Update app.py

app.py

@@ -126,9 +126,16 @@ os.environ["HUGGINGFACEHUB_API_TOKEN"] = HUGGINGFACEHUB_API_TOKEN
 
 ##############################################
 #History - die Frage oder das File eintragen...
-def add_text(history, prompt):
-    history = history + [(prompt, None)]
-    return history, prompt, "" #gr.Textbox(value="", interactive=False)
+def add_text(history, prompt, file):
+    if (file == None):
+        history = history + [(prompt, None)]
+    else:
+        if (prompt == ""):
+            history = history + [((file.name,), "Prompt fehlt!")]
+        else:
+            history = history + [((file.name,), None), (prompt, None)]
+            
+    return history, prompt, gr.Textbox(value="", interactive=False)
     
 def add_file(history, file, prompt):
     if (prompt == ""):
@@ -137,7 +144,7 @@ def add_file(history, file, prompt):
         history = history + [((file.name,), None), (prompt, None)]
     return history, prompt, ""
 
-def create_picture(history,  prompt):
+def create_picture_backup(history,  prompt):
     client = OpenAI()
     response = client.images.generate(model="dall-e-3", prompt=prompt,size="1024x1024",quality="standard",n=1,)
     image_url = response.data[0].url
@@ -325,6 +332,22 @@ def chatbot_response(messages):
             print("Bild.............................")
     return responses
 
+def create_picture(history,  prompt):
+    client = OpenAI()
+    response = client.images.generate(model="dall-e-3", prompt=prompt,size="1024x1024",quality="standard",n=1,)
+    image_url = response.data[0].url
+    return image_url
+
+# prompt describing the desired image 
+#text = "batman art in red and blue color"
+# calling the custom function "generate" 
+# saving the output in "url1" 
+#url1 = create_picture(text) 
+# using requests library to get the image in bytes 
+#response = requests.get(url1) 
+# using the Image module from PIL library to view the image 
+#Image.open(response.raw)
+
   
 def invoke (prompt, 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,):
     global splittet
@@ -334,12 +357,11 @@ def invoke (prompt, history, rag_option, model_option, openai_api_key, k=3, top_
         history_text_und_prompt = generate_prompt_with_history(prompt, history)
     else:
         history_file_und_prompt = generate_prompt_with_history(prompt, history)
+        
     #history für HuggingFace Models formatieren
     #history_text_und_prompt = generate_prompt_with_history_hf(prompt, history)
-
     #history für openAi formatieren
     #history_text_und_prompt = generate_prompt_with_history_openai(prompt, history)
-
     #history für Langchain formatieren
     #history_text_und_prompt = generate_prompt_with_history_langchain(prompt, history)
     
@@ -357,10 +379,10 @@ def invoke (prompt, history, rag_option, model_option, openai_api_key, k=3, top_
         ###########################
         if (model_option == "OpenAI"):
             #Anfrage an OpenAI ----------------------------
-            if (file == None):
+            if (prompt.find('Bild zeichnen')):
+                llm = ChatOpenAI(model_name = MODEL_NAME_OAI_ZEICHNEN,  openai_api_key = openai_api_key, temperature=temperature)#, top_p = top_p)    
+            else: 
                 llm = ChatOpenAI(model_name = MODEL_NAME,  openai_api_key = openai_api_key, temperature=temperature)#, top_p = top_p)
-            else: MODEL_NAME_OAI_ZEICHNEN
-                llm = ChatOpenAI(model_name = MODEL_NAME_OAI_ZEICHNEN,  openai_api_key = openai_api_key, temperature=temperature)#, top_p = top_p)
                 
             print("openAI")
         else:
@@ -385,34 +407,32 @@ def invoke (prompt, history, rag_option, model_option, openai_api_key, k=3, top_
             db = document_retrieval_mongodb(llm, history_text_und_prompt)
             result = rag_chain(llm, history_text_und_prompt, db)
         else:
-            print("LLM aufrufen via HF: ...........")
+            print("LLM aufrufen ohne RAG: ...........")
             result = llm_chain(llm, history_text_und_prompt)
             print(result)
 
     except Exception as e:
         raise gr.Error(e)
 
-    """
-    #Antwort als Stream ausgeben... 
-    for i in range(len(result)):
-        time.sleep(0.05)
-        yield  result[: i+1]
-    """
-
-    #Antwort als Stream ausgeben... 
-    history[-1][1] = ""
-    for character in result:
-        history[-1][1] += character
-        time.sleep(0.03)
-        yield history, "Generating"
-        if shared_state.interrupted:
-            shared_state.recover()
-            try:
-                yield history, "Stop: Success"
-                return
-            except:
-                pass
-    
+
+    if (prompt.find('Bild zeichnen')):
+        history[-1][1] = result
+        return history, "Stop: Success"
+    else:
+        #Antwort als Stream ausgeben... wenn Textantwort gefordert
+        history[-1][1] = ""
+        for character in result:
+            history[-1][1] += character
+            time.sleep(0.03)
+            yield history, "Generating"
+            if shared_state.interrupted:
+                shared_state.recover()
+                try:
+                    yield history, "Stop: Success"
+                    return
+                except:
+                    pass
+        
 ################################################
 #GUI
 ###############################################
@@ -457,7 +477,8 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
                     cancelBtn = gr.Button("Stop")
             with gr.Row():
                 emptyBtn = gr.ClearButton( [user_input, chatbot], value="🧹 Neue Session")  
-                btn = gr.UploadButton("📁", file_types=["image", "video", "audio"])
+                upload = gr.UploadButton("📁", file_types=["image", "video", "audio"])
+                file_display = gr.File(label=None, interactive=False,  height=20)
 
         with gr.Column():
             with gr.Column(min_width=50, scale=1):
@@ -530,17 +551,17 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
     )
 
     # Chatbot
-    transfer_input_args_text = dict(
-        fn=add_text, inputs=[chatbot, user_input], outputs=[chatbot, user_question, user_input], show_progress=True
+    transfer_input_args = dict(
+        fn=add_text, inputs=[ chatbot, user_input, upload], outputs=[chatbot,  user_input], show_progress=True
     )
     transfer_input_args_file = dict(
         fn=add_file, inputs=[chatbot, btn, user_input], outputs=[chatbot, user_question, user_input], show_progress=True
     )
 
     predict_event1 = user_input.submit(**transfer_input_args_text, queue=False,).then(**predict_args)
-    predict_event3 = btn.upload(**transfer_input_args_file,queue=False,).then(**predict_args)
     predict_event2 = submitBtn.click(**transfer_input_args_text, queue=False,).then(**predict_args)
-
+    predict_event3 = upload.upload(file_anzeigen, [ upload], [file_display] ) #.then(**predict_args)
+    
     cancelBtn.click(
         cancels=[predict_event1,predict_event2, predict_event3 ]
     )