183 lines
6.0 KiB
Python
183 lines
6.0 KiB
Python
from fastapi import FastAPI, HTTPException, Request
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from fastapi.middleware.cors import CORSMiddleware
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from fastapi.exceptions import RequestValidationError
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from fastapi.responses import JSONResponse
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from fastapi.encoders import jsonable_encoder
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from pydantic import BaseModel
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import logging, hashlib
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import httpx
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# Logging setup
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logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
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# FastAPI instance
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app = FastAPI()
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# CORS
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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# Ollama endpoint
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OLLAMA_URL = "http://labai.polinema.ac.id:11434/api/generate"
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# Error handler
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@app.exception_handler(RequestValidationError)
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async def validation_exception_handler(request: Request, exc: RequestValidationError):
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logging.error(f"Validation error: {exc}")
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return JSONResponse(
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status_code=422,
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content={"detail": jsonable_encoder(exc.errors()), "body": exc.body},
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)
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# Input models
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class MaterialRequest(BaseModel):
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content: str
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question_type: str # 'multiple_choice' atau 'essay'
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question_count: int = 5
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class FeedbackRequest(BaseModel):
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user_answer: str
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expected_answer: str
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# Utility
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feedback_cache = {}
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def potong_konten(text: str, max_chars: int = 5000):
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if len(text) > max_chars:
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logging.warning(f"Teks terlalu panjang ({len(text)} karakter), dipotong jadi {max_chars}")
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return text[:max_chars]
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return text
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@app.post("/generate-from-material/")
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async def generate_from_material(request: MaterialRequest):
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try:
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if request.question_count < 1 or request.question_count > 20:
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raise HTTPException(status_code=400, detail="Jumlah soal harus antara 1-20")
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if request.question_type not in ["multiple_choice", "essay"]:
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raise HTTPException(status_code=400, detail="Jenis soal tidak valid. Pilih: multiple_choice atau essay")
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mc_count = request.question_count if request.question_type == "multiple_choice" else 0
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essay_count = request.question_count if request.question_type == "essay" else 0
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content_bersih = potong_konten(request.content.strip())
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prompt = f"""
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Buat soal latihan berdasarkan teks materi berikut untuk siswa SD kelas 3.
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**Instruksi:**
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1. Buat total {request.question_count} soal dengan rincian:
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- Soal pilihan ganda: {mc_count}
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- Soal isian: {essay_count}
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2. **Untuk soal isian:**
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- Ambil kutipan **minimal dua kalimat yang saling terhubung** dari teks sebagai dasar soal
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- Awali dengan: **Bacalah kutipan berikut: "[kutipan]"**
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- Buat pertanyaan berdasarkan kutipan tersebut
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- Sertakan **jawaban singkat**
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- Beri bobot antara **3–5** sesuai kompleksitas
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3. **Untuk soal pilihan ganda (jika ada):**
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- Ambil kutipan **1 kalimat yang relevan** dari teks
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- Buat pertanyaan dan 4 pilihan jawaban (A–D)
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- Beri jawaban benar dan bobot antara **1–2** sesuai tingkat kesulitan
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4. Gunakan bahasa sederhana dan sesuai dengan siswa SD kelas 3.
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5. Jangan menambahkan informasi di luar teks materi.
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**Format Output:**
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""" + ("""
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**Soal Pilihan Ganda:**
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1. Bacalah kutipan berikut: "[2 kalimat atau lebih dari teks]"
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Pertanyaan: [Pertanyaan]
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A. [Opsi A]
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B. [Opsi B]
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C. [Opsi C]
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D. [Opsi D]
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Jawaban: [Huruf Opsi]
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Bobot: [1 atau 2]
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""" if mc_count > 0 else "") + ("""
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**Soal Isian:**
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1. Bacalah kutipan berikut: "[2 kalimat atau lebih dari teks]". [Pertanyaan]
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Jawaban: [Jawaban]
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Bobot: [3 - 5]
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""" if essay_count > 0 else "") + f"""
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---
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**Materi:**
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{content_bersih}
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""".strip()
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logging.info("Mengirim prompt ke Ollama...")
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async with httpx.AsyncClient(timeout=120) as client:
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response = await client.post(OLLAMA_URL, json={
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"model": "llama3.1:latest",
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"prompt": prompt,
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"stream": False,
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"options": {
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"num_predict": 2048
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}
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})
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response.raise_for_status()
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result = response.json()
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generated_text = result.get("response", "").strip()
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return {
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"generated_questions": generated_text,
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"question_type": request.question_type,
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"question_count": request.question_count,
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"mc_count": mc_count,
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"essay_count": essay_count
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}
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except Exception as e:
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logging.error(f"Error saat generate: {e}")
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raise HTTPException(status_code=500, detail=f"Terjadi kesalahan internal: {str(e)}")
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@app.post("/generate-feedback/")
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async def generate_feedback(request: FeedbackRequest):
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try:
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user_answer = request.user_answer.strip()
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expected_answer = request.expected_answer.strip()
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prompt_hash = hashlib.sha256(f"{user_answer}|{expected_answer}".encode()).hexdigest()
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if prompt_hash in feedback_cache:
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logging.info("Feedback dari cache.")
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return {"feedback": feedback_cache[prompt_hash]}
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prompt = f"""
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Kamu adalah asisten pengajar untuk siswa SD kelas 3. Siswa memberikan jawaban berikut untuk soal isian.
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**Jawaban Siswa:** {user_answer}
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**Jawaban Ideal:** {expected_answer}
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Beri feedback singkat dan membangun, maksimal 2 kalimat. Gunakan bahasa yang mudah dimengerti oleh siswa SD. Jika jawaban siswa salah, berikan petunjuk atau koreksi yang membantu.
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"""
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logging.info("Mengirim prompt feedback ke Ollama...")
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async with httpx.AsyncClient(timeout=60) as client:
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response = await client.post(OLLAMA_URL, json={
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"model": "llama3.1:latest",
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"prompt": prompt,
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"stream": False
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})
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response.raise_for_status()
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result = response.json()
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feedback = result.get("response", "").strip()
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feedback_cache[prompt_hash] = feedback
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return {"feedback": feedback}
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except Exception as e:
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logging.error(f"Error saat generate feedback: {e}")
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raise HTTPException(status_code=500, detail=f"Terjadi kesalahan: {str(e)}") |