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Update backend/main.py
Browse files- backend/main.py +69 -69
backend/main.py
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from fastapi import FastAPI, UploadFile, File, Form
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from pydantic import BaseModel
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import shutil
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import os
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from backend.models import summarizer, image_captioning, qa_pipeline, translator, code_generator
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from backend.utils import extract_text_from_pdf, extract_text_from_document
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app = FastAPI()
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UPLOAD_DIR = "uploads"
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os.makedirs(UPLOAD_DIR, exist_ok=True)
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class QARequest(BaseModel):
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question: str
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context: str
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@app.get("/")
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async def home():
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return {"message": "AI Web App is Running!"}
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# 1️⃣ استخراج النصوص من المستندات
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@app.post("/extract_text/")
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async def extract_text(file: UploadFile = File(...)):
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file_path = f"{UPLOAD_DIR}/{file.filename}"
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with open(file_path, "wb") as f:
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shutil.copyfileobj(file.file, f)
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text = extract_text_from_document(file_path)
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os.remove(file_path)
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return {"text": text}
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# 2️⃣ تلخيص المستندات
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@app.post("/summarize/")
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async def summarize_text(text: str = Form(...)):
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summary = summarizer(text)
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return {"summary": summary[0]['summary_text']}
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# 3️⃣ تحليل الصور وتوليد وصف لها
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@app.post("/image_caption/")
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async def caption_image(file: UploadFile = File(...)):
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file_path = f"{UPLOAD_DIR}/{file.filename}"
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with open(file_path, "wb") as f:
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shutil.copyfileobj(file.file, f)
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with open(file_path, "rb") as img:
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image_bytes = img.read()
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caption = image_captioning(image_bytes)
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os.remove(file_path)
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return {"caption": caption[0]['generated_text']}
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# 4️⃣ الإجابة على الأسئلة من النصوص
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@app.post("/qa/")
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async def answer_question(request: QARequest):
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answer = qa_pipeline(request.question, request.context)
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return {"answer": answer["answer"]}
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# 5️⃣ ترجمة المستندات
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@app.post("/translate/")
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async def translate_text(text: str = Form(...)):
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translation = translator(text)
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return {"translation": translation[0]['translation_text']}
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# 6️⃣ توليد أكواد التصور من أوامر نصية
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@app.post("/generate_code/")
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async def generate_code(prompt: str = Form(...)):
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code = code_generator(prompt)
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return {"code": code}
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from fastapi import FastAPI, UploadFile, File, Form
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from pydantic import BaseModel
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import shutil
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import os
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from backend.models import summarizer, image_captioning, qa_pipeline, translator, code_generator
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from backend.utils import extract_text_from_pdf, extract_text_from_document
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app = FastAPI()
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UPLOAD_DIR = "/tmp/uploads"
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os.makedirs(UPLOAD_DIR, exist_ok=True)
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class QARequest(BaseModel):
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question: str
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context: str
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@app.get("/")
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async def home():
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return {"message": "AI Web App is Running!"}
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# 1️⃣ استخراج النصوص من المستندات
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@app.post("/extract_text/")
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async def extract_text(file: UploadFile = File(...)):
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file_path = f"{UPLOAD_DIR}/{file.filename}"
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with open(file_path, "wb") as f:
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shutil.copyfileobj(file.file, f)
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text = extract_text_from_document(file_path)
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os.remove(file_path)
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return {"text": text}
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# 2️⃣ تلخيص المستندات
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@app.post("/summarize/")
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async def summarize_text(text: str = Form(...)):
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summary = summarizer(text)
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return {"summary": summary[0]['summary_text']}
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# 3️⃣ تحليل الصور وتوليد وصف لها
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@app.post("/image_caption/")
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async def caption_image(file: UploadFile = File(...)):
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file_path = f"{UPLOAD_DIR}/{file.filename}"
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with open(file_path, "wb") as f:
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shutil.copyfileobj(file.file, f)
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with open(file_path, "rb") as img:
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image_bytes = img.read()
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caption = image_captioning(image_bytes)
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os.remove(file_path)
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return {"caption": caption[0]['generated_text']}
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# 4️⃣ الإجابة على الأسئلة من النصوص
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@app.post("/qa/")
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async def answer_question(request: QARequest):
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answer = qa_pipeline(request.question, request.context)
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return {"answer": answer["answer"]}
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# 5️⃣ ترجمة المستندات
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@app.post("/translate/")
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async def translate_text(text: str = Form(...)):
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translation = translator(text)
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return {"translation": translation[0]['translation_text']}
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# 6️⃣ توليد أكواد التصور من أوامر نصية
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@app.post("/generate_code/")
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async def generate_code(prompt: str = Form(...)):
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code = code_generator(prompt)
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return {"code": code}
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