commit main

main.py

@@ -36,7 +36,10 @@ app.add_middleware(
 
 from transformers import VisionEncoderDecoderModel, ViTImageProcessor, AutoTokenizer
 try:
+    interpreter =None
     interpreter =pipeline("image-to-text", model="Salesforce/blip-image-captioning-base")
+    if interpreter is None :
+        print("\n\n interpreter is nonne \n\n")
     #interpreter_model = VisionEncoderDecoderModel.from_pretrained("nlpconnect/vit-gpt2-image-captioning")
     #interpreter_processor = ViTImageProcessor.from_pretrained("nlpconnect/vit-gpt2-image-captioning")
     #interpreter_tokenizer = AutoTokenizer.from_pretrained("nlpconnect/vit-gpt2-image-captioning")
@@ -47,7 +50,10 @@ except Exception as exp:
 
 
 try:
+    summarizer=None
     summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+    if summarizer is None :
+        print("\n\n summarizer is nonne \n\n")
 except Exception as exp:
     print("[ERROR] Can't load facebook/bart-large-cnn ")
     print(str(exp))
@@ -63,7 +69,10 @@ except Exception as exp:
 
 
 try:
+    generator=None
     generator = pipeline("text-generation", model="deepseek-ai/deepseek-coder-1.3b-instruct")
+    if generator is None :
+        print("\n\n generator is nonne \n\n")
 except Exception as exp:
     print("[ERROR] Can't load deepseek-ai/deepseek-coder-1.3b-instruct ")
     print(str(exp))
@@ -96,9 +105,11 @@ def index(req:Request):
 
 @app.post('/get')
 def g(f:str):
+   global generator
    return generator(f)[0]["generated_text"]
 @app.post('/gets')
 def g(f:str):
+   global summarizer
    return summarizer(f)[0]['summary_text']
 
 
@@ -110,6 +121,7 @@ def caption(file:UploadFile=File(...)):
     if extension not in Supported_extensions:
         return {"error": "Unsupported file type"}
     image = Image.open(file.file)
+     
     caption = interpreter(image)
     #pixel_values = interpreter_processor(images=image, return_tensors="pt").pixel_values
     #output_ids = interpreter_model.generate(pixel_values, max_length=16, num_beams=4)