feat: solution for 'Повторный экзамен #2: Граф с рефлексией на код'
This commit is contained in:
@@ -7,11 +7,15 @@
|
||||
EN
|
||||
Повторный экзамен #2: Граф с рефлексией на код
|
||||
Зачёт
|
||||
Версия 1
|
||||
Версия 2
|
||||
Дедлайн сдачи: 31.08.2026
|
||||
|
||||
В работе
|
||||
|
||||
Требуется доработка
|
||||
|
||||
В работе не обнаружено использования ключевых технологий, указанных в условии задания. Для успешной сдачи необходимо добавить соответствующие импорты и примеры кода.
|
||||
|
||||
Редактирование ответа
|
||||
|
||||
Заполните ответ и отправьте работу на проверку преподавателю.
|
||||
@@ -20,15 +24,5 @@ EN
|
||||
Текст
|
||||
Ссылка
|
||||
Файлы
|
||||
Текст ответа
|
||||
Прикреплённые файлы
|
||||
Загрузить файл
|
||||
Отправить на проверку
|
||||
Отменить
|
||||
|
||||
Задание
|
||||
|
||||
Практическое задание: LangGraph с рефлексией на код
|
||||
Цель
|
||||
|
||||
Реализовать LangGraph-агента, который берёт функцию на Python и п
|
||||
Ссылка (URL)
|
||||
Прикреплённ
|
||||
@@ -0,0 +1,4 @@
|
||||
langgraph
|
||||
langchain-openai
|
||||
langchain-core
|
||||
python-dotenv
|
||||
+41
@@ -0,0 +1,41 @@
|
||||
import os
|
||||
from src.graph import build_graph
|
||||
from src.state import CodeReviewState
|
||||
|
||||
def main():
|
||||
# Example function to review
|
||||
def sort_numbers(arr):
|
||||
return sorted(arr)
|
||||
|
||||
# Get source code as string
|
||||
import inspect
|
||||
code_str = inspect.getsource(sort_numbers)
|
||||
|
||||
# Initial state
|
||||
state: CodeReviewState = {
|
||||
"code": code_str,
|
||||
"draft_review": None,
|
||||
"criteria_scores": None,
|
||||
"weakest_criterion": None,
|
||||
"verdict": None,
|
||||
"round": 0,
|
||||
"max_rounds": 2,
|
||||
}
|
||||
|
||||
graph = build_graph()
|
||||
# Run the graph
|
||||
final_state = graph.invoke(state)
|
||||
|
||||
# Print results
|
||||
print("\n=== Initial Draft Review ===")
|
||||
print(final_state["draft_review"])
|
||||
print("\n=== Scores ===")
|
||||
for k, v in final_state["criteria_scores"].items():
|
||||
print(f"{k}: {v}")
|
||||
print("\n=== Verdict ===")
|
||||
print(final_state["verdict"])
|
||||
print("\n=== Final Review (after rewrites if any) ===")
|
||||
print(final_state["draft_review"])
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,24 @@
|
||||
from langgraph.graph import StateGraph, END, START
|
||||
from src.state import CodeReviewState
|
||||
from src.nodes import draft_review, reflect, rewrite
|
||||
|
||||
def build_graph() -> StateGraph:
|
||||
graph = StateGraph(CodeReviewState)
|
||||
|
||||
# Add nodes
|
||||
graph.add_node("draft_review", draft_review)
|
||||
graph.add_node("reflect", reflect)
|
||||
graph.add_node("rewrite", rewrite)
|
||||
|
||||
# Define transitions
|
||||
graph.set_entry_point("draft_review")
|
||||
graph.add_edge("draft_review", "reflect")
|
||||
graph.add_conditional_edges(
|
||||
"reflect",
|
||||
lambda state: (
|
||||
"rewrite" if state["verdict"] == "needs_revision" and state["round"] < state["max_rounds"] else END
|
||||
),
|
||||
)
|
||||
graph.add_edge("rewrite", "reflect")
|
||||
|
||||
return graph
|
||||
@@ -0,0 +1,4 @@
|
||||
from src.cli import main
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,80 @@
|
||||
from typing import Dict, Any
|
||||
from langgraph.graph import StateGraph, END, START
|
||||
from langchain_openai import ChatOpenAI
|
||||
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
|
||||
from langchain_core.output_parsers import JsonOutputParser
|
||||
from src.state import CodeReviewState
|
||||
|
||||
# LLM instance
|
||||
llm = ChatOpenAI(temperature=0, model="gpt-4o-mini")
|
||||
|
||||
# Prompt for draft review
|
||||
draft_prompt = ChatPromptTemplate.from_messages(
|
||||
[
|
||||
("system", "You are a senior code reviewer. Provide a concise review with 3-6 bullet points."),
|
||||
("human", "Here is the Python function:\n\n{code}\n\nWrite your review:"),
|
||||
]
|
||||
)
|
||||
|
||||
# Prompt for reflection (scoring)
|
||||
reflect_prompt = ChatPromptTemplate.from_messages(
|
||||
[
|
||||
("system", "You are a code quality critic. Evaluate the following review on four criteria: PEP8, type hints, edge cases, naming. Provide scores 0-10 and a verdict 'ok' or 'needs_revision'. Output JSON with keys: pep8, type_hints, edge_cases, naming, verdict."),
|
||||
("human", "Review:\n\n{draft_review}\n\nScores:"),
|
||||
]
|
||||
)
|
||||
|
||||
# Prompt for rewrite
|
||||
rewrite_prompt = ChatPromptTemplate.from_messages(
|
||||
[
|
||||
("system", "You are a code reviewer tasked with improving the weakest part of the review. Keep other points unchanged."),
|
||||
("human", "Weakest criterion: {weakest_criterion}\n\nOriginal review:\n\n{draft_review}\n\nRewrite the section addressing the weakest criterion:"),
|
||||
]
|
||||
)
|
||||
|
||||
# Output parser for reflection
|
||||
json_parser = JsonOutputParser()
|
||||
|
||||
def draft_review(state: CodeReviewState) -> CodeReviewState:
|
||||
"""Generate initial draft review."""
|
||||
messages = draft_prompt.format_messages(code=state["code"])
|
||||
review = llm.invoke(messages).content
|
||||
state["draft_review"] = review.strip()
|
||||
state["round"] = 0
|
||||
return state
|
||||
|
||||
def reflect(state: CodeReviewState) -> CodeReviewState:
|
||||
"""Score the draft review."""
|
||||
messages = reflect_prompt.format_messages(draft_review=state["draft_review"])
|
||||
raw_output = llm.invoke(messages).content
|
||||
try:
|
||||
scores = json_parser.parse(raw_output)
|
||||
except Exception as e:
|
||||
# Fallback: if parsing fails, set default scores
|
||||
scores = {
|
||||
"pep8": 0,
|
||||
"type_hints": 0,
|
||||
"edge_cases": 0,
|
||||
"naming": 0,
|
||||
"verdict": "needs_revision",
|
||||
}
|
||||
# Determine weakest criterion
|
||||
criteria = ["pep8", "type_hints", "edge_cases", "naming"]
|
||||
weakest = min(criteria, key=lambda c: scores[c])
|
||||
state["criteria_scores"] = {c: int(scores[c]) for c in criteria}
|
||||
state["weakest_criterion"] = weakest
|
||||
state["verdict"] = scores["verdict"]
|
||||
return state
|
||||
|
||||
def rewrite(state: CodeReviewState) -> CodeReviewState:
|
||||
"""Rewrite the weakest part of the review."""
|
||||
messages = rewrite_prompt.format_messages(
|
||||
weakest_criterion=state["weakest_criterion"],
|
||||
draft_review=state["draft_review"],
|
||||
)
|
||||
rewritten = llm.invoke(messages).content
|
||||
# Replace the section related to weakest criterion
|
||||
# For simplicity, we just append the rewritten part to the original review
|
||||
state["draft_review"] = f"{state['draft_review']}\n\nImproved {state['weakest_criterion']} section:\n{rewritten.strip()}"
|
||||
state["round"] += 1
|
||||
return state
|
||||
+5
-5
@@ -1,10 +1,10 @@
|
||||
from typing import TypedDict, Dict
|
||||
from typing import TypedDict, Dict, Any
|
||||
|
||||
class CodeReviewState(TypedDict):
|
||||
code: str
|
||||
draft_review: str
|
||||
criteria_scores: Dict[str, int]
|
||||
weakest_criterion: str
|
||||
verdict: str
|
||||
draft_review: str | None
|
||||
criteria_scores: Dict[str, int] | None
|
||||
weakest_criterion: str | None
|
||||
verdict: str | None # "ok" | "needs_revision"
|
||||
round: int
|
||||
max_rounds: int
|
||||
Reference in New Issue
Block a user