Update app.py

app.py

@@ -165,13 +165,11 @@ def process_image(image_path, prompt):
     with open(image_path, "rb") as image_file:
         encoded_string = base64.b64encode(image_file.read()).decode('utf-8')
 
-
     # Prepare the data for the API request (specific to the API you're using)
     headers = {
               "Content-Type": "application/json",
               "Authorization": f"Bearer {OAI_API_KEY}"
             }
-
     payload = {
       "model": MODEL_NAME_IMAGE,
       "messages": [
@@ -228,7 +226,8 @@ def generate_auswahl(prompt, file, chatbot, history, rag_option, model_option, o
 ##################################################
 #zu einem Text-Prompt ein Bild via Stable Diffusion generieren
 def generate_bild(prompt, chatbot,  temperature=0.5, max_new_tokens=4048,top_p=0.6, repetition_penalty=1.3):
-    print("Bild Erzeugung..............................")
+    """
+    print("Bild Erzeugung HF..............................")
     #Bild nach Anweisung zeichnen und in History darstellen...
     data = {"inputs": prompt}
     response = requests.post(API_URL, headers=HEADERS, json=data)
@@ -239,7 +238,13 @@ def generate_bild(prompt, chatbot,  temperature=0.5, max_new_tokens=4048,top_p=0
     image_64 = umwandeln_fuer_anzeige(image)
     chatbot[-1][1]= "<img src='data:image/png;base64,{0}'/>".format(base64.b64encode(image_64).decode('utf-8'))
     return chatbot, "Success"
-
+    """
+    print("Bild Erzeugung DallE..............................")
+    client = OpenAI()
+    #als Format ginge auch 'b64_json', n - Anz. der erzeugten Bilder
+    response = client.images.generate(model="dall-e-3",prompt=prompt,size="1024x1024",quality="standard",n=1, response_format=url) 
+    chatbot[-1][1]=image_url = response.data[0].url
+    return chatbot, "Success"
     
 
 ##################################################