From 412a006ed1f809e3b167d292af682bab98b6192c Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Wed, 23 Oct 2024 00:43:58 +0200 Subject: [PATCH 01/34] add ollama model config --- llm_core/llm_core/models/ollama.py | 110 +++++++++++++++++++++++++++++ 1 file changed, 110 insertions(+) create mode 100644 llm_core/llm_core/models/ollama.py diff --git a/llm_core/llm_core/models/ollama.py b/llm_core/llm_core/models/ollama.py new file mode 100644 index 00000000..ba87e2f4 --- /dev/null +++ b/llm_core/llm_core/models/ollama.py @@ -0,0 +1,110 @@ +import requests +from enum import Enum +from llm_core.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" + 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 + + ollama_models = get_ollama_models() + available_models = {} + + if([os.environ["OLLAMA_ENDPOINT"]]): + 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.""" + logger.info("Available ollama models: %s", ", ".join(available_models.keys())) + + 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 From 0efe62a4a6238430a47263559981fbfa57f0701c Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Wed, 23 Oct 2024 00:44:23 +0200 Subject: [PATCH 02/34] git add it to types and adjust predict and parse to recognise llama --- llm_core/llm_core/models/__init__.py | 7 +++++++ llm_core/llm_core/utils/predict_and_parse.py | 7 ++++++- 2 files changed, 13 insertions(+), 1 deletion(-) diff --git a/llm_core/llm_core/models/__init__.py b/llm_core/llm_core/models/__init__.py index 6f9db4fd..20430e79 100644 --- a/llm_core/llm_core/models/__init__.py +++ b/llm_core/llm_core/models/__init__.py @@ -23,6 +23,13 @@ except AttributeError: pass +try: + import llm_core.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/llm_core/llm_core/utils/predict_and_parse.py b/llm_core/llm_core/utils/predict_and_parse.py index d73748bd..52ccdc45 100644 --- a/llm_core/llm_core/utils/predict_and_parse.py +++ b/llm_core/llm_core/utils/predict_and_parse.py @@ -4,9 +4,13 @@ from langchain_core.pydantic_v1 import BaseModel, ValidationError from langchain_core.runnables import RunnableSequence from athena import get_experiment_environment +from langchain_community.chat_models import ChatOllama # type: ignore T = TypeVar("T", bound=BaseModel) +def isOllama(model: BaseLanguageModel) -> bool: + return isinstance(model, ChatOllama) + async def predict_and_parse( model: BaseLanguageModel, chat_prompt: ChatPromptTemplate, @@ -36,7 +40,8 @@ async def predict_and_parse( if experiment.run_id is not None: tags.append(f"run-{experiment.run_id}") - structured_output_llm = model.with_structured_output(pydantic_object, method="json_mode") + + structured_output_llm = model.with_structured_output(pydantic_object, method="json_mode") if not isOllama(model) else model chain = RunnableSequence( chat_prompt, structured_output_llm From cd20d3a12801affb9cab001a3eed879a28a0b769 Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Wed, 23 Oct 2024 00:44:45 +0200 Subject: [PATCH 03/34] update env example and lock --- modules/text/module_text_llm/.env.example | 4 + modules/text/module_text_llm/poetry.lock | 527 +++++++++++----------- 2 files changed, 268 insertions(+), 263 deletions(-) diff --git a/modules/text/module_text_llm/.env.example b/modules/text/module_text_llm/.env.example index 823e9a30..04fb2825 100644 --- a/modules/text/module_text_llm/.env.example +++ b/modules/text/module_text_llm/.env.example @@ -39,3 +39,7 @@ 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= #'https://gpu-artemis.ase.cit.tum.de/ollama' \ No newline at end of file diff --git a/modules/text/module_text_llm/poetry.lock b/modules/text/module_text_llm/poetry.lock index 860a0f71..5f8efd59 100644 --- a/modules/text/module_text_llm/poetry.lock +++ b/modules/text/module_text_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 = 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13:58:37 +0100 Subject: [PATCH 04/34] reslove conflicts --- llm_core/llm_core/utils/predict_and_parse.py | 8 +------- 1 file changed, 1 insertion(+), 7 deletions(-) diff --git a/llm_core/llm_core/utils/predict_and_parse.py b/llm_core/llm_core/utils/predict_and_parse.py index aa6bea6e..c7973fb2 100644 --- a/llm_core/llm_core/utils/predict_and_parse.py +++ b/llm_core/llm_core/utils/predict_and_parse.py @@ -67,10 +67,4 @@ async def predict_and_parse( return await chain.ainvoke(prompt_input, config={"tags": tags}) except ValidationError as e: raise ValueError(f"Could not parse output: {e}") from e - - - - try: - return await chain.ainvoke(prompt_input, config={"tags": tags}) - except ValidationError as e: - raise ValueError(f"Could not parse output: {e}") from e \ No newline at end of file + \ No newline at end of file From fc22aea489e46069e959bc9cca0f5125d2886746 Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Mon, 2 Dec 2024 14:10:14 +0100 Subject: [PATCH 05/34] use try catch --- llm_core/llm_core/models/ollama.py | 201 ++-- modules/text/module_text_llm/poetry.lock | 1333 +++++++++------------- 2 files changed, 635 insertions(+), 899 deletions(-) diff --git a/llm_core/llm_core/models/ollama.py b/llm_core/llm_core/models/ollama.py index ba87e2f4..9fc2425f 100644 --- a/llm_core/llm_core/models/ollama.py +++ b/llm_core/llm_core/models/ollama.py @@ -6,105 +6,110 @@ import os from langchain_community.chat_models import ChatOllama # type: ignore from athena.logger import logger +from requests.exceptions import RequestException, Timeout if os.environ.get('GPU_USER') and os.environ.get('GPU_PASSWORD') and os.environ.get('OLLAMA_ENDPOINT') is not None: + try: + 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" + 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 + + ollama_models = get_ollama_models() + available_models = {} + + if([os.environ["OLLAMA_ENDPOINT"]]): + 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.""" + logger.info("Available ollama models: %s", ", ".join(available_models.keys())) + + 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="") - 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" - 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 - - ollama_models = get_ollama_models() - available_models = {} - - if([os.environ["OLLAMA_ENDPOINT"]]): - 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.""" - logger.info("Available ollama models: %s", ", ".join(available_models.keys())) - - 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. - """ + 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 - 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 + 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' + except Timeout: + print("Connection timed out. Skipping server connection step.") + except RequestException as e: + print(f"Failed to connect to the server: {e}. 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.../prompt_generate_feedback.py | 46 +++++++ .../prompt_thinking.py | 47 +++++++ 12 files changed, 295 insertions(+), 8 deletions(-) create mode 100644 modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/__init__.py create mode 100644 modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/generate_suggestions.py create mode 100644 modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/prompt_generate_feedback.py create mode 100644 modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/prompt_thinking.py diff --git a/llm_core/llm_core/models/__init__.py b/llm_core/llm_core/models/__init__.py index 022e4a98..ada79f63 100644 --- a/llm_core/llm_core/models/__init__.py +++ b/llm_core/llm_core/models/__init__.py @@ -7,6 +7,7 @@ DefaultModelConfig: Type[ModelConfig] MiniModelConfig: ModelConfig +OllamaModelConfig: ModelConfig default_model_name = os.environ.get("LLM_DEFAULT_MODEL") evaluation_model_name = os.environ.get("LLM_EVALUATION_MODEL") @@ -29,6 +30,7 @@ try: import llm_core.models.ollama as ollama_config #type: ignore types.append(ollama_config.OllamaModelConfig) + OllamaModelConfig = ollama_config.OllamaModelConfig(model_name="llama3.1:70b",max_tokens=1000, temperature=0,top_p=1,presence_penalty=0,frequency_penalty=0) # DefaultModelConfig = ollama_config.OllamaModelConfig except AttributeError: pass diff --git a/llm_core/llm_core/utils/llm_utils.py b/llm_core/llm_core/utils/llm_utils.py index 0bfeb047..9ac6f5dd 100644 --- a/llm_core/llm_core/utils/llm_utils.py +++ b/llm_core/llm_core/utils/llm_utils.py @@ -107,4 +107,24 @@ 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]) \ No newline at end of file + return ChatPromptTemplate.from_messages([system_message_prompt, human_message_prompt]) + +def get_simple_chat_prompt( + system_message: str, + human_message: str, + ) -> ChatPromptTemplate: + + sys = """ + You are an AI Tutor. You are tasked with grading a student submission based on this problem statement and grading instructions. You must not excede the maximum amount of points. Take time to think, which points on the grading instructions are relevant for the students submission. + Further more, if a feedback is specific to a sentence in the student submission, that specify this as well on your feedback. Also specify, when possible, which grading instruction you are refering to. + # Problem statement + {problem_statement} + + # Grading instructions + {grading_instructions} + Max points: {max_points} + """ + + 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]) \ No newline at end of file diff --git a/llm_core/llm_core/utils/predict_and_parse.py b/llm_core/llm_core/utils/predict_and_parse.py index c7973fb2..13315113 100644 --- a/llm_core/llm_core/utils/predict_and_parse.py +++ b/llm_core/llm_core/utils/predict_and_parse.py @@ -5,12 +5,34 @@ from langchain_core.runnables import RunnableSequence from athena import get_experiment_environment from langchain_community.chat_models import ChatOllama # type: ignore - +from langchain.output_parsers import PydanticOutputParser T = TypeVar("T", bound=BaseModel) def isOllama(model: BaseLanguageModel) -> bool: return isinstance(model, ChatOllama) +async def predict_plain_text( + model: BaseLanguageModel, + chat_prompt: ChatPromptTemplate, + prompt_input: dict, + tags: Optional[List[str]]) -> Optional[str]: + """Predict plain text using the provided model and prompt. + + Args: + model (BaseLanguageModel): The model to predict with. + chat_prompt (ChatPromptTemplate): The prompt template to use. + prompt_input (dict): Input parameters to use for the prompt. + tags (Optional[List[str]]): List of tags to tag the prediction with. + + Returns: + Optional[str]: Prediction as a string, or None if it failed. + """ + try: + chain = chat_prompt | model + return await chain.ainvoke(prompt_input, config={"tags": tags}) + except: + raise ValueError("Llm prediction failed.") + async def predict_and_parse( model: BaseLanguageModel, chat_prompt: ChatPromptTemplate, @@ -41,7 +63,14 @@ async def predict_and_parse( if experiment.run_id is not None: tags.append(f"run-{experiment.run_id}") - + if isOllama(model): + try: + outputParser = PydanticOutputParser(pydantic_object = pydantic_object) + chain = chat_prompt | model | outputParser + return await chain.ainvoke(prompt_input, config={"tags": tags}) + except ValidationError as e: + raise ValueError(f"Could not parse output: {e}") from e + if (use_function_calling): structured_output_llm = model.with_structured_output(pydantic_object) chain = chat_prompt | structured_output_llm @@ -67,4 +96,4 @@ async def predict_and_parse( return await chain.ainvoke(prompt_input, config={"tags": tags}) except ValidationError as e: raise ValueError(f"Could not parse output: {e}") from e - \ No newline at end of file + \ No newline at end of file diff --git a/modules/text/module_text_llm/module_text_llm/approach_config.py b/modules/text/module_text_llm/module_text_llm/approach_config.py index 6626fdd8..a4e8fd5e 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_config.py +++ b/modules/text/module_text_llm/module_text_llm/approach_config.py @@ -6,6 +6,7 @@ class ApproachType(str, Enum): basic = "BasicApproach" chain_of_thought = "ChainOfThought" + ollama_cot = "OllamaChainOfThought" class ApproachConfig(BaseModel, ABC): max_input_tokens: int = Field(default=3000, description="Maximum number of tokens in the input prompt.") diff --git a/modules/text/module_text_llm/module_text_llm/approach_controller.py b/modules/text/module_text_llm/module_text_llm/approach_controller.py index 69a5cc69..9f281f4a 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_controller.py +++ b/modules/text/module_text_llm/module_text_llm/approach_controller.py @@ -2,14 +2,18 @@ from athena.text import Exercise, Submission, Feedback from module_text_llm.basic_approach import BasicApproachConfig from module_text_llm.chain_of_thought_approach import ChainOfThoughtConfig +from module_text_llm.ollama_chain_of_thought_approach import ChainOfThoughtConfig as OllamaChainOfThoughtConfig from module_text_llm.approach_config import ApproachConfig from module_text_llm.basic_approach.generate_suggestions import generate_suggestions as generate_suggestions_basic from module_text_llm.chain_of_thought_approach.generate_suggestions import generate_suggestions as generate_cot_suggestions - +from module_text_llm.ollama_chain_of_thought_approach.generate_suggestions import generate_suggestions as generate_cot_ollana_suggestions async def generate_suggestions(exercise: Exercise, submission: Submission, config: ApproachConfig, debug: bool) -> List[Feedback]: if isinstance(config, BasicApproachConfig): return await generate_suggestions_basic(exercise, submission, config, debug) if isinstance(config, ChainOfThoughtConfig): return await generate_cot_suggestions(exercise, submission, config, debug) + if isinstance(config, OllamaChainOfThoughtConfig): + return await generate_cot_ollana_suggestions(exercise, submission, config, debug) raise ValueError("Unsupported config type provided.") + diff --git a/modules/text/module_text_llm/module_text_llm/basic_approach/generate_suggestions.py b/modules/text/module_text_llm/module_text_llm/basic_approach/generate_suggestions.py index 6cdf5b36..7cc14ebd 100644 --- a/modules/text/module_text_llm/module_text_llm/basic_approach/generate_suggestions.py +++ b/modules/text/module_text_llm/module_text_llm/basic_approach/generate_suggestions.py @@ -9,7 +9,6 @@ num_tokens_from_prompt, ) from llm_core.utils.predict_and_parse import predict_and_parse - from module_text_llm.config import BasicApproachConfig from module_text_llm.helpers.utils import add_sentence_numbers, get_index_range_from_line_range, format_grading_instructions from module_text_llm.basic_approach.prompt_generate_suggestions import AssessmentModel diff --git a/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/prompt_generate_feedback.py b/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/prompt_generate_feedback.py index 9065ad67..516ed854 100644 --- a/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/prompt_generate_feedback.py +++ b/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/prompt_generate_feedback.py @@ -52,4 +52,5 @@ class FeedbackModel(BaseModel): class AssessmentModel(BaseModel): """Collection of feedbacks making up an assessment""" - feedbacks: List[FeedbackModel] = Field(description="Assessment feedbacks") \ No newline at end of file + feedbacks: List[FeedbackModel] = Field(description="Assessment feedbacks") + \ No newline at end of file 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 c620e62e..1a767246 100644 --- a/modules/text/module_text_llm/module_text_llm/config.py +++ b/modules/text/module_text_llm/module_text_llm/config.py @@ -4,8 +4,9 @@ from module_text_llm.chain_of_thought_approach import ChainOfThoughtConfig from module_text_llm.basic_approach import BasicApproachConfig +from module_text_llm.ollama_chain_of_thought_approach import ChainOfThoughtConfig as OllamaChainOfThoughtConfig -ApproachConfigUnion = Union[BasicApproachConfig, ChainOfThoughtConfig] +ApproachConfigUnion = Union[BasicApproachConfig, ChainOfThoughtConfig, OllamaChainOfThoughtConfig] @config_schema_provider class Configuration(BaseModel): diff --git a/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/__init__.py b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/__init__.py new file mode 100644 index 00000000..d3ec3b1f --- /dev/null +++ b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/__init__.py @@ -0,0 +1,15 @@ +from pydantic import BaseModel, Field +from typing import Literal +from llm_core.models import ModelConfigType, OllamaModelConfig + +from module_text_llm.approach_config import ApproachConfig +from module_text_llm.ollama_chain_of_thought_approach.prompt_generate_feedback import CoTGenerateSuggestionsPrompt +from module_text_llm.ollama_chain_of_thought_approach.prompt_thinking import ThinkingPrompt + +class ChainOfThoughtConfig(ApproachConfig): + # Defaults to the cheaper mini 4o model + type: Literal['ollama_chain_of_thought'] = 'ollama_chain_of_thought' + model: ModelConfigType = Field(default=OllamaModelConfig) # type: ignore + thikning_prompt: ThinkingPrompt = Field(default=ThinkingPrompt()) + generate_suggestions_prompt: CoTGenerateSuggestionsPrompt = Field(default=CoTGenerateSuggestionsPrompt()) + \ No newline at end of file diff --git a/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/generate_suggestions.py b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/generate_suggestions.py new file mode 100644 index 00000000..acab1e99 --- /dev/null +++ b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/generate_suggestions.py @@ -0,0 +1,122 @@ +from typing import List, Optional +from pydantic import BaseModel, Field + +from athena import emit_meta +from athena.text import Exercise, Submission, Feedback +from athena.logger import logger + +from module_text_llm.chain_of_thought_approach import ChainOfThoughtConfig + +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, + get_simple_chat_prompt +) +from llm_core.utils.predict_and_parse import predict_and_parse, predict_plain_text + +from module_text_llm.helpers.utils import add_sentence_numbers, get_index_range_from_line_range, format_grading_instructions +from module_text_llm.ollama_chain_of_thought_approach.prompt_generate_feedback import AssessmentModel + + +async def generate_suggestions(exercise: Exercise, submission: Submission, config: ChainOfThoughtConfig, debug: bool) -> List[Feedback]: + model = config.model.get_model() # type: ignore[attr-defined] + + prompt_input = { + "max_points": exercise.max_points, + "bonus_points": exercise.bonus_points, + "grading_instructions": format_grading_instructions(exercise.grading_instructions, exercise.grading_criteria), + "problem_statement": exercise.problem_statement or "No problem statement.", + "example_solution": exercise.example_solution, + "submission": add_sentence_numbers(submission.text) + } + + chat_prompt = get_simple_chat_prompt( + system_message=config.thikning_prompt.system_message, + human_message=config.thikning_prompt.human_message, + ) + + + + # Check if the prompt is too long and omit features if necessary (in order of importance) + omittable_features = ["example_solution", "problem_statement", "grading_instructions"] + prompt_input, should_run = check_prompt_length_and_omit_features_if_necessary( + prompt=chat_prompt, + prompt_input= prompt_input, + max_input_tokens=config.max_input_tokens, + omittable_features=omittable_features, + debug=debug + ) + + # Skip if the prompt is too long + if not should_run: + logger.warning("Input too long. Skipping.") + if debug: + emit_meta("prompt", chat_prompt.format(**prompt_input)) + emit_meta("error", f"Input too long {num_tokens_from_prompt(chat_prompt, prompt_input)} > {config.max_input_tokens}") + return [] + + initial_result = await predict_plain_text( + model=model, + chat_prompt=chat_prompt, + prompt_input=prompt_input, + tags=[ + f"exercise-{exercise.id}", + f"submission-{submission.id}", + ], + ) + + second_prompt_input = { + "answer" : initial_result, + + } + + second_chat_prompt = get_chat_prompt_with_formatting_instructions( + model=model, + system_message=config.generate_suggestions_prompt.second_system_message, + human_message=config.generate_suggestions_prompt.answer_message, + pydantic_object=AssessmentModel) + + result = await predict_and_parse( + model=model, + chat_prompt=second_chat_prompt, + prompt_input=second_prompt_input, + pydantic_object=AssessmentModel, + tags=[ + f"exercise-{exercise.id}", + f"submission-{submission.id}", + ] ) + + if debug: + emit_meta("generate_suggestions", { + "prompt": chat_prompt.format(**prompt_input), + "result": result.dict() if result is not None else None + }) + + + if result is None: + return [] + + grading_instruction_ids = set( + grading_instruction.id + for criterion in exercise.grading_criteria or [] + for grading_instruction in criterion.structured_grading_instructions + ) + + feedbacks = [] + for feedback in result.feedback_list: + index_start, index_end = get_index_range_from_line_range(feedback.line_start, feedback.line_end, submission.text) + grading_instruction_id = feedback.grading_instruction_id if feedback.grading_instruction_id in grading_instruction_ids else None + feedbacks.append(Feedback( + exercise_id=exercise.id, + submission_id=submission.id, + title=feedback.title, + description=feedback.description, + index_start=index_start, + index_end=index_end, + credits=feedback.credits, + structured_grading_instruction_id=grading_instruction_id, + meta={} + )) + + return feedbacks \ No newline at end of file diff --git a/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/prompt_generate_feedback.py b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/prompt_generate_feedback.py new file mode 100644 index 00000000..7e25e0d1 --- /dev/null +++ b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/prompt_generate_feedback.py @@ -0,0 +1,46 @@ +from pydantic import BaseModel, Field +from typing import List, Optional + +system_message = """ + Your task is to format the given text from the human into a json. The json must strictly follow the following instructions: +You should only reply in valid json without any additional comments. +The json must begin with the property "feedback_list" which is an array of many feedback elements. Each element of this array only has these fields and it must contain all of them with the exact same name as given here: "feedback_list", which contains "description", "credits", "line_start", "line_end", "title", "grading_instruction_id". + + """ + +human_message = """\ +\"\"\" +{answer} +\"\"\"\ +""" + +# Input Prompt + +class CoTGenerateSuggestionsPrompt(BaseModel): + """\ +Features cit available: **{problem_statement}**, **{example_solution}**, **{grading_instructions}**, **{max_points}**, **{bonus_points}**, **{submission}** + +_Note: **{problem_statement}**, **{example_solution}**, or **{grading_instructions}** might be omitted if the input is too long._\ +""" + second_system_message: str = Field(default=system_message, + description="Message for priming AI behavior and instructing it what to do.") + answer_message: str = Field(default=human_message, + description="Message from a human. The input on which the AI is supposed to act.") + + +# Output Object + +class FeedbackModel(BaseModel): + title: str = Field(description="Very short title, i.e. feedback category or similar", example="Logic Error") + description: str = Field(description="Feedback description") + line_start: Optional[int] = Field(description="Referenced line number start, or empty if unreferenced") + line_end: Optional[int] = Field(description="Referenced line number end, or empty if unreferenced") + credits: float = Field(0.0, description="Number of points received/deducted") + grading_instruction_id: Optional[int] = Field( + description="ID of the grading instruction that was used to generate this feedback, or empty if no grading instruction was used" + ) + +class AssessmentModel(BaseModel): + """Collection of feedbacks making up an assessment""" + + feedback_list: List[FeedbackModel] = Field(description="Assessment feedbacks") \ No newline at end of file diff --git a/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/prompt_thinking.py b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/prompt_thinking.py new file mode 100644 index 00000000..2530b98d --- /dev/null +++ b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/prompt_thinking.py @@ -0,0 +1,47 @@ +from pydantic import BaseModel, Field +from typing import Optional, List + +system_message = """ + You are an AI Tutor. You are tasked with grading a student submission based on this problem statement and grading instructions. You must not excede the maximum amount of points. Take time to think, which points on the grading instructions are relevant for the students submission. + Further more, if a feedback is specific to a sentence in the student submission, that specify this as well on your feedback. Also specify, when possible, which grading instruction you are refering to. + # Problem statement + {problem_statement} + + # Grading instructions + {grading_instructions} + Max points: {max_points} + """ + +human_message = """\ +Student\'s submission to grade (with sentence numbers : ): +\"\"\" +{submission} +\"\"\"\ +""" + +# Input Prompt +class ThinkingPrompt(BaseModel): + """\ +Features available: **{problem_statement}**, **{example_solution}**, **{grading_instructions}**, **{max_points}**, **{bonus_points}**, **{submission}** + +_Note: **{problem_statement}**, **{example_solution}**, or **{grading_instructions}** might be omitted if the input is too long._\ +""" + system_message: str = Field(default=system_message, + description="Message for priming AI behavior and instructing it what to do.") + human_message: str = Field(default=human_message, + description="Message from a human. The input on which the AI is supposed to act.") + +# Output Object +class InitialAssessment(BaseModel): + title: str = Field(description="Very short title, i.e. feedback category or similar", example="Logic Error") + description: str = Field(description="Feedback description") + line_start: Optional[int] = Field(description="Referenced line number start, or empty if unreferenced") + line_end: Optional[int] = Field(description="Referenced line number end, or empty if unreferenced") + credits: float = Field(0.0, description="Number of points received/deducted") + reasoning: str = Field(description="Reasoning why the feedback was given") + impprovment_suggestion: str = Field(description="Suggestion for improvement for the student") + +class InitialAssessmentModel(BaseModel): + """Collection of feedbacks making up an assessment""" + + feedbacks: List[InitialAssessment] = Field(description="Assessment feedbacks") \ No newline at end of file From 5de2759d0d50fcd37332e2fac46d3c5f202d2132 Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Mon, 2 Dec 2024 17:17:18 +0100 Subject: [PATCH 07/34] fix linting issues --- .../module_text_llm/module_text_llm/approach_controller.py | 3 +-- modules/text/module_text_llm/module_text_llm/config.py | 2 +- .../ollama_chain_of_thought_approach/__init__.py | 2 +- 3 files changed, 3 insertions(+), 4 deletions(-) diff --git a/modules/text/module_text_llm/module_text_llm/approach_controller.py b/modules/text/module_text_llm/module_text_llm/approach_controller.py index 9f281f4a..ce851de3 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_controller.py +++ b/modules/text/module_text_llm/module_text_llm/approach_controller.py @@ -2,7 +2,7 @@ from athena.text import Exercise, Submission, Feedback from module_text_llm.basic_approach import BasicApproachConfig from module_text_llm.chain_of_thought_approach import ChainOfThoughtConfig -from module_text_llm.ollama_chain_of_thought_approach import ChainOfThoughtConfig as OllamaChainOfThoughtConfig +from module_text_llm.ollama_chain_of_thought_approach import OllamaChainOfThoughtConfig from module_text_llm.approach_config import ApproachConfig from module_text_llm.basic_approach.generate_suggestions import generate_suggestions as generate_suggestions_basic @@ -16,4 +16,3 @@ async def generate_suggestions(exercise: Exercise, submission: Submission, confi if isinstance(config, OllamaChainOfThoughtConfig): return await generate_cot_ollana_suggestions(exercise, submission, config, debug) raise ValueError("Unsupported config type provided.") - 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 1a767246..8ebc5928 100644 --- a/modules/text/module_text_llm/module_text_llm/config.py +++ b/modules/text/module_text_llm/module_text_llm/config.py @@ -4,7 +4,7 @@ from module_text_llm.chain_of_thought_approach import ChainOfThoughtConfig from module_text_llm.basic_approach import BasicApproachConfig -from module_text_llm.ollama_chain_of_thought_approach import ChainOfThoughtConfig as OllamaChainOfThoughtConfig +from module_text_llm.ollama_chain_of_thought_approach import OllamaChainOfThoughtConfig ApproachConfigUnion = Union[BasicApproachConfig, ChainOfThoughtConfig, OllamaChainOfThoughtConfig] diff --git a/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/__init__.py b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/__init__.py index d3ec3b1f..2bdd0059 100644 --- a/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/__init__.py +++ b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/__init__.py @@ -6,7 +6,7 @@ from module_text_llm.ollama_chain_of_thought_approach.prompt_generate_feedback import CoTGenerateSuggestionsPrompt from module_text_llm.ollama_chain_of_thought_approach.prompt_thinking import ThinkingPrompt -class ChainOfThoughtConfig(ApproachConfig): +class OllamaChainOfThoughtConfig(ApproachConfig): # Defaults to the cheaper mini 4o model type: Literal['ollama_chain_of_thought'] = 'ollama_chain_of_thought' model: ModelConfigType = Field(default=OllamaModelConfig) # type: ignore From c98a8e59c239b8a6e40359d3a7f7e3bc1ce7a9f6 Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Tue, 31 Dec 2024 16:32:14 +0100 Subject: [PATCH 08/34] base of strategy pattern --- .../module_text_llm/approach_config.py | 7 + .../module_text_llm/approach_controller.py | 15 + .../basic_approach/__init__.py | 7 +- .../basic_approach/generate_suggestions.py | 3 +- modules/text/module_text_llm/poetry.lock | 796 +++++++++--------- 5 files changed, 423 insertions(+), 405 deletions(-) diff --git a/modules/text/module_text_llm/module_text_llm/approach_config.py b/modules/text/module_text_llm/module_text_llm/approach_config.py index 6626fdd8..d71e44f5 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_config.py +++ b/modules/text/module_text_llm/module_text_llm/approach_config.py @@ -2,6 +2,9 @@ from pydantic import BaseModel, Field from llm_core.models import ModelConfigType, DefaultModelConfig from enum import Enum +from abc import ABC, abstractmethod +from athena.text import Exercise, Submission + class ApproachType(str, Enum): basic = "BasicApproach" @@ -12,5 +15,9 @@ class ApproachConfig(BaseModel, ABC): model: ModelConfigType = Field(default=DefaultModelConfig()) type: str = Field(..., description="The type of approach config") + # @abstractmethod + # async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, debug: bool): + # pass + class Config: use_enum_values = True \ No newline at end of file diff --git a/modules/text/module_text_llm/module_text_llm/approach_controller.py b/modules/text/module_text_llm/module_text_llm/approach_controller.py index 69a5cc69..c3cc9761 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_controller.py +++ b/modules/text/module_text_llm/module_text_llm/approach_controller.py @@ -6,8 +6,23 @@ from module_text_llm.basic_approach.generate_suggestions import generate_suggestions as generate_suggestions_basic from module_text_llm.chain_of_thought_approach.generate_suggestions import generate_suggestions as generate_cot_suggestions +import importlib +import pkgutil +import inspect + +def discover_approach_configs(base_package="modules/text/module_text_llm/module_text_llm"): + configs = {} + package = importlib.import_module(base_package) + for _, module_name, _ in pkgutil.iter_modules(package.__path__): + module = importlib.import_module(f"{base_package}.{module_name}") + for name, obj in inspect.getmembers(module, inspect.isclass): + if issubclass(obj, ApproachConfig) and obj is not ApproachConfig: + configs[obj.__name__] = obj + return configs async def generate_suggestions(exercise: Exercise, submission: Submission, config: ApproachConfig, debug: bool) -> List[Feedback]: + # print(discover_approach_configs()) + return [] if isinstance(config, BasicApproachConfig): return await generate_suggestions_basic(exercise, submission, config, debug) if isinstance(config, ChainOfThoughtConfig): diff --git a/modules/text/module_text_llm/module_text_llm/basic_approach/__init__.py b/modules/text/module_text_llm/module_text_llm/basic_approach/__init__.py index cc8c8e56..f5ff9f51 100644 --- a/modules/text/module_text_llm/module_text_llm/basic_approach/__init__.py +++ b/modules/text/module_text_llm/module_text_llm/basic_approach/__init__.py @@ -1,11 +1,12 @@ from module_text_llm.approach_config import ApproachConfig from pydantic import Field from typing import Literal - - +# from module_text_llm.basic_approach.generate_suggestions import generate_suggestions +from athena.text import Exercise, Submission from module_text_llm.basic_approach.prompt_generate_suggestions import GenerateSuggestionsPrompt class BasicApproachConfig(ApproachConfig): type: Literal['basic'] = 'basic' generate_suggestions_prompt: GenerateSuggestionsPrompt = Field(default=GenerateSuggestionsPrompt()) - \ No newline at end of file + # async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, debug: bool): + # await generate_suggestions(exercise,submission,config,debug) \ No newline at end of file diff --git a/modules/text/module_text_llm/module_text_llm/basic_approach/generate_suggestions.py b/modules/text/module_text_llm/module_text_llm/basic_approach/generate_suggestions.py index 6cdf5b36..14df255e 100644 --- a/modules/text/module_text_llm/module_text_llm/basic_approach/generate_suggestions.py +++ b/modules/text/module_text_llm/module_text_llm/basic_approach/generate_suggestions.py @@ -1,4 +1,5 @@ from typing import List +# from module_text_llm.approach_config import ApproachConfig from athena import emit_meta from athena.text import Exercise, Submission, Feedback @@ -14,7 +15,7 @@ from module_text_llm.helpers.utils import add_sentence_numbers, get_index_range_from_line_range, format_grading_instructions from module_text_llm.basic_approach.prompt_generate_suggestions import AssessmentModel -async def generate_suggestions(exercise: Exercise, submission: Submission, config: BasicApproachConfig, debug: bool) -> List[Feedback]: +async def generate_suggestions(exercise: Exercise, submission: Submission, config:BasicApproachConfig, debug: bool) -> List[Feedback]: model = config.model.get_model() # type: ignore[attr-defined] prompt_input = { "max_points": exercise.max_points, diff --git a/modules/text/module_text_llm/poetry.lock b/modules/text/module_text_llm/poetry.lock index f09c63c2..9f12b92d 100644 --- a/modules/text/module_text_llm/poetry.lock +++ b/modules/text/module_text_llm/poetry.lock @@ -13,87 +13,87 @@ files = [ [[package]] name = "aiohttp" -version = "3.11.10" +version = "3.11.11" description = "Async http client/server framework (asyncio)" optional = false python-versions = ">=3.9" files = [ - {file = 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a/modules/text/module_text_llm/module_text_llm/approach_config.py +++ b/modules/text/module_text_llm/module_text_llm/approach_config.py @@ -15,9 +15,9 @@ class ApproachConfig(BaseModel, ABC): model: ModelConfigType = Field(default=DefaultModelConfig()) type: str = Field(..., description="The type of approach config") - # @abstractmethod - # async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, debug: bool): - # pass + @abstractmethod + async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, debug: bool): + pass class Config: use_enum_values = True \ No newline at end of file diff --git a/modules/text/module_text_llm/module_text_llm/approach_controller.py b/modules/text/module_text_llm/module_text_llm/approach_controller.py index c3cc9761..3508ca92 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_controller.py +++ b/modules/text/module_text_llm/module_text_llm/approach_controller.py @@ -10,7 +10,7 @@ import pkgutil import inspect -def discover_approach_configs(base_package="modules/text/module_text_llm/module_text_llm"): +def discover_approach_configs(base_package="module_text_llm"):#modules/text/module_text_llm/ configs = {} package = importlib.import_module(base_package) for _, module_name, _ in pkgutil.iter_modules(package.__path__): @@ -20,11 +20,36 @@ def discover_approach_configs(base_package="modules/text/module_text_llm/module_ configs[obj.__name__] = obj return configs +class SuggestionStrategyFactory: + _strategies = {} + + @staticmethod + def initialize_strategies(): + configs = discover_approach_configs() + for config_name, config_class in configs.items(): + strategy_class_name = config_name#f"{config_name.replace('Config', '')}SuggestionStrategy" + strategy_class = globals().get(strategy_class_name) + if strategy_class: + SuggestionStrategyFactory._strategies[config_name] = strategy_class + + @staticmethod + def get_strategy(config): + if not SuggestionStrategyFactory._strategies: + SuggestionStrategyFactory.initialize_strategies() + + config_type = type(config).__name__ + strategy_class = SuggestionStrategyFactory._strategies.get(config_type) + if not strategy_class: + raise ValueError(f"No strategy found for config type: {config_type}") + return strategy_class() + async def generate_suggestions(exercise: Exercise, submission: Submission, config: ApproachConfig, debug: bool) -> List[Feedback]: # print(discover_approach_configs()) - return [] - if isinstance(config, BasicApproachConfig): - return await generate_suggestions_basic(exercise, submission, config, debug) - if isinstance(config, ChainOfThoughtConfig): - return await generate_cot_suggestions(exercise, submission, config, debug) - raise ValueError("Unsupported config type provided.") + # return [] + strategy = SuggestionStrategyFactory.get_strategy(config) + return await strategy.generate_suggestions(exercise, submission, config, debug) + # if isinstance(config, BasicApproachConfig): + # return await generate_suggestions_basic(exercise, submission, config, debug) + # if isinstance(config, ChainOfThoughtConfig): + # return await generate_cot_suggestions(exercise, submission, config, debug) + # raise ValueError("Unsupported config type provided.") diff --git a/modules/text/module_text_llm/module_text_llm/basic_approach/__init__.py b/modules/text/module_text_llm/module_text_llm/basic_approach/__init__.py index f5ff9f51..caee8054 100644 --- a/modules/text/module_text_llm/module_text_llm/basic_approach/__init__.py +++ b/modules/text/module_text_llm/module_text_llm/basic_approach/__init__.py @@ -1,12 +1,14 @@ from module_text_llm.approach_config import ApproachConfig from pydantic import Field from typing import Literal -# from module_text_llm.basic_approach.generate_suggestions import generate_suggestions +from module_text_llm.basic_approach.generate_suggestions import generate_suggestions from athena.text import Exercise, Submission from module_text_llm.basic_approach.prompt_generate_suggestions import GenerateSuggestionsPrompt class BasicApproachConfig(ApproachConfig): type: Literal['basic'] = 'basic' generate_suggestions_prompt: GenerateSuggestionsPrompt = Field(default=GenerateSuggestionsPrompt()) - # async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, debug: bool): - # await generate_suggestions(exercise,submission,config,debug) \ No newline at end of file + + async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, debug: bool): + return await generate_suggestions(exercise,submission,config,debug) + \ No newline at end of file diff --git a/modules/text/module_text_llm/module_text_llm/basic_approach/generate_suggestions.py b/modules/text/module_text_llm/module_text_llm/basic_approach/generate_suggestions.py index 14df255e..1647abbc 100644 --- a/modules/text/module_text_llm/module_text_llm/basic_approach/generate_suggestions.py +++ b/modules/text/module_text_llm/module_text_llm/basic_approach/generate_suggestions.py @@ -1,5 +1,5 @@ from typing import List -# from module_text_llm.approach_config import ApproachConfig +from module_text_llm.approach_config import ApproachConfig from athena import emit_meta from athena.text import Exercise, Submission, Feedback @@ -11,11 +11,11 @@ ) from llm_core.utils.predict_and_parse import predict_and_parse -from module_text_llm.config import BasicApproachConfig +# from module_text_llm.config import BasicApproachConfig from module_text_llm.helpers.utils import add_sentence_numbers, get_index_range_from_line_range, format_grading_instructions from module_text_llm.basic_approach.prompt_generate_suggestions import AssessmentModel -async def generate_suggestions(exercise: Exercise, submission: Submission, config:BasicApproachConfig, debug: bool) -> List[Feedback]: +async def generate_suggestions(exercise: Exercise, submission: Submission, config:ApproachConfig, debug: bool) -> List[Feedback]: model = config.model.get_model() # type: ignore[attr-defined] prompt_input = { "max_points": exercise.max_points, diff --git a/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/__init__.py b/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/__init__.py index f125091b..a058842e 100644 --- a/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/__init__.py +++ b/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/__init__.py @@ -1,14 +1,16 @@ -from pydantic import BaseModel, Field +from pydantic import Field from typing import Literal -from llm_core.models import ModelConfigType, DefaultModelConfig - +from athena.text import Exercise, Submission from module_text_llm.approach_config import ApproachConfig from module_text_llm.chain_of_thought_approach.prompt_generate_feedback import CoTGenerateSuggestionsPrompt from module_text_llm.chain_of_thought_approach.prompt_thinking import ThinkingPrompt +from module_text_llm.chain_of_thought_approach.generate_suggestions import generate_suggestions class ChainOfThoughtConfig(ApproachConfig): type: Literal['chain_of_thought'] = 'chain_of_thought' - model: ModelConfigType = Field(default=DefaultModelConfig) # type: ignore thikning_prompt: ThinkingPrompt = Field(default=ThinkingPrompt()) generate_suggestions_prompt: CoTGenerateSuggestionsPrompt = Field(default=CoTGenerateSuggestionsPrompt()) + + async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, debug: bool): + return await generate_suggestions(exercise,submission,config,debug) \ No newline at end of file diff --git a/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/generate_suggestions.py b/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/generate_suggestions.py index 6b86dc97..ace3997e 100644 --- a/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/generate_suggestions.py +++ b/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/generate_suggestions.py @@ -1,11 +1,10 @@ -from typing import List, Optional -from pydantic import BaseModel, Field +from typing import List from athena import emit_meta from athena.text import Exercise, Submission, Feedback from athena.logger import logger -from module_text_llm.chain_of_thought_approach import ChainOfThoughtConfig +from module_text_llm.approach_config import ApproachConfig from llm_core.utils.llm_utils import ( get_chat_prompt_with_formatting_instructions, @@ -19,7 +18,7 @@ from module_text_llm.chain_of_thought_approach.prompt_generate_feedback import AssessmentModel -async def generate_suggestions(exercise: Exercise, submission: Submission, config: ChainOfThoughtConfig, debug: bool) -> List[Feedback]: +async def generate_suggestions(exercise: Exercise, submission: Submission, config: ApproachConfig, debug: bool) -> List[Feedback]: model = config.model.get_model() # type: ignore[attr-defined] prompt_input = { From 8123e8ec756f72499fcab1fdd88a22743662b940 Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Tue, 31 Dec 2024 19:15:23 +0100 Subject: [PATCH 10/34] fix package/class discovery --- .../module_text_llm/approach_controller.py | 58 +++++++++++++------ 1 file changed, 40 insertions(+), 18 deletions(-) diff --git a/modules/text/module_text_llm/module_text_llm/approach_controller.py b/modules/text/module_text_llm/module_text_llm/approach_controller.py index 3508ca92..1f73e25e 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_controller.py +++ b/modules/text/module_text_llm/module_text_llm/approach_controller.py @@ -1,16 +1,17 @@ from typing import List from athena.text import Exercise, Submission, Feedback -from module_text_llm.basic_approach import BasicApproachConfig -from module_text_llm.chain_of_thought_approach import ChainOfThoughtConfig +# from module_text_llm.basic_approach import BasicApproachConfig +# from module_text_llm.chain_of_thought_approach import ChainOfThoughtConfig from module_text_llm.approach_config import ApproachConfig -from module_text_llm.basic_approach.generate_suggestions import generate_suggestions as generate_suggestions_basic -from module_text_llm.chain_of_thought_approach.generate_suggestions import generate_suggestions as generate_cot_suggestions +# from module_text_llm.basic_approach.generate_suggestions import generate_suggestions as generate_suggestions_basic +# from module_text_llm.chain_of_thought_approach.generate_suggestions import generate_suggestions as generate_cot_suggestions import importlib import pkgutil import inspect +from typing import Dict -def discover_approach_configs(base_package="module_text_llm"):#modules/text/module_text_llm/ +def discover_approach_configs(base_package="module_text_llm"): configs = {} package = importlib.import_module(base_package) for _, module_name, _ in pkgutil.iter_modules(package.__path__): @@ -18,19 +19,46 @@ def discover_approach_configs(base_package="module_text_llm"):#modules/text/modu for name, obj in inspect.getmembers(module, inspect.isclass): if issubclass(obj, ApproachConfig) and obj is not ApproachConfig: configs[obj.__name__] = obj + print("name ", name) + print("module ",module) return configs class SuggestionStrategyFactory: _strategies = {} + @staticmethod + def discover_and_initialize_strategies(base_package="module_text_llm"): + """ + Discover all strategy classes dynamically and initialize the factory. + """ + strategies = {} + package = importlib.import_module(base_package) + + def recursive_import(package_name): + package = importlib.import_module(package_name) + for _, module_name, is_pkg in pkgutil.iter_modules(package.__path__): + full_module_name = f"{package_name}.{module_name}" + if is_pkg: + recursive_import(full_module_name) + else: + module = importlib.import_module(full_module_name) + for name, obj in inspect.getmembers(module, inspect.isclass): + strategies[name] = obj + + recursive_import(base_package) + return strategies + @staticmethod def initialize_strategies(): - configs = discover_approach_configs() - for config_name, config_class in configs.items(): - strategy_class_name = config_name#f"{config_name.replace('Config', '')}SuggestionStrategy" - strategy_class = globals().get(strategy_class_name) - if strategy_class: - SuggestionStrategyFactory._strategies[config_name] = strategy_class + if not SuggestionStrategyFactory._strategies: + configs = discover_approach_configs() # Assuming this function is defined + strategies = SuggestionStrategyFactory.discover_and_initialize_strategies() + + for config_name, config_class in configs.items(): + strategy_class_name = config_name + strategy_class = strategies.get(strategy_class_name) + if strategy_class: + SuggestionStrategyFactory._strategies[config_name] = strategy_class @staticmethod def get_strategy(config): @@ -44,12 +72,6 @@ def get_strategy(config): return strategy_class() async def generate_suggestions(exercise: Exercise, submission: Submission, config: ApproachConfig, debug: bool) -> List[Feedback]: - # print(discover_approach_configs()) - # return [] strategy = SuggestionStrategyFactory.get_strategy(config) return await strategy.generate_suggestions(exercise, submission, config, debug) - # if isinstance(config, BasicApproachConfig): - # return await generate_suggestions_basic(exercise, submission, config, debug) - # if isinstance(config, ChainOfThoughtConfig): - # return await generate_cot_suggestions(exercise, submission, config, debug) - # raise ValueError("Unsupported config type provided.") + From bc920cf0bb0adfd201269814dd59d592014c78c7 Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Tue, 31 Dec 2024 19:16:08 +0100 Subject: [PATCH 11/34] cleanup --- .../module_text_llm/module_text_llm/approach_controller.py | 7 +------ 1 file changed, 1 insertion(+), 6 deletions(-) diff --git a/modules/text/module_text_llm/module_text_llm/approach_controller.py b/modules/text/module_text_llm/module_text_llm/approach_controller.py index 1f73e25e..69d5cd1c 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_controller.py +++ b/modules/text/module_text_llm/module_text_llm/approach_controller.py @@ -1,11 +1,6 @@ from typing import List from athena.text import Exercise, Submission, Feedback -# from module_text_llm.basic_approach import BasicApproachConfig -# from module_text_llm.chain_of_thought_approach import ChainOfThoughtConfig from module_text_llm.approach_config import ApproachConfig - -# from module_text_llm.basic_approach.generate_suggestions import generate_suggestions as generate_suggestions_basic -# from module_text_llm.chain_of_thought_approach.generate_suggestions import generate_suggestions as generate_cot_suggestions import importlib import pkgutil import inspect @@ -51,7 +46,7 @@ def recursive_import(package_name): @staticmethod def initialize_strategies(): if not SuggestionStrategyFactory._strategies: - configs = discover_approach_configs() # Assuming this function is defined + configs = discover_approach_configs() strategies = SuggestionStrategyFactory.discover_and_initialize_strategies() for config_name, config_class in configs.items(): From 320c92de1bf6fa04ff1ad8047b743fd5e7bac615 Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Wed, 1 Jan 2025 13:23:57 +0100 Subject: [PATCH 12/34] refactor and document --- .../module_text_llm/approach_controller.py | 103 ++++++++++++------ 1 file changed, 68 insertions(+), 35 deletions(-) diff --git a/modules/text/module_text_llm/module_text_llm/approach_controller.py b/modules/text/module_text_llm/module_text_llm/approach_controller.py index 69d5cd1c..01d83168 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_controller.py +++ b/modules/text/module_text_llm/module_text_llm/approach_controller.py @@ -6,57 +6,90 @@ import inspect from typing import Dict -def discover_approach_configs(base_package="module_text_llm"): - configs = {} +def discover_classes(base_package, base_class=None): + """ + Discover and return classes within the specified package. + + Args: + base_package (str): The package to search. + base_class (type, optional): A base class to filter discovered classes. + Only subclasses of this base class will be included. + + Returns: + dict: A dictionary mapping class names to class objects. + """ + classes = {} package = importlib.import_module(base_package) - for _, module_name, _ in pkgutil.iter_modules(package.__path__): - module = importlib.import_module(f"{base_package}.{module_name}") - for name, obj in inspect.getmembers(module, inspect.isclass): - if issubclass(obj, ApproachConfig) and obj is not ApproachConfig: - configs[obj.__name__] = obj - print("name ", name) - print("module ",module) - return configs + + def recursive_import(package_name): + package = importlib.import_module(package_name) + for _, module_name, is_pkg in pkgutil.iter_modules(package.__path__): + full_module_name = f"{package_name}.{module_name}" + if is_pkg: + recursive_import(full_module_name) + else: + module = importlib.import_module(full_module_name) + for name, obj in inspect.getmembers(module, inspect.isclass): + if base_class is None or (issubclass(obj, base_class) and obj is not base_class): + classes[name] = obj + + recursive_import(base_package) + return classes + class SuggestionStrategyFactory: + """ + A factory class for discovering, initializing, and retrieving suggestion strategies. + + The `SuggestionStrategyFactory` dynamically loads strategy classes, associates them with + specific configuration types, and provides instances of the strategies based on the given + configuration. It supports modular discovery and initialization to handle a variety of + strategies seamlessly. + + Attributes: + _strategies (dict): A dictionary mapping configuration class names to their corresponding strategy classes. + """ _strategies = {} @staticmethod - def discover_and_initialize_strategies(base_package="module_text_llm"): + def initialize_strategies(base_package="module_text_llm"): """ - Discover all strategy classes dynamically and initialize the factory. - """ - strategies = {} - package = importlib.import_module(base_package) - - def recursive_import(package_name): - package = importlib.import_module(package_name) - for _, module_name, is_pkg in pkgutil.iter_modules(package.__path__): - full_module_name = f"{package_name}.{module_name}" - if is_pkg: - recursive_import(full_module_name) - else: - module = importlib.import_module(full_module_name) - for name, obj in inspect.getmembers(module, inspect.isclass): - strategies[name] = obj - - recursive_import(base_package) - return strategies + Initialize the factory by associating configuration types with their corresponding strategies. - @staticmethod - def initialize_strategies(): + This method uses the `discover_classes` function to identify configuration classes and their + associated strategies. The mappings are stored in the `_strategies` dictionary for later retrieval. + + Args: + base_package (str): The base package to search for strategies and configurations. + Defaults to "module_text_llm". + """ if not SuggestionStrategyFactory._strategies: - configs = discover_approach_configs() - strategies = SuggestionStrategyFactory.discover_and_initialize_strategies() + configs = discover_classes(base_package, base_class=ApproachConfig) + strategies = discover_classes(base_package) for config_name, config_class in configs.items(): - strategy_class_name = config_name - strategy_class = strategies.get(strategy_class_name) + strategy_class = strategies.get(config_name) if strategy_class: SuggestionStrategyFactory._strategies[config_name] = strategy_class @staticmethod def get_strategy(config): + """ + Retrieve an instance of the strategy corresponding to the given configuration. + + If the strategies have not been initialized, this method will initialize them first. + The method then matches the type of the provided configuration with the corresponding + strategy class and returns an instance of it. + + Args: + config (object): The configuration object for which the strategy is required. + + Returns: + object: An instance of the strategy class associated with the given configuration. + + Raises: + ValueError: If no strategy is found for the given configuration type. + """ if not SuggestionStrategyFactory._strategies: SuggestionStrategyFactory.initialize_strategies() From 07bc978bdc5302588175fa0489727aa0747c860b Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Wed, 1 Jan 2025 13:47:43 +0100 Subject: [PATCH 13/34] clean up --- .../module_text_llm/approach_config.py | 9 ++------- .../module_text_llm/approach_controller.py | 11 +++++------ .../chain_of_thought_approach/prompt_thinking.py | 3 +++ 3 files changed, 10 insertions(+), 13 deletions(-) diff --git a/modules/text/module_text_llm/module_text_llm/approach_config.py b/modules/text/module_text_llm/module_text_llm/approach_config.py index 14af96e4..9ba73f77 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_config.py +++ b/modules/text/module_text_llm/module_text_llm/approach_config.py @@ -1,14 +1,8 @@ from abc import ABC from pydantic import BaseModel, Field from llm_core.models import ModelConfigType, DefaultModelConfig -from enum import Enum from abc import ABC, abstractmethod from athena.text import Exercise, Submission - - -class ApproachType(str, Enum): - basic = "BasicApproach" - chain_of_thought = "ChainOfThought" class ApproachConfig(BaseModel, ABC): max_input_tokens: int = Field(default=3000, description="Maximum number of tokens in the input prompt.") @@ -20,4 +14,5 @@ async def generate_suggestions(self, exercise: Exercise, submission: Submission, pass class Config: - use_enum_values = True \ No newline at end of file + use_enum_values = True + \ No newline at end of file diff --git a/modules/text/module_text_llm/module_text_llm/approach_controller.py b/modules/text/module_text_llm/module_text_llm/approach_controller.py index 01d83168..a2c99cb8 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_controller.py +++ b/modules/text/module_text_llm/module_text_llm/approach_controller.py @@ -4,9 +4,8 @@ import importlib import pkgutil import inspect -from typing import Dict -def discover_classes(base_package, base_class=None): +def discover_approach_configs(base_package, base_class=None): """ Discover and return classes within the specified package. @@ -64,11 +63,11 @@ def initialize_strategies(base_package="module_text_llm"): Defaults to "module_text_llm". """ if not SuggestionStrategyFactory._strategies: - configs = discover_classes(base_package, base_class=ApproachConfig) - strategies = discover_classes(base_package) + configs = discover_approach_configs(base_package, base_class=ApproachConfig) + # strategies = discover_approach_configs(base_package) for config_name, config_class in configs.items(): - strategy_class = strategies.get(config_name) + strategy_class = configs.get(config_name) if strategy_class: SuggestionStrategyFactory._strategies[config_name] = strategy_class @@ -98,7 +97,7 @@ def get_strategy(config): if not strategy_class: raise ValueError(f"No strategy found for config type: {config_type}") return strategy_class() - + async def generate_suggestions(exercise: Exercise, submission: Submission, config: ApproachConfig, debug: bool) -> List[Feedback]: strategy = SuggestionStrategyFactory.get_strategy(config) return await strategy.generate_suggestions(exercise, submission, config, debug) diff --git a/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/prompt_thinking.py b/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/prompt_thinking.py index 6f72b2b1..ce2cf111 100644 --- a/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/prompt_thinking.py +++ b/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/prompt_thinking.py @@ -52,6 +52,9 @@ class InitialAssessment(BaseModel): credits: float = Field(0.0, description="Number of points received/deducted") reasoning: str = Field(description="Reasoning why the feedback was given") impprovment_suggestion: str = Field(description="Suggestion for improvement for the student") + grading_instruction_id: Optional[int] = Field( + description="ID of the grading instruction that was used to generate this feedback, or empty if no grading instruction was used" + ) class InitialAssessmentModel(BaseModel): """Collection of feedbacks making up an assessment""" From 78e8a0cb9359e60205ac8c1ca6c843822042165c Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Wed, 1 Jan 2025 14:04:42 +0100 Subject: [PATCH 14/34] fix linting issues --- .../text/module_text_llm/module_text_llm/approach_config.py | 1 - .../module_text_llm/module_text_llm/approach_controller.py | 3 +-- 2 files changed, 1 insertion(+), 3 deletions(-) diff --git a/modules/text/module_text_llm/module_text_llm/approach_config.py b/modules/text/module_text_llm/module_text_llm/approach_config.py index 9ba73f77..71934d81 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_config.py +++ b/modules/text/module_text_llm/module_text_llm/approach_config.py @@ -1,4 +1,3 @@ -from abc import ABC from pydantic import BaseModel, Field from llm_core.models import ModelConfigType, DefaultModelConfig from abc import ABC, abstractmethod diff --git a/modules/text/module_text_llm/module_text_llm/approach_controller.py b/modules/text/module_text_llm/module_text_llm/approach_controller.py index a2c99cb8..bce84465 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_controller.py +++ b/modules/text/module_text_llm/module_text_llm/approach_controller.py @@ -48,7 +48,7 @@ class SuggestionStrategyFactory: Attributes: _strategies (dict): A dictionary mapping configuration class names to their corresponding strategy classes. """ - _strategies = {} + _strategies: dict[str, ApproachConfig] = {} @staticmethod def initialize_strategies(base_package="module_text_llm"): @@ -101,4 +101,3 @@ def get_strategy(config): async def generate_suggestions(exercise: Exercise, submission: Submission, config: ApproachConfig, debug: bool) -> List[Feedback]: strategy = SuggestionStrategyFactory.get_strategy(config) return await strategy.generate_suggestions(exercise, submission, config, debug) - From a912fac5310a5aea65b3ac19a47f6aa348fb713b Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Wed, 1 Jan 2025 14:06:50 +0100 Subject: [PATCH 15/34] type annotations --- .../module_text_llm/module_text_llm/approach_controller.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/modules/text/module_text_llm/module_text_llm/approach_controller.py b/modules/text/module_text_llm/module_text_llm/approach_controller.py index bce84465..5c32c728 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_controller.py +++ b/modules/text/module_text_llm/module_text_llm/approach_controller.py @@ -1,4 +1,4 @@ -from typing import List +from typing import List, Callable from athena.text import Exercise, Submission, Feedback from module_text_llm.approach_config import ApproachConfig import importlib @@ -48,7 +48,7 @@ class SuggestionStrategyFactory: Attributes: _strategies (dict): A dictionary mapping configuration class names to their corresponding strategy classes. """ - _strategies: dict[str, ApproachConfig] = {} + _strategies: dict[str, Callable] = {} @staticmethod def initialize_strategies(base_package="module_text_llm"): From 1f15a488390e452fedf276c68206e897fae31f4b Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Wed, 1 Jan 2025 14:44:19 +0100 Subject: [PATCH 16/34] graceful handling of failed ollama instantiation --- .../chain_of_thought_approach/__init__.py | 2 -- .../ollama_chain_of_thought_approach/__init__.py | 9 ++++++--- 2 files changed, 6 insertions(+), 5 deletions(-) diff --git a/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/__init__.py b/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/__init__.py index f125091b..5905e1ce 100644 --- a/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/__init__.py +++ b/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/__init__.py @@ -1,6 +1,5 @@ from pydantic import BaseModel, Field from typing import Literal -from llm_core.models import ModelConfigType, DefaultModelConfig from module_text_llm.approach_config import ApproachConfig from module_text_llm.chain_of_thought_approach.prompt_generate_feedback import CoTGenerateSuggestionsPrompt @@ -8,7 +7,6 @@ class ChainOfThoughtConfig(ApproachConfig): type: Literal['chain_of_thought'] = 'chain_of_thought' - model: ModelConfigType = Field(default=DefaultModelConfig) # type: ignore thikning_prompt: ThinkingPrompt = Field(default=ThinkingPrompt()) generate_suggestions_prompt: CoTGenerateSuggestionsPrompt = Field(default=CoTGenerateSuggestionsPrompt()) \ No newline at end of file diff --git a/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/__init__.py b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/__init__.py index 2bdd0059..0e5ca768 100644 --- a/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/__init__.py +++ b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/__init__.py @@ -1,13 +1,16 @@ from pydantic import BaseModel, Field from typing import Literal -from llm_core.models import ModelConfigType, OllamaModelConfig - +from llm_core.models import ModelConfigType +try: + from llm_core.models import OllamaModelConfig +except ImportError as e: + print(f"Warning: Failed to import models. {e}") + OllamaModelConfig = None from module_text_llm.approach_config import ApproachConfig from module_text_llm.ollama_chain_of_thought_approach.prompt_generate_feedback import CoTGenerateSuggestionsPrompt from module_text_llm.ollama_chain_of_thought_approach.prompt_thinking import ThinkingPrompt class OllamaChainOfThoughtConfig(ApproachConfig): - # Defaults to the cheaper mini 4o model type: Literal['ollama_chain_of_thought'] = 'ollama_chain_of_thought' model: ModelConfigType = Field(default=OllamaModelConfig) # type: ignore thikning_prompt: ThinkingPrompt = Field(default=ThinkingPrompt()) From c150612ee0f0a14527b7356540dc803097dd5974 Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Mon, 13 Jan 2025 16:05:58 +0100 Subject: [PATCH 17/34] move approach discovery and strategyFactory to athena package --- .../approach_discovery/discover_approaches.py | 34 ++++++ .../approach_discovery/strategy_factory.py | 76 +++++++++++++ .../module_text_llm/__init__.py | 3 + .../module_text_llm/approach_controller.py | 102 +----------------- .../chain_of_thought_approach/__init__.py | 2 +- .../generate_suggestions.py | 4 +- 6 files changed, 120 insertions(+), 101 deletions(-) create mode 100644 athena/athena/approach_discovery/discover_approaches.py create mode 100644 athena/athena/approach_discovery/strategy_factory.py diff --git a/athena/athena/approach_discovery/discover_approaches.py b/athena/athena/approach_discovery/discover_approaches.py new file mode 100644 index 00000000..d88507ca --- /dev/null +++ b/athena/athena/approach_discovery/discover_approaches.py @@ -0,0 +1,34 @@ + +import importlib +import pkgutil +import inspect + +def discover_approach_configs(base_package, base_class=None): + """ + Discover and return classes within the specified package. + + Args: + base_package (str): The package to search. + base_class (type, optional): A base class to filter discovered classes. + Only subclasses of this base class will be included. + + Returns: + dict: A dictionary mapping class names to class objects. + """ + classes = {} + package = importlib.import_module(base_package) + + def recursive_import(package_name): + package = importlib.import_module(package_name) + for _, module_name, is_pkg in pkgutil.iter_modules(package.__path__): + full_module_name = f"{package_name}.{module_name}" + if is_pkg: + recursive_import(full_module_name) + else: + module = importlib.import_module(full_module_name) + for name, obj in inspect.getmembers(module, inspect.isclass): + if base_class is None or (issubclass(obj, base_class) and obj is not base_class): + classes[name] = obj + + recursive_import(base_package) + return classes \ No newline at end of file diff --git a/athena/athena/approach_discovery/strategy_factory.py b/athena/athena/approach_discovery/strategy_factory.py new file mode 100644 index 00000000..af7b32e7 --- /dev/null +++ b/athena/athena/approach_discovery/strategy_factory.py @@ -0,0 +1,76 @@ +from athena.approach_discovery.discover_approaches import discover_approach_configs +from typing import List, Callable + +class SuggestionStrategyFactory: + """ + A factory class for discovering, initializing, and retrieving suggestion strategies. + + The `SuggestionStrategyFactory` dynamically loads strategy classes, associates them with + specific configuration types, and provides instances of the strategies based on the given + configuration. It supports modular discovery and initialization to handle a variety of + strategies seamlessly. + + Attributes: + _strategies (dict): A dictionary mapping configuration class names to their corresponding strategy classes. + """ + _strategies: dict[str, Callable] = {} + def __init__(self, base_package: str, base_class: type): + """ + Initialize the factory by providing the base package and base class for discovering strategies. + + Args: + base_package (str): The base package to search for strategies and configurations. + base_class (type): The base class for configurations that strategies will be associated with. + """ + self.base_package = base_package + self.base_class = base_class + + # Initialize strategies on object creation + self.initialize_strategies() + + def initialize_strategies(self): + """ + Initialize the factory by associating configuration types with their corresponding strategies. + + This method uses the `discover_classes` function to identify configuration classes and their + associated strategies. The mappings are stored in the `_strategies` dictionary for later retrieval. + + Args: + base_package (str): The base package to search for strategies and configurations. + Defaults to "module_text_llm". + """ + if not SuggestionStrategyFactory._strategies: + configs = discover_approach_configs(self.base_package, base_class=self.base_class) + # strategies = discover_approach_configs(base_package) + + for config_name, config_class in configs.items(): + strategy_class = configs.get(config_name) + if strategy_class: + SuggestionStrategyFactory._strategies[config_name] = strategy_class + + + def get_strategy(self, config): + """ + Retrieve an instance of the strategy corresponding to the given configuration. + + If the strategies have not been initialized, this method will initialize them first. + The method then matches the type of the provided configuration with the corresponding + strategy class and returns an instance of it. + + Args: + config (object): The configuration object for which the strategy is required. + + Returns: + object: An instance of the strategy class associated with the given configuration. + + Raises: + ValueError: If no strategy is found for the given configuration type. + """ + # if not SuggestionStrategyFactory._strategies: + # self.initialize_strategies() + + config_type = type(config).__name__ + strategy_class = SuggestionStrategyFactory._strategies.get(config_type) + if not strategy_class: + raise ValueError(f"No strategy found for config type: {config_type}") + return strategy_class() \ No newline at end of file diff --git a/modules/text/module_text_llm/module_text_llm/__init__.py b/modules/text/module_text_llm/module_text_llm/__init__.py index 31c8c578..577d31de 100644 --- a/modules/text/module_text_llm/module_text_llm/__init__.py +++ b/modules/text/module_text_llm/module_text_llm/__init__.py @@ -1,3 +1,6 @@ import dotenv +from athena.approach_discovery.strategy_factory import SuggestionStrategyFactory +from module_text_llm.approach_config import ApproachConfig dotenv.load_dotenv(override=True) +strategyFactory = SuggestionStrategyFactory("module_text_llm", ApproachConfig) diff --git a/modules/text/module_text_llm/module_text_llm/approach_controller.py b/modules/text/module_text_llm/module_text_llm/approach_controller.py index 5c32c728..339440c2 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_controller.py +++ b/modules/text/module_text_llm/module_text_llm/approach_controller.py @@ -1,103 +1,9 @@ -from typing import List, Callable +from typing import List from athena.text import Exercise, Submission, Feedback from module_text_llm.approach_config import ApproachConfig -import importlib -import pkgutil -import inspect - -def discover_approach_configs(base_package, base_class=None): - """ - Discover and return classes within the specified package. - - Args: - base_package (str): The package to search. - base_class (type, optional): A base class to filter discovered classes. - Only subclasses of this base class will be included. - - Returns: - dict: A dictionary mapping class names to class objects. - """ - classes = {} - package = importlib.import_module(base_package) - - def recursive_import(package_name): - package = importlib.import_module(package_name) - for _, module_name, is_pkg in pkgutil.iter_modules(package.__path__): - full_module_name = f"{package_name}.{module_name}" - if is_pkg: - recursive_import(full_module_name) - else: - module = importlib.import_module(full_module_name) - for name, obj in inspect.getmembers(module, inspect.isclass): - if base_class is None or (issubclass(obj, base_class) and obj is not base_class): - classes[name] = obj - - recursive_import(base_package) - return classes - - -class SuggestionStrategyFactory: - """ - A factory class for discovering, initializing, and retrieving suggestion strategies. - - The `SuggestionStrategyFactory` dynamically loads strategy classes, associates them with - specific configuration types, and provides instances of the strategies based on the given - configuration. It supports modular discovery and initialization to handle a variety of - strategies seamlessly. - - Attributes: - _strategies (dict): A dictionary mapping configuration class names to their corresponding strategy classes. - """ - _strategies: dict[str, Callable] = {} - - @staticmethod - def initialize_strategies(base_package="module_text_llm"): - """ - Initialize the factory by associating configuration types with their corresponding strategies. - - This method uses the `discover_classes` function to identify configuration classes and their - associated strategies. The mappings are stored in the `_strategies` dictionary for later retrieval. - - Args: - base_package (str): The base package to search for strategies and configurations. - Defaults to "module_text_llm". - """ - if not SuggestionStrategyFactory._strategies: - configs = discover_approach_configs(base_package, base_class=ApproachConfig) - # strategies = discover_approach_configs(base_package) - - for config_name, config_class in configs.items(): - strategy_class = configs.get(config_name) - if strategy_class: - SuggestionStrategyFactory._strategies[config_name] = strategy_class - - @staticmethod - def get_strategy(config): - """ - Retrieve an instance of the strategy corresponding to the given configuration. - - If the strategies have not been initialized, this method will initialize them first. - The method then matches the type of the provided configuration with the corresponding - strategy class and returns an instance of it. - - Args: - config (object): The configuration object for which the strategy is required. - - Returns: - object: An instance of the strategy class associated with the given configuration. - - Raises: - ValueError: If no strategy is found for the given configuration type. - """ - if not SuggestionStrategyFactory._strategies: - SuggestionStrategyFactory.initialize_strategies() - - config_type = type(config).__name__ - strategy_class = SuggestionStrategyFactory._strategies.get(config_type) - if not strategy_class: - raise ValueError(f"No strategy found for config type: {config_type}") - return strategy_class() async def generate_suggestions(exercise: Exercise, submission: Submission, config: ApproachConfig, debug: bool) -> List[Feedback]: - strategy = SuggestionStrategyFactory.get_strategy(config) + from module_text_llm import strategyFactory + + strategy = strategyFactory.get_strategy(config) return await strategy.generate_suggestions(exercise, submission, config, debug) diff --git a/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/__init__.py b/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/__init__.py index a058842e..66f5d6e0 100644 --- a/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/__init__.py +++ b/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/__init__.py @@ -8,7 +8,7 @@ class ChainOfThoughtConfig(ApproachConfig): type: Literal['chain_of_thought'] = 'chain_of_thought' - thikning_prompt: ThinkingPrompt = Field(default=ThinkingPrompt()) + thinking_prompt: ThinkingPrompt = Field(default=ThinkingPrompt()) generate_suggestions_prompt: CoTGenerateSuggestionsPrompt = Field(default=CoTGenerateSuggestionsPrompt()) async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, debug: bool): diff --git a/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/generate_suggestions.py b/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/generate_suggestions.py index ace3997e..fad66460 100644 --- a/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/generate_suggestions.py +++ b/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/generate_suggestions.py @@ -32,8 +32,8 @@ async def generate_suggestions(exercise: Exercise, submission: Submission, confi chat_prompt = get_chat_prompt_with_formatting_instructions( model=model, - system_message=config.thikning_prompt.system_message, - human_message=config.thikning_prompt.human_message, + system_message=config.thinking_prompt.system_message, + human_message=config.thinking_prompt.human_message, pydantic_object=InitialAssessmentModel ) From 5d062dc10f112054b828c9cc083268a3ddf9e0c1 Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Mon, 13 Jan 2025 16:14:43 +0100 Subject: [PATCH 18/34] linting --- modules/text/module_text_llm/module_text_llm/__init__.py | 2 +- .../module_text_llm/module_text_llm/approach_controller.py | 5 +++-- 2 files changed, 4 insertions(+), 3 deletions(-) diff --git a/modules/text/module_text_llm/module_text_llm/__init__.py b/modules/text/module_text_llm/module_text_llm/__init__.py index 577d31de..5de9668e 100644 --- a/modules/text/module_text_llm/module_text_llm/__init__.py +++ b/modules/text/module_text_llm/module_text_llm/__init__.py @@ -3,4 +3,4 @@ from module_text_llm.approach_config import ApproachConfig dotenv.load_dotenv(override=True) -strategyFactory = SuggestionStrategyFactory("module_text_llm", ApproachConfig) +strategy_factory = SuggestionStrategyFactory("module_text_llm", ApproachConfig) diff --git a/modules/text/module_text_llm/module_text_llm/approach_controller.py b/modules/text/module_text_llm/module_text_llm/approach_controller.py index 339440c2..3adeff5f 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_controller.py +++ b/modules/text/module_text_llm/module_text_llm/approach_controller.py @@ -3,7 +3,8 @@ from module_text_llm.approach_config import ApproachConfig async def generate_suggestions(exercise: Exercise, submission: Submission, config: ApproachConfig, debug: bool) -> List[Feedback]: - from module_text_llm import strategyFactory + # Importing the strategy_factory here to avoid circular imports with ApproachConfig + from module_text_llm import strategy_factory # pylint: disable=import-outside-toplevel - strategy = strategyFactory.get_strategy(config) + strategy = strategy_factory.get_strategy(config) return await strategy.generate_suggestions(exercise, submission, config, debug) From 119cf6b9e5d224c0bedbb3cbeaf683a59d6a3e1c Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Mon, 13 Jan 2025 16:15:08 +0100 Subject: [PATCH 19/34] comment --- .../module_text_llm/module_text_llm/approach_controller.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/modules/text/module_text_llm/module_text_llm/approach_controller.py b/modules/text/module_text_llm/module_text_llm/approach_controller.py index 3adeff5f..c6617015 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_controller.py +++ b/modules/text/module_text_llm/module_text_llm/approach_controller.py @@ -4,7 +4,8 @@ async def generate_suggestions(exercise: Exercise, submission: Submission, config: ApproachConfig, debug: bool) -> List[Feedback]: # Importing the strategy_factory here to avoid circular imports with ApproachConfig - from module_text_llm import strategy_factory # pylint: disable=import-outside-toplevel + # pylint: disable=import-outside-toplevel + from module_text_llm import strategy_factory strategy = strategy_factory.get_strategy(config) return await strategy.generate_suggestions(exercise, submission, config, debug) From 930e63fc670690c7753c7634e2ea94448838e457 Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Mon, 13 Jan 2025 23:57:06 +0100 Subject: [PATCH 20/34] adapt to strategy pattern --- .../ollama_chain_of_thought_approach/__init__.py | 12 ++++++++---- .../generate_suggestions.py | 9 +++++---- .../prompt_generate_feedback.py | 11 +++++++---- 3 files changed, 20 insertions(+), 12 deletions(-) diff --git a/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/__init__.py b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/__init__.py index 0e5ca768..ce6a2183 100644 --- a/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/__init__.py +++ b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/__init__.py @@ -1,18 +1,22 @@ -from pydantic import BaseModel, Field +from pydantic import Field from typing import Literal from llm_core.models import ModelConfigType +from athena.text import Exercise, Submission try: from llm_core.models import OllamaModelConfig except ImportError as e: print(f"Warning: Failed to import models. {e}") OllamaModelConfig = None + from module_text_llm.approach_config import ApproachConfig from module_text_llm.ollama_chain_of_thought_approach.prompt_generate_feedback import CoTGenerateSuggestionsPrompt from module_text_llm.ollama_chain_of_thought_approach.prompt_thinking import ThinkingPrompt - +from module_text_llm.ollama_chain_of_thought_approach.generate_suggestions import generate_suggestions class OllamaChainOfThoughtConfig(ApproachConfig): type: Literal['ollama_chain_of_thought'] = 'ollama_chain_of_thought' model: ModelConfigType = Field(default=OllamaModelConfig) # type: ignore - thikning_prompt: ThinkingPrompt = Field(default=ThinkingPrompt()) + thinking_prompt: ThinkingPrompt = Field(default=ThinkingPrompt()) generate_suggestions_prompt: CoTGenerateSuggestionsPrompt = Field(default=CoTGenerateSuggestionsPrompt()) - \ No newline at end of file + + async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, debug: bool): + return await generate_suggestions(exercise,submission,config,debug) \ No newline at end of file diff --git a/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/generate_suggestions.py b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/generate_suggestions.py index acab1e99..2f8abb53 100644 --- a/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/generate_suggestions.py +++ b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/generate_suggestions.py @@ -5,7 +5,7 @@ from athena.text import Exercise, Submission, Feedback from athena.logger import logger -from module_text_llm.chain_of_thought_approach import ChainOfThoughtConfig +from module_text_llm.approach_config import ApproachConfig from llm_core.utils.llm_utils import ( get_chat_prompt_with_formatting_instructions, @@ -19,7 +19,7 @@ from module_text_llm.ollama_chain_of_thought_approach.prompt_generate_feedback import AssessmentModel -async def generate_suggestions(exercise: Exercise, submission: Submission, config: ChainOfThoughtConfig, debug: bool) -> List[Feedback]: +async def generate_suggestions(exercise: Exercise, submission: Submission, config: ApproachConfig, debug: bool) -> List[Feedback]: model = config.model.get_model() # type: ignore[attr-defined] prompt_input = { @@ -32,8 +32,8 @@ async def generate_suggestions(exercise: Exercise, submission: Submission, confi } chat_prompt = get_simple_chat_prompt( - system_message=config.thikning_prompt.system_message, - human_message=config.thikning_prompt.human_message, + system_message=config.thinking_prompt.system_message, + human_message=config.thinking_prompt.human_message, ) @@ -67,6 +67,7 @@ async def generate_suggestions(exercise: Exercise, submission: Submission, confi ) second_prompt_input = { + "max_points": exercise.max_points, "answer" : initial_result, } diff --git a/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/prompt_generate_feedback.py b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/prompt_generate_feedback.py index 7e25e0d1..4328983a 100644 --- a/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/prompt_generate_feedback.py +++ b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/prompt_generate_feedback.py @@ -2,11 +2,14 @@ from typing import List, Optional system_message = """ - Your task is to format the given text from the human into a json. The json must strictly follow the following instructions: -You should only reply in valid json without any additional comments. -The json must begin with the property "feedback_list" which is an array of many feedback elements. Each element of this array only has these fields and it must contain all of them with the exact same name as given here: "feedback_list", which contains "description", "credits", "line_start", "line_end", "title", "grading_instruction_id". +Your task is to format the given text from the human into a json that will be the assessment presented to a student. +The json must strictly follow the following instructions: +1. You should only reply in valid json without any additional comments. +2. The json must begin with the property "feedback_list" which is an array of many feedback elements. +3. Each element of this array only has these fields and it must contain all of them with the exact same name as given here: "feedback_list", which contains "description", "credits", "line_start", "line_end", "title", "grading_instruction_id". +4. The maximum amount of credits to be given is {max_points} credits. - """ +""" human_message = """\ \"\"\" From aad8789f88e40b1cd36d2a022a4662d400db575a Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Tue, 14 Jan 2025 00:16:53 +0100 Subject: [PATCH 21/34] prompt adjustments --- .../prompt_thinking.py | 14 +++++++++++--- 1 file changed, 11 insertions(+), 3 deletions(-) diff --git a/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/prompt_thinking.py b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/prompt_thinking.py index 2530b98d..f6b6ebc1 100644 --- a/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/prompt_thinking.py +++ b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/prompt_thinking.py @@ -2,14 +2,22 @@ from typing import Optional, List system_message = """ - You are an AI Tutor. You are tasked with grading a student submission based on this problem statement and grading instructions. You must not excede the maximum amount of points. Take time to think, which points on the grading instructions are relevant for the students submission. - Further more, if a feedback is specific to a sentence in the student submission, that specify this as well on your feedback. Also specify, when possible, which grading instruction you are refering to. + You are an AI Tutor. + You are tasked with grading a student submission based on this problem statement and grading instructions. + You must not excede the maximum amount of points. + Take time to think, which points on the grading instructions are relevant for the students submission. + Further more, if a feedback is specific to a sentence in the student submission, that specify this as well on your feedback. + Also specify, when possible, which grading instruction you are refering to. + Referenced sentences must not overlap. # Problem statement {problem_statement} # Grading instructions {grading_instructions} - Max points: {max_points} + Max points: {max_points}. The total points granted in all feedback elements must not exceed {max_points}. + Format your response in the following way: + Grading instruction (sentence to ): , credits: + If the feedback is unreferenced simple right Unreferenced """ human_message = """\ From 7a6a29b227f4c1cdf21ed9e691e1876157d11b07 Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Tue, 14 Jan 2025 16:03:12 +0100 Subject: [PATCH 22/34] script to create approach --- .../module_text_llm/create_approach_script.py | 153 ++++++++++++++++++ 1 file changed, 153 insertions(+) create mode 100644 modules/text/module_text_llm/module_text_llm/create_approach_script.py diff --git a/modules/text/module_text_llm/module_text_llm/create_approach_script.py b/modules/text/module_text_llm/module_text_llm/create_approach_script.py new file mode 100644 index 00000000..f1916459 --- /dev/null +++ b/modules/text/module_text_llm/module_text_llm/create_approach_script.py @@ -0,0 +1,153 @@ +""" +This script creates a new approach for inside the module_text_llm package. + +Run with python create_approach_script.py + +It creates the __init__.py, prompt_generate_suggestions.py, and generate_suggestions.py files for the new approach. + +It also imports the new approach to the conifg.py and adds the new approach to the ApproachConfigUnion. +""" +import os +import re +import argparse +from pathlib import Path + +def to_camel_case(snake_str): + components = snake_str.split('_') + return ''.join(x.title() for x in components) + +def create_approach_directory(approach_name): + base_dir = Path(__file__).parent / approach_name + base_dir.mkdir(parents=True, exist_ok=True) + return base_dir + +def create_init_py(base_dir, approach_name): + init_content = f""" +from module_text_llm.approach_config import ApproachConfig +from pydantic import Field +from typing import Literal +from athena.text import Exercise, Submission +from module_text_llm.{approach_name}.generate_suggestions import generate_suggestions +from module_text_llm.{approach_name}.prompt_generate_suggestions import GenerateSuggestionsPrompt + +class {to_camel_case(approach_name)}Config(ApproachConfig): + type: Literal['{approach_name.lower()}'] = '{approach_name.lower()}' + generate_suggestions_prompt: GenerateSuggestionsPrompt = Field(default=GenerateSuggestionsPrompt()) + + async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, debug: bool): + return await generate_suggestions(exercise,submission,config,debug) +""" + with open(base_dir / "__init__.py", "w") as f: + f.write(init_content.strip()) + +def create_prompt_py(base_dir): + prompt_content = prompt_content = ''' +from pydantic import Field, BaseModel +from typing import List, Optional + +system_message = """\ +You are an AI tutor for text assessment at a prestigious university. + +# Task +Create graded feedback suggestions for a student's text submission that a human tutor would accept. \ +Meaning, the feedback you provide should be applicable to the submission with little to no modification. + +# Style +1. Constructive, 2. Specific, 3. Balanced, 4. Clear and Concise, 5. Actionable, 6. Educational, 7. Contextual + +# Problem statement +{problem_statement} + +# Example solution +{example_solution} + +# Grading instructions +{grading_instructions} +Max points: {max_points}, bonus points: {bonus_points} + +Respond in json. +""" + +human_message = """\ +Student's submission to grade (with sentence numbers : ): + +{submission} +""" + +# Input Prompt +class GenerateSuggestionsPrompt(BaseModel): + """\ +Features available: **{problem_statement}**, **{example_solution}**, **{grading_instructions}**, **{max_points}**, **{bonus_points}**, **{submission}** + +_Note: **{problem_statement}**, **{example_solution}**, or **{grading_instructions}** might be omitted if the input is too long._\ +""" + system_message: str = Field(default=system_message, + description="Message for priming AI behavior and instructing it what to do.") + human_message: str = Field(default=human_message, + description="Message from a human. The input on which the AI is supposed to act.") + +# Output Object +class FeedbackModel(BaseModel): + title: str = Field(description="Very short title, i.e. feedback category or similar", example="Logic Error") + description: str = Field(description="Feedback description") + line_start: Optional[int] = Field(description="Referenced line number start, or empty if unreferenced") + line_end: Optional[int] = Field(description="Referenced line number end, or empty if unreferenced") + credits: float = Field(0.0, description="Number of points received/deducted") + grading_instruction_id: Optional[int] = Field( + description="ID of the grading instruction that was used to generate this feedback, or empty if no grading instruction was used" + ) + +class AssessmentModel(BaseModel): + """Collection of feedbacks making up an assessment""" + + feedbacks: List[FeedbackModel] = Field(description="Assessment feedbacks") +''' + with open(base_dir / "prompt_generate_suggestions.py", "w") as f: + f.write(prompt_content.strip()) + +def create_generate_suggestions_py(base_dir): + generate_suggestions_content = """ +# Placeholder for generate suggestions logic. +def generate_suggestions(): + pass +""" + with open(base_dir / "generate_suggestions.py", "w") as f: + f.write(generate_suggestions_content.strip()) + +def update_config_py(approach_name): + config_path = Path(__file__).parent / "config.py" + camel_case_name = to_camel_case(approach_name) + config_import = f"from module_text_llm.{approach_name.lower()} import {camel_case_name}Config" + + with open(config_path, "r+") as f: + content = f.read() + + # Add import + if config_import not in content: + content = f"{config_import}\n" + content + + # Update Union + union_pattern = r"ApproachConfigUnion = Union\[(.*?)\]" + match = re.search(union_pattern, content, re.DOTALL) + if match: + updated_union = match.group(1).strip() + f", {camel_case_name}Config" + updated_union = updated_union.replace(" ,", ",") + content = re.sub(union_pattern, f"ApproachConfigUnion = Union[{updated_union}]", content) + + f.seek(0) + f.write(content) + f.truncate() + +def create_approach(approach_name): + base_dir = create_approach_directory(approach_name) + create_init_py(base_dir, approach_name) + create_prompt_py(base_dir) + create_generate_suggestions_py(base_dir) + update_config_py(approach_name) + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="Create a new approach for the Athena project.") + parser.add_argument("approach_name", help="The name of the new approach (in snake_case).") + args = parser.parse_args() + + create_approach(args.approach_name) From 3ed2ae259be2140f14be91cb0841ec9998a2c4d6 Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Tue, 14 Jan 2025 19:04:18 +0100 Subject: [PATCH 23/34] fix linting issues --- .../module_text_llm/create_approach_script.py | 41 +++++++++---------- 1 file changed, 20 insertions(+), 21 deletions(-) diff --git a/modules/text/module_text_llm/module_text_llm/create_approach_script.py b/modules/text/module_text_llm/module_text_llm/create_approach_script.py index f1916459..1d8ca048 100644 --- a/modules/text/module_text_llm/module_text_llm/create_approach_script.py +++ b/modules/text/module_text_llm/module_text_llm/create_approach_script.py @@ -1,27 +1,28 @@ +# -*- coding: utf-8 -*- """ -This script creates a new approach for inside the module_text_llm package. +This script creates a new approach inside the module_text_llm package. -Run with python create_approach_script.py +Run with: python create_approach_script.py It creates the __init__.py, prompt_generate_suggestions.py, and generate_suggestions.py files for the new approach. -It also imports the new approach to the conifg.py and adds the new approach to the ApproachConfigUnion. +It also imports the new approach into the config.py and adds the new approach to the ApproachConfigUnion. """ -import os import re import argparse from pathlib import Path +from typing import Union -def to_camel_case(snake_str): +def to_camel_case(snake_str: str) -> str: components = snake_str.split('_') return ''.join(x.title() for x in components) -def create_approach_directory(approach_name): +def create_approach_directory(approach_name: str) -> Path: base_dir = Path(__file__).parent / approach_name base_dir.mkdir(parents=True, exist_ok=True) return base_dir -def create_init_py(base_dir, approach_name): +def create_init_py(base_dir: Path, approach_name: str) -> None: init_content = f""" from module_text_llm.approach_config import ApproachConfig from pydantic import Field @@ -35,13 +36,13 @@ class {to_camel_case(approach_name)}Config(ApproachConfig): generate_suggestions_prompt: GenerateSuggestionsPrompt = Field(default=GenerateSuggestionsPrompt()) async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, debug: bool): - return await generate_suggestions(exercise,submission,config,debug) + return await generate_suggestions(exercise, submission, config, debug) """ - with open(base_dir / "__init__.py", "w") as f: + with open(base_dir / "__init__.py", "w", encoding="utf-8") as f: f.write(init_content.strip()) -def create_prompt_py(base_dir): - prompt_content = prompt_content = ''' +def create_prompt_py(base_dir: Path) -> None: + prompt_content = ''' from pydantic import Field, BaseModel from typing import List, Optional @@ -99,46 +100,44 @@ class FeedbackModel(BaseModel): class AssessmentModel(BaseModel): """Collection of feedbacks making up an assessment""" - feedbacks: List[FeedbackModel] = Field(description="Assessment feedbacks") ''' - with open(base_dir / "prompt_generate_suggestions.py", "w") as f: + with open(base_dir / "prompt_generate_suggestions.py", "w", encoding="utf-8") as f: f.write(prompt_content.strip()) -def create_generate_suggestions_py(base_dir): +def create_generate_suggestions_py(base_dir: Path) -> None: generate_suggestions_content = """ # Placeholder for generate suggestions logic. def generate_suggestions(): pass """ - with open(base_dir / "generate_suggestions.py", "w") as f: + with open(base_dir / "generate_suggestions.py", "w", encoding="utf-8") as f: f.write(generate_suggestions_content.strip()) -def update_config_py(approach_name): +def update_config_py(approach_name: str) -> None: config_path = Path(__file__).parent / "config.py" camel_case_name = to_camel_case(approach_name) config_import = f"from module_text_llm.{approach_name.lower()} import {camel_case_name}Config" - with open(config_path, "r+") as f: + with open(config_path, "r+", encoding="utf-8") as f: content = f.read() # Add import if config_import not in content: - content = f"{config_import}\n" + content + content = f"{config_import}\n{content}" # Update Union union_pattern = r"ApproachConfigUnion = Union\[(.*?)\]" match = re.search(union_pattern, content, re.DOTALL) if match: - updated_union = match.group(1).strip() + f", {camel_case_name}Config" - updated_union = updated_union.replace(" ,", ",") + updated_union = f"{match.group(1).strip()}, {camel_case_name}Config".replace(" ,", ",") content = re.sub(union_pattern, f"ApproachConfigUnion = Union[{updated_union}]", content) f.seek(0) f.write(content) f.truncate() -def create_approach(approach_name): +def create_approach(approach_name: str) -> None: base_dir = create_approach_directory(approach_name) create_init_py(base_dir, approach_name) create_prompt_py(base_dir) From e382446f640df426c93beb42893a875af12131ed Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Tue, 14 Jan 2025 19:30:47 +0100 Subject: [PATCH 24/34] blank line linting --- .../module_text_llm/create_approach_script.py | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/modules/text/module_text_llm/module_text_llm/create_approach_script.py b/modules/text/module_text_llm/module_text_llm/create_approach_script.py index 1d8ca048..61880874 100644 --- a/modules/text/module_text_llm/module_text_llm/create_approach_script.py +++ b/modules/text/module_text_llm/module_text_llm/create_approach_script.py @@ -11,17 +11,18 @@ import re import argparse from pathlib import Path -from typing import Union def to_camel_case(snake_str: str) -> str: components = snake_str.split('_') return ''.join(x.title() for x in components) + def create_approach_directory(approach_name: str) -> Path: base_dir = Path(__file__).parent / approach_name base_dir.mkdir(parents=True, exist_ok=True) return base_dir + def create_init_py(base_dir: Path, approach_name: str) -> None: init_content = f""" from module_text_llm.approach_config import ApproachConfig @@ -41,6 +42,7 @@ async def generate_suggestions(self, exercise: Exercise, submission: Submission, with open(base_dir / "__init__.py", "w", encoding="utf-8") as f: f.write(init_content.strip()) + def create_prompt_py(base_dir: Path) -> None: prompt_content = ''' from pydantic import Field, BaseModel @@ -105,6 +107,7 @@ class AssessmentModel(BaseModel): with open(base_dir / "prompt_generate_suggestions.py", "w", encoding="utf-8") as f: f.write(prompt_content.strip()) + def create_generate_suggestions_py(base_dir: Path) -> None: generate_suggestions_content = """ # Placeholder for generate suggestions logic. @@ -114,6 +117,7 @@ def generate_suggestions(): with open(base_dir / "generate_suggestions.py", "w", encoding="utf-8") as f: f.write(generate_suggestions_content.strip()) + def update_config_py(approach_name: str) -> None: config_path = Path(__file__).parent / "config.py" camel_case_name = to_camel_case(approach_name) @@ -137,6 +141,7 @@ def update_config_py(approach_name: str) -> None: f.write(content) f.truncate() + def create_approach(approach_name: str) -> None: base_dir = create_approach_directory(approach_name) create_init_py(base_dir, approach_name) @@ -144,6 +149,7 @@ def create_approach(approach_name: str) -> None: create_generate_suggestions_py(base_dir) update_config_py(approach_name) + if __name__ == "__main__": parser = argparse.ArgumentParser(description="Create a new approach for the Athena project.") parser.add_argument("approach_name", help="The name of the new approach (in snake_case).") From afed9f649007252f0b9bccd271413c0dc4099cb6 Mon Sep 17 00:00:00 2001 From: Enea Gore <73840596+EneaGore@users.noreply.github.com> Date: Tue, 14 Jan 2025 21:24:13 +0100 Subject: [PATCH 25/34] Update create_approach_script.py --- .../module_text_llm/module_text_llm/create_approach_script.py | 1 - 1 file changed, 1 deletion(-) diff --git a/modules/text/module_text_llm/module_text_llm/create_approach_script.py b/modules/text/module_text_llm/module_text_llm/create_approach_script.py index 61880874..95a788af 100644 --- a/modules/text/module_text_llm/module_text_llm/create_approach_script.py +++ b/modules/text/module_text_llm/module_text_llm/create_approach_script.py @@ -1,4 +1,3 @@ -# -*- coding: utf-8 -*- """ This script creates a new approach inside the module_text_llm package. From 63cdf6a96a9b784d1264c1dfa6f0fb14039d90fd Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Thu, 16 Jan 2025 15:55:16 +0100 Subject: [PATCH 26/34] add is graded --- modules/text/module_text_llm/module_text_llm/__main__.py | 2 +- .../module_text_llm/module_text_llm/approach_controller.py | 4 ++-- .../module_text_llm/basic_approach/__init__.py | 4 ++-- .../module_text_llm/basic_approach/generate_suggestions.py | 3 ++- .../module_text_llm/chain_of_thought_approach/__init__.py | 4 ++-- .../chain_of_thought_approach/generate_suggestions.py | 3 ++- 6 files changed, 11 insertions(+), 9 deletions(-) diff --git a/modules/text/module_text_llm/module_text_llm/__main__.py b/modules/text/module_text_llm/module_text_llm/__main__.py index d4e2b05d..d3e7063b 100644 --- a/modules/text/module_text_llm/module_text_llm/__main__.py +++ b/modules/text/module_text_llm/module_text_llm/__main__.py @@ -31,7 +31,7 @@ def process_incoming_feedback(exercise: Exercise, submission: Submission, feedba async def suggest_feedback(exercise: Exercise, submission: Submission, is_graded: bool, module_config: Configuration) -> List[Feedback]: logger.info("suggest_feedback: %s suggestions for submission %d of exercise %d were requested", "Graded" if is_graded else "Non-graded", submission.id, exercise.id) - return await generate_suggestions(exercise, submission, module_config.approach, module_config.debug) + return await generate_suggestions(exercise, submission, module_config.approach, module_config.debug, is_graded) @evaluation_provider diff --git a/modules/text/module_text_llm/module_text_llm/approach_controller.py b/modules/text/module_text_llm/module_text_llm/approach_controller.py index c6617015..cdaae803 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_controller.py +++ b/modules/text/module_text_llm/module_text_llm/approach_controller.py @@ -2,10 +2,10 @@ from athena.text import Exercise, Submission, Feedback from module_text_llm.approach_config import ApproachConfig -async def generate_suggestions(exercise: Exercise, submission: Submission, config: ApproachConfig, debug: bool) -> List[Feedback]: +async def generate_suggestions(exercise: Exercise, submission: Submission, config: ApproachConfig, debug: bool, is_graded: bool) -> List[Feedback]: # Importing the strategy_factory here to avoid circular imports with ApproachConfig # pylint: disable=import-outside-toplevel from module_text_llm import strategy_factory strategy = strategy_factory.get_strategy(config) - return await strategy.generate_suggestions(exercise, submission, config, debug) + return await strategy.generate_suggestions(exercise, submission, config, debug, is_graded) diff --git a/modules/text/module_text_llm/module_text_llm/basic_approach/__init__.py b/modules/text/module_text_llm/module_text_llm/basic_approach/__init__.py index caee8054..c378c60d 100644 --- a/modules/text/module_text_llm/module_text_llm/basic_approach/__init__.py +++ b/modules/text/module_text_llm/module_text_llm/basic_approach/__init__.py @@ -9,6 +9,6 @@ class BasicApproachConfig(ApproachConfig): type: Literal['basic'] = 'basic' generate_suggestions_prompt: GenerateSuggestionsPrompt = Field(default=GenerateSuggestionsPrompt()) - async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, debug: bool): - return await generate_suggestions(exercise,submission,config,debug) + async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, debug: bool, is_graded: bool): + return await generate_suggestions(exercise,submission,config,debug,is_graded) \ No newline at end of file diff --git a/modules/text/module_text_llm/module_text_llm/basic_approach/generate_suggestions.py b/modules/text/module_text_llm/module_text_llm/basic_approach/generate_suggestions.py index 1647abbc..ecead344 100644 --- a/modules/text/module_text_llm/module_text_llm/basic_approach/generate_suggestions.py +++ b/modules/text/module_text_llm/module_text_llm/basic_approach/generate_suggestions.py @@ -15,7 +15,7 @@ from module_text_llm.helpers.utils import add_sentence_numbers, get_index_range_from_line_range, format_grading_instructions from module_text_llm.basic_approach.prompt_generate_suggestions import AssessmentModel -async def generate_suggestions(exercise: Exercise, submission: Submission, config:ApproachConfig, debug: bool) -> List[Feedback]: +async def generate_suggestions(exercise: Exercise, submission: Submission, config:ApproachConfig, debug: bool, is_graded: bool) -> List[Feedback]: model = config.model.get_model() # type: ignore[attr-defined] prompt_input = { "max_points": exercise.max_points, @@ -90,6 +90,7 @@ async def generate_suggestions(exercise: Exercise, submission: Submission, confi index_start=index_start, index_end=index_end, credits=feedback.credits, + is_graded=is_graded, structured_grading_instruction_id=grading_instruction_id, meta={} )) diff --git a/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/__init__.py b/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/__init__.py index 0bcf3fb6..f5cce56d 100644 --- a/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/__init__.py +++ b/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/__init__.py @@ -12,6 +12,6 @@ class ChainOfThoughtConfig(ApproachConfig): thinking_prompt: ThinkingPrompt = Field(default=ThinkingPrompt()) generate_suggestions_prompt: CoTGenerateSuggestionsPrompt = Field(default=CoTGenerateSuggestionsPrompt()) - async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, debug: bool): - return await generate_suggestions(exercise,submission,config,debug) + async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, debug: bool, is_graded: bool): + return await generate_suggestions(exercise,submission,config,debug,is_graded) \ No newline at end of file diff --git a/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/generate_suggestions.py b/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/generate_suggestions.py index cfe1fc34..e5446259 100644 --- a/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/generate_suggestions.py +++ b/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/generate_suggestions.py @@ -17,7 +17,7 @@ from module_text_llm.chain_of_thought_approach.prompt_generate_feedback import AssessmentModel -async def generate_suggestions(exercise: Exercise, submission: Submission, config: ApproachConfig, debug: bool) -> List[Feedback]: +async def generate_suggestions(exercise: Exercise, submission: Submission, config: ApproachConfig, debug: bool, is_graded: bool) -> List[Feedback]: model = config.model.get_model() # type: ignore[attr-defined] prompt_input = { @@ -118,6 +118,7 @@ async def generate_suggestions(exercise: Exercise, submission: Submission, confi index_start=index_start, index_end=index_end, credits=feedback.credits, + is_graded=is_graded, structured_grading_instruction_id=grading_instruction_id, meta={} )) From 4dd1660c7d68579ce6b68e6e46599f977d4b085d Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Thu, 16 Jan 2025 15:58:03 +0100 Subject: [PATCH 27/34] mreslove fconflicts --- .../module_text_llm/module_text_llm/approach_controller.py | 6 +----- 1 file changed, 1 insertion(+), 5 deletions(-) diff --git a/modules/text/module_text_llm/module_text_llm/approach_controller.py b/modules/text/module_text_llm/module_text_llm/approach_controller.py index 1da050b5..3dc8158a 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_controller.py +++ b/modules/text/module_text_llm/module_text_llm/approach_controller.py @@ -8,9 +8,5 @@ async def generate_suggestions(exercise: Exercise, submission: Submission, confi from module_text_llm import strategy_factory strategy = strategy_factory.get_strategy(config) -<<<<<<< HEAD return await strategy.generate_suggestions(exercise, submission, config, debug, is_graded) -======= - return await strategy.generate_suggestions(exercise, submission, config, debug) - ->>>>>>> 200e0c48ce5a6bd5675e60e1f89196b6138acce4 + From b391e136d4e859763fddd78f3fe56fbe3b2bd812 Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Thu, 16 Jan 2025 16:09:04 +0100 Subject: [PATCH 28/34] import structure --- athena/athena/approach_discovery/discover_approaches.py | 1 - athena/athena/approach_discovery/strategy_factory.py | 2 -- modules/text/module_text_llm/module_text_llm/__init__.py | 5 +++-- .../module_text_llm/module_text_llm/approach_controller.py | 6 ++---- 4 files changed, 5 insertions(+), 9 deletions(-) diff --git a/athena/athena/approach_discovery/discover_approaches.py b/athena/athena/approach_discovery/discover_approaches.py index d88507ca..d0674920 100644 --- a/athena/athena/approach_discovery/discover_approaches.py +++ b/athena/athena/approach_discovery/discover_approaches.py @@ -1,4 +1,3 @@ - import importlib import pkgutil import inspect diff --git a/athena/athena/approach_discovery/strategy_factory.py b/athena/athena/approach_discovery/strategy_factory.py index af7b32e7..b2319532 100644 --- a/athena/athena/approach_discovery/strategy_factory.py +++ b/athena/athena/approach_discovery/strategy_factory.py @@ -66,8 +66,6 @@ def get_strategy(self, config): Raises: ValueError: If no strategy is found for the given configuration type. """ - # if not SuggestionStrategyFactory._strategies: - # self.initialize_strategies() config_type = type(config).__name__ strategy_class = SuggestionStrategyFactory._strategies.get(config_type) diff --git a/modules/text/module_text_llm/module_text_llm/__init__.py b/modules/text/module_text_llm/module_text_llm/__init__.py index 5de9668e..9319f477 100644 --- a/modules/text/module_text_llm/module_text_llm/__init__.py +++ b/modules/text/module_text_llm/module_text_llm/__init__.py @@ -1,6 +1,7 @@ import dotenv from athena.approach_discovery.strategy_factory import SuggestionStrategyFactory -from module_text_llm.approach_config import ApproachConfig dotenv.load_dotenv(override=True) -strategy_factory = SuggestionStrategyFactory("module_text_llm", ApproachConfig) + +def get_strategy_factory(base_class): + return SuggestionStrategyFactory("module_text_llm", base_class) diff --git a/modules/text/module_text_llm/module_text_llm/approach_controller.py b/modules/text/module_text_llm/module_text_llm/approach_controller.py index 3dc8158a..2e284493 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_controller.py +++ b/modules/text/module_text_llm/module_text_llm/approach_controller.py @@ -1,12 +1,10 @@ from typing import List from athena.text import Exercise, Submission, Feedback from module_text_llm.approach_config import ApproachConfig +from module_text_llm import get_strategy_factory async def generate_suggestions(exercise: Exercise, submission: Submission, config: ApproachConfig, debug: bool, is_graded: bool) -> List[Feedback]: - # Importing the strategy_factory here to avoid circular imports with ApproachConfig - # pylint: disable=import-outside-toplevel - from module_text_llm import strategy_factory - + strategy_factory = get_strategy_factory(ApproachConfig) strategy = strategy_factory.get_strategy(config) return await strategy.generate_suggestions(exercise, submission, config, debug, is_graded) From 37fc99b68ea7458795077e7b93f26e1d706a735d Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Thu, 16 Jan 2025 16:30:00 +0100 Subject: [PATCH 29/34] linting --- modules/text/module_text_llm/module_text_llm/approach_config.py | 2 +- .../text/module_text_llm/module_text_llm/approach_controller.py | 1 - 2 files changed, 1 insertion(+), 2 deletions(-) diff --git a/modules/text/module_text_llm/module_text_llm/approach_config.py b/modules/text/module_text_llm/module_text_llm/approach_config.py index 71934d81..bf3d613c 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_config.py +++ b/modules/text/module_text_llm/module_text_llm/approach_config.py @@ -9,7 +9,7 @@ class ApproachConfig(BaseModel, ABC): type: str = Field(..., description="The type of approach config") @abstractmethod - async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, debug: bool): + async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, debug: bool, is_graded: bool): pass class Config: diff --git a/modules/text/module_text_llm/module_text_llm/approach_controller.py b/modules/text/module_text_llm/module_text_llm/approach_controller.py index 2e284493..b650ce5f 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_controller.py +++ b/modules/text/module_text_llm/module_text_llm/approach_controller.py @@ -7,4 +7,3 @@ async def generate_suggestions(exercise: Exercise, submission: Submission, confi strategy_factory = get_strategy_factory(ApproachConfig) strategy = strategy_factory.get_strategy(config) return await strategy.generate_suggestions(exercise, submission, config, debug, is_graded) - From 447b7ce217bca198203565f8011f9e3373ed17e3 Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Thu, 16 Jan 2025 16:55:22 +0100 Subject: [PATCH 30/34] use keyword arguemtn to avoid linting max positional arguments error --- modules/text/module_text_llm/module_text_llm/__main__.py | 4 ++-- .../text/module_text_llm/module_text_llm/approach_config.py | 2 +- .../module_text_llm/module_text_llm/approach_controller.py | 2 +- .../module_text_llm/basic_approach/__init__.py | 2 +- .../module_text_llm/chain_of_thought_approach/__init__.py | 2 +- 5 files changed, 6 insertions(+), 6 deletions(-) diff --git a/modules/text/module_text_llm/module_text_llm/__main__.py b/modules/text/module_text_llm/module_text_llm/__main__.py index d3e7063b..0bfc6e41 100644 --- a/modules/text/module_text_llm/module_text_llm/__main__.py +++ b/modules/text/module_text_llm/module_text_llm/__main__.py @@ -29,8 +29,8 @@ def process_incoming_feedback(exercise: Exercise, submission: Submission, feedba @feedback_provider async def suggest_feedback(exercise: Exercise, submission: Submission, is_graded: bool, module_config: Configuration) -> List[Feedback]: - logger.info("suggest_feedback: %s suggestions for submission %d of exercise %d were requested", - "Graded" if is_graded else "Non-graded", submission.id, exercise.id) + logger.info("suggest_feedback: %s suggestions for submission %d of exercise %d were requested, with approach: %s", + "Graded" if is_graded else "Non-graded", submission.id, exercise.id, module_config.approach.__class__.__name__) return await generate_suggestions(exercise, submission, module_config.approach, module_config.debug, is_graded) diff --git a/modules/text/module_text_llm/module_text_llm/approach_config.py b/modules/text/module_text_llm/module_text_llm/approach_config.py index bf3d613c..71aab1ab 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_config.py +++ b/modules/text/module_text_llm/module_text_llm/approach_config.py @@ -9,7 +9,7 @@ class ApproachConfig(BaseModel, ABC): type: str = Field(..., description="The type of approach config") @abstractmethod - async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, debug: bool, is_graded: bool): + async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, *, debug: bool, is_graded: bool): pass class Config: diff --git a/modules/text/module_text_llm/module_text_llm/approach_controller.py b/modules/text/module_text_llm/module_text_llm/approach_controller.py index b650ce5f..c97fbd81 100644 --- a/modules/text/module_text_llm/module_text_llm/approach_controller.py +++ b/modules/text/module_text_llm/module_text_llm/approach_controller.py @@ -6,4 +6,4 @@ async def generate_suggestions(exercise: Exercise, submission: Submission, config: ApproachConfig, debug: bool, is_graded: bool) -> List[Feedback]: strategy_factory = get_strategy_factory(ApproachConfig) strategy = strategy_factory.get_strategy(config) - return await strategy.generate_suggestions(exercise, submission, config, debug, is_graded) + return await strategy.generate_suggestions(exercise, submission, config, debug = debug, is_graded = is_graded) diff --git a/modules/text/module_text_llm/module_text_llm/basic_approach/__init__.py b/modules/text/module_text_llm/module_text_llm/basic_approach/__init__.py index c378c60d..0c9e8311 100644 --- a/modules/text/module_text_llm/module_text_llm/basic_approach/__init__.py +++ b/modules/text/module_text_llm/module_text_llm/basic_approach/__init__.py @@ -9,6 +9,6 @@ class BasicApproachConfig(ApproachConfig): type: Literal['basic'] = 'basic' generate_suggestions_prompt: GenerateSuggestionsPrompt = Field(default=GenerateSuggestionsPrompt()) - async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, debug: bool, is_graded: bool): + async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, *, debug: bool, is_graded: bool): return await generate_suggestions(exercise,submission,config,debug,is_graded) \ No newline at end of file diff --git a/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/__init__.py b/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/__init__.py index f5cce56d..46ff2ae5 100644 --- a/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/__init__.py +++ b/modules/text/module_text_llm/module_text_llm/chain_of_thought_approach/__init__.py @@ -12,6 +12,6 @@ class ChainOfThoughtConfig(ApproachConfig): thinking_prompt: ThinkingPrompt = Field(default=ThinkingPrompt()) generate_suggestions_prompt: CoTGenerateSuggestionsPrompt = Field(default=CoTGenerateSuggestionsPrompt()) - async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, debug: bool, is_graded: bool): + async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, *, debug: bool, is_graded: bool): return await generate_suggestions(exercise,submission,config,debug,is_graded) \ No newline at end of file From ac4151b63a16444980f3694b2ee95021cb743bf4 Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Thu, 16 Jan 2025 17:26:20 +0100 Subject: [PATCH 31/34] udpate creating script --- .../module_text_llm/create_approach_script.py | 12 +++++++++--- 1 file changed, 9 insertions(+), 3 deletions(-) diff --git a/modules/text/module_text_llm/module_text_llm/create_approach_script.py b/modules/text/module_text_llm/module_text_llm/create_approach_script.py index 95a788af..82a0bb7c 100644 --- a/modules/text/module_text_llm/module_text_llm/create_approach_script.py +++ b/modules/text/module_text_llm/module_text_llm/create_approach_script.py @@ -35,8 +35,8 @@ class {to_camel_case(approach_name)}Config(ApproachConfig): type: Literal['{approach_name.lower()}'] = '{approach_name.lower()}' generate_suggestions_prompt: GenerateSuggestionsPrompt = Field(default=GenerateSuggestionsPrompt()) - async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, debug: bool): - return await generate_suggestions(exercise, submission, config, debug) + async def generate_suggestions(self, exercise: Exercise, submission: Submission, config,*, debug: bool, is_graded: bool): + return await generate_suggestions(exercise, submission, config, debug, is_graded) """ with open(base_dir / "__init__.py", "w", encoding="utf-8") as f: f.write(init_content.strip()) @@ -109,8 +109,14 @@ class AssessmentModel(BaseModel): def create_generate_suggestions_py(base_dir: Path) -> None: generate_suggestions_content = """ +from typing import List +from athena import emit_meta +from athena.text import Exercise, Submission, Feedback +from athena.logger import logger + +from module_text_llm.approach_config import ApproachConfig # Placeholder for generate suggestions logic. -def generate_suggestions(): +def generate_suggestions(exercise: Exercise, submission: Submission, config: ApproachConfig, debug: bool, is_graded: bool): pass """ with open(base_dir / "generate_suggestions.py", "w", encoding="utf-8") as f: From 6985e2c0f82a3c46e2ec1414912c14e30e91be6e Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Thu, 16 Jan 2025 17:31:15 +0100 Subject: [PATCH 32/34] linting --- .../ollama_chain_of_thought_approach/__init__.py | 4 ++-- .../ollama_chain_of_thought_approach/generate_suggestions.py | 3 ++- 2 files changed, 4 insertions(+), 3 deletions(-) diff --git a/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/__init__.py b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/__init__.py index ce6a2183..02c3a2a1 100644 --- a/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/__init__.py +++ b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/__init__.py @@ -18,5 +18,5 @@ class OllamaChainOfThoughtConfig(ApproachConfig): thinking_prompt: ThinkingPrompt = Field(default=ThinkingPrompt()) generate_suggestions_prompt: CoTGenerateSuggestionsPrompt = Field(default=CoTGenerateSuggestionsPrompt()) - async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, debug: bool): - return await generate_suggestions(exercise,submission,config,debug) \ No newline at end of file + async def generate_suggestions(self, exercise: Exercise, submission: Submission, config, *, debug: bool, is_graded: bool): + return await generate_suggestions(exercise,submission,config,debug,is_graded) \ No newline at end of file diff --git a/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/generate_suggestions.py b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/generate_suggestions.py index 2f8abb53..c477d0c3 100644 --- a/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/generate_suggestions.py +++ b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/generate_suggestions.py @@ -19,7 +19,7 @@ from module_text_llm.ollama_chain_of_thought_approach.prompt_generate_feedback import AssessmentModel -async def generate_suggestions(exercise: Exercise, submission: Submission, config: ApproachConfig, debug: bool) -> List[Feedback]: +async def generate_suggestions(exercise: Exercise, submission: Submission, config: ApproachConfig, debug: bool, is_graded:bool) -> List[Feedback]: model = config.model.get_model() # type: ignore[attr-defined] prompt_input = { @@ -116,6 +116,7 @@ async def generate_suggestions(exercise: Exercise, submission: Submission, confi index_start=index_start, index_end=index_end, credits=feedback.credits, + is_graded=is_graded, structured_grading_instruction_id=grading_instruction_id, meta={} )) From 3c5d2a3e3d50c7c3e88e4ccc34a93c7145428bc0 Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Fri, 17 Jan 2025 00:12:34 +0100 Subject: [PATCH 33/34] working evaluation --- llm_core/llm_core/models/__init__.py | 5 ++++- llm_core/llm_core/models/openai.py | 2 +- .../module_text_llm/module_text_llm/generate_evaluation.py | 5 +++-- .../module_text_llm/prompts/generate_evaluation.py | 4 ++++ 4 files changed, 12 insertions(+), 4 deletions(-) diff --git a/llm_core/llm_core/models/__init__.py b/llm_core/llm_core/models/__init__.py index c5cdc3d9..25491886 100644 --- a/llm_core/llm_core/models/__init__.py +++ b/llm_core/llm_core/models/__init__.py @@ -3,7 +3,7 @@ from langchain.base_language import BaseLanguageModel from llm_core.models.model_config import ModelConfig - +from athena.logger import logger DefaultModelConfig: Type[ModelConfig] MiniModelConfig: ModelConfig @@ -20,6 +20,9 @@ if default_model_name in openai_config.available_models: DefaultModelConfig = openai_config.OpenAIModelConfig if evaluation_model_name in openai_config.available_models: + logger.info("Evaluation model: %s", evaluation_model_name) + for model in openai_config.available_models: + logger.info("Available openai models: %s", model) evaluation_model = openai_config.available_models[evaluation_model_name] except AttributeError: pass diff --git a/llm_core/llm_core/models/openai.py b/llm_core/llm_core/models/openai.py index 7bcc0f11..816a9391 100644 --- a/llm_core/llm_core/models/openai.py +++ b/llm_core/llm_core/models/openai.py @@ -24,7 +24,7 @@ if openai_available: openai.api_type = "openai" for model in openai.models.list(): - if "gpt" in model.id: + if ("gpt" in model.id or "o1" in model.id) and "audio" not in model.id and "realtime" not in model.id: available_models[OPENAI_PREFIX + model.id] = ChatOpenAI(model=model.id) # Load Azure OpenAI models 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 50473dd3..0f2a23f4 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 @@ -23,7 +23,7 @@ class AccuracyMetric(BaseModel): level_of_needed_modification_label: Literal["no", "minor", "major"] = Field(..., description="Estimated level of needed modification") class Evaluation(BaseModel): - metrics: Sequence[AccuracyMetric] = Field(...) + metrics: List[AccuracyMetric] = Field(..., description="List of accuracy metrics for each feedback") async def generate_evaluation( @@ -86,7 +86,8 @@ def feedback_to_dict(feedback: Feedback): f"exercise-{exercise.id}", f"submission-{submission.id}", "evaluation" - ] + ], + use_function_calling=True ) if result is None: diff --git a/modules/text/module_text_llm/module_text_llm/prompts/generate_evaluation.py b/modules/text/module_text_llm/module_text_llm/prompts/generate_evaluation.py index 10daa84a..b37c838a 100644 --- a/modules/text/module_text_llm/module_text_llm/prompts/generate_evaluation.py +++ b/modules/text/module_text_llm/module_text_llm/prompts/generate_evaluation.py @@ -18,9 +18,13 @@ # Example (Human) Feedback: {true_feedbacks} + +The final response wil be in json. """ human_message = """\ ### Model Output: {predicted_feedbacks} +The final response wil be in json. + """ \ No newline at end of file From ac9b52d2b141d1ff064e15fb32f2386acf16dab2 Mon Sep 17 00:00:00 2001 From: = Enea_Gore Date: Fri, 17 Jan 2025 03:19:41 +0100 Subject: [PATCH 34/34] adjust prompt --- .../ollama_chain_of_thought_approach/prompt_thinking.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/prompt_thinking.py b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/prompt_thinking.py index f6b6ebc1..ea20ffa8 100644 --- a/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/prompt_thinking.py +++ b/modules/text/module_text_llm/module_text_llm/ollama_chain_of_thought_approach/prompt_thinking.py @@ -16,8 +16,8 @@ {grading_instructions} Max points: {max_points}. The total points granted in all feedback elements must not exceed {max_points}. Format your response in the following way: - Grading instruction (sentence to ): , credits: - If the feedback is unreferenced simple right Unreferenced + Title: Grading instruction (sentence to ): , credits: + If the feedback is unreferenced simple right Unreferenced instead of the sentence range. """ human_message = """\