From 95211211ee204a62a90e460fdf11d1c23c3a542b Mon Sep 17 00:00:00 2001 From: Enea Gore <73840596+EneaGore@users.noreply.github.com> Date: Fri, 11 Oct 2024 16:42:14 +0200 Subject: [PATCH 1/5] Shared llm package refactoring (#336) Co-authored-by: = Enea_Gore --- .github/workflows/build.yml | 7 + assessment_module_manager/poetry.lock | 497 ++-- docker-compose.yml | 10 + modules/llm_core/.env.example | 39 + modules/llm_core/Dockerfile | 24 + modules/llm_core/llm_core/__init__.py | 4 + .../llm_core}/models/__init__.py | 7 +- .../llm_core}/models/callbacks.py | 0 .../llm_core}/models/model_config.py | 0 .../llm_core}/models/openai.py | 0 .../llm_core/utils}/llm_utils.py | 60 +- .../llm_core}/utils/predict_and_parse.py | 22 +- modules/llm_core/poetry.lock | 2471 +++++++++++++++++ modules/llm_core/pyproject.toml | 29 + .../modeling/module_modeling_llm/Dockerfile | 1 + .../module_modeling_llm/config.py | 2 +- .../core/filter_feedback.py | 2 +- .../core/generate_suggestions.py | 2 +- .../get_structured_grading_instructions.py | 2 +- .../models/model_config.py | 10 - .../module_modeling_llm/models/openai.py | 141 - .../modeling/module_modeling_llm/poetry.lock | 613 ++-- .../module_modeling_llm/pyproject.toml | 5 +- .../module_programming_llm/Dockerfile | 1 + .../module_programming_llm/config.py | 2 +- .../generate_graded_suggestions_by_file.py | 5 +- ...generate_non_graded_suggestions_by_file.py | 5 +- .../generate_summary_by_file.py | 5 +- .../helpers/llm_utils.py | 174 -- .../helpers/models/__init__.py | 33 - .../helpers/models/model_config.py | 10 - .../helpers/models/openai.py | 142 - .../helpers/models/replicate.py | 122 - .../split_grading_instructions_by_file.py | 5 +- .../split_problem_statement_by_file.py | 5 +- .../module_programming_llm/poetry.lock | 600 ++-- .../module_programming_llm/pyproject.toml | 6 +- modules/text/module_text_llm/Dockerfile | 1 + .../module_text_llm/module_text_llm/config.py | 2 +- .../module_text_llm/generate_evaluation.py | 7 +- .../module_text_llm/generate_suggestions.py | 5 +- .../helpers/models/__init__.py | 38 - .../helpers/models/replicate.py | 0 modules/text/module_text_llm/poetry.lock | 414 +-- modules/text/module_text_llm/pyproject.toml | 8 +- 45 files changed, 3669 insertions(+), 1869 deletions(-) create mode 100644 modules/llm_core/.env.example create mode 100644 modules/llm_core/Dockerfile create mode 100644 modules/llm_core/llm_core/__init__.py rename modules/{modeling/module_modeling_llm/module_modeling_llm => llm_core/llm_core}/models/__init__.py (85%) rename modules/{text/module_text_llm/module_text_llm/helpers => llm_core/llm_core}/models/callbacks.py (100%) rename modules/{text/module_text_llm/module_text_llm/helpers => llm_core/llm_core}/models/model_config.py (100%) rename modules/{text/module_text_llm/module_text_llm/helpers => llm_core/llm_core}/models/openai.py (100%) rename modules/{text/module_text_llm/module_text_llm/helpers => llm_core/llm_core/utils}/llm_utils.py (65%) rename modules/{modeling/module_modeling_llm/module_modeling_llm => llm_core/llm_core}/utils/predict_and_parse.py (62%) create mode 100644 modules/llm_core/poetry.lock create mode 100644 modules/llm_core/pyproject.toml delete mode 100644 modules/modeling/module_modeling_llm/module_modeling_llm/models/model_config.py delete mode 100644 modules/modeling/module_modeling_llm/module_modeling_llm/models/openai.py delete mode 100644 modules/programming/module_programming_llm/module_programming_llm/helpers/llm_utils.py delete mode 100644 modules/programming/module_programming_llm/module_programming_llm/helpers/models/__init__.py delete mode 100644 modules/programming/module_programming_llm/module_programming_llm/helpers/models/model_config.py delete mode 100644 modules/programming/module_programming_llm/module_programming_llm/helpers/models/openai.py delete mode 100644 modules/programming/module_programming_llm/module_programming_llm/helpers/models/replicate.py delete mode 100644 modules/text/module_text_llm/module_text_llm/helpers/models/__init__.py delete mode 100644 modules/text/module_text_llm/module_text_llm/helpers/models/replicate.py diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index a86ac0131..1c3aa5822 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -56,6 +56,13 @@ jobs: docker build -t athena . cd .. + - name: Build llm_core image + id: set-image-core_llm + run: | + cd modules/llm_core + docker build -t llm_core . + cd .. + - name: Docker Login id: docker-login run: | diff --git a/assessment_module_manager/poetry.lock b/assessment_module_manager/poetry.lock index d2b2a7a3e..33fceb01f 100644 --- a/assessment_module_manager/poetry.lock +++ b/assessment_module_manager/poetry.lock @@ -2,13 +2,13 @@ [[package]] name = "anyio" -version = "4.4.0" +version = "4.6.0" description = "High level compatibility layer for multiple asynchronous event loop implementations" optional = false -python-versions = 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services: image: athena command: echo "Athena build succeeded, exiting (this is normal)" + llm_core: + build: modules/llm_core + depends_on: + - athena + image: llm_core + command: echo "llm_core build succeeded, exiting (this is normal)" + assessment_module_manager: build: ./assessment_module_manager depends_on: @@ -30,6 +37,7 @@ services: build: modules/programming/module_programming_llm depends_on: - athena + - llm_core ports: - "5002:5002" @@ -38,6 +46,7 @@ services: build: modules/text/module_text_llm depends_on: - athena + - llm_core ports: - "5003:5003" @@ -70,5 +79,6 @@ services: build: modules/modeling/module_modeling_llm depends_on: - athena + - llm_core ports: - "5008:5008" diff --git a/modules/llm_core/.env.example b/modules/llm_core/.env.example new file mode 100644 index 000000000..34e279aab --- /dev/null +++ b/modules/llm_core/.env.example @@ -0,0 +1,39 @@ +# 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) +OPENAI_API_KEY="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" + +# Azure OpenAI [leave blank if not used] +# Model names prefixed with `azure_openai_` followed by the deployment id, e.g. `azure_openai_gpt-35` +AZURE_OPENAI_API_KEY="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" +AZURE_OPENAI_ENDPOINT="https://ase-eu01.openai.azure.com/" # change base if needed +OPENAI_API_VERSION="2024-06-01" # change base if needed + +# LangSmith (can be used for tracing LLMs) [leave blank if not used] +# See https://docs.smith.langchain.com +# LANGCHAIN_TRACING_V2=true +# LANGCHAIN_ENDPOINT="https://api.smith.langchain.com" +# LANGCHAIN_API_KEY="XXX" +# LANGCHAIN_PROJECT="XXX" diff --git a/modules/llm_core/Dockerfile b/modules/llm_core/Dockerfile new file mode 100644 index 000000000..f81a37e57 --- /dev/null +++ b/modules/llm_core/Dockerfile @@ -0,0 +1,24 @@ +# syntax=docker/dockerfile:1 + +# This is the Dockerfile for the shared llm package. +# Its output is used as a dependency in the module_* Dockerfiles. + +FROM python:3.11 as llm_core + +WORKDIR /code + +# Poetry +RUN pip install --no-cache-dir poetry==1.5.0 + +# Dependencies +COPY pyproject.toml poetry.lock ./ +COPY --from=athena /code /athena + +RUN poetry config virtualenvs.create false \ + && poetry install --no-interaction --no-ansi + +# Project files +COPY . ./ + +# Build the package +RUN poetry build -f wheel \ No newline at end of file diff --git a/modules/llm_core/llm_core/__init__.py b/modules/llm_core/llm_core/__init__.py new file mode 100644 index 000000000..2f04ff661 --- /dev/null +++ b/modules/llm_core/llm_core/__init__.py @@ -0,0 +1,4 @@ +import dotenv + +# Load environment variables from .env file (for local development) +dotenv.load_dotenv(override=True) \ No newline at end of file diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/models/__init__.py b/modules/llm_core/llm_core/models/__init__.py similarity index 85% rename from modules/modeling/module_modeling_llm/module_modeling_llm/models/__init__.py rename to modules/llm_core/llm_core/models/__init__.py index 92bafdaa1..6f9db4fdd 100644 --- a/modules/modeling/module_modeling_llm/module_modeling_llm/models/__init__.py +++ b/modules/llm_core/llm_core/models/__init__.py @@ -2,8 +2,7 @@ from typing import Type, Union, List, Optional from langchain.base_language import BaseLanguageModel -from module_modeling_llm.models.model_config import ModelConfig - +from llm_core.models.model_config import ModelConfig DefaultModelConfig: Type[ModelConfig] @@ -15,7 +14,7 @@ types: List[Type[ModelConfig]] = [] try: - import module_modeling_llm.models.openai as openai_config + import llm_core.models.openai as openai_config types.append(openai_config.OpenAIModelConfig) if default_model_name in openai_config.available_models: DefaultModelConfig = openai_config.OpenAIModelConfig @@ -36,4 +35,4 @@ ModelConfigType = type0 else: type1 = types[1] - ModelConfigType = Union[type0, type1] # type: ignore + ModelConfigType = Union[type0, type1] # type: ignore \ No newline at end of file diff --git a/modules/text/module_text_llm/module_text_llm/helpers/models/callbacks.py b/modules/llm_core/llm_core/models/callbacks.py similarity index 100% rename from modules/text/module_text_llm/module_text_llm/helpers/models/callbacks.py rename to modules/llm_core/llm_core/models/callbacks.py diff --git a/modules/text/module_text_llm/module_text_llm/helpers/models/model_config.py b/modules/llm_core/llm_core/models/model_config.py similarity index 100% rename from modules/text/module_text_llm/module_text_llm/helpers/models/model_config.py rename to modules/llm_core/llm_core/models/model_config.py diff --git a/modules/text/module_text_llm/module_text_llm/helpers/models/openai.py b/modules/llm_core/llm_core/models/openai.py similarity index 100% rename from modules/text/module_text_llm/module_text_llm/helpers/models/openai.py rename to modules/llm_core/llm_core/models/openai.py diff --git a/modules/text/module_text_llm/module_text_llm/helpers/llm_utils.py b/modules/llm_core/llm_core/utils/llm_utils.py similarity index 65% rename from modules/text/module_text_llm/module_text_llm/helpers/llm_utils.py rename to modules/llm_core/llm_core/utils/llm_utils.py index e7852bda0..4637b8558 100644 --- a/modules/text/module_text_llm/module_text_llm/helpers/llm_utils.py +++ b/modules/llm_core/llm_core/utils/llm_utils.py @@ -1,8 +1,6 @@ -from typing import Optional, Type, TypeVar, List -from pydantic import BaseModel, ValidationError +from typing import Type, TypeVar, List +from pydantic import BaseModel import tiktoken - -from langchain.chains import LLMChain from langchain.chat_models import ChatOpenAI from langchain.base_language import BaseLanguageModel from langchain.prompts import ( @@ -10,11 +8,8 @@ SystemMessagePromptTemplate, HumanMessagePromptTemplate, ) -from langchain.chains.openai_functions import create_structured_output_chain from langchain.output_parsers import PydanticOutputParser -from langchain.schema import OutputParserException - -from athena import emit_meta, get_experiment_environment +from athena import emit_meta T = TypeVar("T", bound=BaseModel) @@ -112,51 +107,4 @@ def get_chat_prompt_with_formatting_instructions( system_message_prompt.prompt.partial_variables = {"format_instructions": output_parser.get_format_instructions()} system_message_prompt.prompt.input_variables.remove("format_instructions") human_message_prompt = HumanMessagePromptTemplate.from_template(human_message + "\n\nJSON response following the provided schema:") - return ChatPromptTemplate.from_messages([system_message_prompt, human_message_prompt]) - - -async def predict_and_parse( - model: BaseLanguageModel, - chat_prompt: ChatPromptTemplate, - prompt_input: dict, - pydantic_object: Type[T], - tags: Optional[List[str]] - ) -> Optional[T]: - """Predicts an LLM completion using the model and parses the output using the provided Pydantic model - - Args: - model (BaseLanguageModel): The model to predict with - chat_prompt (ChatPromptTemplate): Prompt to use - prompt_input (dict): Input parameters to use for the prompt - pydantic_object (Type[T]): Pydantic model to parse the output - tags (Optional[List[str]]: List of tags to tag the prediction with - - Returns: - Optional[T]: Parsed output, or None if it could not be parsed - """ - experiment = get_experiment_environment() - - tags = tags or [] - if experiment.experiment_id is not None: - tags.append(f"experiment-{experiment.experiment_id}") - if experiment.module_configuration_id is not None: - tags.append(f"module-configuration-{experiment.module_configuration_id}") - if experiment.run_id is not None: - tags.append(f"run-{experiment.run_id}") - - if supports_function_calling(model): - chain = create_structured_output_chain(pydantic_object, llm=model, prompt=chat_prompt, tags=tags) - - try: - return await chain.arun(**prompt_input) - except (OutputParserException, ValidationError): - # In the future, we should probably have some recovery mechanism here (i.e. fix the output with another prompt) - return None - - output_parser = PydanticOutputParser(pydantic_object=pydantic_object) - chain = LLMChain(llm=model, prompt=chat_prompt, output_parser=output_parser, tags=tags) - try: - return await chain.arun(**prompt_input) - except (OutputParserException, ValidationError): - # In the future, we should probably have some recovery mechanism here (i.e. fix the output with another prompt) - return None + return ChatPromptTemplate.from_messages([system_message_prompt, human_message_prompt]) \ No newline at end of file diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/utils/predict_and_parse.py b/modules/llm_core/llm_core/utils/predict_and_parse.py similarity index 62% rename from modules/modeling/module_modeling_llm/module_modeling_llm/utils/predict_and_parse.py rename to modules/llm_core/llm_core/utils/predict_and_parse.py index 5703799ab..d73748bdf 100644 --- a/modules/modeling/module_modeling_llm/module_modeling_llm/utils/predict_and_parse.py +++ b/modules/llm_core/llm_core/utils/predict_and_parse.py @@ -8,12 +8,24 @@ T = TypeVar("T", bound=BaseModel) async def predict_and_parse( - model: BaseLanguageModel, - chat_prompt: ChatPromptTemplate, - prompt_input: dict, - pydantic_object: Type[T], + model: BaseLanguageModel, + chat_prompt: ChatPromptTemplate, + prompt_input: dict, + pydantic_object: Type[T], tags: Optional[List[str]] -) -> Optional[T]: + ) -> Optional[T]: + """Predicts an LLM completion using the model and parses the output using the provided Pydantic model + + Args: + 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 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a/modules/modeling/module_modeling_llm/Dockerfile b/modules/modeling/module_modeling_llm/Dockerfile index 6d1c9a666..68b28a215 100644 --- a/modules/modeling/module_modeling_llm/Dockerfile +++ b/modules/modeling/module_modeling_llm/Dockerfile @@ -17,6 +17,7 @@ RUN pip install --no-cache-dir poetry==1.5.0 COPY pyproject.toml poetry.lock ./ # athena module (from the Dockerfile in the athena folder) COPY --from=athena /code /athena +COPY --from=llm_core /code /llm_core # install dependencies RUN poetry config virtualenvs.create true \ && poetry config virtualenvs.in-project true \ diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/config.py b/modules/modeling/module_modeling_llm/module_modeling_llm/config.py index 791dd4eef..169ee047a 100644 --- a/modules/modeling/module_modeling_llm/module_modeling_llm/config.py +++ b/modules/modeling/module_modeling_llm/module_modeling_llm/config.py @@ -1,7 +1,7 @@ from pydantic import BaseModel, Field from athena import config_schema_provider -from module_modeling_llm.models import ModelConfigType, DefaultModelConfig +from llm_core.models import ModelConfigType, DefaultModelConfig from module_modeling_llm.prompts import ( graded_feedback_prompt, filter_feedback_prompt, diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/core/filter_feedback.py b/modules/modeling/module_modeling_llm/module_modeling_llm/core/filter_feedback.py index 59f00d4ef..efe2b1871 100644 --- a/modules/modeling/module_modeling_llm/module_modeling_llm/core/filter_feedback.py +++ b/modules/modeling/module_modeling_llm/module_modeling_llm/core/filter_feedback.py @@ -3,7 +3,7 @@ from athena import emit_meta from module_modeling_llm.config import BasicApproachConfig -from module_modeling_llm.utils.predict_and_parse import predict_and_parse +from llm_core.utils.predict_and_parse import predict_and_parse from module_modeling_llm.models.assessment_model import AssessmentModel from module_modeling_llm.models.exercise_model import ExerciseModel from module_modeling_llm.prompts.filter_feedback_prompt import FilterFeedbackInputs diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/core/generate_suggestions.py b/modules/modeling/module_modeling_llm/module_modeling_llm/core/generate_suggestions.py index c40ff2927..6db69e7d2 100644 --- a/modules/modeling/module_modeling_llm/module_modeling_llm/core/generate_suggestions.py +++ b/modules/modeling/module_modeling_llm/module_modeling_llm/core/generate_suggestions.py @@ -6,7 +6,7 @@ from module_modeling_llm.config import BasicApproachConfig from module_modeling_llm.models.assessment_model import AssessmentModel from module_modeling_llm.prompts.apollon_format_description import apollon_format_description -from module_modeling_llm.utils.predict_and_parse import predict_and_parse +from llm_core.utils.predict_and_parse import predict_and_parse from module_modeling_llm.prompts.graded_feedback_prompt import GradedFeedbackInputs from module_modeling_llm.models.exercise_model import ExerciseModel diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/core/get_structured_grading_instructions.py b/modules/modeling/module_modeling_llm/module_modeling_llm/core/get_structured_grading_instructions.py index 26e18892d..ae84e0ddf 100644 --- a/modules/modeling/module_modeling_llm/module_modeling_llm/core/get_structured_grading_instructions.py +++ b/modules/modeling/module_modeling_llm/module_modeling_llm/core/get_structured_grading_instructions.py @@ -4,7 +4,7 @@ from langchain_core.prompts import ChatPromptTemplate from athena.schemas.grading_criterion import GradingCriterion, StructuredGradingCriterion -from module_modeling_llm.utils.predict_and_parse import predict_and_parse +from llm_core.utils.predict_and_parse import predict_and_parse from module_modeling_llm.config import BasicApproachConfig from module_modeling_llm.models.exercise_model import ExerciseModel from module_modeling_llm.prompts.structured_grading_instructions_prompt import StructuredGradingInstructionsInputs diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/models/model_config.py b/modules/modeling/module_modeling_llm/module_modeling_llm/models/model_config.py deleted file mode 100644 index 7a9de950a..000000000 --- a/modules/modeling/module_modeling_llm/module_modeling_llm/models/model_config.py +++ /dev/null @@ -1,10 +0,0 @@ -from pydantic import BaseModel -from abc import ABC, abstractmethod -from langchain.base_language import BaseLanguageModel - - -class ModelConfig(BaseModel, ABC): - - @abstractmethod - def get_model(self) -> BaseLanguageModel: - pass diff --git a/modules/modeling/module_modeling_llm/module_modeling_llm/models/openai.py b/modules/modeling/module_modeling_llm/module_modeling_llm/models/openai.py deleted file mode 100644 index 1accdd9fd..000000000 --- a/modules/modeling/module_modeling_llm/module_modeling_llm/models/openai.py +++ /dev/null @@ -1,141 +0,0 @@ -import os -import openai -import requests - -from typing import Dict, List -from enum import Enum -from pydantic import Field, validator, PositiveInt -from langchain.base_language import BaseLanguageModel -from langchain_openai import AzureChatOpenAI, ChatOpenAI - -from athena.logger import logger -from .model_config import ModelConfig - -OPENAI_PREFIX = "openai_" -AZURE_OPENAI_PREFIX = "azure_openai_" -openai_available = bool(os.environ.get("OPENAI_API_KEY")) -azure_openai_available = bool(os.environ.get("AZURE_OPENAI_API_KEY")) - -available_models: Dict[str, BaseLanguageModel] = {} - -# Load Non-Azure OpenAI models -if openai_available: - openai.api_type = "openai" - for model in openai.models.list(): - if "gpt" in model.id: - available_models[OPENAI_PREFIX + model.id] = ChatOpenAI(model=model.id) - -# Load Azure OpenAI models -if azure_openai_available: - def _get_azure_openai_deployments() -> List[str]: - # If this breaks in the future we have to use azure-mgmt-cognitiveservices which needs 6 additional environment variables - base_url = f"{os.environ.get('AZURE_OPENAI_ENDPOINT')}/openai" - headers = { - "api-key": os.environ["AZURE_OPENAI_API_KEY"] - } - - models_response = requests.get(f"{base_url}/models?api-version=2023-03-15-preview", headers=headers, timeout=60) - models_data = models_response.json()["data"] - deployments_response = requests.get(f"{base_url}/deployments?api-version=2023-03-15-preview", headers=headers, timeout=60) - deployments_data = deployments_response.json()["data"] - - # Check if deployment["model"] is a substring of model["id"], i.e. "gpt-4o" is substring "gpt-4o-2024-05-13" - chat_completion_models = ",".join(model["id"] for model in models_data if model["capabilities"]["chat_completion"]) - return [deployment["id"] for deployment in deployments_data if deployment["model"] in chat_completion_models] - - for deployment in _get_azure_openai_deployments(): - available_models[AZURE_OPENAI_PREFIX + deployment] = AzureChatOpenAI(azure_deployment=deployment) - -if available_models: - logger.info("Available openai models: %s", ", ".join(available_models.keys())) - - OpenAIModel = Enum('OpenAIModel', {name: name for name in available_models}) # type: ignore - default_model_name = None - if "LLM_DEFAULT_MODEL" in os.environ and os.environ["LLM_DEFAULT_MODEL"] in available_models: - default_model_name = os.environ["LLM_DEFAULT_MODEL"] - if default_model_name not in available_models: - default_model_name = list(available_models.keys())[0] - - default_openai_model = OpenAIModel[default_model_name] # type: ignore - - # Long descriptions will be displayed in the playground UI and are copied from the OpenAI docs - class OpenAIModelConfig(ModelConfig): - """OpenAI LLM configuration.""" - - model_name: OpenAIModel = Field(default=default_openai_model, # type: ignore - description="The name of the model to use.") - max_tokens: PositiveInt = Field(4000, description="""\ -The maximum number of [tokens](https://platform.openai.com/tokenizer) to generate in the chat completion. - -The total length of input tokens and generated tokens is limited by the model's context length. \ -[Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb) for counting tokens.\ -""") - - temperature: float = Field(default=0.0, ge=0, le=2, description="""\ -What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, \ -while lower values like 0.2 will make it more focused and deterministic. - -We generally recommend altering this or `top_p` but not both.\ -""") - - top_p: float = Field(default=1, ge=0, le=1, description="""\ -An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. \ -So 0.1 means only the tokens comprising the top 10% probability mass are considered. - -We generally recommend altering this or `temperature` but not both.\ -""") - - presence_penalty: float = Field(default=0, ge=-2, le=2, description="""\ -Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, \ -increasing the model's likelihood to talk about new topics. - -[See more information about frequency and presence penalties.](https://platform.openai.com/docs/api-reference/parameter-details)\ -""") - - frequency_penalty: float = Field(default=0, ge=-2, le=2, description="""\ -Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, \ -decreasing the model's likelihood to repeat the same line verbatim. - -[See more information about frequency and presence penalties.](https://platform.openai.com/docs/api-reference/parameter-details)\ -""") - - @validator('max_tokens') - def max_tokens_must_be_positive(cls, v): - """ - Validate that max_tokens is a positive integer. - """ - if v <= 0: - raise ValueError('max_tokens must be a positive integer') - return v - - def get_model(self) -> BaseLanguageModel: - """Get the model from the configuration. - - Returns: - BaseLanguageModel: The model. - """ - model = available_models[self.model_name.value] - kwargs = model.__dict__ - secrets = {secret: getattr(model, secret) for secret in model.lc_secrets.keys()} - kwargs.update(secrets) - - model_kwargs = kwargs.get("model_kwargs", {}) - for attr, value in self.dict().items(): - if attr == "model_name": - # Skip model_name - continue - if hasattr(model, attr): - # If the model has the attribute, add it to kwargs - kwargs[attr] = value - else: - # Otherwise, add it to model_kwargs (necessary for chat models) - model_kwargs[attr] = value - kwargs["model_kwargs"] = model_kwargs - - # Initialize a copy of the model using the config - model = model.__class__(**kwargs) - return model - - - class Config: - title = 'OpenAI' \ No newline at end of file diff --git a/modules/modeling/module_modeling_llm/poetry.lock b/modules/modeling/module_modeling_llm/poetry.lock index ab6191ec0..3178de640 100644 --- a/modules/modeling/module_modeling_llm/poetry.lock +++ b/modules/modeling/module_modeling_llm/poetry.lock @@ -2,113 +2,113 @@ [[package]] name = "aiohappyeyeballs" -version = "2.4.2" +version = "2.4.3" description = "Happy Eyeballs for asyncio" optional = false python-versions = ">=3.8" files = [ - {file = "aiohappyeyeballs-2.4.2-py3-none-any.whl", hash = "sha256:8522691d9a154ba1145b157d6d5c15e5c692527ce6a53c5e5f9876977f6dab2f"}, - 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"1.42.0" -langchain = "0.2.15" +llm_core = { path = "../../llm_core", develop = true } python-dotenv = "1.0.0" nltk = "3.8.1" gitpython = "3.1.41" -replicate = "0.11.0" tiktoken = "0.7.0" langsmith = "0.1.106" -langchain-openai = "0.1.23" [tool.poetry.group.dev.dependencies] pydantic = "1.10.17" diff --git a/modules/programming/module_programming_llm/Dockerfile b/modules/programming/module_programming_llm/Dockerfile index 48ad92d42..4f9d93be0 100644 --- a/modules/programming/module_programming_llm/Dockerfile +++ b/modules/programming/module_programming_llm/Dockerfile @@ -17,6 +17,7 @@ RUN pip install --no-cache-dir poetry==1.5.0 COPY pyproject.toml poetry.lock ./ # athena module (from the Dockerfile in the athena folder) COPY --from=athena /code /athena +COPY --from=llm_core /code /llm_core # install dependencies RUN poetry config virtualenvs.create true \ && poetry config virtualenvs.in-project true \ diff --git a/modules/programming/module_programming_llm/module_programming_llm/config.py b/modules/programming/module_programming_llm/module_programming_llm/config.py index 5edd58003..6a632208e 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/config.py +++ b/modules/programming/module_programming_llm/module_programming_llm/config.py @@ -3,7 +3,7 @@ from pydantic import BaseModel, Field from athena import config_schema_provider -from module_programming_llm.helpers.models import ModelConfigType, DefaultModelConfig +from llm_core.models import ModelConfigType, DefaultModelConfig from module_programming_llm.prompts.generate_graded_suggestions_by_file import ( system_message as generate_graded_suggestions_by_file_system_message, human_message as generate_graded_suggestions_by_file_human_message, diff --git a/modules/programming/module_programming_llm/module_programming_llm/generate_graded_suggestions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/generate_graded_suggestions_by_file.py index 1fe4dde47..4a29b8f6d 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/generate_graded_suggestions_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/generate_graded_suggestions_by_file.py @@ -13,12 +13,13 @@ from module_programming_llm.split_problem_statement_by_file import ( split_problem_statement_by_file, ) -from module_programming_llm.helpers.llm_utils import ( +from llm_core.utils.llm_utils import ( check_prompt_length_and_omit_features_if_necessary, get_chat_prompt_with_formatting_instructions, num_tokens_from_string, - predict_and_parse, ) +from llm_core.utils.predict_and_parse import predict_and_parse + from module_programming_llm.helpers.utils import ( get_diff, load_files_from_repo, diff --git a/modules/programming/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py index b857a24f4..de654a427 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py @@ -11,12 +11,13 @@ from module_programming_llm.split_problem_statement_by_file import ( split_problem_statement_by_file, ) -from module_programming_llm.helpers.llm_utils import ( +from llm_core.utils.llm_utils import ( check_prompt_length_and_omit_features_if_necessary, get_chat_prompt_with_formatting_instructions, num_tokens_from_string, - predict_and_parse, ) +from llm_core.utils.predict_and_parse import predict_and_parse + from module_programming_llm.helpers.utils import ( get_diff, load_files_from_repo, diff --git a/modules/programming/module_programming_llm/module_programming_llm/generate_summary_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/generate_summary_by_file.py index 144d750bf..e5ac6aad7 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/generate_summary_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/generate_summary_by_file.py @@ -9,11 +9,12 @@ from athena.programming import Exercise, Submission from module_programming_llm.config import GradedBasicApproachConfig, BasicApproachConfig -from module_programming_llm.helpers.llm_utils import ( +from llm_core.utils.llm_utils import ( get_chat_prompt_with_formatting_instructions, num_tokens_from_prompt, - predict_and_parse, ) +from llm_core.utils.predict_and_parse import predict_and_parse + from module_programming_llm.helpers.utils import ( get_diff, load_files_from_repo, diff --git a/modules/programming/module_programming_llm/module_programming_llm/helpers/llm_utils.py b/modules/programming/module_programming_llm/module_programming_llm/helpers/llm_utils.py deleted file mode 100644 index a035a5970..000000000 --- a/modules/programming/module_programming_llm/module_programming_llm/helpers/llm_utils.py +++ /dev/null @@ -1,174 +0,0 @@ -from typing import Optional, Type, TypeVar, List, Any, Dict - -from langchain.callbacks.tracers import langchain -from pydantic import BaseModel, ValidationError -import tiktoken - -from langchain.chains import LLMChain -from langchain.chat_models import ChatOpenAI -from langchain.base_language import BaseLanguageModel -from langchain.prompts import ( - ChatPromptTemplate, - SystemMessagePromptTemplate, - HumanMessagePromptTemplate, -) -from langchain.chains.openai_functions import create_structured_output_chain -from langchain.output_parsers import PydanticOutputParser -from langchain.schema import ( - OutputParserException, - BaseLLMOutputParser, - Generation, - LLMResult, -) - -from athena import emit_meta, get_experiment_environment -from athena.logger import logger - -T = TypeVar("T", bound=BaseModel) - - -def num_tokens_from_string(string: str) -> int: - """Returns the number of tokens in a text string.""" - encoding = tiktoken.get_encoding("cl100k_base") - num_tokens = len(encoding.encode(string)) - return num_tokens - - -def num_tokens_from_prompt(chat_prompt: ChatPromptTemplate, prompt_input: dict) -> int: - """Returns the number of tokens in a chat prompt.""" - return num_tokens_from_string(chat_prompt.format(**prompt_input)) - - -def check_prompt_length_and_omit_features_if_necessary(prompt: ChatPromptTemplate, - prompt_input: dict, - max_input_tokens: int, - omittable_features: List[str], - debug: bool): - """Check if the input is too long and omit features if necessary. - - Note: Omitted features will be replaced with "omitted" in the prompt - - Args: - prompt (ChatPromptTemplate): Prompt template - prompt_input (dict): Prompt input - max_input_tokens (int): Maximum number of tokens allowed - omittable_features (List[str]): List of features that can be omitted, ordered by priority (least important first) - debug (bool): Debug flag - - Returns: - (dict, bool): Tuple of (prompt_input, should_run) where prompt_input is the input with omitted features and should_run is True if the model should run, False otherwise - """ - if num_tokens_from_prompt(prompt, prompt_input) <= max_input_tokens: - # Full prompt fits into LLM context => should run with full prompt - return prompt_input, True - - omitted_features = [] - - # Omit features until the input is short enough - for feature in omittable_features: - if feature in prompt_input: - omitted_features.append(feature) - prompt_input[feature] = "omitted" - if num_tokens_from_prompt(prompt, prompt_input) <= max_input_tokens: - if debug: - emit_meta("omitted_features", omitted_features) - return prompt_input, True - - # If we get here, we couldn't omit enough features - return prompt_input, False - - -def supports_function_calling(model: BaseLanguageModel): - """Returns True if the model supports function calling, False otherwise - - Args: - model (BaseLanguageModel): The model to check - - Returns: - boolean: True if the model supports function calling, False otherwise - """ - return False # isinstance(model, ChatOpenAI) TODO: find out how to make function calling work again - - -def get_chat_prompt_with_formatting_instructions( - model: BaseLanguageModel, - system_message: str, - human_message: str, - pydantic_object: Type[T] - ) -> ChatPromptTemplate: - """Returns a ChatPromptTemplate with formatting instructions (if necessary) - - Note: Does nothing if the model supports function calling - - Args: - model (BaseLanguageModel): The model to check if it supports function calling - system_message (str): System message - human_message (str): Human message - pydantic_object (Type[T]): Model to parse the output - - Returns: - ChatPromptTemplate: ChatPromptTemplate with formatting instructions (if necessary) - """ - if supports_function_calling(model): - system_message_prompt = SystemMessagePromptTemplate.from_template(system_message) - human_message_prompt = HumanMessagePromptTemplate.from_template(human_message) - return ChatPromptTemplate.from_messages([system_message_prompt, human_message_prompt]) - - output_parser = PydanticOutputParser(pydantic_object=pydantic_object) - system_message_prompt = SystemMessagePromptTemplate.from_template(system_message + "\n{format_instructions}") - system_message_prompt.prompt.partial_variables = {"format_instructions": output_parser.get_format_instructions()} - system_message_prompt.prompt.input_variables.remove("format_instructions") - human_message_prompt = HumanMessagePromptTemplate.from_template(human_message + "\n\nJSON response following the provided schema:") - return ChatPromptTemplate.from_messages([system_message_prompt, human_message_prompt]) - - -async def predict_and_parse( - model: BaseLanguageModel, - chat_prompt: ChatPromptTemplate, - prompt_input: dict, - pydantic_object: Type[T], - tags: Optional[List[str]] - ) -> Optional[T]: - """Predicts an LLM completion using the model and parses the output using the provided Pydantic model - - Args: - model (BaseLanguageModel): The model to predict with - chat_prompt (ChatPromptTemplate): Prompt to use - prompt_input (dict): Input parameters to use for the prompt - pydantic_object (Type[T]): Pydantic model to parse the output - tags (Optional[List[str]]: List of tags to tag the prediction with - - Returns: - Optional[T]: Parsed output, or None if it could not be parsed - """ - langchain.debug = True - - experiment = get_experiment_environment() - - tags = tags or [] - if experiment.experiment_id is not None: - tags.append(f"experiment-{experiment.experiment_id}") - if experiment.module_configuration_id is not None: - tags.append(f"module-configuration-{experiment.module_configuration_id}") - if experiment.run_id is not None: - tags.append(f"run-{experiment.run_id}") - - if supports_function_calling(model): - chain = create_structured_output_chain(pydantic_object, llm=model, prompt=chat_prompt, tags=tags) - chain.verbose = True - try: - return await chain.arun(**prompt_input) - except (OutputParserException, ValidationError) as e: - logger.error("Exception type: %s, Message: %s", type(e).__name__, e) - return None - - output_parser = PydanticOutputParser(pydantic_object=pydantic_object) - chain = LLMChain(llm=model, prompt=chat_prompt, output_parser=output_parser, tags=tags) - try: - return await chain.arun(**prompt_input) - except (OutputParserException, ValidationError) as e: - logger.error("Exception type: %s, Message: %s", type(e).__name__, e) - # In the future, we should probably have some recovery mechanism here (i.e. fix the output with another prompt) - return None - - # todo debug settings diff --git a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/__init__.py b/modules/programming/module_programming_llm/module_programming_llm/helpers/models/__init__.py deleted file mode 100644 index a5fdc01d0..000000000 --- a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/__init__.py +++ /dev/null @@ -1,33 +0,0 @@ -import os -from typing import Type, Union, List -from module_programming_llm.helpers.models.model_config import ModelConfig - - -DefaultModelConfig: Type[ModelConfig] -default_model_name = os.environ.get("LLM_DEFAULT_MODEL") - -types: List[Type[ModelConfig]] = [] -try: - import module_programming_llm.helpers.models.openai as openai_config - types.append(openai_config.OpenAIModelConfig) - if default_model_name in openai_config.available_models: - DefaultModelConfig = openai_config.OpenAIModelConfig -except AttributeError: - pass - -try: - import module_programming_llm.helpers.models.replicate as replicate_config - types.append(replicate_config.ReplicateModelConfig) - if default_model_name in replicate_config.available_models: - DefaultModelConfig = replicate_config.ReplicateModelConfig -except AttributeError: - pass - -if not types: - raise EnvironmentError( - "No model configurations available, please set up at least one provider in the environment variables.") - -if 'DefaultModelConfig' not in globals(): - DefaultModelConfig = types[0] - -ModelConfigType = openai_config.OpenAIModelConfig if 'ReplicateModelConfig' not in globals() else Union[openai_config.OpenAIModelConfig, replicate_config.ReplicateModelConfig] \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/model_config.py b/modules/programming/module_programming_llm/module_programming_llm/helpers/models/model_config.py deleted file mode 100644 index eae644f57..000000000 --- a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/model_config.py +++ /dev/null @@ -1,10 +0,0 @@ -from abc import ABC, abstractmethod -from pydantic import BaseModel -from langchain.base_language import BaseLanguageModel - - -class ModelConfig(BaseModel, ABC): - - @abstractmethod - def get_model(self) -> BaseLanguageModel: - pass diff --git a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/openai.py b/modules/programming/module_programming_llm/module_programming_llm/helpers/models/openai.py deleted file mode 100644 index 23e1669c2..000000000 --- a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/openai.py +++ /dev/null @@ -1,142 +0,0 @@ -import os -import openai -import requests - -from typing import Dict, List -from enum import Enum -from pydantic import Field, validator, PositiveInt -from langchain.base_language import BaseLanguageModel -from langchain_openai import AzureChatOpenAI, ChatOpenAI - -from athena.logger import logger -from .model_config import ModelConfig - -OPENAI_PREFIX = "openai_" -AZURE_OPENAI_PREFIX = "azure_openai_" -openai_available = bool(os.environ.get("OPENAI_API_KEY")) -azure_openai_available = bool(os.environ.get("AZURE_OPENAI_API_KEY")) - -available_models: Dict[str, BaseLanguageModel] = {} - -# Load Non-Azure OpenAI models -if openai_available: - openai.api_type = "openai" - for model in openai.models.list(): - if "gpt" in model.id: - available_models[OPENAI_PREFIX + model.id] = ChatOpenAI(model=model.id) - -# Load Azure OpenAI models -if azure_openai_available: - def _get_azure_openai_deployments() -> List[str]: - # If this breaks in the future we have to use azure-mgmt-cognitiveservices which needs 6 additional environment variables - base_url = f"{os.environ.get('AZURE_OPENAI_ENDPOINT')}/openai" - headers = { - "api-key": os.environ["AZURE_OPENAI_API_KEY"] - } - - models_response = requests.get(f"{base_url}/models?api-version=2023-03-15-preview", headers=headers, timeout=30) - models_data = models_response.json()["data"] - deployments_response = requests.get(f"{base_url}/deployments?api-version=2023-03-15-preview", headers=headers, - timeout=30) - deployments_data = deployments_response.json()["data"] - - # Check if deployment["model"] is a substring of model["id"], i.e. "gpt-4o" is substring "gpt-4o-2024-05-13" - chat_completion_models = ",".join(model["id"] for model in models_data if model["capabilities"]["chat_completion"]) - return [deployment["id"] for deployment in deployments_data if deployment["model"] in chat_completion_models] - - for deployment in _get_azure_openai_deployments(): - available_models[AZURE_OPENAI_PREFIX + deployment] = AzureChatOpenAI(azure_deployment=deployment) - -if available_models: - logger.info("Available openai models: %s", ", ".join(available_models.keys())) - - OpenAIModel = Enum('OpenAIModel', {name: name for name in available_models}) # type: ignore - default_model_name = None - if "LLM_DEFAULT_MODEL" in os.environ and os.environ["LLM_DEFAULT_MODEL"] in available_models: - default_model_name = os.environ["LLM_DEFAULT_MODEL"] - if default_model_name not in available_models: - default_model_name = list(available_models.keys())[0] - - default_openai_model = OpenAIModel[default_model_name] # type: ignore - - # Long descriptions will be displayed in the playground UI and are copied from the OpenAI docs - class OpenAIModelConfig(ModelConfig): - """OpenAI LLM configuration.""" - - model_name: OpenAIModel = Field(default=default_openai_model, # type: ignore - description="The name of the model to use.") - max_tokens: PositiveInt = Field(1000, description="""\ -The maximum number of [tokens](https://platform.openai.com/tokenizer) to generate in the chat completion. - -The total length of input tokens and generated tokens is limited by the model's context length. \ -[Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb) for counting tokens.\ -""") - - temperature: float = Field(default=0.0, ge=0, le=2, description="""\ -What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, \ -while lower values like 0.2 will make it more focused and deterministic. - -We generally recommend altering this or `top_p` but not both.\ -""") - - top_p: float = Field(default=1, ge=0, le=1, description="""\ -An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. \ -So 0.1 means only the tokens comprising the top 10% probability mass are considered. - -We generally recommend altering this or `temperature` but not both.\ -""") - - presence_penalty: float = Field(default=0, ge=-2, le=2, description="""\ -Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, \ -increasing the model's likelihood to talk about new topics. - -[See more information about frequency and presence penalties.](https://platform.openai.com/docs/api-reference/parameter-details)\ -""") - - frequency_penalty: float = Field(default=0, ge=-2, le=2, description="""\ -Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, \ -decreasing the model's likelihood to repeat the same line verbatim. - -[See more information about frequency and presence penalties.](https://platform.openai.com/docs/api-reference/parameter-details)\ -""") - - @validator('max_tokens') - def max_tokens_must_be_positive(cls, v): - """ - Validate that max_tokens is a positive integer. - """ - if v <= 0: - raise ValueError('max_tokens must be a positive integer') - return v - - def get_model(self) -> BaseLanguageModel: - """Get the model from the configuration. - - Returns: - BaseLanguageModel: The model. - """ - model = available_models[self.model_name.value] - kwargs = model.__dict__ - secrets = {secret: getattr(model, secret) for secret in model.lc_secrets.keys()} - kwargs.update(secrets) - - model_kwargs = kwargs.get("model_kwargs", {}) - for attr, value in self.dict().items(): - if attr == "model_name": - # Skip model_name - continue - if hasattr(model, attr): - # If the model has the attribute, add it to kwargs - kwargs[attr] = value - else: - # Otherwise, add it to model_kwargs (necessary for chat models) - model_kwargs[attr] = value - kwargs["model_kwargs"] = model_kwargs - - # Initialize a copy of the model using the config - model = model.__class__(**kwargs) - return model - - - class Config: - title = 'OpenAI' \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/replicate.py b/modules/programming/module_programming_llm/module_programming_llm/helpers/models/replicate.py deleted file mode 100644 index 248d55fce..000000000 --- a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/replicate.py +++ /dev/null @@ -1,122 +0,0 @@ -import os -from pydantic import Field, PositiveInt -from enum import Enum - -from langchain.llms import Replicate -from langchain.base_language import BaseLanguageModel - -from athena.logger import logger -from .model_config import ModelConfig - - -# Hardcoded list of models -# If necessary, add more models from replicate here, the config below might need adjustments depending on the available -# parameters of the model -# -# To update the version of the models, go to the respective page on replicate.com and copy the (latest) version id -# from and paste it after the colon in the value of the dictionary. Ever so often a new version is released. -replicate_models = { - # LLAMA 2 70B Chat - # https://replicate.com/replicate/llama-2-70b-chat - "llama-2-70b-chat": "replicate/llama-2-70b-chat:58d078176e02c219e11eb4da5a02a7830a283b14cf8f94537af893ccff5ee781", - # LLaMA 2 13B Chat - # https://replicate.com/a16z-infra/llama-2-13b-chat - "llama-2-13b-chat": "a16z-infra/llama-2-13b-chat:2a7f981751ec7fdf87b5b91ad4db53683a98082e9ff7bfd12c8cd5ea85980a52", - # LLaMA 2 7B Chat - # https://replicate.com/a16z-infra/llama-2-7b-chat - "llama-2-7b-chat": "a16z-infra/llama-2-7b-chat:7b0bfc9aff140d5b75bacbed23e91fd3c34b01a1e958d32132de6e0a19796e2c", - # CodeLLAMA 2 13B - # https://replicate.com/replicate/codellama-13b - "codellama-13b": "replicate/codellama-13b:1c914d844307b0588599b8393480a3ba917b660c7e9dfae681542b5325f228db", - # CodeLLAMA 2 34B - # https://replicate.com/replicate/codellama-34b - "codellama-34b": "replicate/codellama-34b:0666717e5ead8557dff55ee8f11924b5c0309f5f1ca52f64bb8eec405fdb38a7", -} - -available_models = {} -if os.environ.get("REPLICATE_API_TOKEN"): # If Replicate is available - available_models = { - name: Replicate( - model=model, - model_kwargs={ "temperature": 0.01 } - ) - for name, model in replicate_models.items() - } -else: - logger.warning("REPLICATE_API_TOKEN not found in environment variables. Replicate models are disabled.") - -if available_models: - logger.info("Available replicate models: %s", - ", ".join(available_models.keys())) - - ReplicateModel = Enum('ReplicateModel', {name: name for name in available_models}) # type: ignore - - - default_model_name = "llama-2-13b-chat" - if "LLM_DEFAULT_MODEL" in os.environ and os.environ["LLM_DEFAULT_MODEL"] in available_models: - default_model_name = os.environ["LLM_DEFAULT_MODEL"] - if default_model_name not in available_models: - default_model_name = list(available_models.keys())[0] - - default_replicate_model = ReplicateModel[default_model_name] - - - # Note: Config has been setup with LLaMA 2 chat models in mind, other models may not work as expected - class ReplicateModelConfig(ModelConfig): - """Replicate LLM configuration.""" - - model_name: ReplicateModel = Field(default=default_replicate_model, # type: ignore - description="The name of the model to use.") - max_new_tokens: PositiveInt = Field(1000, description="""\ -Maximum number of tokens to generate. A word is generally 2-3 tokens (minimum: 1)\ -""") - min_new_tokens: int = Field(-1, description="""\ -Minimum number of tokens to generate. To disable, set to -1. A word is generally 2-3 tokens. (minimum: -1)\ -""") - temperature: float = Field(default=0.01, ge=0.01, le=5, description="""\ -Adjusts randomness of outputs, greater than 1 is random and 0 is deterministic, 0.75 is a good starting value.\ -(minimum: 0.01; maximum: 5)\ -""") - top_p: float = Field(default=1, ge=0, le=1, description="""\ -When decoding text, samples from the top p percentage of most likely tokens; lower to ignore less likely tokens (maximum: 1)\ -""") - top_k: PositiveInt = Field(default=250, description="""\ -When decoding text, samples from the top k most likely tokens; lower to ignore less likely tokens\ -""") - repetition_penalty: float = Field(default=1, ge=0.01, le=5, description="""\ -Penalty for repeated words in generated text; 1 is no penalty, values greater than 1 discourage repetition, \ -less than 1 encourage it. (minimum: 0.01; maximum: 5)\ -""") - repetition_penalty_sustain: int = Field(default=-1, description=""" -Number of most recent tokens to apply repetition penalty to, -1 to apply to whole context (minimum: -1)\ -""") - token_repetition_penalty_decay: PositiveInt = Field(default=128, description="""\ -Gradually decrease penalty over this many tokens (minimum: 1)\ -""") - - def get_model(self) -> BaseLanguageModel: - """Get the model from the configuration. - - Returns: - BaseLanguageModel: The model. - """ - model = available_models[self.model_name.value] - kwargs = model._lc_kwargs - - model_kwargs = {} - for attr, value in self.dict().items(): - # Skip model_name - if attr == "model_name": - continue - model_kwargs[attr] = value - - # Set model parameters - kwargs["model_kwargs"] = model_kwargs - - # Initialize a copy of the model using the config - model = model.__class__(**kwargs) - return model - - - class Config: - title = 'Replicate' diff --git a/modules/programming/module_programming_llm/module_programming_llm/split_grading_instructions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/split_grading_instructions_by_file.py index 0e402b378..08c08924f 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/split_grading_instructions_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/split_grading_instructions_by_file.py @@ -8,12 +8,13 @@ from athena.programming import Exercise, Submission from module_programming_llm.config import GradedBasicApproachConfig -from module_programming_llm.helpers.llm_utils import ( +from llm_core.utils.llm_utils import ( get_chat_prompt_with_formatting_instructions, num_tokens_from_string, num_tokens_from_prompt, - predict_and_parse ) +from llm_core.utils.predict_and_parse import predict_and_parse + from module_programming_llm.helpers.utils import format_grading_instructions, get_diff diff --git a/modules/programming/module_programming_llm/module_programming_llm/split_problem_statement_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/split_problem_statement_by_file.py index 46cd64bbb..aecf516ac 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/split_problem_statement_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/split_problem_statement_by_file.py @@ -8,12 +8,13 @@ from athena.programming import Exercise, Submission from module_programming_llm.config import GradedBasicApproachConfig, BasicApproachConfig -from module_programming_llm.helpers.llm_utils import ( +from llm_core.utils.llm_utils import ( get_chat_prompt_with_formatting_instructions, num_tokens_from_string, num_tokens_from_prompt, - predict_and_parse ) +from llm_core.utils.predict_and_parse import predict_and_parse + from module_programming_llm.helpers.utils import get_diff diff --git 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a/modules/text/module_text_llm/Dockerfile b/modules/text/module_text_llm/Dockerfile index 48ad92d42..4f9d93be0 100644 --- a/modules/text/module_text_llm/Dockerfile +++ b/modules/text/module_text_llm/Dockerfile @@ -17,6 +17,7 @@ RUN pip install --no-cache-dir poetry==1.5.0 COPY pyproject.toml poetry.lock ./ # athena module (from the Dockerfile in the athena folder) COPY --from=athena /code /athena +COPY --from=llm_core /code /llm_core # install dependencies RUN poetry config virtualenvs.create true \ && poetry config virtualenvs.in-project true \ diff --git a/modules/text/module_text_llm/module_text_llm/config.py b/modules/text/module_text_llm/module_text_llm/config.py index 82d177eed..0a61eeba6 100644 --- a/modules/text/module_text_llm/module_text_llm/config.py +++ b/modules/text/module_text_llm/module_text_llm/config.py @@ -1,7 +1,7 @@ from pydantic import BaseModel, Field from athena import config_schema_provider -from module_text_llm.helpers.models import ModelConfigType, DefaultModelConfig +from llm_core.models import ModelConfigType, DefaultModelConfig from module_text_llm.prompts.generate_suggestions import ( system_message as generate_suggestions_system_message, human_message as generate_suggestions_human_message diff --git a/modules/text/module_text_llm/module_text_llm/generate_evaluation.py b/modules/text/module_text_llm/module_text_llm/generate_evaluation.py index 4c4a9969b..50473dd3a 100644 --- a/modules/text/module_text_llm/module_text_llm/generate_evaluation.py +++ b/modules/text/module_text_llm/module_text_llm/generate_evaluation.py @@ -5,12 +5,13 @@ from athena.text import Exercise, Submission, Feedback from athena.logger import logger -from module_text_llm.helpers.models import evaluation_model -from module_text_llm.helpers.llm_utils import ( +from llm_core.models import evaluation_model +from llm_core.utils.llm_utils import ( get_chat_prompt_with_formatting_instructions, check_prompt_length_and_omit_features_if_necessary, - predict_and_parse ) +from llm_core.utils.predict_and_parse import predict_and_parse + from module_text_llm.helpers.utils import add_sentence_numbers, get_line_range_from_index_range from module_text_llm.prompts.generate_evaluation import system_message, human_message diff --git a/modules/text/module_text_llm/module_text_llm/generate_suggestions.py b/modules/text/module_text_llm/module_text_llm/generate_suggestions.py index d43563ad6..be928dc2e 100644 --- a/modules/text/module_text_llm/module_text_llm/generate_suggestions.py +++ b/modules/text/module_text_llm/module_text_llm/generate_suggestions.py @@ -6,12 +6,13 @@ from athena.logger import logger from module_text_llm.config import BasicApproachConfig -from module_text_llm.helpers.llm_utils import ( +from llm_core.utils.llm_utils import ( get_chat_prompt_with_formatting_instructions, check_prompt_length_and_omit_features_if_necessary, num_tokens_from_prompt, - predict_and_parse ) +from llm_core.utils.predict_and_parse import predict_and_parse + from module_text_llm.helpers.utils import add_sentence_numbers, get_index_range_from_line_range, format_grading_instructions class FeedbackModel(BaseModel): diff --git a/modules/text/module_text_llm/module_text_llm/helpers/models/__init__.py b/modules/text/module_text_llm/module_text_llm/helpers/models/__init__.py deleted file mode 100644 index 85078d4d7..000000000 --- a/modules/text/module_text_llm/module_text_llm/helpers/models/__init__.py +++ /dev/null @@ -1,38 +0,0 @@ -import os -from typing import Type, Union, List, Optional -from langchain.base_language import BaseLanguageModel - -from module_text_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 - 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"2.11.1" description = "Python style guide checker" optional = false -python-versions = ">=3.6" +python-versions = ">=3.8" files = [ - {file = "pycodestyle-2.9.1-py2.py3-none-any.whl", hash = "sha256:d1735fc58b418fd7c5f658d28d943854f8a849b01a5d0a1e6f3f3fdd0166804b"}, - {file = "pycodestyle-2.9.1.tar.gz", hash = "sha256:2c9607871d58c76354b697b42f5d57e1ada7d261c261efac224b664affdc5785"}, + {file = "pycodestyle-2.11.1-py2.py3-none-any.whl", hash = "sha256:44fe31000b2d866f2e41841b18528a505fbd7fef9017b04eff4e2648a0fadc67"}, + {file = "pycodestyle-2.11.1.tar.gz", hash = "sha256:41ba0e7afc9752dfb53ced5489e89f8186be00e599e712660695b7a75ff2663f"}, ] [[package]] @@ -1466,13 +1575,13 @@ toml = ["tomli (>=1.2.3)"] [[package]] name = "pyflakes" -version = "2.5.0" +version = "3.1.0" description = "passive checker of Python programs" optional = false -python-versions = ">=3.6" +python-versions = ">=3.8" files = [ - {file = "pyflakes-2.5.0-py2.py3-none-any.whl", hash = "sha256:4579f67d887f804e67edb544428f264b7b24f435b263c4614f384135cea553d2"}, - {file = "pyflakes-2.5.0.tar.gz", hash = "sha256:491feb020dca48ccc562a8c0cbe8df07ee13078df59813b83959cbdada312ea3"}, + {file = "pyflakes-3.1.0-py2.py3-none-any.whl", hash = "sha256:4132f6d49cb4dae6819e5379898f2b8cce3c5f23994194c24b77d5da2e36f774"}, + {file = "pyflakes-3.1.0.tar.gz", hash = "sha256:a0aae034c444db0071aa077972ba4768d40c830d9539fd45bf4cd3f8f6992efc"}, ] [[package]] @@ -1739,25 +1848,6 @@ files = [ {file = "regex-2024.9.11.tar.gz", hash = "sha256:6c188c307e8433bcb63dc1915022deb553b4203a70722fc542c363bf120a01fd"}, ] -[[package]] -name = "replicate" -version = "0.11.0" -description = "Python client for Replicate" -optional = false -python-versions = ">=3.8" -files = [ - {file = "replicate-0.11.0-py3-none-any.whl", hash = "sha256:fbb8815068864dc822cd4fa7b6103d6f4089d6ef122abd6c3441ca0f0f110c46"}, - {file = "replicate-0.11.0.tar.gz", hash = "sha256:4d54b5838c1552a6f76cc37c3af8d9a7998105382082d672acad31636ad443b5"}, -] - -[package.dependencies] -packaging = "*" -pydantic = ">1" -requests = ">2" - -[package.extras] -dev = ["black", "mypy", "pytest", "responses", "ruff"] - [[package]] name = "requests" version = "2.32.3" @@ -1779,6 +1869,20 @@ urllib3 = ">=1.21.1,<3" socks = ["PySocks (>=1.5.6,!=1.5.7)"] use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"] +[[package]] +name = "requests-toolbelt" +version = "1.0.0" +description = "A utility belt for advanced users of python-requests" +optional = false +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" +files = [ + {file = "requests-toolbelt-1.0.0.tar.gz", hash = "sha256:7681a0a3d047012b5bdc0ee37d7f8f07ebe76ab08caeccfc3921ce23c88d5bc6"}, + {file = "requests_toolbelt-1.0.0-py2.py3-none-any.whl", hash = "sha256:cccfdd665f0a24fcf4726e690f65639d272bb0637b9b92dfd91a5568ccf6bd06"}, +] + +[package.dependencies] +requests = ">=2.0.1,<3.0.0" + [[package]] name = "requirements-detector" version = "1.2.2" @@ -2330,4 +2434,4 @@ multidict = ">=4.0" [metadata] lock-version = "2.0" python-versions = "3.11.*" -content-hash = "e3d6d9da95585aa2a7cba97910d821d5cda5412c2a37578097b588e49553d19c" +content-hash = "c7054e678876fb7e978fab368eca297d27da931cd56eb8dfc07af4114f960613" diff --git a/modules/text/module_text_llm/pyproject.toml b/modules/text/module_text_llm/pyproject.toml index 121f2a482..ec34bafa7 100644 --- a/modules/text/module_text_llm/pyproject.toml +++ b/modules/text/module_text_llm/pyproject.toml @@ -8,15 +8,11 @@ license = "MIT" [tool.poetry.dependencies] python = "3.11.*" athena = { path = "../../../athena", develop = true } -#athena = { git = "https://github.com/ls1intum/Athena.git", rev = "2da2d33", subdirectory = "athena"} -replicate = "^0.11.0" +# athena = { git = "https://github.com/ls1intum/Athena.git", rev = "2da2d33", subdirectory = "athena"} +llm_core = { path = "../../llm_core", develop = true } langsmith = ">=0.1.0,<0.2.0" gitpython = "3.1.41" -langchain = "0.2.11" -langchain-community="0.2.10" -langchain-openai = "0.1.19" nltk = "3.8.1" -openai = "1.37.1" python-dotenv = "1.0.0" tiktoken = "0.7.0" From 2d629400d2eb4efedb30ad4ff7721153cea8ca1d Mon Sep 17 00:00:00 2001 From: "Felix T.J. Dietrich" Date: Fri, 11 Oct 2024 18:02:00 +0200 Subject: [PATCH 2/5] Move llm_core (#346) --- .github/workflows/build.yml | 2 +- docker-compose.yml | 2 +- {modules/llm_core => llm_core}/.env.example | 0 {modules/llm_core => llm_core}/Dockerfile | 0 .../llm_core/__init__.py | 0 .../llm_core/models/__init__.py | 0 .../llm_core/models/callbacks.py | 0 .../llm_core/models/model_config.py | 0 .../llm_core/models/openai.py | 0 .../llm_core/utils/llm_utils.py | 0 .../llm_core/utils/predict_and_parse.py | 0 {modules/llm_core => llm_core}/poetry.lock | 1056 ++++++++-------- {modules/llm_core => llm_core}/pyproject.toml | 2 +- .../modeling/module_modeling_llm/poetry.lock | 831 +++++++------ .../module_modeling_llm/pyproject.toml | 2 +- .../module_programming_llm/poetry.lock | 897 ++++++++------ .../module_programming_llm/pyproject.toml | 2 +- modules/text/module_text_llm/poetry.lock | 1060 ++++++++--------- modules/text/module_text_llm/pyproject.toml | 2 +- 19 files changed, 2042 insertions(+), 1814 deletions(-) rename {modules/llm_core => llm_core}/.env.example (100%) rename {modules/llm_core => llm_core}/Dockerfile (100%) rename {modules/llm_core => llm_core}/llm_core/__init__.py (100%) rename {modules/llm_core => llm_core}/llm_core/models/__init__.py (100%) rename {modules/llm_core => llm_core}/llm_core/models/callbacks.py (100%) rename {modules/llm_core => llm_core}/llm_core/models/model_config.py (100%) rename {modules/llm_core => llm_core}/llm_core/models/openai.py (100%) rename {modules/llm_core => llm_core}/llm_core/utils/llm_utils.py (100%) rename {modules/llm_core => llm_core}/llm_core/utils/predict_and_parse.py (100%) rename {modules/llm_core => llm_core}/poetry.lock (67%) rename {modules/llm_core => llm_core}/pyproject.toml (92%) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 1c3aa5822..f1f2d894d 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -59,7 +59,7 @@ jobs: - name: Build llm_core image id: set-image-core_llm run: | - cd modules/llm_core + cd ./llm_core docker build -t llm_core . cd .. diff --git a/docker-compose.yml b/docker-compose.yml index 98a3838ee..54dcefbeb 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -9,7 +9,7 @@ services: command: echo "Athena build succeeded, exiting (this is normal)" llm_core: - build: modules/llm_core + build: ./llm_core depends_on: - athena image: llm_core diff --git a/modules/llm_core/.env.example b/llm_core/.env.example similarity index 100% rename from modules/llm_core/.env.example rename to llm_core/.env.example diff --git a/modules/llm_core/Dockerfile b/llm_core/Dockerfile similarity index 100% rename from modules/llm_core/Dockerfile rename to llm_core/Dockerfile diff --git a/modules/llm_core/llm_core/__init__.py b/llm_core/llm_core/__init__.py similarity index 100% rename from modules/llm_core/llm_core/__init__.py rename to llm_core/llm_core/__init__.py diff --git a/modules/llm_core/llm_core/models/__init__.py b/llm_core/llm_core/models/__init__.py similarity index 100% rename from modules/llm_core/llm_core/models/__init__.py rename to llm_core/llm_core/models/__init__.py diff --git a/modules/llm_core/llm_core/models/callbacks.py b/llm_core/llm_core/models/callbacks.py similarity index 100% rename from modules/llm_core/llm_core/models/callbacks.py rename to llm_core/llm_core/models/callbacks.py diff --git a/modules/llm_core/llm_core/models/model_config.py b/llm_core/llm_core/models/model_config.py similarity index 100% rename from modules/llm_core/llm_core/models/model_config.py rename to llm_core/llm_core/models/model_config.py diff --git a/modules/llm_core/llm_core/models/openai.py b/llm_core/llm_core/models/openai.py similarity index 100% rename from modules/llm_core/llm_core/models/openai.py rename to llm_core/llm_core/models/openai.py diff --git a/modules/llm_core/llm_core/utils/llm_utils.py b/llm_core/llm_core/utils/llm_utils.py similarity index 100% rename from modules/llm_core/llm_core/utils/llm_utils.py rename to llm_core/llm_core/utils/llm_utils.py diff --git a/modules/llm_core/llm_core/utils/predict_and_parse.py b/llm_core/llm_core/utils/predict_and_parse.py similarity index 100% rename from modules/llm_core/llm_core/utils/predict_and_parse.py rename to llm_core/llm_core/utils/predict_and_parse.py diff --git a/modules/llm_core/poetry.lock b/llm_core/poetry.lock similarity index 67% rename from modules/llm_core/poetry.lock rename to llm_core/poetry.lock index b8076f8f8..1d67f0b38 100644 --- a/modules/llm_core/poetry.lock +++ b/llm_core/poetry.lock @@ -13,102 +13,102 @@ files = [ [[package]] name = "aiohttp" -version = "3.10.9" +version = "3.10.10" description = "Async http client/server framework (asyncio)" optional = false python-versions = ">=3.8" files = [ - {file = "aiohttp-3.10.9-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:8b3fb28a9ac8f2558760d8e637dbf27aef1e8b7f1d221e8669a1074d1a266bb2"}, - {file = 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b/modules/text/module_text_llm/pyproject.toml @@ -9,7 +9,7 @@ license = "MIT" python = "3.11.*" athena = { path = "../../../athena", develop = true } # athena = { git = "https://github.com/ls1intum/Athena.git", rev = "2da2d33", subdirectory = "athena"} -llm_core = { path = "../../llm_core", develop = true } +llm_core = { path = "../../../llm_core", develop = true } langsmith = ">=0.1.0,<0.2.0" gitpython = "3.1.41" nltk = "3.8.1" From b336006a62091f129266fe34b9ca499944cca268 Mon Sep 17 00:00:00 2001 From: "Felix T.J. Dietrich" Date: Mon, 21 Oct 2024 18:49:29 +0200 Subject: [PATCH 3/5] Fix token usage response (#348) --- llm_core/.env.example | 4 ++- llm_core/llm_core/models/callbacks.py | 32 ++++++++++++------- .../modeling/module_modeling_llm/.env.example | 2 ++ .../module_programming_llm/.env.example | 4 ++- modules/text/module_text_llm/.env.example | 4 ++- 5 files changed, 32 insertions(+), 14 deletions(-) diff --git a/llm_core/.env.example b/llm_core/.env.example index 34e279aab..823e9a302 100644 --- a/llm_core/.env.example +++ b/llm_core/.env.example @@ -12,7 +12,9 @@ DATABASE_URL=sqlite:///../data/data.sqlite # Default model to use # See below for options, available models are also logged on startup -LLM_DEFAULT_MODEL="azure_openai_gpt-35-turbo" +LLM_DEFAULT_MODEL="azure_openai_gpt-4o" +LLM_DEFAULT_MODEL_COST_PER_MILLION_INPUT_TOKEN=5 +LLM_DEFAULT_MODEL_COST_PER_MILLION_OUTPUT_TOKEN=15 # Enable LLM-as-a-judge approach 0 = disabled, 1 = enabled LLM_ENABLE_LLM_AS_A_JUDGE=1 diff --git a/llm_core/llm_core/models/callbacks.py b/llm_core/llm_core/models/callbacks.py index d33b0a6bf..dc8d7b329 100644 --- a/llm_core/llm_core/models/callbacks.py +++ b/llm_core/llm_core/models/callbacks.py @@ -1,3 +1,5 @@ +import os + from langchain.callbacks.base import BaseCallbackHandler from langchain_core.outputs import LLMResult from langchain_core.messages.ai import UsageMetadata @@ -7,10 +9,13 @@ class UsageHandler(BaseCallbackHandler): def on_llm_end(self, response: LLMResult, **kwargs) -> None: + cost_per_million_input_tokens = float(os.environ.get("LLM_DEFAULT_MODEL_COST_PER_MILLION_INPUT_TOKEN", 0.0)) + cost_per_million_output_tokens = float(os.environ.get("LLM_DEFAULT_MODEL_COST_PER_MILLION_OUTPUT_TOKEN", 0.0)) + meta = get_meta() - total_usage = meta.get("total_usage", {"input_tokens": 0, "output_tokens": 0, "total_tokens": 0}) - llm_calls = meta.get("llm_calls", []) + total_usage = meta.get("totalUsage", {"numInputTokens": 0, "numOutputTokens": 0, "numTotalTokens": 0, "cost": 0 }) + llm_calls = meta.get("llmRequests", []) for generations in response.generations: for generation in generations: @@ -18,16 +23,21 @@ def on_llm_end(self, response: LLMResult, **kwargs) -> None: generation_usage: UsageMetadata = message["usage_metadata"] model_name = message["response_metadata"].get("model_name", None) - total_usage["input_tokens"] += generation_usage["input_tokens"] - total_usage["output_tokens"] += generation_usage["output_tokens"] - total_usage["total_tokens"] += generation_usage["total_tokens"] + total_usage["numInputTokens"] += generation_usage["input_tokens"] + total_usage["numOutputTokens"] += generation_usage["output_tokens"] + total_usage["numTotalTokens"] += generation_usage["total_tokens"] + + total_usage["cost"] += int(generation_usage["input_tokens"]) * cost_per_million_output_tokens / 1_000_000 + total_usage["cost"] += int(generation_usage["output_tokens"]) * cost_per_million_output_tokens / 1_000_000 llm_calls.append({ - "model_name": model_name, - "input_tokens": generation_usage["input_tokens"], - "output_tokens": generation_usage["output_tokens"], - "total_tokens": generation_usage["total_tokens"], + "model": model_name, + "costPerMillionInputToken": cost_per_million_input_tokens, + "costPerMillionOutputToken": cost_per_million_output_tokens, + "numInputTokens": generation_usage["input_tokens"], + "numOutputTokens": generation_usage["output_tokens"], + "numTotalTokens": generation_usage["total_tokens"], }) - emit_meta("total_usage", total_usage) - emit_meta("llm_calls", llm_calls) + emit_meta("totalUsage", total_usage) + emit_meta("llmRequests", llm_calls) diff --git a/modules/modeling/module_modeling_llm/.env.example b/modules/modeling/module_modeling_llm/.env.example index 68b0577a1..ebeeb7bc5 100644 --- a/modules/modeling/module_modeling_llm/.env.example +++ b/modules/modeling/module_modeling_llm/.env.example @@ -13,6 +13,8 @@ DATABASE_URL=sqlite:///../data/data.sqlite # Default model to use # See below for options, available models are also logged on startup LLM_DEFAULT_MODEL="azure_openai_gpt-4o" +LLM_DEFAULT_MODEL_COST_PER_MILLION_INPUT_TOKEN=5 +LLM_DEFAULT_MODEL_COST_PER_MILLION_OUTPUT_TOKEN=15 # Enable LLM-as-a-judge approach 0 = disabled, 1 = enabled LLM_ENABLE_LLM_AS_A_JUDGE=1 diff --git a/modules/programming/module_programming_llm/.env.example b/modules/programming/module_programming_llm/.env.example index 2b6d9a889..753874245 100644 --- a/modules/programming/module_programming_llm/.env.example +++ b/modules/programming/module_programming_llm/.env.example @@ -12,7 +12,9 @@ DATABASE_URL=sqlite:///../data/data.sqlite # Default model to use # See below for options, available models are also logged on startup -LLM_DEFAULT_MODEL="azure_openai_gpt-35" +LLM_DEFAULT_MODEL="azure_openai_gpt-4o" +LLM_DEFAULT_MODEL_COST_PER_MILLION_INPUT_TOKEN=5 +LLM_DEFAULT_MODEL_COST_PER_MILLION_OUTPUT_TOKEN=15 # Standard OpenAI (Non-Azure) [leave blank if not used] # Model names prefixed with `openai_` followed by the model name, e.g. `openai_text-davinci-003` diff --git a/modules/text/module_text_llm/.env.example b/modules/text/module_text_llm/.env.example index 34e279aab..823e9a302 100644 --- a/modules/text/module_text_llm/.env.example +++ b/modules/text/module_text_llm/.env.example @@ -12,7 +12,9 @@ DATABASE_URL=sqlite:///../data/data.sqlite # Default model to use # See below for options, available models are also logged on startup -LLM_DEFAULT_MODEL="azure_openai_gpt-35-turbo" +LLM_DEFAULT_MODEL="azure_openai_gpt-4o" +LLM_DEFAULT_MODEL_COST_PER_MILLION_INPUT_TOKEN=5 +LLM_DEFAULT_MODEL_COST_PER_MILLION_OUTPUT_TOKEN=15 # Enable LLM-as-a-judge approach 0 = disabled, 1 = enabled LLM_ENABLE_LLM_AS_A_JUDGE=1 From a373df28f7201ccfbfa3d489da6f59eaa5c7e8e1 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Maximilian=20S=C3=B6lch?= Date: Thu, 24 Oct 2024 14:26:52 +0200 Subject: [PATCH 4/5] Development: Update path for coffee module config to new repo structure in the docker shell script (#351) --- athena-docker.sh | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/athena-docker.sh b/athena-docker.sh index 87fe423eb..6f211bd55 100644 --- a/athena-docker.sh +++ b/athena-docker.sh @@ -40,7 +40,7 @@ function download_cofee_config { mkdir -p ./module_text_cofee for file in traefik.docker.yml node_config.docker.yml; do echo " Downloading $file..." - curl -sSL -o ./module_text_cofee/$file https://raw.githubusercontent.com/ls1intum/Athena/"$pr_branch"/module_text_cofee/"$file" + curl -sSL -o ./module_text_cofee/$file https://raw.githubusercontent.com/ls1intum/Athena/"$pr_branch"/modules/text/module_text_cofee/"$file" done } @@ -146,4 +146,4 @@ case "$subcommand" in general_help exit 1 ;; -esac \ No newline at end of file +esac From 9c49cc8a94d4aec891cd96a65faa96ac5fa6d468 Mon Sep 17 00:00:00 2001 From: Dmytro Polityka <33299157+undernagruzez@users.noreply.github.com> Date: Mon, 28 Oct 2024 16:47:40 +0100 Subject: [PATCH 5/5] `General`: Fix linting issues (#352) --- .../module/request_to_module.py | 1 + .../modeling/module_modeling_llm/poetry.lock | 758 +++++++++--------- .../module_modeling_llm/pyproject.toml | 2 +- .../module_programming_llm/helpers/utils.py | 1 + 4 files changed, 389 insertions(+), 373 deletions(-) diff --git a/assessment_module_manager/assessment_module_manager/module/request_to_module.py b/assessment_module_manager/assessment_module_manager/module/request_to_module.py index 7ce716d06..1e862b269 100644 --- a/assessment_module_manager/assessment_module_manager/module/request_to_module.py +++ b/assessment_module_manager/assessment_module_manager/module/request_to_module.py @@ -33,6 +33,7 @@ async def find_module_by_name(module_name: str) -> Optional[Module]: return None +# pylint: disable=too-many-positional-arguments async def request_to_module(module: Module, headers: dict, path: str, lms_url: str, data: Optional[dict], method: str) -> ModuleResponse: """ Helper function to send a request to a module. diff --git a/modules/modeling/module_modeling_llm/poetry.lock b/modules/modeling/module_modeling_llm/poetry.lock index 5d504ff23..f8b8d2f74 100644 --- a/modules/modeling/module_modeling_llm/poetry.lock +++ b/modules/modeling/module_modeling_llm/poetry.lock @@ -138,13 +138,13 @@ frozenlist = ">=1.1.0" [[package]] name = "anyio" -version = "4.6.0" +version = "4.6.2.post1" description = "High level compatibility layer for multiple asynchronous event loop implementations" optional = false python-versions = ">=3.9" files = [ - {file = "anyio-4.6.0-py3-none-any.whl", hash = "sha256:c7d2e9d63e31599eeb636c8c5c03a7e108d73b345f064f1c19fdc87b79036a9a"}, - {file = "anyio-4.6.0.tar.gz", hash = "sha256:137b4559cbb034c477165047febb6ff83f390fc3b20bf181c1fc0a728cb8beeb"}, + {file = "anyio-4.6.2.post1-py3-none-any.whl", hash = "sha256:6d170c36fba3bdd840c73d3868c1e777e33676a69c3a72cf0a0d5d6d8009b61d"}, + {file = "anyio-4.6.2.post1.tar.gz", hash = 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