Merge 5b935e5b4d into 868e2489b3

.github/workflows/ci.yml

@@ -0,0 +1,29 @@
+name: CI
+
+on: [push]
+
+jobs:
+  auto-tests:
+    name: Pytest Tests
+    runs-on: ubuntu-24.04
+    timeout-minutes: 10
+    steps:
+      - uses: actions/checkout@v2
+        with:
+          submodules: recursive
+
+      - name: Install the latest version of uv
+        uses: astral-sh/setup-uv@v5
+
+      - uses: actions/cache@v3
+        name: Cache venv
+        with:
+          path: ./.venv
+          key: venv-${{ hashFiles('uv.lock') }}
+
+      - name: Install with dev
+        run: uv sync
+
+      - name: Run tests
+        run: |
+          uv run pytest

default.nix

@@ -0,0 +1,36 @@
+with (import <nixpkgs> {});
+let
+  glibStorePath = lib.getLib glib;
+  zstdStorePath = lib.getLib zstd;
+  libGLStorePath = lib.getLib libGL;
+in
+stdenv.mkDerivation {
+  name = "skynet";
+  buildInputs = [
+    # System requirements.
+    glib
+    zstd
+    libGL
+    libgcc.lib
+    # Python requirements.
+    python313Full
+    python313Packages.uv
+  ];
+  src = null;
+  shellHook = ''
+    set -e
+
+    LIB_GCC_PATH="${libgcc.lib}/lib"
+    GLIB_PATH="${glibStorePath}/lib"
+    ZSTD_PATH="${zstdStorePath}/lib"
+    LIBGL_PATH="${libGLStorePath}/lib"
+
+
+    LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$LIB_GCC_PATH"
+    LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$GLIB_PATH"
+    LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$ZSTD_PATH"
+    LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$LIBGL_PATH"
+
+    export LD_LIBRARY_PATH
+  '';
+}

pyproject.toml

@@ -77,7 +77,7 @@ explicit = true
 torch = { index = "torch" }
 triton = { index = "torch" }
 torchvision = { index = "torch" }
-py-leap = { git = "https://github.com/guilledk/py-leap.git", rev = "v0.1a34" }
+py-leap = { git = "https://github.com/guilledk/py-leap.git", rev = "v0.1a35" }
 pytest-dockerctl = { git = "https://github.com/pikers/pytest-dockerctl.git", branch = "g_update" }
 
 [build-system]

skynet/_testing.py

@@ -0,0 +1,32 @@
+from contextlib import asynccontextmanager as acm
+
+from skynet.config import Config, DgpuConfig, set_config_override
+from skynet.dgpu import open_worker
+
+def override_dgpu_config(**kwargs) -> DgpuConfig:
+    config = Config(
+        dgpu=DgpuConfig(**kwargs)
+    )
+    set_config_override(config)
+    return config.dgpu
+
+
+@acm
+async def open_test_worker(
+    cleos, ipfs_node,
+    account: str = 'testworker',
+    permission: str = 'active',
+    hf_token: str = '',
+    **kwargs
+):
+    config = override_dgpu_config(
+        account=account,
+        permission=permission,
+        key=cleos.private_keys[account],
+        node_url=cleos.endpoint,
+        ipfs_url=ipfs_node[1].endpoint,
+        hf_token=hf_token,
+        **kwargs
+    )
+    async with open_worker(config) as worker:
+        yield worker

skynet/cli.py

@@ -1,16 +1,8 @@
 import json
 import logging
-import random
-
-from functools import partial
 
 import click
 
-from leap.protocol import (
-    Name,
-    Asset,
-)
-
 from .config import (
     load_skynet_toml,
     set_hf_vars,
@@ -49,7 +41,7 @@ def txt2img(*args, **kwargs):
 
     config = load_skynet_toml()
     set_hf_vars(config.dgpu.hf_token, config.dgpu.hf_home)
-    utils.txt2img(hf_token, **kwargs)
+    utils.txt2img(config.dgpu.hf_token, **kwargs)
 
 
 @click.command()
@@ -74,7 +66,7 @@ def img2img(model, prompt, input, output, strength, guidance, steps, seed):
     config = load_skynet_toml()
     set_hf_vars(config.dgpu.hf_token, config.dgpu.hf_home)
     utils.img2img(
-        hf_token,
+        config.dgpu.hf_token,
         model=model,
         prompt=prompt,
         img_path=input,
@@ -102,7 +94,7 @@ def inpaint(model, prompt, input, mask, output, strength, guidance, steps, seed)
     config = load_skynet_toml()
     set_hf_vars(config.dgpu.hf_token, config.dgpu.hf_home)
     utils.inpaint(
-        hf_token,
+        config.dgpu.hf_token,
         model=model,
         prompt=prompt,
         img_path=input,

skynet/config.py

@@ -1,5 +1,4 @@
 import os
-import toml
 
 import msgspec
 
@@ -59,7 +58,18 @@ class Config(msgspec.Struct):
     user: UserConfig | None = None
 
 
+__config_override = None
+def set_config_override(config: Config):
+    global __config_override
+    __config_override = config
+
+
 def load_skynet_toml(file_path=DEFAULT_CONFIG_PATH) -> Config:
+    global __config_override
+
+    if __config_override:
+        return __config_override
+
     with open(file_path, 'r') as file:
         return msgspec.toml.decode(file.read(), type=Config)
 

skynet/constants.py

@@ -1,20 +1,9 @@
-import msgspec
+from skynet.types import ModelDesc
 
-from enum import Enum
-from typing import Literal
-
-VERSION = '0.1a12'
+VERSION = '0.1a13'
 
 DOCKER_RUNTIME_CUDA = 'skynet:runtime-cuda'
 
-
-class ModelDesc(msgspec.Struct):
-    short: str  # short unique name
-    mem: float  # recomended mem
-    attrs: dict  # additional mode specific attrs
-    tags: list[Literal['txt2img', 'img2img', 'inpaint', 'upscale']]
-
-
 MODELS: dict[str, ModelDesc] = {
     'RealESRGAN_x4plus': ModelDesc(
         short='realesrgan',

skynet/dgpu/__init__.py

@@ -5,9 +5,9 @@ import trio
 import urwid
 
 from skynet.config import Config
-from skynet.dgpu.tui import init_tui
+from skynet.dgpu.tui import init_tui, WorkerMonitor
 from skynet.dgpu.daemon import dgpu_serve_forever
-from skynet.dgpu.network import NetConnector
+from skynet.dgpu.network import NetConnector, maybe_open_contract_state_mngr
 
 
 @acm
@@ -15,26 +15,28 @@ async def open_worker(config: Config):
     # suppress logs from httpx (logs url + status after every query)
     logging.getLogger("httpx").setLevel(logging.WARNING)
 
-    tui = None
+    tui: WorkerMonitor | None = None
     if config.tui:
         tui = init_tui(config)
 
     conn = NetConnector(config)
-
     try:
-        n: trio.Nursery
-        async with trio.open_nursery() as n:
-            if tui:
-                n.start_soon(tui.run)
+        async with maybe_open_contract_state_mngr(conn) as state_mngr:
+            n: trio.Nursery
+            async with trio.open_nursery() as n:
+                if tui:
+                    n.start_soon(tui.run)
 
-            n.start_soon(conn.iter_poll_update, config.poll_time)
+                n.start_soon(dgpu_serve_forever, config, conn, state_mngr)
 
-            yield conn
+                yield conn, state_mngr
+
+                n.cancel_scope.cancel()
 
     except *urwid.ExitMainLoop:
         ...
 
 
 async def _dgpu_main(config: Config):
-    async with open_worker(config) as conn:
-        await dgpu_serve_forever(config, conn)
+    async with open_worker(config):
+        await trio.sleep_forever()

skynet/dgpu/compute.py

@@ -7,81 +7,90 @@ import gc
 import logging
 
 from hashlib import sha256
+from typing import Callable, Generator
 from contextlib import contextmanager as cm
 
 import trio
 import torch
 
 from skynet.config import load_skynet_toml
+from skynet.types import ModelMode, BodyV0Params
 from skynet.dgpu.tui import maybe_update_tui
 from skynet.dgpu.errors import (
     DGPUComputeError,
     DGPUInferenceCancelled,
 )
 
-from skynet.dgpu.utils import crop_image, convert_from_cv2_to_image, convert_from_image_to_cv2, convert_from_img_to_bytes, init_upscaler, pipeline_for
+from skynet.dgpu.utils import (
+    Pipeline,
+    crop_image,
+    convert_from_cv2_to_image,
+    convert_from_image_to_cv2,
+    convert_from_img_to_bytes,
+    pipeline_for
+)
 
 
 def prepare_params_for_diffuse(
-    params: dict,
-    mode: str,
+    params: BodyV0Params,
+    mode: ModelMode,
     inputs: list[bytes]
 ):
     _params = {}
     match mode:
-        case 'inpaint':
+        case ModelMode.INPAINT:
             image = crop_image(
-                inputs[0], params['width'], params['height'])
+                inputs[0], params.width, params.height)
 
             mask = crop_image(
-                inputs[1], params['width'], params['height'])
+                inputs[1], params.width, params.height)
 
             _params['image'] = image
             _params['mask_image'] = mask
 
-            if 'flux' in params['model'].lower():
+            if 'flux' in params.model.lower():
                 _params['max_sequence_length'] = 512
             else:
-                _params['strength'] = float(params['strength'])
+                _params['strength'] = float(params.strength)
 
-        case 'img2img':
+        case ModelMode.IMG2IMG:
             image = crop_image(
-                inputs[0], params['width'], params['height'])
+                inputs[0], params.width, params.height)
 
             _params['image'] = image
-            _params['strength'] = float(params['strength'])
+            _params['strength'] = float(params.strength)
 
-        case 'txt2img' | 'diffuse':
+        case ModelMode.TXT2IMG | ModelMode.DIFFUSE:
             ...
 
         case _:
             raise DGPUComputeError(f'Unknown mode {mode}')
 
-    # _params['width'] = int(params['width'])
-    # _params['height'] = int(params['height'])
-
     return (
-        params['prompt'],
-        float(params['guidance']),
-        int(params['step']),
-        torch.manual_seed(int(params['seed'])),
-        params['upscaler'] if 'upscaler' in params else None,
+        params.prompt,
+        float(params.guidance),
+        params.step,
+        torch.manual_seed(int(params.seed)),
         _params
     )
 
 _model_name: str = ''
 _model_mode: str = ''
-_model = None
+_model: Pipeline | None = None
 
 @cm
-def maybe_load_model(name: str, mode: str):
-    if mode == 'diffuse':
-        mode = 'txt2img'
+def maybe_load_model(name: str, mode: ModelMode) -> Generator[Pipeline, None, None]:
+    if mode == ModelMode.DIFFUSE:
+        mode = ModelMode.TXT2IMG
 
     global _model_name, _model_mode, _model
     config = load_skynet_toml().dgpu
 
-    if _model_name != name or _model_mode != mode:
+    if (
+        _model_name != name
+        or
+        _model_mode != mode
+    ):
         # unload model
         _model = None
         gc.collect()
@@ -90,34 +99,33 @@ def maybe_load_model(name: str, mode: str):
         _model_name = _model_mode = ''
 
         # load model
-        if mode == 'upscale':
-            _model = init_upscaler()
-
-        else:
-            _model = pipeline_for(
-                name, mode, cache_dir=config.hf_home)
+        _model = pipeline_for(
+            name, mode, cache_dir=config.hf_home)
 
         _model_name = name
         _model_mode = mode
 
-        logging.debug('memory summary:')
-        logging.debug('\n' + torch.cuda.memory_summary())
+        if torch.cuda.is_available():
+            logging.debug(
+                'memory summary:\n'
+                f'{torch.cuda.memory_summary()}'
+            )
 
     yield _model
 
 
 def compute_one(
-    model,
+    model: Pipeline,
     request_id: int,
-    method: str,
-    params: dict,
+    method: ModelMode,
+    params: BodyV0Params,
     inputs: list[bytes] = [],
-    should_cancel = None
+    should_cancel: Callable[[int, ...], dict] = None
 ):
-    total_steps = params['step'] if 'step' in params else 1
+    total_steps = params.step
     def inference_step_wakeup(*args, **kwargs):
         '''This is a callback function that gets invoked every inference step,
-        we need to raise an exception here if we need to cancel work
+        we must raise DGPUInferenceCancelled here if we need to cancel work
         '''
         step = args[0]
         # compat with callback_on_step_end
@@ -128,6 +136,9 @@ def compute_one(
 
         should_raise = False
         if should_cancel:
+            '''Pump main thread event loop, evaluate if we should keep working
+            on this request, based on latest network info like competitors...
+            '''
             should_raise = trio.from_thread.run(should_cancel, request_id)
 
         if should_raise:
@@ -140,68 +151,59 @@ def compute_one(
 
     inference_step_wakeup(0)
 
-    output_type = 'png'
-    if 'output_type' in params:
-        output_type = params['output_type']
-
+    output_type = params.output_type
     output = None
     output_hash = None
-    try:
-        name = params['model']
+    name = params.model
 
-        match method:
-            case 'diffuse' | 'txt2img' | 'img2img' | 'inpaint':
-                arguments = prepare_params_for_diffuse(
-                    params, method, inputs)
-                prompt, guidance, step, seed, upscaler, extra_params = arguments
+    match method:
+        case (
+            ModelMode.DIFFUSE |
+            ModelMode.TXT2IMG |
+            ModelMode.IMG2IMG |
+            ModelMode.INPAINT
+        ):
+            arguments = prepare_params_for_diffuse(
+                params, method, inputs)
+            prompt, guidance, step, seed, extra_params = arguments
 
-                if 'flux' in name.lower():
-                    extra_params['callback_on_step_end'] = inference_step_wakeup
+            if 'flux' in name.lower():
+                extra_params['callback_on_step_end'] = inference_step_wakeup
 
-                else:
-                    extra_params['callback'] = inference_step_wakeup
-                    extra_params['callback_steps'] = 1
+            else:
+                extra_params['callback'] = inference_step_wakeup
+                extra_params['callback_steps'] = 1
 
-                output = model(
-                    prompt,
-                    guidance_scale=guidance,
-                    num_inference_steps=step,
-                    generator=seed,
-                    **extra_params
-                ).images[0]
+            output = model(
+                prompt,
+                guidance_scale=guidance,
+                num_inference_steps=step,
+                generator=seed,
+                **extra_params
+            ).images[0]
 
-                output_binary = b''
-                match output_type:
-                    case 'png':
-                        if upscaler == 'x4':
-                            input_img = output.convert('RGB')
-                            up_img, _ = init_upscaler().enhance(
-                                convert_from_image_to_cv2(input_img), outscale=4)
+            output_binary = b''
+            match output_type:
+                case 'png':
+                    output_binary = convert_from_img_to_bytes(output)
 
-                            output = convert_from_cv2_to_image(up_img)
+                case _:
+                    raise DGPUComputeError(f'Unsupported output type: {output_type}')
 
-                        output_binary = convert_from_img_to_bytes(output)
+            output_hash = sha256(output_binary).hexdigest()
 
-                    case _:
-                        raise DGPUComputeError(f'Unsupported output type: {output_type}')
+        case 'upscale':
+            input_img = inputs[0].convert('RGB')
+            up_img, _ = model.enhance(
+                convert_from_image_to_cv2(input_img), outscale=4)
 
-                output_hash = sha256(output_binary).hexdigest()
+            output = convert_from_cv2_to_image(up_img)
 
-            case 'upscale':
-                input_img = inputs[0].convert('RGB')
-                up_img, _ = model.enhance(
-                    convert_from_image_to_cv2(input_img), outscale=4)
+            output_binary = convert_from_img_to_bytes(output)
+            output_hash = sha256(output_binary).hexdigest()
 
-                output = convert_from_cv2_to_image(up_img)
-
-                output_binary = convert_from_img_to_bytes(output)
-                output_hash = sha256(output_binary).hexdigest()
-
-            case _:
-                raise DGPUComputeError('Unsupported compute method')
-
-    except BaseException as err:
-        raise DGPUComputeError(str(err)) from err
+        case _:
+            raise DGPUComputeError('Unsupported compute method')
 
     maybe_update_tui(lambda tui: tui.set_status(''))
 

skynet/dgpu/daemon.py

@@ -1,32 +1,22 @@
-import json
 import logging
-import random
-import time
-from datetime import datetime
 from functools import partial
 from hashlib import sha256
 
 import trio
+import msgspec
 
 from skynet.config import DgpuConfig as Config
-from skynet.constants import (
-    MODELS,
-    VERSION,
-)
-from skynet.dgpu.errors import (
-    DGPUComputeError,
+from skynet.types import (
+    BodyV0
 )
+from skynet.constants import MODELS
+from skynet.dgpu.errors import DGPUComputeError
 from skynet.dgpu.tui import maybe_update_tui, maybe_update_tui_async
 from skynet.dgpu.compute import maybe_load_model, compute_one
-from skynet.dgpu.network import NetConnector
-
-
-def convert_reward_to_int(reward_str):
-    int_part, decimal_part = (
-        reward_str.split('.')[0],
-        reward_str.split('.')[1].split(' ')[0]
-    )
-    return int(int_part + decimal_part)
+from skynet.dgpu.network import (
+    NetConnector,
+    ContractState,
+)
 
 
 async def maybe_update_tui_balance(conn: NetConnector):
@@ -41,14 +31,18 @@ async def maybe_update_tui_balance(conn: NetConnector):
 async def maybe_serve_one(
     config: Config,
     conn: NetConnector,
-    req: dict,
+    state_mngr: ContractState,
 ):
-    rid = req['id']
-    logging.info(f'maybe serve request #{rid}')
+    logging.info(f'maybe serve request pi: {state_mngr.poll_index}')
+    req = state_mngr.first
+
+    # no requests in queue
+    if not req:
+        return
 
     # parse request
-    body = json.loads(req['body'])
-    model = body['params']['model']
+    body = msgspec.json.decode(req.body, type=BodyV0)
+    model = body.params.model
 
     # if model not known, ignore.
     if model not in MODELS:
@@ -70,32 +64,27 @@ async def maybe_serve_one(
         and
         model in config.model_blacklist
     ):
-        logging.warning('model not blacklisted!, skip...')
+        logging.warning('model is blacklisted!, skip...')
         return
 
-    results = [res['request_id'] for res in conn._tables['results']]
-
     # if worker already produced a result for this request
-    if rid in results:
-        logging.info(f'worker already submitted a result for request #{rid}, skip...')
+    if state_mngr.is_request_filled(req.id):
+        logging.info(f'worker already submitted a result for request #{req.id}, skip...')
         return
 
-    statuses = conn._tables['requests'][rid]
-
     # skip if workers in non_compete already on it
-    competitors = set((status['worker'] for status in statuses))
-    if bool(config.non_compete & competitors):
+    if not state_mngr.should_compete_for_id(req.id):
         logging.info('worker in configured non_compete list already working on request, skip...')
         return
 
     # resolve the ipfs hashes into the actual data behind them
     inputs = []
-    raw_inputs = req['binary_data'].split(',')
+    raw_inputs = req.binary_data.split(',')
     if raw_inputs:
         logging.info(f'fetching IPFS inputs: {raw_inputs}')
 
     retry = 3
-    for _input in req['binary_data'].split(','):
+    for _input in raw_inputs:
         if _input:
             for r in range(retry):
                 try:
@@ -114,24 +103,22 @@ async def maybe_serve_one(
 
     # compute unique request hash used on submit
     hash_str = (
-        str(req['nonce'])
+        str(req.nonce)
         +
-        req['body']
+        req.body
         +
-        req['binary_data']
+        req.binary_data
     )
     logging.debug(f'hashing: {hash_str}')
     request_hash = sha256(hash_str.encode('utf-8')).hexdigest()
     logging.info(f'calculated request hash: {request_hash}')
 
-    params = body['params']
-    total_step = params['step'] if 'step' in params else 1
-    model = body['params']['model']
-    mode = body['method']
+    total_step = body.params.step
+    mode = body.method
 
     # TODO: validate request
 
-    resp = await conn.begin_work(rid)
+    resp = await conn.begin_work(req.id)
     if not resp or 'code' in resp:
         logging.info('begin_work error, probably being worked on already... skip.')
         return
@@ -140,22 +127,24 @@ async def maybe_serve_one(
         try:
             maybe_update_tui(lambda tui: tui.set_progress(0, done=total_step))
 
-            output_type = 'png'
-            if 'output_type' in body['params']:
-                output_type = body['params']['output_type']
-
+            output_type = body.params.output_type
             output = None
             output_hash = None
             match config.backend:
                 case 'sync-on-thread':
+                    '''Block this task until inference completes, pass
+                    state_mngr.should_cancel_work predicate as the inference_step_wakeup cb
+                    used by torch each step of the inference, it will use a
+                    trio.from_thread to unblock the main thread and pump the event loop
+                    '''
                     output_hash, output = await trio.to_thread.run_sync(
                         partial(
                             compute_one,
                             model,
-                            rid,
-                            mode, params,
+                            req.id,
+                            mode, body.params,
                             inputs=inputs,
-                            should_cancel=conn.should_cancel_work,
+                            should_cancel=state_mngr.should_cancel_work,
                         )
                     )
 
@@ -168,43 +157,39 @@ async def maybe_serve_one(
 
             ipfs_hash = await conn.publish_on_ipfs(output, typ=output_type)
 
-            await conn.submit_work(rid, request_hash, output_hash, ipfs_hash)
+            await conn.submit_work(req.id, request_hash, output_hash, ipfs_hash)
 
             await maybe_update_tui_balance(conn)
 
+            await state_mngr.update_state()
+
 
         except BaseException as err:
             if 'network cancel' not in str(err):
                 logging.exception('Failed to serve model request !?\n')
 
-            if rid in conn._tables['requests']:
-                await conn.cancel_work(rid, 'reason not provided')
+            if state_mngr.is_request_in_progress(req.id):
+                await conn.cancel_work(req.id, 'reason not provided')
 
 
-async def dgpu_serve_forever(config: Config, conn: NetConnector):
+async def dgpu_serve_forever(
+    config: Config,
+    conn: NetConnector,
+    state_mngr: ContractState
+):
     await maybe_update_tui_balance(conn)
 
     last_poll_idx = -1
     try:
         while True:
-            await conn.wait_data_update()
-            if conn.poll_index == last_poll_idx:
+            await state_mngr.wait_data_update()
+            if state_mngr.poll_index == last_poll_idx:
                 await trio.sleep(config.poll_time)
                 continue
 
-            last_poll_idx = conn.poll_index
+            last_poll_idx = state_mngr.poll_index
 
-            queue = conn._tables['queue']
-
-            random.shuffle(queue)
-            queue = sorted(
-                queue,
-                key=lambda req: convert_reward_to_int(req['reward']),
-                reverse=True
-            )
-
-            if len(queue) > 0:
-                await maybe_serve_one(config, conn, queue[0])
+            await maybe_serve_one(config, conn, state_mngr)
 
     except KeyboardInterrupt:
         ...

skynet/dgpu/network.py

@@ -1,9 +1,10 @@
 import io
 import json
 import time
+import random
 import logging
 from pathlib import Path
-from typing import AsyncGenerator
+from contextlib import asynccontextmanager as acm
 from functools import partial
 
 import trio
@@ -11,15 +12,21 @@ import leap
 import anyio
 import httpx
 import outcome
+import msgspec
 from PIL import Image
 from leap.cleos import CLEOS
 from leap.protocol import Asset
 from skynet.dgpu.tui import maybe_update_tui
-from skynet.config import DgpuConfig as Config
-from skynet.constants import (
-    DEFAULT_IPFS_DOMAIN,
-    GPU_CONTRACT_ABI,
+from skynet.config import DgpuConfig as Config, load_skynet_toml
+from skynet.types import (
+    ConfigV0,
+    AccountV0,
+    BodyV0,
+    RequestV0,
+    WorkerStatusV0,
+    ResultV0
 )
+from skynet.constants import GPU_CONTRACT_ABI
 
 from skynet.ipfs import (
     AsyncIPFSHTTP,
@@ -67,21 +74,12 @@ class NetConnector:
 
         self.ipfs_client = AsyncIPFSHTTP(config.ipfs_url)
 
-        # poll_index is used to detect stale data
-        self.poll_index = 0
-        self._tables = {
-            'queue': [],
-            'requests': {},
-            'results': []
-        }
-        self._data_event = trio.Event()
-
         maybe_update_tui(lambda tui: tui.set_header_text(new_worker_name=self.config.account))
 
 
     # blockchain helpers
 
-    async def get_work_requests_last_hour(self):
+    async def get_work_requests_last_hour(self) -> list[RequestV0]:
         logging.info('get_work_requests_last_hour')
         rows = await failable(
             partial(
@@ -89,28 +87,30 @@ class NetConnector:
                 'gpu.scd', 'gpu.scd', 'queue',
                 index_position=2,
                 key_type='i64',
-                lower_bound=int(time.time()) - 3600
+                lower_bound=int(time.time()) - 3600,
+                resp_cls=RequestV0
             ), ret_fail=[])
 
         logging.info(f'found {len(rows)} requests on queue')
         return rows
 
-    async def get_status_by_request_id(self, request_id: int):
+    async def get_status_by_request_id(self, request_id: int) -> list[WorkerStatusV0]:
         logging.info('get_status_by_request_id')
         rows = await failable(
             partial(
                 self.cleos.aget_table,
-                'gpu.scd', request_id, 'status'), ret_fail=[])
+                'gpu.scd', request_id, 'status', resp_cls=WorkerStatusV0), ret_fail=[])
 
-        logging.info(f'found status for workers: {[r["worker"] for r in rows]}')
+        logging.info(f'found status for workers: {[r.worker for r in rows]}')
         return rows
 
-    async def get_global_config(self):
+    async def get_global_config(self) -> ConfigV0:
         logging.info('get_global_config')
         rows = await failable(
             partial(
                 self.cleos.aget_table,
-                'gpu.scd', 'gpu.scd', 'config'))
+                'gpu.scd', 'gpu.scd', 'config',
+                resp_cls=ConfigV0))
 
         if rows:
             cfg = rows[0]
@@ -120,7 +120,7 @@ class NetConnector:
             logging.error('global config not found, is the contract initialized?')
             return None
 
-    async def get_worker_balance(self):
+    async def get_worker_balance(self) -> str:
         logging.info('get_worker_balance')
         rows = await failable(
             partial(
@@ -129,77 +129,18 @@ class NetConnector:
                 index_position=1,
                 key_type='name',
                 lower_bound=self.config.account,
-                upper_bound=self.config.account
+                upper_bound=self.config.account,
+                resp_cls=AccountV0
             ))
 
         if rows:
-            b = rows[0]['balance']
+            b = rows[0].balance
             logging.info(f'balance: {b}')
             return b
         else:
             logging.info('no balance info found')
             return None
 
-    async def get_full_queue_snapshot(self):
-        '''
-        Get a "snapshot" of current contract table state
-
-        '''
-        snap = {
-            'requests': {},
-            'results': []
-        }
-
-        snap['queue'] = await self.get_work_requests_last_hour()
-
-        async def _run_and_save(d, key: str, fn, *args, **kwargs):
-            d[key] = await fn(*args, **kwargs)
-
-        async with trio.open_nursery() as n:
-            n.start_soon(_run_and_save, snap, 'results', self.find_results)
-            for req in snap['queue']:
-                n.start_soon(
-                    _run_and_save, snap['requests'], req['id'], self.get_status_by_request_id, req['id'])
-
-
-        maybe_update_tui(lambda tui: tui.network_update(snap))
-
-        return snap
-
-    async def wait_data_update(self):
-        await self._data_event.wait()
-
-    async def iter_poll_update(self, poll_time: float):
-        '''
-        Long running task, polls gpu contract tables latest table rows,
-        awakes any self._data_event waiters
-
-        '''
-        while True:
-            start_time = time.time()
-            self._tables = await self.get_full_queue_snapshot()
-            elapsed = time.time() - start_time
-            self._data_event.set()
-            await trio.sleep(max(poll_time - elapsed, 0.1))
-            self._data_event = trio.Event()
-            self.poll_index += 1
-
-    async def should_cancel_work(self, request_id: int) -> bool:
-        logging.info('should cancel work?')
-        if request_id not in self._tables['requests']:
-            logging.info(f'request #{request_id} no longer in queue, likely its been filled by another worker, cancelling work...')
-            return True
-
-        competitors = set([
-            status['worker']
-            for status in self._tables['requests'][request_id]
-            if status['worker'] != self.config.account
-        ])
-        logging.info(f'competitors: {competitors}')
-        should_cancel = bool(self.config.non_compete & competitors)
-        logging.info(f'cancel: {should_cancel}')
-        return should_cancel
-
     async def begin_work(self, request_id: int):
         '''
         Publish to the bc that the worker is beginning a model-computation
@@ -261,7 +202,7 @@ class NetConnector:
                 )
             )
 
-    async def find_results(self):
+    async def find_results(self) -> list[ResultV0]:
         logging.info('find_results')
         rows = await failable(
             partial(
@@ -270,7 +211,8 @@ class NetConnector:
                 index_position=4,
                 key_type='name',
                 lower_bound=self.config.account,
-                upper_bound=self.config.account
+                upper_bound=self.config.account,
+                resp_cls=ResultV0
             )
         )
         return rows
@@ -344,3 +286,158 @@ class NetConnector:
         logging.info('decoded as image successfully')
 
         return input_data
+
+
+
+def convert_reward_to_int(reward_str):
+    int_part, decimal_part = (
+        reward_str.split('.')[0],
+        reward_str.split('.')[1].split(' ')[0]
+    )
+    return int(int_part + decimal_part)
+
+
+class ContractState:
+
+    def __init__(self, conn: NetConnector):
+        self._conn = conn
+
+        self._poll_index = 0
+
+        self._queue: list[RequestV0] = []
+        self._status_by_rid: dict[int, list[WorkerStatusV0]] = {}
+        self._results: list[ResultV0] = []
+
+        self._new_data = trio.Event()
+
+    @property
+    def poll_index(self) -> int:
+        return self._poll_index
+
+    async def _fetch_results(self):
+        self._results = await self._conn.find_results()
+
+    async def _fetch_statuses_for_id(self, rid: int):
+        self._status_by_rid[rid] = await self._conn.get_status_by_request_id(rid)
+
+    async def update_state(self):
+        '''
+        Get a "snapshot" of current contract table state
+
+        '''
+        # raw queue from chain
+        _queue = await self._conn.get_work_requests_last_hour()
+
+        # filter out invalids
+        self._queue = []
+        for req in _queue:
+            try:
+                msgspec.json.decode(req.body, type=BodyV0)
+                self._queue.append(req)
+
+            except msgspec.ValidationError:
+                logging.exception(f'dropping req {req.id} due to:')
+                ...
+
+        random.shuffle(self._queue)
+        self._queue = sorted(
+            self._queue,
+            key=lambda req: convert_reward_to_int(req.reward),
+            reverse=True
+        )
+
+        async with trio.open_nursery() as n:
+            n.start_soon(self._fetch_results)
+            for req in self._queue:
+                n.start_soon(
+                    self._fetch_statuses_for_id, req.id)
+
+
+        maybe_update_tui(lambda tui: tui.network_update(self))
+
+    async def wait_data_update(self):
+        await self._new_data.wait()
+
+    async def _state_update_task(self, poll_time: float):
+        '''
+        Long running task, polls gpu contract tables latest table rows,
+        awakes any self._data_event waiters
+
+        '''
+        while True:
+            start_time = time.time()
+            await self.update_state()
+            elapsed = time.time() - start_time
+            self._new_data.set()
+            await trio.sleep(max(poll_time - elapsed, 0.1))
+            self._new_data = trio.Event()
+            self._poll_index += 1
+
+    # views into data
+
+    @property
+    def queue_len(self) -> int:
+        return len(self._queue)
+
+    @property
+    def first(self) -> RequestV0 | None:
+        if len(self._queue) > 0:
+            return self._queue[0]
+
+        else:
+            return None
+
+    def competitors_for_id(self, request_id: int) -> set[str]:
+        return set((
+            status.worker
+            for status in self._status_by_rid[request_id]
+            if status.worker != self._conn.config.account
+        ))
+
+    # predicates
+
+    def is_request_filled(self, request_id: int) -> bool:
+        return request_id in [
+            result.request_id for result in self._results
+        ]
+
+    def is_request_in_progress(self, request_id: int) -> bool:
+        return request_id in self._status_by_rid
+
+    def should_compete_for_id(self, request_id: int) -> bool:
+        return not bool(
+            self._conn.config.non_compete &
+            self.competitors_for_id(request_id)
+        )
+
+    async def should_cancel_work(self, request_id: int) -> bool:
+        logging.info('should cancel work?')
+        if request_id not in self._status_by_rid:
+            logging.info(f'request #{request_id} no longer in queue, likely its been filled by another worker, cancelling work...')
+            return True
+
+        should_cancel = not self.should_compete_for_id(request_id)
+        logging.info(f'cancel: {should_cancel}')
+        return should_cancel
+
+
+
+__state_mngr = None
+
+@acm
+async def maybe_open_contract_state_mngr(conn: NetConnector):
+    global __state_mngr
+
+    if __state_mngr:
+        yield __state_mngr
+        return
+
+    config = load_skynet_toml().dgpu
+
+    mngr = ContractState(conn)
+    async with trio.open_nursery() as n:
+        await mngr.update_state()
+        n.start_soon(mngr._state_update_task, config.poll_time)
+        __state_mngr = mngr
+        yield mngr
+        n.cancel_scope.cancel()

skynet/dgpu/pipes/tester.py

@@ -6,7 +6,7 @@ import msgspec
 
 
 __model = {
-    'name': 'skygpu/txt2img-mocker'
+    'name': 'skygpu/mocker'
 }
 
 class MockPipelineResult(msgspec.Struct):

skynet/dgpu/pipes/tester_upscale.py

@@ -0,0 +1,34 @@
+from PIL import Image
+
+import msgspec
+
+from skynet.dgpu.utils import convert_from_image_to_cv2
+
+
+__model = {
+    'name': 'skygpu/mocker-upscale'
+}
+
+class MockPipelineResult(msgspec.Struct):
+    images: list[Image]
+
+class MockUpscalePipeline:
+
+    def enhance(
+        self,
+        img,
+        outscale: int
+    ):
+        img = Image.new('RGB', (outscale, outscale), color='green')
+        output = convert_from_image_to_cv2(img)
+
+        return (output, None)
+
+
+def pipeline_for(
+    model: str,
+    mode: str,
+    mem_fraction: float = 1.0,
+    cache_dir: str | None = None
+):
+    return MockUpscalePipeline()

skynet/dgpu/tui.py

@@ -2,7 +2,6 @@ import json
 import logging
 import warnings
 
-import trio
 import urwid
 
 from skynet.config import DgpuConfig as Config
@@ -79,6 +78,11 @@ class WorkerMonitor:
         """
         row_widgets = []
 
+        requests = sorted(
+            requests,
+            key=lambda r: r['id']
+        )
+
         for req in requests:
             # Build a columns widget for the request row
             prompt = req['prompt'] if 'prompt' in req else 'UPSCALE'
@@ -137,10 +141,6 @@ class WorkerMonitor:
 
         self.progress_bar.current = current
 
-        pct = 0
-        if self.progress_bar.done != 0:
-            pct = int((self.progress_bar.current / self.progress_bar.done) * 100)
-
     def update_requests(self, new_requests):
         """
         Replace the data in the existing ListBox with new request widgets.
@@ -157,14 +157,16 @@ class WorkerMonitor:
         if new_balance is not None:
             self.balance_widget.set_text(new_balance)
 
-    def network_update(self, snapshot: dict):
+    def network_update(self, state_mngr):
         queue = [
             {
-                **r,
-                **(json.loads(r['body'])['params']),
-                'workers': [s['worker'] for s in snapshot['requests'][r['id']]]
+                'id': r.id,
+                'user': r.user,
+                'reward': r.reward,
+                **(json.loads(r.body)['params']),
+                'workers': [s.worker for s in state_mngr._status_by_rid[r.id]]
             }
-            for r in snapshot['queue']
+            for r in state_mngr._queue
         ]
         self.update_requests(queue)
 

skynet/dgpu/utils.py

@@ -1,7 +1,6 @@
 import io
 import os
 import sys
-import time
 import random
 import logging
 import importlib
@@ -76,6 +75,9 @@ class DummyPB:
     def update(self):
         ...
 
+
+type Pipeline = DiffusionPipeline | RealESRGANer
+
 @torch.compiler.disable
 @contextmanager
 def dummy_progress_bar(*args, **kwargs):
@@ -91,7 +93,7 @@ def pipeline_for(
     mode: str,
     mem_fraction: float = 1.0,
     cache_dir: str | None = None
-) -> DiffusionPipeline:
+) -> Pipeline:
     diffusers.utils.logging.disable_progress_bar()
 
     logging.info(f'pipeline_for {model} {mode}')
@@ -125,6 +127,9 @@ def pipeline_for(
     except ImportError:
         logging.info(f'didn\'t find a custom pipeline file for {shortname}')
 
+    # for now, upscaler special case...
+    if mode == 'upscale':
+        return init_upscaler()
 
     req_mem = model_info.mem
 

skynet/types.py

@@ -0,0 +1,230 @@
+from enum import StrEnum
+
+from msgspec import Struct
+
+
+class ModelMode(StrEnum):
+    DIFFUSE = 'diffuse'
+    TXT2IMG = 'txt2img'
+    IMG2IMG = 'img2img'
+    UPSCALE = 'upscale'
+    INPAINT = 'inpaint'
+
+
+class ModelDesc(Struct):
+    short: str  # short unique name
+    mem: float  # recomended mem in gb
+    attrs: dict  # additional mode specific attrs
+    tags: list[ModelMode]
+
+# smart contract types
+# https://github.com/guilledk/telos.contracts/blob/gpu_contracts/contracts/telos.gpu/include/telos.gpu/telos.gpu.hpp
+
+'''
+ConfigV0
+
+singleton containing global info about system, definition:
+
+```c++
+struct [[eosio::table]] global_configuration_struct {
+    name token_contract;
+    symbol token_symbol;
+} global_config_row;
+
+typedef eosio::singleton<"config"_n, global_configuration_struct> global_config;
+```
+'''
+
+class ConfigV0:
+    token_contract: str
+    token_symbol: str
+
+'''
+RequestV0
+
+a request placed on the queue, definition:
+
+scope: get_self()
+
+```c++
+struct [[eosio::table]] work_request_struct {
+    uint64_t id;
+    name user;
+    asset reward;
+    uint32_t min_verification;
+
+    uint64_t nonce;
+
+    string body;
+    string binary_data;
+
+    time_point_sec timestamp;
+
+    uint64_t primary_key() const { return id; }
+    uint64_t by_time() const { return (uint64_t)timestamp.sec_since_epoch(); }
+};
+
+typedef eosio::multi_index<
+    "queue"_n,
+    work_request_struct,
+    indexed_by<
+        "bytime"_n, const_mem_fun<work_request_struct, uint64_t, &work_request_struct::by_time>
+    >
+> work_queue;
+```
+'''
+
+class BodyV0Params(Struct):
+    prompt: str
+    model: str
+    seed: int
+    step: int = 1
+    guidance: str | float | None = None
+    width: int | None = None
+    height: int | None = None
+    strength: str | float | None = None
+    output_type: str | None = 'png'
+    upscaler: str | None = None
+
+
+class BodyV0(Struct):
+    method: ModelMode
+    params: BodyV0Params
+
+
+class RequestV0(Struct):
+    id: int
+    user: str
+    reward: str
+    min_verification: int
+    nonce: int
+    body: str
+    binary_data: str
+    timestamp: str
+
+
+'''
+AccountV0
+
+a user account, users must deposit tokens in order to enqueue requests, definition:
+
+scope: get_self()
+
+```c++
+struct [[eosio::table]] account {
+    name user;
+    asset    balance;
+    uint64_t nonce;
+
+    uint64_t primary_key()const { return user.value; }
+};
+typedef eosio::multi_index<"users"_n, account> users;
+```
+'''
+
+class AccountV0(Struct):
+    user: str
+    balance: str
+    nonce: int
+
+
+'''
+WorkerV0
+
+a registered worker info, definition:
+
+scope: get_self()
+
+```c++
+struct [[eosio::table]] worker {
+    name account;
+    time_point_sec joined;
+    time_point_sec left;
+    string url;
+
+    uint64_t primary_key()const { return account.value; }
+};
+typedef eosio::multi_index<"workers"_n, worker> workers;
+```
+'''
+
+class WorkerV0(Struct):
+    account: str
+    joined: str
+    left: str
+    url: str
+
+'''
+WorkerStatusV0
+
+a worker's status related to a currently in progress fill, definition:
+
+scope: request id
+
+```c++
+struct [[eosio::table]] worker_status_struct {
+    name worker;
+    string status;
+    time_point_sec started;
+
+    uint64_t primary_key() const { return worker.value; }
+};
+```
+'''
+
+class WorkerStatusV0(Struct):
+    worker: str
+    status: str
+    started: str
+
+'''
+ResultV0
+
+a submited result related to a request, definition:
+
+scope: get_self()
+
+```c++
+struct [[eosio::table]] work_result_struct {
+    uint64_t id;
+    uint64_t request_id;
+    name user;
+    name worker;
+    checksum256 result_hash;
+    string ipfs_hash;
+    time_point_sec submited;
+
+    uint64_t primary_key() const { return id; }
+    uint64_t by_request_id() const { return request_id; }
+    checksum256 by_result_hash() const { return result_hash; }
+    uint64_t by_worker() const { return worker.value; }
+    uint64_t by_time() const { return (uint64_t)submited.sec_since_epoch(); }
+};
+
+typedef eosio::multi_index<
+    "results"_n,
+    work_result_struct,
+    indexed_by<
+        "byreqid"_n, const_mem_fun<work_result_struct, uint64_t, &work_result_struct::by_request_id>
+    >,
+    indexed_by<
+        "byresult"_n, const_mem_fun<work_result_struct, checksum256, &work_result_struct::by_result_hash>
+    >,
+    indexed_by<
+        "byworker"_n, const_mem_fun<work_result_struct, uint64_t, &work_result_struct::by_worker>
+    >,
+    indexed_by<
+        "bytime"_n, const_mem_fun<work_result_struct, uint64_t, &work_result_struct::by_time>
+    >
+> work_results;
+```
+'''
+
+class ResultV0(Struct):
+    id: int
+    request_id: int
+    user: str
+    worker: str
+    result_hash: str
+    ipfs_hash: str
+    submited: str

tests/conftest.py

@@ -1,7 +1,7 @@
 import pytest
 
-from skynet.config import *
 from skynet.ipfs import AsyncIPFSHTTP
+from skynet._testing import override_dgpu_config
 
 
 @pytest.fixture(scope='session')
@@ -20,35 +20,76 @@ def postgres_db():
 def skynet_cleos(cleos_bs):
     cleos = cleos_bs
 
-    priv, pub = cleos.create_key_pair()
-    cleos.import_key('telos.gpu', priv)
-    cleos.new_account('telos.gpu', ram=4200000, key=pub)
+    # priv, pub = cleos.create_key_pair()
+    # cleos.import_key('gpu.scd', priv)
+    cleos.new_account('gpu.scd', ram=4200000)
 
     cleos.deploy_contract_from_path(
-        'telos.gpu',
-        'tests/contracts/telos.gpu',
+        'gpu.scd',
+        'tests/contracts/gpu.scd',
         create_account=False
     )
 
     cleos.push_action(
-        'telos.gpu',
+        'gpu.scd',
         'config',
-        ['eosio.token', '4,GPU'],
-        'telos.gpu'
+        ['eosio.token', '4,TLOS'],
+        'gpu.scd'
     )
 
+    cleos.new_account('testworker')
+
     yield cleos
 
 
 @pytest.fixture
 def inject_mockers():
-    from skynet.constants import MODELS, ModelDesc
+    from skynet.constants import MODELS
+    from skynet.types import ModelDesc, ModelMode
 
-    MODELS['skygpu/txt2img-mocker'] = ModelDesc(
+    MODELS['skygpu/mocker'] = ModelDesc(
         short='tester',
         mem=0.01,
         attrs={},
-        tags=['txt2img']
+        tags=[
+            ModelMode.TXT2IMG,
+            ModelMode.IMG2IMG,
+            ModelMode.INPAINT
+        ]
+    )
+
+    MODELS['skygpu/mocker-upscale'] = ModelDesc(
+        short='tester-upscale',
+        mem=0.01,
+        attrs={},
+        tags=[
+            ModelMode.UPSCALE
+        ]
+    )
+
+    override_dgpu_config(
+        account='testworker1',
+        permission='active',
+        key='',
+        node_url='',
+        ipfs_url='http://127.0.0.1:5001',
+        hf_token=''
     )
 
     yield
+
+
+@pytest.fixture(scope='session')
+def ipfs_node(dockerctl):
+    rpc_port = 15001
+    with dockerctl.run(
+        'ipfs/go-ipfs:latest',
+        name='skynet-ipfs',
+        ports={
+            '8080/tcp': 18080,
+            '4001/tcp': 14001,
+            '5001/tcp': ('127.0.0.1', rpc_port)
+        },
+        timeout=60
+    ) as cntr:
+        yield cntr, AsyncIPFSHTTP(f'http://127.0.0.1:{rpc_port}')

tests/test_chain.py

@@ -1,3 +1,52 @@
-def test_dev(skynet_cleos):
+import trio
+from msgspec import json
+
+from skynet.types import BodyV0, BodyV0Params
+
+from skynet._testing import open_test_worker
+
+
+async def test_full_flow(inject_mockers, skynet_cleos, ipfs_node):
     cleos = skynet_cleos
-    ...
+
+    # create account and deposit tokens into gpu
+    account = cleos.new_account()
+    quantity = '1000.0000 TLOS'
+    cleos.transfer_token('eosio', account, quantity)
+    cleos.transfer_token(account, 'gpu.scd', quantity)
+
+    og_body = BodyV0(
+        method='txt2img',
+        params=BodyV0Params(
+            prompt='cyberpunk hacker travis bickle dystopic alley graffiti',
+            model='skygpu/mocker',
+            step=4,
+            seed=0,
+            guidance=10.0
+        )
+    )
+
+    body = json.encode(og_body).decode('utf-8')
+    binary_data = ''
+    reward = '1.0000 TLOS'
+    min_verification = 1
+
+    # send enqueue req
+    cleos.push_action(
+        'gpu.scd',
+        'enqueue',
+        [
+            account,
+            body,
+            binary_data,
+            reward,
+            min_verification
+        ],
+        account,
+        key=cleos.private_keys[account]
+    )
+
+    # open worker and fill request
+    async with open_test_worker(cleos, ipfs_node) as (_conn, state_mngr):
+        while state_mngr.queue_len > 0:
+            await trio.sleep(1)

tests/test_ipfs_client.py

@@ -1,14 +1,16 @@
 from pathlib import Path
 
 
-async def test_connection(ipfs_client):
-    await ipfs_client.connect(
-        '/ip4/169.197.140.154/tcp/4001/p2p/12D3KooWKWogLFNEcNNMKnzU7Snrnuj84RZdMBg3sLiQSQc51oEv')
-    peers = await ipfs_client.peers()
-    assert '12D3KooWKWogLFNEcNNMKnzU7Snrnuj84RZdMBg3sLiQSQc51oEv' in [p['Peer'] for p in peers]
+# async def test_connection(ipfs_node):
+#     _, ipfs_client = ipfs_node
+#     await ipfs_client.connect(
+#         '/ip4/169.197.140.154/tcp/4001/p2p/12D3KooWKWogLFNEcNNMKnzU7Snrnuj84RZdMBg3sLiQSQc51oEv')
+#     peers = await ipfs_client.peers()
+#     assert '12D3KooWKWogLFNEcNNMKnzU7Snrnuj84RZdMBg3sLiQSQc51oEv' in [p['Peer'] for p in peers]
 
 
-async def test_add_and_pin_file(ipfs_client):
+async def test_add_and_pin_file(ipfs_node):
+    _, ipfs_client = ipfs_node
     test_file = Path('hello_world.txt')
     with open(test_file, 'w+') as file:
         file.write('Hello Skynet!')

tests/test_reqs.py

@@ -1,39 +1,50 @@
 import pytest
+from PIL import Image
 
+from skynet.types import ModelMode, BodyV0Params
 from skynet.dgpu.compute import maybe_load_model, compute_one
 
 
-@pytest.mark.parametrize("mode", [
-    ('diffuse'), ('txt2img')
+@pytest.mark.parametrize('mode,model', [
+    (ModelMode.DIFFUSE, 'skygpu/mocker'),
+    (ModelMode.TXT2IMG, 'skygpu/mocker'),
+    (ModelMode.IMG2IMG, 'skygpu/mocker'),
+    (ModelMode.INPAINT, 'skygpu/mocker'),
+    (ModelMode.UPSCALE, 'skygpu/mocker-upscale'),
 ])
-async def test_pipeline_mocker(inject_mockers, mode):
-    model = 'skygpu/txt2img-mocker'
-    params = {
-        "prompt": "Kronos God Realistic 4k",
-        "model": model,
-        "step": 21,
-        "width": 1024,
-        "height": 1024,
-        "seed": 168402949,
-        "guidance": "7.5"
-    }
+async def test_pipeline_mocker(inject_mockers, mode, model):
+    # always insert at least two inputs to make all modes pass
+    inputs = [
+        Image.new('RGB', (1, 1), color='green')
+        for i in range(2)
+    ]
+    params = BodyV0Params(
+        prompt="Kronos God Realistic 4k",
+        model=model,
+        step=4,
+        width=1024,
+        height=1024,
+        seed=168402949,
+        guidance="7.5",
+        strength="0.65"
+    )
 
     with maybe_load_model(model, mode) as model:
-        compute_one(model, 0, mode, params)
+        compute_one(model, 0, mode, params, inputs)
 
-
-async def test_pipeline():
-    model = 'stabilityai/stable-diffusion-xl-base-1.0'
-    mode = 'txt2img'
-    params = {
-        "prompt": "Kronos God Realistic 4k",
-        "model": model,
-        "step": 21,
-        "width": 1024,
-        "height": 1024,
-        "seed": 168402949,
-        "guidance": "7.5"
-    }
-
-    with maybe_load_model(model, mode) as model:
-        compute_one(model, 0, mode, params)
+# disable for now (cuda)
+# async def test_pipeline():
+#     model = 'stabilityai/stable-diffusion-xl-base-1.0'
+#     mode = 'txt2img'
+#     params = BodyV0Params(
+#         prompt="Kronos God Realistic 4k",
+#         model=model,
+#         step=21,
+#         width=1024,
+#         height=1024,
+#         seed=168402949,
+#         guidance="7.5"
+#     )
+# 
+#     with maybe_load_model(model, mode) as model:
+#         compute_one(model, 0, mode, params)

uv.lock

@@ -1,5 +1,5 @@
-# vim: ft=toml
 version = 1
+revision = 1
 requires-python = ">=3.10, <3.13"
 resolution-markers = [
     "python_full_version >= '3.12' and sys_platform == 'darwin'",
@@ -51,16 +51,16 @@ wheels = [
 
 [[package]]
 name = "aiohappyeyeballs"
-version = "2.4.4"
+version = "2.4.6"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/7f/55/e4373e888fdacb15563ef6fa9fa8c8252476ea071e96fb46defac9f18bf2/aiohappyeyeballs-2.4.4.tar.gz", hash = "sha256:5fdd7d87889c63183afc18ce9271f9b0a7d32c2303e394468dd45d514a757745", size = 21977 }
+sdist = { url = "https://files.pythonhosted.org/packages/08/07/508f9ebba367fc3370162e53a3cfd12f5652ad79f0e0bfdf9f9847c6f159/aiohappyeyeballs-2.4.6.tar.gz", hash = "sha256:9b05052f9042985d32ecbe4b59a77ae19c006a78f1344d7fdad69d28ded3d0b0", size = 21726 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/b9/74/fbb6559de3607b3300b9be3cc64e97548d55678e44623db17820dbd20002/aiohappyeyeballs-2.4.4-py3-none-any.whl", hash = "sha256:a980909d50efcd44795c4afeca523296716d50cd756ddca6af8c65b996e27de8", size = 14756 },
+    { url = "https://files.pythonhosted.org/packages/44/4c/03fb05f56551828ec67ceb3665e5dc51638042d204983a03b0a1541475b6/aiohappyeyeballs-2.4.6-py3-none-any.whl", hash = "sha256:147ec992cf873d74f5062644332c539fcd42956dc69453fe5204195e560517e1", size = 14543 },
 ]
 
 [[package]]
 name = "aiohttp"
-version = "3.11.11"
+version = "3.11.12"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "aiohappyeyeballs" },
@@ -72,53 +72,56 @@ dependencies = [
     { name = "propcache" },
     { name = "yarl" },
 ]
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+sdist = { url = "https://files.pythonhosted.org/packages/37/4b/952d49c73084fb790cb5c6ead50848c8e96b4980ad806cf4d2ad341eaa03/aiohttp-3.11.12.tar.gz", hash = "sha256:7603ca26d75b1b86160ce1bbe2787a0b706e592af5b2504e12caa88a217767b0", size = 7673175 }
 wheels = [
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