Merged in develop (pull request #59)

Fix speaking self._conf["slides"]["avatar"] giving 'list indices must be integers or slices, not str'

.dockerignore

@@ -5,3 +5,6 @@ README.md
 *.pyd
 __pycache__
 .pytest_cache
+postman
+/scripts
+/.venv

.env

@@ -1,5 +0,0 @@
-OPENAI_API_KEY=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
-JWT_SECRET_KEY=6e9c124ba92e8814719dcb0f21200c8aa4d0f119a994ac5e06eb90a366c83ab2
-JWT_TEST_TOKEN=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiJ0ZXN0In0.Emrs2D3BmMP4b3zMjw0fJTPeyMwWEBDbxx2vvaWguO0
-GOOGLE_APPLICATION_CREDENTIALS=firebase-configs/storied-phalanx-349916.json
-HEY_GEN_TOKEN=MjY4MDE0MjdjZmNhNDFmYTlhZGRkNmI3MGFlMzYwZDItMTY5NTExNzY3MA==

.gitignore

@@ -1,4 +1,7 @@
 __pycache__
 .idea
 .env
-.DS_Store
+.DS_Store
+.venv
+_scripts
+*.env

.idea/.gitignore

@@ -1,8 +0,0 @@
-# Default ignored files
-/shelf/
-/workspace.xml
-# Editor-based HTTP Client requests
-/httpRequests/
-# Datasource local storage ignored files
-/dataSources/
-/dataSources.local.xml

.idea/ielts-be.iml

@@ -1,24 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<module type="PYTHON_MODULE" version="4">
-  <component name="Flask">
-    <option name="enabled" value="true" />
-  </component>
-  <component name="NewModuleRootManager">
-    <content url="file://$MODULE_DIR$">
-      <excludeFolder url="file://$MODULE_DIR$/venv" />
-    </content>
-    <orderEntry type="jdk" jdkName="Python 3.9" jdkType="Python SDK" />
-    <orderEntry type="sourceFolder" forTests="false" />
-  </component>
-  <component name="PackageRequirementsSettings">
-    <option name="versionSpecifier" value="Don't specify version" />
-  </component>
-  <component name="TemplatesService">
-    <option name="TEMPLATE_CONFIGURATION" value="Jinja2" />
-    <option name="TEMPLATE_FOLDERS">
-      <list>
-        <option value="$MODULE_DIR$/../flaskProject\templates" />
-      </list>
-    </option>
-  </component>
-</module>

.idea/inspectionProfiles/profiles_settings.xml

@@ -1,6 +0,0 @@
-<component name="InspectionProjectProfileManager">
-  <settings>
-    <option name="USE_PROJECT_PROFILE" value="false" />
-    <version value="1.0" />
-  </settings>
-</component>

.idea/misc.xml

@@ -1,4 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.9" project-jdk-type="Python SDK" />
-</project>

.idea/modules.xml

@@ -1,8 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="ProjectModuleManager">
-    <modules>
-      <module fileurl="file://$PROJECT_DIR$/.idea/ielts-be.iml" filepath="$PROJECT_DIR$/.idea/ielts-be.iml" />
-    </modules>
-  </component>
-</project>

.idea/vcs.xml

@@ -1,6 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="VcsDirectoryMappings">
-    <mapping directory="$PROJECT_DIR$" vcs="Git" />
-  </component>
-</project>

Dockerfile

@@ -1,6 +1,12 @@
+FROM python:3.11-slim as requirements-stage
+WORKDIR /tmp
+RUN pip install poetry
+COPY pyproject.toml ./poetry.lock* /tmp/
+# https://python-poetry.org/docs/cli#export
+RUN poetry self add poetry-plugin-export
+RUN poetry export -f requirements.txt --output requirements.txt --without-hashes
+
 
-# Use the official lightweight Python image.
-# https://hub.docker.com/_/python
 FROM python:3.11-slim
 
 # Allow statements and log messages to immediately appear in the logs
@@ -9,18 +15,35 @@ ENV PYTHONUNBUFFERED True
 # Copy local code to the container image.
 ENV APP_HOME /app
 WORKDIR $APP_HOME
+
 COPY . ./
 
-RUN apt update && apt install -y ffmpeg
+COPY --from=requirements-stage /tmp/requirements.txt /app/requirements.txt
 
-# Install production dependencies.
-RUN pip install --no-cache-dir -r requirements.txt
+RUN apt update && apt install -y \
+    ffmpeg \
+    poppler-utils \
+    texlive-latex-base \
+    texlive-fonts-recommended \
+    texlive-latex-extra \
+    texlive-xetex \
+    pandoc \
+    librsvg2-bin \
+    curl \
+    && rm -rf /var/lib/apt/lists/*
 
-EXPOSE 5000
+RUN curl -sL https://deb.nodesource.com/setup_20.x | bash - \
+    && apt-get install -y nodejs
+
+RUN npm install -g firebase-tools
+
+RUN pip install --no-cache-dir -r /app/requirements.txt
+
+EXPOSE 8000
 
 # Run the web service on container startup. Here we use the gunicorn
 # webserver, with one worker process and 8 threads.
 # For environments with multiple CPU cores, increase the number of workers
 # to be equal to the cores available.
 # Timeout is set to 0 to disable the timeouts of the workers to allow Cloud Run to handle instance scaling.
-CMD exec gunicorn --bind 0.0.0.0:5000 --workers 1 --threads 8 --timeout 0 app:app
+ENTRYPOINT ["gunicorn", "--bind", "0.0.0.0:8000", "--workers", "1", "--threads", "8", "--timeout", "0", "-k", "uvicorn.workers.UvicornWorker", "ielts_be:app"]

README.md

@@ -0,0 +1,26 @@
+# Run the app
+
+1. pip install poetry
+2. poetry install
+3. python app.py
+
+# Modules
+
+- api -> endpoints
+- configs -> app configs and constants
+- controllers -> meant for handling exceptions, transforming data or orchestrate complex use cases with several services, for now mostly just calls services directly 
+- dtos -> pydantic models used for receiving data and for validation
+- exceptions -> if custom exceptions are needed to throw in services so they can be handled in the controllers to construct some specific http response
+- helpers -> a bunch of lightweight functions grouped by some kind of logic
+- mappers -> to map complex data
+- middlewares -> classes that are run before executing the endpoint code
+- repositories -> interfaces with data stores
+- services -> all the business logic goes here
+- utils -> loose functions used on one-off occasions
+
+# Dependency injection
+
+If you want to add new controllers/services/repositories you will have to change
+app/configs/dependency_injection.py
+
+Also make sure you have @inject on your endpoint when calling these.

audio-samples/placeholder.txt

@@ -1 +0,0 @@
-THIS FILE ONLY EXISTS TO KEEP THIS FOLDER IN THE REPO

docker-compose.yml

@@ -1,10 +1,10 @@
-version: "3"
-
-services:
-  ielts-be:
-    container_name: ielts-be
-    build: .
-    image: ecrop/ielts-be:latest
-    ports:
-      - 8080:5000
-    restart: unless-stopped
+version: "3"
+
+services:
+  ielts-be:
+    container_name: ielts-be
+    build: .
+    image: ecrop/ielts-be:latest
+    ports:
+      - 8080:8000
+    restart: unless-stopped

download-audio/placeholder.txt

@@ -1 +0,0 @@
-THIS FILE ONLY EXISTS TO KEEP THIS FOLDER IN THE REPO

download-video/placeholder.txt

@@ -1 +0,0 @@
-THIS FILE ONLY EXISTS TO KEEP THIS FOLDER IN THE REPO

elai/AvatarEnum.py

@@ -0,0 +1,62 @@
+from enum import Enum
+
+
+class AvatarEnum(Enum):
+    # Works
+    GIA_BUSINESS = {
+        "avatar_code": "gia.business",
+        "avatar_gender": "female",
+        "avatar_url": "https://elai-avatars.s3.us-east-2.amazonaws.com/common/gia/business/gia_business.png",
+        "avatar_canvas": "https://elai-avatars.s3.us-east-2.amazonaws.com/common/gia/business/gia_business.png",
+        "voice_id": "EXAVITQu4vr4xnSDxMaL",
+        "voice_provider": "elevenlabs"
+    }
+    # Works
+    VADIM_BUSINESS = {
+        "avatar_code": "vadim.business",
+        "avatar_gender": "male",
+        "avatar_url": "https://elai-avatars.s3.us-east-2.amazonaws.com/common/vadim/business/vadim_business.png",
+        "avatar_canvas": "https://d3u63mhbhkevz8.cloudfront.net/common/vadim/business/vadim_business.png",
+        "voice_id": "flq6f7yk4E4fJM5XTYuZ",
+        "voice_provider": "elevenlabs"
+    }
+    ORHAN_BUSINESS = {
+        "avatar_code": "orhan.business",
+        "avatar_gender": "male",
+        "avatar_url": "https://elai-avatars.s3.us-east-2.amazonaws.com/common/orhan/business/orhan.png",
+        "avatar_canvas": "https://d3u63mhbhkevz8.cloudfront.net/common/orhan/business/orhan.png",
+        "voice_id": "en-US-AndrewMultilingualNeural",
+        "voice_provider": "azure"
+    }
+    FLORA_BUSINESS = {
+        "avatar_code": "flora.business",
+        "avatar_gender": "female",
+        "avatar_url": "https://elai-avatars.s3.us-east-2.amazonaws.com/common/flora/business/flora_business.png",
+        "avatar_canvas": "https://d3u63mhbhkevz8.cloudfront.net/common/flora/business/flora_business.png",
+        "voice_id": "en-US-JaneNeural",
+        "voice_provider": "azure"
+    }
+    SCARLETT_BUSINESS = {
+        "avatar_code": "scarlett.business",
+        "avatar_gender": "female",
+        "avatar_url": "https://elai-avatars.s3.us-east-2.amazonaws.com/common/scarlett/business/scarlett_business.png",
+        "avatar_canvas": "https://d3u63mhbhkevz8.cloudfront.net/common/scarlett/business/scarlett_business.png",
+        "voice_id": "en-US-NancyNeural",
+        "voice_provider": "azure"
+    }
+    PARKER_CASUAL = {
+        "avatar_code": "parker.casual",
+        "avatar_gender": "male",
+        "avatar_url": "https://elai-avatars.s3.us-east-2.amazonaws.com/common/parker/casual/parker_casual.png",
+        "avatar_canvas": "https://d3u63mhbhkevz8.cloudfront.net/common/parker/casual/parker_casual.png",
+        "voice_id": "en-US-TonyNeural",
+        "voice_provider": "azure"
+    }
+    ETHAN_BUSINESS = {
+        "avatar_code": "ethan.business",
+        "avatar_gender": "male",
+        "avatar_url": "https://elai-avatars.s3.us-east-2.amazonaws.com/common/ethan/business/ethan_business_low.png",
+        "avatar_canvas": "https://d3u63mhbhkevz8.cloudfront.net/common/ethan/business/ethan_business_low.png",
+        "voice_id": "en-US-JasonNeural",
+        "voice_provider": "azure"
+    }

firebase-configs/encoach-staging.json

@@ -1,13 +1,13 @@
-{
-  "type": "service_account",
-  "project_id": "encoach-staging",
-  "private_key_id": "5718a649419776df9637589f8696a258a6a70f6c",
-  "private_key": "-----BEGIN PRIVATE KEY-----\nMIIEvQIBADANBgkqhkiG9w0BAQEFAASCBKcwggSjAgEAAoIBAQC2C6Es2gY8lLvH\ndVilNtRNm9glSaPXMNw2PzZZbSGuG1uGPFaCzlq1lOb2u17YfMG4GriKIMjIQKXF\nqdvxA8CAmAFRuDjUGmpbO/X1ZW7amOs5Bjed2BYmL01dEqzzwwh7rEfNDjeghRPx\n1uKzH8A6TLT5xq+74I5K1CIgiljBpZimsERu2SDawjkdtZfA7qoylA46Nq66LuwQ\nVyv9CK2SZNpBcT3sunCmRsrCzmSTzKdbcqRPdqUKgZOH/Rjp0sw9VuUgwoxdGZV3\n5SJjObo5ceZ1OSiJm7GwLzp7uq16sqycgSYwppNLI5OtzOfSuWbGD4+a044t2Mlq\n9PHXv7H/AgMBAAECggEAAfhKlFwq8MaL6PggRJq9HbaKgQ4fcOmCmy8AQmPNF1UM\nyVKSKGndjxUfPLCWsaaunUnjZlHoKkvndKXxDyttuVaBE9EiWEqNjRLZ3KpuJ9Jm\nH+CtLbmUCnISQb1n1AlvvZAwhLZbLBL/PhYyWiLapybZAdJAaOWLVKGgBD8gVRQW\nJFCqnszX1O2YlpWHutb979R4qoY/XAf94gyMkTpXZwuETvFqZbau2vxRZ8qARix3\nmic881PwiF6Cod8UPCS9yMK+Q+Se6SomwXU9PCmlummn9xmQBAxYy8gIAVs/J9Fg\n5SvhnImAPDd+zIzzw2cHCiruNWIhroMVZDZJgWdY1QKBgQDjTKKeFOur3ijJJL2/\nWg1SE2jLP0GpXzM5YMx6jdOCNDCzugPngRucRXiTkJ2FnUgyMcQyi6hyrbWXN/6z\nXhx5fwLB4tnTcqOMvNfcay5mDk3RW9ZZJxayB54Sf1Nm/4xiDBnGPT+iHQvK+/pT\nwScWznFkmk60E796o76OLn3PEwKBgQDNCC2uPq+uOcCopIO8HH88gqdxTvpbeHUU\nrdJOmr1VtGNuvay/mfpva9+VEtGbZTFzjhfvfCEIjpj3Llh8Flb9EYa6BmscBiyp\ngszEeFuB3zHndlSCZPnGJ7JiRAdPAEgG3Gl/r9th6PDaEMq0MFS5i7GGhPBIRYCG\nUtmY5eVy5QKBgH5Nuls/YsnJFD7ZNLscziQadvPhvZnhNbSfjmBXaP2EBMAKEFtX\nCcGndN4C0RVLFbAWqWAw7LR0xGA4FEcVd5snsZ+Nb98oZ6sv0H9B67F4J1O7xXsa\n1mitBPBgYjbsr9RXxwa6SB7MJx5vMGXUAeWRZ78wY6V7B76dOKkHOo+TAoGBAJf5\nBOsPueZZFm2qK58GPGVcrsI0+StNuPLP+H+dANQC9mTCIMaQWmm2Oq5jmYwmUKZH\nX4R6rH2MPOOSrbGkWWwRTpyaX1ARX49xzVefoqw8BOB8/Bz+vYjcKcPeitBK9Bhp\nzaUAc4s6PzRTl/xBirtRSQ/df8ECC0cFKBbF6PHlAoGAGqnlpo+k8vAtg6ulCuGu\nx2Y/c5UmvXGHk60pccnW3UtENSDnl99OgMfBz8/qLAMWs6DUQ/kvSlHQPmMBHRWZ\nNTr6ceGXyNs4KdYoj1K7AU3c0Lm0wyQ2giQMoOOUQAm98Xr8z5aiihj10hHPmzzL\n9kwpOmZpjNmC/ERD69imWhY=\n-----END PRIVATE KEY-----\n",
-  "client_email": "firebase-adminsdk-8rs9e@encoach-staging.iam.gserviceaccount.com",
-  "client_id": "108221424237414412378",
-  "auth_uri": "https://accounts.google.com/o/oauth2/auth",
-  "token_uri": "https://oauth2.googleapis.com/token",
-  "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
-  "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/firebase-adminsdk-8rs9e%40encoach-staging.iam.gserviceaccount.com",
-  "universe_domain": "googleapis.com"
+{
+  "type": "service_account",
+  "project_id": "encoach-staging",
+  "private_key_id": "5718a649419776df9637589f8696a258a6a70f6c",
+  "private_key": "-----BEGIN PRIVATE KEY-----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\n9kwpOmZpjNmC/ERD69imWhY=\n-----END PRIVATE KEY-----\n",
+  "client_email": "firebase-adminsdk-8rs9e@encoach-staging.iam.gserviceaccount.com",
+  "client_id": "108221424237414412378",
+  "auth_uri": "https://accounts.google.com/o/oauth2/auth",
+  "token_uri": "https://oauth2.googleapis.com/token",
+  "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
+  "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/firebase-adminsdk-8rs9e%40encoach-staging.iam.gserviceaccount.com",
+  "universe_domain": "googleapis.com"
 }

firebase-configs/mti-ielts-626a2dcf6091.json

@@ -1,13 +1,13 @@
-{
-  "type": "service_account",
-  "project_id": "mti-ielts",
-  "private_key_id": "626a2dcf60916a1b5011f388495b8f9c4fc065ef",
-  "private_key": "-----BEGIN PRIVATE KEY-----\nMIIEvgIBADANBgkqhkiG9w0BAQEFAASCBKgwggSkAgEAAoIBAQDuaLgLNa5yb5LI\nPZYa7qav0URgCF7miK3dUXIBoABQ+U6y1LwdsIiJqHZ4Cm2lotTqeTGOIV83PuA6\n9H/TwnvsHH8jilmsPxO5OX7AyZSDPvN45nJrgQ21RKZCYQGVetBMGhclCRbYFraS\nE6X/p6gSOpSqZ5fLz8BbdCMfib6HSfDmBkYTK42X6d2eNNwLM1wLbE8RmCGwRATC\nQFfMhjlvQcSJ1EDMfkMUUE9U/ux77wfHqs1d+7utVcQTIMFAP9fo1ynJlwp8D1HQ\ntalB6kkpuDQetUR0A1FHMMJekhmuRDUMfokX1F9JfUjR0OetuD3KEH5y2asxC2+0\n8JYcwbvlAgMBAAECggEAKaaW3LJ8rxZp/NyxkDP4YAf9248q0Ti4s00qzzjeRUdA\n5gI/eSphuDb7t34O6NyZOPuCWlPfOB4ee35CpMK59qaF2bYuc2azseznBZRSA1no\nnEsaW0i5Fd2P9FHRPoWtxVXbjEdZu9e//qY7Hn5yYPjmBx1BCkTZ1MBl8HkWlbjR\nbu18uveg5Vg6Wc+rnPmH/gMRLLpq9iQBpzXWT8Mj+k48O8GnW6v8S3R027ymqUou\n3W5b69xDGn0nwxgLIVzdxjoo7RnpjD3mP0x4faiBhScVgFhwZP8hqBeVyqbV5dMh\nfF+p9zLOeilFLJEjH1lZbZAb8wwP23LozIXJWFG3oQKBgQD6COCJ7hNSx9/AzDhO\nh73hKH/KSOJtxHc8795hcZjy9HJkoM45Fm7o2QGZzsZmV+N6VU0BjoDQAyftCq+G\ndIX0wcAGJIsLuQ9K00WI2hn7Uq1gjUl0d9XEorogKa1ZNTLL/9By/xnA7sEpI6Ng\nIsKQ4R2CfqNFU4bs1nyKWCWudQKBgQD0GNYwZt3xV2YBATVYsrvg1OGO/tmkCJ8Y\nLOdM0L+8WMCgw0uQcNFF9uqq6/oFgq7tOvpeZDsY8onRy55saaMT+Lr4xs0sj5B0\ns5Hqc0L37tdXXXXEne8WABMBF9injNgNbAm9W0kqME2Stc53OJQPj2DBdYxWSr8v\n36imCwoJsQKBgH0BBSlQQo7naKFeOGRijvbLpZ//clzIlYh8r+Rtw7brqWlPz+pQ\noeB95cP80coG9K6LiPVXRmU4vrRO3FRPW01ztEod6PpSaifRmnkB+W1h91ZHLMsy\nwkgNxxofXBA2fY/p9FAZ48lGVIH51EtS9Y0zTuqX347gZJtx3E/aI/SlAoGBAJer\nCwM+F2+K352GM7BuNiDoBVLFdVPf64Ko+/sVxdzwxJffYQdZoh634m3bfBmKbsiG\nmeSmoLXKlenefAxewu544SwM0pV6isaIgQTNI3JMXE8ziiZl/5WK7EQEniDVebU1\nSQP4QYjORJUBFE2twQm+C9+I+27uuMa1UOQC/fSxAoGBANuWloacqGfws6nbHvqF\nLZKlkKNPI/0sC+6VlqjoHn5LQz3lcFM1+iKSQIGJvJyru2ODgv2Lmq2W+cx+HMeq\n0BSetK4XtalmO9YflH7uMgvOEVewf4uJ2d+4I1pbY9aI1gHaZ1EUiiy6Ds4kAK8s\nTQqp88pfTbOnkdJBVi0AWs5B\n-----END PRIVATE KEY-----\n",
-  "client_email": "firebase-adminsdk-dyg6p@mti-ielts.iam.gserviceaccount.com",
-  "client_id": "104980563453519094431",
-  "auth_uri": "https://accounts.google.com/o/oauth2/auth",
-  "token_uri": "https://oauth2.googleapis.com/token",
-  "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
-  "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/firebase-adminsdk-dyg6p%40mti-ielts.iam.gserviceaccount.com",
-  "universe_domain": "googleapis.com"
-}
+{
+  "type": "service_account",
+  "project_id": "mti-ielts",
+  "private_key_id": "626a2dcf60916a1b5011f388495b8f9c4fc065ef",
+  "private_key": "-----BEGIN PRIVATE KEY-----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\nTQqp88pfTbOnkdJBVi0AWs5B\n-----END PRIVATE KEY-----\n",
+  "client_email": "firebase-adminsdk-dyg6p@mti-ielts.iam.gserviceaccount.com",
+  "client_id": "104980563453519094431",
+  "auth_uri": "https://accounts.google.com/o/oauth2/auth",
+  "token_uri": "https://oauth2.googleapis.com/token",
+  "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
+  "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/firebase-adminsdk-dyg6p%40mti-ielts.iam.gserviceaccount.com",
+  "universe_domain": "googleapis.com"
+}

firebase-configs/storied-phalanx-349916.json

@@ -1,13 +1,13 @@
-{
-  "type": "service_account",
-  "project_id": "storied-phalanx-349916",
-  "private_key_id": "c9e05f6fe413b1031a71f981160075ff4b044444",
-  "private_key": "-----BEGIN PRIVATE KEY-----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\n8sDu//ohb7nCzceEI0DnWs13\n-----END PRIVATE KEY-----\n",
-  "client_email": "firebase-adminsdk-3ml0u@storied-phalanx-349916.iam.gserviceaccount.com",
-  "client_id": "114163760341944984396",
-  "auth_uri": "https://accounts.google.com/o/oauth2/auth",
-  "token_uri": "https://oauth2.googleapis.com/token",
-  "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
-  "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/firebase-adminsdk-3ml0u%40storied-phalanx-349916.iam.gserviceaccount.com",
-  "universe_domain": "googleapis.com"
+{
+  "type": "service_account",
+  "project_id": "storied-phalanx-349916",
+  "private_key_id": "c9e05f6fe413b1031a71f981160075ff4b044444",
+  "private_key": "-----BEGIN PRIVATE KEY-----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\n8sDu//ohb7nCzceEI0DnWs13\n-----END PRIVATE KEY-----\n",
+  "client_email": "firebase-adminsdk-3ml0u@storied-phalanx-349916.iam.gserviceaccount.com",
+  "client_id": "114163760341944984396",
+  "auth_uri": "https://accounts.google.com/o/oauth2/auth",
+  "token_uri": "https://oauth2.googleapis.com/token",
+  "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
+  "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/firebase-adminsdk-3ml0u%40storied-phalanx-349916.iam.gserviceaccount.com",
+  "universe_domain": "googleapis.com"
 }

helper/api_messages.py

@@ -1,441 +0,0 @@
-from enum import Enum
-
-from typing import List
-
-
-class QuestionType(Enum):
-    LISTENING_SECTION_1 = "Listening Section 1"
-    LISTENING_SECTION_2 = "Listening Section 2"
-    LISTENING_SECTION_3 = "Listening Section 3"
-    LISTENING_SECTION_4 = "Listening Section 4"
-    WRITING_TASK_1 = "Writing Task 1"
-    WRITING_TASK_2 = "Writing Task 2"
-    SPEAKING_1 = "Speaking Task Part 1"
-    SPEAKING_2 = "Speaking Task Part 2"
-    READING_PASSAGE_1 = "Reading Passage 1"
-    READING_PASSAGE_2 = "Reading Passage 2"
-    READING_PASSAGE_3 = "Reading Passage 3"
-
-
-def get_grading_messages(question_type: QuestionType, question: str, answer: str, context: str = None):
-    if QuestionType.WRITING_TASK_1 == question_type:
-        messages = [
-            {
-                "role": "user",
-                "content": "You are a IELTS examiner.",
-            },
-            {
-                "role": "user",
-                "content": f"The question you have to grade is of type Writing Task 1 and is the following: {question}",
-            }
-        ]
-
-        if not (context is None or context == ""):
-            messages.append({
-                "role": "user",
-                "content": f"To grade the previous question, bear in mind the following context: {context}",
-            })
-
-        messages.extend([
-            {
-                "role": "user",
-                "content": "It is mandatory for you to provide your response with the overall grade and breakdown grades, "
-                           "with just the following json format: {'comment': 'comment about answer quality', 'overall': 7.0, "
-                           "'task_response': {'Task Achievement': 8.0, 'Coherence and Cohesion': 6.5, 'Lexical Resource': 7.5, "
-                           "'Grammatical Range and Accuracy': 6.0}}",
-            },
-            {
-                "role": "user",
-                "content": "Example output: { 'comment': 'Overall, the response is good but there are some areas that need "
-                           "improvement.\n\nIn terms of Task Achievement, the writer has addressed all parts of the question "
-                           "and has provided a clear opinion on the topic. However, some of the points made are not fully "
-                           "developed or supported with examples.\n\nIn terms of Coherence and Cohesion, there is a clear "
-                           "structure to the response with an introduction, body paragraphs and conclusion. However, there "
-                           "are some issues with cohesion as some sentences do not flow smoothly from one to another.\n\nIn "
-                           "terms of Lexical Resource, there is a good range of vocabulary used throughout the response and "
-                           "some less common words have been used effectively.\n\nIn terms of Grammatical Range and Accuracy, "
-                           "there are some errors in grammar and sentence structure which affect clarity in places.\n\nOverall, "
-                           "this response would score a band 6.5.', 'overall': 6.5, 'task_response': "
-                           "{ 'Coherence and Cohesion': 6.5, 'Grammatical Range and Accuracy': 6.0, 'Lexical Resource': 7.0, "
-                           "'Task Achievement': 7.0}}",
-            },
-            {
-                "role": "user",
-                "content": f"Evaluate this answer according to ielts grading system: {answer}",
-            },
-        ])
-        return messages
-    elif QuestionType.WRITING_TASK_2 == question_type:
-        return [
-            {
-                "role": "user",
-                "content": "You are a IELTS examiner.",
-            },
-            {
-                "role": "user",
-                "content": f"The question you have to grade is of type Writing Task 2 and is the following: {question}",
-            },
-            {
-                "role": "user",
-                "content": "It is mandatory for you to provide your response with the overall grade and breakdown grades, "
-                           "with just the following json format: {'comment': 'comment about answer quality', 'overall': 7.0, "
-                           "'task_response': {'Task Achievement': 8.0, 'Coherence and Cohesion': 6.5, 'Lexical Resource': 7.5, "
-                           "'Grammatical Range and Accuracy': 6.0}}",
-            },
-            {
-                "role": "user",
-                "content": "Example output: { 'comment': 'Overall, the response is good but there are some areas that need "
-                           "improvement.\n\nIn terms of Task Achievement, the writer has addressed all parts of the question "
-                           "and has provided a clear opinion on the topic. However, some of the points made are not fully "
-                           "developed or supported with examples.\n\nIn terms of Coherence and Cohesion, there is a clear "
-                           "structure to the response with an introduction, body paragraphs and conclusion. However, there "
-                           "are some issues with cohesion as some sentences do not flow smoothly from one to another.\n\nIn "
-                           "terms of Lexical Resource, there is a good range of vocabulary used throughout the response and "
-                           "some less common words have been used effectively.\n\nIn terms of Grammatical Range and Accuracy, "
-                           "there are some errors in grammar and sentence structure which affect clarity in places.\n\nOverall, "
-                           "this response would score a band 6.5.', 'overall': 6.5, 'task_response': "
-                           "{ 'Coherence and Cohesion': 6.5, 'Grammatical Range and Accuracy': 6.0, 'Lexical Resource': 7.0, "
-                           "'Task Achievement': 7.0}}",
-            },
-            {
-                "role": "user",
-                "content": f"Evaluate this answer according to ielts grading system: {answer}",
-            },
-        ]
-    elif QuestionType.SPEAKING_1 == question_type:
-        return [
-            {
-                "role": "user",
-                "content": "You are an IELTS examiner."
-            },
-            {
-                "role": "user",
-                "content": f"The question you need to grade is a Speaking Task Part 1 question, and it is as follows: {question}"
-            },
-            {
-                "role": "user",
-                "content": "Please provide your assessment using the following JSON format: {'comment': 'Comment about answer "
-                           "quality will go here', 'overall': 7.0, 'task_response': {'Fluency and "
-                           "Coherence': 8.0, 'Lexical Resource': 6.5, 'Grammatical Range and Accuracy': 7.5, 'Pronunciation': 6.0}}"
-            },
-            {
-                "role": "user",
-                "content": "Example output: {'comment': 'Comment about answer quality will go here', 'overall': 6.5, "
-                           "'task_response': {'Fluency and Coherence': 7.0, "
-                           "'Lexical Resource': 6.5, 'Grammatical Range and Accuracy': 7.0, 'Pronunciation': 6.0}}"
-            },
-            {
-                "role": "user",
-                "content": "Please assign a grade of 0 if the answer provided does not address the question."
-            },
-            {
-                "role": "user",
-                "content": f"Assess this answer according to the IELTS grading system: {answer}"
-            },
-            {
-                "role": "user",
-                "content": "Remember to consider Fluency and Coherence, Lexical Resource, Grammatical Range and Accuracy, "
-                           "and Pronunciation when grading the response."
-            }
-        ]
-    elif QuestionType.SPEAKING_2 == question_type:
-        return [
-            {
-                "role": "user",
-                "content": "You are an IELTS examiner."
-            },
-            {
-                "role": "user",
-                "content": f"The question you need to grade is a Speaking Task Part 2 question, and it is as follows: {question}"
-            },
-            {
-                "role": "user",
-                "content": "Please provide your assessment using the following JSON format: {\"comment\": \"Comment about "
-                           "answer quality\", \"overall\": 7.0, \"task_response\": {\"Fluency and Coherence\": 8.0, \"Lexical "
-                           "Resource\": 6.5, \"Grammatical Range and Accuracy\": 7.5, \"Pronunciation\": 6.0}}"
-            },
-            {
-                "role": "user",
-                "content": "Example output: {\"comment\": \"The candidate has provided a clear response to the question "
-                           "and has given examples of how they spend their weekends. However, there are some issues with "
-                           "grammar and pronunciation that affect the overall score. In terms of fluency and coherence, "
-                           "the candidate speaks clearly and smoothly with only minor hesitations. They have also provided "
-                           "a well-organized response that is easy to follow. Regarding lexical resource, the candidate "
-                           "has used a range of vocabulary related to weekend activities but there are some errors in "
-                           "word choice that affect the meaning of their sentences. In terms of grammatical range and "
-                           "accuracy, the candidate has used a mix of simple and complex sentence structures but there "
-                           "are some errors in subject-verb agreement and preposition use. Finally, regarding pronunciation, "
-                           "the candidate's speech is generally clear but there are some issues with stress and intonation "
-                           "that make it difficult to understand at times.\", \"overall\": 6.5, \"task_response\": {\"Fluency "
-                           "and Coherence\": 7.0, \"Lexical Resource\": 6.5, \"Grammatical Range and Accuracy\": 7.0, "
-                           "\"Pronunciation\": 6.0}}"
-            },
-            {
-                "role": "user",
-                "content": "Please assign a grade of 0 if the answer provided does not address the question."
-            },
-            {
-                "role": "user",
-                "content": f"Assess this answer according to the IELTS grading system: {answer}"
-            },
-            {
-                "role": "user",
-                "content": "Remember to consider Fluency and Coherence, Lexical Resource, Grammatical Range and Accuracy, "
-                           "and Pronunciation when grading the response."
-            }
-        ]
-    else:
-        raise Exception("Question type not implemented: " + question_type.value)
-
-
-def get_speaking_grading_messages(answers: List):
-    messages = [
-        {
-            "role": "user",
-            "content": "You are an IELTS examiner."
-        },
-        {
-            "role": "user",
-            "content": "The exercise you need to grade is a Speaking Task, and it is has the following questions and answers:"
-        }
-    ]
-    for item in answers:
-        question = item["question"]
-        answer = item["answer_text"]
-        messages.append({
-            "role": "user",
-            "content": f"Question: {question}; Answer: {answer}"
-        })
-    messages.extend([
-        {
-            "role": "user",
-            "content": f"Assess this answer according to the IELTS grading system."
-        },
-        {
-            "role": "user",
-            "content": "Please provide your assessment using the following JSON format: {'comment': 'Comment about answer "
-                       "quality will go here', 'overall': 7.0, 'task_response': {'Fluency and "
-                       "Coherence': 8.0, 'Lexical Resource': 6.5, 'Grammatical Range and Accuracy': 7.5, 'Pronunciation': 6.0}}"
-        },
-        {
-            "role": "user",
-            "content": "Example output: {'comment': 'Comment about answer quality will go here', 'overall': 6.5, "
-                       "'task_response': {'Fluency and Coherence': 7.0, "
-                       "'Lexical Resource': 6.5, 'Grammatical Range and Accuracy': 7.0, 'Pronunciation': 6.0}}"
-        },
-        {
-            "role": "user",
-            "content": "Please assign a grade of 0 if the answer provided does not address the question."
-        },
-        {
-            "role": "user",
-            "content": "Remember to consider Fluency and Coherence, Lexical Resource, Grammatical Range and Accuracy, "
-                       "and Pronunciation when grading the response."
-        }
-    ])
-    return messages
-
-
-def get_question_gen_messages(question_type: QuestionType):
-    if QuestionType.LISTENING_SECTION_1 == question_type:
-        return [
-            {
-                "role": "user",
-                "content": "You are a IELTS program that generates questions for the exams.",
-            },
-            {
-                "role": "user",
-                "content": "Provide me with a transcript similar to the ones in ielts exam Listening Section 1. "
-                           "Create an engaging transcript simulating a conversation related to a unique type of service "
-                           "that requires getting the customer's details. Make sure to include specific details "
-                           "and descriptions to bring"
-                           "the scenario to life. After the transcript, please "
-                           "generate a 'form like' fill in the blanks exercise with 6 form fields (ex: name, date of birth)"
-                           " to fill related to the customer's details. Finally, "
-                           "provide the answers for the exercise. The response must be a json following this format: "
-                           "{ 'type': '<type of registration (ex: hotel, gym, english course, etc)>', "
-                           "'transcript': '<transcript of just the conversation about a registration of some sort, "
-                           "identify the person talking in each speech line>', "
-                           "'exercise': { 'form field': { '1': '<form field 1>', '2': '<form field 2>', "
-                           "'3': '<form field 3>', '4': '<form field 4>', "
-                           "'5': '<form field 5>', '6': '<form field 5>' }, "
-                           "'answers': {'1': '<answer to fill blank space in form field 1>', '2': '<answer to fill blank "
-                           "space in form field 2>', '3': '<answer to fill blank space in form field 3>', "
-                           "'4': '<answer to fill blank space in form field 4>', '5': '<answer to fill blank space in form field 5>',"
-                           " '6': '<answer to fill blank space in form field 6>'}}}",
-            }
-        ]
-    elif QuestionType.LISTENING_SECTION_2 == question_type:
-        return [
-            {
-                "role": "user",
-                "content": "You are a IELTS program that generates questions for the exams.",
-            },
-            {
-                "role": "user",
-                "content": "Provide me with a transcript similar to the ones in ielts exam Listening section 2. After the transcript, please "
-                           "generate a fill in the blanks exercise with 6 statements related to the text content. Finally, "
-                           "provide the answers for the exercise. The response must be a json following this format: "
-                           "{ 'transcript': 'transcript about some subject', 'exercise': { 'statements': { '1': 'statement 1 "
-                           "with a blank space to fill', '2': 'statement 2 with a blank space to fill', '3': 'statement 3 with a "
-                           "blank space to fill', '4': 'statement 4 with a blank space to fill', '5': 'statement 5 with a blank "
-                           "space to fill', '6': 'statement 6 with a blank space to fill' }, "
-                           "'answers': {'1': 'answer to fill blank space in statement 1', '2': 'answer to fill blank "
-                           "space in statement 2', '3': 'answer to fill blank space in statement 3', "
-                           "'4': 'answer to fill blank space in statement 4', '5': 'answer to fill blank space in statement 5',"
-                           " '6': 'answer to fill blank space in statement 6'}}}",
-            }
-        ]
-    elif QuestionType.LISTENING_SECTION_3 == question_type:
-        return [
-            {
-                "role": "user",
-                "content": "You are a IELTS program that generates questions for the exams.",
-            },
-            {
-                "role": "user",
-                "content": "Provide me with a transcript similar to the ones in ielts exam Listening section 3. After the transcript, please "
-                           "generate 4 multiple choice questions related to the text content. Finally, "
-                           "provide the answers for the exercise. The response must be a json following this format: "
-                           "{ 'transcript': 'generated transcript similar to the ones in ielts exam Listening section 3', "
-                           "'exercise': { 'questions': [ { 'question': "
-                           "'question 1', 'options': ['option 1', 'option 2', 'option 3', 'option 4'], 'answer': 1}, "
-                           "{'question': 'question 2', 'options': ['option 1', 'option 2', 'option 3', 'option 4'], "
-                           "'answer': 3}, {'question': 'question 3', 'options': ['option 1', 'option 2', 'option 3', "
-                           "'option 4'], 'answer': 0}, {'question': 'question 4', 'options': ['option 1', 'option 2', "
-                           "'option 3', 'option 4'], 'answer': 2}]}}",
-            }
-        ]
-    elif QuestionType.LISTENING_SECTION_4 == question_type:
-        return [
-            {
-                "role": "user",
-                "content": "You are a IELTS program that generates questions for the exams.",
-            },
-            {
-                "role": "user",
-                "content": "Provide me with a transcript similar to the ones in ielts exam Listening section 4. After the transcript, please "
-                           "generate 4 completion-type questions related to the text content to complete with 1 word. Finally, "
-                           "provide the answers for the exercise. The response must be a json following this format: "
-                           "{ 'transcript': 'generated transcript similar to the ones in ielts exam Listening section 4', "
-                           "'exercise': [ { 'question': 'question 1', 'answer': 'answer 1'}, "
-                           "{'question': 'question 2', 'answer': 'answer 2'}, {'question': 'question 3', 'answer': 'answer 3'}, "
-                           "{'question': 'question 4', 'answer': 'answer 4'}]}",
-            }
-        ]
-    elif QuestionType.WRITING_TASK_2 == question_type:
-        return [
-            {
-                "role": "user",
-                "content": "You are a IELTS program that generates questions for the exams.",
-            },
-            {
-                "role": "user",
-                "content": "The question you have to generate is of type Writing Task 2.",
-            },
-            {
-                "role": "user",
-                "content": "It is mandatory for you to provide your response with the question "
-                           "just with the following json format: {'question': 'question'}",
-            },
-            {
-                "role": "user",
-                "content": "Example output: { 'question': 'We are becoming increasingly dependent on computers. "
-                           "They are used in businesses, hospitals, crime detection and even to fly planes. What things will "
-                           "they be used for in the future? Is this dependence on computers a good thing or should we he more "
-                           "auspicious of their benefits?'}",
-            },
-            {
-                "role": "user",
-                "content": "Generate a question for IELTS exam Writing Task 2.",
-            },
-        ]
-    elif QuestionType.SPEAKING_1 == question_type:
-        return [
-            {
-                "role": "user",
-                "content": "You are a IELTS program that generates questions for the exams.",
-            },
-            {
-                "role": "user",
-                "content": "The question you have to generate is of type Speaking Task Part 1.",
-            },
-            {
-                "role": "user",
-                "content": "It is mandatory for you to provide your response with the question "
-                           "just with the following json format: {'question': 'question'}",
-            },
-            {
-                "role": "user",
-                "content": "Example output: { 'question': 'Let’s talk about your home town or village. "
-                           "What kind of place is it? What’s the most interesting part of your town/village? "
-                           "What kind of jobs do the people in your town/village do? "
-                           "Would you say it’s a good place to live? (Why?)'}",
-            },
-            {
-                "role": "user",
-                "content": "Generate a question for IELTS exam Speaking Task.",
-            },
-        ]
-    elif QuestionType.SPEAKING_2 == question_type:
-        return [
-            {
-                "role": "user",
-                "content": "You are a IELTS program that generates questions for the exams.",
-            },
-            {
-                "role": "user",
-                "content": "The question you have to generate is of type Speaking Task Part 2.",
-            },
-            {
-                "role": "user",
-                "content": "It is mandatory for you to provide your response with the question "
-                           "just with the following json format: {'question': 'question'}",
-            },
-            {
-                "role": "user",
-                "content": "Example output: { 'question': 'Describe something you own which is very important to you. "
-                           "You should say: where you got it from how long you have had it what you use it for and "
-                           "explain why it is important to you.'}",
-            },
-            {
-                "role": "user",
-                "content": "Generate a question for IELTS exam Speaking Task.",
-            },
-        ]
-    else:
-        raise Exception("Question type not implemented: " + question_type.value)
-
-
-def get_question_tips(question: str, answer: str, correct_answer: str, context: str = None):
-    messages = [
-        {
-            "role": "user",
-            "content": "You are a IELTS exam program that analyzes incorrect answers to questions and gives tips to "
-                       "help students understand why it was a wrong answer and gives helpful insight for the future. "
-                       "The tip should refer to the context and question.",
-        }
-    ]
-
-    if not (context is None or context == ""):
-        messages.append({
-            "role": "user",
-            "content": f"This is the context for the question: {context}",
-        })
-
-    messages.extend([
-        {
-            "role": "user",
-            "content": f"This is the question: {question}",
-        },
-        {
-            "role": "user",
-            "content": f"This is the answer: {answer}",
-        },
-        {
-            "role": "user",
-            "content": f"This is the correct answer: {correct_answer}",
-        }
-    ])
-
-    return messages

helper/constants.py

@@ -1,658 +0,0 @@
-AUDIO_FILES_PATH = 'download-audio/'
-FIREBASE_LISTENING_AUDIO_FILES_PATH = 'listening_recordings/'
-VIDEO_FILES_PATH = 'download-video/'
-FIREBASE_SPEAKING_VIDEO_FILES_PATH = 'speaking_videos/'
-
-GRADING_TEMPERATURE = 0.1
-TIPS_TEMPERATURE = 0.2
-GEN_QUESTION_TEMPERATURE = 0.7
-GPT_3_5_TURBO = "gpt-3.5-turbo"
-GPT_4_TURBO = "gpt-4-turbo"
-GPT_4_O = "gpt-4o"
-GPT_3_5_TURBO_16K = "gpt-3.5-turbo-16k"
-GPT_3_5_TURBO_INSTRUCT = "gpt-3.5-turbo-instruct"
-GPT_4_PREVIEW = "gpt-4-turbo-preview"
-
-GRADING_FIELDS = ['comment', 'overall', 'task_response']
-GEN_FIELDS = ['topic']
-GEN_TEXT_FIELDS = ['title']
-LISTENING_GEN_FIELDS = ['transcript', 'exercise']
-READING_EXERCISE_TYPES = ['fillBlanks', 'writeBlanks', 'trueFalse', 'paragraphMatch']
-LISTENING_EXERCISE_TYPES = ['multipleChoice', 'writeBlanksQuestions', 'writeBlanksFill', 'writeBlanksForm']
-
-TOTAL_READING_PASSAGE_1_EXERCISES = 13
-TOTAL_READING_PASSAGE_2_EXERCISES = 13
-TOTAL_READING_PASSAGE_3_EXERCISES = 14
-
-TOTAL_LISTENING_SECTION_1_EXERCISES = 10
-TOTAL_LISTENING_SECTION_2_EXERCISES = 10
-TOTAL_LISTENING_SECTION_3_EXERCISES = 10
-TOTAL_LISTENING_SECTION_4_EXERCISES = 10
-
-LISTENING_MIN_TIMER_DEFAULT = 30
-WRITING_MIN_TIMER_DEFAULT = 60
-SPEAKING_MIN_TIMER_DEFAULT = 14
-
-BLACKLISTED_WORDS = ["jesus", "sex", "gay", "lesbian", "homosexual", "god", "angel", "pornography", "beer", "wine",
-                     "cocaine", "alcohol", "nudity", "lgbt", "casino", "gambling", "catholicism",
-                     "discrimination", "politics", "politic", "christianity", "islam", "christian", "christians",
-                     "jews", "jew", "discrimination", "discriminatory"]
-
-EN_US_VOICES = [
-    {'Gender': 'Female', 'Id': 'Salli', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Salli',
-     'SupportedEngines': ['neural', 'standard']},
-    {'Gender': 'Male', 'Id': 'Matthew', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Matthew',
-     'SupportedEngines': ['neural', 'standard']},
-    {'Gender': 'Female', 'Id': 'Kimberly', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Kimberly',
-     'SupportedEngines': ['neural', 'standard']},
-    {'Gender': 'Female', 'Id': 'Kendra', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Kendra',
-     'SupportedEngines': ['neural', 'standard']},
-    {'Gender': 'Male', 'Id': 'Justin', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Justin',
-     'SupportedEngines': ['neural', 'standard']},
-    {'Gender': 'Male', 'Id': 'Joey', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Joey',
-     'SupportedEngines': ['neural', 'standard']},
-    {'Gender': 'Female', 'Id': 'Joanna', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Joanna',
-     'SupportedEngines': ['neural', 'standard']},
-    {'Gender': 'Female', 'Id': 'Ivy', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Ivy',
-     'SupportedEngines': ['neural', 'standard']}]
-EN_GB_VOICES = [
-    {'Gender': 'Female', 'Id': 'Emma', 'LanguageCode': 'en-GB', 'LanguageName': 'British English', 'Name': 'Emma',
-     'SupportedEngines': ['neural', 'standard']},
-    {'Gender': 'Male', 'Id': 'Brian', 'LanguageCode': 'en-GB', 'LanguageName': 'British English', 'Name': 'Brian',
-     'SupportedEngines': ['neural', 'standard']},
-    {'Gender': 'Female', 'Id': 'Amy', 'LanguageCode': 'en-GB', 'LanguageName': 'British English', 'Name': 'Amy',
-     'SupportedEngines': ['neural', 'standard']}]
-EN_GB_WLS_VOICES = [
-    {'Gender': 'Male', 'Id': 'Geraint', 'LanguageCode': 'en-GB-WLS', 'LanguageName': 'Welsh English', 'Name': 'Geraint',
-     'SupportedEngines': ['standard']}]
-EN_AU_VOICES = [{'Gender': 'Male', 'Id': 'Russell', 'LanguageCode': 'en-AU', 'LanguageName': 'Australian English',
-                 'Name': 'Russell', 'SupportedEngines': ['standard']},
-                {'Gender': 'Female', 'Id': 'Nicole', 'LanguageCode': 'en-AU', 'LanguageName': 'Australian English',
-                 'Name': 'Nicole', 'SupportedEngines': ['standard']}]
-ALL_VOICES = EN_US_VOICES + EN_GB_VOICES + EN_GB_WLS_VOICES + EN_AU_VOICES
-
-NEURAL_EN_US_VOICES = [
-    {'Gender': 'Female', 'Id': 'Danielle', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Danielle',
-     'SupportedEngines': ['neural']},
-    {'Gender': 'Male', 'Id': 'Gregory', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Gregory',
-     'SupportedEngines': ['neural']},
-    {'Gender': 'Male', 'Id': 'Kevin', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Kevin',
-     'SupportedEngines': ['neural']},
-    {'Gender': 'Female', 'Id': 'Ruth', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Ruth',
-     'SupportedEngines': ['neural']},
-    {'Gender': 'Male', 'Id': 'Stephen', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Stephen',
-     'SupportedEngines': ['neural']}]
-NEURAL_EN_GB_VOICES = [
-    {'Gender': 'Male', 'Id': 'Arthur', 'LanguageCode': 'en-GB', 'LanguageName': 'British English', 'Name': 'Arthur',
-     'SupportedEngines': ['neural']}]
-NEURAL_EN_AU_VOICES = [
-    {'Gender': 'Female', 'Id': 'Olivia', 'LanguageCode': 'en-AU', 'LanguageName': 'Australian English',
-     'Name': 'Olivia', 'SupportedEngines': ['neural']}]
-NEURAL_EN_ZA_VOICES = [
-    {'Gender': 'Female', 'Id': 'Ayanda', 'LanguageCode': 'en-ZA', 'LanguageName': 'South African English',
-     'Name': 'Ayanda', 'SupportedEngines': ['neural']}]
-NEURAL_EN_NZ_VOICES = [
-    {'Gender': 'Female', 'Id': 'Aria', 'LanguageCode': 'en-NZ', 'LanguageName': 'New Zealand English', 'Name': 'Aria',
-     'SupportedEngines': ['neural']}]
-NEURAL_EN_IN_VOICES = [
-    {'Gender': 'Female', 'Id': 'Kajal', 'LanguageCode': 'en-IN', 'LanguageName': 'Indian English', 'Name': 'Kajal',
-     'SupportedEngines': ['neural']}]
-NEURAL_EN_IE_VOICES = [
-    {'Gender': 'Female', 'Id': 'Niamh', 'LanguageCode': 'en-IE', 'LanguageName': 'Irish English', 'Name': 'Niamh',
-     'SupportedEngines': ['neural']}]
-ALL_NEURAL_VOICES = NEURAL_EN_US_VOICES + NEURAL_EN_GB_VOICES + NEURAL_EN_AU_VOICES + NEURAL_EN_ZA_VOICES + NEURAL_EN_NZ_VOICES + NEURAL_EN_IE_VOICES
-
-MALE_VOICES = [item for item in ALL_VOICES if item.get('Gender') == 'Male']
-FEMALE_VOICES = [item for item in ALL_VOICES if item.get('Gender') == 'Female']
-
-MALE_NEURAL_VOICES = [item for item in ALL_NEURAL_VOICES if item.get('Gender') == 'Male']
-FEMALE_NEURAL_VOICES = [item for item in ALL_NEURAL_VOICES if item.get('Gender') == 'Female']
-
-difficulties = ["easy", "medium", "hard"]
-
-mti_topics = [
-    "Education",
-    "Technology",
-    "Environment",
-    "Health and Fitness",
-    "Engineering",
-    "Work and Careers",
-    "Travel and Tourism",
-    "Culture and Traditions",
-    "Social Issues",
-    "Arts and Entertainment",
-    "Climate Change",
-    "Social Media",
-    "Sustainable Development",
-    "Health Care",
-    "Immigration",
-    "Artificial Intelligence",
-    "Consumerism",
-    "Online Shopping",
-    "Energy",
-    "Oil and Gas",
-    "Poverty and Inequality",
-    "Cultural Diversity",
-    "Democracy and Governance",
-    "Mental Health",
-    "Ethics and Morality",
-    "Population Growth",
-    "Science and Innovation",
-    "Poverty Alleviation",
-    "Cybersecurity and Privacy",
-    "Human Rights",
-    "Social Justice",
-    "Food and Agriculture",
-    "Cyberbullying and Online Safety",
-    "Linguistic Diversity",
-    "Urbanization",
-    "Artificial Intelligence in Education",
-    "Youth Empowerment",
-    "Disaster Management",
-    "Mental Health Stigma",
-    "Internet Censorship",
-    "Sustainable Fashion",
-    "Indigenous Rights",
-    "Water Scarcity",
-    "Social Entrepreneurship",
-    "Privacy in the Digital Age",
-    "Sustainable Transportation",
-    "Gender Equality",
-    "Automation and Job Displacement",
-    "Digital Divide",
-    "Education Inequality"
-]
-topics = [
-    "Art and Creativity",
-    "History of Ancient Civilizations",
-    "Environmental Conservation",
-    "Space Exploration",
-    "Artificial Intelligence",
-    "Climate Change",
-    "World Religions",
-    "The Human Brain",
-    "Renewable Energy",
-    "Cultural Diversity",
-    "Modern Technology Trends",
-    "Sustainable Agriculture",
-    "Natural Disasters",
-    "Cybersecurity",
-    "Philosophy of Ethics",
-    "Robotics",
-    "Health and Wellness",
-    "Literature and Classics",
-    "World Geography",
-    "Social Media Impact",
-    "Food Sustainability",
-    "Economics and Markets",
-    "Human Evolution",
-    "Political Systems",
-    "Mental Health Awareness",
-    "Quantum Physics",
-    "Biodiversity",
-    "Education Reform",
-    "Animal Rights",
-    "The Industrial Revolution",
-    "Future of Work",
-    "Film and Cinema",
-    "Genetic Engineering",
-    "Climate Policy",
-    "Space Travel",
-    "Renewable Energy Sources",
-    "Cultural Heritage Preservation",
-    "Modern Art Movements",
-    "Sustainable Transportation",
-    "The History of Medicine",
-    "Artificial Neural Networks",
-    "Climate Adaptation",
-    "Philosophy of Existence",
-    "Augmented Reality",
-    "Yoga and Meditation",
-    "Literary Genres",
-    "World Oceans",
-    "Social Networking",
-    "Sustainable Fashion",
-    "Prehistoric Era",
-    "Democracy and Governance",
-    "Postcolonial Literature",
-    "Geopolitics",
-    "Psychology and Behavior",
-    "Nanotechnology",
-    "Endangered Species",
-    "Education Technology",
-    "Renaissance Art",
-    "Renewable Energy Policy",
-    "Modern Architecture",
-    "Climate Resilience",
-    "Artificial Life",
-    "Fitness and Nutrition",
-    "Classic Literature Adaptations",
-    "Ethical Dilemmas",
-    "Internet of Things (IoT)",
-    "Meditation Practices",
-    "Literary Symbolism",
-    "Marine Conservation",
-    "Social Justice Movements",
-    "Sustainable Tourism",
-    "Ancient Philosophy",
-    "Cold War Era",
-    "Behavioral Economics",
-    "Space Colonization",
-    "Clean Energy Initiatives",
-    "Cultural Exchange",
-    "Modern Sculpture",
-    "Climate Mitigation",
-    "Mindfulness",
-    "Literary Criticism",
-    "Wildlife Conservation",
-    "Renewable Energy Innovations",
-    "History of Mathematics",
-    "Human-Computer Interaction",
-    "Global Health",
-    "Cultural Appropriation",
-    "Traditional cuisine and culinary arts",
-    "Local music and dance traditions",
-    "History of the region and historical landmarks",
-    "Traditional crafts and artisanal skills",
-    "Wildlife and conservation efforts",
-    "Local sports and athletic competitions",
-    "Fashion trends and clothing styles",
-    "Education systems and advancements",
-    "Healthcare services and medical innovations",
-    "Family values and social dynamics",
-    "Travel destinations and tourist attractions",
-    "Environmental sustainability projects",
-    "Technological developments and innovations",
-    "Entrepreneurship and business ventures",
-    "Youth empowerment initiatives",
-    "Art exhibitions and cultural events",
-    "Philanthropy and community development projects"
-]
-
-two_people_scenarios = [
-    "Booking a table at a restaurant",
-    "Making a doctor's appointment",
-    "Asking for directions to a tourist attraction",
-    "Inquiring about public transportation options",
-    "Discussing weekend plans with a friend",
-    "Ordering food at a café",
-    "Renting a bicycle for a day",
-    "Arranging a meeting with a colleague",
-    "Talking to a real estate agent about renting an apartment",
-    "Discussing travel plans for an upcoming vacation",
-    "Checking the availability of a hotel room",
-    "Talking to a car rental service",
-    "Asking for recommendations at a library",
-    "Inquiring about opening hours at a museum",
-    "Discussing the weather forecast",
-    "Shopping for groceries",
-    "Renting a movie from a video store",
-    "Booking a flight ticket",
-    "Discussing a school assignment with a classmate",
-    "Making a reservation for a spa appointment",
-    "Talking to a customer service representative about a product issue",
-    "Discussing household chores with a family member",
-    "Planning a surprise party for a friend",
-    "Talking to a coworker about a project deadline",
-    "Inquiring about a gym membership",
-    "Discussing the menu options at a fast-food restaurant",
-    "Talking to a neighbor about a community event",
-    "Asking for help with computer problems",
-    "Discussing a recent sports game with a sports enthusiast",
-    "Talking to a pet store employee about buying a pet",
-    "Asking for information about a local farmer's market",
-    "Discussing the details of a home renovation project",
-    "Talking to a coworker about office supplies",
-    "Making plans for a family picnic",
-    "Inquiring about admission requirements at a university",
-    "Discussing the features of a new smartphone with a salesperson",
-    "Talking to a mechanic about car repairs",
-    "Making arrangements for a child's birthday party",
-    "Discussing a new diet plan with a nutritionist",
-    "Asking for information about a music concert",
-    "Talking to a hairdresser about getting a haircut",
-    "Inquiring about a language course at a language school",
-    "Discussing plans for a weekend camping trip",
-    "Talking to a bank teller about opening a new account",
-    "Ordering a drink at a coffee shop",
-    "Discussing a new book with a book club member",
-    "Talking to a librarian about library services",
-    "Asking for advice on finding a job",
-    "Discussing plans for a garden makeover with a landscaper",
-    "Talking to a travel agent about a cruise vacation",
-    "Inquiring about a fitness class at a gym",
-    "Ordering flowers for a special occasion",
-    "Discussing a new exercise routine with a personal trainer",
-    "Talking to a teacher about a child's progress in school",
-    "Asking for information about a local art exhibition",
-    "Discussing a home improvement project with a contractor",
-    "Talking to a babysitter about childcare arrangements",
-    "Making arrangements for a car service appointment",
-    "Inquiring about a photography workshop at a studio",
-    "Discussing plans for a family reunion with a relative",
-    "Talking to a tech support representative about computer issues",
-    "Asking for recommendations on pet grooming services",
-    "Discussing weekend plans with a significant other",
-    "Talking to a counselor about personal issues",
-    "Inquiring about a music lesson with a music teacher",
-    "Ordering a pizza for delivery",
-    "Making a reservation for a taxi",
-    "Discussing a new recipe with a chef",
-    "Talking to a fitness trainer about weight loss goals",
-    "Inquiring about a dance class at a dance studio",
-    "Ordering a meal at a food truck",
-    "Discussing plans for a weekend getaway with a partner",
-    "Talking to a florist about wedding flower arrangements",
-    "Asking for advice on home decorating",
-    "Discussing plans for a charity fundraiser event",
-    "Talking to a pet sitter about taking care of pets",
-    "Making arrangements for a spa day with a friend",
-    "Asking for recommendations on home improvement stores",
-    "Discussing weekend plans with a travel enthusiast",
-    "Talking to a car mechanic about car maintenance",
-    "Inquiring about a cooking class at a culinary school",
-    "Ordering a sandwich at a deli",
-    "Discussing plans for a family holiday party",
-    "Talking to a personal assistant about organizing tasks",
-    "Asking for information about a local theater production",
-    "Discussing a new DIY project with a home improvement expert",
-    "Talking to a wine expert about wine pairing",
-    "Making arrangements for a pet adoption",
-    "Asking for advice on planning a wedding"
-]
-
-social_monologue_contexts = [
-    "A guided tour of a historical museum",
-    "An introduction to a new city for tourists",
-    "An orientation session for new university students",
-    "A safety briefing for airline passengers",
-    "An explanation of the process of recycling",
-    "A lecture on the benefits of a healthy diet",
-    "A talk on the importance of time management",
-    "A monologue about wildlife conservation",
-    "An overview of local public transportation options",
-    "A presentation on the history of cinema",
-    "An introduction to the art of photography",
-    "A discussion about the effects of climate change",
-    "An overview of different types of cuisine",
-    "A lecture on the principles of financial planning",
-    "A monologue about sustainable energy sources",
-    "An explanation of the process of online shopping",
-    "A guided tour of a botanical garden",
-    "An introduction to a local wildlife sanctuary",
-    "A safety briefing for hikers in a national park",
-    "A talk on the benefits of physical exercise",
-    "A lecture on the principles of effective communication",
-    "A monologue about the impact of social media",
-    "An overview of the history of a famous landmark",
-    "An introduction to the world of fashion design",
-    "A discussion about the challenges of global poverty",
-    "An explanation of the process of organic farming",
-    "A presentation on the history of space exploration",
-    "An overview of traditional music from different cultures",
-    "A lecture on the principles of effective leadership",
-    "A monologue about the influence of technology",
-    "A guided tour of a famous archaeological site",
-    "An introduction to a local wildlife rehabilitation center",
-    "A safety briefing for visitors to a science museum",
-    "A talk on the benefits of learning a new language",
-    "A lecture on the principles of architectural design",
-    "A monologue about the impact of renewable energy",
-    "An explanation of the process of online banking",
-    "A presentation on the history of a famous art movement",
-    "An overview of traditional clothing from various regions",
-    "A lecture on the principles of sustainable agriculture",
-    "A discussion about the challenges of urban development",
-    "A monologue about the influence of social norms",
-    "A guided tour of a historical battlefield",
-    "An introduction to a local animal shelter",
-    "A safety briefing for participants in a charity run",
-    "A talk on the benefits of community involvement",
-    "A lecture on the principles of sustainable tourism",
-    "A monologue about the impact of alternative medicine",
-    "An explanation of the process of wildlife tracking",
-    "A presentation on the history of a famous inventor",
-    "An overview of traditional dance forms from different cultures",
-    "A lecture on the principles of ethical business practices",
-    "A discussion about the challenges of healthcare access",
-    "A monologue about the influence of cultural traditions",
-    "A guided tour of a famous lighthouse",
-    "An introduction to a local astronomy observatory",
-    "A safety briefing for participants in a team-building event",
-    "A talk on the benefits of volunteering",
-    "A lecture on the principles of wildlife protection",
-    "A monologue about the impact of space exploration",
-    "An explanation of the process of wildlife photography",
-    "A presentation on the history of a famous musician",
-    "An overview of traditional art forms from different cultures",
-    "A lecture on the principles of effective education",
-    "A discussion about the challenges of sustainable development",
-    "A monologue about the influence of cultural diversity",
-    "A guided tour of a famous national park",
-    "An introduction to a local marine conservation project",
-    "A safety briefing for participants in a hot air balloon ride",
-    "A talk on the benefits of cultural exchange programs",
-    "A lecture on the principles of wildlife conservation",
-    "A monologue about the impact of technological advancements",
-    "An explanation of the process of wildlife rehabilitation",
-    "A presentation on the history of a famous explorer",
-    "A lecture on the principles of effective marketing",
-    "A discussion about the challenges of environmental sustainability",
-    "A monologue about the influence of social entrepreneurship",
-    "A guided tour of a famous historical estate",
-    "An introduction to a local marine life research center",
-    "A safety briefing for participants in a zip-lining adventure",
-    "A talk on the benefits of cultural preservation",
-    "A lecture on the principles of wildlife ecology",
-    "A monologue about the impact of space technology",
-    "An explanation of the process of wildlife conservation",
-    "A presentation on the history of a famous scientist",
-    "An overview of traditional crafts and artisans from different cultures",
-    "A lecture on the principles of effective intercultural communication"
-]
-
-four_people_scenarios = [
-    "A university lecture on history",
-    "A physics class discussing Newton's laws",
-    "A medical school seminar on anatomy",
-    "A training session on computer programming",
-    "A business school lecture on marketing strategies",
-    "A chemistry lab experiment and discussion",
-    "A language class practicing conversational skills",
-    "A workshop on creative writing techniques",
-    "A high school math lesson on calculus",
-    "A training program for customer service representatives",
-    "A lecture on environmental science and sustainability",
-    "A psychology class exploring human behavior",
-    "A music theory class analyzing compositions",
-    "A nursing school simulation for patient care",
-    "A computer science class on algorithms",
-    "A workshop on graphic design principles",
-    "A law school lecture on constitutional law",
-    "A geology class studying rock formations",
-    "A vocational training program for electricians",
-    "A history seminar focusing on ancient civilizations",
-    "A biology class dissecting specimens",
-    "A financial literacy course for adults",
-    "A literature class discussing classic novels",
-    "A training session for emergency response teams",
-    "A sociology lecture on social inequality",
-    "An art class exploring different painting techniques",
-    "A medical school seminar on diagnosis",
-    "A programming bootcamp teaching web development",
-    "An economics class analyzing market trends",
-    "A chemistry lab experiment on chemical reactions",
-    "A language class practicing pronunciation",
-    "A workshop on public speaking skills",
-    "A high school physics lesson on electromagnetism",
-    "A training program for IT professionals",
-    "A lecture on climate change and its effects",
-    "A psychology class studying cognitive psychology",
-    "A music class composing original songs",
-    "A nursing school simulation for patient assessment",
-    "A computer science class on data structures",
-    "A workshop on 3D modeling and animation",
-    "A law school lecture on contract law",
-    "A geography class examining world maps",
-    "A vocational training program for plumbers",
-    "A history seminar discussing revolutions",
-    "A biology class exploring genetics",
-    "A financial literacy course for teens",
-    "A literature class analyzing poetry",
-    "A training session for public speaking coaches",
-    "A sociology lecture on cultural diversity",
-    "An art class creating sculptures",
-    "A medical school seminar on surgical techniques",
-    "A programming bootcamp teaching app development",
-    "An economics class on global trade policies",
-    "A chemistry lab experiment on chemical bonding",
-    "A language class discussing idiomatic expressions",
-    "A workshop on conflict resolution",
-    "A high school biology lesson on evolution",
-    "A training program for project managers",
-    "A lecture on renewable energy sources",
-    "A psychology class on abnormal psychology",
-    "A music class rehearsing for a performance",
-    "A nursing school simulation for emergency response",
-    "A computer science class on cybersecurity",
-    "A workshop on digital marketing strategies",
-    "A law school lecture on intellectual property",
-    "A geology class analyzing seismic activity",
-    "A vocational training program for carpenters",
-    "A history seminar on the Renaissance",
-    "A chemistry class synthesizing compounds",
-    "A financial literacy course for seniors",
-    "A literature class interpreting Shakespearean plays",
-    "A training session for negotiation skills",
-    "A sociology lecture on urbanization",
-    "An art class creating digital art",
-    "A medical school seminar on patient communication",
-    "A programming bootcamp teaching mobile app development",
-    "An economics class on fiscal policy",
-    "A physics lab experiment on electromagnetism",
-    "A language class on cultural immersion",
-    "A workshop on time management",
-    "A high school chemistry lesson on stoichiometry",
-    "A training program for HR professionals",
-    "A lecture on space exploration and astronomy",
-    "A psychology class on human development",
-    "A music class practicing for a recital",
-    "A nursing school simulation for triage",
-    "A computer science class on web development frameworks",
-    "A workshop on team-building exercises",
-    "A law school lecture on criminal law",
-    "A geography class studying world cultures",
-    "A vocational training program for HVAC technicians",
-    "A history seminar on ancient civilizations",
-    "A biology class examining ecosystems",
-    "A financial literacy course for entrepreneurs",
-    "A literature class analyzing modern literature",
-    "A training session for leadership skills",
-    "A sociology lecture on gender studies",
-    "An art class exploring multimedia art",
-    "A medical school seminar on patient diagnosis",
-    "A programming bootcamp teaching software architecture"
-]
-
-academic_subjects = [
-    "Astrophysics",
-    "Microbiology",
-    "Political Science",
-    "Environmental Science",
-    "Literature",
-    "Biochemistry",
-    "Sociology",
-    "Art History",
-    "Geology",
-    "Economics",
-    "Psychology",
-    "History of Architecture",
-    "Linguistics",
-    "Neurobiology",
-    "Anthropology",
-    "Quantum Mechanics",
-    "Urban Planning",
-    "Philosophy",
-    "Marine Biology",
-    "International Relations",
-    "Medieval History",
-    "Geophysics",
-    "Finance",
-    "Educational Psychology",
-    "Graphic Design",
-    "Paleontology",
-    "Macroeconomics",
-    "Cognitive Psychology",
-    "Renaissance Art",
-    "Archaeology",
-    "Microeconomics",
-    "Social Psychology",
-    "Contemporary Art",
-    "Meteorology",
-    "Political Philosophy",
-    "Space Exploration",
-    "Cognitive Science",
-    "Classical Music",
-    "Oceanography",
-    "Public Health",
-    "Gender Studies",
-    "Baroque Art",
-    "Volcanology",
-    "Business Ethics",
-    "Music Composition",
-    "Environmental Policy",
-    "Media Studies",
-    "Ancient History",
-    "Seismology",
-    "Marketing",
-    "Human Development",
-    "Modern Art",
-    "Astronomy",
-    "International Law",
-    "Developmental Psychology",
-    "Film Studies",
-    "American History",
-    "Soil Science",
-    "Entrepreneurship",
-    "Clinical Psychology",
-    "Contemporary Dance",
-    "Space Physics",
-    "Political Economy",
-    "Cognitive Neuroscience",
-    "20th Century Literature",
-    "Public Administration",
-    "European History",
-    "Atmospheric Science",
-    "Supply Chain Management",
-    "Social Work",
-    "Japanese Literature",
-    "Planetary Science",
-    "Labor Economics",
-    "Industrial-Organizational Psychology",
-    "French Philosophy",
-    "Biogeochemistry",
-    "Strategic Management",
-    "Educational Sociology",
-    "Postmodern Literature",
-    "Public Relations",
-    "Middle Eastern History",
-    "Oceanography",
-    "International Development",
-    "Human Resources Management",
-    "Educational Leadership",
-    "Russian Literature",
-    "Quantum Chemistry",
-    "Environmental Economics",
-    "Environmental Psychology",
-    "Ancient Philosophy",
-    "Immunology",
-    "Comparative Politics",
-    "Child Development",
-    "Fashion Design",
-    "Geological Engineering",
-    "Macroeconomic Policy",
-    "Media Psychology",
-    "Byzantine Art",
-    "Ecology",
-    "International Business"
-]

helper/exam_variant.py

@@ -1,6 +0,0 @@
-from enum import Enum
-
-
-class ExamVariant(Enum):
-    FULL = "full"
-    PARTIAL = "partial"

helper/file_helper.py

@@ -1,17 +0,0 @@
-import datetime
-import os
-from pathlib import Path
-
-
-def delete_files_older_than_one_day(directory):
-    current_time = datetime.datetime.now()
-
-    for entry in os.scandir(directory):
-        if entry.is_file():
-            file_path = Path(entry)
-            file_name = file_path.name
-            file_modified_time = datetime.datetime.fromtimestamp(file_path.stat().st_mtime)
-            time_difference = current_time - file_modified_time
-            if time_difference.days > 1 and "placeholder" not in file_name:
-                file_path.unlink()
-                print(f"Deleted file: {file_path}")

helper/firebase_helper.py

@@ -1,87 +0,0 @@
-import logging
-
-from firebase_admin import firestore
-from google.cloud import storage
-
-
-def download_firebase_file(bucket_name, source_blob_name, destination_file_name):
-    # Downloads a file from Firebase Storage.
-    storage_client = storage.Client()
-    bucket = storage_client.bucket(bucket_name)
-    blob = bucket.blob(source_blob_name)
-    blob.download_to_filename(destination_file_name)
-    logging.info(f"File downloaded to {destination_file_name}")
-    return destination_file_name
-
-
-def upload_file_firebase(bucket_name, destination_blob_name, source_file_name):
-    # Uploads a file to Firebase Storage.
-    storage_client = storage.Client()
-    bucket = storage_client.bucket(bucket_name)
-    try:
-        blob = bucket.blob(destination_blob_name)
-        blob.upload_from_filename(source_file_name)
-        logging.info(f"File uploaded to {destination_blob_name}")
-        return True
-    except Exception as e:
-        import app
-        app.app.logger.error("Error uploading file to Google Cloud Storage: " + str(e))
-        return False
-
-
-def upload_file_firebase_get_url(bucket_name, destination_blob_name, source_file_name):
-    # Uploads a file to Firebase Storage.
-    storage_client = storage.Client()
-    bucket = storage_client.bucket(bucket_name)
-    try:
-        blob = bucket.blob(destination_blob_name)
-        blob.upload_from_filename(source_file_name)
-        logging.info(f"File uploaded to {destination_blob_name}")
-
-        # Make the file public
-        blob.make_public()
-
-        # Get the public URL
-        url = blob.public_url
-        return url
-    except Exception as e:
-        import app
-        app.app.logger.error("Error uploading file to Google Cloud Storage: " + str(e))
-        return None
-
-
-def save_to_db(collection: str, item):
-    db = firestore.client()
-    collection_ref = db.collection(collection)
-    (update_time, document_ref) = collection_ref.add(item)
-    if document_ref:
-        logging.info(f"Document added with ID: {document_ref.id}")
-        return (True, document_ref.id)
-    else:
-        return (False, None)
-
-
-def save_to_db_with_id(collection: str, item, id: str):
-    db = firestore.client()
-    collection_ref = db.collection(collection)
-    # Reference to the specific document with the desired ID
-    document_ref = collection_ref.document(id)
-    # Set the data to the document
-    document_ref.set(item)
-    if document_ref:
-        logging.info(f"Document added with ID: {document_ref.id}")
-        return (True, document_ref.id)
-    else:
-        return (False, None)
-
-
-def get_all(collection: str):
-    db = firestore.client()
-    collection_ref = db.collection(collection)
-
-    all_exercises = (
-        collection_ref
-        .get()
-    )
-
-    return all_exercises

helper/generate_jwt.py

@@ -1,17 +0,0 @@
-import os
-
-import jwt
-from dotenv import load_dotenv
-
-load_dotenv()
-
-# Define the payload (data to be included in the token)
-payload = {'sub': 'test'}
-
-# Define the secret key
-secret_key = os.getenv("JWT_SECRET_KEY")
-
-# Generate the JWT
-jwt_token = jwt.encode(payload, secret_key, algorithm='HS256')
-
-print(jwt_token)

helper/generate_jwt_secret.py

@@ -1,5 +0,0 @@
-import secrets
-
-jwt_secret_key = secrets.token_hex(32)
-
-print(jwt_secret_key)

helper/heygen_api.py

@@ -1,172 +0,0 @@
-import os
-import random
-import time
-
-import requests
-from dotenv import load_dotenv
-
-import app
-from helper.constants import *
-from helper.firebase_helper import upload_file_firebase_get_url, save_to_db_with_id
-from heygen.AvatarEnum import AvatarEnum
-
-load_dotenv()
-
-# Get HeyGen token
-TOKEN = os.getenv("HEY_GEN_TOKEN")
-FIREBASE_BUCKET = os.getenv('FIREBASE_BUCKET')
-
-# POST TO CREATE VIDEO
-CREATE_VIDEO_URL = 'https://api.heygen.com/v1/template.generate'
-GET_VIDEO_URL = 'https://api.heygen.com/v1/video_status.get'
-POST_HEADER = {
-    'X-Api-Key': TOKEN,
-    'Content-Type': 'application/json'
-}
-GET_HEADER = {
-    'X-Api-Key': TOKEN
-}
-
-
-def create_videos_and_save_to_db(exercises, template, id):
-    # Speaking 1
-    # Using list comprehension to find the element with the desired value in the 'type' field
-    found_exercises_1 = [element for element in exercises if element.get('type') == 1]
-    # Check if any elements were found
-    if found_exercises_1:
-        exercise_1 = found_exercises_1[0]
-        app.app.logger.info('Creating video for speaking part 1')
-        sp1_result = create_video(exercise_1["question"], random.choice(list(AvatarEnum)))
-        if sp1_result is not None:
-            sound_file_path = VIDEO_FILES_PATH + sp1_result
-            firebase_file_path = FIREBASE_SPEAKING_VIDEO_FILES_PATH + sp1_result
-            url = upload_file_firebase_get_url(FIREBASE_BUCKET, firebase_file_path, sound_file_path)
-            sp1_video_path = firebase_file_path
-            sp1_video_url = url
-            template["exercises"][0]["text"] = exercise_1["question"]
-            template["exercises"][0]["title"] = exercise_1["topic"]
-            template["exercises"][0]["video_url"] = sp1_video_url
-            template["exercises"][0]["video_path"] = sp1_video_path
-        else:
-            app.app.logger.error("Failed to create video for part 1 question: " + exercise_1["question"])
-
-    # Speaking 2
-    # Using list comprehension to find the element with the desired value in the 'type' field
-    found_exercises_2 = [element for element in exercises if element.get('type') == 2]
-    # Check if any elements were found
-    if found_exercises_2:
-        exercise_2 = found_exercises_2[0]
-        app.app.logger.info('Creating video for speaking part 2')
-        sp2_result = create_video(exercise_2["question"], random.choice(list(AvatarEnum)))
-        if sp2_result is not None:
-            sound_file_path = VIDEO_FILES_PATH + sp2_result
-            firebase_file_path = FIREBASE_SPEAKING_VIDEO_FILES_PATH + sp2_result
-            url = upload_file_firebase_get_url(FIREBASE_BUCKET, firebase_file_path, sound_file_path)
-            sp2_video_path = firebase_file_path
-            sp2_video_url = url
-            template["exercises"][1]["prompts"] = exercise_2["prompts"]
-            template["exercises"][1]["text"] = exercise_2["question"]
-            template["exercises"][1]["title"] = exercise_2["topic"]
-            template["exercises"][1]["video_url"] = sp2_video_url
-            template["exercises"][1]["video_path"] = sp2_video_path
-        else:
-            app.app.logger.error("Failed to create video for part 2 question: " + exercise_2["question"])
-
-    # Speaking 3
-    # Using list comprehension to find the element with the desired value in the 'type' field
-    found_exercises_3 = [element for element in exercises if element.get('type') == 3]
-    # Check if any elements were found
-    if found_exercises_3:
-        exercise_3 = found_exercises_3[0]
-        sp3_questions = []
-        avatar = random.choice(list(AvatarEnum))
-        app.app.logger.info('Creating videos for speaking part 3')
-        for question in exercise_3["questions"]:
-            result = create_video(question, avatar)
-            if result is not None:
-                sound_file_path = VIDEO_FILES_PATH + result
-                firebase_file_path = FIREBASE_SPEAKING_VIDEO_FILES_PATH + result
-                url = upload_file_firebase_get_url(FIREBASE_BUCKET, firebase_file_path, sound_file_path)
-                video = {
-                    "text": question,
-                    "video_path": firebase_file_path,
-                    "video_url": url
-                }
-                sp3_questions.append(video)
-            else:
-                app.app.logger.error("Failed to create video for part 3 question: " + question)
-        template["exercises"][2]["prompts"] = sp3_questions
-        template["exercises"][2]["title"] = exercise_3["topic"]
-
-    if not found_exercises_3:
-        template["exercises"].pop(2)
-    if not found_exercises_2:
-        template["exercises"].pop(1)
-    if not found_exercises_1:
-        template["exercises"].pop(0)
-
-    save_to_db_with_id("speaking", template, id)
-    app.app.logger.info('Saved speaking to DB with id ' + id + " : " + str(template))
-
-
-def create_video(text, avatar):
-    # POST TO CREATE VIDEO
-    create_video_url = 'https://api.heygen.com/v2/template/' + avatar + '/generate'
-    data = {
-        "test": False,
-        "caption": False,
-        "title": "video_title",
-        "variables": {
-            "script_here": {
-                "name": "script_here",
-                "type": "text",
-                "properties": {
-                    "content": text
-                }
-            }
-        }
-    }
-    response = requests.post(create_video_url, headers=POST_HEADER, json=data)
-    app.app.logger.info(response.status_code)
-    app.app.logger.info(response.json())
-
-    # GET TO CHECK STATUS AND GET VIDEO WHEN READY
-    video_id = response.json()["data"]["video_id"]
-    params = {
-        'video_id': response.json()["data"]["video_id"]
-    }
-    response = {}
-    status = "processing"
-    error = None
-
-    while status != "completed" and error is None:
-        response = requests.get(GET_VIDEO_URL, headers=GET_HEADER, params=params)
-        response_data = response.json()
-
-        status = response_data["data"]["status"]
-        error = response_data["data"]["error"]
-
-        if status != "completed" and error is None:
-            app.app.logger.info(f"Status: {status}")
-            time.sleep(10)  # Wait for 10 second before the next request
-
-    app.app.logger.info(response.status_code)
-    app.app.logger.info(response.json())
-
-    # DOWNLOAD VIDEO
-    download_url = response.json()['data']['video_url']
-    output_directory = 'download-video/'
-    output_filename = video_id + '.mp4'
-
-    response = requests.get(download_url)
-
-    if response.status_code == 200:
-        os.makedirs(output_directory, exist_ok=True)  # Create the directory if it doesn't exist
-        output_path = os.path.join(output_directory, output_filename)
-        with open(output_path, 'wb') as f:
-            f.write(response.content)
-        app.app.logger.info(f"File '{output_filename}' downloaded successfully.")
-        return output_filename
-    else:
-        app.app.logger.error(f"Failed to download file. Status code: {response.status_code}")
-        return None

helper/openai_interface.py

@@ -1,246 +0,0 @@
-import json
-import os
-import re
-
-from openai import OpenAI
-from dotenv import load_dotenv
-
-from helper.constants import BLACKLISTED_WORDS, GPT_3_5_TURBO
-from helper.token_counter import count_tokens
-
-load_dotenv()
-client = OpenAI(api_key=os.getenv('OPENAI_API_KEY'))
-
-MAX_TOKENS = 4097
-TOP_P = 0.9
-FREQUENCY_PENALTY = 0.5
-
-TRY_LIMIT = 2
-try_count = 0
-
-# GRADING SUMMARY
-chat_config = {'max_tokens': 1000, 'temperature': 0.2}
-section_keys = ['reading', 'listening', 'writing', 'speaking', 'level']
-grade_top_limit = 9
-
-tools = [{
-    "type": "function",
-    "function": {
-        "name": "save_evaluation_and_suggestions",
-        "description": "Saves the evaluation and suggestions requested by input.",
-        "parameters": {
-            "type": "object",
-            "properties": {
-                "evaluation": {
-                    "type": "string",
-                    "description": "A comment on the IELTS section grade obtained in the specific section and what it could mean without suggestions.",
-                },
-                "suggestions": {
-                    "type": "string",
-                    "description": "A small paragraph text with suggestions on how to possibly get a better grade than the one obtained.",
-                },
-                "bullet_points": {
-                    "type": "string",
-                    "description": "Text with four bullet points to improve the english speaking ability. Only include text for the bullet points separated by a paragraph. ",
-                },
-            },
-            "required": ["evaluation", "suggestions"],
-        },
-    }
-}]
-
-
-def check_fields(obj, fields):
-    return all(field in obj for field in fields)
-
-
-def make_openai_call(model, messages, token_count, fields_to_check, temperature):
-    global try_count
-    result = client.chat.completions.create(
-        model=model,
-        max_tokens=int(MAX_TOKENS - token_count - 300),
-        temperature=float(temperature),
-        messages=messages,
-        response_format={"type": "json_object"}
-    )
-    result = result.choices[0].message.content
-
-    found_blacklisted_word = get_found_blacklisted_words(result)
-
-    if found_blacklisted_word is not None and try_count < TRY_LIMIT:
-        from app import app
-        app.logger.warning("Result contains blacklisted words: " + str(found_blacklisted_word))
-        try_count = try_count + 1
-        return make_openai_call(model, messages, token_count, fields_to_check, temperature)
-    elif found_blacklisted_word is not None and try_count >= TRY_LIMIT:
-        return ""
-
-    if fields_to_check is None:
-        return json.loads(result)
-
-    if check_fields(result, fields_to_check) is False and try_count < TRY_LIMIT:
-        try_count = try_count + 1
-        return make_openai_call(model, messages, token_count, fields_to_check, temperature)
-    elif try_count >= TRY_LIMIT:
-        try_count = 0
-        return json.loads(result)
-    else:
-        try_count = 0
-        return json.loads(result)
-
-
-# GRADING SUMMARY
-def calculate_grading_summary(body):
-    extracted_sections = extract_existing_sections_from_body(body, section_keys)
-
-    ret = []
-
-    for section in extracted_sections:
-        openai_response_dict = calculate_section_grade_summary(section)
-
-        ret = ret + [{'code': section['code'], 'name': section['name'], 'grade': section['grade'],
-                      'evaluation': openai_response_dict['evaluation'],
-                      'suggestions': openai_response_dict['suggestions'],
-                      'bullet_points': parse_bullet_points(openai_response_dict['bullet_points'], section['grade'])}]
-
-    return {'sections': ret}
-
-
-def calculate_section_grade_summary(section):
-    messages = [
-        {
-            "role": "user",
-            "content": "You are a IELTS test section grade evaluator. You will receive a IELTS test section name and the grade obtained in the section. You should offer a evaluation comment on this grade and separately suggestions on how to possibly get a better grade.",
-        },
-        {
-            "role": "user",
-            "content": "Section: " + str(section['name']) + " Grade: " + str(section['grade']),
-        },
-        {"role": "user", "content": "Speak in third person."},
-        {"role": "user",
-         "content": "Don't offer suggestions in the evaluation comment. Only in the suggestions section."},
-        {"role": "user",
-         "content": "Your evaluation comment on the grade should enunciate the grade, be insightful, be speculative, be one paragraph long. "},
-        {"role": "user", "content": "Please save the evaluation comment and suggestions generated."},
-        {"role": "user", "content": f"Offer bullet points to improve the english {str(section['name'])} ability."},
-    ]
-
-    if section['code'] == "level":
-        messages[2:2] = [{
-            "role": "user",
-            "content": "This section is comprised of multiple choice questions that measure the user's overall english level. These multiple choice questions are about knowledge on vocabulary, syntax, grammar rules, and contextual usage. The grade obtained measures the ability in these areas and english language overall."
-        }]
-    elif section['code'] == "speaking":
-        messages[2:2] = [{"role": "user",
-                          "content": "This section is s designed to assess the English language proficiency of individuals who want to study or work in English-speaking countries. The speaking section evaluates a candidate's ability to communicate effectively in spoken English."}]
-
-    res = client.chat.completions.create(
-        model="gpt-3.5-turbo",
-        max_tokens=chat_config['max_tokens'],
-        temperature=chat_config['temperature'],
-        tools=tools,
-        messages=messages)
-
-    return parse_openai_response(res)
-
-
-def parse_openai_response(response):
-    if 'choices' in response and len(response['choices']) > 0 and 'message' in response['choices'][
-        0] and 'tool_calls' in response['choices'][0]['message'] and isinstance(
-        response['choices'][0]['message']['tool_calls'], list) and len(
-        response['choices'][0]['message']['tool_calls']) > 0 and \
-            response['choices'][0]['message']['tool_calls'][0]['function']['arguments']:
-        return json.loads(response['choices'][0]['message']['tool_calls'][0]['function']['arguments'])
-    else:
-        return {'evaluation': "", 'suggestions': "", 'bullet_points': []}
-
-
-def extract_existing_sections_from_body(my_dict, keys_to_extract):
-    if 'sections' in my_dict and isinstance(my_dict['sections'], list) and len(my_dict['sections']) > 0:
-        return list(filter(
-            lambda item: 'code' in item and item['code'] in keys_to_extract and 'grade' in item and 'name' in item,
-            my_dict['sections']))
-
-
-def parse_bullet_points(bullet_points_str, grade):
-    max_grade_for_suggestions = 9
-    if isinstance(bullet_points_str, str) and grade < max_grade_for_suggestions:
-        # Split the string by '\n'
-        lines = bullet_points_str.split('\n')
-
-        # Remove '-' and trim whitespace from each line
-        cleaned_lines = [line.replace('-', '').strip() for line in lines]
-
-        # Add '.' to lines that don't end with it
-        return [line + '.' if line and not line.endswith('.') else line for line in cleaned_lines]
-    else:
-        return []
-
-
-def get_fixed_text(text):
-    messages = [
-        {"role": "system", "content": ('You are a helpful assistant designed to output JSON on this format: '
-                                       '{"fixed_text": "fixed test with no misspelling errors"}')
-         },
-        {"role": "user", "content": (
-                'Fix the errors in the given text and put it in a JSON. Do not complete the answer, only replace what '
-                'is wrong. \n The text: "' + text + '"')
-         }
-    ]
-    token_count = count_total_tokens(messages)
-    response = make_openai_call(GPT_3_5_TURBO, messages, token_count, ["fixed_text"], 0.2)
-    return response["fixed_text"]
-
-
-def get_speaking_corrections(text):
-    messages = [
-        {"role": "system", "content": ('You are a helpful assistant designed to output JSON on this format: '
-                                       '{"fixed_text": "fixed transcription with no misspelling errors"}')
-         },
-        {"role": "user", "content": (
-                'Fix the errors in the provided transcription and put it in a JSON. Do not complete the answer, only '
-                'replace what is wrong. \n The text: "' + text + '"')
-         }
-    ]
-    token_count = count_total_tokens(messages)
-    response = make_openai_call(GPT_3_5_TURBO, messages, token_count, ["fixed_text"], 0.2)
-    return response["fixed_text"]
-
-
-def has_blacklisted_words(text: str):
-    text_lower = text.lower()
-    return any(word in text_lower for word in BLACKLISTED_WORDS)
-
-def get_found_blacklisted_words(text: str):
-    text_lower = text.lower()
-    for word in BLACKLISTED_WORDS:
-        if re.search(r'\b' + re.escape(word) + r'\b', text_lower):
-            return word
-    return None
-
-def remove_special_characters_from_beginning(string):
-    cleaned_string = string.lstrip('\n')
-    if string.startswith("'") or string.startswith('"'):
-        cleaned_string = string[1:]
-    if cleaned_string.endswith('"'):
-        return cleaned_string[:-1]
-    else:
-        return cleaned_string
-
-
-def replace_expression_in_object(obj, expression, replacement):
-    if isinstance(obj, dict):
-        for key in obj:
-            if isinstance(obj[key], str):
-                obj[key] = obj[key].replace(expression, replacement)
-            elif isinstance(obj[key], list):
-                obj[key] = [replace_expression_in_object(item, expression, replacement) for item in obj[key]]
-            elif isinstance(obj[key], dict):
-                obj[key] = replace_expression_in_object(obj[key], expression, replacement)
-    return obj
-
-def count_total_tokens(messages):
-    total_tokens = 0
-    for message in messages:
-        total_tokens += count_tokens(message["content"])["n_tokens"]
-    return total_tokens

helper/speech_to_text_helper.py

@@ -1,129 +0,0 @@
-import os
-import random
-
-import boto3
-import nltk
-import whisper
-
-nltk.download('words')
-from nltk.corpus import words
-from helper.constants import *
-
-
-def speech_to_text(file_path):
-    if os.path.exists(file_path):
-        model = whisper.load_model("base")
-        result = model.transcribe(file_path, fp16=False, language='English', verbose=False)
-        return result["text"]
-    else:
-        print("File not found:", file_path)
-        raise Exception("File " + file_path + " not found.")
-
-
-def text_to_speech(text: str, file_name: str):
-    # Initialize the Amazon Polly client
-    client = boto3.client(
-        'polly',
-        region_name='eu-west-1',
-        aws_access_key_id=os.getenv("AWS_ACCESS_KEY_ID"),
-        aws_secret_access_key=os.getenv("AWS_SECRET_ACCESS_KEY")
-    )
-    voice = random.choice(ALL_NEURAL_VOICES)['Id']
-    # Initialize an empty list to store audio segments
-    audio_segments = []
-    for part in divide_text(text):
-        tts_response = client.synthesize_speech(
-            Engine="neural",
-            Text=part,
-            OutputFormat="mp3",
-            VoiceId=voice
-        )
-        audio_segments.append(tts_response['AudioStream'].read())
-
-    # Add finish message
-    audio_segments.append(client.synthesize_speech(
-        Engine="neural",
-        Text="This audio recording, for the listening exercise, has finished.",
-        OutputFormat="mp3",
-        VoiceId="Stephen"
-    )['AudioStream'].read())
-
-    # Combine the audio segments into a single audio file
-    combined_audio = b"".join(audio_segments)
-    # Save the combined audio to a single file
-    with open(file_name, "wb") as f:
-        f.write(combined_audio)
-
-    print("Speech segments saved to " + file_name)
-
-
-def conversation_text_to_speech(conversation: list, file_name: str):
-    # Initialize the Amazon Polly client
-    client = boto3.client(
-        'polly',
-        region_name='eu-west-1',
-        aws_access_key_id=os.getenv("AWS_ACCESS_KEY_ID"),
-        aws_secret_access_key=os.getenv("AWS_SECRET_ACCESS_KEY")
-    )
-    # Initialize an empty list to store audio segments
-    audio_segments = []
-    # Iterate through the text segments, convert to audio segments, and store them
-    for segment in conversation:
-        response = client.synthesize_speech(
-            Engine="neural",
-            Text=segment["text"],
-            OutputFormat="mp3",
-            VoiceId=segment["voice"]
-        )
-        audio_segments.append(response['AudioStream'].read())
-
-    # Add finish message
-    audio_segments.append(client.synthesize_speech(
-        Engine="neural",
-        Text="This audio recording, for the listening exercise, has finished.",
-        OutputFormat="mp3",
-        VoiceId="Stephen"
-    )['AudioStream'].read())
-
-    # Combine the audio segments into a single audio file
-    combined_audio = b"".join(audio_segments)
-    # Save the combined audio to a single file
-    with open(file_name, "wb") as f:
-        f.write(combined_audio)
-
-    print("Speech segments saved to " + file_name)
-
-
-def has_words(text: str):
-    english_words = set(words.words())
-    words_in_input = text.split()
-    return any(word.lower() in english_words for word in words_in_input)
-
-
-def has_x_words(text: str, quantity):
-    english_words = set(words.words())
-    words_in_input = text.split()
-    english_word_count = sum(1 for word in words_in_input if word.lower() in english_words)
-    return english_word_count >= quantity
-
-
-def divide_text(text, max_length=3000):
-    if len(text) <= max_length:
-        return [text]
-
-    divisions = []
-    current_position = 0
-
-    while current_position < len(text):
-        next_position = min(current_position + max_length, len(text))
-        next_period_position = text.rfind('.', current_position, next_position)
-
-        if next_period_position != -1 and next_period_position > current_position:
-            divisions.append(text[current_position:next_period_position + 1])
-            current_position = next_period_position + 1
-        else:
-            # If no '.' found in the next chunk, split at max_length
-            divisions.append(text[current_position:next_position])
-            current_position = next_position
-
-    return divisions

heygen/AvatarEnum.py

@@ -1,11 +0,0 @@
-from enum import Enum
-
-
-class AvatarEnum(Enum):
-    MATTHEW_NOAH = "5912afa7c77c47d3883af3d874047aaf"
-    VERA_CERISE = "9e58d96a383e4568a7f1e49df549e0e4"
-    EDWARD_TONY = "d2cdd9c0379a4d06ae2afb6e5039bd0c"
-    TANYA_MOLLY = "045cb5dcd00042b3a1e4f3bc1c12176b"
-    KAYLA_ABBI = "1ae1e5396cc444bfad332155fdb7a934"
-    JEROME_RYAN = "0ee6aa7cc1084063a630ae514fccaa31"
-    TYLER_CHRISTOPHER = "5772cff935844516ad7eeff21f839e43"

ielts_be/__init__.py

@@ -0,0 +1,156 @@
+import json
+import os
+import pathlib
+import logging.config
+import logging.handlers
+
+import aioboto3
+import contextlib
+from contextlib import asynccontextmanager
+from collections import defaultdict
+from typing import List
+from http import HTTPStatus
+
+import httpx
+from fastapi import FastAPI, Request
+from fastapi.encoders import jsonable_encoder
+from fastapi.exceptions import RequestValidationError
+from fastapi.middleware import Middleware
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import JSONResponse
+
+import nltk
+from starlette import status
+
+from ielts_be.api import router
+from ielts_be.configs import DependencyInjector
+from ielts_be.exceptions import CustomException
+from ielts_be.middlewares import AuthenticationMiddleware, AuthBackend
+from ielts_be.services.impl import OpenAIWhisper
+
+
+@asynccontextmanager
+async def lifespan(_app: FastAPI):
+    """
+        Startup and Shutdown logic is in this lifespan method
+
+        https://fastapi.tiangolo.com/advanced/events/
+    """
+
+    # NLTK required datasets download
+    nltk.download('words')
+    nltk.download("punkt")
+
+    # AWS Polly client instantiation
+    context_stack = contextlib.AsyncExitStack()
+    session = aioboto3.Session()
+    polly_client = await context_stack.enter_async_context(
+        session.client(
+            'polly',
+            region_name='eu-west-1',
+            aws_secret_access_key=os.getenv("AWS_SECRET_ACCESS_KEY"),
+            aws_access_key_id=os.getenv("AWS_ACCESS_KEY_ID")
+        )
+    )
+
+    http_client = httpx.AsyncClient()
+    stt = OpenAIWhisper()
+
+    DependencyInjector(
+        polly_client,
+        http_client,
+        stt
+    ).inject()
+
+    # Setup logging
+    config_file = pathlib.Path("./ielts_be/configs/logging/logging_config.json")
+    with open(config_file) as f_in:
+        config = json.load(f_in)
+
+    logging.config.dictConfig(config)
+
+    yield
+
+    stt.close()
+    await http_client.aclose()
+    await polly_client.close()
+    await context_stack.aclose()
+
+
+def setup_listeners(_app: FastAPI) -> None:
+    @_app.exception_handler(RequestValidationError)
+    async def custom_form_validation_error(request, exc):
+        """
+            Don't delete request param
+        """
+        reformatted_message = defaultdict(list)
+        for pydantic_error in exc.errors():
+            loc, msg = pydantic_error["loc"], pydantic_error["msg"]
+            filtered_loc = loc[1:] if loc[0] in ("body", "query", "path") else loc
+            field_string = ".".join(filtered_loc)
+            if field_string == "cookie.refresh_token":
+                return JSONResponse(
+                    status_code=401,
+                    content={"error_code": 401, "message": HTTPStatus.UNAUTHORIZED.description},
+                )
+            reformatted_message[field_string].append(msg)
+
+        return JSONResponse(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            content=jsonable_encoder(
+                {"details": "Invalid request!", "errors": reformatted_message}
+            ),
+        )
+
+    @_app.exception_handler(CustomException)
+    async def custom_exception_handler(request: Request, exc: CustomException):
+        """
+            Don't delete request param
+        """
+        return JSONResponse(
+            status_code=exc.code,
+            content={"error_code": exc.error_code, "message": exc.message},
+        )
+
+    @_app.exception_handler(Exception)
+    async def default_exception_handler(request: Request, exc: Exception):
+        """
+            Don't delete request param
+        """
+        return JSONResponse(
+            status_code=500,
+            content=str(exc),
+        )
+
+
+def setup_middleware() -> List[Middleware]:
+    middleware = [
+        Middleware(
+            CORSMiddleware,
+            allow_origins=["*"],
+            allow_credentials=True,
+            allow_methods=["*"],
+            allow_headers=["*"],
+        ),
+        Middleware(
+            AuthenticationMiddleware,
+            backend=AuthBackend()
+        )
+    ]
+    return middleware
+
+
+def create_app() -> FastAPI:
+    env = os.getenv("ENV")
+    _app = FastAPI(
+        docs_url="/docs" if env != "production" else None,
+        redoc_url="/redoc" if env != "production" else None,
+        middleware=setup_middleware(),
+        lifespan=lifespan
+    )
+    _app.include_router(router)
+    setup_listeners(_app)
+    return _app
+
+
+app = create_app()

ielts_be/api/__init__.py

@@ -0,0 +1,15 @@
+from fastapi import APIRouter
+
+from .training import training_router
+from .user import user_router
+from .exam import exam_router
+
+router = APIRouter(prefix="/api", tags=["Home"])
+
+@router.get('/healthcheck')
+async def healthcheck():
+    return {"healthy": True}
+
+router.include_router(training_router, prefix="/training", tags=["Training"])
+router.include_router(user_router, prefix="/user", tags=["Users"])
+router.include_router(exam_router)

ielts_be/api/exam/__init__.py

@@ -0,0 +1,16 @@
+from fastapi import APIRouter
+
+from .listening import listening_router
+from .reading import reading_router
+from .speaking import speaking_router
+from .writing import writing_router
+from .level import level_router
+from .grade import grade_router
+
+exam_router = APIRouter()
+exam_router.include_router(listening_router, prefix="/listening", tags=["Listening"])
+exam_router.include_router(reading_router, prefix="/reading", tags=["Reading"])
+exam_router.include_router(speaking_router, prefix="/speaking", tags=["Speaking"])
+exam_router.include_router(writing_router, prefix="/writing", tags=["Writing"])
+exam_router.include_router(level_router, prefix="/level", tags=["Level"])
+exam_router.include_router(grade_router, prefix="/grade", tags=["Grade"])

ielts_be/api/exam/grade.py

@@ -0,0 +1,64 @@
+from dependency_injector.wiring import inject, Provide
+from fastapi import APIRouter, Depends, Path, Request, BackgroundTasks
+
+from ielts_be.controllers import IGradeController
+from ielts_be.dtos.writing import WritingGradeTaskDTO
+from ielts_be.middlewares import Authorized, IsAuthenticatedViaBearerToken
+
+controller = "grade_controller"
+grade_router = APIRouter()
+
+
+@grade_router.post(
+    '/writing/{task}',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def grade_writing_task(
+    data: WritingGradeTaskDTO,
+    background_tasks: BackgroundTasks,
+    task: int = Path(..., ge=1, le=2),
+    grade_controller: IGradeController = Depends(Provide[controller])
+):
+    return await grade_controller.grade_writing_task(task, data, background_tasks)
+
+
+@grade_router.post(
+    '/speaking/{task}',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def grade_speaking_task(
+    request: Request,
+    background_tasks: BackgroundTasks,
+    task: int = Path(..., ge=1, le=3),
+    grade_controller: IGradeController = Depends(Provide[controller])
+):
+    form = await request.form()
+    return await grade_controller.grade_speaking_task(task, form, background_tasks)
+
+
+@grade_router.post(
+    '/summary',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def grading_summary(
+    request: Request,
+    grade_controller: IGradeController = Depends(Provide[controller])
+):
+    data = await request.json()
+    return await grade_controller.grading_summary(data)
+
+
+@grade_router.post(
+    '/short_answers',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def grade_short_answers(
+    request: Request,
+    grade_controller: IGradeController = Depends(Provide[controller])
+):
+    data = await request.json()
+    return await grade_controller.grade_short_answers(data)

ielts_be/api/exam/level.py

@@ -0,0 +1,67 @@
+from dependency_injector.wiring import Provide, inject
+from fastapi import APIRouter, Depends, UploadFile, Request
+
+from ielts_be.dtos.level import LevelExercisesDTO
+from ielts_be.middlewares import Authorized, IsAuthenticatedViaBearerToken
+from ielts_be.controllers import ILevelController
+
+controller = "level_controller"
+level_router = APIRouter()
+
+
+@level_router.post(
+    '/',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def generate_exercises(
+    dto: LevelExercisesDTO,
+    level_controller: ILevelController = Depends(Provide[controller])
+):
+    return await level_controller.generate_exercises(dto)
+
+@level_router.get(
+    '/',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def get_level_exam(
+    level_controller: ILevelController = Depends(Provide[controller])
+):
+    return await level_controller.get_level_exam()
+
+
+@level_router.get(
+    '/utas',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def get_level_utas(
+    level_controller: ILevelController = Depends(Provide[controller])
+):
+    return await level_controller.get_level_utas()
+
+
+@level_router.post(
+    '/import/',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def import_level(
+    exercises: UploadFile,
+    solutions: UploadFile = None,
+    level_controller: ILevelController = Depends(Provide[controller])
+):
+    return await level_controller.upload_level(exercises, solutions)
+
+@level_router.post(
+    '/custom/',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def custom_level(
+    request: Request,
+    level_controller: ILevelController = Depends(Provide[controller])
+):
+    data = await request.json()
+    return await level_controller.get_custom_level(data)

ielts_be/api/exam/listening.py

@@ -0,0 +1,90 @@
+import random
+from typing import List
+
+from dependency_injector.wiring import Provide, inject
+from fastapi import APIRouter, Depends, Path, Query, UploadFile
+
+from ielts_be.middlewares import Authorized, IsAuthenticatedViaBearerToken
+from ielts_be.controllers import IListeningController
+from ielts_be.configs.constants import EducationalContent
+from ielts_be.dtos.listening import ListeningExercisesDTO, Dialog, InstructionsDTO
+
+controller = "listening_controller"
+listening_router = APIRouter()
+
+@listening_router.post(
+    '/import',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def upload(
+    exercises: UploadFile,
+    solutions: UploadFile = None,
+    listening_controller: IListeningController = Depends(Provide[controller])
+):
+    return await listening_controller.import_exam(exercises, solutions)
+
+
+@listening_router.get(
+    '/{section}',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def generate_listening_dialog(
+    section: int = Path(..., ge=1, le=4),
+    difficulty: List[str] = Query(default=None),
+    topic: str = Query(default=None),
+    listening_controller: IListeningController = Depends(Provide[controller])
+):
+    difficulty = random.choice(EducationalContent.DIFFICULTIES) if not difficulty else difficulty
+    topic = random.choice(EducationalContent.TOPICS) if not topic else topic
+    return await listening_controller.generate_listening_dialog(section, topic, difficulty)
+
+@listening_router.post(
+    '/media',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def generate_mp3(
+    dto: Dialog,
+    listening_controller: IListeningController = Depends(Provide[controller])
+):
+    return await listening_controller.generate_mp3(dto)
+
+
+
+@listening_router.post(
+    '/transcribe',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def transcribe_dialog(
+    audio: UploadFile,
+    listening_controller: IListeningController = Depends(Provide[controller])
+):
+    return await listening_controller.transcribe_dialog(audio)
+
+
+@listening_router.post(
+    '/instructions',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def create_instructions(
+    dto: InstructionsDTO,
+    listening_controller: IListeningController = Depends(Provide[controller])
+):
+    return await listening_controller.create_instructions(dto.text)
+
+
+@listening_router.post(
+    '/',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def generate_listening_exercise(
+    dto: ListeningExercisesDTO,
+    listening_controller: IListeningController = Depends(Provide[controller])
+):
+    return await listening_controller.get_listening_question(dto)
+

ielts_be/api/exam/reading.py

@@ -0,0 +1,51 @@
+import random
+from typing import Optional
+
+from dependency_injector.wiring import Provide, inject
+from fastapi import APIRouter, Depends, Path, Query, UploadFile
+
+from ielts_be.configs.constants import EducationalContent
+from ielts_be.dtos.reading import ReadingDTO
+from ielts_be.middlewares import Authorized, IsAuthenticatedViaBearerToken
+from ielts_be.controllers import IReadingController
+
+controller = "reading_controller"
+reading_router = APIRouter()
+
+
+@reading_router.post(
+    '/import',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def upload(
+    exercises: UploadFile,
+    solutions: UploadFile = None,
+    reading_controller: IReadingController = Depends(Provide[controller])
+):
+    return await reading_controller.import_exam(exercises, solutions)
+
+@reading_router.get(
+    '/{passage}',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def generate_passage(
+    topic: Optional[str] = Query(None),
+    word_count: Optional[int] = Query(None),
+    passage: int = Path(..., ge=1, le=3),
+    reading_controller: IReadingController = Depends(Provide[controller])
+):
+    topic = random.choice(EducationalContent.TOPICS) if not topic else topic
+    return await reading_controller.generate_reading_passage(passage, topic, word_count)
+
+@reading_router.post(
+    '/',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def generate_reading(
+    dto: ReadingDTO,
+    reading_controller: IReadingController = Depends(Provide[controller])
+):
+    return await reading_controller.generate_reading_exercises(dto)

ielts_be/api/exam/speaking.py

@@ -0,0 +1,73 @@
+import random
+from typing import Optional, List
+
+from dependency_injector.wiring import inject, Provide
+from fastapi import APIRouter, Path, Query, Depends
+
+from ielts_be.dtos.speaking import Video
+from ielts_be.middlewares import Authorized, IsAuthenticatedViaBearerToken
+from ielts_be.configs.constants import EducationalContent
+from ielts_be.controllers import ISpeakingController
+
+controller = "speaking_controller"
+speaking_router = APIRouter()
+
+@speaking_router.post(
+    '/media',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def generate_video(
+    video: Video,
+    speaking_controller: ISpeakingController = Depends(Provide[controller])
+):
+    return await speaking_controller.generate_video(video.text, video.avatar)
+
+
+@speaking_router.get(
+    '/media/{vid_id}',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def poll_video(
+    vid_id: str = Path(...),
+    speaking_controller: ISpeakingController = Depends(Provide[controller])
+):
+    return await speaking_controller.poll_video(vid_id)
+
+
+
+@speaking_router.get(
+    '/avatars',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def get_avatars(
+    speaking_controller: ISpeakingController = Depends(Provide[controller])
+):
+    return await speaking_controller.get_avatars()
+
+
+
+@speaking_router.get(
+    '/{task}',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def get_speaking_task(
+    task: int = Path(..., ge=1, le=3),
+    topic: Optional[str] = Query(None),
+    first_topic: Optional[str] = Query(None),
+    second_topic: Optional[str] = Query(None),
+    difficulty: List[str] = Query(default=None),
+    speaking_controller: ISpeakingController = Depends(Provide[controller])
+):
+    if not second_topic:
+        topic_or_first_topic = topic if topic else random.choice(EducationalContent.MTI_TOPICS)
+    else:
+        topic_or_first_topic = first_topic if first_topic else random.choice(EducationalContent.MTI_TOPICS)
+
+    difficulty = [random.choice(EducationalContent.DIFFICULTIES)] if not difficulty else difficulty
+
+    second_topic = second_topic if second_topic else random.choice(EducationalContent.MTI_TOPICS)
+    return await speaking_controller.get_speaking_part(task, topic_or_first_topic, second_topic, difficulty)

ielts_be/api/exam/writing.py

@@ -0,0 +1,43 @@
+import random
+from typing import Optional, List
+
+from dependency_injector.wiring import inject, Provide
+from fastapi import APIRouter, Path, Query, Depends, UploadFile, File
+
+from ielts_be.middlewares import Authorized, IsAuthenticatedViaBearerToken
+from ielts_be.configs.constants import EducationalContent
+from ielts_be.controllers import IWritingController
+
+controller = "writing_controller"
+writing_router = APIRouter()
+
+
+@writing_router.post(
+    '/{task}/attachment',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def generate_writing_academic(
+        task: int = Path(..., ge=1, le=2),
+        file: UploadFile = File(...),
+        difficulty: List[str] = Query(default=None),
+        writing_controller: IWritingController = Depends(Provide[controller])
+):
+    difficulty = [random.choice(EducationalContent.DIFFICULTIES)] if not difficulty else difficulty
+    return await writing_controller.get_writing_task_academic_question(task, file, difficulty)
+
+
+@writing_router.get(
+    '/{task}',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def generate_writing(
+    task: int = Path(..., ge=1, le=2),
+    difficulty: List[str] = Query(default=None),
+    topic: str = Query(default=None),
+    writing_controller: IWritingController = Depends(Provide[controller])
+):
+    difficulty = [random.choice(EducationalContent.DIFFICULTIES)] if not difficulty else difficulty
+    topic = random.choice(EducationalContent.MTI_TOPICS) if not topic else topic
+    return await writing_controller.get_writing_task_general_question(task, topic, difficulty)

ielts_be/api/home.py

@@ -0,0 +1,9 @@
+from fastapi import APIRouter
+home_router = APIRouter()
+
+
+@home_router.get(
+    '/healthcheck'
+)
+async def healthcheck():
+    return {"healthy": True}

ielts_be/api/training.py

@@ -0,0 +1,34 @@
+from dependency_injector.wiring import Provide, inject
+from fastapi import APIRouter, Depends, Request
+
+from ielts_be.dtos.training import FetchTipsDTO
+from ielts_be.middlewares import Authorized, IsAuthenticatedViaBearerToken
+from ielts_be.controllers import ITrainingController
+
+controller = "training_controller"
+training_router = APIRouter()
+
+
+@training_router.post(
+    '/tips',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def get_reading_passage(
+    data: FetchTipsDTO,
+    training_controller: ITrainingController = Depends(Provide[controller])
+):
+    return await training_controller.fetch_tips(data)
+
+
+@training_router.post(
+    '/',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def training_content(
+    request: Request,
+    training_controller: ITrainingController = Depends(Provide[controller])
+):
+    data = await request.json()
+    return await training_controller.get_training_content(data)

ielts_be/api/user.py

@@ -0,0 +1,21 @@
+from dependency_injector.wiring import Provide, inject
+from fastapi import APIRouter, Depends
+
+from ielts_be.dtos.user_batch import BatchUsersDTO
+from ielts_be.middlewares import Authorized, IsAuthenticatedViaBearerToken
+from ielts_be.controllers import IUserController
+
+controller = "user_controller"
+user_router = APIRouter()
+
+
+@user_router.post(
+    '/import',
+    dependencies=[Depends(Authorized([IsAuthenticatedViaBearerToken]))]
+)
+@inject
+async def batch_import(
+    batch: BatchUsersDTO,
+    user_controller: IUserController = Depends(Provide[controller])
+):
+    return await user_controller.batch_import(batch)

ielts_be/configs/__init__.py

@@ -0,0 +1,5 @@
+from .dependency_injection import DependencyInjector
+
+__all__ = [
+    "DependencyInjector"
+]

ielts_be/configs/constants.py

@@ -0,0 +1,780 @@
+from enum import Enum
+
+########################################################################################################################
+# DISCLAIMER                                                                                                           #
+#                                                                                                                      #
+# All the array and dict "constants" are mutable variables, if somewhere in the app you modify them in any way, shape  #
+# or form all the other methods that will use these "constants" will also use the modified version. If you're unsure   #
+# whether a method will modify it use copy's deepcopy:                                                                 #
+#                                                                                                                      #
+# from copy import deepcopy                                                                                            #
+#                                                                                                                      #
+# new_ref = deepcopy(CONSTANT)                                                                                         #
+#                                                                                                                      #
+# Using a wrapper method that returns a "constant" won't handle nested mutables.                                       #
+########################################################################################################################
+
+BLACKLISTED_WORDS = ["jesus", "sex", "gay", "lesbian", "homosexual", "god", "angel", "pornography", "beer", "wine",
+                     "cocaine", "alcohol", "nudity", "lgbt", "casino", "gambling", "catholicism",
+                     "discrimination", "politic", "christianity", "islam", "christian", "christians",
+                     "jews", "jew", "discrimination", "discriminatory"]
+
+
+class UserDefaults:
+    DESIRED_LEVELS = {
+        "reading": 9,
+        "listening": 9,
+        "writing": 9,
+        "speaking": 9,
+    }
+
+    LEVELS = {
+        "reading": 0,
+        "listening": 0,
+        "writing": 0,
+        "speaking": 0,
+    }
+
+
+class ExamVariant(Enum):
+    FULL = "full"
+    PARTIAL = "partial"
+
+
+class ReadingExerciseType(str, Enum):
+    fillBlanks = "fillBlanks"
+    writeBlanks = "writeBlanks"
+    trueFalse = "trueFalse"
+    paragraphMatch = "paragraphMatch"
+    ideaMatch = "ideaMatch"
+    multipleChoice = "multipleChoice"
+
+
+class ListeningExerciseType(str, Enum):
+    multipleChoice = "multipleChoice"
+    multipleChoice3Options = "multipleChoice3Options"
+    writeBlanksQuestions = "writeBlanksQuestions"
+    writeBlanksFill = "writeBlanksFill"
+    writeBlanksForm = "writeBlanksForm"
+    trueFalse = "trueFalse"
+
+class LevelExerciseType(str, Enum):
+    multipleChoice = "multipleChoice"
+    mcBlank = "mcBlank"
+    mcUnderline = "mcUnderline"
+    blankSpace = "blankSpaceText"
+    passageUtas = "passageUtas"
+    fillBlanksMC = "fillBlanksMC"
+
+
+class CustomLevelExerciseTypes(Enum):
+    MULTIPLE_CHOICE_4 = "multiple_choice_4"
+    MULTIPLE_CHOICE_BLANK_SPACE = "multiple_choice_blank_space"
+    MULTIPLE_CHOICE_UNDERLINED = "multiple_choice_underlined"
+    BLANK_SPACE_TEXT = "blank_space_text"
+    READING_PASSAGE_UTAS = "reading_passage_utas"
+    WRITING_LETTER = "writing_letter"
+    WRITING_2 = "writing_2"
+    SPEAKING_1 = "speaking_1"
+    SPEAKING_2 = "speaking_2"
+    SPEAKING_3 = "speaking_3"
+    READING_1 = "reading_1"
+    READING_2 = "reading_2"
+    READING_3 = "reading_3"
+    LISTENING_1 = "listening_1"
+    LISTENING_2 = "listening_2"
+    LISTENING_3 = "listening_3"
+    LISTENING_4 = "listening_4"
+
+
+class QuestionType(Enum):
+    LISTENING_SECTION_1 = "Listening Section 1"
+    LISTENING_SECTION_2 = "Listening Section 2"
+    LISTENING_SECTION_3 = "Listening Section 3"
+    LISTENING_SECTION_4 = "Listening Section 4"
+    WRITING_TASK_1 = "Writing Task 1"
+    WRITING_TASK_2 = "Writing Task 2"
+    SPEAKING_1 = "Speaking Task Part 1"
+    SPEAKING_2 = "Speaking Task Part 2"
+    READING_PASSAGE_1 = "Reading Passage 1"
+    READING_PASSAGE_2 = "Reading Passage 2"
+    READING_PASSAGE_3 = "Reading Passage 3"
+
+
+class FilePaths:
+    AUDIO_FILES_PATH = 'download-audio/'
+    FIREBASE_LISTENING_AUDIO_FILES_PATH = 'listening_recordings/'
+    VIDEO_FILES_PATH = 'download-video/'
+    FIREBASE_SPEAKING_VIDEO_FILES_PATH = 'speaking_videos/'
+    FIREBASE_FAILED_TRANSCRIPTION_FILES_PATH = 'failed_transcriptions/'
+    WRITING_ATTACHMENTS = 'writing_attachments/'
+
+
+class TemperatureSettings:
+    GRADING_TEMPERATURE = 0.1
+    TIPS_TEMPERATURE = 0.2
+    GEN_QUESTION_TEMPERATURE = 0.7
+
+
+class GPTModels:
+    GPT_3_5_TURBO = "gpt-3.5-turbo"
+    GPT_4_TURBO = "gpt-4-turbo"
+    GPT_4_O = "gpt-4o"
+    GPT_3_5_TURBO_16K = "gpt-3.5-turbo-16k"
+    GPT_3_5_TURBO_INSTRUCT = "gpt-3.5-turbo-instruct"
+    GPT_4_PREVIEW = "gpt-4-turbo-preview"
+
+
+class FieldsAndExercises:
+    GRADING_FIELDS = ['comment', 'overall', 'task_response']
+    GEN_FIELDS = ['topic']
+    GEN_TEXT_FIELDS = ['title']
+    LISTENING_GEN_FIELDS = ['transcript', 'exercise']
+    READING_EXERCISE_TYPES = ['fillBlanks', 'writeBlanks', 'trueFalse', 'paragraphMatch']
+    READING_3_EXERCISE_TYPES = ['fillBlanks', 'writeBlanks', 'trueFalse', 'paragraphMatch', 'ideaMatch']
+
+    LISTENING_EXERCISE_TYPES = ['multipleChoice', 'writeBlanksQuestions', 'writeBlanksFill', 'writeBlanksForm']
+    LISTENING_1_EXERCISE_TYPES = ['multipleChoice', 'writeBlanksQuestions', 'writeBlanksFill', 'writeBlanksFill',
+                                  'writeBlanksForm', 'writeBlanksForm', 'writeBlanksForm', 'writeBlanksForm']
+    LISTENING_2_EXERCISE_TYPES = ['multipleChoice', 'writeBlanksQuestions']
+    LISTENING_3_EXERCISE_TYPES = ['multipleChoice3Options', 'writeBlanksQuestions']
+    LISTENING_4_EXERCISE_TYPES = ['multipleChoice', 'writeBlanksQuestions', 'writeBlanksFill', 'writeBlanksForm']
+
+    TOTAL_READING_PASSAGE_1_EXERCISES = 13
+    TOTAL_READING_PASSAGE_2_EXERCISES = 13
+    TOTAL_READING_PASSAGE_3_EXERCISES = 14
+
+    TOTAL_LISTENING_SECTION_1_EXERCISES = 10
+    TOTAL_LISTENING_SECTION_2_EXERCISES = 10
+    TOTAL_LISTENING_SECTION_3_EXERCISES = 10
+    TOTAL_LISTENING_SECTION_4_EXERCISES = 10
+
+
+class MinTimers:
+    LISTENING_MIN_TIMER_DEFAULT = 30
+    WRITING_MIN_TIMER_DEFAULT = 60
+    SPEAKING_MIN_TIMER_DEFAULT = 14
+
+
+class Voices:
+    EN_US_VOICES = [
+        {'Gender': 'Female', 'Id': 'Salli', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Salli',
+         'SupportedEngines': ['neural', 'standard']},
+        {'Gender': 'Male', 'Id': 'Matthew', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Matthew',
+         'SupportedEngines': ['neural', 'standard']},
+        {'Gender': 'Female', 'Id': 'Kimberly', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Kimberly',
+         'SupportedEngines': ['neural', 'standard']},
+        {'Gender': 'Female', 'Id': 'Kendra', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Kendra',
+         'SupportedEngines': ['neural', 'standard']},
+        {'Gender': 'Male', 'Id': 'Justin', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Justin',
+         'SupportedEngines': ['neural', 'standard']},
+        {'Gender': 'Male', 'Id': 'Joey', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Joey',
+         'SupportedEngines': ['neural', 'standard']},
+        {'Gender': 'Female', 'Id': 'Joanna', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Joanna',
+         'SupportedEngines': ['neural', 'standard']},
+        {'Gender': 'Female', 'Id': 'Ivy', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Ivy',
+         'SupportedEngines': ['neural', 'standard']}]
+    EN_GB_VOICES = [
+        {'Gender': 'Female', 'Id': 'Emma', 'LanguageCode': 'en-GB', 'LanguageName': 'British English', 'Name': 'Emma',
+         'SupportedEngines': ['neural', 'standard']},
+        {'Gender': 'Male', 'Id': 'Brian', 'LanguageCode': 'en-GB', 'LanguageName': 'British English', 'Name': 'Brian',
+         'SupportedEngines': ['neural', 'standard']},
+        {'Gender': 'Female', 'Id': 'Amy', 'LanguageCode': 'en-GB', 'LanguageName': 'British English', 'Name': 'Amy',
+         'SupportedEngines': ['neural', 'standard']}]
+    EN_GB_WLS_VOICES = [
+        {'Gender': 'Male', 'Id': 'Geraint', 'LanguageCode': 'en-GB-WLS', 'LanguageName': 'Welsh English', 'Name': 'Geraint',
+         'SupportedEngines': ['standard']}]
+    EN_AU_VOICES = [{'Gender': 'Male', 'Id': 'Russell', 'LanguageCode': 'en-AU', 'LanguageName': 'Australian English',
+                     'Name': 'Russell', 'SupportedEngines': ['standard']},
+                    {'Gender': 'Female', 'Id': 'Nicole', 'LanguageCode': 'en-AU', 'LanguageName': 'Australian English',
+                     'Name': 'Nicole', 'SupportedEngines': ['standard']}]
+
+    ALL_VOICES = EN_US_VOICES + EN_GB_VOICES + EN_GB_WLS_VOICES + EN_AU_VOICES
+
+    MALE_VOICES = [item for item in ALL_VOICES if item.get('Gender') == 'Male']
+    FEMALE_VOICES = [item for item in ALL_VOICES if item.get('Gender') == 'Female']
+
+
+class NeuralVoices:
+    NEURAL_EN_US_VOICES = [
+        {'Gender': 'Female', 'Id': 'Danielle', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Danielle',
+         'SupportedEngines': ['neural']},
+        {'Gender': 'Male', 'Id': 'Gregory', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Gregory',
+         'SupportedEngines': ['neural']},
+        {'Gender': 'Male', 'Id': 'Kevin', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Kevin',
+         'SupportedEngines': ['neural']},
+        {'Gender': 'Female', 'Id': 'Ruth', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Ruth',
+         'SupportedEngines': ['neural']},
+        {'Gender': 'Male', 'Id': 'Stephen', 'LanguageCode': 'en-US', 'LanguageName': 'US English', 'Name': 'Stephen',
+         'SupportedEngines': ['neural']}]
+    NEURAL_EN_GB_VOICES = [
+        {'Gender': 'Male', 'Id': 'Arthur', 'LanguageCode': 'en-GB', 'LanguageName': 'British English', 'Name': 'Arthur',
+         'SupportedEngines': ['neural']}]
+    NEURAL_EN_AU_VOICES = [
+        {'Gender': 'Female', 'Id': 'Olivia', 'LanguageCode': 'en-AU', 'LanguageName': 'Australian English',
+         'Name': 'Olivia', 'SupportedEngines': ['neural']}]
+    NEURAL_EN_ZA_VOICES = [
+        {'Gender': 'Female', 'Id': 'Ayanda', 'LanguageCode': 'en-ZA', 'LanguageName': 'South African English',
+         'Name': 'Ayanda', 'SupportedEngines': ['neural']}]
+    NEURAL_EN_NZ_VOICES = [
+        {'Gender': 'Female', 'Id': 'Aria', 'LanguageCode': 'en-NZ', 'LanguageName': 'New Zealand English', 'Name': 'Aria',
+         'SupportedEngines': ['neural']}]
+    NEURAL_EN_IN_VOICES = [
+        {'Gender': 'Female', 'Id': 'Kajal', 'LanguageCode': 'en-IN', 'LanguageName': 'Indian English', 'Name': 'Kajal',
+         'SupportedEngines': ['neural']}]
+    NEURAL_EN_IE_VOICES = [
+        {'Gender': 'Female', 'Id': 'Niamh', 'LanguageCode': 'en-IE', 'LanguageName': 'Irish English', 'Name': 'Niamh',
+         'SupportedEngines': ['neural']}]
+
+    ALL_NEURAL_VOICES = NEURAL_EN_US_VOICES + NEURAL_EN_GB_VOICES + NEURAL_EN_AU_VOICES + NEURAL_EN_ZA_VOICES + NEURAL_EN_NZ_VOICES + NEURAL_EN_IE_VOICES
+
+    MALE_NEURAL_VOICES = [item for item in ALL_NEURAL_VOICES if item.get('Gender') == 'Male']
+    FEMALE_NEURAL_VOICES = [item for item in ALL_NEURAL_VOICES if item.get('Gender') == 'Female']
+
+
+class EducationalContent:
+    DIFFICULTIES = ["A1", "A2", "B1", "B2", "C1", "C2"]
+
+    MTI_TOPICS = [
+        "Education",
+        "Technology",
+        "Environment",
+        "Health and Fitness",
+        "Engineering",
+        "Work and Careers",
+        "Travel and Tourism",
+        "Culture and Traditions",
+        "Social Issues",
+        "Arts and Entertainment",
+        "Climate Change",
+        "Social Media",
+        "Sustainable Development",
+        "Health Care",
+        "Immigration",
+        "Artificial Intelligence",
+        "Consumerism",
+        "Online Shopping",
+        "Energy",
+        "Oil and Gas",
+        "Poverty and Inequality",
+        "Cultural Diversity",
+        "Democracy and Governance",
+        "Mental Health",
+        "Ethics and Morality",
+        "Population Growth",
+        "Science and Innovation",
+        "Poverty Alleviation",
+        "Cybersecurity and Privacy",
+        "Human Rights",
+        "Food and Agriculture",
+        "Cyberbullying and Online Safety",
+        "Linguistic Diversity",
+        "Urbanization",
+        "Artificial Intelligence in Education",
+        "Youth Empowerment",
+        "Disaster Management",
+        "Mental Health Stigma",
+        "Internet Censorship",
+        "Sustainable Fashion",
+        "Indigenous Rights",
+        "Water Scarcity",
+        "Social Entrepreneurship",
+        "Privacy in the Digital Age",
+        "Sustainable Transportation",
+        "Gender Equality",
+        "Automation and Job Displacement",
+        "Digital Divide",
+        "Education Inequality"
+    ]
+    TOPICS = [
+        "Art and Creativity",
+        "History of Ancient Civilizations",
+        "Environmental Conservation",
+        "Space Exploration",
+        "Artificial Intelligence",
+        "Climate Change",
+        "The Human Brain",
+        "Renewable Energy",
+        "Cultural Diversity",
+        "Modern Technology Trends",
+        "Sustainable Agriculture",
+        "Natural Disasters",
+        "Cybersecurity",
+        "Philosophy of Ethics",
+        "Robotics",
+        "Health and Wellness",
+        "Literature and Classics",
+        "World Geography",
+        "Social Media Impact",
+        "Food Sustainability",
+        "Economics and Markets",
+        "Human Evolution",
+        "Political Systems",
+        "Mental Health Awareness",
+        "Quantum Physics",
+        "Biodiversity",
+        "Education Reform",
+        "Animal Rights",
+        "The Industrial Revolution",
+        "Future of Work",
+        "Film and Cinema",
+        "Genetic Engineering",
+        "Climate Policy",
+        "Space Travel",
+        "Renewable Energy Sources",
+        "Cultural Heritage Preservation",
+        "Modern Art Movements",
+        "Sustainable Transportation",
+        "The History of Medicine",
+        "Artificial Neural Networks",
+        "Climate Adaptation",
+        "Philosophy of Existence",
+        "Augmented Reality",
+        "Yoga and Meditation",
+        "Literary Genres",
+        "World Oceans",
+        "Social Networking",
+        "Sustainable Fashion",
+        "Prehistoric Era",
+        "Democracy and Governance",
+        "Postcolonial Literature",
+        "Geopolitics",
+        "Psychology and Behavior",
+        "Nanotechnology",
+        "Endangered Species",
+        "Education Technology",
+        "Renaissance Art",
+        "Renewable Energy Policy",
+        "Modern Architecture",
+        "Climate Resilience",
+        "Artificial Life",
+        "Fitness and Nutrition",
+        "Classic Literature Adaptations",
+        "Ethical Dilemmas",
+        "Internet of Things (IoT)",
+        "Meditation Practices",
+        "Literary Symbolism",
+        "Marine Conservation",
+        "Sustainable Tourism",
+        "Ancient Philosophy",
+        "Cold War Era",
+        "Behavioral Economics",
+        "Space Colonization",
+        "Clean Energy Initiatives",
+        "Cultural Exchange",
+        "Modern Sculpture",
+        "Climate Mitigation",
+        "Mindfulness",
+        "Literary Criticism",
+        "Wildlife Conservation",
+        "Renewable Energy Innovations",
+        "History of Mathematics",
+        "Human-Computer Interaction",
+        "Global Health",
+        "Cultural Appropriation",
+        "Traditional cuisine and culinary arts",
+        "Local music and dance traditions",
+        "History of the region and historical landmarks",
+        "Traditional crafts and artisanal skills",
+        "Wildlife and conservation efforts",
+        "Local sports and athletic competitions",
+        "Fashion trends and clothing styles",
+        "Education systems and advancements",
+        "Healthcare services and medical innovations",
+        "Family values and social dynamics",
+        "Travel destinations and tourist attractions",
+        "Environmental sustainability projects",
+        "Technological developments and innovations",
+        "Entrepreneurship and business ventures",
+        "Youth empowerment initiatives",
+        "Art exhibitions and cultural events",
+        "Philanthropy and community development projects"
+    ]
+
+    TWO_PEOPLE_SCENARIOS = [
+        "Booking a table at a restaurant",
+        "Making a doctor's appointment",
+        "Asking for directions to a tourist attraction",
+        "Inquiring about public transportation options",
+        "Discussing weekend plans with a friend",
+        "Ordering food at a café",
+        "Renting a bicycle for a day",
+        "Arranging a meeting with a colleague",
+        "Talking to a real estate agent about renting an apartment",
+        "Discussing travel plans for an upcoming vacation",
+        "Checking the availability of a hotel room",
+        "Talking to a car rental service",
+        "Asking for recommendations at a library",
+        "Inquiring about opening hours at a museum",
+        "Discussing the weather forecast",
+        "Shopping for groceries",
+        "Renting a movie from a video store",
+        "Booking a flight ticket",
+        "Discussing a school assignment with a classmate",
+        "Making a reservation for a spa appointment",
+        "Talking to a customer service representative about a product issue",
+        "Discussing household chores with a family member",
+        "Planning a surprise party for a friend",
+        "Talking to a coworker about a project deadline",
+        "Inquiring about a gym membership",
+        "Discussing the menu options at a fast-food restaurant",
+        "Talking to a neighbor about a community event",
+        "Asking for help with computer problems",
+        "Discussing a recent sports game with a sports enthusiast",
+        "Talking to a pet store employee about buying a pet",
+        "Asking for information about a local farmer's market",
+        "Discussing the details of a home renovation project",
+        "Talking to a coworker about office supplies",
+        "Making plans for a family picnic",
+        "Inquiring about admission requirements at a university",
+        "Discussing the features of a new smartphone with a salesperson",
+        "Talking to a mechanic about car repairs",
+        "Making arrangements for a child's birthday party",
+        "Discussing a new diet plan with a nutritionist",
+        "Asking for information about a music concert",
+        "Talking to a hairdresser about getting a haircut",
+        "Inquiring about a language course at a language school",
+        "Discussing plans for a weekend camping trip",
+        "Talking to a bank teller about opening a new account",
+        "Ordering a drink at a coffee shop",
+        "Discussing a new book with a book club member",
+        "Talking to a librarian about library services",
+        "Asking for advice on finding a job",
+        "Discussing plans for a garden makeover with a landscaper",
+        "Talking to a travel agent about a cruise vacation",
+        "Inquiring about a fitness class at a gym",
+        "Ordering flowers for a special occasion",
+        "Discussing a new exercise routine with a personal trainer",
+        "Talking to a teacher about a child's progress in school",
+        "Asking for information about a local art exhibition",
+        "Discussing a home improvement project with a contractor",
+        "Talking to a babysitter about childcare arrangements",
+        "Making arrangements for a car service appointment",
+        "Inquiring about a photography workshop at a studio",
+        "Discussing plans for a family reunion with a relative",
+        "Talking to a tech support representative about computer issues",
+        "Asking for recommendations on pet grooming services",
+        "Discussing weekend plans with a significant other",
+        "Talking to a counselor about personal issues",
+        "Inquiring about a music lesson with a music teacher",
+        "Ordering a pizza for delivery",
+        "Making a reservation for a taxi",
+        "Discussing a new recipe with a chef",
+        "Talking to a fitness trainer about weight loss goals",
+        "Inquiring about a dance class at a dance studio",
+        "Ordering a meal at a food truck",
+        "Discussing plans for a weekend getaway with a partner",
+        "Talking to a florist about wedding flower arrangements",
+        "Asking for advice on home decorating",
+        "Discussing plans for a charity fundraiser event",
+        "Talking to a pet sitter about taking care of pets",
+        "Making arrangements for a spa day with a friend",
+        "Asking for recommendations on home improvement stores",
+        "Discussing weekend plans with a travel enthusiast",
+        "Talking to a car mechanic about car maintenance",
+        "Inquiring about a cooking class at a culinary school",
+        "Ordering a sandwich at a deli",
+        "Discussing plans for a family holiday party",
+        "Talking to a personal assistant about organizing tasks",
+        "Asking for information about a local theater production",
+        "Discussing a new DIY project with a home improvement expert",
+        "Talking to a wine expert about wine pairing",
+        "Making arrangements for a pet adoption",
+        "Asking for advice on planning a wedding"
+    ]
+
+    SOCIAL_MONOLOGUE_CONTEXTS = [
+        "A guided tour of a historical museum",
+        "An introduction to a new city for tourists",
+        "An orientation session for new university students",
+        "A safety briefing for airline passengers",
+        "An explanation of the process of recycling",
+        "A lecture on the benefits of a healthy diet",
+        "A talk on the importance of time management",
+        "A monologue about wildlife conservation",
+        "An overview of local public transportation options",
+        "A presentation on the history of cinema",
+        "An introduction to the art of photography",
+        "A discussion about the effects of climate change",
+        "An overview of different types of cuisine",
+        "A lecture on the principles of financial planning",
+        "A monologue about sustainable energy sources",
+        "An explanation of the process of online shopping",
+        "A guided tour of a botanical garden",
+        "An introduction to a local wildlife sanctuary",
+        "A safety briefing for hikers in a national park",
+        "A talk on the benefits of physical exercise",
+        "A lecture on the principles of effective communication",
+        "A monologue about the impact of social media",
+        "An overview of the history of a famous landmark",
+        "An introduction to the world of fashion design",
+        "A discussion about the challenges of global poverty",
+        "An explanation of the process of organic farming",
+        "A presentation on the history of space exploration",
+        "An overview of traditional music from different cultures",
+        "A lecture on the principles of effective leadership",
+        "A monologue about the influence of technology",
+        "A guided tour of a famous archaeological site",
+        "An introduction to a local wildlife rehabilitation center",
+        "A safety briefing for visitors to a science museum",
+        "A talk on the benefits of learning a new language",
+        "A lecture on the principles of architectural design",
+        "A monologue about the impact of renewable energy",
+        "An explanation of the process of online banking",
+        "A presentation on the history of a famous art movement",
+        "An overview of traditional clothing from various regions",
+        "A lecture on the principles of sustainable agriculture",
+        "A discussion about the challenges of urban development",
+        "A monologue about the influence of social norms",
+        "A guided tour of a historical battlefield",
+        "An introduction to a local animal shelter",
+        "A safety briefing for participants in a charity run",
+        "A talk on the benefits of community involvement",
+        "A lecture on the principles of sustainable tourism",
+        "A monologue about the impact of alternative medicine",
+        "An explanation of the process of wildlife tracking",
+        "A presentation on the history of a famous inventor",
+        "An overview of traditional dance forms from different cultures",
+        "A lecture on the principles of ethical business practices",
+        "A discussion about the challenges of healthcare access",
+        "A monologue about the influence of cultural traditions",
+        "A guided tour of a famous lighthouse",
+        "An introduction to a local astronomy observatory",
+        "A safety briefing for participants in a team-building event",
+        "A talk on the benefits of volunteering",
+        "A lecture on the principles of wildlife protection",
+        "A monologue about the impact of space exploration",
+        "An explanation of the process of wildlife photography",
+        "A presentation on the history of a famous musician",
+        "An overview of traditional art forms from different cultures",
+        "A lecture on the principles of effective education",
+        "A discussion about the challenges of sustainable development",
+        "A monologue about the influence of cultural diversity",
+        "A guided tour of a famous national park",
+        "An introduction to a local marine conservation project",
+        "A safety briefing for participants in a hot air balloon ride",
+        "A talk on the benefits of cultural exchange programs",
+        "A lecture on the principles of wildlife conservation",
+        "A monologue about the impact of technological advancements",
+        "An explanation of the process of wildlife rehabilitation",
+        "A presentation on the history of a famous explorer",
+        "A lecture on the principles of effective marketing",
+        "A discussion about the challenges of environmental sustainability",
+        "A monologue about the influence of social entrepreneurship",
+        "A guided tour of a famous historical estate",
+        "An introduction to a local marine life research center",
+        "A safety briefing for participants in a zip-lining adventure",
+        "A talk on the benefits of cultural preservation",
+        "A lecture on the principles of wildlife ecology",
+        "A monologue about the impact of space technology",
+        "An explanation of the process of wildlife conservation",
+        "A presentation on the history of a famous scientist",
+        "An overview of traditional crafts and artisans from different cultures",
+        "A lecture on the principles of effective intercultural communication"
+    ]
+
+    FOUR_PEOPLE_SCENARIOS = [
+        "A university lecture on history",
+        "A physics class discussing Newton's laws",
+        "A medical school seminar on anatomy",
+        "A training session on computer programming",
+        "A business school lecture on marketing strategies",
+        "A chemistry lab experiment and discussion",
+        "A language class practicing conversational skills",
+        "A workshop on creative writing techniques",
+        "A high school math lesson on calculus",
+        "A training program for customer service representatives",
+        "A lecture on environmental science and sustainability",
+        "A psychology class exploring human behavior",
+        "A music theory class analyzing compositions",
+        "A nursing school simulation for patient care",
+        "A computer science class on algorithms",
+        "A workshop on graphic design principles",
+        "A law school lecture on constitutional law",
+        "A geology class studying rock formations",
+        "A vocational training program for electricians",
+        "A history seminar focusing on ancient civilizations",
+        "A biology class dissecting specimens",
+        "A financial literacy course for adults",
+        "A literature class discussing classic novels",
+        "A training session for emergency response teams",
+        "A sociology lecture on social inequality",
+        "An art class exploring different painting techniques",
+        "A medical school seminar on diagnosis",
+        "A programming bootcamp teaching web development",
+        "An economics class analyzing market trends",
+        "A chemistry lab experiment on chemical reactions",
+        "A language class practicing pronunciation",
+        "A workshop on public speaking skills",
+        "A high school physics lesson on electromagnetism",
+        "A training program for IT professionals",
+        "A lecture on climate change and its effects",
+        "A psychology class studying cognitive psychology",
+        "A music class composing original songs",
+        "A nursing school simulation for patient assessment",
+        "A computer science class on data structures",
+        "A workshop on 3D modeling and animation",
+        "A law school lecture on contract law",
+        "A geography class examining world maps",
+        "A vocational training program for plumbers",
+        "A history seminar discussing revolutions",
+        "A biology class exploring genetics",
+        "A financial literacy course for teens",
+        "A literature class analyzing poetry",
+        "A training session for public speaking coaches",
+        "A sociology lecture on cultural diversity",
+        "An art class creating sculptures",
+        "A medical school seminar on surgical techniques",
+        "A programming bootcamp teaching app development",
+        "An economics class on global trade policies",
+        "A chemistry lab experiment on chemical bonding",
+        "A language class discussing idiomatic expressions",
+        "A workshop on conflict resolution",
+        "A high school biology lesson on evolution",
+        "A training program for project managers",
+        "A lecture on renewable energy sources",
+        "A psychology class on abnormal psychology",
+        "A music class rehearsing for a performance",
+        "A nursing school simulation for emergency response",
+        "A computer science class on cybersecurity",
+        "A workshop on digital marketing strategies",
+        "A law school lecture on intellectual property",
+        "A geology class analyzing seismic activity",
+        "A vocational training program for carpenters",
+        "A history seminar on the Renaissance",
+        "A chemistry class synthesizing compounds",
+        "A financial literacy course for seniors",
+        "A literature class interpreting Shakespearean plays",
+        "A training session for negotiation skills",
+        "A sociology lecture on urbanization",
+        "An art class creating digital art",
+        "A medical school seminar on patient communication",
+        "A programming bootcamp teaching mobile app development",
+        "An economics class on fiscal policy",
+        "A physics lab experiment on electromagnetism",
+        "A language class on cultural immersion",
+        "A workshop on time management",
+        "A high school chemistry lesson on stoichiometry",
+        "A training program for HR professionals",
+        "A lecture on space exploration and astronomy",
+        "A psychology class on human development",
+        "A music class practicing for a recital",
+        "A nursing school simulation for triage",
+        "A computer science class on web development frameworks",
+        "A workshop on team-building exercises",
+        "A law school lecture on criminal law",
+        "A geography class studying world cultures",
+        "A vocational training program for HVAC technicians",
+        "A history seminar on ancient civilizations",
+        "A biology class examining ecosystems",
+        "A financial literacy course for entrepreneurs",
+        "A literature class analyzing modern literature",
+        "A training session for leadership skills",
+        "A sociology lecture on gender studies",
+        "An art class exploring multimedia art",
+        "A medical school seminar on patient diagnosis",
+        "A programming bootcamp teaching software architecture"
+    ]
+
+    ACADEMIC_SUBJECTS = [
+        "Astrophysics",
+        "Microbiology",
+        "Political Science",
+        "Environmental Science",
+        "Literature",
+        "Biochemistry",
+        "Sociology",
+        "Art History",
+        "Geology",
+        "Economics",
+        "Psychology",
+        "History of Architecture",
+        "Linguistics",
+        "Neurobiology",
+        "Anthropology",
+        "Quantum Mechanics",
+        "Urban Planning",
+        "Philosophy",
+        "Marine Biology",
+        "International Relations",
+        "Medieval History",
+        "Geophysics",
+        "Finance",
+        "Educational Psychology",
+        "Graphic Design",
+        "Paleontology",
+        "Macroeconomics",
+        "Cognitive Psychology",
+        "Renaissance Art",
+        "Archaeology",
+        "Microeconomics",
+        "Social Psychology",
+        "Contemporary Art",
+        "Meteorology",
+        "Political Philosophy",
+        "Space Exploration",
+        "Cognitive Science",
+        "Classical Music",
+        "Oceanography",
+        "Public Health",
+        "Gender Studies",
+        "Baroque Art",
+        "Volcanology",
+        "Business Ethics",
+        "Music Composition",
+        "Environmental Policy",
+        "Media Studies",
+        "Ancient History",
+        "Seismology",
+        "Marketing",
+        "Human Development",
+        "Modern Art",
+        "Astronomy",
+        "International Law",
+        "Developmental Psychology",
+        "Film Studies",
+        "American History",
+        "Soil Science",
+        "Entrepreneurship",
+        "Clinical Psychology",
+        "Contemporary Dance",
+        "Space Physics",
+        "Political Economy",
+        "Cognitive Neuroscience",
+        "20th Century Literature",
+        "Public Administration",
+        "European History",
+        "Atmospheric Science",
+        "Supply Chain Management",
+        "Social Work",
+        "Japanese Literature",
+        "Planetary Science",
+        "Labor Economics",
+        "Industrial-Organizational Psychology",
+        "French Philosophy",
+        "Biogeochemistry",
+        "Strategic Management",
+        "Educational Sociology",
+        "Postmodern Literature",
+        "Public Relations",
+        "Middle Eastern History",
+        "Oceanography",
+        "International Development",
+        "Human Resources Management",
+        "Educational Leadership",
+        "Russian Literature",
+        "Quantum Chemistry",
+        "Environmental Economics",
+        "Environmental Psychology",
+        "Ancient Philosophy",
+        "Immunology",
+        "Comparative Politics",
+        "Child Development",
+        "Fashion Design",
+        "Geological Engineering",
+        "Macroeconomic Policy",
+        "Media Psychology",
+        "Byzantine Art",
+        "Ecology",
+        "International Business"
+    ]

ielts_be/configs/dependency_injection.py

@@ -0,0 +1,176 @@
+import json
+import os
+
+from dependency_injector import providers, containers
+from firebase_admin import credentials
+from motor.motor_asyncio import AsyncIOMotorClient
+from openai import AsyncOpenAI
+from httpx import AsyncClient as HTTPClient
+from dotenv import load_dotenv
+from sentence_transformers import SentenceTransformer
+
+from ielts_be.repositories.impl import *
+from ielts_be.services.impl import *
+from ielts_be.controllers.impl import *
+
+load_dotenv()
+
+
+class DependencyInjector:
+
+    def __init__(self, polly_client: any, http_client: HTTPClient, stt: OpenAIWhisper):
+        self._container = containers.DynamicContainer()
+        self._polly_client = polly_client
+        self._http_client = http_client
+        self._stt = stt
+
+    def inject(self):
+        self._setup_clients()
+        self._setup_third_parties()
+        self._setup_repositories()
+        self._setup_services()
+        self._setup_controllers()
+        self._container.wire(
+            packages=["ielts_be"]
+        )
+        return self
+
+    def _setup_clients(self):
+        self._container.openai_client = providers.Singleton(AsyncOpenAI)
+        self._container.polly_client = providers.Object(self._polly_client)
+        self._container.http_client = providers.Object(self._http_client)
+        self._container.stt = providers.Object(self._stt)
+
+    def _setup_third_parties(self):
+        self._container.llm = providers.Factory(OpenAI, client=self._container.openai_client)
+        self._container.tts = providers.Factory(AWSPolly, client=self._container.polly_client)
+
+        """
+        with open('ielts_be/services/impl/third_parties/elai/conf.json', 'r') as file:
+            elai_conf = json.load(file)
+
+        with open('ielts_be/services/impl/third_parties/elai/avatars.json', 'r') as file:
+            elai_avatars = json.load(file)
+            
+        with open('ielts_be/services/impl/third_parties/elai/elai_conf.json', 'r') as file:
+            elai_conf = json.load(file)
+        """
+
+        with open('ielts_be/services/impl/third_parties/elai/avatars.json', 'r') as file:
+            elai_avatars = json.load(file)
+
+        with open('ielts_be/services/impl/third_parties/elai/conf.json', 'r') as file:
+            elai_conf = json.load(file)
+
+        self._container.vid_gen = providers.Factory(
+            ELAI, client=self._container.http_client,
+            token=os.getenv("ELAI_TOKEN"),
+            avatars=elai_avatars,
+            conf=elai_conf
+        )
+        self._container.ai_detector = providers.Factory(
+            GPTZero, client=self._container.http_client, gpt_zero_key=os.getenv("GPT_ZERO_API_KEY")
+        )
+
+    def _setup_repositories(self):
+        cred = credentials.Certificate(os.getenv("GOOGLE_APPLICATION_CREDENTIALS"))
+        firebase_token = cred.get_access_token().access_token
+
+        self._container.document_store = providers.Factory(
+            MongoDB, mongo_db=AsyncIOMotorClient(os.getenv("MONGODB_URI"))[os.getenv("MONGODB_DB")]
+        )
+
+        self._container.firebase_instance = providers.Factory(
+            FirebaseStorage,
+            client=self._container.http_client, token=firebase_token, bucket=os.getenv("FIREBASE_BUCKET")
+        )
+
+    def _setup_services(self):
+        self._container.listening_service = providers.Factory(
+            ListeningService,
+            llm=self._container.llm,
+            stt=self._container.stt,
+            tts=self._container.tts,
+            file_storage=self._container.firebase_instance,
+            document_store=self._container.document_store
+        )
+        self._container.reading_service = providers.Factory(ReadingService, llm=self._container.llm)
+
+        self._container.speaking_service = providers.Factory(
+            SpeakingService, llm=self._container.llm,
+            file_storage=self._container.firebase_instance,
+            stt=self._container.stt
+        )
+
+        self._container.writing_service = providers.Factory(
+            WritingService, llm=self._container.llm, ai_detector=self._container.ai_detector, file_storage=self._container.firebase_instance
+        )
+
+        with open('ielts_be/services/impl/exam/level/mc_variants.json', 'r') as file:
+            mc_variants = json.load(file)
+
+        self._container.level_service = providers.Factory(
+            LevelService, llm=self._container.llm, document_store=self._container.document_store,
+            mc_variants=mc_variants, reading_service=self._container.reading_service,
+            writing_service=self._container.writing_service, speaking_service=self._container.speaking_service,
+            listening_service=self._container.listening_service
+        )
+
+        self._container.grade_service = providers.Factory(
+            GradeService, llm=self._container.llm
+        )
+
+        embeddings = SentenceTransformer('all-MiniLM-L6-v2')
+
+        self._container.training_kb = providers.Factory(
+            TrainingContentKnowledgeBase, embeddings=embeddings
+        )
+
+        self._container.training_service = providers.Factory(
+            TrainingService, llm=self._container.llm,
+            document_store=self._container.document_store, training_kb=self._container.training_kb
+        )
+
+        self._container.user_service = providers.Factory(
+            UserService, document_store=self._container.document_store
+        )
+
+        self._container.evaluation_service = providers.Factory(
+            EvaluationService, db=self._container.document_store,
+            writing_service=self._container.writing_service,
+            speaking_service=self._container.speaking_service
+        )
+
+    def _setup_controllers(self):
+
+        self._container.grade_controller = providers.Factory(
+            GradeController, grade_service=self._container.grade_service,
+            evaluation_service=self._container.evaluation_service
+        )
+
+        self._container.user_controller = providers.Factory(
+            UserController, user_service=self._container.user_service
+        )
+
+        self._container.training_controller = providers.Factory(
+            TrainingController, training_service=self._container.training_service
+        )
+
+        self._container.level_controller = providers.Factory(
+            LevelController, level_service=self._container.level_service
+        )
+        self._container.listening_controller = providers.Factory(
+            ListeningController, listening_service=self._container.listening_service
+        )
+
+        self._container.reading_controller = providers.Factory(
+            ReadingController, reading_service=self._container.reading_service
+        )
+
+        self._container.speaking_controller = providers.Factory(
+            SpeakingController, speaking_service=self._container.speaking_service, vid_gen=self._container.vid_gen
+        )
+
+        self._container.writing_controller = providers.Factory(
+            WritingController, writing_service=self._container.writing_service
+        )

ielts_be/configs/logging/__init__.py

@@ -0,0 +1,7 @@
+from .filters import ErrorAndAboveFilter
+from .queue_handler import QueueListenerHandler
+
+__all__ = [
+    "ErrorAndAboveFilter",
+    "QueueListenerHandler"
+]

ielts_be/configs/logging/filters.py

@@ -0,0 +1,6 @@
+import logging
+
+
+class ErrorAndAboveFilter(logging.Filter):
+    def filter(self, record: logging.LogRecord) -> bool | logging.LogRecord:
+        return record.levelno < logging.ERROR

ielts_be/configs/logging/formatters.py

@@ -0,0 +1,105 @@
+import datetime as dt
+import json
+import logging
+
+LOG_RECORD_BUILTIN_ATTRS = {
+    "args",
+    "asctime",
+    "created",
+    "exc_info",
+    "exc_text",
+    "filename",
+    "funcName",
+    "levelname",
+    "levelno",
+    "lineno",
+    "module",
+    "msecs",
+    "message",
+    "msg",
+    "name",
+    "pathname",
+    "process",
+    "processName",
+    "relativeCreated",
+    "stack_info",
+    "thread",
+    "threadName",
+    "taskName",
+}
+
+"""
+    This isn't being used since the app will be run on gcloud run but this can be used for future apps.
+    If you want to test it:
+     
+    formatters:
+    
+    "json": {
+      "()": "json_formatter.JSONFormatter",
+      "fmt_keys": {
+        "level": "levelname",
+        "message": "message",
+        "timestamp": "timestamp",
+        "logger": "name",
+        "module": "module",
+        "function": "funcName",
+        "line": "lineno",
+        "thread_name": "threadName"
+      }
+    } 
+    
+    handlers:
+    
+    "file_json": {
+      "class": "logging.handlers.RotatingFileHandler",
+      "level": "DEBUG",
+      "formatter": "json",
+      "filename": "logs/log",
+      "maxBytes": 1000000,
+      "backupCount": 3
+    }
+    
+    and add "cfg://handlers.file_json" to queue handler
+"""
+
+# From this video https://www.youtube.com/watch?v=9L77QExPmI0
+# Src here: https://github.com/mCodingLLC/VideosSampleCode/blob/master/videos/135_modern_logging/mylogger.py
+class JSONFormatter(logging.Formatter):
+    def __init__(
+        self,
+        *,
+        fmt_keys: dict[str, str] | None = None,
+    ):
+        super().__init__()
+        self.fmt_keys = fmt_keys if fmt_keys is not None else {}
+
+    def format(self, record: logging.LogRecord) -> str:
+        message = self._prepare_log_dict(record)
+        return json.dumps(message, default=str)
+
+    def _prepare_log_dict(self, record: logging.LogRecord):
+        always_fields = {
+            "message": record.getMessage(),
+            "timestamp": dt.datetime.fromtimestamp(
+                record.created, tz=dt.timezone.utc
+            ).isoformat(),
+        }
+        if record.exc_info is not None:
+            always_fields["exc_info"] = self.formatException(record.exc_info)
+
+        if record.stack_info is not None:
+            always_fields["stack_info"] = self.formatStack(record.stack_info)
+
+        message = {
+            key: msg_val
+            if (msg_val := always_fields.pop(val, None)) is not None
+            else getattr(record, val)
+            for key, val in self.fmt_keys.items()
+        }
+        message.update(always_fields)
+
+        for key, val in record.__dict__.items():
+            if key not in LOG_RECORD_BUILTIN_ATTRS:
+                message[key] = val
+
+        return message

ielts_be/configs/logging/logging_config.json

@@ -0,0 +1,53 @@
+{
+  "version": 1,
+  "objects": {
+    "queue": {
+      "class": "queue.Queue",
+      "maxsize": 1000
+    }
+  },
+  "disable_existing_loggers": false,
+  "formatters": {
+    "simple": {
+      "format": "[%(levelname)s] (%(module)s|L: %(lineno)d) %(asctime)s: %(message)s",
+      "datefmt": "%Y-%m-%dT%H:%M:%S%z"
+    }
+  },
+  "filters": {
+    "error_and_above": {
+      "()": "ielts_be.configs.logging.ErrorAndAboveFilter"
+    }
+  },
+  "handlers": {
+    "console": {
+      "class": "logging.StreamHandler",
+      "level": "INFO",
+      "formatter": "simple",
+      "stream": "ext://sys.stdout",
+      "filters": ["error_and_above"]
+    },
+    "error": {
+      "class": "logging.StreamHandler",
+      "level": "ERROR",
+      "formatter": "simple",
+      "stream": "ext://sys.stderr"
+    },
+    "queue_handler": {
+      "class": "ielts_be.configs.logging.QueueListenerHandler",
+      "handlers": [
+        "cfg://handlers.console",
+        "cfg://handlers.error"
+      ],
+      "queue": "cfg://objects.queue",
+      "respect_handler_level": true
+    }
+  },
+  "loggers": {
+    "root": {
+      "level": "DEBUG",
+      "handlers": [
+        "queue_handler"
+      ]
+    }
+  }
+}

ielts_be/configs/logging/queue_handler.py

@@ -0,0 +1,61 @@
+from logging.config import ConvertingList, ConvertingDict, valid_ident
+from logging.handlers import QueueHandler, QueueListener
+from queue import Queue
+import atexit
+
+
+class QueueHandlerHelper:
+
+    @staticmethod
+    def resolve_handlers(l):
+        if not isinstance(l, ConvertingList):
+            return l
+
+        # Indexing the list performs the evaluation.
+        return [l[i] for i in range(len(l))]
+
+    @staticmethod
+    def resolve_queue(q):
+        if not isinstance(q, ConvertingDict):
+            return q
+        if '__resolved_value__' in q:
+            return q['__resolved_value__']
+
+        cname = q.pop('class')
+        klass = q.configurator.resolve(cname)
+        props = q.pop('.', None)
+        kwargs = {k: q[k] for k in q if valid_ident(k)}
+        result = klass(**kwargs)
+        if props:
+            for name, value in props.items():
+                setattr(result, name, value)
+
+        q['__resolved_value__'] = result
+        return result
+
+
+# The guy from this video https://www.youtube.com/watch?v=9L77QExPmI0 is using logging features only available in 3.12
+# This article had the class required to build the queue handler in 3.11
+# https://rob-blackbourn.medium.com/how-to-use-python-logging-queuehandler-with-dictconfig-1e8b1284e27a
+class QueueListenerHandler(QueueHandler):
+
+    def __init__(self, handlers, respect_handler_level=False, auto_run=True, queue=Queue(-1)):
+        queue = QueueHandlerHelper.resolve_queue(queue)
+        super().__init__(queue)
+        handlers = QueueHandlerHelper.resolve_handlers(handlers)
+        self._listener = QueueListener(
+            self.queue,
+            *handlers,
+            respect_handler_level=respect_handler_level)
+        if auto_run:
+            self.start()
+            atexit.register(self.stop)
+
+    def start(self):
+        self._listener.start()
+
+    def stop(self):
+        self._listener.stop()
+
+    def emit(self, record):
+        return super().emit(record)

ielts_be/controllers/__init__.py

@@ -0,0 +1,3 @@
+from .abc import *
+
+__all__ = abc.__all__

ielts_be/controllers/abc/__init__.py

@@ -0,0 +1,11 @@
+from .grade import IGradeController
+from .training import ITrainingController
+from .user import IUserController
+from .exam import *
+
+__all__ = [
+    "IGradeController",
+    "ITrainingController",
+    "IUserController",
+]
+__all__.extend(exam.__all__)

ielts_be/controllers/abc/exam/__init__.py

@@ -0,0 +1,13 @@
+from .level import ILevelController
+from .listening import IListeningController
+from .reading import IReadingController
+from .writing import IWritingController
+from .speaking import ISpeakingController
+
+__all__ = [
+    "IListeningController",
+    "IReadingController",
+    "IWritingController",
+    "ISpeakingController",
+    "ILevelController",
+]

ielts_be/controllers/abc/exam/level.py

@@ -0,0 +1,27 @@
+from abc import ABC, abstractmethod
+
+from fastapi import UploadFile
+from typing import Dict, Optional
+
+
+class ILevelController(ABC):
+
+    @abstractmethod
+    async def generate_exercises(self, dto):
+        pass
+
+    @abstractmethod
+    async def get_level_exam(self):
+        pass
+
+    @abstractmethod
+    async def get_level_utas(self):
+        pass
+
+    @abstractmethod
+    async def upload_level(self, file: UploadFile, solutions: Optional[UploadFile] = None):
+        pass
+
+    @abstractmethod
+    async def get_custom_level(self, data: Dict):
+        pass

ielts_be/controllers/abc/exam/listening.py

@@ -0,0 +1,31 @@
+from abc import ABC, abstractmethod
+from typing import List
+
+from fastapi import UploadFile
+
+
+class IListeningController(ABC):
+
+    @abstractmethod
+    async def import_exam(self, exercises: UploadFile, solutions: UploadFile = None):
+        pass
+
+    @abstractmethod
+    async def generate_listening_dialog(self, section_id: int, topic: str, difficulty: List[str]):
+        pass
+
+    @abstractmethod
+    async def get_listening_question(self, dto):
+        pass
+
+    @abstractmethod
+    async def generate_mp3(self, dto):
+        pass
+
+    @abstractmethod
+    async def transcribe_dialog(self, audio: UploadFile):
+        pass
+
+    @abstractmethod
+    async def create_instructions(self, text: str):
+        pass

ielts_be/controllers/abc/exam/reading.py

@@ -0,0 +1,20 @@
+from abc import ABC, abstractmethod
+from typing import Optional
+
+from fastapi import UploadFile
+
+
+class IReadingController(ABC):
+
+    @abstractmethod
+    async def import_exam(self, exercises: UploadFile, solutions: UploadFile = None):
+        pass
+
+    @abstractmethod
+    async def generate_reading_passage(self, passage: int, topic: Optional[str], word_count: Optional[int]):
+        pass
+
+    @abstractmethod
+    async def generate_reading_exercises(self, dto):
+        pass
+

ielts_be/controllers/abc/exam/speaking.py

@@ -0,0 +1,21 @@
+from abc import ABC, abstractmethod
+from typing import List
+
+
+class ISpeakingController(ABC):
+
+    @abstractmethod
+    async def get_speaking_part(self, task: int, topic: str, second_topic: str, difficulty: List[str]):
+        pass
+
+    @abstractmethod
+    async def get_avatars(self):
+        pass
+
+    @abstractmethod
+    async def generate_video(self, text: str, avatar: str):
+        pass
+
+    @abstractmethod
+    async def poll_video(self, vid_id: str):
+        pass

ielts_be/controllers/abc/exam/writing.py

@@ -0,0 +1,15 @@
+from abc import ABC, abstractmethod
+from typing import List
+
+from fastapi.datastructures import UploadFile
+
+
+class IWritingController(ABC):
+
+    @abstractmethod
+    async def get_writing_task_general_question(self, task: int, topic: str, difficulty: List[str]):
+        pass
+
+    @abstractmethod
+    async def get_writing_task_academic_question(self, task: int, attachment: UploadFile, difficulty: List[str]):
+        pass

ielts_be/controllers/abc/grade.py

@@ -0,0 +1,30 @@
+from abc import ABC, abstractmethod
+from typing import Dict
+from fastapi import BackgroundTasks
+from fastapi.datastructures import FormData
+
+
+class IGradeController(ABC):
+
+    @abstractmethod
+    async def grade_writing_task(
+        self,
+        task: int, dto: any,
+        background_tasks: BackgroundTasks
+    ):
+        pass
+
+    @abstractmethod
+    async def grade_speaking_task(
+            self, task: int, form: FormData, background_tasks: BackgroundTasks
+    ):
+        pass
+
+    @abstractmethod
+    async def grade_short_answers(self, data: Dict):
+        pass
+
+    @abstractmethod
+    async def grading_summary(self, data: Dict):
+        pass
+

ielts_be/controllers/abc/training.py

@@ -0,0 +1,12 @@
+from abc import ABC, abstractmethod
+
+
+class ITrainingController(ABC):
+
+    @abstractmethod
+    async def fetch_tips(self, data):
+        pass
+
+    @abstractmethod
+    async def get_training_content(self, data):
+        pass

ielts_be/controllers/abc/user.py

@@ -0,0 +1,8 @@
+from abc import ABC, abstractmethod
+
+
+class IUserController(ABC):
+
+    @abstractmethod
+    async def batch_import(self, batch):
+        pass

ielts_be/controllers/impl/__init__.py

@@ -0,0 +1,12 @@
+from .training import TrainingController
+from .grade import GradeController
+from .user import UserController
+from .exam import *
+
+__all__ = [
+    "TrainingController",
+    "GradeController",
+    "UserController"
+]
+
+__all__.extend(exam.__all__)

ielts_be/controllers/impl/exam/__init__.py

@@ -0,0 +1,13 @@
+from .level import LevelController
+from .listening import ListeningController
+from .reading import ReadingController
+from .speaking import SpeakingController
+from .writing import WritingController
+
+__all__ = [
+    "LevelController",
+    "ListeningController",
+    "ReadingController",
+    "SpeakingController",
+    "WritingController",
+]

ielts_be/controllers/impl/exam/level.py

@@ -0,0 +1,26 @@
+from fastapi import UploadFile
+from typing import Dict, Optional
+
+from ielts_be.controllers import ILevelController
+from ielts_be.services import ILevelService
+
+
+class LevelController(ILevelController):
+
+    def __init__(self, level_service: ILevelService):
+        self._service = level_service
+
+    async def generate_exercises(self, dto):
+        return await self._service.generate_exercises(dto)
+
+    async def get_level_exam(self):
+        return await self._service.get_level_exam()
+
+    async def get_level_utas(self):
+        return await self._service.get_level_utas()
+
+    async def upload_level(self, exercises: UploadFile, solutions: Optional[UploadFile] = None):
+        return await self._service.upload_level(exercises, solutions)
+
+    async def get_custom_level(self, data: Dict):
+        return await self._service.get_custom_level(data)

ielts_be/controllers/impl/exam/listening.py

@@ -0,0 +1,54 @@
+import io
+from typing import List
+
+from fastapi import UploadFile
+from fastapi.responses import StreamingResponse, Response
+
+from ielts_be.controllers import IListeningController
+from ielts_be.services import IListeningService
+from ielts_be.dtos.listening import ListeningExercisesDTO, Dialog
+
+
+class ListeningController(IListeningController):
+
+    def __init__(self, listening_service: IListeningService):
+        self._service = listening_service
+
+    async def import_exam(self, exercises: UploadFile, solutions: UploadFile = None):
+        res = await self._service.import_exam(exercises, solutions)
+        if not res:
+            return Response(status_code=500)
+        else:
+            return res
+
+    async def generate_listening_dialog(self, section_id: int, topic: str, difficulty: List[str]):
+        return await self._service.generate_listening_dialog(section_id, topic, difficulty)
+
+    async def get_listening_question(self, dto: ListeningExercisesDTO):
+        return await self._service.get_listening_question(dto)
+
+    async def generate_mp3(self, dto: Dialog):
+        mp3 = await self._service.generate_mp3(dto)
+        return self._mp3_response(mp3)
+
+    async def create_instructions(self, text: str):
+        mp3 = await self._service.create_instructions(text)
+        return self._mp3_response(mp3)
+
+    async def transcribe_dialog(self, audio: UploadFile):
+        dialog = await self._service.transcribe_dialog(audio)
+        if dialog is None:
+            return Response(status_code=500)
+
+        return dialog
+
+    @staticmethod
+    def _mp3_response(mp3: bytes):
+        return StreamingResponse(
+            content=io.BytesIO(mp3),
+            media_type="audio/mpeg",
+            headers={
+                "Content-Type": "audio/mpeg",
+                "Content-Disposition": "attachment;filename=speech.mp3"
+            }
+        )

ielts_be/controllers/impl/exam/reading.py

@@ -0,0 +1,28 @@
+import logging
+from typing import Optional
+
+from fastapi import UploadFile, Response
+
+from ielts_be.controllers import IReadingController
+from ielts_be.services import IReadingService
+from ielts_be.dtos.reading import ReadingDTO
+
+
+class ReadingController(IReadingController):
+
+    def __init__(self, reading_service: IReadingService):
+        self._service = reading_service
+        self._logger = logging.getLogger(__name__)
+
+    async def import_exam(self, exercises: UploadFile, solutions: UploadFile = None):
+        res = await self._service.import_exam(exercises, solutions)
+        if not res:
+            return Response(status_code=500)
+        else:
+            return res
+
+    async def generate_reading_passage(self, passage: int, topic: Optional[str], word_count: Optional[int]):
+        return await self._service.generate_reading_passage(passage, topic, word_count)
+
+    async def generate_reading_exercises(self, dto: ReadingDTO):
+        return await self._service.generate_reading_exercises(dto)

ielts_be/controllers/impl/exam/speaking.py

@@ -0,0 +1,25 @@
+import logging
+from typing import List
+
+from ielts_be.controllers import ISpeakingController
+from ielts_be.services import ISpeakingService, IVideoGeneratorService
+
+
+class SpeakingController(ISpeakingController):
+
+    def __init__(self, speaking_service: ISpeakingService, vid_gen: IVideoGeneratorService):
+        self._service = speaking_service
+        self._vid_gen = vid_gen
+        self._logger = logging.getLogger(__name__)
+
+    async def get_speaking_part(self, task: int, topic: str, second_topic: str, difficulty: List[str]):
+        return await self._service.get_speaking_part(task, topic, second_topic, difficulty)
+
+    async def get_avatars(self):
+        return await self._vid_gen.get_avatars()
+
+    async def generate_video(self, text: str, avatar: str):
+        return await self._vid_gen.create_video(text, avatar)
+
+    async def poll_video(self, vid_id: str):
+        return await self._vid_gen.poll_status(vid_id)

ielts_be/controllers/impl/exam/writing.py

@@ -0,0 +1,20 @@
+from typing import List
+
+from fastapi import UploadFile, HTTPException
+
+from ielts_be.controllers import IWritingController
+from ielts_be.services import IWritingService
+
+
+class WritingController(IWritingController):
+
+    def __init__(self, writing_service: IWritingService):
+        self._service = writing_service
+
+    async def get_writing_task_general_question(self, task: int, topic: str, difficulty: List[str]):
+        return await self._service.get_writing_task_general_question(task, topic, difficulty)
+
+    async def get_writing_task_academic_question(self, task: int, attachment: UploadFile, difficulty: List[str]):
+        if attachment.content_type not in ['image/jpeg', 'image/png']:
+            raise HTTPException(status_code=400, detail="Invalid file type. Only JPEG and PNG allowed.")
+        return await self._service.get_writing_task_academic_question(task, attachment, difficulty)

ielts_be/controllers/impl/grade.py

@@ -0,0 +1,105 @@
+import logging
+from typing import Dict
+
+from fastapi import BackgroundTasks, Response, HTTPException
+from fastapi.datastructures import FormData
+
+from ielts_be.controllers import IGradeController
+from ielts_be.services import IGradeService, IEvaluationService
+from ielts_be.dtos.evaluation import EvaluationType
+from ielts_be.dtos.speaking import GradeSpeakingItem
+from ielts_be.dtos.writing import WritingGradeTaskDTO
+
+class GradeController(IGradeController):
+
+    def __init__(
+            self,
+            grade_service: IGradeService,
+            evaluation_service: IEvaluationService,
+    ):
+        self._service = grade_service
+        self._evaluation_service = evaluation_service
+        self._logger = logging.getLogger(__name__)
+
+    async def grade_writing_task(
+        self,
+        task: int, dto: WritingGradeTaskDTO, background_tasks: BackgroundTasks
+    ):
+        await self._evaluation_service.begin_evaluation(
+            dto.userId, dto.sessionId, task, dto.exerciseId, EvaluationType.WRITING, dto, background_tasks
+        )
+
+        return Response(status_code=200)
+
+    async def grade_speaking_task(self, task: int, form: FormData, background_tasks: BackgroundTasks):
+        answers: Dict[int, Dict] = {}
+        user_id = form.get("userId")
+        session_id = form.get("sessionId")
+        exercise_id = form.get("exerciseId")
+
+        if not session_id or not exercise_id:
+            raise HTTPException(
+                status_code=400,
+                detail="Fields sessionId and exerciseId are required!"
+            )
+
+        for key, value in form.items():
+            if '_' not in key:
+                continue
+
+            field_name, index = key.rsplit('_', 1)
+            index = int(index)
+
+            if index not in answers:
+                answers[index] = {}
+
+            if field_name == 'question':
+                answers[index]['question'] = value
+            elif field_name == 'audio':
+                answers[index]['answer'] = value
+
+        for i, answer in answers.items():
+            if 'question' not in answer or 'answer' not in answer:
+                raise HTTPException(
+                    status_code=400,
+                    detail=f"Incomplete data for answer {i}. Both question and audio required."
+                )
+
+        items = [
+            GradeSpeakingItem(
+                question=answers[i]['question'],
+                answer=answers[i]['answer']
+            )
+            for i in sorted(answers.keys())
+        ]
+
+        ex_type = EvaluationType.SPEAKING if task == 2 else EvaluationType.SPEAKING_INTERACTIVE
+
+        await self._evaluation_service.begin_evaluation(
+            user_id, session_id, task, exercise_id, ex_type, items, background_tasks
+        )
+
+        return Response(status_code=200)
+
+    async def grade_short_answers(self, data: Dict):
+        return await self._service.grade_short_answers(data)
+
+    async def grading_summary(self, data: Dict):
+        section_keys = ['reading', 'listening', 'writing', 'speaking', 'level']
+        extracted_sections = self._extract_existing_sections_from_body(data, section_keys)
+        return await self._service.calculate_grading_summary(extracted_sections)
+
+    @staticmethod
+    def _extract_existing_sections_from_body(my_dict, keys_to_extract):
+        if 'sections' in my_dict and isinstance(my_dict['sections'], list) and len(my_dict['sections']) > 0:
+            return list(
+                filter(
+                    lambda item:
+                    'code' in item and
+                    item['code'] in keys_to_extract and
+                    'grade' in item and
+                    'name' in item,
+                    my_dict['sections']
+                )
+            )
+

ielts_be/controllers/impl/training.py

@@ -0,0 +1,17 @@
+from typing import Dict
+
+from ielts_be.controllers import ITrainingController
+from ielts_be.services import ITrainingService
+from ielts_be.dtos.training import FetchTipsDTO
+
+
+class TrainingController(ITrainingController):
+
+    def __init__(self, training_service: ITrainingService):
+        self._service = training_service
+
+    async def fetch_tips(self, data: FetchTipsDTO):
+        return await self._service.fetch_tips(data.context, data.question, data.answer, data.correct_answer)
+
+    async def get_training_content(self, data: Dict):
+        return await self._service.get_training_content(data)

ielts_be/controllers/impl/user.py

@@ -0,0 +1,12 @@
+from ielts_be.controllers import IUserController
+from ielts_be.services import IUserService
+from ielts_be.dtos.user_batch import BatchUsersDTO
+
+
+class UserController(IUserController):
+
+    def __init__(self, user_service: IUserService):
+        self._service = user_service
+
+    async def batch_import(self, batch: BatchUsersDTO):
+        return await self._service.batch_users(batch)

ielts_be/dtos/evaluation.py

@@ -0,0 +1,18 @@
+from enum import Enum
+from typing import Dict, Optional
+from pydantic import BaseModel
+
+
+class EvaluationType(str, Enum):
+    WRITING = "writing"
+    SPEAKING_INTERACTIVE = "speaking_interactive"
+    SPEAKING = "speaking"
+
+class EvaluationRecord(BaseModel):
+    id: str
+    session_id: str
+    exercise_id: str
+    type: EvaluationType
+    task: int
+    status: str = "pending"
+    result: Optional[Dict] = None

ielts_be/dtos/exams/level.py

@@ -0,0 +1,60 @@
+from pydantic import BaseModel, Field
+from typing import List, Dict, Union, Optional
+from uuid import uuid4, UUID
+
+
+class Option(BaseModel):
+    id: str
+    text: str
+
+
+class MultipleChoiceQuestion(BaseModel):
+    id: str
+    prompt: str
+    variant: str = "text"
+    solution: str
+    options: List[Option]
+
+
+class MultipleChoiceExercise(BaseModel):
+    id: UUID = Field(default_factory=uuid4)
+    type: str = "multipleChoice"
+    prompt: str = "Select the appropriate option."
+    questions: List[MultipleChoiceQuestion]
+    userSolutions: List = Field(default_factory=list)
+
+
+class FillBlanksWord(BaseModel):
+    id: str
+    options: Dict[str, str]
+
+
+class FillBlanksSolution(BaseModel):
+    id: str
+    solution: str
+
+
+class FillBlanksExercise(BaseModel):
+    id: UUID = Field(default_factory=uuid4)
+    type: str = "fillBlanks"
+    variant: str = "mc"
+    prompt: str = "Click a blank to select the appropriate word for it."
+    text: str
+    solutions: List[FillBlanksSolution]
+    words: List[FillBlanksWord]
+    userSolutions: List = Field(default_factory=list)
+
+
+Exercise = Union[MultipleChoiceExercise, FillBlanksExercise]
+
+class Text(BaseModel):
+    content: str
+    title: str
+
+class Part(BaseModel):
+    exercises: List[Exercise]
+    text: Optional[Text] = Field(default=None)
+
+
+class Exam(BaseModel):
+    parts: List[Part]

ielts_be/dtos/exams/listening.py

@@ -0,0 +1,92 @@
+from enum import Enum
+from pydantic import BaseModel, Field
+from typing import List, Union, Optional, Literal, Any
+from uuid import uuid4, UUID
+
+from ielts_be.dtos.listening import Dialog
+
+
+class ExerciseBase(BaseModel):
+    id: UUID = Field(default_factory=uuid4)
+    type: str
+    prompt: str
+
+
+class TrueFalseSolution(str, Enum):
+    TRUE = "true"
+    FALSE = "false"
+    NOT_GIVEN = "not_given"
+
+class TrueFalseQuestions(BaseModel):
+    prompt: str
+    solution: TrueFalseSolution
+    id: str
+
+
+class TrueFalseExercise(ExerciseBase):
+    type: Literal["trueFalse"]
+    questions: List[TrueFalseQuestions]
+
+
+class MCOption(BaseModel):
+    id: str
+    text: str
+
+
+class MCQuestion(BaseModel):
+    id: str
+    prompt: str
+    options: List[MCOption]
+    solution: str
+    variant: str = "text"
+
+
+class MultipleChoiceExercise(ExerciseBase):
+    type: Literal["multipleChoice"]
+    questions: List[MCQuestion]
+
+
+class WriteBlankQuestion(BaseModel):
+    id: str
+    prompt: str
+    solution: List[str]
+
+class WriteBlanksVariant(str, Enum):
+    QUESTIONS = "questions"
+    FILL = "fill"
+    FORM = "form"
+
+class WriteBlanksQuestionExercise(ExerciseBase):
+    type: Literal["writeBlanks"]
+    maxWords: int
+    questions: List[WriteBlankQuestion]
+    variant: WriteBlanksVariant
+
+class WriteBlankSolution(BaseModel):
+    id: str
+    solution: List[str]
+
+class WriteBlanksExercise(ExerciseBase):
+    type: Literal["writeBlanks"]
+    maxWords: int
+    solutions: List[WriteBlankSolution]
+    text: str
+    variant: Optional[WriteBlanksVariant]
+
+
+ListeningExercise = Union[
+    TrueFalseExercise,
+    MultipleChoiceExercise,
+    WriteBlanksExercise
+]
+
+
+class ListeningSection(BaseModel):
+    exercises: List[ListeningExercise]
+    script: Optional[Union[List[Any] | str]] = None
+
+
+class ListeningExam(BaseModel):
+    module: str = "listening"
+    minTimer: Optional[int]
+    parts: List[ListeningSection]

ielts_be/dtos/exams/reading.py

@@ -0,0 +1,107 @@
+from enum import Enum
+
+from pydantic import BaseModel, Field
+from typing import List, Union, Optional
+from uuid import uuid4, UUID
+
+
+class WriteBlanksSolution(BaseModel):
+    id: str
+    solution: List[str]
+
+class WriteBlanksExercise(BaseModel):
+    id: UUID = Field(default_factory=uuid4)
+    type: str = "writeBlanks"
+    maxWords: int
+    solutions: List[WriteBlanksSolution]
+    text: str
+    prompt: str
+
+
+class MatchSentencesOption(BaseModel):
+    id: str
+    sentence: str
+
+class MatchSentencesSentence(MatchSentencesOption):
+    solution: str
+
+class MatchSentencesVariant(str, Enum):
+    HEADING = "heading"
+    IDEAMATCH = "ideaMatch"
+
+class MCOption(BaseModel):
+    id: str
+    text: str
+
+class MCQuestion(BaseModel):
+    id: str
+    prompt: str
+    options: List[MCOption]
+    solution: str
+    variant: Optional[str] = None
+
+class MultipleChoice(BaseModel):
+    questions: List[MCQuestion]
+    type: str
+    prompt: str
+
+
+class MatchSentencesExercise(BaseModel):
+    options: List[MatchSentencesOption]
+    sentences: List[MatchSentencesSentence]
+    type: str = "matchSentences"
+    variant: MatchSentencesVariant
+    prompt: str
+
+class TrueFalseSolution(str, Enum):
+    TRUE = "true"
+    FALSE = "false"
+    NOT_GIVEN = "not_given"
+
+class TrueFalseQuestions(BaseModel):
+    prompt: str
+    solution: TrueFalseSolution
+    id: str
+
+class TrueFalseExercise(BaseModel):
+    id: UUID = Field(default_factory=uuid4)
+    questions: List[TrueFalseQuestions]
+    type: str = "trueFalse"
+    prompt: str = "Do the following statements agree with the information given in the Reading Passage?"
+
+
+
+class FillBlanksSolution(BaseModel):
+    id: str
+    solution: str
+
+class FillBlanksWord(BaseModel):
+    letter: str
+    word: str
+
+class FillBlanksExercise(BaseModel):
+    id: UUID = Field(default_factory=uuid4)
+    solutions: List[FillBlanksSolution]
+    text: str
+    type: str = "fillBlanks"
+    words: List[FillBlanksWord]
+    allowRepetition: bool = False
+    prompt: str
+
+Exercise = Union[FillBlanksExercise, TrueFalseExercise, MatchSentencesExercise, WriteBlanksExercise, MultipleChoice]
+
+
+class Context(BaseModel):
+    title: str
+    content: str
+
+class Part(BaseModel):
+    exercises: List[Exercise]
+    text: Context
+
+class Exam(BaseModel):
+    id: UUID = Field(default_factory=uuid4)
+    module: str = "reading"
+    minTimer: int
+    isDiagnostic: bool = False
+    parts: List[Part]

ielts_be/dtos/level.py

@@ -0,0 +1,19 @@
+from typing import List, Optional
+
+from pydantic import BaseModel
+
+from ielts_be.configs.constants import LevelExerciseType
+
+
+class LevelExercises(BaseModel):
+    type: LevelExerciseType
+    quantity: int
+    text_size: Optional[int] = None
+    sa_qty: Optional[int] = None
+    mc_qty: Optional[int] = None
+    topic: Optional[str] = None
+    difficulty: Optional[str] = None
+
+class LevelExercisesDTO(BaseModel):
+    exercises: List[LevelExercises]
+    difficulty: Optional[List[str]] = None

ielts_be/dtos/listening.py

@@ -0,0 +1,38 @@
+import random
+import uuid
+from typing import List, Dict, Optional
+
+from pydantic import BaseModel, Field
+
+from ielts_be.configs.constants import MinTimers, EducationalContent, ListeningExerciseType
+
+
+class SaveListeningDTO(BaseModel):
+    parts: List[Dict]
+    minTimer: int = MinTimers.LISTENING_MIN_TIMER_DEFAULT
+    difficulty: str = random.choice(EducationalContent.DIFFICULTIES)
+    id: str = str(uuid.uuid4())
+
+
+class ListeningExercises(BaseModel):
+    type: ListeningExerciseType
+    quantity: int
+    difficulty: Optional[str] = None
+
+class ListeningExercisesDTO(BaseModel):
+    text: str
+    exercises: List[ListeningExercises]
+    difficulty: Optional[List[str]] = None
+
+class InstructionsDTO(BaseModel):
+    text: str
+
+class ConversationPayload(BaseModel):
+    name: str
+    gender: str
+    text: str
+    voice: Optional[str] = None
+
+class Dialog(BaseModel):
+    conversation: Optional[List[ConversationPayload]] = Field(default_factory=list)
+    monologue: Optional[str] = None

ielts_be/dtos/reading.py

@@ -0,0 +1,18 @@
+import random
+from typing import List, Optional
+
+from pydantic import BaseModel, Field
+
+from ielts_be.configs.constants import ReadingExerciseType, EducationalContent
+
+class ReadingExercise(BaseModel):
+    type: ReadingExerciseType
+    quantity: int
+    num_random_words: Optional[int] = Field(1)
+    max_words: Optional[int] = Field(3)
+    difficulty: Optional[str] = None
+
+class ReadingDTO(BaseModel):
+    text: str = Field(...)
+    exercises: List[ReadingExercise] = Field(...)
+    difficulty: Optional[List[str]] = None

ielts_be/dtos/sheet.py

@@ -0,0 +1,29 @@
+from pydantic import BaseModel
+from typing import List, Dict, Union, Any, Optional
+
+
+class Option(BaseModel):
+    id: str
+    text: str
+
+
+class MultipleChoiceQuestion(BaseModel):
+    type: str = "multipleChoice"
+    id: str
+    prompt: str
+    variant: str = "text"
+    options: List[Option]
+
+
+class FillBlanksWord(BaseModel):
+    type: str = "fillBlanks"
+    id: str
+    options: Dict[str, str]
+
+
+Component = Union[MultipleChoiceQuestion, FillBlanksWord, Dict[str, Any]]
+
+
+class Sheet(BaseModel):
+    batch: Optional[int] = None
+    components: List[Component]