From a42efdd5812b9c739cf7d45c8b642e613922792a Mon Sep 17 00:00:00 2001
From: Dmytro Polityka <33299157+undernagruzez@users.noreply.github.com>
Date: Mon, 5 Aug 2024 16:31:14 +0200
Subject: [PATCH 1/2] Update documentation for deployments (#324)

---
 docs/administration_of_deployments/configuration.rst | 9 +++++++++
 docs/index.rst                                       | 7 +++++++
 env_example/assessment_module_manager.env            | 3 +--
 3 files changed, 17 insertions(+), 2 deletions(-)
 create mode 100644 docs/administration_of_deployments/configuration.rst

diff --git a/docs/administration_of_deployments/configuration.rst b/docs/administration_of_deployments/configuration.rst
new file mode 100644
index 00000000..e2d8b5e1
--- /dev/null
+++ b/docs/administration_of_deployments/configuration.rst
@@ -0,0 +1,9 @@
+Configuration
+===========================================
+
+Athena can serve requests from multiple LM systems. It uses a custom HTTP header ``X-Server-URL`` to identify the origin of each request. To prevent unauthorized use of resources, the admin must whitelist all supported deployments. This configuration is done in the ``assessment_module_manager/deployments.ini`` file or the corresponding Docker analog for server deployments using Docker images.
+
+For each listed deployment, the admin must define a corresponding secret in the environment variable ``LMS_DEPLOYMENT_NAME_SECRET`` (replace DEPLOYMENT_NAME with the name from the .ini file) of the ``assessment_module_manager``.
+Please note: Playground counts as an LMS and needs its own record.
+
+This configuration does not exclude or replace inter-module authentication; Athena still requires keys between modules and the assessment module manager.
diff --git a/docs/index.rst b/docs/index.rst
index 0b1a3aeb..908ecef7 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -66,3 +66,10 @@ Athena will use the information it is given and provide the automatic suggestion
 
     athena_package/storage
     athena_package/helpers
+
+.. toctree::
+    :caption: Administration of Deployments
+    :includehidden:
+    :maxdepth: 1
+
+    administration_of_deployments/configuration
\ No newline at end of file
diff --git a/env_example/assessment_module_manager.env b/env_example/assessment_module_manager.env
index 6182d37b..2dc42f12 100644
--- a/env_example/assessment_module_manager.env
+++ b/env_example/assessment_module_manager.env
@@ -1,5 +1,4 @@
 PRODUCTION=1
-SECRET=abcdef12345
 
 # module secrets, same as in the module env files
 MODULE_EXAMPLE_SECRET=12345abcdef
@@ -9,7 +8,7 @@ MODULE_TEXT_COFEE_SECRET=12345abcdef
 MODULE_PROGRAMMING_THEMISML_SECRET=12345abcdef
 
 ################################################################
-# LMS Deployments                                          #
+# LMS Deployments                                              #
 ################################################################
 # the deployment name should correspond to the name in deployments.ini
 LMS_DEPLOYMENT_NAME_SECRET=12345abcdef

From accdabc97d73fa0251ff04677db34eed4f72f182 Mon Sep 17 00:00:00 2001
From: EneaGore <73840596+EneaGore@users.noreply.github.com>
Date: Mon, 5 Aug 2024 16:43:58 +0200
Subject: [PATCH 2/2] `Module_text_llm`: Upgrade dependencies and openai model
 retrieval (#323)

Co-authored-by: = Enea_Gore <ge72git@mytum.de>
Co-authored-by: Felix T.J. Dietrich <felixtj.dietrich@tum.de>
---
 module_text_llm/.env.example                  |  13 +-
 .../helpers/models/__init__.py                |  10 -
 .../module_text_llm/helpers/models/openai.py  | 256 ++-------------
 .../helpers/models/replicate.py               | 116 -------
 module_text_llm/poetry.lock                   | 299 +++++++++++-------
 module_text_llm/pyproject.toml                |  18 +-
 6 files changed, 222 insertions(+), 490 deletions(-)
 delete mode 100644 module_text_llm/module_text_llm/helpers/models/replicate.py

diff --git a/module_text_llm/.env.example b/module_text_llm/.env.example
index aedc5bdb..db957e6d 100644
--- a/module_text_llm/.env.example
+++ b/module_text_llm/.env.example
@@ -12,7 +12,7 @@ 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-35-turbo"
 
 # Enable LLM-as-a-judge approach 0 = disabled, 1 = enabled
 LLM_ENABLE_LLM_AS_A_JUDGE=1
@@ -23,13 +23,14 @@ LLM_EVALUATION_MODEL="azure_openai_gpt-4"
 # 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)
-LLM_OPENAI_API_KEY="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
+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`
-LLM_AZURE_OPENAI_API_KEY="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
-LLM_AZURE_OPENAI_API_BASE="https://ase-eu01.openai.azure.com/" # change base if needed
-LLM_AZURE_OPENAI_API_VERSION="2023-07-01-preview" # change base if needed
+AZURE_OPENAI_API_KEY="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
+AZURE_OPENAI_ENDPOINT="https://ase-eu01.openai.azure.com/" # change base if needed
+OPENAI_API_VERSION="2023-07-01-preview" # change base if needed
+AZURE_DEPLOYMENTS=gpt-35-turbo,gpt-4-turbo,gpt-4-vision,gpt-4o
 
 # Replicate [leave blank if not used]
 # See https://replicate.com and adjust model config options in `module_text_llm/helpers/models/replicate.py`
@@ -40,4 +41,4 @@ REPLICATE_API_TOKEN=
 # LANGCHAIN_TRACING_V2=true
 # LANGCHAIN_ENDPOINT="https://api.smith.langchain.com"
 # LANGCHAIN_API_KEY="XXX"
-# LANGCHAIN_PROJECT="XXX"
\ No newline at end of file
+# LANGCHAIN_PROJECT="XXX"
diff --git a/module_text_llm/module_text_llm/helpers/models/__init__.py b/module_text_llm/module_text_llm/helpers/models/__init__.py
index 144bcf92..85078d4d 100644
--- a/module_text_llm/module_text_llm/helpers/models/__init__.py
+++ b/module_text_llm/module_text_llm/helpers/models/__init__.py
@@ -23,16 +23,6 @@
 except AttributeError:
     pass
 
-try:
-    import module_text_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
-    if evaluation_model_name in replicate_config.available_models:
-        evaluation_model = replicate_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.")
diff --git a/module_text_llm/module_text_llm/helpers/models/openai.py b/module_text_llm/module_text_llm/helpers/models/openai.py
index ab304427..e6faaa01 100644
--- a/module_text_llm/module_text_llm/helpers/models/openai.py
+++ b/module_text_llm/module_text_llm/helpers/models/openai.py
@@ -1,254 +1,44 @@
 import os
-from contextlib import contextmanager
-from typing import Any, Callable, Dict, List
+from typing import Any , Dict
 from pydantic import Field, validator, PositiveInt
 from enum import Enum
-
 import openai
-from langchain.chat_models import AzureChatOpenAI, ChatOpenAI
-from langchain.llms import AzureOpenAI, OpenAI
-from langchain.llms.openai import BaseOpenAI
 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_"
-
-
-#########################################################################
-# Monkey patching openai/langchain api                                  #
-# ===================================================================== #
-# This allows us to have multiple api keys i.e. mixing                  #
-# openai and azure openai api keys so we can use not only deployed      #
-# models but also models from the non-azure openai api.                 #
-# This is mostly for testing purposes, in production we can just deploy #
-# the models to azure that we want to use.                              #
-#########################################################################
-
-# Prevent LangChain error, we will set the key later
-os.environ["OPENAI_API_KEY"] = ""
-
-def _wrap(old: Any, new: Any) -> Callable:
-    def repl(*args: Any, **kwargs: Any) -> Any:
-        new(args[0])  # args[0] is self
-        return old(*args, **kwargs)
-    return repl
-
-
-def _async_wrap(old: Any, new: Any):
-    async def repl(*args, **kwargs):
-        new(args[0])  # args[0] is self
-        return await old(*args, **kwargs)
-    return repl
-
-
-def _set_credentials(self):
-    openai.api_key = self.openai_api_key
-
-    api_type = "open_ai"
-    api_base = "https://api.openai.com/v1"
-    api_version = None
-    if hasattr(self, "openai_api_type"):
-        api_type = self.openai_api_type
-
-    if api_type == "azure":
-        if hasattr(self, "openai_api_base"):
-            api_base = self.openai_api_base
-        if hasattr(self, "openai_api_version"):
-            api_version = self.openai_api_version
-
-    openai.api_type = api_type
-    openai.api_base = api_base
-    openai.api_version = api_version
-
-
-# Monkey patching langchain
-# pylint: disable=protected-access
-ChatOpenAI._generate = _wrap(ChatOpenAI._generate, _set_credentials)  # type: ignore
-ChatOpenAI._agenerate = _async_wrap(ChatOpenAI._agenerate, _set_credentials)  # type: ignore
-BaseOpenAI._generate = _wrap(BaseOpenAI._generate, _set_credentials)  # type: ignore
-BaseOpenAI._agenerate = _async_wrap(BaseOpenAI._agenerate, _set_credentials)  # type: ignore
-# pylint: enable=protected-access
-
-#########################################################################
-# Monkey patching end                                                   #
-#########################################################################
-
-
-def _use_azure_credentials():
-    openai.api_type = "azure"
-    openai.api_key = os.environ.get("LLM_AZURE_OPENAI_API_KEY")
-    openai.api_base = os.environ.get("LLM_AZURE_OPENAI_API_BASE")
-    # os.environ.get("LLM_AZURE_OPENAI_API_VERSION")
-    openai.api_version = "2023-03-15-preview"
-
-
-def _use_openai_credentials():
-    openai.api_type = "open_ai"
-    openai.api_key = os.environ.get("LLM_OPENAI_API_KEY")
-    openai.api_base = "https://api.openai.com/v1"
-    openai.api_version = None
-
-
-openai_available = bool(os.environ.get("LLM_OPENAI_API_KEY"))
-azure_openai_available = bool(os.environ.get("LLM_AZURE_OPENAI_API_KEY"))
-
-
-# This is a hack to make sure that the openai api is set correctly
-# Right now it is overkill, but it will be useful when the api gets fixed and we no longer
-# hardcode the model names (i.e. OpenAI fixes their api)
-@contextmanager
-def _openai_client(use_azure_api: bool, is_preference: bool):
-    """Set the openai client to use the correct api type, if available
-
-    Args:
-        use_azure_api (bool): If true, use the azure api, else use the openai api
-        is_preference (bool): If true, it can fall back to the other api if the preferred one is not available
-    """
-    if use_azure_api:
-        if azure_openai_available:
-            _use_azure_credentials()
-        elif is_preference and openai_available:
-            _use_openai_credentials()
-        elif is_preference:
-            raise EnvironmentError(
-                "No OpenAI api available, please set LLM_AZURE_OPENAI_API_KEY, LLM_AZURE_OPENAI_API_BASE and "
-                "LLM_AZURE_OPENAI_API_VERSION environment variables or LLM_OPENAI_API_KEY environment variable"
-            )
-        else:
-            raise EnvironmentError(
-                "Azure OpenAI api not available, please set LLM_AZURE_OPENAI_API_KEY, LLM_AZURE_OPENAI_API_BASE and "
-                "LLM_AZURE_OPENAI_API_VERSION environment variables"
-            )
-    else:
-        if openai_available:
-            _use_openai_credentials()
-        elif is_preference and azure_openai_available:
-            _use_azure_credentials()
-        elif is_preference:
-            raise EnvironmentError(
-                "No OpenAI api available, please set LLM_OPENAI_API_KEY environment variable or LLM_AZURE_OPENAI_API_KEY, "
-                "LLM_AZURE_OPENAI_API_BASE and LLM_AZURE_OPENAI_API_VERSION environment variables"
-            )
-        else:
-            raise EnvironmentError(
-                "OpenAI api not available, please set LLM_OPENAI_API_KEY environment variable"
-            )
-
-    # API client is setup correctly
-    yield
-
-
-def _get_available_deployments(openai_models: Dict[str, List[str]], model_aliases: Dict[str, str]):
-    available_deployments: Dict[str, Dict[str, Any]] = {
-        "chat_completion": {},
-        "completion": {},
-        "fine_tuneing": {},
-    }
-
-    if azure_openai_available:
-        with _openai_client(use_azure_api=True, is_preference=False):
-            deployments = openai.Deployment.list().get("data") or []  # type: ignore
-            for deployment in deployments:
-                model_name = deployment.model
-                if model_name in model_aliases:
-                    model_name = model_aliases[model_name]
-                if model_name in openai_models["chat_completion"]:
-                    available_deployments["chat_completion"][deployment.id] = deployment
-                elif model_name in openai_models["completion"]:
-                    available_deployments["completion"][deployment.id] = deployment
-                elif model_name in openai_models["fine_tuneing"]:
-                    available_deployments["fine_tuneing"][deployment.id] = deployment
-
-    return available_deployments
-
-
-def _get_available_models(openai_models: Dict[str, List[str]], 
-                          available_deployments: Dict[str, Dict[str, Any]]):
-    available_models: Dict[str, BaseLanguageModel] = {}
-
-    if openai_available:
-        openai_api_key = os.environ["LLM_OPENAI_API_KEY"]
-        for model_name in openai_models["chat_completion"]:
-            available_models[OPENAI_PREFIX + model_name] = ChatOpenAI(
-                model=model_name,
-                openai_api_key=openai_api_key,
-                client="",
-                temperature=0
-            )
-        for model_name in openai_models["completion"]:
-            available_models[OPENAI_PREFIX + model_name] = OpenAI(
-                model=model_name,
-                openai_api_key=openai_api_key,
-                client="",
-                temperature=0
-            )
-
-    if azure_openai_available:
-        azure_openai_api_key = os.environ["LLM_AZURE_OPENAI_API_KEY"]
-        azure_openai_api_base = os.environ["LLM_AZURE_OPENAI_API_BASE"]
-        azure_openai_api_version = os.environ["LLM_AZURE_OPENAI_API_VERSION"]
-
-        for model_type, Model in [("chat_completion", AzureChatOpenAI), ("completion", AzureOpenAI)]:
-            for deployment_name, deployment in available_deployments[model_type].items():
-                available_models[AZURE_OPENAI_PREFIX + deployment_name] = Model(
-                    model=deployment.model,
-                    deployment_name=deployment_name,
-                    openai_api_base=azure_openai_api_base,
-                    openai_api_version=azure_openai_api_version,
-                    openai_api_key=azure_openai_api_key,
-                    client="",
-                    temperature=0
-                )
-
-    return available_models
-
-
-_model_aliases = {
-    "gpt-35-turbo": "gpt-3.5-turbo",
-}
-
-# Hardcoded because openai can't provide a trustworthly api to get the list of models and capabilities...
-openai_models = {
-    "chat_completion": [
-        "gpt-4",
-        # "gpt-4-32k", # Not publicly available
-        "gpt-3.5-turbo",
-        "gpt-3.5-turbo-16k"
-    ],
-    "completion": [
-        "text-davinci-003",
-        "text-curie-001",
-        "text-babbage-001",
-        "text-ada-001",
-    ],
-    "fine_tuneing": [
-        "davinci",
-        "curie",
-        "babbage",
-        "ada",
-    ]
-}
-available_deployments = _get_available_deployments(openai_models, _model_aliases)
-available_models = _get_available_models(openai_models, available_deployments)
-
+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] = {}
+
+if openai_available:
+    openai.api_type= "openai"
+    for model in openai.models.list():
+        if model.owned_by == "openai":
+            available_models[OPENAI_PREFIX + model.id] = ChatOpenAI(#type:ignore
+            model=model.id,
+        )
+
+if azure_openai_available:
+    # Will be replaced in the future
+    for deployment in os.environ['AZURE_DEPLOYMENTS'].split(','):
+                available_models[AZURE_OPENAI_PREFIX + deployment] = AzureChatOpenAI(deployment_name=deployment, temperature=0, client="")
+  
 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 = "gpt-3.5-turbo"
+    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]
-
+    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):
@@ -307,7 +97,7 @@ def get_model(self) -> BaseLanguageModel:
                 BaseLanguageModel: The model.
             """
             model = available_models[self.model_name.value]
-            kwargs = model._lc_kwargs
+            kwargs = model.__dict__
             secrets = {secret: getattr(model, secret) for secret in model.lc_secrets.keys()}
             kwargs.update(secrets)
 
diff --git a/module_text_llm/module_text_llm/helpers/models/replicate.py b/module_text_llm/module_text_llm/helpers/models/replicate.py
deleted file mode 100644
index 4941a46a..00000000
--- a/module_text_llm/module_text_llm/helpers/models/replicate.py
+++ /dev/null
@@ -1,116 +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",
-}
-
-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/module_text_llm/poetry.lock b/module_text_llm/poetry.lock
index 31187894..4dd126d4 100644
--- a/module_text_llm/poetry.lock
+++ b/module_text_llm/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
 
 [[package]]
 name = "aiohttp"
@@ -347,6 +347,17 @@ files = [
 [package.extras]
 graph = ["objgraph (>=1.7.2)"]
 
+[[package]]
+name = "distro"
+version = "1.9.0"
+description = "Distro - an OS platform information API"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "distro-1.9.0-py3-none-any.whl", hash = "sha256:7bffd925d65168f85027d8da9af6bddab658135b840670a223589bc0c8ef02b2"},
+    {file = "distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed"},
+]
+
 [[package]]
 name = "dodgy"
 version = "0.2.1"
@@ -699,106 +710,113 @@ files = [
 
 [[package]]
 name = "langchain"
-version = "0.0.350"
+version = "0.2.11"
 description = "Building applications with LLMs through composability"
 optional = false
-python-versions = ">=3.8.1,<4.0"
+python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain-0.0.350-py3-none-any.whl", hash = "sha256:11b605f325a4271a7815baaec05bc7622e3ad1f10f26b05c752cafa27663ed38"},
-    {file = "langchain-0.0.350.tar.gz", hash = "sha256:f0e68a92d200bb722586688ab7b411b2430bd98ad265ca03b264e7e7acbb6c01"},
+    {file = "langchain-0.2.11-py3-none-any.whl", hash = "sha256:5a7a8b4918f3d3bebce9b4f23b92d050699e6f7fb97591e8941177cf07a260a2"},
+    {file = "langchain-0.2.11.tar.gz", hash = "sha256:d7a9e4165f02dca0bd78addbc2319d5b9286b5d37c51d784124102b57e9fd297"},
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 [package.dependencies]
 aiohttp = ">=3.8.3,<4.0.0"
-dataclasses-json = ">=0.5.7,<0.7"
-jsonpatch = ">=1.33,<2.0"
-langchain-community = ">=0.0.2,<0.1"
-langchain-core = ">=0.1,<0.2"
-langsmith = ">=0.0.63,<0.1.0"
-numpy = ">=1,<2"
+langchain-core = ">=0.2.23,<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\""}
 pydantic = ">=1,<3"
 PyYAML = ">=5.3"
 requests = ">=2,<3"
 SQLAlchemy = ">=1.4,<3"
-tenacity = ">=8.1.0,<9.0.0"
-
-[package.extras]
-azure = ["azure-ai-formrecognizer (>=3.2.1,<4.0.0)", "azure-ai-textanalytics (>=5.3.0,<6.0.0)", "azure-ai-vision (>=0.11.1b1,<0.12.0)", "azure-cognitiveservices-speech (>=1.28.0,<2.0.0)", "azure-core (>=1.26.4,<2.0.0)", "azure-cosmos (>=4.4.0b1,<5.0.0)", "azure-identity (>=1.12.0,<2.0.0)", "azure-search-documents (==11.4.0b8)", "openai (<2)"]
-clarifai = ["clarifai (>=9.1.0)"]
-cli = ["typer (>=0.9.0,<0.10.0)"]
-cohere = ["cohere (>=4,<5)"]
-docarray = ["docarray[hnswlib] (>=0.32.0,<0.33.0)"]
-embeddings = ["sentence-transformers (>=2,<3)"]
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-javascript = ["esprima (>=4.0.1,<5.0.0)"]
-llms = ["clarifai (>=9.1.0)", "cohere (>=4,<5)", "huggingface_hub (>=0,<1)", "manifest-ml (>=0.0.1,<0.0.2)", "nlpcloud (>=1,<2)", "openai (<2)", "openlm (>=0.0.5,<0.0.6)", "torch (>=1,<3)", "transformers (>=4,<5)"]
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-qdrant = ["qdrant-client (>=1.3.1,<2.0.0)"]
-text-helpers = ["chardet (>=5.1.0,<6.0.0)"]
+tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
 
 [[package]]
 name = "langchain-community"
-version = "0.0.13"
+version = "0.2.10"
 description = "Community contributed LangChain integrations."
 optional = false
-python-versions = ">=3.8.1,<4.0"
+python-versions = "<4.0,>=3.8.1"
 files = [
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+    {file = "langchain_community-0.2.10-py3-none-any.whl", hash = "sha256:9f4d1b5ab7f0b0a704f538e26e50fce45a461da6d2bf6b7b636d24f22fbc088a"},
+    {file = "langchain_community-0.2.10.tar.gz", hash = "sha256:3a0404bad4bd07d6f86affdb62fb3d080a456c66191754d586a409d9d6024d62"},
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+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,<9.0.0"
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+tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
 
 [[package]]
 name = "langchain-core"
-version = "0.1.12"
+version = "0.2.25"
 description = "Building applications with LLMs through composability"
 optional = false
-python-versions = ">=3.8.1,<4.0"
+python-versions = "<4.0,>=3.8.1"
 files = [
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-packaging = ">=23.2,<24.0"
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+packaging = ">=23.2,<25"
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 PyYAML = ">=5.3"
-requests = ">=2,<3"
-tenacity = ">=8.1.0,<9.0.0"
+tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
 
-[package.extras]
-extended-testing = ["jinja2 (>=3,<4)"]
+[[package]]
+name = "langchain-openai"
+version = "0.1.19"
+description = "An integration package connecting OpenAI and LangChain"
+optional = false
+python-versions = "<4.0,>=3.8.1"
+files = [
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+    {file = "langchain_openai-0.1.19.tar.gz", hash = "sha256:3bf342bb302d1444f4abafdf01c467dbd9b248497e1133808c4bae70396c79b3"},
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+[package.dependencies]
+langchain-core = ">=0.2.24,<0.3.0"
+openai = ">=1.32.0,<2.0.0"
+tiktoken = ">=0.7,<1"
+
+[[package]]
+name = "langchain-text-splitters"
+version = "0.2.2"
+description = "LangChain text splitting utilities"
+optional = false
+python-versions = "<4.0,>=3.8.1"
+files = [
+    {file = "langchain_text_splitters-0.2.2-py3-none-any.whl", hash = "sha256:1c80d4b11b55e2995f02d2a326c0323ee1eeff24507329bb22924e420c782dff"},
+    {file = "langchain_text_splitters-0.2.2.tar.gz", hash = "sha256:a1e45de10919fa6fb080ef0525deab56557e9552083600455cb9fa4238076140"},
+]
+
+[package.dependencies]
+langchain-core = ">=0.2.10,<0.3.0"
 
 [[package]]
 name = "langsmith"
-version = "0.0.63"
+version = "0.1.94"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
-python-versions = ">=3.8.1,<4.0"
+python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langsmith-0.0.63-py3-none-any.whl", hash = "sha256:43a521dd10d8405ac21a0b959e3de33e2270e4abe6c73cc4036232a6990a0793"},
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+    {file = "langsmith-0.1.94-py3-none-any.whl", hash = "sha256:0d01212086d58699f75814117b026784218042f7859877ce08a248a98d84aa8d"},
+    {file = "langsmith-0.1.94.tar.gz", hash = "sha256:e44afcdc9eee6f238f6a87a02bba83111bd5fad376d881ae299834e06d39d712"},
 ]
 
 [package.dependencies]
-pydantic = ">=1,<3"
+orjson = ">=3.9.14,<4.0.0"
+pydantic = {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""}
 requests = ">=2,<3"
 
 [[package]]
@@ -1085,25 +1103,86 @@ files = [
 
 [[package]]
 name = "openai"
-version = "0.27.10"
-description = "Python client library for the OpenAI API"
+version = "1.37.1"
+description = "The official Python library for the openai API"
 optional = false
 python-versions = ">=3.7.1"
 files = [
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+    {file = "openai-1.37.1-py3-none-any.whl", hash = "sha256:9a6adda0d6ae8fce02d235c5671c399cfa40d6a281b3628914c7ebf244888ee3"},
+    {file = "openai-1.37.1.tar.gz", hash = "sha256:faf87206785a6b5d9e34555d6a3242482a6852bc802e453e2a891f68ee04ce55"},
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 [package.dependencies]
-aiohttp = "*"
-requests = ">=2.20"
-tqdm = "*"
+anyio = ">=3.5.0,<5"
+distro = ">=1.7.0,<2"
+httpx = ">=0.23.0,<1"
+pydantic = ">=1.9.0,<3"
+sniffio = "*"
+tqdm = ">4"
+typing-extensions = ">=4.7,<5"
 
 [package.extras]
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-dev = ["black (>=21.6b0,<22.0)", "pytest (==6.*)", "pytest-asyncio", "pytest-mock"]
-embeddings = ["matplotlib", "numpy", "openpyxl (>=3.0.7)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)", "plotly", "scikit-learn (>=1.0.2)", "scipy", "tenacity (>=8.0.1)"]
-wandb = ["numpy", "openpyxl (>=3.0.7)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)", "wandb"]
+datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"]
+
+[[package]]
+name = "orjson"
+version = "3.10.6"
+description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "orjson-3.10.6-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:fb0ee33124db6eaa517d00890fc1a55c3bfe1cf78ba4a8899d71a06f2d6ff5c7"},
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 name = "packaging"
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-
-[package.extras]
-dev = ["black", "mypy", "pytest", "responses", "ruff"]
-
 [[package]]
 name = "requests"
 version = "2.31.0"
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+    {file = "tiktoken-0.7.0-cp311-cp311-win_amd64.whl", hash = "sha256:959d993749b083acc57a317cbc643fb85c014d055b2119b739487288f4e5d1cb"},
+    {file = "tiktoken-0.7.0-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:71c55d066388c55a9c00f61d2c456a6086673ab7dec22dd739c23f77195b1908"},
+    {file = "tiktoken-0.7.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:09ed925bccaa8043e34c519fbb2f99110bd07c6fd67714793c21ac298e449410"},
+    {file = "tiktoken-0.7.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:03c6c40ff1db0f48a7b4d2dafeae73a5607aacb472fa11f125e7baf9dce73704"},
+    {file = "tiktoken-0.7.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d20b5c6af30e621b4aca094ee61777a44118f52d886dbe4f02b70dfe05c15350"},
+    {file = "tiktoken-0.7.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:d427614c3e074004efa2f2411e16c826f9df427d3c70a54725cae860f09e4bf4"},
+    {file = "tiktoken-0.7.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:8c46d7af7b8c6987fac9b9f61041b452afe92eb087d29c9ce54951280f899a97"},
+    {file = "tiktoken-0.7.0-cp312-cp312-win_amd64.whl", hash = "sha256:0bc603c30b9e371e7c4c7935aba02af5994a909fc3c0fe66e7004070858d3f8f"},
+    {file = "tiktoken-0.7.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:2398fecd38c921bcd68418675a6d155fad5f5e14c2e92fcf5fe566fa5485a858"},
+    {file = "tiktoken-0.7.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:8f5f6afb52fb8a7ea1c811e435e4188f2bef81b5e0f7a8635cc79b0eef0193d6"},
+    {file = "tiktoken-0.7.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:861f9ee616766d736be4147abac500732b505bf7013cfaf019b85892637f235e"},
+    {file = "tiktoken-0.7.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:54031f95c6939f6b78122c0aa03a93273a96365103793a22e1793ee86da31685"},
+    {file = "tiktoken-0.7.0-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:fffdcb319b614cf14f04d02a52e26b1d1ae14a570f90e9b55461a72672f7b13d"},
+    {file = "tiktoken-0.7.0-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:c72baaeaefa03ff9ba9688624143c858d1f6b755bb85d456d59e529e17234769"},
+    {file = "tiktoken-0.7.0-cp38-cp38-win_amd64.whl", hash = "sha256:131b8aeb043a8f112aad9f46011dced25d62629091e51d9dc1adbf4a1cc6aa98"},
+    {file = "tiktoken-0.7.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:cabc6dc77460df44ec5b879e68692c63551ae4fae7460dd4ff17181df75f1db7"},
+    {file = "tiktoken-0.7.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:8d57f29171255f74c0aeacd0651e29aa47dff6f070cb9f35ebc14c82278f3b25"},
+    {file = "tiktoken-0.7.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2ee92776fdbb3efa02a83f968c19d4997a55c8e9ce7be821ceee04a1d1ee149c"},
+    {file = "tiktoken-0.7.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e215292e99cb41fbc96988ef62ea63bb0ce1e15f2c147a61acc319f8b4cbe5bf"},
+    {file = "tiktoken-0.7.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:8a81bac94769cab437dd3ab0b8a4bc4e0f9cf6835bcaa88de71f39af1791727a"},
+    {file = "tiktoken-0.7.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:d6d73ea93e91d5ca771256dfc9d1d29f5a554b83821a1dc0891987636e0ae226"},
+    {file = "tiktoken-0.7.0-cp39-cp39-win_amd64.whl", hash = "sha256:2bcb28ddf79ffa424f171dfeef9a4daff61a94c631ca6813f43967cb263b83b9"},
+    {file = "tiktoken-0.7.0.tar.gz", hash = "sha256:1077266e949c24e0291f6c350433c6f0971365ece2b173a23bc3b9f9defef6b6"},
 ]
 
 [package.dependencies]
@@ -2115,4 +2182,4 @@ multidict = ">=4.0"
 [metadata]
 lock-version = "2.0"
 python-versions = "3.11.*"
-content-hash = "fc546e1b84d0435bf224a6a0d311171d6b40c44722c5c690c21f920a476976cb"
+content-hash = "255d802caecee7e3b501e69124430d49a40fe1f7dfcad49f6a03921a317a4143"
diff --git a/module_text_llm/pyproject.toml b/module_text_llm/pyproject.toml
index 76fcab84..b513b71e 100644
--- a/module_text_llm/pyproject.toml
+++ b/module_text_llm/pyproject.toml
@@ -6,16 +6,16 @@ authors = ["Felix Dietrich <felixtj.dietrich@tum.de>"]
 license = "MIT"
 
 [tool.poetry.dependencies]
-python = "3.11.*"
 athena = {path = "../athena", develop = true}
-openai = "^0.27.8"
-langchain = "^0.0.350"
-python-dotenv = "^1.0.0"
-nltk = "^3.8.1"
-gitpython = "^3.1.41"
-replicate = "^0.11.0"
-tiktoken = "^0.4.0"
-langsmith = "^0.0.63"
+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 = "3.11.*"
+python-dotenv = "1.0.0"
+tiktoken = "0.7.0"
 
 [tool.poetry.scripts]
 module = "athena:run_module"