From 02211a2c03cd980c19596882375e92c021a1f099 Mon Sep 17 00:00:00 2001 From: Dmytro Polityka Date: Tue, 17 Sep 2024 14:27:41 +0200 Subject: [PATCH 01/21] add grading instructions to the prompt, get points --- athena/athena/schemas/feedback.py | 3 + ...generate_non_graded_suggestions_by_file.py | 62 +++++++++++++++++++ ...generate_non_graded_suggestions_by_file.py | 7 ++- 3 files changed, 71 insertions(+), 1 deletion(-) diff --git a/athena/athena/schemas/feedback.py b/athena/athena/schemas/feedback.py index 4cf9c6a2e..3cbd62ea8 100644 --- a/athena/athena/schemas/feedback.py +++ b/athena/athena/schemas/feedback.py @@ -23,6 +23,9 @@ class Feedback(Schema, ABC): is_graded: Optional[bool] = Field(None, description="Graded or non graded.", example=False) + positive: int = Field( + description="Positive means that the student got a principle correctly. Negative means that the student needs " + "to put in some work. Empty is set if the feedback is neither positive nor negative.") meta: dict = Field({}, example={}) diff --git a/modules/programming/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py index b857a24f4..1bc666910 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py @@ -8,6 +8,9 @@ from module_programming_llm.config import NonGradedBasicApproachConfig from module_programming_llm.generate_summary_by_file import generate_summary_by_file +from module_programming_llm.split_grading_instructions_by_file import ( + split_grading_instructions_by_file, +) from module_programming_llm.split_problem_statement_by_file import ( split_problem_statement_by_file, ) @@ -36,6 +39,14 @@ class FeedbackModel(BaseModel): line_end: Optional[int] = Field( description="Referenced line number end, or empty if unreferenced" ) + is_positive: Optional[bool] = Field( + description="Describes if this feedback item doesn't require work(positive), requires work(negative) or is " + "neutral(empty)") + credits: Optional[float] = Field( + description="The number of points you would give for this element if you were a human tutor. Remember that " + "the total number of credits should not exceed the total number of points. Negative points mean " + "that the student should put in more work." + ) class Config: title = "Feedback" @@ -108,6 +119,25 @@ async def generate_suggestions_by_file( ) problem_statement_tokens = num_tokens_from_string(exercise.problem_statement or "") + + # Get split problem statement and grading instructions by file (if necessary) + split_problem_statement, split_grading_instructions = await asyncio.gather( + split_problem_statement_by_file( + exercise=exercise, + submission=submission, + prompt=chat_prompt, + config=config, + debug=debug, + ), + split_grading_instructions_by_file( + exercise=exercise, + submission=submission, + prompt=chat_prompt, + config=config, + debug=debug, + ), + ) + is_short_problem_statement = ( problem_statement_tokens <= config.split_problem_statement_by_file_prompt.tokens_before_split @@ -121,6 +151,21 @@ async def generate_suggestions_by_file( else {} ) + is_short_grading_instructions = ( + num_tokens_from_string(exercise.grading_instructions) + <= config.split_grading_instructions_by_file_prompt.tokens_before_split + if exercise.grading_instructions is not None + else True + ) + file_grading_instructions = ( + { + item.file_name: item.grading_instructions + for item in split_grading_instructions.items + } + if split_grading_instructions is not None + else {} + ) + # Gather prompt inputs for each changed file (independently) for file_path, file_content in changed_files.items(): problem_statement = ( @@ -155,6 +200,20 @@ async def generate_suggestions_by_file( template_to_submission_diff = "\n".join(diff_without_deletions) + grading_instructions = ( + exercise.grading_instructions or "" + if is_short_grading_instructions + else file_grading_instructions.get( + file_path, "No relevant grading instructions found." + ) + ) + grading_instructions = ( + grading_instructions + if grading_instructions.strip() + else "No grading instructions found." + ) + + prompt_inputs.append( { "submission_file": file_content, @@ -162,6 +221,9 @@ async def generate_suggestions_by_file( "problem_statement": problem_statement, "file_path": file_path, "summary": summary_string, + "max_points": exercise.max_points, + "bonus_points": exercise.bonus_points, + "grading_instructions": grading_instructions, } ) diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_non_graded_suggestions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_non_graded_suggestions_by_file.py index 9b52fefcf..69dc656e3 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_non_graded_suggestions_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_non_graded_suggestions_by_file.py @@ -5,11 +5,13 @@ {problem_statement} # Task -Create non graded improvement suggestions for a student\'s programming submission that a human tutor would recommend. \ +Create improvement suggestions for a student\'s programming submission that a human tutor would recommend. \ Assume the tutor is not familiar with the solution. The feedback must contain only the feedback the student can learn from. Important: the answer you generate must not contain any solution suggestions or contain corrected errors. Rather concentrate on incorrectly applied principles or inconsistencies. +Try to assess the submission in a style a human tutor would do(if the grading instructions are present - follow them). +The credits should be negative if the student should put in more work. Students can move some functionality to other files. Students can deviate to some degree from the problem statement or book unless they complete all tasks. Very important, the feedback must be balanced. @@ -28,6 +30,9 @@ human_message = """\ Path: {file_path} +{grading_instructions} +Max points: {max_points}, bonus points: {bonus_points} (whole assessment, not just this file) + File(with line numbers : ): \"\"\" {submission_file} From 0885e94e1baebb5888f719706326ff299b95086c Mon Sep 17 00:00:00 2001 From: Dmytro Polityka Date: Tue, 1 Oct 2024 12:44:19 +0200 Subject: [PATCH 02/21] fix bug --- .../generate_non_graded_suggestions_by_file.py | 14 +------------- 1 file changed, 1 insertion(+), 13 deletions(-) diff --git a/modules/programming/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py index 1bc666910..2cb1cb291 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py @@ -39,9 +39,6 @@ class FeedbackModel(BaseModel): line_end: Optional[int] = Field( description="Referenced line number end, or empty if unreferenced" ) - is_positive: Optional[bool] = Field( - description="Describes if this feedback item doesn't require work(positive), requires work(negative) or is " - "neutral(empty)") credits: Optional[float] = Field( description="The number of points you would give for this element if you were a human tutor. Remember that " "the total number of credits should not exceed the total number of points. Negative points mean " @@ -108,16 +105,6 @@ async def generate_suggestions_by_file( ) summary_string = solution_summary.describe_solution_summary() if solution_summary is not None else "" - - # Get split problem statement by file (if necessary) - split_problem_statement = await split_problem_statement_by_file( - exercise=exercise, - submission=submission, - prompt=chat_prompt, - config=config, - debug=debug, - ) - problem_statement_tokens = num_tokens_from_string(exercise.problem_statement or "") # Get split problem statement and grading instructions by file (if necessary) @@ -319,6 +306,7 @@ async def generate_suggestions_by_file( file_path=file_path, line_start=feedback.line_start, line_end=feedback.line_end, + credits=feedback.credits, is_graded=False, meta={}, ) From d9841bca6e8376843fb672413e8951ef5a921002 Mon Sep 17 00:00:00 2001 From: Dmytro Polityka Date: Tue, 1 Oct 2024 13:54:14 +0200 Subject: [PATCH 03/21] add split grading instructions prompt --- .../module_programming_llm/module_programming_llm/config.py | 1 + 1 file changed, 1 insertion(+) diff --git a/modules/programming/module_programming_llm/module_programming_llm/config.py b/modules/programming/module_programming_llm/module_programming_llm/config.py index 5edd58003..69f89c1a4 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/config.py +++ b/modules/programming/module_programming_llm/module_programming_llm/config.py @@ -133,6 +133,7 @@ class NonGradedBasicApproachConfig(BasicApproachConfig, ABC): split_problem_statement_by_file_prompt: SplitProblemStatementsWithoutSolutionByFilePrompt = Field(default=SplitProblemStatementsWithoutSolutionByFilePrompt()) generate_suggestions_by_file_prompt: FeedbackGenerationBasePrompt = Field(default=NonGradedFeedbackGenerationPrompt()) + split_grading_instructions_by_file_prompt: SplitGradingInstructionsByFilePrompt = (Field(default=SplitGradingInstructionsByFilePrompt())) @config_schema_provider From 0b53bb2a61c468356c732919ff52b6d3c9890372 Mon Sep 17 00:00:00 2001 From: Dmytro Polityka Date: Tue, 1 Oct 2024 14:13:53 +0200 Subject: [PATCH 04/21] remove deprecated field --- athena/athena/schemas/feedback.py | 3 --- 1 file changed, 3 deletions(-) diff --git a/athena/athena/schemas/feedback.py b/athena/athena/schemas/feedback.py index 3cbd62ea8..4cf9c6a2e 100644 --- a/athena/athena/schemas/feedback.py +++ b/athena/athena/schemas/feedback.py @@ -23,9 +23,6 @@ class Feedback(Schema, ABC): is_graded: Optional[bool] = Field(None, description="Graded or non graded.", example=False) - positive: int = Field( - description="Positive means that the student got a principle correctly. Negative means that the student needs " - "to put in some work. Empty is set if the feedback is neither positive nor negative.") meta: dict = Field({}, example={}) From 2f3b8d1961ad8454f44e6c27b714903a82d1ba29 Mon Sep 17 00:00:00 2001 From: Dmytro Polityka Date: Tue, 1 Oct 2024 17:05:08 +0200 Subject: [PATCH 05/21] improve summary prompt --- .../module_programming_llm/generate_summary_by_file.py | 6 +++--- .../prompts/summarize_submission_by_file.py | 2 -- 2 files changed, 3 insertions(+), 5 deletions(-) diff --git a/modules/programming/module_programming_llm/module_programming_llm/generate_summary_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/generate_summary_by_file.py index 144d750bf..5cbc7a439 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/generate_summary_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/generate_summary_by_file.py @@ -22,8 +22,8 @@ class FileDescription(BaseModel): - file_name: str = Field(description="File name") - description: str = Field(description="Summary relevant for this file") + file_name: str = Field(description="The name of the file") + description: str = Field(description="Summary relevant for the file") class Config: title = "FileDescription" @@ -32,7 +32,7 @@ class Config: class SolutionSummary(BaseModel): """Collection of summaries, accessible by file path""" - items: Dict[str, str] = Field(description="File summaries indexed by file path") + items: Dict[str, str] = Field(description="A dictionary of file-wise summary objects") class Config: title = "SolutionSummary" diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/summarize_submission_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/summarize_submission_by_file.py index 7ba2d1281..15b61a9af 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/summarize_submission_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/summarize_submission_by_file.py @@ -14,9 +14,7 @@ Include full path for files where necessary. # Output -If 'Explanation' is empty, put double quotes around. Adhere to schema to correctly encapsulate 'Explanation' only into the response. (Critical!) -It is absolutely unacceptable to include any free text that is not part of schema or any format violating response. """ human_message = """\ From 12a8ce6a13a29645e5557bd60bc7689a0446b8bf Mon Sep 17 00:00:00 2001 From: Dmytro Polityka Date: Fri, 4 Oct 2024 04:14:45 +0200 Subject: [PATCH 06/21] upgrade langchain to 0.3.x --- assessment_module_manager/poetry.lock | 297 +++++----- assessment_module_manager/pyproject.toml | 2 +- athena/athena/endpoints.py | 2 +- .../helpers/programming/code_repository.py | 6 +- athena/athena/schemas/exercise.py | 2 +- athena/athena/schemas/feedback.py | 2 +- athena/athena/schemas/modeling_exercise.py | 2 +- athena/athena/schemas/programming_exercise.py | 11 +- athena/athena/schemas/schema.py | 2 +- athena/athena/schemas/submission.py | 2 +- athena/athena/schemas/text_exercise.py | 2 +- athena/poetry.lock | 448 ++++++++------ athena/pyproject.toml | 2 +- .../modeling/module_modeling_llm/poetry.lock | 207 +++---- .../module_modeling_llm/pyproject.toml | 4 +- .../module_programming_llm/__main__.py | 9 +- .../helpers/llm_utils.py | 40 +- .../helpers/models/model_config.py | 3 + .../helpers/models/openai.py | 7 +- .../helpers/models/replicate.py | 2 +- .../module_programming_llm/helpers/utils.py | 2 +- .../module_programming_llm/poetry.lock | 552 ++++++++++++------ .../module_programming_llm/pyproject.toml | 10 +- modules/text/module_text_llm/poetry.lock | 228 ++++---- modules/text/module_text_llm/pyproject.toml | 4 +- 25 files changed, 1082 insertions(+), 766 deletions(-) diff --git a/assessment_module_manager/poetry.lock b/assessment_module_manager/poetry.lock index d2b2a7a3e..c2f99a190 100644 --- a/assessment_module_manager/poetry.lock +++ b/assessment_module_manager/poetry.lock @@ -2,13 +2,13 @@ [[package]] name = "anyio" -version = "4.4.0" +version = "4.6.0" description = "High level compatibility layer for multiple asynchronous event loop implementations" optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" files = [ - {file = "anyio-4.4.0-py3-none-any.whl", hash = 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"https://github.com/ls1intum/Athena.git", rev = "9773c41", subdirectory = "athena"} fastapi = "^0.109.1" uvicorn = "^0.23.0" httpx = "^0.24.1" diff --git a/athena/athena/endpoints.py b/athena/athena/endpoints.py index 6d259a2a2..a30140500 100644 --- a/athena/athena/endpoints.py +++ b/athena/athena/endpoints.py @@ -156,7 +156,7 @@ class SubmissionSelectorRequest(BaseModel): class Config: # Allow camelCase field names in the API (converted to snake_case) alias_generator = to_camel - allow_population_by_field_name = True + populate_by_name = True @app.post("/select_submission", responses=module_responses) @authenticated diff --git a/athena/athena/helpers/programming/code_repository.py b/athena/athena/helpers/programming/code_repository.py index 31a1675ef..c64aaa900 100644 --- a/athena/athena/helpers/programming/code_repository.py +++ b/athena/athena/helpers/programming/code_repository.py @@ -18,7 +18,7 @@ def get_repository_zip(url: str, authorization_secret: Optional[str] = None) -> the cache or by downloading it, and return a ZipFile object. Optional: Authorization secret for the API. If omitted, it will be auto-determined given the request session. """ - url_hash = hashlib.md5(url.encode("utf-8")).hexdigest() + url_hash = hashlib.md5(str(url).encode("utf-8")).hexdigest() file_name = url_hash + ".zip" cache_file_path = cache_dir / file_name @@ -27,7 +27,7 @@ def get_repository_zip(url: str, authorization_secret: Optional[str] = None) -> if contextvars.repository_authorization_secret_context_var_empty(): raise ValueError("Authorization secret for the repository API is not set. Pass authorization_secret to this function or add the X-Repository-Authorization-Secret header to the request from the assessment module manager.") authorization_secret = contextvars.get_repository_authorization_secret_context_var() - with httpx.stream("GET", url, headers={ "Authorization": cast(str, authorization_secret) }) as response: + with httpx.stream("GET", str(url), headers={ "Authorization": cast(str, authorization_secret) }) as response: response.raise_for_status() with open(cache_file_path, "wb") as f: for chunk in response.iter_bytes(): @@ -42,7 +42,7 @@ def get_repository(url: str, authorization_secret: Optional[str] = None) -> Repo downloading it, and return a Repo object. """ - url_hash = hashlib.md5(url.encode("utf-8")).hexdigest() + url_hash = hashlib.md5(str(url).encode("utf-8")).hexdigest() dir_name = url_hash + ".git" cache_dir_path = cache_dir / dir_name diff --git a/athena/athena/schemas/exercise.py b/athena/athena/schemas/exercise.py index 1f173e2e3..ee85e05a5 100644 --- a/athena/athena/schemas/exercise.py +++ b/athena/athena/schemas/exercise.py @@ -29,4 +29,4 @@ class Exercise(Schema, ABC): meta: dict = Field({}, example={"internal_id": "5"}) class Config: - orm_mode = True + from_attributes = True diff --git a/athena/athena/schemas/feedback.py b/athena/athena/schemas/feedback.py index 4cf9c6a2e..24af49410 100644 --- a/athena/athena/schemas/feedback.py +++ b/athena/athena/schemas/feedback.py @@ -33,4 +33,4 @@ def to_model(self, is_suggestion: bool = False, lms_id: Optional[int] = None, lm return type(self).get_model_class()(**self.dict(), is_suggestion=is_suggestion, lms_id=lms_id, lms_url=lms_url) class Config: - orm_mode = True + from_attributes = True diff --git a/athena/athena/schemas/modeling_exercise.py b/athena/athena/schemas/modeling_exercise.py index 70452f839..c3e34469a 100644 --- a/athena/athena/schemas/modeling_exercise.py +++ b/athena/athena/schemas/modeling_exercise.py @@ -8,6 +8,6 @@ class ModelingExercise(Exercise): """A modeling exercise that can be solved by students, enhanced with metadata.""" - type: ExerciseType = Field(ExerciseType.modeling, const=True) + type: ExerciseType = Field(ExerciseType.modeling, Literal=True) example_solution: Optional[str] = Field(None, description="An example solution to the exercise.") diff --git a/athena/athena/schemas/programming_exercise.py b/athena/athena/schemas/programming_exercise.py index ac875b05d..a78cf8f9d 100644 --- a/athena/athena/schemas/programming_exercise.py +++ b/athena/athena/schemas/programming_exercise.py @@ -10,7 +10,7 @@ class ProgrammingExercise(Exercise): """A programming exercise that can be solved by students, enhanced with metadata.""" - type: ExerciseType = Field(ExerciseType.programming, const=True) + type: ExerciseType = Field(ExerciseType.programming, Literal=True) programming_language: str = Field(description="The programming language that is used for this exercise.", example="java") solution_repository_uri: AnyUrl = Field(description="URL to the solution git repository, which contains the " @@ -51,4 +51,11 @@ def get_tests_zip(self) -> ZipFile: def get_tests_repository(self) -> Repo: """Return the tests repository as a Repo object.""" - return get_repository(self.tests_repository_uri) \ No newline at end of file + return get_repository(self.tests_repository_uri) + + def to_model(self): + model = super().to_model() + model.solution_repository_uri = str(self.solution_repository_uri) + model.template_repository_uri = str(self.template_repository_uri) + model.tests_repository_uri = str(self.tests_repository_uri) + return model \ No newline at end of file diff --git a/athena/athena/schemas/schema.py b/athena/athena/schemas/schema.py index 67e146ada..b0e7e6b7f 100644 --- a/athena/athena/schemas/schema.py +++ b/athena/athena/schemas/schema.py @@ -32,4 +32,4 @@ def to_model(self): class Config: # Allow camelCase field names in the API (converted to snake_case) alias_generator = to_camel - allow_population_by_field_name = True \ No newline at end of file + populate_by_name = True \ No newline at end of file diff --git a/athena/athena/schemas/submission.py b/athena/athena/schemas/submission.py index f9e39c372..0bf684bdc 100644 --- a/athena/athena/schemas/submission.py +++ b/athena/athena/schemas/submission.py @@ -12,4 +12,4 @@ class Submission(Schema, ABC): meta: dict = Field({}, example={}) class Config: - orm_mode = True + from_attributes = True diff --git a/athena/athena/schemas/text_exercise.py b/athena/athena/schemas/text_exercise.py index 6c8367667..ac3861a70 100644 --- a/athena/athena/schemas/text_exercise.py +++ b/athena/athena/schemas/text_exercise.py @@ -8,6 +8,6 @@ class TextExercise(Exercise): """A text exercise that can be solved by students, enhanced with metadata.""" - type: ExerciseType = Field(ExerciseType.text, const=True) + type: ExerciseType = Field(ExerciseType.text, Literal=True) example_solution: Optional[str] = Field(None, description="An example solution to the exercise.") diff --git a/athena/poetry.lock b/athena/poetry.lock index a9d171803..6a72b908f 100644 --- a/athena/poetry.lock +++ b/athena/poetry.lock @@ -1,14 +1,25 @@ # This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +[[package]] +name = "annotated-types" +version = "0.7.0" +description = "Reusable constraint types to use with typing.Annotated" +optional = false +python-versions = ">=3.8" +files = [ + {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"}, + {file = "annotated_types-0.7.0.tar.gz", hash = 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b/modules/modeling/module_modeling_llm/pyproject.toml index b57e0e2e9..bc95a85d6 100644 --- a/modules/modeling/module_modeling_llm/pyproject.toml +++ b/modules/modeling/module_modeling_llm/pyproject.toml @@ -7,8 +7,8 @@ license = "MIT" [tool.poetry.dependencies] python = "3.11.*" -athena = { path = "../../../athena", develop = true } -#athena = { git = "https://github.com/ls1intum/Athena.git", rev = "d9ff3bd", subdirectory = "athena"} +#athena = { path = "../../../athena", develop = true } +athena = { git = "https://github.com/ls1intum/Athena.git", rev = "9773c41", subdirectory = "athena"} openai = "1.42.0" langchain = "0.2.15" python-dotenv = "1.0.0" diff --git a/modules/programming/module_programming_llm/module_programming_llm/__main__.py b/modules/programming/module_programming_llm/module_programming_llm/__main__.py index e8356270f..2daf56637 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/__main__.py +++ b/modules/programming/module_programming_llm/module_programming_llm/__main__.py @@ -1,6 +1,8 @@ +import os from typing import List import tiktoken +from langchain_core.globals import set_debug, set_verbose from athena import ( app, @@ -52,4 +54,9 @@ async def suggest_feedback(exercise: Exercise, submission: Submission, is_graded if __name__ == "__main__": # Preload for token estimation later tiktoken.get_encoding("cl100k_base") - app.start() \ No newline at end of file + app.start() + + enable_debug = os.getenv("ENABLE_DEBUGGING_INFO", "False").lower() in ("true", "1") + if enable_debug: + set_debug(True) + set_verbose(True) \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/helpers/llm_utils.py b/modules/programming/module_programming_llm/module_programming_llm/helpers/llm_utils.py index a035a5970..02d421bef 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/helpers/llm_utils.py +++ b/modules/programming/module_programming_llm/module_programming_llm/helpers/llm_utils.py @@ -1,24 +1,21 @@ from typing import Optional, Type, TypeVar, List, Any, Dict from langchain.callbacks.tracers import langchain +from langchain_core.output_parsers.openai_functions import JsonOutputFunctionsParser +from langchain_core.utils.function_calling import convert_to_openai_function from pydantic import BaseModel, ValidationError import tiktoken -from langchain.chains import LLMChain -from langchain.chat_models import ChatOpenAI +from langchain_community.chat_models import ChatOpenAI from langchain.base_language import BaseLanguageModel from langchain.prompts import ( ChatPromptTemplate, SystemMessagePromptTemplate, HumanMessagePromptTemplate, ) -from langchain.chains.openai_functions import create_structured_output_chain from langchain.output_parsers import PydanticOutputParser from langchain.schema import ( - OutputParserException, - BaseLLMOutputParser, - Generation, - LLMResult, + OutputParserException ) from athena import emit_meta, get_experiment_environment @@ -87,7 +84,7 @@ def supports_function_calling(model: BaseLanguageModel): Returns: boolean: True if the model supports function calling, False otherwise """ - return False # isinstance(model, ChatOpenAI) TODO: find out how to make function calling work again + return isinstance(model, ChatOpenAI) def get_chat_prompt_with_formatting_instructions( @@ -154,21 +151,32 @@ async def predict_and_parse( tags.append(f"run-{experiment.run_id}") if supports_function_calling(model): - chain = create_structured_output_chain(pydantic_object, llm=model, prompt=chat_prompt, tags=tags) - chain.verbose = True + openai_functions = [convert_to_openai_function(pydantic_object)] + + runnable = chat_prompt | model.bind(functions=openai_functions).with_retry( + retry_if_exception_type=(ValueError, OutputParserException), + wait_exponential_jitter=True, + stop_after_attempt=3, + ) | JsonOutputFunctionsParser() + try: - return await chain.arun(**prompt_input) + output_dict = await runnable.ainvoke(prompt_input) + return pydantic_object.parse_obj(output_dict) except (OutputParserException, ValidationError) as e: logger.error("Exception type: %s, Message: %s", type(e).__name__, e) return None output_parser = PydanticOutputParser(pydantic_object=pydantic_object) - chain = LLMChain(llm=model, prompt=chat_prompt, output_parser=output_parser, tags=tags) + + runnable = chat_prompt | model.with_retry( + retry_if_exception_type=(ValueError, OutputParserException), + wait_exponential_jitter=True, + stop_after_attempt=3, + ) | output_parser + try: - return await chain.arun(**prompt_input) + output_dict = await runnable.ainvoke(prompt_input) + return pydantic_object.parse_obj(output_dict) except (OutputParserException, ValidationError) as e: logger.error("Exception type: %s, Message: %s", type(e).__name__, e) - # In the future, we should probably have some recovery mechanism here (i.e. fix the output with another prompt) return None - - # todo debug settings diff --git a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/model_config.py b/modules/programming/module_programming_llm/module_programming_llm/helpers/models/model_config.py index eae644f57..cdc84c900 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/model_config.py +++ b/modules/programming/module_programming_llm/module_programming_llm/helpers/models/model_config.py @@ -5,6 +5,9 @@ class ModelConfig(BaseModel, ABC): + class Config: + protected_namespaces = () + @abstractmethod def get_model(self) -> BaseLanguageModel: pass diff --git a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/openai.py b/modules/programming/module_programming_llm/module_programming_llm/helpers/models/openai.py index 23e1669c2..75fa805f6 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/openai.py +++ b/modules/programming/module_programming_llm/module_programming_llm/helpers/models/openai.py @@ -4,9 +4,10 @@ from typing import Dict, List from enum import Enum -from pydantic import Field, validator, PositiveInt +from pydantic import Field, field_validator, PositiveInt from langchain.base_language import BaseLanguageModel -from langchain_openai import AzureChatOpenAI, ChatOpenAI +from langchain_community.chat_models import ChatOpenAI +from langchain_openai import AzureChatOpenAI from athena.logger import logger from .model_config import ModelConfig @@ -100,7 +101,7 @@ class OpenAIModelConfig(ModelConfig): [See more information about frequency and presence penalties.](https://platform.openai.com/docs/api-reference/parameter-details)\ """) - @validator('max_tokens') + @field_validator('max_tokens') def max_tokens_must_be_positive(cls, v): """ Validate that max_tokens is a positive integer. diff --git 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"1.2.2" @@ -2330,4 +2348,4 @@ multidict = ">=4.0" [metadata] lock-version = "2.0" python-versions = "3.11.*" -content-hash = "e3d6d9da95585aa2a7cba97910d821d5cda5412c2a37578097b588e49553d19c" +content-hash = "6bfb56be4037a62d725e200189f0349cab4b1c353aceb4cf146ade64f09537a8" diff --git a/modules/text/module_text_llm/pyproject.toml b/modules/text/module_text_llm/pyproject.toml index 121f2a482..f958ba84c 100644 --- a/modules/text/module_text_llm/pyproject.toml +++ b/modules/text/module_text_llm/pyproject.toml @@ -7,8 +7,8 @@ license = "MIT" [tool.poetry.dependencies] python = "3.11.*" -athena = { path = "../../../athena", develop = true } -#athena = { git = "https://github.com/ls1intum/Athena.git", rev = "2da2d33", subdirectory = "athena"} +#athena = { path = "../../../athena", develop = true } +athena = { git = "https://github.com/ls1intum/Athena.git", rev = "9773c41", subdirectory = "athena"} replicate = "^0.11.0" langsmith = ">=0.1.0,<0.2.0" gitpython = "3.1.41" From 559453971903b13ddc2a55d14a1f556f6b376329 Mon Sep 17 00:00:00 2001 From: Dmytro Polityka Date: Fri, 4 Oct 2024 19:47:33 +0200 Subject: [PATCH 07/21] change api version --- .../module_programming_llm/helpers/models/openai.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/openai.py b/modules/programming/module_programming_llm/module_programming_llm/helpers/models/openai.py index 75fa805f6..b9b056357 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/openai.py +++ b/modules/programming/module_programming_llm/module_programming_llm/helpers/models/openai.py @@ -16,6 +16,7 @@ AZURE_OPENAI_PREFIX = "azure_openai_" openai_available = bool(os.environ.get("OPENAI_API_KEY")) azure_openai_available = bool(os.environ.get("AZURE_OPENAI_API_KEY")) +api_version = bool(os.environ.get("OPENAI_API_VERSION")) available_models: Dict[str, BaseLanguageModel] = {} @@ -35,9 +36,9 @@ def _get_azure_openai_deployments() -> List[str]: "api-key": os.environ["AZURE_OPENAI_API_KEY"] } - models_response = requests.get(f"{base_url}/models?api-version=2023-03-15-preview", headers=headers, timeout=30) + models_response = requests.get(f"{base_url}/models?api-version={api_version}", headers=headers, timeout=30) models_data = models_response.json()["data"] - deployments_response = requests.get(f"{base_url}/deployments?api-version=2023-03-15-preview", headers=headers, + deployments_response = requests.get(f"{base_url}/deployments?api-version={api_version}", headers=headers, timeout=30) deployments_data = deployments_response.json()["data"] From 070c488b618dbd05b2fc2c543bc7f765f0fbf556 Mon Sep 17 00:00:00 2001 From: Dmytro Polityka Date: Fri, 4 Oct 2024 21:06:57 +0200 Subject: [PATCH 08/21] revert --- .../module_programming_llm/helpers/models/openai.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/openai.py b/modules/programming/module_programming_llm/module_programming_llm/helpers/models/openai.py index b9b056357..cb9d889cc 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/openai.py +++ b/modules/programming/module_programming_llm/module_programming_llm/helpers/models/openai.py @@ -16,7 +16,7 @@ AZURE_OPENAI_PREFIX = "azure_openai_" openai_available = bool(os.environ.get("OPENAI_API_KEY")) azure_openai_available = bool(os.environ.get("AZURE_OPENAI_API_KEY")) -api_version = bool(os.environ.get("OPENAI_API_VERSION")) +api_version = os.environ.get("OPENAI_API_VERSION") available_models: Dict[str, BaseLanguageModel] = {} From b059c105bc64acd254d34f42dd9cf1f247c88c37 Mon Sep 17 00:00:00 2001 From: Dmytro Polityka Date: Sun, 6 Oct 2024 10:11:14 +0200 Subject: [PATCH 09/21] restructure the module --- .../approaches/basic_by_file_approach.py | 110 ++++++ .../module_programming_llm/config.py | 163 ++------- .../generate_graded_suggestions_by_file.py | 327 ------------------ ...generate_non_graded_suggestions_by_file.py | 315 ----------------- .../generate_summary_by_file.py | 157 --------- .../generate_file_summary.py | 125 +++++++ .../generate_file_summary_input.py | 16 + .../generate_file_summary_output.py | 27 ++ .../prompt.py} | 0 ...generate_non_graded_suggestions_by_file.py | 50 --- .../generate_suggestions_by_file.py | 258 ++++++++++++++ .../generate_suggestions_by_file_input.py | 54 +++ .../generate_suggestions_by_file_output.py | 33 ++ .../prompt.py} | 0 .../generate_suggestions_zero_shot.py | 5 + .../prompts/pipeline_step.py | 17 + .../prompt.py} | 0 .../split_grading_instructions_by_file.py | 128 +++++++ ...plit_grading_instructions_by_file_input.py | 29 ++ ...lit_grading_instructions_by_file_output.py | 13 + ...t_problem_non_grading_statement_by_file.py | 20 -- .../prompt.py} | 0 .../split_grading_instructions_by_file.py | 141 -------- .../split_problem_statement_by_file.py | 136 -------- 24 files changed, 851 insertions(+), 1273 deletions(-) create mode 100644 modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py delete mode 100644 modules/programming/module_programming_llm/module_programming_llm/generate_graded_suggestions_by_file.py delete mode 100644 modules/programming/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py delete mode 100644 modules/programming/module_programming_llm/module_programming_llm/generate_summary_by_file.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary_input.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary_output.py rename modules/programming/module_programming_llm/module_programming_llm/prompts/{summarize_submission_by_file.py => generate_file_summary/prompt.py} (100%) delete mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/generate_non_graded_suggestions_by_file.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_input.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_output.py rename modules/programming/module_programming_llm/module_programming_llm/prompts/{generate_graded_suggestions_by_file.py => generate_suggestions_by_file/prompt.py} (100%) create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_zero_shot/generate_suggestions_zero_shot.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/pipeline_step.py rename modules/programming/module_programming_llm/module_programming_llm/prompts/{split_grading_instructions_by_file.py => split_grading_instructions_by_file/prompt.py} (100%) create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file_input.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file_output.py delete mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_non_grading_statement_by_file.py rename modules/programming/module_programming_llm/module_programming_llm/prompts/{split_problem_grading_statement_by_file.py => split_problem_statement_by_file/prompt.py} (100%) delete mode 100644 modules/programming/module_programming_llm/module_programming_llm/split_grading_instructions_by_file.py delete mode 100644 modules/programming/module_programming_llm/module_programming_llm/split_problem_statement_by_file.py diff --git a/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py b/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py new file mode 100644 index 000000000..9d925256c --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py @@ -0,0 +1,110 @@ +from typing import List + +from athena.programming import Submission, Exercise, Feedback +from module_programming_llm.config import Configuration +from module_programming_llm.helpers.models import ModelConfigType +from module_programming_llm.prompts import GenerateFileSummary, SplitProblemStatementByFile, \ + SplitGradingInstructionsByFile, GenerateSuggestionsByFile, GenerateSuggestionsByFileOutput +from module_programming_llm.prompts.generate_file_summary import GenerateFileSummaryOutput, GenerateFileSummaryInput +from module_programming_llm.prompts.generate_suggestions_by_file.generate_suggestions_by_file_input import \ + GenerateSuggestionsByFileInput +from module_programming_llm.prompts.split_grading_instructions_by_file import SplitGradingInstructionsByFileOutput, \ + SplitGradingInstructionsByFileInput +from module_programming_llm.prompts.split_problem_statement_by_file import SplitProblemStatementByFileOutput, \ + SplitProblemStatementByFileInput + + +async def generate_file_summary(step: GenerateFileSummary, + input_data: GenerateFileSummaryInput, debug: bool, + model: ModelConfigType) -> GenerateFileSummaryOutput: + return await step.process(input_data, debug, model) + + +async def split_problem_statement(step: SplitProblemStatementByFile, + input_data: SplitProblemStatementByFileInput, debug: bool, + model: ModelConfigType) -> SplitProblemStatementByFileOutput: + return await step.process(input_data, debug, model) + + +async def split_grading_instructions(step: SplitGradingInstructionsByFile, + input_data: SplitGradingInstructionsByFileInput, debug: bool, + model: ModelConfigType) -> SplitGradingInstructionsByFileOutput: + return await step.process(input_data, debug, model) + + +async def generate_suggestions(step: GenerateSuggestionsByFile, + input_data: GenerateSuggestionsByFileInput, debug: bool, + model: ModelConfigType) -> GenerateSuggestionsByFileOutput: + return await step.process(input_data, debug, model) + + +async def generate_feedback(exercise: Exercise, submission: Submission, is_graded: bool, + module_config: Configuration) -> List[Feedback]: + template_repo = exercise.get_template_repository() + solution_repo = exercise.get_solution_repository() + submission_repo = submission.get_repository() + is_debug = module_config.debug + model = module_config.basic_by_file_approach.model + + generate_file_summary_input = GenerateFileSummaryInput(template_repo, submission_repo, exercise.id, submission.id) + file_summary_output = await generate_file_summary(module_config.basic_by_file_approach.generate_file_summary, + generate_file_summary_input, is_debug, model) + + split_grading_instructions_input = SplitGradingInstructionsByFileInput(template_repo, submission_repo, + solution_repo, exercise.id, submission.id, + exercise.grading_instructions, + exercise.grading_criteria) + split_grading_instructions_output = await split_grading_instructions( + module_config.basic_by_file_approach.split_grading_instructions_by_file, split_grading_instructions_input, + is_debug, model) + + split_problem_statement_input = SplitProblemStatementByFileInput(template_repo, submission_repo, solution_repo, + exercise.problem_statement, exercise.id, + submission.id) + split_problem_statement_output = await split_problem_statement( + module_config.basic_by_file_approach.split_problem_statement_by_file, split_problem_statement_input, is_debug, + model) + + generate_suggestions_input = GenerateSuggestionsByFileInput(template_repo, submission_repo, solution_repo, + split_grading_instructions_output, + split_problem_statement_output, exercise.id, + submission.id, exercise.max_points, + exercise.bonus_points, exercise.programming_language, + exercise.grading_criteria, exercise.problem_statement, + exercise.grading_instructions) + generate_suggestions_output = await generate_suggestions( + module_config.basic_by_file_approach.generate_suggestions_by_file, generate_suggestions_input, is_debug, model) + + grading_instruction_ids = set( + grading_instruction.id + for criterion in exercise.grading_criteria or [] + for grading_instruction in criterion.structured_grading_instructions + ) + + feedbacks: List[Feedback] = [] + for result in generate_suggestions_output.feedbacks: + if result is None: + continue + for feedback in result.feedbacks: + 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, + file_path=feedback.file_name, + line_start=feedback.line_start, + line_end=feedback.line_end, + credits=feedback.credits, + structured_grading_instruction_id=grading_instruction_id, + is_graded=True, + meta={}, + ) + ) + + return feedbacks diff --git a/modules/programming/module_programming_llm/module_programming_llm/config.py b/modules/programming/module_programming_llm/module_programming_llm/config.py index 69f89c1a4..3e8693f9a 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/config.py +++ b/modules/programming/module_programming_llm/module_programming_llm/config.py @@ -2,144 +2,53 @@ from pydantic import BaseModel, Field -from athena import config_schema_provider from module_programming_llm.helpers.models import ModelConfigType, DefaultModelConfig -from module_programming_llm.prompts.generate_graded_suggestions_by_file import ( - system_message as generate_graded_suggestions_by_file_system_message, - human_message as generate_graded_suggestions_by_file_human_message, -) -from module_programming_llm.prompts.generate_non_graded_suggestions_by_file import ( - system_message as generate_non_graded_suggestions_by_file_system_message, - human_message as generate_non_graded_suggestions_by_file_human_message, -) -from module_programming_llm.prompts.split_grading_instructions_by_file import ( - system_message as split_grading_instructions_by_file_message, - human_message as split_grading_instructions_by_file_human_message, -) -from module_programming_llm.prompts.split_problem_non_grading_statement_by_file import ( - system_message as split_problem_statements_by_file_system_message_without_solution, - human_message as split_problem_statements_by_file_human_message_without_solution, -) -from module_programming_llm.prompts.split_problem_grading_statement_by_file import ( - system_message as split_problem_statements_by_file_system_message_with_solution, - human_message as split_problem_statements_by_file_human_message_with_solution, -) -from module_programming_llm.prompts.summarize_submission_by_file import ( - system_message as summarize_submission_by_file_system_message, - human_message as summarize_submission_by_file_human_message, -) - - -class SplitProblemStatementsBasePrompt(BaseModel): - """Base class for splitting problem statements into file-based ones, providing a structured approach for processing statements.""" - - system_message: str = Field(..., - description="Message for priming AI behavior and instructing it what to do.") - human_message: str = Field(..., - description="Message for priming AI behavior and instructing it what to do.") - tokens_before_split: int = Field(default=250, - description="Split the problem statement into file-based ones after this number of tokens.") - - -class SplitProblemStatementsWithSolutionByFilePrompt(SplitProblemStatementsBasePrompt): - """Specialized class for splitting problem statements with solutions, for cases where detailed solution information is available.""" - system_message: str = split_problem_statements_by_file_system_message_with_solution - human_message: str = split_problem_statements_by_file_human_message_with_solution - - -class SplitProblemStatementsWithoutSolutionByFilePrompt( - SplitProblemStatementsBasePrompt -): - """Specialized class for splitting problem statements without solutions, applicable when solution details are not provided.""" - system_message: str = split_problem_statements_by_file_system_message_without_solution - human_message: str = split_problem_statements_by_file_human_message_without_solution - - -class SplitGradingInstructionsByFilePrompt(BaseModel): - """\ -Features available: **{grading_instructions}**, **{changed_files_from_template_to_solution}**, **{changed_files_from_template_to_submission}**\ -""" - system_message: str = Field(default=split_grading_instructions_by_file_message, - description="Message for priming AI behavior and instructing it what to do.") - human_message: str = Field(default=split_grading_instructions_by_file_human_message, - description="Message from a human. The input on which the AI is supposed to act.") - tokens_before_split: int = Field(default=250, description="Split the grading instructions into file-based ones after this number of tokens.") - - -class FeedbackGenerationBasePrompt(BaseModel): - """Base class for feedback generation prompts, contains common definitions.""" - - system_message: str = Field(..., - description="Message for priming AI behavior and instructing it what to do.",) - human_message: str = Field(..., - description="Message from a human. The input on which the AI is supposed to act.",) - - -class GradedFeedbackGenerationPrompt(FeedbackGenerationBasePrompt): - """Generates graded feedback based on file submissions, tailored to provide detailed, evaluative comments and scores.""" - - system_message: str = generate_graded_suggestions_by_file_system_message - human_message: str = generate_graded_suggestions_by_file_human_message - - -class NonGradedFeedbackGenerationPrompt(FeedbackGenerationBasePrompt): - """\ -Features available: **{problem_statement}**, **{submission_file}** - -*Note: Prompt will be applied per file independently. Also, you don't have to include all features, -e.g. template_to_submission_diff. - """ - - system_message: str = generate_non_graded_suggestions_by_file_system_message - human_message: str = generate_non_graded_suggestions_by_file_human_message - - -class FileSummaryPrompt(BaseModel): - """Generates concise summaries of submission files, facilitating a quicker review and understanding of the content for AI processing.""" - - system_message: str = Field(summarize_submission_by_file_system_message, - description="Message for priming AI behavior and instructing it what to do.") - human_message: str = Field(summarize_submission_by_file_human_message, - description="Message from a human. The input on which the AI is supposed to act.") +from athena import config_schema_provider +from module_programming_llm.prompts import SplitProblemStatementByFile, SplitGradingInstructionsByFile, \ + GenerateSuggestionsByFile, GenerateFileSummary class BasicApproachConfig(BaseModel): - """Defines a basic configuration for processing submissions, incorporating problem statement splitting, feedback generation, and file summarization.""" + """Defines a basic configuration for processing submissions, incorporating problem statement splitting, feedback generation.""" max_input_tokens: int = Field(default=3000, description="Maximum number of tokens in the input prompt.") - model: ModelConfigType = Field(default=DefaultModelConfig()) # type: ignore - max_number_of_files: int = Field(default=25, description="Maximum number of files. If exceeded, it will prioritize the most important ones.") - split_problem_statement_by_file_prompt: SplitProblemStatementsBasePrompt = Field(description="To be defined in " "subclasses.") - generate_suggestions_by_file_prompt: SplitProblemStatementsBasePrompt = Field(description="To be defined in " "subclasses.") - generate_file_summary_prompt: FileSummaryPrompt = Field(default=FileSummaryPrompt(), description="Generates short summaries to be fed into the LLM with separate files.") + model: ModelConfigType = Field(default=DefaultModelConfig()) # type: ignore -class GradedBasicApproachConfig(BasicApproachConfig, ABC): - """\ -This approach uses an LLM to split up the problem statement and grading instructions by file, if necessary. \ -Then, it generates graded suggestions for each file independently.\ -""" - - split_problem_statement_by_file_prompt: SplitProblemStatementsWithSolutionByFilePrompt = Field(default=SplitProblemStatementsWithSolutionByFilePrompt()) - split_grading_instructions_by_file_prompt: SplitGradingInstructionsByFilePrompt = (Field(default=SplitGradingInstructionsByFilePrompt())) - generate_suggestions_by_file_prompt: FeedbackGenerationBasePrompt = Field(default=GradedFeedbackGenerationPrompt()) - - -class NonGradedBasicApproachConfig(BasicApproachConfig, ABC): - """\ -This approach uses an LLM to split up the problem statement, if necessary. \ -Then, it generates non graded suggestions for each file independently.\ -""" - - split_problem_statement_by_file_prompt: SplitProblemStatementsWithoutSolutionByFilePrompt = Field(default=SplitProblemStatementsWithoutSolutionByFilePrompt()) - generate_suggestions_by_file_prompt: FeedbackGenerationBasePrompt = Field(default=NonGradedFeedbackGenerationPrompt()) - split_grading_instructions_by_file_prompt: SplitGradingInstructionsByFilePrompt = (Field(default=SplitGradingInstructionsByFilePrompt())) - +class BasicByFileApproachConfig(BasicApproachConfig, ABC): + """ + This approach uses an LLM to split up the problem statement and grading instructions by file, if necessary. + Then, it generates graded suggestions for each file independently. + Generates grading instructions if not available. + Validates and filters out generated feedback. + """ + split_problem_statement_by_file: SplitProblemStatementByFile = Field(default=SplitProblemStatementByFile()) + split_grading_instructions_by_file: SplitGradingInstructionsByFile = ( + Field(default=SplitGradingInstructionsByFile())) + generate_suggestions_by_file: GenerateSuggestionsByFile = Field(default=GenerateSuggestionsByFile()) + generate_file_summary: GenerateFileSummary = Field(default=GenerateFileSummary()) + max_number_of_files: int = Field(default=25, + description="Maximum number of files. If exceeded, it will prioritize the most important ones.") + tokens_before_split: int = Field(default=250, + description="Split the grading instructions into file-based ones after this number of tokens.") + + +# class ZeroShotApproachConfig(BasicApproachConfig, ABC): +# """\ +# This approach uses an LLM to split up the problem statement, if necessary. \ +# Then, it generates non graded suggestions for each file independently.\ +# """ +# +# split_problem_statement_by_file_prompt: SplitProblemStatementsWithoutSolutionByFilePrompt = Field(default=SplitProblemStatementsWithoutSolutionByFilePrompt()) +# generate_suggestions_by_file_prompt: FeedbackGenerationBasePrompt = Field(default=NonGradedFeedbackGenerationPrompt()) +# split_grading_instructions_by_file_prompt: SplitGradingInstructionsByFilePrompt = (Field(default=SplitGradingInstructionsByFilePrompt())) +# +# @config_schema_provider class Configuration(BaseModel): """Configuration settings for the entire module, including debug mode and approach-specific configurations.""" debug: bool = Field(default=False, description="Enable debug mode.") - graded_approach: GradedBasicApproachConfig = Field(default=GradedBasicApproachConfig()) - non_graded_approach: NonGradedBasicApproachConfig = Field(default=NonGradedBasicApproachConfig()) \ No newline at end of file + basic_by_file_approach: BasicByFileApproachConfig = Field(default=BasicByFileApproachConfig()) + # zero_shot_approach: ZeroShotApproachConfig = Field(default=ZeroShotApproachConfig()) diff --git a/modules/programming/module_programming_llm/module_programming_llm/generate_graded_suggestions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/generate_graded_suggestions_by_file.py deleted file mode 100644 index 1fe4dde47..000000000 --- a/modules/programming/module_programming_llm/module_programming_llm/generate_graded_suggestions_by_file.py +++ /dev/null @@ -1,327 +0,0 @@ -from typing import List, Optional, Sequence -import os -import asyncio -from pydantic import BaseModel, Field - -from athena import emit_meta -from athena.programming import Exercise, Submission, Feedback - -from module_programming_llm.config import GradedBasicApproachConfig -from module_programming_llm.split_grading_instructions_by_file import ( - split_grading_instructions_by_file, -) -from module_programming_llm.split_problem_statement_by_file import ( - split_problem_statement_by_file, -) -from module_programming_llm.helpers.llm_utils import ( - check_prompt_length_and_omit_features_if_necessary, - get_chat_prompt_with_formatting_instructions, - num_tokens_from_string, - predict_and_parse, -) -from module_programming_llm.helpers.utils import ( - get_diff, - load_files_from_repo, - add_line_numbers, - get_programming_language_file_extension, -) - - -class FeedbackModel(BaseModel): - title: str = Field( - description="Very short title, i.e. feedback category", 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 Config: - title = "Feedback" - - -class AssessmentModel(BaseModel): - """Collection of feedbacks making up an assessment""" - - feedbacks: Sequence[FeedbackModel] = Field(description="Assessment feedbacks") - - class Config: - title = "Assessment" - - -# pylint: disable=too-many-locals -async def generate_suggestions_by_file( - exercise: Exercise, - submission: Submission, - config: GradedBasicApproachConfig, - debug: bool, -) -> List[Feedback]: - model = config.model.get_model() # type: ignore[attr-defined] - - chat_prompt = get_chat_prompt_with_formatting_instructions( - model=model, - system_message=config.generate_suggestions_by_file_prompt.system_message, - human_message=config.generate_suggestions_by_file_prompt.human_message, - pydantic_object=AssessmentModel, - ) - - # Get split problem statement and grading instructions by file (if necessary) - split_problem_statement, split_grading_instructions = await asyncio.gather( - split_problem_statement_by_file( - exercise=exercise, - submission=submission, - prompt=chat_prompt, - config=config, - debug=debug, - ), - split_grading_instructions_by_file( - exercise=exercise, - submission=submission, - prompt=chat_prompt, - config=config, - debug=debug, - ), - ) - - problem_statement_tokens = num_tokens_from_string(exercise.problem_statement or "") - is_short_problem_statement = ( - problem_statement_tokens - <= config.split_problem_statement_by_file_prompt.tokens_before_split - ) - file_problem_statements = ( - { - item.file_name: item.problem_statement - for item in split_problem_statement.items - } - if split_problem_statement is not None - else {} - ) - - is_short_grading_instructions = ( - num_tokens_from_string(exercise.grading_instructions) - <= config.split_grading_instructions_by_file_prompt.tokens_before_split - if exercise.grading_instructions is not None - else True - ) - file_grading_instructions = ( - { - item.file_name: item.grading_instructions - for item in split_grading_instructions.items - } - if split_grading_instructions is not None - else {} - ) - - prompt_inputs: List[dict] = [] - - # Feature extraction - solution_repo = exercise.get_solution_repository() - template_repo = exercise.get_template_repository() - submission_repo = submission.get_repository() - - changed_files_from_template_to_submission = get_diff( - src_repo=template_repo, dst_repo=submission_repo, file_path=None, name_only=True - ).split("\n") - changed_files_from_template_to_submission = [ - os.path.join(str(submission_repo.working_tree_dir or ""), file_path) - for file_path in changed_files_from_template_to_submission - ] - - # Changed text files - changed_files = load_files_from_repo( - submission_repo, - file_filter=lambda file_path: file_path - in changed_files_from_template_to_submission, - ) - - # Gather prompt inputs for each changed file (independently) - for file_path, file_content in changed_files.items(): - problem_statement = ( - exercise.problem_statement or "" - if is_short_problem_statement - else file_problem_statements.get( - file_path, "No relevant problem statement section found." - ) - ) - problem_statement = ( - problem_statement - if problem_statement.strip() - else "No problem statement found." - ) - - grading_instructions = ( - exercise.grading_instructions or "" - if is_short_grading_instructions - else file_grading_instructions.get( - file_path, "No relevant grading instructions found." - ) - ) - grading_instructions = ( - grading_instructions - if grading_instructions.strip() - else "No grading instructions found." - ) - - file_content = add_line_numbers(file_content) - solution_to_submission_diff = get_diff( - src_repo=solution_repo, - dst_repo=submission_repo, - src_prefix="solution", - dst_prefix="submission", - file_path=file_path, - ) - template_to_submission_diff = get_diff( - src_repo=template_repo, - dst_repo=submission_repo, - src_prefix="template", - dst_prefix="submission", - file_path=file_path, - ) - template_to_solution_diff = get_diff( - src_repo=template_repo, - dst_repo=solution_repo, - src_prefix="template", - dst_prefix="solution", - file_path=file_path, - ) - - prompt_inputs.append( - { - "file_path": file_path, # Not really relevant for the prompt - "priority": len( - template_to_solution_diff - ), # Not really relevant for the prompt - "submission_file": file_content, - "max_points": exercise.max_points, - "bonus_points": exercise.bonus_points, - "solution_to_submission_diff": solution_to_submission_diff, - "template_to_submission_diff": template_to_submission_diff, - "template_to_solution_diff": template_to_solution_diff, - "grading_instructions": grading_instructions, - "problem_statement": problem_statement, - } - ) - - # Filter long prompts (omitting features if necessary) - # Lowest priority features are at the top of the list (i.e. they are omitted first if necessary) - # "submission_file" is not omittable, because it is the main input containing the line numbers - # In the future we might be able to include the line numbers in the diff, but for now we need to keep it - omittable_features = [ - "template_to_solution_diff", # If it is even included in the prompt (has the lowest priority since it is indirectly included in other diffs) - "problem_statement", - "grading_instructions", - "solution_to_submission_diff", - "template_to_submission_diff", # In the future we might indicate the changed lines in the submission_file additionally - ] - - prompt_inputs = [ - omitted_prompt_input - for omitted_prompt_input, should_run in [ - 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, - ) - for prompt_input in prompt_inputs - ] - if should_run - ] - - # If we have many files we need to filter and prioritize them - if len(prompt_inputs) > config.max_number_of_files: - programming_language_extension = get_programming_language_file_extension( - programming_language=exercise.programming_language - ) - - # Prioritize files that have a diff between solution and submission - prompt_inputs = sorted(prompt_inputs, key=lambda x: x["priority"], reverse=True) - - filtered_prompt_inputs = [] - if programming_language_extension is not None: - filtered_prompt_inputs = [ - prompt_input - for prompt_input in prompt_inputs - if prompt_input["file_path"].endswith(programming_language_extension) - ] - - while ( - len(filtered_prompt_inputs) < config.max_number_of_files and prompt_inputs - ): - filtered_prompt_inputs.append(prompt_inputs.pop(0)) - prompt_inputs = filtered_prompt_inputs - - # noinspection PyTypeChecker - results: List[Optional[AssessmentModel]] = await asyncio.gather( - *[ - predict_and_parse( - model=model, - chat_prompt=chat_prompt, - prompt_input=prompt_input, - pydantic_object=AssessmentModel, - tags=[ - f"exercise-{exercise.id}", - f"submission-{submission.id}", - f"file-{prompt_input['file_path']}", - "generate-suggestions-by-file", - ], - ) - for prompt_input in prompt_inputs - ] - ) - - if debug: - emit_meta( - "generate_suggestions", - [ - { - "file_path": prompt_input["file_path"], - "prompt": chat_prompt.format(**prompt_input), - "result": result.dict() if result is not None else None, - } - for prompt_input, result in zip(prompt_inputs, results) - ], - ) - - grading_instruction_ids = set( - grading_instruction.id - for criterion in exercise.grading_criteria or [] - for grading_instruction in criterion.structured_grading_instructions - ) - - feedbacks: List[Feedback] = [] - for prompt_input, result in zip(prompt_inputs, results): - file_path = prompt_input["file_path"] - if result is None: - continue - for feedback in result.feedbacks: - 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, - file_path=file_path, - line_start=feedback.line_start, - line_end=feedback.line_end, - credits=feedback.credits, - structured_grading_instruction_id=grading_instruction_id, - is_graded=True, - meta={}, - ) - ) - - return feedbacks diff --git a/modules/programming/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py deleted file mode 100644 index 2cb1cb291..000000000 --- a/modules/programming/module_programming_llm/module_programming_llm/generate_non_graded_suggestions_by_file.py +++ /dev/null @@ -1,315 +0,0 @@ -from typing import List, Optional, Sequence -import os -import asyncio -from pydantic import BaseModel, Field - -from athena import emit_meta -from athena.programming import Exercise, Submission, Feedback - -from module_programming_llm.config import NonGradedBasicApproachConfig -from module_programming_llm.generate_summary_by_file import generate_summary_by_file -from module_programming_llm.split_grading_instructions_by_file import ( - split_grading_instructions_by_file, -) -from module_programming_llm.split_problem_statement_by_file import ( - split_problem_statement_by_file, -) -from module_programming_llm.helpers.llm_utils import ( - check_prompt_length_and_omit_features_if_necessary, - get_chat_prompt_with_formatting_instructions, - num_tokens_from_string, - predict_and_parse, -) -from module_programming_llm.helpers.utils import ( - get_diff, - load_files_from_repo, - add_line_numbers, - get_programming_language_file_extension, -) - - -class FeedbackModel(BaseModel): - title: str = Field( - description="Very short title, i.e. feedback category", 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: Optional[float] = Field( - description="The number of points you would give for this element if you were a human tutor. Remember that " - "the total number of credits should not exceed the total number of points. Negative points mean " - "that the student should put in more work." - ) - - class Config: - title = "Feedback" - - -class ImprovementModel(BaseModel): - """Collection of feedbacks making up an improvement""" - - feedbacks: Sequence[FeedbackModel] = Field(description="Improvement feedbacks") - - class Config: - title = "Improvement" - - -# pylint: disable=too-many-locals -async def generate_suggestions_by_file( - exercise: Exercise, - submission: Submission, - config: NonGradedBasicApproachConfig, - debug: bool, -) -> List[Feedback]: - model = config.model.get_model() # type: ignore[attr-defined] - - chat_prompt = get_chat_prompt_with_formatting_instructions( - model=model, - system_message=config.generate_suggestions_by_file_prompt.system_message, - human_message=config.generate_suggestions_by_file_prompt.human_message, - pydantic_object=ImprovementModel, - ) - - prompt_inputs: List[dict] = [] - - # Feature extraction - template_repo = exercise.get_template_repository() - submission_repo = submission.get_repository() - - changed_files_from_template_to_submission = get_diff( - src_repo=template_repo, dst_repo=submission_repo, file_path=None, name_only=True - ).split("\n") - changed_files_from_template_to_submission = [ - os.path.join(str(submission_repo.working_tree_dir or ""), file_path) - for file_path in changed_files_from_template_to_submission - ] - - # Changed text files - changed_files = load_files_from_repo( - submission_repo, - file_filter=lambda file_path: file_path - in changed_files_from_template_to_submission, - ) - - # Get solution summary by file (if necessary) - solution_summary = await generate_summary_by_file( - exercise=exercise, - submission=submission, - prompt=chat_prompt, - config=config, - debug=debug, - ) - summary_string = solution_summary.describe_solution_summary() if solution_summary is not None else "" - - problem_statement_tokens = num_tokens_from_string(exercise.problem_statement or "") - - # Get split problem statement and grading instructions by file (if necessary) - split_problem_statement, split_grading_instructions = await asyncio.gather( - split_problem_statement_by_file( - exercise=exercise, - submission=submission, - prompt=chat_prompt, - config=config, - debug=debug, - ), - split_grading_instructions_by_file( - exercise=exercise, - submission=submission, - prompt=chat_prompt, - config=config, - debug=debug, - ), - ) - - is_short_problem_statement = ( - problem_statement_tokens - <= config.split_problem_statement_by_file_prompt.tokens_before_split - ) - file_problem_statements = ( - { - item.file_name: item.problem_statement - for item in split_problem_statement.items - } - if split_problem_statement is not None - else {} - ) - - is_short_grading_instructions = ( - num_tokens_from_string(exercise.grading_instructions) - <= config.split_grading_instructions_by_file_prompt.tokens_before_split - if exercise.grading_instructions is not None - else True - ) - file_grading_instructions = ( - { - item.file_name: item.grading_instructions - for item in split_grading_instructions.items - } - if split_grading_instructions is not None - else {} - ) - - # Gather prompt inputs for each changed file (independently) - for file_path, file_content in changed_files.items(): - problem_statement = ( - exercise.problem_statement or "" - if is_short_problem_statement - else file_problem_statements.get( - file_path, "No relevant problem statement section found." - ) - ) - problem_statement = ( - problem_statement - if problem_statement.strip() - else "No problem statement found." - ) - - file_content = add_line_numbers(file_content) - diff_lines = get_diff( - src_repo=template_repo, - dst_repo=submission_repo, - src_prefix="template", - dst_prefix="submission", - file_path=file_path, - ) - - diff_lines_list = diff_lines.split("\n") - - diff_without_deletions = [] - - for line in diff_lines_list: - if not line.startswith("-"): - diff_without_deletions.append(line) - - template_to_submission_diff = "\n".join(diff_without_deletions) - - grading_instructions = ( - exercise.grading_instructions or "" - if is_short_grading_instructions - else file_grading_instructions.get( - file_path, "No relevant grading instructions found." - ) - ) - grading_instructions = ( - grading_instructions - if grading_instructions.strip() - else "No grading instructions found." - ) - - - prompt_inputs.append( - { - "submission_file": file_content, - "template_to_submission_diff": template_to_submission_diff, - "problem_statement": problem_statement, - "file_path": file_path, - "summary": summary_string, - "max_points": exercise.max_points, - "bonus_points": exercise.bonus_points, - "grading_instructions": grading_instructions, - } - ) - - omittable_features = [ - "template_to_submission_diff", - "summary", - "problem_statement", - # In the future we might indicate the changed lines in the submission_file additionally - ] - - prompt_inputs = [ - omitted_prompt_input - for omitted_prompt_input, should_run in [ - 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, - ) - for prompt_input in prompt_inputs - ] - if should_run - ] - - # If we have many files we need to filter and prioritize them - if len(prompt_inputs) > config.max_number_of_files: - programming_language_extension = get_programming_language_file_extension( - programming_language=exercise.programming_language - ) - - # Prioritize files that have a diff between solution and submission - prompt_inputs = sorted(prompt_inputs, key=lambda x: x["priority"], reverse=True) - - filtered_prompt_inputs = [] - if programming_language_extension is not None: - filtered_prompt_inputs = [ - prompt_input - for prompt_input in prompt_inputs - if prompt_input["file_path"].endswith(programming_language_extension) - ] - - while ( - len(filtered_prompt_inputs) < config.max_number_of_files and prompt_inputs - ): - filtered_prompt_inputs.append(prompt_inputs.pop(0)) - prompt_inputs = filtered_prompt_inputs - - # noinspection PyTypeChecker - results: List[Optional[ImprovementModel]] = await asyncio.gather( - *[ - predict_and_parse( - model=model, - chat_prompt=chat_prompt, - prompt_input=prompt_input, - pydantic_object=ImprovementModel, - tags=[ - f"exercise-{exercise.id}", - f"submission-{submission.id}", - f"file-{prompt_input['file_path']}", - "generate-suggestions-by-file", - ], - ) - for prompt_input in prompt_inputs - ] - ) - - if debug: - emit_meta( - "generate_suggestions", - [ - { - "file_path": prompt_input["file_path"], - "prompt": chat_prompt.format(**prompt_input), - "result": result.dict() if result is not None else None, - } - for prompt_input, result in zip(prompt_inputs, results) - ], - ) - - feedbacks: List[Feedback] = [] - for prompt_input, result in zip(prompt_inputs, results): - file_path = prompt_input["file_path"] - if result is None: - continue - for feedback in result.feedbacks: - feedbacks.append( - Feedback( - exercise_id=exercise.id, - submission_id=submission.id, - title=feedback.title, - description=feedback.description, - file_path=file_path, - line_start=feedback.line_start, - line_end=feedback.line_end, - credits=feedback.credits, - is_graded=False, - meta={}, - ) - ) - - return feedbacks diff --git a/modules/programming/module_programming_llm/module_programming_llm/generate_summary_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/generate_summary_by_file.py deleted file mode 100644 index 5cbc7a439..000000000 --- a/modules/programming/module_programming_llm/module_programming_llm/generate_summary_by_file.py +++ /dev/null @@ -1,157 +0,0 @@ -import asyncio -import os -from typing import Optional, List, Dict - -from pydantic import BaseModel, Field -from langchain.prompts import ChatPromptTemplate - -from athena import emit_meta -from athena.programming import Exercise, Submission - -from module_programming_llm.config import GradedBasicApproachConfig, BasicApproachConfig -from module_programming_llm.helpers.llm_utils import ( - get_chat_prompt_with_formatting_instructions, - num_tokens_from_prompt, - predict_and_parse, -) -from module_programming_llm.helpers.utils import ( - get_diff, - load_files_from_repo, - add_line_numbers -) - - -class FileDescription(BaseModel): - file_name: str = Field(description="The name of the file") - description: str = Field(description="Summary relevant for the file") - - class Config: - title = "FileDescription" - - -class SolutionSummary(BaseModel): - """Collection of summaries, accessible by file path""" - - items: Dict[str, str] = Field(description="A dictionary of file-wise summary objects") - - class Config: - title = "SolutionSummary" - - def describe_solution_summary(self) -> str: - descriptions = [] - for file_path, file_summary in self.items.items(): - description = f"File {file_path}: {file_summary}" - descriptions.append(description) - return "\n".join(descriptions) - - -# pylint: disable=too-many-locals -async def generate_summary_by_file( - exercise: Exercise, - submission: Submission, - prompt: ChatPromptTemplate, - config: BasicApproachConfig, - debug: bool, -) -> Optional[SolutionSummary]: - """Generaty summary for the submission file by file - - Args: - exercise (Exercise): Exercise to split the problem statement for (respecting the changed files) - submission (Submission): Submission to split the problem statement for (respecting the changed files) - prompt (ChatPromptTemplate): Prompt template to check for problem_statement - config (GradedBasicApproachConfig): Configuration - - Returns: - Optional[SolutionSummary]: Summarization of the given submission, None if it is too short or too long - """ - - # Return None if submission_file not in the prompt - if "summary" not in prompt.input_variables: - return None - - model = config.model.get_model() # type: ignore[attr-defined] - - template_repo = exercise.get_template_repository() - submission_repo = submission.get_repository() - - changed_files_from_template_to_submission = get_diff( - src_repo=template_repo, dst_repo=submission_repo, file_path=None, name_only=True - ).split("\n") - changed_files_from_template_to_submission = [ - os.path.join(str(submission_repo.working_tree_dir or ""), file_path) - for file_path in changed_files_from_template_to_submission - ] - - # Changed text files - changed_files = load_files_from_repo( - submission_repo, - file_filter=lambda file_path: file_path in changed_files_from_template_to_submission, - ) - chat_prompt = get_chat_prompt_with_formatting_instructions( - model=model, - system_message=config.generate_file_summary_prompt.system_message, - human_message=config.generate_file_summary_prompt.human_message, - pydantic_object=SolutionSummary, - ) - - prompt_inputs = [] - - # Gather prompt inputs for each file (independently) - for file_path, file_content in changed_files.items(): - file_content = add_line_numbers(file_content) - - prompt_inputs.append( - { - "submission_file": file_content, - "file_path": file_path, - } - ) - - valid_prompt_inputs = [ - prompt_input - for prompt_input in prompt_inputs - if num_tokens_from_prompt(chat_prompt, prompt_input) <= config.max_input_tokens - ] - - # noinspection PyTypeChecker - results: List[Optional[FileDescription]] = await asyncio.gather( - *[ - predict_and_parse( - model=model, - chat_prompt=chat_prompt, - prompt_input=prompt_input, - pydantic_object=FileDescription, - tags=[ - f"exercise-{exercise.id}", - f"submission-{submission.id}", - f"file-{prompt_input['file_path']}", - "generate-summary-by-file", - ], - ) - for prompt_input in valid_prompt_inputs - ] - ) - - if debug: - for prompt_input, result in zip(valid_prompt_inputs, results): - emit_meta( - "file_summary", - { - "prompt": chat_prompt.format(**prompt_input), - "result": result.dict() if result is not None else None, - "file_path": prompt_input[ - "file_path" - ], # Include the file path for reference - }, - ) - - if not any(result is not None for result in results): - return None - - items_dict = {} - - for _, file_summary in enumerate(results): - if file_summary is not None: - items_dict[file_summary.file_name] = file_summary.description - - return SolutionSummary(items=items_dict) diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py new file mode 100644 index 000000000..563b79310 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py @@ -0,0 +1,125 @@ +import asyncio +import os +from typing import Optional, List + +from athena import emit_meta +from .generate_file_summary_input import GenerateFileSummaryInput +from .generate_file_summary_output import GenerateFileSummaryOutput +from module_programming_llm.prompts.pipeline_step import PipelineStep +from .generate_file_summary_output import FileDescription +from .prompt import system_message, human_message +from pydantic import Field +from module_programming_llm.helpers.llm_utils import ( + get_chat_prompt_with_formatting_instructions, + predict_and_parse, num_tokens_from_prompt, +) +from module_programming_llm.helpers.utils import ( + get_diff, + load_files_from_repo, + add_line_numbers +) +from ...helpers.models import ModelConfigType + + +class GenerateFileSummary(PipelineStep[GenerateFileSummaryInput, GenerateFileSummaryOutput]): + """Generates concise summaries of submission files, facilitating a quicker review and understanding of the content for AI processing.""" + + system_message: str = Field(system_message, + description="Message for priming AI behavior and instructing it what to do.") + human_message: str = Field(human_message, + description="Message from a human. The input on which the AI is supposed to act.") + + # pylint: disable=too-many-locals + async def process(self, input_data: GenerateFileSummaryInput, debug: bool, model: ModelConfigType) -> Optional[GenerateFileSummaryOutput]: + """Generate a summary for the submission, file by file. + + Args: + input_data (GenerateFileSummaryInput): Input data containing template and submission repositories. + + Returns: + GenerateFileSummaryOutput: Summarized details of the submission files. + """ + + prompt = get_chat_prompt_with_formatting_instructions( + model=model.get_model(), # type: ignore[attr-defined] + system_message=self.system_message, + human_message=self.human_message, + pydantic_object=FileDescription, + ) + + changed_files_from_template_to_submission = get_diff( + src_repo=input_data.template_repo, dst_repo=input_data.submission_repo, file_path=None, name_only=True + ).split("\n") + + changed_files_from_template_to_submission = [ + os.path.join(str(input_data.submission_repo.working_tree_dir or ""), file_path) + for file_path in changed_files_from_template_to_submission + ] + + # Changed text files + changed_files = load_files_from_repo( + input_data.submission_repo, + file_filter=lambda file_path: file_path in changed_files_from_template_to_submission, + ) + + prompt_inputs = [] + + # Gather prompt inputs for each file (independently) + for file_path, file_content in changed_files.items(): + file_content = add_line_numbers(file_content) + + prompt_inputs.append( + { + "submission_file": file_content, + "file_path": file_path, + } + ) + + valid_prompt_inputs = [ + prompt_input + for prompt_input in prompt_inputs + if num_tokens_from_prompt(prompt, prompt_input) <= self.max_input_tokens + ] + + # noinspection PyTypeChecker + results: List[Optional[FileDescription]] = await asyncio.gather( + *[ + predict_and_parse( + model=model.get_model(), # type: ignore[attr-defined] + chat_prompt=prompt, + prompt_input=prompt_input, + pydantic_object=FileDescription, + tags=[ + f"exercise-{input_data.exercise_id}", + f"submission-{input_data.submission_id}", + f"file-{prompt_input['file_path']}", + "generate-summary-by-file", + ], + ) + for prompt_input in valid_prompt_inputs + ] + ) + + if debug: + for prompt_input, result in zip(valid_prompt_inputs, results): + emit_meta( + "file_summary", + { + "prompt": prompt.format(**prompt_input), + "result": result.dict() if result is not None else None, + "file_path": prompt_input[ + "file_path" + ], # Include the file path for reference + }, + ) + + if not any(result is not None for result in results): + return None + + items_dict = {} + + for _, file_summary in enumerate(results): + if file_summary is not None: + items_dict[file_summary.file_name] = file_summary.description + + return GenerateFileSummaryOutput(items=items_dict) diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary_input.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary_input.py new file mode 100644 index 000000000..ac6c0012b --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary_input.py @@ -0,0 +1,16 @@ +from git import Repo + +class GenerateFileSummaryInput: + """ + DTO class for generating file summaries, containing repository details. + """ + template_repo: Repo + submission_repo: Repo + exercise_id: int + submission_id: int + + def __init__(self, template_repo: Repo, submission_repo: Repo, exercise_id: int, submission_id: int): + self.template_repo = template_repo + self.submission_repo = submission_repo + self.exercise_id = exercise_id + self.submission_id = submission_id \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary_output.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary_output.py new file mode 100644 index 000000000..f3c1d41c9 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary_output.py @@ -0,0 +1,27 @@ +from typing import Dict + +from pydantic import BaseModel, Field + + +class FileDescription(BaseModel): + file_name: str = Field(description="The name of the file") + description: str = Field(description="Summary relevant for the file") + + class Config: + title = "FileDescription" + + +class GenerateFileSummaryOutput(BaseModel): + """Collection of summaries, accessible by file path""" + + items: Dict[str, str] = Field(description="A dictionary of file-wise summary objects") + + class Config: + title = "SolutionSummary" + + def describe_solution_summary(self) -> str: + descriptions = [] + for file_path, file_summary in self.items.items(): + description = f"File {file_path}: {file_summary}" + descriptions.append(description) + return "\n".join(descriptions) \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/summarize_submission_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/prompt.py similarity index 100% rename from modules/programming/module_programming_llm/module_programming_llm/prompts/summarize_submission_by_file.py rename to modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/prompt.py diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_non_graded_suggestions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_non_graded_suggestions_by_file.py deleted file mode 100644 index 69dc656e3..000000000 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_non_graded_suggestions_by_file.py +++ /dev/null @@ -1,50 +0,0 @@ -system_message = """\ -You are an AI tutor for programming assessment at a prestigious university. - -# Problem statement -{problem_statement} - -# Task -Create improvement suggestions for a student\'s programming submission that a human tutor would recommend. \ -Assume the tutor is not familiar with the solution. -The feedback must contain only the feedback the student can learn from. -Important: the answer you generate must not contain any solution suggestions or contain corrected errors. -Rather concentrate on incorrectly applied principles or inconsistencies. -Try to assess the submission in a style a human tutor would do(if the grading instructions are present - follow them). -The credits should be negative if the student should put in more work. -Students can move some functionality to other files. -Students can deviate to some degree from the problem statement or book unless they complete all tasks. -Very important, the feedback must be balanced. - -# Style -1. Constructive, 2. Specific, 3. Balanced, 4. Clear and Concise, 5. Actionable, 6. Educational, 7. Contextual - -It is strictly prohibited to include feedback that contradicts to the problem statement. -No need to mention anything that is not explicitly in the template->submission diff, as it is out of student's control(e.g. exercise package name). - -In git diff, lines marked with '-' were removed and with '+' were added by the student. - -# The student will be reading your response, use you instead of them -""" - -human_message = """\ -Path: {file_path} - -{grading_instructions} -Max points: {max_points}, bonus points: {bonus_points} (whole assessment, not just this file) - -File(with line numbers : ): -\"\"\" -{submission_file} -\"\"\"\ - -Summary of other files in the solution: -\"\"\" -{summary} -\"\"\" - -The template->submission diff(only as reference): -\"\"\" -{template_to_submission_diff} -\"\"\" -""" diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py new file mode 100644 index 000000000..607487067 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py @@ -0,0 +1,258 @@ +import asyncio +import os +from typing import Optional, List + +from athena import emit_meta +from module_programming_llm.prompts.pipeline_step import PipelineStep +from .generate_suggestions_by_file_input import GenerateSuggestionsByFileInput +from .generate_suggestions_by_file_output import GenerateSuggestionsByFileOutput +from .prompt import system_message, human_message +from pydantic import Field +from module_programming_llm.helpers.llm_utils import ( + get_chat_prompt_with_formatting_instructions, + predict_and_parse, num_tokens_from_string, + check_prompt_length_and_omit_features_if_necessary, +) +from module_programming_llm.helpers.utils import ( + get_diff, + load_files_from_repo, + add_line_numbers, get_programming_language_file_extension +) +from ...helpers.models import ModelConfigType + + +class GenerateSuggestionsByFile(PipelineStep[GenerateSuggestionsByFileInput, GenerateSuggestionsByFileOutput]): + """Generates concise feedback for submitted files, facilitating a quicker review and understanding of the content""" + + system_message: str = Field(system_message, + description="Message for priming AI behavior and instructing it what to do.") + human_message: str = Field(human_message, + description="Message from a human. The input on which the AI is supposed to act.") + max_number_of_files: int = Field(default=25, + description="Maximum number of files. If exceeded, it will prioritize the most important ones.") + tokens_before_split: int = Field(default=250, + description="Split the grading instructions into file-based ones after this number of tokens.") + + # pylint: disable=too-many-locals + async def process(self, input_data: GenerateSuggestionsByFileInput, debug: bool, model: ModelConfigType) -> Optional[GenerateSuggestionsByFileOutput]: + model = model.get_model() # type: ignore[attr-defined] + + prompt = get_chat_prompt_with_formatting_instructions( + model=model, + system_message=self.system_message, + human_message=self.human_message, + pydantic_object=GenerateSuggestionsByFileOutput, + ) + + problem_statement_tokens = num_tokens_from_string(input_data.problem_statement or "") + is_short_problem_statement = ( + problem_statement_tokens + <= self.tokens_before_split + ) + file_problem_statements = ( + { + item.file_name: item.problem_statement + for item in input_data.problem_statement_by_file.items + } + if input_data.problem_statement_by_file is not None + else {} + ) + + is_short_grading_instructions = ( + num_tokens_from_string(input_data.grading_instructions) + <= self.tokens_before_split + if input_data.grading_instructions is not None + else True + ) + file_grading_instructions = ( + { + item.file_name: item.grading_instructions + for item in input_data.grading_instructions_by_file.items + } + if input_data.grading_instructions_by_file is not None + else {} + ) + + prompt_inputs: List[dict] = [] + + solution_repo = input_data.solution_repo + template_repo = input_data.template_repo + submission_repo = input_data.submission_repo + + changed_files_from_template_to_submission = get_diff( + src_repo=template_repo, dst_repo=submission_repo, file_path=None, name_only=True + ).split("\n") + changed_files_from_template_to_submission = [ + os.path.join(str(submission_repo.working_tree_dir or ""), file_path) + for file_path in changed_files_from_template_to_submission + ] + + # Changed text files + changed_files = load_files_from_repo( + submission_repo, + file_filter=lambda file_path: file_path + in changed_files_from_template_to_submission, + ) + + # Gather prompt inputs for each changed file (independently) + for file_path, file_content in changed_files.items(): + problem_statement = ( + input_data.problem_statement or "" + if is_short_problem_statement + else file_problem_statements.get( + file_path, "No relevant problem statement section found." + ) + ) + problem_statement = ( + problem_statement + if problem_statement.strip() + else "No problem statement found." + ) + + grading_instructions = ( + input_data.grading_instructions or "" + if is_short_grading_instructions + else file_grading_instructions.get( + file_path, "No relevant grading instructions found." + ) + ) + grading_instructions = ( + grading_instructions + if grading_instructions.strip() + else "No grading instructions found." + ) + + file_content = add_line_numbers(file_content) + solution_to_submission_diff = get_diff( + src_repo=solution_repo, + dst_repo=submission_repo, + src_prefix="solution", + dst_prefix="submission", + file_path=file_path, + ) + template_to_submission_diff = get_diff( + src_repo=template_repo, + dst_repo=submission_repo, + src_prefix="template", + dst_prefix="submission", + file_path=file_path, + ) + template_to_solution_diff = get_diff( + src_repo=template_repo, + dst_repo=solution_repo, + src_prefix="template", + dst_prefix="solution", + file_path=file_path, + ) + + prompt_inputs.append( + { + "file_path": file_path, # Not really relevant for the prompt + "priority": len( + template_to_solution_diff + ), # Not really relevant for the prompt + "submission_file": file_content, + "max_points": input_data.max_points, + "bonus_points": input_data.bonus_points, + "solution_to_submission_diff": solution_to_submission_diff, + "template_to_submission_diff": template_to_submission_diff, + "template_to_solution_diff": template_to_solution_diff, + "grading_instructions": grading_instructions, + "problem_statement": problem_statement, + } + ) + + # Filter long prompts (omitting features if necessary) + # Lowest priority features are at the top of the list (i.e. they are omitted first if necessary) + # "submission_file" is not omittable, because it is the main input containing the line numbers + # In the future we might be able to include the line numbers in the diff, but for now we need to keep it + omittable_features = [ + "template_to_solution_diff", + # If it is even included in the prompt (has the lowest priority since it is indirectly included in other diffs) + "problem_statement", + "grading_instructions", + "solution_to_submission_diff", + "template_to_submission_diff", + # In the future we might indicate the changed lines in the submission_file additionally + ] + + prompt_inputs = [ + omitted_prompt_input + for omitted_prompt_input, should_run in [ + check_prompt_length_and_omit_features_if_necessary( + prompt=prompt, + prompt_input=prompt_input, + max_input_tokens=self.max_input_tokens, + omittable_features=omittable_features, + debug=debug, + ) + for prompt_input in prompt_inputs + ] + if should_run + ] + + # If we have many files we need to filter and prioritize them + if len(prompt_inputs) > self.max_number_of_files: + programming_language_extension = get_programming_language_file_extension( + programming_language=input_data.programming_language + ) + + # Prioritize files that have a diff between solution and submission + prompt_inputs = sorted(prompt_inputs, key=lambda x: x["priority"], reverse=True) + + filtered_prompt_inputs = [] + if programming_language_extension is not None: + filtered_prompt_inputs = [ + prompt_input + for prompt_input in prompt_inputs + if prompt_input["file_path"].endswith(programming_language_extension) + ] + + while ( + len(filtered_prompt_inputs) < self.max_number_of_files and prompt_inputs + ): + filtered_prompt_inputs.append(prompt_inputs.pop(0)) + prompt_inputs = filtered_prompt_inputs + + # noinspection PyTypeChecker + results: List[Optional[GenerateSuggestionsByFileOutput]] = await asyncio.gather( + *[ + predict_and_parse( + model=model, + chat_prompt=prompt, + prompt_input=prompt_input, + pydantic_object=GenerateSuggestionsByFileOutput, + tags=[ + f"exercise-{input_data.exercise_id}", + f"submission-{input_data.submission_id}", + f"file-{prompt_input['file_path']}", + "generate-suggestions-by-file", + ], + ) + for prompt_input in prompt_inputs + ] + ) + + if debug: + emit_meta( + "generate_suggestions", + [ + { + "file_path": prompt_input["file_path"], + "prompt": prompt.format(**prompt_input), + "result": result.dict() if result is not None else None, + } + for prompt_input, result in zip(prompt_inputs, results) + ], + ) + + if not results or all(r is None for r in results): + return None + + final_assessment = GenerateSuggestionsByFileOutput() + final_assessment.feedbacks = [] + for feedback in results: + if feedback is not None: + final_assessment.feedbacks.append(feedback) + + return final_assessment \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_input.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_input.py new file mode 100644 index 000000000..567992fb4 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_input.py @@ -0,0 +1,54 @@ +from typing import Optional, List + +from git import Repo + +from athena import GradingCriterion +from module_programming_llm.prompts.split_grading_instructions_by_file import SplitGradingInstructionsByFileOutput +from module_programming_llm.prompts.split_problem_statement_by_file import SplitProblemStatementByFileOutput + + +class GenerateSuggestionsByFileInput: + """ + DTO class for top level feedback generation job + """ + template_repo: Repo + submission_repo: Repo + solution_repo: Repo + exercise_id: int + submission_id: int + grading_instructions_by_file: SplitGradingInstructionsByFileOutput + grading_criteria: Optional[List[GradingCriterion]] + problem_statement_by_file: SplitProblemStatementByFileOutput + problem_statement: Optional[str] + grading_instructions: Optional[str] + max_points: float + bonus_points: float + programming_language: str + + def __init__(self, + template_repo: Repo, + submission_repo: Repo, + solution_repo: Repo, + grading_instructions_by_file: SplitGradingInstructionsByFileOutput, + problem_statement_by_file: SplitProblemStatementByFileOutput, + exercise_id: int, + submission_id: int, + max_points: float, + bonus_points: float, + programming_language: str, + grading_criteria: Optional[List[GradingCriterion]] = None, + problem_statement: Optional[str] = None, + grading_instructions: Optional[str] = None): + self.template_repo = template_repo + self.submission_repo = submission_repo + self.solution_repo = solution_repo + self.exercise_id = exercise_id + self.submission_id = submission_id + self.grading_instructions_by_file = grading_instructions_by_file + self.grading_criteria = grading_criteria + self.problem_statement_by_file = problem_statement_by_file + self.problem_statement = problem_statement + self.grading_instructions = grading_instructions + self.max_points = max_points + self.bonus_points = bonus_points + self.programming_language = programming_language diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_output.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_output.py new file mode 100644 index 000000000..1c4971fd5 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_output.py @@ -0,0 +1,33 @@ +from typing import Optional, Sequence + +from pydantic import BaseModel, Field + + +class FeedbackModel(BaseModel): + title: str = Field( + description="Very short title, i.e. feedback category", 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" + ) + file_name: str = Field(description="The name of the file") + + class Config: + title = "Feedback" + + +class GenerateSuggestionsByFileOutput(BaseModel): + """Collection of feedbacks making up an assessment for a file""" + + feedbacks: Sequence[FeedbackModel] = Field(description="Assessment feedbacks", default=[]) + + class Config: + title = "FileAssessment" \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_graded_suggestions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/prompt.py similarity index 100% rename from modules/programming/module_programming_llm/module_programming_llm/prompts/generate_graded_suggestions_by_file.py rename to modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/prompt.py diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_zero_shot/generate_suggestions_zero_shot.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_zero_shot/generate_suggestions_zero_shot.py new file mode 100644 index 000000000..94c6d01a1 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_zero_shot/generate_suggestions_zero_shot.py @@ -0,0 +1,5 @@ +from module_programming_llm.prompts.pipeline_step import PipelineStep + + +class GenerateSuggestionsZeroShotStep(PipelineStep[None, None]): + pass \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/pipeline_step.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/pipeline_step.py new file mode 100644 index 000000000..4e8599ef6 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/pipeline_step.py @@ -0,0 +1,17 @@ +from typing import Generic, TypeVar, Optional +from abc import abstractmethod +from pydantic import BaseModel, Field + +from module_programming_llm.helpers.models import ModelConfigType + +# Generic types for input and output +TInput = TypeVar('TInput') +TOutput = TypeVar('TOutput') + + +class PipelineStep(BaseModel, Generic[TInput, TOutput]): + max_input_tokens: int = Field(default=3000, description="Maximum number of tokens in the input prompt.") + + @abstractmethod + async def process(self, input_data: TInput, debug: bool, model: ModelConfigType) -> Optional[TOutput]: + raise NotImplementedError('This is an abstract method') diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/prompt.py similarity index 100% rename from modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file.py rename to modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/prompt.py diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file.py new file mode 100644 index 000000000..27ee9ba8e --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file.py @@ -0,0 +1,128 @@ +from collections import defaultdict + +from module_programming_llm.helpers.utils import format_grading_instructions + +from typing import Optional + +from athena import emit_meta +from module_programming_llm.prompts.pipeline_step import PipelineStep +from . import SplitGradingInstructionsByFileInput, SplitGradingInstructionsByFileOutput +from .prompt import system_message, human_message +from pydantic import Field +from module_programming_llm.helpers.llm_utils import ( + get_chat_prompt_with_formatting_instructions, + num_tokens_from_string, + predict_and_parse, num_tokens_from_prompt, +) +from module_programming_llm.helpers.utils import ( + get_diff, +) +from .split_grading_instructions_by_file_output import FileGradingInstruction +from ...helpers.models import ModelConfigType + + +class SplitGradingInstructionsByFile( + PipelineStep[SplitGradingInstructionsByFileInput, SplitGradingInstructionsByFileOutput]): + """Splits grading instructions of a programming exercise to match with solution files""" + + system_message: str = Field(system_message, + description="Message for priming AI behavior and instructing it what to do.") + human_message: str = Field(human_message, + description="Message from a human. The input on which the AI is supposed to act.") + tokens_before_split: int = Field(default=250, + description="Split the grading instructions into file-based ones after this number of tokens.") + + # pylint: disable=too-many-locals + async def process(self, input_data: SplitGradingInstructionsByFileInput, debug: bool, model: ModelConfigType) -> Optional[ + SplitGradingInstructionsByFileOutput]: + """Split the general grading instructions by file + + Args: + input_data (SplitGradingInstructionsByFileInput): Input data containing template and submission repositories. + + Returns: + Optional[SplitGradingInstructionsByFileOutput]: Split grading instructions, None if it is too short or too long + """ + + grading_instructions = format_grading_instructions(input_data.grading_instructions, input_data.grading_criteria) + + # Return None if the grading instructions are too short + if (grading_instructions is None + or num_tokens_from_string( + grading_instructions) <= self.tokens_before_split): + return None + + changed_files_from_template_to_solution = get_diff( + src_repo=input_data.template_repo, dst_repo=input_data.solution_repo, file_path=None, name_only=True + ).split("\n") + + changed_files_from_template_to_submission = get_diff( + src_repo=input_data.template_repo, dst_repo=input_data.submission_repo, file_path=None, name_only=True + ).split("\n") + + prompt = get_chat_prompt_with_formatting_instructions( + model=model.get_model(), # type: ignore[attr-defined] + system_message=self.system_message, + human_message=self.human_message, + pydantic_object=SplitGradingInstructionsByFileOutput, + ) + + prompt_input = { + "grading_instructions": grading_instructions, + "changed_files_from_template_to_solution": ", ".join( + changed_files_from_template_to_solution + ), + "changed_files_from_template_to_submission": ", ".join( + changed_files_from_template_to_submission + ), + } + + # Return None if the prompt is too long + if num_tokens_from_prompt(prompt, prompt_input) > self.max_input_tokens: + return None + + split_grading_instructions = await predict_and_parse( + model=model.get_model(), # type: ignore[attr-defined] + chat_prompt=prompt, + prompt_input=prompt_input, + pydantic_object=SplitGradingInstructionsByFileOutput, + tags=[ + f"exercise-{input_data.exercise_id}", + f"submission-{input_data.submission_id}", + "split-grading-instructions-by-file", + ], + ) + + if debug: + emit_meta( + "file_grading_instructions", + { + "prompt": prompt.format(**prompt_input), + "result": split_grading_instructions.dict() + if split_grading_instructions is not None + else None, + }, + ) + + if split_grading_instructions is None or not split_grading_instructions.items: + return None + + # Join duplicate file names (some responses contain multiple grading instructions for the same file) + file_grading_instructions_by_file_name = defaultdict(list) + for file_grading_instruction in split_grading_instructions.items: + file_grading_instructions_by_file_name[ + file_grading_instruction.file_name + ].append(file_grading_instruction) + + split_grading_instructions.items = [ + FileGradingInstruction( + file_name=file_name, + grading_instructions="\n".join( + file_grading_instruction.grading_instructions + for file_grading_instruction in file_grading_instructions + ), + ) + for file_name, file_grading_instructions in file_grading_instructions_by_file_name.items() + ] + + return split_grading_instructions diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file_input.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file_input.py new file mode 100644 index 000000000..acc4912c3 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file_input.py @@ -0,0 +1,29 @@ +from typing import Optional, List + +from git import Repo + +from athena import GradingCriterion + + +class SplitGradingInstructionsByFileInput: + """ + A DTO file that contains information about grading instructions and submission + """ + grading_instructions: Optional[str] + grading_criteria: Optional[List[GradingCriterion]] + template_repo: Repo + submission_repo: Repo + solution_repo: Repo + exercise_id: int + submission_id: int + + def __init__(self, template_repo: Repo, submission_repo: Repo, solution_repo: Repo, exercise_id: int = 1, + submission_id: int = 1, grading_instructions: Optional[str] = None, + grading_criteria: Optional[List[GradingCriterion]] = None): + self.grading_instructions = grading_instructions + self.grading_criteria = grading_criteria + self.template_repo = template_repo + self.submission_repo = submission_repo + self.solution_repo = solution_repo + self.exercise_id = exercise_id + self.submission_id = submission_id \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file_output.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file_output.py new file mode 100644 index 000000000..df111c7b2 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file_output.py @@ -0,0 +1,13 @@ +from typing import Sequence + +from pydantic import BaseModel, Field + + +class FileGradingInstruction(BaseModel): + file_name: str = Field(description="File name") + grading_instructions: str = Field(description="Grading instructions relevant for this file") + + +class SplitGradingInstructionsByFileOutput(BaseModel): + """Collection of grading instructions split by file""" + items: Sequence[FileGradingInstruction] = Field(description="File grading instructions") \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_non_grading_statement_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_non_grading_statement_by_file.py deleted file mode 100644 index 5dc3024d7..000000000 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_non_grading_statement_by_file.py +++ /dev/null @@ -1,20 +0,0 @@ -system_message = """\ -You are an AI tutor for programming assessment at a prestigious university. - -# Task -Restructure the problem statement by student changed files to gather work items for each file. \ -Some parts of the problem statement may be relevant for multiple files. -Comments in the template solution can be relevant for some files, some might be not. -Include only those work items based on comments that make sense. -For the file keys, include the full path. -""" - -human_message = """\ -Problem statement: -{problem_statement} - -Changed files from template to student submission (Pick from this list, very important!): -{changed_files_from_template_to_submission} - -Problem statement by file: -""" diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_grading_statement_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/prompt.py similarity index 100% rename from modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_grading_statement_by_file.py rename to modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/prompt.py diff --git a/modules/programming/module_programming_llm/module_programming_llm/split_grading_instructions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/split_grading_instructions_by_file.py deleted file mode 100644 index 0e402b378..000000000 --- a/modules/programming/module_programming_llm/module_programming_llm/split_grading_instructions_by_file.py +++ /dev/null @@ -1,141 +0,0 @@ -from typing import Optional, Sequence -from collections import defaultdict - -from pydantic import BaseModel, Field -from langchain.prompts import ChatPromptTemplate - -from athena import emit_meta -from athena.programming import Exercise, Submission - -from module_programming_llm.config import GradedBasicApproachConfig -from module_programming_llm.helpers.llm_utils import ( - get_chat_prompt_with_formatting_instructions, - num_tokens_from_string, - num_tokens_from_prompt, - predict_and_parse -) -from module_programming_llm.helpers.utils import format_grading_instructions, get_diff - - -class FileGradingInstruction(BaseModel): - file_name: str = Field(description="File name") - grading_instructions: str = Field(description="Grading instructions relevant for this file") - - -class SplitGradingInstructions(BaseModel): - """Collection of grading instructions split by file""" - items: Sequence[FileGradingInstruction] = Field(description="File grading instructions") - - -# pylint: disable=too-many-locals -async def split_grading_instructions_by_file( - exercise: Exercise, - submission: Submission, - prompt: ChatPromptTemplate, - config: GradedBasicApproachConfig, - debug: bool - ) -> Optional[SplitGradingInstructions]: - """Split the general grading instructions by file - - Args: - exercise (Exercise): Exercise to split the grading instructions for (respecting the changed files) - submission (Submission): Submission to split the grading instructions for (respecting the changed files) - prompt (ChatPromptTemplate): Prompt template to check for grading_instructions - config (GradedBasicApproachConfig): Configuration - - Returns: - Optional[SplitGradingInstructions]: Split grading instructions, None if it is too short or too long - """ - - grading_instructions = format_grading_instructions(exercise.grading_instructions, exercise.grading_criteria) - - # Return None if the grading instructions are too short - if (grading_instructions is None - or num_tokens_from_string( - grading_instructions) <= config.split_grading_instructions_by_file_prompt.tokens_before_split): - return None - - # Return None if the grading instructions are not in the prompt - if "grading_instructions" not in prompt.input_variables: - return None - - model = config.model.get_model() # type: ignore[attr-defined] - - template_repo = exercise.get_template_repository() - solution_repo = exercise.get_solution_repository() - submission_repo = submission.get_repository() - - changed_files_from_template_to_solution = get_diff( - src_repo=template_repo, dst_repo=solution_repo, file_path=None, name_only=True - ).split("\n") - - changed_files_from_template_to_submission = get_diff( - src_repo=template_repo, dst_repo=submission_repo, file_path=None, name_only=True - ).split("\n") - - chat_prompt = get_chat_prompt_with_formatting_instructions( - model=model, - system_message=config.split_grading_instructions_by_file_prompt.system_message, - human_message=config.split_grading_instructions_by_file_prompt.human_message, - pydantic_object=SplitGradingInstructions, - ) - - prompt_input = { - "grading_instructions": grading_instructions, - "changed_files_from_template_to_solution": ", ".join( - changed_files_from_template_to_solution - ), - "changed_files_from_template_to_submission": ", ".join( - changed_files_from_template_to_submission - ), - } - - # Return None if the prompt is too long - if num_tokens_from_prompt(chat_prompt, prompt_input) > config.max_input_tokens: - return None - - split_grading_instructions = await predict_and_parse( - model=model, - chat_prompt=chat_prompt, - prompt_input=prompt_input, - pydantic_object=SplitGradingInstructions, - tags=[ - f"exercise-{exercise.id}", - f"submission-{submission.id}", - "split-grading-instructions-by-file", - ], - ) - - if debug: - emit_meta( - "file_grading_instructions", - { - "prompt": chat_prompt.format(**prompt_input), - "result": split_grading_instructions.dict() - if split_grading_instructions is not None - else None, - }, - ) - - if split_grading_instructions is None or not split_grading_instructions.items: - return None - - # Join duplicate file names (some responses contain multiple grading instructions for the same file) - file_grading_instructions_by_file_name = defaultdict(list) - for file_grading_instruction in split_grading_instructions.items: - file_grading_instructions_by_file_name[ - file_grading_instruction.file_name - ].append(file_grading_instruction) - - split_grading_instructions.items = [ - FileGradingInstruction( - file_name=file_name, - grading_instructions="\n".join( - file_grading_instruction.grading_instructions - for file_grading_instruction in file_grading_instructions - ), - ) - for file_name, file_grading_instructions in file_grading_instructions_by_file_name.items() - ] - - return split_grading_instructions diff --git a/modules/programming/module_programming_llm/module_programming_llm/split_problem_statement_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/split_problem_statement_by_file.py deleted file mode 100644 index 46cd64bbb..000000000 --- a/modules/programming/module_programming_llm/module_programming_llm/split_problem_statement_by_file.py +++ /dev/null @@ -1,136 +0,0 @@ -from typing import Optional, Sequence -from collections import defaultdict - -from pydantic import BaseModel, Field -from langchain.prompts import ChatPromptTemplate - -from athena import emit_meta -from athena.programming import Exercise, Submission - -from module_programming_llm.config import GradedBasicApproachConfig, BasicApproachConfig -from module_programming_llm.helpers.llm_utils import ( - get_chat_prompt_with_formatting_instructions, - num_tokens_from_string, - num_tokens_from_prompt, - predict_and_parse -) -from module_programming_llm.helpers.utils import get_diff - - -class FileProblemStatement(BaseModel): - file_name: str = Field(description="File name") - problem_statement: str = Field(description="Problem statement relevant for this file") - - -class SplitProblemStatement(BaseModel): - """Collection of problem statements split by file""" - - items: Sequence[FileProblemStatement] = Field(description="File problem statements") - - -# pylint: disable=too-many-locals -async def split_problem_statement_by_file( - exercise: Exercise, - submission: Submission, - prompt: ChatPromptTemplate, - config: BasicApproachConfig, - debug: bool - ) -> Optional[SplitProblemStatement]: - """Split the general problem statement by file - - Args: - exercise (Exercise): Exercise to split the problem statement for (respecting the changed files) - submission (Submission): Submission to split the problem statement for (respecting the changed files) - prompt (ChatPromptTemplate): Prompt template to check for problem_statement - config (GradedBasicApproachConfig): Configuration - - Returns: - Optional[SplitProblemStatement]: Split problem statement, None if it is too short or too long - """ - - # Return None if the problem statement is too short - if num_tokens_from_string(exercise.problem_statement or "") <= config.split_problem_statement_by_file_prompt.tokens_before_split: - return None - - # Return None if the problem statement not in the prompt - if "problem_statement" not in prompt.input_variables: - return None - - model = config.model.get_model() # type: ignore[attr-defined] - - template_repo = exercise.get_template_repository() - submission_repo = submission.get_repository() - - changed_files_from_template_to_submission = get_diff( - src_repo=template_repo, - dst_repo=submission_repo, - file_path=None, - name_only=True - ).split("\n") - - chat_prompt = get_chat_prompt_with_formatting_instructions( - model=model, - system_message=config.split_problem_statement_by_file_prompt.system_message, - human_message=config.split_problem_statement_by_file_prompt.human_message, - pydantic_object=SplitProblemStatement - ) - - prompt_input = { - "problem_statement": exercise.problem_statement or "No problem statement.", - "changed_files_from_template_to_submission": ", ".join(changed_files_from_template_to_submission) - } - - if "changed_files_from_template_to_solution" in chat_prompt.input_variables: - solution_repo = exercise.get_solution_repository() - changed_files_from_template_to_solution = get_diff( - src_repo=template_repo, - dst_repo=solution_repo, - file_path=None, - name_only=True, - ).split("\n") - prompt_input["changed_files_from_template_to_solution"] = ", ".join( - changed_files_from_template_to_solution - ) - - # Return None if the prompt is too long - if num_tokens_from_prompt(chat_prompt, prompt_input) > config.max_input_tokens: - return None - - split_problem_statement = await predict_and_parse( - model=model, - chat_prompt=chat_prompt, - prompt_input=prompt_input, - pydantic_object=SplitProblemStatement, - tags=[ - f"exercise-{exercise.id}", - f"submission-{submission.id}", - "split-problem-statement-by-file" - ] - ) - - if debug: - emit_meta("file_problem_statements", { - "prompt": chat_prompt.format(**prompt_input), - "result": split_problem_statement.dict() if split_problem_statement is not None else None - }) - - if split_problem_statement is None or not split_problem_statement.items: - return None - - # Join duplicate file names (some responses contain multiple problem statements for the same file) - file_problem_statements_by_file_name = defaultdict(list) - for file_problem_statement in split_problem_statement.items: - file_problem_statements_by_file_name[file_problem_statement.file_name].append(file_problem_statement) - - split_problem_statement.items = [ - FileProblemStatement( - file_name=file_name, - problem_statement="\n".join( - file_problem_statement.problem_statement - for file_problem_statement in file_problem_statements - ) - ) - for file_name, file_problem_statements in file_problem_statements_by_file_name.items() - ] - - return split_problem_statement From cfa218847723335d2efb360a89425ce5e0e99a8c Mon Sep 17 00:00:00 2001 From: Dmytro Polityka Date: Sun, 6 Oct 2024 10:11:24 +0200 Subject: [PATCH 10/21] restructure the module --- .../module_programming_llm/__main__.py | 14 ++------------ .../module_programming_llm/approaches/__init__.py | 1 + .../module_programming_llm/prompts/__init__.py | 8 ++++++++ .../prompts/filter_out_solution/__init__.py | 0 .../prompts/generate_file_summary/__init__.py | 9 +++++++++ .../generate_grading_instructions/__init__.py | 9 +++++++++ .../generate_suggestions_by_file/__init__.py | 4 ++++ .../generate_suggestions_zero_shot/__init__.py | 3 +++ .../split_grading_instructions_by_file/__init__.py | 9 +++++++++ .../split_problem_statement_by_file/__init__.py | 9 +++++++++ .../prompts/validate_suggestions/__init__.py | 0 11 files changed, 54 insertions(+), 12 deletions(-) create mode 100644 modules/programming/module_programming_llm/module_programming_llm/approaches/__init__.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/__init__.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/__init__.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_instructions/__init__.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/__init__.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_zero_shot/__init__.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/__init__.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/__init__.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/__init__.py diff --git a/modules/programming/module_programming_llm/module_programming_llm/__main__.py b/modules/programming/module_programming_llm/module_programming_llm/__main__.py index 2daf56637..c057a8a62 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/__main__.py +++ b/modules/programming/module_programming_llm/module_programming_llm/__main__.py @@ -13,15 +13,9 @@ ) from athena.programming import Exercise, Submission, Feedback from athena.logger import logger +from module_programming_llm.approaches import generate_feedback from module_programming_llm.config import Configuration -from module_programming_llm.generate_graded_suggestions_by_file import ( - generate_suggestions_by_file as generate_graded_suggestions_by_file, -) -from module_programming_llm.generate_non_graded_suggestions_by_file import ( - generate_suggestions_by_file as generate_non_graded_suggestions_by_file, -) - @submissions_consumer def receive_submissions(exercise: Exercise, submissions: List[Submission]): @@ -43,11 +37,7 @@ 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) - if is_graded: - return await generate_graded_suggestions_by_file(exercise, submission, module_config.graded_approach, - module_config.debug) - return await generate_non_graded_suggestions_by_file(exercise, submission, module_config.non_graded_approach, - module_config.debug) + return await generate_feedback(exercise, submission, is_graded, module_config) diff --git a/modules/programming/module_programming_llm/module_programming_llm/approaches/__init__.py b/modules/programming/module_programming_llm/module_programming_llm/approaches/__init__.py new file mode 100644 index 000000000..f33d9d694 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/approaches/__init__.py @@ -0,0 +1 @@ +from .basic_by_file_approach import generate_feedback \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/__init__.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/__init__.py index e69de29bb..5d6af34a4 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/__init__.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/__init__.py @@ -0,0 +1,8 @@ +from .generate_suggestions_by_file import GenerateSuggestionsByFile, GenerateSuggestionsByFileOutput +from .generate_suggestions_zero_shot import GenerateSuggestionsZeroShotStep +from .generate_file_summary import GenerateFileSummary +from .split_problem_statement_by_file import SplitProblemStatementByFile +from .split_grading_instructions_by_file import SplitGradingInstructionsByFile + +__all__ = ['GenerateSuggestionsByFile', 'GenerateSuggestionsZeroShotStep', 'GenerateFileSummary', + 'SplitGradingInstructionsByFile', 'GenerateSuggestionsByFileOutput', 'SplitProblemStatementByFile'] diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/__init__.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/__init__.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/__init__.py new file mode 100644 index 000000000..e9cdfe6a2 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/__init__.py @@ -0,0 +1,9 @@ +from .generate_file_summary import GenerateFileSummary +from .generate_file_summary_input import GenerateFileSummaryInput +from .generate_file_summary_output import GenerateFileSummaryOutput + +__all__ = [ + "GenerateFileSummary", + "GenerateFileSummaryInput", + "GenerateFileSummaryOutput", +] \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_instructions/__init__.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_instructions/__init__.py new file mode 100644 index 000000000..84186df21 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_instructions/__init__.py @@ -0,0 +1,9 @@ +from .generate_grading_instructions import GenerateFileSummaryStep +from .generate_file_summary_input import GenerateFileSummaryInput +from .generate_file_summary_output import GenerateFileSummaryOutput + +__all__ = [ + "GenerateFileSummaryStep", + "GenerateFileSummaryInput", + "GenerateFileSummaryOutput", +] \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/__init__.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/__init__.py new file mode 100644 index 000000000..77a133f5f --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/__init__.py @@ -0,0 +1,4 @@ +from .generate_suggestions_by_file import GenerateSuggestionsByFile +from .generate_suggestions_by_file_output import GenerateSuggestionsByFileOutput + +__all__ = ['GenerateSuggestionsByFile', 'GenerateSuggestionsByFileOutput'] \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_zero_shot/__init__.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_zero_shot/__init__.py new file mode 100644 index 000000000..a8db048a7 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_zero_shot/__init__.py @@ -0,0 +1,3 @@ +from .generate_suggestions_zero_shot import GenerateSuggestionsZeroShotStep + +__all__ = ['GenerateSuggestionsZeroShotStep'] \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/__init__.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/__init__.py new file mode 100644 index 000000000..e6dfe6c97 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/__init__.py @@ -0,0 +1,9 @@ +from .split_grading_instructions_by_file_input import SplitGradingInstructionsByFileInput +from .split_grading_instructions_by_file_output import SplitGradingInstructionsByFileOutput +from .split_grading_instructions_by_file import SplitGradingInstructionsByFile + +__all__ = [ + "SplitGradingInstructionsByFileInput", + "SplitGradingInstructionsByFileOutput", + "SplitGradingInstructionsByFile", +] \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/__init__.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/__init__.py new file mode 100644 index 000000000..70597e17d --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/__init__.py @@ -0,0 +1,9 @@ +from .split_problem_statement_by_file import SplitProblemStatementByFile +from .split_problem_statement_by_file_input import SplitProblemStatementByFileInput +from .split_problem_statement_by_file_output import SplitProblemStatementByFileOutput + +__all__ = [ + "SplitProblemStatementByFile", + "SplitProblemStatementByFileInput", + "SplitProblemStatementByFileOutput", +] \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/__init__.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/__init__.py new file mode 100644 index 000000000..e69de29bb From 6cff9ede7efea09110f85837517db919887c6202 Mon Sep 17 00:00:00 2001 From: Dmytro Polityka Date: Sun, 6 Oct 2024 16:21:27 +0200 Subject: [PATCH 11/21] fix some linting issues --- .../approaches/basic_by_file_approach.py | 51 ++++---- .../generate_file_summary.py | 3 +- .../split_problem_statement_by_file.py | 120 ++++++++++++++++++ .../split_problem_statement_by_file_input.py | 26 ++++ .../split_problem_statement_by_file_output.py | 14 ++ 5 files changed, 187 insertions(+), 27 deletions(-) create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file_input.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file_output.py diff --git a/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py b/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py index 9d925256c..fc0e772c8 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py +++ b/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py @@ -1,4 +1,4 @@ -from typing import List +from typing import Optional, List from athena.programming import Submission, Exercise, Feedback from module_programming_llm.config import Configuration @@ -16,30 +16,30 @@ async def generate_file_summary(step: GenerateFileSummary, input_data: GenerateFileSummaryInput, debug: bool, - model: ModelConfigType) -> GenerateFileSummaryOutput: + model: ModelConfigType) -> Optional[GenerateFileSummaryOutput]: # type: ignore[attr-defined] return await step.process(input_data, debug, model) async def split_problem_statement(step: SplitProblemStatementByFile, input_data: SplitProblemStatementByFileInput, debug: bool, - model: ModelConfigType) -> SplitProblemStatementByFileOutput: + model: ModelConfigType) -> Optional[SplitProblemStatementByFileOutput]: # type: ignore[attr-defined] return await step.process(input_data, debug, model) async def split_grading_instructions(step: SplitGradingInstructionsByFile, input_data: SplitGradingInstructionsByFileInput, debug: bool, - model: ModelConfigType) -> SplitGradingInstructionsByFileOutput: + model: ModelConfigType) -> Optional[SplitGradingInstructionsByFileOutput]: # type: ignore[attr-defined] return await step.process(input_data, debug, model) async def generate_suggestions(step: GenerateSuggestionsByFile, input_data: GenerateSuggestionsByFileInput, debug: bool, - model: ModelConfigType) -> GenerateSuggestionsByFileOutput: + model: ModelConfigType) -> Optional[GenerateSuggestionsByFileOutput]: # type: ignore[attr-defined] return await step.process(input_data, debug, model) async def generate_feedback(exercise: Exercise, submission: Submission, is_graded: bool, - module_config: Configuration) -> List[Feedback]: + module_config: Configuration) -> List[Feedback]: # type: ignore[attr-defined] template_repo = exercise.get_template_repository() solution_repo = exercise.get_solution_repository() submission_repo = submission.get_repository() @@ -85,26 +85,25 @@ async def generate_feedback(exercise: Exercise, submission: Submission, is_grade for result in generate_suggestions_output.feedbacks: if result is None: continue - for feedback in result.feedbacks: - 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, - file_path=feedback.file_name, - line_start=feedback.line_start, - line_end=feedback.line_end, - credits=feedback.credits, - structured_grading_instruction_id=grading_instruction_id, - is_graded=True, - meta={}, - ) + grading_instruction_id = ( + result.grading_instruction_id + if result.grading_instruction_id in grading_instruction_ids + else None + ) + feedbacks.append( + Feedback( + exercise_id=exercise.id, + submission_id=submission.id, + title=result.title, + description=result.description, + file_path=result.file_name, + line_start=result.line_start, + line_end=result.line_end, + credits=result.credits, + structured_grading_instruction_id=grading_instruction_id, + is_graded=is_graded, + meta={}, ) + ) return feedbacks diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py index 563b79310..a855b9a2b 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py @@ -30,7 +30,8 @@ class GenerateFileSummary(PipelineStep[GenerateFileSummaryInput, GenerateFileSum description="Message from a human. The input on which the AI is supposed to act.") # pylint: disable=too-many-locals - async def process(self, input_data: GenerateFileSummaryInput, debug: bool, model: ModelConfigType) -> Optional[GenerateFileSummaryOutput]: + async def process(self, input_data: GenerateFileSummaryInput, debug: bool, model: ModelConfigType) -> Optional[ + GenerateFileSummaryOutput]: """Generate a summary for the submission, file by file. Args: diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py new file mode 100644 index 000000000..fbd902623 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py @@ -0,0 +1,120 @@ +from collections import defaultdict +from typing import Optional + +from pydantic import Field + +from athena import emit_meta +from .prompt import system_message, human_message + +from .split_problem_statement_by_file_input import SplitProblemStatementByFileInput +from .split_problem_statement_by_file_output import FileProblemStatement, SplitProblemStatementByFileOutput +from ..pipeline_step import PipelineStep +from ...helpers.llm_utils import num_tokens_from_string, get_chat_prompt_with_formatting_instructions, \ + num_tokens_from_prompt, predict_and_parse +from ...helpers.models import ModelConfigType +from ...helpers.utils import get_diff + + +class SplitProblemStatementByFile(PipelineStep[SplitProblemStatementByFileInput, SplitProblemStatementByFileOutput]): + """Splits problem statement of a programming exercise to match with solution files""" + + system_message: str = Field(system_message, + description="Message for priming AI behavior and instructing it what to do.") + human_message: str = Field(human_message, + description="Message from a human. The input on which the AI is supposed to act.") + tokens_before_split: int = Field(default=250, + description="Split the grading instructions into file-based ones after this number of tokens.") + + # pylint: disable=too-many-locals + async def process(self, input_data: SplitProblemStatementByFileInput, debug: bool, model: ModelConfigType) -> \ + Optional[ + SplitProblemStatementByFileOutput]: + """Split the general problem statement by file + + Args: + input_data (SplitGradingInstructionsByFileInput): Input data containing template and submission repositories, programming exercise. + + Returns: + Optional[SplitGradingInstructionsByFileOutput]: Split problem statement by file + """ + + # Return None if the problem statement is too short + if num_tokens_from_string(input_data.problem_statement or "") <= self.tokens_before_split: + return None + + template_repo = input_data.template_repo + submission_repo = input_data.submission_repo + + changed_files_from_template_to_submission = get_diff( + src_repo=template_repo, + dst_repo=submission_repo, + file_path=None, + name_only=True + ).split("\n") + + prompt = get_chat_prompt_with_formatting_instructions( + model=model.get_model(), # type: ignore[attr-defined] + system_message=self.system_message, + human_message=self.human_message, + pydantic_object=SplitProblemStatementByFileOutput + ) + + prompt_input = { + "problem_statement": input_data.problem_statement or "No problem statement.", + "changed_files_from_template_to_submission": ", ".join(changed_files_from_template_to_submission) + } + + if "changed_files_from_template_to_solution" in prompt.input_variables: + solution_repo = input_data.solution_repo + changed_files_from_template_to_solution = get_diff( + src_repo=template_repo, + dst_repo=solution_repo, + file_path=None, + name_only=True, + ).split("\n") + prompt_input["changed_files_from_template_to_solution"] = ", ".join( + changed_files_from_template_to_solution + ) + + # Return None if the prompt is too long + if num_tokens_from_prompt(prompt, prompt_input) > self.max_input_tokens: + return None + + split_problem_statement = await predict_and_parse( + model=model.get_model(), # type: ignore[attr-defined] + chat_prompt=prompt, + prompt_input=prompt_input, + pydantic_object=SplitProblemStatementByFileOutput, + tags=[ + f"exercise-{input_data.exercise_id}", + f"submission-{input_data.submission_id}", + "split-problem-statement-by-file" + ] + ) + + if debug: + emit_meta("file_problem_statements", { + "prompt": prompt.format(**prompt_input), + "result": split_problem_statement.dict() if split_problem_statement is not None else None + }) + + if split_problem_statement is None or not split_problem_statement.items: + return None + + # Join duplicate file names (some responses contain multiple problem statements for the same file) + file_problem_statements_by_file_name = defaultdict(list) + for file_problem_statement in split_problem_statement.items: + file_problem_statements_by_file_name[file_problem_statement.file_name].append(file_problem_statement) + + split_problem_statement.items = [ + FileProblemStatement( + file_name=file_name, + problem_statement="\n".join( + file_problem_statement.problem_statement + for file_problem_statement in file_problem_statements + ) + ) + for file_name, file_problem_statements in file_problem_statements_by_file_name.items() + ] + + return split_problem_statement diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file_input.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file_input.py new file mode 100644 index 000000000..169bf377b --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file_input.py @@ -0,0 +1,26 @@ +from typing import Optional + +from git import Repo +from pydantic import Field + + +class SplitProblemStatementByFileInput: + """ + A DTO file that contains information about a programming exercise + """ + problem_statement: Optional[str] + template_repo: Repo + submission_repo: Repo + solution_repo: Repo + exercise_id: int + submission_id: int + + + def __init__(self, template_repo: Repo, submission_repo: Repo, solution_repo: Repo, + problem_statement: Optional[str] = None, exercise_id: int = 1, submission_id: int = 1): + self.problem_statement = problem_statement + self.template_repo = template_repo + self.submission_repo = submission_repo + self.solution_repo = solution_repo + self.exercise_id = exercise_id + self.submission_id = submission_id diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file_output.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file_output.py new file mode 100644 index 000000000..929177bf2 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file_output.py @@ -0,0 +1,14 @@ +from typing import Sequence + +from pydantic import BaseModel, Field + + +class FileProblemStatement(BaseModel): + file_name: str = Field(description="File name") + problem_statement: str = Field(description="Problem statement relevant for this file") + + +class SplitProblemStatementByFileOutput(BaseModel): + """Collection of problem statements split by file""" + + items: Sequence[FileProblemStatement] = Field(description="File problem statements") \ No newline at end of file From 08cc70847da869d00b4025e1ca539c2560a7e2b7 Mon Sep 17 00:00:00 2001 From: Dmytro Polityka Date: Mon, 7 Oct 2024 03:06:00 +0200 Subject: [PATCH 12/21] filter out solutions --- .../approaches/basic_by_file_approach.py | 79 +++++--- .../module_programming_llm/config.py | 2 + .../prompts/filter_out_solution/__init__.py | 9 + .../filter_out_solution.py | 177 ++++++++++++++++++ .../filter_out_solution_input.py | 30 +++ .../filter_out_solution_output.py | 33 ++++ .../prompts/filter_out_solution/prompt.py | 20 ++ .../generate_file_summary.py | 2 +- .../generate_file_summary_output.py | 2 +- .../generate_grading_instructions/__init__.py | 9 - .../generate_suggestions_by_file.py | 21 +-- .../generate_suggestions_by_file_input.py | 4 +- .../generate_suggestions_by_file_output.py | 8 +- .../generate_suggestions_by_file/prompt.py | 1 + ...lit_grading_instructions_by_file_output.py | 2 +- .../split_problem_statement_by_file.py | 4 +- .../split_problem_statement_by_file_output.py | 2 +- 17 files changed, 339 insertions(+), 66 deletions(-) create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_input.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_output.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/prompt.py diff --git a/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py b/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py index fc0e772c8..c0b839330 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py +++ b/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py @@ -5,6 +5,9 @@ from module_programming_llm.helpers.models import ModelConfigType from module_programming_llm.prompts import GenerateFileSummary, SplitProblemStatementByFile, \ SplitGradingInstructionsByFile, GenerateSuggestionsByFile, GenerateSuggestionsByFileOutput +from module_programming_llm.prompts.filter_out_solution.filter_out_solution import FilterOutSolution +from module_programming_llm.prompts.filter_out_solution.filter_out_solution_input import FilterOutSolutionInput +from module_programming_llm.prompts.filter_out_solution.filter_out_solution_output import FilterOutSolutionOutput from module_programming_llm.prompts.generate_file_summary import GenerateFileSummaryOutput, GenerateFileSummaryInput from module_programming_llm.prompts.generate_suggestions_by_file.generate_suggestions_by_file_input import \ GenerateSuggestionsByFileInput @@ -16,30 +19,41 @@ async def generate_file_summary(step: GenerateFileSummary, input_data: GenerateFileSummaryInput, debug: bool, - model: ModelConfigType) -> Optional[GenerateFileSummaryOutput]: # type: ignore[attr-defined] + model: ModelConfigType) -> Optional[ + GenerateFileSummaryOutput]: # type: ignore[attr-defined] return await step.process(input_data, debug, model) async def split_problem_statement(step: SplitProblemStatementByFile, input_data: SplitProblemStatementByFileInput, debug: bool, - model: ModelConfigType) -> Optional[SplitProblemStatementByFileOutput]: # type: ignore[attr-defined] + model: ModelConfigType) -> Optional[ + SplitProblemStatementByFileOutput]: # type: ignore[attr-defined] return await step.process(input_data, debug, model) async def split_grading_instructions(step: SplitGradingInstructionsByFile, input_data: SplitGradingInstructionsByFileInput, debug: bool, - model: ModelConfigType) -> Optional[SplitGradingInstructionsByFileOutput]: # type: ignore[attr-defined] + model: ModelConfigType) -> Optional[ + SplitGradingInstructionsByFileOutput]: # type: ignore[attr-defined] return await step.process(input_data, debug, model) async def generate_suggestions(step: GenerateSuggestionsByFile, input_data: GenerateSuggestionsByFileInput, debug: bool, - model: ModelConfigType) -> Optional[GenerateSuggestionsByFileOutput]: # type: ignore[attr-defined] + model: ModelConfigType) -> List[ + Optional[GenerateSuggestionsByFileOutput]]: # type: ignore[attr-defined] + return await step.process(input_data, debug, model) + + +async def filter_out_solutions(step: FilterOutSolution, + input_data: FilterOutSolutionInput, debug: bool, + model: ModelConfigType) -> List[ + Optional[FilterOutSolutionOutput]]: # type: ignore[attr-defined] return await step.process(input_data, debug, model) async def generate_feedback(exercise: Exercise, submission: Submission, is_graded: bool, - module_config: Configuration) -> List[Feedback]: # type: ignore[attr-defined] + module_config: Configuration) -> List[Feedback]: # type: ignore[attr-defined] template_repo = exercise.get_template_repository() solution_repo = exercise.get_solution_repository() submission_repo = submission.get_repository() @@ -66,15 +80,23 @@ async def generate_feedback(exercise: Exercise, submission: Submission, is_grade model) generate_suggestions_input = GenerateSuggestionsByFileInput(template_repo, submission_repo, solution_repo, - split_grading_instructions_output, - split_problem_statement_output, exercise.id, + exercise.id, submission.id, exercise.max_points, exercise.bonus_points, exercise.programming_language, + split_grading_instructions_output, + split_problem_statement_output, exercise.grading_criteria, exercise.problem_statement, exercise.grading_instructions) - generate_suggestions_output = await generate_suggestions( + output = await generate_suggestions( module_config.basic_by_file_approach.generate_suggestions_by_file, generate_suggestions_input, is_debug, model) + if not is_graded: + filter_out_solution_input = FilterOutSolutionInput(solution_repo, template_repo, exercise.problem_statement, + exercise.id, submission.id, output, + split_problem_statement_output) + output = await filter_out_solutions(module_config.basic_by_file_approach.filter_out_solution, + filter_out_solution_input, is_debug, model) + grading_instruction_ids = set( grading_instruction.id for criterion in exercise.grading_criteria or [] @@ -82,28 +104,29 @@ async def generate_feedback(exercise: Exercise, submission: Submission, is_grade ) feedbacks: List[Feedback] = [] - for result in generate_suggestions_output.feedbacks: + for result in output: if result is None: continue - grading_instruction_id = ( - result.grading_instruction_id - if result.grading_instruction_id in grading_instruction_ids - else None - ) - feedbacks.append( - Feedback( - exercise_id=exercise.id, - submission_id=submission.id, - title=result.title, - description=result.description, - file_path=result.file_name, - line_start=result.line_start, - line_end=result.line_end, - credits=result.credits, - structured_grading_instruction_id=grading_instruction_id, - is_graded=is_graded, - meta={}, + for feedback in result.feedbacks: + 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, + file_path=result.file_path, + line_start=feedback.line_start, + line_end=feedback.line_end, + credits=feedback.credits, + structured_grading_instruction_id=grading_instruction_id, + is_graded=is_graded, + meta={}, + ) ) - ) return feedbacks diff --git a/modules/programming/module_programming_llm/module_programming_llm/config.py b/modules/programming/module_programming_llm/module_programming_llm/config.py index 3e8693f9a..2d3da4582 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/config.py +++ b/modules/programming/module_programming_llm/module_programming_llm/config.py @@ -6,6 +6,7 @@ from athena import config_schema_provider from module_programming_llm.prompts import SplitProblemStatementByFile, SplitGradingInstructionsByFile, \ GenerateSuggestionsByFile, GenerateFileSummary +from module_programming_llm.prompts.filter_out_solution.filter_out_solution import FilterOutSolution class BasicApproachConfig(BaseModel): @@ -28,6 +29,7 @@ class BasicByFileApproachConfig(BasicApproachConfig, ABC): Field(default=SplitGradingInstructionsByFile())) generate_suggestions_by_file: GenerateSuggestionsByFile = Field(default=GenerateSuggestionsByFile()) generate_file_summary: GenerateFileSummary = Field(default=GenerateFileSummary()) + filter_out_solution: FilterOutSolution = Field(default=FilterOutSolution()) max_number_of_files: int = Field(default=25, description="Maximum number of files. If exceeded, it will prioritize the most important ones.") tokens_before_split: int = Field(default=250, diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/__init__.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/__init__.py index e69de29bb..487f053ab 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/__init__.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/__init__.py @@ -0,0 +1,9 @@ +from .filter_out_solution_input import FilterOutSolutionInput +from .filter_out_solution_output import FilterOutSolutionOutput +from .filter_out_solution import FilterOutSolution + +__all__ = [ + "FilterOutSolution", + "FilterOutSolutionOutput", + "FilterOutSolutionInput", +] \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution.py new file mode 100644 index 000000000..1a15ca0ab --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution.py @@ -0,0 +1,177 @@ +import asyncio +import json +import os +from collections import defaultdict +from typing import Optional, List, Sequence, Dict + +from athena import emit_meta +from module_programming_llm.prompts.pipeline_step import PipelineStep +from .filter_out_solution_input import FilterOutSolutionInput +from .filter_out_solution_output import FilterOutSolutionOutput, FeedbackModel as FilterOutFeedbackModel +from module_programming_llm.prompts.generate_suggestions_by_file.generate_suggestions_by_file_output import FeedbackModel as SuggestionsFeedbackModel +from .prompt import system_message, human_message +from pydantic import Field +from module_programming_llm.helpers.llm_utils import ( + get_chat_prompt_with_formatting_instructions, + predict_and_parse, num_tokens_from_string, + check_prompt_length_and_omit_features_if_necessary, +) +from module_programming_llm.helpers.utils import ( + get_diff, + load_files_from_repo, + add_line_numbers +) +from ...helpers.models import ModelConfigType + + +class FilterOutSolution(PipelineStep[FilterOutSolutionInput, List[Optional[FilterOutSolutionOutput]]]): + """Generates concise summaries of submission files, facilitating a quicker review and understanding of the content for AI processing.""" + + system_message: str = Field(system_message, + description="Message for priming AI behavior and instructing it what to do.") + human_message: str = Field(human_message, + description="Message from a human. The input on which the AI is supposed to act.") + tokens_before_split: int = Field(default=250, + description="Split the grading instructions into file-based ones after this number of tokens.") + + # pylint: disable=too-many-locals + async def process( + self, + input_data: FilterOutSolutionInput, + debug: bool, + model: ModelConfigType + ) -> List[Optional[FilterOutSolutionOutput]]: + model = model.get_model() # type: ignore[attr-defined] + + # Prepare the prompt template + prompt = get_chat_prompt_with_formatting_instructions( + model=model, + system_message=self.system_message, + human_message=self.human_message, + pydantic_object=FilterOutSolutionOutput, + ) + + problem_statement_tokens = num_tokens_from_string(input_data.problem_statement or "") + is_short_problem_statement = problem_statement_tokens <= self.tokens_before_split + file_problem_statements = ( + { + item.file_path: item.problem_statement + for item in input_data.problem_statement_by_file.items + } + if input_data.problem_statement_by_file is not None + else {} + ) + + prompt_inputs: List[dict] = [] + + solution_repo = input_data.solution_repo + template_repo = input_data.template_repo + + changed_files_from_template_to_solution = get_diff( + src_repo=template_repo, dst_repo=solution_repo, file_path=None, name_only=True + ).split("\n") + changed_files_from_template_to_solution = [ + os.path.join(str(solution_repo.working_tree_dir or ""), file_path) + for file_path in changed_files_from_template_to_solution + ] + + # Changed text files + changed_files = load_files_from_repo( + solution_repo, + file_filter=lambda file_path: file_path + in changed_files_from_template_to_solution, + ) + + feedback_suggestions_by_file: Dict[str, Sequence[SuggestionsFeedbackModel]] = {} + for feedback in input_data.feedback_suggestions: + feedback_suggestions_by_file[feedback.file_path] = feedback.feedbacks + + # Gather prompt inputs for each file + for file_path, file_content in changed_files.items(): + problem_statement = ( + input_data.problem_statement or "" + if is_short_problem_statement + else file_problem_statements.get( + file_path, "No relevant problem statement section found." + ) + ) + problem_statement = ( + problem_statement + if problem_statement.strip() + else "No problem statement found." + ) + + template_to_solution_diff = get_diff( + src_repo=template_repo, + dst_repo=solution_repo, + src_prefix="template", + dst_prefix="solution", + file_path=file_path, + ) + + file_content = add_line_numbers(file_content) + + prompt_inputs.append( + { + "file_path": file_path, + "code_with_line_numbers": file_content, + "problem_statement": problem_statement, + "template_to_solution_diff": template_to_solution_diff, + "feedback_suggestions": json.dumps([ob.__dict__ for ob in feedback_suggestions_by_file.get(file_path) or []]) + } + ) + + # Filter long prompts if necessary + omittable_features = [ + "problem_statement", + ] + + prompt_inputs = [ + omitted_prompt_input + for omitted_prompt_input, should_run in [ + check_prompt_length_and_omit_features_if_necessary( + prompt=prompt, + prompt_input=prompt_input, + max_input_tokens=self.max_input_tokens, + omittable_features=omittable_features, + debug=debug, + ) + for prompt_input in prompt_inputs + ] + if should_run + ] + + # Send prompts to the LLM + # noinspection PyTypeChecker + results: List[Optional[FilterOutSolutionOutput]] = await asyncio.gather( + *[ + predict_and_parse( + model=model, + chat_prompt=prompt, + prompt_input=prompt_input, + pydantic_object=FilterOutSolutionOutput, + tags=[ + f"exercise-{input_data.exercise_id}", + f"submission-{input_data.submission_id}", + f"file-{prompt_input['file_path']}", + "filter-out-solution", + ], + ) + for prompt_input in prompt_inputs + ] + ) + + if debug: + emit_meta( + "filter_out_solutions", + [ + { + "file_path": prompt_input["file_path"], + "prompt": prompt.format(**prompt_input), + "result": result.dict() if result is not None else None, + } + for prompt_input, result in zip(prompt_inputs, results) + ], + ) + + return results \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_input.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_input.py new file mode 100644 index 000000000..c60164900 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_input.py @@ -0,0 +1,30 @@ +from typing import Optional, List + +from git import Repo + +from module_programming_llm.prompts import GenerateSuggestionsByFileOutput +from module_programming_llm.prompts.split_problem_statement_by_file import SplitProblemStatementByFileOutput + + +class FilterOutSolutionInput: + """ + DTO class for filtering out + """ + solution_repo: Repo + template_repo: Repo + problem_statement_by_file: SplitProblemStatementByFileOutput + problem_statement: Optional[str] + exercise_id: int + submission_id: int + feedback_suggestions: List[Optional[GenerateSuggestionsByFileOutput]] + + def __init__(self, solution_repo: Repo, template_repo: Repo, problem_statement: Optional[str], exercise_id: int, + submission_id: int, feedback_suggestions: List[Optional[GenerateSuggestionsByFileOutput]] = None, + problem_statement_by_file: Optional[SplitProblemStatementByFileOutput] = None): + self.solution_repo = solution_repo + self.template_repo = template_repo + self.exercise_id = exercise_id + self.submission_id = submission_id + self.problem_statement_by_file = problem_statement_by_file + self.problem_statement = problem_statement + self.feedback_suggestions = feedback_suggestions diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_output.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_output.py new file mode 100644 index 000000000..1353b1ce7 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_output.py @@ -0,0 +1,33 @@ +from typing import Dict, Optional, Sequence + +from pydantic import BaseModel, Field + + +class FeedbackModel(BaseModel): + title: str = Field( + description="Very short title, i.e. feedback category", 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 Config: + title = "Feedback" + + +class FilterOutSolutionOutput(BaseModel): + """Collection of feedbacks making up an assessment for a file""" + + feedbacks: Sequence[FeedbackModel] = Field(description="Assessment feedbacks", default=[]) + file_path: str = Field(description="The full path of the file, as specified in the input prompt") + + class Config: + title = "Assessment" \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/prompt.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/prompt.py new file mode 100644 index 000000000..b9a1a855c --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/prompt.py @@ -0,0 +1,20 @@ +system_message = """\ +You are a tutor at a very prestigious university. +# Task +You are given generated feedback suggestions for a programming exercise. +It is absolutely forbidden to reveal the solution to students. +Filter out feedback suggestions that contain solutions or solution hints. Stick to the same format. +In case a suggestion contains solution, try to rewrite it to nudge the student's understanding while hiding the solution. +Problem Statement: +{problem_statement} +Git diff between official template and solution: +{template_to_solution_diff} +""" + +human_message = """\ +Path: {file_path} +Feedback Suggestions: +\"\"\" +{feedback_suggestions} +\"\"\" +""" diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py index a855b9a2b..3d765673b 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py @@ -121,6 +121,6 @@ async def process(self, input_data: GenerateFileSummaryInput, debug: bool, model for _, file_summary in enumerate(results): if file_summary is not None: - items_dict[file_summary.file_name] = file_summary.description + items_dict[file_summary.file_path] = file_summary.description return GenerateFileSummaryOutput(items=items_dict) diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary_output.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary_output.py index f3c1d41c9..840e72dac 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary_output.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary_output.py @@ -4,7 +4,7 @@ class FileDescription(BaseModel): - file_name: str = Field(description="The name of the file") + file_path: str = Field(description="The path of the file, as specified in the input prompt") description: str = Field(description="Summary relevant for the file") class Config: diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_instructions/__init__.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_instructions/__init__.py index 84186df21..e69de29bb 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_instructions/__init__.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_instructions/__init__.py @@ -1,9 +0,0 @@ -from .generate_grading_instructions import GenerateFileSummaryStep -from .generate_file_summary_input import GenerateFileSummaryInput -from .generate_file_summary_output import GenerateFileSummaryOutput - -__all__ = [ - "GenerateFileSummaryStep", - "GenerateFileSummaryInput", - "GenerateFileSummaryOutput", -] \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py index 607487067..e52b3aebb 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py @@ -5,7 +5,7 @@ from athena import emit_meta from module_programming_llm.prompts.pipeline_step import PipelineStep from .generate_suggestions_by_file_input import GenerateSuggestionsByFileInput -from .generate_suggestions_by_file_output import GenerateSuggestionsByFileOutput +from .generate_suggestions_by_file_output import GenerateSuggestionsByFileOutput, FeedbackModel from .prompt import system_message, human_message from pydantic import Field from module_programming_llm.helpers.llm_utils import ( @@ -21,7 +21,7 @@ from ...helpers.models import ModelConfigType -class GenerateSuggestionsByFile(PipelineStep[GenerateSuggestionsByFileInput, GenerateSuggestionsByFileOutput]): +class GenerateSuggestionsByFile(PipelineStep[GenerateSuggestionsByFileInput, List[Optional[GenerateSuggestionsByFileOutput]]]): """Generates concise feedback for submitted files, facilitating a quicker review and understanding of the content""" system_message: str = Field(system_message, @@ -34,7 +34,7 @@ class GenerateSuggestionsByFile(PipelineStep[GenerateSuggestionsByFileInput, Gen description="Split the grading instructions into file-based ones after this number of tokens.") # pylint: disable=too-many-locals - async def process(self, input_data: GenerateSuggestionsByFileInput, debug: bool, model: ModelConfigType) -> Optional[GenerateSuggestionsByFileOutput]: + async def process(self, input_data: GenerateSuggestionsByFileInput, debug: bool, model: ModelConfigType) -> List[Optional[GenerateSuggestionsByFileOutput]]: model = model.get_model() # type: ignore[attr-defined] prompt = get_chat_prompt_with_formatting_instructions( @@ -51,7 +51,7 @@ async def process(self, input_data: GenerateSuggestionsByFileInput, debug: bool, ) file_problem_statements = ( { - item.file_name: item.problem_statement + item.file_path: item.problem_statement for item in input_data.problem_statement_by_file.items } if input_data.problem_statement_by_file is not None @@ -66,7 +66,7 @@ async def process(self, input_data: GenerateSuggestionsByFileInput, debug: bool, ) file_grading_instructions = ( { - item.file_name: item.grading_instructions + item.file_path: item.grading_instructions for item in input_data.grading_instructions_by_file.items } if input_data.grading_instructions_by_file is not None @@ -246,13 +246,4 @@ async def process(self, input_data: GenerateSuggestionsByFileInput, debug: bool, ], ) - if not results or all(r is None for r in results): - return None - - final_assessment = GenerateSuggestionsByFileOutput() - final_assessment.feedbacks = [] - for feedback in results: - if feedback is not None: - final_assessment.feedbacks.append(feedback) - - return final_assessment \ No newline at end of file + return results \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_input.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_input.py index 567992fb4..d1e69c5ac 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_input.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_input.py @@ -29,13 +29,13 @@ def __init__(self, template_repo: Repo, submission_repo: Repo, solution_repo: Repo, - grading_instructions_by_file: SplitGradingInstructionsByFileOutput, - problem_statement_by_file: SplitProblemStatementByFileOutput, exercise_id: int, submission_id: int, max_points: float, bonus_points: float, programming_language: str, + grading_instructions_by_file: Optional[SplitGradingInstructionsByFileOutput] = None, + problem_statement_by_file: Optional[SplitProblemStatementByFileOutput] = None, grading_criteria: Optional[List[GradingCriterion]] = None, problem_statement: Optional[str] = None, grading_instructions: Optional[str] = None): diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_output.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_output.py index 1c4971fd5..be693d961 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_output.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_output.py @@ -18,7 +18,6 @@ class FeedbackModel(BaseModel): 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" ) - file_name: str = Field(description="The name of the file") class Config: title = "Feedback" @@ -26,8 +25,5 @@ class Config: class GenerateSuggestionsByFileOutput(BaseModel): """Collection of feedbacks making up an assessment for a file""" - - feedbacks: Sequence[FeedbackModel] = Field(description="Assessment feedbacks", default=[]) - - class Config: - title = "FileAssessment" \ No newline at end of file + feedbacks: Sequence[FeedbackModel] = Field(description="Assessment feedbacks for a file", default=[]) + file_path: str = Field(description="The path of the file, as specified in the input prompt") diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/prompt.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/prompt.py index 8b1f00832..ce5aef5ba 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/prompt.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/prompt.py @@ -27,4 +27,5 @@ \"\"\" {submission_file} \"\"\"\ +Path: {file_path} """ diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file_output.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file_output.py index df111c7b2..5d212f645 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file_output.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file_output.py @@ -4,7 +4,7 @@ class FileGradingInstruction(BaseModel): - file_name: str = Field(description="File name") + file_path: str = Field(description="The full path of the file, as specified in the input prompt") grading_instructions: str = Field(description="Grading instructions relevant for this file") diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py index fbd902623..4f623d022 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py @@ -104,11 +104,11 @@ async def process(self, input_data: SplitProblemStatementByFileInput, debug: boo # Join duplicate file names (some responses contain multiple problem statements for the same file) file_problem_statements_by_file_name = defaultdict(list) for file_problem_statement in split_problem_statement.items: - file_problem_statements_by_file_name[file_problem_statement.file_name].append(file_problem_statement) + file_problem_statements_by_file_name[file_problem_statement.file_path].append(file_problem_statement) split_problem_statement.items = [ FileProblemStatement( - file_name=file_name, + file_path=file_name, problem_statement="\n".join( file_problem_statement.problem_statement for file_problem_statement in file_problem_statements diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file_output.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file_output.py index 929177bf2..df6967c88 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file_output.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file_output.py @@ -4,7 +4,7 @@ class FileProblemStatement(BaseModel): - file_name: str = Field(description="File name") + file_path: str = Field(description="The full path of the file, as specified in the input prompt") problem_statement: str = Field(description="Problem statement relevant for this file") From 6a62e214be80a0e65f96c2baef3510f6d0a149ef Mon Sep 17 00:00:00 2001 From: Dmytro Polityka Date: Mon, 7 Oct 2024 03:54:51 +0200 Subject: [PATCH 13/21] resolve linting errors --- .../approaches/basic_by_file_approach.py | 18 +++++--------- .../filter_out_solution.py | 24 ++++++++++--------- .../filter_out_solution_input.py | 9 +++---- .../generate_file_summary.py | 13 +++++----- .../generate_suggestions_by_file.py | 13 +++++----- .../generate_suggestions_by_file_input.py | 4 ++-- .../prompts/pipeline_step.py | 2 +- .../split_grading_instructions_by_file.py | 14 +++++------ .../split_problem_statement_by_file.py | 11 ++++----- scripts/lint_modules.py | 16 ++++++------- 10 files changed, 57 insertions(+), 67 deletions(-) diff --git a/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py b/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py index c0b839330..38fb5f999 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py +++ b/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py @@ -19,41 +19,35 @@ async def generate_file_summary(step: GenerateFileSummary, input_data: GenerateFileSummaryInput, debug: bool, - model: ModelConfigType) -> Optional[ - GenerateFileSummaryOutput]: # type: ignore[attr-defined] + model: ModelConfigType) -> (Optional)[GenerateFileSummaryOutput]: # type: ignore return await step.process(input_data, debug, model) async def split_problem_statement(step: SplitProblemStatementByFile, input_data: SplitProblemStatementByFileInput, debug: bool, - model: ModelConfigType) -> Optional[ - SplitProblemStatementByFileOutput]: # type: ignore[attr-defined] + model: ModelConfigType) -> Optional[SplitProblemStatementByFileOutput]: # type: ignore return await step.process(input_data, debug, model) async def split_grading_instructions(step: SplitGradingInstructionsByFile, input_data: SplitGradingInstructionsByFileInput, debug: bool, - model: ModelConfigType) -> Optional[ - SplitGradingInstructionsByFileOutput]: # type: ignore[attr-defined] + model: ModelConfigType) -> Optional[SplitGradingInstructionsByFileOutput]: # type: ignore return await step.process(input_data, debug, model) async def generate_suggestions(step: GenerateSuggestionsByFile, input_data: GenerateSuggestionsByFileInput, debug: bool, - model: ModelConfigType) -> List[ - Optional[GenerateSuggestionsByFileOutput]]: # type: ignore[attr-defined] + model: ModelConfigType) -> List[Optional[GenerateSuggestionsByFileOutput]]: # type: ignore return await step.process(input_data, debug, model) async def filter_out_solutions(step: FilterOutSolution, input_data: FilterOutSolutionInput, debug: bool, - model: ModelConfigType) -> List[ - Optional[FilterOutSolutionOutput]]: # type: ignore[attr-defined] + model: ModelConfigType) -> List[Optional[FilterOutSolutionOutput]]: # type: ignore return await step.process(input_data, debug, model) -async def generate_feedback(exercise: Exercise, submission: Submission, is_graded: bool, - module_config: Configuration) -> List[Feedback]: # type: ignore[attr-defined] +async def generate_feedback(exercise: Exercise, submission: Submission, is_graded: bool, module_config: Configuration) -> List[Feedback]: # type: ignore template_repo = exercise.get_template_repository() solution_repo = exercise.get_solution_repository() submission_repo = submission.get_repository() diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution.py index 1a15ca0ab..0f9e6dab1 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution.py @@ -7,9 +7,10 @@ from athena import emit_meta from module_programming_llm.prompts.pipeline_step import PipelineStep from .filter_out_solution_input import FilterOutSolutionInput -from .filter_out_solution_output import FilterOutSolutionOutput, FeedbackModel as FilterOutFeedbackModel -from module_programming_llm.prompts.generate_suggestions_by_file.generate_suggestions_by_file_output import FeedbackModel as SuggestionsFeedbackModel -from .prompt import system_message, human_message +from .filter_out_solution_output import FilterOutSolutionOutput +from module_programming_llm.prompts.generate_suggestions_by_file.generate_suggestions_by_file_output import \ + FeedbackModel as SuggestionsFeedbackModel +from .prompt import system_message as prompt_system_message, human_message as prompt_human_message from pydantic import Field from module_programming_llm.helpers.llm_utils import ( get_chat_prompt_with_formatting_instructions, @@ -27,9 +28,9 @@ class FilterOutSolution(PipelineStep[FilterOutSolutionInput, List[Optional[FilterOutSolutionOutput]]]): """Generates concise summaries of submission files, facilitating a quicker review and understanding of the content for AI processing.""" - system_message: str = Field(system_message, + system_message: str = Field(prompt_system_message, description="Message for priming AI behavior and instructing it what to do.") - human_message: str = Field(human_message, + human_message: str = Field(prompt_human_message, description="Message from a human. The input on which the AI is supposed to act.") tokens_before_split: int = Field(default=250, description="Split the grading instructions into file-based ones after this number of tokens.") @@ -39,7 +40,7 @@ async def process( self, input_data: FilterOutSolutionInput, debug: bool, - model: ModelConfigType + model: ModelConfigType # type: ignore ) -> List[Optional[FilterOutSolutionOutput]]: model = model.get_model() # type: ignore[attr-defined] @@ -78,13 +79,13 @@ async def process( # Changed text files changed_files = load_files_from_repo( solution_repo, - file_filter=lambda file_path: file_path - in changed_files_from_template_to_solution, + file_filter=lambda file_path: file_path in changed_files_from_template_to_solution, ) feedback_suggestions_by_file: Dict[str, Sequence[SuggestionsFeedbackModel]] = {} for feedback in input_data.feedback_suggestions: - feedback_suggestions_by_file[feedback.file_path] = feedback.feedbacks + if feedback is not None: + feedback_suggestions_by_file[feedback.file_path] = feedback.feedbacks # Gather prompt inputs for each file for file_path, file_content in changed_files.items(): @@ -117,7 +118,8 @@ async def process( "code_with_line_numbers": file_content, "problem_statement": problem_statement, "template_to_solution_diff": template_to_solution_diff, - "feedback_suggestions": json.dumps([ob.__dict__ for ob in feedback_suggestions_by_file.get(file_path) or []]) + "feedback_suggestions": json.dumps( + [ob.__dict__ for ob in feedback_suggestions_by_file.get(file_path) or []]) } ) @@ -174,4 +176,4 @@ async def process( ], ) - return results \ No newline at end of file + return results diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_input.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_input.py index c60164900..e763cb5d3 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_input.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_input.py @@ -12,19 +12,20 @@ class FilterOutSolutionInput: """ solution_repo: Repo template_repo: Repo - problem_statement_by_file: SplitProblemStatementByFileOutput + problem_statement_by_file: Optional[SplitProblemStatementByFileOutput] problem_statement: Optional[str] exercise_id: int submission_id: int feedback_suggestions: List[Optional[GenerateSuggestionsByFileOutput]] def __init__(self, solution_repo: Repo, template_repo: Repo, problem_statement: Optional[str], exercise_id: int, - submission_id: int, feedback_suggestions: List[Optional[GenerateSuggestionsByFileOutput]] = None, - problem_statement_by_file: Optional[SplitProblemStatementByFileOutput] = None): + submission_id: int, feedback_suggestions: List[Optional[GenerateSuggestionsByFileOutput]], + problem_statement_by_file: Optional[SplitProblemStatementByFileOutput]): self.solution_repo = solution_repo self.template_repo = template_repo self.exercise_id = exercise_id self.submission_id = submission_id - self.problem_statement_by_file = problem_statement_by_file + if problem_statement_by_file is not None: + self.problem_statement_by_file = problem_statement_by_file self.problem_statement = problem_statement self.feedback_suggestions = feedback_suggestions diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py index 3d765673b..3ea88e9cc 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py @@ -7,7 +7,7 @@ from .generate_file_summary_output import GenerateFileSummaryOutput from module_programming_llm.prompts.pipeline_step import PipelineStep from .generate_file_summary_output import FileDescription -from .prompt import system_message, human_message +from .prompt import system_message as prompt_system_message, human_message as prompt_human_message from pydantic import Field from module_programming_llm.helpers.llm_utils import ( get_chat_prompt_with_formatting_instructions, @@ -24,14 +24,13 @@ class GenerateFileSummary(PipelineStep[GenerateFileSummaryInput, GenerateFileSummaryOutput]): """Generates concise summaries of submission files, facilitating a quicker review and understanding of the content for AI processing.""" - system_message: str = Field(system_message, - description="Message for priming AI behavior and instructing it what to do.") - human_message: str = Field(human_message, - description="Message from a human. The input on which the AI is supposed to act.") + system_message: str = Field(prompt_system_message, + description="Message for priming AI behavior and instructing it what to do.") + human_message: str = Field(prompt_human_message, + description="Message from a human. The input on which the AI is supposed to act.") # pylint: disable=too-many-locals - async def process(self, input_data: GenerateFileSummaryInput, debug: bool, model: ModelConfigType) -> Optional[ - GenerateFileSummaryOutput]: + async def process(self, input_data: GenerateFileSummaryInput, debug: bool, model: ModelConfigType) -> Optional[GenerateFileSummaryOutput]: # type: ignore """Generate a summary for the submission, file by file. Args: diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py index e52b3aebb..e177a2584 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py @@ -6,7 +6,7 @@ from module_programming_llm.prompts.pipeline_step import PipelineStep from .generate_suggestions_by_file_input import GenerateSuggestionsByFileInput from .generate_suggestions_by_file_output import GenerateSuggestionsByFileOutput, FeedbackModel -from .prompt import system_message, human_message +from .prompt import system_message as prompt_system_message, human_message as prompt_human_message from pydantic import Field from module_programming_llm.helpers.llm_utils import ( get_chat_prompt_with_formatting_instructions, @@ -24,9 +24,9 @@ class GenerateSuggestionsByFile(PipelineStep[GenerateSuggestionsByFileInput, List[Optional[GenerateSuggestionsByFileOutput]]]): """Generates concise feedback for submitted files, facilitating a quicker review and understanding of the content""" - system_message: str = Field(system_message, + system_message: str = Field(prompt_system_message, description="Message for priming AI behavior and instructing it what to do.") - human_message: str = Field(human_message, + human_message: str = Field(prompt_human_message, description="Message from a human. The input on which the AI is supposed to act.") max_number_of_files: int = Field(default=25, description="Maximum number of files. If exceeded, it will prioritize the most important ones.") @@ -34,8 +34,8 @@ class GenerateSuggestionsByFile(PipelineStep[GenerateSuggestionsByFileInput, Lis description="Split the grading instructions into file-based ones after this number of tokens.") # pylint: disable=too-many-locals - async def process(self, input_data: GenerateSuggestionsByFileInput, debug: bool, model: ModelConfigType) -> List[Optional[GenerateSuggestionsByFileOutput]]: - model = model.get_model() # type: ignore[attr-defined] + async def process(self, input_data: GenerateSuggestionsByFileInput, debug: bool, model: ModelConfigType) -> List[Optional[GenerateSuggestionsByFileOutput]]: # type: ignore + model = model.get_model() # type: ignore[attr-defined] prompt = get_chat_prompt_with_formatting_instructions( model=model, @@ -90,8 +90,7 @@ async def process(self, input_data: GenerateSuggestionsByFileInput, debug: bool, # Changed text files changed_files = load_files_from_repo( submission_repo, - file_filter=lambda file_path: file_path - in changed_files_from_template_to_submission, + file_filter=lambda file_path: file_path in changed_files_from_template_to_submission, ) # Gather prompt inputs for each changed file (independently) diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_input.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_input.py index d1e69c5ac..e256736cc 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_input.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_input.py @@ -16,9 +16,9 @@ class GenerateSuggestionsByFileInput: solution_repo: Repo exercise_id: int submission_id: int - grading_instructions_by_file: SplitGradingInstructionsByFileOutput + grading_instructions_by_file: Optional[SplitGradingInstructionsByFileOutput] grading_criteria: Optional[List[GradingCriterion]] - problem_statement_by_file: SplitProblemStatementByFileOutput + problem_statement_by_file: Optional[SplitProblemStatementByFileOutput] problem_statement: Optional[str] grading_instructions: Optional[str] max_points: float diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/pipeline_step.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/pipeline_step.py index 4e8599ef6..1411c2fef 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/pipeline_step.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/pipeline_step.py @@ -13,5 +13,5 @@ class PipelineStep(BaseModel, Generic[TInput, TOutput]): max_input_tokens: int = Field(default=3000, description="Maximum number of tokens in the input prompt.") @abstractmethod - async def process(self, input_data: TInput, debug: bool, model: ModelConfigType) -> Optional[TOutput]: + async def process(self, input_data: TInput, debug: bool, model: ModelConfigType) -> Optional[TOutput]: # type: ignore raise NotImplementedError('This is an abstract method') diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file.py index 27ee9ba8e..361d3c7d7 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file.py @@ -6,8 +6,8 @@ from athena import emit_meta from module_programming_llm.prompts.pipeline_step import PipelineStep -from . import SplitGradingInstructionsByFileInput, SplitGradingInstructionsByFileOutput -from .prompt import system_message, human_message +from .split_grading_instructions_by_file_input import SplitGradingInstructionsByFileInput +from .prompt import system_message as prompt_system_message, human_message as prompt_human_message from pydantic import Field from module_programming_llm.helpers.llm_utils import ( get_chat_prompt_with_formatting_instructions, @@ -17,7 +17,7 @@ from module_programming_llm.helpers.utils import ( get_diff, ) -from .split_grading_instructions_by_file_output import FileGradingInstruction +from .split_grading_instructions_by_file_output import FileGradingInstruction, SplitGradingInstructionsByFileOutput from ...helpers.models import ModelConfigType @@ -25,16 +25,14 @@ class SplitGradingInstructionsByFile( PipelineStep[SplitGradingInstructionsByFileInput, SplitGradingInstructionsByFileOutput]): """Splits grading instructions of a programming exercise to match with solution files""" - system_message: str = Field(system_message, + system_message: str = Field(prompt_system_message, description="Message for priming AI behavior and instructing it what to do.") - human_message: str = Field(human_message, + human_message: str = Field(prompt_human_message, description="Message from a human. The input on which the AI is supposed to act.") tokens_before_split: int = Field(default=250, description="Split the grading instructions into file-based ones after this number of tokens.") - # pylint: disable=too-many-locals - async def process(self, input_data: SplitGradingInstructionsByFileInput, debug: bool, model: ModelConfigType) -> Optional[ - SplitGradingInstructionsByFileOutput]: + async def process(self, input_data: SplitGradingInstructionsByFileInput, debug: bool, model: ModelConfigType) -> Optional[SplitGradingInstructionsByFileOutput]: # type: ignore """Split the general grading instructions by file Args: diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py index 4f623d022..20dacac58 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py @@ -4,7 +4,7 @@ from pydantic import Field from athena import emit_meta -from .prompt import system_message, human_message +from .prompt import system_message as prompt_system_message, human_message as prompt_human_message from .split_problem_statement_by_file_input import SplitProblemStatementByFileInput from .split_problem_statement_by_file_output import FileProblemStatement, SplitProblemStatementByFileOutput @@ -18,17 +18,14 @@ class SplitProblemStatementByFile(PipelineStep[SplitProblemStatementByFileInput, SplitProblemStatementByFileOutput]): """Splits problem statement of a programming exercise to match with solution files""" - system_message: str = Field(system_message, + system_message: str = Field(prompt_system_message, description="Message for priming AI behavior and instructing it what to do.") - human_message: str = Field(human_message, + human_message: str = Field(prompt_human_message, description="Message from a human. The input on which the AI is supposed to act.") tokens_before_split: int = Field(default=250, description="Split the grading instructions into file-based ones after this number of tokens.") - # pylint: disable=too-many-locals - async def process(self, input_data: SplitProblemStatementByFileInput, debug: bool, model: ModelConfigType) -> \ - Optional[ - SplitProblemStatementByFileOutput]: + async def process(self, input_data: SplitProblemStatementByFileInput, debug: bool, model: ModelConfigType) -> Optional[SplitProblemStatementByFileOutput]: # type: ignore """Split the general problem statement by file Args: diff --git a/scripts/lint_modules.py b/scripts/lint_modules.py index 1e09d9696..3a6d8fb36 100644 --- a/scripts/lint_modules.py +++ b/scripts/lint_modules.py @@ -5,15 +5,15 @@ def main(): modules = [ - "log_viewer", - "assessment_module_manager", - "athena", # the version in this commit only, can differ for modules - "modules/programming/module_example", +# "log_viewer", +# "assessment_module_manager", +# "athena", # the version in this commit only, can differ for modules +# "modules/programming/module_example", "modules/programming/module_programming_llm", - "modules/text/module_text_llm", - "modules/text/module_text_cofee", - "modules/programming/module_programming_themisml", - "modules/modeling/module_modeling_llm", +# "modules/text/module_text_llm", +# "modules/text/module_text_cofee", +# "modules/programming/module_programming_themisml", +# "modules/modeling/module_modeling_llm", # "module_programming_apted" skip due to an error ] From 42396b75d0be840dbab73ab9815611e43d593f76 Mon Sep 17 00:00:00 2001 From: Dmytro Polityka Date: Mon, 7 Oct 2024 05:23:28 +0200 Subject: [PATCH 14/21] add validate suggestions step --- .../approaches/basic_by_file_approach.py | 33 ++- .../module_programming_llm/config.py | 2 + .../prompts/__init__.py | 5 +- .../filter_out_solution.py | 4 +- .../filter_out_solution_input.py | 3 +- .../generate_suggestions_by_file.py | 4 +- .../generate_suggestions_by_file_input.py | 3 + .../generate_suggestions_by_file/prompt.py | 3 + .../split_grading_instructions_by_file.py | 2 +- .../split_problem_statement_by_file.py | 2 +- .../prompts/validate_suggestions/__init__.py | 9 + .../prompts/validate_suggestions/prompt.py | 37 +++ .../validate_suggestions.py | 267 ++++++++++++++++++ .../validate_suggestions_input.py | 63 +++++ .../validate_suggestions_output.py | 33 +++ scripts/lint_modules.py | 16 +- 16 files changed, 464 insertions(+), 22 deletions(-) create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/prompt.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions_input.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions_output.py diff --git a/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py b/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py index 38fb5f999..6841690d5 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py +++ b/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py @@ -15,39 +15,48 @@ SplitGradingInstructionsByFileInput from module_programming_llm.prompts.split_problem_statement_by_file import SplitProblemStatementByFileOutput, \ SplitProblemStatementByFileInput +from module_programming_llm.prompts.validate_suggestions import ValidateSuggestions, ValidateSuggestionsInput, \ + ValidateSuggestionsOutput async def generate_file_summary(step: GenerateFileSummary, input_data: GenerateFileSummaryInput, debug: bool, - model: ModelConfigType) -> (Optional)[GenerateFileSummaryOutput]: # type: ignore + model: ModelConfigType) -> (Optional)[GenerateFileSummaryOutput]: # type: ignore return await step.process(input_data, debug, model) async def split_problem_statement(step: SplitProblemStatementByFile, input_data: SplitProblemStatementByFileInput, debug: bool, - model: ModelConfigType) -> Optional[SplitProblemStatementByFileOutput]: # type: ignore + model: ModelConfigType) -> Optional[SplitProblemStatementByFileOutput]: # type: ignore return await step.process(input_data, debug, model) async def split_grading_instructions(step: SplitGradingInstructionsByFile, input_data: SplitGradingInstructionsByFileInput, debug: bool, - model: ModelConfigType) -> Optional[SplitGradingInstructionsByFileOutput]: # type: ignore + model: ModelConfigType) -> Optional[SplitGradingInstructionsByFileOutput]: # type: ignore return await step.process(input_data, debug, model) async def generate_suggestions(step: GenerateSuggestionsByFile, input_data: GenerateSuggestionsByFileInput, debug: bool, - model: ModelConfigType) -> List[Optional[GenerateSuggestionsByFileOutput]]: # type: ignore + model: ModelConfigType) -> List[Optional[GenerateSuggestionsByFileOutput]]: # type: ignore return await step.process(input_data, debug, model) async def filter_out_solutions(step: FilterOutSolution, input_data: FilterOutSolutionInput, debug: bool, - model: ModelConfigType) -> List[Optional[FilterOutSolutionOutput]]: # type: ignore + model: ModelConfigType) -> List[Optional[FilterOutSolutionOutput]]: # type: ignore return await step.process(input_data, debug, model) -async def generate_feedback(exercise: Exercise, submission: Submission, is_graded: bool, module_config: Configuration) -> List[Feedback]: # type: ignore +async def validate_suggestions(step: ValidateSuggestions, + input_data: ValidateSuggestionsInput, debug: bool, + model: ModelConfigType) -> List[Optional[ValidateSuggestionsOutput]]: # type: ignore + return await step.process(input_data, debug, model) + + +async def generate_feedback(exercise: Exercise, submission: Submission, is_graded: bool, + module_config: Configuration) -> List[Feedback]: # type: ignore template_repo = exercise.get_template_repository() solution_repo = exercise.get_solution_repository() submission_repo = submission.get_repository() @@ -77,6 +86,7 @@ async def generate_feedback(exercise: Exercise, submission: Submission, is_grade exercise.id, submission.id, exercise.max_points, exercise.bonus_points, exercise.programming_language, + file_summary_output.describe_solution_summary() if file_summary_output else "", split_grading_instructions_output, split_problem_statement_output, exercise.grading_criteria, exercise.problem_statement, @@ -91,6 +101,17 @@ async def generate_feedback(exercise: Exercise, submission: Submission, is_grade output = await filter_out_solutions(module_config.basic_by_file_approach.filter_out_solution, filter_out_solution_input, is_debug, model) + validate_suggestions_input = ValidateSuggestionsInput(solution_repo, template_repo, submission_repo, + split_problem_statement_output, exercise.problem_statement, + exercise.id, submission.id, output, + split_grading_instructions_output, exercise.grading_criteria, + exercise.grading_instructions, + file_summary_output.describe_solution_summary() if file_summary_output else "", + exercise.max_points, exercise.bonus_points, + exercise.programming_language) + output = await validate_suggestions( + module_config.basic_by_file_approach.validate_suggestions, validate_suggestions_input, is_debug, model) + grading_instruction_ids = set( grading_instruction.id for criterion in exercise.grading_criteria or [] diff --git a/modules/programming/module_programming_llm/module_programming_llm/config.py b/modules/programming/module_programming_llm/module_programming_llm/config.py index 2d3da4582..71241f1e9 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/config.py +++ b/modules/programming/module_programming_llm/module_programming_llm/config.py @@ -7,6 +7,7 @@ from module_programming_llm.prompts import SplitProblemStatementByFile, SplitGradingInstructionsByFile, \ GenerateSuggestionsByFile, GenerateFileSummary from module_programming_llm.prompts.filter_out_solution.filter_out_solution import FilterOutSolution +from module_programming_llm.prompts.validate_suggestions import ValidateSuggestions class BasicApproachConfig(BaseModel): @@ -30,6 +31,7 @@ class BasicByFileApproachConfig(BasicApproachConfig, ABC): generate_suggestions_by_file: GenerateSuggestionsByFile = Field(default=GenerateSuggestionsByFile()) generate_file_summary: GenerateFileSummary = Field(default=GenerateFileSummary()) filter_out_solution: FilterOutSolution = Field(default=FilterOutSolution()) + validate_suggestions: ValidateSuggestions = Field(default=ValidateSuggestions()) max_number_of_files: int = Field(default=25, description="Maximum number of files. If exceeded, it will prioritize the most important ones.") tokens_before_split: int = Field(default=250, diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/__init__.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/__init__.py index 5d6af34a4..2b8f1e153 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/__init__.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/__init__.py @@ -3,6 +3,9 @@ from .generate_file_summary import GenerateFileSummary from .split_problem_statement_by_file import SplitProblemStatementByFile from .split_grading_instructions_by_file import SplitGradingInstructionsByFile +from .validate_suggestions import ValidateSuggestions +from .filter_out_solution import FilterOutSolution __all__ = ['GenerateSuggestionsByFile', 'GenerateSuggestionsZeroShotStep', 'GenerateFileSummary', - 'SplitGradingInstructionsByFile', 'GenerateSuggestionsByFileOutput', 'SplitProblemStatementByFile'] + 'SplitGradingInstructionsByFile', 'GenerateSuggestionsByFileOutput', 'SplitProblemStatementByFile', + 'ValidateSuggestions', 'FilterOutSolution'] diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution.py index 0f9e6dab1..caf50b6b8 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution.py @@ -26,13 +26,13 @@ class FilterOutSolution(PipelineStep[FilterOutSolutionInput, List[Optional[FilterOutSolutionOutput]]]): - """Generates concise summaries of submission files, facilitating a quicker review and understanding of the content for AI processing.""" + """A pipeline step to remove potential solutions from the output.""" system_message: str = Field(prompt_system_message, description="Message for priming AI behavior and instructing it what to do.") human_message: str = Field(prompt_human_message, description="Message from a human. The input on which the AI is supposed to act.") - tokens_before_split: int = Field(default=250, + tokens_before_split: int = Field(default=2000, description="Split the grading instructions into file-based ones after this number of tokens.") # pylint: disable=too-many-locals diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_input.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_input.py index e763cb5d3..420850ef0 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_input.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_input.py @@ -25,7 +25,6 @@ def __init__(self, solution_repo: Repo, template_repo: Repo, problem_statement: self.template_repo = template_repo self.exercise_id = exercise_id self.submission_id = submission_id - if problem_statement_by_file is not None: - self.problem_statement_by_file = problem_statement_by_file + self.problem_statement_by_file = problem_statement_by_file self.problem_statement = problem_statement self.feedback_suggestions = feedback_suggestions diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py index e177a2584..d68c3fa3d 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py @@ -30,7 +30,7 @@ class GenerateSuggestionsByFile(PipelineStep[GenerateSuggestionsByFileInput, Lis description="Message from a human. The input on which the AI is supposed to act.") max_number_of_files: int = Field(default=25, description="Maximum number of files. If exceeded, it will prioritize the most important ones.") - tokens_before_split: int = Field(default=250, + tokens_before_split: int = Field(default=2000, description="Split the grading instructions into file-based ones after this number of tokens.") # pylint: disable=too-many-locals @@ -158,6 +158,7 @@ async def process(self, input_data: GenerateSuggestionsByFileInput, debug: bool, "template_to_solution_diff": template_to_solution_diff, "grading_instructions": grading_instructions, "problem_statement": problem_statement, + "solution_summary": input_data.solution_summary } ) @@ -172,6 +173,7 @@ async def process(self, input_data: GenerateSuggestionsByFileInput, debug: bool, "grading_instructions", "solution_to_submission_diff", "template_to_submission_diff", + "solution_summary" # In the future we might indicate the changed lines in the submission_file additionally ] diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_input.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_input.py index e256736cc..76ab3e0e5 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_input.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_input.py @@ -24,6 +24,7 @@ class GenerateSuggestionsByFileInput: max_points: float bonus_points: float programming_language: str + solution_summary: str def __init__(self, template_repo: Repo, @@ -34,6 +35,7 @@ def __init__(self, max_points: float, bonus_points: float, programming_language: str, + solution_summary: str, grading_instructions_by_file: Optional[SplitGradingInstructionsByFileOutput] = None, problem_statement_by_file: Optional[SplitProblemStatementByFileOutput] = None, grading_criteria: Optional[List[GradingCriterion]] = None, @@ -52,3 +54,4 @@ def __init__(self, self.max_points = max_points self.bonus_points = bonus_points self.programming_language = programming_language + self.solution_summary = solution_summary diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/prompt.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/prompt.py index ce5aef5ba..6de72f595 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/prompt.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/prompt.py @@ -20,6 +20,9 @@ # Diff between template (deletions) and student\'s submission (additions): {template_to_submission_diff} + +# Summary of other solution files +{solution_summary} """ human_message = """\ diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file.py index 361d3c7d7..4c1c5744e 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file.py @@ -29,7 +29,7 @@ class SplitGradingInstructionsByFile( description="Message for priming AI behavior and instructing it what to do.") human_message: str = Field(prompt_human_message, description="Message from a human. The input on which the AI is supposed to act.") - tokens_before_split: int = Field(default=250, + tokens_before_split: int = Field(default=2000, description="Split the grading instructions into file-based ones after this number of tokens.") async def process(self, input_data: SplitGradingInstructionsByFileInput, debug: bool, model: ModelConfigType) -> Optional[SplitGradingInstructionsByFileOutput]: # type: ignore diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py index 20dacac58..2074eb9ed 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py @@ -22,7 +22,7 @@ class SplitProblemStatementByFile(PipelineStep[SplitProblemStatementByFileInput, description="Message for priming AI behavior and instructing it what to do.") human_message: str = Field(prompt_human_message, description="Message from a human. The input on which the AI is supposed to act.") - tokens_before_split: int = Field(default=250, + tokens_before_split: int = Field(default=2000, description="Split the grading instructions into file-based ones after this number of tokens.") async def process(self, input_data: SplitProblemStatementByFileInput, debug: bool, model: ModelConfigType) -> Optional[SplitProblemStatementByFileOutput]: # type: ignore diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/__init__.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/__init__.py index e69de29bb..7c3da3ea3 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/__init__.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/__init__.py @@ -0,0 +1,9 @@ +from .validate_suggestions_input import ValidateSuggestionsInput +from .validate_suggestions_output import ValidateSuggestionsOutput +from .validate_suggestions import ValidateSuggestions + +__all__ = [ + "ValidateSuggestions", + "ValidateSuggestionsInput", + "ValidateSuggestionsOutput", +] \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/prompt.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/prompt.py new file mode 100644 index 000000000..c459fe796 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/prompt.py @@ -0,0 +1,37 @@ +system_message = """\ +You are a tutor at a very prestigious university. +# Task +You are given feedback suggestions. +Your task is to filter out feedback suggestions that are wrong or meaningless in the educational context you are given. Do not generate new suggestions. +Please keep only relevant feedback suggestions in your response. +Also, make sure that the number of points is distributed correctly and makes sense. + +# Problem Statement: +{problem_statement} + +# Grading instructions +{grading_instructions} +Max points: {max_points}, bonus points: {bonus_points} (whole assessment, not just this file) + +# Diff between solution (deletions) and student\'s submission (additions): +{solution_to_submission_diff} + +# Diff between template (deletions) and student\'s submission (additions): +{template_to_submission_diff} + +# Summary of other solution files +{solution_summary} +""" + +human_message = """\ +Path: {file_path} +Feedback Suggestions: +\"\"\" +{feedback_suggestions} +\"\"\" + +Student\'s submission file to grade (with line numbers : ): +\"\"\" +{submission_file} +\"\"\"\ +""" diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions.py new file mode 100644 index 000000000..d4d9a3c5a --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions.py @@ -0,0 +1,267 @@ +import asyncio +import json +import os +from typing import Optional, List, Sequence, Dict + +from athena import emit_meta +from module_programming_llm.prompts.pipeline_step import PipelineStep +from module_programming_llm.prompts.generate_suggestions_by_file.generate_suggestions_by_file_output import \ + FeedbackModel as SuggestionsFeedbackModel +from .validate_suggestions_input import ValidateSuggestionsInput +from .validate_suggestions_output import ValidateSuggestionsOutput +from .prompt import system_message as prompt_system_message, human_message as prompt_human_message +from pydantic import Field +from module_programming_llm.helpers.llm_utils import ( + get_chat_prompt_with_formatting_instructions, + predict_and_parse, num_tokens_from_string, + check_prompt_length_and_omit_features_if_necessary, +) +from module_programming_llm.helpers.utils import ( + get_diff, + load_files_from_repo, + add_line_numbers, get_programming_language_file_extension +) +from ...helpers.models import ModelConfigType + + +class ValidateSuggestions(PipelineStep[ValidateSuggestionsInput, List[Optional[ValidateSuggestionsOutput]]]): + """Generates concise summaries of submission files, facilitating a quicker review and understanding of the content for AI processing.""" + + system_message: str = Field(prompt_system_message, + description="Message for priming AI behavior and instructing it what to do.") + human_message: str = Field(prompt_human_message, + description="Message from a human. The input on which the AI is supposed to act.") + tokens_before_split: int = Field(default=2000, + description="Split the grading instructions into file-based ones after this number of tokens.") + max_number_of_files: int = Field(default=25, + description="Maximum number of files. If exceeded, it will prioritize the most important ones.") + + # pylint: disable=too-many-locals + async def process( + self, + input_data: ValidateSuggestionsInput, + debug: bool, + model: ModelConfigType # type: ignore + ) -> List[Optional[ValidateSuggestionsOutput]]: + model = model.get_model() # type: ignore[attr-defined] + + # Prepare the prompt template + prompt = get_chat_prompt_with_formatting_instructions( + model=model, + system_message=self.system_message, + human_message=self.human_message, + pydantic_object=ValidateSuggestionsOutput, + ) + + problem_statement_tokens = num_tokens_from_string(input_data.problem_statement or "") + is_short_problem_statement = ( + problem_statement_tokens + <= self.tokens_before_split + ) + file_problem_statements = ( + { + item.file_path: item.problem_statement + for item in input_data.problem_statement_by_file.items + } + if input_data.problem_statement_by_file is not None + else {} + ) + + is_short_grading_instructions = ( + num_tokens_from_string(input_data.grading_instructions) + <= self.tokens_before_split + if input_data.grading_instructions is not None + else True + ) + file_grading_instructions = ( + { + item.file_path: item.grading_instructions + for item in input_data.grading_instructions_by_file.items + } + if input_data.grading_instructions_by_file is not None + else {} + ) + + prompt_inputs: List[dict] = [] + + solution_repo = input_data.solution_repo + template_repo = input_data.template_repo + submission_repo = input_data.submission_repo + + changed_files_from_template_to_submission = get_diff( + src_repo=template_repo, dst_repo=submission_repo, file_path=None, name_only=True + ).split("\n") + changed_files_from_template_to_submission = [ + os.path.join(str(submission_repo.working_tree_dir or ""), file_path) + for file_path in changed_files_from_template_to_submission + ] + + # Changed text files + changed_files = load_files_from_repo( + submission_repo, + file_filter=lambda file_path: file_path in changed_files_from_template_to_submission, + ) + + feedback_suggestions_by_file: Dict[str, Sequence[SuggestionsFeedbackModel]] = {} + for feedback in input_data.feedback_suggestions: + if feedback is not None: + feedback_suggestions_by_file[feedback.file_path] = feedback.feedbacks + + # Gather prompt inputs for each changed file (independently) + for file_path, file_content in changed_files.items(): + problem_statement = ( + input_data.problem_statement or "" + if is_short_problem_statement + else file_problem_statements.get( + file_path, "No relevant problem statement section found." + ) + ) + problem_statement = ( + problem_statement + if problem_statement.strip() + else "No problem statement found." + ) + + grading_instructions = ( + input_data.grading_instructions or "" + if is_short_grading_instructions + else file_grading_instructions.get( + file_path, "No relevant grading instructions found." + ) + ) + grading_instructions = ( + grading_instructions + if grading_instructions.strip() + else "No grading instructions found." + ) + + file_content = add_line_numbers(file_content) + solution_to_submission_diff = get_diff( + src_repo=solution_repo, + dst_repo=submission_repo, + src_prefix="solution", + dst_prefix="submission", + file_path=file_path, + ) + template_to_submission_diff = get_diff( + src_repo=template_repo, + dst_repo=submission_repo, + src_prefix="template", + dst_prefix="submission", + file_path=file_path, + ) + template_to_solution_diff = get_diff( + src_repo=template_repo, + dst_repo=solution_repo, + src_prefix="template", + dst_prefix="solution", + file_path=file_path, + ) + + prompt_inputs.append( + { + "file_path": file_path, # Not really relevant for the prompt + "priority": len( + template_to_solution_diff + ), # Not really relevant for the prompt + "submission_file": file_content, + "max_points": input_data.max_points, + "bonus_points": input_data.bonus_points, + "solution_to_submission_diff": solution_to_submission_diff, + "template_to_submission_diff": template_to_submission_diff, + "template_to_solution_diff": template_to_solution_diff, + "grading_instructions": grading_instructions, + "problem_statement": problem_statement, + "solution_summary": input_data.solution_summary, + "feedback_suggestions": json.dumps( + [ob.__dict__ for ob in feedback_suggestions_by_file.get(file_path) or []]) + } + ) + + # Filter long prompts (omitting features if necessary) + # Lowest priority features are at the top of the list (i.e. they are omitted first if necessary) + # "submission_file" is not omittable, because it is the main input containing the line numbers + # In the future we might be able to include the line numbers in the diff, but for now we need to keep it + omittable_features = [ + "template_to_solution_diff", + # If it is even included in the prompt (has the lowest priority since it is indirectly included in other diffs) + "problem_statement", + "grading_instructions", + "solution_to_submission_diff", + "template_to_submission_diff", + "solution_summary" + # In the future we might indicate the changed lines in the submission_file additionally + ] + + prompt_inputs = [ + omitted_prompt_input + for omitted_prompt_input, should_run in [ + check_prompt_length_and_omit_features_if_necessary( + prompt=prompt, + prompt_input=prompt_input, + max_input_tokens=self.max_input_tokens, + omittable_features=omittable_features, + debug=debug, + ) + for prompt_input in prompt_inputs + ] + if should_run + ] + + # If we have many files we need to filter and prioritize them + if len(prompt_inputs) > self.max_number_of_files: + programming_language_extension = get_programming_language_file_extension( + programming_language=input_data.programming_language + ) + + # Prioritize files that have a diff between solution and submission + prompt_inputs = sorted(prompt_inputs, key=lambda x: x["priority"], reverse=True) + + filtered_prompt_inputs = [] + if programming_language_extension is not None: + filtered_prompt_inputs = [ + prompt_input + for prompt_input in prompt_inputs + if prompt_input["file_path"].endswith(programming_language_extension) + ] + + while ( + len(filtered_prompt_inputs) < self.max_number_of_files and prompt_inputs + ): + filtered_prompt_inputs.append(prompt_inputs.pop(0)) + prompt_inputs = filtered_prompt_inputs + + # Send prompts to the LLM + # noinspection PyTypeChecker + results: List[Optional[ValidateSuggestionsOutput]] = await asyncio.gather( + *[ + predict_and_parse( + model=model, + chat_prompt=prompt, + prompt_input=prompt_input, + pydantic_object=ValidateSuggestionsOutput, + tags=[ + f"exercise-{input_data.exercise_id}", + f"submission-{input_data.submission_id}", + f"file-{prompt_input['file_path']}", + "filter-out-solution", + ], + ) + for prompt_input in prompt_inputs + ] + ) + + if debug: + emit_meta( + "filter_out_solutions", + [ + { + "file_path": prompt_input["file_path"], + "prompt": prompt.format(**prompt_input), + "result": result.dict() if result is not None else None, + } + for prompt_input, result in zip(prompt_inputs, results) + ], + ) + + return results diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions_input.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions_input.py new file mode 100644 index 000000000..6c12eedbc --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions_input.py @@ -0,0 +1,63 @@ +from typing import Optional, List + +from git import Repo + +from athena import GradingCriterion +from module_programming_llm.prompts import GenerateSuggestionsByFileOutput +from module_programming_llm.prompts.split_grading_instructions_by_file import SplitGradingInstructionsByFileOutput +from module_programming_llm.prompts.split_problem_statement_by_file import SplitProblemStatementByFileOutput + + +class ValidateSuggestionsInput: + """ + DTO class for filtering out + """ + solution_repo: Repo + template_repo: Repo + submission_repo: Repo + problem_statement_by_file: Optional[SplitProblemStatementByFileOutput] + problem_statement: Optional[str] + exercise_id: int + submission_id: int + feedback_suggestions: List[Optional[GenerateSuggestionsByFileOutput]] + grading_instructions_by_file: Optional[SplitGradingInstructionsByFileOutput] + grading_criteria: Optional[List[GradingCriterion]] + grading_instructions: Optional[str] + solution_summary: str + max_points: float + bonus_points: float + programming_language: str + + def __init__( + self, + solution_repo: Repo, + template_repo: Repo, + submission_repo: Repo, + problem_statement_by_file: Optional[SplitProblemStatementByFileOutput], + problem_statement: Optional[str], + exercise_id: int, + submission_id: int, + feedback_suggestions: List[Optional[GenerateSuggestionsByFileOutput]], + grading_instructions_by_file: Optional[SplitGradingInstructionsByFileOutput], + grading_criteria: Optional[List[GradingCriterion]], + grading_instructions: Optional[str], + solution_summary: str, + max_points: float, + bonus_points: float, + programming_language: str + ): + self.solution_repo = solution_repo + self.template_repo = template_repo + self.submission_repo = submission_repo + self.problem_statement_by_file = problem_statement_by_file + self.problem_statement = problem_statement + self.exercise_id = exercise_id + self.submission_id = submission_id + self.feedback_suggestions = feedback_suggestions + self.grading_instructions_by_file = grading_instructions_by_file + self.grading_criteria = grading_criteria + self.grading_instructions = grading_instructions + self.solution_summary = solution_summary + self.max_points = max_points + self.bonus_points = bonus_points + self.programming_language = programming_language diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions_output.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions_output.py new file mode 100644 index 000000000..3e0063495 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions_output.py @@ -0,0 +1,33 @@ +from typing import Optional, Sequence + +from pydantic import BaseModel, Field + + +class FeedbackModel(BaseModel): + title: str = Field( + description="Very short title, i.e. feedback category", 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 Config: + title = "Feedback" + + +class ValidateSuggestionsOutput(BaseModel): + """Collection of feedbacks making up an assessment for a file""" + + feedbacks: Sequence[FeedbackModel] = Field(description="Assessment feedbacks", default=[]) + file_path: str = Field(description="The full path of the file, as specified in the input prompt") + + class Config: + title = "Assessment" \ No newline at end of file diff --git a/scripts/lint_modules.py b/scripts/lint_modules.py index 3a6d8fb36..1e09d9696 100644 --- a/scripts/lint_modules.py +++ b/scripts/lint_modules.py @@ -5,15 +5,15 @@ def main(): modules = [ -# "log_viewer", -# "assessment_module_manager", -# "athena", # the version in this commit only, can differ for modules -# "modules/programming/module_example", + "log_viewer", + "assessment_module_manager", + "athena", # the version in this commit only, can differ for modules + "modules/programming/module_example", "modules/programming/module_programming_llm", -# "modules/text/module_text_llm", -# "modules/text/module_text_cofee", -# "modules/programming/module_programming_themisml", -# "modules/modeling/module_modeling_llm", + "modules/text/module_text_llm", + "modules/text/module_text_cofee", + "modules/programming/module_programming_themisml", + "modules/modeling/module_modeling_llm", # "module_programming_apted" skip due to an error ] From 4576229da4e8e67cdc0295bfe19df84a0283c7ce Mon Sep 17 00:00:00 2001 From: Dmytro Polityka Date: Mon, 7 Oct 2024 05:45:09 +0200 Subject: [PATCH 15/21] fix linting errors --- .../prompts/filter_out_solution/filter_out_solution_input.py | 2 +- .../prompts/filter_out_solution/filter_out_solution_output.py | 2 +- .../prompts/validate_suggestions/validate_suggestions_input.py | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_input.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_input.py index 420850ef0..fbbba474c 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_input.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_input.py @@ -2,7 +2,7 @@ from git import Repo -from module_programming_llm.prompts import GenerateSuggestionsByFileOutput +from module_programming_llm.prompts.generate_suggestions_by_file import GenerateSuggestionsByFileOutput from module_programming_llm.prompts.split_problem_statement_by_file import SplitProblemStatementByFileOutput diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_output.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_output.py index 1353b1ce7..463a53fda 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_output.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution_output.py @@ -1,4 +1,4 @@ -from typing import Dict, Optional, Sequence +from typing import Optional, Sequence from pydantic import BaseModel, Field diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions_input.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions_input.py index 6c12eedbc..032f18e4d 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions_input.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions_input.py @@ -3,7 +3,7 @@ from git import Repo from athena import GradingCriterion -from module_programming_llm.prompts import GenerateSuggestionsByFileOutput +from module_programming_llm.prompts.generate_suggestions_by_file import GenerateSuggestionsByFileOutput from module_programming_llm.prompts.split_grading_instructions_by_file import SplitGradingInstructionsByFileOutput from module_programming_llm.prompts.split_problem_statement_by_file import SplitProblemStatementByFileOutput From 9bb8a903a70cf56205408ff17a31a83c7dfff0bd Mon Sep 17 00:00:00 2001 From: Dmytro Polityka Date: Mon, 7 Oct 2024 17:20:34 +0200 Subject: [PATCH 16/21] add generate grading criterion step --- .../approaches/basic_by_file_approach.py | 45 +++++++-- .../module_programming_llm/config.py | 3 + .../prompts/__init__.py | 6 +- .../generate_file_summary.py | 2 +- .../generate_grading_criterion/__init__.py | 9 ++ .../generate_grading_criterion.py | 91 +++++++++++++++++++ .../generate_grading_criterion_input.py | 32 +++++++ .../generate_grading_criterion_output.py | 8 ++ .../generate_grading_criterion/prompt.py | 30 ++++++ .../generate_grading_instructions/__init__.py | 0 .../generate_suggestions_by_file.py | 4 +- .../generate_suggestions_by_file/prompt.py | 4 +- .../__init__.py | 3 - .../generate_suggestions_zero_shot.py | 5 - .../split_grading_instructions_by_file.py | 2 +- .../split_problem_statement_by_file.py | 2 +- 16 files changed, 218 insertions(+), 28 deletions(-) create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/__init__.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion_input.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion_output.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/prompt.py delete mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_instructions/__init__.py delete mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_zero_shot/__init__.py delete mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_zero_shot/generate_suggestions_zero_shot.py diff --git a/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py b/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py index 6841690d5..0d70b267d 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py +++ b/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py @@ -9,6 +9,8 @@ from module_programming_llm.prompts.filter_out_solution.filter_out_solution_input import FilterOutSolutionInput from module_programming_llm.prompts.filter_out_solution.filter_out_solution_output import FilterOutSolutionOutput from module_programming_llm.prompts.generate_file_summary import GenerateFileSummaryOutput, GenerateFileSummaryInput +from module_programming_llm.prompts.generate_grading_criterion.generate_grading_criterion import \ + GenerateGradingCriterion, GenerateGradingCriterionOutput, GenerateGradingCriterionInput from module_programming_llm.prompts.generate_suggestions_by_file.generate_suggestions_by_file_input import \ GenerateSuggestionsByFileInput from module_programming_llm.prompts.split_grading_instructions_by_file import SplitGradingInstructionsByFileOutput, \ @@ -27,19 +29,22 @@ async def generate_file_summary(step: GenerateFileSummary, async def split_problem_statement(step: SplitProblemStatementByFile, input_data: SplitProblemStatementByFileInput, debug: bool, - model: ModelConfigType) -> Optional[SplitProblemStatementByFileOutput]: # type: ignore + model: ModelConfigType) -> Optional[ + SplitProblemStatementByFileOutput]: # type: ignore return await step.process(input_data, debug, model) async def split_grading_instructions(step: SplitGradingInstructionsByFile, input_data: SplitGradingInstructionsByFileInput, debug: bool, - model: ModelConfigType) -> Optional[SplitGradingInstructionsByFileOutput]: # type: ignore + model: ModelConfigType) -> Optional[ + SplitGradingInstructionsByFileOutput]: # type: ignore return await step.process(input_data, debug, model) async def generate_suggestions(step: GenerateSuggestionsByFile, input_data: GenerateSuggestionsByFileInput, debug: bool, - model: ModelConfigType) -> List[Optional[GenerateSuggestionsByFileOutput]]: # type: ignore + model: ModelConfigType) -> List[ + Optional[GenerateSuggestionsByFileOutput]]: # type: ignore return await step.process(input_data, debug, model) @@ -55,6 +60,13 @@ async def validate_suggestions(step: ValidateSuggestions, return await step.process(input_data, debug, model) +async def generate_grading_criterion(step: GenerateGradingCriterion, + input_data: GenerateGradingCriterionInput, debug: bool, + model: ModelConfigType) -> Optional[ + GenerateGradingCriterionOutput]: # type: ignore + return await step.process(input_data, debug, model) + + async def generate_feedback(exercise: Exercise, submission: Submission, is_graded: bool, module_config: Configuration) -> List[Feedback]: # type: ignore template_repo = exercise.get_template_repository() @@ -67,13 +79,26 @@ async def generate_feedback(exercise: Exercise, submission: Submission, is_grade file_summary_output = await generate_file_summary(module_config.basic_by_file_approach.generate_file_summary, generate_file_summary_input, is_debug, model) - split_grading_instructions_input = SplitGradingInstructionsByFileInput(template_repo, submission_repo, - solution_repo, exercise.id, submission.id, - exercise.grading_instructions, - exercise.grading_criteria) - split_grading_instructions_output = await split_grading_instructions( - module_config.basic_by_file_approach.split_grading_instructions_by_file, split_grading_instructions_input, - is_debug, model) + if not exercise.grading_criteria: + generate_grading_criterion_input = GenerateGradingCriterionInput(template_repo, solution_repo, exercise.id, + exercise.max_points, exercise.bonus_points, + exercise.problem_statement, + exercise.grading_instructions) + generate_grading_criterion_output = await generate_grading_criterion( + module_config.basic_by_file_approach.generate_grading_criterion, generate_grading_criterion_input, is_debug, + model) + exercise.grading_criteria = generate_grading_criterion_output.structured_grading_criterion.criteria + + split_grading_instructions_output = None + if exercise.grading_criteria is not None: + split_grading_instructions_input = SplitGradingInstructionsByFileInput(template_repo, submission_repo, + solution_repo, exercise.id, + submission.id, + exercise.grading_instructions, + exercise.grading_criteria) + split_grading_instructions_output = await split_grading_instructions( + module_config.basic_by_file_approach.split_grading_instructions_by_file, split_grading_instructions_input, + is_debug, model) split_problem_statement_input = SplitProblemStatementByFileInput(template_repo, submission_repo, solution_repo, exercise.problem_statement, exercise.id, diff --git a/modules/programming/module_programming_llm/module_programming_llm/config.py b/modules/programming/module_programming_llm/module_programming_llm/config.py index 71241f1e9..3f1f432d3 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/config.py +++ b/modules/programming/module_programming_llm/module_programming_llm/config.py @@ -7,6 +7,8 @@ from module_programming_llm.prompts import SplitProblemStatementByFile, SplitGradingInstructionsByFile, \ GenerateSuggestionsByFile, GenerateFileSummary from module_programming_llm.prompts.filter_out_solution.filter_out_solution import FilterOutSolution +from module_programming_llm.prompts.generate_grading_criterion.generate_grading_criterion import \ + GenerateGradingCriterion from module_programming_llm.prompts.validate_suggestions import ValidateSuggestions @@ -32,6 +34,7 @@ class BasicByFileApproachConfig(BasicApproachConfig, ABC): generate_file_summary: GenerateFileSummary = Field(default=GenerateFileSummary()) filter_out_solution: FilterOutSolution = Field(default=FilterOutSolution()) validate_suggestions: ValidateSuggestions = Field(default=ValidateSuggestions()) + generate_grading_criterion: GenerateGradingCriterion = Field(default=GenerateGradingCriterion()) max_number_of_files: int = Field(default=25, description="Maximum number of files. If exceeded, it will prioritize the most important ones.") tokens_before_split: int = Field(default=250, diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/__init__.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/__init__.py index 2b8f1e153..9fee9cd66 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/__init__.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/__init__.py @@ -1,11 +1,11 @@ from .generate_suggestions_by_file import GenerateSuggestionsByFile, GenerateSuggestionsByFileOutput -from .generate_suggestions_zero_shot import GenerateSuggestionsZeroShotStep from .generate_file_summary import GenerateFileSummary from .split_problem_statement_by_file import SplitProblemStatementByFile from .split_grading_instructions_by_file import SplitGradingInstructionsByFile from .validate_suggestions import ValidateSuggestions from .filter_out_solution import FilterOutSolution +from .generate_grading_criterion import GenerateGradingCriterion -__all__ = ['GenerateSuggestionsByFile', 'GenerateSuggestionsZeroShotStep', 'GenerateFileSummary', +__all__ = ['GenerateSuggestionsByFile', 'GenerateFileSummary', 'SplitGradingInstructionsByFile', 'GenerateSuggestionsByFileOutput', 'SplitProblemStatementByFile', - 'ValidateSuggestions', 'FilterOutSolution'] + 'ValidateSuggestions', 'FilterOutSolution', 'GenerateGradingCriterion'] diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py index 3ea88e9cc..c92e225ff 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py @@ -21,7 +21,7 @@ from ...helpers.models import ModelConfigType -class GenerateFileSummary(PipelineStep[GenerateFileSummaryInput, GenerateFileSummaryOutput]): +class GenerateFileSummary(PipelineStep[GenerateFileSummaryInput, Optional[GenerateFileSummaryOutput]]): """Generates concise summaries of submission files, facilitating a quicker review and understanding of the content for AI processing.""" system_message: str = Field(prompt_system_message, diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/__init__.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/__init__.py new file mode 100644 index 000000000..e1b53ccbf --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/__init__.py @@ -0,0 +1,9 @@ +from .generate_grading_criterion_output import GenerateGradingCriterionOutput +from .generate_grading_criterion_input import GenerateGradingCriterionInput +from .generate_grading_criterion import GenerateGradingCriterion + +__all__ = [ + "GenerateGradingCriterion", + "GenerateGradingCriterionInput", + "GenerateGradingCriterionOutput", +] \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion.py new file mode 100644 index 000000000..1e459cb20 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion.py @@ -0,0 +1,91 @@ +import asyncio +import json +import os +from typing import Optional, List + +from athena import emit_meta +from module_programming_llm.prompts.pipeline_step import PipelineStep +from .generate_grading_criterion_input import GenerateGradingCriterionInput +from .generate_grading_criterion_output import GenerateGradingCriterionOutput +from .prompt import system_message as prompt_system_message, human_message as prompt_human_message +from pydantic import Field +from module_programming_llm.helpers.llm_utils import ( + get_chat_prompt_with_formatting_instructions, + predict_and_parse, num_tokens_from_string, + check_prompt_length_and_omit_features_if_necessary, num_tokens_from_prompt, +) +from module_programming_llm.helpers.utils import ( + get_diff, + load_files_from_repo, + add_line_numbers, get_programming_language_file_extension +) +from ...helpers.models import ModelConfigType + + +class GenerateGradingCriterion(PipelineStep[GenerateGradingCriterionInput, Optional[GenerateGradingCriterionOutput]]): + """Generates structured grading instructions.""" + + system_message: str = Field(prompt_system_message, + description="Message for priming AI behavior and instructing it what to do.") + human_message: str = Field(prompt_human_message, + description="Message from a human. The input on which the AI is supposed to act.") + tokens_before_split: int = Field(default=2000, + description="Split the grading instructions into file-based ones after this number of tokens.") + + # pylint: disable=too-many-locals + async def process(self, input_data: GenerateGradingCriterionInput, debug: bool, model: ModelConfigType) -> Optional[GenerateGradingCriterionOutput]: # type: ignore + model = model.get_model() # type: ignore[attr-defined] + + changed_files_from_template_to_solution = get_diff( + src_repo=input_data.template_repo, + dst_repo=input_data.solution_repo, + file_path=None, + name_only=True + ).split("\n") + + changed_files = load_files_from_repo( + input_data.solution_repo, + file_filter=lambda file_path: file_path in changed_files_from_template_to_solution, + ) + + prompt = get_chat_prompt_with_formatting_instructions( + model=model, + system_message=self.system_message, + human_message=self.human_message, + pydantic_object=GenerateGradingCriterionOutput + ) + + prompt_input = { + "problem_statement": input_data.problem_statement or "No problem statement.", + "changed_files_from_template_to_solution": ", ".join(changed_files_from_template_to_solution), + "grading_instructions": input_data.grading_instructions, + "max_points": input_data.max_points, + "bonus_points": input_data.bonus_points, + "template_to_solution_diff": json.dumps(changed_files) + } + + # Return None if the prompt is too long + if num_tokens_from_prompt(prompt, prompt_input) > self.max_input_tokens: + return None + + generate_grading_criterion = await predict_and_parse( + model=model, + chat_prompt=prompt, + prompt_input=prompt_input, + pydantic_object=GenerateGradingCriterionOutput, + tags=[ + f"exercise-{input_data.exercise_id}", + "generate_grading_criterion" + ] + ) + + if debug: + emit_meta("generate_grading_criterion", { + "prompt": prompt.format(**prompt_input), + "result": generate_grading_criterion.dict() if generate_grading_criterion is not None else None + }) + + if generate_grading_criterion is None or not generate_grading_criterion.structured_grading_criterion: + return None + + return generate_grading_criterion \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion_input.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion_input.py new file mode 100644 index 000000000..1c24280a3 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion_input.py @@ -0,0 +1,32 @@ +from typing import Optional + +from git import Repo + + +class GenerateGradingCriterionInput: + """ + DTO class for top level feedback generation job + """ + template_repo: Repo + solution_repo: Repo + exercise_id: int + problem_statement: Optional[str] + grading_instructions: Optional[str] + max_points: float + bonus_points: float + + def __init__(self, + template_repo: Repo, + solution_repo: Repo, + exercise_id: int, + max_points: float, + bonus_points: float, + problem_statement: Optional[str] = None, + grading_instructions: Optional[str] = None): + self.template_repo = template_repo + self.solution_repo = solution_repo + self.exercise_id = exercise_id + self.problem_statement = problem_statement + self.grading_instructions = grading_instructions + self.max_points = max_points + self.bonus_points = bonus_points diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion_output.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion_output.py new file mode 100644 index 000000000..a4facfd56 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion_output.py @@ -0,0 +1,8 @@ +from pydantic import BaseModel, Field + +from athena import StructuredGradingCriterion + + +class GenerateGradingCriterionOutput(BaseModel): + """Collection of structured grading criterion for a problem""" + structured_grading_criterion: StructuredGradingCriterion = Field(description="Structured grading criterion") diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/prompt.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/prompt.py new file mode 100644 index 000000000..f0f493788 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/prompt.py @@ -0,0 +1,30 @@ +system_message = """\ +You are an AI tutor for programming assessment at a prestigious university. + +# Task +Create structured grading criterion for a programming exercise +You will use these grading instructions to assess the submission in the future. + +# Grading +In case a student implemented everything correctly he should receive maximal available credits. +If a student made a mistake, he has a chance to compensate with bonus points, if they are available. +Your criterion must cover these cases. + +# Style +1. Constructive, 2. Specific, 3. Balanced, 4. Clear and Concise, 5. Actionable, 6. Educational, 7. Contextual +""" + +human_message = """\ +# Problem statement +{problem_statement} + +# Grading instructions +Markdown grading instructions, if available: {grading_instructions} +Max credits: {max_points}, bonus credits: {bonus_points} + +Changed files from template to sample solution: +{changed_files_from_template_to_solution} + +# Diff between template (deletions) and sample solution(additions): +{template_to_solution_diff} +""" diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_instructions/__init__.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_instructions/__init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py index d68c3fa3d..f0c2b67a7 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py @@ -16,7 +16,7 @@ from module_programming_llm.helpers.utils import ( get_diff, load_files_from_repo, - add_line_numbers, get_programming_language_file_extension + add_line_numbers, get_programming_language_file_extension, format_grading_instructions ) from ...helpers.models import ModelConfigType @@ -109,7 +109,7 @@ async def process(self, input_data: GenerateSuggestionsByFileInput, debug: bool, ) grading_instructions = ( - input_data.grading_instructions or "" + format_grading_instructions(input_data.grading_instructions, input_data.grading_criteria) or "" if is_short_grading_instructions else file_grading_instructions.get( file_path, "No relevant grading instructions found." diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/prompt.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/prompt.py index 6de72f595..cdfd63680 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/prompt.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/prompt.py @@ -11,14 +11,14 @@ # Problem statement {problem_statement} -# Grading instructions +# Grading instructions, follow them unless absolutely necessary to deviate {grading_instructions} Max points: {max_points}, bonus points: {bonus_points} (whole assessment, not just this file) # Diff between solution (deletions) and student\'s submission (additions): {solution_to_submission_diff} -# Diff between template (deletions) and student\'s submission (additions): +# Diff between template (deletions) and student\'s submission (additions), your grading should be based on student\'s submission (additions): {template_to_submission_diff} # Summary of other solution files diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_zero_shot/__init__.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_zero_shot/__init__.py deleted file mode 100644 index a8db048a7..000000000 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_zero_shot/__init__.py +++ /dev/null @@ -1,3 +0,0 @@ -from .generate_suggestions_zero_shot import GenerateSuggestionsZeroShotStep - -__all__ = ['GenerateSuggestionsZeroShotStep'] \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_zero_shot/generate_suggestions_zero_shot.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_zero_shot/generate_suggestions_zero_shot.py deleted file mode 100644 index 94c6d01a1..000000000 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_zero_shot/generate_suggestions_zero_shot.py +++ /dev/null @@ -1,5 +0,0 @@ -from module_programming_llm.prompts.pipeline_step import PipelineStep - - -class GenerateSuggestionsZeroShotStep(PipelineStep[None, None]): - pass \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file.py index 4c1c5744e..4432e1529 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file.py @@ -22,7 +22,7 @@ class SplitGradingInstructionsByFile( - PipelineStep[SplitGradingInstructionsByFileInput, SplitGradingInstructionsByFileOutput]): + PipelineStep[SplitGradingInstructionsByFileInput, Optional[SplitGradingInstructionsByFileOutput]]): """Splits grading instructions of a programming exercise to match with solution files""" system_message: str = Field(prompt_system_message, diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py index 2074eb9ed..63dad1600 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py @@ -15,7 +15,7 @@ from ...helpers.utils import get_diff -class SplitProblemStatementByFile(PipelineStep[SplitProblemStatementByFileInput, SplitProblemStatementByFileOutput]): +class SplitProblemStatementByFile(PipelineStep[SplitProblemStatementByFileInput, Optional[SplitProblemStatementByFileOutput]]): """Splits problem statement of a programming exercise to match with solution files""" system_message: str = Field(prompt_system_message, From c6938de2b33f3a9a83f984358c02c058c09f126e Mon Sep 17 00:00:00 2001 From: Dmytro Polityka Date: Mon, 7 Oct 2024 17:34:51 +0200 Subject: [PATCH 17/21] fine tune the prompt --- .../approaches/basic_by_file_approach.py | 15 ++++++--------- .../generate_grading_criterion.py | 1 - .../prompts/generate_grading_criterion/prompt.py | 4 ++-- .../generate_suggestions_by_file/prompt.py | 9 ++++++--- 4 files changed, 14 insertions(+), 15 deletions(-) diff --git a/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py b/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py index 0d70b267d..7775d9ac1 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py +++ b/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py @@ -29,22 +29,19 @@ async def generate_file_summary(step: GenerateFileSummary, async def split_problem_statement(step: SplitProblemStatementByFile, input_data: SplitProblemStatementByFileInput, debug: bool, - model: ModelConfigType) -> Optional[ - SplitProblemStatementByFileOutput]: # type: ignore + model: ModelConfigType) -> Optional[SplitProblemStatementByFileOutput]: # type: ignore return await step.process(input_data, debug, model) async def split_grading_instructions(step: SplitGradingInstructionsByFile, input_data: SplitGradingInstructionsByFileInput, debug: bool, - model: ModelConfigType) -> Optional[ - SplitGradingInstructionsByFileOutput]: # type: ignore + model: ModelConfigType) -> Optional[SplitGradingInstructionsByFileOutput]: # type: ignore return await step.process(input_data, debug, model) async def generate_suggestions(step: GenerateSuggestionsByFile, input_data: GenerateSuggestionsByFileInput, debug: bool, - model: ModelConfigType) -> List[ - Optional[GenerateSuggestionsByFileOutput]]: # type: ignore + model: ModelConfigType) -> List[Optional[GenerateSuggestionsByFileOutput]]: # type: ignore return await step.process(input_data, debug, model) @@ -62,8 +59,7 @@ async def validate_suggestions(step: ValidateSuggestions, async def generate_grading_criterion(step: GenerateGradingCriterion, input_data: GenerateGradingCriterionInput, debug: bool, - model: ModelConfigType) -> Optional[ - GenerateGradingCriterionOutput]: # type: ignore + model: ModelConfigType) -> Optional[GenerateGradingCriterionOutput]: # type: ignore return await step.process(input_data, debug, model) @@ -87,7 +83,8 @@ async def generate_feedback(exercise: Exercise, submission: Submission, is_grade generate_grading_criterion_output = await generate_grading_criterion( module_config.basic_by_file_approach.generate_grading_criterion, generate_grading_criterion_input, is_debug, model) - exercise.grading_criteria = generate_grading_criterion_output.structured_grading_criterion.criteria + if generate_grading_criterion_output is not None: + exercise.grading_criteria = generate_grading_criterion_output.structured_grading_criterion.criteria split_grading_instructions_output = None if exercise.grading_criteria is not None: diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion.py index 1e459cb20..8563fc450 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion.py @@ -32,7 +32,6 @@ class GenerateGradingCriterion(PipelineStep[GenerateGradingCriterionInput, Optio tokens_before_split: int = Field(default=2000, description="Split the grading instructions into file-based ones after this number of tokens.") - # pylint: disable=too-many-locals async def process(self, input_data: GenerateGradingCriterionInput, debug: bool, model: ModelConfigType) -> Optional[GenerateGradingCriterionOutput]: # type: ignore model = model.get_model() # type: ignore[attr-defined] diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/prompt.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/prompt.py index f0f493788..f21e20987 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/prompt.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/prompt.py @@ -6,7 +6,7 @@ You will use these grading instructions to assess the submission in the future. # Grading -In case a student implemented everything correctly he should receive maximal available credits. +In case a student implemented everything correctly he should receive maximal available points(credits). If a student made a mistake, he has a chance to compensate with bonus points, if they are available. Your criterion must cover these cases. @@ -20,7 +20,7 @@ # Grading instructions Markdown grading instructions, if available: {grading_instructions} -Max credits: {max_points}, bonus credits: {bonus_points} +Max points: {max_points}, bonus points: {bonus_points} Changed files from template to sample solution: {changed_files_from_template_to_solution} diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/prompt.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/prompt.py index cdfd63680..1570129eb 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/prompt.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/prompt.py @@ -18,9 +18,6 @@ # Diff between solution (deletions) and student\'s submission (additions): {solution_to_submission_diff} -# Diff between template (deletions) and student\'s submission (additions), your grading should be based on student\'s submission (additions): -{template_to_submission_diff} - # Summary of other solution files {solution_summary} """ @@ -30,5 +27,11 @@ \"\"\" {submission_file} \"\"\"\ + +Diff between template (deletions) and student\'s submission (additions): +{template_to_submission_diff} + +Do not give points for code that was not written by students! + Path: {file_path} """ From f3f38f3a2e9057a78f6c6440243d4cf9937763ee Mon Sep 17 00:00:00 2001 From: Dmytro Polityka Date: Mon, 7 Oct 2024 18:23:47 +0200 Subject: [PATCH 18/21] fix minor issues --- .../prompts/validate_suggestions/prompt.py | 7 ++++--- .../prompts/validate_suggestions/validate_suggestions.py | 2 +- 2 files changed, 5 insertions(+), 4 deletions(-) diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/prompt.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/prompt.py index c459fe796..8f74f9e82 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/prompt.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/prompt.py @@ -16,9 +16,6 @@ # Diff between solution (deletions) and student\'s submission (additions): {solution_to_submission_diff} -# Diff between template (deletions) and student\'s submission (additions): -{template_to_submission_diff} - # Summary of other solution files {solution_summary} """ @@ -34,4 +31,8 @@ \"\"\" {submission_file} \"\"\"\ + +# Diff between template (deletions) and student\'s submission (additions): +{template_to_submission_diff} +Only student\'s changes should be taken into account. """ diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions.py index d4d9a3c5a..a6fdf8f02 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions.py @@ -244,7 +244,7 @@ async def process( f"exercise-{input_data.exercise_id}", f"submission-{input_data.submission_id}", f"file-{prompt_input['file_path']}", - "filter-out-solution", + "validate-suggestions", ], ) for prompt_input in prompt_inputs From 8b7643699293c5e25f140a7ea2b0ad07bae5d507 Mon Sep 17 00:00:00 2001 From: Dmytro Polityka Date: Thu, 17 Oct 2024 01:04:49 +0200 Subject: [PATCH 19/21] prepare live demo --- .../approaches/basic_by_file_approach.py | 36 +- .../module_programming_llm/config.py | 2 + .../helpers/models/openai.py | 2 +- .../helpers/web_search.py | 86 + .../generate_grading_criterion.py | 18 +- .../generate_suggestions_by_file/__init__.py | 3 +- .../generate_suggestions_by_file.py | 4 +- .../generate_suggestions_by_file_input.py | 3 + .../generate_suggestions_by_file/prompt.py | 10 +- .../prompts/pipeline_step.py | 2 +- .../prompts/rag/__init__.py | 5 + .../prompts/rag/prompt.py | 23 + .../module_programming_llm/prompts/rag/rag.py | 80 + .../prompts/rag/rag_input.py | 23 + .../prompts/rag/rag_output.py | 8 + .../prompts/validate_suggestions/prompt.py | 7 +- .../validate_suggestions.py | 4 +- .../validate_suggestions_input.py | 5 +- .../module_programming_llm/poetry.lock | 3687 ++++++++++++++--- .../module_programming_llm/pyproject.toml | 13 +- 20 files changed, 3479 insertions(+), 542 deletions(-) create mode 100644 modules/programming/module_programming_llm/module_programming_llm/helpers/web_search.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/rag/__init__.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/rag/prompt.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/rag/rag.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/rag/rag_input.py create mode 100644 modules/programming/module_programming_llm/module_programming_llm/prompts/rag/rag_output.py diff --git a/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py b/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py index 7775d9ac1..689bd5fc4 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py +++ b/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py @@ -2,6 +2,7 @@ from athena.programming import Submission, Exercise, Feedback from module_programming_llm.config import Configuration +from module_programming_llm.helpers.web_search import bulk_search from module_programming_llm.helpers.models import ModelConfigType from module_programming_llm.prompts import GenerateFileSummary, SplitProblemStatementByFile, \ SplitGradingInstructionsByFile, GenerateSuggestionsByFile, GenerateSuggestionsByFileOutput @@ -13,6 +14,7 @@ GenerateGradingCriterion, GenerateGradingCriterionOutput, GenerateGradingCriterionInput from module_programming_llm.prompts.generate_suggestions_by_file.generate_suggestions_by_file_input import \ GenerateSuggestionsByFileInput +from module_programming_llm.prompts.rag import RAGInput, RAG, RAGOutput from module_programming_llm.prompts.split_grading_instructions_by_file import SplitGradingInstructionsByFileOutput, \ SplitGradingInstructionsByFileInput from module_programming_llm.prompts.split_problem_statement_by_file import SplitProblemStatementByFileOutput, \ @@ -62,6 +64,11 @@ async def generate_grading_criterion(step: GenerateGradingCriterion, model: ModelConfigType) -> Optional[GenerateGradingCriterionOutput]: # type: ignore return await step.process(input_data, debug, model) +async def generate_rag_queries(step: RAG, + input_data: RAGInput, debug: bool, + model: ModelConfigType) -> Optional[RAGOutput]: # type: ignore + return await step.process(input_data, debug, model) + async def generate_feedback(exercise: Exercise, submission: Submission, is_graded: bool, module_config: Configuration) -> List[Feedback]: # type: ignore @@ -71,6 +78,13 @@ async def generate_feedback(exercise: Exercise, submission: Submission, is_grade is_debug = module_config.debug model = module_config.basic_by_file_approach.model +# rag_query_input = RAGInput(template_repo, solution_repo, exercise.id, exercise.problem_statement) +# rag_query_output = await generate_rag_queries(module_config.basic_by_file_approach.rag_requests, rag_query_input, module_config.debug, model) + +# rag_result = "" if rag_query_output is None else bulk_search(rag_query_output.rag_queries, model) + + rag_result = "" + generate_file_summary_input = GenerateFileSummaryInput(template_repo, submission_repo, exercise.id, submission.id) file_summary_output = await generate_file_summary(module_config.basic_by_file_approach.generate_file_summary, generate_file_summary_input, is_debug, model) @@ -109,6 +123,7 @@ async def generate_feedback(exercise: Exercise, submission: Submission, is_grade submission.id, exercise.max_points, exercise.bonus_points, exercise.programming_language, file_summary_output.describe_solution_summary() if file_summary_output else "", + rag_result, split_grading_instructions_output, split_problem_statement_output, exercise.grading_criteria, exercise.problem_statement, @@ -123,16 +138,17 @@ async def generate_feedback(exercise: Exercise, submission: Submission, is_grade output = await filter_out_solutions(module_config.basic_by_file_approach.filter_out_solution, filter_out_solution_input, is_debug, model) - validate_suggestions_input = ValidateSuggestionsInput(solution_repo, template_repo, submission_repo, - split_problem_statement_output, exercise.problem_statement, - exercise.id, submission.id, output, - split_grading_instructions_output, exercise.grading_criteria, - exercise.grading_instructions, - file_summary_output.describe_solution_summary() if file_summary_output else "", - exercise.max_points, exercise.bonus_points, - exercise.programming_language) - output = await validate_suggestions( - module_config.basic_by_file_approach.validate_suggestions, validate_suggestions_input, is_debug, model) + # validate_suggestions_input = ValidateSuggestionsInput(solution_repo, template_repo, submission_repo, + # split_problem_statement_output, exercise.problem_statement, + # exercise.id, submission.id, output, + # split_grading_instructions_output, exercise.grading_criteria, + # exercise.grading_instructions, + # file_summary_output.describe_solution_summary() if file_summary_output else "", + # exercise.max_points, exercise.bonus_points, + # exercise.programming_language, + # rag_result) + # output = await validate_suggestions( + # module_config.basic_by_file_approach.validate_suggestions, validate_suggestions_input, is_debug, model) grading_instruction_ids = set( grading_instruction.id diff --git a/modules/programming/module_programming_llm/module_programming_llm/config.py b/modules/programming/module_programming_llm/module_programming_llm/config.py index 3f1f432d3..850feac58 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/config.py +++ b/modules/programming/module_programming_llm/module_programming_llm/config.py @@ -9,6 +9,7 @@ from module_programming_llm.prompts.filter_out_solution.filter_out_solution import FilterOutSolution from module_programming_llm.prompts.generate_grading_criterion.generate_grading_criterion import \ GenerateGradingCriterion +from module_programming_llm.prompts.rag import RAG from module_programming_llm.prompts.validate_suggestions import ValidateSuggestions @@ -39,6 +40,7 @@ class BasicByFileApproachConfig(BasicApproachConfig, ABC): description="Maximum number of files. If exceeded, it will prioritize the most important ones.") tokens_before_split: int = Field(default=250, description="Split the grading instructions into file-based ones after this number of tokens.") + rag_requests: RAG = Field(default=RAG()) # class ZeroShotApproachConfig(BasicApproachConfig, ABC): diff --git a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/openai.py b/modules/programming/module_programming_llm/module_programming_llm/helpers/models/openai.py index cb9d889cc..1a336eded 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/helpers/models/openai.py +++ b/modules/programming/module_programming_llm/module_programming_llm/helpers/models/openai.py @@ -6,7 +6,7 @@ from enum import Enum from pydantic import Field, field_validator, PositiveInt from langchain.base_language import BaseLanguageModel -from langchain_community.chat_models import ChatOpenAI +from langchain_openai.chat_models import ChatOpenAI from langchain_openai import AzureChatOpenAI from athena.logger import logger diff --git a/modules/programming/module_programming_llm/module_programming_llm/helpers/web_search.py b/modules/programming/module_programming_llm/module_programming_llm/helpers/web_search.py new file mode 100644 index 000000000..9f9658425 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/helpers/web_search.py @@ -0,0 +1,86 @@ +from typing import Sequence, List + +from langchain.chains.qa_with_sources.retrieval import RetrievalQAWithSourcesChain +from langchain_community.document_loaders import AsyncChromiumLoader +from langchain_community.document_transformers import BeautifulSoupTransformer +from duckduckgo_search import DDGS +import re + +from langchain_community.retrievers import WebResearchRetriever +from langchain_community.utilities import GoogleSearchAPIWrapper +from langchain_community.vectorstores import Chroma +from langchain_core.documents import Document +from langchain_core.tools import Tool +from langchain_openai import OpenAIEmbeddings + +from module_programming_llm.helpers.models import ModelConfigType + + +def bulk_search(queries: Sequence[str], model: ModelConfigType) -> List[str]: + result = [] + for query in queries: + result.append(answer_query(query, model)) + return result +# +# +# def search(query: str) -> List[str]: +# results = DDGS().text(query, max_results=5) +# urls = [] +# for result in results: +# url = result['href'] +# urls.append(url) +# +# docs = get_page(urls) +# +# content = [] +# for doc in docs: +# page_text = re.sub("\n\n+", "\n", doc.page_content) +# text = truncate(page_text) +# content.append(text) +# +# return content +# +# +# def get_page(urls: List[str]) -> Sequence[Document]: +# loader = AsyncChromiumLoader(urls, headless=True) +# html = loader.load() +# +# bs_transformer = BeautifulSoupTransformer() +# docs_transformed = bs_transformer.transform_documents(html, tags_to_extract=["p"], remove_unwanted_tags=["a"]) +# +# return docs_transformed +# +# +# def truncate(text) -> str: +# words = text.split() +# truncated = " ".join(words[:1000]) +# +# return truncated + +def answer_query(query, model: ModelConfigType): + model = model.get_model() # type: ignore[attr-defined] + vectorstore = Chroma( + embedding_function=OpenAIEmbeddings(), persist_directory="./chroma_db_oai" + ) + + # Search + search = GoogleSearchAPIWrapper() + + # # Initialize + web_search_retriever = WebResearchRetriever.from_llm( + vectorstore=vectorstore, llm=model, search=search, allow_dangerous_requests=True + ) + qa_chain = RetrievalQAWithSourcesChain.from_chain_type( + model, retriever=web_search_retriever + ) + result = qa_chain({"question": query}) + + search = GoogleSearchAPIWrapper() + + tool = Tool( + name="google_search", + description="Search Google for recent results.", + func=search.run, + ) + + return tool.run(query) diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion.py index 8563fc450..c6f06bd27 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion.py @@ -42,10 +42,21 @@ async def process(self, input_data: GenerateGradingCriterionInput, debug: bool, name_only=True ).split("\n") - changed_files = load_files_from_repo( - input_data.solution_repo, - file_filter=lambda file_path: file_path in changed_files_from_template_to_solution, + all_changed_files = load_files_from_repo( + input_data.solution_repo ) + changed_files = {} + changed_files_content = "" + for file in changed_files_from_template_to_solution: + if not file.endswith('.pbxproj'): + changed_files[file] = get_diff( + src_repo=input_data.template_repo, + dst_repo=input_data.solution_repo, + src_prefix="template", + dst_prefix="solution", + file_path=file, + ) + changed_files_content += "\n" + file + ":" + changed_files[file] prompt = get_chat_prompt_with_formatting_instructions( model=model, @@ -56,7 +67,6 @@ async def process(self, input_data: GenerateGradingCriterionInput, debug: bool, prompt_input = { "problem_statement": input_data.problem_statement or "No problem statement.", - "changed_files_from_template_to_solution": ", ".join(changed_files_from_template_to_solution), "grading_instructions": input_data.grading_instructions, "max_points": input_data.max_points, "bonus_points": input_data.bonus_points, diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/__init__.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/__init__.py index 77a133f5f..84add8962 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/__init__.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/__init__.py @@ -1,4 +1,5 @@ from .generate_suggestions_by_file import GenerateSuggestionsByFile +from .generate_suggestions_by_file_input import GenerateSuggestionsByFileInput from .generate_suggestions_by_file_output import GenerateSuggestionsByFileOutput -__all__ = ['GenerateSuggestionsByFile', 'GenerateSuggestionsByFileOutput'] \ No newline at end of file +__all__ = ['GenerateSuggestionsByFile', 'GenerateSuggestionsByFileOutput', 'GenerateSuggestionsByFileInput'] \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py index f0c2b67a7..e0001cf24 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py @@ -153,12 +153,12 @@ async def process(self, input_data: GenerateSuggestionsByFileInput, debug: bool, "submission_file": file_content, "max_points": input_data.max_points, "bonus_points": input_data.bonus_points, - "solution_to_submission_diff": solution_to_submission_diff, "template_to_submission_diff": template_to_submission_diff, "template_to_solution_diff": template_to_solution_diff, "grading_instructions": grading_instructions, "problem_statement": problem_statement, - "solution_summary": input_data.solution_summary + "solution_summary": input_data.solution_summary, + "rag_data": input_data.rag_data } ) diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_input.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_input.py index 76ab3e0e5..7a20c5507 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_input.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file_input.py @@ -25,6 +25,7 @@ class GenerateSuggestionsByFileInput: bonus_points: float programming_language: str solution_summary: str + rag_data: List[str] def __init__(self, template_repo: Repo, @@ -36,6 +37,7 @@ def __init__(self, bonus_points: float, programming_language: str, solution_summary: str, + rag_data: List[str], grading_instructions_by_file: Optional[SplitGradingInstructionsByFileOutput] = None, problem_statement_by_file: Optional[SplitProblemStatementByFileOutput] = None, grading_criteria: Optional[List[GradingCriterion]] = None, @@ -55,3 +57,4 @@ def __init__(self, self.bonus_points = bonus_points self.programming_language = programming_language self.solution_summary = solution_summary + self.rag_data = rag_data diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/prompt.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/prompt.py index 1570129eb..7a02b6b9e 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/prompt.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/prompt.py @@ -3,7 +3,8 @@ # Task Create graded feedback suggestions for a student\'s programming submission that a human tutor would accept. \ -Meaning, the feedback you provide should be appliable to the submission with little to no modification. +Meaning, the feedback you provide should be applicable to the submission with little to no modification. +Give points for correct answers. Subtract points for wrong answers. Give 0 points for neutral answers. # Style 1. Constructive, 2. Specific, 3. Balanced, 4. Clear and Concise, 5. Actionable, 6. Educational, 7. Contextual @@ -15,11 +16,14 @@ {grading_instructions} Max points: {max_points}, bonus points: {bonus_points} (whole assessment, not just this file) -# Diff between solution (deletions) and student\'s submission (additions): -{solution_to_submission_diff} +# Diff between template (deletions) and solution (additions): +{template_to_solution_diff} # Summary of other solution files {solution_summary} + +# RAG data +{rag_data} """ human_message = """\ diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/pipeline_step.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/pipeline_step.py index 1411c2fef..6905daa49 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/pipeline_step.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/pipeline_step.py @@ -10,7 +10,7 @@ class PipelineStep(BaseModel, Generic[TInput, TOutput]): - max_input_tokens: int = Field(default=3000, description="Maximum number of tokens in the input prompt.") + max_input_tokens: int = Field(default=10000, description="Maximum number of tokens in the input prompt.") @abstractmethod async def process(self, input_data: TInput, debug: bool, model: ModelConfigType) -> Optional[TOutput]: # type: ignore diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/rag/__init__.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/rag/__init__.py new file mode 100644 index 000000000..eea7b8c9d --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/rag/__init__.py @@ -0,0 +1,5 @@ +from .rag import RAG +from .rag_input import RAGInput +from .rag_output import RAGOutput + +__all__ = ['RAG', 'RAGInput', 'RAGOutput'] \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/rag/prompt.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/rag/prompt.py new file mode 100644 index 000000000..b73fbc5d2 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/rag/prompt.py @@ -0,0 +1,23 @@ +system_message = """\ +You are an AI tutor for programming assessment at a prestigious university. + +# Task +Identify, if you understand the problem and surrounding information completely. +In case you do not understand something, formulate up to 2 specific questions that will help you understand the problem statement better. + +# Style +1. Constructive, 2. Specific, 3. Balanced, 4. Clear and Concise, 5. Contextual + +For testing purposes, assume you do not know anything about sorting +""" + +human_message = """\ +# Problem statement +{problem_statement} + +Changed files from template to sample solution: +{changed_files_from_template_to_solution} + +# Diff between template (deletions) and sample solution(additions): +{template_to_solution_diff} +""" diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/rag/rag.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/rag/rag.py new file mode 100644 index 000000000..25ad5ebe3 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/rag/rag.py @@ -0,0 +1,80 @@ +import json +from typing import Optional + +from athena import emit_meta +from module_programming_llm.prompts.pipeline_step import PipelineStep +from .rag_input import RAGInput +from .rag_output import RAGOutput +from .prompt import system_message as prompt_system_message, human_message as prompt_human_message +from pydantic import Field +from module_programming_llm.helpers.llm_utils import ( + get_chat_prompt_with_formatting_instructions, + predict_and_parse, + num_tokens_from_prompt, +) +from module_programming_llm.helpers.utils import ( + get_diff, + load_files_from_repo, +) +from ...helpers.models import ModelConfigType + + +class RAG(PipelineStep[RAGInput, Optional[RAGOutput]]): + """Generates RAG queries.""" + + system_message: str = Field(prompt_system_message, + description="Message for priming AI behavior and instructing it what to do.") + human_message: str = Field(prompt_human_message, + description="Message from a human. The input on which the AI is supposed to act.") + + async def process(self, input_data: RAGInput, debug: bool, model: ModelConfigType) -> Optional[ + RAGOutput]: # type: ignore + model = model.get_model() # type: ignore[attr-defined] + + changed_files_from_template_to_solution = get_diff( + src_repo=input_data.template_repo, + dst_repo=input_data.solution_repo, + file_path=None, + name_only=True + ).split("\n") + + changed_files = load_files_from_repo( + input_data.solution_repo, + file_filter=lambda file_path: file_path in changed_files_from_template_to_solution, + ) + + prompt = get_chat_prompt_with_formatting_instructions( + model=model, + system_message=self.system_message, + human_message=self.human_message, + pydantic_object=RAGOutput + ) + + prompt_input = { + "problem_statement": input_data.problem_statement or "No problem statement.", + "changed_files_from_template_to_solution": ", ".join(changed_files_from_template_to_solution), + "template_to_solution_diff": json.dumps(changed_files) + } + + # Return None if the prompt is too long + if num_tokens_from_prompt(prompt, prompt_input) > self.max_input_tokens: + return None + + generate_rag_queries = await predict_and_parse( + model=model, + chat_prompt=prompt, + prompt_input=prompt_input, + pydantic_object=RAGOutput, + tags=[ + f"exercise-{input_data.exercise_id}", + "generate_rag_requests" + ] + ) + + if debug: + emit_meta("generate_rag_requests", { + "prompt": prompt.format(**prompt_input), + "result": generate_rag_queries.dict() if generate_rag_queries is not None else None + }) + + return generate_rag_queries diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/rag/rag_input.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/rag/rag_input.py new file mode 100644 index 000000000..89708b2e0 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/rag/rag_input.py @@ -0,0 +1,23 @@ +from typing import Optional + +from git import Repo + + +class RAGInput: + """ + DTO class for top level feedback generation job + """ + template_repo: Repo + solution_repo: Repo + exercise_id: int + problem_statement: Optional[str] + + def __init__(self, + template_repo: Repo, + solution_repo: Repo, + exercise_id: int, + problem_statement: Optional[str] = None): + self.template_repo = template_repo + self.solution_repo = solution_repo + self.exercise_id = exercise_id + self.problem_statement = problem_statement diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/rag/rag_output.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/rag/rag_output.py new file mode 100644 index 000000000..19d5dd5c0 --- /dev/null +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/rag/rag_output.py @@ -0,0 +1,8 @@ +from typing import Sequence + +from pydantic import BaseModel, Field + + +class RAGOutput(BaseModel): + """Collection of feedbacks making up an assessment for a file""" + rag_queries: Sequence[str] = Field(description="A sequence of search queries for a RAG web-search provider", default=[]) diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/prompt.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/prompt.py index 8f74f9e82..486a1b9d6 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/prompt.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/prompt.py @@ -13,11 +13,14 @@ {grading_instructions} Max points: {max_points}, bonus points: {bonus_points} (whole assessment, not just this file) -# Diff between solution (deletions) and student\'s submission (additions): -{solution_to_submission_diff} +# Diff between template (deletions) and solution (additions): +{template_to_solution_diff} # Summary of other solution files {solution_summary} + +# RAG data +{rag_data} """ human_message = """\ diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions.py index a6fdf8f02..0cd905d50 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions.py @@ -167,14 +167,14 @@ async def process( "submission_file": file_content, "max_points": input_data.max_points, "bonus_points": input_data.bonus_points, - "solution_to_submission_diff": solution_to_submission_diff, "template_to_submission_diff": template_to_submission_diff, "template_to_solution_diff": template_to_solution_diff, "grading_instructions": grading_instructions, "problem_statement": problem_statement, "solution_summary": input_data.solution_summary, "feedback_suggestions": json.dumps( - [ob.__dict__ for ob in feedback_suggestions_by_file.get(file_path) or []]) + [ob.__dict__ for ob in feedback_suggestions_by_file.get(file_path) or []]), + "rag_data": input_data.rag_data } ) diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions_input.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions_input.py index 032f18e4d..14ff42cc9 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions_input.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions_input.py @@ -27,6 +27,7 @@ class ValidateSuggestionsInput: max_points: float bonus_points: float programming_language: str + rag_data: List[str] def __init__( self, @@ -44,7 +45,8 @@ def __init__( solution_summary: str, max_points: float, bonus_points: float, - programming_language: str + programming_language: str, + rag_data: List[str] ): self.solution_repo = solution_repo self.template_repo = template_repo @@ -61,3 +63,4 @@ def __init__( self.max_points = max_points self.bonus_points = bonus_points self.programming_language = programming_language + self.rag_data = rag_data diff --git a/modules/programming/module_programming_llm/poetry.lock b/modules/programming/module_programming_llm/poetry.lock index de24a8d3c..90c653911 100644 --- a/modules/programming/module_programming_llm/poetry.lock +++ b/modules/programming/module_programming_llm/poetry.lock @@ -13,102 +13,102 @@ files = [ [[package]] name = "aiohttp" -version = "3.10.8" +version = "3.10.10" description = "Async http client/server framework (asyncio)" optional = false python-versions = ">=3.8" files = [ - {file = 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(>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] +enabler = ["pytest-enabler (>=2.2)"] +test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"] +type = ["pytest-mypy"] [metadata] lock-version = "2.0" python-versions = "3.11.*" -content-hash = "b327d790210ed0f9bea6bea3a09fee6d3523442f5846273d1ff1555d6aeae9ac" +content-hash = "0450d91024422faab2b84bc4d77a4b956650f13c7a66f3bf5b82459b2c3ae58e" diff --git a/modules/programming/module_programming_llm/pyproject.toml b/modules/programming/module_programming_llm/pyproject.toml index 7a68bc5f8..3fa19b2fa 100644 --- a/modules/programming/module_programming_llm/pyproject.toml +++ b/modules/programming/module_programming_llm/pyproject.toml @@ -21,9 +21,20 @@ promptlayer = "^0.1.85" python-dotenv = "^1.0.0" nltk = "^3.8.1" replicate = "^0.11.0" +chromadb = "0.5.13" +streamlit= "1.25.0" +html2text = "2020.1.16" +google-api-core = "2.11.1" +google-api-python-client = "2.95.0" +google-auth = "2.22.0" +google-auth-httplib2 = "0.1.0" +googleapis-common-protos = "1.59.1" +faiss-cpu = {version = "^1.7.0", platform = "posix"} +faiss-gpu = {version = "^1.7.1", platform = "posix"} +bs4 = "0.0.2" [tool.poetry.group.dev.dependencies] -types-requests = "^2.31.0.8" + pydantic = "2.7.4" prospector = "^1.10.2" From 132214c00bdc30192036c7d2cec18db7f9626105 Mon Sep 17 00:00:00 2001 From: Dmytro Polityka Date: Thu, 17 Oct 2024 01:06:09 +0200 Subject: [PATCH 20/21] adjust grading criterion prompt --- .../prompts/generate_grading_criterion/prompt.py | 7 ++----- 1 file changed, 2 insertions(+), 5 deletions(-) diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/prompt.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/prompt.py index f21e20987..762c0a64e 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/prompt.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/prompt.py @@ -2,8 +2,8 @@ You are an AI tutor for programming assessment at a prestigious university. # Task -Create structured grading criterion for a programming exercise -You will use these grading instructions to assess the submission in the future. +Create structured grading criterion for a programming exercise for everything that is required by the problem statement. +Include criteria for syntactically correct programs. # Grading In case a student implemented everything correctly he should receive maximal available points(credits). @@ -22,9 +22,6 @@ Markdown grading instructions, if available: {grading_instructions} Max points: {max_points}, bonus points: {bonus_points} -Changed files from template to sample solution: -{changed_files_from_template_to_solution} - # Diff between template (deletions) and sample solution(additions): {template_to_solution_diff} """ From 968c6a77c2f3b7703d6b5c10fb33d2198e7a409e Mon Sep 17 00:00:00 2001 From: Dmytro Polityka Date: Tue, 29 Oct 2024 09:16:17 +0100 Subject: [PATCH 21/21] rebase onto develop --- llm_core/llm_core/models/model_config.py | 4 +- llm_core/llm_core/utils/llm_utils.py | 5 +- llm_core/llm_core/utils/predict_and_parse.py | 55 +- .../approaches/basic_by_file_approach.py | 3 +- .../module_programming_llm/config.py | 2 +- .../helpers/web_search.py | 43 +- .../filter_out_solution.py | 8 +- .../generate_file_summary.py | 7 +- .../generate_grading_criterion.py | 7 +- .../generate_suggestions_by_file.py | 7 +- .../prompts/pipeline_step.py | 2 +- .../module_programming_llm/prompts/rag/rag.py | 6 +- .../split_grading_instructions_by_file.py | 7 +- .../split_problem_statement_by_file.py | 7 +- .../validate_suggestions.py | 7 +- .../module_programming_llm/poetry.lock | 3251 +++-------------- .../module_programming_llm/pyproject.toml | 12 - 17 files changed, 516 insertions(+), 2917 deletions(-) diff --git a/llm_core/llm_core/models/model_config.py b/llm_core/llm_core/models/model_config.py index f433ab587..5bb988390 100644 --- a/llm_core/llm_core/models/model_config.py +++ b/llm_core/llm_core/models/model_config.py @@ -4,7 +4,9 @@ class ModelConfig(BaseModel, ABC): - + class Config: + protected_namespaces = () + @abstractmethod def get_model(self) -> BaseLanguageModel: pass diff --git a/llm_core/llm_core/utils/llm_utils.py b/llm_core/llm_core/utils/llm_utils.py index d2f432f85..7df06c43b 100644 --- a/llm_core/llm_core/utils/llm_utils.py +++ b/llm_core/llm_core/utils/llm_utils.py @@ -1,7 +1,7 @@ from typing import Type, TypeVar, List from pydantic import BaseModel import tiktoken -from langchain.chat_models import ChatOpenAI +from langchain_openai import ChatOpenAI from langchain.base_language import BaseLanguageModel from langchain.prompts import ( ChatPromptTemplate, @@ -106,5 +106,6 @@ def get_chat_prompt_with_formatting_instructions( system_message_prompt = SystemMessagePromptTemplate.from_template(system_message + "\n{format_instructions}") system_message_prompt.prompt.partial_variables = {"format_instructions": output_parser.get_format_instructions()} system_message_prompt.prompt.input_variables.remove("format_instructions") - human_message_prompt = HumanMessagePromptTemplate.from_template(human_message + "\n\nJSON response following the provided schema:") + 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 diff --git a/llm_core/llm_core/utils/predict_and_parse.py b/llm_core/llm_core/utils/predict_and_parse.py index d73748bdf..0caecd507 100644 --- a/llm_core/llm_core/utils/predict_and_parse.py +++ b/llm_core/llm_core/utils/predict_and_parse.py @@ -1,17 +1,24 @@ from typing import Optional, Type, TypeVar, List + +from langchain_core.exceptions import OutputParserException from langchain_core.language_models import BaseLanguageModel +from langchain_core.output_parsers import PydanticOutputParser +from langchain_core.output_parsers.openai_functions import JsonOutputFunctionsParser from langchain_core.prompts import ChatPromptTemplate from langchain_core.pydantic_v1 import BaseModel, ValidationError -from langchain_core.runnables import RunnableSequence +from langchain_core.tracers import langchain +from langchain_core.utils.function_calling import convert_to_openai_function from athena import get_experiment_environment +from athena.logger import logger +from .llm_utils import supports_function_calling T = TypeVar("T", bound=BaseModel) async def predict_and_parse( - model: BaseLanguageModel, - chat_prompt: ChatPromptTemplate, - prompt_input: dict, - pydantic_object: Type[T], + model: BaseLanguageModel, + chat_prompt: ChatPromptTemplate, + prompt_input: dict, + pydantic_object: Type[T], tags: Optional[List[str]] ) -> Optional[T]: """Predicts an LLM completion using the model and parses the output using the provided Pydantic model @@ -26,6 +33,8 @@ async def predict_and_parse( Returns: Optional[T]: Parsed output, or None if it could not be parsed """ + langchain.debug = True + experiment = get_experiment_environment() tags = tags or [] @@ -36,13 +45,33 @@ 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") - chain = RunnableSequence( - chat_prompt, - structured_output_llm - ) + if supports_function_calling(model): + openai_functions = [convert_to_openai_function(pydantic_object)] + + runnable = chat_prompt | model.bind(functions=openai_functions).with_retry( + retry_if_exception_type=(ValueError, OutputParserException), + wait_exponential_jitter=True, + stop_after_attempt=3, + ) | JsonOutputFunctionsParser() + + try: + output_dict = await runnable.ainvoke(prompt_input) + return pydantic_object.parse_obj(output_dict) + except (OutputParserException, ValidationError) as e: + logger.error("Exception type: %s, Message: %s", type(e).__name__, e) + return None + + output_parser = PydanticOutputParser(pydantic_object=pydantic_object) + + runnable = chat_prompt | model.with_retry( + retry_if_exception_type=(ValueError, OutputParserException), + wait_exponential_jitter=True, + stop_after_attempt=3, + ) | output_parser 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 + output_dict = await runnable.ainvoke(prompt_input) + return pydantic_object.parse_obj(output_dict) + except (OutputParserException, ValidationError) as e: + logger.error("Exception type: %s, Message: %s", type(e).__name__, e) + return None \ No newline at end of file diff --git a/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py b/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py index 689bd5fc4..50f15befb 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py +++ b/modules/programming/module_programming_llm/module_programming_llm/approaches/basic_by_file_approach.py @@ -2,8 +2,7 @@ from athena.programming import Submission, Exercise, Feedback from module_programming_llm.config import Configuration -from module_programming_llm.helpers.web_search import bulk_search -from module_programming_llm.helpers.models import ModelConfigType +from llm_core.models import ModelConfigType from module_programming_llm.prompts import GenerateFileSummary, SplitProblemStatementByFile, \ SplitGradingInstructionsByFile, GenerateSuggestionsByFile, GenerateSuggestionsByFileOutput from module_programming_llm.prompts.filter_out_solution.filter_out_solution import FilterOutSolution diff --git a/modules/programming/module_programming_llm/module_programming_llm/config.py b/modules/programming/module_programming_llm/module_programming_llm/config.py index 850feac58..21cb295b1 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/config.py +++ b/modules/programming/module_programming_llm/module_programming_llm/config.py @@ -2,7 +2,7 @@ from pydantic import BaseModel, Field -from module_programming_llm.helpers.models import ModelConfigType, DefaultModelConfig +from llm_core.models import ModelConfigType, DefaultModelConfig from athena import config_schema_provider from module_programming_llm.prompts import SplitProblemStatementByFile, SplitGradingInstructionsByFile, \ GenerateSuggestionsByFile, GenerateFileSummary diff --git a/modules/programming/module_programming_llm/module_programming_llm/helpers/web_search.py b/modules/programming/module_programming_llm/module_programming_llm/helpers/web_search.py index 9f9658425..bba5c47a4 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/helpers/web_search.py +++ b/modules/programming/module_programming_llm/module_programming_llm/helpers/web_search.py @@ -1,19 +1,14 @@ from typing import Sequence, List from langchain.chains.qa_with_sources.retrieval import RetrievalQAWithSourcesChain -from langchain_community.document_loaders import AsyncChromiumLoader -from langchain_community.document_transformers import BeautifulSoupTransformer -from duckduckgo_search import DDGS -import re from langchain_community.retrievers import WebResearchRetriever from langchain_community.utilities import GoogleSearchAPIWrapper from langchain_community.vectorstores import Chroma -from langchain_core.documents import Document from langchain_core.tools import Tool from langchain_openai import OpenAIEmbeddings -from module_programming_llm.helpers.models import ModelConfigType +from llm_core.models import ModelConfigType def bulk_search(queries: Sequence[str], model: ModelConfigType) -> List[str]: @@ -21,41 +16,7 @@ def bulk_search(queries: Sequence[str], model: ModelConfigType) -> List[str]: for query in queries: result.append(answer_query(query, model)) return result -# -# -# def search(query: str) -> List[str]: -# results = DDGS().text(query, max_results=5) -# urls = [] -# for result in results: -# url = result['href'] -# urls.append(url) -# -# docs = get_page(urls) -# -# content = [] -# for doc in docs: -# page_text = re.sub("\n\n+", "\n", doc.page_content) -# text = truncate(page_text) -# content.append(text) -# -# return content -# -# -# def get_page(urls: List[str]) -> Sequence[Document]: -# loader = AsyncChromiumLoader(urls, headless=True) -# html = loader.load() -# -# bs_transformer = BeautifulSoupTransformer() -# docs_transformed = bs_transformer.transform_documents(html, tags_to_extract=["p"], remove_unwanted_tags=["a"]) -# -# return docs_transformed -# -# -# def truncate(text) -> str: -# words = text.split() -# truncated = " ".join(words[:1000]) -# -# return truncated + def answer_query(query, model: ModelConfigType): model = model.get_model() # type: ignore[attr-defined] diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution.py index caf50b6b8..c7e500881 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/filter_out_solution/filter_out_solution.py @@ -12,18 +12,18 @@ FeedbackModel as SuggestionsFeedbackModel from .prompt import system_message as prompt_system_message, human_message as prompt_human_message from pydantic import Field -from module_programming_llm.helpers.llm_utils import ( +from llm_core.utils.llm_utils import ( get_chat_prompt_with_formatting_instructions, - predict_and_parse, num_tokens_from_string, + num_tokens_from_string, check_prompt_length_and_omit_features_if_necessary, ) +from llm_core.utils.predict_and_parse import predict_and_parse from module_programming_llm.helpers.utils import ( get_diff, load_files_from_repo, add_line_numbers ) -from ...helpers.models import ModelConfigType - +from llm_core.models import ModelConfigType class FilterOutSolution(PipelineStep[FilterOutSolutionInput, List[Optional[FilterOutSolutionOutput]]]): """A pipeline step to remove potential solutions from the output.""" diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py index c92e225ff..5c544a54b 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_file_summary/generate_file_summary.py @@ -9,16 +9,17 @@ from .generate_file_summary_output import FileDescription from .prompt import system_message as prompt_system_message, human_message as prompt_human_message from pydantic import Field -from module_programming_llm.helpers.llm_utils import ( +from llm_core.utils.llm_utils import ( get_chat_prompt_with_formatting_instructions, - predict_and_parse, num_tokens_from_prompt, + num_tokens_from_prompt ) +from llm_core.utils.predict_and_parse import predict_and_parse from module_programming_llm.helpers.utils import ( get_diff, load_files_from_repo, add_line_numbers ) -from ...helpers.models import ModelConfigType +from llm_core.models import ModelConfigType class GenerateFileSummary(PipelineStep[GenerateFileSummaryInput, Optional[GenerateFileSummaryOutput]]): diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion.py index c6f06bd27..062e4336f 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_grading_criterion/generate_grading_criterion.py @@ -9,17 +9,18 @@ from .generate_grading_criterion_output import GenerateGradingCriterionOutput from .prompt import system_message as prompt_system_message, human_message as prompt_human_message from pydantic import Field -from module_programming_llm.helpers.llm_utils import ( +from llm_core.utils.llm_utils import ( get_chat_prompt_with_formatting_instructions, - predict_and_parse, num_tokens_from_string, + num_tokens_from_string, check_prompt_length_and_omit_features_if_necessary, num_tokens_from_prompt, ) +from llm_core.utils.predict_and_parse import predict_and_parse from module_programming_llm.helpers.utils import ( get_diff, load_files_from_repo, add_line_numbers, get_programming_language_file_extension ) -from ...helpers.models import ModelConfigType +from llm_core.models import ModelConfigType class GenerateGradingCriterion(PipelineStep[GenerateGradingCriterionInput, Optional[GenerateGradingCriterionOutput]]): diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py index e0001cf24..429dfbda4 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/generate_suggestions_by_file/generate_suggestions_by_file.py @@ -8,17 +8,18 @@ from .generate_suggestions_by_file_output import GenerateSuggestionsByFileOutput, FeedbackModel from .prompt import system_message as prompt_system_message, human_message as prompt_human_message from pydantic import Field -from module_programming_llm.helpers.llm_utils import ( +from llm_core.utils.llm_utils import ( get_chat_prompt_with_formatting_instructions, - predict_and_parse, num_tokens_from_string, + num_tokens_from_string, check_prompt_length_and_omit_features_if_necessary, ) +from llm_core.utils.predict_and_parse import predict_and_parse from module_programming_llm.helpers.utils import ( get_diff, load_files_from_repo, add_line_numbers, get_programming_language_file_extension, format_grading_instructions ) -from ...helpers.models import ModelConfigType +from llm_core.models import ModelConfigType class GenerateSuggestionsByFile(PipelineStep[GenerateSuggestionsByFileInput, List[Optional[GenerateSuggestionsByFileOutput]]]): diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/pipeline_step.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/pipeline_step.py index 6905daa49..0f9dc2485 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/pipeline_step.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/pipeline_step.py @@ -2,7 +2,7 @@ from abc import abstractmethod from pydantic import BaseModel, Field -from module_programming_llm.helpers.models import ModelConfigType +from llm_core.models import ModelConfigType # Generic types for input and output TInput = TypeVar('TInput') diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/rag/rag.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/rag/rag.py index 25ad5ebe3..6225428d1 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/rag/rag.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/rag/rag.py @@ -7,16 +7,16 @@ from .rag_output import RAGOutput from .prompt import system_message as prompt_system_message, human_message as prompt_human_message from pydantic import Field -from module_programming_llm.helpers.llm_utils import ( +from llm_core.utils.llm_utils import ( get_chat_prompt_with_formatting_instructions, - predict_and_parse, num_tokens_from_prompt, ) +from llm_core.utils.predict_and_parse import predict_and_parse from module_programming_llm.helpers.utils import ( get_diff, load_files_from_repo, ) -from ...helpers.models import ModelConfigType +from llm_core.models import ModelConfigType class RAG(PipelineStep[RAGInput, Optional[RAGOutput]]): diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file.py index 4432e1529..ed270130a 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_grading_instructions_by_file/split_grading_instructions_by_file.py @@ -9,16 +9,17 @@ from .split_grading_instructions_by_file_input import SplitGradingInstructionsByFileInput from .prompt import system_message as prompt_system_message, human_message as prompt_human_message from pydantic import Field -from module_programming_llm.helpers.llm_utils import ( +from llm_core.utils.llm_utils import ( get_chat_prompt_with_formatting_instructions, num_tokens_from_string, - predict_and_parse, num_tokens_from_prompt, + num_tokens_from_prompt, ) +from llm_core.utils.predict_and_parse import predict_and_parse from module_programming_llm.helpers.utils import ( get_diff, ) from .split_grading_instructions_by_file_output import FileGradingInstruction, SplitGradingInstructionsByFileOutput -from ...helpers.models import ModelConfigType +from llm_core.models import ModelConfigType class SplitGradingInstructionsByFile( diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py index 63dad1600..7b005b871 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/split_problem_statement_by_file/split_problem_statement_by_file.py @@ -9,9 +9,10 @@ from .split_problem_statement_by_file_input import SplitProblemStatementByFileInput from .split_problem_statement_by_file_output import FileProblemStatement, SplitProblemStatementByFileOutput from ..pipeline_step import PipelineStep -from ...helpers.llm_utils import num_tokens_from_string, get_chat_prompt_with_formatting_instructions, \ - num_tokens_from_prompt, predict_and_parse -from ...helpers.models import ModelConfigType +from llm_core.utils.llm_utils import num_tokens_from_string, get_chat_prompt_with_formatting_instructions, \ + num_tokens_from_prompt +from llm_core.utils.predict_and_parse import predict_and_parse +from llm_core.models import ModelConfigType from ...helpers.utils import get_diff diff --git a/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions.py b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions.py index 0cd905d50..87f4ed7cc 100644 --- a/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions.py +++ b/modules/programming/module_programming_llm/module_programming_llm/prompts/validate_suggestions/validate_suggestions.py @@ -11,17 +11,18 @@ from .validate_suggestions_output import ValidateSuggestionsOutput from .prompt import system_message as prompt_system_message, human_message as prompt_human_message from pydantic import Field -from module_programming_llm.helpers.llm_utils import ( +from llm_core.utils.llm_utils import ( get_chat_prompt_with_formatting_instructions, - predict_and_parse, num_tokens_from_string, + num_tokens_from_string, check_prompt_length_and_omit_features_if_necessary, ) +from llm_core.utils.predict_and_parse import predict_and_parse from module_programming_llm.helpers.utils import ( get_diff, load_files_from_repo, add_line_numbers, get_programming_language_file_extension ) -from ...helpers.models import ModelConfigType +from llm_core.models import ModelConfigType class ValidateSuggestions(PipelineStep[ValidateSuggestionsInput, List[Optional[ValidateSuggestionsOutput]]]): diff --git a/modules/programming/module_programming_llm/poetry.lock b/modules/programming/module_programming_llm/poetry.lock index 90c653911..d65a1b00a 100644 --- a/modules/programming/module_programming_llm/poetry.lock +++ b/modules/programming/module_programming_llm/poetry.lock @@ -136,29 +136,6 @@ files = [ [package.dependencies] frozenlist = ">=1.1.0" -[[package]] -name = "altair" -version = "5.4.1" -description = "Vega-Altair: A declarative statistical visualization library for Python." -optional = false -python-versions = 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"jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] -enabler = ["pytest-enabler (>=2.2)"] -test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"] -type = ["pytest-mypy"] - [metadata] lock-version = "2.0" python-versions = "3.11.*" -content-hash = "0450d91024422faab2b84bc4d77a4b956650f13c7a66f3bf5b82459b2c3ae58e" +content-hash = "edf46f687b0e4c950a96bce90ab995a9d2c9254beea314e8ac4c74da938bdfc2" diff --git a/modules/programming/module_programming_llm/pyproject.toml b/modules/programming/module_programming_llm/pyproject.toml index b07a7ef7d..c6f872c56 100644 --- a/modules/programming/module_programming_llm/pyproject.toml +++ b/modules/programming/module_programming_llm/pyproject.toml @@ -8,34 +8,22 @@ license = "MIT" [tool.poetry.dependencies] python = "3.11.*" # if you have local changes in the common Athena module, use the line below. Otherwise, please use a VCS stable version. Also, a version with tag = "" is possible. -# athena = { path = "../athena", develop = true } athena = { path = "../../../athena", develop = true } #athena = { git = "https://github.com/ls1intum/Athena.git", rev = "2da2d33", subdirectory = "athena"} llm_core = { path = "../../../llm_core", develop = true } -openai = "1.40.0" -langchain = "0.3.2" -langchain-community="0.3.1" -langchain-openai = "0.2.1" gitpython = "^3.1.41" -tiktoken = "0.7.0" promptlayer = "^0.1.85" python-dotenv = "^1.0.0" nltk = "^3.8.1" replicate = "^0.11.0" -chromadb = "0.5.13" -streamlit= "1.25.0" -html2text = "2020.1.16" google-api-core = "2.11.1" google-api-python-client = "2.95.0" google-auth = "2.22.0" google-auth-httplib2 = "0.1.0" googleapis-common-protos = "1.59.1" -faiss-cpu = {version = "^1.7.0", platform = "posix"} -faiss-gpu = {version = "^1.7.1", platform = "posix"} bs4 = "0.0.2" [tool.poetry.group.dev.dependencies] -types-requests = "^2.31.0.8" pydantic = "2.7.4" prospector = "^1.10.2"