From e03628977167cb496806d4fdd8f3ff75f57c3a24 Mon Sep 17 00:00:00 2001
From: Danu Kim <71139863+DogeLord081@users.noreply.github.com>
Date: Sat, 24 Feb 2024 22:57:32 -0500
Subject: [PATCH] Add files via upload

---
 OneReality.bat      |    3 +-
 OneRealityMemory.py |  419 ++--
 Pipfile.lock        | 4475 +++++++++++++++++++++++++++++++++++++++++++
 setup.py            |   61 +-
 4 files changed, 4771 insertions(+), 187 deletions(-)
 create mode 100644 Pipfile.lock

diff --git a/OneReality.bat b/OneReality.bat
index 6599a37..6514a9d 100644
--- a/OneReality.bat
+++ b/OneReality.bat
@@ -1,4 +1,3 @@
 @echo off
-start cmd /k python vits-simple-api-onereality/app.py
 start cmd /k python OneRealityMemory.py
-pause
\ No newline at end of file
+exit
\ No newline at end of file
diff --git a/OneRealityMemory.py b/OneRealityMemory.py
index 40ecf6a..5035145 100644
--- a/OneRealityMemory.py
+++ b/OneRealityMemory.py
@@ -2,7 +2,6 @@
 import os
 import sounddevice as sd
 import soundfile as sf
-import openai
 import re
 import torch
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
@@ -10,24 +9,40 @@
 import string
 from AppOpener import open as start, close as end
 import json
-from hyperdb import HyperDB
-from sentence_transformers import SentenceTransformer
+from vectordb import Memory
 from dotenv import load_dotenv
 import random
 from requests_toolbelt.multipart.encoder import MultipartEncoder
 import requests
 from datetime import datetime
 import whisperx
+import pyautogui
+import time
+import subprocess
+
+subprocess.Popen("start cmd /k python vits-simple-api-onereality/app.py", shell=True)
 ###
 # Set to True if you want to use tuya
 tuya = True
 ###
 
-#Load env variables
+# Load env variables
 load_dotenv()
 
+# Language
+lang_code = os.getenv("LANGUAGE")
+
+# Initialize memory
+memory = Memory()
+
+
+with open("conversation.jsonl", "r", encoding="utf-8") as f:
+    conversation_data = [json.dumps(json.loads(line)) for line in f]
+memory.save(conversation_data)
+
 # ExLlamaV2
 import sys
+
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 
 from exllamav2 import (
@@ -37,10 +52,7 @@
     ExLlamaV2Tokenizer,
 )
 
-from exllamav2.generator import (
-    ExLlamaV2StreamingGenerator,
-    ExLlamaV2Sampler
-)
+from exllamav2.generator import ExLlamaV2StreamingGenerator, ExLlamaV2Sampler
 
 # Initialize model and cache
 
@@ -61,7 +73,7 @@
 # Initialize generator
 
 generator = ExLlamaV2StreamingGenerator(model, cache, ExLlamatokenizer)
-generator.set_stop_conditions(['"}'])
+generator.set_stop_conditions(['"}', "}", "'}"])
 
 # Settings
 
@@ -72,41 +84,30 @@
 settings.token_repetition_penalty = 1.15
 settings.disallow_tokens(ExLlamatokenizer, [ExLlamatokenizer.eos_token_id])
 
-max_new_tokens = 250
+max_new_tokens = 1000
 
 # WhisperX
 device = "cuda"
-devive_index = "1"
 audio_file = r"temp.wav"
-batch_size = 16 # reduce if low on GPU mem
-compute_type = "int8" # change to "int8" if low on GPU mem (may reduce accuracy)
-language = "en"
-model = os.getenc("WHISPERX_MODEL")
-
-whisper_model = whisperx.load_model("large-v2", device, language=language, compute_type=compute_type, asr_options={"initial_prompt": "A chat between a user and an artificial intelligence assistant named M.I.T.S.U.H.A."})
+batch_size = 12  # reduce if low on GPU mem
+compute_type = "int8"  # change to "int8" if low on GPU mem (may reduce accuracy)
+language = lang_code
+model = os.getenv("WHISPERX_MODEL")
+
+whisper_model = whisperx.load_model(
+    "medium",
+    device,
+    language=language,
+    compute_type=compute_type,
+    asr_options={
+        "initial_prompt": "A chat between a user and an artificial intelligence assistant named M.I.T.S.U.H.A."
+    },
+)
 
 # VITS api
 abs_path = os.path.dirname(__file__)
 base = "http://127.0.0.1:23456"
 
-# Load documents from the JSONL file
-documents = []
-
-with open("conversation.jsonl", "r", encoding="utf-8") as f:
-    for line in f:
-         documents.append(json.loads(line))
-
-# Instantiate HyperDB with the list of documents and the key "description"
-model = SentenceTransformer(os.getenv("SENTENCE_TRANSFORMER"))
-db = HyperDB(documents, key="info.description",
-             embedding_function=model.encode)
-
-# Save the HyperDB instance to a file
-db.save("conversation.pickle.gz")
-
-# set up OpenAI API credentials
-openai.api_key = os.getenv("OPENAI_KEY")
-
 if tuya == True:
     # set up Tuya API credentials
     ACCESS_ID = os.getenv("TUYA_ID")
@@ -120,12 +121,15 @@
 
 # set up NLI RTE transformers model
 tokenizer = AutoTokenizer.from_pretrained(os.getenv("NLI_RTE_TRANSFORMER"))
-model = AutoModelForSequenceClassification.from_pretrained(os.getenv("NLI_RTE_TRANSFORMER"))
+model = AutoModelForSequenceClassification.from_pretrained(
+    os.getenv("NLI_RTE_TRANSFORMER")
+)
 
 # set up Llama model
 lore = os.getenv("LORE")
 
-print('''
+print(
+    """
   _____              ______             _ _           
  / ___ \            (_____ \           | (_)_         
 | |   | |____   ____ _____) ) ____ ____| |_| |_ _   _ 
@@ -133,12 +137,29 @@
 | |___| | | | ( (/ /      | ( (/ ( ( | | | | |_| |_| |
  \_____/|_| |_|\____)     |_|\____)_||_|_|_|\___)__  |
                                                (____/
-        Bridging the real and virtual worlds
-              [PROJECT M.I.T.S.U.H.A.]
-''')
+"""
+)
+
+
+def typewriter_effect(text, delay=0.03):
+    for char in text:
+        print(char, end="", flush=True)
+        time.sleep(delay)
+
+
+text = """        Bridging the real and virtual worlds
+{:^50}
+""".format(
+    "[PROJECT M.I.T.S.U.H.A.]"
+)
+
+typewriter_effect(text)
+
 
 # tts function
-def voice_vits(text, id=0, format="wav", lang="auto", length=1, noise=0.667, noisew=0.8, max=50):
+def voice_vits(
+    text, id=0, format="wav", lang=lang_code, length=1, noise=0.667, noisew=0.8, max=50
+):
     fields = {
         "text": text,
         "id": str(id),
@@ -147,9 +168,11 @@ def voice_vits(text, id=0, format="wav", lang="auto", length=1, noise=0.667, noi
         "length": str(length),
         "noise": str(noise),
         "noisew": str(noisew),
-        "max": str(max)
+        "max": str(max),
     }
-    boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))
+    boundary = "----VoiceConversionFormBoundary" + "".join(
+        random.sample(string.ascii_letters + string.digits, 16)
+    )
 
     m = MultipartEncoder(fields=fields, boundary=boundary)
     headers = {"Content-Type": m.content_type}
@@ -163,6 +186,7 @@ def voice_vits(text, id=0, format="wav", lang="auto", length=1, noise=0.667, noi
     print(path)
     return path
 
+
 # define function to check if user has said "bye", "goodbye", or "see you"
 def check_goodbye(transcript):
     goodbye_words = ["bye", "goodbye", "see you"]
@@ -171,75 +195,85 @@ def check_goodbye(transcript):
             return True
     return False
 
+
 def test_entailment(text1, text2):
-    batch = tokenizer(text1, text2, return_tensors='pt').to(model.device)
+    batch = tokenizer(text1, text2, return_tensors="pt").to(model.device)
     with torch.no_grad():
         proba = torch.softmax(model(**batch).logits, -1)
-    return proba.cpu().numpy()[0, model.config.label2id['ENTAILMENT']]
+    return proba.cpu().numpy()[0, model.config.label2id["ENTAILMENT"]]
+
 
 def test_equivalence(text1, text2):
     return test_entailment(text1, text2) * test_entailment(text2, text1)
 
+
 def replace_device(sentence, word):
     return sentence.replace("[device]", word)
 
+
 def replace_app(sentence, word):
     return sentence.replace("[app]", word)
 
+
 def keep_sentence_with_word(text, word):
-    sentences = text.split('.')
-    filtered_sentences = [sentence.strip() + '.' for sentence in sentences if word in sentence]
-    result = ' '.join(filtered_sentences)
+    sentences = text.split(".")
+    filtered_sentences = [
+        sentence.strip() + "." for sentence in sentences if word in sentence
+    ]
+    result = " ".join(filtered_sentences)
     return result
 
+
 def keep_sentence_with_word(text, word):
-    sentences = re.split(r'[.,!?]', text)
-    filtered_sentences = [sentence.strip() + punct for sentence, punct in zip(sentences, re.findall(r'[.,!?]', text)) if word in sentence]
-    result = ' '.join(filtered_sentences)
+    sentences = re.split(r"[.,!?]", text)
+    filtered_sentences = [
+        sentence.strip() + punct
+        for sentence, punct in zip(sentences, re.findall(r"[.,!?]", text))
+        if word in sentence
+    ]
+    result = " ".join(filtered_sentences)
     return result
 
+
 while True:
     print("Speak now!")
-    
+
     with mic as source:
-        audio = r.listen(source, timeout = None)
-        
+        audio = r.listen(source, timeout=None)
+
     now = datetime.now()
     date = now.strftime("%m/%d/%Y")
-    time = now.strftime("%H:%M:%S")
-    
-    test_text = r.recognize_sphinx(audio)
-    if len(test_text) == 0:
+    time_2 = now.strftime("%H:%M:%S")
+
+    try:
+        test_text = r.recognize_sphinx(audio)
+        if len(test_text) == 0:
+            continue
+    except sr.UnknownValueError:
         continue
-    else:
-        pass
-    
+
     with open("temp.wav", "wb") as f:
         f.write(audio.get_wav_data())
 
     audio = whisperx.load_audio(audio_file)
     result = whisper_model.transcribe(audio, batch_size=batch_size)
-    trans = result["segments"][0]["text"]
 
-    if len(trans) == 0:
+    try:
+        trans = result["segments"][0]["text"]
+        if len(trans) == 0:
+            continue
+    except IndexError:
         continue
-    else:
-        pass
-    
+
     text = trans
-    new_line = {"role": "User", "date": date, "time": time, "content": text}
-    
+    new_line = {"role": "User", "date": date, "time": time_2, "content": text}
+
     print("You:" + text)
-    with open(r"conversation.jsonl", "a", encoding='UTF-8') as c:
+    with open(r"conversation.jsonl", "a", encoding="UTF-8") as c:
         c.write("\n" + json.dumps(new_line, ensure_ascii=False))
-        
-    documents.append(new_line)
-    db.save("conversation.pickle.gz")
 
-    devices = [
-        os.getenv("DEVICE_1"),
-        os.getenv("DEVICE_2")
-    ]
+    devices = [os.getenv("DEVICE_1"), os.getenv("DEVICE_2")]
+
     if tuya == True:
         sentence = "Activate [device]."
         input_sentence = trans.lower()
@@ -248,163 +282,218 @@ def keep_sentence_with_word(text, word):
                 modified_sentence = replace_device(sentence, word)
 
                 input_sentence = keep_sentence_with_word(input_sentence, word)
-                input_sentence = input_sentence.translate(str.maketrans('', '', string.punctuation))
-                similarity = (test_equivalence(modified_sentence, input_sentence))
+                input_sentence = input_sentence.translate(
+                    str.maketrans("", "", string.punctuation)
+                )
+                similarity = test_equivalence(modified_sentence, input_sentence)
                 if similarity >= 0.5:
                     openapi = TuyaOpenAPI(API_ENDPOINT, ACCESS_ID, ACCESS_KEY)
                     openapi.connect()
                     if word == os.getenv("DEVICE_1"):
-                        commands = {'commands': [{'code':'switch_1','value': True}]}	
+                        commands = {"commands": [{"code": "switch_1", "value": True}]}
                         openapi.post(os.getenv("DEVICE_1_ID"), commands)
                     if word == os.getenv("DEVICE_2"):
-                        commands = {'commands': [{'code':'switch_1','value': True}]}	
+                        commands = {"commands": [{"code": "switch_1", "value": True}]}
                         openapi.post(os.getenv("DEVICE_2_ID"), commands)
                 elif similarity < 0.001:
                     openapi = TuyaOpenAPI(API_ENDPOINT, ACCESS_ID, ACCESS_KEY)
                     openapi.connect()
                     if word == os.getenv("DEVICE_1"):
-                        commands = {'commands': [{'code':'switch_1','value': False}]}	
+                        commands = {"commands": [{"code": "switch_1", "value": False}]}
                         openapi.post(os.getenv("DEVICE_1_ID"), commands)
                     if word == os.getenv("DEVICE_2"):
-                        commands = {'commands': [{'code':'switch_1','value': False}]}	
+                        commands = {"commands": [{"code": "switch_1", "value": False}]}
                         openapi.post(os.getenv("DEVICE_2_ID"), commands)
     else:
         pass
-    
+
     apps = [
-    "youtube",
-    "brave",
-    "discord",
-    "spotify",
-    "explorer",
-    "epic games launcher",
-    "tower of fantasy",
-    "steam",
-    "minecraft",
-    "clip studio paint",
-    "premiere pro",
-    "media encoder",
-    "photoshop",
-    "audacity",
-    "obs",
-    "vscode",
-    "terminal",
-    "synapse",
-    "via"
+        "youtube",
+        "brave",
+        "discord",
+        "spotify",
+        "explorer",
+        "epic games launcher",
+        "tower of fantasy",
+        "steam",
+        "minecraft",
+        "clip studio paint",
+        "premiere pro",
+        "media encoder",
+        "photoshop",
+        "audacity",
+        "obs",
+        "vscode",
+        "terminal",
+        "synapse",
+        "via",
     ]
-    
+
     sentence = "Activate [app]."
     input_sentence = trans.lower()
-    
+
     for word in apps:
         if word in input_sentence:
             modified_sentence = replace_app(sentence, word)
-            print(modified_sentence)
             input_sentence = keep_sentence_with_word(input_sentence, word)
-            input_sentence = input_sentence.translate(str.maketrans('', '', string.punctuation))
-            print(input_sentence)
-            similarity = (test_equivalence(modified_sentence, input_sentence))
-            print(similarity)
+            input_sentence = input_sentence.translate(
+                str.maketrans("", "", string.punctuation)
+            )
+            similarity = test_equivalence(modified_sentence, input_sentence)
             if similarity >= 0.5:
                 start(word, match_closest=True)
             elif similarity < 0.001:
                 end(word, match_closest=True)
     else:
         pass
-    
-    db.load("conversation.pickle.gz")
-    
-    results = db.query(new_line, top_k=2)
 
-    extracted_dicts = [item for item, _ in results]
+    query = f"""{text}"""
+
+    results = memory.search(query, top_n=2)
+
+    extracted_dicts = [result["chunk"] for result in results]
 
     line1 = str(extracted_dicts[0])
     line2 = str(extracted_dicts[1])
-    
-    # Specify the file name
-    file_name = "conversation.jsonl"
-
-    # Initialize an empty list to store the lines
-    lines = []
 
     # Read the file and store the lines in the list
-    with open(file_name, 'r', encoding='UTF-8') as file:
+    with open("conversation.jsonl", "r", encoding="UTF-8") as file:
         lines = file.readlines()
 
-    # Check if there are at least 7 lines in the file (6 lines to read and 1 line to exclude)
-    if len(lines) >= 5:
-        # Extract the last 6 lines (excluding the last line) into a string
-        last_six_lines = ''.join(lines[-5:-1])
+    lines = [line.strip() for line in lines]
+    lines = "\n".join(lines)
+    lines = lines.splitlines()
 
-        # Define a list of lines to check
-        lines_to_check = str(extracted_dicts)
+    # Check if there are at least 5 lines in the file (6 lines to read and 1 line to exclude)
+    if len(lines) >= 5:
+        # Extract the last 5 lines (excluding the last line) into a string
+        last_six_lines = "\n".join(lines[-5:-1])
 
         # Iterate over the lines to check
-        for line_to_check in lines_to_check:
-            if line_to_check not in last_six_lines:
-                # If not found in last_six_lines, search for it in the entire file
-                found = False
-                for i, line in enumerate(lines):
-                    if line == line_to_check:
-                        # If found, append line_to_check and the line directly after it to the top of last_six_lines
-                        last_six_lines = line_to_check + lines[i + 1] + last_six_lines
-                        found = True
+        if line1 not in last_six_lines:
+            # If not found in last_six_lines, search for it in the entire file
+            found = False
+            for i, line in enumerate(lines):
+                if line == line1:
+                    # If found, append line_to_check and the line directly after/before it to the top of last_six_lines
+                    found = True
+                    if '''{"role": "User"''' in line:
+                        last_six_lines = (
+                            line1 + "\n" + str(lines[i + 1]) + "\n" + last_six_lines
+                        )
+                        break
+                    elif '''{"role": "M.I.T.S.U.H.A."''' in line:
+                        last_six_lines = (
+                            str(lines[i - 1]) + "\n" + line1 + "\n" + last_six_lines
+                        )
                         break
-                
-                if not found:
-                    # If still not found, append only line_to_check at the top without the line directly after it
-                    last_six_lines = line_to_check + last_six_lines
+            if not found:
+                # If still not found, append only line_to_check at the top without the line directly after it
+                last_six_lines = line1 + "\n" + last_six_lines
+        if line2 not in last_six_lines:
+            # If not found in last_six_lines, search for it in the entire file
+            found = False
+            for i, line in enumerate(lines):
+                if line == line2:
+                    # If found, append line_to_check and the line directly after/before it to the top of last_six_lines
+                    found = True
+                    if '''{"role": "User"''' in line:
+                        last_six_lines = (
+                            line2 + "\n" + str(lines[i + 1]) + "\n" + last_six_lines
+                        )
+                        break
+                    elif '''{"role": "M.I.T.S.U.H.A."''' in line:
+                        last_six_lines = (
+                            str(lines[i - 1]) + "\n" + line2 + "\n" + last_six_lines
+                        )
+                        break
+            if not found:
+                # If still not found, append only line_to_check at the top without the line directly after it
+                last_six_lines = line2 + "\n" + last_six_lines
     else:
         last_six_lines = lines
-            
+
+    memory.save(f"""["{new_line}"]""")
+
     now = datetime.now()
     date = now.strftime("%m/%d/%Y")
-    time = now.strftime("%H:%M:%S")
-
-    prompt = lore + "\n" + "\n" + str(last_six_lines) + str(new_line) + f'\n{{"role": "M.I.T.S.U.H.A.", "date": "{date}", "time": "{time}", "content": "'
+    time_1 = now.strftime("%H:%M:%S")
+
+    prompt = (
+        lore
+        + "\n\n"
+        + str(last_six_lines)
+        + str(new_line)
+        + f'\n{{"role": "M.I.T.S.U.H.A.", "date": "{date}", "time": "{time_1}", "content": "'
+    )
     prompt = str(prompt)
-    
+
     # generate a response (takes several seconds)
     input_ids = ExLlamatokenizer.encode(str(prompt))
     sys.stdout.flush()
-    
+
     generator.begin_stream(input_ids, settings)
-    
+
     generated_tokens = 0
 
-    print("M.I.T.S.U.H.A.: ", end = "")
+    emotion_hotkey_map = {
+        "(wave)": "6",
+        "(thumbs-up)": "7",
+        "(nodding)": "8",
+        "(shaking head)": "9",
+        "(clap)": "0",
+    }
+
+    print("M.I.T.S.U.H.A.: ", end="")
     generated_text = ""  # Initialize an empty string to store the generated text
     while True:
         chunk, eos, _ = generator.stream()
         generated_tokens += 1
         generated_text += chunk  # Append each chunk to the generated_text variable
-        print (chunk, end = "")
+        found_emotion = False
+        for emotion, hotkey in emotion_hotkey_map.items():
+            if chunk == emotion:
+                found_emotion = True
+                break
+        if not found_emotion:
+            print(chunk, end="")
         sys.stdout.flush()
-        if eos or generated_tokens == max_new_tokens: break
+        if eos or generated_tokens == max_new_tokens:
+            break
     print()
     response = generated_text
 
-    new_line = {"role": "M.I.T.S.U.H.A.", "date": date, "time": time, "content": response}
-    
-    with open(r"conversation.jsonl", "a", encoding='UTF-8') as c:
+    new_line = {
+        "role": "M.I.T.S.U.H.A.",
+        "date": date,
+        "time": time_1,
+        "content": response,
+    }
+
+    with open(r"conversation.jsonl", "a", encoding="UTF-8") as c:
         c.write("\n" + json.dumps(new_line, ensure_ascii=False))
-        
-    documents.append(new_line)
-    db.save("conversation.pickle.gz")
-    
-    voice_vits(text=response, lang="en")
-    
-    filename = 'out.wav'
+
+    memory.save(f"""["{new_line}"]""")
+
+    for emotion, hotkey in emotion_hotkey_map.items():
+        if emotion in response.lower():
+            response = re.sub(re.escape(emotion), "", response, flags=re.IGNORECASE)
+            pyautogui.hotkey("ctrl", "alt", hotkey)
+            break
+
+    voice_vits(text=response, lang=lang_code)
+
+    filename = "out.wav"
     # Extract data and sampling rate from file
-    data, fs = sf.read(filename, dtype='float32')
-    #sd.default.device = "Speakers (Realtek(R) Audio), MME"
-    #sd.default.device = "Headphones (AirPods Pro), MME"
+    data, fs = sf.read(filename, dtype="float32")
+    # sd.default.device = "Speakers (Realtek(R) Audio), MME"
+    # sd.default.device = "Headphones (AirPods Pro), MME"
     sd.default.device = "CABLE Input (VB-Audio Virtual C, MME"
-    
+
     sd.play(data, fs)
     status = sd.wait()  # Wait until file is done playing
 
     if check_goodbye(trans):
         break
     else:
-        continue
\ No newline at end of file
+        continue
diff --git a/Pipfile.lock b/Pipfile.lock
new file mode 100644
index 0000000..aa5ba87
--- /dev/null
+++ b/Pipfile.lock
@@ -0,0 +1,4475 @@
+{
+    "_meta": {
+        "hash": {
+            "sha256": "cc18ef383e9262ec1be4990a2ac917d91caebffd1f14bf39666e81c56c84481b"
+        },
+        "pipfile-spec": 6,
+        "requires": {
+            "python_version": "3.10"
+        },
+        "sources": [
+            {
+                "name": "pypi",
+                "url": "https://pypi.org/simple",
+                "verify_ssl": true
+            },
+            {
+                "name": "pypiartrajz",
+                "url": "https://pypi.artrajz.cn/simple",
+                "verify_ssl": true
+            },
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+                "sha256:ffa565331890b90056c01db69c0fe634a776f8019c143a5ae265f9c6bc4bd6d4"
+            ],
+            "markers": "python_version >= '3.6'",
+            "version": "==1.16.0"
+        },
+        "yarl": {
+            "hashes": [
+                "sha256:008d3e808d03ef28542372d01057fd09168419cdc8f848efe2804f894ae03e51",
+                "sha256:03caa9507d3d3c83bca08650678e25364e1843b484f19986a527630ca376ecce",
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+                "sha256:23d32a2594cb5d565d358a92e151315d1b2268bc10f4610d098f96b147370136",
+                "sha256:26a1dc6285e03f3cc9e839a2da83bcbf31dcb0d004c72d0730e755b33466c30e",
+                "sha256:29e0f83f37610f173eb7e7b5562dd71467993495e568e708d99e9d1944f561ec",
+                "sha256:2b134fd795e2322b7684155b7855cc99409d10b2e408056db2b93b51a52accc7",
+                "sha256:2d47552b6e52c3319fede1b60b3de120fe83bde9b7bddad11a69fb0af7db32f1",
+                "sha256:357495293086c5b6d34ca9616a43d329317feab7917518bc97a08f9e55648455",
+                "sha256:35a2b9396879ce32754bd457d31a51ff0a9d426fd9e0e3c33394bf4b9036b099",
+                "sha256:3777ce5536d17989c91696db1d459574e9a9bd37660ea7ee4d3344579bb6f129",
+                "sha256:3986b6f41ad22988e53d5778f91855dc0399b043fc8946d4f2e68af22ee9ff10",
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+                "sha256:6ad6d10ed9b67a382b45f29ea028f92d25bc0bc1daf6c5b801b90b5aa70fb9ec",
+                "sha256:6f5cb257bc2ec58f437da2b37a8cd48f666db96d47b8a3115c29f316313654ff",
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+                "sha256:7855426dfbddac81896b6e533ebefc0af2f132d4a47340cee6d22cac7190022d",
+                "sha256:7d5aaac37d19b2904bb9dfe12cdb08c8443e7ba7d2852894ad448d4b8f442863",
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+                "sha256:824d6c50492add5da9374875ce72db7a0733b29c2394890aef23d533106e2b15",
+                "sha256:8397a3817d7dcdd14bb266283cd1d6fc7264a48c186b986f32e86d86d35fbac5",
+                "sha256:848cd2a1df56ddbffeb375535fb62c9d1645dde33ca4d51341378b3f5954429b",
+                "sha256:84fc30f71689d7fc9168b92788abc977dc8cefa806909565fc2951d02f6b7d57",
+                "sha256:8619d6915b3b0b34420cf9b2bb6d81ef59d984cb0fde7544e9ece32b4b3043c3",
+                "sha256:8a854227cf581330ffa2c4824d96e52ee621dd571078a252c25e3a3b3d94a1b1",
+                "sha256:8be9e837ea9113676e5754b43b940b50cce76d9ed7d2461df1af39a8ee674d9f",
+                "sha256:928cecb0ef9d5a7946eb6ff58417ad2fe9375762382f1bf5c55e61645f2c43ad",
+                "sha256:957b4774373cf6f709359e5c8c4a0af9f6d7875db657adb0feaf8d6cb3c3964c",
+                "sha256:992f18e0ea248ee03b5a6e8b3b4738850ae7dbb172cc41c966462801cbf62cf7",
+                "sha256:9fc5fc1eeb029757349ad26bbc5880557389a03fa6ada41703db5e068881e5f2",
+                "sha256:a00862fb23195b6b8322f7d781b0dc1d82cb3bcac346d1e38689370cc1cc398b",
+                "sha256:a3a6ed1d525bfb91b3fc9b690c5a21bb52de28c018530ad85093cc488bee2dd2",
+                "sha256:a6327976c7c2f4ee6816eff196e25385ccc02cb81427952414a64811037bbc8b",
+                "sha256:a7409f968456111140c1c95301cadf071bd30a81cbd7ab829169fb9e3d72eae9",
+                "sha256:a825ec844298c791fd28ed14ed1bffc56a98d15b8c58a20e0e08c1f5f2bea1be",
+                "sha256:a8c1df72eb746f4136fe9a2e72b0c9dc1da1cbd23b5372f94b5820ff8ae30e0e",
+                "sha256:a9bd00dc3bc395a662900f33f74feb3e757429e545d831eef5bb280252631984",
+                "sha256:aa102d6d280a5455ad6a0f9e6d769989638718e938a6a0a2ff3f4a7ff8c62cc4",
+                "sha256:aaaea1e536f98754a6e5c56091baa1b6ce2f2700cc4a00b0d49eca8dea471074",
+                "sha256:ad4d7a90a92e528aadf4965d685c17dacff3df282db1121136c382dc0b6014d2",
+                "sha256:b8477c1ee4bd47c57d49621a062121c3023609f7a13b8a46953eb6c9716ca392",
+                "sha256:ba6f52cbc7809cd8d74604cce9c14868306ae4aa0282016b641c661f981a6e91",
+                "sha256:bac8d525a8dbc2a1507ec731d2867025d11ceadcb4dd421423a5d42c56818541",
+                "sha256:bef596fdaa8f26e3d66af846bbe77057237cb6e8efff8cd7cc8dff9a62278bbf",
+                "sha256:c0ec0ed476f77db9fb29bca17f0a8fcc7bc97ad4c6c1d8959c507decb22e8572",
+                "sha256:c38c9ddb6103ceae4e4498f9c08fac9b590c5c71b0370f98714768e22ac6fa66",
+                "sha256:c7224cab95645c7ab53791022ae77a4509472613e839dab722a72abe5a684575",
+                "sha256:c74018551e31269d56fab81a728f683667e7c28c04e807ba08f8c9e3bba32f14",
+                "sha256:ca06675212f94e7a610e85ca36948bb8fc023e458dd6c63ef71abfd482481aa5",
+                "sha256:d1d2532b340b692880261c15aee4dc94dd22ca5d61b9db9a8a361953d36410b1",
+                "sha256:d25039a474c4c72a5ad4b52495056f843a7ff07b632c1b92ea9043a3d9950f6e",
+                "sha256:d5ff2c858f5f6a42c2a8e751100f237c5e869cbde669a724f2062d4c4ef93551",
+                "sha256:d7d7f7de27b8944f1fee2c26a88b4dabc2409d2fea7a9ed3df79b67277644e17",
+                "sha256:d7eeb6d22331e2fd42fce928a81c697c9ee2d51400bd1a28803965883e13cead",
+                "sha256:d8a1c6c0be645c745a081c192e747c5de06e944a0d21245f4cf7c05e457c36e0",
+                "sha256:d8b889777de69897406c9fb0b76cdf2fd0f31267861ae7501d93003d55f54fbe",
+                "sha256:d9e09c9d74f4566e905a0b8fa668c58109f7624db96a2171f21747abc7524234",
+                "sha256:db8e58b9d79200c76956cefd14d5c90af54416ff5353c5bfd7cbe58818e26ef0",
+                "sha256:ddb2a5c08a4eaaba605340fdee8fc08e406c56617566d9643ad8bf6852778fc7",
+                "sha256:e0381b4ce23ff92f8170080c97678040fc5b08da85e9e292292aba67fdac6c34",
+                "sha256:e23a6d84d9d1738dbc6e38167776107e63307dfc8ad108e580548d1f2c587f42",
+                "sha256:e516dc8baf7b380e6c1c26792610230f37147bb754d6426462ab115a02944385",
+                "sha256:ea65804b5dc88dacd4a40279af0cdadcfe74b3e5b4c897aa0d81cf86927fee78",
+                "sha256:ec61d826d80fc293ed46c9dd26995921e3a82146feacd952ef0757236fc137be",
+                "sha256:ee04010f26d5102399bd17f8df8bc38dc7ccd7701dc77f4a68c5b8d733406958",
+                "sha256:f3bc6af6e2b8f92eced34ef6a96ffb248e863af20ef4fde9448cc8c9b858b749",
+                "sha256:f7d6b36dd2e029b6bcb8a13cf19664c7b8e19ab3a58e0fefbb5b8461447ed5ec"
+            ],
+            "markers": "python_version >= '3.7'",
+            "version": "==1.9.4"
+        },
+        "zipp": {
+            "hashes": [
+                "sha256:0e923e726174922dce09c53c59ad483ff7bbb8e572e00c7f7c46b88556409f31",
+                "sha256:84e64a1c28cf7e91ed2078bb8cc8c259cb19b76942096c8d7b84947690cabaf0"
+            ],
+            "markers": "python_version >= '3.8'",
+            "version": "==3.17.0"
+        }
+    },
+    "develop": {}
+}
diff --git a/setup.py b/setup.py
index 94f27bd..9853fe0 100644
--- a/setup.py
+++ b/setup.py
@@ -1,4 +1,9 @@
-print('''
+import time
+import requests
+from huggingface_hub import snapshot_download
+
+print(
+    """
   _____              ______             _ _           
  / ___ \            (_____ \           | (_)_         
 | |   | |____   ____ _____) ) ____ ____| |_| |_ _   _ 
@@ -6,40 +11,55 @@
 | |___| | | | ( (/ /      | ( (/ ( ( | | | | |_| |_| |
  \_____/|_| |_|\____)     |_|\____)_||_|_|_|\___)__  |
                                                (____/
-        Bridging the real and virtual worlds
-       [PROJECT M.I.T.S.U.H.A. Install Script]
-''')
+"""
+)
 
-import os
-os.system("python -m pip install -r requirements.txt")
-os.system("python -m pip install huggingface-hub")
 
-import requests
-from huggingface_hub import snapshot_download
+def typewriter_effect(text, delay=0.03):
+    for char in text:
+        print(char, end="", flush=True)
+        time.sleep(delay)
 
-cmd = os.system
 
-cmd("python -m pip install cmake")
-cmd("python -m pip install git+https://github.com/m-bain/whisperx.git")
-cmd("python -m pip install pyopenjtalk -i https://pypi.artrajz.cn/simple --user")
+text = """        Bridging the real and virtual worlds
+{:^50}
+""".format(
+    "[PROJECT M.I.T.S.U.H.A. Install Script]"
+)
+
+typewriter_effect(text)
+
+import os
+cmd = os.system
+cmd("python -m pip install pipenv")
+print("Only Windows + Nvidia has been officially tested. Linux + Nvidia should work, but it is untested. Mac and other GPUs are not currently supported. Would you like to continue? [y/n]")
+w = input()
+if w == "y":
+    print("Okay, installing pytorch...")
+    cmd("python -m pipenv run pip install -U torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121")
+else:
+    exit()
+print("Installing hugging-face-hub...")
+cmd("python -m pip install huggingface-hub")
 
-cmd("python -m pip install cython")
+print("Installing dependencies...")
+cmd("pipenv install --ignore-pipfile")
 
 print('''Now please enter the ID (simply owner/name; e.g. TheBloke/dolphin-2.1-mistral-7B-GPTQ) of the GPTQ model on huggingface you want to download. If you don't know what this is, just answer "d" and the default model 
 dolphin-2.1-mistral-7B-GPTQ  will be downloaded.''')
 x = input("ID: ")
 y = input(r"Directory to download to; e.g. C:\Users\username\Downloads: ")
 if x == "d":
-    snapshot_download(repo_id="TheBloke/dolphin-2.1-mistral-7B-GPTQ", local_dir=f"{y} + \dolphin-2.1-mistral-7B-GPTQ", local_dir_use_symlinks=False)
-    llm_path = y + "\dolphin-2.1-mistral-7B-GPTQ"
+    snapshot_download(repo_id="TheBloke/dolphin-2.1-mistral-7B-GPTQ", local_dir=fr"{y}", local_dir_use_symlinks=False)
+    llm_path = fr"{y} + \dolphin-2.1-mistral-7B-GPTQ"
 else:
     index = x.find('/')
     if index != -1:
         x = x[index + 1:]
     else:
         x = x
-    snapshot_download(repo_id=x, local_dir=f"{y} + \ + {x}", local_dir_use_symlinks=False)
-    llm_path = str(y + r"\dolphin-2.1-mistral-7B-GPTQ")
+    snapshot_download(repo_id=x, local_dir=fr"{y}\{x}", local_dir_use_symlinks=False)
+    llm_path = y
 
 # URL of the file to download
 url = "https://huggingface.co/DogeLord/megumin-VITS/resolve/main/G_latest.pth"
@@ -53,7 +73,8 @@
 # Check if the request was successful (HTTP status code 200)
 if response.status_code == 200:
     # Open a local file for binary writing
-    with open("vits-simple-api-onereality/Model/g/" + local_filename, 'wb') as file:
+    print("Downloading TTS model...")
+    with open(r"vits-simple-api-onereality/Model/g/" + local_filename, 'wb') as file:
         # Iterate over the content in chunks and write it to the local file
         for chunk in response.iter_content(chunk_size=8192):
             file.write(chunk)
@@ -132,4 +153,4 @@
 with open(".env", "w") as f:
     f.write(data)
     
-print("SETUP COMPLETE! If you need help configuring how to control the samrt devices, hit me up on discord. https://discord.gg/PN48PZEXJS. Thanks for using OneReality: PROJECT M.I.T.S.U.H.A.!")
+print("SETUP COMPLETE! If you need help configuring how to control the samrt devices, hit me up on discord. https://discord.gg/PN48PZEXJS. Thanks for using OneReality: PROJECT M.I.T.S.U.H.A.!")
\ No newline at end of file