Update app.py

app.py

@@ -8,6 +8,7 @@ import re
 import io
 from PIL import Image, ImageDraw, ImageOps, ImageFont
 from base64 import b64encode
+import shutil
 
 from langchain.chains import LLMChain, RetrievalQA
 from langchain.chat_models import ChatOpenAI
@@ -76,6 +77,7 @@ HEADERS = {"Authorization": f"Bearer {HUGGINGFACEHUB_API_TOKEN}"}
 PATH_WORK = "."
 CHROMA_DIR  = "/chroma"
 YOUTUBE_DIR = "/youtube"
+HISTORY_PFAD = "/data/history"
 
 ###############################################
 #URLs zu Dokumenten oder andere Inhalte, die einbezogen werden sollen
@@ -154,10 +156,21 @@ def umwandeln_fuer_anzeige(image):
         return buffer.getvalue()
 
 def process_image(image_path, prompt):
+    #Bild aus tmp in Space ablegen
+    #temp_image_path = "/tmp/gradio/01834b95fcf793903d65ab947cc410dc1600d0df/bbb 1.png"
+    # Zielverzeichnis für das dauerhafte Bild
+    #target_directory = HISTORY_PFAD
+    # Ziel-Pfad für das dauerhafte Bild
+    #target_image_path = os.path.join(target_directory, "bbb 1.png")
+    # Kopieren Sie das temporäre Bild in das Zielverzeichnis
+    #shutil.copy(temp_image_path, target_image_path)
+
     # Convert image to base64
-    with open(image_path, "rb") as image_file:
+    #with open(image_path, "rb") as image_file:
+    with open("data/history/bbb 1.png", "rb") as image_file:
         encoded_string = b64encode(image_file.read()).decode()
-
+    print ("necoded string.................")
+    print(encoded_string)
     # Prepare the data for the API request (specific to the API you're using)
     data = {
         'image': encoded_string,
@@ -392,15 +405,10 @@ def generate_auswahl(prompt, file, chatbot, history, rag_option, model_option, o
         result = response.content 
         #Bild ausgeben
         image = Image.open(io.BytesIO(result)) 
-        print("result image...............")
-        print (image)
         image_64 = umwandeln_fuer_anzeige(image)
-        print("result image 64...............")
-        print (image_64)
         chatbot[-1][1] =  "<img src='data:image/png;base64,{0}'/>".format(b64encode(image_64).decode('utf-8')) 
         history = history + [(prompt, result)]  
-        print("history zeichnen......................")
-        print(chatbot)
+
         return chatbot, history, "Success"
      else:
         result = generate_text(prompt, file, chatbot, history, rag_option, model_option, openai_api_key, k=3, top_p=0.6, temperature=0.5, max_new_tokens=4048, max_context_length_tokens=2048, repetition_penalty=1.3,)
@@ -410,11 +418,7 @@ def generate_auswahl(prompt, file, chatbot, history, rag_option, model_option, o
             history = history + [(prompt, result)]
         else:
             history = history + [((file,), None),(prompt, result)]
-            
-        print("history nach Zusatz und mit KI Antwort...........")
-        print(history)
-        print("chatbot nach Zusatz und mit KI Antwort...........")
-        print(chatbot)
+
         return chatbot, history, "Success" 
         """ 
         for character in result:
@@ -452,13 +456,7 @@ def generate_text (prompt, file, chatbot, history, rag_option, model_option, ope
     if (file == None):
         history_text_und_prompt = generate_prompt_with_history_openai(prompt, history)
     else:
-        print("file bild uplad....................")
-        print(file)
-        #image = Image.open(io.BytesIO(file_anzeigen)) 
-        #image_64 = umwandeln_fuer_anzeige(image)
         prompt_neu = process_image(file, prompt)
-        print("prompt_neu............................")
-        print(prompt_neu)
         history_text_und_prompt = generate_prompt_with_history_openai(prompt_neu, history)
         
     #history für HuggingFace Models formatieren