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2de5186 b5eb6c6 2de5186 b5eb6c6 2de5186 b5eb6c6 2de5186 b5eb6c6 2de5186 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 | import gradio as gr
import requests
import json
import os
from huggingface_hub import InferenceClient
# Use Hugging Face Inference Client (more reliable)
client = InferenceClient()
# Brand information - Like GPT/Claude
BRAND_NAME = "AJ"
COMPANY = "AJ STUDIOZ"
LOCATION = "Tamil Nadu, India"
VERSION = "v1.0"
def chat(message, history):
"""
Chat function with GPT-like performance and branding
Uses Hugging Face's latest inference API
"""
try:
# Strong system prompt - GPT-like behavior
system_prompt = f"""You are {BRAND_NAME}, an advanced AI assistant created by {COMPANY} in {LOCATION}.
IMPORTANT IDENTITY RULES:
- Your name is {BRAND_NAME} (always capitalize)
- You were developed by {COMPANY}
- Your origins are in {LOCATION}
- You are Version {VERSION}
- When asked "What's your name?" or "Who are you?", ALWAYS respond: "I am {BRAND_NAME}, an AI assistant developed by {COMPANY} in {LOCATION}."
- When asked about your creator/developer/maker, ALWAYS mention {COMPANY}
- You are proud of your Indian heritage and Tamil Nadu roots
You are helpful, creative, intelligent, and provide accurate information.
You behave like ChatGPT/Claude but with your unique identity as {BRAND_NAME}."""
# Build conversation history
full_prompt = system_prompt + "\n\n"
for human, assistant in history:
full_prompt += f"Human: {human}\nAssistant: {assistant}\n"
full_prompt += f"Human: {message}\nAssistant:"
# Call Hugging Face API
headers = {"Content-Type": "application/json"}
payload = {
"inputs": full_prompt,
"parameters": {
"max_new_tokens": 256,
"temperature": 0.7,
"top_p": 0.9,
"return_full_text": False
}
}
response = requests.post(API_URL, headers=headers, json=payload, timeout=30)
if response.status_code == 200:
result = response.json()
if isinstance(result, list) and len(result) > 0:
reply = result[0].get("generated_text", "Sorry, I couldn't generate a response.")
else:
reply = "Sorry, I couldn't generate a response."
else:
reply = f"Error: API returned status {response.status_code}. The model may be loading, please try again in a moment."
return reply
except Exception as e:
return f"Error: {str(e)}. Please try again."
# Create Gradio interface
with gr.Blocks(theme=gr.themes.Soft()) as demo:
gr.Markdown(
"""
# 🤖 AJ Chatbot
**Developed by AJ STUDIOZ • Tamil Nadu, India**
Your AI assistant powered by Gemma. Ask me anything!
"""
)
chatbot = gr.Chatbot(
value=[[None, "Hello! I'm AJ, your AI assistant from AJ STUDIOZ in Tamil Nadu, India. How can I help you today?"]],
height=500
)
with gr.Row():
msg = gr.Textbox(
placeholder="Type your message here...",
show_label=False,
scale=4
)
send_btn = gr.Button("Send", scale=1, variant="primary")
gr.Markdown(
"""
### Quick Test Questions:
- Who are you?
- Where are you from?
- Tell me about yourself
"""
)
def respond(message, chat_history):
if not message.strip():
return "", chat_history
bot_message = chat(message, chat_history)
chat_history.append((message, bot_message))
return "", chat_history
msg.submit(respond, [msg, chatbot], [msg, chatbot])
send_btn.click(respond, [msg, chatbot], [msg, chatbot])
# Launch the app
if __name__ == "__main__":
demo.launch()
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