[Bug]: Unexpected Function Call Triggered by return in Cloud Requests

[Okaz02]

scratchattach version

2.1.13

What happened?

In Cloud Requests, even when the value returned via return does not exceed the 3000-character limit, there are cases where it unexpectedly causes a function that was not called to be triggered. It seems that Cloud Requests mistakenly invokes an unrelated function through the returned value.

Your code.

import scratchattach as sa
import cv2
import zlib
import base64
import numpy as np
import struct
import requests
from dotenv import load_dotenv
import os
global chash
chash={"IDs":{}}
def zigzag(block):
    h, w = block.shape
    assert h == 8 and w == 8
    result = []
    for s in range(h + w - 1):
        if s % 2 == 0:
            for y in range(s + 1):
                x = s - y
                if x < w and y < h:
                    result.append(block[y, x])
        else:
            for x in range(s + 1):
                y = s - x
                if x < w and y < h:
                    result.append(block[y, x])
    return result

def process_block(block):
    y_ch  = block[:, :, 0].astype(np.float32)
    cr_ch = block[:, :, 1].astype(np.float32)
    cb_ch = block[:, :, 2].astype(np.float32)

    dct_y  = cv2.dct(y_ch)
    dct_cr = cv2.dct(cr_ch)
    dct_cb = cv2.dct(cb_ch)

    q_y  = np.round(dct_y / 100 + 128).astype(np.uint8)
    q_cr = np.round(dct_cr / 100 + 128).astype(np.uint8)
    q_cb = np.round(dct_cb / 100 + 128).astype(np.uint8)

    zz_y  = zigzag(q_y)
    zz_cr = zigzag(q_cr)
    zz_cb = zigzag(q_cb)

    dc = [zz_y[0], zz_cr[0], zz_cb[0]]
    ac = zz_y[1:] + zz_cr[1:] + zz_cb[1:]
    return dc, ac

def compress_and_encode(values):
    num_chunks = 16
    chunk_size = (len(values) + num_chunks - 1) // num_chunks
    chunks = [values[i * chunk_size : (i + 1) * chunk_size] for i in range(num_chunks)]
    encoded_chunks = []
    for chunk in chunks:
        if not chunk:
            continue
        packed = struct.pack(f'{len(chunk)}B', *chunk)
        compressed = zlib.compress(packed, level=9)[2:-4]
        encoded = base64.b64encode(compressed).decode('utf-8')
        encoded_chunks.append(encoded)
    return encoded_chunks

def encode_image(img):
    img_ycrcb = cv2.cvtColor(cv2.cvtColor(img, cv2.COLOR_BGR2RGB), cv2.COLOR_RGB2YCrCb)
    h, w, _ = img_ycrcb.shape
    dc_values = []
    ac_values = []

    for y in range(0, h, 8):
        for x in range(0, w, 8):
            block = img_ycrcb[y:y+8, x:x+8]
            if block.shape[:2] == (8, 8):
                dc, ac = process_block(block)
                dc_values.extend(dc)
                ac_values.extend(ac)
    def split_into_chunks(values, num_chunks=16):
        chunk_size = (len(values) + num_chunks - 1) // num_chunks
        return [values[i * chunk_size : (i + 1) * chunk_size] for i in range(num_chunks)]

    dc_chunks = split_into_chunks(dc_values, 16)
    ac_chunks = split_into_chunks(ac_values, 16)
    encoded_dc = compress_and_encode(dc_values)[:16]
    encoded_ac = compress_and_encode(ac_values)[:16]
    result = [f"{h}:{w}:{encoded_ac[0]}:{encoded_dc[0]}"]
    for i in range(1, 16):
        result.append(f"{encoded_ac[i]}:{encoded_dc[i]}")
    return result


load_dotenv()
session = sa.login(os.getenv("User") , os.getenv("Passward"))
cloud = session.connect_cloud("****")
client = cloud.requests()
twcloud = sa.get_tw_cloud("****")
twclient = twcloud.requests()
@client.request
def AI(Text,Id,Index):
    url = '****'
    data = {'action': 'generate_image', 'prompt': Text,'aspect_ratio':'Select Aspect Ratio','hd':'1'}
    response = requests.post(url, data=data)
    response = response.json()
    print([Text,Id,Index])
    if "data" in response and int(Index) == 0:
     response = requests.get(response["data"]["image_link"])
     img_array = np.frombuffer(response.content, np.uint8)
     img = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
     img = encode_image(img)
     chash["IDs"][Id] = {"Img": img}
     print(Id)
     with open(f"./{Id}.txt", "w", encoding="utf-8") as f:
       f.write("@"+"|".join(img))
     return img[0]
    else:
     if Id in chash["IDs"]:
       return chash["IDs"][Id]["Img"][int(Index)]
     else:
      return "retry"
@client.request
def Shair(Id,Index):
    with open(f"./{Id}.txt", "r", encoding="utf-8") as f:
      img = f.read()
    if img[0]=="@":
     return img[1:].split("|")[int(Index)]
    else:
     return "~"+img
@client.event
def on_ready():
    print("Request handler is running")
@twclient.request
def AI(Text,Id,Index):
    url = '****'
    data = {'action': 'generate_image', 'prompt': Text,'aspect_ratio':'Select Aspect Ratio','hd':'1'}
    response = requests.post(url, data=data)
    response = response.json()
    if "data" in response and int(Index) == 0:
     response = requests.get(response["data"]["image_link"])
     img_array = np.frombuffer(response.content, np.uint8)
     img = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
     img = encode_image(img)
     chash["IDs"][Id] = {"Img": img}
     print(Id)
     with open(f"./{Id}.txt", "w", encoding="utf-8") as f:
       f.write("@"+"|".join(img))
     return img[0]
    else:
     if Id in chash["IDs"]:
      return chash["IDs"][Id]["Img"][int(Index)]
     else:
      return "retry"
@twclient.request
def Shair(Id,Index):
    with open(f"./{Id}.txt", "r", encoding="utf-8") as f:
      img = f.read()
    if img[0]=="@":
     return img[1:].split("|")[int(Index)]
    else:
     return "~"+img
@twclient.event
def on_ready():
    print("Request handler is running")
client.start(thread=True)
twclient.start(thread=True)

Traceback

Warning: Client received an unknown request called ''

[Okaz02]

The tricky part of this bug is that the return transmission gets interrupted by Warning: Client received an unknown request called ''.

[Okaz02]

Someone has reported this same bug before, but the fact that it’s still being ignored without being fixed is unacceptable.

[FAReTek1]

both examples of this bug do not provide code that can be used standalone. For me, the cloud request framework seemed to work, but we will need a minimal reproducible example in order to fix it. I will try it again when I get home

[FAReTek1]

I can't reproduce the issue; it could be that this is caused by some specific condition, or there is a bug in your code. However, one thing I have found, is that the request decorator isn't stackable, which is why you defined multiple functions that do the same thing.

Here's the code I have been using to test this:

NOTE
This doesn't work in the current version of scratchattach; it only works on the version which is in my fork of the repository

Using project here:
https://scratch.mit.edu/projects/1170280159/
https://turbowarp.org/1170280159

import time
import tomllib
from typing import Final
import scratchattach as sa

credentials = tomllib.load(open("../config.toml", "rb"))
username = credentials.pop("username")
password = credentials.pop("password")

sess = sa.login(username, password)

PROJECT_ID: Final[int] = 1170280159

cloud = sess.connect_cloud(PROJECT_ID)
twcloud = sa.get_tw_cloud(PROJECT_ID)

client = cloud.requests()
twclient = twcloud.requests()


@client.request()
@twclient.request()
def ping(*args):
    if len(args) == 1:
        start_t = float(args[0])
        return f"Ping! dt: {time.time() - start_t}"

    return f"Processed at time: \"{time.time()}\"\\"


@client.event
def on_ready():
    print("Client started")


@twclient.event
def on_ready():
    print("TWClient started")


client.start(thread=True)
twclient.start(thread=True)

Stuff about stacking decorators

FYI, you could have done:

def AI(text, id, index):
    ...

# the empty brackets here are for optional decorator arguments
client.request()(AI)
twclient.request()(AI)

This means you only need to define the function once.

I'm going to make this possible:

@client.request
@twclient.request
def AI(text, id, index):
    ...

The only thing stopping this right now is because the function decorator isn't returning the function back

I will now try this again but with sending large amounts of data
When sending extremely large volumes of data, i am now receiving the request called ''
However, other than this, the response and request system is working fine.
Now I am starting to receive requests with no name, even when request payload is small

I am not sure exactly why there are strange requests being handled this way.

One thing I think might be happening is the incorrect parsing of requests that are asking for more data, when large sums of data need to be collected. In the scratch code, there is a comment that suggests that this is an work-in-progress feature, which is not yet complete. This could be why they are being handled as regular requests, and when parsed, give strange, unrecognised output.

[Okaz02]

So does that mean we just have to wait until it’s finished?

[FAReTek1]

I am investogating the code. Hopefully this can be resolved

[Okaz02]

I am investogating the code. Hopefully this can be resolved

Thank you!

[Okaz02]

import scratchattach as sa
import time
import cv2
import zlib
import base64
import numpy as np
import struct
import requests
from dotenv import load_dotenv
import os
global chash
chash={"IDs":{}}
def zigzag(block):
    h, w = block.shape
    assert h == 8 and w == 8
    result = []
    for s in range(h + w - 1):
        if s % 2 == 0:
            for y in range(s + 1):
                x = s - y
                if x < w and y < h:
                    result.append(block[y, x])
        else:
            for x in range(s + 1):
                y = s - x
                if x < w and y < h:
                    result.append(block[y, x])
    return result

def process_block(block):
    y_ch  = block[:, :, 0].astype(np.float32)
    cr_ch = block[:, :, 1].astype(np.float32)
    cb_ch = block[:, :, 2].astype(np.float32)

    dct_y  = cv2.dct(y_ch)
    dct_cr = cv2.dct(cr_ch)
    dct_cb = cv2.dct(cb_ch)

    q_y  = np.round(dct_y / 100 + 128).astype(np.uint8)
    q_cr = np.round(dct_cr / 100 + 128).astype(np.uint8)
    q_cb = np.round(dct_cb / 100 + 128).astype(np.uint8)

    zz_y  = zigzag(q_y)
    zz_cr = zigzag(q_cr)
    zz_cb = zigzag(q_cb)

    dc = [zz_y[0], zz_cr[0], zz_cb[0]]
    ac = zz_y[1:] + zz_cr[1:] + zz_cb[1:]
    return dc, ac

def compress_and_encode(values):
    num_chunks = 8
    chunk_size = (len(values) + num_chunks - 1) // num_chunks
    chunks = [values[i * chunk_size : (i + 1) * chunk_size] for i in range(num_chunks)]
    encoded_chunks = []
    for chunk in chunks:
        if not chunk:
            continue
        packed = struct.pack(f'{len(chunk)}B', *chunk)
        compressed = zlib.compress(packed, level=9)[2:-4]
        encoded = base64.b64encode(compressed).decode('utf-8')
        encoded_chunks.append(encoded)
    return encoded_chunks

def encode_image(img):
    img_ycrcb = cv2.cvtColor(cv2.cvtColor(img, cv2.COLOR_BGR2RGB), cv2.COLOR_RGB2YCrCb)
    h, w, _ = img_ycrcb.shape
    dc_values = []
    ac_values = []

    for y in range(0, h, 8):
        for x in range(0, w, 8):
            block = img_ycrcb[y:y+8, x:x+8]
            if block.shape[:2] == (8, 8):
                dc, ac = process_block(block)
                dc_values.extend(dc)
                ac_values.extend(ac)

    encoded_dc = compress_and_encode(dc_values)[:8]
    encoded_ac = compress_and_encode(ac_values)[:8]

    result = [f"{h}:{w}:{encoded_ac[0]}:{encoded_dc[0]}"]
    for i in range(1, 8):
        result.append(f"{encoded_ac[i]}:{encoded_dc[i]}")
    return result

def cleanup_chash(timeout=600):
    now = time.time()
    expired_ids = [k for k, v in chash["IDs"].items() if now - v.get("Time", now) > timeout]
    for k in expired_ids:
        del chash["IDs"][k]

load_dotenv()
session = sa.login(os.getenv("User") , os.getenv("Passward"))
cloud = session.connect_cloud("****")
client = cloud.requests()
twcloud = sa.get_tw_cloud("****")
twclient = twcloud.requests()
@client.request
def AI(Text,Id,Index):
    cleanup_chash()
    url = '****'
    data = {'action': 'generate_image', 'prompt': Text,'aspect_ratio':'Select Aspect Ratio','hd':'1'}
    response = requests.post(url, data=data)
    response = response.json()
    print([Text,Id,Index])
    if "data" in response and int(Index) == 0:
     response = requests.get(response["data"]["image_link"])
     img_array = np.frombuffer(response.content, np.uint8)
     img = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
     img = encode_image(img)
     chash["IDs"][Id] = {"Img": img, "Time": time.time()}
     print(Id)
     with open(f"./{Id}.txt", "w", encoding="utf-8") as f:
       f.write("@"+"|".join(img))
     return img[0]
    else:
     if Id in chash["IDs"]:
       b=chash["IDs"][Id]["Img"][int(Index)]
       if int(Index) == 7:
        del chash["IDs"][Id]
       return b
     else:
      return "retry"
@client.request
def Shair(Id,Index):
    cleanup_chash()
    with open(f"./{Id}.txt", "r", encoding="utf-8") as f:
      img = f.read()
    if img[0]=="@":
     return img[1:].split("|")[int(Index)]
    else:
     return "~"+img
@client.event
def on_ready():
    cleanup_chash()
    print("Request handler is running")
@twclient.request
def AI(Text,Id,Index):
    cleanup_chash()
    url = '****'
    data = {'action': 'generate_image', 'prompt': Text,'aspect_ratio':'Select Aspect Ratio','hd':'1'}
    response = requests.post(url, data=data)
    response = response.json()
    if "data" in response and int(Index) == 0:
     response = requests.get(response["data"]["image_link"])
     img_array = np.frombuffer(response.content, np.uint8)
     img = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
     img = encode_image(img)
     chash["IDs"][Id] = {"Img": img, "Time": time.time()}
     print(Id)
     with open(f"./{Id}.txt", "w", encoding="utf-8") as f:
       f.write("@"+"|".join(img))
     return img[0]
    else:
     if Id in chash["IDs"]:
      return chash["IDs"][Id]["Img"][int(Index)]
     else:
      return "retry"
@twclient.request
def Shair(Id,Index):
    cleanup_chash()
    with open(f"./{Id}.txt", "r", encoding="utf-8") as f:
      img = f.read()
    if img[0]=="@":
     return img[1:].split("|")[int(Index)]
    else:
     return "~"+img
@twclient.event
def on_ready():
    cleanup_chash()
    print("Request handler is running")
client.start(thread=True)
twclient.start(thread=True)

Hi,
I made a small change to the code. I modified the 16-way split to 8-way. Sorry about that.

I’ve noticed that the warning message
"Warning: Client received an unknown request called ''"
often shows up when the Index in the AI function is around 4 or 5.
I’ve uploaded a text file with the exact string that was sent when this happened.

This is the project where the bug occurs:
https://scratch.mit.edu/projects/1195237621/

Thanks in advance for looking into this.

Files.txt <==

[Okaz02]

import scratchattach as sa
import time
import cv2
import zlib
import base64
import numpy as np
import struct
import requests
from dotenv import load_dotenv
import os
chash = {"IDs": {}}
def zigzag(block):
    h, w = block.shape
    assert h == 8 and w == 8
    result = []
    for s in range(h + w - 1):
        if s % 2 == 0:
            for y in range(s + 1):
                x = s - y
                if x < w and y < h:
                    result.append(block[y, x])
        else:
            for x in range(s + 1):
                y = s - x
                if x < w and y < h:
                    result.append(block[y, x])
    return result
def process_block(block):
    y_ch  = block[:, :, 0].astype(np.float32)
    cr_ch = block[:, :, 1].astype(np.float32)
    cb_ch = block[:, :, 2].astype(np.float32)

    dct_y  = cv2.dct(y_ch)
    dct_cr = cv2.dct(cr_ch)
    dct_cb = cv2.dct(cb_ch)

    q_y  = np.round(dct_y / 100 + 128).astype(np.uint8)
    q_cr = np.round(dct_cr / 100 + 128).astype(np.uint8)
    q_cb = np.round(dct_cb / 100 + 128).astype(np.uint8)

    zz_y  = zigzag(q_y)
    zz_cr = zigzag(q_cr)
    zz_cb = zigzag(q_cb)

    dc = [zz_y[0], zz_cr[0], zz_cb[0]]
    ac = zz_y[1:] + zz_cr[1:] + zz_cb[1:]
    return dc, ac
def compress_and_encode(values):
    num_chunks = 8
    chunk_size = (len(values) + num_chunks - 1) // num_chunks
    chunks = [values[i * chunk_size : (i + 1) * chunk_size] for i in range(num_chunks)]
    encoded_chunks = []
    for chunk in chunks:
        if not chunk:
            continue
        packed = struct.pack(f'{len(chunk)}B', *chunk)
        compressed = zlib.compress(packed, level=9)[2:-4]
        encoded = base64.b64encode(compressed).decode('utf-8')
        encoded_chunks.append(encoded)
    return encoded_chunks
def encode_image(img):
    img_ycrcb = cv2.cvtColor(cv2.cvtColor(img, cv2.COLOR_BGR2RGB), cv2.COLOR_RGB2YCrCb)
    h, w, _ = img_ycrcb.shape
    dc_values = []
    ac_values = []

    for y in range(0, h, 8):
        for x in range(0, w, 8):
            block = img_ycrcb[y:y+8, x:x+8]
            if block.shape[:2] == (8, 8):
                dc, ac = process_block(block)
                dc_values.extend(dc)
                ac_values.extend(ac)

    encoded_dc = compress_and_encode(dc_values)[:8]
    encoded_ac = compress_and_encode(ac_values)[:8]

    result = [f"{h}:{w}:{encoded_ac[0]}:{encoded_dc[0]}"]
    for i in range(1, 8):
        result.append(f"{encoded_ac[i]}:{encoded_dc[i]}")
    return result
def cleanup_chash(timeout=600):
    now = time.time()
    expired_ids = [k for k, v in chash["IDs"].items() if now - v.get("Time", now) > timeout]
    for k in expired_ids:
        del chash["IDs"][k]
def AI(Text, Id, Index):
    cleanup_chash()
    url = '****'
    data = {
        'action': 'generate_image',
        'prompt': Text,
        'aspect_ratio': 'Select Aspect Ratio',
        'hd': '1'
    }
    response = requests.post(url, data=data)
    response = response.json()

    if "data" in response and int(Index) == 0:
        response = requests.get(response["data"]["image_link"])
        img_array = np.frombuffer(response.content, np.uint8)
        img = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
        img = encode_image(img)
        chash["IDs"][Id] = {"Img": img, "Time": time.time()}
        with open(f"./{Id}.txt", "w", encoding="utf-8") as f:
            f.write("@" + "|".join(img))
        return img[0]
    else:
        if Id in chash["IDs"]:
            b = chash["IDs"][Id]["Img"][int(Index)]
            if int(Index) == 7:
                del chash["IDs"][Id]
            return b
        else:
            return "retry"
def Shair(Id, Index):
    cleanup_chash()
    try:
        with open(f"./{Id}.txt", "r", encoding="utf-8") as f:
            img = f.read()
        if img[0] == "@":
            return img[1:].split("|")[int(Index)]
        else:
            return "~" + img
    except FileNotFoundError:
        return "file_not_found"
def on_ready():
    cleanup_chash()
    print("Request handler is running")
load_dotenv()
session = sa.login(os.getenv("User"), os.getenv("Passward"))
project_id = "****"
cloud = session.connect_cloud(project_id)
twcloud = sa.get_tw_cloud(project_id)
client = cloud.requests()
twclient = twcloud.requests()
client.request()(AI)
client.request()(Shair)
client.event(on_ready)
twclient.request()(AI)
twclient.request()(Shair)
twclient.event(on_ready)
client.start(thread=True)
twclient.start(thread=True)

I tried this code as well, but it actually made things worse.

[FAReTek1]

I believe the requests received called '' are caused by a request for more packages which is improperly handled.

Testing is needed to make sure this works correctly in the backend. Currently we are cleaning up some of the code because there are some issues with the python backend framework

[Okaz02]

Thank you for fixing the bug!

[FAReTek1]

its not fixed yet