app.py

import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
import torch

# Configuration
MODEL_NAME = "RekaAI/reka-flash-3"
DEFAULT_MAX_LENGTH = 256
DEFAULT_TEMPERATURE = 0.7
SYSTEM_PROMPT = """You are Reka Flash-3, a helpful AI assistant created by Reka AI."""

# Load model and tokenizer
quantization_config = BitsAndBytesConfig(
    load_in_4bit=True,
    bnb_4bit_compute_dtype=torch.float16,
    bnb_4bit_use_double_quant=True,
    bnb_4bit_quant_type="nf4"
)
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
model = AutoModelForCausalLM.from_pretrained(
    MODEL_NAME,
    quantization_config=quantization_config,
    device_map="auto",
    torch_dtype=torch.float16,
    low_cpu_mem_usage=True
)
tokenizer.pad_token = tokenizer.eos_token

def generate_response(message, chat_history, system_prompt, max_length, temperature, top_p, top_k, repetition_penalty):
    prompt = f"{system_prompt} <sep> human: {message} <sep> assistant: "
    inputs = tokenizer(prompt, return_tensors="pt").to("cpu")
    outputs = model.generate(
        **inputs,
        max_new_tokens=max_length,
        temperature=temperature,
        top_p=top_p,
        top_k=top_k,
        repetition_penalty=repetition_penalty,
        do_sample=True,
        pad_token_id=tokenizer.eos_token_id
    )
    response = tokenizer.decode(outputs[0], skip_special_tokens=True).split("<sep>")[2].strip()
    chat_history.append({"user": message, "assistant": response})
    return "", chat_history

# Gradio Interface
with gr.Blocks(title="Reka Flash-3 Chat") as demo:
    gr.Markdown("# Reka Flash-3 Chat Interface")
    chatbot = gr.Chatbot(type="messages", height=400, label="Conversation")
    with gr.Row():
        message = gr.Textbox(label="Your Message", placeholder="Ask me anything...")
        submit_btn = gr.Button("Send")
    with gr.Accordion("Options", open=False):
        max_length = gr.Slider(128, 512, value=DEFAULT_MAX_LENGTH, label="Max Length")
        temperature = gr.Slider(0.1, 2.0, value=DEFAULT_TEMPERATURE, label="Temperature")
        top_p = gr.Slider(0.0, 1.0, value=0.95, label="Top-p")
        top_k = gr.Slider(1, 100, value=50, label="Top-k")
        repetition_penalty = gr.Slider(0.1, 2.0, value=1.1, label="Repetition Penalty")
    system_prompt = gr.Textbox(label="System Prompt", value=SYSTEM_PROMPT, lines=4)

    inputs = [message, chatbot, system_prompt, max_length, temperature, top_p, top_k, repetition_penalty]
    outputs = [message, chatbot]
    submit_btn.click(generate_response, inputs=inputs, outputs=outputs)
    message.submit(generate_response, inputs=inputs, outputs=outputs)

demo.launch()