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import gradio as gr
from huggingface_hub import InferenceClient
# Custom CSS for dark theme
custom_css = """
#chat-container {
background-color: #0a0a1a;
min-height: 100vh;
color: white;
}
#header {
background-color: #0a0a1a;
padding: 1rem 2rem;
border-bottom: 1px solid #2a2a3a;
}
#logo {
display: flex;
align-items: center;
gap: 0.5rem;
}
#nav {
display: flex;
justify-content: space-between;
align-items: center;
}
#nav-links {
display: flex;
gap: 2rem;
}
.nav-link {
color: #ffffff;
text-decoration: none;
padding: 0.5rem 1rem;
}
#main-content {
max-width: 800px;
margin: 2rem auto;
padding: 0 1rem;
}
#chat-title {
font-size: 2.5rem;
font-weight: bold;
text-align: center;
margin-bottom: 1rem;
}
#chat-description {
text-align: center;
color: #cccccc;
margin-bottom: 2rem;
}
.chatbot-container {
background-color: #13131f;
border-radius: 0.5rem;
padding: 1rem;
}
.message {
background-color: #1a1a2a;
border-radius: 0.5rem;
padding: 1rem;
margin-bottom: 1rem;
}
.chat-input {
background-color: #1a1a2a;
border: 1px solid #2a2a3a;
border-radius: 0.5rem;
color: white;
}
"""
client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
def respond(
message,
chat_history,
system_message,
max_tokens,
temperature,
top_p,
):
if message.strip() == "":
return "", chat_history
messages = [{"role": "system", "content": system_message}]
# Convert chat history to the format expected by the model
for human, assistant in chat_history:
messages.append({"role": "user", "content": human})
if assistant: # Only add assistant message if it exists
messages.append({"role": "assistant", "content": assistant})
messages.append({"role": "user", "content": message})
# Get the response from the model
try:
response = ""
for chunk in client.chat_completion(
messages,
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
):
if hasattr(chunk.choices[0].delta, 'content'):
if chunk.choices[0].delta.content is not None:
response += chunk.choices[0].delta.content
chat_history.append((message, response))
return "", chat_history
except Exception as e:
return "", chat_history + [(message, f"Error: {str(e)}")]
with gr.Blocks(css=custom_css) as demo:
with gr.Column(elem_id="chat-container"):
# Header
with gr.Row(elem_id="header"):
with gr.Column(elem_id="logo"):
gr.Markdown("🌎 ZiF-V0")
with gr.Row(elem_id="nav-links"):
gr.Markdown("[AI Chat](#) [AI Image Generator](#) [AI Video](#) [AI Music Generator](#) [Login](#)")
# Main content
with gr.Column(elem_id="main-content"):
gr.Markdown("# AI Chat", elem_id="chat-title")
gr.Markdown(
"AI Chat is an AI chatbot that writes text. You can use it to write stories, messages, or "
"programming code. You can use the AI chatbot as a virtual tutor in almost any subject.",
elem_id="chat-description"
)
# Chat interface
chatbot = gr.Chatbot(elem_classes="chatbot-container")
msg = gr.Textbox(
placeholder="Chat with AI...",
elem_classes="chat-input",
show_label=False
)
# Hidden controls (collapsible)
with gr.Accordion("Advanced Settings", open=False):
system_message = gr.Textbox(
value="You are a friendly Chatbot.",
label="System message"
)
max_tokens = gr.Slider(
minimum=1,
maximum=2048,
value=512,
step=1,
label="Max new tokens"
)
temperature = gr.Slider(
minimum=0.1,
maximum=4.0,
value=0.7,
step=0.1,
label="Temperature"
)
top_p = gr.Slider(
minimum=0.1,
maximum=1.0,
value=0.95,
step=0.05,
label="Top-p (nucleus sampling)"
)
# Set up chat functionality
msg.submit(
respond,
inputs=[msg, chatbot, system_message, max_tokens, temperature, top_p],
outputs=[msg, chatbot]
)
# Add a clear button
clear = gr.Button("Clear")
clear.click(lambda: None, None, chatbot, queue=False)
if __name__ == "__main__":
demo.launch() |