121 lines
3.5 KiB
Python
121 lines
3.5 KiB
Python
# main.py
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import os
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from typing import TypedDict, Dict
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from langgraph.graph import StateGraph, END
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from langgraph.prebuilt import create_chat_agent
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from langchain_openai import ChatOpenAI
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from langchain_core.messages import HumanMessage, AIMessage
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# Define state
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class CodeReviewState(TypedDict):
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code: str
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draft_review: str
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criteria_scores: Dict[str, int]
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weakest_criterion: str
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verdict: str
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round: int
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max_rounds: int
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# LLM
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llm = ChatOpenAI(temperature=0)
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# Draft review node
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async def draft_review(state: CodeReviewState) -> CodeReviewState:
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prompt = f"""
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You are a senior Python developer. Review the following code and provide a concise code review (3-6 bullet points) highlighting what is good and what can be improved.
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Code:
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{state['code']}
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Review:
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"""
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response = await llm.ainvoke([HumanMessage(content=prompt)])
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state['draft_review'] = response.content
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return state
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# Reflect node
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async def reflect(state: CodeReviewState) -> CodeReviewState:
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prompt = f"""
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You are an AI critic evaluating a code review. Assign a score 0-10 for each of the following criteria based on the draft review:
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- pep8
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- type_hints
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- edge_cases
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- naming
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Provide a JSON object with keys "pep8", "type_hints", "edge_cases", "naming" and integer values.
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Also determine the weakest criterion (the one with lowest score) and a verdict: "ok" if all scores >=7, otherwise "needs_revision".
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Draft review:
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{state['draft_review']}
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Output JSON:
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"""
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response = await llm.ainvoke([HumanMessage(content=prompt)])
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import json
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scores = json.loads(response.content)
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state['criteria_scores'] = scores
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weakest = min(scores, key=scores.get)
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state['weakest_criterion'] = weakest
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state['verdict'] = "ok" if all(v >= 7 for v in scores.values()) else "needs_revision"
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return state
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# Rewrite node
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async def rewrite(state: CodeReviewState) -> CodeReviewState:
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crit = state['weakest_criterion']
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prompt = f"""
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You are a senior Python developer. Rewrite the section of the code review that addresses the {crit} criterion, improving it. Keep the rest of the review unchanged.
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Original review:
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{state['draft_review']}
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Rewrite only the part related to {crit}:
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"""
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response = await llm.ainvoke([HumanMessage(content=prompt)])
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# Replace the part in draft_review that mentions crit
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# For simplicity, just append the new part
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state['draft_review'] = state['draft_review'] + "\n" + response.content
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state['round'] += 1
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return state
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# Build graph
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builder = StateGraph(CodeReviewState)
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builder.add_node("draft_review", draft_review)
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builder.add_node("reflect", reflect)
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builder.add_node("rewrite", rewrite)
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builder.set_entry_point("draft_review")
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builder.add_edge("draft_review", "reflect")
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builder.add_conditional_edges(
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"reflect",
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lambda x: "rewrite" if x["verdict"] == "needs_revision" and x["round"] < x["max_rounds"] else "END",
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)
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builder.add_edge("rewrite", "reflect")
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graph = builder.compile()
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# Demo function
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async def run_demo():
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code = """
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# Example function to sort numbers
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def sort_numbers(arr):
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return sorted(arr)
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"""
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init_state: CodeReviewState = {
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"code": code,
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"draft_review": "",
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"criteria_scores": {},
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"weakest_criterion": "",
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"verdict": "",
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"round": 0,
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"max_rounds": 2,
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}
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result = await graph.ainvoke(init_state)
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print("Final Review:\n", result["draft_review"])
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print("Scores:\n", result["criteria_scores"])
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print("Verdict:\n", result["verdict"])
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if __name__ == "__main__":
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import asyncio
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asyncio.run(run_demo())
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