diff --git a/examples/api_example.py b/examples/api_example.py
new file mode 100644
index 000000000..998bb83a8
--- /dev/null
+++ b/examples/api_example.py
@@ -0,0 +1,30 @@
+import requests
+
+ENDPOINT = "http://localhost:5001/api" # Please visit this link and read OpenAI documentation. It has a LOT more than what is shown here.
+
+# This is a very basic example of how to use the KoboldCpp API in python.
+# For full documentation, you can launch KoboldCpp and read it at http://localhost:5001/api or view the web docs at https://lite.koboldai.net/koboldcpp_api
+# Note: KoboldCpp also provides a fully compatible /v1/completions and /v1/chat/completions API. You can use it as a direct replacement for any OpenAI API usecases.
+# Refer to https://platform.openai.com/docs/api-reference/completions and https://platform.openai.com/docs/api-reference/chat
+
+payload = {
+    "prompt": "Niko the kobold stalked carefully down the alley, his small scaly figure obscured by a dusky cloak that fluttered lightly in the cold winter breeze.",
+    "max_context_length": 4096, # The maximum number of tokens in history that the AI can see. Increase for longer inputs.
+    "max_length": 128, # How many token to be generated at maximum. It might stop before this if EOS is allowed.
+    "rep_pen": 1.1, # Makes outputs less repetitive by penalizing repetition
+    "rep_pen_range": 512, # The range to which to apply repetition penalty
+    "rep_pen_slope": 0.7, # This number determains the strength of the repetition penalty over time
+    "temperature": 0.8, # How random should the AI outputs be? Lower values make output more predictable.
+    "top_k": 100, # Keep the X most probable tokens
+    "top_p": 0.9, # Top P sampling / Nucleus Sampling, https://arxiv.org/pdf/1904.09751.pdf
+    #"sampler_seed": 1337, # Use specific seed for text generation? This helps with consistency across tests.
+}
+
+try:
+    response = requests.post(f"{ENDPOINT}/v1/generate", json=payload) # Send prompt to API
+    if response.status_code == 200:
+        results = response.json()['results'] # Set results as JSON response
+        text = results[0]['text'] # inside results, look in first group for section labeled 'text'
+        print(text)
+except Exception as e:
+    print(f"An error occurred: {e}")
\ No newline at end of file
diff --git a/tools/mtmd/clip.cpp b/tools/mtmd/clip.cpp
index 1930841fa..ca2575ae3 100644
--- a/tools/mtmd/clip.cpp
+++ b/tools/mtmd/clip.cpp
@@ -2872,7 +2872,11 @@ bool clip_image_load_from_file(const char * fname, clip_image_u8 * img) {
 
 //note that the memory here must be subsequently freed!
 uint8_t* make_new_letterbox_img(uint8_t* input_image, int nx, int ny, int nc, int target_width, int target_height) {
-    int new_image_size = target_width * target_height * nc;
+    int new_image_size = (target_width * target_height * nc) + 512; //add some padding
+    if (target_width < nx || target_height < ny) {
+        printf("\nERROR: Target size smaller than input image\n");
+        return nullptr;
+    }
     uint8_t* letterboxed_image = (uint8_t*)malloc(new_image_size);
     if(letterboxed_image==nullptr)
     {
@@ -2960,6 +2964,11 @@ bool clip_image_load_from_bytes(const unsigned char * bytes, size_t bytes_length
             free(letterboxed_image);
             letterboxed_image = nullptr;
         }
+        else
+        {
+            //letterboxing failed. just use original image
+            clip_build_img_from_pixels(data, nx, ny, img);
+        }
     }
     else
     {