diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index a86ac0131..f1f2d894d 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -56,6 +56,13 @@ jobs:
           docker build -t athena .
           cd ..
 
+      - name: Build llm_core image
+        id: set-image-core_llm
+        run: |
+          cd ./llm_core
+          docker build -t llm_core .
+          cd ..
+
       - name: Docker Login
         id: docker-login
         run: |
diff --git a/assessment_module_manager/assessment_module_manager/module/request_to_module.py b/assessment_module_manager/assessment_module_manager/module/request_to_module.py
index 7ce716d06..1e862b269 100644
--- a/assessment_module_manager/assessment_module_manager/module/request_to_module.py
+++ b/assessment_module_manager/assessment_module_manager/module/request_to_module.py
@@ -33,6 +33,7 @@ async def find_module_by_name(module_name: str) -> Optional[Module]:
     return None
 
 
+# pylint: disable=too-many-positional-arguments
 async def request_to_module(module: Module, headers: dict, path: str, lms_url: str, data: Optional[dict], method: str) -> ModuleResponse:
     """
     Helper function to send a request to a module.
diff --git a/assessment_module_manager/poetry.lock b/assessment_module_manager/poetry.lock
index d2b2a7a3e..33fceb01f 100644
--- a/assessment_module_manager/poetry.lock
+++ b/assessment_module_manager/poetry.lock
@@ -2,13 +2,13 @@
 
 [[package]]
 name = "anyio"
-version = "4.4.0"
+version = "4.6.0"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.4.0-py3-none-any.whl", hash = "sha256:c1b2d8f46a8a812513012e1107cb0e68c17159a7a594208005a57dc776e1bdc7"},
-    {file = "anyio-4.4.0.tar.gz", hash = "sha256:5aadc6a1bbb7cdb0bede386cac5e2940f5e2ff3aa20277e991cf028e0585ce94"},
+    {file = "anyio-4.6.0-py3-none-any.whl", hash = "sha256:c7d2e9d63e31599eeb636c8c5c03a7e108d73b345f064f1c19fdc87b79036a9a"},
+    {file = "anyio-4.6.0.tar.gz", hash = "sha256:137b4559cbb034c477165047febb6ff83f390fc3b20bf181c1fc0a728cb8beeb"},
 ]
 
 [package.dependencies]
@@ -16,25 +16,21 @@ idna = ">=2.8"
 sniffio = ">=1.1"
 
 [package.extras]
-doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
-test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
-trio = ["trio (>=0.23)"]
+doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.21.0b1)"]
+trio = ["trio (>=0.26.1)"]
 
 [[package]]
 name = "astroid"
-version = "2.15.8"
+version = "3.3.5"
 description = "An abstract syntax tree for Python with inference support."
 optional = false
-python-versions = ">=3.7.2"
+python-versions = ">=3.9.0"
 files = [
-    {file = "astroid-2.15.8-py3-none-any.whl", hash = "sha256:1aa149fc5c6589e3d0ece885b4491acd80af4f087baafa3fb5203b113e68cd3c"},
-    {file = "astroid-2.15.8.tar.gz", hash = "sha256:6c107453dffee9055899705de3c9ead36e74119cee151e5a9aaf7f0b0e020a6a"},
+    {file = "astroid-3.3.5-py3-none-any.whl", hash = "sha256:a9d1c946ada25098d790e079ba2a1b112157278f3fb7e718ae6a9252f5835dc8"},
+    {file = "astroid-3.3.5.tar.gz", hash = "sha256:5cfc40ae9f68311075d27ef68a4841bdc5cc7f6cf86671b49f00607d30188e2d"},
 ]
 
-[package.dependencies]
-lazy-object-proxy = ">=1.4.0"
-wrapt = {version = ">=1.14,<2", markers = "python_version >= \"3.11\""}
-
 [[package]]
 name = "athena"
 version = "1.0.0"
@@ -94,13 +90,13 @@ files = [
 
 [[package]]
 name = "dill"
-version = "0.3.8"
+version = "0.3.9"
 description = "serialize all of Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "dill-0.3.8-py3-none-any.whl", hash = "sha256:c36ca9ffb54365bdd2f8eb3eff7d2a21237f8452b57ace88b1ac615b7e815bd7"},
-    {file = "dill-0.3.8.tar.gz", hash = "sha256:3ebe3c479ad625c4553aca177444d89b486b1d84982eeacded644afc0cf797ca"},
+    {file = "dill-0.3.9-py3-none-any.whl", hash = "sha256:468dff3b89520b474c0397703366b7b95eebe6303f108adf9b19da1f702be87a"},
+    {file = "dill-0.3.9.tar.gz", hash = "sha256:81aa267dddf68cbfe8029c42ca9ec6a4ab3b22371d1c450abc54422577b4512c"},
 ]
 
 [package.extras]
@@ -139,19 +135,19 @@ all = ["email-validator (>=2.0.0)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)"
 
 [[package]]
 name = "flake8"
-version = "5.0.4"
+version = "6.1.0"
 description = "the modular source code checker: pep8 pyflakes and co"
 optional = false
-python-versions = ">=3.6.1"
+python-versions = ">=3.8.1"
 files = [
-    {file = "flake8-5.0.4-py2.py3-none-any.whl", hash = "sha256:7a1cf6b73744f5806ab95e526f6f0d8c01c66d7bbe349562d22dfca20610b248"},
-    {file = "flake8-5.0.4.tar.gz", hash = "sha256:6fbe320aad8d6b95cec8b8e47bc933004678dc63095be98528b7bdd2a9f510db"},
+    {file = "flake8-6.1.0-py2.py3-none-any.whl", hash = "sha256:ffdfce58ea94c6580c77888a86506937f9a1a227dfcd15f245d694ae20a6b6e5"},
+    {file = "flake8-6.1.0.tar.gz", hash = "sha256:d5b3857f07c030bdb5bf41c7f53799571d75c4491748a3adcd47de929e34cd23"},
 ]
 
 [package.dependencies]
 mccabe = ">=0.7.0,<0.8.0"
-pycodestyle = ">=2.9.0,<2.10.0"
-pyflakes = ">=2.5.0,<2.6.0"
+pycodestyle = ">=2.11.0,<2.12.0"
+pyflakes = ">=3.1.0,<3.2.0"
 
 [[package]]
 name = "flake8-polyfill"
@@ -201,69 +197,84 @@ test = ["coverage[toml]", "ddt (>=1.1.1,!=1.4.3)", "mock", "mypy", "pre-commit",
 
 [[package]]
 name = "greenlet"
-version = "3.0.3"
+version = "3.1.1"
 description = "Lightweight in-process concurrent programming"
 optional = false
 python-versions = ">=3.7"
 files = [
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 [package.extras]
@@ -327,15 +338,18 @@ socks = ["socksio (==1.*)"]
 
 [[package]]
 name = "idna"
-version = "3.8"
+version = "3.10"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
 python-versions = ">=3.6"
 files = [
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 ]
 
+[package.extras]
+all = ["flake8 (>=7.1.1)", "mypy (>=1.11.2)", "pytest (>=8.3.2)", "ruff (>=0.6.2)"]
+
 [[package]]
 name = "isort"
 version = "5.13.2"
@@ -350,52 +364,6 @@ files = [
 [package.extras]
 colors = ["colorama (>=0.4.6)"]
 
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-]
-
 [[package]]
 name = "mccabe"
 version = "0.7.0"
@@ -491,42 +459,42 @@ flake8-polyfill = ">=1.0.2,<2"
 
 [[package]]
 name = "platformdirs"
-version = "4.2.2"
+version = "4.3.6"
 description = "A small Python package for determining appropriate platform-specific dirs, e.g. a `user data dir`."
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "platformdirs-4.3.6-py3-none-any.whl", hash = "sha256:73e575e1408ab8103900836b97580d5307456908a03e92031bab39e4554cc3fb"},
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 ]
 
 [package.extras]
-docs = ["furo (>=2023.9.10)", "proselint (>=0.13)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1.25.2)"]
-test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)"]
-type = ["mypy (>=1.8)"]
+docs = ["furo (>=2024.8.6)", "proselint (>=0.14)", "sphinx (>=8.0.2)", "sphinx-autodoc-typehints (>=2.4)"]
+test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=8.3.2)", "pytest-cov (>=5)", "pytest-mock (>=3.14)"]
+type = ["mypy (>=1.11.2)"]
 
 [[package]]
 name = "prospector"
-version = "1.10.3"
+version = "1.12.0"
 description = "Prospector is a tool to analyse Python code by aggregating the result of other tools."
 optional = false
-python-versions = ">=3.7.2,<4.0"
+python-versions = "<4.0,>=3.8.1"
 files = [
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+    {file = "prospector-1.12.0.tar.gz", hash = "sha256:e598dddc406cbfe8b31a20d4391c7551841ed6772897a290ecaf272ee1ffabf6"},
 ]
 
 [package.dependencies]
 dodgy = ">=0.2.1,<0.3.0"
-flake8 = "<6.0.0"
+flake8 = "<7.0.0"
 GitPython = ">=3.1.27,<4.0.0"
 mccabe = ">=0.7.0,<0.8.0"
 packaging = "*"
 pep8-naming = ">=0.3.3,<=0.10.0"
 pycodestyle = ">=2.9.0"
 pydocstyle = ">=2.0.0"
-pyflakes = ">=2.2.0,<3"
-pylint = ">=2.8.3"
+pyflakes = ">=2.2.0,<4"
+pylint = ">=3.0"
 pylint-celery = "0.3"
 pylint-django = ">=2.5,<2.6"
 pylint-flask = "0.6"
@@ -568,13 +536,13 @@ files = [
 
 [[package]]
 name = "pycodestyle"
-version = "2.9.1"
+version = "2.11.1"
 description = "Python style guide checker"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.8"
 files = [
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+    {file = "pycodestyle-2.11.1.tar.gz", hash = "sha256:41ba0e7afc9752dfb53ced5489e89f8186be00e599e712660695b7a75ff2663f"},
 ]
 
 [[package]]
@@ -655,31 +623,31 @@ toml = ["tomli (>=1.2.3)"]
 
 [[package]]
 name = "pyflakes"
-version = "2.5.0"
+version = "3.1.0"
 description = "passive checker of Python programs"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.8"
 files = [
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-    {file = "pyflakes-2.5.0.tar.gz", hash = "sha256:491feb020dca48ccc562a8c0cbe8df07ee13078df59813b83959cbdada312ea3"},
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 ]
 
 [[package]]
 name = "pylint"
-version = "2.17.7"
+version = "3.3.1"
 description = "python code static checker"
 optional = false
-python-versions = ">=3.7.2"
+python-versions = ">=3.9.0"
 files = [
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+    {file = "pylint-3.3.1-py3-none-any.whl", hash = "sha256:2f846a466dd023513240bc140ad2dd73bfc080a5d85a710afdb728c420a5a2b9"},
+    {file = "pylint-3.3.1.tar.gz", hash = "sha256:9f3dcc87b1203e612b78d91a896407787e708b3f189b5fa0b307712d49ff0c6e"},
 ]
 
 [package.dependencies]
-astroid = ">=2.15.8,<=2.17.0-dev0"
+astroid = ">=3.3.4,<=3.4.0-dev0"
 colorama = {version = ">=0.4.5", markers = "sys_platform == \"win32\""}
 dill = {version = ">=0.3.6", markers = "python_version >= \"3.11\""}
-isort = ">=4.2.5,<6"
+isort = ">=4.2.5,<5.13.0 || >5.13.0,<6"
 mccabe = ">=0.6,<0.8"
 platformdirs = ">=2.2.0"
 tomlkit = ">=0.10.1"
@@ -705,21 +673,21 @@ pylint-plugin-utils = ">=0.2.1"
 
 [[package]]
 name = "pylint-django"
-version = "2.5.3"
+version = "2.5.2"
 description = "A Pylint plugin to help Pylint understand the Django web framework"
 optional = false
 python-versions = "*"
 files = [
-    {file = "pylint-django-2.5.3.tar.gz", hash = "sha256:0ac090d106c62fe33782a1d01bda1610b761bb1c9bf5035ced9d5f23a13d8591"},
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+    {file = "pylint-django-2.5.2.tar.gz", hash = "sha256:1933d82b4a92538a3b12aef91adfd7d866befd051d7a02d6245b0f965587d97c"},
+    {file = "pylint_django-2.5.2-py3-none-any.whl", hash = "sha256:286dce8a31bc8ed5a523e8d8742b5a0e083b87f5f140ea4cde9aad612c03bd2d"},
 ]
 
 [package.dependencies]
-pylint = ">=2.0,<3"
+pylint = ">=2.0"
 pylint-plugin-utils = ">=0.7"
 
 [package.extras]
-for-tests = ["coverage", "django-tables2", "django-tastypie", "factory-boy", "pylint (>=2.13)", "pytest", "wheel"]
+for-tests = ["coverage", "django-tables2", "django-tastypie", "factory-boy", "pytest", "wheel"]
 with-django = ["Django"]
 
 [[package]]
@@ -813,17 +781,17 @@ files = [
 
 [[package]]
 name = "requirements-detector"
-version = "1.2.2"
+version = "1.3.1"
 description = "Python tool to find and list requirements of a Python project"
 optional = false
-python-versions = ">=3.7,<4.0"
+python-versions = "<4.0,>=3.8"
 files = [
-    {file = "requirements_detector-1.2.2-py3-none-any.whl", hash = "sha256:d7c60493bf166da3dd59de0e6cb25765e0e32a1931aeae92614034e5786d0bd0"},
-    {file = "requirements_detector-1.2.2.tar.gz", hash = "sha256:3642cd7a5b261d79536c36bb7ecacf2adabd902d2e0e42bfb2ba82515da10501"},
+    {file = "requirements_detector-1.3.1-py3-none-any.whl", hash = "sha256:3ef72e1c5c3ad11100058e8f074a5762a4902985e698099d2e7f1283758d4045"},
+    {file = "requirements_detector-1.3.1.tar.gz", hash = "sha256:b89e34faf0e4d17f5736923918bd5401949cbe723294ccfefd698b3cda28e676"},
 ]
 
 [package.dependencies]
-astroid = ">=2.0,<3.0"
+astroid = ">=3.0,<4.0"
 packaging = ">=21.3"
 semver = ">=3.0.0,<4.0.0"
 toml = ">=0.10.2,<0.11.0"
@@ -888,60 +856,60 @@ files = [
 
 [[package]]
 name = "sqlalchemy"
-version = "2.0.33"
+version = "2.0.35"
 description = "Database Abstraction Library"
 optional = false
 python-versions = ">=3.7"
 files = [
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-    {file = "wrapt-1.16.0.tar.gz", hash = "sha256:5f370f952971e7d17c7d1ead40e49f32345a7f7a5373571ef44d800d06b1899d"},
-]
-
 [metadata]
 lock-version = "2.0"
 python-versions = "3.11.*"
diff --git a/athena-docker.sh b/athena-docker.sh
index 87fe423eb..6f211bd55 100644
--- a/athena-docker.sh
+++ b/athena-docker.sh
@@ -40,7 +40,7 @@ function download_cofee_config {
   mkdir -p ./module_text_cofee
   for file in traefik.docker.yml node_config.docker.yml; do
     echo "  Downloading $file..."
-    curl -sSL -o ./module_text_cofee/$file https://raw.githubusercontent.com/ls1intum/Athena/"$pr_branch"/module_text_cofee/"$file"
+    curl -sSL -o ./module_text_cofee/$file https://raw.githubusercontent.com/ls1intum/Athena/"$pr_branch"/modules/text/module_text_cofee/"$file"
   done
 }
 
@@ -146,4 +146,4 @@ case "$subcommand" in
         general_help
         exit 1
         ;;
-esac
\ No newline at end of file
+esac
diff --git a/athena/athena/__init__.py b/athena/athena/__init__.py
index 76841e471..f7eee0079 100644
--- a/athena/athena/__init__.py
+++ b/athena/athena/__init__.py
@@ -4,7 +4,7 @@
 
 from . import contextvars
 from .app import app
-from .schemas import ExerciseType, GradingCriterion, StructuredGradingInstruction
+from .schemas import ExerciseType, GradingCriterion, StructuredGradingInstruction, StructuredGradingCriterion
 from .metadata import emit_meta, get_meta
 from .experiment import get_experiment_environment
 from .endpoints import submission_selector, submissions_consumer, feedback_consumer, feedback_provider, config_schema_provider, evaluation_provider  # type: ignore
@@ -36,5 +36,6 @@ def run_module():
     "get_experiment_environment",
     "ExerciseType",
     "GradingCriterion",
-    "StructuredGradingInstruction"
+    "StructuredGradingInstruction",
+    "StructuredGradingCriterion"
 ]
diff --git a/athena/athena/models/db_exercise.py b/athena/athena/models/db_exercise.py
index bab830a95..13fd5593e 100644
--- a/athena/athena/models/db_exercise.py
+++ b/athena/athena/models/db_exercise.py
@@ -7,6 +7,7 @@
 
 class DBExercise(Model):
     id = Column(BigIntegerWithAutoincrement, primary_key=True, index=True, nullable=False)
+    lms_url = Column(String, index=True, nullable=False)
     title = Column(String, index=True, nullable=False)
     type = Column(SqlEnum(ExerciseType), index=True, nullable=False)
     max_points = Column(Float, index=True, nullable=False)
diff --git a/athena/athena/models/db_feedback.py b/athena/athena/models/db_feedback.py
index eb30b9720..b8c74914c 100644
--- a/athena/athena/models/db_feedback.py
+++ b/athena/athena/models/db_feedback.py
@@ -8,6 +8,7 @@ class DBFeedback(Model):
     __table_args__ = (UniqueConstraint('lms_id'),)
 
     id = Column(BigIntegerWithAutoincrement, primary_key=True, index=True, autoincrement=True)
+    lms_url = Column(String, index=True, nullable=False)
     lms_id = Column(BigInteger)
     title = Column(String)
     description = Column(String)
diff --git a/athena/athena/models/db_submission.py b/athena/athena/models/db_submission.py
index c2e490345..2e26d78a1 100644
--- a/athena/athena/models/db_submission.py
+++ b/athena/athena/models/db_submission.py
@@ -1,4 +1,4 @@
-from sqlalchemy import Column, JSON
+from sqlalchemy import Column, JSON, String
 
 from .model import Model
 from .big_integer_with_autoincrement import BigIntegerWithAutoincrement
@@ -6,4 +6,5 @@
 
 class DBSubmission(Model):
     id = Column(BigIntegerWithAutoincrement, primary_key=True, index=True, autoincrement=True,)
+    lms_url = Column(String, index=True, nullable=False)
     meta = Column(JSON, nullable=False)
diff --git a/athena/athena/models/model.py b/athena/athena/models/model.py
index 6ce8d1293..00dbecc1d 100644
--- a/athena/athena/models/model.py
+++ b/athena/athena/models/model.py
@@ -6,12 +6,6 @@
 
 class Model:
 
-    lms_url = Column(String, index=True, nullable=False)
-
-    __table_args__ = (
-        UniqueConstraint('id', 'lms_url'),
-    )
-
     @classmethod
     def get_schema_class(cls) -> BaseModel:
         # The schema class has the same name as myself, but without the "DB" prefix.
diff --git a/athena/athena/schemas/__init__.py b/athena/athena/schemas/__init__.py
index 27af7f037..244c2d9c0 100644
--- a/athena/athena/schemas/__init__.py
+++ b/athena/athena/schemas/__init__.py
@@ -13,4 +13,4 @@
 from .modeling_feedback import ModelingFeedback
 from .modeling_exercise import ModelingExercise
 from .modeling_submission import ModelingSubmission
-from .grading_criterion import GradingCriterion, StructuredGradingInstruction
\ No newline at end of file
+from .grading_criterion import GradingCriterion, StructuredGradingInstruction, StructuredGradingCriterion
\ No newline at end of file
diff --git a/athena/athena/schemas/grading_criterion.py b/athena/athena/schemas/grading_criterion.py
index 2a453cfbc..15225a7dc 100644
--- a/athena/athena/schemas/grading_criterion.py
+++ b/athena/athena/schemas/grading_criterion.py
@@ -1,7 +1,7 @@
 from abc import ABC
 from typing import List, Optional
 
-from pydantic import Field
+from pydantic import BaseModel, Field
 
 from .schema import Schema
 
@@ -24,3 +24,6 @@ class GradingCriterion(Schema, ABC):
     structured_grading_instructions: List[StructuredGradingInstruction] = Field(
         [], example=[{"credits": 1.0, "gradingScale": "Good", "instructionDescription": "Some instructions", "feedback": "Nicely done!", "usageCount": 1},
                      {"credits": 0.0, "gradingScale": "Bad", "instructionDescription": "Some instructions", "feedback": "Try again!", "usageCount": 0}])
+
+class StructuredGradingCriterion(BaseModel):
+    criteria: List[GradingCriterion]
\ No newline at end of file
diff --git a/docker-compose.yml b/docker-compose.yml
index 861bf61cf..54dcefbeb 100644
--- a/docker-compose.yml
+++ b/docker-compose.yml
@@ -8,6 +8,13 @@ services:
     image: athena
     command: echo "Athena build succeeded, exiting (this is normal)"
 
+  llm_core:
+      build: ./llm_core
+      depends_on:
+        - athena
+      image: llm_core
+      command: echo "llm_core build succeeded, exiting (this is normal)"
+
   assessment_module_manager:
     build: ./assessment_module_manager
     depends_on:
@@ -30,6 +37,7 @@ services:
     build: modules/programming/module_programming_llm
     depends_on:
       - athena
+      - llm_core
     ports:
       - "5002:5002"
 
@@ -38,6 +46,7 @@ services:
     build: modules/text/module_text_llm
     depends_on:
       - athena
+      - llm_core
     ports:
       - "5003:5003"
 
@@ -70,5 +79,6 @@ services:
     build: modules/modeling/module_modeling_llm
     depends_on:
       - athena
+      - llm_core
     ports:
       - "5008:5008"
diff --git a/llm_core/.env.example b/llm_core/.env.example
new file mode 100644
index 000000000..823e9a302
--- /dev/null
+++ b/llm_core/.env.example
@@ -0,0 +1,41 @@
+# Comment out the variables that you define somewhere else
+# Environment variables are overwritten by .env file
+
+PRODUCTION=0
+SECRET=12345abcdef
+DATABASE_URL=sqlite:///../data/data.sqlite
+
+
+################################################################
+# LLM Credentials                                              #
+################################################################
+
+# Default model to use
+# See below for options, available models are also logged on startup
+LLM_DEFAULT_MODEL="azure_openai_gpt-4o"
+LLM_DEFAULT_MODEL_COST_PER_MILLION_INPUT_TOKEN=5
+LLM_DEFAULT_MODEL_COST_PER_MILLION_OUTPUT_TOKEN=15
+
+# Enable LLM-as-a-judge approach 0 = disabled, 1 = enabled
+LLM_ENABLE_LLM_AS_A_JUDGE=1
+# Evaluation model to use for the LLM-as-a-judge approach [Only important if you want to use it in the /evaluate endpoint]
+# See below for options, available models are also logged on startup
+LLM_EVALUATION_MODEL="azure_openai_gpt-4o"
+
+# Standard OpenAI (Non-Azure) [leave blank if not used]
+# Model names prefixed with `openai_` followed by the model name, e.g. `openai_text-davinci-003`
+# A list of models can be found in `module_text_llm/helpers/models/openai.py` (openai_models)
+OPENAI_API_KEY="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
+
+# Azure OpenAI [leave blank if not used]
+# Model names prefixed with `azure_openai_` followed by the deployment id, e.g. `azure_openai_gpt-35`
+AZURE_OPENAI_API_KEY="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
+AZURE_OPENAI_ENDPOINT="https://ase-eu01.openai.azure.com/" # change base if needed
+OPENAI_API_VERSION="2024-06-01" # change base if needed
+
+# LangSmith (can be used for tracing LLMs) [leave blank if not used]
+# See https://docs.smith.langchain.com
+# LANGCHAIN_TRACING_V2=true
+# LANGCHAIN_ENDPOINT="https://api.smith.langchain.com"
+# LANGCHAIN_API_KEY="XXX"
+# LANGCHAIN_PROJECT="XXX"
diff --git a/llm_core/Dockerfile b/llm_core/Dockerfile
new file mode 100644
index 000000000..f81a37e57
--- /dev/null
+++ b/llm_core/Dockerfile
@@ -0,0 +1,24 @@
+# syntax=docker/dockerfile:1
+
+# This is the Dockerfile for the shared llm package.
+# Its output is used as a dependency in the module_* Dockerfiles.
+
+FROM python:3.11 as llm_core
+
+WORKDIR /code
+
+# Poetry
+RUN pip install --no-cache-dir poetry==1.5.0
+
+# Dependencies
+COPY pyproject.toml poetry.lock ./
+COPY --from=athena /code /athena
+
+RUN poetry config virtualenvs.create false \
+    && poetry install --no-interaction --no-ansi
+
+# Project files
+COPY . ./
+
+# Build the package
+RUN poetry build -f wheel
\ No newline at end of file
diff --git a/llm_core/llm_core/__init__.py b/llm_core/llm_core/__init__.py
new file mode 100644
index 000000000..2f04ff661
--- /dev/null
+++ b/llm_core/llm_core/__init__.py
@@ -0,0 +1,4 @@
+import dotenv
+
+# Load environment variables from .env file (for local development)
+dotenv.load_dotenv(override=True)
\ No newline at end of file
diff --git a/modules/text/module_text_llm/module_text_llm/helpers/models/__init__.py b/llm_core/llm_core/models/__init__.py
similarity index 85%
rename from modules/text/module_text_llm/module_text_llm/helpers/models/__init__.py
rename to llm_core/llm_core/models/__init__.py
index 85078d4d7..6f9db4fdd 100644
--- a/modules/text/module_text_llm/module_text_llm/helpers/models/__init__.py
+++ b/llm_core/llm_core/models/__init__.py
@@ -2,7 +2,7 @@
 from typing import Type, Union, List, Optional
 from langchain.base_language import BaseLanguageModel
 
-from module_text_llm.helpers.models.model_config import ModelConfig
+from llm_core.models.model_config import ModelConfig
 
 
 DefaultModelConfig: Type[ModelConfig]
@@ -14,7 +14,7 @@
 
 types: List[Type[ModelConfig]] = []
 try:
-    import module_text_llm.helpers.models.openai as openai_config
+    import llm_core.models.openai as openai_config
     types.append(openai_config.OpenAIModelConfig)
     if default_model_name in openai_config.available_models:
         DefaultModelConfig = openai_config.OpenAIModelConfig
@@ -35,4 +35,4 @@
     ModelConfigType = type0
 else:
     type1 = types[1]
-    ModelConfigType = Union[type0, type1] # type: ignore
+    ModelConfigType = Union[type0, type1] # type: ignore
\ No newline at end of file
diff --git a/llm_core/llm_core/models/callbacks.py b/llm_core/llm_core/models/callbacks.py
new file mode 100644
index 000000000..dc8d7b329
--- /dev/null
+++ b/llm_core/llm_core/models/callbacks.py
@@ -0,0 +1,43 @@
+import os
+
+from langchain.callbacks.base import BaseCallbackHandler
+from langchain_core.outputs import  LLMResult
+from langchain_core.messages.ai import UsageMetadata
+
+from athena import emit_meta, get_meta
+
+
+class UsageHandler(BaseCallbackHandler):
+    def on_llm_end(self, response: LLMResult, **kwargs) -> None:
+        cost_per_million_input_tokens = float(os.environ.get("LLM_DEFAULT_MODEL_COST_PER_MILLION_INPUT_TOKEN", 0.0))
+        cost_per_million_output_tokens = float(os.environ.get("LLM_DEFAULT_MODEL_COST_PER_MILLION_OUTPUT_TOKEN", 0.0))
+
+        meta = get_meta()
+        
+        total_usage = meta.get("totalUsage", {"numInputTokens": 0, "numOutputTokens": 0, "numTotalTokens": 0, "cost": 0 })
+        llm_calls = meta.get("llmRequests", [])
+
+        for generations in response.generations:
+            for generation in generations:
+                message = generation.dict()["message"]
+                generation_usage: UsageMetadata = message["usage_metadata"]
+                model_name = message["response_metadata"].get("model_name", None)
+
+                total_usage["numInputTokens"] += generation_usage["input_tokens"]
+                total_usage["numOutputTokens"] += generation_usage["output_tokens"]
+                total_usage["numTotalTokens"] += generation_usage["total_tokens"]
+
+                total_usage["cost"] += int(generation_usage["input_tokens"]) * cost_per_million_output_tokens / 1_000_000
+                total_usage["cost"] += int(generation_usage["output_tokens"]) * cost_per_million_output_tokens / 1_000_000
+
+                llm_calls.append({
+                    "model": model_name,
+                    "costPerMillionInputToken": cost_per_million_input_tokens,
+                    "costPerMillionOutputToken": cost_per_million_output_tokens,
+                    "numInputTokens": generation_usage["input_tokens"],
+                    "numOutputTokens": generation_usage["output_tokens"],
+                    "numTotalTokens": generation_usage["total_tokens"],
+                })
+
+        emit_meta("totalUsage", total_usage)
+        emit_meta("llmRequests", llm_calls)
diff --git a/modules/text/module_text_llm/module_text_llm/helpers/models/model_config.py b/llm_core/llm_core/models/model_config.py
similarity index 100%
rename from modules/text/module_text_llm/module_text_llm/helpers/models/model_config.py
rename to llm_core/llm_core/models/model_config.py
diff --git a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/openai.py b/llm_core/llm_core/models/openai.py
similarity index 98%
rename from modules/programming/module_programming_llm/module_programming_llm/helpers/models/openai.py
rename to llm_core/llm_core/models/openai.py
index 23e1669c2..d12df22d4 100644
--- a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/openai.py
+++ b/llm_core/llm_core/models/openai.py
@@ -10,6 +10,8 @@
 
 from athena.logger import logger
 from .model_config import ModelConfig
+from .callbacks import UsageHandler
+
 
 OPENAI_PREFIX = "openai_"
 AZURE_OPENAI_PREFIX = "azure_openai_"
@@ -132,6 +134,7 @@ def get_model(self) -> BaseLanguageModel:
                     # Otherwise, add it to model_kwargs (necessary for chat models)
                     model_kwargs[attr] = value
             kwargs["model_kwargs"] = model_kwargs
+            kwargs["callbacks"] = [UsageHandler()]
 
             # Initialize a copy of the model using the config
             model = model.__class__(**kwargs)
diff --git a/modules/text/module_text_llm/module_text_llm/helpers/llm_utils.py b/llm_core/llm_core/utils/llm_utils.py
similarity index 65%
rename from modules/text/module_text_llm/module_text_llm/helpers/llm_utils.py
rename to llm_core/llm_core/utils/llm_utils.py
index e7852bda0..4637b8558 100644
--- a/modules/text/module_text_llm/module_text_llm/helpers/llm_utils.py
+++ b/llm_core/llm_core/utils/llm_utils.py
@@ -1,8 +1,6 @@
-from typing import Optional, Type, TypeVar, List
-from pydantic import BaseModel, ValidationError
+from typing import Type, TypeVar, List
+from pydantic import BaseModel
 import tiktoken
-
-from langchain.chains import LLMChain
 from langchain.chat_models import ChatOpenAI
 from langchain.base_language import BaseLanguageModel
 from langchain.prompts import (
@@ -10,11 +8,8 @@
     SystemMessagePromptTemplate,
     HumanMessagePromptTemplate,
 )
-from langchain.chains.openai_functions import create_structured_output_chain
 from langchain.output_parsers import PydanticOutputParser
-from langchain.schema import OutputParserException
-
-from athena import emit_meta, get_experiment_environment
+from athena import emit_meta
 
 T = TypeVar("T", bound=BaseModel)
 
@@ -112,51 +107,4 @@ def get_chat_prompt_with_formatting_instructions(
     system_message_prompt.prompt.partial_variables = {"format_instructions": output_parser.get_format_instructions()}
     system_message_prompt.prompt.input_variables.remove("format_instructions")
     human_message_prompt = HumanMessagePromptTemplate.from_template(human_message + "\n\nJSON response following the provided schema:")
-    return ChatPromptTemplate.from_messages([system_message_prompt, human_message_prompt])
-
-
-async def predict_and_parse(
-        model: BaseLanguageModel, 
-        chat_prompt: ChatPromptTemplate, 
-        prompt_input: dict, 
-        pydantic_object: Type[T], 
-        tags: Optional[List[str]]
-    ) -> Optional[T]:
-    """Predicts an LLM completion using the model and parses the output using the provided Pydantic model
-
-    Args:
-        model (BaseLanguageModel): The model to predict with
-        chat_prompt (ChatPromptTemplate): Prompt to use
-        prompt_input (dict): Input parameters to use for the prompt
-        pydantic_object (Type[T]): Pydantic model to parse the output
-        tags (Optional[List[str]]: List of tags to tag the prediction with
-
-    Returns:
-        Optional[T]: Parsed output, or None if it could not be parsed
-    """
-    experiment = get_experiment_environment()
-
-    tags = tags or []
-    if experiment.experiment_id is not None:
-        tags.append(f"experiment-{experiment.experiment_id}")
-    if experiment.module_configuration_id is not None:
-        tags.append(f"module-configuration-{experiment.module_configuration_id}")
-    if experiment.run_id is not None:
-        tags.append(f"run-{experiment.run_id}")
-
-    if supports_function_calling(model):
-        chain = create_structured_output_chain(pydantic_object, llm=model, prompt=chat_prompt, tags=tags)
-        
-        try:
-            return await chain.arun(**prompt_input)
-        except (OutputParserException, ValidationError):
-            # In the future, we should probably have some recovery mechanism here (i.e. fix the output with another prompt)
-            return None
-
-    output_parser = PydanticOutputParser(pydantic_object=pydantic_object)
-    chain = LLMChain(llm=model, prompt=chat_prompt, output_parser=output_parser, tags=tags)
-    try:
-        return await chain.arun(**prompt_input)
-    except (OutputParserException, ValidationError):
-        # In the future, we should probably have some recovery mechanism here (i.e. fix the output with another prompt)
-        return None
+    return ChatPromptTemplate.from_messages([system_message_prompt, human_message_prompt])
\ No newline at end of file
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/llm_utils.py b/llm_core/llm_core/utils/predict_and_parse.py
similarity index 83%
rename from modules/modeling/module_modeling_llm/module_modeling_llm/helpers/llm_utils.py
rename to llm_core/llm_core/utils/predict_and_parse.py
index 9c136027d..d73748bdf 100644
--- a/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/llm_utils.py
+++ b/llm_core/llm_core/utils/predict_and_parse.py
@@ -4,17 +4,16 @@
 from langchain_core.pydantic_v1 import BaseModel, ValidationError
 from langchain_core.runnables import RunnableSequence
 from athena import get_experiment_environment
-from athena.logger import logger
 
 T = TypeVar("T", bound=BaseModel)
 
 async def predict_and_parse(
-        model: BaseLanguageModel,
-        chat_prompt: ChatPromptTemplate,
-        prompt_input: dict,
-        pydantic_object: Type[T],
+        model: BaseLanguageModel, 
+        chat_prompt: ChatPromptTemplate, 
+        prompt_input: dict, 
+        pydantic_object: Type[T], 
         tags: Optional[List[str]]
-) -> Optional[T]:
+    ) -> Optional[T]:
     """Predicts an LLM completion using the model and parses the output using the provided Pydantic model
 
     Args:
@@ -45,8 +44,5 @@ async def predict_and_parse(
 
     try:
         return await chain.ainvoke(prompt_input, config={"tags": tags})
-    except (ValidationError) as e:
-
-        logger.error("Exception type: %s, Message: %s", type(e).__name__, e)
-
-        return None
\ No newline at end of file
+    except ValidationError as e:
+        raise ValueError(f"Could not parse output: {e}") from e
\ No newline at end of file
diff --git a/llm_core/poetry.lock b/llm_core/poetry.lock
new file mode 100644
index 000000000..1d67f0b38
--- /dev/null
+++ b/llm_core/poetry.lock
@@ -0,0 +1,2463 @@
+# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
+
+[[package]]
+name = "aiohappyeyeballs"
+version = "2.4.3"
+description = "Happy Eyeballs for asyncio"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "aiohappyeyeballs-2.4.3-py3-none-any.whl", hash = "sha256:8a7a83727b2756f394ab2895ea0765a0a8c475e3c71e98d43d76f22b4b435572"},
+    {file = "aiohappyeyeballs-2.4.3.tar.gz", hash = "sha256:75cf88a15106a5002a8eb1dab212525c00d1f4c0fa96e551c9fbe6f09a621586"},
+]
+
+[[package]]
+name = "aiohttp"
+version = "3.10.10"
+description = "Async http client/server framework (asyncio)"
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "yarl-1.14.0-cp39-cp39-win32.whl", hash = "sha256:337912bcdcf193ade64b9aae5a4017a0a1950caf8ca140362e361543c6773f21"},
+    {file = "yarl-1.14.0-cp39-cp39-win_amd64.whl", hash = "sha256:b6d0147574ce2e7b812c989e50fa72bbc5338045411a836bd066ce5fc8ac0bce"},
+    {file = "yarl-1.14.0-py3-none-any.whl", hash = "sha256:c8ed4034f0765f8861620c1f2f2364d2e58520ea288497084dae880424fc0d9f"},
+    {file = "yarl-1.14.0.tar.gz", hash = "sha256:88c7d9d58aab0724b979ab5617330acb1c7030b79379c8138c1c8c94e121d1b3"},
+]
+
+[package.dependencies]
+idna = ">=2.0"
+multidict = ">=4.0"
+propcache = ">=0.2.0"
+
+[metadata]
+lock-version = "2.0"
+python-versions = "3.11.*"
+content-hash = "9f0b58825849fe2c5079cfaa0339cb4f1249abc09864cf17999b57dc1a2f087f"
diff --git a/llm_core/pyproject.toml b/llm_core/pyproject.toml
new file mode 100644
index 000000000..9c984b508
--- /dev/null
+++ b/llm_core/pyproject.toml
@@ -0,0 +1,29 @@
+[tool.poetry]
+name = "llm_core"
+version = "0.1.0"
+description = "SHared LLM module."
+authors = ["Felix Dietrich <felixtj.dietrich@tum.de>"]
+license = "MIT"
+
+[tool.poetry.dependencies]
+python = "3.11.*"
+athena = {path = "../athena", develop = true}
+langsmith = ">=0.1.0,<0.2.0"
+gitpython = "3.1.41"
+langchain = "0.2.15"
+langchain-community="0.2.10"
+langchain-openai = "0.1.23"
+nltk = "3.8.1"
+openai = "1.51.1"
+python-dotenv = "1.0.0"
+tiktoken = "0.7.0"
+
+[tool.poetry.scripts]
+module = "athena:run_module"
+
+[tool.poetry.group.dev.dependencies]
+prospector = "^1.10.2"
+
+[build-system]
+requires = ["poetry-core>=1.0.0"]
+build-backend = "poetry.core.masonry.api"
\ No newline at end of file
diff --git a/modules/modeling/module_modeling_llm/.env.example b/modules/modeling/module_modeling_llm/.env.example
index 68b0577a1..ebeeb7bc5 100644
--- a/modules/modeling/module_modeling_llm/.env.example
+++ b/modules/modeling/module_modeling_llm/.env.example
@@ -13,6 +13,8 @@ DATABASE_URL=sqlite:///../data/data.sqlite
 # Default model to use
 # See below for options, available models are also logged on startup
 LLM_DEFAULT_MODEL="azure_openai_gpt-4o"
+LLM_DEFAULT_MODEL_COST_PER_MILLION_INPUT_TOKEN=5
+LLM_DEFAULT_MODEL_COST_PER_MILLION_OUTPUT_TOKEN=15
 
 # Enable LLM-as-a-judge approach 0 = disabled, 1 = enabled
 LLM_ENABLE_LLM_AS_A_JUDGE=1
diff --git a/modules/modeling/module_modeling_llm/Dockerfile b/modules/modeling/module_modeling_llm/Dockerfile
index 6d1c9a666..68b28a215 100644
--- a/modules/modeling/module_modeling_llm/Dockerfile
+++ b/modules/modeling/module_modeling_llm/Dockerfile
@@ -17,6 +17,7 @@ RUN pip install --no-cache-dir poetry==1.5.0
 COPY pyproject.toml poetry.lock ./
 # athena module (from the Dockerfile in the athena folder)
 COPY --from=athena /code /athena
+COPY --from=llm_core /code /llm_core
 # install dependencies
 RUN poetry config virtualenvs.create true \
     && poetry config virtualenvs.in-project true \
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/__main__.py b/modules/modeling/module_modeling_llm/module_modeling_llm/__main__.py
index d2594df5a..41d4bd981 100644
--- a/modules/modeling/module_modeling_llm/module_modeling_llm/__main__.py
+++ b/modules/modeling/module_modeling_llm/module_modeling_llm/__main__.py
@@ -5,9 +5,13 @@
 
 from athena import app, submission_selector, submissions_consumer, feedback_consumer, feedback_provider
 from athena.logger import logger
-from athena.modeling import Exercise, Submission, Feedback
+from athena.modeling import Exercise, Feedback, Submission
 from module_modeling_llm.config import Configuration
-from module_modeling_llm.generate_suggestions import generate_suggestions
+from module_modeling_llm.core.filter_feedback import filter_feedback
+from module_modeling_llm.core.generate_suggestions import generate_suggestions
+from module_modeling_llm.core.get_structured_grading_instructions import get_structured_grading_instructions
+from module_modeling_llm.utils.convert_to_athana_feedback_model import convert_to_athana_feedback_model
+from module_modeling_llm.utils.get_exercise_model import get_exercise_model
 
 
 @submissions_consumer
@@ -31,7 +35,26 @@ def process_incoming_feedback(exercise: Exercise, submission: Submission, feedba
 async def suggest_feedback(exercise: Exercise, submission: Submission, is_graded: bool, module_config: Configuration) -> List[Feedback]:
     logger.info("suggest_feedback: Suggestions for submission %d of exercise %d were requested", submission.id,
                 exercise.id)
-    return await generate_suggestions(exercise, submission, is_graded, module_config.approach, module_config.debug)
+    
+    # First, we convert the incoming exercise and submission to our internal models and textual representations
+    exercise_model = get_exercise_model(exercise, submission)
+
+    # Next, we retrieve or generate the structured grading instructions for the exercise
+    structured_grading_instructions = await get_structured_grading_instructions(
+        exercise_model, module_config.approach, exercise.grading_instructions, exercise.grading_criteria, module_config.debug
+    )
+
+    # Finally, we generate feedback suggestions for the submission
+    feedback = await generate_suggestions(
+        exercise_model, structured_grading_instructions, module_config.approach, module_config.debug
+    )
+
+    # If the submission is not graded (Student is requesting feedback), we reformulate the feedback to not give away the solution
+    if is_graded is False:
+        feedback = await filter_feedback(exercise_model, feedback, module_config.approach, module_config.debug)
+
+    return convert_to_athana_feedback_model(feedback, exercise_model)
+
 
 
 if __name__ == "__main__":
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/__init__.py b/modules/modeling/module_modeling_llm/module_modeling_llm/apollon_transformer/__init__.py
similarity index 100%
rename from modules/modeling/module_modeling_llm/module_modeling_llm/helpers/__init__.py
rename to modules/modeling/module_modeling_llm/module_modeling_llm/apollon_transformer/__init__.py
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/serializers/diagram_model_serializer.py b/modules/modeling/module_modeling_llm/module_modeling_llm/apollon_transformer/apollon_json_transformer.py
similarity index 70%
rename from modules/modeling/module_modeling_llm/module_modeling_llm/helpers/serializers/diagram_model_serializer.py
rename to modules/modeling/module_modeling_llm/module_modeling_llm/apollon_transformer/apollon_json_transformer.py
index 4b4a78bf8..3d67196df 100644
--- a/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/serializers/diagram_model_serializer.py
+++ b/modules/modeling/module_modeling_llm/module_modeling_llm/apollon_transformer/apollon_json_transformer.py
@@ -1,11 +1,12 @@
-from typing import Optional
-from module_modeling_llm.helpers.serializers.parser.uml_parser import UMLParser
+import json
 
+from module_modeling_llm.apollon_transformer.parser.uml_parser import UMLParser
 
-class DiagramModelSerializer:
+
+class ApollonJSONTransformer:
 
     @staticmethod
-    def serialize_model(model: dict) -> tuple[Optional[str], dict[str, str]]:
+    def transform_json(model: str) -> tuple[str, dict[str, str], str]:
         """
         Serialize a given Apollon diagram model to a string representation.
         This method converts the UML diagram model into a format similar to mermaid syntax, called "apollon".
@@ -14,7 +15,12 @@ def serialize_model(model: dict) -> tuple[Optional[str], dict[str, str]]:
         :return: A tuple containing the serialized model as a string and a dictionary mapping element and relation names
                  to their corresponding IDs.
         """
-        parser = UMLParser(model)
+
+        model_dict = json.loads(model)
+
+        parser = UMLParser(model_dict)
+
+        diagram_type = model_dict.get("type", "unknown")
     
         # Convert the UML diagram to the apollon representation
         apollon_representation = parser.to_apollon()
@@ -25,5 +31,5 @@ def serialize_model(model: dict) -> tuple[Optional[str], dict[str, str]]:
             **{relation['name']: relation['id'] for relation in parser.get_relations()}
         }
     
-        return apollon_representation, names
+        return apollon_representation, names, diagram_type
     
\ No newline at end of file
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/serializers/parser/element.py b/modules/modeling/module_modeling_llm/module_modeling_llm/apollon_transformer/parser/element.py
similarity index 88%
rename from modules/modeling/module_modeling_llm/module_modeling_llm/helpers/serializers/parser/element.py
rename to modules/modeling/module_modeling_llm/module_modeling_llm/apollon_transformer/parser/element.py
index 3b22a0269..415b586a6 100644
--- a/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/serializers/parser/element.py
+++ b/modules/modeling/module_modeling_llm/module_modeling_llm/apollon_transformer/parser/element.py
@@ -27,11 +27,6 @@ def resolve_references(self, element_dict: Dict[str, Any]):
         self.attributes = [element_dict[ref].get("name", "") for ref in self.attribute_refs if ref in element_dict]
         self.methods = [element_dict[ref].get('name', '') for ref in self.method_refs if ref in element_dict]
 
-        for ref_list, target_list in [(self.attribute_refs, self.attributes), (self.method_refs, self.methods)]:
-            target_list.extend(
-                element_dict.get(ref, {}).get("name", "") for ref in ref_list if ref in element_dict
-            )
-
     def to_apollon(self) -> str:
         parts = [f"[{self.type}] {self.name}"]
 
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/serializers/parser/relation.py b/modules/modeling/module_modeling_llm/module_modeling_llm/apollon_transformer/parser/relation.py
similarity index 100%
rename from modules/modeling/module_modeling_llm/module_modeling_llm/helpers/serializers/parser/relation.py
rename to modules/modeling/module_modeling_llm/module_modeling_llm/apollon_transformer/parser/relation.py
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/serializers/parser/uml_parser.py b/modules/modeling/module_modeling_llm/module_modeling_llm/apollon_transformer/parser/uml_parser.py
similarity index 86%
rename from modules/modeling/module_modeling_llm/module_modeling_llm/helpers/serializers/parser/uml_parser.py
rename to modules/modeling/module_modeling_llm/module_modeling_llm/apollon_transformer/parser/uml_parser.py
index 9142c8225..57b9a63ad 100644
--- a/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/serializers/parser/uml_parser.py
+++ b/modules/modeling/module_modeling_llm/module_modeling_llm/apollon_transformer/parser/uml_parser.py
@@ -1,8 +1,8 @@
 from typing import Dict, Any, List
 from string import ascii_uppercase
 
-from module_modeling_llm.helpers.serializers.parser.element import Element
-from module_modeling_llm.helpers.serializers.parser.relation import Relation
+from module_modeling_llm.apollon_transformer.parser.element import Element
+from module_modeling_llm.apollon_transformer.parser.relation import Relation
 
 
 class UMLParser:
@@ -42,9 +42,14 @@ def _parse(self) -> None:
         for element_data in self.data['elements'].values():
             if element_data.get('id') not in referenced_ids:
                 name = element_data.get('name')
-                if name_count[name] > 1:
-                    suffix_index = name_suffix_counters[name]
-                    element_data['name'] = f"{name}{ascii_uppercase[suffix_index]}"
+                suffix_index = name_suffix_counters[name]
+
+                if name == '':
+                    element_data['name'] = f"##{ascii_uppercase[suffix_index]}"
+                    if name_count[name] > 1:
+                        name_suffix_counters[name] += 1
+                elif name_count[name] > 1:
+                    element_data['name'] = f"{name}#{ascii_uppercase[suffix_index]}"
                     name_suffix_counters[name] += 1
 
                 element = Element(element_data, self.data['elements'])
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/config.py b/modules/modeling/module_modeling_llm/module_modeling_llm/config.py
index 3972801e7..169ee047a 100644
--- a/modules/modeling/module_modeling_llm/module_modeling_llm/config.py
+++ b/modules/modeling/module_modeling_llm/module_modeling_llm/config.py
@@ -1,15 +1,13 @@
 from pydantic import BaseModel, Field
 
 from athena import config_schema_provider
-from module_modeling_llm.helpers.models import ModelConfigType, DefaultModelConfig
-from module_modeling_llm.prompts.generate_suggestions import (
-    graded_feedback_system_message as default_graded_feedback_system_message,
-    graded_feedback_human_message as default_graded_feedback_human_message,
-    filter_feedback_system_message as default_filter_feedback_system_message,
-    filter_feedback_human_message as default_filter_feedback_human_message
+from llm_core.models import ModelConfigType, DefaultModelConfig
+from module_modeling_llm.prompts import (
+    graded_feedback_prompt,
+    filter_feedback_prompt,
+    structured_grading_instructions_prompt
 )
 
-
 class GenerateSuggestionsPrompt(BaseModel):
     """
     Features available: **{problem_statement}**, **{example_solution}**, **{grading_instructions}**, **{max_points}**,
@@ -18,16 +16,30 @@ class GenerateSuggestionsPrompt(BaseModel):
     _Note: **{problem_statement}**, **{example_solution}**, or **{grading_instructions}** might be omitted if the input
     is too long._
     """
-    graded_feedback_system_message: str = Field(default=default_graded_feedback_system_message,
-        description="Message for priming AI behavior and instructing it what to do.")
-    graded_feedback_human_message: str = Field(default=default_graded_feedback_human_message,
-        description="Message from a human. The input on which the AI is supposed to act.")
-    filter_feedback_system_message: str = Field(default=default_filter_feedback_system_message,
-        description="Message for priming AI behavior for filtering ungraded feedback.")
-    filter_feedback_human_message: str = Field(default=default_filter_feedback_human_message,
-        description="Message for instructing AI to filter ungraded feedback.")
-    
-
+    graded_feedback_system_message: str = Field(
+        default=graded_feedback_prompt.graded_feedback_system_message,
+        description="Message for priming AI behavior and instructing it what to do."
+    )
+    graded_feedback_human_message: str = Field(
+        default=graded_feedback_prompt.graded_feedback_human_message,
+        description="Message from a human. The input on which the AI is supposed to act."
+    )
+    filter_feedback_system_message: str = Field(
+        default=filter_feedback_prompt.filter_feedback_system_message,
+        description="Message for priming AI behavior for filtering ungraded feedback."
+    )
+    filter_feedback_human_message: str = Field(
+        default=filter_feedback_prompt.filter_feedback_human_message,
+        description="Message for instructing AI to filter ungraded feedback."
+    )
+    structured_grading_instructions_system_message: str = Field(
+        default=structured_grading_instructions_prompt.structured_grading_instructions_system_message,
+        description="Message for instructing AI to structure the Problem Statement"
+    )
+    structured_grading_instructions_human_message: str = Field(
+        default=structured_grading_instructions_prompt.structured_grading_instructions_human_message,
+        description="Message for instructing AI to filter ungraded feedback."
+    )
 
 class BasicApproachConfig(BaseModel):
     """This approach uses a LLM with a single prompt to generate feedback in a single step."""
@@ -35,8 +47,7 @@ class BasicApproachConfig(BaseModel):
     model: ModelConfigType = Field(default=DefaultModelConfig())  # type: ignore
     generate_suggestions_prompt: GenerateSuggestionsPrompt = Field(default=GenerateSuggestionsPrompt())
 
-
 @config_schema_provider
 class Configuration(BaseModel):
     debug: bool = Field(default=False, description="Enable debug mode.")
-    approach: BasicApproachConfig = Field(default=BasicApproachConfig())
+    approach: BasicApproachConfig = Field(default=BasicApproachConfig())
\ No newline at end of file
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/core/filter_feedback.py b/modules/modeling/module_modeling_llm/module_modeling_llm/core/filter_feedback.py
new file mode 100644
index 000000000..efe2b1871
--- /dev/null
+++ b/modules/modeling/module_modeling_llm/module_modeling_llm/core/filter_feedback.py
@@ -0,0 +1,52 @@
+from langchain_core.output_parsers import PydanticOutputParser
+from langchain_core.prompts import ChatPromptTemplate
+
+from athena import emit_meta
+from module_modeling_llm.config import BasicApproachConfig
+from llm_core.utils.predict_and_parse import predict_and_parse
+from module_modeling_llm.models.assessment_model import AssessmentModel
+from module_modeling_llm.models.exercise_model import ExerciseModel
+from module_modeling_llm.prompts.filter_feedback_prompt import FilterFeedbackInputs
+
+async def filter_feedback(
+        exercise: ExerciseModel,
+        original_feedback: AssessmentModel,
+        config: BasicApproachConfig,
+        debug: bool,
+) -> AssessmentModel:
+    
+    print(f"\n\n\n\n\n{original_feedback.json()}\n\n\n\n\n")
+
+    chat_prompt = ChatPromptTemplate.from_messages([
+        ("system", config.generate_suggestions_prompt.filter_feedback_system_message),
+        ("human", config.generate_suggestions_prompt.filter_feedback_human_message)
+    ])
+
+    prompt_inputs = FilterFeedbackInputs(
+        original_feedback=original_feedback.json(),
+        feedback_output_format=PydanticOutputParser(pydantic_object=AssessmentModel).get_format_instructions()
+    )
+
+    feedback_result = await predict_and_parse(
+        model=config.model.get_model(), # type: ignore[attr-defined]
+        chat_prompt=chat_prompt,
+        prompt_input=prompt_inputs.dict(),
+        pydantic_object=AssessmentModel,
+        tags=[
+            f"exercise-{exercise.exercise_id}-filter",
+            f"submission-{exercise.submission_id}-filter",
+        ]
+    )
+
+    if debug:
+        emit_meta("filter_feedback", {
+            "prompt": chat_prompt.format(**prompt_inputs.dict()),
+            "result": feedback_result.dict() if feedback_result is not None else None
+        })
+    
+    if feedback_result is None:
+        raise ValueError("No feedback was returned by the model.")
+    
+    print(f"\n\n\n\n\n{feedback_result.json()}\n\n\n\n\n")
+    
+    return feedback_result
\ No newline at end of file
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/core/generate_suggestions.py b/modules/modeling/module_modeling_llm/module_modeling_llm/core/generate_suggestions.py
new file mode 100644
index 000000000..6db69e7d2
--- /dev/null
+++ b/modules/modeling/module_modeling_llm/module_modeling_llm/core/generate_suggestions.py
@@ -0,0 +1,64 @@
+from athena.schemas.grading_criterion import StructuredGradingCriterion
+from langchain_core.output_parsers import PydanticOutputParser
+from langchain_core.prompts import ChatPromptTemplate
+
+from athena import emit_meta
+from module_modeling_llm.config import BasicApproachConfig
+from module_modeling_llm.models.assessment_model import AssessmentModel
+from module_modeling_llm.prompts.apollon_format_description import apollon_format_description
+from llm_core.utils.predict_and_parse import predict_and_parse
+from module_modeling_llm.prompts.graded_feedback_prompt import GradedFeedbackInputs
+from module_modeling_llm.models.exercise_model import ExerciseModel
+
+async def generate_suggestions(
+        exercise_model: ExerciseModel, 
+        structured_grading_instructions: StructuredGradingCriterion,
+        config: BasicApproachConfig,
+        debug: bool) -> AssessmentModel:
+    """
+    Generate feedback suggestions for modeling exercise submissions
+    :param exercise: The exercise for which a submission is assessed
+    :param submission: The submission that is assessed
+    :param is_graded: Indicates whether the submission is graded
+    :param config: A configuration object for the feedback module
+    :param debug: Indicates whether additional debugging information should be provided
+    :return: A list of feedback items for the assessed submission
+    """
+
+    prompt_inputs = GradedFeedbackInputs(
+        submission=exercise_model.transformed_submission,
+        problem_statement=exercise_model.problem_statement,
+        max_points=exercise_model.max_points,
+        bonus_points=exercise_model.bonus_points,
+        structured_grading_instructions=structured_grading_instructions.json(),
+        submission_uml_type=exercise_model.submission_uml_type,
+        example_solution=exercise_model.transformed_example_solution,
+        uml_diagram_format=apollon_format_description,
+        feedback_output_format=PydanticOutputParser(pydantic_object=AssessmentModel).get_format_instructions()
+    )
+
+    chat_prompt = ChatPromptTemplate.from_messages([
+        ("system", config.generate_suggestions_prompt.graded_feedback_system_message),
+        ("human", config.generate_suggestions_prompt.graded_feedback_human_message)])
+
+    feedback_result = await predict_and_parse(
+        model=config.model.get_model(), # type: ignore[attr-defined]
+        chat_prompt=chat_prompt,
+        prompt_input=prompt_inputs.dict(),
+        pydantic_object=AssessmentModel,
+        tags=[
+            f"exercise-{exercise_model.exercise_id}",
+            f"submission-{exercise_model.submission_id}",
+        ]
+    )
+
+    if debug:
+        emit_meta("generate_suggestions", {
+            "prompt": chat_prompt.format(**prompt_inputs.dict()),
+            "result": feedback_result.dict() if feedback_result is not None else None
+        })
+
+    if feedback_result is None:
+        raise ValueError("No feedback was generated")
+    
+    return feedback_result
\ No newline at end of file
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/core/get_structured_grading_instructions.py b/modules/modeling/module_modeling_llm/module_modeling_llm/core/get_structured_grading_instructions.py
new file mode 100644
index 000000000..ae84e0ddf
--- /dev/null
+++ b/modules/modeling/module_modeling_llm/module_modeling_llm/core/get_structured_grading_instructions.py
@@ -0,0 +1,57 @@
+from typing import List, Optional
+from athena.metadata import emit_meta
+from langchain_core.output_parsers import PydanticOutputParser
+from langchain_core.prompts import ChatPromptTemplate
+
+from athena.schemas.grading_criterion import GradingCriterion, StructuredGradingCriterion
+from llm_core.utils.predict_and_parse import predict_and_parse
+from module_modeling_llm.config import BasicApproachConfig
+from module_modeling_llm.models.exercise_model import ExerciseModel
+from module_modeling_llm.prompts.structured_grading_instructions_prompt import StructuredGradingInstructionsInputs
+
+async def get_structured_grading_instructions(
+        exercise_model: ExerciseModel,
+        config: BasicApproachConfig,
+        grading_instructions: Optional[str],
+        grading_criteria: Optional[List[GradingCriterion]],
+        debug: bool
+) -> StructuredGradingCriterion:
+    
+    if grading_criteria:
+        return StructuredGradingCriterion(criteria=grading_criteria)
+
+    chat_prompt = ChatPromptTemplate.from_messages([
+        ("system", config.generate_suggestions_prompt.structured_grading_instructions_system_message),
+        ("human", config.generate_suggestions_prompt.structured_grading_instructions_human_message)])
+    
+    prompt_inputs = StructuredGradingInstructionsInputs(
+            problem_statement=exercise_model.problem_statement or "No problem statement.",
+            max_points=exercise_model.max_points,
+            bonus_points=exercise_model.bonus_points,
+            grading_instructions=grading_instructions or "No grading instructions.",
+            submission_uml_type=exercise_model.submission_uml_type,
+            example_solution=exercise_model.transformed_example_solution or "No example solution.",
+            structured_instructions_output_format=PydanticOutputParser(pydantic_object=StructuredGradingCriterion).get_format_instructions()
+        )
+
+    grading_instruction_result = await predict_and_parse(
+        model=config.model.get_model(), # type: ignore[attr-defined]
+        chat_prompt=chat_prompt,
+        prompt_input=prompt_inputs.dict(),
+        pydantic_object=StructuredGradingCriterion,
+        tags=[
+            f"exercise-{exercise_model.exercise_id}",
+            f"submission-{exercise_model.submission_id}",
+        ]
+    )
+
+    if debug:
+        emit_meta("get_structured_grading_instructions", {
+            "prompt": chat_prompt.format(**prompt_inputs.dict()),
+            "result": grading_instruction_result.dict() if grading_instruction_result is not None else None
+        })
+
+    if not grading_instruction_result:
+        raise ValueError("No structured grading instructions were returned by the model.")
+
+    return grading_instruction_result
\ No newline at end of file
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/generate_suggestions.py b/modules/modeling/module_modeling_llm/module_modeling_llm/generate_suggestions.py
deleted file mode 100644
index 287bdd536..000000000
--- a/modules/modeling/module_modeling_llm/module_modeling_llm/generate_suggestions.py
+++ /dev/null
@@ -1,152 +0,0 @@
-import json
-from typing import List, Optional, Sequence
-
-from module_modeling_llm.prompts.apollon_format import apollon_format_description
-from pydantic import BaseModel, Field
-
-from athena import emit_meta
-from athena.modeling import Exercise, Submission, Feedback
-from module_modeling_llm.config import BasicApproachConfig
-from langchain_core.output_parsers import PydanticOutputParser
-from langchain_core.prompts import ChatPromptTemplate
-from module_modeling_llm.helpers.llm_utils import predict_and_parse
-from module_modeling_llm.helpers.serializers.diagram_model_serializer import DiagramModelSerializer
-from module_modeling_llm.helpers.utils import format_grading_instructions
-
-
-class FeedbackModel(BaseModel):
-    title: str = Field(description="Very short title, i.e. feedback category or similar", example="Logic Error")
-    description: str = Field(description="Feedback description")
-    element_names: Optional[List[str]] = Field(description="Referenced diagram element names, and relations (R<number>) or empty if unreferenced")
-    credits: float = Field(0.0, description="Number of points received/deducted")
-    grading_instruction_id: Optional[int] = Field(
-        description="ID of the grading instruction that was used to generate this feedback, or empty if no grading instruction was used"
-    )
-
-    class Config:
-        title = "Feedback"
-
-
-class AssessmentModel(BaseModel):
-    """Collection of feedbacks making up an assessment"""
-
-    feedbacks: Sequence[FeedbackModel] = Field(description="Assessment feedbacks, make sure to include all grading instructions")
-
-    class Config:
-        title = "Assessment"
-
-
-async def generate_suggestions(exercise: Exercise, submission: Submission, is_graded: bool, config: BasicApproachConfig, debug: bool) -> \
-        List[Feedback]:
-    """
-    Generate feedback suggestions for modeling exercise submissions
-    :param exercise: The exercise for which a submission is assessed
-    :param submission: The submission that is assessed
-    :param config: A configuration object for the feedback module
-    :param debug: Indicates whether additional debugging information should be provided
-    :return: A list of feedback items for the assessed submission
-    """
-    model = config.model.get_model()  # type: ignore[attr-defined]
-
-    serialized_example_solution = None
-    if exercise.example_solution:
-        example_solution_diagram = json.loads(exercise.example_solution)
-        serialized_example_solution, _ = DiagramModelSerializer.serialize_model(example_solution_diagram)
-
-    submission_diagram = json.loads(submission.model)
-    serialized_submission, element_id_mapping = DiagramModelSerializer.serialize_model(submission_diagram)
-
-    prompt_input = {
-        "max_points": exercise.max_points,
-        "bonus_points": exercise.bonus_points,
-        "grading_instructions": format_grading_instructions(exercise.grading_instructions, exercise.grading_criteria),
-        "submission_format": submission_diagram.get("type"),
-        "problem_statement": exercise.problem_statement or "No problem statement.",
-        "example_solution": serialized_example_solution or "No example solution.",
-        "submission": serialized_submission,
-        "uml_diagram_format": apollon_format_description,
-        "format_instructions": PydanticOutputParser(pydantic_object=AssessmentModel).get_format_instructions()
-    }
-
-    chat_prompt =  ChatPromptTemplate.from_messages([
-        ("system", config.generate_suggestions_prompt.graded_feedback_system_message),
-        ("human", config.generate_suggestions_prompt.graded_feedback_human_message)])
-
-    result = await predict_and_parse(
-        model=model,
-        chat_prompt=chat_prompt,
-        prompt_input=prompt_input,
-        pydantic_object=AssessmentModel,
-        tags=[
-            f"exercise-{exercise.id}",
-            f"submission-{submission.id}",
-        ]
-    )
-
-    if debug:
-        emit_meta("generate_suggestions", {
-            "prompt": chat_prompt.format(**prompt_input),
-            "result": result.dict() if result is not None else None
-        })
-
-    if result is None:
-        return []
-
-    # Check if is graded
-    if is_graded is False:
-        filter_chat_prompt = ChatPromptTemplate.from_messages([
-            ("system", config.generate_suggestions_prompt.filter_feedback_system_message),
-            ("human", config.generate_suggestions_prompt.filter_feedback_human_message)
-        ])
-        
-        filter_prompt_input = {
-            "original_feedback": result.dict(),
-            "format_instructions": PydanticOutputParser(pydantic_object=AssessmentModel).get_format_instructions()
-        }
-
-        result = await predict_and_parse(
-            model=model,
-            chat_prompt=filter_chat_prompt,
-            prompt_input=filter_prompt_input,
-            pydantic_object=AssessmentModel,
-            tags=[
-                f"exercise-{exercise.id}-filter",
-                f"submission-{submission.id}-filter",
-            ]
-        )
-
-        if debug:
-            emit_meta("filter_feedback", {
-                "prompt": filter_chat_prompt.format(**filter_prompt_input),
-                "result": result.dict() if result is not None else None
-            })
-        
-        if result is None:
-            return []
-
-    grading_instruction_ids = set(
-        grading_instruction.id
-        for criterion in exercise.grading_criteria or []
-        for grading_instruction in criterion.structured_grading_instructions
-    )
-
-    feedbacks = []
-    for feedback in result.feedbacks:
-        grading_instruction_id = feedback.grading_instruction_id if feedback.grading_instruction_id in grading_instruction_ids else None
-        element_ids = [element_id_mapping[element] for element in (feedback.element_names or [])]
-
-
-        feedbacks.append(Feedback(
-            exercise_id=exercise.id,
-            submission_id=submission.id,
-            title=feedback.title,
-            description=feedback.description,
-            element_ids=element_ids,
-            credits=feedback.credits,
-            structured_grading_instruction_id=grading_instruction_id,
-            meta={},
-            id=None,
-            is_graded=is_graded
-        ))
-
-    return feedbacks
\ No newline at end of file
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/models/__init__.py b/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/models/__init__.py
deleted file mode 100644
index 9233a644b..000000000
--- a/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/models/__init__.py
+++ /dev/null
@@ -1,38 +0,0 @@
-import os
-from typing import Type, Union, List, Optional
-from langchain.base_language import BaseLanguageModel
-
-from module_modeling_llm.helpers.models.model_config import ModelConfig
-
-
-DefaultModelConfig: Type[ModelConfig]
-default_model_name = os.environ.get("LLM_DEFAULT_MODEL")
-evaluation_model_name = os.environ.get("LLM_EVALUATION_MODEL")
-
-# Model used during evaluation for judging the output (should be a more powerful model)
-evaluation_model: Optional[BaseLanguageModel] = None
-
-types: List[Type[ModelConfig]] = []
-try:
-    import module_modeling_llm.helpers.models.openai as openai_config
-    types.append(openai_config.OpenAIModelConfig)
-    if default_model_name in openai_config.available_models:
-        DefaultModelConfig = openai_config.OpenAIModelConfig
-    if evaluation_model_name in openai_config.available_models:
-        evaluation_model = openai_config.available_models[evaluation_model_name]
-except AttributeError:
-    pass
-
-if not types:
-    raise EnvironmentError(
-        "No model configurations available, please set up at least one provider in the environment variables.")
-
-if 'DefaultModelConfig' not in globals():
-    DefaultModelConfig = types[0]
-
-type0 = types[0]
-if len(types) == 1:
-    ModelConfigType = type0
-else:
-    type1 = types[1]
-    ModelConfigType = Union[type0, type1] # type: ignore
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/models/diagram_types.py b/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/models/diagram_types.py
deleted file mode 100644
index b41d42482..000000000
--- a/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/models/diagram_types.py
+++ /dev/null
@@ -1,16 +0,0 @@
-from enum import Enum
-
-
-class DiagramType(str, Enum):
-    CLASS_DIAGRAM = "ClassDiagram"
-    OBJECT_DIAGRAM = "ObjectDiagram"
-    ACTIVITY_DIAGRAM = "ActivityDiagram"
-    USE_CASE_DIAGRAM = "UseCaseDiagram"
-    COMMUNICATION_DIAGRAM = "CommunicationDiagram"
-    COMPONENT_DIAGRAM = "ComponentDiagram"
-    DEPLOYMENT_DIAGRAM = "DeploymentDiagram"
-    PETRI_NET = "PetriNet"
-    REACHABILITY_GRAPH = "ReachabilityGraph"
-    SYNTAX_TREE = "SyntaxTree"
-    FLOWCHART = "Flowchart"
-    BPMN = "BPMN"
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/models/model_config.py b/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/models/model_config.py
deleted file mode 100644
index 44bccaf29..000000000
--- a/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/models/model_config.py
+++ /dev/null
@@ -1,11 +0,0 @@
-from abc import ABC, abstractmethod
-
-from langchain.base_language import BaseLanguageModel
-from pydantic import BaseModel
-
-
-class ModelConfig(BaseModel, ABC):
-
-    @abstractmethod
-    def get_model(self) -> BaseLanguageModel:
-        pass
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/models/openai.py b/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/models/openai.py
deleted file mode 100644
index bb08e409d..000000000
--- a/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/models/openai.py
+++ /dev/null
@@ -1,141 +0,0 @@
-import os
-import openai
-import requests
-
-from typing import Dict, List
-from enum import Enum
-from pydantic import Field, validator, PositiveInt
-from langchain.base_language import BaseLanguageModel
-from langchain_openai import AzureChatOpenAI, ChatOpenAI
-
-from athena.logger import logger
-from .model_config import ModelConfig
-
-OPENAI_PREFIX = "openai_"
-AZURE_OPENAI_PREFIX = "azure_openai_"
-openai_available = bool(os.environ.get("OPENAI_API_KEY"))
-azure_openai_available = bool(os.environ.get("AZURE_OPENAI_API_KEY"))
-
-available_models: Dict[str, BaseLanguageModel] = {}
-
-# Load Non-Azure OpenAI models
-if openai_available:
-    openai.api_type = "openai"
-    for model in openai.models.list():
-        if "gpt" in model.id:
-            available_models[OPENAI_PREFIX + model.id] = ChatOpenAI(model=model.id)
-
-# Load Azure OpenAI models
-if azure_openai_available:
-    def _get_azure_openai_deployments() -> List[str]:
-        # If this breaks in the future we have to use azure-mgmt-cognitiveservices which needs 6 additional environment variables
-        base_url = f"{os.environ.get('AZURE_OPENAI_ENDPOINT')}/openai"
-        headers = {
-            "api-key": os.environ["AZURE_OPENAI_API_KEY"]
-        }
-
-        models_response = requests.get(f"{base_url}/models?api-version=2023-03-15-preview", headers=headers, timeout=60)
-        models_data = models_response.json()["data"]
-        deployments_response = requests.get(f"{base_url}/deployments?api-version=2023-03-15-preview", headers=headers, timeout=60)
-        deployments_data = deployments_response.json()["data"]
-
-        # Check if deployment["model"] is a substring of model["id"], i.e. "gpt-4o" is substring "gpt-4o-2024-05-13"
-        chat_completion_models = ",".join(model["id"] for model in models_data if model["capabilities"]["chat_completion"])
-        return [deployment["id"] for deployment in deployments_data if deployment["model"] in chat_completion_models]
-
-    for deployment in _get_azure_openai_deployments():
-        available_models[AZURE_OPENAI_PREFIX + deployment] = AzureChatOpenAI(azure_deployment=deployment)
-
-if available_models:
-    logger.info("Available openai models: %s", ", ".join(available_models.keys()))
-
-    OpenAIModel = Enum('OpenAIModel', {name: name for name in available_models}) # type: ignore
-    default_model_name = None
-    if "LLM_DEFAULT_MODEL" in os.environ and os.environ["LLM_DEFAULT_MODEL"] in available_models:
-        default_model_name = os.environ["LLM_DEFAULT_MODEL"]
-    if default_model_name not in available_models:
-        default_model_name = list(available_models.keys())[0]
-
-    default_openai_model = OpenAIModel[default_model_name] # type: ignore
-
-    # Long descriptions will be displayed in the playground UI and are copied from the OpenAI docs
-    class OpenAIModelConfig(ModelConfig):
-        """OpenAI LLM configuration."""
-
-        model_name: OpenAIModel = Field(default=default_openai_model, # type: ignore
-                                        description="The name of the model to use.")
-        max_tokens: PositiveInt = Field(1000, description="""\
-The maximum number of [tokens](https://platform.openai.com/tokenizer) to generate in the chat completion.
-
-The total length of input tokens and generated tokens is limited by the model's context length. \
-[Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb) for counting tokens.\
-""")
-
-        temperature: float = Field(default=0.0, ge=0, le=2, description="""\
-What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, \
-while lower values like 0.2 will make it more focused and deterministic.
-
-We generally recommend altering this or `top_p` but not both.\
-""")
-
-        top_p: float = Field(default=1, ge=0, le=1, description="""\
-An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. \
-So 0.1 means only the tokens comprising the top 10% probability mass are considered.
-
-We generally recommend altering this or `temperature` but not both.\
-""")
-
-        presence_penalty: float = Field(default=0, ge=-2, le=2, description="""\
-Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, \
-increasing the model's likelihood to talk about new topics.
-
-[See more information about frequency and presence penalties.](https://platform.openai.com/docs/api-reference/parameter-details)\
-""")
-
-        frequency_penalty: float = Field(default=0, ge=-2, le=2, description="""\
-Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, \
-decreasing the model's likelihood to repeat the same line verbatim.
-
-[See more information about frequency and presence penalties.](https://platform.openai.com/docs/api-reference/parameter-details)\
-""")
-
-        @validator('max_tokens')
-        def max_tokens_must_be_positive(cls, v):
-            """
-            Validate that max_tokens is a positive integer.
-            """
-            if v <= 0:
-                raise ValueError('max_tokens must be a positive integer')
-            return v
-
-        def get_model(self) -> BaseLanguageModel:
-            """Get the model from the configuration.
-
-            Returns:
-                BaseLanguageModel: The model.
-            """
-            model = available_models[self.model_name.value]
-            kwargs = model.__dict__
-            secrets = {secret: getattr(model, secret) for secret in model.lc_secrets.keys()}
-            kwargs.update(secrets)
-
-            model_kwargs = kwargs.get("model_kwargs", {})
-            for attr, value in self.dict().items():
-                if attr == "model_name":
-                    # Skip model_name
-                    continue
-                if hasattr(model, attr):
-                    # If the model has the attribute, add it to kwargs
-                    kwargs[attr] = value
-                else:
-                    # Otherwise, add it to model_kwargs (necessary for chat models)
-                    model_kwargs[attr] = value
-            kwargs["model_kwargs"] = model_kwargs
-
-            # Initialize a copy of the model using the config
-            model = model.__class__(**kwargs)
-            return model
-
-
-        class Config:
-            title = 'OpenAI'
\ No newline at end of file
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/utils.py b/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/utils.py
deleted file mode 100644
index a7078dc6f..000000000
--- a/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/utils.py
+++ /dev/null
@@ -1,61 +0,0 @@
-from typing import List, Optional
-
-import tiktoken
-
-from athena import GradingCriterion
-
-
-# This is correct for gpt-4 and chat gpt3.5 but might be different for other models
-def num_tokens_from_string(string: str) -> int:
-    """Returns the number of tokens in a text string."""
-    encoding = tiktoken.get_encoding("cl100k_base")
-    num_tokens = len(encoding.encode(string))
-    return num_tokens
-
-
-def format_grading_instructions(grading_instructions: Optional[str],
-                                grading_criteria: Optional[List[GradingCriterion]]) -> Optional[str]:
-    """Formats grading instructions and the grading criteria with nested structured grading instructions into a single string.
-
-    Args:
-        grading_instructions (Optional[str]): Grading instructions
-        grading_criteria (Optional[List[GradingCriterion]]): Grading criteria with nested structured grading instructions
-
-    Returns:
-        Optional[str]: Formatted grading instructions or None if no grading instructions or grading criteria are provided
-    """
-
-    if not grading_instructions and not grading_criteria:
-        return None
-
-    result = ""
-    if grading_instructions:
-        result += grading_instructions + "\n\n"
-
-    if grading_criteria:
-        for grading_criterion in grading_criteria:
-            result += f'Criterion > "{(grading_criterion.title or "Unnamed criterion")}":\n'
-            for grading_instruction in grading_criterion.structured_grading_instructions:
-                result += f'  - grading_instruction_id={grading_instruction.id} > "{grading_instruction.feedback}": ('
-                if grading_instruction.usage_count > 0:
-                    result += f'can be used {grading_instruction.usage_count} times in total'
-                else:
-                    result += "can be used unlimited times"
-                result += f', gives {grading_instruction.credits} credits for "{grading_instruction.grading_scale}" grading scale, '
-                result += f'usage description: "{grading_instruction.instruction_description}")\n'
-            result += "\n"
-
-    return result.strip()
-
-
-def get_elements(model: dict) -> list[dict]:
-    """
-    Helper method to retrieve the elements of a model backwards compatible with Apollon version 2 diagrams
-    """
-
-    elements: list | dict = model.get("elements", {})
-
-    if isinstance(elements, list):
-        return elements
-
-    return list(elements.values())
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/models/assessment_model.py b/modules/modeling/module_modeling_llm/module_modeling_llm/models/assessment_model.py
new file mode 100644
index 000000000..9ccc1933d
--- /dev/null
+++ b/modules/modeling/module_modeling_llm/module_modeling_llm/models/assessment_model.py
@@ -0,0 +1,22 @@
+from typing import List, Optional, Sequence
+from pydantic import BaseModel, Field
+
+class FeedbackModel(BaseModel):
+    title: str = Field(description="Very short title, i.e. feedback category or similar", example="Logic Error")
+    description: str = Field(description="Feedback description")
+    element_names: Optional[List[str]] = Field(description="Referenced diagram element names, and relations (R<number>) or empty if unreferenced")
+    credits: float = Field(0.0, description="Number of points received/deducted")
+    grading_instruction_id: int = Field(
+        description="ID of the grading instruction that was used to generate this feedback"
+    )
+
+    class Config:
+        title = "Feedback"
+
+class AssessmentModel(BaseModel):
+    """Collection of feedbacks making up an assessment"""
+
+    feedbacks: Sequence[FeedbackModel] = Field(description="Assessment feedbacks, make sure to include all grading instructions")
+
+    class Config:
+        title = "Assessment"
\ No newline at end of file
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/models/exercise_model.py b/modules/modeling/module_modeling_llm/module_modeling_llm/models/exercise_model.py
new file mode 100644
index 000000000..3a6f0672f
--- /dev/null
+++ b/modules/modeling/module_modeling_llm/module_modeling_llm/models/exercise_model.py
@@ -0,0 +1,14 @@
+from typing import Optional
+from pydantic import BaseModel
+
+class ExerciseModel(BaseModel):
+    submission_id: int
+    exercise_id: int
+    transformed_submission: str
+    problem_statement: Optional[str] = None
+    max_points: float
+    bonus_points: float
+    grading_instructions: Optional[str] = None
+    submission_uml_type: str
+    transformed_example_solution: Optional[str] = None
+    element_id_mapping: dict[str, str]
\ No newline at end of file
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/prompts/apollon_format.py b/modules/modeling/module_modeling_llm/module_modeling_llm/prompts/apollon_format_description.py
similarity index 85%
rename from modules/modeling/module_modeling_llm/module_modeling_llm/prompts/apollon_format.py
rename to modules/modeling/module_modeling_llm/module_modeling_llm/prompts/apollon_format_description.py
index 7dd4f5b77..e468883de 100644
--- a/modules/modeling/module_modeling_llm/module_modeling_llm/prompts/apollon_format.py
+++ b/modules/modeling/module_modeling_llm/module_modeling_llm/prompts/apollon_format_description.py
@@ -43,6 +43,12 @@
 <ElementOwner>: [<elementName>]
 ```
 
+##### Naming
+
+When there are elements in the original diagram with the same name, the Apollon format appends a unique suffix to each duplicate name to ensure clarity and avoid ambiguity. This suffix can be identified by the `#` symbol followed by an uppercase letter.
+
+When there are elements in the original diagram with no name, the Apollon format assignes them uppercase letters for the name. These can be identified by the `##` symbol followed by an uppercase letter.
+
 ##### Detailed Breakdown
 
 - **Elements**: 
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/prompts/filter_feedback_prompt.py b/modules/modeling/module_modeling_llm/module_modeling_llm/prompts/filter_feedback_prompt.py
new file mode 100644
index 000000000..ef048ebe2
--- /dev/null
+++ b/modules/modeling/module_modeling_llm/module_modeling_llm/prompts/filter_feedback_prompt.py
@@ -0,0 +1,58 @@
+from pydantic import BaseModel
+
+
+class FilterFeedbackInputs(BaseModel):
+    original_feedback: str
+    feedback_output_format: str
+
+
+filter_feedback_system_message = """
+Your task is to modify given feedback. This feedback was originally created for tutors to help them grade student submissions. We want to use this same feedback for students before the due date of the assignment. However we need to make sure that the feedback does not give away the solution. Your task is to modify the feedback so that it is appropriate for students.
+
+Follow these guidelines when filtering and rewriting the feedback:
+
+- Avoid revealing specific solutions or correct answers.
+- Focus on providing general guidance and encouragement.
+- Highlight areas that need improvement without giving away the solution.
+- Maintain a positive and constructive tone.
+- Provide hints or suggestions rather than direct corrections.
+- Keep the feedback concise and to the point.
+- Ensure that the feedback is still relevant and helpful for the student's learning process.
+- Really Important: When its incorrect, make sure to **not** provide the correct answer or mention specific detials
+- When the feedback indicates that the student correctly implemented something, you should acknowledge their success and mention the specific elements they did well. Do not remove or generalize positive feedback.
+
+Keep the original structure, just change the title and description of the feedback
+
+For example, original feedback:
+"title": "Missing Start Event"
+"description": "The process is missing the start event"
+...
+"title": "Method Drive" 
+"description": "Consider adding a 'drive' method to the 'Car' class. Think about what actions this method should perform."
+...
+"title": "Class Car"
+"description": "Class 'Car' is correctly defined."
+
+
+Filtered and rewritten feedback:
+"title": "Process Initiation"
+"description": "Consider how your process begins. Is there a clear starting point? Review the standard elements used to indicate the commencement of a process flow."
+...
+"title": "Missing Method"
+"description": "Read the problem statement carefully and consider what methods are necessary to implement the required functionality. Is the car class missing any methods that are essential for the car to function correctly?"
+...
+"title": "Class Car"
+"description": "Class 'Car' is correctly defined."
+
+Remember, the goal is to guide the student towards improvement without providing a complete solution or grading information in the feedback. Also keep the original structure of the feedback. Just modify the title and description values.
+
+<Output Format>
+{feedback_output_format}
+"""
+
+filter_feedback_human_message = """
+<Original Graded Feedback>
+{original_feedback}
+
+Please return the feedback in the correct output json format:
+"""
\ No newline at end of file
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/prompts/generate_suggestions.py b/modules/modeling/module_modeling_llm/module_modeling_llm/prompts/generate_suggestions.py
deleted file mode 100644
index 644687828..000000000
--- a/modules/modeling/module_modeling_llm/module_modeling_llm/prompts/generate_suggestions.py
+++ /dev/null
@@ -1,113 +0,0 @@
-# Constants for prompt components
-ROLE = "You are an AI tutor for {submission_format} modeling exercise assessment at a prestigious university."
-
-GRADED_FEEDBACK_TASK = """
-Create graded feedback suggestions for a student's {submission_format} modeling submission that a human tutor would accept.
-Meaning, the feedback you provide should be applicable to the submission with little to no modification.
-"""
-
-NON_GRADED_FEEDBACK_TASK = """
-Your task is to modify given feedback. This feedback was originally created for tutors to help them grade student submissions. We want to use this same feedback for students before the due date of the assignment. However we need to make sure that the feedback does not give away the solution. Your task is to modify the feedback so that it is appropriate for students.
-
-Follow these guidelines when filtering and rewriting the feedback:
-
-- Avoid revealing specific solutions or correct answers.
-- Focus on providing general guidance and encouragement.
-- Highlight areas that need improvement without giving away the solution.
-- Maintain a positive and constructive tone.
-- Provide hints or suggestions rather than direct corrections.
-- Keep the feedback concise and to the point.
-- Ensure that the feedback is still relevant and helpful for the student's learning process.
-
-Keep the original strucute, just change the title and description of the feedback
-
-For example, original feedback:
-"title": "Missing Start Event"
-"description": "The process is missing the start event"
-...
-
-Filtered and rewritten feedback:
-"title": "Process Initiation"
-"description": "Consider how your process begins. Is there a clear starting point? Review the standard elements used to indicate the commencement of a process flow."
-...
-
-Remember, the goal is to guide the student towards improvement without providing a complete solution or grading information in the feedback. Also keep the original structure of the feedback. Just modify the title and description values.
-"""
-
-STYLE = """
-<Feedback Style>
-1. Constructive
-2. Specific
-3. Balanced
-4. Clear and Concise
-5. Actionable
-6. Educational
-7. Contextual
-"""
-
-PROBLEM_STATEMENT = """
-<Exercise Problem Statement>
-{problem_statement}
-"""
-
-EXERCISE_GRADING_INSTRUCTIONS = """
-<Grading Instructions>
-
-Max points: {max_points}, bonus points: {bonus_points}\
-
-Instructions:
-{grading_instructions}
-"""
-
-GRADING_INSTRUCTIONS = """
-Important:
-Make sure to provide detailed feedback for each criterion. Always try to be as specific as possible.
-Also make sure your feedback adds up to the correct number of points. If there are n points available and everything is correct, then the feedback should add up to n points.
-Deeply think about the diagram and what the student potentially missed, misunderstood or mixed up.
-
-Example:
-- Element 1: 1 point
-- Element 2: 1 point
-- Element 3: 0 points
-- Element 4: 1 point
-- Element 5: 1 point
-- Relation 1: 1 point
-- Relation 2: 1 point
-...
-"""
-
-UML_DIAGRAM_FORMAT = """
-<UML Diagram Format>
-The submission uses the following UML diagram format:
-{uml_diagram_format}
-"""
-
-FORMAT_INSTRUCTIONS = """
-<Output Format>
-{format_instructions}
-"""
-
-OFFICIAL_EXAMPLE_SOLUTION = """
-<Official Example Solution>
-{example_solution}
-"""
-
-STUDENT_SUBMISSION = """
-<Student Submission>
-{submission}
-"""
-
-OUTPUT_FORMAT = """
-Please return the feedback in the correct json format.
-"""
-
-GRADED_FEEDBACK_OUTPUT = """
-<Original Graded Feedback>
-{original_feedback}
-"""
-
-graded_feedback_system_message = f"{ROLE}\n\n{GRADED_FEEDBACK_TASK}\n\n{STYLE}\n\n{PROBLEM_STATEMENT}\n\n{EXERCISE_GRADING_INSTRUCTIONS}\n\n{OFFICIAL_EXAMPLE_SOLUTION}\n\n{GRADING_INSTRUCTIONS}\n\n{UML_DIAGRAM_FORMAT}\n\n{FORMAT_INSTRUCTIONS}"
-graded_feedback_human_message = f"{STUDENT_SUBMISSION}\n\n{OUTPUT_FORMAT}"
-
-filter_feedback_system_message = f"{NON_GRADED_FEEDBACK_TASK}\n\n{FORMAT_INSTRUCTIONS}"
-filter_feedback_human_message = f"{GRADED_FEEDBACK_OUTPUT}\n\n{OUTPUT_FORMAT}"
\ No newline at end of file
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/prompts/graded_feedback_prompt.py b/modules/modeling/module_modeling_llm/module_modeling_llm/prompts/graded_feedback_prompt.py
new file mode 100644
index 000000000..f2fa1390f
--- /dev/null
+++ b/modules/modeling/module_modeling_llm/module_modeling_llm/prompts/graded_feedback_prompt.py
@@ -0,0 +1,63 @@
+from typing import Optional
+from pydantic import BaseModel
+
+
+class GradedFeedbackInputs(BaseModel):
+    submission: str
+    problem_statement: Optional[str] = None
+    max_points: float
+    bonus_points: float
+    structured_grading_instructions: str
+    submission_uml_type: str
+    example_solution: Optional[str] = None
+    uml_diagram_format: str
+    feedback_output_format: str
+
+
+graded_feedback_system_message = """
+You are an AI tutor for {submission_uml_type} modeling exercise assessment at a prestigious university.
+
+Create graded feedback suggestions for a student's {submission_uml_type} modeling submission that a human tutor would accept.
+Meaning, the feedback you provide should be applicable to the submission with little to no modification.
+
+<Feedback Style>
+1. Constructive
+2. Specific
+3. Balanced
+4. Clear and Concise
+5. Actionable
+6. Educational
+7. Contextual
+
+<Exercise Problem Statement>
+{problem_statement}
+
+<Grading Instructions>
+Max points: {max_points}, bonus points: {bonus_points}
+
+Instructions:
+{structured_grading_instructions}
+
+<Official Example Solution>
+{example_solution}
+
+Important:
+Make sure to provide detailed feedback for each criterion. Always try to be as specific as possible.
+Also make sure your feedback adds up to the correct number of points. If there are n points available and everything is correct, then the feedback should add up to n points.
+Deeply think about the diagram and what the student potentially missed, misunderstood or mixed up.
+
+<UML Diagram Format>
+The submission uses the following UML diagram format:
+{uml_diagram_format}
+- Note: Don't mention elements that have no name, by there articial name: e.g. ##A or ##B, instad just say e.g. the task in ... is missing ...
+
+<Output Format>
+{feedback_output_format}
+"""
+
+graded_feedback_human_message = """
+<Student Submission>
+{submission}
+
+Please return the feedback in the correct output json format:
+"""
\ No newline at end of file
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/prompts/structured_grading_instructions_prompt.py b/modules/modeling/module_modeling_llm/module_modeling_llm/prompts/structured_grading_instructions_prompt.py
new file mode 100644
index 000000000..9db3e6bef
--- /dev/null
+++ b/modules/modeling/module_modeling_llm/module_modeling_llm/prompts/structured_grading_instructions_prompt.py
@@ -0,0 +1,36 @@
+from pydantic import BaseModel
+
+
+class StructuredGradingInstructionsInputs(BaseModel):
+    problem_statement: str
+    max_points: float
+    bonus_points: float
+    grading_instructions: str
+    submission_uml_type: str
+    example_solution: str
+    structured_instructions_output_format: str
+
+
+structured_grading_instructions_system_message = """You are an AI tutor for {submission_uml_type} modeling exercise assessment at a prestigious university.
+
+Create a structured grading instruction based on the given grading instructions (important), the solution diagram (if present) and the problem statement. The structured grading instruction should be highly detailed to ensure consistent grading across different tutors.
+
+<Output Format>
+{structured_instructions_output_format}
+"""
+
+structured_grading_instructions_human_message = """
+<Exercise Problem Statement>
+{problem_statement}
+
+<Grading Instructions>
+Max points: {max_points}, bonus points: {bonus_points}
+
+Instructions:
+{grading_instructions}
+
+<Official Example Solution>
+{example_solution}
+
+Please return the structured grading instructions in the correct output json format.
+"""
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/helpers/serializers/__init__.py b/modules/modeling/module_modeling_llm/module_modeling_llm/utils/__init__.py
similarity index 100%
rename from modules/modeling/module_modeling_llm/module_modeling_llm/helpers/serializers/__init__.py
rename to modules/modeling/module_modeling_llm/module_modeling_llm/utils/__init__.py
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/utils/convert_to_athana_feedback_model.py b/modules/modeling/module_modeling_llm/module_modeling_llm/utils/convert_to_athana_feedback_model.py
new file mode 100644
index 000000000..06b4b5a66
--- /dev/null
+++ b/modules/modeling/module_modeling_llm/module_modeling_llm/utils/convert_to_athana_feedback_model.py
@@ -0,0 +1,43 @@
+from typing import List, Optional
+from athena.modeling import Feedback
+from athena.schemas.grading_criterion import GradingCriterion
+from module_modeling_llm.models.assessment_model import AssessmentModel
+from module_modeling_llm.models.exercise_model import ExerciseModel
+
+
+def convert_to_athana_feedback_model(
+        feedback_result : AssessmentModel, 
+        exercise_model: ExerciseModel, 
+        manual_structured_grading_instructions: Optional[List[GradingCriterion]] = None
+    ) -> List[Feedback]:
+
+    grading_instruction_ids = set(
+        grading_instruction.id
+        for criterion in manual_structured_grading_instructions or []
+        for grading_instruction in criterion.structured_grading_instructions
+    )
+
+    feedbacks = []
+    for feedback in feedback_result.feedbacks:
+        # Each feedback has a grading_instruction_id. However we only want to have the grading_instruction_id in the final feedback that are associated with the manual structured grading instructions
+        grading_instruction_id = feedback.grading_instruction_id if feedback.grading_instruction_id in grading_instruction_ids else None
+        element_ids = [
+            exercise_model.element_id_mapping[element] 
+            for element in (feedback.element_names or [])
+            if element in exercise_model.element_id_mapping
+        ]
+
+        feedbacks.append(Feedback(
+            exercise_id=exercise_model.exercise_id,
+            submission_id=exercise_model.submission_id,
+            title=feedback.title,
+            description=feedback.description,
+            element_ids=element_ids,
+            credits=feedback.credits,
+            structured_grading_instruction_id=grading_instruction_id,
+            meta={},
+            id=None,
+            is_graded=False
+        ))
+
+    return feedbacks
\ No newline at end of file
diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/utils/get_exercise_model.py b/modules/modeling/module_modeling_llm/module_modeling_llm/utils/get_exercise_model.py
new file mode 100644
index 000000000..a2457f1f4
--- /dev/null
+++ b/modules/modeling/module_modeling_llm/module_modeling_llm/utils/get_exercise_model.py
@@ -0,0 +1,27 @@
+from athena.modeling import Exercise, Submission
+from module_modeling_llm.models.exercise_model import ExerciseModel
+from module_modeling_llm.apollon_transformer.apollon_json_transformer import ApollonJSONTransformer
+
+
+def get_exercise_model(exercise: Exercise, submission: Submission) -> ExerciseModel:
+
+    serialized_example_solution = None
+    if exercise.example_solution:
+        serialized_example_solution, _, _ = ApollonJSONTransformer.transform_json(exercise.example_solution)
+
+    transformed_submission, element_id_mapping, diagram_type = ApollonJSONTransformer.transform_json(submission.model)
+
+    return ExerciseModel(
+        submission_id=submission.id,
+        exercise_id=exercise.id,
+        transformed_submission=transformed_submission,
+        problem_statement=exercise.problem_statement,
+        max_points=exercise.max_points,
+        bonus_points=exercise.bonus_points,
+        grading_instructions=exercise.grading_instructions,
+        submission_uml_type=diagram_type,
+        transformed_example_solution=serialized_example_solution,
+        element_id_mapping=element_id_mapping,
+    )
+
+    
diff --git a/modules/modeling/module_modeling_llm/poetry.lock b/modules/modeling/module_modeling_llm/poetry.lock
index b498f3731..f8b8d2f74 100644
--- a/modules/modeling/module_modeling_llm/poetry.lock
+++ b/modules/modeling/module_modeling_llm/poetry.lock
@@ -2,113 +2,113 @@
 
 [[package]]
 name = "aiohappyeyeballs"
-version = "2.4.0"
+version = "2.4.3"
 description = "Happy Eyeballs for asyncio"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "aiohappyeyeballs-2.4.0-py3-none-any.whl", hash = "sha256:7ce92076e249169a13c2f49320d1967425eaf1f407522d707d59cac7628d62bd"},
-    {file = "aiohappyeyeballs-2.4.0.tar.gz", hash = "sha256:55a1714f084e63d49639800f95716da97a1f173d46a16dfcfda0016abb93b6b2"},
+    {file = "aiohappyeyeballs-2.4.3-py3-none-any.whl", hash = "sha256:8a7a83727b2756f394ab2895ea0765a0a8c475e3c71e98d43d76f22b4b435572"},
+    {file = "aiohappyeyeballs-2.4.3.tar.gz", hash = "sha256:75cf88a15106a5002a8eb1dab212525c00d1f4c0fa96e551c9fbe6f09a621586"},
 ]
 
 [[package]]
 name = "aiohttp"
-version = "3.10.5"
+version = "3.10.10"
 description = "Async http client/server framework (asyncio)"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -117,7 +117,7 @@ aiosignal = ">=1.1.2"
 attrs = ">=17.3.0"
 frozenlist = ">=1.1.1"
 multidict = ">=4.5,<7.0"
-yarl = ">=1.0,<2.0"
+yarl = ">=1.12.0,<2.0"
 
 [package.extras]
 speedups = ["Brotli", "aiodns (>=3.2.0)", "brotlicffi"]
@@ -138,13 +138,13 @@ frozenlist = ">=1.1.0"
 
 [[package]]
 name = "anyio"
-version = "4.4.0"
+version = "4.6.2.post1"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
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-    {file = "anyio-4.4.0.tar.gz", hash = "sha256:5aadc6a1bbb7cdb0bede386cac5e2940f5e2ff3aa20277e991cf028e0585ce94"},
+    {file = "anyio-4.6.2.post1-py3-none-any.whl", hash = "sha256:6d170c36fba3bdd840c73d3868c1e777e33676a69c3a72cf0a0d5d6d8009b61d"},
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 ]
 
 [package.dependencies]
@@ -152,25 +152,21 @@ idna = ">=2.8"
 sniffio = ">=1.1"
 
 [package.extras]
-doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
-test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
-trio = ["trio (>=0.23)"]
+doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21.0b1)"]
+trio = ["trio (>=0.26.1)"]
 
 [[package]]
 name = "astroid"
-version = "2.15.8"
+version = "3.3.5"
 description = "An abstract syntax tree for Python with inference support."
 optional = false
-python-versions = ">=3.7.2"
+python-versions = ">=3.9.0"
 files = [
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 ]
 
-[package.dependencies]
-lazy-object-proxy = ">=1.4.0"
-wrapt = {version = ">=1.14,<2", markers = "python_version >= \"3.11\""}
-
 [[package]]
 name = "athena"
 version = "1.0.0"
@@ -178,7 +174,7 @@ description = "This is a helper module for easier development of Athena modules.
 optional = false
 python-versions = "3.11.*"
 files = []
-develop = false
+develop = true
 
 [package.dependencies]
 fastapi = "^0.109.1"
@@ -189,11 +185,8 @@ sqlalchemy = {version = "^2.0.21", extras = ["mypy"]}
 uvicorn = "^0.23.0"
 
 [package.source]
-type = "git"
-url = "https://github.com/ls1intum/Athena.git"
-reference = "ccd00cf8346e76738a66e7f4cf04c84aa4cb4378"
-resolved_reference = "ccd00cf8346e76738a66e7f4cf04c84aa4cb4378"
-subdirectory = "athena"
+type = "directory"
+url = "../../../athena"
 
 [[package]]
 name = "attrs"
@@ -227,101 +220,116 @@ files = [
 
 [[package]]
 name = "charset-normalizer"
-version = "3.3.2"
+version = "3.4.0"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
 optional = false
 python-versions = ">=3.7.0"
 files = [
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 [[package]]
@@ -349,15 +357,30 @@ files = [
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 ]
 
+[[package]]
+name = "dataclasses-json"
+version = "0.6.7"
+description = "Easily serialize dataclasses to and from JSON."
+optional = false
+python-versions = "<4.0,>=3.7"
+files = [
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+]
+
+[package.dependencies]
+marshmallow = ">=3.18.0,<4.0.0"
+typing-inspect = ">=0.4.0,<1"
+
 [[package]]
 name = "dill"
-version = "0.3.8"
+version = "0.3.9"
 description = "serialize all of Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.extras]
@@ -407,19 +430,19 @@ all = ["email-validator (>=2.0.0)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)"
 
 [[package]]
 name = "flake8"
-version = "5.0.4"
+version = "7.1.1"
 description = "the modular source code checker: pep8 pyflakes and co"
 optional = false
-python-versions = ">=3.6.1"
+python-versions = ">=3.8.1"
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 [package.dependencies]
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-pycodestyle = ">=2.9.0,<2.10.0"
-pyflakes = ">=2.5.0,<2.6.0"
+pycodestyle = ">=2.12.0,<2.13.0"
+pyflakes = ">=3.2.0,<3.3.0"
 
 [[package]]
 name = "flake8-polyfill"
@@ -437,88 +460,103 @@ flake8 = "*"
 
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-version = "1.4.1"
+version = "1.5.0"
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 optional = false
 python-versions = ">=3.8"
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 [[package]]
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@@ -688,15 +733,18 @@ socks = ["socksio (==1.*)"]
 
 [[package]]
 name = "idna"
-version = "3.8"
+version = "3.10"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
 python-versions = ">=3.6"
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 ]
 
+[package.extras]
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+
 [[package]]
 name = "isort"
 version = "5.13.2"
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 [[package]]
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 SQLAlchemy = ">=1.4,<3"
 tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
 
+[[package]]
+name = "langchain-community"
+version = "0.2.10"
+description = "Community contributed LangChain integrations."
+optional = false
+python-versions = "<4.0,>=3.8.1"
+files = [
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+[package.dependencies]
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+dataclasses-json = ">=0.5.7,<0.7"
+langchain = ">=0.2.9,<0.3.0"
+langchain-core = ">=0.2.23,<0.3.0"
+langsmith = ">=0.1.0,<0.2.0"
+numpy = {version = ">=1,<2", markers = "python_version < \"3.12\""}
+PyYAML = ">=5.3"
+requests = ">=2,<3"
+SQLAlchemy = ">=1.4,<3"
+tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
+
 [[package]]
 name = "langchain-core"
 version = "0.2.38"
@@ -908,51 +991,49 @@ pydantic = {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""}
 requests = ">=2,<3"
 
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+version = "0.1.0"
+description = "SHared LLM module."
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+python-versions = "3.11.*"
+files = []
+develop = true
+
+[package.dependencies]
+athena = {path = "../athena", develop = true}
+gitpython = "3.1.41"
+langchain = "0.2.15"
+langchain-community = "0.2.10"
+langchain-openai = "0.1.23"
+langsmith = ">=0.1.0,<0.2.0"
+nltk = "3.8.1"
+openai = "1.51.1"
+python-dotenv = "1.0.0"
+tiktoken = "0.7.0"
+
+[package.source]
+type = "directory"
+url = "../../../llm_core"
+
+[[package]]
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+[package.dependencies]
+packaging = ">=17.0"
+
+[package.extras]
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+docs = ["alabaster (==1.0.0)", "autodocsumm (==0.2.13)", "sphinx (==8.1.3)", "sphinx-issues (==5.0.0)", "sphinx-version-warning (==1.1.2)"]
+tests = ["pytest", "simplejson"]
+
 [[package]]
 name = "mccabe"
 version = "0.7.0"
@@ -1067,38 +1148,43 @@ files = [
 
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 [package.extras]
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 install-types = ["pip"]
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 [[package]]
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 type = ["mypy (>=1.11.2)"]
 
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 pylint-celery = "0.3"
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+pylint-django = ">=2.6.1"
 pylint-flask = "0.6"
-pylint-plugin-utils = ">=0.7,<0.8"
 PyYAML = "*"
-requirements-detector = ">=1.2.0"
+requirements-detector = ">=1.3.1"
 setoptconf-tmp = ">=0.3.1,<0.4.0"
 toml = ">=0.10.2,<0.11.0"
 
@@ -1364,35 +1558,31 @@ with-vulture = ["vulture (>=1.5)"]
 
 [[package]]
 name = "psycopg2"
-version = "2.9.9"
+version = "2.9.10"
 description = "psycopg2 - Python-PostgreSQL Database Adapter"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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-    {file = "psycopg2-2.9.9-cp37-cp37m-win32.whl", hash = "sha256:5e0d98cade4f0e0304d7d6f25bbfbc5bd186e07b38eac65379309c4ca3193efa"},
-    {file = "psycopg2-2.9.9-cp37-cp37m-win_amd64.whl", hash = "sha256:7e2dacf8b009a1c1e843b5213a87f7c544b2b042476ed7755be813eaf4e8347a"},
-    {file = "psycopg2-2.9.9-cp38-cp38-win32.whl", hash = "sha256:ff432630e510709564c01dafdbe996cb552e0b9f3f065eb89bdce5bd31fabf4c"},
-    {file = "psycopg2-2.9.9-cp38-cp38-win_amd64.whl", hash = "sha256:bac58c024c9922c23550af2a581998624d6e02350f4ae9c5f0bc642c633a2d5e"},
-    {file = "psycopg2-2.9.9-cp39-cp39-win32.whl", hash = "sha256:c92811b2d4c9b6ea0285942b2e7cac98a59e166d59c588fe5cfe1eda58e72d59"},
-    {file = "psycopg2-2.9.9-cp39-cp39-win_amd64.whl", hash = "sha256:de80739447af31525feddeb8effd640782cf5998e1a4e9192ebdf829717e3913"},
-    {file = "psycopg2-2.9.9.tar.gz", hash = "sha256:d1454bde93fb1e224166811694d600e746430c006fbb031ea06ecc2ea41bf156"},
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+    {file = "psycopg2-2.9.10-cp310-cp310-win_amd64.whl", hash = "sha256:c6f7b8561225f9e711a9c47087388a97fdc948211c10a4bccbf0ba68ab7b3b5a"},
+    {file = "psycopg2-2.9.10-cp311-cp311-win32.whl", hash = "sha256:47c4f9875125344f4c2b870e41b6aad585901318068acd01de93f3677a6522c2"},
+    {file = "psycopg2-2.9.10-cp311-cp311-win_amd64.whl", hash = "sha256:0435034157049f6846e95103bd8f5a668788dd913a7c30162ca9503fdf542cb4"},
+    {file = "psycopg2-2.9.10-cp312-cp312-win32.whl", hash = "sha256:65a63d7ab0e067e2cdb3cf266de39663203d38d6a8ed97f5ca0cb315c73fe067"},
+    {file = "psycopg2-2.9.10-cp312-cp312-win_amd64.whl", hash = "sha256:4a579d6243da40a7b3182e0430493dbd55950c493d8c68f4eec0b302f6bbf20e"},
+    {file = "psycopg2-2.9.10-cp39-cp39-win32.whl", hash = "sha256:9d5b3b94b79a844a986d029eee38998232451119ad653aea42bb9220a8c5066b"},
+    {file = "psycopg2-2.9.10-cp39-cp39-win_amd64.whl", hash = "sha256:88138c8dedcbfa96408023ea2b0c369eda40fe5d75002c0964c78f46f11fa442"},
+    {file = "psycopg2-2.9.10.tar.gz", hash = "sha256:12ec0b40b0273f95296233e8750441339298e6a572f7039da5b260e3c8b60e11"},
 ]
 
 [[package]]
 name = "pycodestyle"
-version = "2.9.1"
+version = "2.12.1"
 description = "Python style guide checker"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.8"
 files = [
-    {file = "pycodestyle-2.9.1-py2.py3-none-any.whl", hash = "sha256:d1735fc58b418fd7c5f658d28d943854f8a849b01a5d0a1e6f3f3fdd0166804b"},
-    {file = "pycodestyle-2.9.1.tar.gz", hash = "sha256:2c9607871d58c76354b697b42f5d57e1ada7d261c261efac224b664affdc5785"},
+    {file = "pycodestyle-2.12.1-py2.py3-none-any.whl", hash = "sha256:46f0fb92069a7c28ab7bb558f05bfc0110dac69a0cd23c61ea0040283a9d78b3"},
+    {file = "pycodestyle-2.12.1.tar.gz", hash = "sha256:6838eae08bbce4f6accd5d5572075c63626a15ee3e6f842df996bf62f6d73521"},
 ]
 
 [[package]]
@@ -1473,31 +1663,31 @@ toml = ["tomli (>=1.2.3)"]
 
 [[package]]
 name = "pyflakes"
-version = "2.5.0"
+version = "3.2.0"
 description = "passive checker of Python programs"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.8"
 files = [
-    {file = "pyflakes-2.5.0-py2.py3-none-any.whl", hash = "sha256:4579f67d887f804e67edb544428f264b7b24f435b263c4614f384135cea553d2"},
-    {file = "pyflakes-2.5.0.tar.gz", hash = "sha256:491feb020dca48ccc562a8c0cbe8df07ee13078df59813b83959cbdada312ea3"},
+    {file = "pyflakes-3.2.0-py2.py3-none-any.whl", hash = "sha256:84b5be138a2dfbb40689ca07e2152deb896a65c3a3e24c251c5c62489568074a"},
+    {file = "pyflakes-3.2.0.tar.gz", hash = "sha256:1c61603ff154621fb2a9172037d84dca3500def8c8b630657d1701f026f8af3f"},
 ]
 
 [[package]]
 name = "pylint"
-version = "2.17.7"
+version = "3.3.1"
 description = "python code static checker"
 optional = false
-python-versions = ">=3.7.2"
+python-versions = ">=3.9.0"
 files = [
-    {file = "pylint-2.17.7-py3-none-any.whl", hash = "sha256:27a8d4c7ddc8c2f8c18aa0050148f89ffc09838142193fdbe98f172781a3ff87"},
-    {file = "pylint-2.17.7.tar.gz", hash = "sha256:f4fcac7ae74cfe36bc8451e931d8438e4a476c20314b1101c458ad0f05191fad"},
+    {file = "pylint-3.3.1-py3-none-any.whl", hash = "sha256:2f846a466dd023513240bc140ad2dd73bfc080a5d85a710afdb728c420a5a2b9"},
+    {file = "pylint-3.3.1.tar.gz", hash = "sha256:9f3dcc87b1203e612b78d91a896407787e708b3f189b5fa0b307712d49ff0c6e"},
 ]
 
 [package.dependencies]
-astroid = ">=2.15.8,<=2.17.0-dev0"
+astroid = ">=3.3.4,<=3.4.0-dev0"
 colorama = {version = ">=0.4.5", markers = "sys_platform == \"win32\""}
 dill = {version = ">=0.3.6", markers = "python_version >= \"3.11\""}
-isort = ">=4.2.5,<6"
+isort = ">=4.2.5,<5.13.0 || >5.13.0,<6"
 mccabe = ">=0.6,<0.8"
 platformdirs = ">=2.2.0"
 tomlkit = ">=0.10.1"
@@ -1523,22 +1713,21 @@ pylint-plugin-utils = ">=0.2.1"
 
 [[package]]
 name = "pylint-django"
-version = "2.5.3"
+version = "2.6.1"
 description = "A Pylint plugin to help Pylint understand the Django web framework"
 optional = false
-python-versions = "*"
+python-versions = "<4.0,>=3.9"
 files = [
-    {file = "pylint-django-2.5.3.tar.gz", hash = "sha256:0ac090d106c62fe33782a1d01bda1610b761bb1c9bf5035ced9d5f23a13d8591"},
-    {file = "pylint_django-2.5.3-py3-none-any.whl", hash = "sha256:56b12b6adf56d548412445bd35483034394a1a94901c3f8571980a13882299d5"},
+    {file = "pylint-django-2.6.1.tar.gz", hash = "sha256:19e8c85a8573a04e3de7be2ba91e9a7c818ebf05e1b617be2bbae67a906b725f"},
+    {file = "pylint_django-2.6.1-py3-none-any.whl", hash = "sha256:359f68fe8c810ee6bc8e1ab4c83c19b15a43b234a24b08978f47a23462b5ce28"},
 ]
 
 [package.dependencies]
-pylint = ">=2.0,<3"
-pylint-plugin-utils = ">=0.7"
+pylint = ">=3.0,<4"
+pylint-plugin-utils = ">=0.8"
 
 [package.extras]
-for-tests = ["coverage", "django-tables2", "django-tastypie", "factory-boy", "pylint (>=2.13)", "pytest", "wheel"]
-with-django = ["Django"]
+with-django = ["Django (>=2.2)"]
 
 [[package]]
 name = "pylint-flask"
@@ -1555,13 +1744,13 @@ pylint-plugin-utils = ">=0.2.1"
 
 [[package]]
 name = "pylint-plugin-utils"
-version = "0.7"
+version = "0.8.2"
 description = "Utilities and helpers for writing Pylint plugins"
 optional = false
-python-versions = ">=3.6.2"
+python-versions = ">=3.7,<4.0"
 files = [
-    {file = "pylint-plugin-utils-0.7.tar.gz", hash = "sha256:ce48bc0516ae9415dd5c752c940dfe601b18fe0f48aa249f2386adfa95a004dd"},
-    {file = "pylint_plugin_utils-0.7-py3-none-any.whl", hash = "sha256:b3d43e85ab74c4f48bb46ae4ce771e39c3a20f8b3d56982ab17aa73b4f98d535"},
+    {file = "pylint_plugin_utils-0.8.2-py3-none-any.whl", hash = "sha256:ae11664737aa2effbf26f973a9e0b6779ab7106ec0adc5fe104b0907ca04e507"},
+    {file = "pylint_plugin_utils-0.8.2.tar.gz", hash = "sha256:d3cebf68a38ba3fba23a873809155562571386d4c1b03e5b4c4cc26c3eee93e4"},
 ]
 
 [package.dependencies]
@@ -1746,25 +1935,6 @@ files = [
     {file = "regex-2024.9.11.tar.gz", hash = "sha256:6c188c307e8433bcb63dc1915022deb553b4203a70722fc542c363bf120a01fd"},
 ]
 
-[[package]]
-name = "replicate"
-version = "0.11.0"
-description = "Python client for Replicate"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "replicate-0.11.0-py3-none-any.whl", hash = "sha256:fbb8815068864dc822cd4fa7b6103d6f4089d6ef122abd6c3441ca0f0f110c46"},
-    {file = "replicate-0.11.0.tar.gz", hash = "sha256:4d54b5838c1552a6f76cc37c3af8d9a7998105382082d672acad31636ad443b5"},
-]
-
-[package.dependencies]
-packaging = "*"
-pydantic = ">1"
-requests = ">2"
-
-[package.extras]
-dev = ["black", "mypy", "pytest", "responses", "ruff"]
-
 [[package]]
 name = "requests"
 version = "2.32.3"
@@ -1788,17 +1958,17 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
 [[package]]
 name = "requirements-detector"
-version = "1.2.2"
+version = "1.3.1"
 description = "Python tool to find and list requirements of a Python project"
 optional = false
-python-versions = ">=3.7,<4.0"
+python-versions = "<4.0,>=3.8"
 files = [
-    {file = "requirements_detector-1.2.2-py3-none-any.whl", hash = "sha256:d7c60493bf166da3dd59de0e6cb25765e0e32a1931aeae92614034e5786d0bd0"},
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+    {file = "requirements_detector-1.3.1-py3-none-any.whl", hash = "sha256:3ef72e1c5c3ad11100058e8f074a5762a4902985e698099d2e7f1283758d4045"},
+    {file = "requirements_detector-1.3.1.tar.gz", hash = "sha256:b89e34faf0e4d17f5736923918bd5401949cbe723294ccfefd698b3cda28e676"},
 ]
 
 [package.dependencies]
-astroid = ">=2.0,<3.0"
+astroid = ">=3.0,<4.0"
 packaging = ">=21.3"
 semver = ">=3.0.0,<4.0.0"
 toml = ">=0.10.2,<0.11.0"
@@ -1863,60 +2033,68 @@ files = [
 
 [[package]]
 name = "sqlalchemy"
-version = "2.0.34"
+version = "2.0.36"
 description = "Database Abstraction Library"
 optional = false
 python-versions = ">=3.7"
 files = [
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 [package.dependencies]
@@ -1930,7 +2108,7 @@ aioodbc = ["aioodbc", "greenlet (!=0.4.17)"]
 aiosqlite = ["aiosqlite", "greenlet (!=0.4.17)", "typing_extensions (!=3.10.0.1)"]
 asyncio = ["greenlet (!=0.4.17)"]
 asyncmy = ["asyncmy (>=0.2.3,!=0.2.4,!=0.2.6)", "greenlet (!=0.4.17)"]
-mariadb-connector = ["mariadb (>=1.0.1,!=1.1.2,!=1.1.5)"]
+mariadb-connector = ["mariadb (>=1.0.1,!=1.1.2,!=1.1.5,!=1.1.10)"]
 mssql = ["pyodbc"]
 mssql-pymssql = ["pymssql"]
 mssql-pyodbc = ["pyodbc"]
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 ]
 
+[[package]]
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+python-versions = "*"
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+
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+typing-extensions = ">=3.7.4"
+
 [[package]]
 name = "urllib3"
 version = "2.2.3"
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 [package.extras]
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+    {file = "yarl-1.16.0-py3-none-any.whl", hash = "sha256:e6980a558d8461230c457218bd6c92dfc1d10205548215c2c21d79dc8d0a96f3"},
+    {file = "yarl-1.16.0.tar.gz", hash = "sha256:b6f687ced5510a9a2474bbae96a4352e5ace5fa34dc44a217b0537fec1db00b4"},
 ]
 
 [package.dependencies]
 idna = ">=2.0"
 multidict = ">=4.0"
+propcache = ">=0.2.0"
 
 [metadata]
 lock-version = "2.0"
 python-versions = "3.11.*"
-content-hash = "ec56dc8aa94f1c2e8b830d4e70a253d0e8f96e9dc31cb1e69e5d5b68660f0af4"
+content-hash = "df320ad329e94a4bd3ab22d79820574c032c17bf641a5b53ad332a48180d2811"
diff --git a/modules/modeling/module_modeling_llm/pyproject.toml b/modules/modeling/module_modeling_llm/pyproject.toml
index da2b3cd3a..d08c40c35 100644
--- a/modules/modeling/module_modeling_llm/pyproject.toml
+++ b/modules/modeling/module_modeling_llm/pyproject.toml
@@ -7,20 +7,18 @@ license = "MIT"
 
 [tool.poetry.dependencies]
 python = "3.11.*"
-athena = { git = "https://github.com/ls1intum/Athena.git", rev = "ccd00cf8346e76738a66e7f4cf04c84aa4cb4378", subdirectory = "athena"}
-openai = "1.42.0"
-langchain = "0.2.15"
+athena = { path = "../../../athena", develop = true }
+#athena = { git = "https://github.com/ls1intum/Athena.git", rev = "d9ff3bd", subdirectory = "athena"}
+llm_core = { path = "../../../llm_core", develop = true }
 python-dotenv = "1.0.0"
 nltk = "3.8.1"
 gitpython = "3.1.41"
-replicate = "0.11.0"
 tiktoken = "0.7.0"
 langsmith = "0.1.106"
-langchain-openai = "0.1.23"
 
 [tool.poetry.group.dev.dependencies]
 pydantic = "1.10.17"
-prospector = "1.10.2"
+prospector = "^1.10.2"
 types-requests = "2.31.0.8"
 
 [tool.poetry.scripts]
diff --git a/modules/programming/module_programming_llm/.env.example b/modules/programming/module_programming_llm/.env.example
index 2b6d9a889..753874245 100644
--- a/modules/programming/module_programming_llm/.env.example
+++ b/modules/programming/module_programming_llm/.env.example
@@ -12,7 +12,9 @@ DATABASE_URL=sqlite:///../data/data.sqlite
 
 # Default model to use
 # See below for options, available models are also logged on startup
-LLM_DEFAULT_MODEL="azure_openai_gpt-35"
+LLM_DEFAULT_MODEL="azure_openai_gpt-4o"
+LLM_DEFAULT_MODEL_COST_PER_MILLION_INPUT_TOKEN=5
+LLM_DEFAULT_MODEL_COST_PER_MILLION_OUTPUT_TOKEN=15
 
 # Standard OpenAI (Non-Azure) [leave blank if not used]
 # Model names prefixed with `openai_` followed by the model name, e.g. `openai_text-davinci-003`
diff --git a/modules/programming/module_programming_llm/Dockerfile b/modules/programming/module_programming_llm/Dockerfile
index 48ad92d42..4f9d93be0 100644
--- a/modules/programming/module_programming_llm/Dockerfile
+++ b/modules/programming/module_programming_llm/Dockerfile
@@ -17,6 +17,7 @@ RUN pip install --no-cache-dir poetry==1.5.0
 COPY pyproject.toml poetry.lock ./
 # athena module (from the Dockerfile in the athena folder)
 COPY --from=athena /code /athena
+COPY --from=llm_core /code /llm_core
 # install dependencies
 RUN poetry config virtualenvs.create true \
     && poetry config virtualenvs.in-project true \
diff --git a/modules/programming/module_programming_llm/module_programming_llm/config.py b/modules/programming/module_programming_llm/module_programming_llm/config.py
index 5edd58003..6a632208e 100644
--- a/modules/programming/module_programming_llm/module_programming_llm/config.py
+++ b/modules/programming/module_programming_llm/module_programming_llm/config.py
@@ -3,7 +3,7 @@
 from pydantic import BaseModel, Field
 
 from athena import config_schema_provider
-from module_programming_llm.helpers.models import ModelConfigType, DefaultModelConfig
+from llm_core.models import ModelConfigType, DefaultModelConfig
 from module_programming_llm.prompts.generate_graded_suggestions_by_file import (
     system_message as generate_graded_suggestions_by_file_system_message,
     human_message as generate_graded_suggestions_by_file_human_message,
diff --git a/modules/programming/module_programming_llm/module_programming_llm/generate_graded_suggestions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/generate_graded_suggestions_by_file.py
index 1fe4dde47..4a29b8f6d 100644
--- a/modules/programming/module_programming_llm/module_programming_llm/generate_graded_suggestions_by_file.py
+++ b/modules/programming/module_programming_llm/module_programming_llm/generate_graded_suggestions_by_file.py
@@ -13,12 +13,13 @@
 from module_programming_llm.split_problem_statement_by_file import (
     split_problem_statement_by_file,
 )
-from module_programming_llm.helpers.llm_utils import (
+from llm_core.utils.llm_utils import (
     check_prompt_length_and_omit_features_if_necessary,
     get_chat_prompt_with_formatting_instructions,
     num_tokens_from_string,
-    predict_and_parse,
 )
+from llm_core.utils.predict_and_parse import predict_and_parse
+
 from module_programming_llm.helpers.utils import (
     get_diff,
     load_files_from_repo,
diff --git a/modules/programming/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py
index b857a24f4..de654a427 100644
--- a/modules/programming/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py
+++ b/modules/programming/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py
@@ -11,12 +11,13 @@
 from module_programming_llm.split_problem_statement_by_file import (
     split_problem_statement_by_file,
 )
-from module_programming_llm.helpers.llm_utils import (
+from llm_core.utils.llm_utils import (
     check_prompt_length_and_omit_features_if_necessary,
     get_chat_prompt_with_formatting_instructions,
     num_tokens_from_string,
-    predict_and_parse,
 )
+from llm_core.utils.predict_and_parse import predict_and_parse
+
 from module_programming_llm.helpers.utils import (
     get_diff,
     load_files_from_repo,
diff --git a/modules/programming/module_programming_llm/module_programming_llm/generate_summary_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/generate_summary_by_file.py
index 144d750bf..e5ac6aad7 100644
--- a/modules/programming/module_programming_llm/module_programming_llm/generate_summary_by_file.py
+++ b/modules/programming/module_programming_llm/module_programming_llm/generate_summary_by_file.py
@@ -9,11 +9,12 @@
 from athena.programming import Exercise, Submission
 
 from module_programming_llm.config import GradedBasicApproachConfig, BasicApproachConfig
-from module_programming_llm.helpers.llm_utils import (
+from llm_core.utils.llm_utils import (
     get_chat_prompt_with_formatting_instructions,
     num_tokens_from_prompt,
-    predict_and_parse,
 )
+from llm_core.utils.predict_and_parse import predict_and_parse
+
 from module_programming_llm.helpers.utils import (
     get_diff,
     load_files_from_repo,
diff --git a/modules/programming/module_programming_llm/module_programming_llm/helpers/llm_utils.py b/modules/programming/module_programming_llm/module_programming_llm/helpers/llm_utils.py
deleted file mode 100644
index a035a5970..000000000
--- a/modules/programming/module_programming_llm/module_programming_llm/helpers/llm_utils.py
+++ /dev/null
@@ -1,174 +0,0 @@
-from typing import Optional, Type, TypeVar, List, Any, Dict
-
-from langchain.callbacks.tracers import langchain
-from pydantic import BaseModel, ValidationError
-import tiktoken
-
-from langchain.chains import LLMChain
-from langchain.chat_models import ChatOpenAI
-from langchain.base_language import BaseLanguageModel
-from langchain.prompts import (
-    ChatPromptTemplate,
-    SystemMessagePromptTemplate,
-    HumanMessagePromptTemplate,
-)
-from langchain.chains.openai_functions import create_structured_output_chain
-from langchain.output_parsers import PydanticOutputParser
-from langchain.schema import (
-    OutputParserException,
-    BaseLLMOutputParser,
-    Generation,
-    LLMResult,
-)
-
-from athena import emit_meta, get_experiment_environment
-from athena.logger import logger
-
-T = TypeVar("T", bound=BaseModel)
-
-
-def num_tokens_from_string(string: str) -> int:
-    """Returns the number of tokens in a text string."""
-    encoding = tiktoken.get_encoding("cl100k_base")
-    num_tokens = len(encoding.encode(string))
-    return num_tokens
-
-
-def num_tokens_from_prompt(chat_prompt: ChatPromptTemplate, prompt_input: dict) -> int:
-    """Returns the number of tokens in a chat prompt."""
-    return num_tokens_from_string(chat_prompt.format(**prompt_input))
-
-
-def check_prompt_length_and_omit_features_if_necessary(prompt: ChatPromptTemplate,
-                                                       prompt_input: dict,
-                                                       max_input_tokens: int,
-                                                       omittable_features: List[str],
-                                                       debug: bool):
-    """Check if the input is too long and omit features if necessary.
-
-    Note: Omitted features will be replaced with "omitted" in the prompt
-
-    Args:
-        prompt (ChatPromptTemplate): Prompt template
-        prompt_input (dict): Prompt input
-        max_input_tokens (int): Maximum number of tokens allowed
-        omittable_features (List[str]): List of features that can be omitted, ordered by priority (least important first)
-        debug (bool): Debug flag
-
-    Returns:
-        (dict, bool): Tuple of (prompt_input, should_run) where prompt_input is the input with omitted features and should_run is True if the model should run, False otherwise
-    """
-    if num_tokens_from_prompt(prompt, prompt_input) <= max_input_tokens:
-        # Full prompt fits into LLM context => should run with full prompt
-        return prompt_input, True
-
-    omitted_features = []
-
-    # Omit features until the input is short enough
-    for feature in omittable_features:
-        if feature in prompt_input:
-            omitted_features.append(feature)
-            prompt_input[feature] = "omitted"
-            if num_tokens_from_prompt(prompt, prompt_input) <= max_input_tokens:
-                if debug:
-                    emit_meta("omitted_features", omitted_features)
-                return prompt_input, True
-
-    # If we get here, we couldn't omit enough features
-    return prompt_input, False
-
-
-def supports_function_calling(model: BaseLanguageModel):
-    """Returns True if the model supports function calling, False otherwise
-
-    Args:
-        model (BaseLanguageModel): The model to check
-
-    Returns:
-        boolean: True if the model supports function calling, False otherwise
-    """
-    return False  # isinstance(model, ChatOpenAI) TODO: find out how to make function calling work again
-
-
-def get_chat_prompt_with_formatting_instructions(
-            model: BaseLanguageModel,
-            system_message: str,
-            human_message: str,
-            pydantic_object: Type[T]
-        ) -> ChatPromptTemplate:
-    """Returns a ChatPromptTemplate with formatting instructions (if necessary)
-
-    Note: Does nothing if the model supports function calling
-
-    Args:
-        model (BaseLanguageModel): The model to check if it supports function calling
-        system_message (str): System message
-        human_message (str): Human message
-        pydantic_object (Type[T]): Model to parse the output
-
-    Returns:
-        ChatPromptTemplate: ChatPromptTemplate with formatting instructions (if necessary)
-    """
-    if supports_function_calling(model):
-        system_message_prompt = SystemMessagePromptTemplate.from_template(system_message)
-        human_message_prompt = HumanMessagePromptTemplate.from_template(human_message)
-        return ChatPromptTemplate.from_messages([system_message_prompt, human_message_prompt])
-
-    output_parser = PydanticOutputParser(pydantic_object=pydantic_object)
-    system_message_prompt = SystemMessagePromptTemplate.from_template(system_message + "\n{format_instructions}")
-    system_message_prompt.prompt.partial_variables = {"format_instructions": output_parser.get_format_instructions()}
-    system_message_prompt.prompt.input_variables.remove("format_instructions")
-    human_message_prompt = HumanMessagePromptTemplate.from_template(human_message + "\n\nJSON response following the provided schema:")
-    return ChatPromptTemplate.from_messages([system_message_prompt, human_message_prompt])
-
-
-async def predict_and_parse(
-        model: BaseLanguageModel,
-        chat_prompt: ChatPromptTemplate,
-        prompt_input: dict,
-        pydantic_object: Type[T],
-        tags: Optional[List[str]]
-    ) -> Optional[T]:
-    """Predicts an LLM completion using the model and parses the output using the provided Pydantic model
-
-    Args:
-        model (BaseLanguageModel): The model to predict with
-        chat_prompt (ChatPromptTemplate): Prompt to use
-        prompt_input (dict): Input parameters to use for the prompt
-        pydantic_object (Type[T]): Pydantic model to parse the output
-        tags (Optional[List[str]]: List of tags to tag the prediction with
-
-    Returns:
-        Optional[T]: Parsed output, or None if it could not be parsed
-    """
-    langchain.debug = True
-
-    experiment = get_experiment_environment()
-
-    tags = tags or []
-    if experiment.experiment_id is not None:
-        tags.append(f"experiment-{experiment.experiment_id}")
-    if experiment.module_configuration_id is not None:
-        tags.append(f"module-configuration-{experiment.module_configuration_id}")
-    if experiment.run_id is not None:
-        tags.append(f"run-{experiment.run_id}")
-
-    if supports_function_calling(model):
-        chain = create_structured_output_chain(pydantic_object, llm=model, prompt=chat_prompt, tags=tags)
-        chain.verbose = True
-        try:
-            return await chain.arun(**prompt_input)
-        except (OutputParserException, ValidationError) as e:
-            logger.error("Exception type: %s, Message: %s", type(e).__name__, e)
-            return None
-
-    output_parser = PydanticOutputParser(pydantic_object=pydantic_object)
-    chain = LLMChain(llm=model, prompt=chat_prompt, output_parser=output_parser, tags=tags)
-    try:
-        return await chain.arun(**prompt_input)
-    except (OutputParserException, ValidationError) as e:
-        logger.error("Exception type: %s, Message: %s", type(e).__name__, e)
-        # In the future, we should probably have some recovery mechanism here (i.e. fix the output with another prompt)
-        return None
-
-    # todo debug settings
diff --git a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/__init__.py b/modules/programming/module_programming_llm/module_programming_llm/helpers/models/__init__.py
deleted file mode 100644
index a5fdc01d0..000000000
--- a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/__init__.py
+++ /dev/null
@@ -1,33 +0,0 @@
-import os
-from typing import Type, Union, List
-from module_programming_llm.helpers.models.model_config import ModelConfig
-
-
-DefaultModelConfig: Type[ModelConfig]
-default_model_name = os.environ.get("LLM_DEFAULT_MODEL")
-
-types: List[Type[ModelConfig]] = []
-try:
-    import module_programming_llm.helpers.models.openai as openai_config
-    types.append(openai_config.OpenAIModelConfig)
-    if default_model_name in openai_config.available_models:
-        DefaultModelConfig = openai_config.OpenAIModelConfig
-except AttributeError:
-    pass
-
-try:
-    import module_programming_llm.helpers.models.replicate as replicate_config
-    types.append(replicate_config.ReplicateModelConfig)
-    if default_model_name in replicate_config.available_models:
-        DefaultModelConfig = replicate_config.ReplicateModelConfig
-except AttributeError:
-    pass
-
-if not types:
-    raise EnvironmentError(
-        "No model configurations available, please set up at least one provider in the environment variables.")
-
-if 'DefaultModelConfig' not in globals():
-    DefaultModelConfig = types[0]
-
-ModelConfigType = openai_config.OpenAIModelConfig if 'ReplicateModelConfig' not in globals() else Union[openai_config.OpenAIModelConfig, replicate_config.ReplicateModelConfig]
\ No newline at end of file
diff --git a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/model_config.py b/modules/programming/module_programming_llm/module_programming_llm/helpers/models/model_config.py
deleted file mode 100644
index eae644f57..000000000
--- a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/model_config.py
+++ /dev/null
@@ -1,10 +0,0 @@
-from abc import ABC, abstractmethod
-from pydantic import BaseModel
-from langchain.base_language import BaseLanguageModel
-
-
-class ModelConfig(BaseModel, ABC):
-
-    @abstractmethod
-    def get_model(self) -> BaseLanguageModel:
-        pass
diff --git a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/replicate.py b/modules/programming/module_programming_llm/module_programming_llm/helpers/models/replicate.py
deleted file mode 100644
index 248d55fce..000000000
--- a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/replicate.py
+++ /dev/null
@@ -1,122 +0,0 @@
-import os
-from pydantic import Field, PositiveInt
-from enum import Enum
-
-from langchain.llms import Replicate
-from langchain.base_language import BaseLanguageModel
-
-from athena.logger import logger
-from .model_config import ModelConfig
-
-
-# Hardcoded list of models
-# If necessary, add more models from replicate here, the config below might need adjustments depending on the available
-# parameters of the model
-#
-# To update the version of the models, go to the respective page on replicate.com and copy the (latest) version id 
-# from and paste it after the colon in the value of the dictionary. Ever so often a new version is released.
-replicate_models = {
-    # LLAMA 2 70B Chat
-    # https://replicate.com/replicate/llama-2-70b-chat
-    "llama-2-70b-chat": "replicate/llama-2-70b-chat:58d078176e02c219e11eb4da5a02a7830a283b14cf8f94537af893ccff5ee781",
-    # LLaMA 2 13B Chat
-    # https://replicate.com/a16z-infra/llama-2-13b-chat
-    "llama-2-13b-chat": "a16z-infra/llama-2-13b-chat:2a7f981751ec7fdf87b5b91ad4db53683a98082e9ff7bfd12c8cd5ea85980a52",
-    # LLaMA 2 7B Chat
-    # https://replicate.com/a16z-infra/llama-2-7b-chat
-    "llama-2-7b-chat": "a16z-infra/llama-2-7b-chat:7b0bfc9aff140d5b75bacbed23e91fd3c34b01a1e958d32132de6e0a19796e2c",
-    # CodeLLAMA 2 13B 
-    # https://replicate.com/replicate/codellama-13b
-    "codellama-13b": "replicate/codellama-13b:1c914d844307b0588599b8393480a3ba917b660c7e9dfae681542b5325f228db",
-    # CodeLLAMA 2 34B
-    # https://replicate.com/replicate/codellama-34b
-    "codellama-34b": "replicate/codellama-34b:0666717e5ead8557dff55ee8f11924b5c0309f5f1ca52f64bb8eec405fdb38a7",
-}
-
-available_models = {}
-if os.environ.get("REPLICATE_API_TOKEN"):  # If Replicate is available
-    available_models = {
-        name: Replicate(
-            model=model,
-            model_kwargs={ "temperature": 0.01 }
-        )
-        for name, model in replicate_models.items()
-    }
-else:
-    logger.warning("REPLICATE_API_TOKEN not found in environment variables. Replicate models are disabled.")
-
-if available_models:
-    logger.info("Available replicate models: %s",
-                ", ".join(available_models.keys()))
-
-    ReplicateModel = Enum('ReplicateModel', {name: name for name in available_models})  # type: ignore
-
-
-    default_model_name = "llama-2-13b-chat"
-    if "LLM_DEFAULT_MODEL" in os.environ and os.environ["LLM_DEFAULT_MODEL"] in available_models:
-        default_model_name = os.environ["LLM_DEFAULT_MODEL"]
-    if default_model_name not in available_models:
-        default_model_name = list(available_models.keys())[0]
-
-    default_replicate_model = ReplicateModel[default_model_name]
-
-
-    # Note: Config has been setup with LLaMA 2 chat models in mind, other models may not work as expected
-    class ReplicateModelConfig(ModelConfig):
-        """Replicate LLM configuration."""
-
-        model_name: ReplicateModel = Field(default=default_replicate_model,  # type: ignore
-                                           description="The name of the model to use.")
-        max_new_tokens: PositiveInt = Field(1000, description="""\
-Maximum number of tokens to generate. A word is generally 2-3 tokens (minimum: 1)\
-""")
-        min_new_tokens: int = Field(-1, description="""\
-Minimum number of tokens to generate. To disable, set to -1. A word is generally 2-3 tokens. (minimum: -1)\
-""")
-        temperature: float = Field(default=0.01, ge=0.01, le=5, description="""\
-Adjusts randomness of outputs, greater than 1 is random and 0 is deterministic, 0.75 is a good starting value.\
-(minimum: 0.01; maximum: 5)\
-""")
-        top_p: float = Field(default=1, ge=0, le=1, description="""\
-When decoding text, samples from the top p percentage of most likely tokens; lower to ignore less likely tokens (maximum: 1)\
-""")
-        top_k: PositiveInt = Field(default=250, description="""\
-When decoding text, samples from the top k most likely tokens; lower to ignore less likely tokens\
-""")
-        repetition_penalty: float = Field(default=1, ge=0.01, le=5, description="""\
-Penalty for repeated words in generated text; 1 is no penalty, values greater than 1 discourage repetition, \
-less than 1 encourage it. (minimum: 0.01; maximum: 5)\
-""")
-        repetition_penalty_sustain: int = Field(default=-1, description="""
-Number of most recent tokens to apply repetition penalty to, -1 to apply to whole context (minimum: -1)\
-""")
-        token_repetition_penalty_decay: PositiveInt = Field(default=128, description="""\
-Gradually decrease penalty over this many tokens (minimum: 1)\
-""")
-
-        def get_model(self) -> BaseLanguageModel:
-            """Get the model from the configuration.
-
-            Returns:
-                BaseLanguageModel: The model.
-            """
-            model = available_models[self.model_name.value]
-            kwargs = model._lc_kwargs
-
-            model_kwargs = {}
-            for attr, value in self.dict().items():
-                # Skip model_name
-                if attr == "model_name":
-                    continue
-                model_kwargs[attr] = value
-
-            # Set model parameters
-            kwargs["model_kwargs"] = model_kwargs
-
-            # Initialize a copy of the model using the config
-            model = model.__class__(**kwargs)
-            return model
-        
-
-        class Config:
-            title = 'Replicate'
diff --git a/modules/programming/module_programming_llm/module_programming_llm/helpers/utils.py b/modules/programming/module_programming_llm/module_programming_llm/helpers/utils.py
index 6f55670c4..f708fa5af 100644
--- a/modules/programming/module_programming_llm/module_programming_llm/helpers/utils.py
+++ b/modules/programming/module_programming_llm/module_programming_llm/helpers/utils.py
@@ -104,6 +104,7 @@ def temporary_remote(remote_name: str, repo: Repo, remote_url: str) -> Iterator[
         repo.delete_remote(remote)
 
 
+# pylint: disable=too-many-positional-arguments
 def get_diff(src_repo: Repo, 
              dst_repo: Repo, 
              src_prefix: str = "a",
diff --git a/modules/programming/module_programming_llm/module_programming_llm/split_grading_instructions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/split_grading_instructions_by_file.py
index 0e402b378..08c08924f 100644
--- a/modules/programming/module_programming_llm/module_programming_llm/split_grading_instructions_by_file.py
+++ b/modules/programming/module_programming_llm/module_programming_llm/split_grading_instructions_by_file.py
@@ -8,12 +8,13 @@
 from athena.programming import Exercise, Submission
 
 from module_programming_llm.config import GradedBasicApproachConfig
-from module_programming_llm.helpers.llm_utils import (
+from llm_core.utils.llm_utils import (
     get_chat_prompt_with_formatting_instructions,
     num_tokens_from_string,
     num_tokens_from_prompt,
-    predict_and_parse
 )
+from llm_core.utils.predict_and_parse import predict_and_parse
+
 from module_programming_llm.helpers.utils import format_grading_instructions, get_diff
 
 
diff --git a/modules/programming/module_programming_llm/module_programming_llm/split_problem_statement_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/split_problem_statement_by_file.py
index 46cd64bbb..aecf516ac 100644
--- a/modules/programming/module_programming_llm/module_programming_llm/split_problem_statement_by_file.py
+++ b/modules/programming/module_programming_llm/module_programming_llm/split_problem_statement_by_file.py
@@ -8,12 +8,13 @@
 from athena.programming import Exercise, Submission
 
 from module_programming_llm.config import GradedBasicApproachConfig, BasicApproachConfig
-from module_programming_llm.helpers.llm_utils import (
+from llm_core.utils.llm_utils import (
     get_chat_prompt_with_formatting_instructions,
     num_tokens_from_string,
     num_tokens_from_prompt,
-    predict_and_parse
 )
+from llm_core.utils.predict_and_parse import predict_and_parse
+
 from module_programming_llm.helpers.utils import get_diff
 
 
diff --git a/modules/programming/module_programming_llm/poetry.lock b/modules/programming/module_programming_llm/poetry.lock
index b4d55ff8d..9f91758c4 100644
--- a/modules/programming/module_programming_llm/poetry.lock
+++ b/modules/programming/module_programming_llm/poetry.lock
@@ -2,113 +2,113 @@
 
 [[package]]
 name = "aiohappyeyeballs"
-version = "2.4.0"
+version = "2.4.3"
 description = "Happy Eyeballs for asyncio"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "aiohappyeyeballs-2.4.0-py3-none-any.whl", hash = "sha256:7ce92076e249169a13c2f49320d1967425eaf1f407522d707d59cac7628d62bd"},
-    {file = "aiohappyeyeballs-2.4.0.tar.gz", hash = "sha256:55a1714f084e63d49639800f95716da97a1f173d46a16dfcfda0016abb93b6b2"},
+    {file = "aiohappyeyeballs-2.4.3-py3-none-any.whl", hash = "sha256:8a7a83727b2756f394ab2895ea0765a0a8c475e3c71e98d43d76f22b4b435572"},
+    {file = "aiohappyeyeballs-2.4.3.tar.gz", hash = "sha256:75cf88a15106a5002a8eb1dab212525c00d1f4c0fa96e551c9fbe6f09a621586"},
 ]
 
 [[package]]
 name = "aiohttp"
-version = "3.10.5"
+version = "3.10.10"
 description = "Async http client/server framework (asyncio)"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -117,7 +117,7 @@ aiosignal = ">=1.1.2"
 attrs = ">=17.3.0"
 frozenlist = ">=1.1.1"
 multidict = ">=4.5,<7.0"
-yarl = ">=1.0,<2.0"
+yarl = ">=1.12.0,<2.0"
 
 [package.extras]
 speedups = ["Brotli", "aiodns (>=3.2.0)", "brotlicffi"]
@@ -138,13 +138,13 @@ frozenlist = ">=1.1.0"
 
 [[package]]
 name = "anyio"
-version = "4.4.0"
+version = "4.6.0"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.4.0-py3-none-any.whl", hash = "sha256:c1b2d8f46a8a812513012e1107cb0e68c17159a7a594208005a57dc776e1bdc7"},
-    {file = "anyio-4.4.0.tar.gz", hash = "sha256:5aadc6a1bbb7cdb0bede386cac5e2940f5e2ff3aa20277e991cf028e0585ce94"},
+    {file = "anyio-4.6.0-py3-none-any.whl", hash = "sha256:c7d2e9d63e31599eeb636c8c5c03a7e108d73b345f064f1c19fdc87b79036a9a"},
+    {file = "anyio-4.6.0.tar.gz", hash = "sha256:137b4559cbb034c477165047febb6ff83f390fc3b20bf181c1fc0a728cb8beeb"},
 ]
 
 [package.dependencies]
@@ -152,25 +152,21 @@ idna = ">=2.8"
 sniffio = ">=1.1"
 
 [package.extras]
-doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
-test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
-trio = ["trio (>=0.23)"]
+doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.21.0b1)"]
+trio = ["trio (>=0.26.1)"]
 
 [[package]]
 name = "astroid"
-version = "2.15.8"
+version = "3.3.5"
 description = "An abstract syntax tree for Python with inference support."
 optional = false
-python-versions = ">=3.7.2"
+python-versions = ">=3.9.0"
 files = [
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 ]
 
-[package.dependencies]
-lazy-object-proxy = ">=1.4.0"
-wrapt = {version = ">=1.14,<2", markers = "python_version >= \"3.11\""}
-
 [[package]]
 name = "athena"
 version = "1.0.0"
@@ -178,7 +174,7 @@ description = "This is a helper module for easier development of Athena modules.
 optional = false
 python-versions = "3.11.*"
 files = []
-develop = false
+develop = true
 
 [package.dependencies]
 fastapi = "^0.109.1"
@@ -189,11 +185,8 @@ sqlalchemy = {version = "^2.0.21", extras = ["mypy"]}
 uvicorn = "^0.23.0"
 
 [package.source]
-type = "git"
-url = "https://github.com/ls1intum/Athena.git"
- reference = "2da2d33"
-resolved_reference = "2da2d33bb7045793de0fd74b245dd97166fd45f0"
-subdirectory = "athena"
+type = "directory"
+url = "../../../athena"
 
 [[package]]
 name = "attrs"
@@ -227,101 +220,116 @@ files = [
 
 [[package]]
 name = "charset-normalizer"
-version = "3.3.2"
+version = "3.4.0"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
 optional = false
 python-versions = ">=3.7.0"
 files = [
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 ]
 
 [[package]]
@@ -366,13 +374,13 @@ typing-inspect = ">=0.4.0,<1"
 
 [[package]]
 name = "dill"
-version = "0.3.8"
+version = "0.3.9"
 description = "serialize all of Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.extras]
@@ -422,19 +430,19 @@ all = ["email-validator (>=2.0.0)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)"
 
 [[package]]
 name = "flake8"
-version = "5.0.4"
+version = "7.1.1"
 description = "the modular source code checker: pep8 pyflakes and co"
 optional = false
-python-versions = ">=3.6.1"
+python-versions = ">=3.8.1"
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-pyflakes = ">=2.5.0,<2.6.0"
+pycodestyle = ">=2.12.0,<2.13.0"
+pyflakes = ">=3.2.0,<3.3.0"
 
 [[package]]
 name = "flake8-polyfill"
@@ -552,95 +560,101 @@ smmap = ">=3.0.1,<6"
 
 [[package]]
 name = "gitpython"
-version = "3.1.43"
+version = "3.1.41"
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+test = ["black", "coverage[toml]", "ddt (>=1.1.1,!=1.4.3)", "mock", "mypy", "pre-commit", "pytest (>=7.3.1)", "pytest-cov", "pytest-instafail", "pytest-mock", "pytest-sugar", "sumtypes"]
 
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 python-versions = ">=3.7"
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 colors = ["colorama (>=0.4.6)"]
 
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 [[package]]
 name = "joblib"
 version = "1.4.2"
@@ -768,18 +864,18 @@ files = [
 
 [[package]]
 name = "langchain"
-version = "0.2.11"
+version = "0.2.15"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
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+    {file = "langchain-0.2.15.tar.gz", hash = "sha256:f613ce7594be34f9bac687134a56f6e8274951907b798dbd037aefc95df78953"},
 ]
 
 [package.dependencies]
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+langchain-core = ">=0.2.35,<0.3.0"
 langchain-text-splitters = ">=0.2.0,<0.3.0"
 langsmith = ">=0.1.17,<0.2.0"
 numpy = {version = ">=1,<2", markers = "python_version < \"3.12\""}
@@ -814,13 +910,13 @@ tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
 
 [[package]]
 name = "langchain-core"
-version = "0.2.40"
+version = "0.2.41"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
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 ]
 
 [package.dependencies]
@@ -834,18 +930,18 @@ typing-extensions = ">=4.7"
 
 [[package]]
 name = "langchain-openai"
-version = "0.1.19"
+version = "0.1.23"
 description = "An integration package connecting OpenAI and LangChain"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
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 ]
 
 [package.dependencies]
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-openai = ">=1.32.0,<2.0.0"
+langchain-core = ">=0.2.35,<0.3.0"
+openai = ">=1.40.0,<2.0.0"
 tiktoken = ">=0.7,<1"
 
 [[package]]
@@ -864,13 +960,13 @@ langchain-core = ">=0.2.38,<0.3.0"
 
 [[package]]
 name = "langsmith"
-version = "0.1.120"
+version = "0.1.134"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
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 ]
 
 [package.dependencies]
@@ -878,52 +974,32 @@ httpx = ">=0.23.0,<1"
 orjson = ">=3.9.14,<4.0.0"
 pydantic = {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""}
 requests = ">=2,<3"
+requests-toolbelt = ">=1.0.0,<2.0.0"
 
 [[package]]
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-version = "1.10.0"
-description = "A fast and thorough lazy object proxy."
+name = "llm-core"
+version = "0.1.0"
+description = "SHared LLM module."
 optional = false
-python-versions = ">=3.8"
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+files = []
+develop = true
+
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+langchain = "0.2.15"
+langchain-community = "0.2.10"
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+openai = "1.51.1"
+python-dotenv = "1.0.0"
+tiktoken = "0.7.0"
+
+[package.source]
+type = "directory"
+url = "../../../llm_core"
 
 [[package]]
 name = "marshmallow"
@@ -1115,13 +1191,13 @@ files = [
 
 [[package]]
 name = "nltk"
-version = "3.9.1"
+version = "3.8.1"
 description = "Natural Language Toolkit"
 optional = false
-python-versions = ">=3.8"
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 sniffio = "*"
 tqdm = ">4"
-typing-extensions = ">=4.7,<5"
+typing-extensions = ">=4.11,<5"
 
 [package.extras]
 datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"]
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 [[package]]
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 python-versions = ">=3.8"
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 requests = ">=2.31.0,<3.0.0"
 
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+
 [[package]]
 name = "prospector"
-version = "1.10.3"
+version = "1.12.1"
 description = "Prospector is a tool to analyse Python code by aggregating the result of other tools."
 optional = false
-python-versions = ">=3.7.2,<4.0"
+python-versions = "<4.0,>=3.9"
 files = [
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 ]
 
 [package.dependencies]
 dodgy = ">=0.2.1,<0.3.0"
-flake8 = "<6.0.0"
+flake8 = "*"
 GitPython = ">=3.1.27,<4.0.0"
 mccabe = ">=0.7.0,<0.8.0"
 packaging = "*"
 pep8-naming = ">=0.3.3,<=0.10.0"
 pycodestyle = ">=2.9.0"
 pydocstyle = ">=2.0.0"
-pyflakes = ">=2.2.0,<3"
-pylint = ">=2.8.3"
+pyflakes = ">=2.2.0"
+pylint = ">=3.0"
 pylint-celery = "0.3"
-pylint-django = ">=2.5,<2.6"
+pylint-django = ">=2.6.1"
 pylint-flask = "0.6"
-pylint-plugin-utils = ">=0.7,<0.8"
 PyYAML = "*"
-requirements-detector = ">=1.2.0"
+requirements-detector = ">=1.3.1"
 setoptconf-tmp = ">=0.3.1,<0.4.0"
 toml = ">=0.10.2,<0.11.0"
 
@@ -1391,13 +1574,13 @@ files = [
 
 [[package]]
 name = "pycodestyle"
-version = "2.9.1"
+version = "2.12.1"
 description = "Python style guide checker"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.8"
 files = [
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+    {file = "pycodestyle-2.12.1-py2.py3-none-any.whl", hash = "sha256:46f0fb92069a7c28ab7bb558f05bfc0110dac69a0cd23c61ea0040283a9d78b3"},
+    {file = "pycodestyle-2.12.1.tar.gz", hash = "sha256:6838eae08bbce4f6accd5d5572075c63626a15ee3e6f842df996bf62f6d73521"},
 ]
 
 [[package]]
@@ -1478,31 +1661,31 @@ toml = ["tomli (>=1.2.3)"]
 
 [[package]]
 name = "pyflakes"
-version = "2.5.0"
+version = "3.2.0"
 description = "passive checker of Python programs"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.8"
 files = [
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-    {file = "pyflakes-2.5.0.tar.gz", hash = "sha256:491feb020dca48ccc562a8c0cbe8df07ee13078df59813b83959cbdada312ea3"},
+    {file = "pyflakes-3.2.0-py2.py3-none-any.whl", hash = "sha256:84b5be138a2dfbb40689ca07e2152deb896a65c3a3e24c251c5c62489568074a"},
+    {file = "pyflakes-3.2.0.tar.gz", hash = "sha256:1c61603ff154621fb2a9172037d84dca3500def8c8b630657d1701f026f8af3f"},
 ]
 
 [[package]]
 name = "pylint"
-version = "2.17.7"
+version = "3.3.1"
 description = "python code static checker"
 optional = false
-python-versions = ">=3.7.2"
+python-versions = ">=3.9.0"
 files = [
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-    {file = "pylint-2.17.7.tar.gz", hash = "sha256:f4fcac7ae74cfe36bc8451e931d8438e4a476c20314b1101c458ad0f05191fad"},
+    {file = "pylint-3.3.1-py3-none-any.whl", hash = "sha256:2f846a466dd023513240bc140ad2dd73bfc080a5d85a710afdb728c420a5a2b9"},
+    {file = "pylint-3.3.1.tar.gz", hash = "sha256:9f3dcc87b1203e612b78d91a896407787e708b3f189b5fa0b307712d49ff0c6e"},
 ]
 
 [package.dependencies]
-astroid = ">=2.15.8,<=2.17.0-dev0"
+astroid = ">=3.3.4,<=3.4.0-dev0"
 colorama = {version = ">=0.4.5", markers = "sys_platform == \"win32\""}
 dill = {version = ">=0.3.6", markers = "python_version >= \"3.11\""}
-isort = ">=4.2.5,<6"
+isort = ">=4.2.5,<5.13.0 || >5.13.0,<6"
 mccabe = ">=0.6,<0.8"
 platformdirs = ">=2.2.0"
 tomlkit = ">=0.10.1"
@@ -1528,22 +1711,21 @@ pylint-plugin-utils = ">=0.2.1"
 
 [[package]]
 name = "pylint-django"
-version = "2.5.3"
+version = "2.6.1"
 description = "A Pylint plugin to help Pylint understand the Django web framework"
 optional = false
-python-versions = "*"
+python-versions = "<4.0,>=3.9"
 files = [
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-    {file = "pylint_django-2.5.3-py3-none-any.whl", hash = "sha256:56b12b6adf56d548412445bd35483034394a1a94901c3f8571980a13882299d5"},
+    {file = "pylint-django-2.6.1.tar.gz", hash = "sha256:19e8c85a8573a04e3de7be2ba91e9a7c818ebf05e1b617be2bbae67a906b725f"},
+    {file = "pylint_django-2.6.1-py3-none-any.whl", hash = "sha256:359f68fe8c810ee6bc8e1ab4c83c19b15a43b234a24b08978f47a23462b5ce28"},
 ]
 
 [package.dependencies]
-pylint = ">=2.0,<3"
-pylint-plugin-utils = ">=0.7"
+pylint = ">=3.0,<4"
+pylint-plugin-utils = ">=0.8"
 
 [package.extras]
-for-tests = ["coverage", "django-tables2", "django-tastypie", "factory-boy", "pylint (>=2.13)", "pytest", "wheel"]
-with-django = ["Django"]
+with-django = ["Django (>=2.2)"]
 
 [[package]]
 name = "pylint-flask"
@@ -1560,13 +1742,13 @@ pylint-plugin-utils = ">=0.2.1"
 
 [[package]]
 name = "pylint-plugin-utils"
-version = "0.7"
+version = "0.8.2"
 description = "Utilities and helpers for writing Pylint plugins"
 optional = false
-python-versions = ">=3.6.2"
+python-versions = ">=3.7,<4.0"
 files = [
-    {file = "pylint-plugin-utils-0.7.tar.gz", hash = "sha256:ce48bc0516ae9415dd5c752c940dfe601b18fe0f48aa249f2386adfa95a004dd"},
-    {file = "pylint_plugin_utils-0.7-py3-none-any.whl", hash = "sha256:b3d43e85ab74c4f48bb46ae4ce771e39c3a20f8b3d56982ab17aa73b4f98d535"},
+    {file = "pylint_plugin_utils-0.8.2-py3-none-any.whl", hash = "sha256:ae11664737aa2effbf26f973a9e0b6779ab7106ec0adc5fe104b0907ca04e507"},
+    {file = "pylint_plugin_utils-0.8.2.tar.gz", hash = "sha256:d3cebf68a38ba3fba23a873809155562571386d4c1b03e5b4c4cc26c3eee93e4"},
 ]
 
 [package.dependencies]
@@ -1574,13 +1756,13 @@ pylint = ">=1.7"
 
 [[package]]
 name = "python-dotenv"
-version = "1.0.1"
+version = "1.0.0"
 description = "Read key-value pairs from a .env file and set them as environment variables"
 optional = false
 python-versions = ">=3.8"
 files = [
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 socks = ["PySocks (>=1.5.6,!=1.5.7)"]
 use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
+[[package]]
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 packaging = ">=21.3"
 semver = ">=3.0.0,<4.0.0"
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+    {file = "yarl-1.14.0-py3-none-any.whl", hash = "sha256:c8ed4034f0765f8861620c1f2f2364d2e58520ea288497084dae880424fc0d9f"},
+    {file = "yarl-1.14.0.tar.gz", hash = "sha256:88c7d9d58aab0724b979ab5617330acb1c7030b79379c8138c1c8c94e121d1b3"},
 ]
 
 [package.dependencies]
 idna = ">=2.0"
 multidict = ">=4.0"
+propcache = ">=0.2.0"
 
 [metadata]
 lock-version = "2.0"
 python-versions = "3.11.*"
-content-hash = "8ea3ba1563ec0773161423a822a5842d9796805b820046d0fa2b6808ce74433a"
+content-hash = "cbadc308177fe76c3676a9ce88f1e7118f5c64d0c963e4c2c2e779ed8a5b82d4"
diff --git a/modules/programming/module_programming_llm/pyproject.toml b/modules/programming/module_programming_llm/pyproject.toml
index f656768d5..855300fc1 100644
--- a/modules/programming/module_programming_llm/pyproject.toml
+++ b/modules/programming/module_programming_llm/pyproject.toml
@@ -9,17 +9,14 @@ license = "MIT"
 python = "3.11.*"
 # if you have local changes in the common Athena module, use the line below. Otherwise, please use a VCS stable version. Also, a version with tag = "" is possible.
 # athena = { path = "../athena", develop = true }
-athena = { git = "https://github.com/ls1intum/Athena.git", rev = "2da2d33", subdirectory = "athena"}
-openai = "1.37.1"
-langchain = "0.2.11"
-langchain-community="0.2.10"
-langchain-openai = "0.1.19"
+athena = { path = "../../../athena", develop = true }
+#athena = { git = "https://github.com/ls1intum/Athena.git", rev = "2da2d33", subdirectory = "athena"}
+llm_core = { path = "../../../llm_core", develop = true }
 gitpython = "^3.1.41"
 tiktoken = "0.7.0"
 promptlayer = "^0.1.85"
 python-dotenv = "^1.0.0"
 nltk = "^3.8.1"
-replicate = "^0.11.0"
 
 [tool.poetry.group.dev.dependencies]
 types-requests = "^2.31.0.8"
diff --git a/modules/text/module_text_llm/.env.example b/modules/text/module_text_llm/.env.example
index 34e279aab..823e9a302 100644
--- a/modules/text/module_text_llm/.env.example
+++ b/modules/text/module_text_llm/.env.example
@@ -12,7 +12,9 @@ DATABASE_URL=sqlite:///../data/data.sqlite
 
 # Default model to use
 # See below for options, available models are also logged on startup
-LLM_DEFAULT_MODEL="azure_openai_gpt-35-turbo"
+LLM_DEFAULT_MODEL="azure_openai_gpt-4o"
+LLM_DEFAULT_MODEL_COST_PER_MILLION_INPUT_TOKEN=5
+LLM_DEFAULT_MODEL_COST_PER_MILLION_OUTPUT_TOKEN=15
 
 # Enable LLM-as-a-judge approach 0 = disabled, 1 = enabled
 LLM_ENABLE_LLM_AS_A_JUDGE=1
diff --git a/modules/text/module_text_llm/Dockerfile b/modules/text/module_text_llm/Dockerfile
index 48ad92d42..4f9d93be0 100644
--- a/modules/text/module_text_llm/Dockerfile
+++ b/modules/text/module_text_llm/Dockerfile
@@ -17,6 +17,7 @@ RUN pip install --no-cache-dir poetry==1.5.0
 COPY pyproject.toml poetry.lock ./
 # athena module (from the Dockerfile in the athena folder)
 COPY --from=athena /code /athena
+COPY --from=llm_core /code /llm_core
 # install dependencies
 RUN poetry config virtualenvs.create true \
     && poetry config virtualenvs.in-project true \
diff --git a/modules/text/module_text_llm/module_text_llm/config.py b/modules/text/module_text_llm/module_text_llm/config.py
index 82d177eed..0a61eeba6 100644
--- a/modules/text/module_text_llm/module_text_llm/config.py
+++ b/modules/text/module_text_llm/module_text_llm/config.py
@@ -1,7 +1,7 @@
 from pydantic import BaseModel, Field
 
 from athena import config_schema_provider
-from module_text_llm.helpers.models import ModelConfigType, DefaultModelConfig
+from llm_core.models import ModelConfigType, DefaultModelConfig
 from module_text_llm.prompts.generate_suggestions import (
   system_message as generate_suggestions_system_message, 
   human_message as generate_suggestions_human_message
diff --git a/modules/text/module_text_llm/module_text_llm/generate_evaluation.py b/modules/text/module_text_llm/module_text_llm/generate_evaluation.py
index 4c4a9969b..50473dd3a 100644
--- a/modules/text/module_text_llm/module_text_llm/generate_evaluation.py
+++ b/modules/text/module_text_llm/module_text_llm/generate_evaluation.py
@@ -5,12 +5,13 @@
 from athena.text import Exercise, Submission, Feedback
 from athena.logger import logger
 
-from module_text_llm.helpers.models import evaluation_model
-from module_text_llm.helpers.llm_utils import (
+from llm_core.models import evaluation_model
+from llm_core.utils.llm_utils import (
     get_chat_prompt_with_formatting_instructions,
     check_prompt_length_and_omit_features_if_necessary,
-    predict_and_parse
 )
+from llm_core.utils.predict_and_parse import predict_and_parse
+
 from module_text_llm.helpers.utils import add_sentence_numbers, get_line_range_from_index_range
 from module_text_llm.prompts.generate_evaluation import system_message, human_message
 
diff --git a/modules/text/module_text_llm/module_text_llm/generate_suggestions.py b/modules/text/module_text_llm/module_text_llm/generate_suggestions.py
index d43563ad6..be928dc2e 100644
--- a/modules/text/module_text_llm/module_text_llm/generate_suggestions.py
+++ b/modules/text/module_text_llm/module_text_llm/generate_suggestions.py
@@ -6,12 +6,13 @@
 from athena.logger import logger
 
 from module_text_llm.config import BasicApproachConfig
-from module_text_llm.helpers.llm_utils import (
+from llm_core.utils.llm_utils import (
     get_chat_prompt_with_formatting_instructions, 
     check_prompt_length_and_omit_features_if_necessary, 
     num_tokens_from_prompt,
-    predict_and_parse
 )
+from llm_core.utils.predict_and_parse import predict_and_parse
+
 from module_text_llm.helpers.utils import add_sentence_numbers, get_index_range_from_line_range, format_grading_instructions
 
 class FeedbackModel(BaseModel):
diff --git a/modules/text/module_text_llm/module_text_llm/helpers/models/openai.py b/modules/text/module_text_llm/module_text_llm/helpers/models/openai.py
deleted file mode 100644
index 23e1669c2..000000000
--- a/modules/text/module_text_llm/module_text_llm/helpers/models/openai.py
+++ /dev/null
@@ -1,142 +0,0 @@
-import os
-import openai
-import requests
-
-from typing import Dict, List
-from enum import Enum
-from pydantic import Field, validator, PositiveInt
-from langchain.base_language import BaseLanguageModel
-from langchain_openai import AzureChatOpenAI, ChatOpenAI
-
-from athena.logger import logger
-from .model_config import ModelConfig
-
-OPENAI_PREFIX = "openai_"
-AZURE_OPENAI_PREFIX = "azure_openai_"
-openai_available = bool(os.environ.get("OPENAI_API_KEY"))
-azure_openai_available = bool(os.environ.get("AZURE_OPENAI_API_KEY"))
-
-available_models: Dict[str, BaseLanguageModel] = {}
-
-# Load Non-Azure OpenAI models
-if openai_available:
-    openai.api_type = "openai"
-    for model in openai.models.list():
-        if "gpt" in model.id:
-            available_models[OPENAI_PREFIX + model.id] = ChatOpenAI(model=model.id)
-
-# Load Azure OpenAI models
-if azure_openai_available:
-    def _get_azure_openai_deployments() -> List[str]:
-        # If this breaks in the future we have to use azure-mgmt-cognitiveservices which needs 6 additional environment variables
-        base_url = f"{os.environ.get('AZURE_OPENAI_ENDPOINT')}/openai"
-        headers = {
-            "api-key": os.environ["AZURE_OPENAI_API_KEY"]
-        }
-
-        models_response = requests.get(f"{base_url}/models?api-version=2023-03-15-preview", headers=headers, timeout=30)
-        models_data = models_response.json()["data"]
-        deployments_response = requests.get(f"{base_url}/deployments?api-version=2023-03-15-preview", headers=headers,
-                                            timeout=30)
-        deployments_data = deployments_response.json()["data"]
-
-        # Check if deployment["model"] is a substring of model["id"], i.e. "gpt-4o" is substring "gpt-4o-2024-05-13"
-        chat_completion_models = ",".join(model["id"] for model in models_data if model["capabilities"]["chat_completion"])
-        return [deployment["id"] for deployment in deployments_data if deployment["model"] in chat_completion_models]
-
-    for deployment in _get_azure_openai_deployments():
-        available_models[AZURE_OPENAI_PREFIX + deployment] = AzureChatOpenAI(azure_deployment=deployment)
-
-if available_models:
-    logger.info("Available openai models: %s", ", ".join(available_models.keys()))
-
-    OpenAIModel = Enum('OpenAIModel', {name: name for name in available_models}) # type: ignore
-    default_model_name = None
-    if "LLM_DEFAULT_MODEL" in os.environ and os.environ["LLM_DEFAULT_MODEL"] in available_models:
-        default_model_name = os.environ["LLM_DEFAULT_MODEL"]
-    if default_model_name not in available_models:
-        default_model_name = list(available_models.keys())[0]
-
-    default_openai_model = OpenAIModel[default_model_name] # type: ignore
-
-    # Long descriptions will be displayed in the playground UI and are copied from the OpenAI docs
-    class OpenAIModelConfig(ModelConfig):
-        """OpenAI LLM configuration."""
-
-        model_name: OpenAIModel = Field(default=default_openai_model, # type: ignore
-                                        description="The name of the model to use.")
-        max_tokens: PositiveInt = Field(1000, description="""\
-The maximum number of [tokens](https://platform.openai.com/tokenizer) to generate in the chat completion.
-
-The total length of input tokens and generated tokens is limited by the model's context length. \
-[Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb) for counting tokens.\
-""")
-
-        temperature: float = Field(default=0.0, ge=0, le=2, description="""\
-What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, \
-while lower values like 0.2 will make it more focused and deterministic.
-
-We generally recommend altering this or `top_p` but not both.\
-""")
-
-        top_p: float = Field(default=1, ge=0, le=1, description="""\
-An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. \
-So 0.1 means only the tokens comprising the top 10% probability mass are considered.
-
-We generally recommend altering this or `temperature` but not both.\
-""")
-
-        presence_penalty: float = Field(default=0, ge=-2, le=2, description="""\
-Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, \
-increasing the model's likelihood to talk about new topics.
-
-[See more information about frequency and presence penalties.](https://platform.openai.com/docs/api-reference/parameter-details)\
-""")
-
-        frequency_penalty: float = Field(default=0, ge=-2, le=2, description="""\
-Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, \
-decreasing the model's likelihood to repeat the same line verbatim.
-
-[See more information about frequency and presence penalties.](https://platform.openai.com/docs/api-reference/parameter-details)\
-""")
-
-        @validator('max_tokens')
-        def max_tokens_must_be_positive(cls, v):
-            """
-            Validate that max_tokens is a positive integer.
-            """
-            if v <= 0:
-                raise ValueError('max_tokens must be a positive integer')
-            return v
-
-        def get_model(self) -> BaseLanguageModel:
-            """Get the model from the configuration.
-
-            Returns:
-                BaseLanguageModel: The model.
-            """
-            model = available_models[self.model_name.value]
-            kwargs = model.__dict__
-            secrets = {secret: getattr(model, secret) for secret in model.lc_secrets.keys()}
-            kwargs.update(secrets)
-
-            model_kwargs = kwargs.get("model_kwargs", {})
-            for attr, value in self.dict().items():
-                if attr == "model_name":
-                    # Skip model_name
-                    continue
-                if hasattr(model, attr):
-                    # If the model has the attribute, add it to kwargs
-                    kwargs[attr] = value
-                else:
-                    # Otherwise, add it to model_kwargs (necessary for chat models)
-                    model_kwargs[attr] = value
-            kwargs["model_kwargs"] = model_kwargs
-
-            # Initialize a copy of the model using the config
-            model = model.__class__(**kwargs)
-            return model
-
-
-        class Config:
-            title = 'OpenAI'
\ No newline at end of file
diff --git a/modules/text/module_text_llm/poetry.lock b/modules/text/module_text_llm/poetry.lock
index 37eb9e922..860a0f71e 100644
--- a/modules/text/module_text_llm/poetry.lock
+++ b/modules/text/module_text_llm/poetry.lock
@@ -2,113 +2,113 @@
 
 [[package]]
 name = "aiohappyeyeballs"
-version = "2.4.0"
+version = "2.4.3"
 description = "Happy Eyeballs for asyncio"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "aiohappyeyeballs-2.4.0-py3-none-any.whl", hash = "sha256:7ce92076e249169a13c2f49320d1967425eaf1f407522d707d59cac7628d62bd"},
-    {file = "aiohappyeyeballs-2.4.0.tar.gz", hash = "sha256:55a1714f084e63d49639800f95716da97a1f173d46a16dfcfda0016abb93b6b2"},
+    {file = "aiohappyeyeballs-2.4.3-py3-none-any.whl", hash = "sha256:8a7a83727b2756f394ab2895ea0765a0a8c475e3c71e98d43d76f22b4b435572"},
+    {file = "aiohappyeyeballs-2.4.3.tar.gz", hash = "sha256:75cf88a15106a5002a8eb1dab212525c00d1f4c0fa96e551c9fbe6f09a621586"},
 ]
 
 [[package]]
 name = "aiohttp"
-version = "3.10.5"
+version = "3.10.10"
 description = "Async http client/server framework (asyncio)"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "aiohttp-3.10.5-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:18a01eba2574fb9edd5f6e5fb25f66e6ce061da5dab5db75e13fe1558142e0a3"},
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-    {file = "aiohttp-3.10.5-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4f7acae3cf1a2a2361ec4c8e787eaaa86a94171d2417aae53c0cca6ca3118ff6"},
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 ]
 
 [package.dependencies]
@@ -117,7 +117,7 @@ aiosignal = ">=1.1.2"
 attrs = ">=17.3.0"
 frozenlist = ">=1.1.1"
 multidict = ">=4.5,<7.0"
-yarl = ">=1.0,<2.0"
+yarl = ">=1.12.0,<2.0"
 
 [package.extras]
 speedups = ["Brotli", "aiodns (>=3.2.0)", "brotlicffi"]
@@ -138,13 +138,13 @@ frozenlist = ">=1.1.0"
 
 [[package]]
 name = "anyio"
-version = "4.4.0"
+version = "4.6.0"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
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 ]
 
 [package.dependencies]
@@ -152,25 +152,21 @@ idna = ">=2.8"
 sniffio = ">=1.1"
 
 [package.extras]
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-test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
-trio = ["trio (>=0.23)"]
+doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.21.0b1)"]
+trio = ["trio (>=0.26.1)"]
 
 [[package]]
 name = "astroid"
-version = "2.15.8"
+version = "3.3.5"
 description = "An abstract syntax tree for Python with inference support."
 optional = false
-python-versions = ">=3.7.2"
+python-versions = ">=3.9.0"
 files = [
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-[package.dependencies]
-lazy-object-proxy = ">=1.4.0"
-wrapt = {version = ">=1.14,<2", markers = "python_version >= \"3.11\""}
-
 [[package]]
 name = "athena"
 version = "1.0.0"
@@ -224,101 +220,116 @@ files = [
 
 [[package]]
 name = "charset-normalizer"
-version = "3.3.2"
+version = "3.4.0"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
 optional = false
 python-versions = ">=3.7.0"
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 ]
 
 [[package]]
@@ -363,13 +374,13 @@ typing-inspect = ">=0.4.0,<1"
 
 [[package]]
 name = "dill"
-version = "0.3.8"
+version = "0.3.9"
 description = "serialize all of Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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 [[package]]
 name = "flake8-polyfill"
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@@ -692,15 +718,18 @@ socks = ["socksio (==1.*)"]
 
 [[package]]
 name = "idna"
-version = "3.8"
+version = "3.10"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
 python-versions = ">=3.6"
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+[package.extras]
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+
 [[package]]
 name = "isort"
 version = "5.13.2"
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 [package.extras]
 colors = ["colorama (>=0.4.6)"]
 
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+
 [[package]]
 name = "joblib"
 version = "1.4.2"
@@ -753,18 +864,18 @@ files = [
 
 [[package]]
 name = "langchain"
-version = "0.2.11"
+version = "0.2.15"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
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+    {file = "langchain-0.2.15.tar.gz", hash = "sha256:f613ce7594be34f9bac687134a56f6e8274951907b798dbd037aefc95df78953"},
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 [package.dependencies]
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+langchain-core = ">=0.2.35,<0.3.0"
 langchain-text-splitters = ">=0.2.0,<0.3.0"
 langsmith = ">=0.1.17,<0.2.0"
 numpy = {version = ">=1,<2", markers = "python_version < \"3.12\""}
@@ -799,18 +910,18 @@ tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
 
 [[package]]
 name = "langchain-core"
-version = "0.2.38"
+version = "0.2.41"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
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 [package.dependencies]
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 packaging = ">=23.2,<25"
 pydantic = {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""}
 PyYAML = ">=5.3"
@@ -819,18 +930,18 @@ typing-extensions = ">=4.7"
 
 [[package]]
 name = "langchain-openai"
-version = "0.1.19"
+version = "0.1.23"
 description = "An integration package connecting OpenAI and LangChain"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
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 ]
 
 [package.dependencies]
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-openai = ">=1.32.0,<2.0.0"
+langchain-core = ">=0.2.35,<0.3.0"
+openai = ">=1.40.0,<2.0.0"
 tiktoken = ">=0.7,<1"
 
 [[package]]
@@ -849,13 +960,13 @@ langchain-core = ">=0.2.38,<0.3.0"
 
 [[package]]
 name = "langsmith"
-version = "0.1.111"
+version = "0.1.134"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
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 ]
 
 [package.dependencies]
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 orjson = ">=3.9.14,<4.0.0"
 pydantic = {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""}
 requests = ">=2,<3"
+requests-toolbelt = ">=1.0.0,<2.0.0"
 
 [[package]]
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-version = "1.10.0"
-description = "A fast and thorough lazy object proxy."
+name = "llm-core"
+version = "0.1.0"
+description = "SHared LLM module."
 optional = false
-python-versions = ">=3.8"
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 [[package]]
 name = "prospector"
-version = "1.10.3"
+version = "1.12.1"
 description = "Prospector is a tool to analyse Python code by aggregating the result of other tools."
 optional = false
-python-versions = ">=3.7.2,<4.0"
+python-versions = "<4.0,>=3.9"
 files = [
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 ]
 
 [package.dependencies]
 dodgy = ">=0.2.1,<0.3.0"
-flake8 = "<6.0.0"
+flake8 = "*"
 GitPython = ">=3.1.27,<4.0.0"
 mccabe = ">=0.7.0,<0.8.0"
 packaging = "*"
 pep8-naming = ">=0.3.3,<=0.10.0"
 pycodestyle = ">=2.9.0"
 pydocstyle = ">=2.0.0"
-pyflakes = ">=2.2.0,<3"
-pylint = ">=2.8.3"
+pyflakes = ">=2.2.0"
+pylint = ">=3.0"
 pylint-celery = "0.3"
-pylint-django = ">=2.5,<2.6"
+pylint-django = ">=2.6.1"
 pylint-flask = "0.6"
-pylint-plugin-utils = ">=0.7,<0.8"
 PyYAML = "*"
-requirements-detector = ">=1.2.0"
+requirements-detector = ">=1.3.1"
 setoptconf-tmp = ">=0.3.1,<0.4.0"
 toml = ">=0.10.2,<0.11.0"
 
@@ -1359,13 +1559,13 @@ files = [
 
 [[package]]
 name = "pycodestyle"
-version = "2.9.1"
+version = "2.12.1"
 description = "Python style guide checker"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.8"
 files = [
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 ]
 
 [[package]]
@@ -1446,31 +1646,31 @@ toml = ["tomli (>=1.2.3)"]
 
 [[package]]
 name = "pyflakes"
-version = "2.5.0"
+version = "3.2.0"
 description = "passive checker of Python programs"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.8"
 files = [
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-    {file = "pyflakes-2.5.0.tar.gz", hash = "sha256:491feb020dca48ccc562a8c0cbe8df07ee13078df59813b83959cbdada312ea3"},
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 ]
 
 [[package]]
 name = "pylint"
-version = "2.17.7"
+version = "3.3.1"
 description = "python code static checker"
 optional = false
-python-versions = ">=3.7.2"
+python-versions = ">=3.9.0"
 files = [
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+    {file = "pylint-3.3.1-py3-none-any.whl", hash = "sha256:2f846a466dd023513240bc140ad2dd73bfc080a5d85a710afdb728c420a5a2b9"},
+    {file = "pylint-3.3.1.tar.gz", hash = "sha256:9f3dcc87b1203e612b78d91a896407787e708b3f189b5fa0b307712d49ff0c6e"},
 ]
 
 [package.dependencies]
-astroid = ">=2.15.8,<=2.17.0-dev0"
+astroid = ">=3.3.4,<=3.4.0-dev0"
 colorama = {version = ">=0.4.5", markers = "sys_platform == \"win32\""}
 dill = {version = ">=0.3.6", markers = "python_version >= \"3.11\""}
-isort = ">=4.2.5,<6"
+isort = ">=4.2.5,<5.13.0 || >5.13.0,<6"
 mccabe = ">=0.6,<0.8"
 platformdirs = ">=2.2.0"
 tomlkit = ">=0.10.1"
@@ -1496,22 +1696,21 @@ pylint-plugin-utils = ">=0.2.1"
 
 [[package]]
 name = "pylint-django"
-version = "2.5.3"
+version = "2.6.1"
 description = "A Pylint plugin to help Pylint understand the Django web framework"
 optional = false
-python-versions = "*"
+python-versions = "<4.0,>=3.9"
 files = [
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+    {file = "pylint-django-2.6.1.tar.gz", hash = "sha256:19e8c85a8573a04e3de7be2ba91e9a7c818ebf05e1b617be2bbae67a906b725f"},
+    {file = "pylint_django-2.6.1-py3-none-any.whl", hash = "sha256:359f68fe8c810ee6bc8e1ab4c83c19b15a43b234a24b08978f47a23462b5ce28"},
 ]
 
 [package.dependencies]
-pylint = ">=2.0,<3"
-pylint-plugin-utils = ">=0.7"
+pylint = ">=3.0,<4"
+pylint-plugin-utils = ">=0.8"
 
 [package.extras]
-for-tests = ["coverage", "django-tables2", "django-tastypie", "factory-boy", "pylint (>=2.13)", "pytest", "wheel"]
-with-django = ["Django"]
+with-django = ["Django (>=2.2)"]
 
 [[package]]
 name = "pylint-flask"
@@ -1528,13 +1727,13 @@ pylint-plugin-utils = ">=0.2.1"
 
 [[package]]
 name = "pylint-plugin-utils"
-version = "0.7"
+version = "0.8.2"
 description = "Utilities and helpers for writing Pylint plugins"
 optional = false
-python-versions = ">=3.6.2"
+python-versions = ">=3.7,<4.0"
 files = [
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-    {file = "pylint_plugin_utils-0.7-py3-none-any.whl", hash = "sha256:b3d43e85ab74c4f48bb46ae4ce771e39c3a20f8b3d56982ab17aa73b4f98d535"},
+    {file = "pylint_plugin_utils-0.8.2-py3-none-any.whl", hash = "sha256:ae11664737aa2effbf26f973a9e0b6779ab7106ec0adc5fe104b0907ca04e507"},
+    {file = "pylint_plugin_utils-0.8.2.tar.gz", hash = "sha256:d3cebf68a38ba3fba23a873809155562571386d4c1b03e5b4c4cc26c3eee93e4"},
 ]
 
 [package.dependencies]
@@ -1618,111 +1817,107 @@ files = [
 
 [[package]]
 name = "regex"
-version = "2024.7.24"
+version = "2024.9.11"
 description = "Alternative regular expression module, to replace re."
 optional = false
 python-versions = ">=3.8"
 files = [
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-[package.dependencies]
-packaging = "*"
-pydantic = ">1"
-requests = ">2"
-
-[package.extras]
-dev = ["black", "mypy", "pytest", "responses", "ruff"]
-
 [[package]]
 name = "requests"
 version = "2.32.3"
@@ -1744,19 +1939,33 @@ urllib3 = ">=1.21.1,<3"
 socks = ["PySocks (>=1.5.6,!=1.5.7)"]
 use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
+[[package]]
+name = "requests-toolbelt"
+version = "1.0.0"
+description = "A utility belt for advanced users of python-requests"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
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+
+[package.dependencies]
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+
 [[package]]
 name = "requirements-detector"
-version = "1.2.2"
+version = "1.3.1"
 description = "Python tool to find and list requirements of a Python project"
 optional = false
-python-versions = ">=3.7,<4.0"
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 ]
 
 [package.dependencies]
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+astroid = ">=3.0,<4.0"
 packaging = ">=21.3"
 semver = ">=3.0.0,<4.0.0"
 toml = ">=0.10.2,<0.11.0"
@@ -1821,60 +2030,60 @@ files = [
 
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 name = "sqlalchemy"
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+version = "2.0.35"
 description = "Database Abstraction Library"
 optional = false
 python-versions = ">=3.7"
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 [package.extras]
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+    {file = "yarl-1.14.0-py3-none-any.whl", hash = "sha256:c8ed4034f0765f8861620c1f2f2364d2e58520ea288497084dae880424fc0d9f"},
+    {file = "yarl-1.14.0.tar.gz", hash = "sha256:88c7d9d58aab0724b979ab5617330acb1c7030b79379c8138c1c8c94e121d1b3"},
 ]
 
 [package.dependencies]
 idna = ">=2.0"
 multidict = ">=4.0"
+propcache = ">=0.2.0"
 
 [metadata]
 lock-version = "2.0"
 python-versions = "3.11.*"
-content-hash = "e3d6d9da95585aa2a7cba97910d821d5cda5412c2a37578097b588e49553d19c"
+content-hash = "f7ea4d2b80e6f70b76d43640120511ec255c3a7bf226592d711e142b9ece9192"
diff --git a/modules/text/module_text_llm/pyproject.toml b/modules/text/module_text_llm/pyproject.toml
index 3f3d43ab6..d0e73bd67 100644
--- a/modules/text/module_text_llm/pyproject.toml
+++ b/modules/text/module_text_llm/pyproject.toml
@@ -7,15 +7,12 @@ license = "MIT"
 
 [tool.poetry.dependencies]
 python = "3.11.*"
-athena = {path = "../../../athena", develop = true}
-replicate = "^0.11.0"
+athena = { path = "../../../athena", develop = true }
+# athena = { git = "https://github.com/ls1intum/Athena.git", rev = "2da2d33", subdirectory = "athena"}
+llm_core = { path = "../../../llm_core", develop = true }
 langsmith = ">=0.1.0,<0.2.0"
 gitpython = "3.1.41"
-langchain = "0.2.11"
-langchain-community="0.2.10"
-langchain-openai = "0.1.19"
 nltk = "3.8.1"
-openai = "1.37.1"
 python-dotenv = "1.0.0"
 tiktoken = "0.7.0"
 
diff --git a/playground/.gitignore b/playground/.gitignore
index 1f6d92b2c..5220babfb 100644
--- a/playground/.gitignore
+++ b/playground/.gitignore
@@ -35,6 +35,9 @@ yarn-error.log*
 # vercel
 .vercel
 
+# gradle
+.gradle/
+
 # typescript
 *.tsbuildinfo
 next-env.d.ts
\ No newline at end of file
diff --git a/modules/text/module_text_llm/module_text_llm/helpers/models/replicate.py b/playground/data/expert_evaluation/.gitkeep
similarity index 100%
rename from modules/text/module_text_llm/module_text_llm/helpers/models/replicate.py
rename to playground/data/expert_evaluation/.gitkeep
diff --git a/playground/package-lock.json b/playground/package-lock.json
index 3e582f6ac..527605e45 100644
--- a/playground/package-lock.json
+++ b/playground/package-lock.json
@@ -9,6 +9,9 @@
       "version": "0.1.0",
       "dependencies": {
         "@blueprintjs/core": "5.5.1",
+        "@fortawesome/fontawesome-svg-core": "6.6.0",
+        "@fortawesome/free-solid-svg-icons": "6.6.0",
+        "@fortawesome/react-fontawesome": "0.2.2",
         "@ls1intum/apollon": "3.3.5",
         "@monaco-editor/react": "4.6.0",
         "@radix-ui/react-collapsible": "1.0.3",
@@ -26,6 +29,7 @@
         "react": "18.2.0",
         "react-complex-tree": "2.2.2",
         "react-complex-tree-blueprintjs-renderers": "2.2.2",
+        "react-confetti": "6.1.0",
         "react-dom": "18.2.0",
         "react-full-screen": "1.1.1",
         "react-markdown": "9.0.0",
@@ -746,6 +750,48 @@
         "node": "^12.22.0 || ^14.17.0 || >=16.0.0"
       }
     },
+    "node_modules/@fortawesome/fontawesome-common-types": {
+      "version": "6.6.0",
+      "resolved": "https://registry.npmjs.org/@fortawesome/fontawesome-common-types/-/fontawesome-common-types-6.6.0.tgz",
+      "integrity": "sha512-xyX0X9mc0kyz9plIyryrRbl7ngsA9jz77mCZJsUkLl+ZKs0KWObgaEBoSgQiYWAsSmjz/yjl0F++Got0Mdp4Rw==",
+      "engines": {
+        "node": ">=6"
+      }
+    },
+    "node_modules/@fortawesome/fontawesome-svg-core": {
+      "version": "6.6.0",
+      "resolved": "https://registry.npmjs.org/@fortawesome/fontawesome-svg-core/-/fontawesome-svg-core-6.6.0.tgz",
+      "integrity": "sha512-KHwPkCk6oRT4HADE7smhfsKudt9N/9lm6EJ5BVg0tD1yPA5hht837fB87F8pn15D8JfTqQOjhKTktwmLMiD7Kg==",
+      "dependencies": {
+        "@fortawesome/fontawesome-common-types": "6.6.0"
+      },
+      "engines": {
+        "node": ">=6"
+      }
+    },
+    "node_modules/@fortawesome/free-solid-svg-icons": {
+      "version": "6.6.0",
+      "resolved": "https://registry.npmjs.org/@fortawesome/free-solid-svg-icons/-/free-solid-svg-icons-6.6.0.tgz",
+      "integrity": "sha512-IYv/2skhEDFc2WGUcqvFJkeK39Q+HyPf5GHUrT/l2pKbtgEIv1al1TKd6qStR5OIwQdN1GZP54ci3y4mroJWjA==",
+      "dependencies": {
+        "@fortawesome/fontawesome-common-types": "6.6.0"
+      },
+      "engines": {
+        "node": ">=6"
+      }
+    },
+    "node_modules/@fortawesome/react-fontawesome": {
+      "version": "0.2.2",
+      "resolved": "https://registry.npmjs.org/@fortawesome/react-fontawesome/-/react-fontawesome-0.2.2.tgz",
+      "integrity": "sha512-EnkrprPNqI6SXJl//m29hpaNzOp1bruISWaOiRtkMi/xSvHJlzc2j2JAYS7egxt/EbjSNV/k6Xy0AQI6vB2+1g==",
+      "dependencies": {
+        "prop-types": "^15.8.1"
+      },
+      "peerDependencies": {
+        "@fortawesome/fontawesome-svg-core": "~1 || ~6",
+        "react": ">=16.3"
+      }
+    },
     "node_modules/@humanwhocodes/config-array": {
       "version": "0.11.13",
       "resolved": "https://registry.npmjs.org/@humanwhocodes/config-array/-/config-array-0.11.13.tgz",
@@ -5928,9 +5974,9 @@
       }
     },
     "node_modules/nanoid": {
-      "version": "3.3.6",
-      "resolved": "https://registry.npmjs.org/nanoid/-/nanoid-3.3.6.tgz",
-      "integrity": "sha512-BGcqMMJuToF7i1rt+2PWSNVnWIkGCU78jBG3RxO/bZlnZPK2Cmi2QaffxGO/2RvWi9sL+FAiRiXMgsyxQ1DIDA==",
+      "version": "3.3.7",
+      "resolved": "https://registry.npmjs.org/nanoid/-/nanoid-3.3.7.tgz",
+      "integrity": "sha512-eSRppjcPIatRIMC1U6UngP8XFcz8MQWGQdt1MTBQ7NaAmvXDfvNxbvWV3x2y6CdEUciCSsDHDQZbhYaB8QEo2g==",
       "funding": [
         {
           "type": "github",
@@ -5999,6 +6045,33 @@
         }
       }
     },
+    "node_modules/next/node_modules/postcss": {
+      "version": "8.4.31",
+      "resolved": "https://registry.npmjs.org/postcss/-/postcss-8.4.31.tgz",
+      "integrity": "sha512-PS08Iboia9mts/2ygV3eLpY5ghnUcfLV/EXTOW1E2qYxJKGGBUtNjN76FYHnMs36RmARn41bC0AZmn+rR0OVpQ==",
+      "funding": [
+        {
+          "type": "opencollective",
+          "url": "https://opencollective.com/postcss/"
+        },
+        {
+          "type": "tidelift",
+          "url": "https://tidelift.com/funding/github/npm/postcss"
+        },
+        {
+          "type": "github",
+          "url": "https://github.com/sponsors/ai"
+        }
+      ],
+      "dependencies": {
+        "nanoid": "^3.3.6",
+        "picocolors": "^1.0.0",
+        "source-map-js": "^1.0.2"
+      },
+      "engines": {
+        "node": "^10 || ^12 || >=14"
+      }
+    },
     "node_modules/no-case": {
       "version": "3.0.4",
       "resolved": "https://registry.npmjs.org/no-case/-/no-case-3.0.4.tgz",
@@ -6384,9 +6457,9 @@
       "integrity": "sha512-5yHVB9OHqKd9fr/OIsn8ss0NgThQ9buaqrEuwr9Or5YjPp6h+WTDKWZI+xZLaBGZCtODTnFtlSHNmhFsq67THg=="
     },
     "node_modules/picocolors": {
-      "version": "1.0.0",
-      "resolved": "https://registry.npmjs.org/picocolors/-/picocolors-1.0.0.tgz",
-      "integrity": "sha512-1fygroTLlHu66zi26VoTDv8yRgm0Fccecssto+MhsZ0D/DGW2sm8E8AjW7NU5VVTRt5GxbeZ5qBuJr+HyLYkjQ=="
+      "version": "1.1.1",
+      "resolved": "https://registry.npmjs.org/picocolors/-/picocolors-1.1.1.tgz",
+      "integrity": "sha512-xceH2snhtb5M9liqDsmEw56le376mTZkEX/jEb/RxNFyegNul7eNslCXP9FDj/Lcu0X8KEyMceP2ntpaHrDEVA=="
     },
     "node_modules/picomatch": {
       "version": "2.3.1",
@@ -6416,9 +6489,9 @@
       }
     },
     "node_modules/postcss": {
-      "version": "8.4.31",
-      "resolved": "https://registry.npmjs.org/postcss/-/postcss-8.4.31.tgz",
-      "integrity": "sha512-PS08Iboia9mts/2ygV3eLpY5ghnUcfLV/EXTOW1E2qYxJKGGBUtNjN76FYHnMs36RmARn41bC0AZmn+rR0OVpQ==",
+      "version": "8.4.49",
+      "resolved": "https://registry.npmjs.org/postcss/-/postcss-8.4.49.tgz",
+      "integrity": "sha512-OCVPnIObs4N29kxTjzLfUryOkvZEq+pf8jTF0lg8E7uETuWHA+v7j3c/xJmiqpX450191LlmZfUKkXxkTry7nA==",
       "funding": [
         {
           "type": "opencollective",
@@ -6434,9 +6507,9 @@
         }
       ],
       "dependencies": {
-        "nanoid": "^3.3.6",
-        "picocolors": "^1.0.0",
-        "source-map-js": "^1.0.2"
+        "nanoid": "^3.3.7",
+        "picocolors": "^1.1.1",
+        "source-map-js": "^1.2.1"
       },
       "engines": {
         "node": "^10 || ^12 || >=14"
@@ -6668,6 +6741,20 @@
       "resolved": "https://registry.npmjs.org/react-complex-tree-blueprintjs-renderers/-/react-complex-tree-blueprintjs-renderers-2.2.2.tgz",
       "integrity": "sha512-6VRIjYhMcxLB3HxzpGLnz2sRHM50YpMLuIAutPpbByjYW5RVsB1EUPvtk7ZO4rhj5MLFzRhqHgCt1exFGZJ/Sw=="
     },
+    "node_modules/react-confetti": {
+      "version": "6.1.0",
+      "resolved": "https://registry.npmjs.org/react-confetti/-/react-confetti-6.1.0.tgz",
+      "integrity": "sha512-7Ypx4vz0+g8ECVxr88W9zhcQpbeujJAVqL14ZnXJ3I23mOI9/oBVTQ3dkJhUmB0D6XOtCZEM6N0Gm9PMngkORw==",
+      "dependencies": {
+        "tween-functions": "^1.2.0"
+      },
+      "engines": {
+        "node": ">=10.18"
+      },
+      "peerDependencies": {
+        "react": "^16.3.0 || ^17.0.1 || ^18.0.0"
+      }
+    },
     "node_modules/react-dom": {
       "version": "18.2.0",
       "resolved": "https://registry.npmjs.org/react-dom/-/react-dom-18.2.0.tgz",
@@ -7401,9 +7488,9 @@
       }
     },
     "node_modules/source-map-js": {
-      "version": "1.0.2",
-      "resolved": "https://registry.npmjs.org/source-map-js/-/source-map-js-1.0.2.tgz",
-      "integrity": "sha512-R0XvVJ9WusLiqTCEiGCmICCMplcCkIwwR11mOSD9CR5u+IXYdiseeEuXCVAjS54zqwkLcPNnmU4OeJ6tUrWhDw==",
+      "version": "1.2.1",
+      "resolved": "https://registry.npmjs.org/source-map-js/-/source-map-js-1.2.1.tgz",
+      "integrity": "sha512-UXWMKhLOwVKb728IUtQPXxfYU+usdybtUrK/8uGE8CQMvrhOpwvzDBwj0QhSL7MQc7vIsISBG8VQ8+IDQxpfQA==",
       "engines": {
         "node": ">=0.10.0"
       }
@@ -7913,6 +8000,11 @@
       "integrity": "sha512-Xni35NKzjgMrwevysHTCArtLDpPvye8zV/0E4EyYn43P7/7qvQwPh9BGkHewbMulVntbigmcT7rdX3BNo9wRJg==",
       "dev": true
     },
+    "node_modules/tween-functions": {
+      "version": "1.2.0",
+      "resolved": "https://registry.npmjs.org/tween-functions/-/tween-functions-1.2.0.tgz",
+      "integrity": "sha512-PZBtLYcCLtEcjL14Fzb1gSxPBeL7nWvGhO5ZFPGqziCcr8uvHp0NDmdjBchp6KHL+tExcg0m3NISmKxhU394dA=="
+    },
     "node_modules/type-check": {
       "version": "0.4.0",
       "resolved": "https://registry.npmjs.org/type-check/-/type-check-0.4.0.tgz",
diff --git a/playground/package.json b/playground/package.json
index c2ef3fba0..82c2c92a2 100644
--- a/playground/package.json
+++ b/playground/package.json
@@ -14,6 +14,9 @@
   },
   "dependencies": {
     "@blueprintjs/core": "5.5.1",
+    "@fortawesome/fontawesome-svg-core": "6.6.0",
+    "@fortawesome/free-solid-svg-icons": "6.6.0",
+    "@fortawesome/react-fontawesome": "0.2.2",
     "@ls1intum/apollon": "3.3.5",
     "@monaco-editor/react": "4.6.0",
     "@radix-ui/react-collapsible": "1.0.3",
@@ -31,6 +34,7 @@
     "react": "18.2.0",
     "react-complex-tree": "2.2.2",
     "react-complex-tree-blueprintjs-renderers": "2.2.2",
+    "react-confetti": "6.1.0",
     "react-dom": "18.2.0",
     "react-full-screen": "1.1.1",
     "react-markdown": "9.0.0",
diff --git a/playground/src/assets/evaluation_backgrounds/congratulations.jpeg b/playground/src/assets/evaluation_backgrounds/congratulations.jpeg
new file mode 100644
index 000000000..18f136431
Binary files /dev/null and b/playground/src/assets/evaluation_backgrounds/congratulations.jpeg differ
diff --git a/playground/src/assets/evaluation_backgrounds/exercise.jpeg b/playground/src/assets/evaluation_backgrounds/exercise.jpeg
new file mode 100644
index 000000000..d2f7f16ac
Binary files /dev/null and b/playground/src/assets/evaluation_backgrounds/exercise.jpeg differ
diff --git a/playground/src/assets/evaluation_backgrounds/save-progress.jpeg b/playground/src/assets/evaluation_backgrounds/save-progress.jpeg
new file mode 100644
index 000000000..cf40d481d
Binary files /dev/null and b/playground/src/assets/evaluation_backgrounds/save-progress.jpeg differ
diff --git a/playground/src/assets/evaluation_backgrounds/welcome-screen.jpeg b/playground/src/assets/evaluation_backgrounds/welcome-screen.jpeg
new file mode 100644
index 000000000..8ce600884
Binary files /dev/null and b/playground/src/assets/evaluation_backgrounds/welcome-screen.jpeg differ
diff --git a/playground/src/assets/evaluation_tutorial/continue_later.gif b/playground/src/assets/evaluation_tutorial/continue_later.gif
new file mode 100644
index 000000000..eb17d4abe
Binary files /dev/null and b/playground/src/assets/evaluation_tutorial/continue_later.gif differ
diff --git a/playground/src/assets/evaluation_tutorial/evaluate_metrics.gif b/playground/src/assets/evaluation_tutorial/evaluate_metrics.gif
new file mode 100644
index 000000000..f742c5f0c
Binary files /dev/null and b/playground/src/assets/evaluation_tutorial/evaluate_metrics.gif differ
diff --git a/playground/src/assets/evaluation_tutorial/exercise_details.gif b/playground/src/assets/evaluation_tutorial/exercise_details.gif
new file mode 100644
index 000000000..be056f5fe
Binary files /dev/null and b/playground/src/assets/evaluation_tutorial/exercise_details.gif differ
diff --git a/playground/src/assets/evaluation_tutorial/metrics-explanation.gif b/playground/src/assets/evaluation_tutorial/metrics-explanation.gif
new file mode 100644
index 000000000..5a3f37d53
Binary files /dev/null and b/playground/src/assets/evaluation_tutorial/metrics-explanation.gif differ
diff --git a/playground/src/assets/evaluation_tutorial/read_submission.gif b/playground/src/assets/evaluation_tutorial/read_submission.gif
new file mode 100644
index 000000000..2636f751a
Binary files /dev/null and b/playground/src/assets/evaluation_tutorial/read_submission.gif differ
diff --git a/playground/src/assets/evaluation_tutorial/view-next.gif b/playground/src/assets/evaluation_tutorial/view-next.gif
new file mode 100644
index 000000000..38c375acb
Binary files /dev/null and b/playground/src/assets/evaluation_tutorial/view-next.gif differ
diff --git a/playground/src/components/details/editor/file_editor.tsx b/playground/src/components/details/editor/file_editor.tsx
index d75f33e74..7a7b85a69 100644
--- a/playground/src/components/details/editor/file_editor.tsx
+++ b/playground/src/components/details/editor/file_editor.tsx
@@ -25,6 +25,7 @@ type FileEditorProps = {
   createNewFeedback?: () => Feedback;
   manualRatings?: ManualRating[];
   onManualRatingsChange?: (manualRatings: ManualRating[]) => void;
+  hideFeedbackDetails?: boolean;
 };
 
 export default function FileEditor({
@@ -38,6 +39,7 @@ export default function FileEditor({
   createNewFeedback,
   manualRatings,
   onManualRatingsChange,
+  hideFeedbackDetails
 }: FileEditorProps) {
   const monaco = useMonaco();
   const editorRef = useRef<editor.IStandaloneCodeEditor>();
@@ -358,6 +360,7 @@ export default function FileEditor({
                       }
                       model={model}
                       className="mr-4"
+                      hideDetails={hideFeedbackDetails}
                     />
                   </EditorWidget>
                 )
diff --git a/playground/src/components/details/editor/inline_feedback.tsx b/playground/src/components/details/editor/inline_feedback.tsx
index 7e5b16d29..764471e74 100644
--- a/playground/src/components/details/editor/inline_feedback.tsx
+++ b/playground/src/components/details/editor/inline_feedback.tsx
@@ -19,6 +19,7 @@ type InlineFeedbackProps = {
   onManualRatingChange?: (manualRating: ManualRating) => void;
   model?: editor.ITextModel;
   className?: string;
+  hideDetails?: boolean;
 };
 
 export default function InlineFeedback({
@@ -28,6 +29,7 @@ export default function InlineFeedback({
   onManualRatingChange,
   model,
   className,
+  hideDetails,
 }: InlineFeedbackProps) {
   const [isEditing, setIsEditing] = useState(false);
   const [confirmDelete, setConfirmDelete] = useState(false);
@@ -145,29 +147,31 @@ export default function InlineFeedback({
       onMouseEnter={() => setIsHovering(true)}
       onMouseLeave={() => setIsHovering(false)}
     >
-      <div className="flex items-center justify-between px-4 py-2 border-b border-gray-300 text-xs text-gray-600">
-        <div className="break-all">
-          {referenceType === "unreferenced" && "Unreferenced"}
-          {"file_path" in feedback &&
-            referenceType === "unreferenced_file" &&
-            `References ${feedback.file_path}`}
-          {referenceType === "referenced" &&
-            `References ${formatReference(feedback)}`}
-        </div>
-        <div className="flex gap-1">
-          {feedback.structured_grading_instruction_id && (
-            <span className="text-xs text-orange-800 rounded-full px-2 py-0.5 bg-orange-100">
-              Grading&nbsp;Instruction&nbsp;
-              {feedback.structured_grading_instruction_id}
-            </span>
-          )}
-          {feedback.isSuggestion && (
-            <span className="text-xs text-violet-800 rounded-full px-2 py-0.5 bg-violet-100">
-              Suggestion
-            </span>
-          )}
+      {hideDetails ? null : (
+        <div className="flex items-center justify-between px-4 py-2 border-b border-gray-300 text-xs text-gray-600">
+          <div className="break-all">
+            {referenceType === "unreferenced" && "Unreferenced"}
+            {"file_path" in feedback &&
+              referenceType === "unreferenced_file" &&
+              `References ${feedback.file_path}`}
+            {referenceType === "referenced" &&
+              `References ${formatReference(feedback)}`}
+          </div>
+          <div className="flex gap-1">
+            {feedback.structured_grading_instruction_id && (
+              <span className="text-xs text-orange-800 rounded-full px-2 py-0.5 bg-orange-100">
+                Grading&nbsp;Instruction&nbsp;
+                {feedback.structured_grading_instruction_id}
+              </span>
+            )}
+            {feedback.isSuggestion && (
+              <span className="text-xs text-violet-800 rounded-full px-2 py-0.5 bg-violet-100">
+                Suggestion
+              </span>
+            )}
+          </div>
         </div>
-      </div>
+      )}
       <div className="flex justify-start items-start space-x-2 px-4 py-2">
         {isEditing && onFeedbackChange ? (
           <input
diff --git a/playground/src/components/details/exercise_detail/index.tsx b/playground/src/components/details/exercise_detail/index.tsx
index 18fd5db15..460edd1c7 100644
--- a/playground/src/components/details/exercise_detail/index.tsx
+++ b/playground/src/components/details/exercise_detail/index.tsx
@@ -20,7 +20,7 @@ export default function ExerciseDetail({
   const specificExerciseDetail = (() => {
     switch (exercise.type) {
       case "text":
-        return <TextExerciseDetail exercise={exercise} openedInitially={openedInitially}/>;
+        return <TextExerciseDetail exercise={exercise} openedInitially={openedInitially} />;
       case "programming":
         return <ProgrammingExerciseDetail exercise={exercise} openedInitially={openedInitially} />;
       default:
@@ -29,7 +29,7 @@ export default function ExerciseDetail({
   })();
 
   return hideDisclosure ? (
-    <div className="mt-2 space-y-1">
+    <div className="mt-2 space-y-1 w-full lg:w-[60vw] max-h-[50vh] overflow-y-auto overflow-x-hidden flex flex-col">
       <CommonExerciseDetail exercise={exercise} openedInitially={openedInitially} />
       {specificExerciseDetail}
     </div>
@@ -40,7 +40,7 @@ export default function ExerciseDetail({
       openedInitially={openedInitially}
     >
       <>
-        <CommonExerciseDetail exercise={exercise}/>
+        <CommonExerciseDetail exercise={exercise} />
         {specificExerciseDetail}
       </>
     </Disclosure>
diff --git a/playground/src/components/details/submission_detail/text.tsx b/playground/src/components/details/submission_detail/text.tsx
index d461f10dc..8d032ef7f 100644
--- a/playground/src/components/details/submission_detail/text.tsx
+++ b/playground/src/components/details/submission_detail/text.tsx
@@ -14,6 +14,7 @@ type TextSubmissionDetailProps = {
   onFeedbacksChange?: (feedback: Feedback[]) => void;
   manualRatings?: ManualRating[];
   onManualRatingsChange?: (manualRatings: ManualRating[]) => void;
+  hideFeedbackDetails?: boolean;
 };
 
 export default function TextSubmissionDetail({
@@ -23,6 +24,7 @@ export default function TextSubmissionDetail({
   onFeedbacksChange,
   manualRatings,
   onManualRatingsChange,
+  hideFeedbackDetails,
 }: TextSubmissionDetailProps) {
   const unreferencedFeedbacks = feedbacks?.filter(
     (feedback) => getFeedbackReferenceType(feedback) === "unreferenced"
@@ -41,6 +43,7 @@ export default function TextSubmissionDetail({
           manualRatings={manualRatings}
           onManualRatingsChange={onManualRatingsChange}
           createNewFeedback={() => createNewFeedback(submission)}
+          hideFeedbackDetails={hideFeedbackDetails}
         />
       </div>
       {((unreferencedFeedbacks && unreferencedFeedbacks.length > 0) ||
@@ -64,6 +67,7 @@ export default function TextSubmissionDetail({
                     onManualRatingsChange &&
                     createManualRatingItemUpdater(feedback.id, manualRatings, onManualRatingsChange)
                   }
+                  hideDetails={hideFeedbackDetails}
                 />
               )
           )}
diff --git a/playground/src/components/expert_evaluation/expert_evaluation_buttons.tsx b/playground/src/components/expert_evaluation/expert_evaluation_buttons.tsx
new file mode 100644
index 000000000..7d92b7ffd
--- /dev/null
+++ b/playground/src/components/expert_evaluation/expert_evaluation_buttons.tsx
@@ -0,0 +1,84 @@
+import React from 'react';
+import { FontAwesomeIcon } from '@fortawesome/react-fontawesome';
+import { faCircleInfo } from '@fortawesome/free-solid-svg-icons';
+
+const buttonBase = "px-4 py-2 rounded focus:outline-none transition-all";
+const buttonPrimary = `${buttonBase} bg-blue-500 text-white hover:bg-blue-600`;
+const buttonSecondary = `${buttonBase} bg-gray-300 text-gray-700 hover:bg-gray-400`;
+const buttonFinish = `${buttonBase} bg-green-600 text-white hover:bg-green-700`;
+
+
+interface NextButtonProps {
+    onClick?: () => void;
+    isFinish?: boolean;
+    isInline?: boolean;
+    className?: string;
+}
+
+export function NextButton(nextButtonProps: NextButtonProps) {
+    const { onClick, isFinish, isInline, className } = nextButtonProps;
+    return <button
+        onClick={onClick}
+        className={`${isFinish ? buttonFinish : buttonPrimary}  ${isInline ? 'inline-block' : 'w-full'} ${className}`}
+    >
+        {isFinish ? 'Finish 🏁' : 'Next ➡️'}
+    </button>
+}
+
+
+interface SecondaryButtonProps {
+    onClick?: () => void;
+    isInline?: boolean;
+    className?: string;
+    text: string;
+    isDisabled?: boolean;
+}
+
+export function SecondaryButton(secondaryButtonProps: SecondaryButtonProps) {
+    const { onClick, isInline, className, text, isDisabled } = secondaryButtonProps;
+    return <button
+        onClick={onClick}
+        className={`${buttonSecondary} ${isInline ? 'inline-block' : ''} ${className}`}
+        disabled={isDisabled}
+    >
+        {text}
+    </button>
+}
+
+
+interface PrimaryButtonProps {
+    onClick?: () => void;
+    isInline?: boolean;
+    isDisabled?: boolean,
+    className?: string;
+    text: string;
+}
+
+export function PrimaryButton(primaryButtonProps: PrimaryButtonProps) {
+    const { onClick, isInline, isDisabled, className, text } = primaryButtonProps;
+    return <button
+        onClick={onClick}
+        className={`${buttonPrimary} ${isInline ? 'inline-block' : ''} ${className}`}
+        disabled={isDisabled}
+    >
+        {text}
+    </button>
+}
+
+
+interface InfoIconButtonProps {
+    onClick?: () => void;
+    className?: string;
+}
+
+export function InfoIconButton(infoIconButtonProps: InfoIconButtonProps) {
+    const { onClick, className } = infoIconButtonProps;
+    return <span
+        onClick={onClick}
+        className={`text-gray-400 cursor-pointer hover:text-gray-600 ${className}`}
+        role="img"
+        aria-label="info"
+    >
+        <FontAwesomeIcon icon={faCircleInfo} />
+    </span>
+}
diff --git a/playground/src/components/expert_evaluation/expert_view/congratulation_screen.tsx b/playground/src/components/expert_evaluation/expert_view/congratulation_screen.tsx
new file mode 100644
index 000000000..b00a5e3ca
--- /dev/null
+++ b/playground/src/components/expert_evaluation/expert_view/congratulation_screen.tsx
@@ -0,0 +1,44 @@
+import React, { useEffect, useState } from 'react';
+import Confetti from 'react-confetti';
+import background_image from "@/assets/evaluation_backgrounds/congratulations.jpeg";
+
+export default function CongratulationScreen() {
+  const [windowSize, setWindowSize] = useState({ width: window.innerWidth, height: window.innerHeight });
+
+  useEffect(() => {
+    const handleResize = () => {
+      setWindowSize({
+        width: window.innerWidth,
+        height: window.innerHeight
+      });
+    };
+
+    window.addEventListener('resize', handleResize);
+    return () => window.removeEventListener('resize', handleResize);
+  }, []);
+
+  return (
+    <div
+      className="fixed inset-0 bg-congratulation-bg bg-cover bg-center bg-black bg-opacity-75 flex items-center justify-center z-50"
+      style={{
+        backgroundImage: `url(${background_image.src})`,
+        backgroundSize: 'cover',
+        backgroundPosition: 'center',
+      }}>
+      {/* Confetti effect */}
+      <Confetti
+        width={windowSize.width}
+        height={windowSize.height}
+        numberOfPieces={300}
+        gravity={0.2}
+      />
+
+      <div className="bg-white p-8 rounded-lg shadow-lg max-w-lg w-full text-center relative z-10">
+        <h1 className="text-4xl font-bold mb-4">Congratulations!</h1>
+        <p className="text-lg mb-6">
+          You have successfully completed the expert evaluation. Thank you for your hard work!
+        </p>
+      </div>
+    </div>
+  );
+};
diff --git a/playground/src/components/expert_evaluation/expert_view/continue_later_screen.tsx b/playground/src/components/expert_evaluation/expert_view/continue_later_screen.tsx
new file mode 100644
index 000000000..f15e37436
--- /dev/null
+++ b/playground/src/components/expert_evaluation/expert_view/continue_later_screen.tsx
@@ -0,0 +1,34 @@
+import React from 'react';
+import background_image from "@/assets/evaluation_backgrounds/save-progress.jpeg";
+import { PrimaryButton } from "@/components/expert_evaluation/expert_evaluation_buttons";
+
+
+interface ContinueLaterScreenProps {
+  onClose: () => void;
+}
+
+export default function ContinueLaterScreen(continueLaterScreenProps: ContinueLaterScreenProps) {
+  const { onClose } = continueLaterScreenProps;
+
+  return (
+    <div className="fixed inset-0 bg-black bg-opacity-75 flex items-center justify-center z-50"
+      style={{
+        backgroundImage: `url(${background_image.src})`,
+        backgroundSize: 'cover',
+        backgroundPosition: 'center',
+      }}
+    >
+      <div className="bg-white p-8 rounded-lg shadow-lg max-w-lg w-full text-center">
+        <h1 className="text-4xl font-bold mb-4">Continue Later</h1>
+        <p className="text-lg mb-6">
+          Your progress has been saved. You can continue the evaluation later using the same link.
+        </p>
+        <PrimaryButton
+          onClick={onClose}
+          text="Continue Evaluation"
+          className="px-6 py-3 ml-4"
+        />
+      </div>
+    </div>
+  );
+};
diff --git a/playground/src/components/expert_evaluation/expert_view/exercise_detail_popup.tsx b/playground/src/components/expert_evaluation/expert_view/exercise_detail_popup.tsx
new file mode 100644
index 000000000..b182996e1
--- /dev/null
+++ b/playground/src/components/expert_evaluation/expert_view/exercise_detail_popup.tsx
@@ -0,0 +1,20 @@
+import React from 'react';
+import Popup from "@/components/expert_evaluation/expert_view/popup";
+import ExerciseDetail from "@/components/details/exercise_detail";
+import { Exercise } from "@/model/exercise";
+
+interface ExerciseDetailPopupProps {
+  isOpen: boolean;
+  onClose: () => void;
+  exercise: Exercise;
+}
+
+export default function ExerciseDetailPopup(exerciseDetailPopupProps: ExerciseDetailPopupProps) {
+  const { isOpen, onClose, exercise } = exerciseDetailPopupProps;
+
+  return (
+    <Popup isOpen={isOpen} onClose={onClose} title={`Exercise Details: ${exercise.title}`}>
+      <ExerciseDetail exercise={exercise} hideDisclosure={true} openedInitially={true} />
+    </Popup>
+  );
+};
diff --git a/playground/src/components/expert_evaluation/expert_view/exercise_screen.tsx b/playground/src/components/expert_evaluation/expert_view/exercise_screen.tsx
new file mode 100644
index 000000000..4b7e21d6d
--- /dev/null
+++ b/playground/src/components/expert_evaluation/expert_view/exercise_screen.tsx
@@ -0,0 +1,70 @@
+import React, { useState } from 'react';
+import ExerciseDetailPopup from "@/components/expert_evaluation/expert_view/exercise_detail_popup";
+import { Exercise } from "@/model/exercise";
+import { SecondaryButton } from "@/components/expert_evaluation/expert_evaluation_buttons";
+import background_image from "@/assets/evaluation_backgrounds/exercise.jpeg";
+
+interface ExerciseScreenProps {
+  onCloseExerciseDetail: () => void;
+  onOpenContinueLater: () => void;
+  exercise: Exercise;
+  currentExerciseIndex: number;
+  totalExercises: number;
+}
+
+export default function ExerciseScreen(exerciseScreenProps: ExerciseScreenProps) {
+  const {
+    onCloseExerciseDetail,
+    onOpenContinueLater,
+    exercise,
+    currentExerciseIndex,
+    totalExercises,
+  } = exerciseScreenProps;
+  const [isExerciseDetailOpen, setExerciseDetailOpen] = useState(false);
+
+  const closeExerciseDetail = () => {
+    setExerciseDetailOpen(false);
+    onCloseExerciseDetail();
+  }
+
+  return (
+    <div className="fixed inset-0 bg-black bg-opacity-75 flex items-center justify-center z-50"
+      style={{
+        backgroundImage: `url(${background_image.src})`,
+        backgroundSize: 'cover',
+        backgroundPosition: 'center',
+      }}
+    >
+      <div className="bg-white p-8 rounded-lg shadow-lg max-w-lg w-full text-center">
+        <h1 className="text-4xl font-bold mb-4">You have
+          evaluated {currentExerciseIndex}/{totalExercises} exercises!</h1>
+        <p className="text-lg mb-6">
+          Great job! Feel free to take a break and
+          continue later. Your progress has been saved.
+        </p>
+        <p className="text-lg mb-6">
+          When you are ready, continue with the next exercise: {exercise.title}.
+        </p>
+        <div className="flex justify-center mt-4">
+          <SecondaryButton
+            onClick={onOpenContinueLater}
+            text="😴 Continue Later"
+            className="px-6 py-3"
+          />
+
+          <SecondaryButton
+            onClick={() => setExerciseDetailOpen(true)}
+            text="📄 Exercise Details"
+            className="ml-4 px-6 py-3"
+          />
+        </div>
+      </div>
+      {/* ExerciseDetailPopup that shows up when isExerciseDetailOpen is true */}
+      <ExerciseDetailPopup
+        isOpen={isExerciseDetailOpen}
+        onClose={closeExerciseDetail}
+        exercise={exercise}
+      />
+    </div>
+  );
+};
diff --git a/playground/src/components/expert_evaluation/expert_view/likert_scale.tsx b/playground/src/components/expert_evaluation/expert_view/likert_scale.tsx
new file mode 100644
index 000000000..675fcee52
--- /dev/null
+++ b/playground/src/components/expert_evaluation/expert_view/likert_scale.tsx
@@ -0,0 +1,108 @@
+import React, { useEffect, useState } from 'react';
+import Popup from "@/components/expert_evaluation/expert_view/popup";
+import ReactMarkdown from "react-markdown";
+import rehypeRaw from "rehype-raw";
+import { InfoIconButton } from "@/components/expert_evaluation/expert_evaluation_buttons";
+
+interface SingleChoiceLikertScaleProps {
+    title: string;
+    summary: string;
+    description: string;
+    passedValue: number | null;
+    onLikertChange: (value: number) => void;
+    isHighlighted: boolean;
+}
+
+export default function SingleChoiceLikertScale(singleChoiceLikertScale: SingleChoiceLikertScaleProps) {
+    const {
+        title,
+        summary,
+        description,
+        passedValue,
+        onLikertChange,
+        isHighlighted,
+    } = singleChoiceLikertScale;
+    const [selectedValue, setSelectedValue] = useState<number | null>(null);
+    const [isPopupOpen, setIsPopupOpen] = useState(false);
+
+    const handleInfoClick = () => {
+        setIsPopupOpen(true);
+    };
+
+    useEffect(() => {
+        setSelectedValue(passedValue);
+    }, [passedValue]);
+
+    const handleChange = (value: number) => {
+        setSelectedValue(value);
+        onLikertChange(value);
+    };
+
+    const closePopup = () => {
+        setIsPopupOpen(false);
+    };
+
+    const borderColors = [
+        'border-gray-500',   // Not Applicable
+        'border-red-600',    // Strongly Disagree
+        'border-orange-500', // Disagree
+        'border-yellow-400', // Neutral
+        'border-green-400',  // Agree
+        'border-green-700',  // Strongly Agree
+    ];
+
+    const selectedBgColors = [
+        'bg-gray-200',
+        'bg-red-200',
+        'bg-orange-200',
+        'bg-yellow-200',
+        'bg-green-200',
+        'bg-green-300',
+    ];
+
+    const scaleLabels = [
+        'Not Ratable',
+        'Strongly Disagree',
+        'Disagree',
+        'Neutral',
+        'Agree',
+        'Strongly Agree',
+    ];
+
+    return (
+        <>
+            {/* Title and Info Section */}
+            <div className="flex items-center">
+                <h3 className="text-sm font-semibold mr-1">{title}</h3>
+                <InfoIconButton onClick={handleInfoClick} />
+            </div>
+            <Popup isOpen={isPopupOpen} onClose={closePopup} title="Information">
+                <ReactMarkdown rehypePlugins={[rehypeRaw]} className="prose prose-sm max-w-none">
+                    {description}
+                </ReactMarkdown>
+            </Popup>
+
+            {/* Summary */}
+            <p className="text-gray-700 text-xs mb-0.5">{summary}</p>
+
+            {/* Single Choice Likert Scale */}
+            <div className="flex justify-between w-full">
+                {scaleLabels.map((label, index) => (
+                    <button
+                        key={index}
+                        onClick={() => handleChange(index)}
+                        className={`flex-1 text-xs py-0.5 text-center transition-colors duration-200 ease-in-out
+                            ${selectedValue === index ? selectedBgColors[index] : isHighlighted ? 'bg-red-100' : 'bg-white'}
+                            ${selectedValue === index ? `${borderColors[index]} border-l border-t border-r` : 'border-gray-300 border-l border-t border-r'}
+                            border-b-4 ${borderColors[index]}
+                            ${index === 0 ? 'rounded-l-md' : ''} ${index === scaleLabels.length - 1 ? 'rounded-r-md' : ''}`}
+                    >
+                        <span className={`block font-normal ${selectedValue === index ? 'underline' : ''}`}>
+                            {label}
+                        </span>
+                    </button>
+                ))}
+            </div>
+        </>
+    );
+};
diff --git a/playground/src/components/expert_evaluation/expert_view/likert_scale_form.tsx b/playground/src/components/expert_evaluation/expert_view/likert_scale_form.tsx
new file mode 100644
index 000000000..1e33ab42e
--- /dev/null
+++ b/playground/src/components/expert_evaluation/expert_view/likert_scale_form.tsx
@@ -0,0 +1,88 @@
+import React from 'react';
+import SingleChoiceLikertScale from "@/components/expert_evaluation/expert_view/likert_scale";
+import TextSubmissionDetail from "@/components/details/submission_detail/text";
+import type { TextSubmission } from "@/model/submission";
+import { CategorizedFeedback } from "@/model/feedback";
+import { Exercise } from "@/model/exercise";
+import { Metric } from "@/model/metric";
+
+interface LikertScaleFormProps {
+    submission: TextSubmission;
+    exercise: Exercise;
+    feedback: CategorizedFeedback;
+    metrics: Metric[];
+    selectedValues: { // Selected values for each exercise, submission, and feedback type
+        [exerciseId: string]: {
+            [submissionId: string]: {
+                [feedbackType: string]: {
+                    [metricId: string]: number; // The Likert scale value for a metric
+                };
+            };
+        };
+    };
+    onLikertValueChange: (feedbackType: string, metricId: string, value: number) => void;
+    isMarkMissingValue: boolean
+}
+
+
+export default function LikertScaleForm(likertScaleFormProps: LikertScaleFormProps) {
+    const {
+        submission,
+        exercise,
+        feedback,
+        metrics,
+        selectedValues,
+        onLikertValueChange,
+        isMarkMissingValue,
+    } = likertScaleFormProps;
+
+    if (!exercise || !submission) {
+        return <div>Loading...</div>;
+    }
+
+    return (
+        <div className="overflow-x-scroll">
+            <div className="flex space-x-6">
+                {Object.entries(feedback).map(([feedbackType, feedbackList]) => (
+                    <div key={feedbackType} className="flex-1 min-w-[480px] flex flex-col">
+                        {/* Render TextSubmissionDetail */}
+                        <div className="flex-grow flex flex-col mb-4">
+                            <TextSubmissionDetail
+                                identifier={`id-${submission.id}-${feedbackType}`}
+                                key={submission.id}
+                                submission={submission}
+                                feedbacks={feedbackList}
+                                onFeedbacksChange={undefined}
+                                hideFeedbackDetails={true}
+                            />
+                        </div>
+
+                        {/* Render SingleChoiceLikertScale components */}
+                        <div className="flex flex-col mt-auto mb-4">
+                            {metrics.map((metric) => {
+                                const selectedValue =
+                                    selectedValues?.[exercise.id]?.[submission.id]?.[feedbackType]?.[metric.id] ?? null;
+                                const isHighlighted = isMarkMissingValue && (selectedValue === null);
+
+                                return (
+                                    <div key={`${feedbackType}-${metric.id}`} className="mb-2">
+                                        <SingleChoiceLikertScale
+                                            title={metric.title}
+                                            summary={metric.summary}
+                                            description={metric.description}
+                                            passedValue={selectedValue}
+                                            onLikertChange={(value: number) =>
+                                                onLikertValueChange(feedbackType, metric.id, value)
+                                            }
+                                            isHighlighted={isHighlighted}
+                                        />
+                                    </div>
+                                );
+                            })}
+                        </div>
+                    </div>
+                ))}
+            </div>
+        </div>
+    );
+};
diff --git a/playground/src/components/expert_evaluation/expert_view/popup.tsx b/playground/src/components/expert_evaluation/expert_view/popup.tsx
new file mode 100644
index 000000000..f41c23aab
--- /dev/null
+++ b/playground/src/components/expert_evaluation/expert_view/popup.tsx
@@ -0,0 +1,43 @@
+import React, { ReactNode } from 'react';
+
+interface PopupProps {
+    isOpen: boolean;
+    onClose: () => void;
+    title: string;
+    children: ReactNode;
+    disableCloseOnOutsideClick?: boolean;
+}
+
+export default function Popup(popupProps: PopupProps) {
+    const { isOpen, onClose, title, children, disableCloseOnOutsideClick } = popupProps;
+    if (!isOpen) return null;
+
+    return (
+        <div className="fixed inset-0 z-50 bg-black bg-opacity-50 flex items-center justify-center p-6"
+            onClick={() => {
+                if (!disableCloseOnOutsideClick) {
+                    onClose();
+                }
+            }}
+        >
+            <div
+                className="bg-white p-6 rounded-lg shadow-lg max-w-7xl max-h-full relative"
+                onClick={(e) => e.stopPropagation()}
+            >
+                <div className="flex justify-between items-center mb-4">
+                    <h1 className="text-xl font-semibold">{title}</h1>
+                    <button
+                        className="text-gray-500 hover:text-gray-700 focus:outline-none"
+                        onClick={onClose}
+                    >
+                        ╳
+                    </button>
+                </div>
+                {/* Scrollable content wrapper */}
+                <div className="overflow-y-auto max-h-[80vh]">
+                    {children}
+                </div>
+            </div>
+        </div>
+    );
+};
diff --git a/playground/src/components/expert_evaluation/expert_view/side_by_side_header.tsx b/playground/src/components/expert_evaluation/expert_view/side_by_side_header.tsx
new file mode 100644
index 000000000..689e3e599
--- /dev/null
+++ b/playground/src/components/expert_evaluation/expert_view/side_by_side_header.tsx
@@ -0,0 +1,107 @@
+import React, { useState } from 'react';
+import Popup from "@/components/expert_evaluation/expert_view/popup";
+import { Metric } from "@/model/metric";
+import rehypeRaw from "rehype-raw";
+import ReactMarkdown from "react-markdown";
+import ExerciseDetailPopup from "@/components/expert_evaluation/expert_view/exercise_detail_popup";
+import TutorialPopup from "@/components/expert_evaluation/expert_view/tutorial_popup";
+import { SecondaryButton, NextButton, PrimaryButton } from "@/components/expert_evaluation/expert_evaluation_buttons";
+
+type SideBySideHeaderProps = {
+    exercise: any;
+    globalSubmissionIndex: number;
+    totalSubmissions: number;
+    metrics: Metric[];
+    onNext: () => void;
+    onPrevious: () => void;
+    onContinueLater: () => void;
+}
+
+export default function SideBySideHeader(sideBySideHeaderProps: SideBySideHeaderProps) {
+    const {
+        exercise,
+        globalSubmissionIndex,
+        totalSubmissions,
+        metrics,
+        onNext,
+        onPrevious,
+        onContinueLater,
+    } = sideBySideHeaderProps;
+    const [isExerciseDetailOpen, setIsExerciseDetailOpen] = useState<boolean>(false);
+    const [isMetricDetailOpen, setIsMetricDetailOpen] = useState<boolean>(false);
+    const [isEvaluationTutorialOpen, setIsEvaluationTutorialOpen] = useState<boolean>(false);
+
+    const openExerciseDetail = () => setIsExerciseDetailOpen(true);
+    const closeExerciseDetail = () => setIsExerciseDetailOpen(false);
+    const openMetricDetail = () => setIsMetricDetailOpen(true);
+    const closeMetricDetail = () => setIsMetricDetailOpen(false);
+    const openEvaluationTutorial = () => setIsEvaluationTutorialOpen(true);
+    const closeEvaluationTutorial = () => setIsEvaluationTutorialOpen(false);
+
+    if (!exercise) {
+        return <div>Loading...</div>;
+    }
+
+    return (
+        <div className="mb-4 sticky top-0 z-10 bg-white"> {/* Sticky header */}
+            {/* Subtitle and Details Buttons Section */}
+            <div className="flex flex-col md:flex-row justify-between items-start md:items-end gap-4 mb-4">
+
+                {/* Align heading to the top */}
+                <div className="flex flex-col gap-2 w-full md:w-auto self-start">
+                    <h1 className="text-xl font-semibold text-gray-900">
+                        Evaluation: {exercise.title}
+                    </h1>
+
+                    {/* Details Buttons */}
+                    <div className="flex flex-col md:flex-row gap-2 w-full">
+                        <SecondaryButton text={'📄 Exercise Details'} onClick={openExerciseDetail} />
+                        <ExerciseDetailPopup
+                            exercise={exercise}
+                            isOpen={isExerciseDetailOpen}
+                            onClose={closeExerciseDetail} />
+
+                        <SecondaryButton text={'📊 Metric Details'} onClick={openMetricDetail} />
+                        <Popup isOpen={isMetricDetailOpen} onClose={closeMetricDetail} title="Metric Details">
+                            <div className="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-3 gap-4">
+                                {metrics.map((metric, index) => (
+                                    <div key={index} className="border border-gray-300 rounded-md p-4">
+                                        <h2 className="font-semibold mb-4">{metric.title}</h2>
+                                        <ReactMarkdown rehypePlugins={[rehypeRaw]} className="prose-sm">
+                                            {metric.description}
+                                        </ReactMarkdown>
+                                    </div>
+                                ))}
+                            </div>
+                        </Popup>
+
+                        <SecondaryButton text={'📚 Evaluation Tutorial'} onClick={openEvaluationTutorial} />
+                        <TutorialPopup isOpen={isEvaluationTutorialOpen} onClose={closeEvaluationTutorial} />
+                    </div>
+                </div>
+
+                {/* Align buttons to the end */}
+                <div className="flex flex-col items-end gap-2 mt-4 md:mt-0 w-full md:w-[250px] self-end">
+                    <SecondaryButton text={'😴 Continue Later'} onClick={onContinueLater} className={'w-full'} />
+
+                    {/* Wrapping buttons to match the width */}
+                    <div className="flex gap-2 w-full md:w-[250px]">
+                        <PrimaryButton text={'⬅️ Previous'} onClick={onPrevious} isDisabled={globalSubmissionIndex === 0} className={'w-full'} />
+                        <NextButton onClick={onNext} isFinish={globalSubmissionIndex === totalSubmissions - 1} />
+                    </div>
+                </div>
+            </div>
+
+            {/* Progress Bar */}
+            <div className="relative w-full bg-gray-300 h-2 rounded">
+                <div
+                    className="bg-blue-500 h-2 rounded"
+                    style={{ width: `${(globalSubmissionIndex + 1) / totalSubmissions * 100}%` }}
+                />
+            </div>
+            <span className="text-sm text-gray-700">
+                {globalSubmissionIndex + 1} / {totalSubmissions}
+            </span>
+        </div>
+    );
+}
diff --git a/playground/src/components/expert_evaluation/expert_view/tutorial_popup.tsx b/playground/src/components/expert_evaluation/expert_view/tutorial_popup.tsx
new file mode 100644
index 000000000..06fcba90f
--- /dev/null
+++ b/playground/src/components/expert_evaluation/expert_view/tutorial_popup.tsx
@@ -0,0 +1,138 @@
+import React, { useState } from 'react';
+import Popup from "@/components/expert_evaluation/expert_view/popup";
+import exerciseDetails from "@/assets/evaluation_tutorial/exercise_details.gif";
+import readSubmission from "@/assets/evaluation_tutorial/read_submission.gif";
+import evaluateMetrics from "@/assets/evaluation_tutorial/evaluate_metrics.gif";
+import metricsExplanation from "@/assets/evaluation_tutorial/metrics-explanation.gif";
+import viewNext from "@/assets/evaluation_tutorial/view-next.gif";
+import continueLater from "@/assets/evaluation_tutorial/continue_later.gif";
+import {
+    InfoIconButton,
+    NextButton,
+    PrimaryButton,
+    SecondaryButton
+} from "@/components/expert_evaluation/expert_evaluation_buttons";
+import { Exercise } from "@/model/exercise";
+import ExerciseDetail from "@/components/details/exercise_detail";
+
+const baseTutorialSteps = [
+    {
+        image: exerciseDetails.src,
+        description: (
+            <>
+                1. Read the
+                <SecondaryButton text={'📄 Exercise Details'} isInline={true} className="mx-1" />
+            </>
+        ),
+    },
+    {
+        image: readSubmission.src,
+        description: "2. Read the Submission and the corresponding feedback"
+    },
+    {
+        image: evaluateMetrics.src,
+        description: "3. Evaluate the feedback based on the metrics"
+    },
+    {
+        image: metricsExplanation.src,
+        description: (
+            <>
+                4. If unsure what a metric means, press the
+                <InfoIconButton className="mx-1" />
+                or look at the
+                <SecondaryButton text={'📊 Metric Details'} isInline={true} className="mx-1" />
+            </>
+        ),
+    },
+    {
+        image: viewNext.src,
+        description: (
+            <>
+                5. After evaluating all metrics for all feedbacks, click on the
+                <NextButton isInline={true} className="mx-1" /> button to view the next submission.
+            </>),
+    },
+    {
+        image: continueLater.src,
+        description: (
+            <>
+                6. When you are ready to take a break, click on the
+                <SecondaryButton text={'😴 Continue Later'} isInline={true} className="mx-1" />
+            </>
+        ),
+    },
+];
+
+interface TutorialPopupProps {
+    isOpen: boolean;
+    onClose: () => void;
+    disableCloseOnOutsideClick?: boolean;
+    exercise?: Exercise;
+}
+
+export default function TutorialPopup(tutorialPopupProps: TutorialPopupProps) {
+    const { isOpen, onClose, disableCloseOnOutsideClick, exercise } = tutorialPopupProps;
+    const [currentStep, setCurrentStep] = useState(0);
+
+    // If the tutorial was opened in welcome window, add a last step involving the first exercise
+    const tutorialSteps = exercise
+        ? [
+            ...baseTutorialSteps,
+            {
+                image: "",
+                description: (
+                    <>
+                        <div className="text-left">
+                            Now you are ready to start the evaluation! Read the description of the first exercise
+
+                            <ExerciseDetail exercise={exercise} hideDisclosure={true} openedInitially={true} />
+                        </div>
+                    </>),
+            },
+        ]
+        : baseTutorialSteps;
+
+    const handleNext = () => {
+        if (currentStep < tutorialSteps.length - 1) {
+            setCurrentStep(currentStep + 1);
+        }
+    };
+
+    const handlePrevious = () => {
+        if (currentStep > 0) {
+            setCurrentStep(currentStep - 1);
+        }
+    };
+
+    const { image, description } = tutorialSteps[currentStep];
+
+    const isLastStep = currentStep === tutorialSteps.length - 1;
+    return (
+        <Popup isOpen={isOpen} onClose={onClose} title="Evaluation Tutorial"
+            disableCloseOnOutsideClick={disableCloseOnOutsideClick}>
+            <div className="text-center">
+                {/* Display the current GIF */}
+                {image && <img src={image} alt={`Tutorial Step ${currentStep + 1}`} className="w-full h-auto mb-4" />}
+
+                {/* Render the description directly, which may include text and button */}
+                <div className={"text-lg mb-4"}>
+                    {description}
+                </div>
+
+                {/* Navigation buttons */}
+                <div className="flex justify-between mt-4">
+                    <SecondaryButton
+                        text="Previous"
+                        onClick={handlePrevious}
+                        isDisabled={currentStep === 0}
+                    />
+                    <span className="text-lg">{`${currentStep + 1} / ${tutorialSteps.length}`}</span>
+                    <PrimaryButton
+                        onClick={isLastStep ? onClose : handleNext}
+                        text={isLastStep ? 'Start Evaluation' : 'Next ➡️'}
+                    />
+                </div>
+            </div>
+        </Popup>
+    );
+};
diff --git a/playground/src/components/expert_evaluation/expert_view/welcome_screen.tsx b/playground/src/components/expert_evaluation/expert_view/welcome_screen.tsx
new file mode 100644
index 000000000..dda857b74
--- /dev/null
+++ b/playground/src/components/expert_evaluation/expert_view/welcome_screen.tsx
@@ -0,0 +1,50 @@
+import React, { useState } from 'react';
+import TutorialPopup from "@/components/expert_evaluation/expert_view/tutorial_popup";
+import background_image from "@/assets/evaluation_backgrounds/welcome-screen.jpeg";
+import { PrimaryButton } from "@/components/expert_evaluation/expert_evaluation_buttons";
+import { Exercise } from "@/model/exercise";
+
+interface WelcomeScreenProps {
+  exercise: Exercise;
+  onClose: () => void;
+}
+
+export default function WelcomeScreen(welcomeScreenProps: WelcomeScreenProps) {
+  const { exercise, onClose } = welcomeScreenProps;
+  const [isTutorialOpen, setTutorialOpen] = useState(false);
+
+  const closeTutorial = () => {
+    setTutorialOpen(false);
+    onClose();
+  }
+
+  const startTutorial = () => {
+    setTutorialOpen(true);
+  }
+
+  return (
+    <div className="fixed inset-0 bg-black bg-opacity-75 flex items-center justify-center z-50"
+      style={{
+        backgroundImage: `url(${background_image.src})`,
+        backgroundSize: 'cover',
+        backgroundPosition: 'center',
+      }}>
+      <div className="bg-white p-8 rounded-lg shadow-lg max-w-lg w-full text-center">
+        <h1 className="text-4xl font-bold mb-4">Welcome to the Expert Evaluation!</h1>
+        <p className="text-lg mb-6">
+          Thank you for taking the time to participate. Your input is valuable to us, and we appreciate your
+          effort.
+        </p>
+        <PrimaryButton
+          onClick={startTutorial}
+          text="📚 Start Tutorial"
+          className="px-6 py-3"
+        />
+      </div>
+      <TutorialPopup isOpen={isTutorialOpen}
+        onClose={closeTutorial}
+        disableCloseOnOutsideClick={true}
+        exercise={exercise} />
+    </div>
+  );
+};
diff --git a/playground/src/components/selectors/evaluation_config_selector.tsx b/playground/src/components/selectors/evaluation_config_selector.tsx
new file mode 100644
index 000000000..5f2e6df99
--- /dev/null
+++ b/playground/src/components/selectors/evaluation_config_selector.tsx
@@ -0,0 +1,29 @@
+import React from "react";
+import { ExpertEvaluationConfig } from "@/model/expert_evaluation_config";
+
+type EvaluationConfigSelectorProps = {
+  selectedConfigId: string;
+  setSelectedConfigId: (id: string) => void;
+  expertEvaluationConfigs: ExpertEvaluationConfig[];
+};
+
+export default function EvaluationConfigSelector(evaluationConfigSelectorProps: EvaluationConfigSelectorProps) {
+  const { selectedConfigId, setSelectedConfigId, expertEvaluationConfigs } = evaluationConfigSelectorProps;
+  return (
+    <section className="flex flex-col">
+      <span className="text-lg font-bold mb-2">Evaluation</span>
+      <select
+        className="border border-gray-300 rounded-md p-2"
+        value={selectedConfigId}
+        onChange={(e) => setSelectedConfigId(e.target.value)}
+      >
+        <option value="new">New Evaluation</option>
+        {expertEvaluationConfigs.map((config) => (
+          <option key={config.id} value={config.id}>
+            {config.name}: {config.creationDate?.toString() ?? ""}
+          </option>
+        ))}
+      </select>
+    </section>
+  );
+};
diff --git a/playground/src/components/view_mode/evaluation_mode/expert_evaluation/evaluation_management.tsx b/playground/src/components/view_mode/evaluation_mode/expert_evaluation/evaluation_management.tsx
new file mode 100644
index 000000000..fc9c57527
--- /dev/null
+++ b/playground/src/components/view_mode/evaluation_mode/expert_evaluation/evaluation_management.tsx
@@ -0,0 +1,244 @@
+import { useEffect, useState } from "react";
+import { v4 as uuidv4 } from "uuid";
+import { downloadJSONFile } from "@/helpers/download";
+import { twMerge } from "tailwind-merge";
+import MetricsForm from "@/components/view_mode/evaluation_mode/expert_evaluation/metrics_form";
+import { ExpertEvaluationConfig } from "@/model/expert_evaluation_config";
+import EvaluationConfigSelector from "@/components/selectors/evaluation_config_selector";
+import {
+  EvaluationManagementExportImport
+} from "@/components/view_mode/evaluation_mode/expert_evaluation/evaluation_management_export_import";
+import {
+  fetchAllExpertEvaluationConfigs,
+  saveExpertEvaluationConfig as externalSaveExpertEvaluationConfig
+} from "@/hooks/playground/expert_evaluation_config";
+import ExpertLinks from "@/components/view_mode/evaluation_mode/expert_evaluation/expert_links";
+import ExerciseImport from "@/components/view_mode/evaluation_mode/expert_evaluation/exercise_import";
+import useDownloadExpertEvaluationData from "@/hooks/playground/expert_evaluation";
+
+const createNewEvaluationConfig = (name = ""): ExpertEvaluationConfig => ({
+  type: "evaluation_config",
+  id: "new",
+  name,
+  started: false,
+  creationDate: new Date(),
+  metrics: [],
+  exercises: [],
+  expertIds: [],
+});
+
+export default function EvaluationManagement() {
+  const [expertEvaluationConfigs, setExpertEvaluationConfigs] = useState<ExpertEvaluationConfig[]>([]);
+  const [selectedConfig, setSelectedConfig] = useState<ExpertEvaluationConfig>(createNewEvaluationConfig());
+  const [hasUnsavedChanges, setHasUnsavedChanges] = useState(false);
+  const dataMode = "expert_evaluation";
+
+  useEffect(() => {
+    const fetchData = async () => {
+      const savedConfigs = await fetchAllExpertEvaluationConfigs(dataMode);
+      setExpertEvaluationConfigs(savedConfigs);
+    };
+    fetchData();
+  }, []);
+
+  const handleSelectConfig = (id: string) => {
+    if (id === "new") {
+      setSelectedConfig(createNewEvaluationConfig());
+    } else {
+      const existingConfig = expertEvaluationConfigs.find((config) => config.id === id);
+      if (existingConfig) {
+        setSelectedConfig(existingConfig);
+      }
+    }
+    setHasUnsavedChanges(false);
+  };
+
+  const updateSelectedConfig = (updatedFields: Partial<ExpertEvaluationConfig>): ExpertEvaluationConfig => {
+    const isUpdatingOnlyExpertIds =
+      Object.keys(updatedFields).length === 1 && updatedFields.hasOwnProperty('expertIds');
+    const newConfig = { ...selectedConfig, ...updatedFields };
+
+    if (!selectedConfig.started || isUpdatingOnlyExpertIds) {
+      setSelectedConfig(newConfig);
+      setHasUnsavedChanges(true);
+    }
+
+    return newConfig;
+  };
+
+  const saveExpertEvaluationConfig = (configToSave = selectedConfig) => {
+    const isNewConfig = configToSave.id === "new";
+    const newConfig = isNewConfig ? { ...configToSave, id: uuidv4() } : configToSave;
+    setExpertEvaluationConfigs((prevConfigs) => {
+      const existingIndex = prevConfigs.findIndex((config) => config.id === newConfig.id);
+      if (existingIndex !== -1) {
+        const updatedConfigs = [...prevConfigs];
+        updatedConfigs[existingIndex] = newConfig;
+        return updatedConfigs;
+      } else {
+        return [...prevConfigs, newConfig];
+      }
+    });
+
+    setSelectedConfig(newConfig);
+    externalSaveExpertEvaluationConfig(dataMode, newConfig, isNewConfig);
+    setHasUnsavedChanges(false);
+  };
+
+  const handleExport = () => {
+    downloadJSONFile(`evaluation_config_${selectedConfig.name}_${selectedConfig.id}`, selectedConfig);
+  };
+
+  const handleImport = async (fileContent: string) => {
+    const importedConfig = JSON.parse(fileContent) as ExpertEvaluationConfig;
+    if (importedConfig.type !== "evaluation_config") {
+      alert("Invalid config type");
+      return;
+    }
+    importedConfig.id = "new";
+    importedConfig.creationDate = new Date();
+    importedConfig.started = false;
+    importedConfig.expertIds = [];
+    setSelectedConfig(importedConfig);
+  };
+
+  const { mutate: downloadEvaluationData, isLoading: isExporting } = useDownloadExpertEvaluationData({
+    onSuccess: (blob: Blob) => {
+      const url = window.URL.createObjectURL(blob);
+      const a = document.createElement("a");
+      a.style.display = "none";
+      a.href = url;
+      a.download = `evaluation_${selectedConfig.id}.zip`;
+      document.body.appendChild(a);
+      a.click();
+      window.URL.revokeObjectURL(url);
+    },
+    onError: (error) => {
+      console.error("Download failed:", error.message);
+      alert("An error occurred during download. Please try again later.");
+    },
+  });
+
+  const startEvaluation = () => {
+    if (confirm("Are you sure you want to start the evaluation? Once started, you can add new expert links but no other changes can be made to the configuration!")) {
+      const updatedConfig = updateSelectedConfig({ started: true });
+      saveExpertEvaluationConfig(updatedConfig);
+    }
+  };
+
+  const resetChanges = () => {
+    if (selectedConfig.id === "new") {
+      setSelectedConfig(createNewEvaluationConfig());
+    } else {
+      const existingConfig = expertEvaluationConfigs.find((config) => config.id === selectedConfig.id);
+      if (existingConfig) {
+        setSelectedConfig(existingConfig);
+      }
+    }
+    setHasUnsavedChanges(false);
+  };
+
+  const inputDisabledStyle = selectedConfig.started
+    ? "bg-gray-100 text-gray-500 cursor-not-allowed"
+    : "";
+
+  return (
+    <div className="bg-white rounded-md p-4 mb-8 space-y-4">
+      <div className="flex flex-row justify-between items-center">
+        <h3 className="text-2xl font-bold">Manage Evaluations</h3>
+        <EvaluationManagementExportImport
+          definedExpertEvaluationConfig={selectedConfig}
+          handleExport={handleExport}
+          handleImport={handleImport}
+        />
+      </div>
+
+      <EvaluationConfigSelector
+        selectedConfigId={selectedConfig.id}
+        setSelectedConfigId={handleSelectConfig}
+        expertEvaluationConfigs={expertEvaluationConfigs}
+      />
+
+      <label className="flex flex-col">
+        <span className="text-lg font-bold mb-2">Evaluation Name</span>
+        <input
+          type="text"
+          placeholder="Enter a name for the evaluation."
+          className={`border border-gray-300 rounded-md p-2 ${inputDisabledStyle}`}
+          value={selectedConfig.name}
+          onChange={(e) => updateSelectedConfig({ name: e.target.value })}
+          disabled={selectedConfig.started}
+        />
+      </label>
+
+      <ExerciseImport
+        exercises={selectedConfig.exercises}
+        setExercises={(newExercises) => updateSelectedConfig({ exercises: newExercises })}
+        disabled={selectedConfig.started}
+      />
+
+      <MetricsForm
+        metrics={selectedConfig.metrics}
+        setMetrics={(newMetrics) => updateSelectedConfig({ metrics: newMetrics })}
+        disabled={selectedConfig.started}
+      />
+
+      <ExpertLinks
+        expertIds={selectedConfig.expertIds!}
+        setExpertIds={(newExpertIds) => updateSelectedConfig({ expertIds: newExpertIds })}
+        configId={selectedConfig.id}
+        started={selectedConfig.started}
+      />
+
+      <div className="flex flex-row gap-2 mt-4">
+        <button
+          className={twMerge(
+            selectedConfig.id === "new" ? "bg-blue-500 hover:bg-blue-600" : "bg-green-500 hover:bg-green-600",
+            "text-white rounded-md p-2",
+            !hasUnsavedChanges ? "opacity-60 cursor-not-allowed" : ""
+          )}
+          onClick={() => saveExpertEvaluationConfig(selectedConfig)}
+          disabled={!hasUnsavedChanges}
+        >
+          {selectedConfig.id === "new" ? "Define Experiment" : "Save Changes"}
+        </button>
+
+        <button
+          className={twMerge(
+            selectedConfig.id === "new"
+              ? "bg-red-500 hover:bg-red-600"
+              : "bg-gray-500 hover:bg-gray-600",
+            "text-white rounded-md p-2",
+            !hasUnsavedChanges ? "opacity-60 cursor-not-allowed" : ""
+          )}
+          onClick={resetChanges}
+          disabled={!hasUnsavedChanges}
+        >
+          {selectedConfig.id === "new" ? "Cancel" : "Reset Changes"}
+        </button>
+
+        {selectedConfig.started && (
+          <button
+            className={twMerge(
+              "bg-blue-500 text-white rounded-md p-2 hover:bg-blue-600",
+              isExporting ? "opacity-75 cursor-not-allowed" : ""
+            )}
+            onClick={() => downloadEvaluationData({ configId: selectedConfig.id })}
+            disabled={isExporting}
+          >
+            {isExporting ? "Downloading..." : "Download Results"}
+          </button>
+        )}
+
+        {selectedConfig.id !== "new" && !selectedConfig.started && (
+          <button
+            className="bg-green-500 text-white rounded-md p-2 hover:bg-green-600"
+            onClick={startEvaluation}
+          >
+            Start Evaluation
+          </button>
+        )}
+      </div>
+    </div>
+  );
+}
diff --git a/playground/src/components/view_mode/evaluation_mode/expert_evaluation/evaluation_management_export_import.tsx b/playground/src/components/view_mode/evaluation_mode/expert_evaluation/evaluation_management_export_import.tsx
new file mode 100644
index 000000000..f8ae50628
--- /dev/null
+++ b/playground/src/components/view_mode/evaluation_mode/expert_evaluation/evaluation_management_export_import.tsx
@@ -0,0 +1,42 @@
+import React from "react";
+
+type EvaluationManagementExportImportProps = {
+  definedExpertEvaluationConfig: any;
+  handleExport: () => void;
+  handleImport: (fileContent: string) => void;
+};
+
+export function EvaluationManagementExportImport(evaluationManagementExportImportProps: EvaluationManagementExportImportProps) {
+  const { definedExpertEvaluationConfig, handleExport, handleImport } = evaluationManagementExportImportProps;
+
+  const onFileChange = (e: React.ChangeEvent<HTMLInputElement>) => {
+    if (e.target.files && e.target.files.length > 0) {
+      const file = e.target.files[0];
+      const reader = new FileReader();
+      reader.onload = (e) => {
+        if (e.target && typeof e.target.result === "string") {
+          handleImport(e.target.result);
+        }
+      };
+      reader.readAsText(file);
+    }
+    e.target.value = ""; // Reset file input
+  };
+
+  return (
+    <div className="flex flex-row">
+      <button
+        disabled={!definedExpertEvaluationConfig}
+        className="rounded-md p-2 text-primary-500 hover:text-primary-600 hover:bg-gray-100 disabled:text-gray-500 disabled:cursor-not-allowed"
+        onClick={handleExport}
+      >
+        Export
+      </button>
+      <label
+        className="rounded-md p-2 cursor-pointer text-primary-500 hover:text-primary-600 hover:bg-gray-100">
+        Import
+        <input className="hidden" type="file" accept=".json" onChange={onFileChange} />
+      </label>
+    </div>
+  );
+}
diff --git a/playground/src/components/view_mode/evaluation_mode/expert_evaluation/exercise_import.tsx b/playground/src/components/view_mode/evaluation_mode/expert_evaluation/exercise_import.tsx
new file mode 100644
index 000000000..b47d58ddb
--- /dev/null
+++ b/playground/src/components/view_mode/evaluation_mode/expert_evaluation/exercise_import.tsx
@@ -0,0 +1,102 @@
+import React from "react";
+import { Exercise } from "@/model/exercise";
+import { FontAwesomeIcon } from "@fortawesome/react-fontawesome";
+import { faTrash, faPlus } from "@fortawesome/free-solid-svg-icons";
+
+type ExerciseImportProps = {
+  exercises: Exercise[];
+  setExercises: (exercises: Exercise[]) => void;
+  disabled: boolean;
+};
+
+export default function ExerciseImport(exerciseImportProps: ExerciseImportProps) {
+  const { exercises, setExercises, disabled } = exerciseImportProps;
+
+  const handleExerciseImport = async (fileContents: string[]) => {
+    const importedExercises = fileContents.map((fileContent) => JSON.parse(fileContent) as Exercise);
+    setExercises([...exercises, ...importedExercises]);
+  };
+
+  const onFileChange = (e: React.ChangeEvent<HTMLInputElement>) => {
+    if (e.target.files && e.target.files.length > 0) {
+      const files = Array.from(e.target.files);
+      const fileReaders = files.map(file => {
+        return new Promise<string>((resolve, reject) => {
+          const reader = new FileReader();
+          reader.onload = (event) => {
+            if (event.target && typeof event.target.result === "string") {
+              resolve(event.target.result);
+            } else {
+              reject(new Error("File reading failed"));
+            }
+          };
+          reader.readAsText(file);
+        });
+      });
+
+      Promise.all(fileReaders)
+        .then((fileContents) => {
+          handleExerciseImport(fileContents);
+        })
+        .catch((error) => {
+          console.error("Error importing exercises:", error);
+        });
+    }
+    e.target.value = ""; // Reset file input
+  };
+
+  const removeExercise = (exerciseId: number) => {
+    setExercises(exercises.filter((exercise) => exercise.id !== exerciseId));
+  };
+
+  return (
+    <section className="flex flex-col">
+      <div className="flex justify-between items-center mb-2">
+        {/* Heading */}
+        <span className="text-lg font-bold">Exercises</span>
+
+        {/* Import New Exercises Button */}
+        {!disabled && (
+          <label className="bg-green-500 text-white rounded-md p-2 hover:bg-green-600 flex items-center gap-2 cursor-pointer">
+            <FontAwesomeIcon icon={faPlus} />
+            Import Exercises
+            <input
+              type="file"
+              accept=".json"
+              className="hidden"
+              multiple
+              onChange={onFileChange}
+            />
+          </label>
+        )}
+      </div>
+
+      {/* List of Imported Exercises */}
+      <ul className="space-y-2">
+        {exercises.length === 0 ? (
+          <li className="border p-2 rounded-md shadow-sm bg-gray-50 text-center">
+            No exercises added! Please add exercises with submissions and categorized feedback.
+          </li>
+        ) : (
+          exercises.map((exercise) => (
+            <li key={exercise.id} className="flex justify-between items-center border p-2 rounded-md shadow-sm">
+              <span>{exercise.title}</span>
+
+              <div className="flex space-x-2">
+                {!disabled && (
+                  <button
+                    className="bg-red-500 text-white rounded-md p-2 hover:bg-red-600"
+                    onClick={() => removeExercise(exercise.id)}
+                    title="Delete Exercise"
+                  >
+                    <FontAwesomeIcon icon={faTrash} />
+                  </button>
+                )}
+              </div>
+            </li>
+          ))
+        )}
+      </ul>
+    </section>
+  );
+};
diff --git a/playground/src/components/view_mode/evaluation_mode/expert_evaluation/expert_links.tsx b/playground/src/components/view_mode/evaluation_mode/expert_evaluation/expert_links.tsx
new file mode 100644
index 000000000..5f3f6ed7b
--- /dev/null
+++ b/playground/src/components/view_mode/evaluation_mode/expert_evaluation/expert_links.tsx
@@ -0,0 +1,134 @@
+import React, { useEffect, useState } from 'react';
+import { v4 as uuidv4 } from 'uuid';
+import { FontAwesomeIcon } from '@fortawesome/react-fontawesome';
+import { faCheck, faCopy, faPlus, faSyncAlt, faTrash } from '@fortawesome/free-solid-svg-icons';
+import baseUrl from '@/helpers/base_url';
+import { fetchExpertEvaluationProgressStats } from '@/hooks/playground/expert_evaluation_progress_stats';
+import { ExpertEvaluationProgressStats } from "@/model/expert_evaluation_progress_stats";
+
+type ExpertLinksProps = {
+  expertIds: string[];
+  setExpertIds: (newExpertIds: string[]) => void;
+  started: boolean;
+  configId: string;
+};
+
+export default function ExpertLinks(props: ExpertLinksProps) {
+  const { expertIds, setExpertIds, started, configId } = props;
+
+  const [copiedLink, setCopiedLink] = useState<string | null>(null);
+  const [progressStats, setProgressStats] = useState<ExpertEvaluationProgressStats>();
+  const [loading, setLoading] = useState(false);
+
+  const updateProgressStats = async () => {
+    setLoading(true);
+    const minimumDelay = new Promise((resolve) => setTimeout(resolve, 1000));
+    try {
+      const statsPromise = fetchExpertEvaluationProgressStats(configId);
+      const [stats] = await Promise.all([statsPromise, minimumDelay]);
+      setProgressStats(stats);
+    } catch (error) {
+      console.error('Failed to fetch progress stats:', error);
+    } finally {
+      setLoading(false);
+    }
+  };
+
+  useEffect(() => {
+    if (started) updateProgressStats();
+  }, [configId, started]);
+
+  const addExpertId = () => setExpertIds([...expertIds, uuidv4()]);
+
+  const copyLink = (link: string) => {
+    navigator.clipboard.writeText(link);
+    setCopiedLink(link);
+    setTimeout(() => setCopiedLink(null), 2000);
+  };
+
+  const deleteExpertId = (id: string) => setExpertIds(expertIds.filter((expertId) => expertId !== id));
+
+  return (
+    <section className="flex flex-col">
+      <div className="flex justify-between items-center mb-2">
+        <span className="text-lg font-bold">Expert Links</span>
+        {/* Add New Expert and Conditional Update Stats Button */}
+        <div className="flex gap-2">
+          <button
+            className="bg-green-500 text-white rounded-md p-2 hover:bg-green-600 flex items-center gap-2"
+            onClick={addExpertId}
+          >
+            <FontAwesomeIcon icon={faPlus} />
+            Add New Expert
+          </button>
+          {started && (
+            <button
+              className="bg-blue-500 text-white rounded-md p-2 hover:bg-blue-600 flex items-center gap-2"
+              onClick={updateProgressStats}
+              disabled={loading}
+            >
+              <FontAwesomeIcon icon={faSyncAlt} spin={loading} />
+              Update Progress
+            </button>
+          )}
+        </div>
+      </div>
+
+      {/* List of Expert Links */}
+      <ul className="space-y-2">
+        {expertIds.length ? (
+          expertIds.map((expertId) => {
+            const expertLink = `${window.location.origin}${baseUrl}/${configId}/${expertId}/expert_view`;
+            const completed = progressStats?.[expertId] ?? 0;
+            const total = progressStats?.totalSubmissions ?? 0;
+            const progressPercentage = total ? (completed / total) * 100 : 0;
+
+            return (
+              <li key={expertId} className="flex flex-col border p-2 rounded-md shadow-sm space-y-1">
+                <div className="flex justify-between items-center">
+                  <a href={expertLink} target="_blank" rel="noopener noreferrer" className="text-blue-500 underline">
+                    {expertLink}
+                  </a>
+                  <div className="flex space-x-2">
+                    {/* Copy Link Button */}
+                    <button
+                      className="bg-blue-500 text-white rounded-md p-2 hover:bg-blue-600"
+                      onClick={() => copyLink(expertLink)}
+                      title="Copy Link"
+                    >
+                      <FontAwesomeIcon icon={copiedLink === expertLink ? faCheck : faCopy} />
+                    </button>
+                    {/* Delete Button */}
+                    {!started && (
+                      <button
+                        className="bg-red-500 text-white rounded-md p-2 hover:bg-red-600"
+                        onClick={() => deleteExpertId(expertId)}
+                        title="Delete Link"
+                      >
+                        <FontAwesomeIcon icon={faTrash} />
+                      </button>
+                    )}
+                  </div>
+                </div>
+
+                {/* Progress Bar */}
+                {started && (
+                  <>
+                    <div className="relative w-full bg-gray-300 h-2 rounded mt-1">
+                      <div className="bg-blue-500 h-2 rounded" style={{ width: `${progressPercentage}%` }} />
+                    </div>
+                    <span className="text-sm text-gray-700">
+                      {completed === 0 ? 'Not started' : completed === total ? 'Finished 🏁' : `${completed} / ${total} completed`}
+                    </span>
+                  </>
+                )}
+              </li>
+            );
+          })
+        ) : (
+          <li className="border p-2 rounded-md shadow-sm bg-gray-50 text-center">No expert links added</li>
+        )}
+      </ul>
+    </section>
+  );
+}
diff --git a/playground/src/components/view_mode/evaluation_mode/expert_evaluation/metrics_form.tsx b/playground/src/components/view_mode/evaluation_mode/expert_evaluation/metrics_form.tsx
new file mode 100644
index 000000000..b82c2ddbe
--- /dev/null
+++ b/playground/src/components/view_mode/evaluation_mode/expert_evaluation/metrics_form.tsx
@@ -0,0 +1,240 @@
+import { useState } from "react";
+import { v4 as uuidv4 } from 'uuid';
+import { FontAwesomeIcon } from "@fortawesome/react-fontawesome";
+import { faEdit, faPlus, faSave, faTrash } from "@fortawesome/free-solid-svg-icons";
+import ReactMarkdown from 'react-markdown';
+import rehypeRaw from "rehype-raw";
+import { Metric } from "@/model/metric";
+
+type MetricsFormProps = {
+  metrics: Metric[];
+  setMetrics: (metrics: Metric[]) => void;
+  disabled: boolean;
+};
+
+export default function MetricsForm(metricsFormProps: MetricsFormProps) {
+  const { metrics, setMetrics, disabled } = metricsFormProps;
+
+  const [editIndex, setEditIndex] = useState<number | null>(null);
+  const [editingMetric, setEditingMetric] = useState<Metric>({
+    id: "",
+    title: "",
+    summary: "",
+    description: "",
+  });
+  const [newMetric, setNewMetric] = useState<Metric>({
+    id: "",
+    title: "",
+    summary: "",
+    description: "",
+  });
+
+  const handleChange = (
+    e: React.ChangeEvent<HTMLInputElement | HTMLTextAreaElement>,
+    isEditing: boolean = false
+  ) => {
+    const { name, value } = e.target;
+    if (isEditing) {
+      setEditingMetric((prevMetric) => ({
+        ...prevMetric,
+        [name]: value,
+      }));
+    } else {
+      setNewMetric((prevMetric) => ({
+        ...prevMetric,
+        [name]: value,
+      }));
+    }
+  };
+
+  const addMetric = () => {
+    if (!newMetric.title.trim() || !newMetric.summary.trim() || !newMetric.description.trim()) {
+      return;
+    }
+
+    const metricWithId = { ...newMetric, id: uuidv4() };
+    setMetrics([...metrics, metricWithId]);
+    setNewMetric({ id: "", title: "", summary: "", description: "" }); // Reset form
+  };
+
+  const startEditMetric = (index: number) => {
+    setEditIndex(index);
+    setEditingMetric(metrics[index]);
+  };
+
+  const saveMetric = () => {
+    if (editIndex !== null) {
+      const updatedMetrics = metrics.map((metric, index) =>
+        index === editIndex ? editingMetric : metric
+      );
+      setMetrics(updatedMetrics);
+      setEditIndex(null); // Exit editing mode
+    }
+  };
+
+  const removeMetric = (index: number) => {
+    setMetrics(metrics.filter((_, i) => i !== index));
+  };
+
+  const inputDisabledStyle = disabled
+    ? "bg-gray-100 text-gray-500 cursor-not-allowed"
+    : "";
+
+  const buttonDisabledStyle = disabled ? "hidden" : "";
+
+  return (
+    <section className="flex flex-col">
+      <span className="text-lg font-bold mb-2">Metrics</span>
+      <div className="flex flex-col gap-4">
+
+        {/* List of Metrics */}
+        {metrics.map((metric, index) => (
+          <div
+            key={metric.id}
+            className="flex justify-between items-start border p-4 rounded-md shadow-sm"
+          >
+            {editIndex === index ? (
+              <div className="space-y-2 flex-1">
+                <input
+                  type="text"
+                  name="title"
+                  value={editingMetric.title}
+                  onChange={(e) => handleChange(e, true)}
+                  className={`border border-gray-300 rounded-md p-2 w-full ${inputDisabledStyle}`}
+                  placeholder="Metric Title"
+                  disabled={disabled}
+                />
+                <input
+                  type="text"
+                  name="summary"
+                  value={editingMetric.summary}
+                  onChange={(e) => handleChange(e, true)}
+                  className={`border border-gray-300 rounded-md p-2 w-full ${inputDisabledStyle}`}
+                  placeholder="Metric Summary"
+                  disabled={disabled}
+                />
+                <textarea
+                  name="description"
+                  value={editingMetric.description}
+                  onChange={(e) => handleChange(e, true)}
+                  className={`border border-gray-300 rounded-md p-2 w-full ${inputDisabledStyle}`}
+                  rows={2}
+                  placeholder="Metric Description"
+                  disabled={disabled}
+                />
+                <button
+                  onClick={saveMetric}
+                  className={`bg-green-500 text-white rounded-md p-2 hover:bg-green-600 flex items-center gap-2 ${buttonDisabledStyle}`}
+                  disabled={disabled}
+                >
+                  <FontAwesomeIcon icon={faSave} />
+                  Save
+                </button>
+              </div>
+            ) : (
+              <div className="space-y-2 flex-1">
+                <input
+                  type="text"
+                  value={metric.title}
+                  readOnly
+                  className={`border border-gray-300 rounded-md p-2 w-full ${inputDisabledStyle}`}
+                  placeholder="Metric Title"
+                />
+                <input
+                  type="text"
+                  value={metric.summary}
+                  readOnly
+                  className={`border border-gray-300 rounded-md p-2 w-full ${inputDisabledStyle}`}
+                  placeholder="Metric Summary"
+                />
+                <div className="border border-gray-300 rounded-md p-2 w-full">
+                  <ReactMarkdown rehypePlugins={[rehypeRaw]} className="prose-sm">
+                    {metric.description}
+                  </ReactMarkdown>
+                </div>
+              </div>
+            )}
+
+            {/* Buttons for Edit and Remove */}
+            <div className="flex flex-col gap-2 items-center ml-4">
+              <button
+                onClick={() => startEditMetric(index)}
+                className={`bg-gray-500 text-white rounded-md p-2 hover:bg-gray-600 flex items-center gap-2 ${buttonDisabledStyle}`}
+                disabled={disabled}
+              >
+                <FontAwesomeIcon icon={faEdit} />
+              </button>
+              <button
+                onClick={() => removeMetric(index)}
+                className={`bg-red-500 text-white rounded-md p-2 hover:bg-red-600 flex items-center gap-2 ${buttonDisabledStyle}`}
+                disabled={disabled}
+              >
+                <FontAwesomeIcon icon={faTrash} />
+              </button>
+            </div>
+          </div>
+        ))}
+
+        {/* New Metric Form */}
+        {!disabled && (
+          <div className="flex flex-col gap-2 border p-4 rounded-md shadow-sm">
+            <div>
+              <label className="block text-sm">
+                <span className="text-gray-700">Title</span>
+                <input
+                  type="text"
+                  name="title"
+                  value={newMetric.title}
+                  onChange={(e) => handleChange(e, false)}
+                  className={`mt-1 block w-full border border-gray-300 rounded-md p-2 ${inputDisabledStyle}`}
+                  placeholder="Enter a title for the new metric."
+                  disabled={disabled}
+                />
+              </label>
+            </div>
+
+            <div>
+              <label className="block text-sm">
+                <span className="text-gray-700">Summary</span>
+                <input
+                  type="text"
+                  name="summary"
+                  value={newMetric.summary}
+                  onChange={(e) => handleChange(e, false)}
+                  className={`mt-1 block w-full border border-gray-300 rounded-md p-2 ${inputDisabledStyle}`}
+                  placeholder="Enter a short statement that the expert can agree or disagree with."
+                  disabled={disabled}
+                />
+              </label>
+            </div>
+
+            <div>
+              <label className="block text-sm">
+                <span className="text-gray-700">Description</span>
+                <textarea
+                  name="description"
+                  value={newMetric.description}
+                  onChange={(e) => handleChange(e, false)}
+                  className={`mt-1 block w-full border border-gray-300 rounded-md p-2 ${inputDisabledStyle}`}
+                  rows={3}
+                  placeholder="You can provide a detailed description of the metric here. You can use markdown to format the text."
+                  disabled={disabled}
+                />
+              </label>
+            </div>
+
+            <div className="flex gap-2">
+              <button
+                onClick={addMetric}
+                className={`bg-green-500 text-white rounded-md p-2 hover:bg-green-600 flex items-center gap-2 ${buttonDisabledStyle}`}
+              >
+                <FontAwesomeIcon icon={faPlus} />
+                Add Metric
+              </button>
+            </div>
+          </div>
+        )}
+      </div>
+    </section>
+  );
+}
diff --git a/playground/src/components/view_mode/evaluation_mode/index.tsx b/playground/src/components/view_mode/evaluation_mode/index.tsx
index f029d6673..14f2f7b1f 100644
--- a/playground/src/components/view_mode/evaluation_mode/index.tsx
+++ b/playground/src/components/view_mode/evaluation_mode/index.tsx
@@ -6,6 +6,7 @@ import { useState } from "react";
 import DefineExperiment from "./define_experiment";
 import ConfigureModules from "./configure_modules";
 import ConductExperiment from "./conduct_experiment";
+import EvaluationManagement from "@/components/view_mode/evaluation_mode/expert_evaluation/evaluation_management";
 
 export default function EvaluationMode() {
   const [experiment, setExperiment] = useState<Experiment | undefined>(
@@ -40,6 +41,8 @@ export default function EvaluationMode() {
           )}
         </>
       )}
+      <h2 className="text-4xl font-bold text-white mb-4">Expert Evaluation</h2>
+      <EvaluationManagement />
     </>
   );
 }
diff --git a/playground/src/helpers/get_data.ts b/playground/src/helpers/get_data.ts
index 5351693b5..19c0b33ee 100644
--- a/playground/src/helpers/get_data.ts
+++ b/playground/src/helpers/get_data.ts
@@ -1,12 +1,16 @@
 import type { Exercise } from "@/model/exercise";
 import type { Submission } from "@/model/submission";
-import type { Feedback } from "@/model/feedback";
+import type { CategorizedFeedback, Feedback } from "@/model/feedback";
 import type { DataMode } from "@/model/data_mode";
 
 import path from "path";
 import fs from "fs";
 
 import baseUrl from "@/helpers/base_url";
+import { ExpertEvaluationProgress } from "@/model/expert_evaluation_progress";
+import { ExpertEvaluationConfig } from "@/model/expert_evaluation_config";
+import { v4 as uuidv4 } from "uuid";
+import { ExpertEvaluationProgressStats } from "@/model/expert_evaluation_progress_stats";
 
 /**
  * Splits the given data mode into its parts.
@@ -100,10 +104,14 @@ function addExerciseTypeToSubmissionsAndFeedbacks(json: any): any {
 
   json.submissions = json.submissions?.map((submissionJson: any) => {
     submissionJson.type = exerciseType;
-    submissionJson.feedbacks = submissionJson.feedbacks?.map((feedbackJson: any) => {
-      feedbackJson.type = exerciseType;
-      return feedbackJson;
-    });
+
+    if (Array.isArray(submissionJson.feedbacks)) {
+      submissionJson.feedbacks = submissionJson.feedbacks?.map((feedbackJson: any) => {
+        feedbackJson.type = exerciseType;
+        return feedbackJson;
+      });
+    }
+
     return submissionJson;
   });
   return json;
@@ -206,6 +214,42 @@ function jsonToExercise(json: any): Exercise {
   return exercise;
 }
 
+export function addStructuredGradingInstructionsToFeedback(
+  config: ExpertEvaluationConfig | undefined,
+) {
+  if (config) {
+    config.exercises.forEach((exercise) => {
+      const submissions = exercise.submissions;
+      if (submissions) {
+        for (const submission of submissions) {
+          const feedback = submission.feedbacks;
+
+          if (feedback) {
+            const processedFeedbacks: CategorizedFeedback = {};
+
+            Object.keys(feedback).forEach((category) => {
+              // Map over feedback and link structured grading instructions
+              processedFeedbacks[category] = feedback[category].map((feedbackItem) => {
+                if (feedbackItem.structured_grading_instruction_id) {
+                  feedbackItem.structured_grading_instruction = exercise?.grading_criteria
+                    ?.flatMap((criteria) => criteria.structured_grading_instructions)
+                    .find(
+                      (instruction) =>
+                        instruction.id === feedbackItem.structured_grading_instruction_id
+                    );
+                }
+                return feedbackItem;
+              });
+
+            });
+            submission.feedbacks = processedFeedbacks;
+          }
+        }
+      }
+    });
+  }
+}
+
 function jsonToSubmissions(json: any): Submission[] {
   return json.submissions.map((submissionJson: any) => {
     const submission = submissionJson as Submission;
@@ -221,7 +265,7 @@ function jsonToSubmissions(json: any): Submission[] {
 function jsonToFeedbacks(json: any): Feedback[] {
   return json.submissions.flatMap((submissionJson: any) => {
     if (Array.isArray(submissionJson.feedbacks)) {
-      const feedbacks = submissionJson.feedbacks.map((feedbackJson: any) => {
+      return submissionJson.feedbacks.map((feedbackJson: any) => {
         const feedback = feedbackJson as Feedback;
         // exercise_id is not provided in the json for convenience, so we add it here
         feedback.exercise_id = json.id;
@@ -229,7 +273,6 @@ function jsonToFeedbacks(json: any): Feedback[] {
         feedback.submission_id = submissionJson.id;
         return feedback;
       });
-      return feedbacks;
     }
     return [];
   });
@@ -260,3 +303,232 @@ export function getFeedbacks(
   }
   return getAllExerciseJSON(dataMode, athenaOrigin).flatMap(jsonToFeedbacks);
 }
+
+export function saveProgressToFileSync(
+  dataMode: DataMode,
+  expertEvaluationId: string,
+  expertId: string,
+  expertEvaluationProgress: ExpertEvaluationProgress
+) {
+  const progressData = JSON.stringify(expertEvaluationProgress, null, 2);
+
+  const progressPath = path.join(
+    process.cwd(),
+    "data",
+    ...getDataModeParts(dataMode),
+    `evaluation_${expertEvaluationId}`,
+    `evaluation_progress_${expertId}.json`
+  );
+
+  return fs.writeFileSync(progressPath, progressData, 'utf8');
+}
+
+export function anonymizeFeedbackCategoriesAndShuffle(
+  expertEvaluationConfig: ExpertEvaluationConfig
+) {
+  const mappings: { [key: string]: string } = {};
+
+  // Iterate over exercises
+  for (const exercise of expertEvaluationConfig.exercises) {
+    const submissions = exercise.submissions;
+    if (submissions) {
+      // Shuffle submissions
+      exercise.submissions = submissions.sort(() => Math.random() - 0.5);
+
+      // Iterate over submissions
+      for (const submission of submissions) {
+        const feedback = submission.feedbacks;
+
+        if (feedback) {
+          const anonymizedFeedback: CategorizedFeedback = {};
+
+          // Iterate over each feedback category and anonymize the category names
+          Object.keys(feedback).forEach((originalCategory) => {
+            const anonymizedCategory = uuidv4();
+            mappings[anonymizedCategory] = originalCategory;
+
+            anonymizedFeedback[anonymizedCategory] = feedback[originalCategory];
+          });
+
+          // Now shuffle the anonymized feedback categories
+          const shuffledFeedbackEntries = Object.entries(anonymizedFeedback).sort(() => Math.random() - 0.5);
+          submission.feedbacks = Object.fromEntries(shuffledFeedbackEntries);
+        }
+      }
+    }
+  }
+  // Save the mappings as a plain object in the config
+  expertEvaluationConfig.mappings = mappings;
+}
+
+export function saveConfigToFileSync(
+  dataMode: DataMode,
+  expertEvaluation: ExpertEvaluationConfig,
+) {
+  const configData = JSON.stringify(expertEvaluation, null, 2);
+
+  const configPath = path.join(
+    process.cwd(),
+    "data",
+    ...getDataModeParts(dataMode),
+    `evaluation_config_${expertEvaluation.id}.json`
+  );
+
+  const progress: ExpertEvaluationProgress = {
+    current_submission_index: 0,
+    current_exercise_index: 0,
+    selected_values: {},
+    has_started_evaluating: false,
+    is_finished_evaluating: false,
+  };
+  const expertProgressData = JSON.stringify(progress, null, 2);
+
+  let dirPath = path.join(
+    process.cwd(),
+    "data",
+    ...getDataModeParts(dataMode),
+    `evaluation_${expertEvaluation.id}`);
+
+  // Create parent directory
+  if (!fs.existsSync(dirPath)) {
+    fs.mkdirSync(dirPath, { recursive: true });
+  }
+
+  if (expertEvaluation.expertIds) {
+    for (const expertId of expertEvaluation.expertIds) {
+      // Create progress json for each expert
+      let expertProgressPath = path.join(
+        dirPath,
+        `evaluation_progress_${expertId}.json`
+      );
+
+      // Only create a new empty progress file if it does not yet exist
+      if (!fs.existsSync(expertProgressPath)) {
+        fs.writeFileSync(expertProgressPath, expertProgressData, 'utf8');
+      }
+    }
+  }
+
+  // Create or update config file with exercises and data
+  return fs.writeFileSync(configPath, configData, 'utf8');
+}
+
+export function getProgressStatsFromFileSync(
+  dataMode: DataMode,
+  expertEvaluationId: string
+): ExpertEvaluationProgressStats | undefined {
+  let config = getConfigFromFileSync(dataMode, expertEvaluationId);
+  if (!config) {
+    return undefined;
+  }
+
+  let expertIds = config.expertIds;
+  if (!expertIds || expertIds.length === 0) {
+    return undefined;
+  }
+
+  const totalSubmissions = config.exercises.reduce((acc, exercise) => acc + (exercise.submissions?.length || 0), 0);
+
+  let progressStats: { [expertId: string]: number } = {};
+  for (const expertId of expertIds) {
+    let progress = getProgressFromFileSync(dataMode, expertEvaluationId, expertId);
+
+    if (progress && progress.is_finished_evaluating) {
+      progressStats[expertId] = totalSubmissions;
+    } else if (progress && progress.has_started_evaluating) {
+      progressStats[expertId] = config.exercises.slice(0, progress.current_exercise_index).reduce((sum, exercise) => sum + exercise.submissions!.length, 0) + progress.current_submission_index;
+    }
+  }
+
+  return {
+    totalSubmissions: totalSubmissions,
+    ...progressStats
+  };
+}
+
+export function getProgressFromFileSync(
+  dataMode: DataMode,
+  expertEvaluationId: string,
+  expertId: string
+): ExpertEvaluationProgress | undefined {
+
+  const progressPath = path.join(
+    process.cwd(),
+    "data",
+    ...getDataModeParts(dataMode),
+    `evaluation_${expertEvaluationId}`,
+    `evaluation_progress_${expertId}.json`
+  );
+
+  if (!fs.existsSync(progressPath)) {
+    console.log(`Could not find expert ${expertId}, belonging to expert evaluation ${expertEvaluationId}`);
+    return undefined;
+  }
+
+  return JSON.parse(fs.readFileSync(progressPath, "utf8"));
+}
+
+export function getConfigFromFileSync(
+  dataMode: DataMode,
+  expertEvaluationId: string
+): ExpertEvaluationConfig | undefined {
+  const configPath = path.join(
+    process.cwd(),
+    "data",
+    ...getDataModeParts(dataMode),
+    `evaluation_config_${expertEvaluationId}.json`
+  );
+
+  if (!fs.existsSync(configPath)) {
+    console.log(`Could not find find expert evaluation ${expertEvaluationId}`);
+    return undefined;
+  }
+  return JSON.parse(fs.readFileSync(configPath, "utf8"));
+}
+
+export function getAnonymizedConfigFromFileSync(
+  dataMode: DataMode,
+  expertEvaluationId: string
+): ExpertEvaluationConfig | undefined {
+  let config = getConfigFromFileSync(dataMode, expertEvaluationId);
+
+  if (config) {
+    delete config["expertIds"];
+    delete config["mappings"];
+  }
+
+  return config;
+}
+
+export function getAllConfigsFromFilesSync(
+  dataMode: DataMode,
+): ExpertEvaluationConfig[] {
+
+  const configPath = path.join(
+    process.cwd(),
+    "data",
+    ...getDataModeParts(dataMode));
+
+  const configs: ExpertEvaluationConfig[] = [];
+
+  if (!fs.existsSync(configPath)) {
+    return configs;
+  }
+
+  fs.readdirSync(configPath)
+    .filter((file) => file.startsWith('evaluation_config_') && file.endsWith('.json'))
+    .forEach((file) => {
+      const filePath = path.join(configPath, file);
+      const fileContents = fs.readFileSync(filePath, 'utf8');
+
+      try {
+        const config = JSON.parse(fileContents) as ExpertEvaluationConfig;
+        configs.push(config);
+
+      } catch (error) {
+        console.error(`Error parsing JSON from file ${file}:`, error);
+      }
+    });
+
+  return configs;
+}
diff --git a/playground/src/hooks/playground/exercises.ts b/playground/src/hooks/playground/exercises.ts
index ac38bec28..fe18c5b99 100644
--- a/playground/src/hooks/playground/exercises.ts
+++ b/playground/src/hooks/playground/exercises.ts
@@ -19,7 +19,7 @@ export async function fetchExercises(dataMode: DataMode) {
  * @param options The react-query options.
  */
 export default function useExercises(
-  options: Omit<UseQueryOptions<Exercise[], Error, Exercise[]>, 'queryFn'> = {}
+  options: Omit<UseQueryOptions<Exercise[], Error, Exercise[]>, 'queryFn'> & { eager?: boolean } = {},
 ) {
   const { dataMode } = useBaseInfo();
 
@@ -30,4 +30,4 @@ export default function useExercises(
     },
     ...options
   });
-}
\ No newline at end of file
+}
diff --git a/playground/src/hooks/playground/expert_evaluation.ts b/playground/src/hooks/playground/expert_evaluation.ts
new file mode 100644
index 000000000..afd83118d
--- /dev/null
+++ b/playground/src/hooks/playground/expert_evaluation.ts
@@ -0,0 +1,23 @@
+import base_url from "@/helpers/base_url";
+import { useMutation, UseMutationOptions } from "react-query";
+
+export default function useDownloadExpertEvaluationData(
+  options: Omit<
+    UseMutationOptions<Blob, { status: number; message: string }, { configId: string }>,
+    "mutationFn"
+  > = {}
+) {
+  return useMutation({
+    mutationFn: async ({ configId }) => {
+      const response = await fetch(`${base_url}/api/data/evaluation/expert_evaluation/${configId}/export`);
+
+      if (!response.ok) {
+        const errorData = await response.json();
+        throw { status: response.status, message: errorData.error || "Failed to download data" };
+      }
+
+      return response.blob();
+    },
+    ...options,
+  });
+}
diff --git a/playground/src/hooks/playground/expert_evaluation_config.ts b/playground/src/hooks/playground/expert_evaluation_config.ts
new file mode 100644
index 000000000..5e54d8653
--- /dev/null
+++ b/playground/src/hooks/playground/expert_evaluation_config.ts
@@ -0,0 +1,47 @@
+import baseUrl from "@/helpers/base_url";
+import { ExpertEvaluationConfig } from "@/model/expert_evaluation_config";
+import { DataMode } from "@/model/data_mode";
+
+/** Saves a new or existing expert evaluation config to the server */
+export async function saveExpertEvaluationConfig(
+    dataMode: DataMode,
+    config: ExpertEvaluationConfig,
+    isCreate: boolean) {
+
+    const response = await fetch(`${baseUrl}/api/data/${dataMode}/expert_evaluation/${config.id}/config`, {
+        method: isCreate ? 'POST' : 'PUT',
+        headers: { "Content-Type": "application/json" },
+        body: JSON.stringify(config),
+    });
+
+    if (!response.ok) {
+        throw new Error("Failed to save expert evaluation config");
+    }
+    return await response.json() as Promise<ExpertEvaluationConfig>;
+}
+
+export async function fetchExpertEvaluationConfig(
+    dataMode: DataMode,
+    expertEvaluationId: string
+) {
+    const response = await fetch(`${baseUrl}/api/data/${dataMode}/expert_evaluation/${expertEvaluationId}/config`);
+
+    if (!response.ok) {
+        throw new Error("Failed to fetch expert evaluation config");
+    }
+
+    return await response.json() as Promise<ExpertEvaluationConfig>;
+}
+
+/** Fetches the list of expert evaluation configs from the server */
+export async function fetchAllExpertEvaluationConfigs(
+    dataMode: DataMode
+) {
+    const response = await fetch(`${baseUrl}/api/data/${dataMode}/expert_evaluation/configs`);
+
+    if (!response.ok) {
+        throw new Error("Failed to fetch expert evaluation configs");
+    }
+
+    return await response.json() as Promise<ExpertEvaluationConfig[]>;
+}
diff --git a/playground/src/hooks/playground/expert_evaluation_progress.ts b/playground/src/hooks/playground/expert_evaluation_progress.ts
new file mode 100644
index 000000000..f21bc37e8
--- /dev/null
+++ b/playground/src/hooks/playground/expert_evaluation_progress.ts
@@ -0,0 +1,29 @@
+import { DataMode } from "@/model/data_mode";
+import baseUrl from "@/helpers/base_url";
+import { ExpertEvaluationProgress } from "@/model/expert_evaluation_progress";
+
+export async function saveExpertEvaluationProgress(
+  dataMode: DataMode,
+  expertEvaluationId: string,
+  expertId: string,
+  progress: ExpertEvaluationProgress) {
+  const response = await fetch(`${baseUrl}/api/data/${dataMode}/expert_evaluation/${expertEvaluationId}/${expertId}/progress`, {
+    method: 'PUT',
+    headers: {
+      'Content-Type': 'application/json',
+    },
+    body: JSON.stringify(progress),
+  });
+
+  return response.status;
+}
+
+export async function fetchExpertEvaluationProgress(
+  dataMode: DataMode,
+  expertEvaluationId: string,
+  expertId: string,
+) {
+  const response = await fetch(`${baseUrl}/api/data/${dataMode}/expert_evaluation/${expertEvaluationId}/${expertId}/progress`);
+
+  return await response.json() as Promise<ExpertEvaluationProgress>;
+}
diff --git a/playground/src/hooks/playground/expert_evaluation_progress_stats.ts b/playground/src/hooks/playground/expert_evaluation_progress_stats.ts
new file mode 100644
index 000000000..89c507012
--- /dev/null
+++ b/playground/src/hooks/playground/expert_evaluation_progress_stats.ts
@@ -0,0 +1,10 @@
+import baseUrl from "@/helpers/base_url";
+import { ExpertEvaluationProgressStats } from "@/model/expert_evaluation_progress_stats";
+
+export async function fetchExpertEvaluationProgressStats(
+  expertEvaluationId: string
+) {
+  const response = await fetch(`${baseUrl}/api/data/expert_evaluation/expert_evaluation/${expertEvaluationId}/progress_stats`);
+
+  return await response.json() as Promise<ExpertEvaluationProgressStats>;
+}
diff --git a/playground/src/model/data_mode.ts b/playground/src/model/data_mode.ts
index 91688ae85..3c975d04b 100644
--- a/playground/src/model/data_mode.ts
+++ b/playground/src/model/data_mode.ts
@@ -1 +1 @@
-export type DataMode = "example" | "evaluation" | string;
+export type DataMode = "example" | "evaluation" | "expert_evaluation" | string;
diff --git a/playground/src/model/exercise.ts b/playground/src/model/exercise.ts
index 7f7de665a..d4330e45f 100644
--- a/playground/src/model/exercise.ts
+++ b/playground/src/model/exercise.ts
@@ -1,3 +1,5 @@
+import { Submission } from "@/model/submission";
+
 export type ExerciseType = "text" | "programming" | "modeling";
 
 export type StructuredGradingInstruction = {
@@ -25,6 +27,7 @@ type ExerciseBase = {
   grading_instructions?: string;
   grading_criteria?: GradingCriteria[];
   problem_statement?: string;
+  submissions?: Submission[]; // Playground only
   meta: {
     [key: string]: any;
   };
diff --git a/playground/src/model/expert_evaluation_config.ts b/playground/src/model/expert_evaluation_config.ts
new file mode 100644
index 000000000..aa16daa45
--- /dev/null
+++ b/playground/src/model/expert_evaluation_config.ts
@@ -0,0 +1,14 @@
+import { Exercise } from "@/model/exercise";
+import { Metric } from "@/model/metric";
+
+export type ExpertEvaluationConfig = {
+    type: "evaluation_config";
+    started: boolean;
+    creationDate: Date;
+    id: string;
+    name: string;
+    metrics: Metric[];
+    exercises: Exercise[];
+    expertIds?: string[];
+    mappings?: { [key: string]: string };
+}
diff --git a/playground/src/model/expert_evaluation_progress.ts b/playground/src/model/expert_evaluation_progress.ts
new file mode 100644
index 000000000..55eecf3b2
--- /dev/null
+++ b/playground/src/model/expert_evaluation_progress.ts
@@ -0,0 +1,15 @@
+export type ExpertEvaluationProgress = {
+  current_submission_index: number;
+  current_exercise_index: number;
+  selected_values: {
+    [exerciseId: string]: { // Group by exercise ID
+      [submissionId: string]: { // Group by submission ID within each exercise
+        [feedbackType: string]: { // Group by feedback type
+          [metricId: string]: number; // Store metric Likert scale values for each feedback type
+        };
+      };
+    };
+  };
+  has_started_evaluating: boolean;
+  is_finished_evaluating: boolean;
+};
diff --git a/playground/src/model/expert_evaluation_progress_stats.ts b/playground/src/model/expert_evaluation_progress_stats.ts
new file mode 100644
index 000000000..e1ab53620
--- /dev/null
+++ b/playground/src/model/expert_evaluation_progress_stats.ts
@@ -0,0 +1,4 @@
+export type ExpertEvaluationProgressStats = {
+  totalSubmissions: number;
+  [expertId: string]: number;
+};
diff --git a/playground/src/model/feedback.ts b/playground/src/model/feedback.ts
index 82ce4e4a6..f515b0402 100644
--- a/playground/src/model/feedback.ts
+++ b/playground/src/model/feedback.ts
@@ -40,6 +40,10 @@ export type ModelingFeedback = FeedbackBase & {
 
 export type Feedback = TextFeedback | ProgrammingFeedback | ModelingFeedback;
 
+export type CategorizedFeedback = {
+  [key: string]: Feedback[];
+};
+
 /**
  * Returns the formatted reference of a given feedback. This can be a line range or an element ID depending on the
  * exercise type.
diff --git a/playground/src/model/metric.ts b/playground/src/model/metric.ts
new file mode 100644
index 000000000..fd6a03ae8
--- /dev/null
+++ b/playground/src/model/metric.ts
@@ -0,0 +1,6 @@
+export type Metric = {
+    id: string;
+    title: string;
+    summary: string;
+    description: string;
+}
diff --git a/playground/src/model/submission.ts b/playground/src/model/submission.ts
index 50341485d..e813844f9 100644
--- a/playground/src/model/submission.ts
+++ b/playground/src/model/submission.ts
@@ -1,9 +1,11 @@
 import type { ExerciseType } from "./exercise";
+import { CategorizedFeedback } from "@/model/feedback";
 
 type SubmissionBase = {
     id: number;
     type: ExerciseType; // Playground only
     exercise_id: number;
+    feedbacks?: CategorizedFeedback; // Playground only
     meta: {
         [key: string]: any;
     };
diff --git a/playground/src/pages/[expert_evaluation_config_id]/[expert_id]/expert_view.tsx b/playground/src/pages/[expert_evaluation_config_id]/[expert_id]/expert_view.tsx
new file mode 100644
index 000000000..72b968c71
--- /dev/null
+++ b/playground/src/pages/[expert_evaluation_config_id]/[expert_id]/expert_view.tsx
@@ -0,0 +1,280 @@
+import SideBySideHeader from '@/components/expert_evaluation/expert_view/side_by_side_header';
+import React, { useEffect, useState } from 'react';
+import LikertScaleForm from "@/components/expert_evaluation/expert_view/likert_scale_form";
+import { Exercise } from "@/model/exercise";
+import { TextSubmission } from "@/model/submission";
+import { Metric } from "@/model/metric";
+import {
+  fetchExpertEvaluationProgress,
+  saveExpertEvaluationProgress
+} from "@/hooks/playground/expert_evaluation_progress";
+import { ExpertEvaluationProgress } from "@/model/expert_evaluation_progress";
+import { useRouter } from "next/router";
+import { fetchExpertEvaluationConfig } from "@/hooks/playground/expert_evaluation_config";
+import { ExpertEvaluationConfig } from "@/model/expert_evaluation_config";
+import CongratulationScreen from "@/components/expert_evaluation/expert_view/congratulation_screen";
+import WelcomeScreen from "@/components/expert_evaluation/expert_view/welcome_screen";
+import ExerciseScreen from "@/components/expert_evaluation/expert_view/exercise_screen";
+import ContinueLaterScreen from "@/components/expert_evaluation/expert_view/continue_later_screen";
+
+export default function SideBySideExpertView() {
+  const router = useRouter();
+  const { expert_evaluation_config_id, expert_id } = router.query as {
+    expert_evaluation_config_id: string;
+    expert_id: string
+  };
+  const dataMode = "expert_evaluation";
+
+  const [exercises, setExercises] = useState<Exercise[]>([]);
+  const [submissionsLength, setSubmissionsLength] = useState<number>(0);
+  const [currentSubmissionIndex, setCurrentSubmissionIndex] = useState<number>(0);
+  const [currentExerciseIndex, setCurrentExerciseIndex] = useState<number>(0);
+  const [metrics, setMetrics] = useState<Metric[]>([]);
+  const [selectedValues, setSelectedValues] = useState<ExpertEvaluationProgress['selected_values']>({});
+  const [evaluationStarted, setEvaluationStarted] = useState<boolean>(true);
+  const [hasStartedEvaluating, setHasStartedEvaluating] = useState<boolean>(true);
+  const [isFinishedEvaluating, setIsFinishedEvaluating] = useState<boolean>(false);
+  const [isNewExercise, setIsNewExercise] = useState<boolean>(false);
+  const [isContinueLater, setContinueLater] = useState<boolean>(false);
+  const [isMarkMissingValues, setMarkMissingVaues] = useState<boolean>(false);
+
+  useEffect(() => {
+    const fetchData = async () => {
+      if (expert_evaluation_config_id && expert_id) {
+        try {
+          // Fetch and set data from evaluation config
+          const config: ExpertEvaluationConfig = await fetchExpertEvaluationConfig(dataMode, expert_evaluation_config_id);
+          setExercises(config.exercises);
+          setMetrics(config.metrics);
+          setEvaluationStarted(config.started);
+        } catch
+        (error) {
+          console.error('Error loading expert evaluation configuration: ', error);
+        }
+
+        try {
+          let expertEvaluationProgress = await fetchExpertEvaluationProgress(dataMode, expert_evaluation_config_id, expert_id);
+          setCurrentSubmissionIndex(expertEvaluationProgress.current_submission_index);
+          setCurrentExerciseIndex(expertEvaluationProgress.current_exercise_index);
+          setSelectedValues(expertEvaluationProgress.selected_values);
+          setHasStartedEvaluating(expertEvaluationProgress.has_started_evaluating);
+          setIsFinishedEvaluating(expertEvaluationProgress.is_finished_evaluating);
+
+        } catch (error) {
+          console.error('Error loading expert evaluation progress: ', error);
+        }
+        setContinueLater(false);
+      }
+    }
+      ; fetchData();
+  }, [expert_evaluation_config_id, expert_id]
+  );
+
+  useEffect(() => {
+    if (exercises && exercises.length > 0) {
+      let total_submissions = 0;
+      for (const exercise of exercises) {
+        if (exercise.submissions) {
+          total_submissions += exercise.submissions.length;
+        }
+      }
+      setSubmissionsLength(total_submissions);
+    }
+  }, [exercises, metrics]);
+
+  const isExerciseComplete = (): boolean => {
+    const exerciseData = selectedValues[currentExercise.id];
+    if (!exerciseData) return false;
+
+    if (currentSubmission) {
+      const submissionData = exerciseData[currentSubmission.id];
+      if (!submissionData) return false;
+      const currentFeedbacks = currentSubmission.feedbacks;
+
+      if (currentFeedbacks) {
+        // Check if all required feedback types and metrics are selected
+        for (const feedbackType of Object.keys(currentFeedbacks)) {
+          const feedbackData = submissionData[feedbackType];
+          if (!feedbackData) return false;
+
+          for (const metric of metrics) {
+            if (!(metric.id in feedbackData)) return false;
+          }
+        }
+      }
+    }
+    return true;
+  }
+
+  const currentExercise = exercises[currentExerciseIndex];
+  const currentSubmission = currentExercise?.submissions?.[currentSubmissionIndex];
+  const globalSubmissionIndex = exercises.slice(0, currentExerciseIndex).reduce((sum, exercise) => sum + exercise.submissions!.length, 0) + currentSubmissionIndex;
+
+  const handleNext = () => {
+    let confirmed = true;
+    if (!isExerciseComplete()) {
+      setMarkMissingVaues(true);
+      confirmed = confirm("Are you sure want to continue with the next submission? You did not yet evaluate all metrics!");
+    }
+
+    if (globalSubmissionIndex === submissionsLength - 1 && confirmed) {
+      confirmed = confirm("Are you sure you want to finish the evaluation? Once you finish, you can no longer make any changes!");
+    }
+
+    if (confirmed) {
+      const currentExercise = exercises[currentExerciseIndex];
+      // If we are at the last submission for the current exercise, go to the next exercise
+      if (currentSubmissionIndex < currentExercise.submissions!.length - 1) {
+        setCurrentSubmissionIndex((prevIndex) => prevIndex + 1);
+
+      } else if (currentExerciseIndex < exercises.length - 1) {
+        // Move to the next exercise, reset submission index
+        setCurrentExerciseIndex((prevIndex) => prevIndex + 1);
+        setCurrentSubmissionIndex(0);
+        setIsNewExercise(true);
+
+      } else {
+        setIsFinishedEvaluating(true);
+      }
+      setMarkMissingVaues(false);
+    }
+  };
+
+  useEffect(() => {
+    saveProgress();
+  }, [currentSubmissionIndex, currentExerciseIndex, isFinishedEvaluating]);
+
+  const handlePrevious = () => {
+    // If we are not at the first submission, just decrement the submission index
+    if (currentSubmissionIndex > 0) {
+      setCurrentSubmissionIndex((prevIndex) => prevIndex - 1);
+
+
+    } else if (currentExerciseIndex > 0) {
+      setCurrentExerciseIndex((prevIndex) => prevIndex - 1);
+      // Set the submission index to the last submission of the previous exercise
+      const previousExercise = exercises[currentExerciseIndex - 1];
+      setCurrentSubmissionIndex(previousExercise.submissions!.length - 1);
+    }
+  };
+
+
+  const handleWelcomeClose = () => {
+    setHasStartedEvaluating(false);
+    saveProgress();
+  };
+
+  const handleNextExercise = () => {
+    setIsNewExercise(false);
+  }
+
+  const handleCloseContinueLater = () => {
+    setContinueLater(false);
+  }
+
+  const handleOpenContinueLater = () => {
+    saveProgress();
+    setContinueLater(true);
+  }
+
+  const saveProgress = () => {
+    if (expert_evaluation_config_id && expert_id) {
+      setHasStartedEvaluating(true);
+      const progress: ExpertEvaluationProgress = {
+        current_submission_index: currentSubmissionIndex,
+        current_exercise_index: currentExerciseIndex,
+        selected_values: selectedValues,
+        has_started_evaluating: true,
+        is_finished_evaluating: isFinishedEvaluating,
+      };
+      saveExpertEvaluationProgress(dataMode, expert_evaluation_config_id, expert_id, progress);
+    }
+  }
+
+  const handleLikertValueChange = (feedbackType: string, metricId: string, value: number) => {
+    const exerciseId = currentExercise.id.toString();
+    let submissionId = "";
+    if (currentExercise.submissions) {
+      submissionId = currentExercise.submissions[currentSubmissionIndex].id.toString();
+    }
+
+    setSelectedValues((prevValues) => ({
+      ...prevValues,
+      [exerciseId]: {
+        ...prevValues[exerciseId],
+        [submissionId]: {
+          ...prevValues[exerciseId]?.[submissionId],
+          [feedbackType]: {
+            ...prevValues[exerciseId]?.[submissionId]?.[feedbackType],
+            [metricId]: value
+          }
+        }
+      }
+    }));
+  }
+
+  if (!exercises && !metrics) {
+    return <div className={"bg-white p-6 text-red-600"}>
+      Could not fetch config data for expert evaluation (id={expert_evaluation_config_id})
+    </div>;
+  }
+
+  if (!currentSubmissionIndex && !currentExerciseIndex && !selectedValues) {
+    return <div className={"bg-white p-6 text-red-600"}>
+      Could not find expert (id={expert_id}) belonging to expert evaluation (id={expert_evaluation_config_id}).
+    </div>;
+  }
+
+  if (!evaluationStarted) {
+    return <div className={"bg-white p-6 text-red-600"}>The expert evaluation (id={expert_evaluation_config_id})
+      has not yet started.</div>;
+  }
+
+  if (!hasStartedEvaluating) {
+    return <WelcomeScreen exercise={currentExercise} onClose={handleWelcomeClose} />;
+  }
+
+  if (isContinueLater) {
+    return <ContinueLaterScreen onClose={handleCloseContinueLater} />
+  }
+
+
+  if (isNewExercise) {
+    return <ExerciseScreen
+      onCloseExerciseDetail={handleNextExercise}
+      onOpenContinueLater={handleOpenContinueLater}
+      exercise={currentExercise}
+      currentExerciseIndex={currentExerciseIndex}
+      totalExercises={exercises.length}
+    />;
+  }
+
+  if (isFinishedEvaluating) {
+    return <CongratulationScreen />;
+  }
+
+  if (currentExercise && currentSubmission && currentSubmission.feedbacks) {
+    return (
+      <div className={"bg-white p-6"}>
+        <SideBySideHeader
+          exercise={exercises[currentExerciseIndex]}
+          globalSubmissionIndex={globalSubmissionIndex}
+          totalSubmissions={submissionsLength}
+          onNext={handleNext}
+          onPrevious={handlePrevious}
+          metrics={metrics}
+          onContinueLater={handleOpenContinueLater}
+        />
+        <LikertScaleForm submission={currentSubmission as TextSubmission}
+          exercise={currentExercise}
+          feedback={currentSubmission.feedbacks}
+          metrics={metrics}
+          selectedValues={selectedValues}
+          onLikertValueChange={handleLikertValueChange}
+          isMarkMissingValue={isMarkMissingValues} />
+      </div>
+    );
+  } else {
+    return <div>Loading...</div>;
+  }
+}
diff --git a/playground/src/pages/api/data/[dataMode]/data/export.ts b/playground/src/pages/api/data/[dataMode]/data/export.ts
index 453b5f5d5..2f318751d 100644
--- a/playground/src/pages/api/data/[dataMode]/data/export.ts
+++ b/playground/src/pages/api/data/[dataMode]/data/export.ts
@@ -9,13 +9,17 @@ const EXPORT_DIR = path.join(process.cwd(), "data");
 async function handler(req: NextApiRequest, res: NextApiResponse) {
   const { dataMode } = req.query as { dataMode: string };
   const directoryPath = path.join(EXPORT_DIR, ...getDataModeParts(dataMode));
-  
+  const filename = `${dataMode}.zip`;
+  await exportHandler(res, directoryPath, filename);
+}
+
+export async function exportHandler(res: NextApiResponse, directoryPath: string, filename: string) {
   if (!fs.existsSync(directoryPath)) {
     return res.status(404).json({ error: "Directory not found" });
   }
   
   res.setHeader("Content-Type", "application/zip");
-  res.setHeader("Content-Disposition", `attachment; filename=${dataMode}.zip`);
+  res.setHeader("Content-Disposition", `attachment; filename=${filename}`);
   
   const archive = archiver("zip", { zlib: { level: 9 } });
   archive.on("error", (err) => res.status(500).send({ error: err.message }));
diff --git a/playground/src/pages/api/data/[dataMode]/expert_evaluation/[expertEvaluationId]/[expertId]/progress.ts b/playground/src/pages/api/data/[dataMode]/expert_evaluation/[expertEvaluationId]/[expertId]/progress.ts
new file mode 100644
index 000000000..776a1871f
--- /dev/null
+++ b/playground/src/pages/api/data/[dataMode]/expert_evaluation/[expertEvaluationId]/[expertId]/progress.ts
@@ -0,0 +1,43 @@
+import { NextApiRequest, NextApiResponse } from "next";
+import { DataMode } from "@/model/data_mode";
+import { getProgressFromFileSync, saveProgressToFileSync } from "@/helpers/get_data";
+import { validateDataModeMiddleware } from "@/helpers/validate_data_mode_middleware";
+import { ExpertEvaluationProgress } from "@/model/expert_evaluation_progress";
+
+function handler(req: NextApiRequest, res: NextApiResponse) {
+    if (req.method == 'PUT') {
+        const { dataMode, expertEvaluationId, expertId } = req.query as {
+            dataMode: DataMode;
+            expertEvaluationId: string;
+            expertId: string
+        };
+        const expertEvaluationProgress: ExpertEvaluationProgress = req.body;
+
+        saveProgressToFileSync(dataMode, expertEvaluationId, expertId, expertEvaluationProgress);
+        return res.status(200).json({ message: 'Progress saved successfully' });
+
+    } else if (req.method == 'GET') {
+        const { dataMode, expertEvaluationId, expertId } = req.query as {
+            dataMode: DataMode;
+            expertEvaluationId: string;
+            expertId: string
+        };
+        let progress = getProgressFromFileSync(dataMode, expertEvaluationId, expertId);
+
+        if (!progress || Object.keys(progress).length === 0) {
+            return res.status(404).json({ message: 'Progress not found' });
+        }
+        return res.status(200).json(progress);
+
+    } else {
+        res.setHeader('Allow', ['POST']);
+        return res.status(405).json({ message: 'Only GET or PUT requests allowed' });
+    }
+}
+
+export default function handlerWithMiddleware(
+    req: NextApiRequest,
+    res: NextApiResponse
+) {
+    validateDataModeMiddleware(req, res, () => handler(req, res));
+}
diff --git a/playground/src/pages/api/data/[dataMode]/expert_evaluation/[expertEvaluationId]/config.ts b/playground/src/pages/api/data/[dataMode]/expert_evaluation/[expertEvaluationId]/config.ts
new file mode 100644
index 000000000..1bc5a2a6d
--- /dev/null
+++ b/playground/src/pages/api/data/[dataMode]/expert_evaluation/[expertEvaluationId]/config.ts
@@ -0,0 +1,45 @@
+import { NextApiRequest, NextApiResponse } from "next";
+import { DataMode } from "@/model/data_mode";
+import {
+    getAnonymizedConfigFromFileSync,
+    saveConfigToFileSync,
+    addStructuredGradingInstructionsToFeedback,
+    anonymizeFeedbackCategoriesAndShuffle
+} from "@/helpers/get_data";
+import { validateDataModeMiddleware } from "@/helpers/validate_data_mode_middleware";
+import { ExpertEvaluationConfig } from "@/model/expert_evaluation_config";
+
+function handler(req: NextApiRequest, res: NextApiResponse) {
+    if (req.method == 'POST') {
+        const { dataMode } = req.query as { dataMode: DataMode };
+        const expertEvaluationConfig: ExpertEvaluationConfig = req.body;
+
+        anonymizeFeedbackCategoriesAndShuffle(expertEvaluationConfig);
+        saveConfigToFileSync(dataMode, expertEvaluationConfig);
+        return res.status(200).json({ message: 'Config created successfully' });
+
+    } else if (req.method == 'PUT') {
+        const { dataMode } = req.query as { dataMode: DataMode };
+        const expertEvaluationConfig: ExpertEvaluationConfig = req.body;
+
+        saveConfigToFileSync(dataMode, expertEvaluationConfig);
+        return res.status(200).json({ message: 'Config saved successfully' });
+
+    } else if (req.method == 'GET') {
+        const { dataMode, expertEvaluationId } = req.query as { dataMode: DataMode; expertEvaluationId: string };
+        let config = getAnonymizedConfigFromFileSync(dataMode, expertEvaluationId);
+
+        addStructuredGradingInstructionsToFeedback(config);
+        return res.status(200).json(config);
+    } else {
+        res.setHeader('Allow', ['POST']);
+        return res.status(405).json({ message: 'Only GET, POST and PUT requests allowed' });
+    }
+}
+
+export default function handlerWithMiddleware(
+    req: NextApiRequest,
+    res: NextApiResponse
+) {
+    validateDataModeMiddleware(req, res, () => handler(req, res));
+}
diff --git a/playground/src/pages/api/data/[dataMode]/expert_evaluation/[expertEvaluationId]/export.ts b/playground/src/pages/api/data/[dataMode]/expert_evaluation/[expertEvaluationId]/export.ts
new file mode 100644
index 000000000..d9a80a74d
--- /dev/null
+++ b/playground/src/pages/api/data/[dataMode]/expert_evaluation/[expertEvaluationId]/export.ts
@@ -0,0 +1,15 @@
+import type { NextApiRequest, NextApiResponse } from "next";
+import path from "path";
+import { exportHandler } from "@/pages/api/data/[dataMode]/data/export";
+
+const EXPORT_DIR = path.join(process.cwd(), "data", "expert_evaluation");
+
+async function handler(req: NextApiRequest, res: NextApiResponse) {
+  const { expertEvaluationId } = req.query as { expertEvaluationId: string };
+  const directoryPath = path.join(EXPORT_DIR, `evaluation_${expertEvaluationId}`);
+  const filename = `evaluation_${expertEvaluationId}.zip`;
+
+  await exportHandler(res, directoryPath, filename);
+}
+
+export default handler;
diff --git a/playground/src/pages/api/data/[dataMode]/expert_evaluation/[expertEvaluationId]/progress_stats.ts b/playground/src/pages/api/data/[dataMode]/expert_evaluation/[expertEvaluationId]/progress_stats.ts
new file mode 100644
index 000000000..3c6aec192
--- /dev/null
+++ b/playground/src/pages/api/data/[dataMode]/expert_evaluation/[expertEvaluationId]/progress_stats.ts
@@ -0,0 +1,21 @@
+import { NextApiRequest, NextApiResponse } from "next";
+import { DataMode } from "@/model/data_mode";
+import { getProgressStatsFromFileSync } from "@/helpers/get_data";
+import { validateDataModeMiddleware } from "@/helpers/validate_data_mode_middleware";
+
+function handler(req: NextApiRequest, res: NextApiResponse) {
+  const { dataMode, expertEvaluationId } = req.query as {
+    dataMode: DataMode;
+    expertEvaluationId: string;
+  };
+
+  let progressStats = getProgressStatsFromFileSync(dataMode, expertEvaluationId);
+  return res.status(200).json(progressStats)
+}
+
+export default function handlerWithMiddleware(
+  req: NextApiRequest,
+  res: NextApiResponse
+) {
+  validateDataModeMiddleware(req, res, () => handler(req, res));
+}
diff --git a/playground/src/pages/api/data/[dataMode]/expert_evaluation/configs.ts b/playground/src/pages/api/data/[dataMode]/expert_evaluation/configs.ts
new file mode 100644
index 000000000..8a116be5a
--- /dev/null
+++ b/playground/src/pages/api/data/[dataMode]/expert_evaluation/configs.ts
@@ -0,0 +1,23 @@
+import { NextApiRequest, NextApiResponse } from "next";
+import { DataMode } from "@/model/data_mode";
+import { getAllConfigsFromFilesSync } from "@/helpers/get_data";
+import { validateDataModeMiddleware } from "@/helpers/validate_data_mode_middleware";
+
+function handler(req: NextApiRequest, res: NextApiResponse) {
+    if (req.method == 'GET') {
+        const { dataMode, expertEvaluationId } = req.query as { dataMode: DataMode; expertEvaluationId: string };
+
+        let configs = getAllConfigsFromFilesSync(dataMode);
+        return res.status(200).json(configs);
+
+    } else {
+        return res.status(405).json({ message: 'Only GET allowed' });
+    }
+}
+
+export default function handlerWithMiddleware(
+    req: NextApiRequest,
+    res: NextApiResponse
+) {
+    validateDataModeMiddleware(req, res, () => handler(req, res));
+}