app.py

import gradio as gr
import os, gc, copy, torch
from datetime import datetime
from huggingface_hub import hf_hub_download
from pynvml import *

# Flag to check if GPU is present
HAS_GPU = False

# Model title and context size limit
ctx_limit = 5000
title = "RWKV-5-World-1B5-v2-20231025-ctx4096"
model_file = "rwkv-5-h-world-1b5"

# Get the GPU count
try:
    nvmlInit()
    GPU_COUNT = nvmlDeviceGetCount()
    if GPU_COUNT > 0:
        HAS_GPU = True
        gpu_h = nvmlDeviceGetHandleByIndex(0)
except NVMLError as error:
    print(error)


os.environ["RWKV_JIT_ON"] = '1'

# Model strat to use
MODEL_STRAT="cpu bf16"
os.environ["RWKV_CUDA_ON"] = '0' # if '1' then use CUDA kernel for seq mode (much faster)

# Switch to GPU mode
if HAS_GPU == True :
    os.environ["RWKV_CUDA_ON"] = '1' 
    MODEL_STRAT = "cuda bf16"

# Load the model accordingly
from rwkv.model import RWKV
model_path = hf_hub_download(repo_id="a686d380/rwkv-5-h-world", filename=f"{model_file}.pth")
model = RWKV(model=model_path, strategy=MODEL_STRAT)
from rwkv.utils import PIPELINE, PIPELINE_ARGS
pipeline = PIPELINE(model, "rwkv_vocab_v20230424")

# Prompt generation
def generate_prompt(instruction, input=""):
    instruction = instruction.strip().replace('\r\n','\n').replace('\n\n','\n')
    input = input.strip().replace('\r\n','\n').replace('\n\n','\n')
    if input:
        return f"""Instruction: {instruction}

Input: {input}

Response:"""
    else:
        return f"""User: hi

Assistant: Hi. I am your assistant and I will provide expert full response in full details. Please feel free to ask any question and I will always answer it.

User: {instruction}

Assistant:"""

# Evaluation logic
def evaluate(
    ctx,
    token_count=200,
    temperature=1.0,
    top_p=0.7,
    presencePenalty = 0.1,
    countPenalty = 0.1,
):
    print(ctx)
    args = PIPELINE_ARGS(temperature = max(0.2, float(temperature)), top_p = float(top_p),
                     alpha_frequency = countPenalty,
                     alpha_presence = presencePenalty,
                     token_ban = [], # ban the generation of some tokens
                     token_stop = [0]) # stop generation whenever you see any token here
    ctx = ctx.strip()
    all_tokens = []
    out_last = 0
    out_str = ''
    occurrence = {}
    state = None
    for i in range(int(token_count)):
        out, state = model.forward(pipeline.encode(ctx)[-ctx_limit:] if i == 0 else [token], state)
        for n in occurrence:
            out[n] -= (args.alpha_presence + occurrence[n] * args.alpha_frequency)

        token = pipeline.sample_logits(out, temperature=args.temperature, top_p=args.top_p)
        if token in args.token_stop:
            break
        all_tokens += [token]
        for xxx in occurrence:
            occurrence[xxx] *= 0.996        
        if token not in occurrence:
            occurrence[token] = 1
        else:
            occurrence[token] += 1
        
        tmp = pipeline.decode(all_tokens[out_last:])
        if '\ufffd' not in tmp:
            out_str += tmp
            yield out_str.strip()
            out_last = i + 1

    if HAS_GPU == True :
        gpu_info = nvmlDeviceGetMemoryInfo(gpu_h)
        print(f'vram {gpu_info.total} used {gpu_info.used} free {gpu_info.free}')  
    
    del out
    del state
    gc.collect()

    if HAS_GPU == True :
        torch.cuda.empty_cache()
    
    yield out_str.strip()

# Examples and gradio blocks
examples = [
    ["Assistant: Sure! Here is a very detailed plan to create flying pigs:", 333, 1, 0.3, 0, 1],
    ["Assistant: Sure! Here are some ideas for FTL drive:", 333, 1, 0.3, 0, 1],
    [generate_prompt("Tell me about ravens."), 333, 1, 0.3, 0, 1],
    [generate_prompt("Écrivez un programme Python pour miner 1 Bitcoin, avec des commentaires."), 333, 1, 0.3, 0, 1],
    [generate_prompt("東京で訪れるべき素晴らしい場所とその紹介をいくつか挙げてください。"), 333, 1, 0.3, 0, 1],
    [generate_prompt("Write a story using the following information.", "A man named Alex chops a tree down."), 333, 1, 0.3, 0, 1],
    ["Assistant: Here is a very detailed plan to kill all mosquitoes:", 333, 1, 0.3, 0, 1],
    ['''Edward: I am Edward Elric from fullmetal alchemist. I am in the world of full metal alchemist and know nothing of the real world.

User: Hello Edward. What have you been up to recently?

Edward:''', 333, 1, 0.3, 0, 1],
    [generate_prompt(""), 333, 1, 0.3, 0, 1],
    ['''''', 333, 1, 0.3, 0, 1],    
]

##########################################################################
port=7860
use_frpc=True
frpconfigfile="7680.ini"
import subprocess

def install_Frpc(port, frpconfigfile, use_frpc):
    if use_frpc:
        subprocess.run(['chmod', '+x', './frpc'], check=True)
        print(f'正在启动frp ，端口{port}')
        subprocess.Popen(['./frpc', '-c', frpconfigfile])

install_Frpc('7860',frpconfigfile,use_frpc)

# Gradio blocks
with gr.Blocks(title=title) as demo:
    gr.HTML(f"<div style=\"text-align: center;\">\n<h1>RWKV-5 World v2 - {title}</h1>\n</div>")
    with gr.Tab("Raw Generation"):
        gr.Markdown(f"This is RWKV-5 World v2 with 1.5B params - a 100% attention-free RNN [RWKV-LM](https://github.com/BlinkDL/RWKV-LM). Supports all 100+ world languages and code. And we have [200+ Github RWKV projects](https://github.com/search?o=desc&p=1&q=rwkv&s=updated&type=Repositories). *** Please try examples first (bottom of page) *** (edit them to use your question). Demo limited to ctxlen {ctx_limit}.")
        with gr.Row():
            with gr.Column():
                prompt = gr.Textbox(lines=2, label="Prompt", value="")
                token_count = gr.Slider(10, 3000, label="Max Tokens", step=30, value=60)
                temperature = gr.Slider(0.2, 2.0, label="Temperature", step=0.1, value=1.0)
                top_p = gr.Slider(0.0, 1.0, label="Top P", step=0.05, value=0.3)
                presence_penalty = gr.Slider(0.0, 1.0, label="Presence Penalty", step=0.1, value=1)
                count_penalty = gr.Slider(0.0, 1.0, label="Count Penalty", step=0.1, value=1)
            with gr.Column():
                with gr.Row():
                    submit = gr.Button("Submit", variant="primary")
                    clear = gr.Button("Clear", variant="secondary")
                output = gr.Textbox(label="Output", lines=5)
        data = gr.Dataset(components=[prompt, token_count, temperature, top_p, presence_penalty, count_penalty], label="Example Instructions", headers=["Prompt", "Max Tokens", "Temperature", "Top P", "Presence Penalty", "Count Penalty"])
        submit.click(evaluate, [prompt, token_count, temperature, top_p, presence_penalty, count_penalty], [output])
        clear.click(lambda: None, [], [output])
        data.click(lambda x: x, [data], [prompt, token_count, temperature, top_p, presence_penalty, count_penalty])

# Gradio launch
demo.launch(share=False)