v2.1

Author: BBC-Esq

config.yaml

@@ -29,7 +29,13 @@ AVAILABLE_MODELS:
 - sentence-transformers/gtr-t5-large
 - sentence-transformers/gtr-t5-base
 COMPUTE_DEVICE: cuda
-EMBEDDING_MODEL_NAME: C:/PATH/Scripts/LM Search Vector Database/v1_7 - working/Embedding_Models/sentence-transformers--all-mpnet-base-v2
+EMBEDDING_MODEL_NAME: C:/PATH/Scripts/LM Search Vector Database/v2_0_1 - working/Embedding_Models/hkunlp--instructor-xl
+styles:
+  button: 'background-color: #323842; color: light gray; font: 10pt "Segoe UI Historic";
+    width: 29;'
+  frame: 'background-color: #161b22;'
+  input: 'background-color: #2e333b; color: light gray; font: 13pt "Segoe UI Historic";'
+  text: 'background-color: #092327; color: light gray; font: 12pt "Segoe UI Historic";'
 tabs:
 - name: Settings
   placeholder: Placeholder text for Settings tab.

gui.py

@@ -14,33 +14,15 @@
 from metrics_gpu import GPU_Monitor
 from metrics_system import SystemMonitor
 from initialize import determine_compute_device, is_nvidia_gpu, get_os_name
-
-styles = {
-    "button": 'background-color: #323842; color: light gray; font: 10pt "Segoe UI Historic"; width: 29;',
-    "frame": 'background-color: #161b22;',
-    "input": 'background-color: #2e333b; color: light gray; font: 13pt "Segoe UI Historic";',
-    "text": 'background-color: #092327; color: light gray; font: 12pt "Segoe UI Historic";'
-}
+from voice_recorder_module import VoiceRecorder
+from gui_tabs import create_tabs
+from gui_threads import CreateDatabaseThread, SubmitButtonThread
 
 with open('config.yaml', 'r') as config_file:
     config = yaml.safe_load(config_file)
 
 tabs_config = config.get('tabs', [])
-
-class CreateDatabaseThread(QThread):
-    def run(self):
-        create_database.main()
-
-class SubmitButtonThread(QThread):
-    responseSignal = Signal(str)
-
-    def __init__(self, user_question, parent=None):
-        super(SubmitButtonThread, self).__init__(parent)
-        self.user_question = user_question
-
-    def run(self):
-        response = server_connector.ask_local_chatgpt(self.user_question)
-        self.responseSignal.emit(response['answer'])
+styles = config.get('styles', {})
 
 class DocQA_GUI(QWidget):
     def __init__(self):
@@ -64,20 +46,10 @@ def init_ui(self):
         self.setGeometry(300, 300, 850, 910)
         self.setMinimumSize(550, 610)
 
-        self.left_frame = QFrame()  # Changed here
+        self.left_frame = QFrame()
         left_vbox = QVBoxLayout()
-        tab_widget = QTabWidget()
-        tab_widget.setTabPosition(QTabWidget.South)
-
-        tab_widgets = [QTextEdit(tab.get('placeholder', '')) for tab in tabs_config]
-        for i, tab in enumerate(tabs_config):
-            tab_widget.addTab(tab_widgets[i], tab.get('name', ''))
-
-        tutorial_tab = QWebEngineView()
-        tab_widget.addTab(tutorial_tab, 'Tutorial')
-        user_manual_folder = os.path.join(os.path.dirname(__file__), 'User_Manual')
-        html_file_path = os.path.join(user_manual_folder, 'number_format.html')
-        tutorial_tab.setUrl(QUrl.fromLocalFile(html_file_path))
+
+        tab_widget = create_tabs(tabs_config)
         left_vbox.addWidget(tab_widget)
 
         button_data = [
@@ -108,9 +80,21 @@ def init_ui(self):
         submit_button.setStyleSheet(styles.get('button', ''))
         submit_button.clicked.connect(self.on_submit_button_clicked)
 
-        right_vbox.addWidget(self.read_only_text, 5)
+        right_vbox.addWidget(self.read_only_text, 4)
         right_vbox.addWidget(self.text_input, 1)
         right_vbox.addWidget(submit_button)
+        
+        self.recorder = VoiceRecorder()
+
+        self.start_button = QPushButton("Start Recording")
+        self.start_button.setStyleSheet(styles.get('button', ''))
+        self.start_button.clicked.connect(self.start_recording)
+        right_vbox.addWidget(self.start_button)
+
+        self.stop_button = QPushButton("Stop Recording")
+        self.stop_button.setStyleSheet(styles.get('button', ''))
+        self.stop_button.clicked.connect(self.stop_recording)
+        right_vbox.addWidget(self.stop_button)
 
         right_frame.setLayout(right_vbox)
         right_frame.setStyleSheet(styles.get('frame', ''))
@@ -140,7 +124,6 @@ def resizeEvent(self, event):
         self.left_frame.setMaximumWidth(self.width() * 0.5)
         super().resizeEvent(event)
 
-
     def on_create_button_clicked(self):
         self.create_database_thread = CreateDatabaseThread(self)
         self.create_database_thread.start()
@@ -151,6 +134,12 @@ def on_submit_button_clicked(self):
         self.submit_button_thread.responseSignal.connect(self.update_response)
         self.submit_button_thread.start()
 
+    def start_recording(self):
+        self.recorder.start_recording()
+
+    def stop_recording(self):
+        self.recorder.stop_recording()
+
     def update_response(self, response):
         self.read_only_text.setPlainText(response)
 

gui_tabs.py

@@ -0,0 +1,22 @@
+# tabs.py
+
+from PySide6.QtWebEngineWidgets import QWebEngineView
+from PySide6.QtWidgets import QTextEdit, QTabWidget
+from PySide6.QtCore import QUrl
+import os
+
+def create_tabs(tabs_config):
+    tab_widget = QTabWidget()
+    tab_widget.setTabPosition(QTabWidget.South)
+
+    tab_widgets = [QTextEdit(tab.get('placeholder', '')) for tab in tabs_config]
+    for i, tab in enumerate(tabs_config):
+        tab_widget.addTab(tab_widgets[i], tab.get('name', ''))
+
+    tutorial_tab = QWebEngineView()
+    tab_widget.addTab(tutorial_tab, 'Tutorial')
+    user_manual_folder = os.path.join(os.path.dirname(__file__), 'User_Manual')
+    html_file_path = os.path.join(user_manual_folder, 'number_format.html')
+    tutorial_tab.setUrl(QUrl.fromLocalFile(html_file_path))
+
+    return tab_widget

gui_threads.py

@@ -0,0 +1,20 @@
+# Creates threads for gui functions
+
+from PySide6.QtCore import QThread, Signal
+import server_connector
+import create_database
+
+class CreateDatabaseThread(QThread):
+    def run(self):
+        create_database.main()
+
+class SubmitButtonThread(QThread):
+    responseSignal = Signal(str)
+
+    def __init__(self, user_question, parent=None):
+        super(SubmitButtonThread, self).__init__(parent)
+        self.user_question = user_question
+
+    def run(self):
+        response = server_connector.ask_local_chatgpt(self.user_question)
+        self.responseSignal.emit(response['answer'])

initialize.py

@@ -1,3 +1,5 @@
+# determine OS compute device for gui and save to config and determine whether to display metrics
+
 import torch
 import yaml
 import platform

main.py

@@ -0,0 +1,78 @@
+import sys
+import pyaudio
+import wave
+import os
+import tempfile
+import threading
+import pyperclip
+from faster_whisper import WhisperModel
+from PySide6.QtWidgets import QApplication, QWidget, QVBoxLayout, QPushButton, QLabel
+from PySide6.QtCore import Qt
+
+class VoiceRecorder:
+    def __init__(self, window, format=pyaudio.paInt16, channels=1, rate=44100, chunk=1024):
+        self.format, self.channels, self.rate, self.chunk = format, channels, rate, chunk
+        self.window = window
+        self.is_recording, self.frames = False, []
+        self.model = WhisperModel("large-v2", device="cuda", compute_type="int8_float32")
+
+    def transcribe_audio(self, audio_file):
+        segments, _ = self.model.transcribe(audio_file)
+        pyperclip.copy("\n".join([segment.text for segment in segments]))
+        self.window.update_status("Audio saved and transcribed")
+
+    def record_audio(self):
+        self.window.update_status("Recording...")
+        p = pyaudio.PyAudio()
+        try:
+            stream = p.open(format=self.format, channels=self.channels, rate=self.rate, input=True, frames_per_buffer=self.chunk)
+            [self.frames.append(stream.read(self.chunk)) for _ in iter(lambda: self.is_recording, False)]
+            stream.stop_stream()
+            stream.close()
+        finally:
+            p.terminate()
+
+    def save_audio(self):
+        self.is_recording = False
+        temp_filename = tempfile.mktemp(suffix=".wav")
+        with wave.open(temp_filename, "wb") as wf:
+            wf.setnchannels(self.channels)
+            wf.setsampwidth(pyaudio.PyAudio().get_sample_size(self.format))
+            wf.setframerate(self.rate)
+            wf.writeframes(b"".join(self.frames))
+        self.transcribe_audio(temp_filename)
+        os.remove(temp_filename)
+        self.frames.clear()
+
+    def start_recording(self):
+        if not self.is_recording:
+            self.is_recording = True
+            threading.Thread(target=self.record_audio).start()
+
+class MyWindow(QWidget):
+    def __init__(self):
+        super().__init__()
+        self.recorder = VoiceRecorder(self)
+        layout = QVBoxLayout(self)
+
+        for text, callback in [("Record", self.recorder.start_recording), 
+                               ("Stop and Copy to Clipboard", self.recorder.save_audio)]:
+            button = QPushButton(text, self)
+            button.clicked.connect(callback)
+            layout.addWidget(button)
+
+        self.status_label = QLabel('', self)
+        layout.addWidget(self.status_label)
+        self.setFixedSize(300, 150)
+        
+        self.setWindowFlag(Qt.WindowStaysOnTopHint)
+
+    def update_status(self, text):
+        self.status_label.setText(text)
+
+if __name__ == "__main__":
+    app = QApplication(sys.argv)
+    app.setStyle('Fusion')
+    window = MyWindow()
+    window.show()
+    sys.exit(app.exec())

metrics_gpu.py

@@ -2,6 +2,7 @@
 from multiprocessing import Process, Pipe, Event
 import time
 from PySide6.QtCore import QTimer
+import humanize
 
 def monitor_nvml(pipe, stop_event):
     nvmlInit()
@@ -11,7 +12,7 @@ def monitor_nvml(pipe, stop_event):
         memory_info = nvmlDeviceGetMemoryInfo(handle)
         utilization_rates = nvmlDeviceGetUtilizationRates(handle)
 
-        memory_used_str = f"{memory_info.used / (1024 * 1024):.2f} MiB"
+        memory_used_str = humanize.naturalsize(memory_info.used, binary=True)
         gpu_utilization = f"{utilization_rates.gpu}%"
 
         data = (memory_used_str, gpu_utilization)
@@ -51,4 +52,4 @@ def update_gpu_info(self):
     def stop_and_exit_gpu_monitor(self):
         self.timer.stop()
         stop_monitoring_gpu(self.process, self.stop_event)
-        self.root.close()
+        self.root.close()

metrics_system.py

@@ -2,12 +2,13 @@
 import time
 from multiprocessing import Process, Pipe, Event
 from PySide6.QtCore import QTimer
+import humanize
 
 def monitor_system(pipe, stop_event):
     while not stop_event.is_set():
         cpu_percent = collect_cpu_metrics()
-        ram_percent, ram_used_mib = collect_ram_metrics()
-        data = (cpu_percent, ram_percent, ram_used_mib)
+        ram_percent, ram_used = collect_ram_metrics()
+        data = (cpu_percent, ram_percent, ram_used)
         pipe.send(data)
         time.sleep(0.5)
 
@@ -17,8 +18,8 @@ def collect_cpu_metrics():
 
 def collect_ram_metrics():
     ram = psutil.virtual_memory()
-    ram_used_mib = round(ram.used / (1024 ** 2), 2)
-    return round(ram.percent, 2), ram_used_mib
+    ram_used = humanize.naturalsize(ram.used, binary=True)
+    return round(ram.percent, 2), ram_used
 
 def start_monitoring_system():
     stop_event = Event()
@@ -44,12 +45,12 @@ def __init__(self, cpu_label, ram_label, ram_usage_label, root):
 
     def update_system_info(self):
         if self.parent_conn.poll():
-            cpu_percent, ram_percent, ram_used_mib = self.parent_conn.recv()
+            cpu_percent, ram_percent, ram_used = self.parent_conn.recv()
             self.cpu_label.setText(f"CPU: {cpu_percent}%")
             self.ram_label.setText(f"RAM: {ram_percent}%")
-            self.ram_usage_label.setText(f"RAM: {ram_used_mib:.2f} MiB")
+            self.ram_usage_label.setText(f"RAM: {ram_used}")
 
     def stop_and_exit_system_monitor(self):
         self.timer.stop()
         stop_monitoring_system(self.process, self.stop_event)
-        self.root.close()
+        self.root.close()

requirements.txt

@@ -13,4 +13,8 @@ openpyxl==3.1.2
 unstructured==0.10.12
 nvidia-ml-py==12.535.108
 psutil==5.9.5
-PySide6==6.5.2
+PySide6==6.5.2
+Humanize==4.8.0
+PyAudio==0.2.13
+pyperclip==1.8.2
+faster-whisper==0.9.0

server_connector.py

@@ -63,7 +63,7 @@ def ask_local_chatgpt(query, persist_directory=PERSIST_DIRECTORY, client_setting
     retriever = db.as_retriever()
     relevant_contexts = retriever.get_relevant_documents(query)
     contexts = [document.page_content for document in relevant_contexts]
-    prepend_string = "Only base your answer to the following question on the provided context.  If the provided context does not provide an answer, simply state that is the case."
+    prepend_string = "Only base your answer to the following question on the provided context."
     augmented_query = "\n\n---\n\n".join(contexts) + "\n\n-----\n\n" + query
     response_json = connect_to_local_chatgpt(augmented_query)