99 lines
2.8 KiB
Python
99 lines
2.8 KiB
Python
from fastapi import FastAPI, HTTPException
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from fastapi.middleware.cors import CORSMiddleware
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from pydantic import BaseModel
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from typing import List
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from groq import Groq
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import pandas as pd
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import os
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from dotenv import load_dotenv
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load_dotenv()
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# Initialize FastAPI app
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app = FastAPI()
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app.add_middleware(
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CORSMiddleware,
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allow_origins=[
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"https://askalquran.com",
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"https://www.askalquran.com",
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"http://localhost:3000",
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"http://127.0.0.1:3000",
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"http://0.0.0.0:3000"
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],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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# ... other parameters
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)
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# Load Groq API key
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api_key = os.getenv("GROQ_API_KEY")
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if not api_key:
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raise EnvironmentError("GROQ_API_KEY environment variable not set.")
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client = Groq(api_key=api_key)
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# Load Quran data
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try:
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data = pd.read_csv('quran_arabic.csv', encoding='utf-8')
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new_data = data[['verse_key', 'text_uthmani']]
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verse_dict = dict(zip(new_data['verse_key'], new_data['text_uthmani']))
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except FileNotFoundError:
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raise FileNotFoundError("CSV file 'quran_arabic.csv' not found. Please check the path.")
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class VerseItem(BaseModel):
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surahNo: int
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verseNo: int
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verseText: str
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class TafsirRequest(BaseModel):
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verses: List[VerseItem]
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# Prompt builder
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def build_arabic_prompt(text: str) -> str:
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return (
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"أنت عالم متخصص في تفسير القرآن الكريم.\n"
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"يرجى تقديم تفسير مختصر ومبسط للآية التالية:\n\n"
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f"{text}\n\n"
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" اكتب التفسير باللغة العربية الفصحى وبأسلوب مختصر و واضح وميسر للقارئ العام."
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)
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# Call Groq LLM
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def query_llm_arabic(prompt: str) -> str:
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try:
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response = client.chat.completions.create(
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model="llama3-70b-8192",
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messages=[{"role": "user", "content": prompt}],
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temperature=0.3
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)
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return response.choices[0].message.content
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except Exception as e:
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raise HTTPException(status_code=500, detail=f"LLM Error: {str(e)}")
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# Tafsir logic for list of verses
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def get_tafsir_for_verses(verses: List[VerseItem]) -> List[dict]:
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results = {}
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final_prompts = ""
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for verse in verses:
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prompt = str(verse.surahNo) + ":" + str(verse.verseNo) + "\t" + verse.verseText
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final_prompts += prompt + "\n"
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results = build_arabic_prompt(final_prompts)
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tafsir = query_llm_arabic(results)
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results = {
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"verseText": final_prompts,
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"tafsir": tafsir
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}
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return results
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# API endpoint
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@app.post("/tafsir")
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async def get_tafsir(request: TafsirRequest):
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return get_tafsir_for_verses(request.verses)
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# Health check
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@app.get("/health")
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def health_check():
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return {"status": "ok", "quran_verses_loaded": len(verse_dict)} |