main.orig

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from deepeval.metrics import GEval
from deepeval.test_case import LLMTestCase, LLMTestCaseParams
from deepeval import assert_test
from typing import Optional

app = FastAPI()

class TestData(BaseModel):
    input: str
    actual_output: str
    expected_output: Optional[str] = None 
    context: Optional[str] = None
    retrieval_context: Optional[list[str]] = None
    evaluation_criteria: Optional[list[str]] = None

@app.post("/evaluate/")
async def evaluate_llm_response(data: TestData):
    try:
        user_fields = data.dict(exclude_none=True).keys()
        evaluation_params = [
            param
            for param in LLMTestCaseParams
            if param.value in user_fields
        ]


        correctness_metric = GEval(
            name="Correctness",
            evaluation_steps=data.evaluation_criteria or [
                "Check whether 'actual output' has all the files or code snippets (Controller, service, entity, repository) from 'expected output'",
                "The entity class import statements should use 'jakarta.persistence' instead of 'javax.persistence'",
                "Check if the correct dependencies are added in the 'pom.xml' file",
            ],
            evaluation_params=evaluation_params,
            threshold=0.8
        )

        test_case = LLMTestCase(
            input=data.input,
            actual_output=data.actual_output,
            expected_output=data.expected_output,
            context=data.context,
            retrieval_context=data.retrieval_context
        )

        correctness_metric.measure(test_case)
        # assert_test(test_case, [correctness_metric])

        result = {
            "score": correctness_metric.score,
            "reason": correctness_metric.reason
        }

        print("Evaluation Result:", result)
        return result
        
    except Exception as e:
        print("Error:", str(e))
        raise HTTPException(status_code=500, detail=str(e))