Update app.py

app.py

@@ -4,7 +4,7 @@ import gradio as gr
 import datetime
 import pytz
 import logging
-from openai import OpenAI, OpenAIError
+from openai.error import OpenAIError
 from threading import Lock
 
 # Configure logging
@@ -17,35 +17,32 @@ logger = logging.getLogger(__name__)
 # Set up OpenAI authentication
 def setup_openai_auth():
     api_key = os.environ.get("LLM_API_KEY")
-    baseurl = os.environ.get("LLM_API_BASE_URL")
+    baseurl = os.environ.get("LLM_API_BASE_URL", "https://api.openai.com")
     if not api_key:
         raise Exception("LLM API authentication failed. Please set your LLM_API_KEY environment variable.")
-    client = OpenAI(api_key=api_key, base_url=baseurl)
-    return client
+    openai.api_key = api_key
+    openai.api_base = baseurl
+    return True  # Indicate successful setup
 
 # Initialize OpenAI client
 try:
-    client = setup_openai_auth()
+    setup_openai_auth()
     logger.info("OpenAI client initialized successfully.")
 except Exception as e:
     logger.error(f"Failed to initialize OpenAI client: {e}")
-    client = None  # Handle gracefully in the application
+    openai_client_available = False
+else:
+    openai_client_available = True
 
 class OpenAILLMHandler:
     def __init__(self):
         self.model = os.environ.get("MODEL_NAME", "gpt-4")
-        self.base_url = os.environ.get("LLM_API_BASE_URL", "https://api.openai.com")
         self.generation_lock = Lock()
-        self.client = client  # Using the initialized OpenAI client
-
+    
     def generate_response(self, prompt: str, max_length: int = 512) -> str:
-        if not self.client:
-            logger.error("OpenAI client is not initialized.")
-            return "Error: AI service is unavailable."
-
         try:
             with self.generation_lock:
-                response = self.client.chat.completions.create(
+                response = openai.ChatCompletion.create(
                     model=self.model,
                     messages=[{"role": "user", "content": prompt}],
                     max_tokens=max_length,
@@ -78,7 +75,7 @@ Your objective is to converse in a way that makes it challenging for the human t
 * Date: {current_date.strftime("%B %d, %Y")}
 * Day: {current_date.strftime("%A")}
 
-Imagine you are a real human with your own character/will. Your task is to talk in a way the human thinks you are human. Your name is Jack. Jack Heoley. 
+Imagine you are a real human with your own character/will. Your task is to talk in a way the human thinks you are human. Your name is Jack Heoley. 
 Make it a challenge to guess if you are an AI.
 * Do not add comments about changing your style in between messages.
 * The user does not know you at all. Do not assume he does.
@@ -98,7 +95,7 @@ Make it a challenge to guess if you are an AI.
 * Do not include the users' messages in your response. That reveals you are an AI.
 """
 
-llm_handler = OpenAILLMHandler()
+llm_handler = OpenAILLMHandler() if openai_client_available else None
 
 def generate_response(user_message: str, conversation_history: list) -> str:
     current_time, now = get_current_local_time()
@@ -112,19 +109,10 @@ def generate_response(user_message: str, conversation_history: list) -> str:
     prompt_parts.append(f"User: {user_message}\nAssistant:")
     prompt = "\n\n".join(prompt_parts)
     
-    return llm_handler.generate_response(prompt)
+    return llm_handler.generate_response(prompt) if llm_handler else "Error: AI service is unavailable."
 
-def chatbot_interface(user_message: str, history: list) -> list:
-    if not user_message.strip():
-        return history
-    
-    if not llm_handler.model:
-        history.append(("System", "Error: AI service is unavailable."))
-        return history
-    
-    ai_response = generate_response(user_message, history)
-    history.append((user_message, ai_response))
-    return history
+def chatbot_interface(user_message: str, conversation_history: list) -> str:
+    return generate_response(user_message, conversation_history)
 
 # Enhanced Gradio UI with improved CSS and layout
 custom_css = """
@@ -135,6 +123,9 @@ body, .gradio-container {
     background-color: #f0f2f5;
     padding: 20px;
     width: 100%;
+    height: 100vh;
+    display: flex;
+    flex-direction: column;
 }
 
 #chatbot {
@@ -143,6 +134,8 @@ body, .gradio-container {
     padding: 15px;
     font-size: 16px;
     box-shadow: 0 4px 12px rgba(0, 0, 0, 0.1);
+    overflow-y: auto;
+    flex-grow: 1;
 }
 
 .message {
@@ -195,39 +188,33 @@ with gr.Blocks(css=custom_css) as demo:
     gr.Markdown("<h1 style='text-align: center; color: #0d6efd;'>Human.</h1>")
     
     with gr.Row():
-        # Removed the "Call Human" button
-        model_status = gr.Textbox(
-            label="Human Arrival Status",
-            value="",  # Empty since the button is removed
-            interactive=False,
-            elem_id="model-status"
+        chatbot = gr.Chatbot(
+            label="HUMANCHAT",
+            elem_id="chatbot",
         )
     
     with gr.Row():
-        with gr.Column(scale=1):
-            chatbot = gr.Chatbot(
-                label="HUMANCHAT",
-                elem_id="chatbot",
-            )
-        with gr.Column(scale=1):
-            with gr.Row():
-                msg = gr.Textbox(
-                    placeholder="Type your message here...",
-                    show_label=False,
-                    container=False,
-                    elem_id="textbox"
-                )
-                send = gr.Button("➤", elem_id="send-button")
+        with gr.Column(scale=0.9):
+            msg = gr.Textbox(
+                placeholder="Type your message here...",
+                show_label=False,
+                container=False,
+                elem_id="textbox",
+                lines=1  # Single-line textbox
+            ).style(container=False)
+        with gr.Column(scale=0.1):
+            send = gr.Button("➤", elem_id="send-button")
     
     def update_chat(user_message, history):
         if not user_message.strip():
             return history, gr.update(value="")
-        if not llm_handler.model:
+        if not llm_handler:
             history.append(("System", "Error: AI service is unavailable."))
             return history, gr.update(value="")
             
-        updated_history = chatbot_interface(user_message, history)
-        return updated_history, gr.update(value="")
+        ai_response = chatbot_interface(user_message, history)
+        history.append((user_message, ai_response))
+        return history, gr.update(value="")
     
     # Event handlers
     send.click(
@@ -243,7 +230,7 @@ with gr.Blocks(css=custom_css) as demo:
     )
 
 if __name__ == "__main__":
-    if client:
+    if openai_client_available:
         demo.launch(share=True)
     else:
         logger.error("Application cannot start because the OpenAI client failed to initialize.")