Update app.py

app.py

@@ -1,12 +1,20 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+from gradio_client import Client, handle_file
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+# Gradio Client
+client = Client("vikhyatk/moondream2")
 
+# Resmi tanımlayan fonksiyon
+def describe_image(image):
+    result = client.predict(
+        img=handle_file(image),
+        prompt="Describe this image.",
+        api_name="/answer_question"
+    )
+    return result
 
+# ChatInterface ve resim işleme fonksiyonu
 def respond(
     message,
     history: list[tuple[str, str]],
@@ -14,19 +22,26 @@ def respond(
     max_tokens,
     temperature,
     top_p,
+    image
 ):
+    # Sistem mesajını ve önceki sohbeti al
     messages = [{"role": "system", "content": system_message}]
-
+    
     for val in history:
         if val[0]:
             messages.append({"role": "user", "content": val[0]})
         if val[1]:
             messages.append({"role": "assistant", "content": val[1]})
 
+    # Resim ile ilgili açıklamayı ekle
+    image_description = describe_image(image)
+    messages.append({"role": "assistant", "content": image_description})
+
+    # Kullanıcı mesajını ekle
     messages.append({"role": "user", "content": message})
 
     response = ""
-
+    # Modelden gelen yanıtı al ve döngüde token'ları birleştir
     for message in client.chat_completion(
         messages,
         max_tokens=max_tokens,
@@ -35,30 +50,21 @@ def respond(
         top_p=top_p,
     ):
         token = message.choices[0].delta.content
-
         response += token
         yield response
 
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
+# Gradio app arayüzünü oluştur
+demo = gr.Interface(
+    fn=respond,
+    inputs=[
         gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
         gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
         gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
+        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
+        gr.Image(type="pil", label="Upload an Image")  # Resim girişi
     ],
+    outputs="text",  # Çıktıyı metin olarak ver
 )
 
-
 if __name__ == "__main__":
     demo.launch()