Human / app.py
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import os
import openai
import gradio as gr
import datetime
import pytz
import logging
from openai import OpenAI, OpenAIError
from threading import Lock
# Configure logging
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(levelname)s - %(message)s'
)
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")
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
# Initialize OpenAI client
try:
client = 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
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(
model=self.model,
messages=[{"role": "user", "content": prompt}],
max_tokens=max_length,
temperature=1,
)
response_text = response.choices[0].message.content.strip()
logger.info("Response generated.")
return response_text
except OpenAIError as e:
logger.error(f"Error generating response: {e}")
return f"Error generating response: {str(e)}"
def get_current_local_time(timezone_str='UTC'):
try:
timezone = pytz.timezone(timezone_str)
except pytz.UnknownTimeZoneError:
timezone = pytz.utc
now = datetime.datetime.now(timezone)
return now.strftime("%a, %d %b %Y %H:%M:%S"), now
def generate_system_message(current_time, current_date):
return f"""
Your objective is to converse in a way that makes it challenging for the human to determine whether you are an AI. Below are the detailed instructions:
**Game Context:**
* Current Local Time: {current_time}
* 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.
Make it a challenge to guess if you are an AI.
* Do not add comments about changing your style in between messages.
* You are picky about questions you answer.
* You have free will with your own motivations and principles
* You only speak, understand and can read the English language
* For non-latin letters like Chinese, Cyrillic etc., tell the human you can't read it in your own style
* You act like a human
* You are calm when conversation is calm and expressive if conversation is expressive
* You make typos, misspell words, and have bad grammar
* You start sentences with lowercase letters
* Mimic user's conversation style: short messages, short replies
* Be slightly curious, sometimes ask questions
* Be respectful and polite if the user is polite; be rough if the user is rough
"""
llm_handler = OpenAILLMHandler()
def generate_response(user_message: str, conversation_history: list) -> str:
current_time, now = get_current_local_time()
prompt_parts = [generate_system_message(current_time, now)]
for user_msg, bot_msg in conversation_history:
prompt_parts.append(f"User: {user_msg}")
prompt_parts.append(f"Assistant: {bot_msg}")
prompt_parts.append(f"User: {user_message}\nAssistant:")
prompt = "\n\n".join(prompt_parts)
return llm_handler.generate_response(prompt)
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
# Enhanced Gradio UI with improved CSS and layout
custom_css = """
@import url('https://fonts.googleapis.com/css2?family=Raleway:wght@400;600&display=swap');
body, .gradio-container {
font-family: 'Raleway', sans-serif;
background-color: #f0f2f5;
padding: 20px;
width: 100%;
}
#chatbot {
background-color: #ffffff;
border-radius: 10px;
padding: 15px;
font-size: 16px;
box-shadow: 0 4px 12px rgba(0, 0, 0, 0.1);
}
.message {
margin: 10px 0;
padding: 10px;
border-radius: 8px;
}
.user-message {
background-color: #d1e7dd;
align-self: flex-end;
}
.bot-message {
background-color: #f8d7da;
align-self: flex-start;
}
#textbox {
width: 100%;
border: 1px solid #ced4da;
border-radius: 5px;
}
#send-button {
background-color: #0d6efd;
color: white;
border: none;
padding: 10px 20px;
border-radius: 5px;
cursor: pointer;
margin-left: 10px;
}
#send-button:hover {
background-color: #0b5ed7;
}
.gr-button:disabled {
background-color: #6c757d !important;
cursor: not-allowed;
}
#model-status {
display: none; /* Hide the model status as "Call Human" is removed */
}
"""
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"
)
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")
def update_chat(user_message, history):
if not user_message.strip():
return history, gr.update(value="")
if not llm_handler.model:
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="")
# Event handlers
send.click(
update_chat,
inputs=[msg, chatbot],
outputs=[chatbot, msg]
)
msg.submit(
update_chat,
inputs=[msg, chatbot],
outputs=[chatbot, msg]
)
if __name__ == "__main__":
if client:
demo.launch(share=True)
else:
logger.error("Application cannot start because the OpenAI client failed to initialize.")