Separate the project into client and server and implement the api

docker-compose.yml

@@ -0,0 +1,24 @@
+version: "3.8"
+
+services:
+  web:
+    build:
+      context: .
+      dockerfile: ./docker/dockerfile
+    command: uvicorn server.core.processor:app --reload --host 0.0.0.0
+    volumes:
+      - .:/app
+    ports:
+      - 8008:8000
+
+  mongodb_container:
+    image: mongo:latest
+    environment:
+      MONGO_INITDB_ROOT_USERNAME: root
+      MONGO_INITDB_ROOT_PASSWORD: rootpassword
+    ports:
+      - 27017:27017
+    volumes:
+      - mongodb_data_container:/data/db
+volumes:
+  mongodb_data_container:

docker/dockerfile

@@ -0,0 +1,21 @@
+# Dockerfile
+
+# pull the official docker image
+FROM python:3.9.4
+
+# set work directory
+WORKDIR /app
+
+# set env variables
+ENV PYTHONDONTWRITEBYTECODE 1
+ENV PYTHONUNBUFFERED 1
+
+# install dependencies
+COPY requirements.txt .
+RUN pip install -r requirements.txt
+RUN pip install --no-cache-dir numpy scikit-learn 
+RUN python3 -c "import nltk; nltk.download('punkt'); nltk.download('averaged_perceptron_tagger')"
+# copy project
+COPY . .
+
+WORKDIR /app/src/jarvis

requirements.txt

@@ -1,51 +1,39 @@
-appdirs==1.4.3
 APScheduler==3.6.0
 backports.entry-points-selectable==1.1.0
 beautifulsoup4==4.7.1
 bs4==0.0.1
 certifi==2019.3.9
 chardet==3.0.4
 Click==7.0
-colorize==1.1.0
-Cython==0.29.24
-distlib==0.3.3
 filelock==3.3.0
 geojson==2.4.1
-google==2.0.2
-gTTS-token==1.1.3
 idna==2.8
 inflect==2.1.0
 jaraco.itertools==4.4.2
 joblib==0.14.0
 lxml==4.6.3
 mock==3.0.5
 more-itertools==7.0.0
-nltk==3.4.5
-numpy==1.16.4
 patch==1.16
 platformdirs==2.4.0
 playsound==1.2.2
-psutil==5.6.6
 PTable==0.9.2
-PyAudio==0.2.11
-pycairo==1.20.1
-PyGObject==3.42.0
 pymongo==3.10.1
 pyowm==2.10.0
 pyttsx3==2.71
 pytz==2019.1
 requests==2.21.0
 scipy==1.5.4
+nltk
 six==1.12.0
 soupsieve==1.9.1
-SpeechRecognition==3.8.1
-speedtest-cli==2.1.1
 textblob==0.15.3
 tzlocal==1.5.1
 urllib3==1.24.3
-virtualenv==20.8.1
 web-cache==1.1.0
 wikipedia==1.4.0
 wolframalpha==3.0.1
 word2number==1.1
 xmltodict==0.12.0
+fastapi
+uvicorn

src/jarvis/client/api.py

@@ -0,0 +1,14 @@
+from enum import Enum
+
+class Status_code(Enum):
+    Success = 200
+    Server_Error = 500
+    Client_Error = 400
+
+
+class api_manager:
+    def __init__(self) -> None:
+        pass
+
+    def post_user_input(transcript: str) -> Status_code:
+        pass

src/jarvis/jarvis/core/console.py → src/jarvis/client/console.py

@@ -25,10 +25,10 @@
 import psutil
 import logging
 
-from jarvis import settings
-from jarvis.utils.mongoDB import db
-from jarvis.utils.console import jarvis_logo, start_text, OutputStyler, headerize
-from jarvis.enumerations import MongoCollections, InputMode
+from server import settings
+from server.utils.mongoDB import db
+from server.utils.console import jarvis_logo, start_text, OutputStyler, headerize
+from server.enumerations import MongoCollections, InputMode
 
 
 class ConsoleManager:

src/jarvis/jarvis/engines/stt.py → src/jarvis/client/engines/stt.py

@@ -23,8 +23,8 @@
 import logging
 import speech_recognition as sr
 
-import jarvis
-from jarvis.core.console import ConsoleManager
+import server
+from server.core.console import ConsoleManager
 
 
 class STTEngine:

src/jarvis/jarvis/engines/tts.py → src/jarvis/client/engines/tts.py

@@ -25,7 +25,7 @@
 import pyttsx3
 import queue
 
-from jarvis.core.console import ConsoleManager
+from server.core.console import ConsoleManager
 
 
 class TTS:

src/jarvis/jarvis/engines/ttt.py → src/jarvis/client/engines/ttt.py

@@ -21,8 +21,8 @@
 # SOFTWARE.
 
 import logging
-from jarvis.core.console import ConsoleManager
-from jarvis.utils.console import user_input
+from server.core.console import ConsoleManager
+from server.utils.console import user_input
 
 
 class TTTEngine:

src/jarvis/client/main.py

@@ -0,0 +1,19 @@
+import engines
+from api import api_manager
+
+class Client:
+    def __init__(self, console_manager) -> None:
+        self.console_manager = console_manager
+        self.api_manger = api_manager()
+
+    def run() -> None:
+        """
+         Assistant starting point.
+
+        - STEP 1: Get user input based on the input mode (voice or text)
+        - STEP 2: Send the user input to the api
+        - STEP 3: Get api response and either execute a local skill or give the user a respone
+
+        """
+        transcript = engines.input_engine.recognize_input()
+        self.api_manger.post_user_input(transcript)

src/jarvis/jarvis/__init__.py → src/jarvis/server/__init__.py

@@ -22,12 +22,10 @@
 
 from logging import config
 
-from jarvis import settings
-from jarvis.settings import ROOT_LOG_CONF
-from jarvis.utils.mongoDB import db
-from jarvis.utils.startup import configure_MongoDB
-from jarvis.enumerations import InputMode
-import jarvis.engines as engines
+import server.settings
+from server.settings import ROOT_LOG_CONF
+from server.utils.mongoDB import db
+from server.utils.startup import configure_MongoDB
 
 # ----------------------------------------------------------------------------------------------------------------------
 # Create a Console & Rotating file logger
@@ -55,5 +53,5 @@
 # ----------------------------------------------------------------------------------------------------------------------
 # Create assistant input and output engine instances
 # ----------------------------------------------------------------------------------------------------------------------
-input_engine = engines.STTEngine() if input_mode == InputMode.VOICE.value else engines.TTTEngine()
-output_engine = engines.TTSEngine() if response_in_speech else engines.TTTEngine()
+#input_engine = engines.STTEngine() if input_mode == InputMode.VOICE.value else engines.TTTEngine()
+#output_engine = engines.TTSEngine() if response_in_speech else engines.TTTEngine()