Update main.py

main.py

@@ -30,11 +30,22 @@ import threading
 import firebase_admin
 from firebase_admin import credentials
 from firebase_admin import firestore
+from transformers import BertTokenizer, AutoModelForSeq2SeqLM, pipeline
+from arabert.preprocess import ArabertPreprocessor
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import re
 # Firebase ininlaziton
 cred = credentials.Certificate(
     "text-to-emotions-firebase-adminsdk-8isbn-dffbdf01e8.json")
 firebase_admin.initialize_app(cred)
 
+# Model summury
+model_name="abdalrahmanshahrour/auto-arabic-summarization"
+preprocessor = ArabertPreprocessor(model_name="")
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+modelsummary = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+pipeline1 = pipeline("text2text-generation",model=modelsummary,tokenizer=tokenizer)
 
 # Model inilization
 isristemmer = ISRIStemmer()
@@ -142,7 +153,16 @@ def original_values(num):
         return 'sympathy'
     elif num == 6:
         return 'fear'
-
+def modelsummary(data):
+    result = pipeline1(text,
+    pad_token_id= tokenizer.eos_token_id,
+    num_beams=4,
+    repetition_penalty=3.0,
+    max_length=600,
+    length_penalty=1.0,
+    no_repeat_ngram_size = 3)[0]['generated_text']
+    result = remove_punctuations(result)
+    return { 'summary':result}
 
 def modelpredict(data):
     data = txt_preprocess(data)
@@ -158,7 +178,13 @@ app = FastAPI()
 @app.get("/")
 def index():
     return "Hello World"
-
+@app.post("/summary")
+async def read_root(request:Request):
+    json_data = await request.json()
+    if 'text'in json_data:
+        return modelsummary(json_data['text'])
+    else:
+        raise HTTPException(status_code=400, detail="Missing text value")
 @app.post("/predict")
 async def read_root(request: Request):
     json_data = await request.json()