evaluator.py

import os
import base64
from groq import Groq

TEXT_MODEL = "llama-3.1-8b-instant"
FAST_MODEL = "qwen/qwen3-32b"
VISION_MODEL = "meta-llama/llama-4-maverick-17b-128e-instruct"


# ================================================================
# TASK 2 EVALUATOR
# ================================================================
class IELTSTask2Evaluator:
    def __init__(self):
        self.client = Groq(api_key=os.getenv("GROQ_API_KEY"))
        self.model = TEXT_MODEL

    def evaluate_essay(self, question, essay):
        prompt = f"""
Evaluate this IELTS Task 2 essay...

Question: {question}
Essay:
{essay}
"""
        return self._get_completion(prompt)

    def analyze_grammar(self, essay):
        prompt = f"Grammar analysis:\n{essay}"
        return self._get_completion(prompt)

    def analyze_vocabulary(self, essay):
        prompt = f"Vocabulary analysis:\n{essay}"
        return self._get_completion(prompt)

    def analyze_cohesion_coherence(self, essay):
        prompt = f"Cohesion & Coherence analysis:\n{essay}"
        return self._get_completion(prompt)

    def analyze_task_achievement(self, question, essay):
        prompt = f"Task Achievement analysis for:\n{question}\nEssay:\n{essay}"
        return self._get_completion(prompt)

    def _get_completion(self, prompt):
        response = self.client.chat.completions.create(
            model=self.model,
            messages=[{"role": "user", "content": prompt}],
        )
        return response.choices[0].message.content


# ================================================================
# TASK 2 EXERCISE GENERATOR
# ================================================================
class IELTSTask2ExerciseGenerator:
    def __init__(self):
        self.client = Groq(api_key=os.getenv("GROQ_API_KEY"))
        self.model = FAST_MODEL

    def generate_grammar_exercises(self, grammar, essay):
        prompt = f"Generate grammar exercises:\n{grammar}\nEssay:\n{essay}"
        return self._get_completion(prompt)

    def generate_vocabulary_exercises(self, vocab):
        prompt = f"Generate vocabulary exercises:\n{vocab}"
        return self._get_completion(prompt)

    def _get_completion(self, prompt):
        resp = self.client.chat.completions.create(
            model=self.model,
            messages=[{"role": "user", "content": prompt}],
        )
        return resp.choices[0].message.content


# ================================================================
# TASK 1 EVALUATOR
# ================================================================
class IELTSTask1Evaluator:
    def __init__(self):
        self.client = Groq(api_key=os.getenv("GROQ_API_KEY"))
        self.text_model = TEXT_MODEL
        self.vision_model = VISION_MODEL

    def encode_image(self, path):
        with open(path, "rb") as f:
            return base64.b64encode(f.read()).decode()

    def analyze_graph(self, path, question):
        img = self.encode_image(path)
        response = self.client.chat.completions.create(
            model=self.vision_model,
            messages=[
                {
                    "role": "user",
                    "content": [
                        {"type": "text", "text": question},
                        {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{img}"}},
                    ],
                }
            ],
        )
        return response.choices[0].message.content

    def evaluate_task1_response(self, question, graph, essay):
        prompt = f"Evaluate Task 1 response:\n{question}\nGraph:\n{graph}\nEssay:\n{essay}"
        return self._get_completion(prompt)

    def analyze_grammar(self, essay):
        return self._get_completion(f"Grammar analysis:\n{essay}")

    def analyze_vocabulary(self, essay):
        return self._get_completion(f"Vocabulary analysis:\n{essay}")

    def analyze_task_achievement(self, question, graph, essay):
        return self._get_completion(f"Task Achievement:\n{question}\nGraph:\n{graph}\nEssay:\n{essay}")

    def analyze_cohesion_coherence(self, essay, graph):
        return self._get_completion(f"Cohesion & Coherence:\nGraph:\n{graph}\nEssay:\n{essay}")

    def _get_completion(self, prompt):
        resp = self.client.chat.completions.create(
            model=self.text_model,
            messages=[{"role": "user", "content": prompt}],
        )
        return resp.choices[0].message.content


# ================================================================
# TASK 1 EXERCISE GENERATOR
# ================================================================
class IELTSTask1ExerciseGenerator:
    def __init__(self):
        self.client = Groq(api_key=os.getenv("GROQ_API_KEY"))
        self.model = FAST_MODEL

    def generate_grammar_exercises(self, grammar, essay):
        prompt = f"Generate grammar exercises:\n{grammar}\nEssay:\n{essay}"
        return self._get_completion(prompt)

    def generate_vocabulary_exercises(self, vocab):
        prompt = f"Generate vocabulary exercises:\n{vocab}"
        return self._get_completion(prompt)

    def _get_completion(self, prompt):
        resp = self.client.chat.completions.create(
            model=self.model,
            messages=[{"role": "user", "content": prompt}],
        )
        return resp.choices[0].message.content