matrix-pygmalion-bot/matrix_pygmalion_bot/ai/runpod.py

import asyncio
import os, tempfile
import logging

import json
import requests

from transformers import AutoTokenizer, AutoConfig
from huggingface_hub import hf_hub_download

import io
import base64
from PIL import Image, PngImagePlugin

from .model_helpers import get_full_prompt, num_tokens

logger = logging.getLogger(__name__)


async def generate_sync(
    prompt: str,
    api_key: str,
    bot,
    typing_fn,
    api_endpoint = "pygmalion-6b"
):
    # Set the API endpoint URL
    endpoint = f"https://api.runpod.ai/v2/{api_endpoint}/run"

    # Set the headers for the request
    headers = {
        "Content-Type": "application/json",
        "Authorization": f"Bearer {api_key}"
    }

    max_new_tokens = 200
    prompt_num_tokens = await num_tokens(prompt, bot.model)

    # Define your inputs
    input_data = {
        "input": {
            "prompt": prompt,
            "max_length": min(prompt_num_tokens+max_new_tokens, 2048),
            "temperature": bot.temperature,
            "do_sample": True,
        }
    }

    logger.info(f"sending request to runpod.io")

    # Make the request
    try:
        r = requests.post(endpoint, json=input_data, headers=headers, timeout=180)
    except requests.exceptions.RequestException as e:
        raise ValueError(f"<HTTP ERROR>")
    r_json = r.json()
    logger.info(r_json)

    if r.status_code == 200:
        status = r_json["status"]
        job_id = r_json["id"]
        TIMEOUT = 360
        DELAY = 5
        for i in range(TIMEOUT//DELAY):
            endpoint = f"https://api.runpod.ai/v2/{api_endpoint}/status/{job_id}"
            r = requests.get(endpoint, headers=headers)
            r_json = r.json()
            logger.info(r_json)
            status = r_json["status"]
            if status == 'IN_PROGRESS':
                await typing_fn()
                await asyncio.sleep(DELAY)
            elif status == 'IN_QUEUE':
                await asyncio.sleep(DELAY)
            elif status == 'COMPLETED':
                output = r_json["output"]
                if isinstance(output, list):
                    output.sort(key=len, reverse=True)
                    text = output[0]
                else:
                    text = r_json["output"]
                answer = text.removeprefix(prompt)
#                lines = reply.split('\n')
#                reply = lines[0].strip()
                idx = answer.find(f"\nYou:")
                if idx != -1:
                    reply = answer[:idx].strip()
                else:
                    reply = answer.removesuffix('<|endoftext|>').strip()
                reply = reply.replace(f"<BOT>", f"{bot.name}")
                reply = reply.replace(f"<USER>", f"You")
                reply = reply.replace(f"\n{bot.name}: ", " ")
                return reply
            else:
                err_msg = r_json["error"] if "error" in r_json else ""
                err_msg = err_msg.replace("\\n", "\n")
                raise ValueError(f"<ERROR> RETURN CODE {status}: {err_msg}")
        raise ValueError(f"<ERROR> TIMEOUT")
    else:
        raise ValueError(f"<ERROR>")


async def download_image(url, path):
    r = requests.get(url, stream=True)
    if r.status_code == 200:
        with open(path, 'wb') as f:
            for chunk in r:
                f.write(chunk)

async def generate_image(input_prompt: str, negative_prompt: str, api_url: str, api_key: str, typing_fn):

    # Set the API endpoint URL
    endpoint = api_url + "run"

    # Set the headers for the request
    headers = {
        "Content-Type": "application/json",
        "Authorization": f"Bearer {api_key}"
    }

    # Define your inputs
    input_data = {
        "input": {
            "prompt": input_prompt,
            "negative_prompt": negative_prompt,
            "width": 512,
            "height": 768,
            "num_outputs": 3,
#            "nsfw": True
        },
    }

    logger.info(f"sending request to runpod.io")

    # Make the request
    try:
        r = requests.post(endpoint, json=input_data, headers=headers)
    except requests.exceptions.RequestException as e:
        raise ValueError(f"<ERROR> HTTP ERROR")
    r_json = r.json()
    logger.debug(r_json)

    if r.status_code == 200:
        status = r_json["status"]
        if status != 'IN_QUEUE':
            err_msg = r_json["error"] if "error" in r_json else ""
            raise ValueError(f"<ERROR> RETURN CODE {status}: {err_msg}")
        job_id = r_json["id"]
        TIMEOUT = 360
        DELAY = 5
        output = None
        for i in range(TIMEOUT//DELAY):
            endpoint = api_url + "status/" + job_id
            r = requests.get(endpoint, headers=headers)
            r_json = r.json()
            logger.debug(r_json)
            status = r_json["status"]
            if status == 'IN_PROGRESS':
                await typing_fn()
                await asyncio.sleep(DELAY)
            elif status == 'IN_QUEUE':
                await asyncio.sleep(DELAY)
            elif status == 'COMPLETED':
                output = r_json["output"]
                break
            else:
                err_msg = r_json["error"] if "error" in r_json else ""
                err_msg = err_msg.replace("\\n", "\n")
                raise ValueError(f"<ERROR> RETURN CODE {status}: {err_msg}")

        if not output:
            raise ValueError(f"<ERROR>")

        os.makedirs("./images", exist_ok=True)
        files = []
        for image in output:
            temp_name = next(tempfile._get_candidate_names())
            filename = "./images/" + temp_name + ".jpg"
            await download_image(image["image"], filename)
            files.append(filename)

        return files

async def generate_image1(input_prompt: str, negative_prompt: str, api_key: str, typing_fn):
# AnythingV4
    return await generate_image(input_prompt, negative_prompt, "https://api.runpod.ai/v1/sd-anything-v4/", api_key, typing_fn)

async def generate_image2(input_prompt: str, negative_prompt: str, api_key: str, typing_fn):
# OpenJourney
    return await generate_image(input_prompt, negative_prompt, "https://api.runpod.ai/v1/sd-openjourney/", api_key, typing_fn)

async def generate_image3(input_prompt: str, negative_prompt: str, api_key: str, typing_fn):
# Hassanblend
    return await generate_image(input_prompt, negative_prompt, "https://api.runpod.ai/v1/mf5f6mocy8bsvx/", api_key, typing_fn)

async def generate_image4(input_prompt: str, negative_prompt: str, api_key: str, typing_fn):
# DeliberateV2
    return await generate_image_automatic(input_prompt, negative_prompt, "https://api.runpod.ai/v1/lxdhmiccp3vdsf/", api_key, typing_fn)

async def generate_image5(input_prompt: str, negative_prompt: str, api_key: str, typing_fn):
# Hassanblend
    return await generate_image_automatic(input_prompt, negative_prompt, "https://api.runpod.ai/v1/13rrs00l7yxikf/", api_key, typing_fn)

async def generate_image6(input_prompt: str, negative_prompt: str, api_key: str, typing_fn):
# PFG
    return await generate_image_automatic(input_prompt, negative_prompt, "https://api.runpod.ai/v1/5j1xzlsyw84vk5/", api_key, typing_fn)

async def generate_image7(input_prompt: str, negative_prompt: str, api_key: str, typing_fn):
# ChilloutMix
    return await generate_image_automatic(input_prompt, negative_prompt, "https://api.runpod.ai/v2/rrjxafqx66osr4/", api_key, typing_fn)

async def generate_image8(input_prompt: str, negative_prompt: str, api_key: str, typing_fn):
# AbyssOrangeMixV3
    return await generate_image_automatic(input_prompt, negative_prompt, "https://api.runpod.ai/v2/vuyifmsasm3ix7/", api_key, typing_fn)


async def serverless_automatic_request(payload, cmd, api_url: str, api_key: str, typing_fn):
    # Set the API endpoint URL
    endpoint = api_url + "run"

    # Set the headers for the request
    headers = {
        "Content-Type": "application/json",
        "Authorization": f"Bearer {api_key}"
    }

    # Define your inputs
    payload.update({"api_endpoint": str(cmd)})
    input_data = {
        "input": payload,
        "cmd": cmd,
    }

    logger.info(f"sending request to runpod.io")

    # Make the request
    try:
        r = requests.post(endpoint, json=input_data, headers=headers)
    except requests.exceptions.RequestException as e:
        raise ValueError(f"<ERROR> HTTP ERROR")
    r_json = r.json()
    logger.debug(r_json)

    if r.status_code == 200:
        status = r_json["status"]
        if status != 'IN_QUEUE':
            err_msg = r_json["error"] if "error" in r_json else ""
            raise ValueError(f"<ERROR> RETURN CODE {status}: {err_msg}")
        job_id = r_json["id"]
        TIMEOUT = 360
        DELAY = 5
        output = None
        for i in range(TIMEOUT//DELAY):
            endpoint = api_url + "status/" + job_id
            r = requests.get(endpoint, headers=headers)
            r_json = r.json()
            logger.debug(r_json)
            status = r_json["status"]
            if status == 'IN_PROGRESS':
                await typing_fn()
                await asyncio.sleep(DELAY)
            elif status == 'IN_QUEUE':
                await asyncio.sleep(DELAY)
            elif status == 'COMPLETED':
                output = r_json["output"]
                break
            else:
                err_msg = r_json["error"] if "error" in r_json else ""
                raise ValueError(f"<ERROR> RETURN CODE {status}: {err_msg}")

        if not output:
            raise ValueError(f"<ERROR> {status}")

        return output


async def generate_image_automatic(input_prompt: str, negative_prompt: str, api_url: str, api_key: str, typing_fn):
    payload = {
        "prompt": input_prompt,
        "nagative_prompt": negative_prompt,
        "steps": 25,
        "cfg_scale": 7,
        "seed": -1,
        "width": 512,
        "height": 768,
        "batch_size": 3,
#        "sampler_index": "DPM++ 2M Karras",
#        "enable_hr": True,
#        "hr_scale": 2,
#        "hr_upscaler": "ESRGAN_4x", # "Latent"
#        "denoising_strength": 0.5,
#        "hr_second_pass_steps": 15,
        "restore_faces": True,
#        "gfpgan_visibility": 0.5,
#        "codeformer_visibility": 0.5,
#        "codeformer_weight": 0.5,
##        "override_settings": {
##            "filter_nsfw": False,
##        },
    }

    output = await serverless_automatic_request(payload, "txt2img", api_url, api_key, typing_fn)

    upscale = False
    if upscale:
        count = 0
        for i in output['images']:
            payload = {
                "init_images": [i],
                "prompt": input_prompt,
                "nagative_prompt": negative_prompt,
                "steps": 20,
                "seed": -1,
                #"sampler_index": "Euler",
#                                  tile_width, tile_height, mask_blur, padding, seams_fix_width, seams_fix_denoise, seams_fix_padding, upscaler_index, save_upscaled_image, redraw_mode, save_seams_fix_image, seams_fix_mask_blur, seams_fix_type, target_size_type, custom_width, custom_height, custom_scale
#                "script_args": ["",512,0,8,32,64,0.275,32,3,False,0,True,8,3,2,1080,1440,1.875],
#                "script_name": "Ultimate SD upscale",
            }
            upscaled_output = await serverless_automatic_request(payload, "img2img", api_url, api_key, typing_fn)
            output['images'][count] = upscaled_output['images'][count]

    os.makedirs("./images", exist_ok=True)
    files = []
    for i in output['images']:
        temp_name = next(tempfile._get_candidate_names())
        filename = "./images/" + temp_name + ".png"
        image = Image.open(io.BytesIO(base64.b64decode(i.split(",",1)[0])))
        info = output['info']
        parameters = output['parameters']
        pnginfo = PngImagePlugin.PngInfo()
        pnginfo.add_text("parameters", info)
        image.save(filename, pnginfo=pnginfo)

        files.append(filename)

    return files