69 lines
2.3 KiB
Python
69 lines
2.3 KiB
Python
import json
|
|
|
|
from ollama import AsyncClient
|
|
from pydantic import BaseModel
|
|
|
|
from haiku.rag.config import Config
|
|
|
|
|
|
class LLMJudgeResponseSchema(BaseModel):
|
|
equivalent: bool
|
|
|
|
|
|
class LLMJudge:
|
|
"""LLM-as-judge for evaluating answer equivalence using Ollama."""
|
|
|
|
def __init__(self, model: str = "qwen3"):
|
|
self.model = model
|
|
self.client = AsyncClient(host=Config.OLLAMA_BASE_URL)
|
|
|
|
async def judge_answers(
|
|
self, question: str, answer: str, expected_answer: str
|
|
) -> bool:
|
|
"""
|
|
Judge whether two answers are equivalent for a given question.
|
|
|
|
Args:
|
|
question: The original question
|
|
answer: The generated answer to evaluate
|
|
expected_answer: The reference/expected answer
|
|
|
|
Returns:
|
|
Dictionary with judgment result:
|
|
- equivalent: bool indicating if answers are equivalent
|
|
- explanation: str explaining the reasoning
|
|
- score: str rating from 1-5
|
|
"""
|
|
|
|
prompt = f"""
|
|
You are an expert judge evaluating the equivalence of two answers to the same question.
|
|
|
|
Question: {question}
|
|
|
|
Generated Answer: {answer}
|
|
|
|
Expected Answer: {expected_answer}
|
|
|
|
Your task is to determine if these two answers are equivalent in meaning and both correctly answer the question. Consider:
|
|
|
|
1. Do both answers provide the same answer?
|
|
2. Do both answers directly address the question asked?
|
|
3. Minor differences in wording or style are acceptable if the meaning of the answer is the same.
|
|
4. If one answer is more detailed but the other is correct, they can still be considered equivalent.
|
|
|
|
Be strict but fair in your evaluation. Focus on factual correctness and whether both answers would satisfy someone asking the question."""
|
|
|
|
response = await self.client.chat(
|
|
model=self.model,
|
|
messages=[{"role": "user", "content": prompt}],
|
|
format=LLMJudgeResponseSchema.model_json_schema(),
|
|
think=False,
|
|
)
|
|
|
|
answer = response["message"]["content"].strip()
|
|
try:
|
|
res = json.loads(answer)
|
|
assert "equivalent" in res, "Response must contain 'equivalent' key"
|
|
return res["equivalent"]
|
|
except json.JSONDecodeError:
|
|
assert False, "Response is not valid JSON"
|