self.phrase_complete = False
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if self.phrase_time and time.monotonic() > start + self.phrase_timeout:
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self.last_sample = bytes()
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self.phrase_complete = True
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self.phrase_time = time.monotonic() - start
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# Concatenate our current audio data with the latest audio data.
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while self.speech_waiting():
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data = self.data_queue.get()
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self.last_sample += data
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# Use AudioData to convert the raw data to wav data.
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return sr.AudioData(
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self.last_sample,
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self.microphone.SAMPLE_RATE,
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self.microphone.SAMPLE_WIDTH,
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)
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return None
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self._audio = audio
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def _start_listening(self):
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if not self.listener_handle:
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@ -93,20 +60,19 @@ class Listener:
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return self.listener_handle is not None
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def speech_waiting(self):
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return not self.data_queue.empty()
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return self._audio is not None
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def recognize(self):
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audio = self._get_audio()
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if audio:
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if self._audio:
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# Transcribe the audio data to text using Whisper
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print("Recognizing...")
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attempts = 0
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while attempts < 3:
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try:
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result = self.recognizer.recognize_whisper_api(
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audio, api_key=self.api_key
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self._audio, api_key=self.api_key
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)
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self._audio = None
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return result.strip()
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except sr.RequestError as e:
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print(f"Error: {e}")
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@ -28,6 +28,7 @@ def main():
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APP_PATH = "~/Magic_AI_Storybook/story.py"
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APP_ICON = "~/Magic_AI_Storybook/images/magic_book_icon.png"
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FILENAME = "storybook.desktop"
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ENV_PATH = "~/story"
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AUTO_START = True
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if os.geteuid() == 0:
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@ -41,12 +42,16 @@ def main():
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APP_PATH = APP_PATH.replace("~", user_homedir)
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APP_ICON = APP_ICON.replace("~", user_homedir)
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PYTHON_PATH = "python"
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if ENV_PATH is not None:
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ENV_PATH = ENV_PATH.replace("~", user_homedir)
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PYTHON_PATH = ENV_PATH + "/bin/" + PYTHON_PATH
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shortcut_template = f"""[Desktop Entry]
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Comment=Run {APP_TITLE}
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Terminal={"true" if RUN_IN_TERMINAL else "false"}
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Name={APP_TITLE}
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Exec=sudo python {APP_PATH}
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Exec=sudo -E env PATH=$PATH {PYTHON_PATH} {APP_PATH}
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Type=Application
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Icon={APP_ICON}
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"""
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@ -16,7 +16,7 @@ from collections import deque
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import board
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import digitalio
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import neopixel
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import openai
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from openai import OpenAI
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import pygame
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from rpi_backlight import Backlight
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from adafruit_led_animation.animation.pulse import Pulse
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@ -87,12 +87,11 @@ PARAGRAPH_SPACING = 30
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# ChatGPT Parameters
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SYSTEM_ROLE = "You are a master AI Storyteller that can tell a story of any length."
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CHATGPT_MODEL = "gpt-3.5-turbo"
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CHATGPT_MODEL = "gpt-3.5-turbo" # You can also use "gpt-4", which is slower, but more accurate
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WHISPER_MODEL = "whisper-1"
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# Speech Recognition Parameters
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ENERGY_THRESHOLD = 300 # Energy level for mic to detect
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PHRASE_TIMEOUT = 1.0 # Space between recordings for separating phrases
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RECORD_TIMEOUT = 30 # Maximum time in seconds to wait for speech
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# Do some checks and Import API keys from API_KEYS_FILE
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@ -118,7 +117,10 @@ if "OPENAI_API_KEY" not in config["openai"]:
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if len(config["openai"]["OPENAI_API_KEY"]) < 10:
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print("Please set OPENAI_API_KEY in your API keys file with a valid key.")
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sys.exit(1)
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openai.api_key = config["openai"]["OPENAI_API_KEY"]
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openai = OpenAI(
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# This is the default and can be omitted
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api_key=config["openai"]["OPENAI_API_KEY"],
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)
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# Check that the prompt file exists and load it
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if not os.path.isfile(PROMPT_FILE):
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@ -250,7 +252,7 @@ class Book:
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# Initialize the Listener
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self.listener = Listener(
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openai.api_key, ENERGY_THRESHOLD, PHRASE_TIMEOUT, RECORD_TIMEOUT
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openai.api_key, ENERGY_THRESHOLD, RECORD_TIMEOUT
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)
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# Preload remaining images
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@ -728,8 +730,9 @@ class Book:
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def _sendchat(self, prompt):
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response = ""
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print("Sending to chatGPT")
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print("Prompt: ", prompt)
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# Package up the text to send to ChatGPT
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completion = openai.ChatCompletion.create(
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stream = openai.chat.completions.create(
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model=CHATGPT_MODEL,
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messages=[
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{"role": "system", "content": SYSTEM_ROLE},
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@ -738,9 +741,9 @@ class Book:
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stream=True,
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)
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for chunk in completion:
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if "delta" in chunk.choices[0] and "content" in chunk.choices[0]["delta"]:
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response += chunk.choices[0]["delta"]["content"]
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for chunk in stream:
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if chunk.choices[0].delta.content is not None:
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response += chunk.choices[0].delta.content
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if self._sleep_request:
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return None
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