Update app.py

app.py

@@ -1,189 +1,122 @@
 import gradio as gr
 import os
 import sys
-import json 
+import json
 import requests
 import random
+from tenacity import retry, wait_fixed, stop_after_attempt
 
-
+# 模型配置和API URL
 MODEL = "o1-preview"
 API_URL = os.getenv("API_URL")
-DISABLED = os.getenv("DISABLED") == 'True'
-OPENAI_API_KEYS = os.getenv("OPENAI_API_KEYS").split(',')
-print (API_URL)
-print (OPENAI_API_KEYS)
-NUM_THREADS = int(os.getenv("NUM_THREADS"))
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
 
-print (NUM_THREADS)
+print(API_URL)
+print(OPENAI_API_KEY)
 
+# 异常处理函数
 def exception_handler(exception_type, exception, traceback):
     print("%s: %s" % (exception_type.__name__, exception))
 sys.excepthook = exception_handler
 sys.tracebacklimit = 0
-    
-def predict(inputs, top_p, temperature, chat_counter, chatbot, history, request:gr.Request):
+
+# 重试机制：如果请求失败，最多重试5次，每次等待2秒
+@retry(stop=stop_after_attempt(5), wait=wait_fixed(2))
+def call_openai_api(payload, headers):
+    response = requests.post(API_URL, headers=headers, json=payload, stream=True)
+    response.raise_for_status()  # 如果返回状态码不是200，抛出异常
+    return response
+
+# 处理API请求的核心函数
+def predict(inputs, top_p, temperature, chat_counter, chatbot, history):
     payload = {
         "model": MODEL,
         "messages": [{"role": "user", "content": f"{inputs}"}],
-        "temperature" : 1.0,
-        "top_p":1.0,
-        "n" : 1,
+        "temperature": temperature,
+        "top_p": top_p,
+        "n": 1,
         "stream": True,
-        "presence_penalty":0,
-        "frequency_penalty":0,
+        "presence_penalty": 0,
+        "frequency_penalty": 0,
     }
-    OPENAI_API_KEY = random.choice(OPENAI_API_KEYS)
-    print (OPENAI_API_KEY)
-    headers_dict = {key.decode('utf-8'): value.decode('utf-8') for key, value in request.headers.raw}
+    
     headers = {
         "Content-Type": "application/json",
-        "Authorization": f"Bearer {OPENAI_API_KEY}",
-        "Headers": f"{headers_dict}"
+        "Authorization": f"Bearer {OPENAI_API_KEY}"
     }
 
-    # print(f"chat_counter - {chat_counter}")
-    if chat_counter != 0 :
+    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
+            role = 'user' if i % 2 == 0 else 'assistant'
+            message = {"role": role, "content": data}
             messages.append(message)
-        
-        message = {}
-        message["role"] = "user" 
-        message["content"] = inputs
-        messages.append(message)
+
+        messages.append({"role": "user", "content": inputs})
         payload = {
             "model": MODEL,
             "messages": messages,
-            "temperature" : temperature,
+            "temperature": temperature,
             "top_p": top_p,
-            "n" : 1,
+            "n": 1,
             "stream": True,
-            "presence_penalty":0,
-            "frequency_penalty":0,
+            "presence_penalty": 0,
+            "frequency_penalty": 0,
         }
 
     chat_counter += 1
-
     history.append(inputs)
-    token_counter = 0 
-    partial_words = "" 
+    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}")
-        
+        # 使用重试机制的 API 请求
+        response = call_openai_api(payload, headers)
+
         for chunk in response.iter_lines():
-            #print (chunk)
-            #sys.stdout.flush()
-            #Skipping first chunk
             if counter == 0:
                 counter += 1
                 continue
-                #counter+=1
-            # check whether each line is non-empty
-            if chunk.decode() :
+            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"]
+                    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 [(history[i], 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}  
+                    yield [(history[i], history[i + 1]) for i in range(0, len(history) - 1, 2)], history, chat_counter  # 更新chatbot内容
+
     except Exception as e:
-        print (f'error found: {e}')
-    yield [(history[i], 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}))
-                   
+        print(f'Error encountered: {e}')
+    yield [(history[i], history[i + 1]) for i in range(0, len(history) - 1, 2)], history, chat_counter
 
+# 重置输入框
 def reset_textbox():
-    return gr.update(value='', interactive=False), gr.update(interactive=False)
-
-title = """<h1 align="center">OpenAI-O1-Preview: Research Preview (Short-Term Availability)</h1>"""
-if DISABLED:
-    title = """<h1 align="center" style="color:red">This app has reached OpenAI's usage limit. Please check back tomorrow.</h1>"""
-description = """Language models can be conditioned to act like dialogue agents through a conversational prompt that typically takes the form:
-```
-User: <utterance>
-Assistant: <utterance>
-User: <utterance>
-Assistant: <utterance>
-...
-```
-In this app, you can explore the outputs of a gpt-4 turbo LLM.
-"""
-
-theme = gr.themes.Default(primary_hue="green")                
-
-with gr.Blocks(css = """#col_container { margin-left: auto; margin-right: auto;}
-                #chatbot {height: 520px; overflow: auto;}""",
-              theme=theme) as demo:
+    return gr.update(value='', interactive=False)
+
+# Gradio 界面部分
+title = """<h1 align="center">OpenAI-O1-Preview: Personal Version</h1>"""
+description = """This app allows a single user to interact with an OpenAI GPT-4 Turbo model."""
+
+with gr.Blocks() as demo:
     gr.HTML(title)
-    gr.HTML("""<h3 align="center" style="color: red;">If this app doesn't respond, consider trying our O1-mini app:<br/><a href="https://huggingface.co/spaces/yuntian-deng/o1mini">https://huggingface.co/spaces/yuntian-deng/o1mini</a></h3>""")
-
-    #gr.HTML('''<center><a href="https://huggingface.co/spaces/ysharma/ChatGPT4?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:
-        #GPT4 API Key is provided by Huggingface 
-        #openai_api_key = gr.Textbox(type='password', label="Enter only your GPT4 OpenAI API key here")
-        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(visible=not DISABLED) #.style(full_width=True)
-            with gr.Column(scale=3):
-                server_status_code = gr.Textbox(label="Status code from OpenAI server", )
-    
-        #inputs, top_p, temperature, top_k, repetition_penalty
-        with gr.Accordion("Parameters", open=False):
-            top_p = gr.Slider( minimum=-0, maximum=1.0, value=1.0, step=0.05, interactive=True, label="Top-p (nucleus sampling)",)
-            temperature = gr.Slider( minimum=-0, maximum=5.0, value=1.0, step=0.1, interactive=True, label="Temperature",)
-            #top_k = gr.Slider( minimum=1, maximum=50, value=4, step=1, interactive=True, label="Top-k",)
-            #repetition_penalty = gr.Slider( minimum=0.1, maximum=3.0, value=1.03, step=0.01, interactive=True, label="Repetition Penalty", )
-            chat_counter = gr.Number(value=0, visible=False, precision=0)
     
-    with gr.Column(elem_id = "user_consent_container") as user_consent_block:
-        # Get user consent
-        accept_checkbox = gr.Checkbox(visible=False)
-        js = "(x) => confirm('By clicking \"OK\", I agree that my data may be published or shared.')"
-        with gr.Accordion("User Consent for Data Collection, Use, and Sharing", open=True):
-            gr.HTML("""
-            <div>
-                <p>By using our app, which is powered by OpenAI's API, you acknowledge and agree to the following terms regarding the data you provide:</p>
-                <ol>
-                    <li><strong>Collection:</strong> We may collect information, including the inputs you type into our app, the outputs generated by OpenAI's API, and certain technical details about your device and connection (such as browser type, operating system, and IP address) provided by your device's request headers.</li>
-                    <li><strong>Use:</strong> We may use the collected data for research purposes, to improve our services, and to develop new products or services, including commercial applications, and for security purposes, such as protecting against unauthorized access and attacks.</li>
-                    <li><strong>Sharing and Publication:</strong> Your data, including the technical details collected from your device's request headers, may be published, shared with third parties, or used for analysis and reporting purposes.</li>
-                    <li><strong>Data Retention:</strong> We may retain your data, including the technical details collected from your device's request headers, for as long as necessary.</li>
-                </ol>
-                <p>By continuing to use our app, you provide your explicit consent to the collection, use, and potential sharing of your data as described above. If you do not agree with our data collection, use, and sharing practices, please do not use our app.</p>
-            </div>
-            """)
-            accept_button = gr.Button("I Agree")
-
-        def enable_inputs():
-            return gr.update(visible=False), gr.update(visible=True)
-
-    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)
-
-    inputs.submit(reset_textbox, [], [inputs, b1], queue=False)
-    inputs.submit(predict, [inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter, server_status_code, inputs, b1],)  #openai_api_key
-    b1.click(reset_textbox, [], [inputs, b1], queue=False)
-    b1.click(predict, [inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter, server_status_code, inputs, b1],)  #openai_api_key
-             
-    demo.queue(max_size=10, default_concurrency_limit=NUM_THREADS, api_open=False).launch(share=False)
+    chatbot = gr.Chatbot()  # 对话框
+    inputs = gr.Textbox(placeholder="Type your input here", label="Input")
+    state = gr.State([])  # 保存历史对话
+    chat_counter = gr.Number(value=0, visible=False, precision=0)  # 计数器
+
+    # 参数控制
+    with gr.Accordion("Advanced Parameters", open=False):
+        top_p = gr.Slider(minimum=0, maximum=1.0, value=1.0, step=0.05, interactive=True, label="Top-p")
+        temperature = gr.Slider(minimum=0, maximum=5.0, value=1.0, step=0.1, interactive=True, label="Temperature")
+
+    # 处理用户提交的输入
+    inputs.submit(reset_textbox, [], [inputs], queue=False)
+    inputs.submit(predict, [inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter], queue=False)
+
+# 启动Gradio应用
+demo.launch(share=False)