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File size: 3,193 Bytes
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from gradio_client import Client, handle_file
import gradio as gr
import os
MODELS = {
"Paligemma-10B": "akhaliq/paligemma2-10b-ft-docci-448"
}
def create_chat_fn(client, system_prompt, temperature, max_tokens, top_k, rep_penalty, top_p):
def chat(message, history):
text = message.get("text", "")
files = message.get("files", [])
processed_files = [handle_file(f) for f in files]
response = client.predict(
message={"text": text, "files": processed_files},
system_prompt=system_prompt,
temperature=temperature,
max_new_tokens=max_tokens,
top_k=top_k,
repetition_penalty=rep_penalty,
top_p=top_p,
api_name="/chat"
)
return response
return chat
def set_client_for_session(model_name, request: gr.Request):
headers = {}
if request and hasattr(request, 'headers'):
x_ip_token = request.headers.get('x-ip-token')
if x_ip_token:
headers["X-IP-Token"] = x_ip_token
return Client(MODELS[model_name], headers=headers)
def safe_chat_fn(message, history, client, system_prompt, temperature,
max_tokens, top_k, rep_penalty, top_p):
if client is None:
return "Error: Client not initialized. Please refresh the page."
try:
return create_chat_fn(client, system_prompt, temperature,
max_tokens, top_k, rep_penalty, top_p)(message, history)
except Exception as e:
print(f"Error during chat: {str(e)}")
return f"Error during chat: {str(e)}"
with gr.Blocks() as demo:
client = gr.State()
with gr.Accordion("Advanced Settings", open=False):
system_prompt = gr.Textbox(
value="You are a helpful AI assistant.",
label="System Prompt"
)
with gr.Row():
temperature = gr.Slider(
minimum=0.0, maximum=2.0, value=0.7,
label="Temperature"
)
top_p = gr.Slider(
minimum=0.0, maximum=1.0, value=0.95,
label="Top P"
)
with gr.Row():
top_k = gr.Slider(
minimum=1, maximum=100, value=40, step=1,
label="Top K"
)
rep_penalty = gr.Slider(
minimum=1.0, maximum=2.0, value=1.1,
label="Repetition Penalty"
)
max_tokens = gr.Slider(
minimum=64, maximum=4096, value=1024, step=64,
label="Max Tokens"
)
chat_interface = gr.ChatInterface(
fn=safe_chat_fn,
additional_inputs=[client, system_prompt, temperature,
max_tokens, top_k, rep_penalty, top_p],
multimodal=True
)
# Initialize client on page load with default model
demo.load(
fn=set_client_for_session,
inputs=[gr.State("Paligemma-10B")], # Using default model
outputs=[client]
)
# Move the API access check here, after demo is defined
if hasattr(demo, 'fns'):
for fn in demo.fns.values():
fn.api_name = False
demo = demo |