Done

app.py

@@ -26,8 +26,8 @@ peft_lora_adapter = PeftModel.from_pretrained(base_model, peft_lora_adapter_path
 base_model.load_adapter(peft_lora_adapter_path, adapter_name="lora_adapter")
 
 processor = AutoProcessor.from_pretrained("HuggingFaceH4/vsft-llava-1.5-7b-hf-trl")
-# model = M2M100ForConditionalGeneration.from_pretrained("facebook/m2m100_418M")
-# tokenizer = M2M100Tokenizer.from_pretrained("facebook/m2m100_418M")
+model = M2M100ForConditionalGeneration.from_pretrained("facebook/m2m100_418M")
+tokenizer = M2M100Tokenizer.from_pretrained("facebook/m2m100_418M")
 
 
 # model_id = r"C:\Users\prave\OneDrive\Desktop\MLOPS\Mlops_2\huggingface_model"
@@ -140,7 +140,7 @@ def get_bot_response():
     try:
       if 'image' in image_cache:
           image = image_cache['image']
-          # print(image)
+          print(image)
           query = request.args.get('msg')
           # output = query
           output = google_response(image, query)

templates/index.html

@@ -27,7 +27,7 @@
                 <div class="text">Send</div>
             </div>
             <form id="uploadForm" enctype="multipart/form-data" class="upload_wrapper">
-                <input type="file" name="file" id="fileInput" accept=".jpg">
+                <input type="file" name="file" id="fileInput" accept=".png, .jpg, .jpeg">
                 <button type="submit">Upload</button>
             </form>            
             <div id="uploadStatus"></div>