diff --git a/assessment_module_manager/assessment_module_manager/endpoints/health_endpoint.py b/assessment_module_manager/assessment_module_manager/endpoints/health_endpoint.py index effdf9267..2b9cfb60c 100644 --- a/assessment_module_manager/assessment_module_manager/endpoints/health_endpoint.py +++ b/assessment_module_manager/assessment_module_manager/endpoints/health_endpoint.py @@ -29,7 +29,7 @@ class HealthResponse(BaseModel): and whether all the modules are healthy (i.e. reachable). Additional information about the modules is also provided. """ - status: str = Field(const=True, default="ok", example="ok") + status: str = Field(Literal=True, default="ok", example="ok") modules: dict = Field( example=[ { diff --git a/athena-workspace.code-workspace b/athena-workspace.code-workspace index 49b528cf6..7e781f29d 100644 --- a/athena-workspace.code-workspace +++ b/athena-workspace.code-workspace @@ -33,6 +33,7 @@ ], "settings": { "python.linting.prospectorEnabled": true, - "python.linting.mypyEnabled": true + "python.linting.mypyEnabled": true, + "liveServer.settings.multiRootWorkspaceName": "Athena" } } diff --git a/athena/athena/schemas/exercise.py b/athena/athena/schemas/exercise.py index 1f173e2e3..4cb2b1d3e 100644 --- a/athena/athena/schemas/exercise.py +++ b/athena/athena/schemas/exercise.py @@ -29,4 +29,5 @@ class Exercise(Schema, ABC): meta: dict = Field({}, example={"internal_id": "5"}) class Config: + from_attributes=True orm_mode = True diff --git a/athena/athena/schemas/feedback.py b/athena/athena/schemas/feedback.py index 4cf9c6a2e..2c25d310b 100644 --- a/athena/athena/schemas/feedback.py +++ b/athena/athena/schemas/feedback.py @@ -33,4 +33,5 @@ def to_model(self, is_suggestion: bool = False, lms_id: Optional[int] = None, lm return type(self).get_model_class()(**self.dict(), is_suggestion=is_suggestion, lms_id=lms_id, lms_url=lms_url) class Config: + from_attributes=True orm_mode = True diff --git a/athena/athena/schemas/modeling_exercise.py b/athena/athena/schemas/modeling_exercise.py index 70452f839..c3e34469a 100644 --- a/athena/athena/schemas/modeling_exercise.py +++ b/athena/athena/schemas/modeling_exercise.py @@ -8,6 +8,6 @@ class ModelingExercise(Exercise): """A modeling exercise that can be solved by students, enhanced with metadata.""" - type: ExerciseType = Field(ExerciseType.modeling, const=True) + type: ExerciseType = Field(ExerciseType.modeling, Literal=True) example_solution: Optional[str] = Field(None, description="An example solution to the exercise.") diff --git a/athena/athena/schemas/programming_exercise.py b/athena/athena/schemas/programming_exercise.py index ac875b05d..d214c1bbf 100644 --- a/athena/athena/schemas/programming_exercise.py +++ b/athena/athena/schemas/programming_exercise.py @@ -1,4 +1,4 @@ -from pydantic import Field, AnyUrl +from pydantic import Field, HttpUrl from zipfile import ZipFile from git.repo import Repo @@ -10,16 +10,16 @@ class ProgrammingExercise(Exercise): """A programming exercise that can be solved by students, enhanced with metadata.""" - type: ExerciseType = Field(ExerciseType.programming, const=True) + type: ExerciseType = Field(ExerciseType.programming, Literal=True) programming_language: str = Field(description="The programming language that is used for this exercise.", example="java") - solution_repository_uri: AnyUrl = Field(description="URL to the solution git repository, which contains the " + solution_repository_uri: str = Field(description="URL to the solution git repository, which contains the " "reference solution.", example="http://localhost:3000/api/example-solutions/1") - template_repository_uri: AnyUrl = Field(description="URL to the template git repository, which is the starting " + template_repository_uri: str = Field(description="URL to the template git repository, which is the starting " "point for students.", example="http://localhost:3000/api/example-template/1") - tests_repository_uri: AnyUrl = Field(description="URL to the tests git repository, which contains the tests that " + tests_repository_uri: str = Field(description="URL to the tests git repository, which contains the tests that " "are used to automatically grade the exercise.", example="http://localhost:3000/api/example-tests/1") diff --git a/athena/athena/schemas/schema.py b/athena/athena/schemas/schema.py index 67e146ada..72fa0dee1 100644 --- a/athena/athena/schemas/schema.py +++ b/athena/athena/schemas/schema.py @@ -8,9 +8,8 @@ # https://stackoverflow.com/a/42450252/4306257 def to_camel(snake_str): - first, *others = snake_str.split('_') - return ''.join([first.lower(), *map(str.title, others)]) - + first, *others = snake_str.split('_') + return ''.join([first.lower(), *map(str.title, others)]) class Schema(BaseModel, abc.ABC): @classmethod @@ -32,4 +31,4 @@ def to_model(self): class Config: # Allow camelCase field names in the API (converted to snake_case) alias_generator = to_camel - allow_population_by_field_name = True \ No newline at end of file + populate_by_name = True \ No newline at end of file diff --git a/athena/athena/schemas/submission.py b/athena/athena/schemas/submission.py index f9e39c372..93898c1aa 100644 --- a/athena/athena/schemas/submission.py +++ b/athena/athena/schemas/submission.py @@ -12,4 +12,5 @@ class Submission(Schema, ABC): meta: dict = Field({}, example={}) class Config: + from_attributes=True orm_mode = True diff --git a/athena/athena/schemas/text_exercise.py b/athena/athena/schemas/text_exercise.py index 6c8367667..ac3861a70 100644 --- a/athena/athena/schemas/text_exercise.py +++ b/athena/athena/schemas/text_exercise.py @@ -8,6 +8,6 @@ class TextExercise(Exercise): """A text exercise that can be solved by students, enhanced with metadata.""" - type: ExerciseType = Field(ExerciseType.text, const=True) + type: ExerciseType = Field(ExerciseType.text, Literal=True) example_solution: Optional[str] = Field(None, description="An example solution to the exercise.") diff --git a/module_modeling_llm/module_modeling_llm/config.py b/module_modeling_llm/module_modeling_llm/config.py index 738c72bab..6bdfba081 100644 --- a/module_modeling_llm/module_modeling_llm/config.py +++ b/module_modeling_llm/module_modeling_llm/config.py @@ -1,7 +1,7 @@ from pydantic import BaseModel, Field from athena import config_schema_provider -from module_modeling_llm.helpers.models import ModelConfigType, DefaultModelConfig +from shared_llm.helpers.models import ModelConfigType, DefaultModelConfig from module_modeling_llm.prompts.generate_suggestions import ( system_message as generate_suggestions_system_message, human_message as generate_suggestions_human_message diff --git a/module_modeling_llm/module_modeling_llm/generate_suggestions.py b/module_modeling_llm/module_modeling_llm/generate_suggestions.py index 21c9eaf7c..463738d90 100644 --- a/module_modeling_llm/module_modeling_llm/generate_suggestions.py +++ b/module_modeling_llm/module_modeling_llm/generate_suggestions.py @@ -7,15 +7,15 @@ from athena.logger import logger from athena.modeling import Exercise, Submission, Feedback from module_modeling_llm.config import BasicApproachConfig -from module_modeling_llm.helpers.llm_utils import ( +from shared_llm.helpers.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 module_modeling_llm.helpers.models.diagram_types import DiagramType -from module_modeling_llm.helpers.serializers.diagram_model_serializer import DiagramModelSerializer -from module_modeling_llm.helpers.utils import format_grading_instructions, get_elements +from shared_llm.helpers.models.diagram_types import DiagramType +from shared_llm.helpers.serializers.diagram_model_serializer import DiagramModelSerializer +from shared_llm.helpers.modeling_utils import format_grading_instructions, get_elements from module_modeling_llm.prompts.submission_format.submission_format_remarks import get_submission_format_remarks diff --git a/module_modeling_llm/module_modeling_llm/helpers/llm_utils.py b/module_modeling_llm/module_modeling_llm/helpers/llm_utils.py deleted file mode 100644 index 7cbf026f6..000000000 --- a/module_modeling_llm/module_modeling_llm/helpers/llm_utils.py +++ /dev/null @@ -1,163 +0,0 @@ -from typing import Optional, Type, TypeVar, List - -import tiktoken -from langchain.base_language import BaseLanguageModel -from langchain.chains import LLMChain -from langchain.chains.openai_functions import create_structured_output_chain -from langchain.chat_models import ChatOpenAI -from langchain.output_parsers import PydanticOutputParser -from langchain.prompts import ( - ChatPromptTemplate, - SystemMessagePromptTemplate, - HumanMessagePromptTemplate, -) -from langchain.schema import OutputParserException -from pydantic import BaseModel, ValidationError - -from athena import emit_meta, get_experiment_environment - -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 isinstance(model, ChatOpenAI) - - -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 - """ - 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 diff --git a/module_modeling_llm/module_modeling_llm/helpers/models/__init__.py b/module_modeling_llm/module_modeling_llm/helpers/models/__init__.py deleted file mode 100644 index ce987b33b..000000000 --- a/module_modeling_llm/module_modeling_llm/helpers/models/__init__.py +++ /dev/null @@ -1,40 +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/module_modeling_llm/module_modeling_llm/helpers/models/model_config.py b/module_modeling_llm/module_modeling_llm/helpers/models/model_config.py deleted file mode 100644 index 44bccaf29..000000000 --- a/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/module_modeling_llm/module_modeling_llm/helpers/models/openai.py b/module_modeling_llm/module_modeling_llm/helpers/models/openai.py deleted file mode 100644 index fec3d2fa2..000000000 --- a/module_modeling_llm/module_modeling_llm/helpers/models/openai.py +++ /dev/null @@ -1,338 +0,0 @@ -import os -from contextlib import contextmanager -from enum import Enum -from typing import Any, Callable, Dict, List - -import openai -from langchain.base_language import BaseLanguageModel -from langchain.chat_models import AzureChatOpenAI, ChatOpenAI -from langchain.llms import AzureOpenAI, OpenAI -from langchain.llms.openai import BaseOpenAI -from pydantic import Field, validator, PositiveInt - -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")) - -print("azure_openai_available", azure_openai_available) - - -# 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) - -print("available_models", available_models) - -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" - 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] - - - # 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._lc_kwargs - 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' diff --git a/module_modeling_llm/module_modeling_llm/helpers/serializers/__init__.py b/module_modeling_llm/module_modeling_llm/helpers/serializers/__init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/module_modeling_llm/module_modeling_llm/prompts/submission_format/submission_format_remarks.py b/module_modeling_llm/module_modeling_llm/prompts/submission_format/submission_format_remarks.py index 068739eb7..b90568225 100644 --- a/module_modeling_llm/module_modeling_llm/prompts/submission_format/submission_format_remarks.py +++ b/module_modeling_llm/module_modeling_llm/prompts/submission_format/submission_format_remarks.py @@ -1,4 +1,4 @@ -from module_modeling_llm.helpers.models.diagram_types import DiagramType +from shared_llm.helpers.models.diagram_types import DiagramType from module_modeling_llm.prompts.submission_format.bpmn import \ submission_format_remarks as bpmn_submission_format_remarks from module_modeling_llm.prompts.submission_format.general import \ diff --git a/module_modeling_llm/poetry.lock b/module_modeling_llm/poetry.lock index 5b9fa7acb..c91837d5e 100644 --- a/module_modeling_llm/poetry.lock +++ b/module_modeling_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" @@ -699,56 +710,115 @@ files = [ [[package]] name = "langchain" -version = "0.0.334" +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-0.0.334-py3-none-any.whl", hash = "sha256:55532c7d717a3f2cbf0895e47818a84bb8750badc35131f2dd16ce06821d0486"}, - {file = "langchain-0.0.334.tar.gz", 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-tiktoken = "^0.4.0" -langsmith = "^0.0.63" +tiktoken = "^0.7.0" [tool.poetry.scripts] module = "athena:run_module" diff --git a/module_programming_llm/module_programming_llm/config.py b/module_programming_llm/module_programming_llm/config.py index 5edd58003..093c4a362 100644 --- a/module_programming_llm/module_programming_llm/config.py +++ b/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 shared_llm.helpers.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/module_programming_llm/module_programming_llm/generate_graded_suggestions_by_file.py b/module_programming_llm/module_programming_llm/generate_graded_suggestions_by_file.py index 1fe4dde47..ac6830a0f 100644 --- a/module_programming_llm/module_programming_llm/generate_graded_suggestions_by_file.py +++ b/module_programming_llm/module_programming_llm/generate_graded_suggestions_by_file.py @@ -13,13 +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 shared_llm.helpers.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 module_programming_llm.helpers.utils import ( +from shared_llm.helpers.programming_utils import ( get_diff, load_files_from_repo, add_line_numbers, diff --git a/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py b/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py index b857a24f4..f38b5faa3 100644 --- a/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py +++ b/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py @@ -11,13 +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 shared_llm.helpers.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 module_programming_llm.helpers.utils import ( +from shared_llm.helpers.programming_utils import ( get_diff, load_files_from_repo, add_line_numbers, diff --git a/module_programming_llm/module_programming_llm/generate_summary_by_file.py b/module_programming_llm/module_programming_llm/generate_summary_by_file.py index 144d750bf..31797ffea 100644 --- a/module_programming_llm/module_programming_llm/generate_summary_by_file.py +++ b/module_programming_llm/module_programming_llm/generate_summary_by_file.py @@ -9,12 +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 shared_llm.helpers.llm_utils import ( get_chat_prompt_with_formatting_instructions, num_tokens_from_prompt, predict_and_parse, ) -from module_programming_llm.helpers.utils import ( +from shared_llm.helpers.programming_utils import ( get_diff, load_files_from_repo, add_line_numbers diff --git a/module_programming_llm/module_programming_llm/helpers/models/__init__.py b/module_programming_llm/module_programming_llm/helpers/models/__init__.py index a5fdc01d0..0504481f3 100644 --- a/module_programming_llm/module_programming_llm/helpers/models/__init__.py +++ b/module_programming_llm/module_programming_llm/helpers/models/__init__.py @@ -1,6 +1,6 @@ import os from typing import Type, Union, List -from module_programming_llm.helpers.models.model_config import ModelConfig +from shared_llm.helpers.models.model_config import ModelConfig DefaultModelConfig: Type[ModelConfig] @@ -8,7 +8,7 @@ types: List[Type[ModelConfig]] = [] try: - import module_programming_llm.helpers.models.openai as openai_config + import shared_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 @@ -16,7 +16,7 @@ pass try: - import module_programming_llm.helpers.models.replicate as replicate_config + import shared_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 diff --git a/module_programming_llm/module_programming_llm/helpers/utils.py b/module_programming_llm/module_programming_llm/helpers/programming_utils.py similarity index 100% rename from module_programming_llm/module_programming_llm/helpers/utils.py rename to module_programming_llm/module_programming_llm/helpers/programming_utils.py diff --git a/module_programming_llm/module_programming_llm/split_grading_instructions_by_file.py b/module_programming_llm/module_programming_llm/split_grading_instructions_by_file.py index 0e402b378..422ceaa5e 100644 --- a/module_programming_llm/module_programming_llm/split_grading_instructions_by_file.py +++ b/module_programming_llm/module_programming_llm/split_grading_instructions_by_file.py @@ -8,13 +8,13 @@ from athena.programming import Exercise, Submission from module_programming_llm.config import GradedBasicApproachConfig -from module_programming_llm.helpers.llm_utils import ( +from shared_llm.helpers.llm_utils import ( get_chat_prompt_with_formatting_instructions, num_tokens_from_string, num_tokens_from_prompt, predict_and_parse ) -from module_programming_llm.helpers.utils import format_grading_instructions, get_diff +from shared_llm.helpers.programming_utils import format_grading_instructions, get_diff class FileGradingInstruction(BaseModel): diff --git a/module_programming_llm/module_programming_llm/split_problem_statement_by_file.py b/module_programming_llm/module_programming_llm/split_problem_statement_by_file.py index 46cd64bbb..84f9cd5de 100644 --- a/module_programming_llm/module_programming_llm/split_problem_statement_by_file.py +++ b/module_programming_llm/module_programming_llm/split_problem_statement_by_file.py @@ -8,13 +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 shared_llm.helpers.llm_utils import ( get_chat_prompt_with_formatting_instructions, num_tokens_from_string, num_tokens_from_prompt, predict_and_parse ) -from module_programming_llm.helpers.utils import get_diff +from shared_llm.helpers.programming_utils import get_diff class FileProblemStatement(BaseModel): diff --git a/module_programming_llm/poetry.lock b/module_programming_llm/poetry.lock index 5a4016ec9..e36c278a6 100644 --- a/module_programming_llm/poetry.lock +++ b/module_programming_llm/poetry.lock @@ -1,91 +1,118 @@ -# 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 = "aiohappyeyeballs" +version = "2.4.0" +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 = 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hash = "sha256:928cecb0ef9d5a7946eb6ff58417ad2fe9375762382f1bf5c55e61645f2c43ad"}, + {file = "yarl-1.9.4.tar.gz", hash = "sha256:566db86717cf8080b99b58b083b773a908ae40f06681e87e589a976faf8246bf"}, ] [package.dependencies] @@ -2210,4 +2370,4 @@ multidict = ">=4.0" [metadata] lock-version = "2.0" python-versions = "3.11.*" -content-hash = "93244b7fdfafdc95d776d56f4c8fb149d9e74905cc55998e902c17af7585ab2f" +content-hash = "19c6152a73aeac16b6b4bd93e39418edbe822801334c6ccce16552950f0dc6d4" diff --git a/module_programming_llm/pyproject.toml b/module_programming_llm/pyproject.toml index 0677a20e7..1038900f2 100644 --- a/module_programming_llm/pyproject.toml +++ b/module_programming_llm/pyproject.toml @@ -8,14 +8,11 @@ license = "MIT" [tool.poetry.dependencies] python = "3.11.*" athena = {path = "../athena", develop = true} -openai = "^0.27.8" -langchain = "^0.1.11" +shared_llm = {path = "../shared_llm", develop = true} gitpython = "^3.1.41" -tiktoken = "^0.4.0" promptlayer = "^0.1.85" python-dotenv = "^1.0.0" nltk = "^3.8.1" -replicate = "^0.11.0" [tool.poetry.scripts] module = "athena:run_module" diff --git a/module_text_llm/.env.example b/module_text_llm/.env.example index 34e279aab..8e5bdd94f 100644 --- a/module_text_llm/.env.example +++ b/module_text_llm/.env.example @@ -30,6 +30,7 @@ OPENAI_API_KEY="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" 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 +AZURE_DEPLOYMENTS=gpt-35-turbo,gpt-4-turbo,gpt-4-vision,gpt-4o # LangSmith (can be used for tracing LLMs) [leave blank if not used] # See https://docs.smith.langchain.com @@ -37,3 +38,7 @@ OPENAI_API_VERSION="2024-06-01" # change base if needed # LANGCHAIN_ENDPOINT="https://api.smith.langchain.com" # LANGCHAIN_API_KEY="XXX" # LANGCHAIN_PROJECT="XXX" + +# GPU_USER= +# GPU_PASSWORD= +# OLLAMA_ENDPOINT= diff --git a/module_text_llm/module_text_llm/__init__.py b/module_text_llm/module_text_llm/__init__.py index 2f04ff661..2e2f5a8f9 100644 --- a/module_text_llm/module_text_llm/__init__.py +++ b/module_text_llm/module_text_llm/__init__.py @@ -1,4 +1,10 @@ import dotenv +import os # Load environment variables from .env file (for local development) -dotenv.load_dotenv(override=True) \ No newline at end of file +dotenv.load_dotenv(override=True) +# Assuming B is a sibling directory to A +# module_shared_llm_env_path = os.path.join(os.path.dirname(__file__), '..', 'shared_llm', '.env') + +# Load the .env file from module B +# dotenv.load_dotenv(module_shared_llm_env_path) \ No newline at end of file diff --git a/module_text_llm/module_text_llm/config.py b/module_text_llm/module_text_llm/config.py index 82d177eed..2e44911f6 100644 --- a/module_text_llm/module_text_llm/config.py +++ b/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 shared_llm.helpers.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/module_text_llm/module_text_llm/generate_evaluation.py b/module_text_llm/module_text_llm/generate_evaluation.py index 4c4a9969b..9705968f2 100644 --- a/module_text_llm/module_text_llm/generate_evaluation.py +++ b/module_text_llm/module_text_llm/generate_evaluation.py @@ -5,13 +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 shared_llm.helpers.models import evaluation_model +from shared_llm.helpers.llm_utils import ( get_chat_prompt_with_formatting_instructions, check_prompt_length_and_omit_features_if_necessary, predict_and_parse ) -from module_text_llm.helpers.utils import add_sentence_numbers, get_line_range_from_index_range +from shared_llm.helpers.text_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/module_text_llm/module_text_llm/generate_suggestions.py b/module_text_llm/module_text_llm/generate_suggestions.py index d43563ad6..87eee6be9 100644 --- a/module_text_llm/module_text_llm/generate_suggestions.py +++ b/module_text_llm/module_text_llm/generate_suggestions.py @@ -6,13 +6,13 @@ from athena.logger import logger from module_text_llm.config import BasicApproachConfig -from module_text_llm.helpers.llm_utils import ( +from shared_llm.helpers.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 module_text_llm.helpers.utils import add_sentence_numbers, get_index_range_from_line_range, format_grading_instructions +from shared_llm.helpers.text_utils import add_sentence_numbers, get_index_range_from_line_range, format_grading_instructions class FeedbackModel(BaseModel): title: str = Field(description="Very short title, i.e. feedback category or similar", example="Logic Error") diff --git a/module_text_llm/poetry.lock b/module_text_llm/poetry.lock index 4dd126d40..15169e8c6 100644 --- a/module_text_llm/poetry.lock +++ b/module_text_llm/poetry.lock @@ -1,91 +1,118 @@ # This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +[[package]] +name = "aiohappyeyeballs" +version = "2.4.0" +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 = 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[tool.poetry.dependencies] athena = {path = "../athena", develop = true} +shared_llm = {path = "../shared_llm", develop = true} 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" diff --git a/playground/package-lock.json b/playground/package-lock.json index 8a5bd8bf7..7f4175091 100644 --- a/playground/package-lock.json +++ b/playground/package-lock.json @@ -23,7 +23,6 @@ "jszip": "3.10.1", "monaco-editor": "0.44.0", "next": "14.1.1", - "postcss": "8.4.31", "react": "18.2.0", "react-complex-tree": "2.2.2", "react-complex-tree-blueprintjs-renderers": "2.2.2", diff --git a/shared_llm/.env.example b/shared_llm/.env.example new file mode 100644 index 000000000..8e5bdd94f --- /dev/null +++ b/shared_llm/.env.example @@ -0,0 +1,44 @@ +# 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-35-turbo" + +# 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) 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"255d802caecee7e3b501e69124430d49a40fe1f7dfcad49f6a03921a317a4143" diff --git a/shared_llm/pyproject.toml b/shared_llm/pyproject.toml new file mode 100644 index 000000000..babb70600 --- /dev/null +++ b/shared_llm/pyproject.toml @@ -0,0 +1,28 @@ +[tool.poetry] +name = "shared_llm" +version = "0.1.0" +description = "SHared LLM module." +authors = ["Felix Dietrich "] +license = "MIT" + +[tool.poetry.dependencies] +athena = {path = "../athena", develop = true} +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" + +[tool.poetry.group.dev.dependencies] +prospector = "^1.10.2" + +[build-system] +requires = ["poetry-core>=1.0.0"] +build-backend = "poetry.core.masonry.api" diff --git a/shared_llm/shared_llm/__init__.py b/shared_llm/shared_llm/__init__.py new file mode 100644 index 000000000..2f04ff661 --- /dev/null +++ b/shared_llm/shared_llm/__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/module_text_llm/module_text_llm/helpers/llm_utils.py b/shared_llm/shared_llm/helpers/llm_utils.py similarity index 100% rename from module_text_llm/module_text_llm/helpers/llm_utils.py rename to shared_llm/shared_llm/helpers/llm_utils.py diff --git a/module_modeling_llm/module_modeling_llm/helpers/utils.py b/shared_llm/shared_llm/helpers/modeling_utils.py similarity index 100% rename from module_modeling_llm/module_modeling_llm/helpers/utils.py rename to shared_llm/shared_llm/helpers/modeling_utils.py diff --git a/module_text_llm/module_text_llm/helpers/models/__init__.py b/shared_llm/shared_llm/helpers/models/__init__.py similarity index 77% rename from module_text_llm/module_text_llm/helpers/models/__init__.py rename to shared_llm/shared_llm/helpers/models/__init__.py index 85078d4d7..c679327d1 100644 --- a/module_text_llm/module_text_llm/helpers/models/__init__.py +++ b/shared_llm/shared_llm/helpers/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 shared_llm.helpers.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 shared_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 @@ -23,6 +23,13 @@ except AttributeError: pass +try: + import shared_llm.helpers.models.ollama as ollama_config #type: ignore + types.append(ollama_config.OllamaModelConfig) + # DefaultModelConfig = ollama_config.OllamaModelConfig +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_modeling_llm/module_modeling_llm/helpers/models/diagram_types.py b/shared_llm/shared_llm/helpers/models/diagram_types.py similarity index 100% rename from module_modeling_llm/module_modeling_llm/helpers/models/diagram_types.py rename to shared_llm/shared_llm/helpers/models/diagram_types.py diff --git a/module_text_llm/module_text_llm/helpers/models/model_config.py b/shared_llm/shared_llm/helpers/models/model_config.py similarity index 100% rename from module_text_llm/module_text_llm/helpers/models/model_config.py rename to shared_llm/shared_llm/helpers/models/model_config.py diff --git a/shared_llm/shared_llm/helpers/models/ollama.py b/shared_llm/shared_llm/helpers/models/ollama.py new file mode 100644 index 000000000..cca16c3fe --- /dev/null +++ b/shared_llm/shared_llm/helpers/models/ollama.py @@ -0,0 +1,115 @@ +import requests +from enum import Enum +from langchain_community.llms import Ollama # type: ignore +from shared_llm.helpers.models.model_config import ModelConfig # type: ignore +from pydantic import validator, Field, PositiveInt +from langchain.base_language import BaseLanguageModel +import os +from langchain_community.chat_models import ChatOllama # type: ignore +from athena.logger import logger + +if os.environ.get('GPU_USER') and os.environ.get('GPU_PASSWORD') and os.environ.get('OLLAMA_ENDPOINT') is not None: + + if(os.environ["GPU_USER"] and os.environ["GPU_PASSWORD"]): + auth_header= { + 'Authorization': requests.auth._basic_auth_str(os.environ["GPU_USER"],os.environ["GPU_PASSWORD"]) # type: ignore + } + + + def get_ollama_models(): + url = os.environ["OLLAMA_ENDPOINT"] + "/api/tags" + try: + response = requests.get(url, auth=(os.environ["GPU_USER"], os.environ["GPU_PASSWORD"])) + data = response.json() + model_list = [model['name'] for model in data['models']] + return model_list + except requests.exceptions.RequestException as e: + logger.info(f"Error occurred while retrieving models. GPU Server may not be available or your VPN might not be set up properly: {e}") + return [] + + ollama_models = get_ollama_models() + available_models = {} + + if(os.environ["OLLAMA_ENDPOINT"] and ollama_models): + available_models = { + name : ChatOllama( + name = name, + model = name, + base_url = os.environ["OLLAMA_ENDPOINT"], + headers = auth_header, + format = "json" + ) for name in ollama_models + } + + + + default_model_name = "llama3.1:70b" + LlamaModel = Enum('LlamaModel', {name: name for name in available_models}) # type: ignore + class OllamaModelConfig(ModelConfig): + """Ollama LLM configuration.""" + + model_name: LlamaModel = Field(default=default_model_name, # type: ignore + description="The name of the model to use.") + + fromat : str = Field(default = "json" , description="The format to respond with") + + max_tokens: PositiveInt = Field(1000, description="") + + temperature: float = Field(default=0.0, ge=0, le=2, description="") + + top_p: float = Field(default=1, ge=0, le=1, description="") + + headers : dict = Field(default= auth_header, description="headers for authentication") + + presence_penalty: float = Field(default=0, ge=-2, le=2, description="") + + frequency_penalty: float = Field(default=0, ge=-2, le=2, description="") + + base_url : str = Field(default="https://gpu-artemis.ase.cit.tum.de/ollama", description=" Base Url where ollama is hosted") + @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: + print("Getting Model: ", self.model_name.value) + """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 + + allowed_fields = set(self.__fields__.keys()) + filtered_kwargs = {k: v for k, v in kwargs.items() if k in allowed_fields} + filtered_kwargs["headers"] = auth_header + filtered_kwargs["model"]= self.model_name.value + + # Initialize a copy of the model using the filtered kwargs + model = model.__class__(**filtered_kwargs) + + return model + + + class Config: + title = 'Ollama' \ No newline at end of file diff --git a/module_text_llm/module_text_llm/helpers/models/openai.py b/shared_llm/shared_llm/helpers/models/openai.py similarity index 100% rename from module_text_llm/module_text_llm/helpers/models/openai.py rename to shared_llm/shared_llm/helpers/models/openai.py diff --git a/shared_llm/shared_llm/helpers/programming_utils.py b/shared_llm/shared_llm/helpers/programming_utils.py new file mode 100644 index 000000000..6f55670c4 --- /dev/null +++ b/shared_llm/shared_llm/helpers/programming_utils.py @@ -0,0 +1,140 @@ +import os + +from contextlib import contextmanager +from collections.abc import Iterator +from typing import List, Dict, Optional, Callable, Tuple + +from git import Remote +from git.repo import Repo +from langchain.document_loaders import GitLoader + +from athena import GradingCriterion + +def load_files_from_repo(repo: Repo, file_filter: Optional[Callable[[str], bool]] = None) -> Dict[str, str]: + return { + doc.metadata['file_path']: doc.page_content + for doc in GitLoader(repo_path=str(repo.working_tree_dir), file_filter=file_filter).load() + } + + +def merge_repos_by_filepath(*repos: Repo, file_filter: Optional[Callable[[str], bool]] = None) -> Iterator[Tuple[str, List[Optional[str]]]]: + docs = [load_files_from_repo(repo, file_filter) for repo in repos] + files = {file for doc in docs for file in doc} + + for file in files: + yield (file, [doc.get(file) for doc in docs]) + + +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 add_line_numbers(content: str) -> str: + lines = content.splitlines() + line_number_max_length = len(str(len(lines))) + return "\n".join( + f"{str(line_number).rjust(line_number_max_length)} {line}" + for line_number, line + in enumerate(lines) + ) + + +def get_programming_language_file_extension(programming_language: str) -> str | None: + # JAVA, C, OCAML, HASKELL, PYTHON, SWIFT, VHDL, ASSEMBLER, EMPTY, KOTLIN + file_extensions = { + "JAVA": ".java", + "C": ".c", + "OCAML": ".ml", + "HASKELL": ".hs", + "PYTHON": ".py", + "SWIFT": ".swift", + "VHDL": ".vhd", + "ASSEMBLER": ".asm", + "KOTLIN": ".kt", + } + return file_extensions.get(programming_language.upper()) + + +@contextmanager +def temporary_remote(remote_name: str, repo: Repo, remote_url: str) -> Iterator[Optional[Remote]]: + """Context manager for temporarily adding a remote to a Git repository. + + Args: + remote_name (str): The name of the remote + repo (Repo): The repository to add the remote to + remote_url (str): The URL of the remote + """ + try: + remote = repo.remote(remote_name) + yield remote + except ValueError: + remote = repo.create_remote(remote_name, remote_url) + remote.fetch() + yield remote + repo.delete_remote(remote) + + +def get_diff(src_repo: Repo, + dst_repo: Repo, + src_prefix: str = "a", + dst_prefix: str = "b", + file_path: Optional[str] = None, + name_only: bool = False, + branch: str = "main", + remote_name: str = "diff_target") -> str: + """Get the diff between two branches of two Git repositories. + + Args: + src_repo (Repo): Repository to diff from + dst_repo (Repo): Repository to diff to + src_prefix (str, optional): Prefix for the source files. Defaults to "a". + dst_prefix (str, optional): Prefix for the destination files. Defaults to "b". + file_path (Optional[str], optional): Path to the file(s), supports glob patterns. Defaults to None. + name_only (bool, optional): Only show names of changed files. Defaults to False. + branch (str, optional): Branch to diff. Defaults to "main". + remote_name (str, optional): Name of the remote to use. Defaults to "diff_target". + + Returns: + str: The diff between the two branches + """ + + # Check if we are diffing a specific file + if file_path is not None and "*" not in file_path: + specific_file_path = os.path.join(str(src_repo.working_tree_dir), file_path) + if not os.path.exists(specific_file_path): + # Change error from 'No such file or directory' to something more meaningful (non-standard diff output) + return f"- {src_prefix}/{file_path} does not exist.\n+ {dst_prefix}/{file_path} has been added." + + with temporary_remote(remote_name, src_repo, str(dst_repo.working_tree_dir)): + diff = src_repo.git.diff(branch, f"{remote_name}/{branch}", f"--src-prefix={src_prefix}/", f"--dst-prefix={dst_prefix}/", file_path, name_only=name_only) + return diff \ No newline at end of file diff --git a/module_modeling_llm/module_modeling_llm/helpers/__init__.py b/shared_llm/shared_llm/helpers/serializers/__init__.py similarity index 100% rename from module_modeling_llm/module_modeling_llm/helpers/__init__.py rename to shared_llm/shared_llm/helpers/serializers/__init__.py diff --git a/module_modeling_llm/module_modeling_llm/helpers/serializers/bpmn_serializer.py b/shared_llm/shared_llm/helpers/serializers/bpmn_serializer.py similarity index 100% rename from module_modeling_llm/module_modeling_llm/helpers/serializers/bpmn_serializer.py rename to shared_llm/shared_llm/helpers/serializers/bpmn_serializer.py diff --git a/module_modeling_llm/module_modeling_llm/helpers/serializers/diagram_model_serializer.py b/shared_llm/shared_llm/helpers/serializers/diagram_model_serializer.py similarity index 96% rename from module_modeling_llm/module_modeling_llm/helpers/serializers/diagram_model_serializer.py rename to shared_llm/shared_llm/helpers/serializers/diagram_model_serializer.py index 36e5dc42c..204a130bf 100644 --- a/module_modeling_llm/module_modeling_llm/helpers/serializers/diagram_model_serializer.py +++ b/shared_llm/shared_llm/helpers/serializers/diagram_model_serializer.py @@ -3,8 +3,8 @@ from xml.dom import minidom from xml.etree import ElementTree -from module_modeling_llm.helpers.models.diagram_types import DiagramType -from module_modeling_llm.helpers.serializers.bpmn_serializer import BPMNSerializer +from shared_llm.helpers.models.diagram_types import DiagramType +from shared_llm.helpers.serializers.bpmn_serializer import BPMNSerializer class DiagramModelSerializer: diff --git a/module_text_llm/module_text_llm/helpers/utils.py b/shared_llm/shared_llm/helpers/text_utils.py similarity index 100% rename from module_text_llm/module_text_llm/helpers/utils.py rename to shared_llm/shared_llm/helpers/text_utils.py