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Matt Flax 2025-05-14 05:14:33 +00:00 committed by GitHub
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@ -9,6 +9,7 @@ import streamlit as st
from aider import urls from aider import urls
from aider.coders import Coder from aider.coders import Coder
from aider.dump import dump # noqa: F401 from aider.dump import dump # noqa: F401
from aider.gui_speech_to_text import SpeechToText
from aider.io import InputOutput from aider.io import InputOutput
from aider.main import main as cli_main from aider.main import main as cli_main
from aider.scrape import Scraper, has_playwright from aider.scrape import Scraper, has_playwright
@ -153,6 +154,7 @@ class GUI:
# self.do_recommended_actions() # self.do_recommended_actions()
self.do_add_to_chat() self.do_add_to_chat()
self.do_speech_to_text()
self.do_recent_msgs() self.do_recent_msgs()
self.do_clear_chat_history() self.do_clear_chat_history()
# st.container(height=150, border=False) # st.container(height=150, border=False)
@ -211,6 +213,14 @@ class GUI:
with st.popover("Add a web page to the chat"): with st.popover("Add a web page to the chat"):
self.do_web() self.do_web()
def do_speech_to_text(self):
# Initialize the speech-to-text component if not already done
if not hasattr(self, "speech_to_text"):
self.speech_to_text = SpeechToText()
# Render the speech-to-text component
self.speech_to_text.render()
def do_add_image(self): def do_add_image(self):
with st.popover("Add image"): with st.popover("Add image"):
st.markdown("Hello World 👋") st.markdown("Hello World 👋")

196
aider/gui_speech_to_text.js Normal file
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@ -0,0 +1,196 @@
(function() {
// Generate a unique ID for this component instance
const compId = 'st-speech-to-text-' + Math.random().toString(36).substring(2, 9);
// Find the container element
const container = document.getElementById('speech-to-text-container');
if (!container) {
console.error('Could not find speech-to-text-container');
return;
}
// Style the container
container.style.display = 'flex';
container.style.alignItems = 'center';
container.style.padding = '5px';
container.style.justifyContent = 'space-between';
// Create LED indicator
const led = document.createElement('div');
led.id = 'led-' + compId;
led.style.width = '12px';
led.style.height = '12px';
led.style.borderRadius = '50%';
led.style.backgroundColor = 'gray';
led.style.marginRight = '10px';
// Create button
const button = document.createElement('button');
button.id = 'button-' + compId;
button.textContent = 'Voice Input';
button.style.padding = '4px 8px';
// Create stop button (initially hidden)
const stopButton = document.createElement('button');
stopButton.id = 'stop-button-' + compId;
stopButton.textContent = 'Stop';
stopButton.style.padding = '4px 8px';
stopButton.style.marginLeft = '5px';
stopButton.style.display = 'none';
// Create checkbox and label container
const checkContainer = document.createElement('div');
checkContainer.style.display = 'flex';
checkContainer.style.alignItems = 'center';
checkContainer.style.marginLeft = '10px';
// Create auto-transcribe checkbox
const autoTranscribe = document.createElement('input');
autoTranscribe.id = 'auto-transcribe-' + compId;
autoTranscribe.type = 'checkbox';
autoTranscribe.style.marginRight = '5px';
// Create label for checkbox
const label = document.createElement('label');
label.htmlFor = autoTranscribe.id;
label.textContent = 'Auto Transcribe';
label.style.fontSize = '14px';
label.style.color = 'white';
// Assemble components
checkContainer.appendChild(autoTranscribe);
checkContainer.appendChild(label);
// Add elements to container
container.appendChild(led);
container.appendChild(button);
container.appendChild(stopButton);
container.appendChild(checkContainer);
// Check if browser supports the Web Speech API
if (!('webkitSpeechRecognition' in window) && !('SpeechRecognition' in window)) {
button.disabled = true;
button.textContent = 'Not supported';
return;
}
// Function to populate the chat input
function populateChatInput(text) {
const parentDoc = window.parent.document;
let chatInput = parentDoc.querySelector('textarea[data-testid="stChatInputTextArea"]');
const reactProps = Object.keys(chatInput).find(key => key.startsWith('__reactProps$'));
const syntheticEvent = { target: chatInput, currentTarget: chatInput,
preventDefault: () => {}, nativeEvent: new Event('input', { bubbles: true })};
if (!chatInput || !reactProps) {
if (!chatInput)
console.error("Could not find chat input textarea");
if (!reactProps)
console.error("Error setting chat input value:", err);
return false;
}
// Append to the existing value
chatInput.value = chatInput.value + ' ' + text;
// Call React's onChange handler
chatInput[reactProps].onChange(syntheticEvent);
return true;
}
// Initialize speech recognition
const SpeechRecognition = window.SpeechRecognition || window.webkitSpeechRecognition;
const recognition = new SpeechRecognition();
let isListening = false;
recognition.continuous = false;
recognition.interimResults = false;
// Use browser's language or fall back to 'en-US'
recognition.lang = navigator.language || 'en-US';
console.log('Speech recognition language:', recognition.lang);
// Setup button click handler
button.addEventListener('click', function() {
if (isListening) return;
isListening = true;
// Set initial LED color based on auto-transcribe mode
if (autoTranscribe.checked) {
led.style.backgroundColor = 'red'; // Red when waiting for voice
stopButton.style.display = 'inline-block';
recognition.continuous = true;
} else {
led.style.backgroundColor = 'lime';
}
recognition.start();
});
// Setup stop button click handler
stopButton.addEventListener('click', function() {
if (isListening) {
recognition.stop();
stopButton.style.display = 'none';
isListening = false;
}
});
// Handle speech detection
recognition.onspeechstart = function() {
console.log('Speech detected');
if (autoTranscribe.checked) {
led.style.backgroundColor = 'lime'; // Lime green when voice is detected
}
};
// Handle speech end
recognition.onspeechend = function() {
console.log('Speech ended');
if (autoTranscribe.checked && isListening) {
led.style.backgroundColor = 'red'; // Red when waiting for voice
}
};
// Combined event handler function for speech recognition events
function handleSpeechEvent(eventType, event) {
if (eventType === 'result') {
// Get the latest transcript
const resultIndex = event.resultIndex;
const transcript = event.results[resultIndex][0].transcript;
// Try to populate the chat input directly
const success = populateChatInput(transcript);
if (!success)
console.error('populateChatInput failed');
// If not in auto-transcribe mode, reset the LED
if (!autoTranscribe.checked) {
led.style.backgroundColor = 'gray';
}
// In auto-transcribe mode, we'll keep the LED color as is (lime while speaking)
// The LED will be set back to red in the speechend event
}
else if (eventType === 'error') {
console.error('Speech recognition error', event.error);
isListening = false;
stopButton.style.display = 'none';
led.style.backgroundColor = 'gray';
}
else if (eventType === 'end') {
// If auto transcribe is enabled and we're still supposed to be listening,
// restart recognition
if (autoTranscribe.checked && isListening) {
setTimeout(() => recognition.start(), 100);
} else {
isListening = false;
stopButton.style.display = 'none';
led.style.backgroundColor = 'gray';
}
}
}
// Set up event handlers using the combined function
recognition.onresult = function(event) { handleSpeechEvent('result', event); };
recognition.onerror = function(event) { handleSpeechEvent('error', event); };
recognition.onend = function() { handleSpeechEvent('end'); };
})();

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@ -0,0 +1,37 @@
import base64
import os
import streamlit as st
import streamlit.components.v1 as components
class SpeechToText:
"""Class to handle speech-to-text functionality in the GUI"""
def render(self):
"""Render the speech-to-text component with LED indicator"""
self._js_dir = os.path.dirname(__file__)
# Create JS file path
js_path = os.path.join(self._js_dir, "gui_speech_to_text.js")
if not os.path.exists(js_path):
st.error(f"JavaScript file not found: {js_path}")
return
# Read the JS file for data URL
with open(js_path, "r") as f:
js_content = f.read()
# Create data URL for the JS file
js_b64 = base64.b64encode(js_content.encode("utf-8")).decode("utf-8")
js_data_url = f"data:text/javascript;base64,{js_b64}"
# Create simple HTML component with a container for the JS to populate
components.html(
f"""
<div id="speech-to-text-container"></div>
<!-- Load JS file via data URL since direct src paths don't work in Streamlit iframe -->
<script src="{js_data_url}"></script>
""",
height=50,
)