Update app.py

app.py

@@ -15,6 +15,8 @@ OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
 NUM_THREADS = int(16)
 TOTAL_K = 5
 SAMPLE_IDX = []
+RANDOM_POSITION = [(145 + 200 * i + 400 * (i//2), j * 110 + 900) for i in range(4) for j in range(4) ]
+CURRENT_POSITION = []
 
 print (NUM_THREADS)
 
@@ -42,89 +44,90 @@ def parse_codeblock(text):
                 lines[i] = "<br/>" + line.replace("<", "&lt;").replace(">", "&gt;")
     return "".join(lines)
     
-def predict(inputs, top_p, temperature, chat_counter, chatbot, history, request:gr.Request):
-    payload = {
-        "model": MODEL,
-        "messages": [{"role": "user", "content": f"{inputs}"}],
-        "temperature" : 1.0,
-        "top_p":1.0,
-        "n" : 1,
-        "stream": True,
-        "presence_penalty":0,
-        "frequency_penalty":0,
-    }
-
-    headers = {
-        "Content-Type": "application/json",
-        "Authorization": f"Bearer {OPENAI_API_KEY}",
-        "Headers": f"{request.kwargs['headers']}"
-    }
-
-    # print(f"chat_counter - {chat_counter}")
-    if chat_counter != 0 :
-        messages = []
-        for i, data in enumerate(history):
-            if i % 2 == 0:
-                role = 'user'
-            else:
-                role = 'assistant'
-            message = {}
-            message["role"] = role
-            message["content"] = data
-            messages.append(message)
+    
+# def predict(inputs, top_p, temperature, chat_counter, chatbot, history, request:gr.Request):
+#     payload = {
+#         "model": MODEL,
+#         "messages": [{"role": "user", "content": f"{inputs}"}],
+#         "temperature" : 1.0,
+#         "top_p":1.0,
+#         "n" : 1,
+#         "stream": True,
+#         "presence_penalty":0,
+#         "frequency_penalty":0,
+#     }
+
+#     headers = {
+#         "Content-Type": "application/json",
+#         "Authorization": f"Bearer {OPENAI_API_KEY}",
+#         "Headers": f"{request.kwargs['headers']}"
+#     }
+
+#     # print(f"chat_counter - {chat_counter}")
+#     if chat_counter != 0 :
+#         messages = []
+#         for i, data in enumerate(history):
+#             if i % 2 == 0:
+#                 role = 'user'
+#             else:
+#                 role = 'assistant'
+#             message = {}
+#             message["role"] = role
+#             message["content"] = data
+#             messages.append(message)
         
-        message = {}
-        message["role"] = "user" 
-        message["content"] = inputs
-        messages.append(message)
-        payload = {
-            "model": MODEL,
-            "messages": messages,
-            "temperature" : temperature,
-            "top_p": top_p,
-            "n" : 1,
-            "stream": True,
-            "presence_penalty":0,
-            "frequency_penalty":0,
-        }
-
-    chat_counter += 1
-
-    history.append(inputs)
-    token_counter = 0 
-    partial_words = "" 
-    counter = 0
-
-    try:
-        # make a POST request to the API endpoint using the requests.post method, passing in stream=True
-        response = requests.post(API_URL, headers=headers, json=payload, stream=True)
-        response_code = f"{response}"
-        #if response_code.strip() != "<Response [200]>":
-        #    #print(f"response code - {response}")
-        #    raise Exception(f"Sorry, hitting rate limit. Please try again later. {response}")
+#         message = {}
+#         message["role"] = "user" 
+#         message["content"] = inputs
+#         messages.append(message)
+#         payload = {
+#             "model": MODEL,
+#             "messages": messages,
+#             "temperature" : temperature,
+#             "top_p": top_p,
+#             "n" : 1,
+#             "stream": True,
+#             "presence_penalty":0,
+#             "frequency_penalty":0,
+#         }
+
+#     chat_counter += 1
+
+#     history.append(inputs)
+#     token_counter = 0 
+#     partial_words = "" 
+#     counter = 0
+
+#     try:
+#         # make a POST request to the API endpoint using the requests.post method, passing in stream=True
+#         response = requests.post(API_URL, headers=headers, json=payload, stream=True)
+#         response_code = f"{response}"
+#         #if response_code.strip() != "<Response [200]>":
+#         #    #print(f"response code - {response}")
+#         #    raise Exception(f"Sorry, hitting rate limit. Please try again later. {response}")
         
-        for chunk in response.iter_lines():
-            #Skipping first chunk
-            if counter == 0:
-                counter += 1
-                continue
-                #counter+=1
-            # check whether each line is non-empty
-            if chunk.decode() :
-                chunk = chunk.decode()
-                # decode each line as response data is in bytes
-                if len(chunk) > 12 and "content" in json.loads(chunk[6:])['choices'][0]['delta']:
-                    partial_words = partial_words + json.loads(chunk[6:])['choices'][0]["delta"]["content"]
-                    if token_counter == 0:
-                        history.append(" " + partial_words)
-                    else:
-                        history[-1] = partial_words
-                    token_counter += 1
-                    yield [(parse_codeblock(history[i]), parse_codeblock(history[i + 1])) for i in range(0, len(history) - 1, 2) ], history, chat_counter, response, gr.update(interactive=False), gr.update(interactive=False)  # resembles {chatbot: chat, state: history}  
-    except Exception as e:
-        print (f'error found: {e}')
-    yield [(parse_codeblock(history[i]), parse_codeblock(history[i + 1])) for i in range(0, len(history) - 1, 2) ], history, chat_counter, response, gr.update(interactive=True), gr.update(interactive=True)
-    print(json.dumps({"chat_counter": chat_counter, "payload": payload, "partial_words": partial_words, "token_counter": token_counter, "counter": counter}))
+#         for chunk in response.iter_lines():
+#             #Skipping first chunk
+#             if counter == 0:
+#                 counter += 1
+#                 continue
+#                 #counter+=1
+#             # check whether each line is non-empty
+#             if chunk.decode() :
+#                 chunk = chunk.decode()
+#                 # decode each line as response data is in bytes
+#                 if len(chunk) > 12 and "content" in json.loads(chunk[6:])['choices'][0]['delta']:
+#                     partial_words = partial_words + json.loads(chunk[6:])['choices'][0]["delta"]["content"]
+#                     if token_counter == 0:
+#                         history.append(" " + partial_words)
+#                     else:
+#                         history[-1] = partial_words
+#                     token_counter += 1
+#                     yield [(parse_codeblock(history[i]), parse_codeblock(history[i + 1])) for i in range(0, len(history) - 1, 2) ], history, chat_counter, response, gr.update(interactive=False), gr.update(interactive=False)  # resembles {chatbot: chat, state: history}  
+#     except Exception as e:
+#         print (f'error found: {e}')
+#     yield [(parse_codeblock(history[i]), parse_codeblock(history[i + 1])) for i in range(0, len(history) - 1, 2) ], history, chat_counter, response, gr.update(interactive=True), gr.update(interactive=True)
+#     print(json.dumps({"chat_counter": chat_counter, "payload": payload, "partial_words": partial_words, "token_counter": token_counter, "counter": counter}))
                    
 
 def reset_textbox():
@@ -134,12 +137,11 @@ def random_sample():
     SAMPLE_IDX = random.choices(range(25), k=TOTAL_K)
     image = np.array(Image.open(os.path.join(os.path.dirname(__file__), "data/Court.jpeg")))
     random_characters = [Image.open(os.path.join(os.path.dirname(__file__), f'data/characters_{idx:02}.png')).resize((64, 64)) for idx in SAMPLE_IDX]
-    random_position = [(145 + 200 * i + 400 * (i//2), j * 110 + 900) for i in range(4) for j in range(4) ]
-    random_position = random.choices(random_position, k = TOTAL_K)
+    current_position = random.choices(RANDOM_POSITION, k = TOTAL_K)
     new_image = Image.fromarray(image).convert('RGBA')
     for k in range(TOTAL_K):
-        new_image.paste(random_characters[k], random_position[k], random_characters[k])
-    return np.array(new_image)
+        new_image.paste(random_characters[k], current_position[k], random_characters[k])
+    return np.array(new_image), current_position
 
 def reset_sample():
     image = np.array(Image.open(os.path.join(os.path.dirname(__file__), "data/Court.jpeg")))
@@ -160,6 +162,9 @@ Assistant: <utterance>
 In this app, you can explore the outputs of a gpt-3.5 LLM.
 """
 
+def sumbit(image):
+    
+
 theme = gr.themes.Default(primary_hue="green")
 agents = []
 with gr.Blocks(css = """#col_container { margin-left: auto; margin-right: auto;}
@@ -170,14 +175,7 @@ with gr.Blocks(css = """#col_container { margin-left: auto; margin-right: auto;}
 
     #gr.HTML('''<center><a href="https://huggingface.co/spaces/yuntian-deng/ChatGPT?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>Duplicate the Space and run securely with your OpenAI API Key</center>''')
     with gr.Column(elem_id = "col_container", visible=False) as main_block:
-        #API Key is provided by OpenAI 
-        #openai_api_key = gr.Textbox(type='password', label="Enter only your OpenAI API key here")
-        # gr.HTML(f"""
-        #     <a href="https://huggingface.co/spaces/JiheonJeong/Temp2/resolve/main/data/Court.jpeg" target="_blank">
-        #         <img class="image-container" src="https://huggingface.co/spaces/JiheonJeong/Temp2/resolve/main/data/Court.jpeg" alt="이미지">
-
-        #     </a>
-        # """)
+
         with gr.Row():
             with gr.Column(scale=7):
                 image = gr.Image(os.path.join(os.path.dirname(__file__), "data/Court.jpeg"), height = 800, width = 1600)
@@ -185,19 +183,14 @@ with gr.Blocks(css = """#col_container { margin-left: auto; margin-right: auto;}
                 for idx in range(TOTAL_K):
                     text = gr.Textbox(label=f"Random Sample - {idx+1}")
                     agents.append(text)
-                
-                # text1 = gr.Textbox(label="Random Sample - 1")
-                # text2 = gr.Textbox(label="Random Sample - 2")
-                # text3 = gr.Textbox(label="Random Sample - 3")
 
         # chatbot = gr.Chatbot(elem_id='chatbot') #c
-        inputs = gr.Textbox(placeholder= "Hi there!", label= "Type an input and press Enter") #t
-        # state = gr.State([]) #s
-        # with gr.Row():
-        #     with gr.Column(scale=7):
-        #         b1 = gr.Button("Submission", visible=not DISABLED)
-        #     with gr.Column(scale=3):
-        #         server_status_code = gr.Textbox(label="Status code from OpenAI server", )
+        with gr.Row():
+            with gr.Column(scale=7):
+                inputs = gr.Textbox(placeholder= "Hi there!", label= "Type an input and press Enter") #t
+            with gr.Column(scale=3):
+                b1 = gr.Button('Submit', visible=not DISABLED)
+
         with gr.Row():
             with gr.Column(scale=7):
                 b0 = gr.Button('Random Sample', visible=not DISABLED)
@@ -238,7 +231,7 @@ with gr.Blocks(css = """#col_container { margin-left: auto; margin-right: auto;}
     accept_button.click(None, None, accept_checkbox, _js=js, queue=False)
     accept_checkbox.change(fn=enable_inputs, inputs=[], outputs=[user_consent_block, main_block], queue=False)
 
-    b0.click(random_sample, inputs = [], outputs = [image])
+    b0.click(random_sample, inputs = [], outputs = [image, CURRENT_POSITION])
     b2.click(reset_sample, inputs = [], outputs = [image])
                   
     # inputs.submit(reset_textbox, [], [inputs, b1], queue=False)