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Merge pull request 'Fixed embeds' (#11) from React-Group/ai-virtual-assistant:main into main

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Reviewed-on: https://interstellardevelopment.org/code/code/sageTheDm/ai-virtual-assistant/pulls/11
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sageTheDm 2024-09-16 15:16:19 +02:00
commit 8849b80d84
3 changed files with 11 additions and 0 deletions
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3
py/api.py
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@ -4,6 +4,7 @@ from transformers import AutoTokenizer, LlamaForCausalLM
class API: class API:
# This method processes a message via transformers. (NOT FINISHED!)
@staticmethod @staticmethod
def process_text_transformers(prompt, model): def process_text_transformers(prompt, model):
model = LlamaForCausalLM.from_pretrained(model) model = LlamaForCausalLM.from_pretrained(model)
@ -14,6 +15,7 @@ class API:
generate_ids = model.generate(inputs.input_ids, max_length=30) generate_ids = model.generate(inputs.input_ids, max_length=30)
return tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0] return tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# This method processes a message via ollama
@staticmethod @staticmethod
def process_text_local(prompt, model): def process_text_local(prompt, model):
ollama_url = "http://localhost:11434" ollama_url = "http://localhost:11434"
@ -34,6 +36,7 @@ class API:
else: else:
return "Error: " + response.text return "Error: " + response.text
# This method sends a message to a certain AI.
def send_message(self, message, model): def send_message(self, message, model):
if model == 1: if model == 1:
answer = self.process_text_local(message, "phi3.5") answer = self.process_text_local(message, "phi3.5")

3
py/venv.sh
View file

@ -5,3 +5,6 @@ source venv/bin/activate
pip install transformers pip install transformers
pip install torch pip install torch
pip install flask pip install flask
pip install SpeechRecognition
pip install pyaudio
pip install pocketsphinx

5
py/web_flask.py
View file

@ -1,11 +1,15 @@
from flask import Flask, request, render_template from flask import Flask, request, render_template
from api import API from api import API
from voice_recognition import Voice
APP = Flask(__name__) APP = Flask(__name__)
api = API() api = API()
voice = Voice()
messages = [] messages = []
# The following method shows the user the GUI and does the backend connections to the API.
@APP.route('/', methods=['GET', 'POST']) @APP.route('/', methods=['GET', 'POST'])
def index(): def index():
global messages global messages
@ -16,6 +20,7 @@ def index():
user_message = request.form['user_message'] user_message = request.form['user_message']
if option == "voice": if option == "voice":
user_message = voice.listen()
messages.append(f"User: {user_message}") messages.append(f"User: {user_message}")
elif option == "chat": elif option == "chat":
messages.append(f"User: {user_message}") messages.append(f"User: {user_message}")